Modelling, Volume 6, Issue 1 (March 2025) – 24 articles

Mechanical metamaterials have become a critical research focus across various engineering fields. Recent advancements have pushed the development of reprogrammable mechanical metamaterials to achieve adaptive mechanical behaviours against external stimuli. The relevant designs strongly depend on a thorough understanding of the response spectrum of the original structure, where establishing an accurate virtual model is regarded as the most efficient approach to this end up to now. By employing an extended support vector regression (X-SVR), a powerful machine learning algorithm model, this study explores the uncertainty and sensitivity analysis and inverse study of re-entrant honeycombs under quasi-static compressive loads. The proposed framework enables accurate uncertainty quantification, sensitivity analysis, and inverse study, facilitating the related design and optimisation of metastructures when extended to responsive materials. The proposed framework is considered an effective tool for uncertainty quantification and sensitivity analysis, enabling the identification of key parameters affecting mechanical performance. Finally, the inverse study approach leverages X-SVR to swiftly obtain the required structural configurations based on targeted mechanical responses. Full article

A three-dimensional mathematical model and simulation of the impurity diffusion process are developed under the given statistical characteristics of the system of internal stochastically disposed point sources of mass. These sources, possessing varying intensities, are located within the sub-strip according to a uniform distribution. The random source statistics are known, and the problem solution is expressed as the sum of the solution to the homogeneous problem and the convolution of Green’s function with the random point source system. The impurity concentration is averaged. Diffusive fluxes and the total amount of substance passing through any cross-sectional area over a specified time period are modeled using Fick’s laws. General and calculating formulas for averaged diffusive fluxes, including those applicable to steady-state regimes, are derived. A calculating formula for the total substance that has passed through the strip within a given time interval is obtained. A comprehensive software suite is developed to simulate the behavior of the averaged characteristics of the diffusion process influenced by the point source system. The second statistical moments of the impurity concentration are obtained and studied. Full article

A novel concrete-filled corrugated steel tubular (CFCST) column composed of corner steel bars and corrugated steel plates filled with concrete has been proposed recently. Columns with large height-to-width ratios are commonly used in practice, where they are often subjected to eccentric compression. However, there is a lack of research on their stability behavior under such conditions. This study presented a numerical analysis to evaluate the stability performance of CFCST columns under eccentric compression, with eccentricity ratios ranging from 0 to 2.0 and height-to-width ratios between 10 and 30. The numerical results indicated that the N–M interaction curve became less convex as the height-to-width ratio increased. Concrete strength and column width had a greater impact on the stability performance of the CFCST columns at low eccentricity ratios, while steel strength and steel bar width were more influential at high eccentricity ratios. The comparison between numerical and calculation results specified in AISC 360 and GB 50936 showed that both of them were unsuitable to estimate the stability performance of the column under eccentric compression. Finally, a formula was fitted, and the error was basically within 15%, which offered significantly improved accuracy over current design codes. Full article

This study addresses the critical issue of basal heave stability in deep excavations within Bangkok’s soft clay, particularly under conditions of confined groundwater recovery. Historical failures in excavation projects highlight the urgent need for effective stability assessments that account for fluctuating groundwater levels. Utilizing a comprehensive dataset derived from case studies and numerical simulations, this research employs the finite element method (FEM) to analyze the interactions between excavation depth, undrained shear strength, and groundwater dynamics. The findings reveal that groundwater recovery significantly influences effective stress, leading to increased uplift pressures that can destabilize excavation support systems. The numerical analyses indicate that Terzaghi’s method overestimates safety factors, while Bjerrum and Eide’s and Chang’s methods closely match numerical results, emphasizing the need for robust analysis that integrates groundwater effects to enhance stability assessments in urban excavations. Grouting techniques applied 10 m below the diaphragm wall significantly improved stability, with safety factors increasing by 63.47%, 87.86%, and 138.72% over various periods. This study contributes valuable insights into excavation design practices and provides empirical data that can inform future research aimed at mitigating hydraulic heave risks in urban environments. Ultimately, the findings advocate for the integration of advanced modeling techniques in geotechnical engineering to improve safety and structural integrity in excavation projects. Full article

