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multi-objective optimization of the refrigerant-direct convective-radiant cooling system considering the thermal and economic performances

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ENERGY AND BUILDINGS 2022年第0期254卷 111609-111609页

作者： Jiang, Tingting You, Shijun Wu, Zhangxiang Zhang, Huan Wang, Yaran Wei, Shen Tianjin Univ Sch Environm Sci & Engn Tianjin 300350 Peoples R China Tianjin Univ Minist Educ China Key Lab Efficient Utilizat Low & Medium Grade Ene Tianjin 300350 Peoples R China Univ Coll London UCL Bartlett Sch Sustainable Construct 1-19 Torrington Pl London WC1E 7HB England

The refrigerant-direct convective-radiant cooling (RCC) system is attracting widespread concern due to its advantages of good thermal comfort, high energy efficiency and simple structure. However, researches on thermal and economic optimization of this system are rare. In this study, a novel heuristic approach is proposed to optimize the aluminum column-wing type refrigerant-direct convective-radiant cooling (ACT-RCC) system, which adopts artificial neural network (ANN) integrated with multi-objective genetic algorithm (MOGA). The numerical and economic models of the ACT-RCC terminal are developed and the numerical model is validated by the experimental data. Besides, the ANN model is adopted to accelerate the prediction of the thermal and economic performances of this system. Results show that the training values of the ANN model are fitted well with simulated results and the ANN model can greatly improve the runtime in comparison with original numerical and economic models. Based on the heuristic optimization approach, the optimal structure of the ACT-RCC terminal is the copper pipe diameter with 8.7 mm, the copper pipe spacing with 25.5 mm and the rib height with 30.3 mm. Compared with the original structure, the cooling capacity of the improved ACT-RCC system is enhanced by 16.0% and the initial cost is reduced by 10.0%. The appearance area equals to the direct product of the length and width, and results show that the appearance area of the improved ACT-RCC terminal is decreased from 1.04 m(2) to 0.78 m(2). Therefore, the proposed heuristic approach provides guidance for improving the thermal and economic performances of the RCC systems. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Refrigerant-direct convective-radiant cooling system Thermal and economic optimization Artificial neural network multi-objective genetic algorithm

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Optimal Design of Intermittent Water Distribution Network Considering Network Resilience and Equity in Water Supply

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WATER 2023年第18期15卷 3265页

作者： Ramani, Katineni Rudraswamy, G. K. Umamahesh, Nanduri V. Natl Inst Technol Warangal Dept Civil Engn Hanamkonda 506004 Telangana India

In urban areas of developing countries, due to industrialization and population growth, water demand has been increasing significantly, thereby increasing stress on the existing water distribution systems (WDSs). Under these circumstances, maintaining equity in the allocation of water becomes a significant challenge. When building an intermittent water distribution system, it is important to provide a minimum level of supply that is acceptable as well as water supply equity. A non-dominated sorting genetic algorithm (NSGA-II) is employed for the optimal design of an intermittent water distribution network (WDN). Network resilience is taken as a measure of reliability (In), while the uniformity coefficient (CU) is taken as a measure of equity in the water supply. Maximizing network resilience, uniformity coefficient, and minimization of cost of the network are considered as the objectives in the multi-objective optimization model. Pressure-driven analysis (PDA) is used for the hydraulic simulation of the network. The NSGA-II model is applied and demonstrated over two water distribution networks taken from the literature. The results indicate that reliability and equity in WDNs can be accomplished to a reasonable extent with minimal cost.

关键词： water distribution networks intermittent supply uniformity coefficient network resilience reliability pressure driven analysis multi-objective genetic algorithm

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Space optimizing design of ecological constructions based on attribute hierarchy model

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ARABIAN JOURNAL OF GEOSCIENCES 2020年第19期13卷 1016-1016页

作者： Han, Xu Zhongyuan Univ Technol Sch Art & Design Zhengzhou 450000 Peoples R China

Aiming at the problem of low user satisfaction of traditional ecological building space optimization methods, this paper introduces attribute analytic hierarchy process (AHP) model to effectively improve the effect of ecological building space optimization. This paper constructs an index system for the optimal design of ecological building space, and divides it into target level, criterion level and space level. Using the attribute analytic hierarchy process (AHP) model to construct attribute judgment matrix and weight, the general evaluation model of ecological building space optimization design is obtained. In this paper, multi-objective genetic algorithm is used to collect the spatial information of ecological building and determine the specific value of each parameter of ecological building. It used octopus to optimize the calculation results of multiple fitness functions and realized the optimized design of ecological building space. The experimental results show that the proposed method can significantly improve the user satisfaction of ecological building space, and people's satisfaction of the three open spaces of the overhead fire fighting channel, the main building, and the arc wall enclosure space are 62.13 points, 43.93 points, and 52.55 points, respectively, which shows that the satisfaction of the sunken courtyard is the highest.

