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Influential Yield Strength of Steel Materials with Return Random Walk Gravity Centrality

Author

Listed:
  • Rocío Rodríguez

    (Tidop Research Group, University of Salamanca, Patio de Escuelas 1, E-38008 Salamanca, Spain
    These authors contributed equally to this work.)

  • Manuel Curado

    (Department of Computer Science and Artificial Intelligence, University of Alicante, Campus de San Vicente, Ap. Correos 99, E-03080 Alicante, Spain
    These authors contributed equally to this work.)

  • Francy D. Rodríguez

    (Department of Computer, Catholic University of Ãvila, Calle Canteros, s/n, E-05005 Ãvila, Spain
    These authors contributed equally to this work.)

  • José F. Vicent

    (Department of Computer Science and Artificial Intelligence, University of Alicante, Campus de San Vicente, Ap. Correos 99, E-03080 Alicante, Spain
    These authors contributed equally to this work.)

Abstract

In complex networks, important nodes have a significant impact, both functional and structural. From the perspective of data flow pattern detection, the evaluation of the importance of a node in a network, taking into account the role it plays as a transition element in random paths between two other nodes, has important applications in many areas. Advances in complex networks and improved data generation are very important for the growth of computational materials science. The search for patterns of behavior of the elements that make up steels through complex networks can be very useful in understanding their mechanical properties. This work aims to study the influence of the connections between the elements of steel and the impact of these connections on their mechanical properties, more specifically on the yield strength. The patterns found in the results show the significance of the proposed approach for the development of new steel compositions.

Suggested Citation

  • Rocío Rodríguez & Manuel Curado & Francy D. Rodríguez & José F. Vicent, 2024. "Influential Yield Strength of Steel Materials with Return Random Walk Gravity Centrality," Mathematics, MDPI, vol. 12(3), pages 1-12, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:3:p:439-:d:1329299
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    References listed on IDEAS

    as
    1. Flaviano Morone & Hernán A. Makse, 2015. "Correction: Corrigendum: Influence maximization in complex networks through optimal percolation," Nature, Nature, vol. 527(7579), pages 544-544, November.
    2. Flaviano Morone & Hernán A. Makse, 2015. "Influence maximization in complex networks through optimal percolation," Nature, Nature, vol. 524(7563), pages 65-68, August.
    3. Curado, Manuel & Rodriguez, Rocio & Tortosa, Leandro & Vicent, Jose F., 2022. "Anew centrality measure in dense networks based on two-way random walk betweenness," Applied Mathematics and Computation, Elsevier, vol. 412(C).
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