Parallel Genetic Algorithm for Shortest Path Routing Problem with Collaborative Neighbors

Shortest path routing is generally known as a kind of routing widely availed in computer networks nowadays. Although advantageous algorithms exist for finding the shortest path, however alternative methods may have their own supremacy. In this paper, parallel genetic algorithm for finding the shortest path routing is resorted to. In order to improve the computation time in this routing algorithm and to distribute the load balance between the processors as well, Fine-Grained parallel GA model is opted for. The proposed algorithm was simulated on Wraparound Mesh network topologies in different sizes. To this end, several experiments were anchored to identify the most influential parameters such as Migration rate, Mutation rate, and Crossover rate. The simulation result shows that best result of mutation rate is: about 0.02 and 0.03, and migration rate for transmission to the neighbor’s node is 3 of the best chromosomes. This study has already shown that through using performance-based GA which uses fine-grained parallel algorithms, timing germane shortest path routing can be improved

On the grain level deformation of BCC metals with crystal plasticity modeling:Application to an RPV steel and the effect of irradiation

Capturing realistic deformation behavior in BCC metals at the polycrystal scale is an important aspect of predicting the material’s strength and failure. Furthermore, local deformation/strength heterogeneity also influences the lifetime and its assessments in reactor pressure vessel (RPV) steels, especially with accumulating irradiation doses during long-term operational conditions. This work utilizes a micromorphic crystal plasticity (CP) model for BCC materials with the capability to address temperature-dependent stress–strain response and irradiation effects relevant to RPV materials. The microstructure of the investigated material was characterized prior to and during testing using electron microscopy experiments, which are used for finite element model generation and simulation result validation. To analyze the validity of the model to predict strain localization under monotonic tensile loading, micro digital image correlation (DIC) was employed jointly with the CP simulations. Different modeling choices, such as the use Schmid/non-Schmid laws and gradient based CP modeling, greatly affected the capability of the model to represent similar magnitudes in strain localization and grain reorientation. The requirement for experimental measurements, including image based analyses, on a microstructural level as a validation tool for CP modeling is clearly demonstrated