The micro-structural characterization of composite materials uses X-ray tomography to collect information about the internal characteristics of the samples, in order to educate the researcher about their intrinsic properties. The raw tomographic data need to go through several steps of computational processing, starting with the elimination of noise and other artifacts. Given the extremely large datasets involved, the experience gained by the authors has shown that in some cases the required processing time is too long and therefore not easy for a materials scientist to interact with the program in order to define the most adequate computing parameters and the correct sequence of operations. This article describes a Problem Solving Environment (PSE) - a specific type of computational environment - called Tomo-GPU, dedicated specifically to the field of tomography, and targeted to run on a desktop computer equipped with one or more General Purpose Graphical Processing Units (GPGPU). The processing capabilities of GPUs allow, even with large volumes of data, execution times that are short enough to be compatible with an interactive use. Tomo-GPU is thus particularly suited to allow a non-specialist in Computer Science to define visual programs that specify a sequence of processing steps. The PSE also includes adequate visualization modules and the possibility of steering the computations through parameter changes. Test runs of Tomo-GPU are currently undertaken intent on the characterization of functionally graded particle-reinforced metal-matrix composites, through the analysis of tomographic data obtained both in the phase-contrast and the holotomographic modes.
|Number of pages||4|
|Journal||Ciência & Tecnologia dos Materiais|
|Publication status||Published - 2012|
- Functionally Graded Materials
- Metal-matrix composites
- Problem Solving Environments