Search Results (135)

Prediction accuracy for complex flexible support systems is often limited by insufficiently characterized thermo-mechanical couplings and nonlinearities. To address this, we propose a multilevel hybrid parallel–serial model that integrates the thermo-viscous effects of a Squeeze Film Damper (SFD) via a coupled Reynolds–Walther equation, the structural flexibility of a squirrel-cage support using Finite Element analysis, and the load-dependent stiffness of a four-point contact ball bearing based on Hertzian theory. The resulting state-dependent system is solved using a force-controlled iterative numerical algorithm. For validation, a dedicated bidirectional excitation test rig was constructed to decouple and characterize the support’s dynamics via frequency-domain impedance identification. Experimental results indicate that equivalent damping is temperature-sensitive, decreasing by approximately 50% as the lubricant temperature rises from 30 °C to 100 °C. In contrast, the system exhibits pronounced stiffness hardening under increasing loads. Theoretical analysis attributes this nonlinearity primarily to the bearing’s Hertzian contact mechanics, which accounts for a stiffness increase of nearly 240%. This coupled model offers a distinct advancement over traditional linear approaches, providing a validated framework for the design and vibration control of aero-engine flexible supports. Full article

Symmetry and asymmetry jointly govern the dynamics and surface integrity of thin-wall AA7075 end milling. In this work, a symmetry-aware simulation and experimental framework is developed to connect process parameters with milling forces, dynamic response, surface quality, and through-thickness residual stress. A mechanistic milling-force model is first established for multi-tooth end milling, where the periodically repeated tooth-order excitation provides a nominally symmetric load pattern along the tool path. The predicted forces are then used as input for finite-element modal and harmonic-response analysis of a thin-walled component, revealing how symmetric and anti-symmetric mode shapes interact with the tooth-order excitation to generate locally amplified, asymmetric vibration of the compliant wall. Orthogonal and single-factor milling experiments on AA7075 thin-wall specimens are performed to calibrate and validate the force model, and to quantify the influence of feed per tooth, axial depth of cut, spindle speed, and radial width of cut on deformation, surface roughness, and geometric accuracy. Finally, a thermo-mechanically coupled finite-element model is employed to evaluate the residual-stress field, showing a characteristic pattern in which an initially symmetric thermal–mechanical loading produces depth-wise symmetry breaking between tensile surface layers and compressive subsurface zones. The proposed symmetry-aware framework, which combines milling-force theory, finite-element simulation, and systematic experiments, provides practical guidance for selecting parameter windows that suppress vibration, control residual stress, and improve the machining quality of thin-wall AA7075 components. Full article

Radially bolted cylindrical–cylindrical shell joints are critical load-bearing components in aerospace vehicles. These joints experience complex thermo–mechanical environments during flight, where aerodynamic heating and mechanical loads jointly induce nonlinear deformation and stiffness variation through evolving interfacial contact states. To elucidate these mechanisms, this study develops a sequentially coupled thermo–mechanical finite-element framework to analyze the stiffness evolution of RBCCSJs under transient heating and combined mechanical loads (tension, compression, and bending). The results show that the global stiffness evolves through distinct contact-controlled stages (sticking → microslip → macroslip → mechanical bearing), producing pronounced nonlinear stiffness troughs spanning over two orders of magnitude. Under tension and bending, stiffness peaks during full sticking and decreases with slip, whereas under compression, it recovers earlier due to its end-face-bearing formation. Transient heating introduces two competing effects, thermal-expansion-induced frictional stiffening during short-term heating and temperature-dependent material softening during sustained exposure, leading to a 19.2–34% reduction in stiffness under steady thermal conditions. These findings clarify the dominant role of contact-state evolution and thermo–mechanical coupling in joint behavior and provide a quantitative analytical basis for enhancing the stiffness reliability and design optimization of aerospace bolted assemblies operating in transient thermal environments. Full article

