This award will support travel for ten U.S. participants to the U.S.-India Workshop: Forensic Engineering (FE) and Curriculum Development , National Institute of Technology at Tiruchirapalli (NIT-T), India, December 2010. The co-organizers of the 5-day activity are Professors Shen-en Chen, Department of Civil Engineering, University of North Carolina at Charlotte and C. Natarajan, Head of the Department of Civil Engineering, NIT-T. The objective of this workshop is to enhance performance and failure analysis of civil infrastructures and to promote bilateral collaborative research and curriculum development.
Intellectual Merit U.S. scholars will have the opportunity to work with Indian counterparts on developing new tools, methodologies, and investigative techniques for forensic engineering. While this field is not well developed in India, engineers at Indian institutions of higher learning have extensive practice performing forensic investigations. There will be a review of US and Indian forensic engineering practices plus an overview of advanced sensing techniques used in forensic work. US participants will have the opportunity to make site visits to Indian universities and to the Structural Engineering Research Center (SERC) in Chennai with the idea of seeding collaborations with Indian researchers. Particular attention will be given to developing new structural failure theories and design approaches leading to improved technical understanding.
Broader Impacts The proposed effort is aimed at developing a forensic engineering curriculum as well as collaborative research and education in forensic engineering. This includes the establishment of a UNC & NIT-T joint research laboratory and a centralized global data base of failed structures. Four US graduates and undergraduates will be participants and will have the opportunity to participate in an international research and culturally rich experience. The activity is expected to contribute to enhancing FE theory and practice, instrumentation development, and new methodologies for data synthesis and interpretation.
