The numerical dispersion phenomenon in the finite-difference forward modeling simulations of the wave equation significantly affects the imaging accuracy in acoustic reflection logging.This issue is particularly prono...The numerical dispersion phenomenon in the finite-difference forward modeling simulations of the wave equation significantly affects the imaging accuracy in acoustic reflection logging.This issue is particularly pronounced in the reverse time migration(RTM)method used for shear-wave(S-wave)logging imaging.This not only affects imaging accuracy but also introduces ambiguities in the interpretation of logging results.To address this challenge,this study proposes the use of a least-squares difference coefficient optimization algorithm aiming to suppress the numerical dispersion phenomenon in the RTM of S-wave reflection imaging logging.By optimizing the difference coefficients,the high-precision finite-difference algorithm serves as an effective operator for both forward and backward RTM processes.This approach is instrumental in eliminating migration illusions,which are often caused by numerical dispersion.The effectiveness of this optimized algorithm is demonstrated through numerical results,which indicate that it can achieve more accurate forward imaging results across various conditions,including high-and low-velocity strata,and is effective in both large and small spatial grids.The results of processing real data demonstrate that numerical dispersion optimization effectively reduces migration artifacts and diminishes ambiguities in logging interpretations.This optimization offers crucial technical support to the RTM method,enhancing its capability for accurately modeling and imaging S-wave reflections.展开更多
Laplace–Fourier(L-F)domain finite-difference(FD)forward modeling is an important foundation for L-F domain full-waveform inversion(FWI).An optimal modeling method can improve the efficiency and accuracy of FWI.A fl e...Laplace–Fourier(L-F)domain finite-difference(FD)forward modeling is an important foundation for L-F domain full-waveform inversion(FWI).An optimal modeling method can improve the efficiency and accuracy of FWI.A fl exible FD stencil,which requires pairing and centrosymmetricity of the involved gridpoints,is used on the basis of the 2D L-F domain acoustic wave equation.The L-F domain numerical dispersion analysis is then performed by minimizing the phase error of the normalized numerical phase and attenuation propagation velocities to obtain the optimization coefficients.An optimal FD forward modeling method is finally developed for the L-F domain acoustic wave equation and applied to the traditional standard 9-point scheme and 7-and 9-point schemes,where the latter two schemes are used in discontinuous-grid FD modeling.Numerical experiments show that the optimal L-F domain FD modeling method not only has high accuracy but can also be applied to equal and unequal directional sampling intervals and discontinuous-grid FD modeling to reduce computational cost.展开更多
Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome...Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome this defect, a finite-difference method in the frequency-space domain is introduced in the migration process, because it can adapt to strong lateral velocity variation and the coefficient is optimized by a hybrid genetic and simulated annealing algorithm. The two measures improve the precision of the approximation dispersion equation. Thus, the imaging effect is improved for areas of high-dip structure and strong lateral velocity variation. The migration imaging of a 2-D SEG/EAGE salt dome model proves that a better imaging effect in these areas is achieved by optimized phase-shift migration operator plus a finite-difference method based on a hybrid genetic and simulated annealing algorithm. The method proposed in this paper is better than conventional methods in imaging of areas of high-dip angle and strong lateral velocity variation.展开更多
Aiming at the demand for optimization of hydrodynamic coefficients in submarine's motion equations,an adaptive weight immune genetic algorithm was proposed to optimize hydrodynamic coefficients in motion equations...Aiming at the demand for optimization of hydrodynamic coefficients in submarine's motion equations,an adaptive weight immune genetic algorithm was proposed to optimize hydrodynamic coefficients in motion equations.Some hydrodynamic coefficients of high sensitivity to control and maneuver were chosen as the optimization objects in the algorithm.By using adaptive weight method to determine the weight and target function,the multi-objective optimization could be translated into single-objective optimization.For a certain kind of submarine,three typical maneuvers were chosen to be the objects of study:overshoot maneuver in horizontal plane,overshoot maneuver in vertical plane and turning circle maneuver in horizontal plane.From the results of computer simulations using primal hydrodynamic coefficient and optimized hydrodynamic coefficient,the efficiency of proposed method is proved.展开更多
