: This study presents energy and exergy analyses conducted on a Gifford-McMahon cycle refriger-ator. Through detailed numerical simulations, the performance of the refrigerator is thoroughly assessed, with a particular focus on energy and exergy losses. The obtained results are compared with Sankey and Grassman diagrams, providing visual representations of energy and exergy flows within the system. The localization of exergy losses is carefully analysed to identify key areas for optimization aimed at enhancing efficiency and power output. By pinpointing sources of ex-ergy destruction, targeted improvements can be implemented to maximize the overall perfor-mance of the refrigerator. Overall, this research contributes to a deeper understanding of the thermodynamic behaviour of Gifford-McMahon cycle refrigerators and provides valuable insights for optimizing their performance in practical applications.

In this paper, possibilities for the bandwidth and wavelength utilization in future next-generation passive optical networks are presented and reasons for realizing and utilizing of extended dynamic wavelength and bandwidth algorithms for NG-PON2 networks are analyzed. Next, principles of the effective dynamic bandwidth allocation are introduced in details, focused on the importance of the decision criterion optimization. For achieving better bandwidth utilization of dedicated wavelengths, this paper is focused on the novel effective dynamic bandwidth allocation algorithm with adaptive allocation of wavelengths to ONU units and on the optimization of the decision criterion. For analyzing the novel extended DWBA algorithm utilizing for various wavelength allocation cases possible in NG-PON2 networks, a simulation program with the enhancement of the EDBA algorithm is realized. Finally, an optimization of the decision criterion defining a minimum bandwidth utilization of the actual wavelength is executed for NG-PON2 networks based on the hybrid TWDM technique.

Drafting formations have been long recognized as highly effective for reducing drag and enhancing athletic performance, particularly in race walking events. The precise spacing and positioning of the race walkers are critical to optimizing the effectiveness of drafting. In this study, the drag reduction of 15 drafting formations is investigated using wind-tunnel experiments and CFD numerical simulations. The results show excellent consistency in drag reduction rate between the two methods, with differences being within 10%. This can be attributed to spacing replacing body shape differences as the primary factor influencing drag reduction. Optimal double, triple, and quadruple drafting formations produce the same results in both wind-tunnel experiments and CFD simulation, resulting in drag reductions of 67%, 66%, and 81% (wind-tunnel) and 65%, 72%, and 85% (CFD). The sources of drag differences in the two methods are discussed from various aspects. The flow field obtained through CFD analysis is used to examine the mechanism of drag reduction, revealing that drafting formations have a significant shielding effect on incoming air, which reduces the number and speed of airflow impacting the core race walker. This shielding effect is identified as the primary cause of drag reduction. Using an empirical model for mechanical power output, optimal double, triple, and quadruple drafting formations enhance sport economy (4.4-5.7%), speed (3.61-4.67%), and performance (173.8-223.3s) compared to race walking alone. The findings can serve as a reference for race walkers' positioning strategy and provide insights for considering drafting formations in various running events.

Recently, there has been increasing attention toward inhaled nanoparticles (NPs) to develop in-halation therapies for diseases associated with the pulmonary system and investigate the toxic ef-fects of hazardous environmental particles on human lung health. Taking advantage of microfluidic technology for cell culture applications, lung-on-a-chip devices with great potential in replicating the lung air-blood barrier (ABB) have opened new research insights in preclinical pathology and therapeutic studies associated with aerosol NPs. Surprisingly, the air interface in such devices, which makes them tremendously unique among the other common liquid-based cellular mi-crosystems and enables exposure of cultivated cells to the drug/toxic aerosols, has been largely disregarded. Accordingly, there exists a significant research gap in the comprehensive under-standing of the NPs’ dynamics in the lung-on-a-chip devices, which is momentous to control the injection of aerosols to the target area and attain a desired physiochemical efficacy. To address this research gap, a numerical parametric study is presented to provide a deep insight into the dynamic behavior of the airborne NPs in a gas-liquid dual-channel lung-on-a-chip device with a porous membrane separating the channels. A finite element multi-physics model is developed to enable a particle tracing investigation simultaneously in both air and medium phases to replicate the in vivo conditions avoiding laborious and costly experimental trials. The results include the impact of fluid flow as well as geometrical properties on the distribution, deposition, and translocation of the NPs with diameters ranging from 10 nm to 900 nm in the lung-on-a-chip. The obtained results strongly suggest the aerosol injection of NPs instead of the aqueous solution for more efficient deposition on the substrate of the air channel and higher translocation to the media channel. The current study proposes to optimize the affecting parameters to control the injection and delivery of aerosol par-ticles into the lung-on-chip device depending on the objectives of biomedical investigations and provides optimized values for some specific cases. Therefore, this study can assist scientists and researchers in complementing their experimental investigation in future preclinical studies on pulmonary pathology associated with inhaled hazardous and toxic environmental particles, as well as therapeutic studies for developing inhalation drug delivery.

This paper focuses on the combination of the method of moments and the wire-grid approximation as an effective computational technique for modeling symmetrical antennas with low computational cost and quite accurate results. The criteria and conditions for the use of wire-grid surface approximation from various sources are presented together with new recommendations for modeling symmetrical antenna structures using the wire-grid approximation. These recommendations are used to calculate the characteristics of biconical and horn antennas at different frequencies. The results obtained using different grid and mesh settings are compared to those obtained analytically. Moreover, the results are compared to those obtained using the finite difference time domain numerical method, as well as the measured ones. All results are shown to be in a good agreement. The used recommendations for building a symmetrical wire-grid of those symmetrical antenna elements provided the most advantageous parameters of the grid and mesh settings and the wire radius, which are able to give a quite accurate results with low computational cost. Additionally, the known equal area rule was modified for a rectangular grid form. The obtained radiation patterns of a conductive plate using both the original rule and the modified one are compared with the electrodynamic analysis results. It is shown that the use of the modified rule is more accurate when using a rectangle grid form.

Tornadoes remain an active subject of observational and numerical research due to the damage and fatalities they cause worldwide as well as poor understanding of their behavior, such as what processes result in their genesis and what determines their longevity and morphology. A numerical model executed on a supercomputer run at high resolution can serve as a powerful tool for exploring the rapidly evolving tornado-scale features within a simulated storm, but saving large amounts data for meaningful analysis can result in unacceptably slow model performance, an unwieldy amount of saved data, and saved data spread across millions of files. In this paper, a system for efficiently saving and managing hundreds of terabytes of compressed model output is described in order to support a supercomputer simulation of a tornadic supercell thunderstorm. The challenges of managing a simulation spanning over a quarter trillion grid volumes across the Blue Waters supercomputer are also described. The simulated supercell produces a long-track EF5 tornado, and the near-tornado environment is described during tornadogenesis, where single upward-growing vortex undergoes several vortex mergers before transitioning into a multiple vortex tornado.

First of all the paper presents a solid solution of piezoelectric ceramic that was synthesized according to the general formula Pb(1-x)Srx(Ti0.48Zr0.52)(1-y)NbyO3 with x = 0.05 and y = 0.02, using wet ceramic processing technology and using an oxide mix as prime material. The effects of dopants (Sr2+ and Nb5+) on phase constitution, on microstructure and on the dielectric and piezoelectric properties were determinate. The Zr/Ti ratio was chosen near the morphotropic phase boundary of the PZT system in studied composition. The XRD data revealed that the PZT doped composition had tetragonal perovskite structure. Secondly the paper presents the design of the novel piezo-motor based on a surface wave which translates the linear extension of different piezoelectric segments of a piezoelectric cylinder into a rotational bending movement. This rotational bending of the piezoelectric cylinder is then transformed into a continuous rotation of the rotor through a calculated contact. The design of the motor takes advantage of the high piezoelectric constants of the developed material in an optimal way in order to increase the energetic efficiency. A brief mathematical model of electromechanical answer of piezoelectric materials is presented as it was used in the modeling of the material during the numerical simulations.

Based on the geologic conditions of natural gas hydrate (NGH) accumulations in the Shenhu area, northern slope of the South China Sea, this paper used a method of combining reservoir stimulation technique (RST) with depressurization to investigate the conversion efficiency of marine NGH reservoirs in different intrinsic permeability and initial NGH saturation conditions, and analyze the influence of variably-stimulation effect on marine NGH conversion efficiency in different accumulation conditions, provided a reference scheme for improving the NGH conversion efficiency in the Shenhu area. In this work, we performed calculations for the variations in CH4 production rate and cumulative volume of CH4 in different initial NGH saturation, intrinsic permeability and stimulation effect conditions, variance analysis and range analysis methods were used to analyze the significance of these key factors and their interaction, and investigated the sensitivity of stimulation effect on NGH conversion efficiency, respectively. The simulation results showed that stimulation effect have a significant influence on NGH conversion efficiency, and the influence of interaction between these three factors were not obvious. Possibly most important, we clarified an optimum stimulation effect for higher NGH conversion efficiency under different accumulation conditions, especially in low-permeability and high-saturation, which corresponding stimulation effect were different.

There are numerous approaches to model an influence of manufacturing parameters on the dissolution and disintegration of solid dosage forms. A modern approach for modelling and simulating complex and heterogeneous systems such as pharmaceutical tablets focuses on computationally-intensive finite-element or discreet element methods. Industrial challenges such as Process Analytical Technology (PAT) and Quality by Design are stimulating computer-based technologies to design, control and improve the quality of pharmaceutical compacts and their performance. In this study the disintegration and dissolution model based on the numerical solutions of the Noyes-Whitney equation and cellular automata supported disintegration model are proposed and evaluated. The results from in vitro release studies of the mefenamic acid formulations were compared to the calculated release patterns from the tablet structures obtained from microtomography experiments and the purely algorithmically created virtual tablets.

Chipless radio frequency identification (RFID) technology is expected to replace barcode technology due to its ability to read in non-line-of-sight (NLOS) situations, long reading range, and low cost. Currently, there is extensive research being conducted on frequency-coded (FC) co-polarized radar cross-section (RCS)-based tags, which are widely used. However, detecting co-polarized chipless RFID tags in cluttered environments is still a challenge, as confirmed by measuring two co-polarized tags in front of a perfect metal reflector (30.5cm×22.5cm). To address this challenge, a realistic mathematical model for a chipless RFID system has been developed that takes into account the characteristics of the reader and the tag, as well as reflections from cluttered objects. This model has been simulated and verified with measurement results by placing a single flat metal reflector behind two co-polarized one-bit designs: a dipole array tag and a square patch tag. The results showed that the interfering signal completely overlaps the ID of the co-polarized tag, severely limiting its detectability. To solve this issue, the proposed solution involves reading the tag in cross-polarization mode by etching a diagonal slot in the square patch tag. This proposed tag provides high immunity to the environment and can be detected in front of both dielectric and metallic objects.

The effects of wastewater step-feeding on the performance of Horizontal Subsurface Flow Constructed Wetlands (HSF CWs) are numerically investigated. The purpose is to check if this alternative feeding technique increases the ability of HSF CWs to remove pollutants. Two methodologies are used: Initially, the Tanks-In-series (TIS) methodology, based on Finite Volume Method (FVM), is analyzed by using the volumetric degradation coefficient λ. In this case the operation of CW is similar with a series of Continuous Stirred-Tank Reactors (CSTR), under steady conditions. Then, the Step-Feeding (SF) procedure is presented, when the CW is operated like a Plug Flow Reactor (PFR). The results show that the SF procedure does not improve the performance of HSF CWs on removing Biochemical Oxygen Demand (BOD), operating under Mediterranean conditions.

