Quantitative X-ray tomography of advanced polymer composites.

Advanced composite materials (ACMs) typically contain two or more constituents, such as matrix, fibers, and pores, with different physical and chemical characteristics. When combined, they produce a material with unique properties in terms of weight, strength, stiffness, or corrosion resistance. To inspect and study their 3D internal structure in a non-destructive way, the ACMs are imaged with X-rays, after which a 3D image is reconstructed from the X-ray radiographs, and further processed and analyzed in multiple sequential steps. This conventional workflow, however, suffers from inaccurate modeling and error propagation which severely limits the accuracy with which ACM parameters of interest can be estimated. In this project, we will develop a paradigm shifting approach in which the quantification of ACM parameters is substantially improved. This will be realized in a novel workflow by 1) accurately modelling all constituents of the ACM (matrix, pores, and fibers); 2) directly estimating the ACM model parameters from the X-ray radiographs, thereby preventing error propagation by providing a feedback mechanism; 3) analyzing the workflow's parameter space with respect to sensitivity and stability of parameters of interest. In this project, we develop methods that quantify ACM parameters, by targeting a new workflow for 1) accurately modeling all components of the ACM (matrix, pores and fibers); 2) estimating directly the parameters of the ACM model of the X-rays, thus preventing error propagation.

Keywords:FIBER REINFORCED POLYMERS, X-RAY IMAGING

Disciplines:Polymer composites, Modelling and simulation, Signal processing not elsewhere classified