Flow Resistance Coefficient Identification of Chilled Water System Based on Multi-Objective Optimization and Experiment Validation

2014 ◽  
Author(s):  
Zhijian Hou ◽  
Ming Qu ◽  
Zhirui Wang
Keyword(s):  
Flow Rate ◽  
Air Conditioning ◽  
Optimization Problems ◽  
Water Flow Rate ◽  
Resistance Coefficient ◽  
Fundamental Parameter ◽  
Multi Objective Optimization ◽  
Air Conditioning System ◽  
Multi Objective ◽  
Terminal Unit

Hydraulic resistance coefficient (HRC) is a fundamental parameter that characterizes the hydraulic state of a water pipeline and significantly determines the efficiency of the water-transport process. To estimate HRC and diagnose hydraulic process fault in building air conditioning system, a novel method called multi-objective optimization (MBO) strategy was developed in the research effort. MBO is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. In this paper, first, the basic principle of the approach is presented. Then several experiments are conducted to identify the HRC in a real air conditioning system. And the water flow rate of each air handling terminal unit is estimated by the flow rate of primary pipe and identified HRC. The experiment results show that the model can accurately estimate HRCs. The HRCs of each pipe and terminal unit were obtained by the flow rate and the pressure difference of primary pipe without requiring geometric specifications, which is very convenient in real engineering application.

Flow Resistance Coefficient Identification of Chilled Water System Based on Multi-Objective Optimization and Experiment Validation

2014 ◽  
Vol 651-653 ◽  
pp. 742-746
Author(s):  
Zhi Jian Hou ◽  
Ming Qu ◽  
Zhi Rui Wang
Keyword(s):  
Flow Rate ◽  
Air Conditioning ◽  
Optimization Problems ◽  
Water Flow Rate ◽  
Resistance Coefficient ◽  
Fundamental Parameter ◽  
Multi Objective Optimization ◽  
Air Conditioning System ◽  
Multi Objective ◽  
Terminal Unit

Hydraulic resistance coefficient (HRC) is a fundamental parameter that characterizes the hydraulic state of a water pipeline and significantly determines the efficiency of the water-transport process. To estimate HRC and diagnose hydraulic process fault in building air conditioning system, a novel method called multi-objective optimization (MBO) strategy was developed in the research effort. MBO is concerned with mathematical optimization problems involving more than one objective function to be optimized simultaneously. In this paper, first, the basic principle of the approach is presented. Then several experiments are conducted to identify the HRC in a real air conditioning system. And the water flow rate of each air handling terminal unit is estimated by the flow rate of primary pipe and identified HRC. The experiment results show that the model can accurately estimate HRCs. The HRCs of each pipe and terminal unit were obtained by the flow rate and the pressure difference of primary pipe without requiring geometric specifications, which is very convenient in real engineering application.

Application of Genetic Algorithm in Hydraulic Calculation of Capillary Air-Conditioning System

2013 ◽  
Vol 291-294 ◽  
pp. 1884-1886
Author(s):  
Yong An Li ◽  
Xin Yang Cui ◽  
Xue Lai Liu ◽  
Chuan Yang Zhao ◽  
Zhi Xin Liu ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Air Conditioning ◽  
Optimization Problem ◽  
Optimal Solution ◽  
Frictional Resistance ◽  
Specific Model ◽  
Hydraulic Calculation ◽  
Multi Objective Optimization ◽  
Air Conditioning System ◽  
Multi Objective

This paper briefly introduced the design and operation features of capillary air conditioning system, put forward multi-objective optimization problem in hydraulic calculation process, using genetic algorithm to solve multi-objective optimization problem and established a capillary air-conditioning system hydraulic calculation model. The problems of hydraulic calculation were transformed into the problems of multi-objective optimization Pareto optimal solution using genetic algorithm (GA). And GA was applied to illustrate corresponding to specific model. The optimal specific frictional resistance under the different flow conditions was described here.

scholarly journals Theoretical Prediction of Optimum Chilled Water Distribution Configuration in Air Conditioning Terminal Unit

2019 ◽  
Vol 14 (2) ◽  
pp. 137-146
Author(s):  
Ahmed Abd Mohammed Saleh ◽  
Ali Reyadh Shabeeb
Keyword(s):  
Standard Deviation ◽  
Water Supply ◽  
Water Flow ◽  
Flow Rate ◽  
Air Conditioning ◽  
Water Flow Rate ◽  
Total Water ◽  
Terminal Unit ◽  
Chilled Water ◽  
Valve Opening

