Theoretical and Applied Mechanics Letters最新文献

In-situ layerwise imaging measurement of laser powder bed fusion (LPBF) provides a wealth of forming and defect data which enables monitoring of components quality and powder bed homogeneity. Using high-resolution camera layerwise imaging and image processing algorithms to monitor fusion area and powder bed geometric defects has been studied by many researchers, which successfully monitored the contours of components and evaluated their accuracy. However, research for the methods of in-situ 3D contour measurement or component edge warping identification is rare. In this study, a 3D contour measurement method combining gray intensity and phase difference is proposed, and its accuracy is verified by designed experiments. The results show that the high-precision of the 3D contours can be achieved by the constructed energy minimization function. This method can detect the deviations of common geometric features as well as warpage at LPBF component edges, and provides fundamental data for in-situ quality monitoring tools.

In this paper, the path integral solutions for a general n-dimensional stochastic differential equations (SDEs) with $\alpha$-stable Lévy noise are derived and verified. Firstly, the governing equations for the solutions of n-dimensional SDEs under the excitation of $\alpha$-stable Lévy noise are obtained through the characteristic function of stochastic processes. Then, the short-time transition probability density function of the path integral solution is derived based on the Chapman-Kolmogorov-Smoluchowski (CKS) equation and the characteristic function, and its correctness is demonstrated by proving that it satisfies the governing equation of the solution of the SDE, which is also called the Fokker-Planck-Kolmogorov equation. Besides, illustrative examples are numerically considered for highlighting the feasibility of the proposed path integral method, and the pertinent Monte Carlo solution is also calculated to show its correctness and effectiveness.

A stratified wake has multiple flow regimes, and exhibits different behaviors in these regimes due to the competing physical effects of momentum and buoyancy. This work aims at automated classification of the weakly and the strongly stratified turbulence regimes based on information available in a full Reynolds stress model. First, we generate a direct numerical simulation database with Reynolds numbers from 10,000 to 50,000 and Froude numbers from 2 to 50. Order (100) independent realizations of temporally evolving wakes are computed to get converged statistics. Second, we train a linear logistic regression classifier with weight thresholding for automated flow regime classification. The classifier is designed to identify the physics critical to classification. Trained against data at one flow condition, the classifier is found to generalize well to other Reynolds and Froude numbers. The results show that the physics governing wake evolution is universal, and that the classifier captures that physics.

The interplay between noise and nonlinearites can lead to escape dynamics. Associated nonlinear phenomena have been observed in various applications ranging from climatology to biology and engineering. For reasons of computational ease, in most studies, Gaussian white noise is used. However, this noise model is not physical due to the associated infinite energy content. Here, the authors present extensive experimental investigations and numerical simulations conducted to examine the impact of noise color on escape times in nonlinear oscillators. With a careful parameterization of the numerical simulations, the authors are able to make quantitative comparisons with experimental results. Through the experiments and simulations, it is illustrated that the noise color can drastically influence escape times and escape probability.

In this paper, the approximate Bayesian computation combines the particle swarm optimization and sequential Monte Carlo methods, which identify the parameters of the Mathieu-van der Pol-Duffing chaotic energy harvester system. Then the proposed method is applied to estimate the coefficients of the chaotic model and the response output paths of the identified coefficients compared with the observed, which verifies the effectiveness of the proposed method. Finally, a partial response sample of the regular and chaotic responses, determined by the maximum Lyapunov exponent, is applied to detect whether chaotic motion occurs in them by a 0–1 test. This paper can provide a reference for data-based parameter identification and chaotic prediction of chaotic vibration energy harvester systems.

Acoustic tweezing cytometry (ATC) is a recently developed method for cell mechanics regulation. Targeted microbubbles, which are attached to integrins and subsequently the actin cytoskeleton, anchor, amplify and transmit the mechanical energy in an acoustic field inside the cells, eliciting prominent cytoskeleton contractile force increases in various cell types. We propose that a mechanochemical conversion mechanism is critical for the high efficiency of ATC to activate cell contractility responses. Our models predict key experimental observations. Moreover, we study the influences of ATC parameters (ultrasound center frequency, pulse repetition frequency, duty cycle, and acoustic pressure), cell areas, the number of ATC stimuli, and extracellular matrix rigidity on cell contractility responses to ATC. The simulation results suggest that it is large molecules, rather than small ions, that facilitate global responses to the local ATC stimulation, and the incorporation of visible stress fiber bundles improves the accuracy of modeling.

The snap fit is a common mechanical mechanism. We have studied the spherical snap fit carefully for its physical asymmetry, which is easy to assemble but difficult to disassemble. Because of the complexity of spherical snap fit, it is difficult to get a theoretical formula to describe its physical asymmetry. In this paper, the pushing assembly and pulling disassembly of spherical snap fit are studied by both finite element analysis and experiments. The theoretical formulaes of spherical snap fit have been obtained based on numerical simulations and theoretical results of cylindrical snap fit.

To study the kinematics of flow rate and ventricular dilatation, an analytical perturbation approach of hydrocephalus has been devised. This research provides a comprehensive investigation of the characteristics of cerebrospinal fluid (CSF) flow and pressure in a hydrocephalic patient. The influence of hydrocephalic CSF, flowing rotationally with realistic dynamical characteristics on pulsatile boundaries of subarachnoid space, was demonstrated using a nonlinear controlling system of CSF. An analytical perturbation method of hydrocephalus has been developed to investigate the biomechanics of fluid flow rate and the ventricular enlargement. In this paper presents a detailed analysis of CSF flow and pressure dynamics in a hydrocephalic patient. It was elaborated with a nonlinear governing model of CSF to show the influence of hydrocephalic CSF, flowing rotationally with realistic dynamical behaviors on pulsatile boundaries of subarachnoid space. In accordance with the suggested model, the elasticity factor changes depending on how much a porous layer, in this case the brain parenchyma, is stretched. It was improved to include the relaxation of internal mechanical stresses for various perturbation orders, modelling the potential plasticity of brain tissue. The initial geometry that was utilised to create the framework of CSF with pathological disease hydrocephalus and indeed the output of simulations using this model were compared to the actual progression of ventricular dimensions and shapes in patients. According to this observation, the non - linear and elastic mechanical phenomena incorporated into the current model are probably true. Further modelling of ventricular dilation at a normal pressure may benefit from the existence of a valid model whose parameters approximate genuine mechanical characteristics of the cerebral cortex.

The interaction between free fast-moving bodies (or particles) and the fluid surrounding them is studied, motivated by applications in different branches of industry, biomedicine, the environment and science such as flying droplets, ice growth, dust, impacts, food grains, sport, complexity and storms. New inviscid-based modelling and results on the behaviour of two interacting bodies inside a channel flow are described. This is followed by discussion of the more-bodies extension with a view to treating arrays of bodies in a rational manner. Significant dependences on initial conditions and on the comparative body masses and moments of inertia are found for the occurrence of body-body impacts as opposed to wall-body impacts and for the associated impact times.