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 handable可再生能源的可持续能源产生的重要性，从而使环境影响最小化的可再生能源现在已被全球认可，并且是国家的优先事项。该项目的重点是对反应气体固体流动的基本科学理解，这是为了克服技术障碍而成功地开发一种这样的可再生能源，即生产生物燃料的生产。生物量快速热解的预测计算模型是使用流化床反应器大规模生产生物燃料的。流化床反应堆的最新计算代码使用简单的模型来达到平均反应速率，以及1970年代后期开发的热量和传质相关性，最近的研究表明这是有问题的。为了解决这一缺点，将在该项目中使用高保真直接数值模拟，以获得对反应气体流动的基本理解。这种基本的理解将导致基于物理的模型，这些模型将被实现为流行的开源多流体代码MFIX。行业可以使用改进和经过验证的反应气体流量模型来评估和优化流化床反应器，以快速热解的生物质热解。这些改进还将导致更准确地模拟流化床，以使用干吸尘器捕获化学环燃烧和二氧化碳。 PI协调了一项成功的招聘和保留计划，名为《机械工程女性》，这两个PI将继续努力培训研究生和本科妇女和少数民族学生，作为该研究项目的一部分。