Detailed design of shell-and-tube heat exchanger using intelligent evolutionary algorithms

doi:10.11949/0438-1157.20240761

CIESC Journal ›› 2025, Vol. 76 ›› Issue (1): 241-255.DOI: 10.11949/0438-1157.20240761

• Process system engineering • Previous Articles Next Articles

Detailed design of shell-and-tube heat exchanger using intelligent evolutionary algorithms

Haidong LI¹(), Qiqi ZHANG¹, Lu YANG¹, Naeem AKRAM², Chenglin CHANG¹(), Wenlong MO³^,⁴, Weifeng SHEN¹

^1.National－municipal Joint Engineering Laboratory for Chemical Process Intensification and Reaction, School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 401331, China
^2.School of Chemical Engineering, Minhaj University Lahore, Lahore 54000, Punjab, Pakistan
^3.State Key Laboratory of Carbon－based Energy Resource Chemistry and Utilization, Xinjiang Key Laboratory of Clean Coal Transformation and Chemical Process, College of Chemical Engineering, Xinjiang University, Urumqi 830017, Xinjiang, China
^4.Xinjiang Zhundong Coal High Value Diversified Engineering Technology Research Center，Xinjiang Yihua Chemical Company Limited, Changji 831100, Xinjiang, China

Received:2024-07-05 Revised:2024-08-02 Online:2025-02-08 Published:2025-01-25
Contact: Chenglin CHANG

采用智能进化算法的管壳式换热器详细设计

李海东¹(), 张奇琪¹, 杨路¹, AKRAM Naeem², 常承林¹(), 莫文龙³^,⁴, 申威峰¹

^1.重庆大学化学化工学院，化工过程强化与反应国家地方联合工程实验室，重庆 401331
^2.明哈吉大学拉合尔分校化工学院，巴基斯坦旁遮普拉合尔 54000
^3.新疆大学化工学院，省部共建碳基能源资源化学与利用国家重点实验室，煤炭清洁转化与化工过程新疆维吾尔自治区重点实验室，新疆乌鲁木齐 830017
^4.新疆宜化化工有限公司，新疆准东煤高值多元化工程技术研究中心，新疆昌吉 831100

通讯作者: 常承林
作者简介:李海东(2000—)，男，硕士研究生，202218021091@stu.cqu.edu.cn
基金资助:
新疆自治区区域协同创新专项科技援疆计划项目(2024E02036);中央高校基本科研业务费专项资金项目(2024CDJXY010);重庆市出站留（来）渝博士后择优资助项目(Z20240373);重庆市技术创新与应用发展重点专项项目(2024TIAD-KPX0168);国家自然科学基金项目(22008210)

Abstract

Abstract:

The shell heat exchanger is the most widely used calorie recovery equipment in the process of oil, chemical industry, etc., and its mathematical models are usually very complicated non-linear optimization problems. The existing commercial solution device and optimization algorithm have long computing time, and the computing time is long. It is difficult to converge and easily fall into part of the optimal problem. In order to address these challenges, this research draws inspiration from the manufacturing norms of shell-and-tube heat exchangers. It delineates the dimensions of the internal components of heat exchangers as discrete variables and formulates a mixed integer nonlinear programming model for the intricate design of shell-and-tube heat exchangers. The model aims to minimize heat transfer area, annual total cost, environmental impact factor, and maximize heat transfer efficiency. At the same time, enhancements have been made to the traditional intelligent evolutionary algorithm, which includes the genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm. This allows for the selection of design variables for the heat exchanger from a range of discrete values, eliminating the need for manual rounding of optimization results. Test results demonstrate that the enhanced intelligent evolutionary algorithm can achieve the optimal design solution within 1.0 s, reducing optimization time by over 99% compared to the global solver and enhancing optimization solution efficiency. Compared to the local solver, the enhanced intelligent evolution algorithm can achieve the global optimal solution, reduce heat transfer area by 15.4%—56.6%, lower annual total cost by 15.8%—77.8%, and guarantee design quality. Furthermore, multi-objective optimization is utilized to balance different objective functions, while sensitivity analysis results illustrate the impact of various design variables on the objective functions.

