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Effect of An Image Resolution Change on the Effective Transport Coefficient of Heterogeneous Materials

机译:图像分辨率变化对异质材料有效传输系数的影响

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摘要

Electrochemical electrodes comprise multiple phenomena at different scales. Several works have tried to model such phenomena using statistical techniques. This paper proposes a novel process to work with reduced size images to reconstruct microstructures with the Simulated Annealing method. Later, using the Finite Volume Method, it is verified the effect of the image resolution on the effective transport coefficient (ETC). The method can be applied to synthetic images or images from the Scanning Electron Microscope. The first stage consists of obtaining the image of minimum size, which contains at least 98% of the statistical information of the original image, allowing an equivalent statistical study. The image size reduction was made by applying an iterative decimation over the image using the normalized coarseness to compare the amount of information contained at each step. Representative improvements, especially in processing time, are achieved by reducing the size of the reconstructed microstructures without affecting their statistical behavior. The process ends computing the conduction efficiency from the microstructures. The simulation results, obtained from two kinds of images from different materials, demonstrate the effectivity of the proposed approach. It is important to remark that the controlled decimation allows a reduction of the processor and memory use during the reconstruction and ETC computation of electrodes.
机译:电化学电极在不同尺度上包含多种现象。几项工作已尝试使用统计技术对此类现象进行建模。本文提出了一种新的过程,可以处理缩小尺寸的图像,从而通过模拟退火方法重建微观结构。后来,使用有限体积方法,验证了图像分辨率对有效传输系数(ETC)的影响。该方法可以应用于合成图像或来自扫描电子显微镜的图像。第一阶段包括获取最小尺寸的图像,该图像至少包含原始图像的统计信息的98%,从而可以进行等效的统计研究。通过使用归一化的粗糙度对图像进行迭代抽取来比较每个步骤中包含的信息量,可以减小图像尺寸。通过减小重建的微结构的尺寸而不影响其统计行为,可以实现代表性的改进,尤其是在处理时间方面。该过程结束于从微结构计算传导效率。从不同材料的两种图像获得的仿真结果证明了该方法的有效性。重要的是要指出,受控的抽取允许减少电极的重建和ETC计算期间的处理器和内存使用。

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