In order to explore the thermal conductivity of the natural poly-mineral rock,numerical tests of rock models with randomly-distributed components were conducted and compared with each other.Elaborately designed Monte Carlo method was adopted to ingratiate the requirement of the random characteristics of grain size and the grains＇spatial distribution.This requirement was fulfilled by clustering the randomly generated unstructured tetrahedral elements in full three dimensions.Natural rocks are consisted of randomly distributed crystal particles or intergranular minerals.Our primary results verify that the thermal conductivity of the rock is strongly sensitive to the ingredients＇ volume fraction and their spatial distribution.Furthermore,we proved that,in order to reduce the measurement error to a reasonable range,the numerical specimen must be large enough or include sufficient number of mineral particles.Our numerical test results are in accordance with a variety of empirical formulas which are currently employed in petrology.
Recent rapid progress in cyberinfrastructure in geosciences is providing seismologists an enormous boost for addressing multi-physical phenomena of regional seismic activities. The inherent nature of their multi-scale properties, from temporal to spatial spaces, makes it inevitably to be solved using large-scale computations and distributed parallel data processing schemes. Under such circumstance, using the advanced numerical algorithms and unstructured mesh generation technologies become the obstacles for modern seismologists. The main objective of this paper is to present a framework, which includes a parallel finite element simulation and distributed data infrastructure, to address the novel algorithms, state-of-the-art modeling and their implementation in regional seismicgenic systems. We also discuss and implement this framework to analyze the strong earthquake evolution processes in the Sichuan-Yunnan region. This study is the key to long-term seismic risk by estimates, providing a platform for predictive large-scale numerical simulation modeling of regional earthquake activities.
