We are witnessing a progressive divestment of some institutions with strong traditions and skills in physical modelling and their consequent impoverishment, to the detriment of numerical modelling. For many reasons, the economic imperatives and the exponential growth of computational means and numerical methods should certainly not be excluded. In this work, we aimed to highlight the new requirements of the recent sophisticated developments in physical modelling, precisely due to the new needs imposed on them by mathematical and numerical modelling and the growing risks in civil construction works. In this context, reflections are reported, justified by scientific and real-world examples, on the need for maintenance and reinforcement of investments in physical modelling, both to support the scientific community and to design buildings of significant economic, social and environmental impact.

This paper presents a three-dimensional model of pollutant diffusion in the atmosphere. The model is based on the advection-diffusion equation taking into account pollution sources and decay processes of substances. The numerical solution of the equation is realized using the finite difference method on a three-dimensional grid. The model takes into account the spatial distribution of pollutant concentrations, the influence of wind and atmospheric diffusion. Key parameters include diffusion coefficient, wind speed components, intensity of pollution sources and decay coefficient of substances. Special attention is paid to the vertical distribution of pollutants, which allows for more accurate modeling of atmospheric processes. The presented model can be used to predict the spread of pollutants, assess the impact of different sources on air quality and develop strategies to reduce air pollution in urban and industrial areas.

Numerical modelling is becoming a major tool for supporting environmental studies at different scales, thanks to the capability of up-to-date codes in reproducing the natural behaviour in a quite reliable manner. In evaluating the habitat diversity of anthropized rivers, however, many issues are rising because of the intrinsic complexity of the processes involved. Using a reach of the Po River in Italy as a case study, the present works aims to provide an estimate of the changes of the Eco-Environmental Diversity as a response to different constant flow discharges. The goals are achieved by means of two solvers of the iRIC suite, applied in sequence to firstly simulate the fluvial hydrodynamics and subsequently provide an estimate of the habitat conditions. Despite the simplifications intrinsically present in the models and the ones introduced for practical purposes, the results pointed out that the reduction of the flow discharge recently observed can threat the overall biological status of the river. Because of the modelling uncertainties, on the other side, these preliminary outcomes show the need for more research, both in terms of data acquisition and numerical schematization, for adequately evaluate the effects of transient hydrology on the river ecosystems. Moreover, additional field surveys are necessary to calibrate and validate the used model for having sufficiently reliable estimates.

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.

The electric vehicle (EV) industry challenges battery joining technologies by requiring higher energy density both by mass and volume. Improving the energy density via new battery chemistry would be the holy grail but is seriously hindered and progresses slowly. In the meantime, alternative ways, such as implementing more efficient cell packaging by minimizing the electrical resistance of joints are of primary focus. In this paper we discuss the challenges associated with the electrical characterisation of laser soldered joints in general, and the minimization of their resistive losses, in particular. In order to assess the impact of the joint resistance on the overall resistance of the sample, the alteration in resistance was monitored as a function of voltage probe distance and modelled by finite element simulation. The experimental measurements showed two different regimes: one far from of the joint area and another in its vicinity and within the joints cross section. The presented results confirm the importance of the thickness of the filler material, the effective and the total soldered area, and the area and the position of the voids within the total soldered area in determining the electrical resistance of joints.

Distributions with bounded support show considerable sparsity over those with unbounded support, despite the fact that there are a number of real-world contexts where observations take values from a bounded range (proportions, percentages, and fractions are typical examples). For proportion modelling, a flexible family of two-parameter distribution functions associated with the exponential distribution is proposed here. Mathematical and statistical properties of the novel distribution are examined, including quantiles, mode, moments, hazard rate function, and its characterization. The parameter estimation procedure using the maximum likelihood method was carried out, and applications to environmental and engineering data were also considered. To this end, various statistical tests are used, along with some other information criterion indicators to determine how well the model fits the data. The proposed model is found to be the most efficient plan in most cases for the datasets considered.

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).

A time integration scheme based on semi-Lagrangian advection and Laplace transform adjustment has been implemented in a baroclinic primitive equation model. The semi-Lagrangian scheme makes it possible to use large time steps. However, errors arising from the semi-implicit scheme increase with the time step size. In contrast, the errors using the Laplace transform adjustment remain relatively small for typical time steps used with semi-Lagrangian advection. Numerical experiments confirm the superior performance of the Laplace transform scheme relative to the semi-implicit reference model. The algorithmic complexity of the scheme is comparable to the reference model, making it computationally competitive, and indicating its potential for integrating weather and climate prediction models.

Experimental methodologies for fatigue lifetime prediction are time-intensive and susceptible to environmental variables. While the cohesive zone model is popular for predicting adhesive fatigue lifetime, entropy-based methods have also shown promise. This study aims to provide an understanding of the durability characteristics of CFRP adhesive joints by incorporating an entropy damage model within the context of the finite element method (FEM), examined the effects of different adhesive layer thicknesses on SLS models. As the adhesive layer increased in thickness, DAMAGE VARIABLES initially rose and then declined, peaking at 0.3mm. This finding provides crucial understanding into the stress behavior at the resin-CFRP interface and the resin's fatigue mechanisms.

This study identifies new Alkali Activated Composite Mud Mortar to alternate Cement Mortar used for laying masonry works. This study handles both experimental and numerical analysis of strength and durability for mortar, especially bond strength along mortar and brick joints have studied detail and compared with ANSYS. The bond strength has estimated through the triplet brick prism of shear behavior. The strength and deformation characteristics of masonry constituents obtained from these tests depend on the actual composite conduct of masonry. There is always a good reception for environmentally friendly, low energy, new construction materials, and used in preparing mortar/brick unit combinations all around the world. Also, this study fulfills those requirements. Especially, masonry laid with the mud mortar meets all. Fly Ash, Ground Granulated Blast furnace Slag, and Quarry Dust have utilized the new composites' preparation with 8Molority, 10Molority developed excellent strength. The composite specimens are having compression and bond strength, ranging from 4.84-5.14 and 0.12-0.18N/mm2. The mixed ratio of materials has taken (0.5 parts of Fly Ash, 0.5 parts of Steel Slag, 1.75 parts of Soil, and 0.25 parts of Quarry Dust). The samples tested resistance against acidic, sulfate, and alkalinity indicated PH values less than 7 and 9 simultaneously. Compression strength varied from 10-20% and gained more and fit composite used for mortar in masonry works.

This paper investigates the effects that rain drop erosion has on the integrity of wind turbine materials. This research involves analysis of impact models and theoretical equations to simulate the impact phenomena when a raindrop collides with a wind turbine blade at high speed. Impact phenomena that occur when a raindrop impacts with a wind turbine blade were evaluated. Additionally, the use of various types of software was considered to simulate this impact event. The model results of the raindrop impact with respect to a comparison of the governing equations and impact behaviour are addressed. Future work is outlined including adding variables to the erosion modelling algorithms.

The treatment of critically ill patients remains an evolving and controversial issue. Mechanical circulatory support through a percutaneous approach for the management of cardiogenic shock has taken place in recent years. The combined use of IABP and Impella 2.5 device may have a role to play for this group of patients. A simulation approach may help with a quantitative as-sessment of the achievable degree of assistance. In this paper, we analyse the interaction be-tween Impella 2.5 pump applied as LVAD and IABP using the numerical simulator of the cardi-ovascular system developed in our laboratory. Starting with pathological conditions reproduced using literature data, the simulations were performed setting different rotational speeds for the LVAD and driving the IABP in full mode (1:1) or partial mode (1:2, 1:3 and 1:4). The effects in-duced by drug administration during the assistance were simulated too. The haemodynamic pa-rameters under investigation were: mean aortic pressure, systolic and diastolic aortic pressure, mean pulmonary arterial pressure, mean left and right atrial pressure, cardiac output, cardiac index, left and right ventricular end-systolic volume, left ventricular end-diastolic volume and mean coronary blood flow. The energetic variables considered in the study were: left and right ventricular external work and left and right atrial pressure-volume area. The outcome of our simulations shows that the combined use of IABP and Impella 2.5 achieves adequate support in the acute phase of cardiogenic shock compared to each standalone device. This would allow fur-ther stabilisation and transfer to a transplant centre should escalation of treatment be required.

