The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform
Guillaume Balarac - One of the best experts on this subject based on the ideXlab platform.
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Subgrid-scale scalar flux modelling based on Optimal estimation theory and machine-learning procedures
Journal of Turbulence, 2017Co-Authors: Antoine Vollant, Guillaume Balarac, Christophe Eric CorreAbstract:New procedures are explored for the development of models in the context of large eddy simulation (LES) of a passive scalar. They rely on the combination of the Optimal Estimator theory with machine-learning algorithms. The concept of Optimal Estimator allows to identify the most accurate set of parameters to be used when deriving a model. The model itself can then be defined by training an artificial neural network (ANN) on a database derived from the filtering of direct numerical simulation (DNS) results. This procedure leads to a subgrid scale model displaying good structural performance, which allows to perform LESs very close to the filtered DNS results. However, this first procedure does not control the functional performance so that the model can fail when the flow configuration differs from the training database. Another procedure is then proposed, where the model functional form is imposed and the ANN used only to define the model coefficients. The training step is a bi-objective optimisation in order to control both structural and functional performances. The model derived from this second procedure proves to be more robust. It also provides stable LESs for a turbulent plane jet flow configuration very far from the training database but over-estimates the mixing process in that case.
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Optimal Estimator and artificial neural network as efficient tools for the subgrid-scale scalar flux modeling
2014Co-Authors: Antoine Vollant, Guillaume Balarac, Gianluca Geraci, Christophe Eric CorreAbstract:This work is devoted to exploring a new procedure to develop subgrid-scale (SGS) models in the context of large-eddy simulation (LES) of a passive scalar. Starting from the Noll's formula (Noll 1967), the concept of an Optimal Estimator is first used to de- termine an accurate set of parameters to derive a SGS model. The SGS model is then defined as a surrogate model built from this set of parameters by training an artificial neural network (ANN) on a filtered DNS database. This ANN model is next compared with the dynamic nonlinear tensorial diffusivity (DNTD) model proposed by Wang et al. (2007). The DNTD model is also based on Noll's formula, and can be seen as a nonlinear extension of the dynamic eddy-diffusivity (DED) model proposed by Moin et al. (1991). The a priori and a posteriori tests performed on the ANN model demonstrate the abil- ity of this new model to well reproduce the behavior of the exact SGS term, and show an improvement in comparison with DED and DNTD models. The concept of Optimal Estimator associated with machine learning procedure thus appears as a useful tool for SGS model development
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Development of a new dynamic procedure for the Clark model of the subgrid-scale scalar flux using the concept of Optimal Estimator
Physics of Fluids, 2011Co-Authors: Yannick Fabre, Guillaume BalaracAbstract:Accurate prediction of a scalar advected by a turbulent flow is needed for various applications. In the framework of large-eddy simulation (LES), an accurate subgrid-scale (SGS) model for the subgrid-scale scalar flux has to be used. In this work, the performance of various dynamic SGS models is first evaluated by a priori tests through the concept of Optimal Estimator. Direct numerical simulation (DNS) in homogeneous isotropic turbulence is performed on 5123 grid points. Filtered quantities are extracted from the DNS data using a box or a spectral cut-off filter. The models' accuracy is then evaluated in term of structural and functional performances, i.e., the model capacity to locally approximate the SGS unknown term and to reproduce its energetic action, respectively. It is shown that the Clark model has the best set of parameters to describe the SGS scalar flux. However, the classic dynamic procedure usually applied to compute the model coefficient leads to a large error. A new dynamic procedure is thus proposed to reduce this error. The results show that the new dynamic model leads to a good accuracy, which is not expectable from a model based only on the parameters of the classic dynamic Smagorinsky model. To better evaluate the improvement of the new dynamic procedure, a posteriori (large-eddy simulation) tests are performed for three different Schmidt numbers. It is shown that the new model allows to improve substantially the prediction of various scalar statistics.
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Development of a new dynamic procedure for the Clark model of the subgrid-scale scalar flux using the concept of Optimal Estimator
Physics of Fluids, 2011Co-Authors: Yannick Fabre, Guillaume BalaracAbstract:Accurate prediction of a scalar advected by a turbulent flow is needed for various applications. In the framework of large-eddy simulation (LES), an accurate subgrid-scale (SGS) model for the subgrid-scale scalar flux has to be used. In this work, the performance of various dynamic SGS models is first evaluated by a priori tests through the concept of Optimal Estimator. Direct numerical simulation (DNS) in homogeneous isotropic turbulence is performed on 5123 grid points. Filtered quantities are extracted from the DNS data using a box or a spectral cut-off filter. The models’ accuracy is then evaluated in term of structural and functional performances, i.e., the model capacity to locally approximate the SGS unknown term and to reproduce its energetic action, respectively. It is shown that the Clark model has the best set of parameters to describe the SGS scalar flux. However, the classic dynamic procedure usually applied to compute the model coefficient leads to a large error. A new dynamic procedure is t...
