Modelling, Volume 6, Issue 3 (September 2025) – 40 articles

We present a simple algorithm for synthesizing volumetric 3D puzzles from a 3D freeform geometric model represented volumetrically as trivariate NURBs functions, $\mathcal{M}$. The construction algorithm is based on the functional composition of puzzle elements, positioned in the domain of $\mathcal{M}$, with $\mathcal{M}$. The puzzle elements can be (heterogeneous) freeform polygonal models or freeform surface or trivariate functions and of arbitrary shape, and can include added joints to neighboring puzzle elements. The proposed approach is demonstrated via several examples of such volumetric puzzles, 3D printed and assembled. Full article

The solid electrolyte interphase (SEI) is a passive layer, typically a few hundred angstroms thick, that forms on the electrode surface in the first few battery cycles when the electrode is in contact with the electrolyte in lithium-metal batteries. Composed of a combination of lithium salts and organic compounds, the SEI plays a critical role in battery performance, serving as a channel for Li-ion shuttling. Its structure typically comprises an inorganic component-rich sublayer near the electrode and an outer organic component-rich sublayer. Understanding heat transport through the SEI is crucial for improving battery pack safety, particularly since the Li-ion diffusion coefficient exhibits an exponential temperature dependence. This study employs first-principles calculations to investigate phonon-mediated temperature-dependent lattice thermal conductivity across the inorganic components of the SEI, including, LiF, Li₂O, Li₂S, Li₂CO₃, and LiOH. This study is also extended to the dependence of the grain size on thermal conductivity, considering the mosaic-structured nature of the SEI. Full article

The Kolmogorov–Arnold network (KAN) is a regression model that is based on a representation of an arbitrary continuous multivariate function by a composition of functions of a single variable. Experimentally obtained datasets for regression models typically include uncertainties, which in some cases, cannot be neglected. The conventional way to account for the latter is to model confidence intervals of the systems’ outputs in addition to the expected values of the outputs. However, such information may be insufficient, and in some cases, researchers aim to obtain probability distributions of the outputs. The present paper proposes a method for estimating probability distributions of the outputs by constructing an ensemble of models. The suggested approach covers input-dependent probability distributions of the outputs and is capable of capturing the multi-modality, as well as the variation of the distribution type with the inputs. Although the method is applicable to any regression model, the present paper combines it with KANs, since their specific structure leads to the construction of computationally efficient models. The source codes are available online. Full article

A novel right-sidewall gas blowing method is proposed to improve the flow behavior in a single-strand tundish. Despite advances in tundish flow control, the impact of slag layers and sidewall gas injection on flow dynamics and tracer transport remains underexplored. This study combines 1:3.57 scale water model experiments and Compuational Fluid Dynamics (CFD) simulations to investigate the effects of gas injection heights (50 mm and 100 mm) on flow structure, mixing efficiency, and slag layer interactions. Particle Image Velocimetry (PIV) and the stimulus-response method are used for quantitative validation. Results show that sidewall gas blowing suppresses short-circuit flow, increases average residence time by up to 37%, and reduces dead zone volume by up to 19%. The 50 mm blowing height induces stronger surface turbulence, while the 100 mm height improves flow uniformity. The presence of a slag layer significantly dampens surface fluctuations and alters vortex formation. These findings fill a critical research gap in tundish metallurgy and offer a practical reference for optimizing gas blowing strategies in industrial applications. Full article

In this paper, a switched model for DC-DC boost converters with modeling uncertainty is considered. Based on the switched model, a continuous switching control law is first designed to guarantee the robust stability of the closed-loop system. Then, to reduce the data transmission amount and ease the communication burden, a sampled-data switching control law is explored, where the switching action is executed based on a state-dependent condition at each sampling time. The proposed control strategies can track a specific reference point and varying reference points in the presence of modeling uncertainty. Finally, the simulation results show that the proposed sampling switch control reduces steady-state errors and the transient response is significantly smoother. These results confirm the effectiveness and practical potential of the proposed approach. Full article

