An Efficient Anti-Optimization Approach for Uncertainty Analysis in Composite Laminates

Abstract

This work presents an efficient approach to quantify uncertainties in composite laminates using the interval analysis, anti-optimization technique, and the α-cut procedure. The solutions are compared with the traditional and robust Monte Carlo method in 3 cases scenarios: natural frequencies, buckling, and strength safe factor. For natural frequencies and buckling loads, the presented Interval based methodology showed 2.5% to 4.5% larger error values when compared to the Monte Carlo method using the same number of function calls. This implies a larger uncertain area, and hence, a better solution. For the strength test using Tsai-Wu failure theory, the error values are even greater: 22% to 46%. A violation of the failure limit was detected by the proposed Interval based approach, but not detected by Monte Carlo method. The solutions show that the presented methodology yields a safer and more precise analysis when compared to the traditional Monte Carlo approach.