Generally, FD coefficients can be obtained by using Taylor series expansion （TE） or optimization methods to minimize the dispersion error. However, the TE-based FD method only achieves high modeling precision over a...Generally, FD coefficients can be obtained by using Taylor series expansion （TE） or optimization methods to minimize the dispersion error. However, the TE-based FD method only achieves high modeling precision over a limited range of wavenumbers, and produces large numerical dispersion beyond this range. The optimal FD scheme based on least squares （LS） can guarantee high precision over a larger range of wavenumbers and obtain the best optimization solution at small computational cost. We extend the LS-based optimal FD scheme from two-dimensional （2D） forward modeling to three-dimensional （3D） and develop a 3D acoustic optimal FD method with high efficiency, wide range of high accuracy and adaptability to parallel computing. Dispersion analysis and forward modeling demonstrate that the developed FD method suppresses numerical dispersion. Finally, we use the developed FD method to source wavefield extrapolation and receiver wavefield extrapolation in 3D RTM. To decrease the computation time and storage requirements, the 3D RTM is implemented by combining the efficient boundary storage with checkpointing strategies on GPU. 3D RTM imaging results suggest that the 3D optimal FD method has higher precision than conventional methods.展开更多
The optimization models and algorithms with their implementations on flow over time problems have been an emerging field of research because of largely increasing human-created and natural disasters worldwide.For an o...The optimization models and algorithms with their implementations on flow over time problems have been an emerging field of research because of largely increasing human-created and natural disasters worldwide.For an optimal use of transportation network to shift affected people and normalize the disastrous situation as quickly and efficiently as possible,contraflow configuration is one of the highly applicable operations research(OR)models.It increases the outbound road capacities by reversing the direction of arcs towards the safe destinations that not only minimize the congestion and increase the flow but also decrease the evacuation time significantly.In this paper,we sketch the state of quickest flow solutions and solve the quickest contraflow problem with constant transit times on arcs proving that the problem can be solved in strongly polynomial time O(nm^2(long n)~2)where n and m are number of nodes and number of arcs,respectively in the network.This contraflow solution has the same computational time bound as that of the best min-cost flow solution.Moreover,we also introduce the contraflow approach with load dependent transit times on arcs and present an efficient algorithm to solve the quickest contraflow problem approximately.Supporting the claim,our computational experiments on Kathmandu road network and on randomly generated instances perform very well matching the theoretical results.For a sufficiently large number of evacuees,about double flow can be shifted with the same evacuation time and about half time is sufficient to push the given flow value with contraflow reconfiguration.展开更多
基金supported by the National Natural Science Foundation of China(No.41474110)Shell Ph.D. Scholarship to support excellence in geophysical research
文摘Generally, FD coefficients can be obtained by using Taylor series expansion （TE） or optimization methods to minimize the dispersion error. However, the TE-based FD method only achieves high modeling precision over a limited range of wavenumbers, and produces large numerical dispersion beyond this range. The optimal FD scheme based on least squares （LS） can guarantee high precision over a larger range of wavenumbers and obtain the best optimization solution at small computational cost. We extend the LS-based optimal FD scheme from two-dimensional （2D） forward modeling to three-dimensional （3D） and develop a 3D acoustic optimal FD method with high efficiency, wide range of high accuracy and adaptability to parallel computing. Dispersion analysis and forward modeling demonstrate that the developed FD method suppresses numerical dispersion. Finally, we use the developed FD method to source wavefield extrapolation and receiver wavefield extrapolation in 3D RTM. To decrease the computation time and storage requirements, the 3D RTM is implemented by combining the efficient boundary storage with checkpointing strategies on GPU. 3D RTM imaging results suggest that the 3D optimal FD method has higher precision than conventional methods.
基金supported by Deutscher Akademischer Austauschdienst (German Academic Exchange Service) Partnership Program (with University of Kaiserslautern, Germany and Mindanao State University, Iligan Institute of Technology, Iligan, Philippines)Av H Research Group Linkage Program (with Technische Universitt Bergakademie Freiberg) in Graph Theory and Optimization at Central Department of Mathematics, Tribhuvan University, Kathmandu, Nepalsupported by the Av H Foundation for the Georg Forster Research Fellowship for post doctoral researchers at Technische Universitt Bergakademie Freiberg Germany
文摘The optimization models and algorithms with their implementations on flow over time problems have been an emerging field of research because of largely increasing human-created and natural disasters worldwide.For an optimal use of transportation network to shift affected people and normalize the disastrous situation as quickly and efficiently as possible,contraflow configuration is one of the highly applicable operations research(OR)models.It increases the outbound road capacities by reversing the direction of arcs towards the safe destinations that not only minimize the congestion and increase the flow but also decrease the evacuation time significantly.In this paper,we sketch the state of quickest flow solutions and solve the quickest contraflow problem with constant transit times on arcs proving that the problem can be solved in strongly polynomial time O(nm^2(long n)~2)where n and m are number of nodes and number of arcs,respectively in the network.This contraflow solution has the same computational time bound as that of the best min-cost flow solution.Moreover,we also introduce the contraflow approach with load dependent transit times on arcs and present an efficient algorithm to solve the quickest contraflow problem approximately.Supporting the claim,our computational experiments on Kathmandu road network and on randomly generated instances perform very well matching the theoretical results.For a sufficiently large number of evacuees,about double flow can be shifted with the same evacuation time and about half time is sufficient to push the given flow value with contraflow reconfiguration.