The goal of this lab is to look at how the characteristics of cementitious materials are affected by bending loads combined with dry and wet cycles of sulfate. In this paper, three sets of specimens with different water–cement ratios were designed. This study applied 20% and 40% of the ultimate bending load as a continuous bending load to the cementitious material specimens for a sulfate erosion test. It was discovered that the specimens' porosity, flexural strength, and compressive strength all tended to improve initially before declining as the cementitious material was degraded in the sulfate solution aged. The flexural strength of the cementitious materials declined as the bending load increased, and their internal sulfate ion concentration rose. A transport model of sulfate ions in cementitious materials under the coupling effect of bending load and sulfate erosion was created by combining the improved version of Fick’s second law and chemical reaction kinetics. The simulation results show that the ion transport properties of sulfate ions in cementitious materials are in accordance with the experimental laws. These research results formed the basis of the unified standards for the coupling of load dry and wet cycle systems, as well as evaluating the durability of cementitious materials under corrosive environments.

Solid asperity interactions are common and inevitable under severe loading conditions for any lubricated contact. Heavy-duty machine components (gear, bearings etc.) generally operate under Mixed Lubrication, where uneven surface features contact each other when generated fluid pressure is not enough to support the external load. The Reynolds equation is commonly used to simulate smooth lubricated contacts numerically. In rough lubricated interfaces where opposite surface asperities make contact, the Reynolds equation alone cannot accurately predict pressure using the traditional numerical simulation method. In this paper, Lubrication-Contact interface conditions (LCICs) have been implemented and extended to solve the multiple asperity contact problem using the full-multigrid approach. The developed novel algorithm has significantly accelerated the solution process and improved the accuracy and efficiency of pressure calculation for fluid-solid sub-interactions that can occur under ML regions. The Finite Difference Method (FDM) results have been compared with Computational Fluid Dynamics (CFD) simulation to validate the newly developed model. Hence, the proposed optimized solution method will provide valuable insight to researchers and industry engineers interested in simulating the ML problem where the effect of the fluid-solid interface can be captured effectively to improve reliability in the calculation of the life expectancy of the lubricated parts.

Keywords: underground engineering; numerical simulation; excavation length effect, major principal stress; displacement; damage initiation; CPU time

Recently, Indium Tin Oxide, a highly transparent, well conductive, and CMOS-compatible material, has been paying strong attention to the thermo-optic controlled silicon photonics industry because it allows a miniature of the gap between the core silicon and the heater, thus enabling reducing the electric power consumption and enhancing the switching speed. In this article, we propose an ultralow loss and small-size ITO microheater for the phase shift tuning. The designated microheater is manipulated in realizing a numerical co-design of compact and high bandwidth three-mode converter and three-mode selective router. Simulation results illustrate the 3-dB bandwidth for the three-mode converter and three-mode selective router as much as 100-nm and 40-nm during crosstalk under -25 dB, respectively. Besides, co-designed devices attain relatively large fabrication tolerances corresponding to width and height tolerances of ±50 nm and ±5 nm. In addition, the proposed devices consumed less than 90 mW total power consumption and took a fast switching time below 8 μs. Moreover, both two co-designs can be integrated into an estimated compact footprint of 8 μm2160 μm. Such excellent performances demonstrate the attractive potential of ITO as low-loss thermo-optic phase shifters and open an alternative way for enabling ultrafast and high-speed mode division multiplexing systems and very large-scale photonic integrated circuits.

Predictive simulation of concurrent debris flow using only pre-disaster information has proven to be difficult as a result of problems in predicting the location of debris-flow initiation (i.e., slope failure). However, because catchment topography has concave characteristics, with all channels in a catchment joining each other as they flow downstream, it is possible to predict damage to downstream area using relatively inaccurate initiation points. Based on this, this paper presents methodologies employing debris-flow initiation points generated randomly using statistical slope failure prediction. A many-case simulation across numerous initiation points was performed to quantify the effect of slope-failure location in terms of deviations in the predicted water level and terrain deformation. It was found that the relative standard deviation diminished as the points approached the downstream area, indicating a location-based predictability effect.

In view of the complexity of the pile foundation underpinning structure system and the stringent requirements of the construction process, this paper briefly describes the necessity of introducing epoxy resin reinforcing adhesive of planting rebar in the design of pile foundation underpinning beam structure to im-prove the mechanical properties of the underpinning beam new and old concrete joint surfaces and proposes a new type of pile foundation underpinning beam system construction method by “chiseling + prestressed reinforcement + epoxy resin reinforcing adhesive”. This paper uses an actual pile foundation underpinning project of an urban overpass as a prototype, designs and creates a model structure with a similarity ratio of 1/6, and performs repeated pro-gressive static loading tests to study the load carrying capacity, displacement change, and other properties of the underpinning structure, as well as analyses and distorts the overall working performance and failure mode of them. On this basis, the prototype structure's finite element analysis model was built, and the finite element analysis results were compared with the test results to get the mechanical properties and deformation characters of the actual pile foundation under-pinning structure system corresponding to the actual underpinning beam load. This paper's study can lay the theoretical and experimental foundation for the smooth development of similar projects.

Molten salt reactors have gained substantial interest in the last years due to their flexibility and their potential for simplified closed fuel cycle operation for massive net-zero energy production. However, a zero-power reactor experiment will be an essential first step into the process delivering this technology. The choice of the optimal reflector material is one of the key issues for such experiments since on the one hand it offers huge cost saving potential due to reduced fuel demand, on the other hand an improper choice of the reflector material can have negative effects on the quality of the experiments. The choice of the reflector material is for the first time introduced through a literature review and a discussion of potential roles of the reflector. The 2D study of different potential reflector materials has delivered a first down selection with SS 304 as representative for stainless steel, lead, copper, graphite, and beryllium oxide. A deeper look identified in addition iron-based material with high Si content. The following evaluation of the power distribution has shown the strong influence of the moderating reflectors creating a massively disturbed power distribution with a peak at the core boundary. This effect has been confirmed through a deeper analysis of the 2D multi-group flux distribution which lead to the exclusion of the BeO and the graphite reflector. The most promising materials identified have been SS 304, lead, and copper. The final 3D Monte-Carlo study demonstrated that all three materials have the potential to reduce the required amount of fuel by up to 60% compared NaCl which has been used in previous studies and is now taken as reference A first cost analysis has identified the SS 304 reflector as the most attractive solution. The results of the 2D multi group deterministic study and the 3D multi group Monte-Carlo study have been confirmed through a continuous energy Monte-Carlo reference calculation showing only minor differences.

In this study, a Traveling-Wave Mach-Zehnder intensity Modulator (TW-MZM) was designed and optimized for six different electro-optical (EO) crystals: Lithium Niobate (LNB), Potassium Niobate (KNB), Lithium Titanate (LTO), Beta Barium Borate (BBO), Cadmium Telluride (CdTe), and Indium phosphide (InP). The performance of each EO crystal, including optical and radio frequency (RF) loss, applied voltage, and modulation bandwidth, was estimated and compared. The results suggested that, in theory, KNB, LTO, BBO, and CdTe have the potential to outperform LNB. However, it should be noted that the loss associated with KNB and LTO is comparable to that of LNB. The findings demonstrated that BBO and CdTe exhibit a modulation bandwidth exceeding 100 GHz and demonstrate the lowest loss among the considered crystals based on the assumed geometry.

In this paper, low circumferential reciprocating load foot-scale tests were performed on two truncated PHC B 600 130 tubular piles with bearing nodes to characterize the damage process and morphology of the specimens and to investigate the load-carrying performance of the members. The test results reveal that under the action of tensile-bending-shear loading, the bearing concrete in the node area buckles and is damaged, the anchored reinforcement in the node area yields, the constraint is weakened, an articulation point is formed, and the node rotational capacity increases. When the embedment depth increases from 200 mm to 300 mm, the ultimate bearing capacities of the positive and negative nodes increase by 57.60% and 54.60%, respectively. A numerical simulation is used to verify the test results. Considering the three types of piles with truncated nodes, the numerical simulation is used to analyze the node-bearing capacity at different embedment depths. Finally, two preferred node types are proposed as follows: pipe pile core-filled longitudinal reinforcement anchored into the bearing node and pipe pile body longitudinal reinforcement anchored into the bearing node + pipe pile core-filled longitudinal reinforcement anchored into the bearing node, with preferred embedment depths of 350 mm and 200 mm, respectively.

This paper proposes a lightweight joint with bamboo culm cross connection, which is constructed by screwing one side of the screw into the other side of the wooden plug, its simple construction makes it easy to manufacture and cost-effective. This form connects adjacent bamboo culms to form corner joints, and bolt connects adjacent bamboo culm frames to form edge joints, to explore the mechanical properties of the combination joints formed by corner joints and edge joints, by combining experiments and numerical simulations, the method discovered and explained the relationship and mechanism between the number and position of bolts and the stiffness of edge joints. A calculation model for frame-unit bamboo culm members considering semi-stiffness of joints is proposed, and the conversion equations between linear stiffness of corner and edge joint and their rotational stiffnesses are derived. By establishing the series and parallel relationship between the corner and edge joints in the assembled members, a generalized relational equation between the total stiffness of the assembled joint and the stiffness of the corner and edge joints is derived. A numerical simulation method for frame-unit bamboo culm members with semi-rigid joints is proposed, which can obtain the stiffness calculation formula of edge joints and the average rotational stiffness value of semi-rigid corner joints. A finite element analysis method based on semi-rigid joints is proposed for frame-unit bamboo culm members, and the internal force sketches and calculation methods for bamboo culms and joints are presented, which can be used for the internal force analysis and design of frame-unit bamboo culm lattice structures.

The first paper of this two-part series paper discussed the development of a novel lightweight 3D wood dowel-reinforced glass epoxy hybrid composite material (3DdrFRP) and its manufacturing procedures. It also experimentally compared the performance of scaled utility poles made from conventional 2D E-glass epoxy and 3DdrFRP materials. In the second part, we developed robust finite element (FE) models in LS-DYNA, calibrated them based on experimental results, and used them to simulate the performance of equivalent 2D and 3D poles, proving the integrity of the numerical model. Additionally, we developed a simplified analytical calculation method for engi-neers to determine the stiffness of 3D-DrFRP poles accurately and quickly.

Bistatic scattering coefficient have important application of ocean active microwave remote sensing. In this paper, a general expression of the composite scattering coefficient for multiple dielectric targets of one-dimensional fractal sea surface is derived by MOM method. Secondly, the bistatic scattering coefficient is computed, there are two class missile targets and one class ship target of one-dimensional fractal sea surface, and the influence of the water dielectric constant, fractal dimension, wind speed, the target dielectric constant and spatial position is discussed, and the corresponding conclusions are given. The proposed algorithm is able to solve some composite scattering problems, such as “dielectric or conductive object + rough surface”, “dielectric or conductive floating object +rough ”and it has certain generalization and reference.

