飞机客舱地板供热温度—热流反正耦合模型及应用
发布时间：2018-08-12 13:59
【摘要】：飞机客舱合理的热边界条件是创建舱内舒适热环境的关键因素,是保证乘客舒适性的重要条件。据研究报道客舱内乘客上半身区域24℃C以及脚部区域26℃的温度分布是理想的热环境。鉴于此,根据该温度分布需设计出合理的飞机客舱送风温度及地板供热功率,发展基于反向求解原理的数学计算模型。根据指定的舱内温度分布不能直接确定热边界条件,可通过一个冗长的迭代、猜测、矫正过程获得合理的热边界条件,该方法虽然可行,但计算量庞大,工作效率低。为修正这个问题,有必要基于设计目标建立-种有效的“由果及因”的反向求解模型。本文采用温度贡献率(Contribution Ratio of Indoor Climate, CRI)方法将复杂的能量方程转换为简单形式的线性系统,基于边界对流换热量的温度贡献率与Tikhonov正则化方法相结合,应用计算流体动力学(Computational Fluid Dynamics, CFD)方法建立依据空间内数个目标离散温度求解所需的边界对流换热量的反问题数学模型。在稳态流场下,首先将边界对流换热量与空间内数个目标离散温度之间表示成因果关系的CRI矩阵,通过选定合适的Tikhonov正则化参数确定边界对流换热量。再以反模型计算得到的边界对流换热量作为正模型的已知信息,求解边界温度及边界辐射换热量。因此,所建立的飞机客舱地板供热温度-热流反正耦合模型包含一个反模型和两个正模型。CRI矩阵受测点温度数量及其分布位置的共同影响,且易于呈现病态特性。基于矩阵奇异值分解和矩阵特征值分解原理,本文提出一种分析温度测点数量与位置对温度-热流反正耦合模型计算结果影响的简单有效的评价方法,将矩阵条件数表述为矩阵特征值的函数(矩阵的最大特征值与最小特征值之比),以矩阵的最小条件数作为准则,应用该方法优选温度测点数量及其分布位置。本文搭建空腔实验平台以及选择真实飞机MD-82作为测试空间进行试验验证,用测试结果验证本文所建温度-热流反正耦合模型的实际可行性。基于二维空腔算例,应用本文提出的温度测点数量与位置对温度-热流反正耦合模型计算结果的评价方法对温度测点进行优选。以一排座三维飞机半舱模型(含三位乘客)形成的客舱环境为算例,对本文建立的温度-热流反正耦合模型以及温度测点数量与位置对温度-热流反正耦合模型计算结果的评价方法进行验证。研究结果表明,空腔实验台中两组实验工况以及MD-82客舱中实验工况的实测结果与温度-热流反正耦合模型的计算结果取得了良好一致,验证了温度-热流反正耦合模型在实际应用中具有可行性。通过二维空腔算例验证温度测点数量与位置对温度-热流反正耦合模型计算结果的评价方法,计算结果表明若选取的温度测点数量多于待求解的热边界数量时,CRJ矩阵将形成长方阵,而长方阵转换为方阵时,增大了原始矩阵的条件数,因此没有必要选取多于待求解热边界数量的温度测点。若选取的温度测点数量多于待求解的热边界数量,需应用矩阵特征值分解原理优选温度测点,由于一个温度测点对应CRI矩阵的一个特征值,因此应保留矩阵特征值远离零的温度测点。布置在空间内固体壁面附近的温度测点易于感知热边界条件所发生的变化,因此壁面附近是温度测点位置的理想选择。流动漩涡中温度测点彼此之间的温度很接近,应避开这样的位置。通过三维机舱算例验证求解热边界条件的温度-热流反正耦合模型,获得了合理的机舱送风温度以及地板供热总功率；应用温度测点数量与位置对温度-热流反正耦合模型计算结果的评价方法对温度测点进行优选后,计算精度得到了提高。
[Abstract]:Reasonable thermal boundary condition is the key factor to create comfortable thermal environment in the cabin and the important condition to ensure passenger comfort. It is reported that the temperature distribution of upper body area 24 C and foot area 26 C in the cabin is the ideal thermal environment. A mathematical calculation model based on the principle of inverse solution is developed for the air supply temperature and floor heating power. The thermal boundary conditions can not be determined directly according to the specified temperature distribution in the cabin. The reasonable thermal boundary conditions can be obtained through a lengthy iteration, guess and rectification process. Although the method is feasible, the calculation is huge and the work efficiency is low. In this paper, the complex energy equation is transformed into a simple linear system by the method of Contribution Ratio of Indoor Climate (CRI), and the temperature contribution rate based on the boundary convection heat transfer and Tikhonov positive are used. Combining the regularization method with the computational fluid dynamics (CFD) method, the inverse problem mathematical model of the boundary convection heat transfer is established by solving the discrete temperatures of several targets in space. The CRI matrix of the relation is used to determine the boundary convection heat transfer by choosing appropriate Tikhonov regularization parameters, and then the boundary convection heat transfer calculated by the inverse model is taken as the known information of the positive model to solve the boundary temperature and the boundary radiation heat transfer. An inverse model and two positive models are presented. The CRI matrix is affected by the number and distribution of temperature at the measured points, and is easy to be ill-conditioned. Based on the principle of matrix singular value decomposition and matrix eigenvalue decomposition, a simple method is proposed to analyze the influence of the number and location of temperature measurement points on the results of the temperature-heat flow inverse coupling model. An effective evaluation method is presented in which the matrix condition number is expressed as a function of the matrix eigenvalue (the ratio of the maximum eigenvalue to the minimum eigenvalue), and the minimum condition number of the matrix is taken as the criterion to optimize the number and distribution of temperature measurement points. The experimental results show that the proposed temperature-heat flow inverse coupling model is feasible. Based on a two-dimensional cavity example, the temperature measurement points are optimized by using the number and position of temperature measurement points proposed in this paper to evaluate the results of the temperature-heat flow inverse coupling model. Taking the cabin environment with three passengers as an example, the temperature-heat flow inverse coupling model established in this paper and the evaluation method of temperature-heat flow inverse coupling model based on the number and position of temperature measurement points are validated. The results show that the experimental conditions of two groups of cabin test bench and MD-82 cabin are measured. The results are in good agreement with the calculated results of the temperature-heat flow coupling model, which verifies the feasibility of the temperature-heat flow coupling model in practical application. When the number of temperature measurement points is more than the number of thermal boundary to be solved, the CRJ matrix will form a rectangular matrix, and when the rectangular matrix is transformed into a square matrix, the conditional number of the original matrix will be increased. Therefore, it is not necessary to select more temperature measurement points than the number of thermal boundary to be solved. Matrix eigenvalue decomposition principle is used to optimize the temperature measurement point. Since a temperature measurement point corresponds to an eigenvalue of the CRI matrix, the temperature measurement point whose eigenvalue is far from zero should be retained. The temperature-heat flow inverse coupling model for solving the thermal boundary conditions is verified by a three-dimensional engine room example, and the reasonable cabin air supply temperature and the total floor heating power are obtained. The temperature-heat flow inverse coupling model is applied to the temperature measurement points. The evaluation method of positive coupling model results is used to optimize the temperature measurement points, and the calculation accuracy is improved.