Prestack reverse time migration （RTM） is an accurate imaging method ofsubsurface media. The viscoacoustic prestack RTM is of practical significance because itconsiders the viscosity of the subsurface media. One of t...Prestack reverse time migration （RTM） is an accurate imaging method ofsubsurface media. The viscoacoustic prestack RTM is of practical significance because itconsiders the viscosity of the subsurface media. One of the steps of RTM is solving thewave equation and extrapolating the wave field forward and backward; therefore, solvingaccurately and efficiently the wave equation affects the imaging results and the efficiencyof RTM. In this study, we use the optimal time-space domain dispersion high-order finite-difference （FD） method to solve the viscoacoustic wave equation. Dispersion analysis andnumerical simulations show that the optimal time-space domain FD method is more accurateand suppresses the numerical dispersion. We use hybrid absorbing boundary conditions tohandle the boundary reflection. We also use source-normalized cross-correlation imagingconditions for migration and apply Laplace filtering to remove the low-frequency noise.Numerical modeling suggests that the viscoacoustic wave equation RTM has higher imagingresolution than the acoustic wave equation RTM when the viscosity of the subsurface isconsidered. In addition, for the wave field extrapolation, we use the adaptive variable-lengthFD operator to calculate the spatial derivatives and improve the computational efficiencywithout compromising the accuracy of the numerical solution.展开更多
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
Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow ...Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.展开更多
A new heat flux coefficient model and improved refreshing rules were introduced for optimizing coiling temperature model.The off-line simulation of the new strategy was performed by laminar cooling intelligent softwar...A new heat flux coefficient model and improved refreshing rules were introduced for optimizing coiling temperature model.The off-line simulation of the new strategy was performed by laminar cooling intelligent software,and the on-line application shows that the control of coiling temperature has been improved significantly.展开更多
The horizontal diffusion coefficients of the operational model (T42L9) in numerical weather prediction are optimized by the steepest descent search of multi-dimensional optimization. In order to improve prediction acc...The horizontal diffusion coefficients of the operational model (T42L9) in numerical weather prediction are optimized by the steepest descent search of multi-dimensional optimization. In order to improve prediction accuracy in low latitudes, the optimum horizontal diffusion coefficients are chosen, with changing variation of the basic diffusion coefficient with the passage of time, and later forecasts are also made better. In view of the averages of forecast verifications of 9 cases, the forecasts with optimum diffusion coefficients are an improvement on operational forecasts. It means that the forecasts are got much better with optimum values of some important parameters by optimization in numerical weather prediction.展开更多
The fatigue performance of optimized welded detail has been investigated by fatigue experiments of three welded specimens under different loadings.In addition,local finite element models of this welded detail were est...The fatigue performance of optimized welded detail has been investigated by fatigue experiments of three welded specimens under different loadings.In addition,local finite element models of this welded detail were established using finite element software ANSYS.The influences of different factors such as plate thickness,plate gap and initial geometric imperfections on the stress concentration coefficient(SCC) were discussed.The experimental results indicate that the fatigue life of three specimens for this welded detail is 736,000,1,044,200 and 1,920,300 times,respectively.The web thickness,the filler plate thickness and the initial geometric imperfection have relatively less effect on the SCCs of this welded detail.However,cope-hole radius is influential on the SCCs of the web and the weld.The SCC of weld is significantly affected by the weld size and plate gap,but the SCCs of other parts of the welded detail are hardly affected by the plate gap.展开更多
To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network...To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.展开更多
Aiming at working out more accurate pollutant degradation coefficient of the deep tunnel system, this work puts forward a novel optimized algorithm to calibrate such coefficient and compare it with the ordinary fittin...Aiming at working out more accurate pollutant degradation coefficient of the deep tunnel system, this work puts forward a novel optimized algorithm to calibrate such coefficient and compare it with the ordinary fitting method. This algorithm incorporates the outlier filtration mechanism and the gradient descent mechanism to improve its performance, and the calibration result is substituted into storm water management model (SWMM) source codes to validate its effectiveness between simulated and observed data. COD, NH3-N, TN and TP are chosen as pollutant indicators of the observed data, and the RMSE, MSE and ME are selected as indicators to present the efficiency. The results show that the outlier filtration mechanism obtains better performance than fitting method, with the gradient descent mechanism nearly reduces 92.42% of the iterative amounts and improves 55 times of the computation efficiency than the ordinary iterative method, such algorithm is expected to function better with substantial observed data.展开更多
