Engineering

Abstract: An approach for the control of linear control systems with a single time-delay is proposed. The main contribution is the inclusion of a symmetric-injection virtual reference trajectory into the controller to render stability robustness of single-delay linear control systems. The dynamics of the virtual trajectory is included into the closed-loop dynamics allowing theoretical computation of the critical time-delay before losing stability. Moreover, an energy-based symmetry interpretation of the proposed approach is drawn. Numerical simulations considering stable and unstable linear systems are shown, and experiments to control a DC-motor with time-delay measurements validate our proposal.

Abstract: Emerging materials often face challenges in market adoption due to limited comparability and reliability of measurement-based material information, despite their potential to drive technological innovation. While standardization is widely recognized as an important mechanism for market diffusion, existing approaches provide limited insight into how material specifications facilitate the comparative evaluation of material characteristics and their use in market decision-making. This study proposes a complementary perspective that interprets standardization as an infrastructure for organizing the generation, sharing, and evaluation of measurement-based material information across industry, standard development organizations (SDOs), and markets. Within this framework, the study distinguishes between two complementary types of standards for material specifications. Type A standards enable the structured disclosure of measured characteristic values and associated measurement uncertainties, allowing application-specific evaluation without predefined acceptance criteria. In contrast, Type B standards define predefined characteristic values and compliance criteria, providing a basis for conformity assessment, certification, and quality assurance. These two types may be understood as complementary mechanisms that fulfill different functions of comparability and compliance under varying technological and market conditions in emerging material systems. Consequently, they contribute to both innovation-oriented market evaluation and quality-assured market acceptance.

Abstract: This work deals with the time-domain analysis of asymmetrical faults in three-phase systems. Conventional three-phase analysis provides steady-state solutions for asymmetrical faults. Transient analysis, however, is usually performed by resorting either to oversimplified approximate circuits, or to numerical methods. In this paper, a rigorous analytical methodology based on the time-domain Clarke transformation is presented for the most common asymmetrical faults in three-phase systems. In particular, it is shown that asymmetrical faults result in circuit coupling in the Clarke equivalent circuits. Circuit representation of coupling is also derived in the paper. Coupled equivalent circuits allow rigorous analytical solution of transients in case of asymmetrical faults. The analytical results derived in the paper are validated through proper numerical simulation of faulted radial systems.

Abstract: In the hyper-arid climate of Riyadh, Saudi Arabia, the building envelope represents the most critical determinant of energy demand and occupant comfort. This study evaluates the environmental and energy performance of a 6,581m2 mixed-use development through an experiential learning framework, where students utilized Sefaira (Ener-gyPlus/Radiance engines) to bridge the gap between theoretical architectural design and national code compliance. This pedagogical approach allowed for the practical application of Building Energy Modelling (BEM) principles to a real-world capstone project. A baseline analysis conducted in accordance with the Saudi Building Code (SBC 601) re-vealed a high Energy Use Intensity (EUI) of 139 kWh/m2. yr, driven primarily by solar heat gains and an "overlit" floor plate as noted above exceeded Annual Sunlight Exposure (ASE) thresholds. To mitigate these deficiencies, students implemented a series of passive interventions, including the optimization of glazing U-values (0.5~W/m²·K), reduction of Solar Heat Gain Coefficient (SHGC to 0.20), and the integration of external shading fins. Post-intervention results demonstrated a significant EUI reduction to 130 kWh/m²·yr" to "a 6.95% reduction in EUI from 139 to 130 kWh/m²·yr, equating to 63,659 kWh in annual energy savings. Furthermore, daylighting analysis confirmed a more uniform distri-bution and the successful mitigation of disability glare. The findings validate that ex-periential learning in performance-driven envelope optimization is essential for de-veloping the technical proficiency required to achieve full SBC compliance and opera-tional efficiency in hot-arid regions.

