Inverse radiation analysis in an absorbing, emitting and non-gray participating medium

Cui, Miao; Gao, Xiao‐Wei; Hai-geng, Chen

doi:10.1016/j.ijthermalsci.2011.01.018

Cited by 33 publications

(19 citation statements)

References 20 publications

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“…It is employed for the determination of the sensitivity coefficient matrix, which is composed of first order derivatives. This method has been validated to be accurate for calculating sensitivity coefficients in the previous works [23][24][25][26][27]. In CVDM, the variable X of a real function f(X) is replaced by the complex variable X + ih, with the imaginary part h being very small (usually h = 10 À20 ).…”

Section: Sensitivity Analysis [23]mentioning

confidence: 99%

“…In recent years, the first author and the co-authors have been focused on the accurate calculation of sensitivity coefficients in gradient-based methods [3,[23][24][25][26][27]. We introduced the com plex-variable-differentiation method (CVDM) [28] into inverse heat transfer problems, and have successfully overcome the difficulty in accurately calculating sensitivity coefficients.…”

Section: Introductionmentioning

confidence: 99%

“…We introduced the com plex-variable-differentiation method (CVDM) [28] into inverse heat transfer problems, and have successfully overcome the difficulty in accurately calculating sensitivity coefficients. Based on CVDM, a least-squares method was developed, and numerical examples showed that it was efficient, accurate and robust [23][24][25][26][27]. http In the previous works [23][24][25][26][27], the relaxation factor was a key parameter between 0 and 1, and it was a constant during the whole iteration process, which was empirically determined by trials.…”

Section: Introductionmentioning

confidence: 99%

“…In the new method, the least-squares method in the previous works [23][24][25][26][27] is employed, and the relaxation factor is adaptively updated at each iteration, rather than an empirical constant during the whole iteration process. The advantages of high efficiency, good accuracy and robustness of the least-squares method are to be kept, and the convergence stability is expected to be improved, to effectively resist the ill-posedness.…”

Section: Introductionmentioning

confidence: 99%

“…(17), w is defined as a relaxation factor. In the previous works [23][24][25][26][27], the relaxation factor was a constant between 0 and 1, and it was empirically determined by trials. In the present work, the relaxation factor will be optimized and adaptively updated at each iteration, rather than a constant during the whole iteration process.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A new inverse analysis method based on a relaxation factor optimization technique for solving transient nonlinear inverse heat conduction problems

Cui

Duan

Gao

2015

International Journal of Heat and Mass Transfer

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Section: Sensitivity Analysis [23]mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A new inverse analysis method based on a relaxation factor optimization technique for solving transient nonlinear inverse heat conduction problems

Cui

Duan

Gao

2015

International Journal of Heat and Mass Transfer

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Radiant energy exchange through participating media composed of arbitrary concentrations of H₂O, CO₂, and CO

Camaraza‐Medina,

Hernandez‐Guerrero,

Luviano‐Ortiz

2024

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In this work, an approximate analytical solution (AS) is presented to evaluate the radiative thermal exchange through a gaseous participating medium composed of H2O, CO2, and CO, which is valid for the product values of pressure path‐length (PL) from 0.06 to 20 atm m and temperatures (T) from 300 K to 2100 K. The Spence root weighting method is used to approximate the exact solutions. For each set of , the value of exact spectral emissivity and absorptivity and for the gas mixture is calculated using the AS, the Hottel graphical method (HGM) and the proposed approximate solution. The weaker adjustment was achieved in the modeling of the HGM, with a mean deviation obtained of ±15% and ±20% for 43.8% and 56.3% of the data evaluated, respectively, while the best indices were obtained in the estimation of the proposed method, with a mean deviation obtained of ±10% and ±15% for 81.3% and 98.1% of the available data, respectively. In all cases, the agreement of the proposed model with the available experimental data is good enough to be considered satisfactory for practical design.

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Gas emissivities and absorptivities for H₂O–CO₂–CO mixtures

Camaraza‐Medina

2024

Heat Trans

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In this work, an approximate solution is given to compute the gas emissivities and absorptivities for H2O–CO2–CO mixtures. The proposed model is valid for temperatures from 300 to 2700 K and pressure path‐length from 0.06 to 40 atm m. In the calculation of the analytical solution (AS), the nonlinear methods of Galerkin and Ritz were implemented based on the residual solution of the differential roots of the Finite Element Method. For each point value using the AS, the spectral absorptivity and emissivity were determined, while for the gas mixture the emissivity and absorptivity were computed using the Hottel Graphical Method (HGM) and the proposed method. In the emissivity calculations, the HGM shows less adjustment, with values of ±20% and ±15% for 79.1% and 56.2% of the available analytical data, while the proposed model correlates adequately with the available data, showing an average deviation of ±15% and ±10% for 91.4% and 76.2% of the available data. In the absorptivity estimations, the HGM shows a weaker fit, with values of ±20% and ±15% for 77.3% and 51.4% of the experimental data, respectively, while the proposed model shows good agreement with the available data, with a mean deviation of ±15% and ±10% for 89.8% and 74.1% of the test made.

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Inverse radiation analysis in an absorbing, emitting and non-gray participating medium

Cited by 33 publications

References 20 publications

A new inverse analysis method based on a relaxation factor optimization technique for solving transient nonlinear inverse heat conduction problems

A new inverse analysis method based on a relaxation factor optimization technique for solving transient nonlinear inverse heat conduction problems

Radiant energy exchange through participating media composed of arbitrary concentrations of H₂O, CO₂, and CO

Gas emissivities and absorptivities for H₂O–CO₂–CO mixtures

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Inverse radiation analysis in an absorbing, emitting and non-gray participating medium

Cited by 33 publications

References 20 publications

A new inverse analysis method based on a relaxation factor optimization technique for solving transient nonlinear inverse heat conduction problems

A new inverse analysis method based on a relaxation factor optimization technique for solving transient nonlinear inverse heat conduction problems

Radiant energy exchange through participating media composed of arbitrary concentrations of H2O, CO2, and CO

Gas emissivities and absorptivities for H2O–CO2–CO mixtures

Contact Info

Product

Resources

About

Radiant energy exchange through participating media composed of arbitrary concentrations of H₂O, CO₂, and CO

Gas emissivities and absorptivities for H₂O–CO₂–CO mixtures