This paper presents a numerical study on the simultaneous reconstruction of temperature and volume fraction fields of soot and metal-oxide nanoparticles in an axisymmetric nanofluid fuel sooting flame based on the rad...This paper presents a numerical study on the simultaneous reconstruction of temperature and volume fraction fields of soot and metal-oxide nanoparticles in an axisymmetric nanofluid fuel sooting flame based on the radiative energy images captured by a charge-coupled device(CCD)camera.The least squares QR decomposition method was introduced to deal with the reconstruction inverse problem.The effects of ray numbers and measurement errors on the reconstruction accuracy were investigated.It was found that the reconstruction accuracies for volume fraction fields of soot and metaloxide nanoparticles were easily affected by the measurement errors for radiation intensity,whereas only the metal-oxide volume fraction field reconstruction was more sensitive to the measurement error for the volume fraction ratio of metaloxide nanoparticles to soot.The results show that the temperature,soot volume fraction,and metal-oxide nanoparticles volume fraction fields can be simultaneously and accurately retrieved for exact and noisy data using a single CCD camera.展开更多
Mining operation, especially underground coal mining, always has the remarkable risks of ground control. Passive seismic velocity tomography based on simultaneous iterative reconstructive technique （SIRT） inversion ...Mining operation, especially underground coal mining, always has the remarkable risks of ground control. Passive seismic velocity tomography based on simultaneous iterative reconstructive technique （SIRT） inversion is used to deduce the stress redistribution around the longwall mining panel. The mining-induced microseismic events were recorded by mounting an array of receivers on the surface, above the active panel. After processing and filtering the seismic data, the three-dimensional tomography images of the p-wave velocity variations by SIRT passive seismic velocity tomography were provided. To display the velocity changes on coal seam level and subsequently to infer the stress redistribution, these three-dimensional tomograms into the coal seam level were sliced. In addition, the boundary element method （BEM） was used to simulate the stress redistribution. The results show that the inferred stresses from the passive seismic tomograms are conformed to numerical models and theoretical concept of the stress redistribution around the longwall panel. In velocity tomograms, the main zones of the stress redistribution arotmd the panel, including front and side abutment pressures, and gob stress are obvious and also the movement of stress zones along the face advancement is evident. Moreover, the effect of the advance rate of the face on the stress redistribution is demonstrated in tomography images. The research result proves that the SIRT passive seismic velocity tomography has an ultimate potential for monitoring the changes of stress redistribution around the longwall mining panel continuously and subsequently to improve safety of mining operations.展开更多
Asymmetric flames exhibit distinct dynamic characteristics and combustion patterns during combustion,which are crucial for optimizing combustion efficiency and performance.Accurate derivation of three-dimensional temp...Asymmetric flames exhibit distinct dynamic characteristics and combustion patterns during combustion,which are crucial for optimizing combustion efficiency and performance.Accurate derivation of three-dimensional temperature and absorption coefficient distributions in asymmetric flames is essential for real-world flame measurement applications.However,retrieving these data presents a significant challenge,as the process requires solving an ill-posed inverse problem.To tackle this issue,we propose a multi-spectral light field imaging model that utilizes the Monte Carlo ray tracing method to capture these distributions.This model enables the reconstruction of both temperature and absorption coefficients using Tikhonov regularization combined with Bayesian optimization method.Our analysis investigates the uncertainties associated with temperature reconstruction,taking into account factors such as uniform and non-uniform absorption coefficient distributions,the reconstruction technique employed,and the signal-to-noise ratio.Notably,our findings suggest that the absorption properties within the flame have a minimal impact due to the flame medium's optical thickness.Moreover,a comparative assessment between the Tikhonov regularization method and the least-square QR decomposition method reveals that,for comparable accuracy in reconstruction,the Tikhonov method requires a shorter computational time.Ultimately,the uncertainty related to the signal-to-noise ratio emerges as the most influential factor affecting the relative error in the reconstruction of the flame's absorption coefficient.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.51576100)the Project of"Six Talent Summit"of Jiangsu Province,China(Grant No.2014-XNY-002)
文摘This paper presents a numerical study on the simultaneous reconstruction of temperature and volume fraction fields of soot and metal-oxide nanoparticles in an axisymmetric nanofluid fuel sooting flame based on the radiative energy images captured by a charge-coupled device(CCD)camera.The least squares QR decomposition method was introduced to deal with the reconstruction inverse problem.The effects of ray numbers and measurement errors on the reconstruction accuracy were investigated.It was found that the reconstruction accuracies for volume fraction fields of soot and metaloxide nanoparticles were easily affected by the measurement errors for radiation intensity,whereas only the metal-oxide volume fraction field reconstruction was more sensitive to the measurement error for the volume fraction ratio of metaloxide nanoparticles to soot.The results show that the temperature,soot volume fraction,and metal-oxide nanoparticles volume fraction fields can be simultaneously and accurately retrieved for exact and noisy data using a single CCD camera.
文摘Mining operation, especially underground coal mining, always has the remarkable risks of ground control. Passive seismic velocity tomography based on simultaneous iterative reconstructive technique （SIRT） inversion is used to deduce the stress redistribution around the longwall mining panel. The mining-induced microseismic events were recorded by mounting an array of receivers on the surface, above the active panel. After processing and filtering the seismic data, the three-dimensional tomography images of the p-wave velocity variations by SIRT passive seismic velocity tomography were provided. To display the velocity changes on coal seam level and subsequently to infer the stress redistribution, these three-dimensional tomograms into the coal seam level were sliced. In addition, the boundary element method （BEM） was used to simulate the stress redistribution. The results show that the inferred stresses from the passive seismic tomograms are conformed to numerical models and theoretical concept of the stress redistribution around the longwall panel. In velocity tomograms, the main zones of the stress redistribution arotmd the panel, including front and side abutment pressures, and gob stress are obvious and also the movement of stress zones along the face advancement is evident. Moreover, the effect of the advance rate of the face on the stress redistribution is demonstrated in tomography images. The research result proves that the SIRT passive seismic velocity tomography has an ultimate potential for monitoring the changes of stress redistribution around the longwall mining panel continuously and subsequently to improve safety of mining operations.
基金supported by the National Natural Science Foundation of China (Grant Nos.52306213, 52376115)the Natural Science Foundation of Jiangsu Province (BK20220955)the Fundamental Research Funds for the Central Universities (Grant No.30924010921)。
文摘Asymmetric flames exhibit distinct dynamic characteristics and combustion patterns during combustion,which are crucial for optimizing combustion efficiency and performance.Accurate derivation of three-dimensional temperature and absorption coefficient distributions in asymmetric flames is essential for real-world flame measurement applications.However,retrieving these data presents a significant challenge,as the process requires solving an ill-posed inverse problem.To tackle this issue,we propose a multi-spectral light field imaging model that utilizes the Monte Carlo ray tracing method to capture these distributions.This model enables the reconstruction of both temperature and absorption coefficients using Tikhonov regularization combined with Bayesian optimization method.Our analysis investigates the uncertainties associated with temperature reconstruction,taking into account factors such as uniform and non-uniform absorption coefficient distributions,the reconstruction technique employed,and the signal-to-noise ratio.Notably,our findings suggest that the absorption properties within the flame have a minimal impact due to the flame medium's optical thickness.Moreover,a comparative assessment between the Tikhonov regularization method and the least-square QR decomposition method reveals that,for comparable accuracy in reconstruction,the Tikhonov method requires a shorter computational time.Ultimately,the uncertainty related to the signal-to-noise ratio emerges as the most influential factor affecting the relative error in the reconstruction of the flame's absorption coefficient.
