力学, 本领域期刊类期刊, -365足球

this paper presents a macroscopic theory, alongside its numerical implementation, aimed at describing, explaining, and predicting the nucleation and propagation of fracture in viscoelastic materials subjected to quasistatic loading conditions. the focus is on polymers, in particular, on elastomers. to this end, the starting point of this work is devoted to summarizing the large body of experimental

a numerical green’s function-based approach is developed for attenuation characterization in two-phase matrix-inclusion microstructures. this approach avoids the critical boundary enforcement in plane wave modeling and is extensively tested and compared to current analytical methodologies based on the first-order smoothing approximation (fosa). assuming each phase is isotropic with constant density

in this paper, we study the nitsche’s extended serendipity virtual element method for the eigenvalue problem in two and three dimensions. we start from the introduction of two- and three-dimensional serendipity virtual element spaces, in which the serendipity technique helps us drop all internal-to-face and internal-to-element degrees of freedom with the suitable projection operators fitting into virtual

the proper orthogonal decomposition (pod) enables effective reduced-order modeling of geometrically nonlinear structures through low-dimensional subspace projection. the conventional pod-based methods construct the reduced-order model solely from the reduced-order bases of global displacement field, leading to the high-order internal force vector and stiffness tensor of reduced coordinates. in this

a new contact enrichment technique is proposed to improve accuracy and efficiency in contact simulations. while traditional finite element analysis (fea) is commonly used, it can lead to geometric approximation errors and become computationally expensive when high accuracy is required, especially in contact problems. isogeometric analysis (iga) addresses these issues by providing exact geometric representation

the fatigue crack propagation (fcp) resistance anisotropy of al-li alloy cold-rolled (cr) sheets and hot-rolled (hr) plates was systematically investigated through the integrated microstructural and crystallographic analysis. by employing the equivalent slip system number (essn) as a novel metric to quantify crack path tortuosity and slip activity. it was revealed that the t8-aged cr and hr samples

this paper proposes a full-scale isogeometric topology optimization (ito) method based on bézier extraction for design of freeform fiber-reinforced composite (frc) shells. in this method, freeform shells are modeling by multiple nurbs patches, where a penalty method is introduced to enhance displacement and rotation continuity at the coupling interfaces between multiple nurbs patches. a multi-patch

axial low cycle fatigue tests were performed on the thermal aged low alloy steels (lass). the fatigue life declined after thermal aging for 20000 h, characterized by diminished plastic strain amplitude, enhanced cyclic hardening, and reduced ductility. post-fatigue fractography of the material after thermal aging revealed elevated dislocation density, dense dislocation pile-ups and tangles, which compromised

quasicrystals (qcs) are a class of aperiodic ordered structures that emerge in various systems, from metallic alloys to soft matter and driven non-equilibrium systems. within a mesoscale theory based on slowly-varying complex amplitudes for qcs, we track dislocations as topological defects harbored by the amplitudes and characterize their burgers vectors and induced deformations. we study the formation

only single-fidelity information is considered in existing studies when conducting reliability analysis for small failure probabilities, making it difficult to further improve computational accuracy and efficiency for estimating structural failure where highly nonlinear limit state functions and time-consuming high-fidelity (hf) finite element simulation exist at the same time. to address this challenge

particle swarm optimization (pso) is one of the most classical meta-heuristic algorithms (mas), and the algorithm is extensively used in solving practical engineering application problems. to address the challenges of particle swarm optimization in high-dimensional complex engineering problems, including accuracy, stability, and resource utilization, we propose a pso variant called pdpso, which incorporates

this study develops a numerical framework for thermo-poroelastic fracture analysis using the scaled boundary finite element method (sbfem) and adaptive phase-field modelling. the framework integrates the equilibrium, mass balance, and heat transfer equations, solving them as a coupled system, while fracture evolution is handled using a phase-field approach in a staggered manner. by formulating the

we present an efficient and robust numerical algorithm for solving two-dimensional linear elasticity problems that combines the quantized tensor train format and a domain partitioning strategy. this method substantially decreases memory usage and achieves a notable rank reduction compared to established finite element implementations like the fenics platform. this performance gain, however, requires