Key words: heat transfer, shell-and-tube heat exchanger, optimal design, intelligent evolutionary algorithm, multi-objective optimization

摘要：

管壳式换热器是石油、化工等过程工业中应用最广泛的热量回收设备，其数学模型通常是十分复杂的非线性优化问题，现有的商业求解器和优化算法存在运算时间长、收敛困难、易陷入局部最优等难题。针对这些难题，参考管壳式换热器制造标准，将换热器内构件尺寸定义成离散变量，分别以最小化换热面积、年度总费用、环境影响因子及最大化传热效率为目标函数，建立管壳式换热器详细设计的混合整数非线性规划模型。同时，对传统智能进化算法包括遗传算法、粒子群算法及模拟退火算法进行改进，使得换热器设计变量能够在一系列离散值中自由选择，不需要对优化结果进行人工圆整处理。案例测试结果表明，改进的智能进化算法能在1.0 s内得到最优设计方案，相对于全局求解器，优化时间节约99%以上，提高了优化求解效率；相对于局部求解器，改进的智能进化算法能够获取全局最优解，换热面积节约15.4%~56.6%，年度总费用节约 15.8%~77.8%，保证设计质量。通过多目标优化在不同目标函数之间进行权衡，通过灵敏度分析展示了不同设计变量对目标函数的影响趋势。

关键词: 传热, 管壳式换热器, 优化设计, 智能进化算法, 多目标优化

CLC Number:

TQ 051.5

Haidong LI, Qiqi ZHANG, Lu YANG, Naeem AKRAM, Chenglin CHANG, Wenlong MO, Weifeng SHEN. Detailed design of shell-and-tube heat exchanger using intelligent evolutionary algorithms[J]. CIESC Journal, 2025, 76(1): 241-255.

李海东, 张奇琪, 杨路, AKRAM Naeem, 常承林, 莫文龙, 申威峰. 采用智能进化算法的管壳式换热器详细设计[J]. 化工学报, 2025, 76(1): 241-255.

