In order to obtain an accurate tide description in the China Seas, the 2-dimensional nonlinear numerical Princeton Ocean Model （POM） is employed to incorporate in situ tidal measurements both from tide gauges and TO...In order to obtain an accurate tide description in the China Seas, the 2-dimensional nonlinear numerical Princeton Ocean Model （POM） is employed to incorporate in situ tidal measurements both from tide gauges and TOPEX/POSEIDON （T/P） derived datasets by means of the variational adjoint approach in such a way that unknown internal model parameters, bottom topography, friction coefficients and open boundary conditions, for example, are adjusted during the process. The numerical model is used as a forward model. After the along-track T/P data are processed, two classical methods, i.e. harmonic and response analysis, are implemented to estimate the tide from such datasets with a domain covering the model area extending from 0° to 41°N in latitude and from 99°E to 142°E in longitude. And the results of these two methods are compared and interpreted. The numerical simulation is performed for 16 major constituents. In the data assimilation experiments, three types of unknown parameters （water depth, bottom friction and tidal open boundary conditions in the model equations） are chosen as control variables. Among the various types of data assimilation experiments, the calibration of water depth brings the most promising results. By comparing the results with selected tide gauge data, the average absolute errors are decreased from 7.9 cm to 6.8 cm for amplitude and from 13.0° to 9.0° for phase with respect to the semidiurnal tide M2 constituent, which is the largest tidal constituent in the model area. After the data assimilation experiment is performed, the comparison between model results and tide gauge observation for water levels shows that the RMS errors decrease by 9 cm for a total of 14 stations, mostly selected along the coast of China's Mainland, when a one-month period is considered, and the correlation coefficients improve for most tidal stations among these stations.展开更多
We present a new aerodynamic design method based on the lattice Boltzmann method （LBM） and the adjoint approach. The flow field and the adjoint equation are numerically simulated by the GILBM （generalized form of i...We present a new aerodynamic design method based on the lattice Boltzmann method （LBM） and the adjoint approach. The flow field and the adjoint equation are numerically simulated by the GILBM （generalized form of interpolation supplemented LBM） on non-uniform meshes. The first-order approximation for the equilibrium dis- tribution function on the boundary is proposed to diminish the singularity of boundary conditions. Further, a new treatment of the solid boundary in the LBM is described par- ticularly for the airfoil optimization design problem. For a given objective function, the adjoint equation and its boundary conditions are derived analytically. The feasibility and accuracy of the new approach have been perfectly validated by the design optimization of NACA0012 airfoil.展开更多
The significance of flow optimization utilizing the lattice Boltzmann(LB)method becomes obvious regarding its advantages as a novel flow field solution method compared to the other conventional computational fluid dyn...The significance of flow optimization utilizing the lattice Boltzmann(LB)method becomes obvious regarding its advantages as a novel flow field solution method compared to the other conventional computational fluid dynamics techniques.These unique characteristics of the LB method form the main idea of its application to optimization problems.In this research,for the first time,both continuous and discrete adjoint equations were extracted based on the LB method using a general procedure with low implementation cost.The proposed approach could be performed similarly for any optimization problem with the corresponding cost function and design variables vector.Moreover,this approach was not limited to flow fields and could be employed for steady as well as unsteady flows.Initially,the continuous and discrete adjoint LB equations and the cost function gradient vector were derived mathematically in detail using the continuous and discrete LB equations in space and time,respectively.Meanwhile,new adjoint concepts in lattice space were introduced.Finally,the analytical evaluation of the adjoint distribution functions and the cost function gradients was carried out.展开更多
