In order to establish a new method for measuring the dimensions of coarse aggregates, five different-size flat and elongated (F&E) coarse aggregates were glued into two specimens by epoxy resin, respectively, and ...In order to establish a new method for measuring the dimensions of coarse aggregates, five different-size flat and elongated (F&E) coarse aggregates were glued into two specimens by epoxy resin, respectively, and slice images were obtained by X-ray CT, then the aggregates were extracted by the fuzzy c-means clustering algorithm. Attributions of the particle on different cross-sections were determined by the ‘overlap area method’. And unified three-dimensional Cartesian coordinate system was established based on continuous slice images. The coefficient values of spherical harmonics descriptor representing particles surface profile were gained, then each scanned particle was represented by 60×120 discrete points conformably with spherical harmonics descriptor. The chord length and direction angles were determined by the calculation. With the major axis (L) and orthogonal axis (W and T), the calculated results were compared with those measured by caliper. It is concluded that the new L, W, and T dimension measuring method is able to take the place of the present manual measurement.展开更多
When inverting the S-wave velocity and azimuthal anisotropy from ambient noise data, it is always to obtain the partial overlapped inversion results in contiguous different regions. Merging different data to achieve a...When inverting the S-wave velocity and azimuthal anisotropy from ambient noise data, it is always to obtain the partial overlapped inversion results in contiguous different regions. Merging different data to achieve a consistent model becomes an essential requirement. Based on the S-wave velocity and azimuthal anisotropy obtained from different contiguous regions, this paper introduces three kinds of methods for merging data. For data from different regions with partial overlapping areas, the merged results could be calculated by direct average weighting(DAW), linear dynamic weighting(LDW), and Gaussian function weighting(GFW), respectively. Data tests demonstrate that the LDW and GFW methods can effectively merge data by reasonably allocating data weights to capitalize on the data quality advantages in each zone. In particular, they can resolve the data smoothness at the boundaries of data areas, resulting in a consistent data model in larger regions. This paper presents the effective methods and valuable experiences that can be referred to as advancing data merging technology.展开更多
基金Project(51038004) supported by the National Natural Science Foundation of ChinaProject(2009318000078) supported by the Western China Communications Construction and Technology Program, China
文摘In order to establish a new method for measuring the dimensions of coarse aggregates, five different-size flat and elongated (F&E) coarse aggregates were glued into two specimens by epoxy resin, respectively, and slice images were obtained by X-ray CT, then the aggregates were extracted by the fuzzy c-means clustering algorithm. Attributions of the particle on different cross-sections were determined by the ‘overlap area method’. And unified three-dimensional Cartesian coordinate system was established based on continuous slice images. The coefficient values of spherical harmonics descriptor representing particles surface profile were gained, then each scanned particle was represented by 60×120 discrete points conformably with spherical harmonics descriptor. The chord length and direction angles were determined by the calculation. With the major axis (L) and orthogonal axis (W and T), the calculated results were compared with those measured by caliper. It is concluded that the new L, W, and T dimension measuring method is able to take the place of the present manual measurement.
基金supported by the National Natural Science Foundation of China (Project 42330311)the Central Public-interest Scientific Institution Basal Research Fund (No. 2021IEF0103)the National Key R&D Project of China (2017YFC1500304)。
文摘When inverting the S-wave velocity and azimuthal anisotropy from ambient noise data, it is always to obtain the partial overlapped inversion results in contiguous different regions. Merging different data to achieve a consistent model becomes an essential requirement. Based on the S-wave velocity and azimuthal anisotropy obtained from different contiguous regions, this paper introduces three kinds of methods for merging data. For data from different regions with partial overlapping areas, the merged results could be calculated by direct average weighting(DAW), linear dynamic weighting(LDW), and Gaussian function weighting(GFW), respectively. Data tests demonstrate that the LDW and GFW methods can effectively merge data by reasonably allocating data weights to capitalize on the data quality advantages in each zone. In particular, they can resolve the data smoothness at the boundaries of data areas, resulting in a consistent data model in larger regions. This paper presents the effective methods and valuable experiences that can be referred to as advancing data merging technology.