Lamb waves occur in thin-walled structures in two wave modes, the symmetric and antisymmetric mode. Their oscillation on the structures‘ surfaces is either in phase (symmetric) or shifted by a phase angle of π (antisymmetric). In this work, a method is developed to compare the surfaces‘ oscillation phase relation. It is based on the evaluation of time signals regarding the instantaneous phase angle using the continuous wavelet transformation and as a comparative method the short-time Fourier transformation. For this purpose, numerical simulations utilizing the finite element method provide time signals from the top and bottom surface of different thin-walled structures. They differ with respect to their material settings and laminate configurations. The numerically obtained time signals are evaluated by the developed methods. The occurring oscillation phase differences on the top and bottom surface are studied and both methods are compared. Subsequently, the oscillation phase is evaluated experimentally for the wave propagation in a fiber metal laminate. It is shown that the method based on the continuous wavelet transformation is suitable for the evaluation of oscillation phase relations in time signals. Additionally, it is proven that fiber metal laminates show only two phase relations which indicates the occurrence of Lamb waves.

This work investigates how integrated polyimide inlays with applied sensor bodies influence the guided ultrasonic wave propagation in narrow glass fiber-reinforced polymer specimens. Preliminary numerical simulations indicate that in a damping-free specimen, the inlays show reflections for the S0-mode propagation. Hence, an air-coupled ultrasonic technique and a 3D laser Doppler vibrometer measurement are used to measure different parts of the propagating waves’ displacement field after burst excitation at different frequencies. No significant reflections on the inlay can be seen in the experiments. However, it is shown that the reflections from the strip specimen’s narrow width cause periodical reflections that superimpose with the excited wave fronts. A continuous wavelet transformation in the time-frequency domain filters discontinuities from the measurement signal and is used for reconstruction of the time signals. The reconstructed signals are used in a spatial continuous wavelet transformation to identify the occurring wavelengths and hence to prove the assumption of reflections from the narrow edges. Since the amplitude of the reflections identified in the numerical data at the polyimide inlays are an order of magnitude smaller than the excited wave packages, it is concluded that material damping of the epoxy resin matrix extincts possible reflections from the inlays.

The work presents an approach to instrument the load sensing bearings for automotive applications for estimation of the loads acting on the wheels. The system comprises fiber-optic sensors based on addressed fiber Bragg structures (AFBS) with two symmetrical phase shifts. A mathematical model for load-deformation relation is presented, and the AFBS interrogation principle is described. The simulation includes (i) modeling of vehicle dynamics in a split-mu braking test, during which the longitudinal wheel loads are obtained, (ii) the subsequent estimation of bearing outer ring deformation using a beam model with simply supported boundary conditions, (iii) the conversion of strain into central wavelength shift of AFBS, and (iv) modeling of the beating signal at the photodetector. The simulation results show that the estimation error of the longitudinal wheel force from the strain data acquired from a single measurement point was 5.44% with root-mean-square error of 113.64 N. A prototype load sensing bearing was instrumented with a single AFBS sensor and mounted in a front right wheel hub of an experimental vehicle. The experimental setup demonstrated comparable results with the simulation during the braking test. The proposed system with load-sensing bearings is aimed at estimation of the loads acting on the wheels, which serve as input parameters for active safety systems, such as automatic braking, adaptive cruise control, or fully automated driving, in order to enhance their effectiveness and safety of the vehicle.

Polydimethylsiloxane (PDMS) is one of the most popular elastomers and has been used in different fields, especially in biomechanics research. Among the many interesting features of this material, its hyperelastic behaviour stands out, which allows the use of PDMS in various applications, like the ones that mimic soft tissues. However, the hyperelastic behaviour is not linear and needs detailed analysis, especially the characterization of shear strain. In this work, two approaches, numerical and experimental, were proposed to characterize the effect of shear strain on PDMS. The experimental method was implemented as a simple shear testing associated with 3D digital image correlation and was made using two specimens with two thicknesses of PDMS (2 and 4 mm). A finite element software was used to implement the numerical simulations, in which four different simulations using the Mooney-Rivlin, Yeoh, Gent, and Polynomial hyperelastic constitutive models were performed. These approaches showed that the maximum value of shear strain occurred in the central region of the PDMS, and higher values emerged for the 2 mm PDMS thickness. Qualitatively, in the central area of the specimen, the numerical and experimental results have similar behaviours and the values of shear strain are close. For higher values of displacement and thicknesses, the numerical simulation results move further away from experimental values.

In the steeply inclined and extremely thick coal seams (SIETCS) mined using the horizontal sublevel top-coal caving (HSTCC) method, the uncertainty of gas emission is a safety threat to the mining operations. In order to reduce the occurrence of accidents, the determination of gas emission is crucial. In this paper, we first proposed a prediction model for workers at the floor coalbed to calculate gas emission on site. We then put forward a finite element numerical simulation for researchers to predict gas emission from the floor coalbed. At last, we measured gas emitted from the floor coalbed of SIETCS in Wudong Coal Mine in a specific mining period and used the data to verify the applicability and accuracy of these two gas-emission prediction methods. The results showed that the gas emission from Wudong Coal Mine was 1.08 m³/min calculated based on the prediction model and 1.07 m³/min obtained using the user-defined integration method. Both methods have their own advantages, disadvantages and applicable objects, and are important in predicting gas emission from SIETCS mined using HSTCC method.

The object of this work is to determine the correlation on the Nusselt number on the individual rows of a four-row tubular finned heat exchanger with continuous fins with a staggered tube arrangement using CFD modelling. Correlations for calculating Darcy-Weisbach friction factors on individual tube rows were also determined. Relationships for the Nusselt number and friction factor derived for the entire exchanger based on CFD modelling were compared with those available in the literature determined using experimental data. The maximum relative differences between the Nusselt number for a four-row exchanger determined experimentally and by CFD modelling are in the range from 22% for a Reynolds number based on a tube's outside diameter of 1,000 to 30% for a Reynolds number of 13,000. The maximum relative differences between the friction factor for a four-row exchanger determined experimentally and by CFD modelling are in the range of 50% for a Reynolds number based on a tube outer diameter of 1,000 to 10% for a Reynolds number of 13,000. The CFD modeling performed shows that in the range of Reynolds numbers based on hydraulic diameters from 150 to 1,400, the Nusselt number for the first row in a four-row finned heat exchanger is about 22% to 15% higher than the average Nusselt number for the entire exchanger. In the range of Reynolds number changes based on hydraulic diameter from 2,800 to 6,000, the Nusselt numbers on the first and second rows of tubes are close to each other. Correlations on Nusselt numbers and friction factors derived for individual tube rows can be used in the design of plate-fin and tube heat exchangers used in equipment such as air-source heat pumps, automotive radiators, air-conditioning systems and in air hot-liquid coolers. In particular, the correlations can be used to select the optimum number of tube rows in the exchanger.

In the process of use and manufacture, carbon fiber foam sandwich structures were often damaged by low-energy impact, resulting in performance degradation. Therefore, it was necessary to study the damage caused by low-speed impact of composite sandwich structures. In this paper, based on Hashin failure criterion, an equivalent finite element model of carbon fiber foam sandwich panel under low velocity impact was established. The model was used to simulate the damage of foam sandwich panel with [±45°/±45°/ (core) /±45°/±45°] ply structure under the impact energy of 10.58J, 21.17J, 31.75J and 42.34J. The simulation results of impact damage depth were compared with the experimental results. The error was less than 10%, which proved the rationality of the impact equivalent model. The model was used to predict and analyze the damage of foam sandwich panels with [±45°/ (core) /±45°], [±45°/ (0°, 90°) / (core) /±45°] and [±45°/ (0°, 90°) (core) / (0°, 90°) /±45°] ply structures under 21.17J impact energy. By comparing and analyzing the damage situation, impact force response time and impact velocity response time, the low energy impact resistance was analyzed. The results showed that increasing the number of ply structure of [±45°] can reduce the impact damage degree and improve the bearing capacity of sandwich panels.

Promoting the use of solar energy resources has always faced the challenges of instability and supply-demand mismatch. The key to solving these issues is to efficiently store and utilize solar energy resources using high-performance heat storage devices. This study designed a high-performance shell-and-tube phase change thermal storage device and established a numerical model using ANSYS software to summarize the device's dynamic melting law. To verify the accuracy of the numerical simulation, a performance testing platform for the phase change thermal storage device was built to investigate the impact of factors such as inlet water temperature, inlet water flow rate, type of heat storage, and initial temperature of the device, and to reveal the change law of the device's performance. The results show that the inlet water temperature has the most significant impact on the device's heat storage and release performance. When the device's heat storage or release is used for heating, changing the inlet water flow rate has a weak and limited effect on the device's performance. However, when the device's heat release is used to provide domestic hot water, increasing the makeup water temperature and reducing the inlet water flow rate can significantly improve the device's effective heat release. Furthermore, based on the experimental validation of the model's correctness, this study further simulated and studied the impact of different factors on the device's heat storage process to optimize its structural design and provide technical references for the device's actual operation and installation. The results show that the placement of fins has a negligible effect on the performance of the heat storage device while reducing the fin spacing and increasing the fin thickness can significantly improve the melting efficiency of the phase change material (PCM). Additionally, the heat storage characteristics of the device are significantly better in the vertical installation mode than in the horizontal installation mode. This study provides theoretical guidance and technical references for the design and use of phase change thermal storage devices.

The paper is dedicated to the topical problem of examining permafrost state and the processes of its geocryological changes by means of geophysical methods. To monitor the cryolithozone, we propose and scientifically substantiate a new technique of pulsed electromagnetic cross-well sounding. Based on the vector finite-element method, we created a mathematical model of the cross-well sounding process with a pulsed source in a three-dimensional spatially heterogeneous medium. A high-performance parallel computing algorithm was developed and verified. Through realistic geoelectric models of permafrost with a talik under a highway, constructed following the results of electrotomography field data interpretation, we numerically simulated the pulsed sounding on the computing resources of the Siberian Supercomputer Center of SB RAS. The simulation results suggest the proposed system of pulsed electromagnetic cross-well monitoring to be characterized by a high sensitivity to the presence and dimensions of the talik. The devised approach can be oriented to addressing a wide range of issues related to monitoring permafrost rocks under civil and industrial facilities, buildings and constructions.

Human number understanding is thought to rely on the analogue number system (ANS), working according to Weber’s law. We propose an alternative account, suggesting that symbolic mathematical knowledge is based on a discrete semantic system (DSS), a representation that stores values in a semantic network, similar to the mental lexicon or to a conceptual network. Here, focusing on the phenomena of numerical distance and size effects in comparison tasks, first we discuss how a DSS model could explain these numerical effects. Second, we demonstrate that DSS model can give quantitatively as appropriate a description of the effects as the ANS model. Finally, we show that symbolic numerical size effect is mainly influenced by the frequency of the symbols, and not by the ratios of their values. This last result suggests that numerical distance and size effects cannot be caused by the ANS, while the DSS model might be the alternative approach that can explain the frequency-based size effect.