Abstract: Limited access to clean water and reliable electricity infrastructure remains a major challenge in many remote regions of Indonesia, particularly for building‑scale domestic use. Conventional water treatment systems are often constrained by high operational costs and dependence on grid power, highlighting the need for sustainable and autonomous infrastructure solutions. This study presents the design, development, and performance evaluation of an integrated solar‑powered clean water treatment system for smart building applications in remote areas using a Research and Development (R&D) approach. The proposed system combines off‑grid polycrystalline photovoltaic panels with a multi‑stage water treatment process consisting of a floss (mud) filter, activated carbon filter, water hyacinth cellulose bio‑filter, ultraviolet (UV) sterilization unit, storage tank, and an IoT‑based real‑time water quality monitoring system. System performance was evaluated through microbiological, physical, and chemical water quality testing, with monitoring conducted via Wi‑Fi‑enabled sensors connected to the Blynk platform. The results demonstrate substantial improvements in treated water quality. Escherichia coli and total coliform bacteria were eliminated (100% reduction). Total dissolved solids (TDS) decreased from 450 mg/L to 218 mg/L (51.6%), and dissolved manganese was reduced from 30 mg/L to 0.01 mg/L (99.97%), while nitrate levels decreased by 50%. Water pH and temperature remained stable and within regulatory limits. All treated water parameters complied with national clean water standards for hygiene and sanitation. The system operated independently using solar energy and achieved a clean water production capacity of 1,000–1,500 L/day. These findings indicate that the proposed system is a feasible, cost‑effective, and sustainable civil engineering solution for clean water infrastructure in remote building environments.

Abstract: Double-sided solar greenhouses are recognized as energy-efficient agricultural facilities that significantly enhance land utilization and thermal performance through their unique double-sided lighting design, thereby promoting crop growth. However, challenges persist regarding insufficient heat storage capacity and suboptimal thermal environments within the shaded shed during the winter and spring seasons. To fully exploit the advantages of this greenhouse type, this study proposes a structural optimization methodology utilizing Computational Fluid Dynamics simulation. A CFD model was developed and validated against experimental data to ensure accuracy. Subsequently, the influence of key parameters, including roof geometry and wall thickness, on the internal photothermal environment was systematically analyzed. The results demonstrate that the 370 mm thick wall configuration achieves a daily peak temperature approximately 2°C lower than the 240 mm wall, indicating a more uniform spatial distribution, while exhibiting a nighttime temperature increase of up to 2.5°C, thereby confirming superior thermal insulation properties. Furthermore, the presence of a rear roof structure is critical for nighttime heat retention, maintaining a minimum temperature of approximately 5°C compared to 2°C in greenhouses lacking this feature, with a maximum temperature difference of 4.2°C, effectively optimizing temperature uniformity. Based on these findings, this research provides a robust theoretical foundation and technical support for the structural optimization of double-sided solar greenhouses and the advancement of facility agriculture.

Abstract: Ground failure during major seismic events associated with soil liquefaction can lead to major structural damage in both the columns and the bridge upper deck, due to large seismic-induced displacements in the support foundation. Liquefaction-driven ground motion incoherence during the dynamic event, and permanent soil deformations are key variables in the observed damage. This paper summarizes a numerical study of an alternative bridge foundation design proposed to reduce support displacements and bearing capacity failure during and after an earthquake, as well as relative settlement associated with partial loss of bearing capacity when the bridge column is founded on a potential liquefiable layer. Three-dimensional numerical models were developed using FLAC3D. The seismic environment was characterized by a uniform hazard spectrum, UHS, for intraplate and interplate earthquakes, as presented in the current construction Mexico City regulations. Initially, a one-dimensional analysis was performed using SHAKE to evaluate liquefaction susceptibility. Results show that the structured cell foundation reduces excess pore pressure generation by up to 42% compared to shallow foundations and 25% compared to pile systems. This improvement is associated with (i) restriction of cyclic shear strain, (ii) modification of deformation patterns, (iii) partial hydraulic isolation of the confined soil, and (iv) preservation of effective stresses during shaking. Additionally, the system reduces shear strain localization and decreases acceleration transmitted to the superstructure by up to 25%. The findings demonstrate that structured confinement systems can significantly alter the mechanisms governing liquefaction, offering a promising alternative for bridge foundations in seismic regions.

Abstract: Channel estimation is important for Orthogonal Frequency-Division Multiplexing (OFDM) in wireless channel communication and requires algorithms that offer the best accuracy while at the same time have very low computational and runtime complexities. Newtonised Orthogonal Matching Pursuit (NOMP) is a promising algorithm for channel estimation; however, it suffers from high computational complexity due to repeated refinement and least-squares updates. In this paper, we propose a low complexity NOMP variant that reduces the dominant computational cost through three modifications: (i) a residual energy-based stopping criterion for NOMP to avoid expensive CFAR evaluation, (ii) a partial cyclic refinement with frozen atoms, and (iii) approximate one-sweep per atom least-squares updates. Complexity analysis shows a reduction from O(K³) to O(KN) in the gain update and from O(K²N) to O(KN) in refinement. Simulation results show that the proposed method achieves ∼87% reduction in runtime, while the symbol error rate (SER) performance is comparable to classical NOMP and outperforms Oversampled OMP at high signal-to-noise ratio (SNR). These results show that NOMP can be computationally efficient for OFDM systems without sacrificing estimation accuracy.