Traditional median filtering with a fixed window easily leads to edge blurring and adaptive median filtering requires manual presetting of the maximum window parameter and has insufficient retention of details when dealing with high-density salt-and-pepper noise. Aiming at these problems, this paper proposes a hybrid decision-making adaptive median filtering algorithm with dual-window detection in collaboration with particle swarm optimization (PSO). The algorithm quickly locates suspected noise points through a 3 × 3 small window and enhances noise identification accuracy by using a PSO dynamically optimized 5–35-pixel large window. Meanwhile, a hybrid decision-making mechanism based on local statistical properties was introduced to dynamically select median filtering, weighted average based on spatial distance, or pixel preservation strategy to balance noise suppression and detail preservation, and the PSO algorithm was used to automatically find the optimal parameters of the large window’s size to avoid the manual parameter-tuning process. Experiments were conducted on standard grayscale and color images and compared with four traditional methods and two more advanced methods. The experiments showed that the algorithm improved the peak signal-to-noise ratio (PSNR) value by 2–4 dB and the structural similarity index measure (SSIM) metric by 0.05–0.2 under high salt-and-pepper noise density compared with the traditional methods, which effectively improved the contradiction between noise suppression and detail retention in traditional filtering algorithms and provided a highly efficient and intelligent solution for image denoising in high-noise scenarios. Full article

In this paper, a predator–prey model with hunting cooperation and maturation delay is studied. Through theoretical analysis, we investigate the existence of multiple stability switches of the positive equilibrium. By applying Hopf bifurcation theory, the conditions for Hopf bifurcation are derived, indicating the emergence of periodic solutions as the maturation delay passes through critical values. Utilizing center manifold theory and normal form analysis, we determine the stability and direction of the bifurcating orbits. Numerical simulations are performed to validate the theoretical results. Furthermore, the simulations vividly demonstrate the appearance of period-doubling bifurcations, which is the onset of chaotic behavior. Bifurcation diagrams and phase portraits are employed to precisely characterize the transition processes from a stable equilibrium to periodic, period-doubling solutions and chaotic states under different maturation delay values. The study reveals the significant influence of maturation delay on the stability and complex dynamics of predator–prey systems with hunting cooperation. Full article

This study conducts numerical analysis of fatigue crack propagation in deck-rib welded joints of orthotropic steel decks (OSDs) using linear elastic fracture mechanics. The stress intensity factor for central surface cracks under constant range bending stress is calculated, and single and multi-crack propagation are simulated by a numerical integration method. The research results show that deck geometry critically influences crack propagation behavior. Wider decks accelerate propagation of cracks after the crack depth exceeds half the deck thickness, thicker decks exhibit linearly faster propagation rates yet retain larger residual section to bear loads, and increased weld penetration reduces fatigue life. Initial defects rapidly converge to a preferred propagation path, stabilizing near $a_f/c_f\approx 0.1$ ($a_f$ is the failure crack depth and $c_f$ is the half surface crack length) regardless of initial aspect ratio. For multi-crack scenarios, defect density dominates merging, doubling density increases final cracks by 45%. Merged cracks adhere closely to the single-crack path, while total section loss escalates with defect density and deck thickness but remains stress range independent. The identified convergence preferred propagation path enables depth estimation from surface-length measurements during real bridge inspections. Full article

In three-dimensional (3D) logistics environments, finding optimal paths for unmanned aerial vehicles (UAVs) is challenging due to positioning inaccuracies that require ground-based corrections. These inaccuracies are exacerbated in harsh environments, leading to a significant risk of correction failure. This research proposes a multi-objective mixed integer programming model (MILP) that transforms dynamic uncertainties into binary constraints, utilizing a hierarchical sequencing strategy in the Gurobi optimizer to efficiently identify optimal paths. Our simulations indicate that achieving an 80% mission success probability necessitates an optimal path of 104,946 m with nine corrections. For a 100% success rate, the path length increases to 105,874 m, with corrections remaining constant. These results validate the model’s effectiveness in navigating environments with probabilistic constraints, highlighting its potential for addressing complex logistical challenges. Full article

In weak carbonate rock masses, small-sized karst features ranging from greater than 2 cm to over 1 m in diameter can significantly compromise slope stability, yet they are often overlooked in traditional geotechnical models. This study employs the equivalent porous medium (EPM) approach to incorporate these small-sized voids into two-dimensional finite element slope stability analysis using RS2 software (Version 11.022). By treating the matrix of karst hollows as a porous continuum, we simulate the mechanical and hydraulic influence of their presence on pit slope performance. Results show that even small voids substantially reduce the factor of safety, with destabilization intensifying as void density and pore fluid infiltration increase. Distinct failure mechanisms—including circular sliding, localized subsidence due to cavity collapse, and rockfalls from intersecting shear planes—emerge from the simulations. The stress trajectories and yield elements highlight how minor voids influence the distribution and initiation of shear and tensile failures. These findings reveal that karst features previously considered negligible can be critical structural discontinuities that trigger failure. The EPM framework thus provides a computationally efficient and mechanistically sound means of modelling the cumulative impact of small-sized karst features, bridging a significant gap in geotechnical design for karst-prone weak rock slopes. Full article