Reliable performance of TRISO (tristructural isotropic) nuclear fuel depends on the interplay between its multilayer architecture and the buffer-layer microstructure, which are difficult to isolate experimentally. We implement a multiscale, multiphysics model in the open-source MOOSE (Multiphysics Object-Oriented Simulation Environment) framework that couples particle-scale thermo-mechanical finite-element analysis with mesoscale phase-field fracture to link microstructure to effective stiffness and strength. The model resolves the combined influence of pore volume fraction, size, and aspect ratio and explicitly separates the effects of reduced load-bearing capacity from stress concentrations in the porous buffer. Simulations reveal substantial hoop stresses across coating layers under nominal thermal conditions due to material property mismatches and temperature gradients. In the buffer, stiffness and strength decrease with porosity; morphology is decisive: as aspect ratio decreases, strength degrades far more rapidly than stiffness, consistent with crack-like pores that amplify local stresses. The framework reproduces logarithmic trends with aspect ratio and explains the higher sensitivity of strength, providing parameters that can inform design and acceptance criteria (e.g., limits on pore elongation and porosity gradients). Implemented within MOOSE, the approach is readily extensible to irradiation-dependent kinetics, interface debonding, and uncertainty-quantified 3D analyses to support risk-informed TRISO fuel development. Full article

This review surveys the recent literature on the fire resistance of reinforced concrete (RC) columns based on a bibliometric analysis of publications to reveal research trends and focus areas. The collected studies are synthesized from the perspectives of materials, structural behaviors, parameter influences, and predictive modeling. From the material aspect, the review summarizes the degradation mechanisms of conventional concrete at elevated temperatures and highlights the improved performance of ultra-high-performance concrete (UHPC) and reactive powder concrete (RPC), where dense microstructures and fiber bridging effectively suppress spalling and help maintain residual capacity. In terms of structural behavior, experimental and numerical studies on RC columns under fire are reviewed to clarify the deformation, failure modes, and effects of axial load ratio, slenderness, cover thickness, reinforcement ratio, boundary restraint, and load eccentricity on fire endurance. Parametric analyses addressing the influence of these factors, as well as the heating–cooling history, on overall stability and post-fire performance is discussed. Recent advances in thermomechanical finite element analysis and the integration of data-driven approaches such as machine learning have been summarized for evaluating and predicting fire performance. Future directions are outlined, emphasizing the need for standardized parameters for fiber-reinforced systems, a combination of multi-scale numerical and machine-learning models, and further exploration of multi-hazard coupling, durability, and digital-twin-based monitoring to support next-generation performance-based fire design. Full article

This study presents an artificial intelligence-based predictive framework as an efficient alternative to conventional analytical procedures for evaluating elastic–plastic thermal stresses in long functionally graded solid cylinders (FGSCs) subjected to uniform internal heat generation. A hybrid artificial neural network-based fuzzy logic (ANNBFL) model is developed to estimate dimensionless thermal load parameters at both the cylinder center and outer surface by learning from validated analytical reference solutions. The material properties, including yield strength, elastic modulus, thermal conductivity, and thermal expansion coefficient, are assumed to vary radially following a parabolic gradation law. Eight influential material parameters are incorporated as input variables to describe the coupled thermo-mechanical behavior of the FGSC. Multiple ANNBFL subnetworks are trained using analytically generated datasets and subsequently integrated into a unified prediction framework, enabling rapid and accurate stress field estimation without repeated analytical calculations. Model performance is systematically assessed by direct comparison with analytical solutions, demonstrating an overall prediction consistency of approximately 98.2%. The results confirm that the proposed ANNBFL approach provides a reliable, computationally efficient surrogate modeling tool for parametric evaluation and optimum material design of functionally graded cylindrical structures under thermal loading. Full article

This paper presents a novel implementation of the Polynomial Point Interpolation Collocation Method (PPCM) for analyzing the coupled electrothermal and thermomechanical behavior of V-shaped microactuators. Within the PPCM framework, the governing equations for heat transfer and structural mechanics are discretized over the computational domain. The resulting discrete electrothermal system is solved in a fully coupled manner via an incremental load method to determine the temperature field. Subsequently, the displacement field is computed by solving the discrete mechanical equation, which incorporates terms from the natural boundary conditions. The MQ radial basis function behaves well in convergence when its parameters p_a and p_q are 1 and 1.8. Under a 6 V voltage, the difference between the PPCM and FEM temperature values is less than 1 °C. Meanwhile, the discrepancy between the PPCM and experimental temperature values is approximately 20 °C, corresponding to an approximate error of 10%. Furthermore, the displacement error between the PPCM and FEM is as low as approximately 2 μm under an applied voltage of 12 V. These results validate the PPCM for predicting the driving characteristics of V-shaped microactuators. Full article

