Integration of Parallelized Iowa RBDO (I-RBDO) Codes
|Principal Investigator:||K. K. Choi, University of Iowa, firstname.lastname@example.org|
|Student:||Liang Zhao, Nick Gaul, University of Iowa|
|Government:||David Lamb, David Gorsich, James Sheng, Bob Garcia, U.S. Army TARDEC|
|Industry:|| Ren-Jye Yang, Ford Motor Company
Dmitry Tanenko, General Dynamics Land Systems
This project began in 2010 and was completed by 2012.
The use of Reliability-Based Design Optimization (RBDO) by TARDEC is expected to improve future Army ground vehicle designs by reducing weight, increasing the average life of all parts subject to fatigue, increasing survivability against explosion, and decreasing the total lifecycle cost. After testing RBDO methods on the Stryker vehicle and the HMMWV, the method was judged by TARDEC to be an important tool. Thus, we developed and installed a parallelized software system that integrates the University of Iowa developed DRAW (durability analysis) and LS-DYNA codes on the TARDEC High Performance Computing (HPC) platform. A particular target of this effort was the integration of the technical developments made in the accompanying basic research project "System Reliability-Based Design Optimization with Associated Confidence Level under Simulation and Input Model Uncertainties".
As this code is general and easy to use, the project team seeks research collaboration with those who wish to add reliability to their analysis and RBDO design investigations. I-RBDO is general enough to support various engineering applications, such as sur vivability analysis, advanced & hybrid powertrain, robotics, electric power & on-board electrification, vehicle dynamic analysis, etc. Users simply need to wrap their application specific modeling and simulation codes in a batch executable code that reads design parameter and random variable values from an ASCII file generated by the I-RBDO code and writes response values (and sensitivities for sensitivity-based RBDO methods) to an ASCII file to be read by the code. Their application will be treated as a black box code.
We collaborated with TARDEC's survivability group to apply I-RBDO for reliability analysis of their underbody explosion analysis using LS-DYNA.
ALL of the basic research results obtained in this project (and complementary ARC project) were successfully integrated to develop a pre-commercial code I-RBDO. This code was delivered to the start-up company RAMDO Solutions, LLC, established by the PI and University of Iowa in August 2013 to commercialize I-RBDO. The commercialized product is called RAMDO (Reliability Analysis & Multidisciplinary Design Optimization).
- Hyunkyoo Cho, Sangjune Bae, K. K. Choi, David Lamb, Ren-Jye Yang, "An efficient variable screening method for effective surrogate models for reliability-based design optimization", Structural and Multidisciplinary Optimization, Volume 50, Issue 5, pp 717-738, November 2014. doi: 10.1007/s00158-014-1096-9
- Ikjin Lee, Jaekwan Shin, K. K. Choi, "Equivalent target probability of failure to convert high-reliability model to low-reliability model for efficiency of sampling-based RBDO", Structural and Multidisciplinary Optimization, Volume 48, Issue 2, pp 235-248, August 2013. doi: 10.1007/s00158-013-0905-x
- Liang Zhao; K. K. Choi; Ikjin Lee; David Gorsich, "Conservative Surrogate Model Using Weighted Kriging Variance for Sampling-Based RBDO", J. Mech. Des., 135(9):091003-091003-10, Paper No: MD-12-1356, 2013. doi: 10.1115/1.4024731
- Song, H., Choi, K.K., Lee, I., Zhao, L., and Gorsich, D., "Adaptive Virtual Support Vector Machine for Reliability Analysis of High-Dimensional Problems", Structural and Multidisciplinary Optimization, Volume 47, Issue 4, pp. 479-491, 2013. doi: 10.1007/s00158-012-0857-6
- Lee, I., Choi, K.K., Noh, Y., Lamb, D., "Comparison Study between Probabilistic and Possibilistic Methods for Problems under a Lack of Correlated Input Statistical Information", Structural and Multidisciplinary Optimization, Volume 47, Issue 2 , pp 175-189, 2013. doi:10.1007/s00158-012-0833-1