Application Of Data-constrained Model And CT In Coal And Coal Product Characterization

Three-dimensional (3D) characterization of materials microstructure is very important in understanding their physical and chemical properties and for their application. X-ray CT imaging technology has become an important method for materials microscopic 3D structural characterization. Such characterization relies on the correlation between the CT image grey-scale and compositions of a material sample. Image threshold segmentation and dual-energy CT have been successfully used to establish this correlation for many materials. Despite the success of these two methods, partial volume effect is still one of the main factors that hinder applications of X-ray CT technology for materials with intrinsic spatial structures over 3 order of length-scale range.In China, coal is not only the primary energy source at present, but also the storage media and transport matrix of coal-bed methane (CBM). Knowledge of the microscopic structure of coal is required for understanding the transformation of the minerals during coal processing and the fluid transportation in coal matrix during ECBM (enhanced coalbed methane) process. Multiple-scale information of coal sample is important for understanding the chemical and physical properties of coal. Although a large body of efforts by the R&D community had been devoted to the application of CT in coal microstructure characterization, there still exist many unanswered questions. Firstly, it is not possible for sample size to go beyond 104 times of voxel size. Secondly, there are many sub-voxel-sized compositions (micro-pore or mineral) in coal. The partial volume effect makes it difficult to establish a unique correlationship between the CT image grey-scale and the composition.Coal liquefaction technique can not only realize the clean utilization of coal, but can also make up for the petroleum-based motor fuel shortage in our country. A large amount of coal liquefaction residue is generated in the process of coal liquefaction. The idle residue will cause damage to the environment, which still contains a significant fraction of high heat value components:heavy oil and asphalt. Understanding the spatial structure of residue compositions is useful for developing new method for residue recycle and improving coal liquefaction technology. Coal liquefaction residue contains more complex compositions than coal. Especially, the heavy oil, asphalt and coal matrix are all organic material, which have similar X-ray absorption properties. It is difficult to identify these compositions in CT slices using existing methods.One of the focuses of this thesis is on the determination of voxel partial volumes, which is one of the unresolved technical barriers in coal and coal direct liquefaction residue structure characterization. The problem is tackled using the data-constrained modelling method (DCM) with multiple-spectrum synchrotron-based X-ray CT. The methodology has been applied in microstructure characterization of coal and coal direct liquefaction product. Main conclusions of the thesis include the following:(1) The basic properties of a Yangquan coal sample are characterized. The compositions of the sample are classified into four groups based on their X-ray absorption characteristics. A data-constrained model of the sample has been established. Multiple-scale microstructure of the sample has been obtained using a data-constrained modelling (DCM) approach with multi-spectrum synchrotron-based X-ray CT. It has been demonstrated that the DCM enables incorporation of composition distributions whose size is smaller than the CT imaging resolution.(2) The microstructure of a coal sample is investigated by synchrotron-based multiple-energy X-ray CT at two different spatial resolutions. A data-constrained modeling (DCM) approach was used to quantitatively characterize the multi-scale compositional distributions at the two resolutions. In order to evaluate the reliability of the application of the DCM in coal microstructure multiple-scale characterization, the DCM results at different spatial resolutions have been compared each other. The comparisons indicate that DCM approach can account for compositions smaller than the X-ray CT voxel size with adequate accuracy. Using DCM, it is possible to characterize a relatively large coal sample at low spatial resolution with minimal loss of the effect due to sub-pixel fine length scale structures. With a higher image resolution, spatial distributions of compositions can be resolved more precisely. However, with the reduced spatial resolution, computational efficiency is improved.(3) The basic properties of a direct coal liquefaction residue sample have been characterized. The X-ray absorption properties of residue compositions were analyzed. A data-constrained modelling (DCM) approach with multi-spectrum synchrotron X-ray CT has been used to characterizing the microstructure of a direct coal liquefaction residue sample. The research shows that the DCM can identify the unconverted coal matrix, asphaltene and heavy oil. However, the asphaltene and heavy oil are difficult to be distinguished between each other by the DCM at present. The iron element existing in catalyst or pyrite/ pyrrhotite also can be detected in the CT slice by DCM.The approach of this thesis presented is a combination of synchrotron-based X-ray CT with statistical physics and mathematical programming. This constitute a new methodology for coal and coal related materials microstructure multiple-scale characterization. The X-ray source used in this thesis is the most advanced synchrotron radiation in China. The excellent monochromaticity effectively eliminate the beam hardening artifact which is common with lab-based CT equipment. The high light intensity of synchrotron-based X-ray shortens the experimental time, which diminish the error aroused by long exposure time. The DCM has effectively resolved the partial volume effect to some extent. At the same time, the methology presented in this thesis is helpful in gaining microscopic insight in relation to the production of CBM and the development of clean coal technology.