 The distribution of chilled water flow rate in terminal unit is a major factor used to evaluate the performance of central air conditioning unit. In this work, a theoretical chilled water distribution in the terminal units has been studied to predict the optimum heat performance of terminal unit. The central Air-conditioning unit model consists of cooling/ heating coil (three units), chilled water source (chiller), three-way and two-way valve with bypass, piping network, and pump. The term of optimization in terminal unit ingredient has two categories, the first is the uniform of the water flow rate representing in statically permanents standard deviation (minimum value) and the second category is the maximum heat transfer rate from all terminal units. The hydraulic and energy equations governing the performance of unit solved with the aid of FORTRAN code with considering the following parameters: total water flow rate, chilled water supply temperature, and variable valve opening. It was found that the optimum solution of three-way valve case at 8°C water supply temperature, 0.12 kg/s total water flow rate and valve opening order (valve 1: 100%, valve 2: 100% and valve 3: 75%) with total heat rate (987.92 Watt) and standard deviation (1.181E-3). Also, for the two-way valve case the results showed that the optimum condition at 8°C water supply temperature, 0.12 kg/s total water flow rate and valve opening order (valve 1: 75%, valve 2: 75% and valve 3: 50%) with total heat rate and standard deviation (717Watt) and (5.69E-4) respectively.

scholarly journals Multi-Objective Optimization and Scenario-based Robustness Analysis of the MoneyMaker Hip Pump

2018 ◽  
Author(s):  
Christopher McComb ◽  
Nathan G Johnson ◽  
Pablo S Santaeufemia ◽  
Brandon T Gorman ◽  
Brent Kolste ◽  
...  
Keyword(s):  
Water Flow ◽  
Flow Rate ◽  
Water Flow Rate ◽  
Robustness Analysis ◽  
Optimization Techniques ◽  
Great Success ◽  
Multi Objective Optimization ◽  
Pump Design ◽  
Multi Objective ◽  
Human Powered

Water-lifting technologies for irrigation have significant potential to increase agricultural yields and stimulate economic growth in rural areas of the developing world. Human-powered water pumps have been used with great success in this rapidly developing market. KickStart's MoneyMaker Hip Pump is a human-powered water pump with additional design features that make it lightweight and portable for use in remote fields in several countries throughout Africa. This work first applied numerical optimization techniques to the design of the MoneyMaker Hip Pump and offers further improvements to its design. Deterministic multi-objective optimization methods were employed to maximize the flow rate of the pump, maximize the pumping height of water, and minimize cost. Following optimization, the robustness of the optimized pump design was analyzed under several modified scenarios, including fouling of the hoses and a decrease in operator power due to fatigue or aging. The set of cost-optimized pump designs was then compared to a second set of optimal designs that was found using material volume as a simplified proxy for the cost objective function. Findings indicate that several technical improvements can be made to the current MoneyMaker Hip Pump design to reduce cost by up to 37% without affecting water flow rate, or increase water flow rate by up to 88% without increasing cost. The numerical model was validated through physical experimentation of the MoneyMaker Hip Pump, and design alterations to reduce cost were experimentally shown to maintain pump performance.

scholarly journals Multi-Objective Optimization of Energy Saving Control for Air Conditioning System in Data Center

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1474 ◽  
Author(s):  
Leehter Yao ◽  
Jin-Hao Huang
Keyword(s):  
Energy Saving ◽  
Air Temperature ◽  
Data Center ◽  
Air Conditioning ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Air Conditioning System ◽  
Multi Objective ◽  
Control Scheme ◽  
Energy Saving Control

A multi-objective optimization scheme is proposed to save energy for a data center air conditioning system (ACS). Since the air handling units (AHU) and chillers are the most energy consuming facilities, the proposed energy saving control scheme aims to maximize the saved energy for these two facilities. However, the rack intake air temperature tends to increase if the energy saving control scheme applied to AHU and chillers is conducted inappropriately. Both ACS energy consumption and rack intake air temperature stabilization are set as two objectives for multi-objective optimization. The non-dominated sorting genetic algorithm II (NSGA-II) is utilized to solve the multi-objective optimization problem. In order for the NSGA-II to evaluate fitness functions that are both the ACS total power consumption and AHU outlet cold air temperature deviations from a specified range, neural network models are utilized. Feedforward neural networks are utilized to learn the power consumption models for both chillers and AHUs as well as the AHU outlet cold air temperature based on the recorded data collected in the field. The effectiveness and efficiency of the proposed energy saving control scheme is verified through practical experiments conducted on a campus data center ACS.

Performance assessment and multi objective optimization of an Organic Rankine Cycle driven cooling air conditioning system

2019 ◽  
Vol 191 ◽  
pp. 13-30 ◽  
Author(s):  
Muhammad Tauseef Nasir ◽  
Muhammad Ansab Ali ◽  
Tariq S. Khan ◽  
Ebrahim Al-Hajri ◽  
Muhammad Bilal Kadri ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Air Conditioning ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Multi Objective Optimization ◽  
Air Conditioning System ◽  
Multi Objective ◽  
Cooling Air

Multi-objective optimization of the HVAC (heating, ventilation, and air conditioning) system performance

Energy ◽  
2015 ◽  
Vol 83 ◽  
pp. 294-306 ◽  
Author(s):  
Xiupeng Wei ◽  
Andrew Kusiak ◽  
Mingyang Li ◽  
Fan Tang ◽  
Yaohui Zeng
Keyword(s):  
System Performance ◽  
Air Conditioning ◽  
Multi Objective Optimization ◽  
Air Conditioning System ◽  
Multi Objective
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