Figures/Tables 16

References 30

1	王杨君,邓先和,陈颖,等. 平行流分隔板管壳式换热器壳侧流场与传热性能[J].化工学报, 2004, 55(2): 275-279.
	Wang Y J, Deng X H, Chen Y, et al. Flow and heat transfer characteristics in shell side of shell-and-tube heat exchangers with separated baffles parallel to segmental baffles[J]. Journal of Chemical Industry and Engineering(China), 2004, 55(2): 275-279.
2	刘健鑫,崔汉国,代星,等. 换热器设计方案多级可拓综合评价[J]. 化工学报, 2011, 62(7): 1970-1976.
	Liu J X, Cui H G, Dai X, et al. Multilevel comprehensive evaluation for heat exchanger design schemes based on extension theory[J]. CIESC Journal, 2011, 62(7): 1970-1976.
3	黄兴华,王启杰,陆震. 管壳式换热器壳程流动和传热的三维数值模拟[J]. 化工学报, 2000, 51(3): 297-302.
	Huang X H, Wang Q J, Lu Z. Three-dimensional numerical simulation of shell flow and heat transfer in shell-and-tube heat exchangers [J]. Journal of Chemical Industry and Engineering(China), 2000, 51(3): 297-302.
4	邓斌, 陶文铨. 管壳式换热器壳侧湍流流动与换热的三维数值模拟[J]. 化工学报, 2004, 55(7): 1053-1059.
	Deng B, Tao W Q. Three-dimensional numerical simulation of turbulent flow and heat transfer characteristics in shell side of shell-and-tube heat exchangers[J]. Journal of Chemical Industry and Engineering(China), 2004, 55(7): 1053-1059.
5	吕明璐, 杨鑫, 张瑶, 等. 换热器的现状分析及分类应用[J]. 当代化工, 2018, 47(3): 582-584.
	Lyu M L, Yang X, Zhang Y, et al. Current situation analysis and classified application of heat exchangers[J]. Contemporary Chemical Industry, 2018, 47(3): 582-584.
6	肖武, 史朝霞, 姜晓滨, 等. 考虑管壳式换热器传热强化的换热网络综合研究进展[J]. 化工进展, 2018, 37(4): 1267.
	Xiao W, Shi Z X, Jiang X B, et al. Research progress on heat exchanger network considering heat transfer enhancement of shell-and-tube exchangers[J]. Chemical Industry and Engineering Progress, 2018, 37(4): 1267-1275.
7	古新, 宋帅, 张大波, 等. 一种双扭转流换热器壳程传热性能与机理分析[J]. 化工学报, 2021, 72(4): 1987-1997.
	Gu X, Song S, Zhang D B, et al. Analysis of heat transfer performance and mechanism of a double torsion flow heat exchanger[J]. CIESC Journal, 2021, 72(4): 1987-1997.
8	高正源, 张翔, 白佳龙, 等. 管壳式换热器折流部件优化研究进展[J]. 热能动力工程,2023, 38(7): 1-12.
	Gao Z Y, Zhang X, Bai J L, et al. Research progress of improvement of baffle components of shell and tube heat exchangers[J]. Journal of Engineering for Thermal Energy and Power, 2023, 38(7): 1-12.
9	宋立法, 董林峰. 管壳式换热器改进的思路措施及发展方向[J]. 设备管理与维修, 2023(18): 112-113.
	Song L F, Dong L F. Thoughts, measures and development direction of shell-and-tube heat exchanger improvement[J]. Plant Maintenance Engineering, 2023(18): 112-113.
10	王菁, 刘远凤, 田玲. 管壳式换热器计算机辅助设计与优化设计[J]. 新型工业化, 2022, 12(11): 239-242, 246.
	Wang J, Liu Y F, Tian L. Computer aided design and optimization design of shell-and-tube heat exchanger[J]. The Journal of New Industrialization, 2022, 12(11): 239-242, 246.
11	Osman Abuhalima, 张隽, 孙琳, 等. 换热网络综合中管壳式换热器设计研究进展[J]. 计算机与应用化学, 2015, 32(1): 9-14.
	Abuhalima O, Zhang J, Sun L, et al. Research advances in the design for shell-and-tube heat exchangers of heat exchanger networks[J]. Computers and Applied Chemistry, 2015, 32(1): 9-14.
12	Selbaş R, Kızılkan Ö, Reppich M. A new design approach for shell-and-tube heat exchangers using genetic algorithms from economic point of view[J]. Chemical Engineering and Processing: Process Intensification, 2006, 45(4): 268-275.
13	Hadidi A, Hadidi M, Nazari A. A new design approach for shell-and-tube heat exchangers using imperialist competitive algorithm (ICA) from economic point of view[J]. Energy Conversion and Management, 2013, 67: 66-74.