Understanding the dynamic interaction between piles and surrounding soil under vehicular impacts is essential for effectively designing and optimizing soil-embedded vehicle barrier systems. The complex behavior of pile-soil systems under impact loading, attributed to the soil’s nonlinear behavior and large deformation experienced by both components, presents significant simulation challenges. Popular computation techniques, such as the Updated Lagrangian Finite Element Method (UL-FEM), encounter difficulties in scenarios marked by large soil deformation, e.g., impacts involving rigid piles. While mesh-free particle and discrete element methods offer another option, their computational demands for field-scale pile-soil impact simulations are considerable. We introduce the erosion method to bridge this gap by integrating UL-FEM with an erosion algorithm designed for simulating large soil deformations during vehicular impacts. Validation against established physical impact tests confirmed the method’s effectiveness for flexible and rigid pile failure mechanisms. Additionally, this method was used to investigate the effects of soil mesh density, soil domain sizes, and boundary conditions on the dynamic impact response of pile-soil systems. Our findings provide guidelines for optimal soil domain size, mesh density, and boundary conditions. This investigation sets the stage for improved, computationally efficient techniques for the pile-soil impact problem, leading to better pile designs for vehicular impacts.

This paper reviews how dynamically adaptive wavelet methods can be designed to simulate atmosphere and ocean dynamics in both flat and spherical geometries. We highlight the special features that these models must have in order to be valid for climate modelling applications. These include exact mass conservation and various mimetic properties that ensure the solutions remain physically realistic, even in the under-resolved conditions typical of climate models. Particular attention is paid to the implementation of complex topography in adaptive models. Using \textsc{wavetrisk} as an example, we explain in detail how to build a semi-realistic global atmosphere or ocean model of interest to the geophysical community. We end with a discussion of the challenges that remain to developing a realistic dynamically adaptive atmosphere or ocean climate models. These include scale-aware subgrid scale parameterizations of physical processes, such as clouds. Although we focus on adaptive wavelet methods, many of the topics we discuss are relevant for adaptive mesh refinement (AMR).

Space-based gravitational wave detection is extremely sensitive to disturbances. The Keplerian configuration cannot accurately reflect the variations in spacecraft configuration. Planetary gravitational disturbances are one of the main sources. Numerical simulation is an effective method to investigate the impact of perturbation on spacecraft orbits. This study shows that, in the context of the Taiji project, Earth’s gravity is an essential factor in the change in heliocentric formation configuration, contributing to the relative acceleration between spacecrafts in the order of O(10−6)m·s−2. Considering 00:00:00 on October 27, 2032 as the initial orbiting moment, under the influence of Earth’s gravitational perturbation, the maximum relative change in armlengths and variation rates of armlengths for Taiji is 1.6×105km, 32m·s−1 respectively, compared with the unperturbed Keplerian orbit. Additionally, by considering the gravitational perturbations of Venus and Jupiter, the armlength and relative velocity for Taiji are reduced by 16.01% and 17.45%, respectively, compared with when only considering that of Earth. The maximum amplitude of the formation motion indicator changes with the orbit entry time. Results show that the relative velocity increase between the spacecrafts is minimal when the initial orbital moment occurs in July. Moreover, the numerical simulation results are inconsistent when using different ephemerises. The differences between ephemeris DE440 and DE430 are smaller than those between DE440 and DE421.

Cladding is typically used to protect components from wear and corrosion while also improving the aesthetic value and reliability of the substrate. The cladding process induces significant residual stresses due to the temperature difference between the substrate and the clad layer. However, these residual stresses could be effectively utilized by modifying processes and geometrical parameters. This paper introduces a novel methodology for using the weld-cladding process as a cost-effective alternative to various existing reinforcement techniques. The numerical analyses are performed to maximize the reinforcement of a cylindrical tool. The investigation of how the weld cladding develops compressive stresses on the specimen in response to a change in the weld beads and the welding sequence is presented. For the benchmark shape, experimental verification of the numerical model is performed. The impact of the distance between the weld beads and the effect of the tool diameter is numerically investigated. Furthermore, the variation in compressive stresses due to temperature fluctuations during the extrusion process has been evaluated. The results showed that adequate compressive stresses are generated on the welded parts through the cladding process after cooling. Hence, the targeted reinforcement of the substrate can be achieved by optimizing the welding sequence and process parameters.

Nanoparticle (NP) transport is increasingly relevant to subsurface engineering applications such as aquifer characterization, fracture electromagnetic imaging and environmental remediation. An efficient field-scale simulation framework is critical for predicting NP performance and designing subsurface applications. In this work, for the first time, a streamline-based model is presented to simulate NP transport in field-scale subsurface systems. It considers a series of behaviors exhibited by engineered nanoparticles (NPs), including time-triggered encapsulation, retention, formation damage effects and variable nanofluid viscosity. The key methods employed by the algorithm are streamline-based simulation (SLS) and an operator-splitting (OS) technique for modeling NP transport. SLS has proven to be efficient for solving transport in large and heterogeneous systems, where the pressure and velocity fields are firstly solved on underlying grids using finite-difference (FD) methods. After tracing streamlines, one-dimensional (1D) NP transport is solved independently along each streamline. The adoption of OS enhances flexibility for the entire solution procedure by allowing different numerical schemes to solve different governing equations efficiently and accurately. For the NP transport model, an explicit FD scheme is used to solve the advection term, an implicit FD scheme is used for the diffusion term and an adaptive numerical integration is used to solve the retention terms. The model is implemented in an in-house streamline-based code, which is verified against analytical solutions, a commercial FD reservoir simulator (ECLIPSE) and an academic FD colloid transport code (MNMs). For a 1D homogeneous case, the effluent breakthrough curves (BTC) produced by the in-house simulator are in good agreement with the analytical solution and MNMs, respectively. For a two-dimensional (2D) heterogeneous case, the BTC and concentration pattern of the in-house simulator all match well with the solution produced by commercial simulator. Simulations on a synthetic three-dimensional (3D) nanocapsule application engineering design case, are performed to investigate the effect of fluid and NP properties on the displacement pattern of an existing subsurface fluid.

Summary: Studying biological systems generally relies on computational modeling and simulation, e.g., for model-driven discovery and hypothesis testing. Progress in standardization efforts led to the development of interrelated file formats to exchange and reuse models in systems biology, such as SBML, the Simulation Experiment Description Markup Language (SED-ML), or the Open Modeling EXchange format (OMEX). Conducting simulation experiments based on these formats requires efficient and reusable implementations to make them accessible to the broader scientific community and to ensure the reproducibility of the results. The Systems Biology Simulation Core Library (SBSCL) provides interpreters and solvers for these standards as a versatile open-source API in Java™. The library simulates even complex bio-models and supports deterministic Ordinary Differential Equations (ODEs); Stochastic Differential Equations (SDEs); constraint-based analyses; recent SBML and SED-ML versions; exchange of results, and visualization of in silico experiments; open modeling exchange formats (COMBINE archives); hierarchically structured models; and compatibility with standard testing systems, including the Systems Biology Test Suite and published models from the BioModels and BiGG databases. Availability and implementation: SBSCL is freely available at https://draeger-lab.github.io/SBSCL/.

Bare slope instability is a prevalent concern. The root system of, herbaceous vegetation enhances the shear strength of shallow–slope soil. Indoor experiments were conducted on rootless undisturbed soil (RUS) and undisturbed soil with a root system (USRS) using a triaxial compression apparatus to analyze the slope stability of composite soil with a Tagetes erecta root system. Significance tests and correlation analysis of the factors affecting shear performance were conducted using R software. The slope reinforcement, effect by the plant root system was simulated under 24 working conditions using the MIDAS finite element method. The results revealed the influence of the–root content (RC), moisture content (MC), and stress on the shear strength of USRS, the contribution degree, and the variables’ influences on slope stability. Both RUS and USRS exhibited strain hardening during shearing. The internal friction angle (φ) and cohesion (c) of USRS were negatively and positively correlated with the RC and MC (root burial depth), respectively, and a good fit was obtained for the relationship. The maximum deviatoric stress during shear failure was 1.29 times higher for USRS than for RUS. The RC (root depth) was positively correlated with the slope safety coefficient and the slope of the line under different working conditions, whereas the slope gradient was negatively correlated with the slope safety coefficient. The reinforcement effect by the root system resulted in a 13.2% increase in the safety coefficient and improved stability of slopes with a gradient larger than 1.5%. This article investigated the mechanism of the root–soil system and, the effects of different influencing factors on the shear strength of the soil, and slope stability. The findings provide new insights into shallow slope stability in practical slope protection projects.

Transition between free-surface and pressurized flows is an crucial phenomenon in many hydraulic systems, including water distribution systems, urban drainage systems, etc. During the transition, the force exerted on the structures changes drastically, thus it is meaningful to simulate this process. However, severe numerical oscillations are widely observed behind filling-bores, causing unphysical pressure variations and even computation failure. In this paper, some oscillation-suppressing approaches are reviewed and evaluated on a benchmark model. Then a new oscillation-suppressing approach is proposed to admit numerical viscosity when the water surface is at proximity of conduct roof which has first order accuracy. This approach adds numerical viscosity when water surface is at the proximity of conduct roof. It can sufficiently suppress numerical oscillations under an acoustic wave speed of 1000m/s and is simple to apply. In comparison with two experiments, the simulation results of this method show good agreement and little numerical oscillations. The results in this paper can help readers to choose an appropriate oscillation-suppressing method to improve the robustness and accuracy of flow regime transition simulations.

Several factors impact the durability of concrete bridge decks, including traffic loads, fatigue, temperature changes, environmental stress, and maintenance activities. Detecting problems such as corrosion, delamination, or concrete degradation early on can lower maintenance costs. Nondestructive evaluation (NDE) techniques can detect these issues at early stages. Each NDE method, meanwhile, has limitations that reduce the accuracy of the assessment. In this study, multiple NDE technologies were combined with machine learning algorithms to improve the interpretation of half-cell potential (HCP) and electrical resistivity (ER) measurements. A parametric study was performed to analyze the influence of five parameters on HCP and ER measurements, such as degree of saturation, corrosion length, delamination depth, concrete cover, and moisture condition of delamination. The results were obtained through finite element simulations and used to build two machine learning algorithms, a classification algorithm and a regression algorithm, based on the Random Forest methodology. The algorithms were tested using data collected from a bridge deck in the BEAST® facility. Both machine learning algorithms were effective in improving the interpretation of ER and HCP measurements using data from multiple NDE technologies.

We provide a very general review of the resonant transmission line method for optical fiber problems. The method has been found to work seamlessly for a variety of difficult problems including elliptical and eccentric core fibers as well as “holey”, photonic crystal fibers. A latest version has been shown to offer great versatility with respect to cases of unconventional, inhomogeneous index profiles.

In this paper major machine learning (ML) tools and the most important applications developed elsewhere for numerical weather and climate modeling systems (NWCMS) are reviewed. NWCMSs are briefly introduced. The most important papers published in this field in recent years are reviewed. The advantages and limitations of the ML approach in applications to NWCMS are briefly discussed. Currently, this field is experiencing explosive growth. Several important papers are published every week. Thus, this paper should be considered a simple introduction to the problem.

