飞机客舱地板加热功率及送风温度的反向建模
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摘要
飞机客舱的热边界条件对于营造舒适的机舱环境至关重要。为营造舱内乘客足部区域的均温达到26°C,上身的均温达到24°C的舒适性环境温度,建立一种用于设计飞机客舱地板加热功率及送风温度的反向求解模型。该模型包含3个子模型:边界对流换热量的求解模型以及边界温度与边界辐射换热量的求解模型。将反向模型应用于一个三维飞机客舱算例和一个三维空腔试验台中,研究结果表明,该模型能有效地求解地板加热功率及送风温度。
Thermal boundary conditions in commercial airliner cabins are crucial for creating a comfortable cabin environment. In order to create a comfortable environment where the average temperature in the foot area of the passengers reaches 26 ℃ and the average temperature of upper body of the passenger reaches 24 ℃ in the cabin,this paper proposed a combined inverse model for designers to determine the total underfloor heating rates and the air-supply temperature in an aircraft cabin. This model contains three sub-models:(i)model for computation of the convective heat rates of the underfloor heaters,(ii)model for solution of underfloor heater's surface temperatures,and(iii)model for computation of the radiant heat rates.The above model was in a 3 D aircraft cabin computation example and a 3 D cavity test bench. The research results show that the proposed model can effectively determine the total underfloor heating rates and air-supply temperature,which are in good agreement with the measurement data.
Thermal boundary conditions in commercial airliner cabins are crucial for creating a comfortable cabin environment. In order to create a comfortable environment where the average temperature in the foot area of the passengers reaches 26 ℃ and the average temperature of upper body of the passenger reaches 24 ℃ in the cabin,this paper proposed a combined inverse model for designers to determine the total underfloor heating rates and the air-supply temperature in an aircraft cabin. This model contains three sub-models:(i)model for computation of the convective heat rates of the underfloor heaters,(ii)model for solution of underfloor heater's surface temperatures,and(iii)model for computation of the radiant heat rates.The above model was in a 3 D aircraft cabin computation example and a 3 D cavity test bench. The research results show that the proposed model can effectively determine the total underfloor heating rates and air-supply temperature,which are in good agreement with the measurement data.
引文
[1]Cui W,Ouyang Q,Zhu Y.Field study of thermal environment spatial distribution and passenger local thermal comfort in aircraft cabin[J].Building and Environment,2014(80):213-220.
[2]龚永奇,邓建,刘慎洋.蒸气压缩式飞机空调车除湿的改进研究[J].流体机械,2017,45(5):83-86.
[3]Hellwig R T.Local and overall thermal comfort in an aircraft cabin and their interrelations[J].Building and Environment,2011,46(5):1056-1064.
[4]The Boeing Company.A private communication[Z].2014.
[5]李鹏辉.大型商用客机舱内气流组织的研究[D].大连:大连理工大学,2010.
[6]Liu W,Chen Q.Optimal air distribution design in enclosed spaces using an adjoint method[J].Inverse Probl.Sci.Environ,2015(23):760-779.
[7]Xue Y,Zhai Z,Chen Q.Inverse prediction and optimization of flow control conditions for confined spaces using a CFD-based genetic algorithm[J].Building and Environment,2013:77-84.
[8]Zhai Z,Xue Y,Chen Q.Inverse design methods for indoor ventilation systems using CFD-based multiobjective genetic algorithm[J].Building Simulation,2014(7):661-669.
[9]Zhang T,You X.A simulation-based inverse design of preset aircraft cabin environment[J].Building and Environment,2014(82):20-26.
[10]Luchesi V M,Coelho R T.An inverse method to estimate the moving heat source in machining process[J].Applied Thermal Engineering,2012(45):64-78.
[11]Lei L,Xue Y,Zheng W,et al.An inverse method based on CFD to determine the temporal release rate of a heat source in indoor environments[J].Applied Thermal Engineering,2018(134):12-19.
[12]Reza P,Hassan D,Seyed H T.Solving an inverse heat conduction problem using genetic algorithm:Sequential and multi-core parallelization approach[J].Applied Mathematical Modelling,2014,38:1948-1958.
[13]Balázs C,Keith A W,Gyula G.Simultaneous estimation of temperature-dependent volumetric heat capacity and thermal conductivity functions via neural networks[J].International Journal of Heat and Mass Transfer,2014(68):1-13.
[14]Sasamoto T,Kato S,Zhang W.Control of indoor thermal environment based on concept of contribution ratio of indoor climate[J].Building Simulation,2010(3):263-278.
[15]Tikhonov A N,Arsenin V Y.Solutions of Ill-posed Problems[M].Halsted Press,Washington DC,1977.
[16]Hansen P C.Rank-deficient and discrete ill-posed problem:Numerical aspects of linear inversion[M].SIAM,Philadelphia,1997.
[2]龚永奇,邓建,刘慎洋.蒸气压缩式飞机空调车除湿的改进研究[J].流体机械,2017,45(5):83-86.
[3]Hellwig R T.Local and overall thermal comfort in an aircraft cabin and their interrelations[J].Building and Environment,2011,46(5):1056-1064.
[4]The Boeing Company.A private communication[Z].2014.
[5]李鹏辉.大型商用客机舱内气流组织的研究[D].大连:大连理工大学,2010.
[6]Liu W,Chen Q.Optimal air distribution design in enclosed spaces using an adjoint method[J].Inverse Probl.Sci.Environ,2015(23):760-779.
[7]Xue Y,Zhai Z,Chen Q.Inverse prediction and optimization of flow control conditions for confined spaces using a CFD-based genetic algorithm[J].Building and Environment,2013:77-84.
[8]Zhai Z,Xue Y,Chen Q.Inverse design methods for indoor ventilation systems using CFD-based multiobjective genetic algorithm[J].Building Simulation,2014(7):661-669.
[9]Zhang T,You X.A simulation-based inverse design of preset aircraft cabin environment[J].Building and Environment,2014(82):20-26.
[10]Luchesi V M,Coelho R T.An inverse method to estimate the moving heat source in machining process[J].Applied Thermal Engineering,2012(45):64-78.
[11]Lei L,Xue Y,Zheng W,et al.An inverse method based on CFD to determine the temporal release rate of a heat source in indoor environments[J].Applied Thermal Engineering,2018(134):12-19.
[12]Reza P,Hassan D,Seyed H T.Solving an inverse heat conduction problem using genetic algorithm:Sequential and multi-core parallelization approach[J].Applied Mathematical Modelling,2014,38:1948-1958.
[13]Balázs C,Keith A W,Gyula G.Simultaneous estimation of temperature-dependent volumetric heat capacity and thermal conductivity functions via neural networks[J].International Journal of Heat and Mass Transfer,2014(68):1-13.
[14]Sasamoto T,Kato S,Zhang W.Control of indoor thermal environment based on concept of contribution ratio of indoor climate[J].Building Simulation,2010(3):263-278.
[15]Tikhonov A N,Arsenin V Y.Solutions of Ill-posed Problems[M].Halsted Press,Washington DC,1977.
[16]Hansen P C.Rank-deficient and discrete ill-posed problem:Numerical aspects of linear inversion[M].SIAM,Philadelphia,1997.