报告人:AssociateProf.YongmingLiu (刘永明副教授)，School for Engineering of Matter, Transport, and Engergy, Arizoan State University, USA(美国亚利桑那州立大学)

主持人：邓露教授

报告时间:2016年12月8日，上午10:00 - 11:30

报告地点:土木学院风洞楼会议室

主讲人简介：

刘永明副教授，1977年生于河北省邯郸市。1999年，毕业于同济大学土木工程学院建筑工程系，2002年获同济大学硕士学位，2006年获得美国范德比尔特大学（Vanderbilt University）博士学位。2007年起在美国克拉克森大学任助理教授，2012年起在美国亚利桑那州立大学任副教授。

主要研究方向为结构材料疲劳损伤分析、随即方法和可靠度理论，结构健康监测，和多尺度多物理场计算模拟。现为ASCE Journal of Bridge Engineering副主编，ASCE-ASME可靠度与风险分析杂志编委，发表国际期刊和会议论文150余篇，参与5本专业书籍撰写，主持多项美国自然科学基金，以及交通部、能源部和其他联邦部门资助的项目。

讲座摘要:

A generalmethodologyfor probabilistic fatigue damage diagnosis and prognosis for engineering structural materials, such as metallic and composite materials is presented. Themethodologyis based on the Bayesian inference of physics-basedmodellingandsensing measurements of various damage features using advanced instrumentation. The method is first demonstrated for aluminium materials under fatigue cyclic loading and crack growth-based life prediction model is used to predict the remaining useful life of the structural components. Following this, the stiffness degradation kinetic modelling and piezo-electric sensor-based in situ measurement is illustrated for carbon-reinforced composite materials. Next, some recent advancement on the multimodality sensing and imaging technique are discussed. Adjoint method-based inversion algorithm is used to reconstruct the high resolution damage imaging with limited sensors. SONIC infrared imaging, piezo sensor network imaging, and optoacoustic imaging technique are discussed with the help of the newly developed signal inversion technique. Numerical verifications are performed by various type of damage and property changes in metals and composites. Several conclusions and future work are drawn based on the proposed study.