Numerical simulation in the frequency-space domain has inherent advantages, such as： it is possible to simulate wave propagation from multiple sources simultaneously; there are no cumulative errors; only the interest...Numerical simulation in the frequency-space domain has inherent advantages, such as： it is possible to simulate wave propagation from multiple sources simultaneously; there are no cumulative errors; only the interesting frequencies can be selected; and it is more suitable for wave propagation in viscoelastic media. The only obstacle to using the method is the requirement of huge computer storage. We extend the compressed format for storing the coefficient matrix. It can reduce the required computer storage dramatically. We get the optimal coefficients by least-squares method to suppress the numerical dispersion and adopt the perfectly matched layer （PML） boundary conditions to eliminate the artificial boundary reflections. Using larger grid intervals decreases computer storage requirements and provides high computational efficiency. Numerical experiments demonstrate that these means are economic and effective, providing a good basis for elastic wave imaging and inversion.展开更多
In order to increase the performance of horizontal tidal turbines, a multi-objective optimization model was proposed in this study. Firstly, the prediction model for horizontal tidal turbines was built, which coupled ...In order to increase the performance of horizontal tidal turbines, a multi-objective optimization model was proposed in this study. Firstly, the prediction model for horizontal tidal turbines was built, which coupled the blade element momentum (BEM) theory and the CFD calculation. Secondly, a multi-objective optimization method coupled the response surface method (RSM) with the multi-objective genetic algorithm NSGA-II was applied to obtain the optimal blade profiles. The pitch angle and the chord length distribution were chosen as the design variables, while the mean power coefficient and the variance of power coefficient were chosen as the objective functions. With the mean power coefficient improved by 4.1% and the variance of power coefficient decreased by 46.7%, results showed that both objective functions could be improved.展开更多
The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robus...The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions.The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory.In this paper,an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio.The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model,and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time,which are updated with time progressing.The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road,and the minimum statistical error is used as the recognition principle to improve identification robustness.Once the road type is recognized,the maximum road friction coefficient and optimal slip ratio are determined.The numerical simulation tests are conducted on two typical road friction conditions（single-friction and joint-friction）by using CarSim software.The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim.The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations,and the identification results can be used for the adjustment of vehicle active safety control strategies.展开更多
In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is...In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.展开更多
The spatial organization of the Chinese petrochemical industry was optimized according to the status of development of the industry employing linear programming and ArcGIS spatial analysis tools. We first identified t...The spatial organization of the Chinese petrochemical industry was optimized according to the status of development of the industry employing linear programming and ArcGIS spatial analysis tools. We first identified the indexes of the spatial organization of the petrochemical industry and established a comprehensive evaluation index system that in- cludes four major categories and 11 indicators. The weight of each index was then deter- mined by the analytical hierarchy process. Afterward, taking the 337 Chinese prefecture-level administrations as basic units and scientifically evaluating the potential comprehensive layout coefficients of the cities, 151 prefecture-level administrative units were selected as the basis for the choice of optimization sites with a linear programming model. Secondly, using the 151 prefecture-level administrative units and the maximum-coverage model, the optimal number and spatial distribution of refineries were identified for service radii of 100, 200 and 300 km. Thirdly, considering the actual distribution of China＇s refineries, general rules for the number of refinery layout points and objective values were summarized, and 52 refinery layout points were selected for China. Finally, with ArcGIS spatial analysis tools, the spatial effect of the 52 optimal refinery layout points was simulated for the service scope and socioeconomic factors respectively, and the GDP and population data for each refinery layout point were then ex- tracted within the service scope. On this basis and with estimation of the intensity of crude-oil consumption, final results were obtained for the optimal spatial organization of the Chinese refining capacity and ethylene production capacity.展开更多