The increasing adoption of electric vehicles has introduced challenges in maintaining grid stability, energy efficiency, and economic optimization. Advanced control strategies are required to ensure seamless integration while enhancing system reliability. This study systematically reviews predictive control applications in energy systems, particularly in electric vehicle integration and bidirectional energy exchange. Using the PRISMA 2020 methodology, 101 high-quality studies were selected from an initial dataset of 5150 records from Scopus and Web of Science. The findings demonstrate that predictive control strategies can significantly enhance energy system performance, achieving up to 35% reduction in frequency deviations, 20–30% mitigation of harmonic distortion, and a 15–20% extension of battery lifespan. Additionally, hybrid approaches combining predictive control with adaptive learning techniques improve system responsiveness by 25% under uncertain conditions, making them more suitable for dynamic and decentralized networks. Despite these advantages, major barriers remain, including high computational demands, limited scalability for large-scale electric vehicle integration, and the absence of standardized communication frameworks. Future research should focus on integrating digital modeling, real-time optimization, and machine learning techniques to improve predictive accuracy and operational resilience. Additionally, the development of collaborative platforms and regulatory frameworks is crucial for large-scale implementation. Full article

Equal-channel angular pressing (ECAP) is one of the most effective methods for obtaining ultrafine-grained structures in metals and alloys, significantly improving their mechanical properties. In this work, FEM modeling and development of a new design of the instrument for ECAP were carried out, followed by the production of real samples of working dies and casing. Four different designs of dies have been studied: with channel intersection angles of 90° and 45° and two schemes with the same angles and a spherical cavity to create back pressure. The main purpose of the study was to study the effect of dies geometry on the stress–strain state and pressing load, as well as to develop an optimal tool design that ensures the reliability and durability of the process. The simulation results showed that reducing the channel intersection angle to 45° increases the degree of accumulated deformation to 4.5 mm/mm but also increases the pressing load to 280 kN. The introduction of a spherical cavity contributes to a more uniform distribution of deformations, although the pressing load increases to 416 kN. Based on the data obtained, an improved tool design with a massive steel casing was developed and manufactured. The analysis and production of real samples confirmed its effectiveness and reliability, which will improve the ECAP process and obtain materials with improved characteristics while reducing operating costs. Full article

In this paper, we compare three mathematical models for the mean velocity and Reynolds stress profiles for fully developed pressure-driven turbulent channel flow with the aim of assessing the level of accuracy of each model. Each model is valid over the whole boundary layer thickness (0 $\le y\le$ $\delta$), and it is formulated in terms of a law of the wall and a law of the wake. To calibrate the mathematical models, we use data obtained by direct numerical simulations (DNS) of pressure-driven turbulent channel flow in the range 182 $\le {Re}_{\tau }\le$10,049. The models selected for performance evaluation are two models (Musker’s and AL84) originally developed based on high Reynolds boundary layer experimental data and Luchini’s model, which was developed when some DNS data were also available for wall-bounded turbulent flows. Differences are quantified in terms of local relative or absolute errors. Luchini’s model outperforms the other two models in the “low” and “intermediate” Reynolds number cases (${Re}_{\tau }=$ 182 to 5186). However, for the “high” Reynolds number cases (${Re}_{\tau }=$ 8016 and ${Re}_{\tau }=$ 10,049). Luchini’s model exhibits larger errors than the other two models. Both Musker’s and AL84 models exhibit comparable accuracy levels when compared with the DNS datasets, and their performance improves as the Reynolds number increases. Full article

