Inverse radiation analysis of simultaneous estimation of temperature field and radiative properties in a two-dimensional participating medium

Liu, Dong; Yan, Jun; Wang, F.; Huang, Qunxing; Chi, Yong; Cen, Kefa

doi:10.1016/j.ijheatmasstransfer.2010.06.046

Cited by 44 publications

(10 citation statements)

References 27 publications

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“…In order to evaluate the performance of the Direct Solution algorithm proposed in this paper, several common traditional reconstruction algorithms of flame temperature distribution are selected for comparison, such as SART (Liu et al, 2017), LSQR (Liu et al, 2010), NNLS (Li et al, 2019) algorithms. In terms of reconstruction accuracy, the following criteria are used for evaluation (Resnick et al, 1985): 1) The normalized mean square distance, q; 2) The normalized average absolute distance, r; The worstcase distance, e. The specific expressions are shown in Eqs ( 5)-( 7).…”

Section: Results and Discussion Evaluation Criterionmentioning

confidence: 99%

“…To solve the above-mentioned problems, Zhou et al (2002) used an improved Tikhonov regularization algorithm to reconstruct a three-dimensional temperature distribution of N x × N y × N z 10 × 10 × 10 from the flame image obtained by the CCD camera, which proved the robustness of the algorithm, but the reconstruction efficiency is not studied. Liu et al (2010) used the Least Square QR decomposition (LSQR) algorithm to achieve a two-dimensional temperature distribution reconstruction with a discrete area of N x × N y 10 × 10 based on an 8-camera system combined with the Monte Carlo method. However, if the LSQR algorithm is directly used for large-scale illconditioned problems, there will be a "semi-convergence" problem, which will affect the accuracy and reconstruction time.…”

Section: Introductionmentioning

confidence: 99%

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A Fast Tomographic Reconstruction Method for Flame Temperature Distribution Measurement Based on Direct Solution Algorithm

Zhang

Peng

et al. 2021

Front. Energy Res.

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The rapid and accurate measurement of the flame temperature distribution is of great significance to the structural design and health diagnosis of the engine. Aiming at the low reconstruction efficiency of traditional flame temperature distribution reconstruction algorithms, a Direct Solution algorithm for flame temperature distribution reconstruction is proposed in this paper based on the structural characteristics of the reconstruction equations. By setting several numerical cases, the performance of the Direct Solution algorithm and some commonly used traditional algorithms, such as Simultaneous Algebraic Reconstruction Technique (SART), Least Squares QR-factorization (LSQR) algorithm, Non-Negative Least Squares QR-factorization (NNLS) algorithm, is compared in the reconstruction of the flame temperature distribution. The results show that the efficiency of the Direct Solution method is 169.4, 7.4, and 3483.3 times higher than that of the SART, LSQR, and NNLS algorithms under the condition of 40 × 40 grids. In addition, with the increase of the number of grids, the growth rate of the reconstruction time of the Direct Solution algorithm is much lower than that of other algorithms. The overall reconstruction accuracy of the Direct Solution algorithm is better than that of SART and LSQR algorithms. This shows that it has an excellent comprehensive performance and has a great application prospect in the rapid reconstruction of the temperature distribution.

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Section: Results and Discussion Evaluation Criterionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Fast Tomographic Reconstruction Method for Flame Temperature Distribution Measurement Based on Direct Solution Algorithm

Zhang

Peng

et al. 2021

Front. Energy Res.

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“…For aerogel nano-porous materials, the radiation heat imported from the outside or emitted by the solid skeleton in the nano-porous material will be absorbed and scattered by the solid phase material when it passes through the pores or skeleton in the nano-porous material [ 22 , 23 ]. It must be mentioned that aerogel has strong permeability to near-infrared radiation with wavelengths of 3–8 μm at high temperature, which leads to the poor shielding ability of aerogel at high temperature, and the thermal conductivity of aerogel increases significantly with the increase in temperature [ 24 ].…”

Section: Analysis On Heat Transfer Mechanismmentioning

confidence: 99%

Thermal Insulation Performance of Aerogel Nano-Porous Materials: Characterization and Test Methods

