2S-ML:一种基于仿真的深拉深可拉伸性评价分类与回归方法

IF 2.6 3区材料科学 Q2 ENGINEERING, MANUFACTURING

International Journal of Material Forming Pub Date : 2023-08-22 DOI:10.1007/s12289-023-01770-3

Tobias Lehrer, A. Kaps, I. Lepenies, F. Duddeck, Marcus Wagner

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

2S-ML: A simulation-based classification and regression approach for drawability assessment in deep drawing

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2S-ML: A simulation-based classification and regression approach for drawability assessment in deep drawing

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来源期刊

International Journal of Material Forming ENGINEERING, MANUFACTURING-MATERIALS SCIENCE, MULTIDISCIPLINARY

CiteScore

5.10

自引率

4.20%

发文量

审稿时长

>12 weeks

期刊介绍： The Journal publishes and disseminates original research in the field of material forming. The research should constitute major achievements in the understanding, modeling or simulation of material forming processes. In this respect ‘forming’ implies a deliberate deformation of material. The journal establishes a platform of communication between engineers and scientists, covering all forming processes, including sheet forming, bulk forming, powder forming, forming in near-melt conditions (injection moulding, thixoforming, film blowing etc.), micro-forming, hydro-forming, thermo-forming, incremental forming etc. Other manufacturing technologies like machining and cutting can be included if the focus of the work is on plastic deformations. All materials (metals, ceramics, polymers, composites, glass, wood, fibre reinforced materials, materials in food processing, biomaterials, nano-materials, shape memory alloys etc.) and approaches (micro-macro modelling, thermo-mechanical modelling, numerical simulation including new and advanced numerical strategies, experimental analysis, inverse analysis, model identification, optimization, design and control of forming tools and machines, wear and friction, mechanical behavior and formability of materials etc.) are concerned.