Collaborative Research: Uncertainty Quantification and Model Validation in Thin-Walled Structures: A Probabilistic Paradigm for Advancing Analysis-Based Design

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This project will pursue research towards an advanced framework for nonlinear stability analysis of thin-walled structures taking into account the uncertainty associated with geometric imperfections. Thin-walled structures most commonly fail in buckling failure mode. Whether this buckling is benign or catastrophic depends, to a great extent, on the details of the structure, most importantly its geometric imperfections. The research aims at providing a leap towards uncertainty quantification and model validation in the analysis of thin-walled structures by devising a probabilistic paradigm that uses advanced uncertainty quantification techniques along with novel structural analysis methods. Methodologies for the characterization and representation of geometric uncertainties as well as probabilistic imperfection sensitivity analysis frameworks are proposed that have the potential to pave the way for a fully stochastic nonlinear analysis of thin-walled structures. The proposed techniques are complemented by experimental measurements of imperfections with high accuracy, and testing of imperfect members.If successful, the results of this research will transform how geometric imperfections are handled in advanced analysis-based design of thin-walled structures. Because of the very general and mathematics-driven nature of the stochastic approaches adopted in this project, the methodologies developed will be applicable to a wide variety of problems and will have potential impact across all science and engineering disciplines. Alongside graduate student mentoring, undergraduate research will be a focus of the efforts at both University of Massachusetts Dartmouth (UMD) and Johns Hopkins University (JHU). The involved undergraduates will be asked to share their experience with students at local high schools and a community college as well as students attending Freshman Summer Institute at UMD, in hopes that their success will be emulated by others. Also, in collaboration with programs that specifically target underrepresented groups, qualified students are invited to participate in research at both universities. In addition to academic dissemination through conferences and papers and providing all developed work as open source, the PIs will capitalize on their involvement in engineering committees (e.g. AISC, AISI etc.) to disseminate the findings outside of the academic community.