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.

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.

This study introduces a new approach to modeling galaxy rotation curves by integrating concepts from Perelman’s functional with modifications to General Relativity. While initial numerical simulations indicate that our P-E Integration model may offer a closer fit to observed data than existing theories, we recognize the preliminary nature of these findings [14]. The results, though promising, should be interpreted cautiously. Further validation across different galactic systems and refinement of the model are necessary to confirm its broader applicability [15]. This work aims to contribute to the understanding of galactic dynamics, with the hope of opening new avenues for future research.

This study presents a numerical analysis of rock deformation and damage behaviors induced by dynamic loadings, specifically focusing on the fracturing of tight oil reservoirs. An elastoplastic model based on finite element methods was utilized to simulate the effects of varying loading and perforation parameters. Three distinct scenarios were modeled: a single perforation, boundary loading on three sides, and multiple perforations, each providing unique insights into the mechanical responses of the rock material. The analysis revealed that dynamic effects are highly localized around perforations and loaded boundaries across all scenarios. Acceleration magnitudes are captured with rapid attenuation observed as the distance from the perforation increased. This indicated that the highest stress concentrations and deformation occurred close to the points of loading or perforation. Strain rate analysis in the x direction showed significant fluctuations near the perforations, reflecting intense stress redistributions and compressive deformation, especially prominent in the scenario with multiple perforations. Plastic strain, representing irreversible damage, was found to concentrate near perforation tips and loaded boundaries. However, the pattern of plastic strain accumulation varied: in the small domain scenario with boundary loading, plastic strain did not immediately accumulate next to the loading boundary, whereas in scenarios with single and multiple perforations, damage developed from the loading boundaries. These findings highlight the need for precise control in perforation and dynamic loading processes to manage stress and deformation effectively. It is concluded that optimizing perforation patterns and loading strategies can enhance reservoir stimulation efficiency while minimizing unintended damage to the surrounding formation.

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.

This paper aims to present a robust computational technique utilizing finite difference schemes for accurately solving time fractional reaction-diffusion models, which are prevalent in chemical and biological phenomena. The time-fractional derivative is treated in the Caputo sense, addressing both linear and nonlinear scenarios. The proposed schemes were rigorously evaluated for stability and convergence. Additionally, the effectiveness of the developed schemes was validated through various linear and nonlinear models, including the Allen-Cahn equation, the KPP-Fisher equation, and the Complex Ginzburg-Landau oscillatory problem. These models were tested in one, two, and three-dimensional spaces to investigate the diverse patterns and dynamics that emerge. Comprehensive numerical results were provided, showcasing different cases of the fractional order parameter, highlighting the schemes' versatility and reliability in capturing complex behaviors in fractional reaction-diffusion dynamics.

In this paper we consider constructions of first derivative approximations using the generating function. The weights of the approximations contain the powers of a parameter whose modulus is less than one. The values of the initial weights are determined, and the convergence and order of the approximations are proved. The paper discusses applications of approximations of first derivative for numerical solution of ordinary and partial differential equations and proposes an algorithm for fast computation of the numerical solution. Proofs of the convergence and accuracy of the numerical solutions are presented and the performance of the numerical methods considered is compared with the Euler method. The main goal of constructing approximations for integer-order derivatives of this type is their application in deriving high-order approximations for fractional derivatives, whose weights have specific properties. The paper proposes the construction of an approximation for the fractional derivative and its application for numerically solving fractional differential equations. The theoretical results for the accuracy and order of the numerical methods are confirmed by the experimental results presented in the paper.

This study is dedicated to understanding and simulating the mechanical properties of concrete, with a specific focus on the mesoscopic scale. Investigating concrete at this level involves examining its composition as a heterogeneous amalgamation comprising mortar, aggregates, and the interfacial transition zone (ITZ). Such an approach provides a detailed examination of the material's behavior and attributes. Numerical models are utilized, leveraging the finite element method (FEM), to examine the behavior of concrete. The study employs MATLAB programming to develop three-dimensional models, subsequently subjected to FEM analysis. Various mesoscopic Representative Volume Elements (RVEs) are formulated, encompassing varied shapes and dimensions. The MATLAB framework generates input files for numerical FEM simulations, replicating compression strength tests. As complexity increases with the inclusion of the ITZ, prismatic RVEs are developed. The proposed mesoscopic model establishes a foundational framework for a numerical simulation methodology tailored to laboratory compression tests. It provides detailed insights into concrete behavior, elucidating deformation, and fracture mechanisms. Although not a complete substitute for experimental methods, these models offer a cost-effective and expeditious alternative, pinpointing vulnerable areas and exploring the implications of additional materials on concrete behavior. Experimental data and virtual tests pave the way for mitigating carbon footprint and improving concrete sustainability.

A case of low level windshear at Beijing Daxing International Airport is studied in the present pa-per. It is related to the synoptic scale/mesoscale changes of the airflow pattern over northern China. The shear was captured well by the Doppler LIDAR at the airport and timely alerts had been issued. This study considers the technical feasibility of forecasting the shear feature using a high resolution numerical weather prediction model with a lead time of several hours. It turns out that the shear feature could be forecast well, and is generally consistent with the actual observations. However, there are still discrepancies between reality and the simulation, such as the strength of the shear and persistency of the feature. More cases of windshear at Daxing airport would be studied in the fu-ture in order to understand the nature of windshear over there.

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.

The annual energy matrix has been changing in the last years because of the necessity of less dependence on fossil fuels, which are running out on the planet. Therefore, a study was started to simulate the most efficient production of H2 through COMSOL Multiphysics®, as it is a gas that in the future will be essential to supply the world's energy necessities, due to its easy to get and insert in piped gas pipes. From this study, we were able to present an optimization of parameters that presents good indications of how to obtain efficient hydrogen production in an idealized reactor.

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.

In the present paper, laminar forced convection nanofluid flows in a uniformly heated horizontal tube were revisited by direct numerical simulations. Single and two-phase models were employed with constant and temperature-dependent properties. Comparisons with experimental data showed that the mixture model performs better than the single-phase model in the all cases studied. Temperature-dependent fluid properties also resulted in a better prediction of the thermal field. A particular attention was paid to the grid arrangement. The two-phase model was used then confidently to investigate the influence of the nanoparticle size on the heat and fluid flow with a particular emphasis on the sedimentation process. Four nanoparticle diameters were considered: 10, 42, 100 and 200 nm for both copper-water and alumina/water nanofluids. For the largest diameter dnp = 200 nm, the Cu nanoparticles were more sedimented by around 80 %, while the Al₂O₃ nanoparticles sedimented only by 2.5 %. Besides, it was found that increasing the Reynolds number improved the heat transfer rate, while it decreased the friction factor allowing the nanoparticles to stay more dispersed in the base fluid. The effect of nanoparticle type on the heat transfer coefficient was also investigated for six different water-based nanofluids. Results showed that the Cu-water nanofluid achieved the highest heat transfer coefficient, followed by C, Al₂O₃, CuO, TiO₂, and SiO₂, respectively. All results were presented and discussed for four different values of the concentration in nanoparticles, namely φ = 0, 0.6, 1 and 1.6%. Empirical correlations for the friction coefficient and the average Nusselt number were also provided summarizing all the presented results.

Apart from headwind changes, crosswind changes may be hazardous to the aircraft operation. This paper presents two cases of recently observed crosswind changes from the range height indicator scans of ground-based remote-sensing meteorological equipment, namely, an X-band microwave radar and a short-range LIDAR. Rapidly evolving winds have been observed by the equipment in tropical cyclone situations, and they are found to have high level of turbulence and possibly to be associated with vertically propagating waves. In order to study the feasibility of predicting such disturbed airflow, mesoscale meteorological model and computational fluid dynamics model with high spatial resolution are used in this paper. It is found that the models could capture the rapidly evolving airflow features rather well, including the turbulence level, the waves, the rapidly changing wind speeds and the presence of reverse flow. This paper aims at providing a reference to the airports to consider the feasibility of performing high resolution numerical simulation of rapidly evolving airflow to alert the pilots in advance for airports in complex terrain and setup of buildings.