14	Patel V K, Rao R V. Design optimization of shell-and-tube heat exchanger using particle swarm optimization technique[J]. Applied Thermal Engineering, 2010, 30(11/12): 1417-1425.
15	de O Gonçalves C, Costa A L H, Bagajewicz M J. Shell and tube heat exchanger design using mixed-integer linear programming[J]. AIChE Journal, 2017, 63(6): 1907-1922.
16	钱颂文. 换热器设计手册[M]. 北京: 化学工业出版社, 2002.
	Qian S W. Heat Exchanger Design Manual[M]. Beijing: Chemical Industry Press, 2002.
17	Serna M, Jiménez A. A compact formulation of the Bell—Delaware method for heat exchanger design and optimization [J]. Chemical Engineering Research and Design, 2005, 83(5): 539-550.
18	Fettaka S, Thibault J, Gupta Y. Design of shell-and-tube heat exchangers using multiobjective optimization[J]. International Journal of Heat and Mass Transfer, 2013, 60: 343-354.
19	Ponce-Ortega J M, Serna-González M, Jiménez-Gutiérrez A. Use of genetic algorithms for the optimal design of shell-and-tube heat exchangers[J]. Applied Thermal Engineering, 2009, 29(2/3): 203-209.
20	Costa A L H, Queiroz E M. Design optimization of shell-and-tube heat exchangers[J]. Applied Thermal Engineering, 2008, 28(14/15): 1798-1805.
21	Onishi V C, Ravagnani M A S S, Caballero J A. Mathematical programming model for heat exchanger design through optimization of partial objectives[J]. Energy Conversion and Management, 2013, 74: 60-69.
22	de O Gonçalves C, Costa A L H, Bagajewicz M J. Linear method for the design of shell and tube heat exchangers using the Bell-Delaware method[J]. AIChE Journal, 2019, 65: e16602.
23	Lemos J C, Costa A L H, Bagajewicz M J. Set trimming procedure for the design optimization of shell and tube heat exchangers [J]. Industrial & Engineering Chemistry Research, 2020, 59(31): 14048-14054.
24	Mizutani F T, Pessoa F L P, Queiroz E M, et al. Mathematical programming model for heat-exchanger network synthesis including detailed heat-exchanger designs (2): Network synthesis[J]. Industrial & Engineering Chemistry Research, 2003, 42(17): 4019-4027.
25	Pavão L V, Costa C B B, Ravagnani M A S S, et al. Costs and environmental impacts multi-objective heat exchanger networks synthesis using a meta-heuristic approach[J]. Applied Energy, 2017, 203: 304-320.
26	Bakr M, Hegazi A A, Haikal A Y, et al. Genetic algorithm for the design and optimization of a shell and tube heat exchanger from a performance point of view[J]. International Journal of Electrical and Computer Engineering Systems, 2022, 13(7): 601-610.
27	Chang C L, Shen W F. Global optimization of the design of intensified shell and tube heat exchanger using tube inserts[J]. The Canadian Journal of Chemical Engineering, 2024, 102(1): 350-365.
28	李笠, 李广鹏, 常亮, 等. 约束进化算法及其应用研究综述[J]. 计算机科学,2021, 48(4): 1-13.
	Li L, Li G P, Chang L, et al. Survey of constrained evolutionary algorithms and their applications[J]. Computer Science, 2021, 48(4): 1-13.
29	冯茜, 李擎, 全威, 等. 多目标粒子群优化算法研究综述[J]. 工程科学学报, 2021, 43(6): 745-753.
	Feng Q, Li Q, Quan W, et al. Overview of multiobjective particle swarm optimization algorithm[J]. Chinese Journal of Engineering, 2021, 43(6): 745-753.
30	张九龙, 王晓峰, 芦磊, 等. 改进的模拟退火算法求解规则可满足性问题[J]. 现代电子技术, 2022, 45(5): 122-128.
	Zhang J L, Wang X F, Lu L, et al. Improved simulated annealing algorithm for regular satisfiability problem[J]. Modern Electronics Technique, 2022, 45(5): 122-128.

