Developed the Performance Measure Approach (PMA) in 1999. The paper received 582 citations in journal and conference papers.
Developed the Hybrid Mean Value Method (HMV) for RBDO in 2001. It received the 2001 ASME Black and Decker Best Paper Award at Pittsburg, PA. The paper received 426 citations in journal and conference papers.
Developed methods for efficient identification of feasible probabilistic constraints and fast reliability analysis using the condition of design closeness using HMV. The paper received the ISSMO-Springer Prize 2003.
Developed the Enriched Performance Measure Approach (PMA+) for the RBDO process in 2004. The paper received 191 citations in journal and conference papers.
Developed the Dimension Reduction Method (DRM) based RBDO for highly nonlinear systems. The paper received the ISSMO-Springer Prize 2007.
Developed input modeling methods for correlated input variables using copula for RBDO. The paper was a runner-up for the ISSMO-Springer Prize 2007.
The RBDO method was successfully demonstrated to provide an optimum design with approximately 20% reduction in weight, more than 10 times improved fatigue lives and 2-sigma reliable design of a U.S. Army Stryker A-arm in 2007.
Developed the Dynamic Kriging (DKG) method for surrogate models in sampling-based RBDO in 2010.
Demonstrated Iowa developed RBDO (I-RBDO) software at a workshop at the U.S. Army TARDEC in April 2011 with all attendees having successful hands-on experiences to solve example problems.
Developed an efficient variable screening method to mitigate the curse-of-dimensionality in surrogate models for RBDO in 2013.
With the success of I-RBDO, the team established a small start-up company, RAMDO Solutions, LLC, in fall 2013 to develop the commercial software Reliability Analysis & Multidisciplinary Design Optimization (RAMDO).
Developed the Confidence-Based RBDO (C-RBDO) method and Virtual Support Vector Machine (V-SVM) method for limited input data for input uncertainty modeling in 2014.
RAMDO Solutions successfully obtained an Army SBIR Phase I funding in May 2014 and Army SBIR Phase II funding in June 2015.