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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Chandrashekarappa, Manjunath Patel Gowdru

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (10/10 displayed)

  • 2022Effect of Pin Geometry and Orientation on Friction and Wear Behavior of Nickel-Coated EN8 Steel Pin and Al6061 Alloy Disc Pair9citations
  • 2021Corrosion behaviour of high-strength Al 7005 alloy and its composites reinforced with industrial waste-based fly ash and glass fibre: comparison of stir cast and extrusion conditions38citations
  • 2021Experimental investigation of selective laser melting parameters for higher surface quality and microhardness properties46citations
  • 2021Image processing of Mg-Al-Sn alloy microstructures for determining phase ratios and grain size and correction with manual measurement25citations
  • 2021The effect of Zn and Zn–WO3 composites nano-coatings deposition on hardness and corrosion resistance in steel substrate21citations
  • 2016Multi-Objective Optimization of Squeeze Casting Process using Evolutionary Algorithms25citations
  • 2016Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization24citations
  • 2015Prediction of Secondary Dendrite Arm Spacing in Squeeze Casting Using Fuzzy Logic Based Approaches9citations
  • 2014Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approachescitations
  • 2014Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches13citations

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Yadav, Shiv Pratap Singh
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Avvari, Muralidhar
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Ranganath, Siddappa
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Anand, Praveena Bindiganavile
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Lakshmikanthan, Avinash
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Shankar, Vijay Kumar
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Giasin, Khaled
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Mylaraiah, Shantharaja
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Pimenov, Danil Yurievich
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Wojciechowski, Szymon
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Simsir, Ercan
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Akkoyun, Fatih
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Kulkarni, Raviraj Mahabaleshwar
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Kumar, Channagiri Mohankumar Praveen
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Parappagoudar, Mahesh
1 / 3 shared
Krishna, Prasad
1 / 1 shared
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2021
2016
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Co-Authors (by relevance)

  • Yadav, Shiv Pratap Singh
  • Avvari, Muralidhar
  • Ranganath, Siddappa
  • Anand, Praveena Bindiganavile
  • Lakshmikanthan, Avinash
  • Shankar, Vijay Kumar
  • Giasin, Khaled
  • Krishna, Munishamaiah
  • Mylaraiah, Shantharaja
  • Pimenov, Danil Yurievich
  • Swamy, Praveen Kumar
  • Nagaraj, Mohan
  • Sheshadri, Rohith
  • Pimenov, Danil Yu
  • Prasad, Raghupatruni Venkata Satya
  • Wojciechowski, Szymon
  • Ercetin, Ali
  • Simsir, Ercan
  • Akkoyun, Fatih
  • Kulkarni, Raviraj Mahabaleshwar
  • Kumar, Channagiri Mohankumar Praveen
  • Parappagoudar, Mahesh
  • Krishna, Prasad
OrganizationsLocationPeople

article

Prediction of Secondary Dendrite Arm Spacing in Squeeze Casting Using Fuzzy Logic Based Approaches

  • Chandrashekarappa, Manjunath Patel Gowdru
Abstract

<jats:title>Abstract</jats:title><jats:p> The quality of the squeeze castings is significantly affected by secondary dendrite arm spacing, which is influenced by squeeze cast input parameters. The relationships of secondary dendrite arm spacing with the input parameters, namely time delay, pressure duration, squeeze pressure, pouring and die temperatures are complex in nature. The present research work focuses on the development of input-output relationships using fuzzy logic approach. In fuzzy logic approach, squeeze cast process variables are expressed as a function of input parameters and secondary dendrite arm spacing is expressed as an output parameter. It is important to note that two fuzzy logic based approaches have been developed for the said problem. The first approach deals with the manually constructed mamdani based fuzzy system and the second approach deals with automatic evolution of the Takagi and Sugeno’s fuzzy system. It is important to note that the performance of the developed models is tested for both linear and non-linear type membership functions. In addition the developed models were compared with the ten test cases which are different from those of training data. The developed fuzzy systems eliminates the need of a number of trials in selection of most influential squeeze cast process parameters. This will reduce time and cost of trial experimentations. The results showed that, all the developed models can be effectively used for making prediction. Further, the present research work will help foundrymen to select parameters in squeeze casting to obtain the desired quality casting without much of time and resource consuming.</jats:p>

Topics
  • impedance spectroscopy
  • casting