共查询到20条相似文献,搜索用时 171 毫秒
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本文基于BP神经网络方法结合蒙特卡洛和BEER定律辐射传输模拟方法建立了联合反演各向异性散射介质的辐射特性参数模型。首先采用半球透射率结合半球反射率反演模型反演了各向同性介质的吸收系数和散射系数,在此基础上增加准直透射率,建立了联合反演各向异性介质的吸收系数、散射系数和散射不对称因子三参数联合反演模型。反演结果表明该模型能准确反演出介质辐射特性参数,具有实用意义。此外,为了检验测量误差对模型的反演准确性的影响,分别在不同程度测量误差情况下进行反演,结果显示测量误差对散射不对称因子反演值影响较大。 相似文献
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多孔介质预混燃烧中辐射属性影响的敏感性分析 总被引:1,自引:0,他引:1
建立了惰性多孔介质中预混合燃烧的数学模型,采用辐射传递的有限体积法求解固相能量方程中的辐射源项,研究多孔介质热辐射在燃烧系统中的作用,考察辐射属性(吸收系数和散射反照率)对轴向温度场和辐射热流量影响的敏感性。研究表明,辐射属性参数波动对预测结果影响明显,固体热辐射在多孔介质预混燃烧中的影响不可忽略。 相似文献
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考虑了实际物体表面BRDF的影响,利用方向半球反射率、方向半球透射率、法向反射率和法向透射率等光谱数据,同时反演了一维平板内介质和表面的辐射特性参数。将该方法用于吸收散射、强散射和强吸收三种介质的辐射特性参数反演,反演结果与给定初值较吻合。 相似文献
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Hongwu Fan Bingxi LiLidan Yang Ruzhu Wang 《Journal of Quantitative Spectroscopy & Radiative Transfer》2002,74(1):85-95
An inverse radiation analysis is presented for estimating the temperature and the heat load distributions of the heating surface from the temperature and the heat flux measurements of the heated object. The Monte Carlo method is employed to solve the direct radiation problem. The inverse radiation problem is solved using the conjugate gradient and singular value decomposition methods. The measured data are simulated by adding random errors to the exact solution of the direct problem. The effects of the measurement errors on the accuracy of the inverse analysis are investigated. The study shows that the heat load distribution of the heating surface can be estimated accurately for the exact and noisy data. And the conjugate gradient method is better than the singular value decomposition method since the former can obtain more accurate results if the measurement errors are the same. 相似文献
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Hongwu Fan Bingxi LiLidan Yang Ruzhu Wang 《Journal of Quantitative Spectroscopy & Radiative Transfer》2002,74(1):75-83
A new inverse radiation analysis is presented for estimating the heat rate and temperature distributions in the combustion region from the information of the temperature and heat flux profiles of wall elements in the system. The Monte Carlo method is employed to solve the radiative heat transfer equation. The inverse radiation problem is posed as a minimization problem of the least squares criterion, which is solved by the conjugate gradient method. The performance of the present technique of inverse analysis is evaluated and the effects of the errors of the absorption coefficient, emissivity and convective heat transfer coefficient on the inverse analysis are investigated. The results show that the present technique is robust and yields accurate estimation even with noisy measurement. 相似文献
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A. Namjoo A. Behzadmehr 《Journal of Quantitative Spectroscopy & Radiative Transfer》2009,110(8):491-505
In this paper, an inverse analysis is performed for estimation of source term distribution from the measured exit radiation intensities at the boundary surfaces in a one-dimensional absorbing, emitting and isotropically scattering medium between two parallel plates with variable refractive index. The variation of refractive index is assumed to be linear. The radiative transfer equation is solved by the constant quadrature discrete ordinate method. The inverse problem is formulated as an optimization problem for minimizing an objective function which is expressed as the sum of square deviations between measured and estimated exit radiation intensities at boundary surfaces. The conjugate gradient method is used to solve the inverse problem through an iterative procedure. The effects of various variables on source estimation are investigated such as type of source function, errors in the measured data and system parameters, gradient of refractive index across the medium, optical thickness, single scattering albedo and boundary emissivities. The results show that in the case of noisy input data, variation of system parameters may affect the inverse solution, especially at high error values in the measured data. The error in measured data plays more important role than the error in radiative system parameters except the refractive index distribution; however the accuracy of source estimation is very sensitive toward error in refractive index distribution. Therefore, refractive index distribution and measured exit intensities should be measured accurately with a limited error bound, in order to have an accurate estimation of source term in a graded index medium. 相似文献
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Inverse radiation problem in one-dimensional slab by time-resolved reflected and transmitted signals
A time-domain inverse approach is proposed for estimating the distribution of absorbing and scattering coefficients in one-dimensional inhomogeneous media. The temporal reflected and transmitted signals are detected when an ultra-short pulse irradiates on the boundary of semi-transparent scattering media. Forward computation and inverse algorithm employ the least-squares finite element method and conjugate gradient method, respectively. As the prevalent diffusion approximation is not employed in our model, the present approach can be extended to more comprehensive application. The investigation about detected signals indicates that the reflected signals play a significant role in reconstructing optical properties; the signals in early sampling time are more important than those at long-time logarithm slope, and so, more attention should be paid to the early signals in the solution of inverse radiation problem. Three different inverse radiation problems are investigated to show the ability of the present approach to deal with the two-layer, three-layer and continuous inhomogeneous media. The effect of measured errors on the accuracy of reconstruction is investigated by adding artificial random errors. The results indicate that accurate reconstruction depends on not only precise numerical simulation but also quality of detected data. 相似文献
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A Meshless Regularization Method for a Two-Dimensional Two-Phase Linear Inverse Stefan Problem
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B. Tomas Johansson Daniel Lesnic & Thomas Reeve 《advances in applied mathematics and mechanics.》2013,5(6):825-845
In this paper, a meshless regularization method of fundamental solutions is proposed for
a two-dimensional, two-phase linear inverse Stefan problem. The numerical implementation
and analysis are challenging since one needs to handle composite materials in higher dimensions.
