Rigorous quantification of porous microstructures exhibiting a wide variety of pore shapes, sizes, and their spatial distributions presents a significant challenge. In this work, novel data science approaches are used...
详细信息
Rigorous quantification of porous microstructures exhibiting a wide variety of pore shapes, sizes, and their spatial distributions presents a significant challenge. In this work, novel data science approaches are used to characterize the complex microstructures in porous membranes, and to extract the salient features at the pore-scale. Towards this goal, a microstructure generator is developed and utilized to create a large ensemble of porous structures covering a substantial range in measures of features such as the stretched pore shapes (geometrical anisotropy), porosity, specific surface, and pore sizes. Additionally, the morphology of real porous membranes are obtained experimentally by high resolution X-ray tomography. The statistical representations for the simulated and real membrane microstructures are calculated and compared rigorously using novel data science approaches that are based on principal component analyses of the 2-point spatial correlations. This approach allows an objective measure of the difference between any two selected microstructures. The versatility and benefits of this approach for the quantification of microstructures in porous membranes are demonstrated in this paper.
Wireless sensor networks (WSN) emerge at the center of the fast expanding Internet of Things (IoT) revolution, and hence increased research efforts are being directed towards its efficient deployment, optimization and...
详细信息
ISBN:
(纸本)9783319744391;9783319744384
Wireless sensor networks (WSN) emerge at the center of the fast expanding Internet of Things (IoT) revolution, and hence increased research efforts are being directed towards its efficient deployment, optimization and adaptive operation. Rapid deployment of WSN in an unknown open environment is a critical challenge that involves finding optimal locations for the network nodes to deliver optimally balanced sensing and communication services at the maximum possible coverage subject to complex mutual constraints. We address this challenge with a variant of the voronoi-based algorithm that leverages the converged movement towards voronoi cells' centers with the intelligent nodes' provisioning algorithm to deliver fully automated and autonomous WSN that rapidly self-deploys itself to any finite indoor environment without using any prior knowledge of the size and structure of the target space. Sequential provisioning supports realistic implementation that accounts for collision avoidance and mitigates the risk of wasteful over-deployment. The preliminary comparative simulation results carried out in a simplified environment indicate very fast convergence to the well balanced WSN at the fairly small deployment cost and thereby validate our model as a very promising compared to the previous approaches to WSN deployment.
Wireless networks have gained considerable popularity during recent years. Optimum deployment of sensors in wireless networks has turned into one of the most significant topics of this area. Extensive research has bee...
详细信息
暂无评论