Acta Mechanica Sinica最新文献

In this paper, a probabilistic crystal plasticity modelling framework is proposed to consider the influence of material variability (including material properties and microstructure) on the fatigue life of notched components. First, a dual-scale crystal plasticity finite element (CPFE) model is incorporated to predict the cyclic plasticity and fatigue damage of notched components. Specifically, new fatigue indicator parameters considering the mean stress effect are developed for fatigue life prediction under different stress ratios. Subsequently, by quantifying the material variability based on the CPFE method, a framework for probabilistic fatigue life prediction is then established. The simulation results based on the V-notched specimen of Ni-based superalloy GH4169 can well describe the scatter of experimental fatigue life, which confirms the feasibility of the proposed method.

The cavity expansion model (CEM) holds significant engineering value for high-speed impact and blast analysis, yet its theoretical development suffers from three critical limitations: failure to quantify the influence of elastic strain accumulation on initial cavity size, solution discontinuity caused by conceptual confusion between elastic/plastic compressibility, and inadequate applicability of traditional solutions to non-zero initial cavity conditions. This study establishes a unified theoretical framework within the Eulerian framework based on the quasi-static spherical CEM, simultaneously considering both compressibility and incompressibility during the plastic phase. By introducing initial cavity size and elastic pre-strain, we derived a general analytical solution enabling continuous elastic-plastic transition, supported by numerical validation. The results demonstrate that incorporating both elastic compressibility and initial cavity size under plastic incompressibility assumptions yields continuous analytical solutions. For cavity wall pressure evolution, the improved theory shows closer alignment with numerical solutions in pre-critical pressure regimes, accurately captures momentum conservation characteristics under high-pressure conditions, and resolves longstanding ambiguities in volumetric compressibility concepts.

The unique shock pattern evolution and its corresponding thrust variation of a recently proposed rocket permeable nozzle during an ascent-descent operation are investigated using numerical methods. In the present permeable nozzle flow, the flow pattern and shock system evolution are discussed to demonstrate the flow and hysteresis phenomenon. The formation mechanisms of two featured shocks, permeable shock (PS) and detached shock (DS) are interpreted in two typical scenarios. Accordingly, the interconnection between the nozzle thrust coefficient variation and the shock evolution is clarified. New flow characteristics emerge because of the nozzle permeable section. First, the hysteresis phenomenon manifests through the existence-absence of both the Mach disk and PS/DS. Second, the formation mechanisms of PS and DS differ in low nozzle pressure ratio (NPR, 38.49–134.19) and high NPR (134.19–322.00) scenarios. In the low NPR scenario, PS is formed by the core flow deflection due to ambient air inflow, and the DS detachment is formed by a mild pressure gradient between inflow and backflow. In the high NPR scenario, the PS is formed by the boundary layer re-development after the outflow-induced expansion wave, and the DS detachment is formed by the outflow-induced pressure gradient reduction. Third, the hysteresis of thrust coefficient variation is essentially manifested in a low NPR range. Notably, the hysteresis of PS/DS existence resides well in that of the thrust coefficient, suggesting that their existence plays a vital role in varying the nozzle thrust coefficient.

Owing to the dispersion and multi-mode characteristics, guided wave non-destructive technology is promising for characterizing the interface state of incompressible viscoelastic multilayered soft plates. To effectively apply the guided waves in structural health monitoring, it is essential to attain a comprehensive understanding of dispersion and attenuation properties for Lamb waves in these plates, particularly those with weak interfaces. To achieve this, a hyper-viscoelastic fractional order model is employed to investigate Lamb waves in multilayered soft plates with weak interfaces. The analysis encompasses weak connections in both shear and vertical directions. An improved Legendre polynomial method with analytical integration expressions is employed to solve dynamic equations. The influence of weak interfaces, fractional order, and pre-deformation on wave characteristics is studied. Interestingly, results reveal the appearance of the transverse quasi-resonance for the S0 mode when pre-compression deformations reach sufficiently large magnitudes. Furthermore, phase velocity and attenuation variations are nonlinear as the weak interface coefficients increase. As these coefficients become adequately large, the variations diminish progressively, ultimately approaching a saturation point.

This paper presents a theoretical model designed to predict the elastic response of simply supported cylindrical shells under internal explosion loads at arbitrary positions along the central axis. The model accounts for the propagation and attenuation effects of explosion waves over time and space. To accurately capture the varying impact area of the blast on the shell wall, the explosion wave function is divided into three distinct stages. By integrating classical shell theory and applying the Laplace transform solution method, the model provides an effective means of calculating the dynamic displacement response. The accuracy of the theoretical model is validated through finite element simulations across various cylinder radii. The strong agreement between theoretical and numerical results demonstrates the robustness of the model across a wide range of applications. This work provides a fundamental understanding of the dynamic behavior of cylindrical shells under internal blast loading, essential for enhancing safety and reliability in engineering applications.

