Search Results (734)

Under extreme steady-state temperature gradients, external thermal insulation composite systems (ETICSs) are prone to thermal deformation, which can cause mortar cracking, hollowing, and even delamination and detachment of insulation boards, thus degrading building envelope performance and threatening structural and personal safety. In this study, a combined method of numerical simulation using ANSYS software and experimental testing was adopted to investigate the thermal deformation characteristics of three commonly used insulation materials: Expanded Polystyrene (EPS), Extruded Polystyrene (XPS), and Polyurethane (PU). The effects of temperature difference from 10 °C to 30 °C, insulation board thickness from 30 mm to 100 mm, and surface mortar thickness from 5 mm to 10 mm on strain distribution and deformation mechanism were systematically analyzed. Experimental validation showed good agreement with the simulation results, quantified by an estimated relative error of less than 15% across the investigated insulation thicknesses and steady-state temperature conditions. The results indicate that the strains of EPS, XPS, and PU boards all increase significantly as the temperature difference across the board rises. Under outdoor temperatures of 30 °C, 40 °C and 50 °C with a constant indoor temperature of 20 °C, the thickness-direction strain at the EPS–mortar interface increases by approximately 35% when the temperature difference increases from 10 °C to 30 °C. Increasing both insulation board thickness and mortar protective layer thickness effectively reduces thermal deformation. Specifically, when the EPS board thickness increases from 30 mm to 100 mm, the thickness-direction strain decreases by approximately 73%; and when the mortar thickness increases from 5 mm to 10 mm, the interfacial strain decreases by approximately 32%. Due to differences in linear expansion coefficients, the three insulation materials exhibit distinctly different thermal deformation behaviors, with the thickness-direction strain following the order EPS > XPS > PU. These findings provide a theoretical basis and data support for material selection, structural optimization, and safety design of external wall insulation systems. Full article

Metal matrix composites (MMCs) are engineered multiphase materials in which a continuous metallic matrix contains deliberately introduced reinforcing phases. Their properties arise from the combined effects of the matrix, reinforcement, interface, processing route and spatial architecture. The matrix provides metallic continuity, plastic deformation capacity, processability and thermal or electrical conduction, whereas the reinforcement is selected to modify stiffness, strength, hardness, wear resistance, thermal stability, corrosion response or functional behavior. From a practical interpretation standpoint, MMC performance should not be ascribed solely to the reinforcement fraction, but rather to the coupled effects of reinforcement distribution, interfacial bonding, porosity, residual stress, heat-treatment state, and architecture. Full article

In wildfire environments, high temperatures generated by wildfires may cause thermal aging, deformation, and even burning damage to the silicone rubber sheds of composite insulators, thereby deteriorating their surface hydrophobicity and insulation characteristics. Meanwhile, ash and carbonaceous particles produced by vegetation combustion tend to accumulate on insulator surfaces, forming conductive contamination layers that reduce surface resistance, intensify leakage current activity, and increase the risk of flashover. To investigate these effects, FXBW₄-35/70 composite insulators were selected as the research object. A simulated burning test platform was established to evaluate variations in the mechanical properties of insulator sheds under wildfire conditions. In addition, the feasibility of using simulated ash was assessed. AC flashover tests were conducted on contaminated insulators to quantify the influence of ash deposition on flashover performance. Beyond confirming the thermal aging behavior of silicone rubber under wildfire exposure, this study establishes a quantitative relationship between wildfire ash deposition, equivalent contamination severity, and flashover performance. A correction model for post-fire pollution withstand voltage is further proposed, providing a practical basis for condition assessment and maintenance of transmission line insulators after wildfire events. Full article

Shape-memory polymers (SMPs) are gaining significant attention for their ability to recover predefined shapes via external stimuli. Among thermally activated systems, biodegradable blends of polylactic acid (PLA) and polycaprolactone (PCL) are particularly promising for biomedical devices and soft actuators. This study develops a thermo-mechanical theoretical model to investigate the shape-memory behavior of a PLA/PCL composite blend under controlled thermal cycling. The framework integrates transient heat transfer, temperature-dependent elasticity, and viscoelastic dynamics to predict temperature evolution, deformation, and internal stress. The thermal response is computed via Newton’s law of convection, while the mechanical transition is described by a sigmoidal temperature- and crystallinity-dependent Young’s modulus. Beam bending theory is employed to evaluate the spatial distribution of strain and stress. A parametric sensitivity analysis was performed to evaluate the influence of different parameters, including the crystallinity grade, convective heat transfer coefficient, glass transition temperature, and viscoelastic recovery constant. The theoretical study accurately reproduces the shape-memory cycle, quantifying performance through fixation and recovery ratios. This model provides a robust tool for the rational design and optimization of biodegradable smart polymer structures. Full article

