Nicolas Relun

7 papers receiving 646 citations

Nicolas Relun's Hit Papers

A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models 2012 · 547 citations
5470+4+9Years since publication100200300400500

Peers

Nicolas Relun
Comparison fields: 5 of 32
  • Statistics, Probability and Uncertainty 578
  • Computational Theory and Mathematics 286
  • Management Science and Operations Research 142
  • Civil and Structural Engineering 245
  • Safety, Risk, Reliability and Quality 76
Replace Roland Schöbi with:
Roland Schöbi Switzerland
Harok Bae United States
Beiqing Huang United States
François Deheeger France
V. Dubourg France
Changcong Zhou China
Xiukai Yuan China
Zhenzhong Chen China
Chuang Xiong China
Guo‐Dong Lu China
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Citations per field
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Citations per year

Countries citing papers authored by Nicolas Relun

Since Specialization
Citations

This map shows the geographic impact of Nicolas Relun's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nicolas Relun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolas Relun more than expected).

Fields of papers citing papers by Nicolas Relun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nicolas Relun. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nicolas Relun. The network helps show where Nicolas Relun may publish in the future.

Co-authors

The 7 scholars most cited alongside Nicolas Relun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nicolas Relun Line = papers co-authored together Nicolas Relun links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown

About Nicolas Relun

Nicolas Relun is a scholar working on Statistics, Probability and Uncertainty, Mechanics of Materials, Computational Theory and Mathematics, Statistical and Nonlinear Physics and Biomedical Engineering, having authored 7 papers that have together received 657 indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (5 papers), Elasticity and Material Modeling (2 papers), Advanced Mathematical Modeling in Engineering (2 papers), Model Reduction and Neural Networks (2 papers), Composite Material Mechanics (2 papers), Advanced Multi-Objective Optimization Algorithms (1 paper), Structural Integrity and Reliability Analysis (1 paper) and Wind and Air Flow Studies (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (578 citations), Computational Theory and Mathematics (286 citations), Management Science and Operations Research (142 citations), Civil and Structural Engineering (245 citations) and Safety, Risk, Reliability and Quality (76 citations). Nicolas Relun has collaborated with scholars based in France. Frequent co-authors include Nicolas Gayton, Maurice Lemaire, Benjamin Echard, Pierre‐Alain Boucard, David Néron, Pierre Beaurepaire and Cécile Mattrand. Their work appears in journals such as Reliability Engineering & System Safety, International Journal for Numerical Methods in Engineering, Computational Mechanics, Wind Energy and European Journal of Computational Mechanics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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