There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution...There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.展开更多
Microwave sintering is being developed as a novel technique for the preparation of dense structural ceramics,but the mature theory has not been established due to the technical difficulties.The synchrotron radiation X...Microwave sintering is being developed as a novel technique for the preparation of dense structural ceramics,but the mature theory has not been established due to the technical difficulties.The synchrotron radiation X-ray computed tomography(SR-CT) technique was introduced for the first time into the study of microwave sintering to in-situ observe the microstructure evolution of silicon carbide(SiC) material in this paper.By applying the SR-CT technique,the reconstructed 2D and 3D images of the specimen were obtained and the double logarithm curve of mean neck size and time(Ln(x)-Ln(t)) were obtained from these reconstructed images.Various sintering phenomena including sintering neck growth during microwave treatment were observed from the reconstructed images.Furthermore,the differences in microstructure evolution and sintering kinetics between microwave and conventional sintering were analyzed based on the reconstructed images and the Ln(x)-Ln(t) curve.1) The sharp surface of grains near the contact region distinctly grew blunt and the sintering neck growth between these grains were obviously observed at the early stage.Besides,the larger particles grew faster than smaller ones.The main reason for these phenomena may be the micro-focusing effect of electric fields.2) During each of the three sintering stages,the sintering kinetics curve of double logarithm relationship between mean neck size and time shows a good linear relationship,but at the middle stage the slope of the curve increases dramatically,which is quite larger than conventional sintering.The preliminary interpretation for these extraordinary phenomena has been discussed in details.展开更多
Three dimensional (3D) microscopic distributions of dolomite and calcite in a limestone sample have been analyzed with a data-constrained modeling (DCM) technique using synchrotron radiation-based multi-energy X-ray c...Three dimensional (3D) microscopic distributions of dolomite and calcite in a limestone sample have been analyzed with a data-constrained modeling (DCM) technique using synchrotron radiation-based multi-energy X-ray computed tomography (CT) data as constraints. In order to optimize the experimental parameters, X-ray CT simulations and DCM analysis of a numerical phantom consisting of calcite (CaCO3) and dolomite (CaMg(CO3)2) have been used to investigate the effects on the predicted results in relation to noise, X-ray energy and sample-to-detector distance (SDD). The simulation results indicate that the optimal X-ray energies are 25 and 35 keVs, and the SDD is 10 mm. The high resolution 3D distributions of mineral phases of a natural limestone have been obtained. The results are useful for quantitative understanding of mineral, porosity, and physical property distributions in relation to oil and gas reservoirs hosted in carbonate rocks, which account for more than half of the world’s conventional hydrocarbon resources. The case studied is also instructive for the applicability of the DCM methods for other types of composite materials with modest atomic number contrasts between the mineral phases.展开更多
基金supported by the National Nature Science Foundation of China(Nos.12027901 and 12041202)Synchrotron Radiation Joint Fund of University of Science and Technology of China(Nos.KY2090000059 and KY2090000054)。
文摘There is a contradiction between the evolution rate of materials and the time resolution of SR-CT characterization in the in situ synchrotron radiation computed tomography(SR-CT)characterization of ultrafast evolution process.The sampling strategy of the ultra-sparse angle is an effective method for improving time resolution.Accurate reconstruction under sparse sampling conditions has always been a bottleneck problem.In recent years,convolutional neural networks have shown outstanding advantages in sparse-angle CT reconstruction given the development of deep learning.However,existing ideas did not consider the expression of high-frequency details in neural networks,limiting their application in accurate SR-CT characterization.A novel high-frequency information-constrained deep learning network(HFIC-Net)is proposed in response to this problem.Additional high-frequency information constraints are added to improve the accuracy of the reconstruction results.Further,a series of numerical reconstruction experiments are conducted to verify this new method,and the results indicate that the reconstruction results of HFIC-Net method effectively improve reconstruction quality.This new method uses only eight-angle projections to achieve the reconstruction effect of the filtered backprojection method(FBP)method in 360 projections.The results of the HFIC-Net method demonstrate clear boundaries and accurate detailed structures,correcting the misinformation caused by using other methods.For quantitative evaluation,the SSIM used to evaluate image structure similarity is increased from 0.1951,0.9212,and 0.9308 for FBP,FBP-Conv,and DDC-Net,respectively,to 0.9620 for HFIC-Net.Finally,the results of actual SR-CT experimental data indicate that the new method can suppress artifacts and achieve accurate reconstruction,and it is suitable for the in situ SR-CT accurate characterization of ultxafast evolution process.
基金supported by the National Natural Science Foundation of China (Grant Nos 10902108, 10732080, 10872190)the National Basic Research Program of China ("973" Project) (Grant No 2007CB936800)
文摘Microwave sintering is being developed as a novel technique for the preparation of dense structural ceramics,but the mature theory has not been established due to the technical difficulties.The synchrotron radiation X-ray computed tomography(SR-CT) technique was introduced for the first time into the study of microwave sintering to in-situ observe the microstructure evolution of silicon carbide(SiC) material in this paper.By applying the SR-CT technique,the reconstructed 2D and 3D images of the specimen were obtained and the double logarithm curve of mean neck size and time(Ln(x)-Ln(t)) were obtained from these reconstructed images.Various sintering phenomena including sintering neck growth during microwave treatment were observed from the reconstructed images.Furthermore,the differences in microstructure evolution and sintering kinetics between microwave and conventional sintering were analyzed based on the reconstructed images and the Ln(x)-Ln(t) curve.1) The sharp surface of grains near the contact region distinctly grew blunt and the sintering neck growth between these grains were obviously observed at the early stage.Besides,the larger particles grew faster than smaller ones.The main reason for these phenomena may be the micro-focusing effect of electric fields.2) During each of the three sintering stages,the sintering kinetics curve of double logarithm relationship between mean neck size and time shows a good linear relationship,but at the middle stage the slope of the curve increases dramatically,which is quite larger than conventional sintering.The preliminary interpretation for these extraordinary phenomena has been discussed in details.
文摘Three dimensional (3D) microscopic distributions of dolomite and calcite in a limestone sample have been analyzed with a data-constrained modeling (DCM) technique using synchrotron radiation-based multi-energy X-ray computed tomography (CT) data as constraints. In order to optimize the experimental parameters, X-ray CT simulations and DCM analysis of a numerical phantom consisting of calcite (CaCO3) and dolomite (CaMg(CO3)2) have been used to investigate the effects on the predicted results in relation to noise, X-ray energy and sample-to-detector distance (SDD). The simulation results indicate that the optimal X-ray energies are 25 and 35 keVs, and the SDD is 10 mm. The high resolution 3D distributions of mineral phases of a natural limestone have been obtained. The results are useful for quantitative understanding of mineral, porosity, and physical property distributions in relation to oil and gas reservoirs hosted in carbonate rocks, which account for more than half of the world’s conventional hydrocarbon resources. The case studied is also instructive for the applicability of the DCM methods for other types of composite materials with modest atomic number contrasts between the mineral phases.
