Data-driven and physics-based methods to optimize structures against delamination

被引:0
|
作者
Kumar, Tota Rakesh [1 ,2 ]
Paggi, Marco [1 ]
机构
[1] IMT Sch Adv Studies Lucca, Res Unit MUSAM Multiscale Anal Mat, Computat Mech Grp, Piazza San Francesco 19, I-55100 Lucca, Italy
[2] Indian Maritime Univ, Sch Marine Engn & Technol, Chennai, Tamil Nadu, India
关键词
Cohesive fracture; joining technologies; graded interfaces; particle swarm optimization; SIMP topology optimization; TOPOLOGY OPTIMIZATION; LEVEL SET; IDENTIFICATION; ALGORITHM; FRAMEWORK; ADHESION; DESIGN; FORMULATION; PARAMETERS; CURVES;
D O I
10.1080/15376494.2024.2372696
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Composite materials and multi-material components often fail at their internal interfaces/adhesive joints, and hence special attention should be given to such catastrophic delamination events to guarantee the system's functional requirements. So far, however, the majority of structural topology optimization problems have focused on optimal distribution of the bulk materials by considering interfaces as perfectly bonded. This motivates the introduction of optimization methods that explicitly take into account the role of the material interfaces to optimize structures against delamination. In this work, we propose a data-driven heuristic optimization approach for the identification of optimal cohesive interfaces with linearly graded fracture properties to increase the ability of the composite structure to withstand peeling. Moreover, for given cohesive interface properties, we investigate the applicability of the physics-based Solid Isotropic Material with Penalty (SIMP) topology optimization approach to optimize the internal structure of a substrate in problems where the stress field is affected by interface delamination.
引用
收藏
页数:17
相关论文
共 50 条
  • [21] A PHYSICS-BASED DATA-DRIVEN APPROACH FOR MODELING OF ENVIRONMENTAL DEGRADATION IN ELASTOMERS
    Ghaderi, Aref
    Chen, Yang
    Dargazany, Roozbeh
    PROCEEDINGS OF ASME 2022 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, IMECE2022, VOL 9, 2022,
  • [22] A deeper look into natural sciences with physics-based and data-driven measures
    Rodrigues, Davi Rohe
    Everschor-Sitte, Karin
    Gerber, Susanne
    Horenko, Illia
    ISCIENCE, 2021, 24 (03)
  • [23] Hybrid physics-based and data-driven impact localisation for composite laminates
    Xiao, Dong
    Sharif-Khodaei, Zahra
    Aliabadi, M. H.
    INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES, 2024, 274
  • [24] A Data-Driven and Physics-Based Approach to Exploring Interdependency of Interconnected Infrastructure
    Zhou, Shenghua
    Ng, S. Thomas
    Yang, Yifan
    Xu, Frank Jun
    Li, Dezhi
    COMPUTING IN CIVIL ENGINEERING 2019: DATA, SENSING, AND ANALYTICS, 2019, : 82 - 88
  • [25] Distributed Planning of Collaborative Locomotion: A Physics-Based and Data-Driven Approach
    Fawcett, Randall T.
    Ames, Aaron D.
    Hamed, Kaveh Akbari
    IEEE ACCESS, 2023, 11 : 128369 - 128382
  • [26] Data-driven and physics-based approach for wave downscaling: A comparative study
    Juan, Nerea Portillo
    Rodriguez, Javier Olalde
    Valdecantos, Vicente Negro
    Iglesias, Gregorio
    OCEAN ENGINEERING, 2023, 285
  • [27] Design of a Physics-Based and Data-Driven Hybrid Model for Predictive Maintenance
    Traini, Emiliano
    Bruno, Giulia
    Lombardi, Franco
    ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AND RESILIENT PRODUCTION SYSTEMS, PT V, 2021, 634 : 536 - 543
  • [28] Physics-based modeling and data-driven algorithm for prediction and diagnosis of atherosclerosis
    Bahloul, Mohamed
    Belkhatir, Zehor
    Aboelkassem, Yasser
    Laleg-Kirati, Meriem T.
    BIOPHYSICAL JOURNAL, 2022, 121 (03) : 419A - 420A
  • [29] A new model updating strategy with physics-based and data-driven models
    Yongyong Xiang
    Baisong Pan
    Luping Luo
    Structural and Multidisciplinary Optimization, 2021, 64 : 163 - 176
  • [30] A Physics-Based and Data-Driven Approach for Localized Statistical Channel Modeling
    Zhang, Shutao
    Ning, Xinzhi
    Zheng, Xi
    Shi, Qingjiang
    Chang, Tsung-Hui
    Luo, Zhi-Quan
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (06) : 5409 - 5424