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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Newcastle University

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2020Alumina nanoparticles for firefighting and fire prevention27citations
  • 2018A CRITICAL ASSESSMENT OF KASSAPOGLOU'S STATISTICAL MODEL FOR COMPOSITES FATIGUE6citations

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Chart of shared publication
Krivoshapkin, Pavel
1 / 2 shared
Nazarova, Elena
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Mosina, Kseniia
1 / 7 shared
Vinogradov, Aleksandr
1 / 1 shared
Krivoshapkina, Elena
1 / 1 shared
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2020
2018

Co-Authors (by relevance)

  • Krivoshapkin, Pavel
  • Nazarova, Elena
  • Mosina, Kseniia
  • Vinogradov, Aleksandr
  • Krivoshapkina, Elena
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article

A CRITICAL ASSESSMENT OF KASSAPOGLOU'S STATISTICAL MODEL FOR COMPOSITES FATIGUE

  • Vinogradov, Vladimir
Abstract

<jats:p>Kassapoglou has recently proposed a model for fatigue of composite materials which seems to suggest that the fatigue SN curve can be fully predicted on the basis of the statistical distribution of static strengths. The original abstract writes expressions for the cycles to failure as a function of R ratio are derived. These expressions do not require any curve fitting and do not involve any experimentally determined parameters. The fatigue predictions do not require any fatigue tests for calibration". These surprisingly ambitious claims and attractive results deserve careful scrutiny. We contend that the result, which originates from the reliability theory where exponential distributions is sometimes used to model distribution of failures when age (or wearout) has no influence on the probability of failure, does not conform to a fatigue testing with the resulting SN curve distribution. Despite Kassapoglou's attempt to use a wearout law which seems to confirm this result even with wearout, we contend that a proper statistical treatment of the fatigue process should not make wear-out constants disappear, and hence the SN curves would depend on them, and not just on scatter of static data. These concerns explain the large discrepancies found by 3 independent studies which have tried to apply Kassapoglou's model to composite fatigue data.</jats:p>

Topics
  • impedance spectroscopy
  • theory
  • strength
  • fatigue
  • composite
  • fatigue testing