Summit on Predictive Modeling of Ductile Failure; Austin, Texas; March 2-3, 2015
University Of Texas At Austin, Austin TX
Investigators
Abstract
Modeling of ductile fracture in structural materials has been a problem of longstanding interest in engineering. The assessment of the durability, reliability and failure of structures and structural components through crack growth relies critically on the ability to offer predictive solutions to these engineering problems through such modeling. The goal of the Summit is to bring together researchers in the area of predictive modeling of structural failure to assess the capabilities of state-of-the-art predictive modeling tools. Discussions will focus on the ability to generate blind predictions of failure; the results will be disseminated to the community through an open-access peer-reviewed journal article. The impact of this workshop lies in the generation of a group-based consensus on the open issues that remain in ductile failure modeling that can be used as a basis to guide future investments in failure modeling. Currently, ductile failure in structural materials is modeled through many different methods, incorporating various aspects of deformation and failure processes in models of the microscale response. The discussions at this Summit will be focused around blind predictions of response, made without prior knowledge of failure modes. The Challenge problem posed by the Sandia National Laboratories provides a vehicle for assessing the capabilities of the community to provide such solutions. In this Challenge, fourteen teams made predictions of the response and failure in a complex geometrical part, made of an important engineering alloy - Ti6Al4V - exhibiting complex constitutive behavior; these predictions will be compared to laboratory experiments from three independent laboratories. The discussions will focus on the capabilities of the different models in predicting ductile failure, and more importantly identify gaps in our modeling capability and provide directions/challenges for future research in this area. Participation is open to researchers who provided blind predictions and to interested researchers to participate as observers.
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