a thermodynamically consistent finite deformation macroscale damage model for the nucleation and growth of voids under dynamic loading conditions is presented. voids are modelled as thick-walled spheres within a representative volume element (rve). thick-walled spheres are distributed according to a physically informed probability distribution function which serves as integration weight for formation

this study extends the deep material network (dmn), a physics-informed machine learning framework, to predict the homogenized mechanical response of composite materials with micropolar (cosserat-type) constitutive behavior. this extension incorporates microstructure-dependent size effects, enabling accurate, efficient, and size-aware predictions for composites with complex internal architectures. while

accurate finite element analysis of refined shell theories is crucial but often hindered by membrane and shear locking effects. while various element-based locking-free techniques exist, this work addresses the problem at the theoretical level by utilizing results from asymptotic analysis. a formulation of a 2d refined shell theory incorporating transverse shear is developed using rescaled coordinates

to further enhance the prediction performance of multiaxial fatigue life based on physics informed neural network (pinn), domain knowledge guided symbolic regression-neural network (dksr-nn) framework is proposed. at first, domain knowledge is employed to guide symbolic regression in generating expressions that possess both physical interpretability and high predictive accuracy. these expressions are

natural materials commonly exhibit cellular architectures that demonstrate remarkable toughness, even when made of intrinsically brittle constituents. understanding this unique behavior requires investigating the origins of toughness across the length scales that cellular solids occupy. in this work, we produce microcellular and nanocellular polyetherimide (pei) foams via a solid-state foaming process

structures in extreme thermal environments are susceptible to thermo-mechanical fatigue damage under cyclic thermal and mechanical loading. to effectively address this issue via structural optimization design, this study proposes a thermo-mechanical fatigue damage-constrained topology optimization (tmfdcto) method, aiming to achieve lightweight designs while rigorously accounting for fatigue damage

high-order methods have recently been shown to be an effective tool for high-fidelity flow computations like direct numerical simulations and large-eddy simulations because of their strong balance between accuracy and computational cost. in this work, a high-order discontinuous galerkin spectral element method (dgsem) is developed to solve the chemically reacting navier-stokes equations. to handle

stainless-clad bimetallic steel has attracted increasing attention in structural applications due to its superior corrosion resistance and cost-effectiveness. however, its post-fire low-cycle fatigue behavior remains largely unexplored. this paper presents an experimental investigation into the post-fire low-cycle fatigue behavior of 316l   q355 stainless-clad bimetallic steel, considered three key

the high cycle fatigue behavior of a non-oriented electrical steel (noes) and a grain-oriented electrical steel (goes) was investigated under two loading conditions with respect to the rolling direction and the transverse direction. the deformation behavior under non-symmetric cyclic loading, i.e. rσ = 0.1 is characterized by strongly pronounced ratcheting. while ratcheting starts within the first

accurate life prediction for high-temperature components subjected to fatigue, creep, and their interactions presents considerable complexity, driven not only by coupled degradation mechanisms but also by the inherent intricacy of high-precision models requiring rigorous parameter fitting. in practice, model selection is often guided by application-specific requirements through resource-intensive trial-and-error

the therapeutic efficacy employing mechanical effect of focused ultrasound (fus) largely depends on precise control of the key features of acoustic radiation force (arf) including spatial localization, magnitude distribution, and force field geometry. however, the heterogeneous nature of biological tissues poses persistent challenges in quantitative arf characterization. here, we report a novel methodology

with the development of aviation technology, the optimal design of composite structures for aircraft has gradually become a key issue in the field of structural optimization research. however, in the actual engineering situation, it is also necessary to consider the coupling of disciplines brought by the complex environment as well as the uncertainty factors, so there is an urgent need for an efficient

crack detection is critical for ensuring structural integrity; however, existing methods often suffer from limited applicability and inefficient convergence. this study introduces a topology optimization framework for efficient detection of internal cracks in structures through structural surface deformation in the context of peridynamics (pd). from the perspective of topology optimization, the proposed

anisotropic microstructures and defect distributions impart a strong build-orientation dependence to the cyclic deformation behaviour of additively manufactured metallic materials. accurately capturing this anisotropy through tailored cyclic elasto-plastic constitutive models is critical for ensuring structural integrity. this study investigates the high-temperature anisotropic cyclic plasticity of