This paper presents the study of the viscoelastic behavior of high-density polyethylene (HDPE) ASTM 4710 pipes under diametral loads. The experimental procedure consists of applying a displacement ramp followed by a stress relaxation stage on six ring specimens extracted from pipes with varying thickness-to-diameter ratios. The proposed methodology combines the Standard Linear Solid Model (SLSM) with beam theory, introduces adjustment equations for estimating SLSM parameters, and discusses the influence of residual stresses induced during pipe manufacturing and cooling. Finally, the paper shows the validation of the modeling approach based on the results of the mechanical response of an independent test case. Full article

This work investigates the effect of sealing grease on inhibiting the leakage of supercritical carbon dioxide (CO₂) using molecular dynamics simulation. Consideration is given to the effects of temperature, pressure, and leakage channel height. It is found that CO₂ primarily leaks by diffusing into the interface between the grease and the channel at low temperatures, but the leakage is dominated by interfacial diffusion and the bulk penetration of CO₂ across the greases at high temperatures. Moreover, the presence of a large amount of supercritical CO₂ at the interface weakens the interactions between the grease and the channel, resulting in the extrusion of greases at high temperatures. For the pressure effect, the leakage always happens through interfacial diffusion with a low or high pressure. The high pressure can cause the extrusion of greases, as CO₂ distributed in both the interface and the grease can enhance its fluidity and make it more likely to be extruded from the channel under high pressure. Finally, leakage primarily involves interfacial diffusion for a small channel height, but it is also dominated by such diffusion and bulk penetrations with a large height, which is due to the boundary effect on the fluidity of greases. Full article

This paper presents a theoretical model of a thin, penny-shaped piezoelectric actuator bonded to an isotropic thermo-elastic substrate under coupled electrical-thermal-diffusive loading. The problem is assumed to be axisymmetric, and the peeling stress of the film is neglected in accordance with membrane theory, yielding a simplified equilibrium equation for the piezoelectric film. By employing potential theory and the Hankel transform technique, the surface strain of the substrate is analytically derived. Under the assumption of perfect bonding, a governing integral equation is established in terms of interfacial shear stress. The solution to this integral equation is obtained numerically using orthotropic Chebyshev polynomials. The derived results include the interfacial shear stress, stress intensity factors, as well as the radial and hoop stresses within the system. Finite element analysis is conducted to validate the theoretical predictions. Furthermore, parametric studies elucidate the influence of material mismatch and actuator geometry on the mechanical response. The findings demonstrate that, the performance of the piezoelectric actuator can be optimized through judicious control of the applied electrical-thermal-diffusive loads and careful selection of material and geometric parameters. This work provides valuable insights for the design and optimization of piezoelectric actuator structures in practical engineering applications. Full article

This research explores the application of NiTiNOL-steel (NiTi–ST) wire ropes as nonlinear damping devices for mitigating vibrations in composite stiffened panels. A dynamic model is formulated by coupling the composite panel with a modified Bouc–Wen hysteresis representation and employing the first-order shear deformation theory (FSDT), based on Hamilton’s principle. Using the Galerkin truncation method (GTM), the model is converted into a system of nonlinear ordinary differential equations. The dynamic response to axial harmonic excitations is analyzed, emphasizing the vibration reduction provided by the embedded NiTi–ST ropes. Finite element analysis (FEA) validates the model by comparing natural frequencies and force responses with and without ropes. A newly developed experimental apparatus demonstrates that NiTi–ST cables provide outstanding vibration damping while barely affecting the system’s inherent frequency. The N3a configuration of NiTi–ST ropes demonstrates optimal vibration reduction, influenced by excitation frequency, amplitude, length-to-width ratio, and composite layering. Full article

