Dr. Xiaoping Du

Professor

Mechanical & Aerospace Engineering

 

Dr. Xiaoping Du - Title: Curators' Distinguished Teaching Professor of Mechanical Engineering - Research and Teaching Are: Design and Manufacturing. Dr. Du is currently an Assistant Professor in Mechanical Engineering at Missouri S&T. Dr. Du received Ph.D.s in Mechanical Engineering from the University of Illinois at Chicago in 2002 and from the Southwest Petroleum Institute in 1995. Dr. Du’s research interests include probabilistic/statistic methods in engineering design, reliability-based design, robust design, and design of experiments, model validation, design optimization and multidisciplinary design optimization, mechanism analysis, and synthesis, and petroleum machinery.

  • Reliability-Based Multidisciplinary Sys Design under Time-Dependent Uncertainty
  • Quantitative Reliability Prediction in Early Design Stages
  • Reliability Prediction for System Designs with Outsourced Components
  • Engineering Uncertainty Repository

Reliability-Based Multidisciplinary Sys Design under Time-Dependent Uncertainty


Reliability-Based Multidisciplinary Systems Design under Time-Dependent Uncertainty


Dr. Xiaoping Du Project 1


INVESTIGATORS

Xiaoping Du (dux@mst.edu, 573-341-7249)


FUNDING SOURCE
National Science Foundation


PROJECT DESCRIPTION
The objective of this award is to explore optimal ways to design high reliability into multidisciplinary systems under time-dependent uncertainty. Varying randomly over time, time-dependent uncertainty is the major factor that hinders the ability or reliability of a system to perform its intended function over its service period. This research aims to optimally reduce the effect of time-dependent uncertainty on the system reliability. To best address the challenges in multidisciplinary systems design, the developed methodologies will specifically account for complexities such as coupling between subsystems, nonlinearity of system responses, and expensive system simulations. This research will integrate methodologies of both multidisciplinary systems design and advanced time-dependent reliability analysis. The integration will accurately predict the time-to-failure distribution for a given set of design variables, hence allowing for a direct link between design variables and time-dependent system reliability. Then with multidisciplinary design optimization (MDO), optimal system designs can be automatically identified with desired system reliability and reduced cost.

If successful, the results of this research will impact broad areas of engineering design and will be applicable to wide engineering applications, ranging from large defense and civil systems to small integrated circuit systems. Beyond engineering design, potential areas that will benefit include energy, system engineering, operations research, management, and reliability engineering, where time-dependent probabilistic approaches play a vital role. The knowledge from this project will be transferred through seminars, conference presentations, and journal articles. The introduction of the research results into the classroom will also increase awareness of uncertainties and better foster engineering students' probabilistic skills.