This study aims to precisely characterize the use of magnetoelectric nanoparticles (MENPs) for stimulating peripheral nerves. Numerical methods were employed to quantify the interaction between MENPs and nervous tissue. The influence of MENPs orientation, concentration and distance was assessed in terms of the external potential distribution exerted by the MENPs, the amplification of the exerted MENPs stimulation required to excite the neural fibers and the current injected into the intracellular space. The results highlight the significance of MENPs concentration for stimulation accuracy and efficiency, the impact of MENPs orientation on the electric potential distribution sensed by the nervous tissue, as well as the importance of the MENPs distance over the fibers’ recruitment. Given the considerable variability in the interaction between MENPs and nerves, our research provides a crucial step towards understanding this interaction, offering quantitative support for the application of MENPs in nervous tissue stimulation.

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.

The paper continues the study of efficient algorithms for the computation of zeta functions over the complex plane. We aim to apply the modifications of algorithms to the investigation of underlying fractal structures associated with the Riemann zeta function. We discuss the computational complexity and numerical aspects of the implemented algorithms based on series with binomial-like coefficients.

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.

A multiscale modeling concept for numerical simulation of multiphysics turbulent flow utilizing map-based advection is described. The approach is outlined with emphasis on its theoretical foundations and physical interpretations in order to establish the context for subsequent presentation of the associated numerical algorithms and the results of validation studies. The model formulation is a synthesis of existing methods, modified and extended in order to obtain a qualitatively new capability. The salient feature of the approach is that time advancement of the flow is fully resolved both spatially and temporally, albeit with modeled advancement processes restricted to one spatial dimension. This one-dimensional advancement is the basis of a bottom-up modeling approach in which three-dimensional space is discretized into under-resolved mesh cells, each of which contains an instantiation of the modeled one-dimensional advancement. Filtering is done only to provide inputs to a pressure correction that enforces continuity and to obtain mesh-scale-filtered outputs if desired. The one-dimensional advancement, the pressure correction, and coupling of one-dimensional instantiations using a Lagrangian implementation of mesh-resolved volume fluxes is sufficient to advance the three-dimensional flow without time advancing coarse-grained equations, a feature that motivates the designation of the approach as autonomous microscale evolution (AME). In this sense, the one-dimensional treatment is not a closure because there are no unclosed terms to evaluate. However, the approach is additionally suitable for use as a subgrid-scale closure of existing large-eddy-simulation methods. The potential capabilities and limitations of both of these implementations of the approach are assessed conceptually and with reference to demonstrated capabilities of related methods.

The study of the influence of the nanoparticle volume fraction and aspect ratio of microchannels on the fluid flow and heat transfer characteristics of nanofluids in microchannels is important in the optimal design of heat dissipation systems with high heat flux. In this work, the computational fluid dynamics method was adopted to simulate the flow and heat transfer characteristics of two types of water–Al2O3 nanofluids with two different volume fractions and five types of microchannel heat sinks with different aspect ratios. Results showed that increasing the nanoparticle volume fraction reduced the average temperature of the liquid–solid heat transfer surface and thereby improved the heat transfer capacity of the nanofluids. Meanwhile, the increase of the nanoparticle volume fraction led to a considerable increase in the pumping power of the system. Changing the aspect ratio of the microchannel effectively improved the heat transfer capacity of the heat sink. Moreover, increasing the aspect ratio effectively reduced the average temperature of the heating surface of the heat sink without significantly increasing the flow resistance loss. When the aspect ratio exceeded 30, the heat transfer coefficient did not increase with the increase of the aspect ratio. The results of this work may offer guiding significance for the optimal design of high heat flux microchannel heat sinks.

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.

The majority of existing numerical simulations of the effect of bridge piers on water movement are based on a limited number of bridge piers at a laboratory scale. Furthermore, some 2D numerical simulations for actual bridge projects have deficiencies, including the use of overly large mesh sizes and an inadequate treatment of bridge piers. In this study, we compare three methods of structural mesh encryption, suspension mesh, and nonstructural mesh based on Delft3D, and apply the optimization scheme to a real bridge project. It is demonstrated that optimal results can be achieved by utilising a grid size comparable to the pier diameter (Dp) in the region away from the piers. In the vicinity of the piers, the grid cell size should be no larger than 1/9 Dp. The suspended grid technique (DD Boundary) can yield results consistent with those obtained using a full-area high-resolution grid, provided that the total number of grids can be reduced and the computational time is considerably reduced. In this study, the unstructured mesh (Deflt3D Flexible Mesh) scheme was unable to capture the oscillations of the wake flow behind the bridge piers. However, the application of the optimized scheme in bridge engineering has demonstrated its practical value. The findings of this study on mesh resolution and suspension mesh scheme can be applied to the Delft3D software and are also useful for other numerical simulation work.

We perform new measurements of the expansion rate and the sound horizon at the end of the baryon decoupling and derive constraints on cosmic key parameters in the framework of the ΛCDM model, flat wCDM model, the ΛCDM+ΩK model and the phenomenological emergent dark energy (PEDE) model. We keep rd and H0 completely free and use the recent dark energy spectroscopic instrument (DESI) Year 1 and dark energy survey (DES) Year 6 BAO measurements in the effective redshift range 0.3<z<2.33 combined with the compressed form of the Pantheon sample of Type Ia supernovae, the latest 33 observational H(z) measurements based on the differential age method, and the recent H0 measurement from SH0ES 2022 as an additional Gaussian prior. Combining BAO data with the observational H(z) measurements, and the Pantheon SNe Ia data, we get H0=69.65±1.07 km s−1 Mpc−1, rd=147.71±2.18 Mpc in ΛCDM model, H0=70.06±1.07 km s−1 Mpc−1, rd=147.39±2.50 Mpc in PEDE model. The spatial curvature is Ωk=0.025±0.026 and the dark energy equation of state is w=−1.016±0.056, consistent with a cosmological constant. We apply the Akaike information and the Bayesian information criterion test to compare the four models, and see that PEDE model performs better.

Multi-stage hydraulic fracturing with horizontal well technology has been widely used in shale oil reservoir. After hydraulic fracturing, hydraulic fractures and opened beddings are intertwined, which result in a complex fracture network. As well as the migration of multi-phase fluids during fracturing and soaking processes, which lead to complex flowback performance, and brings dif-ficulty to productivity evaluation and flowback strategies optimization. In this paper, taking the Daqing Gulong shale reservoir as an example, a numerical model for flowback period, which considered oil-water-gas three-phase flow and orthogonal fracture network has been established. The characteristics and influencing factors of flowback performance have been deeply studied, and the flowback modes of shale oil are reasonably optimized. Factors such as PTPG (pseu-do-threshold pressure gradient), opened bedding stress sensitivity, opened bedding permeability and matrix permeability have obvious effects on the flowback performance, resulting in signifi-cant variations in production peaks, high yield periods, and decline rates. In addition, three flowback modes are distinguished based on the rate at which the BHP (bottom hole pressure) drops. These correspond to three types of choke modes. Based on the result of numerical model, three flowback modes are optimized and the impacts of different flowback modes on shale oil flowback are clarified. This study is particularly important for understanding the performance of shale oil flowback and guiding the efficient exploitation of shale oil.

The control of the fine particle emission from the coal-fired power plants has been a big challenge in china. Either the conventional electrostatic precipitator or the fabric filter has some shortages. The electrostatic precipitator is hard to keep high efficiency for the submicron particles. The fabric filter could keep high efficiency but with very high pressure drop. One solution is to combine them together. Several types of hybrid particle collectors (HPC) combining the electrostatic precipitator and the fabric filter together have been developed and applied in a number of projects in China. In recent years, numerical simulation technology has been widely used in the design of the collectors. In this paper, an unsteady numerical model is used to investigate the particle deposition characteristics in a scale hybrid collector. The fluid field is modeled by using incompressible Navier-Stokes equations with the RNG turbulence equations. The corona discharge is solved by using a finite volume method. The particle charging is modeled by using a filed-diffusing combined model. And an unsteady cake formation model is used to simulate the filtration process.

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.