In the present research, the AlZnMgCu1.5 alloy was machined via an industrial-type Nd-YAG laser cutting process. The Box–Behnken design of response surface methodology was used to plan the trials. The experiments were carried out by varying the nitrogen pressure (4–10 bar), pulse energy (2.5–5.5 J), cutting speed (10–18 mm/min), and pulse width (1.5–2 ms). ANOVA was conducted to assess the impact of process factors on response characteristics. The ANOVA results suggest that nitrogen pressure has the greatest influence on the input process parameters. A detailed investigation was conducted to examine the effects of various parameters on kerf deviation. The metaheuristic algorithms (i.e., Giant Trevally Optimizer—GTO; and Zebra Optimization Algorithm—ZOA) were implemented to determine the optimum process parameters for producing the best performance measures. A comparative analysis demonstrated that the parametric value provided by the GTO algorithm, which adheres to the ZOA method, yielded the lowest response. Optimization using GTO resulted in a 6.71% improvement in kerf deviation prediction accuracy compared to experimental values, while ZOA achieved a 2.37% improvement. Furthermore, GTO demonstrated superior computational efficiency, converging in 5.687 s, significantly faster than the 11.548 s required by ZOA. The optimal solution suggested by the GTO algorithm is further verified using a confirmation test on the random settings. In addition, the surface morphology of the laser-cut kerf surfaces was analyzed using SEM images. Through this, it is confirmed that the metaheuristic algorithm of GTO is more suitable for finding the optimum process parameters. Full article

The Birnbaum–Saunders (BS) distribution, defined only for non-negative values, is asymmetrical. However, it can be transformed into a normal distribution, which is symmetric. The BS distribution is particularly useful for analyzing data consisting of values greater than zero. This study aims to introduce six approaches for constructing confidence intervals for the difference and ratio of percentiles in Birnbaum–Saunders distributions containing zero values. The proposed approaches include the generalized confidence interval (GCI) approach, the bootstrap approach, the highest posterior density (HPD) approach based on the bootstrap method, the Bayesian approach, the HPD approach based on the Bayesian method, and the method of variance estimates recovery (MOVER) approach. To assess their performance, a Monte Carlo simulation study is conducted, focusing on coverage probability and average length. The results indicate that the MOVER approach and the HPD approach based on the Bayesian method perform better than other approaches for constructing confidence intervals for the difference between percentiles. Moreover, the GCI and Bayesian approaches outperform others when constructing confidence intervals for the ratio of percentiles. Finally, daily wind speed data from the Rayong and Prachin Buri provinces are used to demonstrate the efficacy of the proposed approaches. Full article

Analyzing wildfire behavior is crucial due to its significant environmental repercussions. Among the various influencing factors, terrain slope and wind velocity are pivotal in governing fire spread characteristics. In the present study, we investigate the influence of negative terrain slopes (up to −45°), backward wind velocities (up to 2 m/s), and their combined effects on the surface fire spread rate using the Wildland-Urban Fire Dynamics Simulator (WFDS). Wind velocity in backward flows reduces the rate of spread by 40% at 30° angles, primarily due to the suppression of radiative heat transfer leading to reduced preheating unburnt areas. However, this effect reduces on lower slopes. The key findings reveal a significant increase in fire intensity and the rate of spread when the terrain slope exceeds 20°. The fire front shape evolves from a relatively flat rounded U-shape to a V-shape; it is shown that a downward slope slightly affects the spread rate, and the fire front shape stays flat. Full article

This study explores the performance of a novel curved steel damper system in lessening the seismic response of elevated steel tanks. It specifically examines two types of tanks, broad and tall, by analyzing their behavior during past earthquakes. Non-linear time history analyses were executed using various ground motion records to evaluate the dynamic characteristics and structural responses of the tank systems. The application of the curved steel damper, placed between the tank container and its supporting structure, resulted in a significant reduction in base shear forces and deformations of the tank walls when compared to traditional designs. The findings highlight the effectiveness of the damping system, showing that the curved damper leads to decreased maximum displacement and base shear forces during seismic activities. This research contributes essential knowledge for the seismic design of elevated steel tanks and proposes an innovative, cost-efficient strategy for enhancing their earthquake resilience. Full article

The Bivariate Odd Lindley Half-Logistic (BOLiHL) distribution with progressive Type-II censoring provides a powerful statistical tool for analyzing dependent data effectively. This approach benefits society by enhancing engineering systems, improving healthcare decisions, and supporting effective risk management, all while optimizing resources and minimizing experimental burdens. In this paper, the likelihood function derived under progressive Type-II censoring is generalized for the BOLiHL distribution. The well-known maximum likelihood estimation method and Bayesian estimation are applied to evaluate the parameters of the distribution. A study utilizing simulation techniques is performed to evaluate the performance of the estimators, using statistical analysis metrics for censored observations under a progressive Type-II censoring scheme with varying sample sizes, failure times, and censoring schemes. Additionally, a real dataset is studied to validate the proposed model, delivering impactful analyses for practical applications. Full article

