The Experts below are selected from a list of 15315 Experts worldwide ranked by ideXlab platform
M Mierzwiczak - One of the best experts on this subject based on the ideXlab platform.
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the singular boundary method for steady state nonlinear heat Conduction Problem with temperature dependent thermal conductivity
International Journal of Heat and Mass Transfer, 2015Co-Authors: M Mierzwiczak, Wen Chen, Zhuojia FuAbstract:Abstract This paper presents the singular boundary method for steady-state nonlinear heat Conduction Problems. In the steady-state nonlinear heat Conduction Problem, the Kirchhoff transformation is employed to remove the nonlinearity associated with the temperature dependence of the thermal conductivity. Then the transformed Laplace-type equation is investigated by the present singular boundary method with a simple iteration procedure. Finally, the temperature field is derived by the inverse Kirchhoff transformation. The present algorithm is verified on several examples involving various expressions of temperature dependent thermal conductivity and different computational domains. Numerical results show good accuracy and stability of the proposed strategy.
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the determination temperature dependent thermal conductivity as inverse steady heat Conduction Problem
International Journal of Heat and Mass Transfer, 2011Co-Authors: M Mierzwiczak, Jan Adam KolodziejAbstract:The paper deals with the non-iterative inverse determination of the temperature-dependent thermal conductivity in 2-D steady-state heat Conduction Problem. The thermal conductivity is modeled as a polynomial function of temperature with the unknown coefficients. The identification of the thermal conductivity is obtained by using the boundary data and additionally from the knowledge of temperature inside the domain. The method of fundamental solutions is used to solve the 2-D heat Conduction Problem. The golden section search is used to find the optimal place for pseudo-boundary on which are placed the singularities in the frame of method of fundamental solutions.
Jan Adam Kolodziej - One of the best experts on this subject based on the ideXlab platform.
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the determination temperature dependent thermal conductivity as inverse steady heat Conduction Problem
International Journal of Heat and Mass Transfer, 2011Co-Authors: M Mierzwiczak, Jan Adam KolodziejAbstract:The paper deals with the non-iterative inverse determination of the temperature-dependent thermal conductivity in 2-D steady-state heat Conduction Problem. The thermal conductivity is modeled as a polynomial function of temperature with the unknown coefficients. The identification of the thermal conductivity is obtained by using the boundary data and additionally from the knowledge of temperature inside the domain. The method of fundamental solutions is used to solve the 2-D heat Conduction Problem. The golden section search is used to find the optimal place for pseudo-boundary on which are placed the singularities in the frame of method of fundamental solutions.
Keith A Woodbury - One of the best experts on this subject based on the ideXlab platform.
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inverse heat Conduction Problem sensitivity coefficient insights filter coefficients and intrinsic verification
International Journal of Heat and Mass Transfer, 2016Co-Authors: James V Beck, Keith A WoodburyAbstract:Abstract The inverse heat Conduction Problem is the estimation of the time and/or space dependence of the surface heat flux or temperature utilizing interior temperature measurements at discrete times and/or locations. This Problem is ill-posed since it is very sensitive to omnipresent measurement errors. Many solution methods have been proposed including exact-matching, function specification, Tikhonov regularization, iterative regularization, conjugate gradient, steepest descent and singular value decomposition. In this paper, the tools provided by the scaled sensitivity coefficients, digital filter coefficients, and intrinsic verification are used to investigate and compare several of these methods. The utility of digital filters designed for on-line instrumentation for “continuous” measurements of the surface heat flux and temperature in manufacturing settings is also demonstrated.
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filter solution of inverse heat Conduction Problem using measured temperature history as remote boundary condition
International Journal of Heat and Mass Transfer, 2014Co-Authors: Keith A Woodbury, James V Beck, Hamidreza NajafiAbstract:Abstract The inverse heat Conduction Problem (IHCP) involves estimation of a surface heat flux from transient temperature measurements inside a heat conducting body. Commonly an insulated remote boundary or one with a known heat transfer coefficient is modeled. However, in many practical applications, the precise thermal condition at the remote boundary is not known. In this paper, a method of accounting for thermal action at the remote boundary using a second measured temperature history is presented. The measurement need not be at an actual boundary but can be at an interior point in the domain. The IHCP solution herein is achieved through the filter coefficient method, which uses filter coefficients in a convolution summation. By using the filter technique, near real-time heat flux measurements can be continuously obtained in manufacturing settings to enhance productivity. Also the filter concept opens the way for the development of new scientific instruments that incorporate inverse Problem methods.
