Global sensitivity analysis for fiber reinforced composite fiber path based on D-MORPH-HDMR algorithm

Abstract

This study presents a quantitative sensitivity analysis for the assessment of fiber reinforced composites (FRCs). Global sensitivity analysis (GSA) approach is based on the variance based method incorporating Random Sampling-High Dimensional Model Representation (RS-HDMR) expansion in which component functions are determined by diffeomorphic modulation under observable response preserving homotopy (D-MORPH) regression. The advantage of the D-MORPH regression lies in its capability to solve linear algebraic equations with a limited number of sample points. The main purpose is to investigate the influence of fiber path, regarded as the design variable, on the formability and structural performance of FRCs. Wherein, spring-back and load-carrying capacity are two meaningful problems to be addressed. Two typical FRCs are included that an L-shaped part with straight fiber path using autoclave manufacturing process and a variable stiffness composite cylindrical shell under pure bending. The work not only focuses on the ranking of design variables but also hopes to find out their interactions represented by the second order global sensitivity indexes. After being tested by three typical numerical functions, the GSA algorithm highlights that spring-back of FRC using autoclave manufacturing process is most sensitive to fiber orientation angles on plies close to the tool. And buckling performance of the VS cylinder is dominated by fiber orientation angles at compression/tension regions.