关键词： Analytic hierarchy Ecological construction space Spatial hierarchy Fitness function multi-objective genetic algorithm

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multi-objective optimization on structural parameters of torsional flow heat exchanger

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APPLIED THERMAL ENGINEERING 2019年 161卷 113831-000页

作者： Gu, Xin Wang, Tongtong Chen, Weijie Luo, Yuankun Tao, Zhilin Zhengzhou Univ Key Lab Proc Heat Transfer & Energy Saving Henan Zhengzhou 450002 Henan Peoples R China CNTC Zhengzhou Tobacco Res Inst Zhengzhou 450001 Henan Peoples R China

Torsional flow heat exchanger is a new type of shell-and-tube heat exchanger with high heat transfer efficiency and low flow resistance. In this paper, the holistic model of the torsional flow heat exchanger is established, and the pressure drop, heat transfer coefficient and thermal performance factor in the shell-side are numerically studied. In order to achieve a better heat transfer performance in a torsional flow heat exchanger, the multi objective structure optimization on the baffle was carried out by using the method of response surface optimization. The results show that the shell-side pressure drop is significantly affected by the angle and width of the baffle;however, for the heat transfer performance, such as the heat transfer coefficient, is mainly attributed to the inclination angle. Three parameters were fitted with the multi-objective genetic algorithm in Ansys, with which the heat transfer performance of the torsional heat exchanger is improved by the value of 15.17%. This study provides a novel method to estimate and optimize the structure of the shell-and-tube heat exchanger.

关键词： Shell-and-tube heat exchanger Torsional flow Structural parameter multi-objective genetic algorithm Response surface method Numerical simulation

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Sensitivity and stress analysis of serrated fin structure in plate-fin heat exchanger on cryogenic condition

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2019年 145卷 106013-000页

作者： Li, Ke Wen, Jian Yang, Huizhu Wang, Simin Li, Yanzhong Xi An Jiao Tong Univ Dept Refrigerat & Cryogen Engn Sch Energy & Power Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Chem Engn & Technol Dept Proc Equipment & Control Engn Xian 710049 Shaanxi Peoples R China Harbin Inst Technol Shenzhen Sch Mech Engn & Automat Ctr Microflows & Nanoflows Shenzhen 518055 Peoples R China

The effects and interaction effects of fin height, fin space, fin thickness and fin interrupted length on flow resistance, heat transfer and stress of plate fin heat exchanger (PFHE) on cryogenic condition are analyzed quantitatively, based on computational fluid dynamics (CFD), fluid structure interaction (FSI), response surface methodology (RSM) and sobol sensitivity analysis. The stress distribution in serrated fin structure shows that the large stress is mainly distributed in the regions of keen-edged geometric structure such as weld joint region and the region connecting two rows of fin. The sensitivity analysis results reveal that j factor is the most sensitive to fin interrupted length, and f factor and maximum stress are most sensitive to fin thickness. The sobol sensitivity analysis results show that, for j factor and maximum stress, it is sufficient to investigate the first-order sensitivity indices and high-order sensitivity is weak. For f factor, it is necessary to consider the second-order sensitivity, especially for fin space and fin thickness. Based on above analyses, by combining with multi-objective genetic algorithm (MOGA), the serrated fin structure is optimized from perspective of two objectives (maximizing JF factor and minimizing maximum stress) and three objectives (maximizing j factor, minimizing f factor and minimizing maximum stress). In general, the optimization results based on two objectives are more intuitive, and they offer a smaller solution space. An original point is optimized, the results reveal that, compared with original point, JF factor of optimized point 1 increases by 17.8% without changing maximum stress, while maximum stress of optimized point 2 decreases by 50.0% without changing JF factor.

关键词： Plate-fin heat exchanger Serrated fin Cryogenic condition Stress analysis Response surface multi-objective genetic algorithm Optimization

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The Spectral Optimization of a Commercializable multi-Channel LED Panel With Circadian Impact

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IEEE ACCESS 2020年 8卷 136498-136511页

作者： Saw, Yi Jiau Kalavally, Vineetha Tan, Chee Pin Monash Univ Malaysia Dept Elect & Comp Syst Engn Sch Engn & Intelligent Lighting Lab Bandar Sunway 47500 Malaysia Monash Univ Malaysia Dept Mechatron Engn Sch Engn & Adv Engn Platform Bandar Sunway 47500 Malaysia