The elasticity-based Locally Exact Homogenization Theory(LEHT) is extended to study the mechanical-hygrothermal behaviors of unidirectionally-reinforced composites. Based on the framework developed previously, thermal...The elasticity-based Locally Exact Homogenization Theory(LEHT) is extended to study the mechanical-hygrothermal behaviors of unidirectionally-reinforced composites. Based on the framework developed previously, thermal and moisture effects are incorporated into the LEHT to study the homogenized and localized responses of heterogeneous materials, which are validated using available analytical and numerical techniques. The LEHT programs are then encapsulated as subroutines with Input/Output(I/O) interfaces, to be readily applied in different computational scenarios. In order to illustrate the efficiency of the LEHT, the theory is firstly coupled to the Particle Swarm Optimization(PSO) algorithm in order to minimize the axial thermal expansion mismatch in hexagonal and square fiber arrays by tailoring the fiber volume fraction. The LEHT is then implemented into the lamination theory to study fabrication-induced residual stresses arising during the cool-down process which introduces local laminate stresses owing to thermo-mechanical property mismatch between plies. Both of these applications illustrate the efficiency and accuracy of the LEHT in generating effective properties and local stress distributions, making the theory a golden standard in validating other analytical or numerical techniques as well as a reliable tool in composite design and practice for professionals and non-professionals alike.展开更多
During the pipeline plugging process,both the pipeline and the pipe isolation tool(PIT)will be greatly damaged,due to the violent vibration of the flow field.In this study,it was proposed for the first time to reduce ...During the pipeline plugging process,both the pipeline and the pipe isolation tool(PIT)will be greatly damaged,due to the violent vibration of the flow field.In this study,it was proposed for the first time to reduce the vibration of the flow field during the plugging process by optimizing the surface structure of the PIT.Firstly,the central composite design(CCD)was used to obtain the optimization schemes,and the drag coefficient and pressure coefficient were proposed to evaluate the degree of flow field changes.Secondly,a series of computational fluid dynamics(CFD)simulations were performed to obtain the drag coefficient and pressure coefficient during dynamic plugging.And the mathematical model of drag coefficient and pressure coefficient with the surface structure of the PIT were established respectively.Then,a modified particle swarm optimization(PSO)was applied to predict the optimal value of the surface structure of the PIT.Finally,an experimental rig was built to verify the effectiveness of the optimization.The results showed that the improved method could reduce the flow field vibration by 49.56%.This study provides a reference for the design of the PIT surface structure for flow field vibration technology.展开更多
In this paper, a hybrid improved particle swarm optimization （IPSO） algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimizati...In this paper, a hybrid improved particle swarm optimization （IPSO） algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimization （PSO） algorithm is improved in two ways： （1） The linearly decreasing inertia weight coefficient （LDIWC） is replaced by a self-adaptive exponential inertia weight coefficient （SEIWC）, which could make the PSO algorithm more balanceable and more effective in both global and local searches. （2） The crossover and mutation idea inspired by the genetic algorithm （GA） is imported into the particle updating method to enhance the diversity of populations. The potential ability of IPSO in nonlinear numerical function optimization was first tested with three classical benchmark functions. Then, a long-term multi-reservoir system operation model based on IPSO was designed and a case study was carried out in the Minjiang Basin in China, where there is a power system consisting of 26 hydroelectric power plants. The scheduling results of the IPSO algorithm were found to outperform PSO and to be comparable with the results of the dynamic programming successive approximation （DPSA） algorithm.展开更多
基金supported by Scientific Research and Technology Development Project of CNPC(2021DJ4002,2022DJ3908).
文摘The numerical dispersion phenomenon in the finite-difference forward modeling simulations of the wave equation significantly affects the imaging accuracy in acoustic reflection logging.This issue is particularly pronounced in the reverse time migration(RTM)method used for shear-wave(S-wave)logging imaging.This not only affects imaging accuracy but also introduces ambiguities in the interpretation of logging results.To address this challenge,this study proposes the use of a least-squares difference coefficient optimization algorithm aiming to suppress the numerical dispersion phenomenon in the RTM of S-wave reflection imaging logging.By optimizing the difference coefficients,the high-precision finite-difference algorithm serves as an effective operator for both forward and backward RTM processes.This approach is instrumental in eliminating migration illusions,which are often caused by numerical dispersion.The effectiveness of this optimized algorithm is demonstrated through numerical results,which indicate that it can achieve more accurate forward imaging results across various conditions,including high-and low-velocity strata,and is effective in both large and small spatial grids.The results of processing real data demonstrate that numerical dispersion optimization effectively reduces migration artifacts and diminishes ambiguities in logging interpretations.This optimization offers crucial technical support to the RTM method,enhancing its capability for accurately modeling and imaging S-wave reflections.