Hollow and concrete-filled steel tubes (CFSTs) are widely used as columns in many structural systems and local buckling can occur when they are subjected to axial compression loading. The critical regions for the local buckling of the columns are near the ends of the column where the moments are the highest. To strengthen the critical regions of the CFSTs the CFRP provides a simple and effective method which used previously as an enhancement for both of strength and ductility. So, this study suggests investigating the axial load behaviour of CFST strengthened with CFRP using FE method after a verification study and then a various parametric studies were carried out to cover the effect of the CFRP layers, number, confinement length and position. The FE results proved that, one CFRP sheet with thickness equal to 1.2 mm was strengthened the composite column by 8.5%, two CFRP sheets with total thickness equal to 2.4 mm was strengthened the composite column by 23.5%, three CFRP sheets with total thickness equal to 3.6 mm was strengthened the composite column by 35.1% and four CFRP sheets with total thickness equal to 4.8 mm was strengthened the composite column by 44.5%. Moreover, this study proved that by strengthened the composite columns with CFRP sheets with different lengths, the axial load resistance was improved by 8.5%, 4.6%, 0.1% and 0.0% for length percentages 100%, 75%, 50% and 25% respectively.

For the polymer electrolyte fuel cell (PEFC), the separator thickness plays an important role to determine the weight, the volume and the costs of the PEFC. In addition, thermal management, i.e. temperature distribution is also important for the PEFC system to obtain higher performance. However, there were few reports investigating the relationship between the temperature distribution and the power generation performance such as current density distribution of PEFC operated at higher temperature (HT-PEFC). The aim of this study is to clarify the impact of separator thickness on the relationship between the temperature distribution and the current density distribution of HT-PEFC. This study has also investigated the impact of separator thickness on the relationship between the temperature distribution and the gases such as H2, O2 and the current density distribution of HT-PEFC numerically using CFD software COMSOL Multiphysics. The separator thicknesses of 2.0 mm, 1.5 mm and 1.0 mm were studied. In the study, the operation temperature and the relative humidity (RH) of supply gas were also changed. As a result, it was revealed that the optimum separator thickness was 2.0 mm to obtain higher power generation of HT-PEFC. Since the heat capacity in the case of the separator thickness of 2.0 mm was the largest among the separators investigated in this study, the dehydration of PEM and catalyst layer was smaller compared with the thinner separator thicknesses. It was also revealed that the impacts of separator thickness on distribution of gases, e.g. O2, H2O, and current density distribution became larger under higher temperature and lower RH conditions. This study also concluded that the tendency of temperature distribution matched those of O2, H2O and current density distributions.

In the context of post-harvest pest management in agricultural products, the adoption of modified atmospheres presents an eco-friendly alternative to conventional pesticides. This study focuses on nitrogen gas as a potential agent for insect control in stored commodities, utilizing computational simulations to investigate its penetration and distribution within two common storage configurations: chamber-contained pallets and silos. By employing the convection-diffusion equation, the simulations reveal insights into nitrogen distribution dynamics and duration required for oxygen reduction. The results highlight the influence of boundary conditions, commodity porosity, and convection effects on nitrogen dispersion. In chamber scenarios, boundary condition type significantly affects oxygen reduction time, while in silos, convection and diffusion interact to establish a consistent diffusion layer thickness. This research enhances the understanding of modified atmosphere techniques and their potential for sustainable pest management. It provides practitioners with valuable quantitative insights, paving the way for optimized modified atmosphere strategies in real-world agricultural contexts.

Understanding the infiltration and solidification processes of liquid 5083Al alloy into Al2O3 three-dimensional reticulated porous ceramic (Al2O3(3D) RPC) is essential for optimizing the microstructure and properties of Al2O3(3D)/5083Al interpenetrating phase composites (IPCs) prepared by low-pressure infiltration process (LPIP). This study employs ProCAST software to simulate the infiltration and solidification processes of liquid 5083Al with pouring velocities (PV) of 0.4 m/s infiltrating into Al2O3(3D) RPC preforms with varying porosities at different pouring temperatures (PT) to prepare Al2O3(3D)/5083Al IPCs using LPIP. The results demonstrate that pore diameter of Al2O3(3D) RPC preforms and PT of liquid 5083Al significantly influence the of the infiltration. Solidification process analysis reveals that the Al2O3(3D) RPC preform with smaller pore diameters allows the lower pouring velocity of 5083Al to solidify faster compared to the preform with larger pore diameters. Al2O3(3D)/5083Al IPCs were prepared successfully from Al2O3(3D) RPC porosity of 15 PPI with liquid 5083Al at PV 0.4 m/s and PT 800 °C using LPIP, resulting in nearly fully dense composites, where both Al2O3(3D) RPCs and 5083Al interpenetrate throughout the microstructure. The infiltration and solidification defects were reduced under air pressure of 0.3 MPa (corresponding to PV of 0.4 m/s) during LPIP. Finite volume method simulations are in good agreement with experimental data, validating the suitability of the simplified model for Al2O3(3D) RPCs in the infiltration simulation.

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.

The popularity and growth of additive manufacturing(AM) in recent years are due to its ability to provide innovative solutions to complex manufacturing challenges and its potential to transform the way products are designed, developed, and produced. In this work, the numerical simulation geometry of the model extruder from nozzle is established along with the material extrusion process. The high gravity material extrusion system (HG-MEX) properties and characteristics during filament fabrication are evaluated. This work investigates the effects of gravity on the material extrusion process from nozzle extrusion. This work is unique in the incorporation of fluid surface characteristics to represent the performance and contact with the material extrusion in additive manufacturing. The use of simulation in high gravity material extrusion in additive manufacturing is a meaningful and valuable approach to improving the quality and efficiency of the process.

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.

High density of buildings and the large traffic volume of cities give rise to narrow spaces and high passenger flows in most subway stations. When evacuation is required during an emergency, these problems may trigger issues in operational safety. Therefore, it is imperative to comprehensively assess subway station emergency evacuation times and capacities during the operating process to ensure the design is safe, science-based, and rational. To further enhance safe evacuation capacity, this paper proposes an overall evacuation time model that considers the multielement charac-teristics of subway stations in multiple segments. The evacuation route is decomposed into five stages according to the critical nodes in the evacuation process. An overall emergency evacuation time model is established based on the diversity of bottlenecks in the five stages, integrating elements such as the horizontal movement velocity of passengers, subway equipment parameters, and human density. Taking Xi’an Wulukou Subway Station as an example, this paper verifies the outcomes of the theoretical model against the Pathfinder software and conducts additional anal-yses of the evacuation conditions of stairs and exits. The results show that the error between the theoretical emergency evacuation time and simulation evacuation time was 5.4%, The emergency evacuation model established in this study boasts strong robustness and stability.

Herein we foremost detailed the numerical modeling of the double absorber layer- methyl ammonium lead iodide– carbon nitride layer solar cell and subsequently provided in-depth insight on the active layer associated with dominant radiative and non-radiative recombination losses limiting the efficiency ( ) of the solar cell. Under recombination kinetics phenomena, we explored the influence of Radiative recombination, Auger recombination, Shockley Read Hall recombination, the energy distribution of defects; Band Tail recombination (Hoping Model), Gaussian distribution, metastable defect states including single donor (0/+), single acceptor (-/0), Double Donor (0/+/2+), double acceptor (2/-/0-), and the interface layer defects on the output characteristics of the solar cell. Setting defect (or trap) density to with uniform energy distribution of defects for all the layers, we achieved the of 24. 16 %. A considerable enhancement in power conversion efficiency was perceived as we reduced the trap density to for the absorber layers. Further, it was observed that for the absorber layer with double donor defect states, the active layer should be carefully synthesized to reduce crystal order defects to keep the total defect density as low as to achieve efficient device characteristics

The scope of this work was part of our previous research on Pulsed Power Plasma Stimulation Technique. Electromagnetic fields generated during a pulsed power plasma discharge were simulated using a finite element method in the COMSOL RF module. The field distributions were calculated during and after the pulse. The current paper takes advantage of prior work measuring and modeling the current distribution in the plasma arc. Agreement with laboratory experimental measurements provides support for extension of the model to reservoir scale. The validated model was used to quantify the signal attenuation level in different medium environment.