There exists a need for the design of light emitting diode (LED) luminaires which can deliver both visual and non-visual benefits of light to humans. In this work, we introduce an optimization approach based on spectral shaping for a minimalistic and practical design of a circadian-tunable multi-channel luminaire which also outputs white light with high quality and luminous efficacy of radiation (LER). The spectral optimization approach utilizes multi-objective genetic algorithm to maximize circadian tunability, light quality and LER while minimizing the number of channels. Solution sets are constrained using the non-visual quality metric, Melanopic Efficacy of Luminous Radiation (MELR) from the Melanopic Equivalent Daylight Illuminance (MEDI) approach and the more stringent visual quality metric TM-30 in addition to conventional Color Rendering Index (CRI). By matching theoretically optimized LED parameters to commercially available LED parameters for commercialization purposes, we establish the maximum MELR tunability that is achievable with 4 and 5 LED channels and the resulting trade-off in efficacy and light quality. Based on the results and analysis in this work, we detail a spectral optimization approach to propel the field of indoor lighting towards human-centric lighting.

关键词： Optimization Light emitting diodes Lighting Visualization genetic algorithms Color Commercialization Circadian lighting human-centric lighting indoor lighting LED luminaire design melanopic equivalent daylight illuminance multi-objective genetic algorithm spectral optimization

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Thermal-Hydraulic Performance and Optimization of Tube Ellipticity in a Plate Fin-And-Tube Heat Exchanger

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JOURNAL OF ELECTRONIC PACKAGING 2019年第3期141卷 031008页

作者： Zhu, Hua Yang, Zhuo Khan, Tariq Amin Li, Wei Sun, Zhijian Du, Jincai Zhang, Zhengjiang Zhou, Jianxin Zhejiang Univ Dept Energy Engn Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Coinnovat Ctr Adv Aeroengine Dept Energy Engn Hangzhou 310027 Zhejiang Peoples R China NFC Inst Engn & Technol Dept Mech Engn PO Fertilizer ProjectKhanewal Rd Multan 60000 Pakistan Hangzhou Yuhu Technol Co Ltd Hangzhou 310027 Zhejiang Peoples R China

The flow field inside the heat exchangers is associated with maximum heat transfer and minimum pressure drop. Designing a heat exchanger and employing various techniques to enhance its overall performance has been widely investigated and is still an active research. The application of elliptic tube is an effective alternative to circular tube which can reduce the pressure drop significantly. In this study, numerical simulation and optimization of variable tube ellipticity is studied. The three-dimensional numerical analysis and a multi-objective genetic algorithm (MOGA) with surrogate modeling are performed. Tubes in staggered arrangement in fin-and-tube heat exchanger are investigated for combination of various elliptic ratios and Reynolds numbers. Results show that increasing elliptic ratio increases the friction factor due to increased flow blocking area, however, the effect on the Colburn factor is not significant. Moreover, tube with lower elliptic ratio followed by higher elliptic ratio tube has better thermal-hydraulic performance. To achieve the best overall performance, the Pareto optimal strategy is adopted for which the computational fluid dynamics (CFD) results, artificial neural network (ANN), and MOGA are combined. The tubes elliptic ratio and Reynolds number are the design variables. The objective functions include Colburn factor (j) and friction factor (f). The CFD results are input into ANN model. Once the ANN is computed, it is then used to estimate the model responses as a function of inputs. The final trained ANN is used to drive the MOGA to obtain the Pareto optimal solution. The optimal values of these parameters are finally presented.

关键词： fin-and-tube heat exchanger thermal-hydraulic performance CFD neural network multi-objective genetic algorithm

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multi-objective optimization of a dual mass flywheel with centrifugal pendulum vibration absorbers in a single-shaft parallel hybrid electric vehicle powertrain for torsional vibration reduction

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2022年 163卷 108152-108152页

作者： Lee, Hyung Joon Shim, Jae Kyung Korea Univ Dept Automot Convergence Engn Seoul 02841 South Korea Korea Univ Sch Mech Engn Seoul 02841 South Korea

This research deals with an optimization of a dual mass flywheel (DMF) with centrifugal pendulum vibration absorbers (CPVAs) used in a single-shaft parallel hybrid electric vehicle (HEV) powertrain for the reduction of the torsional vibration at the rotor of the electric motor and the total moment of inertia of the DMF and CPVAs. Unlike the previous studies, this research considers the overall behavior of an entire powertrain with an in-line four-cylinder engine and a five-speed automatic transmission for the optimization of the DMF with CPVAs. For this purpose, the multibody dynamics model of the HEV powertrain is constructed and used to analyze the transient response of the system for a given gas pressure map and acceleration condition of the vehicle. Then, a multi-objective genetic algorithm is applied to determine the Pareto optimal front that yields the design parameter values of the DMF and CPVAs effective in the torsional vibration reduction and inertia minimization. The result of the optimization is compared with the HEV powertrain system with a flywheel only, and shows that the vibrations transmitted to the motor are significantly reduced in all the solutions of the Pareto front. By using the method proposed in this research, various parameter combinations of the DMF and CPVAs can be considered in the early design process.