Inventory counting of logistics boxes in complex scenarios has always been a core task in intelligent logistics systems. To solve the problems of a high leakage rate and low computational efficiency caused by stacking, occlusion, and rotation in box detection against complex backgrounds in logistics environments, this paper proposes a lightweight, rotated object detection model: REW-YOLO (RepViT-Block YOLO with Efficient Local Attention and Wise-IoU). By integrating structural reparameterization techniques, the C2f-RVB module was designed to reduce computational redundancy in traditional convolutions. Additionally, the ELA-HSFPN multi-scale feature fusion network was constructed to enhance edge feature extraction for occluded boxes and improve detection accuracy in densely packed scenarios. A rotation angle regression branch and a dynamic Wise-IoU loss function were introduced to further refine localization and balance sample quality. Experimental results on the self-constructed BOX-data dataset demonstrate that the REW-YOLO achieves 90.2% mAP50 and 130.8 FPS, with a parameter count of only 2.18 M, surpassing YOLOv8n by 2.9% in accuracy while reducing computational cost by 28%. These improvements provide an efficient solution for automated box detection in logistics applications. Full article

This study proposes a coupled constitutive model that captures the anisotropic failure characteristics and damage evolution of nickel-based single-crystal (SX) superalloys under various temperature conditions. The model accounts for both creep rate and material damage evolution, enabling accurate prediction of the typical three-stage creep curves, macroscopic fracture morphologies, and microstructural features under uniaxial tensile creep for specimens with different crystallographic orientations. Creep behavior of SX superalloys was simulated under multiple orientations and various temperature-stress conditions using the proposed model. The resulting creep curves aligned well with experimental observations, thereby validating the model’s feasibility and accuracy. Furthermore, a finite element model of cylindrical specimens was established, and simulations of the macroscopic fracture morphology were performed using a user-defined material subroutine. By integrating the rafting theory governed by interfacial energy density, the model successfully predicts the rafting morphology of the microstructure at the fracture surface for different crystallographic orientations. The proposed model maintains low programming complexity and computational cost while effectively predicting the creep life and deformation behavior of anisotropic materials. The model accurately captures the three-stage creep deformation behavior of SX specimens and provides reliable predictions of stress fields and microstructural changes at critical cross-sections. The model demonstrates high accuracy in life prediction, with all predicted results falling within a ±1.5× error band and an average error of 14.6%. Full article

This paper presents a novel four-dimensional autonomous conservative model characterized by an infinite set of equilibrium points and an unusual algebraic structure in which all eigenvalues of the Jacobian matrix are zero. The linearization of the proposed model implies that classical stability analysis is inadequate, as only the center manifolds are obtained. Consequently, the stability of the system is investigated through both analytical and numerical methods using Lyapunov functions and numerical simulations. The proposed model exhibits rich dynamics, including hyperchaotic behavior, which is characterized using the Lyapunov exponents, bifurcation diagrams, sensitivity analysis, attractor projections, and Poincaré map. Moreover, in this paper, we explore the model with fractional-order derivatives, demonstrating that the fractional dynamics fundamentally change the geometrical structure of the attractors and significantly change the system stability. The Grünwald–Letnikov formulation is used for modeling, while numerical integration is performed using the Caputo operator to capture the memory effects inherent in fractional models. Finally, an analog electronic circuit realization is provided to experimentally validate the theoretical and numerical findings. Full article

The efficient thermal management of cutting tools is critical for ensuring dimensional accuracy, surface integrity, and tool longevity, especially in the high-speed dry machining process. However, conventional cooling methods often fall short in reaching the heat-intensive zones near the cutting inserts. This study proposes a novel internal cooling strategy that integrates triply periodic minimal surface (TPMS) structures into the toolholder, aiming to enhance localized heat removal from the cutting region. The thermal-fluidic behaviors of four TPMS topologies (Gyroid, Diamond, I-WP, and Fischer–Koch S) were systematically analyzed under varying coolant velocities using computational fluid dynamics (CFD). Several key performance indicators, including the convective heat transfer coefficient, Nusselt number, friction factor, and thermal resistance, were evaluated. The Diamond and Gyroid structures exhibited the most favorable balance between heat transfer enhancement and pressure loss. The experimental validation confirmed the CFD prediction accuracy. The results establish a new design paradigm for integrating TPMS structures into toolholders, offering a promising solution for efficient, compact, and sustainable cooling in advanced cutting applications. Full article