Heat transport in heterogeneous materials can deviate markedly from classical Fourier behavior when microstructural disorder, trapping effects, nonlinear mobility, and long-range temporal correlations interact across multiple spatial and temporal scales. These mechanisms may produce delayed relaxation, persistent thermal footprints, front deformation, and non-classical spreading patterns that are not adequately represented by conventional integer-order diffusion models. In this study, a modeling and simulation framework is developed for anomalous heat transport in heterogeneous media using a two-dimensional time-fractional porous medium equation. The model combines a Caputo fractional time derivative, which represents thermal memory, with nonlinear degenerate porous-medium diffusion, spatially heterogeneous conductivity, localized volumetric heating, and Robin-type convective boundary exchange. A conservative fully discrete numerical scheme is constructed using flux-based finite differences for the heterogeneous nonlinear diffusion operator and an $L1$ approximation for the Caputo derivative. The nonlinear algebraic system at each time level is solved using an under-relaxed Picard frozen-coefficient iteration with non-negativity enforcement and sparse direct solution of the resulting linear systems. The numerical implementation is verified through a manufactured-solution convergence study, and additional analyses are performed to examine computational cost, Picard iteration behavior, coefficient-regularization sensitivity, strong-source effects, heterogeneous conductivity structures, and long-time thermal-footprint persistence. The results show that heterogeneous conductivity mainly redirects heat through preferential pathways and enlarges the spatial footprint while producing negligible changes in global heat content. Stronger fractional memory, represented by smaller fractional order, increases the persistence and spatial reach of moderate heating, whereas larger porous-medium exponents confine heat near the source and preserve higher local peaks. Source amplitude increases the thermal burden and footprint monotonically over the tested range, including strong forcing, without producing an abrupt localization-spreading transition. Boundary exchange remains secondary in the short-time interior-heating regime considered. These findings demonstrate that the proposed two-dimensional time-fractional porous medium framework provides a verified and physically interpretable model for non-Fourier heat transport in heterogeneous materials, where local intensity, global heat retention, and spatial thermal exposure must be assessed jointly. Full article

The construction sector is undergoing a rapid transition toward more resilient, sustainable, and digitally connected systems, creating increasing demand for materials capable of providing functions beyond conventional structural performance. In this context, smart materials have emerged as promising solutions due to their ability to respond to mechanical, thermal, chemical, or electromagnetic stimuli through adaptive behaviors such as self-healing, structural sensing, energy regulation, vibration control, and reversible deformation. Despite growing scientific interest, available knowledge remains fragmented across specific material families and isolated application domains. Therefore, this study presents a PRISMA-based systematic review of smart materials in construction using peer-reviewed journal literature indexed in Scopus during the 2021–2026 period. The review examines the principal smart material families currently applied in construction, including self-healing concretes, self-sensing cementitious systems, Shape Memory Alloys (SMA), piezoelectric materials, phase change materials, adaptive coatings, conductive nanocomposites, and multifunctional geopolymers. Their engineering functions, structural and architectural applications, reported performance characteristics, sustainability contributions, digital integration potential, and implementation barriers are comparatively discussed and qualitatively synthesized based on the reviewed literature. The findings indicate that smart materials can improve durability, structural health monitoring, seismic resilience, thermal efficiency, lifecycle performance, and carbon reduction when properly integrated into buildings and infrastructure. However, large-scale adoption remains constrained by high initial costs, manufacturing scalability, regulatory uncertainty, long-term durability validation, and limited market confidence. The review further shows that the greatest future potential lies in combining material intelligence with IoT platforms, artificial intelligence, BIM environments, and digital twins. Overall, smart materials are positioned as strategic enablers of next-generation low-carbon, adaptive, and intelligent construction systems. Full article

