Chun Lou

A NEW MODEL OF RADIATIVE IMAGE FORMATION USED IN VISUALIZATION OF 3-D TEMPERATURE DISTRIBUTIONS IN LARGE-SCALE FURNACES

Since it is difficult to calibrate the absolute radiative energy information from any digital image data, a new model is proposed by which the temperature distributions in furnaces are no longer related with the absolute radiative energy images, but with a sort of temperature image. The temperature images are obtained through using the so-called monochromatic-reference method, described in detail. It is shown that the new model has its objectivity in reflecting the temperature distributions in furnaces, and does not change significantly with the aperture or shutter speed of the camera used. The easier calibration for the temperature than for absolute radiative energy makes this treatment more applicable.

Decoupled Reconstruction Method for Simultaneous Estimation of Temperatures and Radiative Properties in a One-Dimensional, Gray, Participating Medium

In the decoupled reconstruction method, using an improved Tikhonov regularization method, the temperature distribution in a participating medium is reconstructed from the boundary temperature image, and the radiative properties (absorption and scattering coefficients) are updated from the measured radiative intensity image. These two steps are taken alternately until convergence is reached. The distributions of temperature and radiative properties for two one-dimensional cases are reconstructed by the method from the boundary temperature and intensity images disturbed by measuremental errors with standard deviations up to 0.05, and the method shows good accuracy and robustness.

Simultaneous Determination of Distributions of Temperature and Soot Volume Fraction in Sooting Flames Using Decoupled Reconstruction Method

This article presents a simulation investigation for simultaneous determination of distributions of temperature and soot volume fraction in a nonoptically thin sooting flame using a decoupled reconstruction method. Flame temperature and emissivity images can be calculated from two monochromatic radiative intensity images in the visible spectrum range. Then, the distributions of temperature and soot volume fraction were reconstructed from flame temperature and emissivity images. Based on experimental data from a laminar ethylene diffusion flame available in the literature, the effects of measurement errors, detection wavelengths, and optical thickness on the accuracy of the reconstruction have been investigated.

Assessment of Regularized Reconstruction of Three-Dimensional Temperature Distributions in Large-Scale Furnaces

Three-dimensional (3-D) temperature distributions in large-scale furnaces can be reconstructed from temperature images captured by CCD cameras through inverse calculation of radiative heat transfer. This article assesses the reconstruction method for 3-D temperature distribution using the Tikhonov regularization by simulation. In a 10 m × 10 m × 20 m furnace with different optical thicknesses, the 3-D temperature distribution was reconstructed with errors in measurements and radiative properties of the combustion medium, and the influence of the radiative contribution from the wall surfaces. The results show that the Tikhonov regularization method is robust and, when the optical thickness is within the range from 1 to 15, the reconstruction errors of the 3-D temperature distribution in the furnace are less than 6%, which is acceptable in applications.

Experimental investigation on soot volume fraction in an ethylene diffusion flame by emission spectrometry without optically-thin assumption

An improved soot diagnostics technique based on tomographic reconstruction of flame emission spectra has been developed for an axisymmetric laminar diffusion flame without optically-thin assumption. Emission from the flame is scanned along the horizontal lateral axis of flame at several altitudes above the burner. At each measurement position, the local line-of-sight flame emission spectra is collected by a spectrometry over a spectral range of 700-1100 nm. Inversion of these data through one-dimensional tomography using a three-point Abel inversion yields radial distributions of the soot radiation from which soot volume fraction profiles are extracted. Traditionally, this procedure was applied only in the optically-thin flames for which the self-attenuation term of emitted radiation is ignored. However, this self-attenuation term is considered by iterative calculations in the paper. The configuration of the investigation flame is similar to the flames reported in the literatures. The results by the conventional method is found to be almost twice to the results by the improved method. This discrepancy revealed that the optically-thin assumption for the flames will cause serious errors in the conventional method, and the improved method could overcome this deficiency effectively.

Recent achievements in measurements of soot volume fraction and temperatures in a coflow, diffuse Ethylene-air flame by visible image processing

In this review paper, the recent achievements in measurements of soot volume fraction and temperatures in a coflow, diffuse Ethylene-air flame by visible image processing are briefly outlined. For the inverse analysis of the radiative properties and temperatures, different methods show different features. The least-squares method, a regularization method and a linear programming method are all suitable for this problem, and a linear programming method can give more reasonable results. The red, green and blue flame images, which can be captured by some colour CCD camera, can be taken approximately as monochromatic images, and can be used to reconstruct temperature and soot volume fraction. But more ideal is the true monochromatic images filtered by filters at certain wavelengths. Finally, the optically-thin assumption, which is adopted widely, will cause large errors, about 100 K for temperature and 50% for soot volume fraction, as the absorption of the flame medium is neglected.

A Hybrid Method for Reconstructing Temperature Distributions in a Radiant Enclosure

A hybrid method combining Tikhonov regularization and generalized singular value decomposition (TR–GSVD) was proposed to reconstruct temperature distributions in radiant enclosures. The regularization parameter, which is crucial to accurately inverse temperature distributions, could be fast updated in TR–GSVD. Numerical reconstruction of three-dimensional temperature fields in a 10 m × 10 m × 20 m furnace proved TR–GSVD possesses the same computational accuracy but higher efficiency compared with TR. Experimental reconstruction results from practical flames in the furnace also showed the regularization parameter changed significantly in some combustion conditions. It is necessary to update the regularization parameter during the reconstruction.