This study employs molecular dynamics simulations to investigate the frictional behavior of fullerene nano-additives on Fe-C alloy surfaces under varying loads and temperatures, focusing on boundary lubrication conditions. The results show that the x-direction friction force exhibits minimal sensitivity to normal pressure due to the high rigidity of fullerene molecules, which limits variations in real contact area and atomic interactions. In contrast, temperature has a significant effect: as it rises, enhanced atomic vibrations and thermal activation lower energy barriers for sliding. The coefficient of friction (COF) consistently decreases with both increasing load and temperature, driven by the mechanism of thermally activated motion. Although partial rotational motion from sliding to rolling friction was not explicitly observed in the simulations, the study remains within the sliding-dominated regime, highlighting the importance of temperature over load in controlling friction. A linear relationship between $\ln COF$ and $1/k_{B}T$ yields an average activation energy of ~0.03 eV, supporting a thermally activated friction mechanism. By introducing a composite parameter that combines load and temperature effects, the study provides a predictive framework for modeling friction behavior under thermo-mechanical coupling. These findings enhance the understanding of the friction-reducing capabilities of fullerene additives and offer a foundation for designing advanced nano-lubricants in boundary lubrication systems. Full article

Aluminum alloys require improved surface performance to satisfy the demands of today’s aerospace, automotive, marine, and structural applications. This paper compares three key surface hardening methods: diffusion-assisted microalloying, thermomechanical deformation-based treatments, and composite/hybrid reinforcing procedures. Diffusion-assisted Zn/Mg enrichment allows for localized precipitation hardening but is limited by the native Al₂O₃ barrier, slow solute mobility, alloy-dependent solubility, and shallow hardened depths. In contrast, thermomechanical techniques such as shot peening, surface mechanical attrition treatment (SMAT), and laser shock peening produce ultrafine/nanocrystalline layers, high dislocation densities, and deep compressive residual stresses, allowing for predictable increases in hardness, fatigue resistance, and corrosion performance. Composite and hybrid reinforcement systems, such as SiC, B₄C, graphene, and graphite-based aluminum matrix composites (AMCs), use load transfer, Orowan looping, interfacial strengthening, and solid lubrication effects to enhance wear resistance and through-thickness strengthening. Comparative evaluations show that, while diffusion-assisted procedures are still labor-intensive and solute-sensitive, thermomechanical treatments are more industrially established and scalable. Composite and hybrid systems provide the best tribological and load-bearing performance but necessitate more sophisticated processing approaches. Recent corrosion studies show that interfacial chemistry, precipitate distribution, and galvanic coupling all have a significant impact on pitting and stress corrosion cracking (SCC). These findings highlight the importance of treating corrosion as a fundamental design variable in all surface hardening techniques. This work uses unified tables and drawings to provide a thorough examination of strengthening mechanisms, corrosion and fatigue behavior, hardening depth, alloy suitability, and industrial feasibility. Future research focuses on overcoming diffusion barriers, establishing next-generation gradient topologies and hybrid processing approaches, improving strength ductility corrosion trade-offs, and utilizing machine-learning-guided alloy design. This research presents the first comprehensive framework for selecting multifunctional aluminum surfaces in demanding aerospace, automotive, and marine applications by seeing composite reinforcements as supplements rather than strict alternatives to diffusion-assisted and thermomechanical approaches. Full article

