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Simulations of impact events in the automotive industry are now common practice. Vehicle crashworthiness simulations on plastic components cover a wide range of strain rates from 0.01 to 500 s-1. Because plastics mechanical properties are very dependent on strain rate, developing experimental methods for generating stress-strain curves at this strain rate range is of great technological importance. In this paper, a modified Charpy machine capable of acquiring useful information to obtain the stress-strain curve is presented. Strain rates between 300 to 400 s-1 were achieved. Three thermoplastics were tested: high-density polyethylene, polypropylene-copolymer and polypropylene-homopolymer. Impact simulations using LS-DYNA were performed using the acquired high-strain rates stress-strain curves and compared with experimental data. Simulations using stress-strain curves from quasi-static tests were also performed for comparison. Very good agreement between the simulation and experimental results was found when the ASTM D1822 type S specimen was used for testing each material.

Numerical evaluation of experimental test in which reinforced concrete beam is subjected to TNT explosions is the subject of the paper. Prediction of damage responses is being conducted by utilizing both numerical analyses and stochastic experimental methods where ABAQUS and LS-DYNA are being used. Material parameters of concrete and reinforcement, together with the mass of the TNT charge are considered in sensitivity study which is further used for metamodel creation. The Box–Behnken experimental method is used to construct both the samples and the surrogate models for the prediction process by employing the least-squares method and MATLAB codes. The results demonstrate the high capability of the coupled finite element–stochastic methods to predict damages of the reinforced concrete beam. Results of the numerical simulations were verified by reference cases. Introduced coupled methods can be, therefore, considered a tool for not only structural response prediction but optimization as well.

Lightweight construction in modern car design leads to an increased usage of various aluminium semi-finished products. Besides sheet material, aluminium extrusion profiles are frequently used due to their high stiffness and variety of possible cross-sections. However, similar to sheet material, aluminium profiles exhibit limited formability in comparison to mild steel materials. One possibility to increase the forming limits of precipitation hardened aluminium alloys is the so-called Tailored Heat Treatment technology. By a local short-term heat treatment, the material is softened and the material flow can be controlled to reduce stresses in critical forming zones. The purposeful definition of the heat treatment zones is mandatory to improve the forming results. Therefore, numerical methods are necessary. In this investigation, a numerical process chain is presented. It combines the thermo-mechanical simulation of a local laser heat treatment with a subsequent bending process of the heat-treated profile using the alloy EN AW-6082. The temperature distribution, mechanical properties, and finally, the bending result of the numerical model are validated by experimental tests.

Purpose The purpose of this paper is to compare the performance of implicit and explicit integration schemes for simulating the metal rolling process using commercial software packages ANSYS™ and LS-DYNA™. Design/methodology/approach For the industrial application of finite element method, the time discretization is one of the most important factors that determine the stability and efficiency of the analysis. An iterative approach, which is unconditionally stable in linear analyses, is the obvious choice for a quasi-static problem such as metal rolling. However, this approach may be challenging in achieving convergence with non-linear material behavior and complicated contact conditions. Therefore, a non-iterative method is usually adopted, in order to achieve computational accuracy through very small time steps. Models using both methods were constructed and compared for computational efficiency. Findings The results indicate that the explicit method yields higher levels of efficiency compared to the implicit method as model complexity increases. Furthermore, the implicit method displayed instabilities and numerical difficulties in certain load conditions further disfavoring the solver’s performance. Originality/value Comparison of the implicit and explicit procedures for time stepping was applied in 3D finite element analysis of the plate rolling process in order to evaluate and quantify the computational efficiency.

Automatic acoustic classification and diagnosis of mitral valve disease remain outstanding biomedical problems. Although considerable attention has been given to the evolution of signal processing techniques, the mechanics of the first heart sound generation has been largely overlooked. In this study, the haemodynamic determinants of the first heart sound were examined in a computational model. Specifically, the relationship of the transvalvular pressure and its maximum derivative to the time-frequency content of the acoustic pressure was examined. To model the transient vibrations of the mitral valve apparatus bathed in a blood medium, a dynamic, non-linear, fluid-coupled finite element model of the mitral valve leaflets and chordae tendinae was constructed. It was found that the root mean squared (RMS) acoustic pressure varied linearly (r2= 0.99) from 0.010 to 0.259 mmHg, following an increase in maximum dP/dt from 415 to 12470 mm Hg s(-1). Over that same range, peak frequency varied non-linearly from 59.6 to 88.1 Hz. An increase in left-ventricular pressure at coaptation from 22.5 to 58.5mm Hg resulted in a linear (r2= 0.91) rise in RMS acoustic pressure from 0.017 to 1.41mm Hg. This rise in transmitral pressure was accompanied by a non-linear rise in peak frequency from 63.5 to 74.1 Hz. The relationship between the transvalvular pressure and its derivative and the time-frequency content of the first heart sound has been examined comprehensively in a computational model for the first time. Results suggest that classification schemes should embed both of these variables for more accurate classification.