个人简介

李索，副教授、硕士生导师。长期从事计算焊接力学与结构完整性评价研究，主要包括焊接与增材制造过程的多物理场建模与仿真、残余应力与变形预测及调控，以及相关构件的疲劳与断裂分析和微小试样蠕变试验研究。主持全国重点实验室开放课题，参与日本核能重大专项和欧盟“地平线2020”计划等科研项目。发表学术论文20余篇。

基本信息

办公地点：北京航空航天大学沙河校区三号楼613

电子邮箱：lisuo@buaa.edu.cn

教育背景

重庆大学 材料科学与工程 工学博士 2017-2021

英国诺丁汉大学 机械工程 博士联合培养 2019-2020

重庆大学 材料科学与工程 工学硕士 2014-2017

华中科技大学 材料成型及控制工程 工学学士 2010-2014

工作经历

北京航空航天大学 机械工程及自动化学院 副教授 2026至今

日本原子能研究开发机构 核安全研究中心 博士后 2022-2026

研究方向

计算焊接力学

结构完整性评价

代表性学术论文（*为通讯作者）

1、Li S, Li J, Sun G, Deng D*. Modeling of welding residual stress in a dissimilar metal butt-welded joint between P92 ferritic steel and SUS304 austenitic stainless steel. Journal of Materials Research and Technology, 2023, 23: 4938-4954.

2、Li S, Hu L, Dai P, Bi T, Deng D*. Influence of the groove shape on welding residual stresses in P92/SUS304 dissimilar metal butt-welded joints. Journal of Manufacturing Processes, 2021, 66: 376-386.

3、Li S, Chen W, Hu L, Deng D*. Influence of strain hardening and annealing effect on the prediction of welding residual stresses in a thick-wall 316 stainless steel butt-welded pipe joint. Acta Metallurgica Sinica, 2021, 57(12): 1653-1666.

4、Li S, Purdy D, Brett S J, Deng D, Shibli A, Sun W*. Effect of indentation depth in impression creep test: Conversion relationships and correction functions. Materials at High Temperatures, 2021, 38 (5): 358-367.

5、Li S, Ren S, Zhang Y, Deng D*, Murakawa H. Numerical investigation of formation mechanism of welding residual stress in P92 steel multi-pass joints. Journal of Materials Processing Technology, 2017, 244: 240-252.

Profile

Suo Li, Ph.D.

Beihang University

School of Mechanical Engineering and Automation

lisuo@buaa.edu.cn

Biography

Suo Li is an associate professor in the School of Mechanical Engineering and Automation at Beihang University. He received his doctoral degree in Materials Science and Engineering from Chongqing University in 2021. Before joining Beihang University, he was a postdoctoral fellow at Japan Atomic Energy Agency.

His research focuses on physics-based modeling of advanced manufacturing processes, including additive manufacturing and welding, with particular emphasis on advancing computational welding mechanics to predict and mitigate residual stress and distortion, thereby supporting structural integrity assessment of critical components for aerospace and nuclear applications.

More details are available in his ORCID record: https://orcid.org/0000-0002-9742-367X