This manuscript presents a theoretical study of a newly developed energy-efficient external wall structure in comparison with a traditional ventilated facade. To conduct numerical studies based on mathematical models of the heat transfer of water vapor filtration through a multilayer filler structure with ventilated and non-ventilated air gaps, a calculation method was developed that additionally considers the presence of heat-reflecting screens and different variations in the geometric parameters of air gaps and thermal insulation layers. The study results demonstrated that the new energy-efficient multilayer wall structure was 6.1–7.2% more efficient in terms of heat transfer resistance than the traditional one, and due to the presence of heat-reflecting screens, the efficiency increased to 15.2–16.3% depending on the geometric parameters of the air and thermal insulation layers of the wall structure. In addition, in all the considered variants of the filler structure geometry (i.e., with closed and ventilated air gaps), there were water vapor condensation zones, but it was established that according to the value of the inadmissibility of moisture accumulation in multilayer wall structures, over the annual period of operation, the structures complied with the standard climatic conditions of Shymkent. The results of this study thus positively complement the existing catalog of energy-efficient wall structures, and the new wall structure can be used while considering the necessary geometric parameters of air and heat-insulating layers when designing buildings in the corresponding climatic conditions. Full article

The importance of using sophisticated interface models to obtain realistic numerical solutions of soil–structure interaction (SSI) problems has been recognised in recent decades. With this aim, various advanced interface models have been developed, which assume that the same advanced constitutive model can describe the soil behaviour inside and outside the shear zone. These models fail to adequately address the experimentally observed stick–slip transition, assuming permanent sticking between the soil and structure. Furthermore, the influence of interface roughness requires model parameter adjustments, e.g., in the critical state of the soil, which are questionable from a physical point of view. To overcome these shortcomings, we propose a general relationship to describe the evolution of the shear strain in the shear zone as a function of the surface roughness, the density, and the normal stress. This relationship, which assumes a stick–slip transition at the interface, can be combined with an advanced constitutive model to describe soil–structure interface behaviour using the same set of model parameters as for the surrounding soil. Depending on the surface roughness of the interface, this transition leads to a localisation within the soil in the shear zone (for rough surfaces) or at the contact surface (for smooth surfaces). The proposed model was validated using interface shear tests from the literature on dry granular soils. A hypoplastic constitutive model was used in the simulations. The comparison of experimental and calculated results demonstrates the ability of the proposed model to realistically reproduce shear stress and relative displacements, including the stick–slip transition observed in the experiments. This instils confidence in the model’s reliability and accuracy, thus providing a reliable numerical tool for SSI analyses. Full article

This paper investigates the flow dynamics of a turbulent fountain with negative buoyancy using a Computational Fluid Dynamics (CFD) model, developed using OpenFOAM^® and calibrated against laboratory experiments. The simulations effectively replicate the geometry and buoyancy fluxes of the fountain, showing a fairly good agreement between the numerical and experimental velocity fields. These simulations are then used to investigate momentum and buoyancy fluxes for various source fluid densities. We find a dominant out-upward momentum transfer in the body of the fountain, while it is mainly out-downward below the inlet section. Furthermore, the vertical flux is almost twice the radial flux, while the tangential components are negligible on the inner side of the fountain. For small density differences between the fountain and the surrounding environment, we find a greater diffusion of the source fluid, while both the vertical and radial salt fluxes increase with increasing density of the fountain. The data generated serve as a significant resource for the development of future CFD models. Full article

Particle swarm optimization (PSO), an important solving method in the field of swarm intelligence, is recognized as one of the most effective metaheuristics for addressing optimization problems. Many adaptive strategies have been developed to improve the performance of PSO. Despite these advances, a key problem lies in defining the configuration criteria of the adaptive algorithm. This study presents an adaptive variant of PSO that relies on fitness landscape analysis, particularly via ruggedness factor estimation. Our approach involves adaptively updating the cognitive and acceleration factors based on the estimation of the ruggedness factor using a machine learning-based method and a deterministic way. We tested them on global optimization functions and the feature selection problem. The proposed method gives encouraging results, outperforming native PSO in almost all instances and remaining competitive with state-of-the-art methods. Full article