A single fracture is the basic unit of fracture medium, and the roughness of fracture wall surface is an important factor influencing hydraulic characteristics of the flow in bedrock fracture. However, effects of the shape and density of roughness elements (various bulges/pits on rough fracture wall surfaces) on water flow in a single rough fracture have not been thoroughly discovered. Thus the water flow in single fracture with different shapes and densities of roughness elements was simulated by using Fluent software in this study. The results show that in wider fractures the flow rate mainly depends on fracture aperture, while in narrow and close fracture medium the surface roughness of fracture wall is the main factor of head loss of seepage; there is a negative power exponential relation between the hydraulic gradient index and the average fracture aperture, i.e. with the increase of fracture aperture, the relative roughness of fracture and the influence weight of hydraulic gradient both decrease; and in symmetrical-uncoupled fractures there is a super-cubic relation between the discharge per unit width and average aperture. Above results would help to deepen the understanding of rough fracture seepage.

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.

The conventional explanation of delayed-choice experiments seems to violate our causal intuition. This apparent violation is caused by a misinterpretation of the conventional formulation of quantum mechanics. I reanalyze these experiments using advanced and time-symmetric formulations of quantum mechanics. All three formulations give the same experimental predictions, but the advanced and time-symmetric formulations violate our causal intuition that effects only happen after causes. I explore reasons why our causal intuition may be wrong at the quantum level. I also suggest how conventional causation might be recovered in the classical limit, and speculate on cosmological boundary conditions.

This code provides computational facilities to simulate current versus time during the charging of Li-ion cells at desire constant voltage by considering multiscale physical phenomena. This code only considers a powder of active materials (at microscale or nanoscale) and a small part of electrolyte around it as a half cell. Then it is extended to a complete cell by applying correct boundary conditions. This code is very useful by modifying code parameters to understand the effect of the complex shape of active materials powder (surface area and powder size), kind of electrolyte, and the applied voltages on the charging response of Li-ion cell. As a summary, a microscale approach to the design of Li-ion cells has been provided via this code.

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 the present paper four passive micromixers designs (G1, G2, G3 and G4) inspired on distillation columns trays were proposed. The devices performance was assessed by numerical simulations. The mixing performance was investigated for a Reynolds number range from 0.01 to 100 and channel height of 200 µm, 500 µm and 1000 µm for oil/ethanol flow. G1 and G4 designs provided high mixing index (> 0.975). The G1 device achieved superior mixing performance with a moderate pressure drop (about 0.5 MPa) due to the induced flow recirculation pattern for a relative high flow rate of 0.21 L/min, highlighting the potential use of such microdevice for scale-up and numbering-up of microdevices in modular chemical plant processing.

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.

The structure of turbulent flow over non-flat surfaces is a topic of major interest in practical applications in both engineering and geophysical settings. A lot of work has been done in the fully rough regime at high Reynolds numbers where the effect on the outer layer turbulence structure and the resulting friction drag is well documented. It turns out that surface topology plays a significant role on the flow drag especially in the transitional roughness regime and therefore, hard to characterize. Survey of literature shows that roughness function depends on the interaction of roughness height, flow Reynolds number and topology shape. In addition, if the surface topology contains large enough scales then it can impact the outer layer dynamics and in turn modulate the total frictional force. Therefore, it is important to understand the mechanisms underlying drag increase from systematically varied surface undulations in order to better interpret quantifications based on mean statistics such as roughness function. In this study, we explore the mechanisms that modulate the turbulence structure over a two-dimensional (2D) sinusoidal wavy surface with a fixed amplitude, but varying slope. To accomplish this, we model the turbulent flow between two infinitely wide 2D wavy plates at a friction Reynolds number, $Re_{\tau}=180$. We pursue two different but related flavors of analysis. The first one adopts a roughness characterization flavor of such wavy surfaces. The second one focuses on understanding the non-equilibrium near surface turbulence structure and their impact on roughness characterization. Analysis of the different statistical quantifications show strong dependence on wave slope for the roughness function indicating drag increase due to enhanced turbulent stresses resulting from increased production of vertical velocity variance from the surface undulations.

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.

Technologies for rapid and high-throughput separation of rare cells from large populations of other types of cells have recently attracted much attention in the field of bioengineering. Among the various cell separation technologies proposed in the past, dielectrophoresis has shown particular promise because of its preciseness of manipulation and noninvasiveness to cells. However, one drawback of dielectrophoresis devices is that their application of high-voltage generates Joule heat that exposes the cells within the device to high temperature. To further explore this problem, this study investigated the temperature field in the previously developed cell separation device in detail. The temperature rise at the bottom of the microfluidic channel in the device was measured using a micro-LIF method. Moreover, the thermofluidic behavior of the cell separation device was numerically investigated by adopting a heat generation model that takes the electric-field-dependent heat generation term into account in the energy equation. Under the operating conditions of the previously developed cell separation device, the experimentally obtained temperature rise in the device was approximately 20 ℃, and the numerical simulation results generally agreed well. Next, parametric calculations were performed with changes in the flow rate of the cell sample solution and the solution conductivity, and a temperature increase of more than 40 ℃ was predicted. The results demonstrated that an increase in temperature within the cell separation device may have a significant impact on the physiological functions of the cells, depending on the operating conditions of the device.

A previous research showed the 1755 tsunami would inundate the Marginal Avenue, the railway and the low ground area of Caxias, Oeiras municipality, Portugal. Thus, in this study several proposals for coastal protection are presented. A new Lidar data of local topography allowed the construction of a more accurate DEM, including the representation of the streets of Caxias downtown, to be used in the tsunami numerical model. The results were combined with field survey on Caxias and other coastal areas of Portugal and Japan. The new calculations show the low ground areas up to 6 m in height area inundated by the tsunami. However, with the new proposal DEM the tsunami inundation is restricted to the beaches. The proposal includes the construction of a new sea wall with 7 m in height at Caxias beach, the increase in height of the Barcarena Stream levees and the elevation of the sidewalk at São Bruno beach, with a gentle slope up to 7 m in height. It is also proposed the construction of a third bridge over the Barcarena Stream for pedestrian ranging from 5 to 7 m in height that will serve as a gate for the incoming tsunami waves.

The material properties and structural characteristics of ballistic composites are crucial to their ballistic performance. Investigation for the influence of the material and structural parameters of UHMWPE body armor on anti-fragmentation penetration performance has been made by numerical simulation in this paper, with a numerical modeling simulating the penetration of a 1.1 g FSP into the target plate of UHMWPE body armor, by which the simulation results demonstrate that the failure process of the body armor target plate primarily involves shear damage, interlayer delamination, and tensile damage. Furthermore, the study evaluates the effects of elastic modulus, tensile strength, shear strength, number of layers, and interlayer strength on the ballistic limit velocity of UHMWPE body armor. The findings reveal that the ballistic limit velocity is most sensitive to changes in shear strength, with variation rates ranging from -18.02% to 10.81%, showing an approximate positive correlation, while the elastic modulus has the smallest impact on ballistic limit velocity, with variation rates ranging from -1.8% to 3.6%. Additionally, appropriate interlayer strength can improve the ballistic limit velocity of the body armor to a certain extent. This study provides theoretical methods and recommendations for optimizing anti-penetration performance of UHMWPE body armor.

The water exit problem, which is ubiquitous in ocean engineering, is one of the significant research topics in the interaction between navigators and water. The study of the water exit problem can help to improve the structure design for marine ships and underwater weapons for better strength and movement status. However, the water exit problem involves complex processes such as gas-liquid-solid three-phase coupling, cavitation, water separation, liquid surface deformation and fragmentation, making it challenging to study. According to the works carried out by many researchers towards this issue, we summarize the recent developments from three aspects, i.e. theoretical research, numerical simulation and experimental results. In theoretical research, the improved von Kaman model and linearized water exit model are introduced. Several classical experimental devices, data acquisition means and cavitation are introduced in experimental development. Three methods, namely, BEM(boundary element method), FVM(finite volume method) and LES(large eddy simulation) are concluded for numerical simulation. The limitations and shortcomings of these three aspects are then analyzed. Finally, an outlook on the future research improvements and developments of the water exit problem is provided.