in this paper, we investigate the nonlinear behaviour of ribbons subjected to coaxial compression and twisting through theoretical, numerical, and experimental approaches. using anisotropic kirchhoff rod theory and continuation techniques, we construct global bifurcation diagrams and identify stability transition points via the conjugate-point test. here, we show that the twist induces supercritical

numerical solvers for partial differential equations (pdes) often struggle to balance computational efficiency with accuracy, especially in multiscale and time-dependent systems. neural operators offer a promising avenue to accelerate simulations, but their practical deployment is hindered by several challenges: they typically require large volumes of training data generated from high-fidelity solvers

classical plasticity models typically rely on equations to express constitutive behaviors such as yield surfaces and elastic energy. however, deducing these equation-based models requires extensive trial-and-error and strong intuitions. while neural networks may enable the parameterization of material models, they require additional costs for supervised learning and may lead to slower inference. in

physics-informed neural networks (pinns) have revolutionized the computation of pde solutions by integrating partial differential equations (pdes) into the neural network’s training process as soft constraints, becoming an important component of the scientific machine learning (sciml) ecosystem. more recently, physics-informed kolmogorv-arnold networks (pikans) have also shown to be effective and comparable

grey cast iron (gci) water pipes often develop localised corrosion pits that act as notches and can also experience biaxial fatigue stresses, resulting in a multiaxial notch fatigue problem. this paper experimentally investigates for the first time, the high-cycle fatigue sensitivity of gci to localised notches, under bending and biaxal loading, and validates a multiaxial notch fatigue model for gci

this study investigates the microstructure, tensile, and fatigue behavior of post-aged powder bed fused-laser beam (pbf-lb) al2139zrti alloy, developed by eos north america. the microstructure exhibits an equiaxed grain structure with an average grain size of approximately 1.5 µm and lacks any strong crystallographic texture. it also contains a dense dispersion of fine, uniformly distributed precipitates

in this work, multiaxial experiments on a structural adhesive with varying levels of non-proportionality are analyzed with a focus on the stiffness degradation process. a load level-dependent stiffness degradation model is employed that captures both, young’s and shear modulus degradation. it was found that a multiaxial stiffness degradation can be modeled with good approximation as a superposition

in multi-component vibrating systems, some components can be inherently complex or expensive to model using first principles of physics. this creates a serious bottleneck in the dynamic analysis of the built-up system. in more complicated scenarios, even a baseline mechanistic model may not be available to update these sub-components. practical examples of such systems include dampers, bridge supports

once sulfate ions enter a concrete structure, they can react with multiple aluminate phases within the concrete to form ettringite, which eventually leads to swelling and cracking of the structure. to reveal the mechanism of external sulfate attack (esa), a fully coupled nonlinear constitutive model is developed for transient diffusion-reaction-deformation response of concrete exposed to sulfate environment

the inverse design of metamaterial architectures presents a significant challenge, particularly for nonlinear mechanical properties involving large deformations, buckling, contact, and plasticity. traditional methods, such as gradient-based optimization, and recent generative deep-learning approaches often rely on binary pixel-based representations, which introduce jagged edges that hinder finite element

this work presents a revised formulation that combines the uniform strain method (usm) and the scaled boundary finite element method (sbfem) for static and dynamic elastoplastic analysis in two dimensions. this revised formulation introduces the average strain and splits the strain field of an arbitrarily shaped polygon element into an average and a stabilization part, which are energetically orthogonal

we revisit finite element discretizations of the reissner-mindlin plate in the case of non-simply connected (holey) domains with mixed boundary conditions. guided by the de rham complex, we develop conditions under which schemes deliver locking-free, optimal rates of convergence. we naturally recover the typical assumptions arising for clamped, simply supported plates. more importantly, we also see

concrete cone (or breakout) failure mode is the dominant failure for cast-in headed anchors under tension in mature brittle concrete, however, other failure modes such as plug failure has been found experimentally to dominate in early age concrete. design codes generally assume concrete cone failure and do not cover plug failure. a new model for concrete at early ages is proposed based on continuum