Abstract: This study proposes a reproducible exploratory framework to link long-term territorial development with electricity demand in data-scarce contexts, and applies it to Ecuador’s Costa region. The pipeline combines three commonly available input streams: periodic census microdata, an official demand series, and macroeconomic aggregates. Socioeconomic heterogeneity across five non-uniform census rounds (1974, 1982, 1990, 2001, 2010) is summarized through Principal Component Analysis (PCA), and territorial indicators are projected to the demand horizon using low-order polynomial functions. Eleven regression specifications are compared on a log-transformed demand variable, and a rollingorigin backtesting scheme plus a 2020–2024 holdout are used for validation. The selected Trend OLS log model attains R2 = 0.551 and MAPE = 6.08%, and projects a regional demand of approximately 6,940 MW by 2050, equivalent to a compound annual growth rate of 3.45%. Beyond the Ecuadorian case, the results show that transparent, low-data pipelines based on harmonized census information, macroeconomic drivers and simple regression models can provide defensible medium- and long-term demand signals for planners in other emerging economies with limited high-frequency data.

Abstract: Events such as landslides and slope failures happen suddenly and can be catastrophic. To predict the onset of such events, as well as the flow and final deposition of the material, engineers make use of numerical modeling techniques. These events are associated with large deformation and mesh-based methods, such as the finite element method, are not capable of modeling them due to mesh distortion. The material point method (MPM) is a particle-based continuum method capable of modeling large deformation and material flow. In this paper, MPM is used to model the sudden and dynamic flow of material by modeling the collapse and runout of a non-cohesive sand column. The results from two- and three-dimensional models are compared to experiments, showing that MPM accurately predicts the free-surface profile of the material during collapse. Furthermore, the model accurately predicts the runout distance with an error of less than 5%.

Abstract: To alleviate the shortage of natural river sand and promote the utilization of aeolian sand, concrete was prepared by replacing river sand with Taklamakan Desert aeolian sand at different mass ratios. The effects of replacement ratio and curing age on compressive strength and microstructure were investigated using compressive strength tests, SEM, and EDS. A quadratic regression model was established by response surface methodology using replacement ratio, curing age, and Ca/Si ratio as variables. The results showed that compressive strength first increased and then decreased with increasing aeolian sand content, with the 20% replacement group achieving the highest strength. Strength increased with curing age, but the growth rate slowed after 28 days. SEM and EDS results indicated that suitable aeolian sand content promoted hydration product formation and matrix densification, whereas excessive replacement increased pores and interfacial defects. The Ca/Si ratio generally increased with curing age. The model showed good fitting accuracy, with R² = 0.9970, providing a reference for strength prediction and mix design optimization of aeolian sand concrete. Keywords: aeolian sand concrete; compressive strength; microstructure; Ca/Si ratio; response surface methodology

Abstract: The current work uses Iterated Fission Probability (IFP) routine that was recently implemented in OpenMC to calculate reactor kinetics parameters. IFP is calculated from the product of the multiplication factors tracked across the L+1 generations of fission progenies. Since IFP is an excellent estimator of adjoint flux, it is able to calculate Λ_eff , β_eff and β_i of the reactor. OpenMC calculation of the reactor itself has k_eff = 1.01687 with an effective mean neutron generation time, Λ_eff = 44.82 μs. The effective delayed neutron fraction, β_eff that we get is 0.007235 or 723.5 pcm. Other calculations of β_eff using prompt methods for reactors with similar designs gave us values between 724 pcm to 752 pcm. Our own calculations using the prompt method in OpenMC gave us an effective delayed neutron fraction of 734.1 pcm. The group β_i that we obtain is 24 pcm, 131.4 pcm,124.1 pcm, 284.0 pcm, 112.7 pcm and 47.4 pcm respectively. If we strip away the influences of β_eff on β_i , by looking at only the abundances of each delayed neutron group, a_i ; we are able to see that the a_i is similar to the abundances of just ²³⁵U in the six group abundances of ENDF/B-VIII.0 evaluated cross section library. When we adopt a different evaluated cross section library in OpenMC, changes in β_i is due to the different β_eff and λ_i adopted in these libraries.

