Predictive Computational Tools for Biomass Fast Pyrolysis in Fluidized Bed Reactors using Particle-Resolved Direct Numerical Simulation of Reacting Gas-Solid Flow

使用反应气固流的粒子分辨直接数值模拟实现流化床反应器中生物质快速热解的预测计算工具

• 批准号: 1336941
• 负责人: Shankar Subramaniam
• 金额: $ 26万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1336941&HistoricalAwards=false
• 关键词: Predictive; Computational; Tools; Biomass; Fast

1336941SubramaniamThe importance of sustainable energy generation from renewable sources that minimizes environmental impact is now globally recognized, and is a national priority. This project focuses on fundamental scientific understanding of reacting gas-solid flows that is needed to overcome technological barriers for the successful development of one such renewable energy source, namely, the production of biofuels. Predictive computational models of biomass fast pyrolysis are needed for large-scale production of biofuel using fluidized-bed reactors. State-of-the-art computational codes for fluidized-bed reactors use simplistic models for average reaction rates as well as heat and mass transfer correlations developed in the late 1970s, which recent research reveals are problematic. To address this shortcoming, high-fidelity direct numerical simulations will be used in this project to gain fundamental understanding of reacting gas-solid flow. This fundamental understanding will result in physics-based models that will be implemented into a popular open-source multi-fluid code MFIX. The improved and validated model for reacting gas-solid flow can be used by industry to evaluate and optimize fluidized-bed reactors for fast pyrolysis of biomass. These improvements will also result in more accurate simulation of fluidized beds for chemical looping combustion and CO2 capture using dry sorbents. The PI has coordinated a successful recruitment and retention program entitled Women in Mechanical Engineering, and both PIs will continue ongoing efforts to train graduate and undergraduate women and minority students as part of this research project.

1336941 Subramaniam可再生能源的可持续能源生产的重要性，最大限度地减少对环境的影响，现在是全球公认的，是一个国家的优先事项。该项目的重点是对反应气-固流动的基本科学认识，这是克服技术障碍成功开发一种可再生能源，即生产生物燃料所必需的。利用流化床反应器大规模生产生物质燃料需要生物质快速热解的预测计算模型。流化床反应器的最先进的计算代码使用的平均反应速率，以及在20世纪70年代后期开发的传热和传质的相关性，最近的研究表明是有问题的简单化模型。为了解决这个缺点，高保真直接数值模拟将在这个项目中使用，以获得反应气固流动的基本了解。这种基本的理解将导致基于物理的模型，这些模型将被实施到流行的开源多流体代码MFIX中。改进后的气固两相流模型可用于生物质快速热解流化床反应器的评价和优化。这些改进也将导致更准确的模拟流化床化学链燃烧和二氧化碳捕获使用干吸附剂。PI已经协调了一个成功的招聘和保留方案，题为妇女在机械工程，两个PI将继续努力培训研究生和本科生的妇女和少数民族学生作为这个研究项目的一部分。