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Titlebook: Numerical Methods in Industrial Forming Processes; Numiform 2023 Jan Kusiak,?ukasz Rauch,Krzysztof Regulski Conference proceedings‘‘‘‘‘‘‘‘

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樓主: 威風(fēng)
51#
發(fā)表于 2025-3-30 10:28:32 | 只看該作者
52#
發(fā)表于 2025-3-30 15:01:36 | 只看該作者
Analysis of Multiaxial Tensile Stresses in Cold Forging Tools, tool stresses is simulated and the simulation results are compared to experimental values in order to validate the model. The simulation is then used to analyse the die load depending on the prestressing system.
53#
發(fā)表于 2025-3-30 17:03:41 | 只看該作者
54#
發(fā)表于 2025-3-30 21:37:03 | 只看該作者
Numerical and Experimental Investigation of Multi-axial Forging of AA6082 Alloy,by a finite element simulation of the multi-axial forging with a Voce hardening model, and it has been correlated with an experimentally determined hardness variation. The peak loads in all of the passes have also been compared.
55#
發(fā)表于 2025-3-31 02:52:56 | 只看該作者
Evaluation of Forming Factors for Titanium Gr. 2 Alloy Sheets with Multistage SPIF Process,ges, angle interval between the stages, and tool diameter. The present research focuses on the influence of process parameters on section thickness, equivalent plastic strain, and spring back. A simulation study of various process parameters of multistage forming and their effects on multistage incr
56#
發(fā)表于 2025-3-31 06:13:55 | 只看該作者
,Optimization of Process Variables in Warm Extrusion of a Mg–Al–Zn Alloy by Numerical Simulation,ict the optimum combination of process parameters, namely, extrusion ratio, extrusion speed, and extrusion temperature. Hansel Spittle model was used to define the flow stress curve in the simulation. The effect of the process parameters on extrusion load was studied, and the optimum die angle requi
57#
發(fā)表于 2025-3-31 09:53:20 | 只看該作者
58#
發(fā)表于 2025-3-31 17:26:18 | 只看該作者
59#
發(fā)表于 2025-3-31 17:49:31 | 只看該作者
60#
發(fā)表于 2025-3-31 23:45:25 | 只看該作者
Sensitivity Analysis and Formulation of the Inverse Problem in the Stochastic Approach to Modellingerefore, in the second part of the paper, a specific form of the objective function for the inverse analysis was developed. In the first approach, an objective function based on measurements of the average parameters was used and primary optimization was performed. Various optimization methods were
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