Abstract: This paper presents the complete design and development of a dried whole blood cartridge designed for point-of-care (POC) clinical diagnostics. The system integrates a near-infrared (NIR) spectroscopy sensor with a disposable multilayer paper cartridge capable of collecting and analyzing small, controlled volumes of capillary blood (20 μL). The work emphasizes a technical and iterative design approach that combines product design with both additive and subtractive prototyping, supported by experimental validation. The development process involved multiple design iterations focusing on fluid transport, capillary dynamics, usability, and optical integration. Several materials and manufacturing processes, such as CNC (Computer Numerical Control) machining and Material Jetting (MJ), were explored to optimize channel geometry and flow behavior. Experimental results guided successive refinements, leading to a cartridge configuration that ensures efficient capillary action, minimal coagulation, and consistent optical alignment with the sensor’s analysis zone. The study underscores the importance of an integrated engineering approach that unites design methodology, material selection, and manufacturing processes to achieve a reliable and reproducible cartridge for point-of-care blood diagnostics. It demonstrates how iterative design, supported by experimenal testing, can effectively bridge the gap between experimental prototyping and practical implementation in medical device development.

Abstract: This paper introduces bending anisotropy of gun drill rods, caused by asymmetric cross-section, into chatter stability analysis. A dynamic model considering different stiffnesses along the two principal inertia axes is established. The Galerkin method and semi-discretization method are used to solve the governing equations and generate stability lobe diagrams. Parameter sensitivity analysis shows that drill rod length and material damping coefficient are high-sensitivity parameters, while coolant hole size and eccentric position are low-sensitivity ones. The results reveal the mechanism of bending anisotropy on stability and provide theoretical guidance for chatter suppression in deep-hole machining.

Abstract: This paper presents a method for continuously optimizing the turn-on and turn-off angles of a switched reluctance generator (SRG) operating in single-pulse mode and connected to an asymmetric bridge converter. The optimal angles are defined as those that minimize total SRG loss while ensuring accurate tracking of the terminal voltage reference. The Pearson correlation coefficient between SRG loss and selected SRG variables was calculated, with the highest correlation found for the average value of all phase currents. Therefore, the average phase current was selected as the variable to be minimized in a perturb-and-observe (P&O) method used to determine the optimal turn-on angle at a given operating point. The turn-off angle was calculated to maintain the terminal voltage at its reference value. The method was validated using both a conventional SRG simulation model and an advanced model that accounts for mutual coupling, iron losses, and remanent magnetism, and was further verified experimentally on an 8/6 SRG rated at 1.1 kW under various load conditions, terminal voltages, and rotor speeds.

Abstract: This study examines how the Internet of Things (IoT) acts as a key enabler of sustainability in industrial production systems within the Industry 4.0 paradigm, addressing the fragmented understanding of the mechanisms linking digital technologies to environmental, operational, and emerging human-centric outcomes. A systematic literature review was conducted following PRISMA 2020 guidelines using the Web of Science Core Collection. After applying explicit inclusion and exclusion criteria, 69 peer-reviewed studies published between 2016 and 2026 were analyzed through qualitative thematic synthesis and comparative analysis. The findings reveal that IoT functions as a foundational digital infrastructure enabling real-time monitoring, operational transparency, and data-driven decision-making in production environments. Four dominant application domains are identified: (i) energy and resource efficiency, (ii) production monitoring and control, (iii) predictive maintenance and asset management, and (iv) emerging human-centric production systems aligned with Industry 5.0. While IoT consistently improves operational reliability and resource efficiency, its contribution to the social dimension of sustainability remains comparatively underdeveloped. This study advances existing literature by providing a mechanism-oriented synthesis that explains how IoT-enabled infrastructures generate sustainability outcomes across production systems. Furthermore, it establishes a conceptual bridge between Industry 4.0 digitalization and the transition toward human-centric and resilient manufacturing models associated with Industry 5.0. From a practical perspective, the results highlight that IoT adoption contributes to reducing energy consumption, optimizing resource utilization, and enhancing operational performance, while also supporting safer and more adaptive working environments. However, challenges related to data integration, workforce adaptation, and digital capability gaps persist, underscoring the need for inclusive and strategically aligned digital transformation processes.