The availability of rail infrastructure resources is a major driver of rail operations performance. To evaluate the impact of infrastructure provision, network simulation models can be used to accurately represent train traffic behavior in a wide range of scenarios. However, performing this task can result in a problem of high combinatorial nature as the number of factors and their associated levels increase. This requires more sophisticated techniques such as experimental design formulations or optimization modeling in order to yield satisfactory results. Yet the research in network simulation models for rail systems has hitherto been limited to simple what-if analysis, made up from few factors that cannot represent the whole spectrum of interventions. This is especially critical in closed-loop rail systems where trains are subject to various interferences. Local improvements can be misleading as the queues are merely transferred within the network. Considering this, we propose a hybrid simulation-optimization model to aid the strategic decision of minimizing supplementary capital costs in a heavy-haul Brazilian railroad under construction. As soon as the railroad is completed, investments in both loading and unloading rail terminals will be necessary. First, we developed a representative and flexible model capable of dealing with complex relations between variable infrastructure provision and the resulting operational performance. Then, we simulated this system to prove that the current set of proposed infrastructure resources cannot meet the transportation demands. Afterwards, we demonstrate that local improvements can be delusive as the queues are shifted from loading to unloading operations, reciprocally. Then, we solve an optimization model to define the minimal supplementary investment in order to meet the commercial goals of mining companies. This is done by choosing the best trackage configuration, equipment quantity and capacity and fleet sizing in 3 different production scenarios. The best values of the objective function were found by improving both loading and unloading equipment and increasing the number of trains.

When there is uncertainty in the value of parameters of the input random components of a stochastic simulation model, two-level nested simulation algorithms are used to estimate the expectation of performance variables of interest. In the outer level of the algorithm (n) observations are generated for the parameters, and in the inner level (m) observations of the simulation model are generated with the value of parameters fixed at the value generated in the outer level. In this article, we consider the case in which the observations at both levels of the algorithm are independent, showing how the variance of the observations can be decomposed into the sum of a parametric variance and a stochastic variance. Next, we derive central limit theorems that allow us to compute asymptotic confidence intervals to assess the accuracy of the simulation-based estimators for the point forecast and the variance components. Under this framework, we derive analytical expressions for the point forecast and the variance components of a Bayesian model to forecast sporadic demand; and we use these expressions to illustrate the validity of our theoretical results by performing simulation experiments using this forecast model.

Background: Simulation plays a crucial role in health studies, as it helps medical students apply their theoretical knowledge in real-life situations. Moulage is one of the techniques that helps in making simulation more realistic or high-fidelity. It uses special effects to emulate wounds for a better understanding of what the wound is like visually. Still, moulage is expensive, time-consuming, resource-intensive, and requires the training of staff, which is why we need to find low-cost substitutes for moulage materials. Method: When searching the database “PubMed” for the terms “Low-cost and Medical moulage”, we retrieved 222 studies, out of which when excluding results not related to low-cost, we obtained 62 studies, from which when removing studies that do not contain information regarding moulage, we found two papers, after referring to citations and cited articles of those papers, we ended up with six studies. Based on the selected articles and additional articles sourced from their reference list, a total of 11 studies were included in the review. Results: We understand that moulage is a technique that helps make simulations come alive, but the resources required to use it are at times, expensive, which is why we need to find methods to do low-cost moulage, and many studies address that it can be as simple as using homemade ingredients. Students from a previous study have talked about their opinions regarding the realistic component of moulage and whether if it is any different from other moulages. Most of the students agreed that the moulage ranked well in face and content validity. However, further innovations must be introduced in the field to be widely spread and lead to newer opportunities. Conclusion: Although the research done under moulage is limited, it is accepted that moulage is helpful for simulation-based studies and that low-cost moulage can help make medical studies a better experience for students studying it. Students have a favorable opinion on the realistic aspect of the low-cost moulage applied to them. Newer methods can be introduced to moulage, and it can be implemented in low-income countries.

Introduction: Alzheimer's disease (AD) is the first cause of dementia worldwide without any current curative treatment. Facing an increasing prevalence and its associated costs, AD represents a public health challenge. Usual diagnostic methods still rely on extended interviews and paper tests provided by an exterior examiner. We aim to create a novel, quick cognitive-screening tool on a numerical tablet. Methods: This program, built and edited with Unity®, runs on Android® for the Samsung Galaxy Tab S7 FE®. Composed of seven tasks inspired by the Mini-Mental Status Examination and the Montréal Cognitive Assessment, it browses several cognitive functions. The architectural design of this tablet application is distinguished by its multifaceted capabilities, encompassing not only seamless offline functionality but also a mechanism to ensure the singularity of data amalgamated from diverse sites. Additionally, a paramount emphasis is placed on safeguarding the confidentiality of patient information in the healthcare domain. Furthermore, the application empowers individual site managers to access and peruse specific datasets, enhancing their operational efficacy and decision-making processes. We performed a preliminary usability assessment among healthy subjects. Results: 24 healthy patients were included with a final F-SUS score of "excellent". Participants perceived the tool as simple to use and achieved the test in a mean time of 142 seconds. No technical errors occurred. Conclusion: These preliminary results suggest that our new assessment on a numerical tablet allows a short cognitive screening.

This paper presents the results of laboratory tests of CFRP (carbon fibre-reinforced polymer) laminates, which allowed the development of numerical material models. The obtained data were used in a further stage to perform numerical simulations of four variants of medical tabletops differing, among other features, in the shape of the cross-section. Maximum deflections and effort in the composite material were analyzed. The final step was to perform a laboratory test for one of the tabletop versions, the results of which confirmed the correctness of the numerical calculations. This work is aimed at both researchers and designers involved in the practical application of fibre-reinforced polymer matrix composites.

The fractional derivatives are a generalization the derivatives of integer order and find applications in studying memory processes in various scientific fields. Numerical methods are used to solve and analyze fractional models of real world problems. In this paper, we consider an approximation of the Caputo fractional derivative and its asymptotic formula, whose generating function is the polylogarithmic function. In the paper, we prove the convergence of the approximation and derive an estimate for the error and order. We consider an application of the approximation for the construction of finite difference schemes for numerical solution of the two-term ordinary fractional differential equation and the time-fractional Black-Scholes equation for option pricing. The properties of the approximation are used to prove the convergence of the methods used for numerical solution of the fractional differential equations. The theoretical results for the error and order of the methods are illustrated by the results of numerical experiments.

We measure the accelerated cosmic expansion rate of the late-time Universe and derive constraints on cosmological parameters from the final baryon acoustic oscillation (BAO) uncorrelated measurements of different surveys after two decades of dedicated spectroscopic observation combined with the Pantheon sample of Type Ia supernovae, the Hubble diagram of gamma-ray bursts & quasars data, the Cosmic Chronometers data, and the recent Hubble constant value measurement from the Hubble Space Telescope and the SH0ES Team as an additional prior. In Λ cold dark matter (ΛCDM) scenario, the model fit yields Ωm=0.313±0.034 and ΩΛ=0.672±0.025. Combining BAO with CC+Pantheon+QSR+GRB data sets we get H0=69.21±1.22 km s−1 Mpc−1, rd=133.46±2.49 Mpc. For the a flat wCDM model, we get w=−1.111±0.030. For a dynamical evolution of dark energy in a flat w0waCDM cosmology, we get wa=−0.292±0.167. We apply the Akaike information criteria probe to compare the three models, and see that all models are favored and cannot be discarded from the current data.

Tsunami modeling and simulation has changed in the past few years more than it had in decades, especially so with respect to coastal inundation. Among other things, this change is supported by the approaching era of exa-scale computing, whether via GPU or more likely forms of hybrid computing whose presence is growing across the geosciences. For reasons identified across this review, exa-scale computing efforts will impact the on-shore, highly turbulent r\'egime to higher degree than the 2D shallow water equations used to model tsunami propagation in the open ocean. This short review describes the different approaches to tsunami modeling from generation to impact and underlines the limits of each model based on the flow r\'egime. Moreover, from the perspective of a future comprehensive multi-scale modeling infrastructure to simulate a full tsunami, we underline the current challenges associated with this approach and review the few efforts that are currently underway to achieve this goal. A table of existing tsunami software packages is provided along with an open Github repository to allow developers and model users to update the table with additional models as they are published and help with model discoverability.

A method for solving the turbulence equations embedded in the sigma ocean general ocean circulation model is proposed. Like the general circulation model, the turbulence equations are solved using the splitting method by physical processes. The turbulence equations are split into two main stages describing transport-diffusion and generation-dissipation processes. Parameterization of turbulence in the framework of equations allows, at the generation-dissipation stage, to use both numerical and analytical solutions and to ensure high efficiency of the algorithm. The results of large-scale ocean dynamics simulation taking into account the parameterization of vertical turbulent exchange are considered. Numerical experiments were carried out using k-omega turbulence model embedded to the Institute of Numerical Mathematics Ocean general circulation Model (INMOM). Both the circulation and turbulence models are solved using the splitting method with respect to physical processes. The coupled model is used to simulate the hydrophysical fields of the North Atlantic and Arctic Oceans for 1948--2009. The model has a horizontal resolution of 0.25 degree and 40 sigma-levels along the vertical. The sensitivity of the solution to the changes in mixing parameterization is studied. Experiments demonstrate that taking into account the climatic annual mean buoyancy frequency improves the reproduction of large-scale ocean characteristics. There is a positive effect of Prandtl number variations for reproducing the upper mixed layer depth. The experiments also demonstrate the computational effectiveness of the proposed approach in solving the turbulence equations.

The ferrocell is an optical viewing device that interacts with a magnetic field and one or more light sources to produce a real-time visual light display. Although this device has been extensively studied by several researchers, a proper computer simulation replicating this optical effect has not yet been presented. Using numerical methods and the law of reflection, a computer simulation was developed that shows that the light patterns as seen in the ferrocell are primarily caused by light reflections off the ferrofluid nano-particles that self organize into needle-like filaments and align along magnetic flux lines in the presence of a magnetic field.

Hydrothermal /super critical processes are important process to synthesize materials which are otherwise difficult to form under normal conditions. A mathematical model is developed using standard transport equations to calculate the time for heating of hydrothermal reactor and computer simulation of the model was carried out in SOLIDWORKS® to validate it. The materials used to form reactor vessel were stainless steel (outer body) and TEFLON (PFA) (inner vessel). It was shown that composite wall, its geometry, construction & properties greatly affect the time and pattern of heat transfer. The time calculated and pattern generated were found to be in good agreement with experimental values.

U-turns and left turns are sometimes forbidden even though it increases travel distances. The greater travel distances are sometimes outweighed by the improved movement through intersections due to there being fewer conflicting lanes of traffic. One can, further, forbid straight-throughs. Restricting a sufficient number of turns can make intersections free from crossing lanes of traffic (``zero traffic conflict,'' ``ZTC"), though there may still be merging lanes of traffic. It's possible to make \begin{it}all\end{it} intersections in a road \begin{it}network\end{it} ZTC. However, keeping all destinations accessible and travel distances moderate requires careful selection of allowed driving directions and turning directions. We demonstrate through numerical microscopic and macroscopic simulations that there are road networks and ranges of traffic loads for which, in comparison with conventional schemes, ZTC road network can carry approximately $50$\% more vehicular traffic without incurring gridlock.

