山地地形重气扩散模拟中湍流模型的选择  被引量:9

On how to choose the turbulence models of heavy gas dispersion for hill-shaped terrains

在线阅读下载全文

作  者:李剑峰[1] 刘茂[1] 王靖文[1] 

机构地区:[1]南开大学城市公共安全中心

出  处:《安全与环境学报》2008年第4期118-124,共7页Journal of Safety and Environment

基  金:“十一五”科技支撑计划项目(200603746006)

摘  要:针对类似开县井喷的毒气扩散事故,研究山地地形条件下如何合理选择湍流模型对重气扩散进行大范围数值模拟。在初始条件和边界条件相同条件下,采用密切值法对6个RANS模型(RSM、标准k-ε、RNGk-ε、可实现k-ε、标准k-ω和SSTk-ω)的计算结果进行多方案选择,同时参考模拟中所消耗的CPU时间,使选用的模型尽可能在"计算精度"和"计算时间"之间取得平衡。结果表明,对山地条件下的大范围毒气扩散事故的模拟,采用标准k-ε模型时可在"计算精度"和"计算时间"之间取得较好平衡。可见,对山地地形条件下大范围重气扩散的数值模拟宜采用标准k-ε模型。This article aims at presenting its authors' research results on how to choose heavy gas dispersion models for hill-shaped terrains when dealing with the poisonous gas diffusion accident similar to Kaixian Blowout. Though progress has been made in reasonably choosing the turbulence model to carry out the wide range numerical simulations, it remains a hard-nut how to choose the complicated tarbulence model. The key problem here to be solved is how to use the ANSYS Corporation' s Fluent as the simulation tool under the topographical condition of hill-shaped terrains. Also, it is necessary to solve the problem on how to do the multi-plan model selection under the same initial and boundary condition by applying the TOPSIS method to six RANS models' simulation provided by Fluent. As is well known, the selection model is aimed at gaining the balance between "the computation precision" and "the computing time" so long as it is possible. The data analysis results indicate that, in view of the topographical condition of hill-shaped large-sphere poisonous gas diffusion, a better balance can be obtained between "the computation precision" and "the computing time" by using the standard κ-ε model. Therefore, it is worthwhile to use the standard κ-ε model under the simulation of heavy gas dispersion for hill-shaped terrains.

关 键 词:工业灾害控制 山地地形 重气 湍流模型 环境风险分析 

分 类 号:K913.1[历史地理—人文地理学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象