Acta Mechanica Sinica最新文献

AISI 430 ferritic stainless steel is popular in modern industry, while conventional welding methods with filler metals produce welded joints with tensile strength (586 MPa) and elongation (7.35%), which is insufficient to meet the growing engineering requirements. In this work, the elongation of the joint is doubled (15.11%) while yield strength remains unchanged after post-weld heat treatment (PWHT). Microstructural analysis of heat affected zone (HAZ) reveals the transformation process between equiaxed ferrite, intergranular martensite, and intragranular acicular martensite in the welded joint at 750 °C and 800 °C. Additionally, molecular dynamics simulations demonstrate the impact of various types of martensite on single crystals of ferritic stainless steel under tension. The results indicate that intergranular martensite and acicular martensite demonstrate transgranular fracture, while granular martensite exhibits intragranular fracture. Intergranular martensite and granular martensite are distributed near high-strain regions within the crystal, whereas acicular martensite is concentrated at the grain boundaries, away from the high-strain regions. The comparison of hardening parameters for different types of martensite reveals that granular martensite (58.98) has higher ductility than acicular martensite (97.40) and intergranular martensite (111.54). These findings are valuable for developing advanced stainless steel welded joints that balance high ductility and strength, meeting modern engineering demands.

Lumbar degeneration leads to changes in geometry and density distribution of vertebrae, which could further influence the mechanical property and behavior. This study aimed to quantitatively describe the variations in shape and density distribution for degenerated vertebrae by statistical models, and utilized the specific statistical shape model (SSM)/statistical appearance model (SAM) modes to assess compressive strength and fracture behavior. Highly detailed SSM and SAM were developed based on the 75 L1 vertebrae of elderly men, and their variations in shape and density distribution were quantified with principal component (PC) modes. All vertebrae were classified into mild (n = 22), moderate (n = 29), and severe (n = 24) groups according to the overall degree of degeneration. Quantitative computed tomography-based finite element analysis was used to calculate compressive strength for each L1 vertebra, and the associations between compressive strength and PC modes were evaluated by multivariable linear regression (MLR). Moreover, the distributions of equivalent plastic strain (PEEQ) for the vertebrae assigned with the first modes of SSM and SAM at mean ± 3SD were investigated. The Leave-One-Out analysis showed that our SSM and SAM had good performance, with mean absolute errors of 0.335±0.084 mm and 64.610±26.620 mg/cm³, respectively. A reasonable accuracy of bone strength prediction was achieved by using four PC modes (SSM 1, SAM 1, SAM 4, and SAM 5) to construct the MLR model. Furthermore, the PEEQ values were more sensitive to degeneration-related variations of density distribution than those of morphology. The density variations may change the deformity type (compression deformity or wedge deformity), which further affects the fracture pattern. Statistical models can identify the morphology and density variations in degenerative vertebrae, and the SSM/SAM modes could be used to assess compressive strength and fracture behavior. The above findings have implications for assisting clinicians in pathological diagnosis, fracture risk assessment, implant design, and preoperative planning.

The ground-based experimental tests are crucial to verify the related technologies of the drag-free satellite. This work presents a design method of the ground simulator testbed for emulating the planar dynamics of the space drag-free systems. In this paper, the planar dynamic characteristics of the drag-free satellite with double test masses are analyzed and non-dimensionalized. A simulator vehicle composed of an air bearing testbed and two inverted pendulums is devised on the basic of equivalent mass and equivalent stiffness proposed firstly in this paper. And the dynamic model of the simulator equivalent to the sensitive axis motion of the test mass and the planar motion of the satellite is derived from the Euler-Lagrange method. Then, the dynamic equivalence conditions between the space prototype system and the ground model system are derived from Pi theorem. To satisfy these conditions, the scaling laws of two systems and requirements for the inverted pendulum are put forward. Besides, the corresponding control scaling laws and a closed-loop control strategy are deduced and applied to establishing the numerical simulation experiments of underactuated system. Subsequently, the comparative simulation results demonstrate the similarity of dynamical behavior between the scaled-down ground model and the space prototype. As a result, the rationality and effectiveness of the design method are proved, facilitating the ground simulation of future gravitational wave detection satellites.