基金National Natural Science Foundation of China(no.41604037)Natural Science Foundation of Hubei Province(no.2022CFB125)+2 种基金Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources(Yangtze University)Ministry of Education(no.K2021-09)College Students'Innovation and Entrepreneurship Training Program(no.2019053)。
文摘Laplace–Fourier(L-F)domain finite-difference(FD)forward modeling is an important foundation for L-F domain full-waveform inversion(FWI).An optimal modeling method can improve the efficiency and accuracy of FWI.A fl exible FD stencil,which requires pairing and centrosymmetricity of the involved gridpoints,is used on the basis of the 2D L-F domain acoustic wave equation.The L-F domain numerical dispersion analysis is then performed by minimizing the phase error of the normalized numerical phase and attenuation propagation velocities to obtain the optimization coefficients.An optimal FD forward modeling method is finally developed for the L-F domain acoustic wave equation and applied to the traditional standard 9-point scheme and 7-and 9-point schemes,where the latter two schemes are used in discontinuous-grid FD modeling.Numerical experiments show that the optimal L-F domain FD modeling method not only has high accuracy but can also be applied to equal and unequal directional sampling intervals and discontinuous-grid FD modeling to reduce computational cost.
基金the Open Fund(PLC201104)of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Chengdu University of Technology)the National Natural Science Foundation of China(No.61072073)the Key Project of Education Commission of Sichuan Province(No.10ZA072)
文摘Although the phase-shift seismic processing method has characteristics of high accuracy, good stability, high efficiency, and high-dip imaging, it is not able to adapt to strong lateral velocity variation. To overcome this defect, a finite-difference method in the frequency-space domain is introduced in the migration process, because it can adapt to strong lateral velocity variation and the coefficient is optimized by a hybrid genetic and simulated annealing algorithm. The two measures improve the precision of the approximation dispersion equation. Thus, the imaging effect is improved for areas of high-dip structure and strong lateral velocity variation. The migration imaging of a 2-D SEG/EAGE salt dome model proves that a better imaging effect in these areas is achieved by optimized phase-shift migration operator plus a finite-difference method based on a hybrid genetic and simulated annealing algorithm. The method proposed in this paper is better than conventional methods in imaging of areas of high-dip angle and strong lateral velocity variation.
文摘Aiming at the demand for optimization of hydrodynamic coefficients in submarine's motion equations,an adaptive weight immune genetic algorithm was proposed to optimize hydrodynamic coefficients in motion equations.Some hydrodynamic coefficients of high sensitivity to control and maneuver were chosen as the optimization objects in the algorithm.By using adaptive weight method to determine the weight and target function,the multi-objective optimization could be translated into single-objective optimization.For a certain kind of submarine,three typical maneuvers were chosen to be the objects of study:overshoot maneuver in horizontal plane,overshoot maneuver in vertical plane and turning circle maneuver in horizontal plane.From the results of computer simulations using primal hydrodynamic coefficient and optimized hydrodynamic coefficient,the efficiency of proposed method is proved.
基金This research was supported by the National Nature Science Foundation of China （No. 41074100） and the Program for NewCentury Excellent Talents in the University of the Ministry of Education of China （No. NCET- 10-0812）.
文摘Prestack reverse time migration （RTM） is an accurate imaging method ofsubsurface media. The viscoacoustic prestack RTM is of practical significance because itconsiders the viscosity of the subsurface media. One of the steps of RTM is solving thewave equation and extrapolating the wave field forward and backward; therefore, solvingaccurately and efficiently the wave equation affects the imaging results and the efficiencyof RTM. In this study, we use the optimal time-space domain dispersion high-order finite-difference （FD） method to solve the viscoacoustic wave equation. Dispersion analysis andnumerical simulations show that the optimal time-space domain FD method is more accurateand suppresses the numerical dispersion. We use hybrid absorbing boundary conditions tohandle the boundary reflection. We also use source-normalized cross-correlation imagingconditions for migration and apply Laplace filtering to remove the low-frequency noise.Numerical modeling suggests that the viscoacoustic wave equation RTM has higher imagingresolution than the acoustic wave equation RTM when the viscosity of the subsurface isconsidered. In addition, for the wave field extrapolation, we use the adaptive variable-lengthFD operator to calculate the spatial derivatives and improve the computational efficiencywithout compromising the accuracy of the numerical solution.
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.