The electromechanical braking (EMB) system is an important component of intelligent vehicles and is also the core actuator for longitudinal dynamic control in autonomous driving motion control. Therefore, we propose a new mechanism layout form for EMB and a feedforward second-order linear active disturbance rejection controller based on clamping force. This solves the problem of excessive axial distance in traditional EMB and reduces the axial distance by 30%, while concentrating the PCB control board for the wheels on the EMB housing. This enables the ABS and ESP functions to be integrated into the EMB system, further enhancing the integration of line control and active safety functions. A feedforward second-order linear active disturbance rejection controller (LADRC) based on the clamping force of the brake caliper is proposed. Compared with the traditional clamping force control methods three-loop PID and adaptive fuzzy PID, it improves the response speed, steady-state error, and anti-interference ability. Moreover, the LADRC has more advantages in parameter adjustment. Simulation results show that the response speed is increased by 130 ms, the overshoot is reduced by 9.85%, and the anti-interference ability is increased by 41.2%. Finally, the feasibility of this control algorithm was verified through the EMB hardware-in-the-loop test bench. Full article

Traffic crashes represent a major challenge for road safety, public health, and mobility management in complex urban environments, particularly in metropolitan areas characterized by intense traffic flows, high population density, and strong commuter dynamics. The development of short-term traffic crash prediction models represents a fundamental line of analysis in road safety research within the scientific community. Among these efforts, macro-level modeling plays a key role by enabling the analysis of the spatiotemporal relationships between diverse factors at an aggregated zonal scale. However, in cities like Bogotá, predicting short-term traffic crashes remains challenging due to the complexity of these spatiotemporal dynamics, underscoring the need for models that more effectively integrate spatial and temporal data. This paper presents a strategy based on deep learning techniques to predict short-term spatiotemporal traffic crashes in Bogotá using 2019 data on socioeconomic, land use, mobility, weather, lighting, and crash records across TMAU and TAZ zones. The results showed that the strategy performed with a model called SpatioConvGru-Net with top performance at the TMAU level, achieving $R^2$ = 0.983, MSE = 0.017, and MAPE = 5.5%. Its hybrid design captured spatiotemporal patterns better than CNN, LSTM, and others. Performance improved at the TAZ level using transfer learning. Full article

To clarify the potential failure modes of reinforced concrete (RC) beams under impact and understand their impact resistance safety, a comprehensive study was conducted by focusing on the failure mode discrimination and failure probability of RC beams under impact loads. This research utilized drop hammer impact tests, ABAQUS2022 software, and theoretical methods. The study examined three typical failure modes of RC beams under impact loads: flexural failure, flexural-shear failure, and shear failure. A discrimination criterion based on the flexural-shear capacity–effect curve was developed. Utilizing this criterion, along with the basic principles of structural reliability theory, the failure probability of RC beams under impact loads was calculated and analyzed using the Monte Carlo method. The results indicate that the criterion based on the flexural-shear capacity–effect curve can be used for discriminating failure modes of RC beams under impact loads. The impact velocity and stirrup ratio were identified as crucial factors that influenced the failure modes of RC beams under impact. Specifically, an increase in the stirrup spacing reduced the reliability of the RC beams under impact, while an increase in the stirrup ratio could significantly enhance their impact resistance. Furthermore, with a constant impact energy, an increase in beam span correlated with the improved reliability of RC beams under impact, where larger spans yielded a better impact resistance. Full article

As industrialization and economic growth accelerate, PM_2.5 pollution has become a critical environmental concern. Predicting PM_2.5 concentration is challenging due to its nonlinear and complex temporal dynamics, limiting the accuracy and robustness of traditional machine learning models. To enhance prediction accuracy, this study focuses on Ma’anshan City, China and proposes a novel hybrid model (QMEWOA-QCAM-BiTCN-BiLSTM) based on an “optimization first, prediction later” approach. Feature selection using Pearson correlation and RFECV reduces model complexity, while the Whale Optimization Algorithm (WOA) optimizes model parameters. To address the local optima and premature convergence issues of WOA, we introduce a quantum-enhanced multi-strategy improved WOA (QMEWOA) for global optimization. A Quantum Causal Attention Mechanism (QCAM) is incorporated, leveraging Quantum State Mapping (QSM) for higher-order feature extraction. The experimental results show that our model achieves a MedAE of 1.997, MAE of 3.173, MAPE of 10.56%, and RMSE of 5.218, outperforming comparison models. Furthermore, generalization experiments confirm its superior performance across diverse datasets, demonstrating its robustness and effectiveness in PM_2.5 concentration prediction. Full article