变量	取值
管外径/m	0.019, 0.025, 0.031, 0.038, 0.051
总管长/m	1.219, 1.829, 2.439, 3.049, 3.658, 4.877, 6.098
换热管间径比	1.25，1.33，1.50
换热管排布方式	正方形布局，三角形布局
管程数	1，2，4，6
挡板数	1，2，3，…，20
壳程直径 / m	0.787, 0.838, 0.889, 0.940, 0.991, 1.067, 1.143, 1.219, 1.372, 1.524

变量	取值
管外径/m	0.019, 0.025, 0.031, 0.038, 0.051
总管长/m	1.219, 1.829, 2.439, 3.049, 3.658, 4.877, 6.098
换热管间径比	1.25，1.33，1.50
换热管排布方式	正方形布局，三角形布局
管程数	1，2，4，6
挡板数	1，2，3，…，20
壳程直径 / m	0.787, 0.838, 0.889, 0.940, 0.991, 1.067, 1.143, 1.219, 1.372, 1.524

案例	最小化换热面积Area/m²					最小化年度总费用TAC/（10⁴ USD/a）
案例	DICOPT	BARON	GA	SA	PSO	DICOPT	BARON	GA	SA	PSO
案例1	NC	624.6	624.6	624.6	624.6	1.836	1.349	1.349	1.349	1.349
案例2	369.0	319.7	319.7	319.7	319.7	0.987	0.817	0.817	0.817	0.817
案例3	NC	199.3	199.3	199.3	199.3	0.862	0.529	0.529	0.529	0.529
案例4	NC	143.8	143.8	143.8	143.8	NC	0.558	0.558	0.558	0.558
案例5	385.0	332.1	332.1	332.1	332.1	0.905	0.781	0.781	0.781	0.781
案例6	325.0	207.6	207.6	207.6	207.6	0.843	0.592	0.592	0.592	0.592
案例7	995.0	915.2	915.2	915.2	915.2	2.558	1.889	1.889	1.889	1.889
案例8	367.0	287.5	287.5	287.5	287.5	0.999	0.799	0.799	0.799	0.799
案例9	NC	327.8	327.8	327.8	327.8	1.664	0.936	0.936	0.936	0.936

案例	最小化换热面积Area/m²					最小化年度总费用TAC/（10⁴ USD/a）
案例	DICOPT	BARON	GA	SA	PSO	DICOPT	BARON	GA	SA	PSO
案例1	NC	624.6	624.6	624.6	624.6	1.836	1.349	1.349	1.349	1.349
案例2	369.0	319.7	319.7	319.7	319.7	0.987	0.817	0.817	0.817	0.817
案例3	NC	199.3	199.3	199.3	199.3	0.862	0.529	0.529	0.529	0.529
案例4	NC	143.8	143.8	143.8	143.8	NC	0.558	0.558	0.558	0.558
案例5	385.0	332.1	332.1	332.1	332.1	0.905	0.781	0.781	0.781	0.781
案例6	325.0	207.6	207.6	207.6	207.6	0.843	0.592	0.592	0.592	0.592
案例7	995.0	915.2	915.2	915.2	915.2	2.558	1.889	1.889	1.889	1.889
案例8	367.0	287.5	287.5	287.5	287.5	0.999	0.799	0.799	0.799	0.799
案例9	NC	327.8	327.8	327.8	327.8	1.664	0.936	0.936	0.936	0.936

案例	最小环境影响因子EI/(10³ points/a)					最大传热效率ɛ
案例	DICOPT	BARON	GA	SA	PSO	DICOPT	BARON	GA	SA	PSO
案例1	NC	5.770	5.770	5.770	5.770	0.800	0.831	0.831	0.831	0.831
案例2	3.351	3.020	3.020	3.020	3.020	0.887	0.894	0.894	0.894	0.894
案例3	1.761	1.722	1.722	1.722	1.722	0.829	0.829	0.829	0.829	0.829
案例4	1.897	1.844	1.844	1.844	1.844	0.765	0.772	0.772	0.772	0.772
案例5	2.943	2.878	2.878	2.878	2.878	0.936	0.936	0.936	0.936	0.936
案例6	2.002	2.002	2.002	2.002	2.002	0.815	0.822	0.822	0.822	0.822
案例7	NC	8.340	8.340	8.340	8.340	NC	0.883	0.883	0.883	0.883
案例8	2.950	2.950	2.950	2.950	2.950	0.672	0.672	0.672	0.672	0.672
案例9	3.889	3.622	3.622	3.622	3.622	0.659	0.659	0.659	0.659	0.659

Detailed design of shell-and-tube heat exchanger using intelligent evolutionary algorithms