COVID-19 infection is extremely dangerous for persons with comorbidities such as kidney disease and diabetes. Although many people of all ages and socioeconomic backgrounds have suffered due to this pandemic, those with underlying medical conditions like kidney disease and diabetes are more vulnerable to becoming infected with COVID-19 related to weak immunity. However, the role of vaccination in the co-infection of COVID-19 with diabetics is not available in the literature. Therefore, we examine the unique challenges presented by the co-infection of COVID-19 in individuals with diabetes, focusing on its disease transmission dynamics. A mathematical modelling technique is to be employed in this work to analyse the dynamics of COVID-19 outbreaks with seven compartments, including vaccination with comorbidities such as diabetes. We also investigated analytically by displaying the solutions' existence, boundedness, positivity and sensitivity. After calculating the basic reproduction numbers, the stability analysis of model equilibrium points is also covered. If the reproduction numbers are less than unity, the disease-free equilibrium points of the model appear to be both locally and globally stable. The findings of this study are that as the vaccination rate rises, the incidence of COVID-19 and its co-infections with diabetes decreases. Effective disease treatment strategies may be based partly on the possible impact of vaccination on the co-infection of COVID-19 related to diabetic disease insights.

This study investigates the impact of thin flame combustor design on hydrogen flame characteristics and combustion performance through numerical simulations. Variations in flame shape and combustibility between 100% methane and 100% hydrogen combustion are analyzed. Three combustor header shapes (flat, concave, and convex) are modeled to assess their influence on flame behavior. Results show distinct flow patterns, with concave headers promoting strong central flows and convex headers dispersing the flow outward. Temperature field analysis indicates that hydrogen flames have higher temperatures and shorter quenching distances compared to methane flames. A comparative analysis of combustion products is conducted to evaluate combustion performance and NOx emissions. Consequently, the concave header has high combustibility and increases temperatures and NOx fraction in hydrogen combustion.

Our study essentially concerns the dynamic behavior of an SIRS epidemic model in discrete time. Two equilibrium points are obtained; one is disease-free while the other is endemic. We are interested in the endemic fixed point as well as its asymptotic stability. Depending on the parameters which are estimated using the data from US Department of health and SIRS modelling with optimization, two Flip and Transcritical bifurcations appear. We illustrate their diagrams, as well as their bifurcation curves using the method of Carcasses \cite{carcasses1993determination,carcasses1995singularities} for the Flip bifurcation and by an implicit function deduced from such an equation for the Transcritical bifurcation. We use the scanning of the parametric plane to have a global view of the behavior of the model and to highlight the zones of stability of the existing singularities. A superposition of the bifurcation curves with the parametric plane can show the overlap of the curves with the boundaries of the stability domains, which confirms the smooth running of the simulation and its correspondence with the theory, we finish this article with constrained optimal control applied to infection rate and recruitment rate for an SIRS discrete epidemic model. Pontryagin's maximum principle is used to determine these optimal controls. Finally using COVID-19 data in the USA, we obtain results that demonstrate the effectiveness of the proposed control strategy to mitigate the spread of the pandemic.

Frontal Polymerization (FP) is recognized as a polymer synthesis method capable of generating a highly localized and self-propagating exothermic front, considered a more rapid and energy-efficient manufacturing scheme for polymer-based fiber-reinforced composite materials. This study conducts a numerical investigation based on the Finite Element Method into the initiation and propagation of frontal polymerization of acrylamide. Utilizing Differential Scanning Calorimetry (DSC) experiments, the study phenomenologically tests the curing kinetics reactions of acrylamide (AM) in deep eutectic solvent (DES)-based polymerizable systems, thereby establishing a curing kinetics model for the autocatalytic reaction of polyacrylamide. By coupling the heat conduction diffusion equation of the frontal polymerization reaction, the Finite Element Method is employed to solve the reaction-diffusion model, aiming to explore the evolution of temperature and degree of curing during the manufacturing process. The results demonstrate the reliability and accuracy of the nth-order autocatalytic model in the study of curing kinetics for DES-based synthesis, indicating that the front propagation speed of the AM-based FP reaction is influenced by the activation temperature, duration of activation temperature, and initial temperature of the solution. Experimental validation of the polyacrylamide manufacturing through frontal polymerization corroborates the accuracy and reliability of the model predictions, providing a reference for the numerical model study and temperature control in the synthesis of acrylamide composite hydrogels via FP.

A problem of efficacy of crystal growth methods for crystallization from solution or melt has been investigated. Axial vibrational control (AVC) technique was considered as a perspective method to manage both heat-mass transfer and chemical component composition of the melts in the case of crystallization of complex chemical compounds. Numerical modeling and the search for generalized dependencies made it possible to predict the AVC parameters that provide optimal heat and mass transfer modes for creating flat liquid-solid interfaces, as well as the component composition of dissociated melts of various chemical compounds – Ge, NaNO3, CdTe.

The problem of intensification of melt crystal growth process has been analyzed using CdTe as an actual material. Numerical simulation of 100 mm diameter CdTe crystal growth by VGF technique has been carried out. The heat-mass transfer was controlled by introducing of low-frequency oscillating baffle into the melt, so called axial vibrational control (AVC) technique. The baffle configuration has been optimized to destroy solid «tails», which were formed near the crucible walls at high cooling rates due to the low thermoconductivity and the corresponding latent heat. Analysis of CdTe homogeneity range showed that during fast crystal cooling Te micro precipitations were formed resulting from decay of oversaturated Cd-riched nonstoichiometric solid solution at Bridgman crystal growth technique. A VGF grown CdTe crystal after full crystallization stays inside the phase field of the high temperature wurtzite polymorph. This makes it possible to go through the polymorph transition without Te micro-precipitating using the advantages of VGF specific feature of very slow cooling.

Plastic pollution of the ocean is currently one of the most serious environmental threat. Analysis of observations in the Arctic ocean shows that microplastic particles have been found in Arctic snow cover, sea ice, water and sediments. Possible pathways and deposition locations of microplastics in the Arctic Ocean can be assessed based on 3D numerical modeling of thermohaline structure and water circulation, sea ice conditions and drift. The problem is that in addition to transport by currents, a number of other processes affect the state of microplastics. These include mechanical fragmentation, freezing into sea ice and release back into the water, biofouling, adsorption of contaminants and other factors. In this study, based on scenario calculations for a 5-year period, we analyzed the possible spread of microplastics brought by Siberian rivers to the Kara Sea shelf. The Lagrangian particle model used daily 3D numerical simulation data to simulate microplastic transport by ocean currents and by sea ice drift. The results of a series of scenario calculations show how the distribution of particles and their subsequent deposition depend on their type (density), size, processes of freezing into the ice and biofouling.

In this paper, four lithological parameters, i.e. thermal conductivity, particle size, porosity and saturation, are investigated by combining experimental observations with numerical simulations to study the influence laws and mechanisms of action on the combustion process of methane hydrate sediments. The variation of combustion characteristics parameters such as flame height, effective combustion ratio and dimensionless discharge water mass with the lithological parameters are studied. In addition, the combustion mechanism of lithologic parameters on methane hydrate deposits is revealed. Combining the experimental results and simulation calculations, to optimize the combustion of methane hydrate sediments, it is recommended to use methane hydrate sediment samples with high saturation and low thermal conductivity, while the oxidant concentration and porosity of methane hydrate sediment samples should be increased.

This article presents the impact analysis of space harmonics (SH) presence on a single-sided three-phase linear induction motor, along with a comprehensive parametric investigation. The presence of SH often reduces the LIM performances. The electromagnetic phenomena are governed by Maxwell's equations associated with equivalent circuit modelling. The chosen mathematical model uses 2D formulation with magnetic vector potential A. The model implementation is performed with finite element method on Gmsh-GetDP free platform. The electromagnetic thrust is calculated in current excitation case by a numerical model (FEM) with and without term generating SH in order to highlight the effect of SH. The adaptation to voltage supply operation is obtained by equivalent electric circuits (EEC), through calculation of the operational impedance. The main objective of the study consists in a comparative exploration of SH presence using two numerical models (single and multi-harmonics), and an assessment of parameters effect on space harmonic presence and various machine characteristics such as thrust, efficiency, and power factor. The motor’s characteristics (ie: thrust, efficiency and power factor) strongly depend on parameters such as the pole pair number and conductivity. Improving the operation and maximizing the performances of such a machine for a given specification requires the use of optimization algorithms.

