CAJ | 학술논문

介绍了文章提出的数据规范微结构模型(DCM)在确定材料孔隙及物相分布方面的应用.多光谱X光CT数据约束下的DCM模型,是一种南CPU计算效率的线性及非线性最优化途径.DCM模型的非线性最优化途径允许把对材料的前期了解或其他实验测试结果植入其中,从而使得对材料的微观结构表征更加精确.文章通过与油气资源相关的具体实例展示了DCM模型的应用.对材料组分三维分布的精确表征有助于更加准确地表征及计算包括渗透性在内的材料其他物理性质.
개소료문장제출적수거규범미결구모형(DCM)재학정재료공극급물상분포방면적응용.다광보X광CT수거약속하적DCM모형,시일충남CPU계산효솔적선성급비선성최우화도경.DCM모형적비선성최우화도경윤허파대재료적전기료해혹기타실험측시결과식입기중,종이사득대재료적미관결구표정경가정학.문장통과여유기자원상관적구체실례전시료DCM모형적응용.대재료조분삼유분포적정학표정유조우경가준학지표정급계산포괄삼투성재내적재료기타물이성질.
This paper outlines our data-constrained microstructure modelling (DCM) approach to determine microscopic distributions of pores (voids) and material phases.The DCM model incorporates multiple sets of X-ray computed-tomography (X-ray CT) data sets as constraints acquired at different X-ray beam energies.The DCM can be implemented either as a CPU efficient linear optimisation or a non-linear optimisation approaches.The nonlinear optimisation implementation allows integration of prior knowledge about the underlying system and other experimental observations which leads to elevated accuracy in microstructure characterisation.The DCM approach is demonstrated with examples related to hydrocarbon resources.The capability to characterise the 3D microscopic compositions of materials enables more accurate characterisation and computations of permeability and various other physical properties.