In this paper, we develop a peridynamic computational framework to analyze thermomechanical interactions in fractured thin films subjected to ultrashort-pulsed laser excitation, employing nonlocal discrete material point discretization to eliminate mesh dependency artifacts. The generalized Cattaneo–Fourier thermal flux formulation uncovers contrasting dynamic responses: hyperbolic heat propagation ($F_T=0$) generates intensified temperature localization and elevates transient crack-tip stress concentrations relative to classical Fourier diffusion ($F_T=1$). A GSSSS (Generalized Single Step Single Solve) i-Integration temporal scheme achieves oscillation-free numerical solutions across picosecond-level laser–matter interactions, effectively resolving steep thermal fronts through adaptive stabilization. These findings underscore hyperbolic conduction’s essential influence on stress-mediated fracture evolution during ultrafast laser processing, providing critical guidelines for thermal management in micro-/nano-electromechanical systems. Full article

The study aims to increase productivity in the cold room door manufacturing industry by addressing non-value-adding operations, identifying bottlenecks, and reducing processing time through digital twin (DT)-based simulation. The goal is to eliminate the need for supply chain outsourcing and increase overall efficiency. The research involves developing a DT of the existing production process for five distinct categories of cold room doors: flush door, single door, double door, face-mounted door, and sliding door. Simulation was used to uncover problems at multiple stations, encompassing curing, welding, and packing. Lean principles were used to identify the causes of inefficiency, and the process was improved using TRIZ principles. These changes produced a 42.90% improvement in productivity, a 20% dependence reduction on outsourcing and an increase of 10.5% added inventory to the shortage demand level. The approach presented is provided for a particular manufacturer of cold room doors, but the methods and techniques used are generally applicable to other manufacturing companies to support systematic innovation. Combining DT simulation, lean techniques and TRIZ principles, this study presents a strong approach to addressing the productivity challenges in manufacturing. The incorporation of these methods has brought considerable operational efficiency and has minimised dependency on external outsourcing. Full article

This study presents a numerical comparison between Direct numerical simulation (DNS) and the standard κ-ε turbulence model to evaluate natural convection in a two-dimensional, differentially heated, air-filled cavity over the Rayleigh number range 10³ to 10¹⁰. The objective is to assess the predictive capabilities of both methods across laminar and turbulent regimes, with a particular emphasis on the quantitative comparison of thermal characteristics under high Rayleigh number conditions. The Navier–Stokes and energy equations were solved using the finite element method with Boussinesq approximation, employing refined meshes near the hot and cold walls to resolve thermal and velocity boundary layers. The results indicate that for Ra ≤ 10⁶, the κ-ε model significantly underestimates temperature gradients, maximum velocities, and average Nusselt numbers, with errors up to 19.39%, due to isotropic assumptions and empirical formulation. DNS, in contrast, achieves global energy balance errors of less than 0.0018% across the entire range. As Ra increases, the κ-ε model predictions converge to DNS, with Nusselt number deviations dropping below 1.2% at Ra = 10¹⁰. Streamlines, temperature profiles, and velocity distributions confirm that DNS captures flow dynamics more accurately, particularly near the wall vortices. These findings validate DNS as a reference solution for high-Ra natural convection and establish benchmark data for assessing turbulence models in confined geometries Full article

To investigate the impermeability characteristics of composite geomembranes in rigid landfills, a three-dimensional finite element seepage analysis model, which incorporates a composite geomembrane, was established based on a case study of a rigid landfill project in Tongling. Utilizing the seepage mechanism of the composite geomembrane, the seepage distribution patterns of the hazardous waste leachate within the unit cell were computed under representative operating conditions. Different thickness amplification factor schemes for the equivalent treatment of the composite geomembrane were comparatively analyzed, considering both isotropic and anisotropic seepage conditions. The relationships between the seepage flow rate, velocity, and thickness amplification factor were determined. The results showed that the leachate experiences a rapid drop in the water head as it passes through the composite geomembrane, with a low seepage flow rate and velocity, highlighting the membrane’s significant impermeability effect. The finite element analysis indicated that thickness amplification of the composite geomembrane based on the flow equivalence is feasible to some degree, but treating the geomembrane as an anisotropic material during the equivalent process better approximates the actual conditions. Full article

