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Multiphase Models for CO2 Cleanup: Heat and Mass Transfer in Fluid-Particle Suspensions through Direct Numerical Simulation and Laser-Based Measurements

Multiphase Models for CO2 Cleanup: Heat and Mass Transfer in Fluid-Particle Suspensions through Direct Numerical Simulation and Laser-Based Measurements
二氧化碳净化的多相模型:通过直接数值模拟和基于激光的测量来研究流体颗粒悬浮液中的传热和传质
批准号:
1034307
负责人:
Shankar Subramaniam
金额:
$35.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-09-01 至 2015-08-31

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中文摘要
翻译
1034307 subramanian .要实现碳中性能源发电技术,如煤或生物质的化学循环燃烧,以及从发电厂的烟气中捕集二氧化碳,需要多相流传热传质的预测模型。最近对流动经过固定粒子集合的直接数值模拟(DNS)表明,目前使用的传热和传质模型不能准确地捕捉相关现象。为了解决这一缺点,本研究将结合DNS和激光测量速度场和标量场来研究流体-颗粒悬浮液中的传热和传质,从而改进流体-颗粒悬浮液流动模型。经过改进和验证的传热模型可用于工业评估和优化二氧化碳捕集流化床设计。知识优势:目前的双流体CFD模型中的传热传质模型尚未得到充分验证。具体来说,输运方程中的未知项没有被量化。本研究通过使用激光测量和DNS对这些未知术语进行量化来解决这一需求。这一新的认识将有助于改进流体-颗粒悬浮液中相间传热和传质的模型和模拟方法。这些模型的有效性将在立管流配置中得到验证。更广泛的影响:对传热和传质模型的改进将导致使用干吸附剂对化学循环燃烧和二氧化碳捕获的流化床进行更准确的模拟。这将使工程师能够快速评估所提出设计的可行性。该项目将利用各种机构外展计划来增加学生的参与,包括那些来自代表性不足群体的学生。
英文摘要
1034307SubramanianPredictive models for heat and mass transfer in multiphase flows are needed for implementing carbon-neutral energy-generation technologies such as chemical looping combustion with coal or biomass, and CO2 capture from the flue gas of power plants. Recent direct numerical simulations (DNS) of flow past fixed particle assemblies suggest that heat and mass transfer models currently in use do not accurately capture relevant phenomena. To address this shortcoming, this research will investigate heat and mass transfer in fluid-particle suspensions using a combination of DNS and laser measurements of velocity and scalar fields, resulting in improved models for fluid-particle suspension flows. The improved and validated models for heat transfer can then be used by industry to evaluate and optimize fluidized bed design for CO2 capture.Intellectual Merit: Current models for heat and mass transfer in two-fluid CFD models have not been fully validated. Specifically, unknown terms in the transport equations have not been quantified. This research addresses this need by quantifying these unknown terms using laser measurements and DNS. This new understanding will lead to improved models and simulation methodologies for interphase heat and mass transfer in fluid-particle suspensions. The validity of these models will be verified in a riser flow configuration. Broader Impacts: Improvements to heat and mass transfer models will result in more accurate simulation of fluidized beds for chemical looping combustion and CO2 capture using dry sorbents. This will enable engineers to rapidly evaluate the viability of proposed designs. The project will leverage various institutional outreach programs to increase participation of students including those from underrepresented groups.
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CDS&E: Collaborative Research: CDS&E: Advances in closure modeling for turbulent flows with finite-sized particles informed by massive simulations on heterogeneous architec
  • 批准号:
    1953298
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.21万
  • 财政年份:
    2020
  • 负责人:
    Shankar Subramaniam
  • 依托单位:
Collaborative Research: Bridging the gap between particle-scale thermal transport and device-scale predictions
  • 批准号:
    1905017
  • 项目类别:
    Standard Grant
  • 资助金额:
    $19.67万
  • 财政年份:
    2019
  • 负责人:
    Shankar Subramaniam
  • 依托单位:
Predictive Computational Tools for Biomass Fast Pyrolysis in Fluidized Bed Reactors using Particle-Resolved Direct Numerical Simulation of Reacting Gas-Solid Flow
  • 批准号:
    1336941
  • 项目类别:
    Standard Grant
  • 资助金额:
    $26.0万
  • 财政年份:
    2013
  • 负责人:
    Shankar Subramaniam
  • 依托单位:
Stability Limits for Gas-Solid Suspensions with Finite Fluid Inertia using Particle-Resolved Direct Numerical Simulations
  • 批准号:
    1134500
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.05万
  • 财政年份:
    2011
  • 负责人:
    Shankar Subramaniam
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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