Furthermore, the inverse Stefan problem is ill-posed since small errors in the input data
cause large errors in the desired output solution. Therefore, regularization is necessary
in order to obtain a stable solution. Numerical results for several benchmark test examples
are presented and discussed. 相似文献
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初始场误差和模式误差是制约数值预报准确率的两个关键因素,本文主要考虑利用历史观测资料实现时空演变的模式误差的估计问题.通过把模式误差综合考虑成为准确模式中的未知项,把历史资料看作是带有未知项的准确模式的特解,构造了求解时空演变的模式误差项的反问题及其最优控制问题.给出了一个解决最优控制问题的无导数优化方法,该方法的优点是不需要建立原数值模式的切线性模式与伴随模式,它只需在增加一个外强迫项的基础上运行原数值模式即可实现模式误差项的最优估计.关于Burgers方程的算例表明,无论模式的初始状态是否准确已知,无导数优化方法都能有效解决时空演变的模式误差的最优估计问题,它为实际业务模式利用历史数据提取模式误差信息并显著地改进预报效果提供了一种方便可行的数值方法与理论依据. 相似文献
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An approach to estimating and extrapolating model error based on inverse problem methods:towards accurate numerical weather prediction 总被引:1,自引:0,他引:1
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Model error is one of the key factors restricting the accuracy of numerical weather prediction(NWP). Considering the continuous evolution of the atmosphere, the observed data(ignoring the measurement error) can be viewed as a series of solutions of an accurate model governing the actual atmosphere. Model error is represented as an unknown term in the accurate model, thus NWP can be considered as an inverse problem to uncover the unknown error term. The inverse problem models can absorb long periods of observed data to generate model error correction procedures. They thus resolve the deficiency and faultiness of the NWP schemes employing only the initial-time data. In this study we construct two inverse problem models to estimate and extrapolate the time-varying and spatial-varying model errors in both the historical and forecast periods by using recent observations and analogue phenomena of the atmosphere. Numerical experiment on Burgers’ equation has illustrated the substantial forecast improvement using inverse problem algorithms. The proposed inverse problem methods of suppressing NWP errors will be useful in future high accuracy applications of NWP. 相似文献
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The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find unknown parameters such as distributed model coefficients or boundary conditions. The equation for the optimal solution error is derived through the errors of the input data (background and observation errors), and the optimal solution error covariance operator through the input data error covariance operators, respectively. The quasi-Newton BFGS algorithm is adapted to construct the covariance matrix of the optimal solution error using the inverse Hessian of an auxiliary data assimilation problem based on the tangent linear model constraints. Preconditioning is applied to reduce the number of iterations required by the BFGS algorithm to build a quasi-Newton approximation of the inverse Hessian. Numerical examples are presented for the one-dimensional convection–diffusion model. 相似文献
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I.Yu. Gejadze G.J.M. Copeland F.-X. Le Dimet V. Shutyaev 《Journal of computational physics》2011,230(22):7923-7943
The problem of variational data assimilation for a nonlinear evolution model is formulated as an optimal control problem to find the initial condition function. The data contain errors (observation and background errors), hence there will be errors in the optimal solution. For mildly nonlinear dynamics, the covariance matrix of the optimal solution error can often be approximated by the inverse Hessian of the cost functional. Here we focus on highly nonlinear dynamics, in which case this approximation may not be valid. The equation relating the optimal solution error and the errors of the input data is used to construct an approximation of the optimal solution error covariance. Two new methods for computing this covariance are presented: the fully nonlinear ensemble method with sampling error compensation and the ‘effective inverse Hessian’ method. The second method relies on the efficient computation of the inverse Hessian by the quasi-Newton BFGS method with preconditioning. Numerical examples are presented for the model governed by Burgers equation with a nonlinear viscous term. 相似文献