This paper presents the development of a computer simulation framework, designed as a cost–effective and technically efficient alternative to experimental studies. The framework focuses on the Bio–Neural Dust System proposed in our previous works, which consists of two components: a light–emitting bio–nanosensor and an opsin–expressing genetically modified neuron. This innovative system holds significant potential for applications in neuroscience and biotechnology research. Programmed in Python, the framework provides researchers with a virtual tool to test and evaluate the Bio–Neural Dust System, enabling the prediction of outcomes for future in vivo experiments. This approach not only conserves resources, but also offers scientists a flexible and accessible means to investigate the complex interactions within the system prior to real–world applications. The framework’s adaptability and potential for diverse research applications highlight its importance in advancing the field of bio–nanotechnology. Full article

Grain storage in silos plays a fundamental role in preserving the quality and safety of agricultural products. This study presents a comparative evaluation of two-dimensional (2D) and three-dimensional (3D) mathematical models to predict the temperature and moisture distribution during unventilated corn storage in cylindrical silos with conical roofs. The models incorporate external temperature fluctuations, solar radiation, grain moisture equilibrium with air humidity via sorption isotherm (water activity), and grain respiration to simulate real-world storage conditions. The 2D model offers computational efficiency and is suitable for preliminary assessments but simplifies natural convection effects and underestimates axial temperature gradients. Conversely, the 3D model provides a detailed representation of heat and moisture transfer phenomena, capturing complex interactions such as buoyancy-driven flow and localized effects of solar radiation. The results reveal that temperature and moisture accumulation are more pronounced in the upper regions of the silo, driven by solar radiation and natural convection, with significant implications for large-scale silos where thermal inertia plays a key role. This dual modeling approach demonstrates that while the 2D model is valuable for quick evaluations, the 3D model is essential for comprehensive insights into thermal and moisture gradients. The findings support informed decision-making in silo design, optimization, and management, enhancing grain storage strategies globally. Full article

Green logistics has gained significant attention in recent years due to increasing pollution levels and their negative effects. This area of research is crucial as governments and countries worldwide recognize the severity of pollution and its detrimental effects. Despite progress, significant gaps remain due to the lack of advanced models that consider additional factors and the influence of speed on their outcomes. This paper presents a case study on the Volume-based Pollution-Routing Problem with Time Windows (VPRPTW). The objective is to minimize CO${}_2$ emissions and improve customer satisfaction using a fleet of delivery vehicles. We propose a mathematical model and a probabilistic Tabu Search (TS) algorithm to solve the studied VPRPTW. The study revealed a decrease in daily fleet size from 16 to 12, indicating improved operational efficiency. In our study, we evaluate the impact of vehicle speed on fuel consumption and compare the results with a constant route speed to those obtained at varying speeds. Computational experiments reveal a significant difference of over 20% between fixed and variable speed assumptions. Additionally, we confirm that distance alone does not always correlate with energy consumption and CO${}_2$ emissions. This highlights the importance of considering variable speeds in routing problems to assist logistics companies, urban planners, and policymakers achieve more accurate and environmentally friendly transportation solutions. Full article

Fibre-reinforced polymers based on natural fibers, such as flax fibers, exhibit pronounced nonlinear orthotropic material behavior. This presents a significant challenge in finite element analysis (FEA) simulations, as the nonlinear constitutive models available in commercial FEA tools are difficult to apply and fail to capture all the material’s specific characteristics. Relying on initial or reduced secant moduli in linear quasi-static analyses of deformations or stress states can result in inaccurate outcomes and overly optimistic strength predictions, particularly in compression-dominated cases. However, with appropriate modifications, classical laminate theory (CLT) can be adapted for nonlinear analysis. This involves iteratively updating the components of the stiffness matrix for the unidirectional (UD) ply during the calculation process based on the current strain state and stress interactions. This study presents and discusses a computational algorithm for the FEA software ABAQUS/CAE 2019, which incorporates material-related orthotropic nonlinearities and stress-dependent interactions within the CLT framework. The algorithm represents a single-scale material model at the meso level (UD ply) and is based on the concept of orthotropic elasto-damage within the framework of continuum damage mechanics (CDM) theory. Numerical implementation is achieved through a user-defined field (USDFLD) subroutine, accompanied by a pre-processing Python script for managing experimental data, computing data fields, and calculating parameters. As shown below, this type of implementation appears justified compared to a user material subroutine (UMAT) subroutine in terms of computational efficiency and practicality. Full article