文摘Prediction of reservoir fracture is the key to explore fracture-type reservoir. When a shear-wave propagates in anisotropic media containing fracture,it splits into two polarized shear waves: fast shear wave and slow shear wave. The polarization and time delay of the fast and slow shear wave can be used to predict the azimuth and density of fracture. The current identification method of fracture azimuth and fracture density is cross-correlation method. It is assumed that fast and slow shear waves were symmetrical wavelets after completely separating,and use the most similar characteristics of wavelets to identify fracture azimuth and density,but in the experiment the identification is poor in accuracy. Pearson correlation coefficient method is one of the methods for separating the fast wave and slow wave. This method is faster in calculating speed and better in noise immunity and resolution compared with the traditional cross-correlation method. Pearson correlation coefficient method is a non-linear problem,particle swarm optimization( PSO) is a good nonlinear global optimization method which converges fast and is easy to implement. In this study,PSO is combined with the Pearson correlation coefficient method to achieve identifying fracture property and improve the computational efficiency.
基金Item Sponsored by National Natural Science Foundation of China(59995440)Doctoral Program of Higher EducationFoundation of China(97014515)
文摘A new heat flux coefficient model and improved refreshing rules were introduced for optimizing coiling temperature model.The off-line simulation of the new strategy was performed by laminar cooling intelligent software,and the on-line application shows that the control of coiling temperature has been improved significantly.
文摘The horizontal diffusion coefficients of the operational model (T42L9) in numerical weather prediction are optimized by the steepest descent search of multi-dimensional optimization. In order to improve prediction accuracy in low latitudes, the optimum horizontal diffusion coefficients are chosen, with changing variation of the basic diffusion coefficient with the passage of time, and later forecasts are also made better. In view of the averages of forecast verifications of 9 cases, the forecasts with optimum diffusion coefficients are an improvement on operational forecasts. It means that the forecasts are got much better with optimum values of some important parameters by optimization in numerical weather prediction.
基金supported by the National Natural Science Foundation of China(51308467 and 51378431)China railway corporation research and development of science and technology key project(2013G001-A-2)
文摘The fatigue performance of optimized welded detail has been investigated by fatigue experiments of three welded specimens under different loadings.In addition,local finite element models of this welded detail were established using finite element software ANSYS.The influences of different factors such as plate thickness,plate gap and initial geometric imperfections on the stress concentration coefficient(SCC) were discussed.The experimental results indicate that the fatigue life of three specimens for this welded detail is 736,000,1,044,200 and 1,920,300 times,respectively.The web thickness,the filler plate thickness and the initial geometric imperfection have relatively less effect on the SCCs of this welded detail.However,cope-hole radius is influential on the SCCs of the web and the weld.The SCC of weld is significantly affected by the weld size and plate gap,but the SCCs of other parts of the welded detail are hardly affected by the plate gap.
文摘To support the explosive growth of Information and Communications Technology(ICT),Mobile Edge Comput-ing(MEC)provides users with low latency and high bandwidth service by offloading computational tasks to the network’s edge.However,resource-constrained mobile devices still suffer from a capacity mismatch when faced with latency-sensitive and compute-intensive emerging applications.To address the difficulty of running computationally intensive applications on resource-constrained clients,a model of the computation offloading problem in a network consisting of multiple mobile users and edge cloud servers is studied in this paper.Then a user benefit function EoU(Experience of Users)is proposed jointly considering energy consumption and time delay.The EoU maximization problem is decomposed into two steps,i.e.,resource allocation and offloading decision.The offloading decision is usually given by heuristic algorithms which are often faced with the challenge of slow convergence and poor stability.Thus,a combined offloading algorithm,i.e.,a Gini coefficient-based adaptive genetic algorithm(GCAGA),is proposed to alleviate the dilemma.The proposed algorithm optimizes the offloading decision by maximizing EoU and accelerates the convergence with the Gini coefficient.The simulation compares the proposed algorithm with the genetic algorithm(GA)and adaptive genetic algorithm(AGA).Experiment results show that the Gini coefficient and the adaptive heuristic operators can accelerate the convergence speed,and the proposed algorithm performs better in terms of convergence while obtaining higher EoU.The simulation code of the proposed algorithm is available:https://github.com/Grox888/Mobile_Edge_Computing/tree/GCAGA.