. The impedance change of an induction coil surrounding a metal tube adapter is investigated by the truncated region eigenfunction expansion (TREE) method. Conventional TREE method is inapplicable to this problem as a consequence of the numerical overflow of eigenfunctions of the air-metal multi-subdomain regions. The difficulty is surmounted by a normalization procedure for the numerical eigenfunctions obtained from the finite element method (FEM). Efficient algorithm is devised by the Clenshaw-Curtis quadrature rule for integrals involving the numerical eigenfunctions. Numerical results of the TREE and FEM simulation coincide very well in all cases, and the efficiency of the proposed method is also confirmed.

To solve the problem of deformation and stress in segments when a full-face hard rock tunnel boring machine (TBM) tunnel for an urban subway passes through existing buildings, a three-dimensional mechanical calculation model of TBM tunneling under existing buildings was established based on numerical analysis to comprehensively study the spatial attributes of tunnel segments during TBM tunneling. The Qingdao Metro Line 1 TBM tunnel in the hard rock stratum of Xiaobei District passes through existing buildings. The results indicated that (1) the stress and deformation of the segments were different at different positions. The horizontal and vertical stress and displacement of the segments in front of the building were significantly affected by the building. When the segment was not in the area below the horizontal plane of the building, the vertical stress of the segment was significantly greater than the two stresses in the horizontal direction. (2) The vertical displacements of the vault and the arch bottom were the largest, and the influence of vertical accessories was stronger when the segment was closer to the building.(3) When the tunnel was excavated to approximately one tunnel diameter in front of the building, the building was affected. If the surrounding rock is unstable, the excavation face may collapse and the ground surface may sink, possibly leading to inclination, cracking, and uneven settlement of the building.

The mountains in northern Xinjiang of China were studied during the snowmelt season. Multi-source fusion live data Chinese Land Data Assimilation System (CLDAS,0.05°× 0.05°,hourly data) were used as real data, and Central Meteorological Observatory guidance forecast (SCMOC,0.05°× 0.05 °,forecasting the following 10 days in 3 h intervals) was used as forecast data, both issued by the China Meteorological Administration. The dynamic linear regression and the average filter correction algorithms were selected to revise the original forecast products SCMOC.Based on conventional temperature forecast information,we designed four temperature rise prediction algorithms for essential factors affecting snowmelt.Temperature rise prediction algorithms included the daily maximum temperature algorithm, daily temperature rise range algorithm, snowmelt temperature algorithm, and daily snowmelt duration algorithm.Four temperature rise prediction algorithms values were calculated of each prediction product.Root-mean-square error algorithm and temperature prediction accuracy algorithm were used to compare and test each prediction algorithm value from the time sequence and spatial distribution.Comprehensive tests show that the forecast product revised by the average filter algorithm was superior to revised by the dynamic linear regression algorithm as well as the original forecast product.Through these algorithms, the more suitable temperature rise forecast value for each grid point in the study area can be obtained at different prediction times. The comprehensive and accurate temperature forecast value in mountainous snowmelt season can provide an accurate theoretical basis for effective prediction of the runoff in snowmelt areas and prevention of snowmelt flooding.

With the popularization of natural gas and the requirements for environmental protection, the development and utilization of natural gas is particularly important. The status of natural gas in China's oil and gas exploration and development is constantly improving, and the country is paying more and more attention to the exploitation and utilization of natural gas. The Upper Paleozoic tight sandstone in the Ordos Basin is characterized by low porosity, low permeability and large area of concealed gas reservoirs. By injecting CO2 into the formation, the recovery of natural gas can be improved, and at the same time, the stable storage of CO2 can be achieved to achieve a win-win situation of CO2 emission reduction and utilization. Injecting greenhouse gas CO2 into gas reservoirs for storage and improving recovery has also become a hot research issue. In order to improve the recovery efficiency of tight sandstone gas reservoir, this paper takes the complex tight sandstone of Upper Paleozoic in Ordos Basin as the research object, through indoor physical simulation experiments, carried out the influence of displacement rate, fracture dip angle, core permeability, core dryness and wetness on CO2 gas displacement efficiency and storage efficiency, and analyzed the influence of different factors on CO2 gas displacement efficiency and storage efficiency to improve the recovery and storage efficiency. The research results show that under different conditions, when the CO2 injection pore volume is less than 1PV, the relationship between the CH4 recovery rate and the CO2 injection pore volume is linear, and the tilt angle is 45 °. When the CO2 injection pore volume exceeds 1PV, the CH4 recovery rate increases slightly with the increase of displacement speed, the recovery rate of CO2 displacement CH4 is between 87% - 97%, and the CO2 breakthrough time is 0.7PV-0.9PV. In low-permeability and low-speed displacement cores, the diffusion of CO2 molecules is more significant. The lower the displacement speed is, the earlier the breakthrough time of CO2 is, and the final recovery of CH4 slightly decreases. Gravity has a great impact on CO2 storage and enhanced recovery. The breakthrough of high injection and low recovery of CO2 is earlier, and the recovery of CH4 is about 3.3% lower than that of low injection and high recovery. The bound water makes the displacement phase CO2 partially dissolved in the formation water, and the CO2 breakthrough lags about 0.1PV. Ultimately, CH4 recovery factor and CO2 storage rate are higher than those of dry core displacement. The research results provide theoretical data support for CO2 injection to improve recovery and storage efficiency in complex tight sandstone gas reservoirs.

On the aero-engine combustor liner, a phenomenon of overheating resembling a hot spot exists, accompanied by a preferential peeling of the YSZ thermal barrier coating that will negatively affect the service life of the component. The temperature gradient of the hot spot may affect the YSZ fracture pattern.In this paper, the morphological and property changes of YSZ sintering is investigated experimentally, and a coupled analysis of the YSZ Crack Propagation Mode under the hot spot is performed using ABAQUS. The results show that the pore fractal size D of YSZ increases by 15%. Inside the hot spot region, the coating has a shear stress of 75MPa. By inserting Cohesive units globally in the model to simulate the random crack initiation and propagation, unlike the thinning of YSZ layered peeling caused by uniform superheating, hot spot will cause the crack initiation at the tip of the pores inside the coating and the oblique propagation, eventually forming an oblique crack connection through the pores. When the temperature gradient reaches 30K/mm, the crack propagation is 40% greater than in a uniform temperature field; consequently, the YSZ in the hot spot boundary region with a greater temperature gradient results in more severe bulk peeling.

Hydrogel microneedles are a promising technology for the delivery of different types of medicines locally and painlessly, as well as ISF extraction. As the hydrogel microneedles are inserted into the tissue, they swell and release drugs. To improve the effectiveness of this technology in delivering medicine at controlled and desirable doses and intervals, a deep understanding of the mechanism of drug delivery inside the microneedles is required. In this work, drug diffusion inside a tapered microneedle is investigated using numerical simulation. The microneedle is divided into many small elements, and the mass transfer equation of meloxicam is solved in each element over time. The skin is simulated as the sink in the microneedle surface for drug absorption. Simulations are performed for different sizes of microneedles. For a microneedle with a height of 500 µm and a base diameter of 250 µm, the drug completely penetrates the skin within 3.2 seconds. The rate of drug diffusion from the tip of the microneedle is higher than diffusion from the side area near the microneedle base. The obtained data demonstrate that in addition to the height and the base diameter, the microneedle’s aspect ratio, h/d, also affects the time of drug diffusion. We present a nonlinear equation to predict the time of complete drug diffusion as a function of the microneedle geometrical parameter, including the height and base diameter. The proposed equation calculates the total drug diffusion time with an error of less than 7% for all studied cases. Predicting drug diffusion patterns inside microneedles can be helpful in the biomedical field, especially in the drug-controlled release system for the optimization of drug delivery.