The anterior cruciate ligament plays a crucial role in maintaining stability within the knee joint, particularly for athletes who frequently experience its rupture. This study presents a novel approach using personalized three-dimensional (3D) parametric finite element modeling of the knee joint to simulate the treatment following anterior cruciate ligament reconstruction (ACLR) in both forward walking (FW) and drop landing (DL) tasks. The study encompasses two distinct cohorts: five healthy athletes and five ACLR patients. Biomechanical motion analysis was conducted on both cohorts, with the ACLR patient group evaluated at 6 and 9 months post-surgery. A comprehensive 3D parametric model of the knee joint was meticulously crafted. The findings reveal a notable reduction in stress on crucial knee structures such as the autograft, meniscus, and cartilages over time for both FW and DL tasks following ACLR, with a reduction in tissue tension of approximately 9.5% and 37% for FW and DL, respectively. This personalized model not only facilitates the investigation of knee joint tissue biomechanics post-ACLR but also aids in estimating the return-to-sports timeline for patients. By accommodating individual tissue geometries and incorporating patient-specific kinetic data, this model enhances our comprehension of post-ACLR biomechanics across various functional tasks, thereby optimizing rehabilitation strategies.

The diffusion and dynamic behaviors of liquid metal droplet during impact significantly affect its application in 3D printing and painting processes. To obtain a better understanding of the impact process of liquid metal droplets, we analyze the influence of different initial conditions and substrate materials on droplet spreading, impact force, and elastic wave propagation on the substrate. It is found that an agglomeration phenomenon can be observed when the liquid metal droplets impact onto a soft elastomer substrate, which is not observed as a metal substrate is employed. Regardless of the substrate material, when surface tension dominates the diffusion, the diffusion factor of droplets is proportional to (sqrt{We}) (Weber number). It is also observed that the self-similarity of liquid metal droplet impact force on copper substrates, which is not the case for soft elastomer substrates. Using smoothed particle hydrodynamics (SPH) simulations, the time-domain curve and peak point of the droplet can be well predicted for a metal substrate. Furthermore, by recording the acceleration signal on the substrates, we further obtain the energy radiated by elastic waves, providing an explanation for energy conversion during the impact process with varying parameters. The results provide an additional understanding on the complex impact behaviors of liquid metal droplets.

This study utilizes Direct FE² multiscale simulation techniques to propose an innovative approach for analyzing hydrogen diffusion in Zircaloy cladding. This method combines finite element simulations at two scales into a monolithic framework by utilizing downscaling rules and scaling factors. Through the investigation, it was found that voids induce non-uniform diffusion of lattice hydrogen, demonstrating a strong correlation between trapped concentration and microstructure. Additionally, the accumulation of trapped hydrogen leads to localized plastic deformation and a reduction in effective diffusivity. Furthermore, two representative volume elements were established to depict the void distribution at various stages of its evolution. It is evident that in the initial phases of void evolution, the hydrogen-induced softening effect facilitates crack propagation deep within the zirconium alloy cladding. Moreover, as void evolution progresses into the second stage, this effect intensifies the incidence of localized damage at the narrow inter-void ligaments.

Transient negative capacitance (NC), as an available dynamic charge effect achieved in resistor-ferroelectric capacitor (R-FEC) circuits, has triggered a series of theoretical and experimental works focusing on its physical mechanism and device application. Here, we analytically derived the effects of different mechanical conditions on the transient NC behaviors in the R-FEC circuit based on the phenomenological model. It shows that the ferroelectric capacitor can exhibit either NC (i.e., “single NC” and “double NC”) or positive capacitance, depending on the mechanical condition and temperature. Further numerical calculations show that the voltage drop caused by NC can be effectively controlled by temperature, applied stress, or strain. The relationship between NC voltage drop and system configurations including external resistance, dynamical coefficient of polarization, and input voltage are presented, showing diverse strategies to manipulate the NC effect. These results provide theoretical guidelines for rational design and efficient control of NC-related electronic devices.