At container terminals, many cargo handling processes are interconnected and take place in parallel. Within short time windows, many operational decisions need to be taken considering both time and equipment efficiency. During operation, many sources for disturbance exist. These are the reason why perfectly coordinated processes are possibly unraveled. An approach that considers disturbance factors while optimizing a given objective is simulation-based optimization. This study analyses simulation-based optimization as a procedure to simultaneously scale the number of utilized equipment and to adjust the choice and tuning of operational policies. The four meta-heuristics Tree-structured Parzen Estimator, Bayesian Optimization, Simulated Annealing, and Random Search guide the simulation-based optimization process. The results show that simulation-based optimization is suitable to identify the amount of required equipment and well-performing policies. Thereby, there is no clear ranking which of the meta-heuristics finds the best approximation of the optimum. The approximated optima suggest that pooling terminal trucks as well as a yard block assignment close to the quay crane is preferable. With an increasing number of quay cranes, the number of optimal terminal trucks for each quay crane decreases as well as the range of truck utilization within one experiment.

During the last decades, the production systems have developed different strategies to increase their competitiveness in the global market. In a manufacturing and services systems, Lean Manufacturing has been consolidated through the correct implementation of its tools. The present paper presents a case study developed in a Food Packer company where a Simulation Model was considered as an alternative to reduce the waste time generated by the poor distribution of operations and transportation areas for a product within the factory. As a matter of fact, the company has detected problems on the layout distribution that prevents to fulfill the market demand. In addition, the principal aim was to create a simulation model to test different hypothetical scenarios and alternative designs for the layout distribution without modifying its facilities. Moreover, the implemented methodology was based on classical models of simulation projects and a compendium of the manufacturing systems optimization by simulation process used during the last ten years. Also, a mathematic model supported by the Promodel ® simulation software was developed considering the company characteristics; along with the model development, it was possible to compare the production system performance from the percentage of used locations, the percentage of resources utilization, the number of finished products, and the level of Work in Process (WIP). Finally, the verification and validation stages were performed before running the scenarios in the real production area. The results generated by the implementation of the project represent an increase of 68% in the production capacity and a reduction of 5% in the WIP. In addition, both outcomes are associated with the resources management, which were reassigned to other production areas.

The results of numerical experiments with the chemistry-climate model of the Institute of Numerical Mathematics of the Russian Academy of Sciences - Russian State Hydro-Meteorological University (INM-RSHU CCM) in comparison with the MERRA2 reanalysis data are presented. To assess the impact of sea surface temperature (SST) on stratospheric processes and the ozone layer, numerical experiments were carried out for scenarios corresponding to the El Niño and La Niña Southern Oscillation phases. It is shown that the El Niño phase contributes to the enhancement of heat and mass transfer to the polar stratosphere, which strengthen the Brewer-Dobson circulation and the flux of wave activity that affect the zonal wind. As a result, during El Niño, the probability of sudden stratospheric warming increases and the stratospheric polar vortex (SPV) weakens, re-sulting in an increase in total polar stratospheric ozone. The La Niña phase, on the contrary, is accompanied by a weakening of heat and mass transfer from the troposphere to the stratosphere, as a result of which the stratospheric polar vortex strengthens and the total column ozone decreases. It is shown that the effect associated with the Southern Oscillation is more pronounced in the Northern Hemisphere than in the Southern Hemisphere. Numerical experiments were also carried out for scenarios in which the sea surface temperature was set corresponding to the early 1980s, and the results were compared with calculations in which the SST was set corresponding to the late 2010s. This allowed us to assess the influence of the multiyear trend in the SST increase on stra-tospheric processes and the ozone layer. It was shown that the SST increase is most pronounced in the Arctic, which corresponds to the phenomenon of "Arctic amplification", and therefore, the heat and mass transfer to the stratosphere increases in the Northern Hemisphere, which contributes to some weakening of the SPV and increase of the total column ozone. But, compared to the Southern Oscillation, the influence of the SST trend on the SPV and total column ozone is much weaker and is observed mainly in the Northern Hemisphere.

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rain water. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima (2019). The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increases approximately 17%~18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.

This study assesses the impact of incorporating an adaptive learning mechanism into an agent-based model (ABMS) simulating behavior on a university campus during the course of a pandemic outbreak, with a particular case on the COVID-19 pandemic. The aim is to reduce overcrowding and infections on campus through the use of Reinforcement Learning (RL). Our findings indicate that RL is a viable approach for effectively representing agents’ behavior within this context. The results reveal specific temporal patterns of overcrowding violations. While our study successfully mitigated campus crowding, it had limited influence on altering the course of the epidemic. This highlights the necessity for comprehensive epidemic control strategies that consider the role of individual decision-making influenced by adaptive learning, along with the implementation of targeted interventions. This research significantly contributes to our understanding of adaptive learning within complex systems and offers valuable insights for shaping future public health policies in similar community settings. Future research directions encompass exploring various parameter settings and updating representations of the disease’s natural history.

In this work, new refinements of some numerical radius inequalities are proved. Namely, new improvements and refinements purify the recent inequalities of some famous inequalities concerning the numerical radius of Hilbert space operators. The proven inequalities in this work are not only an improvement over old inequalities, but rather they are stronger than them. Several examples that support the validity of our results are established as well.

Groundwater models serve as support tools to among others: assess water resources, evaluate management strategies, design remediation systems and optimize monitoring networks. Thus, the assimilation of information from observations into models is crucial to improve forecasts and reduce uncertainty of their results. As more information is collected routinely due to the use of automatic sensors, data loggers and real time transmission systems; groundwater modelers are becoming increasingly aware of the importance of using sophisticated tools to perform model calibration in combination with sensitivity and uncertainty analysis. Despite their usefulness, available approaches to perform this kind of analyses still present some challenges such as non-unique solution for the parameter estimation problem, high computational burden and a need of a deep understanding of the theoretical basis for the correct interpretation and use of their results, in particular the ones related to uncertainty analysis. We present a brief derivation of the main equations that serve as basis for this kind of analysis. We demonstrate how to use them to estimate parameters, assess the sensitivity and quantify the uncertainty of the model results using an example inspired by a real world setting. We analyze some of the main pitfalls that can occur when performing such kind of analyses and comment on practical approaches to overcome them. We also demonstrate that including groundwater flow estimations, although helpful in constraining the solution of the inverse problem as shown previously, may be difficult to apply in practice and, in some cases, may not provide enough information to significantly constrain the set of potential solutions.

This paper presents a hydrodynamic numerical model for a pitching wave energy converter (WEC). The model uses potential wave theory and is based on Cummins' equation, with nonlinear hydrostatic restoring stiffness and excitation forces based on instantaneous body position and water surface elevation. The numerical model can include non-linear forces, like quadratic drag, power-take-off and other forces that may account for unknown viscous effects observed in experiments. The paper discusses the applicability and limitations of the code and presents the cases where assumptions and simplifications can be made. The goal is to conclude on the simplest, yet accurate, version of the model by evaluating its accuracy using experimental data. The case study for validation is Floating Power Plant's (FPP's) WEC [1]. In the full-scale commercial project, FPP's device consists of a semisubmersible platform hosting a wind turbine (5-8MW) and 4 WECs, each one connected to the platform by a rotation shaft. Due to the configuration of the platform, strong interactions occur between the WECs and the structure, as they are very closely spaced. In order to validate a numerical model able to simulate these hydrodynamic interactions, wave basin experiments with a similar but simplified setup were performed.

Some cognitive functions, shared by humans and certain animals, were acquired early in the course of phylogeny and, in humans, are operational in their primitive form shortly after birth. This is the case for the quantification of discrete objects. The further phylogenetic evolution of the human brain allows such functions to be reconstructed in a much more sophisticated way during child development. Certain functional characteristics of the brain (plasticity, multiple cognitive processes involved in the same response, interactions and substitution relationships between those processes) provide degrees of freedom that open up the possibility of different pathways of reconstruction. The within- and between-individual variability of these developmental pathways offers an original window on the dynamics of development. Here, I will illustrate this theoretical approach to cognitive development—which can be called “reconstructivist” and “pluralistic”—using children's construction of number as an example.

By installing FBG sensors on the geogrids, smart geogrids can both reinforce and monitor the stability for geogrid-reinforced slopes. In this paper, a geogrid-reinforced sand slope model test was conducted in the laboratory and fiber Bragg grating (FBG) sensing technology is used to measure the strain distribution of the geogrid. Based on the model test, the performance of the reinforced soil slope is simulated by finite element software Midas-GTS, and the stability of the reinforced soil slope is analyzed by strength reduction method. The relationship between the geogrid strain and safety factor is set up. The results indicate that the measured strain and calculated results agree very well. The geogrid strain measured by FBG sensor can be applied to evaluate the stability of geogrid-reinforced sand slopes.

In this paper the attention is focused on the analysis and the optimization of energy flows in networked systems via a fluid-dynamic model. In particular, a cost functional that represents a term proportional to the kinetic energy of an energy system is studied. First, the functional is optimized for a simple network having a unique node, with an incoming arc and two outgoing ones. The optimization deals with distribution coefficients and explicit solutions are found. Then, the global optimization is obtained using the local optimal parameters at the various nodes of the system. Considering the case study of an energy hub, interesting results are obtained for the whole network, proving the correctness of the proposed approach.

We present a new model formulation for a class of capacitated lot-sizing problem considering setup costs, product returns, and remanufacturing (CLSP-RM). We investigate a broad class of instances that fall into two groups, in the first group we can reformulate the problem with a relaxation and test whether the original problem is solvable. The relaxation gives near optimal solutions and the solution of this class does not give any difficulty to known solvers such as Cplex, Gurobi or Xpress. The second group of instances are of category NP and will be solved with a simple period-by-period simulation

This paper presents the common methods and corresponding drawbacks concerning nonlinear analysis of fluxgate excitation circuits and emphasizes the importance of nonlinear analysis for these circuits. With regard to the nonlinearity of the excitation circuit, this paper proposes the use of the core-measured hysteresis curve for mathematical analysis and the use of a nonlinear model that considers the coupling effect of the core and winding and influence of the historical magnetic field on the core for simulation analysis. The feasibility of mathematical calculations and simulation for the nonlinear study of fluxgate excitation circuit is verified via experiments. The results demonstrate that, in this regard, the simulation is better than a mathematical calculation. The simulation and experimental results of the excitation current and voltage waveforms under different excitation circuit parameters and structures are essentially consistent with each other, thereby verifying the effectiveness of the nonlinear excitation analysis method.

A rehabilitation technique for asphalt pavements with geosynthetic is the application of impregnated nonwoven geotextiles between deteriorated and new asphalt overlays. The performance investigation of impregnated geotextiles proves that they are enhancing in mechanical and hydraulic properties. Although, the installation process may cause severe impacts on these materials’ performance. During the installation, the geotextile suffers damage due to the traffic of high load vehicles, as compactors and pavers, and the friction with granular materials found under its layer or poured above it. This paper aims to investigate how the damage caused by granular materials on nonwoven geotextiles impregnated with different asphalt emulsions effect on their strength resistance and permittivity. From two types of nonwoven geotextiles: polypropylene and polyethylene terephthalate, the comparison uses geotextiles in three conditions: not impregnated, impregnated with asphalt emulsion of rapid setting, and impregnated with asphalt emulsion changed by an elastomeric polymer. Part of the samples followed the damage according to ISO 10722 procedure, placed between three different scenarios of granular materials, applying gravel, sand, and clay. After the damage process, the samples were submitted to mechanical and hydraulic properties evaluations.