文摘Aiming at working out more accurate pollutant degradation coefficient of the deep tunnel system, this work puts forward a novel optimized algorithm to calibrate such coefficient and compare it with the ordinary fitting method. This algorithm incorporates the outlier filtration mechanism and the gradient descent mechanism to improve its performance, and the calibration result is substituted into storm water management model (SWMM) source codes to validate its effectiveness between simulated and observed data. COD, NH3-N, TN and TP are chosen as pollutant indicators of the observed data, and the RMSE, MSE and ME are selected as indicators to present the efficiency. The results show that the outlier filtration mechanism obtains better performance than fitting method, with the gradient descent mechanism nearly reduces 92.42% of the iterative amounts and improves 55 times of the computation efficiency than the ordinary iterative method, such algorithm is expected to function better with substantial observed data.
基金supported by the 863 Program (Grant no.2006AA09Z323)the 973 Program (Grant No.2006CB202402)
文摘Numerical simulation in the frequency-space domain has inherent advantages, such as： it is possible to simulate wave propagation from multiple sources simultaneously; there are no cumulative errors; only the interesting frequencies can be selected; and it is more suitable for wave propagation in viscoelastic media. The only obstacle to using the method is the requirement of huge computer storage. We extend the compressed format for storing the coefficient matrix. It can reduce the required computer storage dramatically. We get the optimal coefficients by least-squares method to suppress the numerical dispersion and adopt the perfectly matched layer （PML） boundary conditions to eliminate the artificial boundary reflections. Using larger grid intervals decreases computer storage requirements and provides high computational efficiency. Numerical experiments demonstrate that these means are economic and effective, providing a good basis for elastic wave imaging and inversion.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.51706198 and 51839010)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LQ17E090004)
文摘In order to increase the performance of horizontal tidal turbines, a multi-objective optimization model was proposed in this study. Firstly, the prediction model for horizontal tidal turbines was built, which coupled the blade element momentum (BEM) theory and the CFD calculation. Secondly, a multi-objective optimization method coupled the response surface method (RSM) with the multi-objective genetic algorithm NSGA-II was applied to obtain the optimal blade profiles. The pitch angle and the chord length distribution were chosen as the design variables, while the mean power coefficient and the variance of power coefficient were chosen as the objective functions. With the mean power coefficient improved by 4.1% and the variance of power coefficient decreased by 46.7%, results showed that both objective functions could be improved.
基金Supported by National Hi-tech Research and Development Program of China(863 Program,Grant No.2006AA110101)
文摘The identification of maximum road friction coefficient and optimal slip ratio is crucial to vehicle dynamics and control.However,it is always not easy to identify the maximum road friction coefficient with high robustness and good adaptability to various vehicle operating conditions.The existing investigations on robust identification of maximum road friction coefficient are unsatisfactory.In this paper,an identification approach based on road type recognition is proposed for the robust identification of maximum road friction coefficient and optimal slip ratio.The instantaneous road friction coefficient is estimated through the recursive least square with a forgetting factor method based on the single wheel model,and the estimated road friction coefficient and slip ratio are grouped in a set of samples in a small time interval before the current time,which are updated with time progressing.The current road type is recognized by comparing the samples of the estimated road friction coefficient with the standard road friction coefficient of each typical road,and the minimum statistical error is used as the recognition principle to improve identification robustness.Once the road type is recognized,the maximum road friction coefficient and optimal slip ratio are determined.The numerical simulation tests are conducted on two typical road friction conditions（single-friction and joint-friction）by using CarSim software.The test results show that there is little identification error between the identified maximum road friction coefficient and the pre-set value in CarSim.The proposed identification method has good robustness performance to external disturbances and good adaptability to various vehicle operating conditions and road variations,and the identification results can be used for the adjustment of vehicle active safety control strategies.
基金supported in part by the CNRST Morocco,the Volkswagen Foundation:Grant number I/79315Hydromed project
文摘In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.