Orthotropic steel decks (OSDs) serve as critical load-bearing components in long-span steel bridges, but high-amplitude welding residual stresses (WRSs) generated during the welding process pose significant threats to structural integrity. To mitigate these stresses, post-weld heat treatment (PWHT) has emerged as a promising technique. This investigation first establishes a semi-structural thermo-elasto-plastic finite element model of the Deck-U-rib-Diaphragm system with a six-pass welding sequence. The temperature field is modeled via a double-ellipsoidal heat source and birth–death element approach. Subsequently, thermo-mechanical coupling analysis is conducted to investigate the distribution characteristics of Von Mises residual stresses. The stress relief effect of PWHT is then explored by comparing different holding temperatures (T) and holding times (t), achieving a balance between stress reduction effectiveness and economic efficiency, when T = 550 °C and t = 40 min. Finally, full-scale experimental tests are designed, and the hole-drilling method is utilized to validate the numerical simulation results. This research provides valuable insights for the design of PWHT processes for OSDs. Full article

Ruggedized computers are the core of modern communication, guidance, control, and data-processing systems, and typically operate under extreme environmental conditions. However, under extreme service conditions such as temperature cycling, vibration, and mechanical shock, thermo–electro–mechanical (TME) multi-physics coupling in ball grid array (BGA) solder joints is particularly significant, severely affecting system reliability and signal integrity. To comprehensively elucidate the effects of thermal, electrical, and mechanical fields on solder joints and signal transmission, this study proposes a multiscale multi-physics modeling and analysis framework for BGA solder joints in microelectronic systems of ruggedized computers, covering the computer system level, motherboard level, solder joint level, and solder interconnect level. A model correlation study under ten thermal cycling conditions demonstrated an accuracy of 88.89%, confirming the validity and applicability of the proposed model. Based on this validated framework and model, the temperature distribution, stress–strain response, and signal integrity characteristics were further analyzed under combined conditions of thermal cycling, random vibration, and mechanical shock. The results indicate that a rise in temperature in solder joints induces thermal stresses and deformations, while variations in electrical conductivity under thermal loading trigger electromigration and concentration evolution, which further couple with stress gradients to form TME multi-physics interactions. Under such coupling, critical solder balls exhibit stress concentration at the metallurgical interfaces, with a maximum von Mises stress of 191.51 MPa accompanied by plastic strain accumulation. In addition, the PCIe high-speed interconnect experienced a maximum deformation of 16.104 μm and a voltage amplitude reduction of approximately 18.51% after 928 thermal cycles, exceeding the normal operating range. This research provides a theoretical basis and engineering reference for reliability assessment and optimization design of microelectronic systems in ruggedized computers in complex service environments. Full article

Wet milling of aluminum alloys involves complex interactions among thermal, fluid, and mechanical fields that strongly affect cutting temperature, stress distribution, and surface integrity. To achieve reproducible and physics-based predictions of these coupled phenomena, this study develops a three-dimensional thermo–fluid–solid-coupled Eulerian–Lagrangian (CEL) framework for the wet milling of Al6061. The model system in this study evaluated the effects of milling cutter feed rate and spindle speed, feed per tooth of the milling cutter, axial cutting depth, and coolant flow rate on equivalent stress and peak milling temperature., as well as their correlation with surface roughness metrics (Ra, Sa). Simulation results reveal that higher feed rates significantly raise T_peak (+12.9%) while reducing σ_eq (−22.7%) and deteriorating surface quality (Ra +104.2%, Sa +29.9%). Increasing spindle speed lowers both T_peak (−2.2%) and σ_eq (−8.5%) and improves surface finish (Ra −39.3%, Sa −16.6%). A greater depth of cut amplifies mechanical and thermal loads, increasing T_peak (+10.3%) and σ_eq (+17%). Enhanced coolant flow reduces T_peak (−23.5%) and σ_eq (−6.1%) and markedly improves surface quality (Ra −88.8%, Sa −51.3%). Research findings indicate that coolant coverage is the dominant factor determining surface integrity. Although experimental data for T_peak and σeq were not directly validated, this framework clearly articulates modeling assumptions, quantifies parameter sensitivities, and provides a reproducible methodology for future experimental-numerical verification. Full article