Projected future sea level rise and marine storminess is a serious threat for beaches as they induce beach flooding and erosion. Among other factors, wave runup play an important role in beach evolution and must be robustly assessed. However, little attention has been paid to the uncertainties associated to its characterization and how do they compare to other sources of uncertainty. As a first step towards this goal, we have quantified the impact of several sources of error in the estimation of wave runup on sandy beaches. Understanding what factors are more influential in the quality of the results will help to determine the main sources of uncertainty in beach flooding projections. To reach that goal, a calibrated state-of-the-art numerical modelling system has been setup for two beaches in the Mallorca islands (NW Mediterranean). The system has been forced with the best available information of nearshore incoming waves and has been validated against observations to define the benchmark quality. To determine the key factors affecting the quality of the system’s results, different systems configurations have been tested with different degrees of complexity.Our results show that using the most sophisticated modelling system with the best information on boundary conditions, bottom bathymetry, and submerged vegetation leads to a swash RMSE comparable to the standard deviation of the observed swash. We have also found that the choice of lateral boundary conditions (i.e., source of information for the incoming waves) can double the RMSE and induce large biases. Our results also show that using a simple empirical approach usually underestimates the wave runup. However, in locations with vegetated seabed there is a compensation error, and the empirical approach can lead to acceptable results if forced by nearshore waves. In addition, we have compared the error estimates obtained with uncertainties associated to projected sea level rise. Our findings suggest that the uncertainty associated with wave runup modelling should be considered in the assessment of the total uncertainty of future beach flooding, since the analysis performed indicates that this uncertainty can account for between 16% to 60% of the uncertainties linked to mean sea level projections.

Dynamic Realistic Failure Process Analysis (DRFPA) is a numerical software based on FEM it is firstly validated by comparing with the experimental test. Such validation is carried out under two consistent concrete specimens under uniaxial compression. After validation, DRFPA is used to study the influence of two parallel pre-existing crack inclination angles on the fracture of concrete under dynamic loads. The evolution of wing cracks and secondary cracks is investigated by observing the initiation, coalescence, and propagation of them. Meanwhile, the relationship between failure mode and inclination angles is discussed via analyzing the acoustic emission events. Finally, it is concluded the relationship between inclination angles of pre-cracks and performance/stability of concrete structure.

For the numerical simulation of components made of short fiber-reinforced composites the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study numerical simulations of tensile test specimens are conducted utilizing a finite deformation elastic-ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach tensile tests until failure are carried out experimentally, that confirm the assumption of spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations are performed for different values of the correlation length. The numerical simulations endorse the influence of the correlation length on the overall behavior. For a correlation length of 5mm a good conformity with the experimental results is obtained. Therefore, it is concluded, that the presented modeling approach is suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.

Relativistic atomic and molecular structure calculations start from very different premises to quantum electrodynamics (QED). QED predicts radiative corrections that can nly be approximated crudely in today's atomic structure programs. This paper describes rigorous simple algorithms for including accurate vacuum polarization and self-energy corrections in the GRASP programs.

Our aim is to implement and test some less known numerical methods that might be used to solve an advection equation. The description is restricted to information necessary to implement and test the presented methods and it is given only for one-dimensional case.

This paper examines the influence of physical parameters on the collapse dynamics of a spherical bubble filled with diatomic gas ($\kappa=7/5$). The present numerical investigation shows that each physical parameter affects the bubble collapse dynamics differently. After comparing the contribution of each physical parameter, it appears that, of all the parameters, the surrounding liquid environment affects the bubble collapse dynamics the most. Meanwhile, surface tension has the weakest influence and can be ignored in the bubble collapse dynamics. However, surface tension must be retained in the initial analysis since this, as well as the pressure difference jointly control initial bubble formation. As an essential part of this study, a general Maple code is provided.

This paper revisits a classic problem in physics - Hertz elastic dynamics of two colliding elastic spheres. This study obtains impact period in terms of hypergeometric function and successfully combines Deresiewicz's three segmental solutions into one single solution. Our numerical investigation confirms that Deresiewicz's inversion is a good approximation. As an essential part of this study, a general Maple code is provided.

Motivated by the way animals react in nature, we introduce a fully-connected neural-network model, which incorporates the external pattern presented to the system as a fundamental tool of the recognition process. In this new scenario, in the absence of this external field, memories are not attractors inside basins of attraction, as in usual attractor neural networks, although basins may be created according to the external pattern, thus allowing storing a much larger number of memories. The key point consists in calibrating the influence of the external pattern such as to cancel the noise generated by those memories not correlated with the external pattern.We illustrate how this proposal works by including this new contribution in the standard Hopfield model, showing a significant increase in its recognition capacity (typically by a factor $10^{2}$). As an additional feature of this model, we show its ability to react promptly to changes in the external environment, a crucial attribute of living beings. This procedure can be applied to a wide variety of neural-network models to increase considerably their recognition and reaction capabilities.

The effects of the surface waves generated by the wind have a significant effect on the currents. A wave current coupled model plays an important role in the design of offshore structures. The interaction between fluids such as incompressible ocean waves and current and offshore structures is significant with many real-time applications in offshore engineering. These coupled models can be applied to Offshore Floating Production Operating and offloading (FPSO), Wind or current turbines and offshore pipelines. The complex issues related to the design are analyzed by using Computational Fluid Dynamics, which requires an investigation of the multiphase flow between wave and current and the structure which is considered restrictive due to the computational cost. If viscous effects are neglected then the single-phase flow models have been recommended, where wave-current interaction have been modelled successfully. Models have been developed where velocities and pressure are computed and the results can be verified with the experimental results available in the literature. In this study the existing numerical methods, mesh types are discussed along with their coupling methods. Here single-phase and multiphase models with small and medium movement are reviewed and their applications are highlighted.

Rapidly spreading disease, COVID-19 is classified as the human-to-human transmission-able disease and currently is a pandemic in the Globe. In this paper, we propose conceptual mathematical models for COVID-19 outbreak and it's control measurement; quarantine, hospitalization and the effect of panic and anxiety. In this situation, mathematical models are a important tool to employ an effective strategy in order to fight against this pandemic. We establish the positivity and boundedness of solutions, local and global stability analysis of equilibria to examine its epidemiological relevance. To validate the model and estimating the important model parameters and prediction about the disease, we consider the real cases of Italy from $15^{th}$ Feb to $13^{th} $ April 2020. In a series of graphical map, we have presented the comparative study to estimate the current scenarios and to predict the control measurement time boundary of the outbreak.

In order to reveal the mechanism and influencing factors of high pressure jet cavitation of nozzle in submerged environment, this study focused on the evolutionary process of cavitation bubbles and combined finite volume method and mixed multi-phase flow model to analyze the cavitation, velocity distribution and experimental cavitation intensity of fishing net cleaning equipment. Results show that the cavitation inception, growth and collapse mainly occurred in the peripheral region of the flow field. Ring-shaped cavitation erosion zone appeared on the test sample target. A lot of small dense erosion pits were densely distributed in the ring-shaped erosion zone, erosion marks were observed in the center. The cavitation erosion intensity was greatly affected by the nozzle structure. As the diameter of nozzle increased from 0.6 mm to 1 mm, the maximum gas volume fraction increased by 8.53%. The nozzle outlet enlargement angle greatly increased the cavitation intensity. The nozzle with an outlet angle of 30° exhibited the optimal cavitation erosion performance . The cavitation volume fraction of the nozzle with short necking structure was slightly larger than that of the nozzle with long necking structure at the same level in the necking length rang of 3mm to 7mm. In terms of the influence of nozzle structure on the cavitation erosion effect, the nozzle diameter D ranked the first, followed by the outlet angle α, and the necking length L was at the last.

The aim of this study is to model hydrodynamic processes of the Istanbul Strait with its stratified flow characteristic and calibrate the most important parameters using local and global search algorithms. For that two open boundary conditions are defined, which are in the North and South part of the Strait. Observed bathymetric, hydrographic, meteorological and water level data are used to set up the Delft3D-FLOW model. First, the sensitivities of model parameters on the numerical model outputs are assessed using PEST toolbox. Then, the model is calibrated based on the objective functions focusing on the flowrates of upper and lower layers. The salinity and temperature profiles of the Strait are only used for model validation. The results show that the calibrated model outputs of Istanbul Strait are reliable and consistent with the in-situ measurements. The sensitivity analysis reveals that the Spatial Low-Pass Filter Coefficient, Horizontal Eddy Viscosity, Prandtl-Schmidt Number, Slope in log-log Spectrum and Manning Roughness Coefficient are most sensitive parameters affecting flowrate performance of the model. The agreement between observed salinity profiles and simulated model outputs is promising whereas the match between observed and simulated temperature profiles is weak showing that the model can be improved particularly for simulating the mixing layer.