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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Materials Map under construction

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 (2/2 displayed)

  • 2021Programming for Machining in Electrical Discharge Machine1citations
  • 2021Application of Evolutionary Optimization Techniques Towards Non-Traditional Machining for Performance Enhancementcitations

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Chart of shared publication
Vardhan, T. V.
1 / 1 shared
Babu, Dr B. Sridhar
1 / 4 shared
Chart of publication period
2021

Co-Authors (by relevance)

  • Vardhan, T. V.
  • Babu, Dr B. Sridhar
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booksection

Application of Evolutionary Optimization Techniques Towards Non-Traditional Machining for Performance Enhancement

  • Babu, Dr B. Sridhar
  • Kalita, Hridayjit
Abstract

Electro-chemical machining is a non-conventional machining method that is used for machining of very complicated shape. In this chapter an attempt has been made to carry out multi-objective optimization of the surface roughness (SR) and material removal rate (MRR) for the ECM process of EN 19 on a CNC ECM machine using copper electrode through evolutionary optimization techniques like teaching-learning-based optimization (TLBO) technique and biogeography-based optimization (BBO) technique. The input parameters considered are electrolyte concentration, voltage, feed rate, inter-electrode gap. TLBO and BBO techniques were used to obtain maximum MRR and minimum SR. In addition, obtained optimized values were validated for testing the significance of the TLBO and BBO techniques, and a very small error value of MRR and SR was found. BBO outperformed TLBO in every aspect like less percentage error and better-optimized values; however, TLBO took less computation time than the BBO.

Topics
  • impedance spectroscopy
  • surface
  • laser emission spectroscopy
  • copper