Characterizing Physicochemical Evolution of Biomass Particles during Fast Pyrolysis Using High-Resolution Simulation

使用高分辨率模拟表征快速热解过程中生物质颗粒的物理化学演化

• 批准号: 2029861
• 负责人: Song-Charng Kong
• 金额: $ 34.77万
• 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: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2022-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2029861&HistoricalAwards=false
• 关键词: Characterizing; Physicochemical; Evolution; Biomass; Particles

Fast pyrolysis is a prominent technology in converting waste biomass to combustible gases and liquids; pyrolysis also occurs at the early stage of solid fuel combustion. Fast pyrolysis-derived liquid fuels are regarded as an economically feasible alternative to fossil fuels and some facilities for heat and power generation have been brought online in recent years. However, despite its promising potential, the development of fast pyrolysis has been hindered by the complexity of reactor conditions in biomass pyrolysis, and to date, methods capable of predicting the detailed processes are unavailable. The objectives of this project are to characterize accurately the behaviors of biomass particles and predict the product yields of a fast pyrolysis reactor by using high-fidelity numerical simulations. The proposed research activities will lead to advances in the fundamental science of biomass pyrolysis for energy applications. The educational activities are to engage K-12 science teachers in research in order to promote education on renewable energy. In the U.S., a significant number of K-12 science teachers have not majored in the physical sciences. The research training of K-12 science teachers can enrich their critical thinking and enable them to incorporate their new knowledge into their classroom teaching.The proposed research plan is to conduct high-resolution simulations of biomass fast pyrolysis and to derive submodels for use in engineering CFD codes. A novel simulation approach, one that combines the lattice Boltzmann method, discrete element method, chemical kinetics, and particle shrinkage modeling, will be employed to describe the physicochemical evolution of biomass particles. Computational results will be validated by experimental data. Based on the simulation results, a drag coefficient model will be derived and tested. This work will address several scientific topics of paramount importance to biomass pyrolysis: physicochemical changes of particles, particle-particle and gas-particle interactions, and effects of particle properties and operating conditions on the pyrolysis products. The underlying difficulty of designing and optimizing an efficient biomass reactor is the lack of fundamental understanding of particle behaviors under realistic conditions. This research will characterize intra-particle transport, flow fields smaller than particle size, chemical reactions, and evolutions of particle size and properties. The resulting open-source code can be used by the scientific community as a baseline tool for further advanced numerical study on the pyrolysis of solid particles, e.g., coal, wood chips, municipal solid waste, or polymer materials.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

快速热解是将废弃生物质转化为可燃气体和液体的重要技术;热解也发生在固体燃料燃烧的早期阶段。快速热解衍生的液体燃料被认为是经济上可行的化石燃料替代品，近年来，一些供热和发电设施已投入使用。然而，尽管其有前途的潜力，快速热解的发展一直受到生物质热解反应器条件的复杂性的阻碍，并且到目前为止，能够预测详细过程的方法是不可用的。本计画的目的是利用高逼真度的数值模拟，精确地描述生物质颗粒的行为，并预测快速热解反应器的产物产率。拟议的研究活动将导致生物质热解能源应用基础科学的进步。教育活动是让K-12科学教师参与研究，以促进可再生能源教育。在美国，相当多的K-12科学教师没有主修物理科学。K-12科学教师的研究培训可以丰富他们的批判性思维，使他们能够将他们的新知识融入到他们的课堂教学中。拟议的研究计划是进行高分辨率的生物质快速热解模拟，并推导出用于工程CFD代码的子模型。一种新的模拟方法，一个相结合的格子玻尔兹曼方法，离散元方法，化学动力学，颗粒收缩建模，将被用来描述生物质颗粒的物理化学演变。计算结果将通过实验数据进行验证。基于模拟结果，将推导和测试阻力系数模型。这项工作将解决几个科学主题的生物质热解至关重要的：物理化学变化的颗粒，颗粒-颗粒和气体-颗粒的相互作用，以及颗粒的性质和操作条件对热解产物的影响。设计和优化高效生物质反应器的潜在困难是缺乏对现实条件下颗粒行为的基本理解。这项研究将表征颗粒内传输，小于颗粒尺寸的流场，化学反应以及颗粒尺寸和性质的演变。由此产生的开源代码可以被科学界用作进一步对固体颗粒热解进行高级数值研究的基线工具，例如，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。