线性唯象传热定律下热驱动分离过程最优性能

黄炼; 查长松; 吴问鲍; 陈宪刚

您当前的位置：

首页 >

文章列表页 >

线性唯象传热定律下热驱动分离过程最优性能

更新时间：2025-12-10

- 线性唯象传热定律下热驱动分离过程最优性能
- CIESC Journal Issue 4, Pages: 994-999(2011)
- 作者机构：
  
  海军驻芜湖地区军事代表室,安徽,芜湖,241000
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：05 April 2011，
  
  Published：05 April 2011
- 稿件说明：
移动端阅览
黄炼, 查长松, 吴问鲍, et al. 线性唯象传热定律下热驱动分离过程最优性能[J]. CIESC Journal, 2011, (4): 994-999.
DOI：

黄炼, 查长松, 吴问鲍, et al. 线性唯象传热定律下热驱动分离过程最优性能[J]. CIESC Journal, 2011, (4): 994-999. DOI：

摘要

考虑传热和传质过程分别服从线性不可逆热力学中的线性唯象传热定律和线性传质定律，研究了热驱动分离过程的最小耗热量和最大生产率。得到了线性唯象传热定律下给定功率输出时的内可逆热机最大效率的解析解，导出了热驱动分离过程的最小耗热量和最大生产率的解析解

并将两种不同传热规律下的优化结果进行了比较，结果表明传热规律影响热驱动分离过程最优性能。本文的研究结果可用于估算热驱动分离过程的能量需求，对实际分离过程最优设计与运行具有一定指导意义。

Abstract

The minimum heat consumption and maximum productivity of a heat-driven separation process

in which the heat and mass transfer obey the linear phenomenological heat transfer law and linear mass transfer law in linear irreversible thermodynamics

is investigated.An analytical solution for the maximum efficiency of an endoreversible heat engine with the linear phenomenological heat transfer law for a given power output is obtained

and those of the minimum heat consumption and the maximum productivity of the heat-driven separation process are also obtained.The results with different heat transfer laws are compared.The results show that the heat transfer behavior has significant effects on the optimal performance of the heat-driven separation process.The results may be used to estimate the energy demand in a heat-driven separation process

and provide some theoretical guidelines for the optimal design and operation of practical separation processes.

关键词

Keywords

references

Views

167

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Methods of adaptive prediction and abnormal states traceability for sulphur content in flue gas desulfurization process

Study on dissolution kinetics of erythromycin thiocyanate

Corrosion health status assessment method for refining unit pipeline based on GLAE-MLP

Analysis of flow field characteristics and mixing performance of different SK-type static mixers

Physics-informed spatio-temporal graph convolutional network for fermentation processes

Related Author

No data

Related Institution

No data

⁰