Copper and its alloys are widely used in electrical, automotive, aerospace, and energy applications because of their excellent thermal and electrical conductivity. However, the low hardness and poor wear resistance of pure Cu limit its use under tribologically demanding sliding conditions. In this study, Cu matrix composites reinforced with 1 wt.% boron carbide (B₄C), boron (B), chromium (Cr), cobalt (Co), alumina (Al₂O₃), and graphite (Gr) were fabricated by powder metallurgy and comparatively evaluated under identical processing and testing conditions. Phase constitution and microstructural characteristics were analyzed by XRD, SEM, and EDS, while mechanical and tribological behavior was assessed by Vickers hardness and dry sliding wear tests. All reinforcements improved the hardness of the Cu matrix compared with unreinforced Cu. The hardness increase followed the order Cu–B₄C (68.91%) > Cu–B (66.43%) > Cu–Gr (63.97%) > Cu–Al₂O₃ (61.79%) > Cu–Cr (42.69%) > Cu–Co (36.04%). Dry sliding wear tests, performed under a 10 N normal load, 0.05 m s⁻¹ sliding speed, and 1000 m sliding distance against a 316L stainless-steel ball, showed that all reinforced composites exhibited lower mass loss and more stable sliding behavior than pure Cu. Among all samples, Cu–B₄C displayed the best wear performance, with a 154.8% improvement in wear resistance relative to pure Cu. SEM analysis of the worn surfaces revealed that reinforcement addition reduced severe plastic deformation, groove formation, and delamination, leading to a more stable wear regime. Graphite- and boron-containing composites benefited from interfacial lubrication and contact stabilization, whereas B₄C and Al₂O₃ improved wear resistance through rigid-particle strengthening and enhanced load-bearing capacity. By comparing ceramic, metalloid, metallic, oxide, and solid-lubricating reinforcements at the same low addition level and under identical processing and testing conditions, this study provides a reinforcement-selection framework for Cu-based composites requiring improved hardness and dry-sliding durability. Full article

ETFE cushions are applied to building facades in a wide range of geometric forms and sizes. However, information on how cushion geometry and dimensions affect bulging behavior, thickness and area values, structural strength, thermal conductivity, and energy performance remains limited. Therefore, this study investigates cushion typology in eight geometries (isosceles and equilateral triangle, square, rectangle, rhombus, pentagon, hexagon, circular) with side lengths or radius values between 1 and 10 m, covering 115 variations. Geometric/physical mathematical area calculations, the parabolic dome model, elastic plate bending theory, the empirical thickness model, and thermal-resistance and degree day-based energy calculation approaches are used to obtain planar area, inflated curved surface area, maximum and average thickness, R and U values, and heating, cooling, and total energy consumption for each typology. The use of AI in numerical calculations provides fast and efficient design solutions in architecture and enables various geometric and performance scenarios to be produced rapidly. Circular, hexagon, and pentagon cushions lower U values and provide energy savings due to their high bulging capacity and deformation homogeneity; square, rhombus, and rectangle cushions show medium-level performance; isosceles and equilateral triangles limit energy savings because they produce higher U values. In conclusion, an increase in average bulging thickness and characteristic length reduces the number of cushions required to cover the facade, decreases the U value, reduces total heating and cooling energy consumption, and improves thermal performance. When a facade is covered with cushions of different geometries and sizes, it provides up to approximately 99.24% energy savings. Full article

The extreme thermal environment during the underground coal gasification (UCG) process poses a severe threat to the stability of the gasification cavity and the integrity of the surrounding rock. This paper aims to reveal the thermo-mechanical response characteristics and damage evolution mechanism of sandstone under true triaxial unloading conditions following exposure to high temperatures. Sandstone specimens were thermally pre-treated at five temperature gradients (25 °C, 200 °C, 400 °C, 600 °C, and 800 °C) and subsequently subjected to true triaxial loading and unloading experiments. The effects of varying temperatures on the strength, deformation parameters, dilation angle evolution, and macroscopic failure modes of the sandstone were systematically analyzed. The results indicate a significant critical transition point in the mechanical behavior of the sandstone at 400 °C. Below this threshold, thermal-induced microcrack closure leads to an increase in peak strength (with the peak strength at 800 °C increasing by approximately 67% compared to room temperature). Conversely, above 400 °C, thermal damage to the mineral grains intensifies, causing the crack propagation pattern to transition from brittle shear to a complex tension-shear splitting mode, accompanied by severe dilatancy (with a generalized Poisson’s ratio exceeding 0.8). Based on these findings, this study proposes a stage-wise damage evolution model alongside a targeted zonal support strategy, recommending the application of high-prestressed support in high-temperature zones above 400 °C to suppress tensile failure. Ultimately, this research provides a crucial theoretical basis for evaluating the long-term stability of high-temperature underground engineering projects and ensuring operational safety. Full article

