首页> 外文学位 >OPERATION AND MODELING OF A PILOT-SCALE FLUIDIZED BED COAL GASIFIER (KENTUCKY, NEW MEXICO, NORTH CAROLINA, TEXAS, PEAT, LIGNITE).
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OPERATION AND MODELING OF A PILOT-SCALE FLUIDIZED BED COAL GASIFIER (KENTUCKY, NEW MEXICO, NORTH CAROLINA, TEXAS, PEAT, LIGNITE).

机译:中试流化床煤气化炉(肯塔基州,新墨西哥州,北卡罗来纳州,德克萨斯州,泥煤,褐煤)的操作和建模。

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摘要

A devolatilized Kentucky bituminous coal, a New Mexico subbituminous coal, a North Carolina peat, and a Texas lignite were gasified with steam and oxygen in a pilot-scale fluidized bed reactor. The reactor was operated at pressures of 570-840 kPa (80-120 psia), molar H(,2)O/C feed ratios of 0.6 to 1.9, and average bed temperatures of 795-1010(DEGREES)C (1460-1850(DEGREES)F). The coal feed rate ranged from 14 to 33 kg/hr (30-73 lb/hr). All reactor effluent streams were measured and analyzed, enabling performance of mass and energy balances and identification of potentially hazardous species.; Two main reactor models were developed to simulate the gasification reactor--a simple well-mixed model, and a two-phase bubbling bed model. The simple model assumes instantaneous devolatilization and combustion, and steam/carbon gasification and water gas shift reaction in a single perfectly mixed stage. The two-phase model takes the hydrodynamics of a fluidized bed into consideration, as it assumes the fluidized bed to consist of an incipiently fluidized emulsion phase and a solids-free bubble phase.; Both models were used to correlate data for the gasification of the Kentucky char and the New Mexico coal. In general, the agreement between model predictions and experimentally measured variables was excellent.
机译:将脱挥发分的肯塔基州烟煤,新墨西哥州次烟煤,北卡罗莱纳州的泥煤和德克萨斯州的褐煤在中试规模的流化床反应器中用蒸汽和氧气气化。反应器在570-840 kPa(80-120 psia)的压力,H(,2)O / C摩尔进料比为0.6至1.9,平均床温为795-1010(DEGREES)C(1460-1850)的条件下运行(学位)F)。煤的进料速度为14至33千克/小时(30-73磅/小时)。对所有反应堆流出物流进行了测量和分析,从而实现了质量和能量平衡,并确定了潜在的有害物质。开发了两个主要的反应器模型来模拟气化反应器-一个简单的均匀混合模型和一个两相鼓泡床模型。这个简单的模型假设瞬间脱挥发分和燃烧,以及蒸汽/碳气化和水煤气变换反应在一个完美的混合阶段中进行。两相模型考虑了流化床的流体动力学,因为它假定流化床由初期流化的乳液相和无固体的气泡相组成。两种模型都用于关联肯塔基煤焦和新墨西哥州煤的气化数据。通常,模型预测与实验测量变量之间的一致性非常好。

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