RESEARCH

Engineering Design under Uncertainty

In this research area, the techniques of reliability analysis and design optimization are integrated to develop reliability-based design methodologies that offer probabilistic approaches to engineering design. Our research aims to develop theoretically sound, self-consistent, and computationally efficient methods to support engineering design under uncertainty.

Prognostics and health management (PHM)

Prognostics and health management (PHM) focuses on utilizing sensor signals acquired from an operating system to monitor the health and predict the remaining useful life of the system. This health information provides an advance warning of potential failures and a window of opportunity for implementing measures to avert these failures. Our research has been focused on three technical components of PHM: health sensing, health reasoning, and health prognostics.

Prognostics of Lithium-Ion Battery

To improve the reliability and safety of lithium-ion (Li-ion) battery, it is essential to develop effective PHM techniques that can be used to detect battery anomalies and prevent failures. Our research in this area has led to the development of onboard diagnostics and prognostics to determine degradation mechanisms and predict the lifetime of Li-ion battery.

Design for Resilience

Most of the existing design methods only design passive reliability into engineered systems without the consideration of failure prognostics and prevention. Our research on resilience-driven system design enables concurrent development of reliable system functions, and robust prognostics and timely prevention of system failures. The research will lead to a shift in the design paradigm from the conventional design for reliability to design for resilience.

Research Projects

  1. Simon Laflamme (PI) and Chao Hu (Co-PI), “RTML: Small: Collaborative: A programming model and platform architecture for real-time machine learning for sub-second systems,” National Science Foundation, 10/01/2019–09/30/2022. [ More Info ]
  2. Chao Hu (PI) and Gul Okudan Kremer (Co-PI), “Data-Driven Design Decision Support for Re-X of High-Value Components in Industrial and Agricultural Equipment,” Department of Energy through The Reducing EMbodied-Energy And Decreasing Emissions (REMADE) Institute, 09/25/2019–09/24/2020. [ More Info ]
  3. Chao Hu (PI), “Onboard Monitoring of Shaft Unbalance and Bearing Health (Phase 1),” Vermeer Corporation, 09/15/2019–03/15/2020.
  4. Chao Hu (PI), Matthew J. Darr (Co-PI), Simon Laflamme (Co-PI), and Carey E. Novak (Co-PI), “PFI-TT: Physics-based Deep Transfer Learning for Predictive Maintenance of Industrial and Agricultural Machinery,” National Science Foundation, 08/15/2019–08/14/2021. [ More Info ]
  5. Chao Hu (PI), “Deep Learning and IIoT Platform for Predictive Maintenance of Industrial Equipment,” State of Iowa Regents Innovation Fund, 08/01/2019–03/31/2020.
  6. Chao Hu (PI), “Intelligent Fault Diagnostics of Rolling-Element Bearings,” Grace Engineered Products and ISU, 01/15/2019–09/15/2019.
  7. Chao Hu (PI), “Reliability Analysis of Hydraulic Drive Systems,” Deere & Company, 01/01/2018 – 04/30/2019.
  8. Chao Hu (PI), “Validation of Computer Models for Engineering Systems with Multiple Dynamic Responses,” National Science Foundation I/UCRC, ISU Center for e-Design, 09/15/2017 – 09/14/2019.
  9. Chao Hu (PI), “Predictive Modeling with Automated Analytics for Intelligent Bearing Prognostics,” State of Iowa Regents Innovation Fund, 07/01/2017 – 05/31/2018.
  10. Chao Hu (PI) and Shan Hu (Co-PI), “Data-Driven Dynamic Reliability Assessment of Lithium-Ion Battery Considering Degradation Mechanisms,” National Science Foundation, 08/15/2016 – 07/31/2020. [ More Info ]
  11. Chao Hu (PI), “Efficient Reliability-based Design Optimization of Engineered Systems with Multiple Inter-Dependent Components,” National Science Foundation I/UCRC, ISU Center for e-Design, 08/15/2016 – 08/14/2018.
  12. Carbon Solutions Inc. (PI), Chao Hu (Co-PI), and Liangbin Hu from the University of Maryland, College Park (Co-PI), “Lifetime Prediction of Hybrid Energy Storage Devices in Operating and Storage Conditions,” US Army SBIR Phase II, 07/15/2016 – 07/13/2020.
  13. Chao Hu (PI), “Model Validation and Uncertainty Quantification of Medical Devices,” Medtronic, Inc., 06/01/2016 – 03/31/2018.
  14. Chao Hu (PI), “CRII: CPS: Designing Complex Cyber-Physical Systems for Failure Resilience,” National Science Foundation, 06/01/2016 – 05/31/2019. [NSF Computer Systems Research (CSR) Spotlight Project; More Info ]
  15. Chao Hu (PI), “On-Board Prediction of Remaining Useful Life of Lithium-Ion Battery,” Department of Transportation through Midwest Transportation Center (MTC), 03/01/2016–02/28/2017.

Sponsors

SRSL projects have been sponsored or supported by the following state agencies, federal government agencies, and companies.

DOT

Medtronic

 

 

carbon-solutions

 

 

 

us-army

edesign