Lou

Dong

Zhu

et al. 2023

Gels

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Due to the extremely high porosity and extremely low density of nano-porous thermal insulation materials, the characteristic size of the pores inside the materials and the characteristic size of the solid skeleton structure are on the nanometer scale, which leads to the obvious nanoscale effect of the heat transfer law inside the aerogel materials. Therefore, the nanoscale heat transfer characteristics inside the aerogel materials and the existing mathematical models for calculating the thermal conductivity of various heat transfer modes at the nanoscale need to be summarized in detail. Moreover, in order to verify the accuracy of the thermal conductivity calculation model of aerogel nano-porous materials, correct experimental data are required to modify the model. Because the medium is involved in radiation heat transfer, the existing test methods have a large error, which brings great difficulties to the design of nano-porous materials. In this paper, the heat transfer mechanism, characterization methods, and test methods of thermal conductivity of nano-porous materials are summarized and discussed. The main contents of this review are as follows. The first part introduces the structural characteristics and specific application environment of aerogel. In the second part, the characteristics of nanoscale heat transfer of aerogel insulation materials are analyzed. In the third part, the characterization methods of thermal conductivity of aerogel insulation materials are summarized. In the fourth part, the test methods of thermal conductivity of aerogel insulation materials are summarized. The fifth part gives a brief conclusion and prospect.

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“…Lou et al [ 21 ] and Cheng et al [ 22 ] optimized the reconstruction model and further carried out the reconstruction of temperature and nonuniform radiation properties of soot in the coal-fired furnace and gas-fired pilot tubular furnace, respectively. Liu et al [ 23 , 24 ] presented an inverse radiation model for the concurrent estimation of the temperature and radiative properties, which introduced the backward Monte Carlo method to trace the radiative transfer of the flame radiation energy captured by four CCD cameras mounted staggered to each other on the four sides of the two-dimensional rectangular area.…”

Section: Introductionmentioning

confidence: 99%

Edge Effects on Simultaneous Reconstructions of Flame Temperature and Soot Volume Fraction Profiles by a CCD Camera

Chen

et al. 2022

Sensors

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In this paper, the influence of the edge effect on the simultaneous reconstruction of axisymmetric flame temperature and soot volume fraction profiles by a single CCD camera was investigated in detail. The reconstruction accuracy of the flame temperature profile and soot volume fraction was insensitive to the measurement error of the coefficient matrix. When the signal to ratio (SNR) of the measurement system for both the radiation intensity and coefficient matrix was as low as 46 dB, the reconstruction accuracy for both temperature and soot volume fraction was acceptable and was more influenced by the radiation intensity measurement error. The reconstruction of the flame temperature and soot volume fraction was greatly influenced by the edge effect. When the flame edge with weak radiation signals was ignored during the reconstruction, the relative reconstruction error for the temperature and soot volume fraction increased from the flame center to the edge, and reached an unacceptable value at the reconstruction boundary, especially for the soot volume fraction. The flame image boundary could be chosen as the unified reconstruction boundary to reconstruct the two-dimensional distribution of the temperature and soot volume fraction with satisfactory accuracy. The low soot volume fraction could influence the reconstruction accuracy for both the temperature and soot concentration in non-sooting regions. Moreover, there was no obvious regularity between the reconstruction accuracy of the temperature and soot volume fraction and the extension of the reconstruction boundary.

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Inverse radiation analysis of simultaneous estimation of temperature field and radiative properties in a two-dimensional participating medium

Cited by 44 publications

References 27 publications

A Fast Tomographic Reconstruction Method for Flame Temperature Distribution Measurement Based on Direct Solution Algorithm

A Fast Tomographic Reconstruction Method for Flame Temperature Distribution Measurement Based on Direct Solution Algorithm

Thermal Insulation Performance of Aerogel Nano-Porous Materials: Characterization and Test Methods

Edge Effects on Simultaneous Reconstructions of Flame Temperature and Soot Volume Fraction Profiles by a CCD Camera

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