We introduce a mission design for an interstellar expedition to nearby earth-like exoplanets, which our analysis determined to be Tau Ceti and Gliese 667C, at the time of analysis in 2013. We review the research problems in propulsion and AGI that must be addressed to launch an AI guided interstellar probe within 100 years. We propose a new semi-autonomous agent approach for intelligent control of the spacecraft. We introduce the concept of a semi-autonomous agent as having built-in safety guarantees that constrain operation. An autonomous agent case study is presented formulating the objective, constraints, AGI implementation of the agent based on Solomono's Alpha architecture, and adding specicity. We discuss the training required to reach human-level and trans-sapient levels of intelligence which corresponds to an entire crew of AI experts specialized in elds such as astrophysics, astromechanics, astrobiology, quantum physics, computer science, molecular biology, and so forth. We project the feasibility of the human-level AI technology based on empirical ndings in neuroscience, and nd that it should be feasible by 2030. We analyze Solomono's innity point hypothesis in light of Koomey's law about energy eciency of computing and nd that the trends in 2013 indicated an early singularity by 2035, which implies that we might encounter physical bottlenecks which will decelerate computing technology improvements signicantly. We recommend thus year 2040 for launching the probe by which date other required technologies will have been developed. We discuss the scenario of a virtual crew made of brain simulations, which is a bio-information based AI approach. We detail the subsystems of command and control, communication, scientic instrumentation, power, propulsion, navigation, and shielding. We propose a variation of ICAN-II/AIMStar propulsion which uses a positron source instead of anti-protons to initiate micro-fusion reactions. We combine the positron initiated fusion pulse propulsion scheme with a miniaturized version of the Daedelus fusion thruster obtaining high performance. We derive two mission proles one for fusion pulse propulsion, and the yet hypothetical Q-Thruster. Fusion thruster requires 132.2 years for Tau Ceti, and 233.2 years for Gliese 667C, while Q-Thruster takes only 42.3 years for Tau Ceti, and 62.5 years for Gliese 667C. We also discuss extended roles for intelligent interstellar probes such as self-reproduction via nanotechnology, refueling, construction, robotic bodies, and transmission of brain simulations.

Whether evaluating gridded population dataset estimates (e.g. WorldPop, LandScan) or household survey sample designs, a population census linked to residential locations are needed. Geolocated census microdata data, however, are almost never available and are thus best simulated. In this paper, we simulate a close-to-reality population of individuals nested in households geolocated to realistic building locations. Using the R simPop package and ArcGIS, multiple realizations of a geolocated synthetic population are derived from the Namibia 2011 census 20% microdata sample, Namibia census enumeration area boundaries, Namibia 2013 Demographic and Health Survey (DHS), and dozens of publicly available spatial datasets. Realistic household latitude-longitude coordinates are manually generated based on public satellite imagery. Simulated households are linked to latitude-longitude coordinates by identifying distinct household types with multivariate kmeans analysis, and modelling a probability surface for each household type using Random Forest machine learning methods. We simulate five realizations of a synthetic population in Namibia's Oshikoto region, including demographic, socioeconomic and outcome characteristics at the level of household, woman, and child. Comparison of variables in the synthetic population were made with 2011 census 20% sample and 2013 DHS data by primary sampling unit/enumeration area. We found that synthetic population variable distributions matched observed observations and followed expected spatial patterns. We outline a novel process to simulate a close-to-reality microdata census geolocated to realistic building locations in a low- or middle-income country setting to support spatial demographic research and survey methodological development while avoiding disclosure risk of individuals.

Blazars show rapid and high amplitude variability. In this work , Fermi daily light curve of 130 sources are analyzed, distribution of daily variability are compared with each other by using Kolmogorov-Smirnov (K-S) test. results show: 1)Some pairs of the distributions are similar; 2) In most cases, the distributions are not Gaussian.

In this work, we'll present the power spectra density, auto-correlation function, dentrended fluctuation analysis and multifractal spectrum are performed to the daily light curves of Blazars monitored by Fermi LAT. Some signs of power law are found.

Intersections within urban centers do not allow all citizens to move in a fluid manner. In this sense, this paper proposes a queuing network model based on Kendall's notation for the intersection of two urban streets (East 53rd Street and East 56th Street) in Panama City. A set of traffic lights operating under a fixed time scheme controls the vehicular flow at the intersection. The objective is to optimize the vehicular flow at the intersection by minimizing the waiting time of the vehicles using mathematical models, Linear Regressor Model, and simulations performed in MATLAB evaluating the waiting time experienced by the vehicles. Based on the results obtained, the optimal signal timing of the traffic lights is determined to minimize the waiting time for both streets.

The today competitive advantage of Ready-made garment industries depends on the ability to improve the efficiency and effectiveness of resource utilization. Ready-made garment industries have long historically adopted fewer technological and process advancement as compared to automotive, electronics and semiconductor industries. Simulation modeling of garment assembly line system has attracted a number of researchers as one way for insightful analysis of system behaviour and improving its performance. However, most of simulation studies have considered ill-defined experimental design which cannot fully explore the assembly line design alternatives and does not uncover the interaction effects of the input variables. Simulation metamodeling is an approach to assembly line design which has recently been of interest to so many researchers. However, its application in garment assembly line design has never been well explored. In this paper, simulation metamodeling of trouser assembly line with 72 operations has been demonstrated. The linear regression metamodel technique with resolution-V design was used. The effects of five factors: bundle size, job release policy, task assignment pattern, machine number and helper number on the production throughput of the trouser assembly line were studied. The increase of 28.63% of the production throughput was achieved for the best factors’ setting of the metamodel.

Due to the continued deepening of today’s mining projects, there is a need to develop new or improved rockbolts that are strong and yielding and have high energy absorption when exposed to dynamic loading. Impact tests can provide useful information about the dynamic response of rockbolts but most laboratory tests involve high costs in preparation and result validation. Numerical modeling is an alternative that, in addition to complementing laboratory results, can be used to represent the process of deformation and energy absorption of support elements. In this paper the implementation and results obtained from a finite difference (FDM) numerical model are presented. The model functions as a simulation tool to illuminate all the elements that conform the large-scale (1:1) impact test and their behavior and influence on the dynamic response of a threadbar bolt (22 mm nominal diameter). The model was calibrated using published results and based on these results as well as parametric analysis, the response of each component (steel tube, grout, and bolt) could be identified and its behavior in terms of absorbed energy and displacement could be observed. Results show the model can provide important preliminary information to make design decisions about support elements design.

This study explores how the properties of heater materials impact nucleate pool boiling using a comprehensive simulation model. The model integrates well-known heat transfer mechanisms, allowing us to assess the effects of two distinct heater materials. Findings indicate that materials with higher thermal conductivity, such as copper, notably improve refrigeration efficiency in nucle- ate boiling. The study provides insights into the relationship between bubble growth, microlayer recovery beneath a bubble, temperature fluctuations, and heater properties. Comparisons between copper and silicon oxide underscore variations in bubble frequency, attributed to differences in bubble growth time, microlayer recovery time, and material-dependent behavior. The influence of neighboring bubbling sites, especially pronounced in silicon oxide due to its low thermal conductivity and diffusivity, was observed. Temperature variations in such materials became highly visible due to their significant inertia in recovery. Simulation results align well with empirical correlations, confirming the model’s versatility in capturing the intricate phenomena of nucleate pool boiling.

It is difficult to obtain necessary information accurately from Social Networking Service (SNS) while raising children, and it is thought that there is a certain demand for the development of a system that presents appropriate information to users according to the child's developmental stage. There are still few examples of research on knowledge extraction that focuses on childcare. This research aims to develop a system that extracts and presents useful knowledge for people who are actually raising children, using texts about childcare posted on Twitter. In many systems numbers in text data are just strings like words and are normalized to zero or simply ignored. In this paper, we created a set of tweet texts and a set of profiles created according to the developmental stages of infants from "0-year-old child" to "6-year-old child". For each set, we used ML algorithms such as NB (Naive Bayes), LR (Logistic Regression), ANN (Approximate Nearest Neighbor algorithms search), XGboost, RF (random forest), decision trees, and SVM (Support Vector Machine) to compare with BERT, a neural language model, to construct a classification model that predicts numbers from "0" to "6" from sentences. The accuracy rate predicted by the BERT (Bidirectional Encoder Representations from Transformers) classifier was slightly higher than that of the NB, LR, ANN, XGboost, RF, decision trees, and SVM classifiers, indicating that the BERT classification method was better.

Since the discovery of graphene, due to its excellent optical, thermal, mechanical and electrical properties, it has a broad application prospect in energy, materials, biomedicine, electromagnetism and other fields. A great quantity of researches on the physical mechanism of graphene has been applied to engineering in electromagnetism and optics. To study the properties of graphene, different kinds of numerical methods have been developed for simulating the electromagnetic field effects of graphene, and equivalent boundary conditions have been employed to replace graphene in the computational domain. In this work, the numerical methods with equivalent boundary conditions are reviewed, and some examples are provided to illustrate their applicability.

It is difficult to obtain necessary information accurately from Social Networking Service (SNS) while raising children, and it is thought that there is a certain demand for the development of a system that presents appropriate information to users according to the child's developmental stage. There are still few examples of research on knowledge extraction that focuses on childcare. This research aims to develop a system that extracts and presents useful knowledge for people who are actually raising children, using texts about childcare posted on Twitter. In many systems numbers in text data are just strings like words and are normalized to zero or simply ignored. In this paper, we created a set of tweet texts and a set of profiles created according to the developmental stages of infants from "0-year-old child" to "6-year-old child". For each set, we used Support Vector Machine (SVM), and Bidirectional Encoder Representations from Transformers (BERT), a neural language model, to construct a classification model that predicts numbers from "0" to "6" from sentences. The accuracy rate predicted by the BERT classifier was slightly higher than that of the SVM classifier, indicating that the BERT classification method was better.

In this study, we have considered for numerical solution of a Poisson equation in a domain. we have presented a first and second order finite difference method for solving the system of the intial boundary value. We have presented the numerical solution of the Poisson equations in a two-dimensional finite region. Numerical Solution and exact solution for the presented method has been compared and the figures presented. The present error analysis tables demonstrate the efficiency of the method.

The previously developed models for fuel droplet heating and evaporation processes, mainly the Discrete Multi Component Model (DMCM), and Multi-Dimensional Quasi-Discrete Model (MDQDM) are investigated for the aerodynamic combustion simulation. The models have been recently improved, and generalised for a broad range of bio-fossil fuel blends so that the application areas are broadened with increased accuracy. The main distinctive features of these models are that they consider the impacts of species thermal conductivities and diffusivities within the droplets to account for the temperature gradient, transient diffusion of species and recirculation. A formulation of fuel surrogates is made, using the recently introduced model, referred to as ‘’Complex Fuel Surrogate Model (CFSM)’’ and analysing their heating, evaporation, and combustion characteristics. The CFSM is aimed to reduce the full composition of fuel to a much smaller number of components based on their mass fractions, and to formulate fuel surrogates. Such approach has provided a proof of concept with the implementation of the developed model into a commercial CFD code ANSYS-Fluent. A case study is made for the CFD modelling of gas-turbine engine using kerosene fuel surrogate. The surrogate is proposed using the CFSM. The model is implemented into ANSYS-Fluent via a user-defined function to provide the first full simulation of the combustion process. Detailed chemical mechanism is also implemented into ANSYS Chemkin for the combustion study.