基金China Postdoctoral Science Foundation, No.2011M500375 National Natural Science Foundation of China, No.40635026 Knowledge Innovation Program of the Chinese Academy of Sciences, No.KZCXZ-YW-Q10-4
文摘The spatial organization of the Chinese petrochemical industry was optimized according to the status of development of the industry employing linear programming and ArcGIS spatial analysis tools. We first identified the indexes of the spatial organization of the petrochemical industry and established a comprehensive evaluation index system that in- cludes four major categories and 11 indicators. The weight of each index was then deter- mined by the analytical hierarchy process. Afterward, taking the 337 Chinese prefecture-level administrations as basic units and scientifically evaluating the potential comprehensive layout coefficients of the cities, 151 prefecture-level administrative units were selected as the basis for the choice of optimization sites with a linear programming model. Secondly, using the 151 prefecture-level administrative units and the maximum-coverage model, the optimal number and spatial distribution of refineries were identified for service radii of 100, 200 and 300 km. Thirdly, considering the actual distribution of China＇s refineries, general rules for the number of refinery layout points and objective values were summarized, and 52 refinery layout points were selected for China. Finally, with ArcGIS spatial analysis tools, the spatial effect of the 52 optimal refinery layout points was simulated for the service scope and socioeconomic factors respectively, and the GDP and population data for each refinery layout point were then ex- tracted within the service scope. On this basis and with estimation of the intensity of crude-oil consumption, final results were obtained for the optimal spatial organization of the Chinese refining capacity and ethylene production capacity.
文摘The elasticity-based Locally Exact Homogenization Theory(LEHT) is extended to study the mechanical-hygrothermal behaviors of unidirectionally-reinforced composites. Based on the framework developed previously, thermal and moisture effects are incorporated into the LEHT to study the homogenized and localized responses of heterogeneous materials, which are validated using available analytical and numerical techniques. The LEHT programs are then encapsulated as subroutines with Input/Output(I/O) interfaces, to be readily applied in different computational scenarios. In order to illustrate the efficiency of the LEHT, the theory is firstly coupled to the Particle Swarm Optimization(PSO) algorithm in order to minimize the axial thermal expansion mismatch in hexagonal and square fiber arrays by tailoring the fiber volume fraction. The LEHT is then implemented into the lamination theory to study fabrication-induced residual stresses arising during the cool-down process which introduces local laminate stresses owing to thermo-mechanical property mismatch between plies. Both of these applications illustrate the efficiency and accuracy of the LEHT in generating effective properties and local stress distributions, making the theory a golden standard in validating other analytical or numerical techniques as well as a reliable tool in composite design and practice for professionals and non-professionals alike.
基金financially supported by the National Natural Science Foundation of China(Grant No.51575528)。
文摘During the pipeline plugging process,both the pipeline and the pipe isolation tool(PIT)will be greatly damaged,due to the violent vibration of the flow field.In this study,it was proposed for the first time to reduce the vibration of the flow field during the plugging process by optimizing the surface structure of the PIT.Firstly,the central composite design(CCD)was used to obtain the optimization schemes,and the drag coefficient and pressure coefficient were proposed to evaluate the degree of flow field changes.Secondly,a series of computational fluid dynamics(CFD)simulations were performed to obtain the drag coefficient and pressure coefficient during dynamic plugging.And the mathematical model of drag coefficient and pressure coefficient with the surface structure of the PIT were established respectively.Then,a modified particle swarm optimization(PSO)was applied to predict the optimal value of the surface structure of the PIT.Finally,an experimental rig was built to verify the effectiveness of the optimization.The results showed that the improved method could reduce the flow field vibration by 49.56%.This study provides a reference for the design of the PIT surface structure for flow field vibration technology.
基金supported by the National Natural Science Foundation of China (Grant No. 50679011)
文摘In this paper, a hybrid improved particle swarm optimization （IPSO） algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimization （PSO） algorithm is improved in two ways： （1） The linearly decreasing inertia weight coefficient （LDIWC） is replaced by a self-adaptive exponential inertia weight coefficient （SEIWC）, which could make the PSO algorithm more balanceable and more effective in both global and local searches. （2） The crossover and mutation idea inspired by the genetic algorithm （GA） is imported into the particle updating method to enhance the diversity of populations. The potential ability of IPSO in nonlinear numerical function optimization was first tested with three classical benchmark functions. Then, a long-term multi-reservoir system operation model based on IPSO was designed and a case study was carried out in the Minjiang Basin in China, where there is a power system consisting of 26 hydroelectric power plants. The scheduling results of the IPSO algorithm were found to outperform PSO and to be comparable with the results of the dynamic programming successive approximation （DPSA） algorithm.