关键词： Dual mass flywheel (DMF) Single-shaft parallel hybrid electric vehicle (HEV) powertrain multibody dynamics Transient analysis multi-objective genetic algorithm Centrifugal pendulum vibration absorber (CPVA)

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Structural optimization of phase change material based heat exchanger for breathing air cooling

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APPLIED THERMAL ENGINEERING 2021年 191卷 116829-116829页

作者： Lv, You Huang, Yawen Duan, Qiyao Xiao, Jie Feng, Naiyi Zhu, Yuan Chen, Tinghan Zhou, Shaoxin Southern Univ Sci & Technol Sch Microelect Shenzhen 518055 Peoples R China Tsinghua Univ Tsinghua Berkeley Shenzhen Inst TBSI Shenzhen 518005 Peoples R China Southern Univ Sci & Technol Sch Innovat & Entrepreneurship Shenzhen 518055 Peoples R China Southern Univ Sci & Technol Key Lab Energy Convers & Storage Technol Minist Educ Shenzhen 518055 Peoples R China Southern Univ Sci & Technol Engn Res Ctr Integrated Circuits Next Generat Com Minist Educ Shenzhen 518055 Peoples R China Peking Univ Sch Life Sci Beijing 100871 Peoples R China Yantai Nanshan Univ Coll Engn Yantai 265713 Peoples R China

The enormous amount of heat in fires can bring the inhaled air temperature to an extremely high level, which is fatal to the civilians. However, conventional rescue respirators are unable to control the breathing air temperature. In our previous work, a phase change material-based heat exchanger has been designed to cool down the inlet air from 500 K to a breathable 313 K and sustaining for more than 20 min. As a part of wearable respirator, its wearing comfort must be considered by minimizing its pressure drop and keeping it lightweight. Hence, the design is modified by proposing a cooling module with twin heat exchangers and the structural design of the heat exchangers is optimized by response surface methodology and multi-objective genetic algorithm. The optimized design can offer the required cooling performance with up to 65% lower breathing resistance and 30% lighter weight, which is beneficial for the further applications.

关键词： Heat exchanger Breathing air cooling Structure optimization Response surface method multi-objective genetic algorithm

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Analysis of the effect of roughness and concentration of Fe₃O₄/water nanofluid on the boiling heat transfer using the artificial neural network: An experimental and numerical study

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INTERNATIONAL JOURNAL OF THERMAL SCIENCES 2021年 163卷 106863-106863页

作者： Peng, Yeping Ghahnaviyeh, Milad Boroumand Ahmad, Mohammad Nazir Abdollahi, Ali Bagherzadeh, Seyed Amin Azimy, Hamidreza Mosavi, Amirhosein Karimipour, Aliakbar Shenzhen Univ Coll Mech & Control Engn Guangdong Key Lab Electromagnet Control & Intelli Shenzhen 518060 Peoples R China Islamic Azad Univ Najafabad Branch Dept Mech Engn Najafabad Iran Univ Kebangsaan Malaysia Inst IR 4 0 Bangi 43600 Selangor Malaysia Ton Duc Thang Univ Environm Qual Atmospher Sci & Climate Change Res Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Environm & Labour Safety Ho Chi Minh City Vietnam Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam

Since experimental studies in the field of nanofluid pool boiling requires costly and time-consuming tests, numerical methods such as artificial neural networks with higher predictability and nonlinear features are suitable for prediction and modeling of problem parameters. In this paper, 180 pool boiling laboratory data of Fe3O4/water nanofluid are employed as datasets used for network training to determine the effect of different parameters of nanofluid pool boiling on Boiling Heat Transfer Coefficient (BHTC) and wall superheat. The concerned input parameters for the neural network include concentration, roughness, and heat flux, while the network outputs are the BHTC and wall superheat. Finally, it becomes clear that the trainbr training algorithm with the optimal quantity of 41 neurons within the hidden layer shows the best performance. In addition, the present model can accurately predict the BHTC and wall superheat with correlation coefficients (R) of 0.99936 and 0.9986 and the mean square error (mse) of 0.103 and 0.013, respectively. Also, given the optimization objectives considered in this research, including maximizing the heat transfer coefficient and minimizing the wall superheat in the nanofluid pool boiling process, the multi-objective genetic algorithm has been used to optimize the two objective functions concerned.

关键词： Artificial neural network multi-objective genetic algorithm Pool boiling Fe3O4/Water nanofluid BHTC Surface roughness

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