Advanced coal gasifier designs using large-scale simulations

• Published in: Journal of physics. Conference series 2009-07, Vol.180 (1), p.012034
• Main Authors: Syamlal, M, Guenther, C, Gel, A, Pannala, S
• Format: Article
• Language: English
• Subjects: 01 COAL, LIGNITE, AND PEAT; ACCURACY; CHEMICAL REACTIONS; COAL; COMMUNICATIONS; COMPUTERS; DATA ANALYSIS; DESIGN; DISTRIBUTION; Gasification; High resolution; MULTIPHASE FLOW; Parallel processing; Physics; PROGRAMMING; Programming environments; QUEUES; Reacting flow; RESOLUTION; Simulation; Solids flow; SPATIAL RESOLUTION
• ISSN: 1742-6596; 1742-6588; 1742-6596
• DOI: 10.1088/1742-6596/180/1/012034

Porting of the legacy code MFIX to a high performance computer (HPC) and the use of high resolution simulations for the design of a coal gasifier are described here. MFIX is based on a continuum multiphase flow model that considers gas and solids to form interpenetrating continua. Low resolution simulations of a commercial scale gasifier with a validated MFIX model revealed interesting physical phenomena with implications on the gasifier design, which prompted the study reported here. To be predictive, the simulations need to model the spatiotemporal variations in gas and solids volume fractions, velocities, temperatures with any associated phase change and chemical reactions. These processes occur at various time- and length-scales requiring very high spatial resolution and large number of iterations with small time-steps. We were able to perform perhaps the largest known simulations of gas-solids reacting flows, providing detailed information about the gas-solids flow structure and the pressure, temperature and species distribution in the gasifier. One key finding is the new features of the coal jet trajectory revealed with the high spatial resolution, which provides information on the accuracy of the lower resolution simulations. Methodologies for effectively combining high and low resolution simulations for design studies must be developed. From a computational science perspective, we found that global communication has to be reduced to achieve scalability to 1000s of cores, hybrid parallelization is required to effectively utilize the multicore chips, and the wait time in the batch queue significantly increases the actual time-to-solution. From our experience, development is required in the following areas: efficient solvers for heterogeneous, massively parallel systems; data analysis tools to extract information from large data sets; and programming environments for easily porting legacy codes to HPC.