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estimation metrics and optimal regularization in a tikhonov digital filter for the inverse heat Conduction Problem
International Journal of Heat and Mass Transfer, 2013Co-Authors: Keith A Woodbury, James V BeckAbstract:Abstract Tikhonov regularization for the inverse heat Conduction Problem (IHCP) is considered a “whole domain” or “batch” method, meaning that observations are needed over the entire time domain of interest, and that calculations must be performed all-at-once in a batch. This paper examines the structure of the Tikhonov regularization Problem and concludes that the method can be interpreted as a sequential filter formulation for continuous processing of data. Several general observations regarding features of the filter formulation are noted. Two error norms are discussed: one regarding temperature and one regarding heat flux. It is shown that these metrics can be split into two parts: one dependent on the heat flux history (bias error) and one dependent on the measurement noise (random error). Two examples demonstrate that the optimal selection of the regularization parameter to minimize the heat flux error yields results similar to the classical Morozov principle defined through temperature error, and that the results are relatively insensitive to the precise selection of the parameter.
Chong Wang - One of the best experts on this subject based on the ideXlab platform.
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collocation methods for fuzzy uncertainty propagation in heat Conduction Problem
International Journal of Heat and Mass Transfer, 2017Co-Authors: Chong Wang, Menghui XuAbstract:Abstract Based on the combination of collocation technology and fuzzy theory, this paper proposes a full grid fuzzy collocation method (FGFCM) and a sparse grid fuzzy collocation method (SGFCM) for fuzzy uncertainty propagation in heat Conduction Problem. Converting fuzzy parameters into interval variables by level-cut strategy, the Legendre polynomial series provides a surrogate function for temperature response. To calculate the expansion coefficients, FGFCM evaluates the deterministic solutions directly on the full tensor product grids, whereas Smolyak algorithm is introduced in SGFCM to reduce the number of collocation points. According to the smoothness property of surrogate function and fuzzy decomposition theorem, the interval bounds and membership functions of uncertain temperature response are derived, respectively. Comparing result with traditional Monte Carlo simulation and parameter perturbation method, two numerical examples evidence the remarkable accuracy and effectiveness of proposed methods for fuzzy temperature field prediction in engineering.
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uncertainty propagation of heat Conduction Problem with multiple random inputs
International Journal of Heat and Mass Transfer, 2016Co-Authors: Chong Wang, Yaowen YangAbstract:Abstract Uncertainty propagation analysis in engineering systems constitutes a significant challenge. To effectively solve the uncertain heat Conduction Problem with multiple random inputs, a random collocation method (RCM) and a modified random collocation method (MRCM) are established based on the spectral analysis theory. In both methods, the truncated high-order polynomial series is adopted to approximate the temperature responses with respect to random parameters, and the eventual probabilistic moments are derived by using the orthogonal relationship of polynomial bases. In the pivotal process of calculating the expansion coefficients, RCM evaluates the deterministic solutions directly on full tensor product grids, whereas the Smolyak sparse grids are reconstructed in MRCM to avoid the huge computational cost caused by high dimensions. Comparing the results with traditional Monte Carlo simulation, two numerical examples verify the remarkable accuracy and effectiveness of the proposed methods for random temperature field prediction in engineering.
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improved numerical prediction and reliability based optimization of transient heat Conduction Problem with interval parameters
Structural and Multidisciplinary Optimization, 2015Co-Authors: Chong WangAbstract:In this paper, a high-order interval parameter perturbation method (HIPPM) and a reliability-based optimization model are proposed to solve the transient heat Conduction Problem with uncertainties in both the material properties and initial/boundary conditions. Interval variables are used to quantitatively describe the uncertain parameters with limited information. A modified stability theory is proposed and used to select space step and time step in the interval discrete schemes. Compared with the traditional first-order perturbation method, HIPPM can yield more accurate ranges of the uncertain temperature field by adopting the higher order terms of the Neumann series to approximate the interval matrix inverse. In the following investigated optimization model, a satisfaction degree of interval is employed to deal with the interval constraint functions. Given a reliability index representing the confidence level, uncertain constraints can be transformed into deterministic ones. The proposed HIPPM is used to predict the intervals of the constraints, and whereby eliminate the optimization nesting. A numerical example modeling a thermal protection system is presented to demonstrate the feasibility and efficiency of the proposed method.