Fires are complex multi-physics problems that span wide spatial scale ranges. Capturing this complexity in computationally affordable numerical simulations for process studies and “outer-loop” techniques (e.g., optimization and uncertainty quantification) is a fundamental challenge in reacting flow research. Further complications arise for propagating fires where a priori knowledge of the fire spread rate and direction is typically not available. In such cases, static mesh refinement at all possible fire locations is a computationally inefficient approach to bridging the wide range of spatial scales relevant to fire behavior. In the present study, we address this challenge by incorporating adaptive mesh refinement (AMR) in fireFoam, an OpenFOAM solver for simulations of complex fire phenomena involving pyrolyzing solid surfaces. The AMR functionality in the extended solver, called fireDyMFoam, is load balanced, models gas, solid, and liquid phases, and allows us to dynamically track regions of interest, thus avoiding inefficient over-resolution of areas far from a propagating flame. We demonstrate the AMR capability and computational efficiency for fire spread on vertical panels, showing that the AMR solver reproduces results obtained using much larger statically refined meshes, but at a substantially reduced computational cost. We then leverage the computational efficiency of the AMR solver to demonstrate an optimization framework for fire suppression based on the open-source Dakota toolkit.

We investigated preschool-aged children’s understanding of early fractional tasks and how that performance correlates with fine motor skills and use of gestures while counting. Participants were 33 preschoolers aged 4 to 5 in two Southeastern public elementary schools. Children were tested individually in an interview-like setting. Mathematics tasks were presented in a paper and pencil format and the Grooved Pegboard test assessed fine motor skills. Finally, utilization of gestures was evaluated by taking a behavioral rating of the child’s hand morphology, accuracy of gestures, and synchrony of gestures and spoken word while performing a counting task. Results indicate performance on fractional reasoning tasks significantly predicts both fine motor ability and accuracy of gestures.

There are many criterion to generalize the concept of numerical radius; one of the most recent interesting generalization is what so called the generalized Euclidean operator radius. Simply, it is the numerical radius of multivariable operators. In this work, several new inequalities, refinements and generalizations are established for this kind of numerical radius.

In this work, some numerical radius inequalities based on the recent Dragomir extension of Furuta's inequality are obtained. Some particular cases are also provided.

Currently, the use of numerical models for reproducing the landscape evolution of a river basin is part of the day-by-day research activities of fluvial engineers and geomorphologists. However, despite landscape modelling is based on a rather long tradition, and scientists and practitioners are trying to schematize the processes involved in the evolution of a landscape since decades, there is still the need for improving both the knowledge of the physical mechanisms and their numerical coding. The present review focuses on the first aspect, discussing the main components of a landscape evolution model and their more common schematizations, presenting possible open questions to be addressed towards an improvement of the reliability of such kind of models in describing the fluvial geomorphology.

A simple optimization strategy for the computation of 3D finite-differencing kernels on many-cores architectures is proposed. The 3D finite-differencing computation is split direction-by-direction and exploits two level of parallelism: in-core vectorization and multi-threads shared-memory parallelization. The main application of this method is to accelerate the high-order stencil computations in numerical relativity codes.

Small and micro hydropower represents an attractive solution for electricity generation, with low cost and low environmental impact. The pump-as-turbine (PAT) approach has promise in this application owing to its low purchase and maintenance costs. In this paper, a new method to predict the inverse characteristic of industrial centrifugal pumps is presented. This method is based on results of simulations performed with commercial three-dimensional CFD software. Model results have been first validated in pumping mode using data supplied by pump manufacturers. Then, results have been compared to experimental data for a pump running in reverse condition. Experimentation has been performed on a dedicated test bench installed in the Department of Civil Construction and Environmental Engineering of the University of Naples Federico II. Three different pumps, with different specific speeds, have been analyzed. Using the model results, the inverse characteristic and the best efficiency point have been evaluated. Finally, results of this methodology have been compared to prediction methods available in the literature.

The difficult current environmental situation, caused by construction industry residues containing ceramic materials could be improved by using these materials as recycled aggregates in mortars, with their processing causing a reduction in their use in landfill, contributing to recycling and also minimizing the consumption of virgin materials. Although some research is currently being carried out into recycled mortars, little is known about their stress-strain (σ-ε); therefore this work will provide the experimental results obtained from recycled mortars with recycled ceramic aggregates (with contents of 0, 10, 20, 30, 50 and 100%), such as: the density, the compression strength, as well as the σ-ε curves representative of their behavior. The values obtained from the analysis process of the results are those of: σ (elastic ranges and failure maximum), ε (elastic ranges and failure maximum), and Resilience and Toughness; in order to finally obtain, through numerical analysis, the equations to predict their behavior (related to their recycled content). At the end of the investigation it is established that mortars with recycled ceramic aggregate contents of up to 20% could be assimilated just like mortars with the usual aggregates, and the prediction equations produced could be used in cases of similar applications.

This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 hours. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-hour forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-hour forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station.

3D bioprinting, like 3D printing, is a process that builds structures by depositing material layer by layer. In the specific case of bioprinting, these layers are composed of a biocompatible material together with living cells, allowing the creation of three-dimensional structures that recreate functional tissues and organs. Bioprinting cell-laden structures is complicated by the high rate of cell damage and stress that occurs during the process, caused by the high pressures and stresses to which they are subjected. To minimise damage during the process, it is important to study and optimise certain bioprinting conditions beforehand and to analyse how they affect the cells by means of computational simulations. In this review, both quantitative and qualitative data are collected to improve the nozzle geometry through computational simulation studies. Optimal ranges for nozzle diameter (0.2-1mm) and length (8-10mm; 300-900μm) have been defined, and recommendations for improving nozzle performance during bioprinting, such as the provision of an inner angle of 20-30°, an inner EDTA coating and a shear stress of less than 10kPa, have been gathered. Finally, based on the data collected, a design of experiments is proposed to obtain an optimal bioprinting configuration for a particular bioink.

Given the problem of climate change caused by fossil fuels, there is a need to seek efficient alternative energies that have a lower impact on the environment and are obtained from renewable resources. Biomass gasification technology is attracting constant interest in sustainable energy research as an alternative to traditional combustion technology. Its numerous advantages include the availability of raw materials, reduction in harmful emission streams, performance, and costs. In gasification, thermochemical conversion of the raw material is carried out, obtaining a gaseous product of great interest known as synthesis gas. As this is a growing topic within the global energy framework, it is necessary to achieve the maturity of this technology by working on its weaknesses, mainly in terms of efficiency. The objective of this project was to study the hydrogen production process from the simulation of glucose gasification as a biomass model compound through a static model and a dynamic model, in order to determine the maximum concentration of the resulting components in each model studied. Since glucose is the most abundant component in biomass, it was used as a composite model, these models were built, and the basis for the adaptability of subsequent studies of optimization present one was laid. A H_2:CO ratio of 2.2 and molar fluxes were obtained for H_2,〖CO,CO〗_(2,) 〖CH〗_4 and H_2 O as would generally occur in an organic matter gasification process.

This paper starts with hypothesis (and presents some evidence) that anxiety in migrants is sufficiently important to be modelled. It presents a small (and very incomplete) review of emotion modelling in literature. It asks the question of how to translate these into agent-based modelling, and whether this can be orthogonal to specific modelling of goals and capabilities of agents. This short paper is offered as a motivator for discussion, rather than a discussion of results.

This study aims to understand the contents of debriefing performance in simulation education and its results by comprehensively examining the learning performance of the education ac-cording to the difference in the debriefing methods employed in domestic and overseas nursing simulation training. This is a literature review conducted to identify the effect of debriefing of simulation nursing practice education. The existing literature was found in electronic databases using Pubmed, Embase, MEDLINE complete, PsycINFO, Web of Science, CINAHL, the Cochrane Library, KoreaMed, National Discovery for Science Leaders, and Research Information Sharing Service and the key words were “nurse,” “nursing student,” “simulation,” “simulator,” “stand-ardized patient,” “debriefing.” Finally, 32 studies were analyzed. All the studies were conducted from 2012 to 2021. A total of 11 RCT, 17 quasi-experimental studies, 3 mixed method studies and 1 pilot study were identified. The debriefing process used media, structured questionnaires, and a method of teaching or peer-led debriefing. The outcome variables that were statistically significant were skill, performance, knowledge, problem-solving competency, critical thinking disposition, clinical judgement, self-confidence, satisfaction, and debriefing quality evaluation. It is necessary to educate the debriefers who are responsible for strategy development and meeting effective debriefing goals.

The aim of this paper is to examine the beneficial impact of feedback information in the dynamics of production-inventory control systems. Two production-inventory control system models are analyzed: APIOBPCS and 2APIOBPCS models. The simulation-based experiment designs were conducted by using the state-space equations of the two models. The bullwhip effect as measured by the variance ratio between the order rate and the consumption rate, and inventory responsiveness as measured by the Integral of Absolute Error between the actual and the target levels of inventory, are two metrics used to evaluate the performance of the production-inventory control system in response to a random customer demand. To ensure that both models work under optimal performance, multi-objective particle swarm optimization (MOPSO) is employed to address the problem of tuning the controller’s parameters. The simulation results show the 2APIOBPCS model outperforms the APIOBPCS model at achieving the desired bullwhip effect and being able to provide better inventory responsiveness. The improvement in the inventory responsiveness becomes more significant when the system operates under mismatched lead time and/or an initial condition.

Welded structures are subjected to internal residual stress after manufacturing that may affect the structural strength and normally are associated with an increase on initial geometrical imperfections. This study presents a simplified method to generate an adequate representation of residual stresses on Finite Element models for structural analysis of thin-walled structures and other applications. The results obtained shown that the methodology proposed to introduce residual stresses is simple, accurate and efficient on the modulation of post-welding stresses and their pattern, thus it may be used for simulation of the thermal process.

This publicly available simulation analysis compares baseline construction options versus sustainable options and evaluates both break-even costs as well as environmental effects. The simulation (https://rminator.shinyapps.io/sustain4/) provides users with comparative estimates based upon existing research on costs. This is the first simulation of its type that quantifies multiple sustainable construction options, associated break-even points, and environmental considerations for public use. Results estimate that a 100% solar solution for the baseline 3,000 square foot / 279 square meter house with 2 occupants results in a break-even of 9 years. The simulation includes options for rainwater harvesting or wells, Icynene foam, engineered lumber, Energy Star windows and doors, low flow water fixtures, aerobic / non-aerobic waste treatment or municipal services, and many other options. This is the first simulation of its type to provide publicly available sustainable construction analysis based on research, and it illustrates that sustainable construction might be both green for the environment and green for the pocketbook.

Several factors influence traffic congestion and overall traffic dynamics. Simulation modeling has been utilized to understand the traffic performance parameters during traffic congestions. This paper focuses on driver behavior of route selection by differentiating three distinguishable decisions, which are shortest distance routing, shortest time routing and less crowded road routing. This research generated 864 different scenarios to capture various traffic dynamics under collective driving behavior of route selection. Factors such as vehicle arrival rate, behaviors at system boundary and traffic light phasing were considered. The simulation results revealed that shortest time routing scenario offered the best solution considering all forms of interactions among the factors. Overall, this routing behavior reduces traffic wait time and total time (by 69.5% and 65.72%) compared to shortest distance routing.