The optimization of Fused Filament Fabrication (FFF) process parameters is commonly performed using room-temperature mechanical properties as the main decision criteria, while the temperature-dependent thermomechanical response of printed polymers is often not explicitly considered. This limitation is relevant for functional components intended to operate above room temperature, where stiffness retention and viscoelastic behavior may strongly affect service performance. This work proposes an experimental–statistical framework for selecting FFF parameters by integrating Design of Experiments (DoE), tensile testing, dynamic mechanical analysis (DMA), Analysis of Variance (ANOVA), the Entropy Weight Method (EWM) and the VIKOR method. Two materials with contrasting thermomechanical behavior were investigated: a high-performance semicrystalline polymer, Z-PEEK, and an elastomeric thermoplastic, TPU 95A. For each material, a DoE was defined to evaluate the influence of key printing parameters, and the manufactured specimens were characterized in terms of maximum tensile force, maximum deformation and storage modulus at selected temperatures. The ANOVA results showed a material-dependent influence of the processing parameters, with thermally driven parameters being especially relevant for Z-PEEK and deposition-related parameters having a stronger influence on TPU 95A. The EWM–VIKOR analysis identified the optimal Z-PEEK configuration as 400 °C extrusion temperature, 200 °C build plate temperature and 150 °C chamber temperature, whereas the optimal TPU 95A configuration corresponded to 225 °C extrusion temperature, 0.10 mm layer height, 50 mm/s printing speed and 80 °C build plate temperature. Overall, the results demonstrate that incorporating DMA-derived thermomechanical indicators into MCDM-based optimization provides a more application-oriented basis for FFF parameter selection than approaches based only on room-temperature mechanical properties. Full article

The emergence of organic–inorganic hybrid composites integrating magnetic nanoparticles (MNPs) with polymers has been an important advancement in modern biological research. Among these systems, magnetic sodium alginate (SA)-based hydrogels (MSABHs), produced by embedding MNPs within an SA framework, exhibit remarkable potential for biomedical applications owing to their high biocompatibility, rapid magnetic response, controllable spatiotemporal behavior, and remote, non-invasive operation. Under the influence of an alternating magnetic field (AMF), MSABHs can exhibit various responses, including deformation, motion, and thermal generation, which are highly valuable for diagnostic and therapeutic medical applications. This review first outlines the key studies on SA and MNPs, along with the various synthesis routes used to fabricate MSABHs. Subsequently, the discussion primarily focuses on their versatile biomedical applications, including tissue engineering, targeted drug delivery, thermotherapy, imaging, and micro-robotics, followed by an evaluation of current challenges and prospects for future improvement. Through this comprehensive examination and synthesis, the review aims to further reveal the full potential of MSABHs and broaden their applications in the biological domain. Full article

The sealing behavior of fracture-filling minerals in the near-field of the deep geological repository (DGR) is critical for the safe disposal of high-level radioactive waste (HLW). In granite host rocks, natural fractures are often filled with polymineralic assemblages of calcite, quartz, and clay minerals; however, their coupled compaction–pressure solution mechanisms under thermal–hydraulic–mechanical–chemical (THMC) conditions remain poorly understood. In this study, 12 fracture sealing tests were conducted on Beishan granite and its typical fracture fillings at 90 °C and 15 MPa effective stress, using different pore fluids and systematically varying grain size (75–250 μm), mineral proportions, and clay content. The results indicate that stress-assisted dissolution–precipitation of calcite in saturated CaCO₃ solution is a key process contributing to porosity reduction and chemo-mechanical densification of the fracture filling, achieving a compaction strain of 24.6%—substantially higher than those obtained in deionized water (20.6%) and under dry conditions (14.8%). Fine-grained calcite compacts more effectively than its coarse-grained counterpart, reaching a porosity as low as 4.8%; rigid quartz locally redistributes contact stress at quartz–calcite interfaces, promoting preferential deformation or dissolution of adjacent calcite, although increasing quartz abundance reduces the bulk compaction efficiency. A moderate amount of clay minerals (~20 wt%) further reduces porosity to 2.1% through lubrication and micropore filling. The study reveals a multi-stage process transitioning from mechanical compaction to chemo-mechanical sealing, and a synergistic mechanism dominated by calcite compaction–pressure solution, augmented by quartz stress redistribution and clay lubrication. These findings provide direct experimental evidence for the progressive chemo-mechanical densification of mineral-filled granite fractures, and offer quantitative constraints for long-term THMC modeling of fracture sealing behavior in HLW repositories. Full article