James V Beck - One of the best experts on this subject based on the ideXlab platform.
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inverse heat Conduction Problem sensitivity coefficient insights filter coefficients and intrinsic verification
International Journal of Heat and Mass Transfer, 2016Co-Authors: James V Beck, Keith A WoodburyAbstract:Abstract The inverse heat Conduction Problem is the estimation of the time and/or space dependence of the surface heat flux or temperature utilizing interior temperature measurements at discrete times and/or locations. This Problem is ill-posed since it is very sensitive to omnipresent measurement errors. Many solution methods have been proposed including exact-matching, function specification, Tikhonov regularization, iterative regularization, conjugate gradient, steepest descent and singular value decomposition. In this paper, the tools provided by the scaled sensitivity coefficients, digital filter coefficients, and intrinsic verification are used to investigate and compare several of these methods. The utility of digital filters designed for on-line instrumentation for “continuous” measurements of the surface heat flux and temperature in manufacturing settings is also demonstrated.
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filter solution of inverse heat Conduction Problem using measured temperature history as remote boundary condition
International Journal of Heat and Mass Transfer, 2014Co-Authors: Keith A Woodbury, James V Beck, Hamidreza NajafiAbstract:Abstract The inverse heat Conduction Problem (IHCP) involves estimation of a surface heat flux from transient temperature measurements inside a heat conducting body. Commonly an insulated remote boundary or one with a known heat transfer coefficient is modeled. However, in many practical applications, the precise thermal condition at the remote boundary is not known. In this paper, a method of accounting for thermal action at the remote boundary using a second measured temperature history is presented. The measurement need not be at an actual boundary but can be at an interior point in the domain. The IHCP solution herein is achieved through the filter coefficient method, which uses filter coefficients in a convolution summation. By using the filter technique, near real-time heat flux measurements can be continuously obtained in manufacturing settings to enhance productivity. Also the filter concept opens the way for the development of new scientific instruments that incorporate inverse Problem methods.
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estimation metrics and optimal regularization in a tikhonov digital filter for the inverse heat Conduction Problem
International Journal of Heat and Mass Transfer, 2013Co-Authors: Keith A Woodbury, James V BeckAbstract:Abstract Tikhonov regularization for the inverse heat Conduction Problem (IHCP) is considered a “whole domain” or “batch” method, meaning that observations are needed over the entire time domain of interest, and that calculations must be performed all-at-once in a batch. This paper examines the structure of the Tikhonov regularization Problem and concludes that the method can be interpreted as a sequential filter formulation for continuous processing of data. Several general observations regarding features of the filter formulation are noted. Two error norms are discussed: one regarding temperature and one regarding heat flux. It is shown that these metrics can be split into two parts: one dependent on the heat flux history (bias error) and one dependent on the measurement noise (random error). Two examples demonstrate that the optimal selection of the regularization parameter to minimize the heat flux error yields results similar to the classical Morozov principle defined through temperature error, and that the results are relatively insensitive to the precise selection of the parameter.
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numerical solution of the general two dimensional inverse heat Conduction Problem ihcp
Journal of Heat Transfer-transactions of The Asme, 1997Co-Authors: A M Osman, K J Dowding, James V BeckAbstract:This paper presents a method for calculating the heat flux at the surface of a body from experimentally measured transient temperature data, which has been called the inverse heat Conduction Problem (IHCP). The analysis allows for two-dimensional heat flow in an arbitrarily shaped body and orthotropic temperature dependent thermal properties. A combined function specification and regularization method is used to solve the IHCP with a sequential-in-time concept used to improve the computational efficiency. To enhance the accuracy, the future information used in the sequential-in-time method and the regularization parameter are variable during the analysis. An example using numerically simulated data is presented to demonstrate the application of the method. Finally, a case using actual experimental data is presented. For this case, the boundary condition was experimentally measured and hence, it was known. A good comparison is demonstrated between the known and estimated boundary conditions for the analysis of the numerical, as well as the experimental data. 20 refs., 6 figs.