In order to reconstruct the evolution process and characterize the fragments’ motion of the debris cloud, the space and velocity field models of debris cloud generated by a hypervelocity disk projectile impacting a thin plate are developed by using the shock wave theory in this study. To obtain the characteristic velocity of the debris cloud accurately, shock wave loading and isentropic unloading are considered. In particular, the effect of the isentropic unloading of rarefaction wave on particle velocity is considered based on the Bless model. The difference in particle velocity between shock wave loading and rarefaction wave isentropic unloading is calculated for oxygen-free high-conductivity copper (used as projectile material) and Al 6061-T6 (used as bumper material) considering different shock pressure values. To solve the characteristic velocity of the debris cloud, a modified isentropic unloading model is developed. Then, based on the self-similarity assumption and modified isentropic unloading model, the structural contour function of the debris cloud at a stable expansion stage is introduced to establish the space and velocity field models. Furthermore, numerical simulation using smooth particle hydrodynamics is conducted to verify and analyze the model results. The spray angle of the debris cloud and contour map of the velocity of particles in the cloud are obtained. Finally, the evolution process of the debris cloud is reconstructed, and the motion characteristics of the fragments in the cloud are quantitatively described.

Simulation models are increasingly being built to predict and analyze nonlinear dynamic system behavior as a cheaper alternative to expensive physical testing. However, the simulation models may not perfectly represent the complicated physics due to the flawed understanding of the system, numerical approximations, and/or missing physical insight. The objective of this paper is to provide a better understanding of two nonlinear dynamic model bias correction strategies, namely δ learning (missing physics) and δ learning (machine learning (ML) prediction), which are two out of the six commonly used hybrid modeling strategies (also called physics-informed/enhanced machine learning methods). While these two δ learning strategies for model bias correction have been widely used in correcting static computational simulation models, their application to nonlinear dynamic simulation models is scarce. Even though there are a few applications of these two strategies to autonomous vehicle systems, battery state estimation, and river discharge prediction (for example), there are insufficient details provided about the theories and implementation details, which makes it difficult for practitioners to adopt these methods in practical applications. In this paper, we provide insights into the theories behind these two methods, explaining why they work, as well as details about the implementation procedures to facilitate the wide adoption. In addition, two examples, including a single-degree-of-freedom nonlinear oscillator and a six-story nonlinear shear-building model, are used to (1) demonstrate the effectiveness of these two hybrid modeling methods, and (2) comprehensively analyze the advantages and disadvantages of these two methods. Results show that both strategies can effectively correct a nonlinear dynamic simulation using a limited number of experiments. The δ learning (missing physics) method appears to be more accurate than the δ learning (ML prediction) method.

The ductile fracture behavior of metals is profoundly influenced by the stress state, often determined by stress triaxiality and the Lode angle, as well as the strain rate. This study delves into the ductile fracture mechanisms of 2024-T4 aluminum alloy under multiple stress states, including pure tensile, pure torsion, and a combined tensile-torsion scenario. We employ a state-of-the-art electromagnetic tensile-torsion split Hopkinson bar for dynamic testing and a servo-hydraulic testing machine for quasi-static testing. By utilizing two high-speed cameras and three-dimensional digital image correlation techniques, the fracture properties and strain distribution of the specimens were accurately captured. The test results demonstrated that the fracture properties of specimens are significantly influenced by the stress state, while they are not sensitive to the strain rate within the tested range. In light of the experimental data, the Johnson-Cook (J-C) model and the ASCE-modified J-C model are calibrated and compared. The ASCE-modified J-C model shows improved accuracy with the introduction of the Lode angle parameter. Furthermore, the micro-fracture mechanisms under different loading conditions that occur in the evaluated specimens are studied.

Force is the sculptor of life. Plant growth is driven by mechanical processes operating across multiple scales, from the cellular to the organ level. This review explores these processes from a multi-scale perspective. It begins with the historical development of mechanics models for plant cell growth, with a particular focus on the classical Lockhart equation. The structure and properties of the cell wall are then scrutinized, emphasizing its regulatory role in cell growth and how its viscosity, elasticity, and plasticity influence cell expansion and morphogenesis. Next, this review investigates mechanical interactions at the cell-tissue interface, focusing on how cellular stress and tissue structural characteristics influence plant growth through cross-scale mechanisms. At the macroscopic scale the mechanical principles governing tissue growth and morphology are analyzed, illustrating how mechanical forces and differential growth shape organ development. Additionally, the recently developed biomechanical morphogenesis approach, based on topology optimization, is explored. By synthesizing plant growth models across different scales, this review enhances our understanding of biomechanics and provides key insights into plant growth. The knowledge gaps identified in this article offer a roadmap for future research in the field.

For the optimization of fundamental eigenfrequency in vibrating structures, it has been proven that multi-scale structures have advantages over single scale structures. This study introduces a two-scale topology optimization method using a data-driven microstructure model based on a multiple variable cutting (M-VCUT) level set approach. This method aims to maximize the fundamental eigenfrequency of two-scale structures. The method consists of two parts: offline database construction and online topology optimization. In the process of offline database construction, many microstructures are obtained by varying the value of geometric parameters according to the M-VCUT level set approach; then, a mapping relationship between the geometric parameters and the homogenized mechanical properties of microstructures is established by compactly supported radial basis function interpolation, which gives the data-driven microstructure model. In the process of online optimization, the homogenized mechanical properties corresponding to arbitrary design variables are obtained by using the data-driven microstructure model, whose computational costs are much less than those of the homogenization. Topology optimization is carried out with this data-driven model to enhance computational efficiency. In order to adapt the method of moving asymptotes (MMA), the eigenfrequency maximization problem is converted to its reciprocal minimization problem for sensitivity calculation. The method’s effectiveness is proved through several numerical examples.