Reliability-based Design Optimization

Reliability-based design optimization (RBDO) search for a design of consistent system performance regardless of various uncertain factors including material properties, loading conditions, geometry tolerances.

Sensor network design under uncertainty: Multifunctional structural materials possess attractive attributes that can be designed to realize smart system functionalities such as integrated sensing systems for failure diagnostics and prognostics. With the integrated sensing capabilities, real-time monitoring of potentially damaging structural responses becomes possible. However, due to various uncertainties introduced by structural material properties, manufacturing processes, as well as operating conditions, ensuring the robustness of sensing performance is of vital importance for smart sensing system development. This research presents a reliability-based robust design approach to develop piezoelectric materials based structural sensing systems for failure diagnostics and prognostics. In the proposed approach, a detectability measure is defined to evaluate the performance of any given sensing system, and the sensoring system design problem can be formulated to maximize the detectability for different failure modes by optimally allocating piezoelectric materials into a target structure. This formulation can be conveniently solved using reliability-based robust design framework to ensure design robustness while considering the uncertainties.

Piezoelectric sensor design for joint monitoring (left); Experimental verification (middle); Smart wireless transmitter for battery free monitoring (right)

RBDO for vibrational energy harvesting device: The power output of a vibration energy harvesting device is highly sensitive to uncertainties in materials, manufacturing, and operating conditions. In this research, we present a reliability-based design optimization (RBDO) study of vibration energy harvesters. RBDO is performed to find the optimum design that satisfies a target reliability on power generation, while accounting for uncertainty in material properties and geometric parameters, and compared to Deterministic optimization (DO) to show great performance of RBDO design.

Related recent papers:

A. T. Eshghi and S. Lee, “Adaptive Improved Response Surface Method for Reliability-Based Design Optimization,” Engineering Optimization, pp. 1-19, 2019 

M. Li, M. K. Sadoughi, C. Hu, Z. Hu, A. T. Eshghi, and S. Lee, “High-Dimensional Reliability-based Design Optimization Involving Highly Nonlinear Constraints and Computationally Expensive Simulations,” Journal of Mechanical Design, Vol. 141, No. 5, pp. 051402, 2019 

Sadoughi, Mohammad Kazem, et al. “A High-Dimensional Reliability Analysis Method for Simulation-Based Design Under Uncertainty.” Journal of Mechanical Design 140.7: 071401, 2018