[Poster Presentation]基于广义塑性的神经网络本构建模框架

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

基于广义塑性的神经网络本构建模框架

ID：147 Submission ID：195 View Protection：ATTENDEE Updated Time：2024-04-10 17:19:45 Hits：488 Poster Presentation

Start Time：Pending （Asia/Shanghai）

Duration：Pending

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

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Abstract

采用数据驱动的方法建立材料本构模型是一种新兴的本构建模范式，能够为颗粒材料力学性质的研究和数值计算提供新的途径，然而，纯粹的数据驱动建模方法缺少物理理论的支撑，得到的结果可能会违背物理法则。本研究结合了传统的广义塑性模型建模理论和神经网络建模方法，提出了一种基于广义塑性的神经网络本构建模框架。这一框架引入了一定的唯象假设，将材料的应力状态、一些包含历史信息的状态量、应变增量作为网络输入，将弹性参数、塑性流动方向、塑性模量作为网络的中间量，基于广义塑性理论得到应力增量作为网络的输出。训练完成后，该框架能够较容易地在通用有限元软件中实现，应用于边值问题求解。数值算例计算结果表明，该框架建立的模型能够再现原材料数据的力学响应特点。

Keywords

颗粒材料，数据驱动，神经网络，本构建模，广义塑性，边值问题

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