Diffuse optical tomography (DOT) using near-infrared (NIR) light is a promising tool for noninvasive imaging of deep tissue. The approach is capable of reconstructing the quantitative optical parameters (absorption co...Diffuse optical tomography (DOT) using near-infrared (NIR) light is a promising tool for noninvasive imaging of deep tissue. The approach is capable of reconstructing the quantitative optical parameters (absorption coefficient and scattering coefficient) of a soft tissue. The motivation for reconstructing the optical property variation is that it and, in particular, the absorption coefficient variation, can be used to diagnose different metabolic and disease states of tissue. In DOT, like any other medical imaging modality, the aim is to produce a reconstruction with good spatial resolution and in contrast with noisy measurements. The parameter recovery known as inverse problem in highly scattering biological tissues is a nonlinear and ill-posed problem and is generally solved through iterative methods. The algorithm uses a forward model to arrive at a prediction flux density at the tissue boundary. The forward model uses light transport models such as stochastic Monte Carlo simulation or deterministic methods such as radioactive transfer equation (RTE) or a simplified version of RTE namely the diffusion equation (DE). The finite element method (FEM) is used for discretizing the diffusion equation. The frequently used algorithm for solving the inverse problem is Newton-based Model based Iterative Image Reconstruction (N-MoBIIR). Many Variants of Gauss-Newton approaches are proposed for DOT reconstruction. The focuses of such developments are 1) to reduce the computational complexity;2) to improve spatial recovery;and 3) to improve contrast recovery. These algorithms are 1) Hessian based MoBIIR;2) Broyden-based MoBIIR;3) adjoint Broyden-based MoBIIR;and 4) pseudo-dynamic approaches.展开更多
In this paper,we study the state estimation of compressible single phase flow in compressible porous media.The initial pressure distribution is estimated according to discrete adjoint approach based on the collected w...In this paper,we study the state estimation of compressible single phase flow in compressible porous media.The initial pressure distribution is estimated according to discrete adjoint approach based on the collected well pressure data.The first-order Tykhonov regularization method is used to obtain reasonable estimation.By analyzing the optimality condition of estimation problem,the discrete adjoint state equation and discrete adjoint gradient are derived based on the numerical scheme of the continuous equations.A quasi-Newton numerical optimization method related to adjoint gradient is proposed to solve the estimation problem.The estimation results with different regularization coefficients are compared and analyzed by numerical experiments.The deviation between the estimated pressure obtained without regularization and the real pressure is large.Estimation result with smaller deviation and higher smoothness can be obtained through appropriate regularization coefficient.When the observation error is large,the observed values generated by the estimated pressure fit well with the real pressure.展开更多
文摘In order to obtain an accurate tide description in the China Seas, the 2-dimensional nonlinear numerical Princeton Ocean Model （POM） is employed to incorporate in situ tidal measurements both from tide gauges and TOPEX/POSEIDON （T/P） derived datasets by means of the variational adjoint approach in such a way that unknown internal model parameters, bottom topography, friction coefficients and open boundary conditions, for example, are adjusted during the process. The numerical model is used as a forward model. After the along-track T/P data are processed, two classical methods, i.e. harmonic and response analysis, are implemented to estimate the tide from such datasets with a domain covering the model area extending from 0° to 41°N in latitude and from 99°E to 142°E in longitude. And the results of these two methods are compared and interpreted. The numerical simulation is performed for 16 major constituents. In the data assimilation experiments, three types of unknown parameters （water depth, bottom friction and tidal open boundary conditions in the model equations） are chosen as control variables. Among the various types of data assimilation experiments, the calibration of water depth brings the most promising results. By comparing the results with selected tide gauge data, the average absolute errors are decreased from 7.9 cm to 6.8 cm for amplitude and from 13.0° to 9.0° for phase with respect to the semidiurnal tide M2 constituent, which is the largest tidal constituent in the model area. After the data assimilation experiment is performed, the comparison between model results and tide gauge observation for water levels shows that the RMS errors decrease by 9 cm for a total of 14 stations, mostly selected along the coast of China's Mainland, when a one-month period is considered, and the correlation coefficients improve for most tidal stations among these stations.