采用智能进化算法的管壳式换热器详细设计

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 16

References 30

Related Articles 15

Recommended Articles 0

Metrics

Comments

参数	案例8	案例9
管外径/m	0.025	0.019
总管长/m	4.877	6.098
换热管间径比	1.25	1.33
换热管排布方式	正三角形排布	正方形排布
管程数	2	4
挡板数	5	6
壳程直径 / m	1.143	1.067
换热器传热效率	0.476(0.474~0.648)	0.515(0.474~0.627)

输入参数	案例1		案例2		案例3		案例4
输入参数	原油	冷水	原油	冷水	甲醇	冷水	热水	甲醇
质量流量/(kg/s)	110.0	228.8	50.0	56.6	27.8	56.6	40.0	133.3
进口温度/℃	90	30	100	30	70	30	220.0	30.0
出口温度/℃	50	40	50	40	40	40	110.2	80.0
压降上限/kPa	100	100	60	50	70	100	70	70
质量密度/(kg/m³)	786	995	786	995	750	995	888	750
黏度/(mPa·s)	1.89	0.72	1.89	0.8	0.34	0.8	0.15	0.34
比定压热容/(J/(kg·K))	2177	4187	2177	4187	2840	4187	4312	284
热导率/(W/(m·K))	0.12	0.59	0.12	0.59	0.19	0.59	0.17	0.19
污垢系数/(m²·K/W)	0.0002	0.0004	0.0002	0.0003	0.0002	0.0002	0.0001	0.0001

输入参数	案例5		案例6		案例7		案例8		案例9
输入参数	乙醇	冷水	热水	蔗糖水	蔗糖水	冷水	乙醇	丙酮	乙醇	丙酮
质量流量/(kg/s)	55.6	295.0	40.0	133.3	83.3	358.3	111.1	166.7	111.1	166.7
进口温度/℃	150	30	220.0	30	90.0	30	190	30	190	30
出口温度/℃	60	40	80.8	80.0	40.0	40.0	120.0	79.7	120.0	79.7
压降上限/kPa	70	70	70	70	100	100	100	100	100	100
质量密度/(kg/m³)	789	995	888	1080	1080	995	789	736	789	736
黏度/(mPa·s)	0.67	0.80	0.15	1.30	1.30	0.80	0.67	0.21	0.67	0.21
比定压热容/(J/(kg·K))	2470	4187	4312	3601	3601	4187	2470	2320	2470	2320
热导率/(W/(m·K))	0.17	0.59	0.70	0.58	0.58	0.59	0.17	0.14	0.17	0.14
污垢系数/(m²·K/W)	0.0002	0.0004	0.0001	0.0001	0.0001	0.0004	0.0002	0.0002	0.0002	0.0002

Available scheme	Area/m²	TAC/(USD/a)	EI/(points/a)	ε
Ⅰ	309.38	19312.98	8041.44	0.473
Ⅱ	321.34	16799.88	6907.75	0.491
Ⅲ	405.50	10503.09	4082.60	0.487
Ⅳ	411.72	8716.09	3278.36	0.476

Available scheme	Area/m²	TAC/(USD/a)	EI/(points/a)	ε
Ⅰ	356.46	26660.45	11360.57	0.477
Ⅱ	388.28	18749.83	7798.38	0.486
Ⅲ	405.50	16814.57	6930.30	0.483
Ⅳ	448.13	13836.30	5602.66	0.490
Ⅴ	457.25	11526.50	4564.55	0.515

Available scheme	Case 8(Ranking)	Case 9(Ranking)
Ⅰ	0.3083(4)	0.3614(5)
Ⅱ	0.4434(3)	0.5610(4)
Ⅲ	0.6558(2)	0.6157(3)
Ⅳ	0.6908(1)	0.6124(2)
Ⅴ	—	0.6386(1)