This paper discusses the process of high-velocity oxygen fuel (HVOF) spraying with modeling of the gas flow parameters and behavior of WC-Co-Cr powder particles of different fractions (up to 20 µm, 21–35 μm and 36–45 μm). It was found that the temperature of the gas stream reaches a maximum of about 2700 °C, after which it gradually decreases, and the pressure in the combustion chamber (before the exit of gases through the nozzle) reaches maximum values, exceeding 400,000 Pa, and the pressure at the exit of the nozzle stabilizes at about 100,000 Pa, which corresponds to the standard atmospheric pressure. The gas velocity increases to 1300–1400 m/s and then decreases to 400 m/s at a distance of about 150 mm. It was determined that powder particles of the 21–35 µm fraction provide more stable parameters of velocity and temperature. Small particles (up to 20 µm) lose velocity and temperature faster as they advance, which deteriorates the coating quality, which was also experimentally confirmed. All results obtained from the HVOF process modeling fully align with the data from experimental studies. Full article

This study presents an experimental and numerical investigation into the stress field in cylinders manufactured from photosensitive resin using the Masked Stereolithography (MSLA) technique. For material characterization, tensile and bending test data from resin specimens were utilized. The stress field in resin disks was experimentally analyzed using photoelasticity and Digital Image Correlation (DIC) methods, subjected to compressive loads, according to the cylinder–plane contact model. Images were captured during the experiments using polarizing film and a low-cost CPL lens, coupled to a smartphone. The experimental results were compared with numerical and analytical simulations, where the formation of fringes and regions indicating the direction and magnitude of normal and shear stresses were observed, with variations ranging from 0.6% to 8.2%. The convergence of the results demonstrates the feasibility of using parts produced with commercially available photosensitive resin on non-professional printers for studying contact theory and stress fields. In the future, this methodology is intended to be applied to studies on stress in gears. Full article

A frequency-reconfigurable MIMO antenna with high gain, low mutual coupling and highly suppressed side lobe level (SLL) for applications in 24 GHz ISM band sensing and automotive radar systems was designed, modeled, and simulated. The reconfigurability feature was modeled with the implementation of a varactor diode in the model to alter the frequency in a wide band around 24 GHz. The design features 2- and 4-port MIMO antenna each comprising a 1 × 8 microstrip patch array. At the core of achieving both a high gain of 16 dBi and high isolation of 38.4 dB at a resonance frequency of 24.120 GHz lies the integration of a metamaterial absorber, comprising an optimized split-ring unit cell to effectively mitigate interference among the MIMO elements. Noteworthy impedance bandwidths of the sensor antenna span from 23.8 to 24.3 GHz, catering to diverse frequency requirements. The proposed sensor antenna feature a half-power beamwidth of 74° in the E-plane and 11° in the H-plane and an SLL of −24 dB at 24.120 GHz showing its robust performance characteristics across multiple operational dimensions. Full article

This study investigates the seismic performance of two-, four-, and six-story composite buildings equipped with viscous wall dampers, focusing on structures with concrete-filled steel tubular (CFST) columns and steel beams. Through nonlinear time history analyses using sequential ground motions, the research evaluates the effectiveness of viscous wall dampers in mitigating seismic demands. Results demonstrate significant reductions in both interstory drift ratios and peak floor accelerations across all building heights when dampers are installed. The study particularly highlights the dampers’ effectiveness in controlling drift demands in lower and middle floors while managing acceleration amplification at upper levels. The findings validate the integration of viscous wall dampers into mid-rise composite structures and underscore the importance of considering sequential ground motions in seismic performance evaluations. Full article