[Oral Presentation]基于图神经网络的三维颗粒滑坡体系的力链预测

Organized By

Hohai University

Monash University

Co-organized by

Southeast University

Jiangxi University of Science and Technology

Northeast University

DUT-BSU Scientific Research and Innovation Center

Suzhou University of Science and Technology

State Key Laboratory of Structural Analysis, Optimization and CAE Software for Industrial Equipment

Sponsoring agency

KELI SDEM Software (Dalian) Co., Ltd.

Sugon Smart Computing Information Technology Co., Ltd.

Beijing Paratera Technology Co., Ltd.

Simpop Information Technology Co., Ltd.

Important Dates

Conference Announcement

December 2023, release First Round Announcement
Abstract Submission Deadline
March 31^th, 2024
Paper Submission Deadline
April 30^th, 2024
Registration
From January 1^st, 2024
Conference Schedule
May 31^st (Friday), 2024 On-Site Registration
June 1^st to 3^rd, 2024 Conference

基于图神经网络的三维颗粒滑坡体系的力链预测

ID：205 Submission ID：338 View Protection：ATTENDEE Updated Time：2024-04-30 10:28:14 Hits：624 Oral Presentation

Start Time：Pending （Asia/Shanghai）

Duration：Pending

Session：[No Session] » [No Session Block]

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Abstract

力链是指颗粒物质等非晶固体中由携带超过体系平均应力的颗粒所组成的类似于细丝的结构，对于非晶体系的力学与传输性质都起着非常关键的作用。而在颗粒滑坡过程中便往往伴随着力链的断裂与重构，因此如何捕获与识别三维颗粒滑坡体系中的力链结构对于滑坡物理机制的理解具有重要意义。在本文中，课题组利用LAMMPS分子动力学模拟方法模拟了三维水平滚筒中的颗粒滑坡过程，并在仅输入颗粒体系静态初始构型的前提下，通过优化后的新型图神经网络模型准确预测了整个滑坡过程中的力链结构，并得到其衍化过程。在图神经网络的优化过程中，课题组在传统模型的基础上增加了强力链在图数据中的权重，从而优化了相应的模型参数。通过对比不同时刻与不同模型下的测试结果，课题组进一步证明了优化后的图神经网络具有更好的鲁棒性与泛化能力。

Keywords

颗粒物质，颗粒滑坡，力链，图神经网络

Speaker

曹嘉炜

学生 中南大学

Submission Author

曹嘉炜中南大学

张玲中南大学

Sponsored By

Hohai University

Panel of Computational Mechanics on Granular Materials, Working Party of Computational Mechanics, Chinese Society of Theoretical and Applied Mechanics

Jiangsu Society of Theoretical and Applied Mechanics