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 (4/4 displayed)

  • 2022Shear Strength Model for Reinforced Concrete Corner Joints Based on Soft Computing Techniques2citations
  • 2022Shear Strength Prediction Model for RC Exterior Joints Using Gene Expression Programming3citations
  • 2022Gene Expression Programming for Estimating Shear Strength of RC Squat Wall10citations
  • 2022Improved shear strength prediction model of steel fiber reinforced concrete beams by adopting gene expression programming16citations

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Ullah, Asad
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Waseem, Muhammad
1 / 6 shared
Jamil, Irfan
1 / 1 shared
Khan, Azam
4 / 4 shared
Nasir, Hassan
1 / 3 shared
Ahmad, Mahmood
1 / 6 shared
Zamin, Bakht
1 / 1 shared
Shayanfar, Javad
1 / 5 shared
Niaz, Momina
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2022

Co-Authors (by relevance)

  • Ullah, Asad
  • Waseem, Muhammad
  • Jamil, Irfan
  • Khan, Azam
  • Nasir, Hassan
  • Ahmad, Mahmood
  • Zamin, Bakht
  • Shayanfar, Javad
  • Niaz, Momina
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article

Shear Strength Prediction Model for RC Exterior Joints Using Gene Expression Programming

  • Ullah, Asad
  • Khan, Azam
  • Tariq, Moiz
Abstract

<jats:p>Predictive models were developed to effectively estimate the RC exterior joint’s shear strength using gene expression programming (GEP). Two separate models are proposed for the exterior joints: the first with shear reinforcement and the second without shear reinforcement. Experimental results of the relevant input parameters using 253 tests were extracted from the literature to carry out a knowledge analysis of GEP. The database was further divided into two portions: 152 exterior joint experiments with joint transverse reinforcements and 101 unreinforced joint specimens. Moreover, the effects of different material and geometric factors (usually ignored in the available models) were incorporated into the proposed models. These factors are beam and column geometries, concrete and steel material properties, longitudinal and shear reinforcements, and column axial loads. Statistical analysis and comparisons with previously proposed analytical and empirical models indicate a high degree of accuracy of the proposed models, rendering them ideal for practical application.</jats:p>

Topics
  • experiment
  • strength
  • steel