基金Project supported by the National Basic Research Program of China(No.2014CB744100)the National Natural Science Foundation of China(Nos.61403245 and 91648119)the Shanghai Municipal Science and Technology Commision(No.14500500400)
文摘We present a new aerodynamic design method based on the lattice Boltzmann method （LBM） and the adjoint approach. The flow field and the adjoint equation are numerically simulated by the GILBM （generalized form of interpolation supplemented LBM） on non-uniform meshes. The first-order approximation for the equilibrium dis- tribution function on the boundary is proposed to diminish the singularity of boundary conditions. Further, a new treatment of the solid boundary in the LBM is described par- ticularly for the airfoil optimization design problem. For a given objective function, the adjoint equation and its boundary conditions are derived analytically. The feasibility and accuracy of the new approach have been perfectly validated by the design optimization of NACA0012 airfoil.
文摘The significance of flow optimization utilizing the lattice Boltzmann(LB)method becomes obvious regarding its advantages as a novel flow field solution method compared to the other conventional computational fluid dynamics techniques.These unique characteristics of the LB method form the main idea of its application to optimization problems.In this research,for the first time,both continuous and discrete adjoint equations were extracted based on the LB method using a general procedure with low implementation cost.The proposed approach could be performed similarly for any optimization problem with the corresponding cost function and design variables vector.Moreover,this approach was not limited to flow fields and could be employed for steady as well as unsteady flows.Initially,the continuous and discrete adjoint LB equations and the cost function gradient vector were derived mathematically in detail using the continuous and discrete LB equations in space and time,respectively.Meanwhile,new adjoint concepts in lattice space were introduced.Finally,the analytical evaluation of the adjoint distribution functions and the cost function gradients was carried out.
文摘Diffuse optical tomography (DOT) using near-infrared (NIR) light is a promising tool for noninvasive imaging of deep tissue. The approach is capable of reconstructing the quantitative optical parameters (absorption coefficient and scattering coefficient) of a soft tissue. The motivation for reconstructing the optical property variation is that it and, in particular, the absorption coefficient variation, can be used to diagnose different metabolic and disease states of tissue. In DOT, like any other medical imaging modality, the aim is to produce a reconstruction with good spatial resolution and in contrast with noisy measurements. The parameter recovery known as inverse problem in highly scattering biological tissues is a nonlinear and ill-posed problem and is generally solved through iterative methods. The algorithm uses a forward model to arrive at a prediction flux density at the tissue boundary. The forward model uses light transport models such as stochastic Monte Carlo simulation or deterministic methods such as radioactive transfer equation (RTE) or a simplified version of RTE namely the diffusion equation (DE). The finite element method (FEM) is used for discretizing the diffusion equation. The frequently used algorithm for solving the inverse problem is Newton-based Model based Iterative Image Reconstruction (N-MoBIIR). Many Variants of Gauss-Newton approaches are proposed for DOT reconstruction. The focuses of such developments are 1) to reduce the computational complexity;2) to improve spatial recovery;and 3) to improve contrast recovery. These algorithms are 1) Hessian based MoBIIR;2) Broyden-based MoBIIR;3) adjoint Broyden-based MoBIIR;and 4) pseudo-dynamic approaches.
文摘In this paper,we study the state estimation of compressible single phase flow in compressible porous media.The initial pressure distribution is estimated according to discrete adjoint approach based on the collected well pressure data.The first-order Tykhonov regularization method is used to obtain reasonable estimation.By analyzing the optimality condition of estimation problem,the discrete adjoint state equation and discrete adjoint gradient are derived based on the numerical scheme of the continuous equations.A quasi-Newton numerical optimization method related to adjoint gradient is proposed to solve the estimation problem.The estimation results with different regularization coefficients are compared and analyzed by numerical experiments.The deviation between the estimated pressure obtained without regularization and the real pressure is large.Estimation result with smaller deviation and higher smoothness can be obtained through appropriate regularization coefficient.When the observation error is large,the observed values generated by the estimated pressure fit well with the real pressure.