Physics-informed neural networks (PINNs) have shown remarkable prospects in solving the forward and inverse problems involving partial differential equations (PDEs). The method embeds PDEs into the neural network by calculating the PDE loss at a set of collocation points, providing advantages such as meshfree and more convenient adaptive sampling. However, when solving PDEs using nonuniform collocation points, PINNs still face challenge regarding inefficient convergence of PDE residuals or even failure. In this work, we first analyze the ill-conditioning of the PDE loss in PINNs under nonuniform collocation points. To address the issue, we define volume weighting residual and propose volume weighting physics-informed neural networks (VW-PINNs). Through weighting the PDE residuals by the volume that the collocation points occupy within the computational domain, we embed explicitly the distribution characteristics of collocation points in the loss evaluation. The fast and sufficient convergence of the PDE residuals for the problems involving nonuniform collocation points is guaranteed. Considering the meshfree characteristics of VW-PINNs, we also develop a volume approximation algorithm based on kernel density estimation to calculate the volume of the collocation points. We validate the universality of VW-PINNs by solving the forward problems involving flow over a circular cylinder and flow over the NACA0012 airfoil under different inflow conditions, where conventional PINNs fail. By solving the Burgers’ equation, we verify that VW-PINNs can enhance the efficiency of existing the adaptive sampling method in solving the forward problem by three times, and can reduce the relative L₂ error of conventional PINNs in solving the inverse problem by more than one order of magnitude.

F-actin microstructures dominate cellular viscoelasticity and have been used to identify the migration and malignance of living cancer cells. Diabetic cancer patients suffer from increased metastasis and tumor recurrence. However, the long-term evolution and correlation of F-actin microstructures and viscoelasticity distribution are still poorly understood in living cancer cells under varying glucose environment. Herein, by using atomic force microscopy with amplitude modulation-frequency modulation and nanoindentation mode, we characterized the hierarchical F-actin microstructures and the multi-passage viscoelasticity evolution in living Huh-7 cancer cells transferred from high to low glucose level. The highly oriented stress fibers connected by thinner fiber networks were observed in high glucose environment. The circumferential actin networks composed by straight segment-like fibers and the randomly distributed actin fragments connected by ultrathin crosslinking fibers were observed in low glucose environment. The viscoelasticity within the nucleus and the cytoplasm of living Huh-7 cancer cells showed long-term fluctuations over tens of passages after switching glucose environments. The viscoelasticity of cytoplasm was more responsive to the change of glucose environments than nucleus, which was due to the reorganization of F-actin microstructures. Our work provides the microstructural and nanomechanical understanding on the migration and proliferation of living cancer cells under varying glucose environment.

A hybrid approach based on the immersed boundary method (IBM) is developed for computation of flow-induced sound around moving bodies. In this method, a high-fidelity direct numerical simulation (DNS) solver is used to simulate the incompressible flow field. The sound field is predicted by discretizing acoustic perturbation equations (APEs) with dispersion-relation-preserving space scheme and low-dispersion and low-dissipation Runge-Kutta time integration. A sharp-interface IBM based on ghost-cell is implemented for present two-step DNS-APE approach to deal with complex moving bodies with Cartesian grids. The present method is validated through simulations of sound generation caused by flow past a rotating cylinder, an oscillating cylinder, and tandem oscillating and stationary cylinders. The sound generated by typical kinds of complicated bio-inspired locomotions, i.e., flapping flight by wings of varied shapes and collective undulatory swimming in tandem, are investigated using present method. The results demonstrate potential of the hybrid approach in addressing flow-induced sound generation and propagation with complex moving boundaries in a fluid medium, especially for the sound characteristics of bio-mimetic flows, which might shed lights on investigations on bio-acoustics, ethology of complex animal system, and related bio-mimetic design for quietness.