[1]	Yushi LI, Yuan CHEN, Yuntang LI, Xudong PENG, Bingqing WANG, Xiaolu LI. Intelligent optimization and deformation analysis of novel flexible dam foil face gas seal [J]. CIESC Journal, 2025, 76(1): 324-334.
[2]	Hanbin WANG, Shuai HU, Fenglei BI, Junsen LI, Laibin HE. Desorption performance analysis of a metal hydride reactor with novel corrugated fins based on finite element method [J]. CIESC Journal, 2025, 76(1): 221-230.
[3]	Ye YANG, Jiangang LU. Mooney viscosity prediction modeling based on fusion Transformer [J]. CIESC Journal, 2025, 76(1): 266-282.
[4]	Han CHEN, Chang CAI, Hong LIU, Hongchao YIN. Experimental investigation on spray cooling heat transfer enhancement by n-pentanol additive [J]. CIESC Journal, 2025, 76(1): 131-140.
[5]	Ping LIU, Yusheng QIU, Shijing LI, Ruiqi SUN, Chen SHEN. Heat transfer and flow characteristics of nanofluids in microchannels [J]. CIESC Journal, 2025, 76(1): 184-197.
[6]	Xinyu DONG, Longfei BIAN, Yiyi YANG, Yuxuan ZHANG, Lu LIU, Teng WANG. Study on flow and heat transfer mechanism of supercritical CO₂ in inclined upward tube under cooling conditions [J]. CIESC Journal, 2024, 75(S1): 195-205.
[7]	Su TANG, Zi'ao ZHENG, Hanze WEI, Xiaoling XU, Xiaoqiang ZHAI. Preparation and thermal conductivity reinforcement of PMMA/PEG600/CNT composite shaped phase change materials [J]. CIESC Journal, 2024, 75(S1): 309-320.
[8]	Siyu QIN, Yijia LIU, Jiacheng YANG, Wei TONG, Liwen JIN, Xiangzhao MENG. Characteristics of gas-liquid two-phase heat transfer in a confined vapor chamber [J]. CIESC Journal, 2024, 75(S1): 47-55.
[9]	Jian HU, Jinghua JIANG, Shengjun FAN, Jianhao LIU, Haijiang ZOU, Wanlong CAI, Fenghao WANG. Research on heat extraction performance of deep U-type borehole heat exchanger [J]. CIESC Journal, 2024, 75(S1): 76-84.
[10]	Dehui DU, Wei FENG, Jianghui ZHANG, Yanlong XIANG, Gaopan QIAO, Wei LI. Prediction model of flow boiling heat transfer in microfinned hydrophobic composite enhanced tube [J]. CIESC Journal, 2024, 75(S1): 95-107.
[11]	Guanyu REN, Yifei ZHANG, Xinze LI, Wenjing DU. Numerical study on flow and heat transfer characteristics of airfoil printed circuit heat exchangers [J]. CIESC Journal, 2024, 75(S1): 108-117.
[12]	Xinze LI, Shuangxing ZHANG, Guanyu REN, Rui HONG, Wenjing DU. Thermal performance of pulsating heat pipe for high power LED thermal management [J]. CIESC Journal, 2024, 75(S1): 126-134.
[13]	Juhui CHEN, Tong SU, Dan LI, Liwei CHEN, Wensheng LYU, Fanqi MENG. Study on the heat transfer characteristics of microchannels under the action of fin-shaped spoilers [J]. CIESC Journal, 2024, 75(9): 3122-3132.
[14]	Chaowei CHEN, Yang LIU, Wenjing DU, Jinbo LI, Dakuo SHI, Gongming XIN. Flow and heat transfer characteristics of micro ribs channel with local hot spots [J]. CIESC Journal, 2024, 75(9): 3113-3121.
[15]	Ziliang ZHU, Shuang WANG, Yu'ang JIANG, Mei LIN, Qiuwang WANG. Solid-liquid phase change algorithm with Euler-Lagrange iteration [J]. CIESC Journal, 2024, 75(8): 2763-2776.