A new computational method for studying heat transfer in fluid bed reactors

Zongyan Zhou, Aibing Yu, Paul Zulli

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Effective thermal conductivity (ETC) is an important parameter describing the thermal behaviour of packed beds with a stagnant or dynamic fluid, and has been extensively examined in the past decades. Recently, an approach of coupled discrete particle simulation (DPS) and computational fluid dynamics (CFD) has been extended to predict the ETC, allowing the elucidation of the underlying heat transfer mechanisms at a particle scale. However, because of the sensitivity of heat transfer to particle-particle contact, a large Young s modulus and small time step have to be employed in the DPS to generate accurate results, resulting in a high computational cost. This paper proposed a method to overcome this problem. It is done by introducing a correction coefficient in the calculation of the particle-particle contact radius between colliding particles. The treatment is first implemented in our recent DPS-CFD modeling of the heat transfer in gas fluidization, and is validated by comparing the predicted ETC with literature data. The effects of model parameters, particle size, and bed average temperature on ETC are also analyzed.
Original languageEnglish
Pages (from-to)102 - 110
Number of pages9
JournalPowder Technology
Volume197
Issue number1-2
DOIs
Publication statusPublished - 2010
Externally publishedYes

Cite this

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title = "A new computational method for studying heat transfer in fluid bed reactors",
abstract = "Effective thermal conductivity (ETC) is an important parameter describing the thermal behaviour of packed beds with a stagnant or dynamic fluid, and has been extensively examined in the past decades. Recently, an approach of coupled discrete particle simulation (DPS) and computational fluid dynamics (CFD) has been extended to predict the ETC, allowing the elucidation of the underlying heat transfer mechanisms at a particle scale. However, because of the sensitivity of heat transfer to particle-particle contact, a large Young s modulus and small time step have to be employed in the DPS to generate accurate results, resulting in a high computational cost. This paper proposed a method to overcome this problem. It is done by introducing a correction coefficient in the calculation of the particle-particle contact radius between colliding particles. The treatment is first implemented in our recent DPS-CFD modeling of the heat transfer in gas fluidization, and is validated by comparing the predicted ETC with literature data. The effects of model parameters, particle size, and bed average temperature on ETC are also analyzed.",
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A new computational method for studying heat transfer in fluid bed reactors. / Zhou, Zongyan; Yu, Aibing; Zulli, Paul.

In: Powder Technology, Vol. 197, No. 1-2, 2010, p. 102 - 110.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - A new computational method for studying heat transfer in fluid bed reactors

AU - Zhou, Zongyan

AU - Yu, Aibing

AU - Zulli, Paul

PY - 2010

Y1 - 2010

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AB - Effective thermal conductivity (ETC) is an important parameter describing the thermal behaviour of packed beds with a stagnant or dynamic fluid, and has been extensively examined in the past decades. Recently, an approach of coupled discrete particle simulation (DPS) and computational fluid dynamics (CFD) has been extended to predict the ETC, allowing the elucidation of the underlying heat transfer mechanisms at a particle scale. However, because of the sensitivity of heat transfer to particle-particle contact, a large Young s modulus and small time step have to be employed in the DPS to generate accurate results, resulting in a high computational cost. This paper proposed a method to overcome this problem. It is done by introducing a correction coefficient in the calculation of the particle-particle contact radius between colliding particles. The treatment is first implemented in our recent DPS-CFD modeling of the heat transfer in gas fluidization, and is validated by comparing the predicted ETC with literature data. The effects of model parameters, particle size, and bed average temperature on ETC are also analyzed.

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