【学位授予单位】：大连理工大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：V245.34
本文编号：2179272
[Abstract]:Reasonable thermal boundary condition is the key factor to create comfortable thermal environment in the cabin and the important condition to ensure passenger comfort. It is reported that the temperature distribution of upper body area 24 C and foot area 26 C in the cabin is the ideal thermal environment. A mathematical calculation model based on the principle of inverse solution is developed for the air supply temperature and floor heating power. The thermal boundary conditions can not be determined directly according to the specified temperature distribution in the cabin. The reasonable thermal boundary conditions can be obtained through a lengthy iteration, guess and rectification process. Although the method is feasible, the calculation is huge and the work efficiency is low. In this paper, the complex energy equation is transformed into a simple linear system by the method of Contribution Ratio of Indoor Climate (CRI), and the temperature contribution rate based on the boundary convection heat transfer and Tikhonov positive are used. Combining the regularization method with the computational fluid dynamics (CFD) method, the inverse problem mathematical model of the boundary convection heat transfer is established by solving the discrete temperatures of several targets in space. The CRI matrix of the relation is used to determine the boundary convection heat transfer by choosing appropriate Tikhonov regularization parameters, and then the boundary convection heat transfer calculated by the inverse model is taken as the known information of the positive model to solve the boundary temperature and the boundary radiation heat transfer. An inverse model and two positive models are presented. The CRI matrix is affected by the number and distribution of temperature at the measured points, and is easy to be ill-conditioned. Based on the principle of matrix singular value decomposition and matrix eigenvalue decomposition, a simple method is proposed to analyze the influence of the number and location of temperature measurement points on the results of the temperature-heat flow inverse coupling model. An effective evaluation method is presented in which the matrix condition number is expressed as a function of the matrix eigenvalue (the ratio of the maximum eigenvalue to the minimum eigenvalue), and the minimum condition number of the matrix is taken as the criterion to optimize the number and distribution of temperature measurement points. The experimental results show that the proposed temperature-heat flow inverse coupling model is feasible. Based on a two-dimensional cavity example, the temperature measurement points are optimized by using the number and position of temperature measurement points proposed in this paper to evaluate the results of the temperature-heat flow inverse coupling model. Taking the cabin environment with three passengers as an example, the temperature-heat flow inverse coupling model established in this paper and the evaluation method of temperature-heat flow inverse coupling model based on the number and position of temperature measurement points are validated. The results show that the experimental conditions of two groups of cabin test bench and MD-82 cabin are measured. The results are in good agreement with the calculated results of the temperature-heat flow coupling model, which verifies the feasibility of the temperature-heat flow coupling model in practical application. When the number of temperature measurement points is more than the number of thermal boundary to be solved, the CRJ matrix will form a rectangular matrix, and when the rectangular matrix is transformed into a square matrix, the conditional number of the original matrix will be increased. Therefore, it is not necessary to select more temperature measurement points than the number of thermal boundary to be solved. Matrix eigenvalue decomposition principle is used to optimize the temperature measurement point. Since a temperature measurement point corresponds to an eigenvalue of the CRI matrix, the temperature measurement point whose eigenvalue is far from zero should be retained. The temperature-heat flow inverse coupling model for solving the thermal boundary conditions is verified by a three-dimensional engine room example, and the reasonable cabin air supply temperature and the total floor heating power are obtained. The temperature-heat flow inverse coupling model is applied to the temperature measurement points. The evaluation method of positive coupling model results is used to optimize the temperature measurement points, and the calculation accuracy is improved.
【学位授予单位】：大连理工大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：V245.34
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