Precise and continuous monitoring of thermal effects are critical for ensuring the structural safety of bridges and preventing potential failures. This study presents a methodology integrating unmanned aerial vehicle (UAV)-based thermal measurements with interferometric synthetic aperture radar (InSAR) satellite data to assess and monitor the thermomechanical response of bridges. A three-dimensional (3D) finite element model (FEM) of a prestressed concrete (PC) bridge was developed and validated using in situ displacement measurements. High-resolution, 3D temperature distributions of bridge elements were obtained daily and seasonally using UAV-based infrared thermography (UAV–IRT). Thermal maps were validated with point temperature measurements on the structure. Simultaneously, long-term wide-area deformation trends were investigated using satellite-based InSAR observations. The thermo-mechanical displacement behavior derived from UAV–IRT measurements was compared with historical InSAR-derived seasonal deformation patterns to develop an integrated multi-source structural monitoring framework. The behavior of the bridge in daily and seasonal temperature cycles was simulated and analyzed by integrating UAV–IRT thermal load data into FEM. Maximum stress levels occurring under the most adverse thermal loading conditions and over a one-year period were calculated, taking into account stress limits. The FEM revealed a maximum vertical displacement of 12.3 mm under extreme thermal loading, with tensile stresses in the deck mid-depth exceeding the 3.5 MPa limit, signaling a potential risk for thermally induced cracking. Integration of UAV–IRT thermal observations and historical InSAR deformation measurements revealed vertical temperature gradients of up to 24 °C during summer conditions and indicated that the observed structural response was predominantly governed by thermo-elastic deformation. UAV-satellite methodology offers a rapid, economical, and comprehensive solution for the structural health monitoring of bridges exposed to thermal effects. Full article

Bipolar plates are critical components of proton exchange membrane fuel cells (PEMFCs), strongly influencing thermal management, mechanical stability, and overall system efficiency. In this study, an integrated framework combining multiphysics simulation, artificial intelligence (AI), and data augmentation techniques was developed for PEMFC bipolar plate optimization. A coupled thermal–structural finite element model was established in COMSOL Multiphysics to evaluate temperature distribution, thermal stress, and structural deformation under varying operating conditions. A total of 80 parametric design cases were generated by varying six key parameters: hole radius, plate thickness, heating power, manifold pressure, plate number, and heat transfer coefficient. The dataset was expanded using SMOTE, GAN, and LLM-based augmentation techniques and used to train ANN, LR, RF, XGBoost, and SVR models. Model performance was evaluated using 5-fold cross-validation with MAE, RMSE, and LogCosh metrics. The results showed that ensemble tree-based methods, particularly RF and XGBoost, achieved the highest prediction accuracy and computational efficiency. XGBoost produced the best temperature prediction performance for the SMOTE-based dataset (RMSE = 3.668), while RF achieved the lowest stress prediction error (RMSE = 0.0490). GAN-augmented datasets provided stable and reliable predictions, whereas LLM-generated datasets resulted in higher prediction errors and lower physical consistency. Feature importance analysis revealed that plate thickness dominates displacement prediction (≈0.72 importance), manifold pressure governs stress behavior (≈0.999), and heating power is the primary factor affecting temperature prediction. The proposed AI-assisted surrogate modeling framework enables rapid and accurate thermo-mechanical prediction while significantly reducing computational cost compared to conventional multiphysics simulations. The findings demonstrate that integrating physics-based simulations with data-driven approaches provides an efficient strategy for the optimization of next-generation PEM fuel cell bipolar plates. Full article

Crimped electrical connections must maintain electrical continuity and mechanical load transfer capability under combined environmental and operational stressors throughout their service life. Although the environmental durability of electrical connectors has been extensively studied, previous studies have mainly focused on material, environmental, or electrical effects in isolation, whereas the coupled influence of crimp geometry on electrical–mechanical degradation and contact evolution remains insufficiently understood. In this study, crimp geometry was isolated as the primary independent variable to investigate geometry-driven degradation behavior in crimped connections. Three crimp configurations (Type A, Type B, and Type C) were subjected to temperature cycling (−55 °C to +70 °C), high humidity (90–95% RH), and combined chemical–electrical loading conditions involving representative fluids and short-circuit current. Electrical and mechanical responses were evaluated using relative resistance variation ΔR (%) and tensile strength change ΔT (%), while factorial ANOVA quantified parameter contributions. The results indicate that crimp geometry dominates the response under thermal–humidity exposure, whereas the chemical exposure type becomes the governing factor for electrical degradation under coupled chemical–electrical conditions. SEM analysis reveals that geometry-dependent plastic deformation governs contact continuity and void formation, leading to a transition from continuous conductive networks to fragmented contact structures. These findings are further supported by FEM analyses, which provide qualitative insight into the deformation response as a function of the geometric parameters. This work presents a geometry-based experimental framework for understanding the degradation behavior of crimped bonding structures under dual-exposure test conditions. Full article