Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2024Prediction of defects in deep drawn rectangular parts using Finite Element Analysis (FEA) and Response Surface Methodology (RSM)citations

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Shazly, Mostafa
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Mohamed, Tamer A.
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Wifi, Abdallah S.
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2024

Co-Authors (by relevance)

  • Shazly, Mostafa
  • Mohamed, Tamer A.
  • Wifi, Abdallah S.
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article

Prediction of defects in deep drawn rectangular parts using Finite Element Analysis (FEA) and Response Surface Methodology (RSM)

  • Gadallah, Mohamed H.
  • Shazly, Mostafa
  • Mohamed, Tamer A.
  • Wifi, Abdallah S.
Abstract

<jats:title>Abstract</jats:title><jats:p>Deep drawing defects such as thinning and earing present challenges to sheet metal forming industry while designers tend to favour the usage of new materials and production processes. The present work introduces an integrated approach using Design of Experiment, FEA experimentation and RSM to study the effect of deep drawing process parameters and resulting defects associated with sheet metal forming processes such as thinning and earing particularly in deep drawing of non-circular parts. The Design of Experiment (DoE) is used to generate a series of experiments for different process parameters in deep drawn rectangular products which are then simulated using Simulia 2022, a finite element package. The results are then fed to statistical analysis software, Design Expert 12.0, to develop regression equations that predict minimum sheet thickness and earing defects using RSM. FE models for deep drawing of different products have been built and results have been verified through comparisons with published data. Critical process parameters were selected for investigation in the present work. Based on the results of these experiments, a two-level design of experiment is conduct to generate 64 FE experiments. The relationships between these parameters and minimum sheet thickness after drawing and earing defects are then obtained using RSM. Optimum values of different parameters are obtained for maximum sheet thickness after drawing and minimum earing.</jats:p>

Topics
  • impedance spectroscopy
  • surface
  • experiment
  • defect
  • finite element analysis
  • drawing