Microstructural analysis of neutron-irradiation induced changes in polyester fibre studied using EPMA

Electron microscopy is an important characterization technique for the study of textile fibre as it gives more information on fabric wear, nature of fibre fracture, chemical degradation, abrasion, fatigue and many others. Electron Probe Micro Analyzer (EPMA) micrographs of virgin and some neutron-irradiated samples (graphite coated) are discussed. The filament diameter, D, of virgin PET fibre obtained from EPMA study was 12.5 µn. The surface topography of single filament distinctly reveals the core and sheath parts of the filament. The core diameter of the virgin fibre was estimated to be 1.43 µm. The fibre irradiated at fluence 1 × 1012 n/cm2 shows radiation induced sphere like polymer balls or spherulites of diameter 2.27 µm in the expanded core region. Due to irradiation, the sheath area crosslinks with expanded core region, which may be responsible for increase of strength and hardness of the polymer materials. Moreover, the micrograph at 3000 X magnifications clearly shows that there is no preferred orientation of the polymer in any direction confirming the isotropic nature of the sample.Microstructural analysis of neutron-irradiation induced changes in polyester fibre studied using EPMA Biswajit Mallick1*, Ramesh Chandra Behera2, Simanchal Panigrahi1, Tanmaya Badapanda1, Biswanath Parija1, Banita Behera1, Manas Panigrahi1 and Madhumita Sarangi2 1Department of Physics, National Institute of Technology, Rourkela-769 008, Orissa, India 2Department of Metallurgical and Materials Engineering, National Institute of Technology, Rourkela-769 008, Orissa, India E-mail : [email protected] of Physics, National Institute of Technology, Rourkela-769 008, Orissa, India 2Department of Metallurgical and Materials Engineering, National Institute of Technology, Rourkela-769 008, Orissa, Indi

PERFORMANCE ANALYSIS OF TEST DATA GENERATION FOR PATH COVERAGE BASED TESTING USING THREE METAHEURISTIC ALGORITHMS

This paper discusses an approach to generate test data for path coverage based testing using Genetic Algorithms, Differential Evolution and Artificial Bee Colony optimization algorithms. Control flow graph and cyclomatic complexity of the example program has been used to find out the number of feasible paths present in the program and it is compared with the actual no of paths covered by the evolved test cases using those meta-heuristic algorithms. Genetic Algorithms, Artificial Bee Colony optimization and Differential Evolution are acting here as meta-heuristic search paradisms for path coverage based test data generation. Finally the performance of the test data generation using three meta-heuristic optimization algorithms are empirically evaluated and compared