TY - GEN
T1 - Robust and physically-constrained interpolation of fluid flow fields
AU - Zhong, Jialin
AU - Weng, Juyang
AU - Huang, Thomas S.
N1 - This work was supported by National Science Foundation Grant IRI-89-08255; and Air Force Grant AFOSR-90-0044 of Center for Supercomputer Research and Development at University of Illinois at Urbana-Champaign. The authors would like to thank Professor Th. Dracos and Dr. H.-G. Maas of ETH, Zurich, Switzerland very much for their kindly supplying the flow data
PY - 1992
Y1 - 1992
N2 - This paper investigates the problem of interpolating, under physical constraints, 3D vector fields from sample vectors at random positions. This problem arises from analysis of fluid motion, but our results can also be applied to such areas as geometric modeling, approximation theory, and other types of nonrigid body motion. The algorithm proposed in this paper combines the generalized multivariate quadratic interpolation and physical constraints into one step to form an over-determined linear equation system whose solution gives the coefficients of interpolation, which are much less sensitive to noise compared to other interpolation methods. We utilize methods in robust statistics to detect outliers in the sample data so that the results are more stable in the presence of gross errors. The algorithm is applied to both synthesized velocity fields of fluid and empirically measured 3D velocity fields.
AB - This paper investigates the problem of interpolating, under physical constraints, 3D vector fields from sample vectors at random positions. This problem arises from analysis of fluid motion, but our results can also be applied to such areas as geometric modeling, approximation theory, and other types of nonrigid body motion. The algorithm proposed in this paper combines the generalized multivariate quadratic interpolation and physical constraints into one step to form an over-determined linear equation system whose solution gives the coefficients of interpolation, which are much less sensitive to noise compared to other interpolation methods. We utilize methods in robust statistics to detect outliers in the sample data so that the results are more stable in the presence of gross errors. The algorithm is applied to both synthesized velocity fields of fluid and empirically measured 3D velocity fields.
UR - https://www.scopus.com/pages/publications/85019592675
UR - https://www.scopus.com/pages/publications/85019592675#tab=citedBy
U2 - 10.1109/ICASSP.1992.226245
DO - 10.1109/ICASSP.1992.226245
M3 - Conference contribution
AN - SCOPUS:85019592675
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 185
EP - 188
BT - ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
Y2 - 23 March 1992 through 26 March 1992
ER -