Wind turbine performance in cold regions is affected by icing which can lead to power reduction due to the aerodynamic degradation of the turbine blade. The development of airfoil shapes applied as blade sections contributes to improving the aerodynamic performance under a wide range of weather conditions. The present study considers inverse design coupled with numerical modelling to simulate the effects of varying airfoil thickness and maximum camber. The inverse design process was implemented in MATLAB R2023a, whereas the numerical models were constructed using ANSYS Fluent and FENSAP ICE 2023 R1. The inverse design process applied the modified Garabedian–McFadden (MGM) iterative technique. Shear velocities were calculated from the flow over an airfoil with slip conditions, and then this velocity distribution was modified according to the prevailing icing conditions to obtain the target velocities. A parameter was proposed to consider the airfoil thickness as well when calculating the target velocities. The airfoil generated was then exposed to various atmospheric conditions to check the improvement in the aerodynamic performance. The ice mass and lift-to-drag ratio were determined considering cloud characteristics under varying liquid water content (LWC) from mild to severe (0.1 g/m³ to 1 g/m³), median volume diameter (MVD) of 50 µm, and two ambient temperatures (−4 °C and −20 °C) that characterize freezing drizzle and in-cloud icing conditions. The ice mass on the blade section was not significantly impacted by modifying the shape after applying the process developed (i.e., <5%). However, the lift-to-drag ratio that describes the aerodynamic performance may even be doubled in the icing scenarios considered. Full article

To address thermal imbalance and ground temperature degradation in shallow geothermal heat pump (GSHP) systems in severely cold climates, this study analyzes a typical logistics building using an hourly dynamic load model. Multiyear simulations were conducted to investigate the coupling between building load variation and soil thermal response. The results indicate that with a cumulative heating load of 14.681 million kWh and cooling load of 6.3948 million kWh, annual heat extraction significantly exceeds heat rejection, causing ground temperature to decline by about 1 °C per year. Over five and ten years, the cumulative drops reached 2.65 °C and 4.71 °C, respectively, leading to a noticeable reduction in borehole heat exchanger performance and system COP. The study quantitatively evaluates ground temperature and heat exchange degradation, highlighting the key role of load imbalance. To mitigate long-term thermal deterioration, strategies such as load optimization, summer heat reinjection, and operational adjustments are proposed. The findings offer guidance for the design and sustainable operation of GSHP systems in cold regions. Full article

Efficient logistics and transport infrastructure are critical in contemporary urban and interurban scenarios due to their impact on economic development, environmental sustainability, and quality of life. This study explores the use of the Ant Colony Optimization (ACO) metaheuristic applied to the Vehicle Routing Problem (VRP) and the strategic positioning of service stations along major highways. Through a systematic mapping of the literature and practical application to a real-world scenario—specifically, a case study on the Bandeirantes Highway (SP348), connecting Limeira to São Paulo, Brazil—the effectiveness of ACO is demonstrated in addressing complex logistical challenges, including capacity constraints, route optimization, and resource allocation. The proposed method integrates graph theory principles, entropy concepts from information theory, and economic analyses into a unified computational model implemented using Python (version 3.12), showcasing its accessibility for educational and practical business contexts. The results highlight significant improvements in operational efficiency, cost reductions, and optimized service station placement, emphasizing the algorithm’s robustness and versatility. Ultimately, this research provides valuable insights for policymakers, engineers, and logistics managers seeking sustainable and cost-effective solutions in transport infrastructure planning and management. Full article

Thermal barrier coatings have been widely used in industrial fields where thermal damage occurs, and they are crucial for insulation technology and for the safe service of high-temperature components. So, it is critical to accurately predict the reliability of thermal barrier coatings. In this work, an adaptive reliability analysis method based on radial basis functions is proposed, in which different shape parameters and subsets are used to initiate different radial basis function models for multiple predictions. An active learning function that comprehensively considers local uncertainty, limit state function information, and distance among samples is then used for sequential sampling, and the proposed method is validated via a four-branch series connection system. Finally, a reliability analysis is conducted on the failure of interface oxidation in thermal barrier coatings, which verifies the feasibility of the proposed method. Full article