This study presents an analytical investigation of the thermomechanical stability of hyperbolic doubly curved shells reinforced with graphene origami auxetic metamaterials (GOAMs) and resting on a Pasternak elastic foundation. The proposed model integrates shell geometry, thermal–mechanical loading, and architected auxetic reinforcement to capture their coupled influence on buckling behavior. Stability equations are derived using the First-Order Shear Deformation Theory (FSDT) and the principle of virtual work, while the effective thermoelastic properties of the GOAM phase are obtained through micromechanical homogenization as functions of folding angle, mass fraction, and spatial distribution. Closed-form eigenvalue solutions are achieved with Navier’s method for simply supported boundaries. The results reveal that GOAM reinforcement enhances the critical buckling load at low folding angles, whereas higher folding induces compliance that diminishes stability. The Pasternak shear layer significantly improves buckling resistance up to about 46% with pronounced effects in asymmetrically graded configurations. Compared with conventional composite shells, the proposed GOAM-reinforced shells exhibit tunable, folding-dependent stability responses. These findings highlight the potential of origami-inspired graphene metamaterials for designing lightweight, thermally stable thin-walled structures in aerospace morphing skins and multifunctional mechanical systems. Full article

In this study, the thermal and structural behavior of battery module components produced from polymer-based composites was systematically evaluated using coupled Moldflow 2016 and ANSYS Fluent 2024 simulations. Three thermoplastics—metal-flake-reinforced PC+ABS (Polycarbonate/Acrylonitrile Butadiene Styrene), carbon-fiber-reinforced PEEK (Polyether Ether Ketone), and hybrid mineral-filled PP (Polypropylene)—were investigated as alternatives to conventional aluminum components. Moldflow simulations enabled the assessment of injection molding performance by determining injection pressure, volumetric shrinkage, warpage, residual stress, flow front temperature, and part weight. PEEK exhibited the best dimensional stability, with minimal warpage and shrinkage, while PP showed significant thermomechanical distortion, indicating poor resistance to thermally induced deformation. For thermal management, steady-state simulations were performed on a 1P3S pouch cell battery configuration using the NTGK/DCIR model under a constant heat load of 190 W. Material properties, including temperature-dependent thermal conductivity, density, and specific heat capacity, were defined based on validated databases. The results revealed that temperature distribution and Joule heat generation were strongly influenced by thermal conductivity. While aluminum exhibited the most favorable thermal dissipation, PC+ABS closely matched its electrical performance, with only a 1.3% lower average current magnitude. In contrast, PEEK and PP generated higher cell core temperatures (up to 20 K) due to limited heat conduction, although they had comparable current magnitudes imposed by the energy-conserving model. Overall, the findings indicate that reinforced thermoplastics, particularly PC+ABS, can serve as lightweight and cost-effective alternatives to aluminum in mid-range battery modules, providing similar electrical performance and thermal losses within acceptable limits. Full article

The line contact behavior of multiscale meshing interfaces necessitates synergistic investigation spanning nano-to centimeter-scale ranges. When nominally smooth gear teeth surfaces come into contact, the mechanical–thermal coupling effect at the meshing interface actually occurs over a collection of microscale asperities (roughness peaks) exhibiting hierarchical distribution characteristics. The emergent deformation phenomena across multiple asperity scales govern the self-organized evolution of interface conformity, thereby regulating both the load transfer efficiency and thermal transport properties within the contact zone. The fractal nature of the roughness topography on actual meshing interfaces calls for the development of a cross-scale theoretical framework that integrates micro-texture optimization with multi-physics coupling contact behavior. Conventional roughness characterization methods based on statistical parameters suffer from inherent limitations: their parameter values are highly dependent on measurement scale, lacking uniqueness under varying sampling intervals and instrument resolutions, and failing to capture the scale-invariant nature of meshing interface topography. A scale-independent parameter system grounded in fractal geometry theory enables essential feature extraction and quantitative characterization of three-dimensional interface morphology. This study establishes a progressive deformation theory for gear line contact interfaces with fractal geometric characteristics, encompassing elastic, elastoplastic transition, and perfectly plastic stages. By systematically investigating the force–thermal coupling mechanisms in textured meshing interfaces under multiscale conditions, the research provides a theoretical foundation and numerical implementation pathways for high-precision multiscale thermo-mechanical analysis of meshing interfaces. Full article