PUBLICATIONS

  1. "Reliability Analysis with Monte Carlo Simulation and Dependent Kriging Predictions," Zhu, Z, Du, X., accepted by ASME Journal of Mechanical Design, 2016.
  2. "Uncertainty Quantification of Time-Dependent Reliability Analysis in the Presence of Parametric Uncertainty," ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B. Mechanical Engineering, 2(3), 031001-031001-9, 2016.
  3. "Reliability-Based Design Optimization under Stationary Stochastic Process Loads," Hu, Z., Du, X., Engineering Optimization, 48(8), 1296-1312, 2016.
  4. "Time-Dependent Reliability Analysis for Function Generation Mechanisms with Random Joint Clearances," Zhang, J., Du, X., Mechanism and Machine Theory, 92, 184-199, 2015.
  5. "A Random Field Approach to Reliability Analysis with Random and Interval Variables," Hu, Z., Du, X., ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B. Mechanical Engineering, 1(4), 041005-1 - 041005-11, 2015.
  6. "Mixed Efficient Global Optimization for Time-Dependent Reliability Analysis,” Hu, Z., Du, X., ASME Journal of Mechanical Design, 137(5), 051401-1 - 051401-9, 2015.
  7. "First Order Reliability Method for Time-Variant Problems Using Series Expansions," Hu, Z., Du, X., Structural and Multidisciplinary Optimization, 51(1), 1-21, 2015.
  8. "Reliability-Based Fatigue Life Investigation for A Medium-Scale Composite Hydrokinetic Turbineblade," Li, H., Hu, A., Chandrashekhara K., Du, X., and Mishra R., Ocean Engineering, 89(1), 230-242, 2014.
  9. "Robust Design for Multivariate Quality Characteristics Using Extreme Value Distribution," Yang, C., Du, X., ASME Journal of Mechanical Design, 136(10), 101405-1 - 101405-8, 2014.
  10. Time-Dependent Mechanism Reliability Analysis With Envelope Functions and First-Order Approximation," Du, X., ASME Journal of Mechanical Design, 136(8), 081010-1 - 081010-7, 2014.
  11. Robust Design with Imprecise Random Variables and Its Application in Hydrokinetic Turbine Optimization,” Hu, Z., Du, X., Kolekarb, N.S., and Banerjee, A., Engineering Optimization, 46(3), 393-419, 2014.
  12. Fatigue Reliability Analysis for Structures with Known Loading Trend,” Hu, Z., Du, X., Conrad, D., Twohy, R., and Walmsley, M., 50(1), 9-23, Structural and Multidisciplinary Optimization, 2014.
  13. "Lifetime Cost Optimization with Time-Dependent Reliability," Hu, Z., Du, X., Engineering Optimization, 46(10), 1389-1410, 2014.
  14. "Probabilistic Inverse Simulation and Its Application in Vehicle Accident Reconstruction," Zhang, X., Hu, Z., and Du, X., ASME Journal of Mechanical Design, 135(12), 121006-1 - 121006-10, 2013.
  15. A Sampling Approach to Extreme Values of Stochastic Processes for Reliability Analysis,” Hu, Z. and Du, X., ASME Journal of Mechanical Design, 135(7), 071003-1 – 071003-8, 2013.
  16. Time-Dependent Reliability Analysis with Joint Upcrossing Rates,” Hu, Z. and Du, X., Structural and Multidisciplinary Optimization, 48(5), 893-907, 2013.
  17. Inverse Simulation under Uncertainty by Optimization,” Du, X., ASME Computing and Information Science in Engineering, 13(2), 021005-1 - 021005-8, 2013.
  18. Simulation-Based Time-Dependent Reliability Analysis for Composite Hydrokinetic Turbine Blades,” Hu, Z. and Du, X., Structural and Multidisciplinary Optimization, 47(5), 765-781, 2013.
  19. First Order Reliability Method with Truncated Random Variables,” Du, X. and Hu, Z., ASME Journal of Mechanical Design, 134(9), 091005-1 - 091005-9, 2012.
  20. Reliability Analysis for Hydrokinetic Turbine Blades,” Hu, Z. and Du, X., Renewable Energy, 48, 251–262, 2012   
  21. Robust Design Optimization with Bivariate Quality Characteristics,” Du, X., Structural and Multidisciplinary Optimization, 46(2), 187-199, 2012.
  22. Reliability-Based Design Optimization with Dependent Interval Variables,” Du, X., International Journal for Numerical Methods in Engineering, 91(2), 218–228, 2012.
  23. Towards Time-Dependent Robustness Metrics,” Du, X., ASME Journal of Mechanical Design, 134(1), 011004-1 - 011004-8, 2012.
  24. Time-Dependent Probabilistic Synthesis for Function Generator Mechanisms,” Zhang, J., Wang, J., and Du, X., Mechanism and Machine Theory, 46(9), 1236-1250, 2011.
  25. Time-Dependent Reliability Analysis for Function Generator Mechanisms,” Zhang, J., Wang, J., and Du, X., ASME Journal of Mechanical Design, 133(3), 031005-1 - 031005-9, 2011.

Quantitative Reliability Prediction in Early Design Stages

Reliability Prediction for System Designs with Outsourced Components

Engineering Uncertainty Repository