Abstract: Determining the compatible prestress and geometry under self-weight constitutes a key challenge in the form-finding of cable-truss structures. To overcome the limitations of experience-dependent trial methods and enhance computational efficiency, this paper proposes an automated and integrated methodology by synergistically combining a simplified mechanical model with an improved Particle Swarm Optimization (PSO) algorithm. The core of the method lies in formulating the form-finding process as an optimization problem, where the horizontal inclination angles of the lower chord cables serve as the design variables for all radial cable-truss frames. To efficiently solve this high-dimensional optimization problem, an improved PSO algorithm, which introduces logistic chaotic mapping for particle initialization and a mutation operator within the iterative loop. Ablation studies confirm the individual contribution of each algorithmic enhancement. The algorithm intelligently searches for the optimal angle set, thereby simultaneously resolving the prestress and geometry. The proposed approach is rigorously validated through two representative numerical examples: a circular Type I and an elliptical Type II cable-truss, considering both cases with and without self-weight. The results demonstrate that the improved PSO-based solution achieves prestress distributions and nodal coordinates in excellent agreement with established benchmark data. More importantly, it attains this high precision with significantly reduced computational cost in terms of particle swarm size and iteration number. In conclusion, this improved PSO‑based approach provides an efficient, accurate, and automated tool for the integrated prestress‑geometry design of cable‑truss structures, demonstrating strong potential for practical engineering application.

Abstract: We conduct a theoretical analysis on the diffusiophoretic motion of a dielectric droplet in a cylindrical pore in the presence of an induced diffusion potential, such as in the NaCl electrolyte solution. The fundamental electrokinetic governing equations are solved using a patched pseudo-spectral method based on Chebyshev polynomials, coupled with a geometric mapping scheme to handle the irregular solution domain. The impact of boundary confinement effect on droplet mobility is examined in detail. Interesting electrokinetic phenomena are found in this work, such as mobility reversal in narrow cylindrical pores with the droplet moving against the direction expected based on the classical Coulomb electrostatic law due to the strong boundary confinement effect. Two critical points of κa are found, where κ is the electrolyte strength and a is the droplet radius. The spinning orientation on the droplet surface changes each time past them. The profound boundary confinement effect, both electrostatically and hydrodynamically, is responsible for these peculiar phenomena. The results presented here has direct applications in microfluidic and nanofluidic operations as well as drug delivery applications.

Abstract: Adaptive Sidelobe Cancellation (ASLC) is a core technology for modern radar systems to suppress active sidelobe jamming. From the perspective of disrupting the ASLC system’s ability to stably track the jamming direction, this paper proposes a distributed jamming method based on random phase perturbation. The method employs two spatially separated jamming sources that simultaneously transmit coherent signals. By actively applying controllable random jumps to the relative phase between the two sources, the equivalent wavefront direction of the synthesized signal at the radar receiver changes rapidly, forming a non-stationary jamming that destroys the null-tracking capability of ASLC. An analytical model of the ASLC cancellation ratio under random phase perturbation is established, with a focus on analyzing the effects of time synchronization accuracy and phase synchronization accuracy on jamming performance. Monte Carlo simulation results show that the proposed method can reduce the average ASLC cancellation ratio from 26.80 dB to 19.73 dB (a decrease of 7.07 dB). This study provides a theoretical basis and parameter design references for the engineering implementation of distributed cooperative jamming.

Abstract: The high cost and complexity of Industry 4.0 laboratory infrastructure limit the adoption of Digital Twin concepts in engineering education. This paper proposes a low-cost Digital Twin framework for sustainable manufacturing education integrating SAP NetWeaver, Node-RED, and AI-based decision support. The framework adopts a layered architecture that connects PLC-based simulation, IoT middleware, enterprise resource planning systems, and intelligent decision-making components. Node-RED enables real-time data exchange, while SAP NetWeaver provides enterprise-level integration through OData services. An AI module supports decision-making for production and inventory management. The proposed framework is implemented as a functional prototype, demonstrating end-to-end integration without requiring physical manufacturing equipment. Competency-based mapping aligns the framework with Industry 4.0 engineering skills, supporting its use in academic environments. A sustainability assessment highlights reductions in infrastructure cost, energy consumption, and resource usage compared to traditional laboratory approaches. The results indicate that the framework provides a scalable and accessible solution for teaching Digital Twin concepts, contributing to sustainable engineering education in resource-constrained contexts.