as hot-end components in aero-engines, tial alloys are expected to experience cyclic creep in service. in this work, hybrid-reinforced tial alloys with superior creep resistance were developed through synergistic micro-alloying of c and y2o3 combined with long-term annealing. monotonic and cyclic creep tests under various loading conditions were conducted to specifically investigate the cyclic creep

this study conducted a series of ultra-low cyclic fatigue (ulcf) tests and investigated the cyclic responses of structural steel q345 under various cyclic loading cases at a relatively large inelastic strain range whose maximum amplitude reached ±10 %. test results reveal that q345 steel exhibits pronounced strain memory effects (sme), transient bauschinger effect (tbe), and loading history dependence

multi-material structures are widely used in aerospace, energy, automotive and other industrial fields due to their excellent performance and design flexibility. however, existing multi-material topology optimization methods (mmto) rarely accounts the interface strength due to the tightly coupled thermal and dynamic loads, causing insufficient structural robustness. therefore, this paper proposes a

this paper introduces a peridynamic (pd) model for simulating the advection-reaction-diffusion (ard) processes in a non-uniform flow. the ard phenomena are influenced by the flow, and the flow is modified by phase-changes (driven by interface reactions) that transform the boundaries of solids in the flow, for example. by coupling the pd governing equations for viscous flow with the pd equations for

the accuracy of coarse-grained continuum models of dense granular flows is limited by the lack of high-fidelity closure models for granular rheology. one approach to addressing this issue, referred to as the hierarchical multiscale method, is to use a high-fidelity fine-grained model to compute the closure terms needed by the coarse-grained model. the difficulty with this approach is that the overall

this paper proposes a novel consistent δ - updated lagrangian particle hydrodynamics (ulph) model. although the smoothed particle hydrodynamics (sph) model has gained recognized achievements, it is afflicted by excessive numerical dissipation when the neighboring particles are insufficient. the present proposed consistent δ -ulph model has advantages in overcoming this problem. to improve the accuracy

the application of artificial intelligence to partial differential equations has gained significant attention, especially with the rise of physics-informed neural networks (pinns). recent advancements in graph-based data further highlight the potential of combining graph neural networks with pinns, offering a promising approach to solve differential equations by leveraging the strengths of both techniques

as intermetallic alloy with complex three-phase microstructure, tnm-tial alloy offers significant advantages for replacing superalloys in the fabrication of aero-engine turbine blades. however, a deep understanding of the damage evolution behavior under high cycle fatigue (hcf) at high service temperatures is still lacking. therefore, we propose an idea whether we can systematically clarify the deformation

the present experimental work revealed that under fully reversed creep–fatigue loading conditions (r=−1), the material exhibits a recurring cyclic transient creep phase, never entering the steady-state creep regime. the cyclic creep process is dominated by primary creep, with the creep rate during the transient phase being 1–2 orders of magnitude higher than that of steady-state creep. as the loading

this work addresses a challenging problem in the high-performance design for additive manufacturing (am): improving the structural performance (stiffness and strength) by comprehensively utilizing the material intrinsic anisotropy (local) and process-induced anisotropy (global). a novel am-oriented structural topology optimization considering multi-source anisotropic failure strength from printing

hydrogels are soft, stimuli-responsive materials with attractive applications from soft robotics to biomedical engineering. their multiphysics nature combined with their ability to undergo large deformation and mechanical instability makes their computational modeling challenging. as a potential remedy, we here introduce a meshless multiphysics framework based on enhanced local maximum-entropy (max-ent)

fully coupled cardiac electromechanics simulations have in the last few years become feasible on a tissue and organ scale. however, free and open-source tools for running these simulations are still limited. furthermore, due to the high computational expense of coupling electrophysiology (ep) and mechanics, investigations into choice of coupling scheme is warranted. in this study, we investigate the

the low cycle fatigue (lcf) behavior of twinning induced plasticity (twip1000) steels was analyzed in its as-received (ar: 0 % pre-strained) and pre-strained conditions of 30 % and 60 %. the microstructural evolution during pre-straining and cyclic loading was characterized by x-ray diffraction, scanning electron microscopy, and transmission electron microscopy. results indicated that pre-straining