N.j. Kasdin - One of the best experts on this subject based on the ideXlab platform.
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Designing an Optimal Estimator for more efficient wavefront correction
Techniques and Instrumentation for Detection of Exoplanets V, 2011Co-Authors: Tyler Groff, N.j. KasdinAbstract:Space-based coronagraphs for future earth-like planet detection will require focal plane wavefront control techniques to achieve the necessary contrast levels. These correction algorithms are iterative and the control methods require an estimate of the electric field at the science camera, which requires nearly all of the images taken for the correction. In order to maximize science time the amount of time required for correction must be minimized, which means reducing the number of exposures required for correction. This means reducing both the number of iterations and the number of exposures per iteration required to achieve a targeted contrast. Given the large number of images required for estimation, the ideal choice is to use fewer exposures to estimate the electric field. Here we demonstrate an Optimal Estimator that uses prior knowledge to create the estimate of the electric field. In this way we can Optimally estimate the electric field by minimizing the number of exposures required to estimate under an error constraint. The performance of this method is compared to a pairwise Estimator which is designed to give the least-squares minimal error. This allows us to evaluate the number of images necessary to achieve a contrast target and is the first step towards generating an adaptive algorithm which combines estimation and control to optimize the entire correction problem.
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Two-step Optimal Estimator for three dimensional target tracking
IEEE Transactions on Aerospace and Electronic Systems, 2005Co-Authors: Pini Gurfil, N.j. KasdinAbstract:This study presents an adaptation of a novel estimation methodology to the general nonlinear three-dimensional problem of tracking a maneuvering target. The two-step Optimal Estimator (TSE) suggests an attractive alternative to the standard extended Kalman filter (EKF). A superior performance is accomplished by dividing the estimation problem into two steps: a linear first step and a nonlinear second step. The target tracking performance of the TSE is shown to be better than an EKF implemented in either inertial or modified spherical coordinates. In the passive case, where bearing/elevation angles only are measured, the TSE yields excellent range and target acceleration estimates. In the active case, where range measurement is available as well, a homing missile employing closed-loop Optimal guidance based on the TSE state estimates obtains smaller miss distances than with either versions of the EKF.
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Recursive Satellite Attitude Estimation with the Two-Step Optimal Estimator
AIAA Guidance Navigation and Control Conference and Exhibit, 2002Co-Authors: N.j. Kasdin, Thomas J. M. WeaverAbstract:This paper presents a new approach to recursive satellite attitude determination from vector observations that utilizes the two-step Optimal Estimator. It will be shown that near Optimal results are obtained with very realistic noise and sensor models. The twostep Estimator was introduced in 1995 as an alternative to the Extended Kalman Filter (EKF) for recursive estimation with nonlinear measurements. By breaking the measurement update process into two-steps, a linear first step using a nonlinear transformation of the desired states and a non-recursive second step minimization to recover the desired states, a near Optimal estimation is possible. It has been shown that for certain systems this process recovers the global Optimal solution. It will be demonstrated here that the problem of estimating the quaternion attitude representation of a satellite comes very close to this global optimum. Simulations will show dramatic improvements in performance over the traditional EKF and other attitude Estimators.
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Two-step Optimal Estimator for three dimensional target tracking
Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 1Co-Authors: Pini Gurfil, N.j. KasdinAbstract:This study presents an adaptation of a novel estimation methodology to the general nonlinear three-dimensional problem of tracking a maneuvering target. The two-step Optimal Estimator (TSE) suggests an attractive alternative to the standard extended Kalman filter (EKF). A superior performance is accomplished by dividing the estimation problem into two steps: a linear first step and a nonlinear second step. The target tracking performance of the TSE is shown to be better than the EKF implemented in either inertial or modified spherical coordinates.
F. Schiavon - One of the best experts on this subject based on the ideXlab platform.
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An Optimal Estimator for the CMB-LSS angular power spectrum and its application to WMAP and NVSS data
Monthly Notices of the Royal Astronomical Society, 2012Co-Authors: F. Schiavon, Fabio Finelli, Alessandro Gruppuso, A. Marcos-caballero, P. Vielva, Robert Crittenden, R. B. Barreiro, Enrique Martínez-gonzálezAbstract:We use a Quadratic Maximum Likelihood (QML) method to estimate the angular power spectrum of the cross-correlation between cosmic microwave background and large scale structure maps as well as their individual auto-spectra. We describe our implementation of this method and demonstrate its accuracy on simulated maps. We apply this Optimal Estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. With the correction of the declination systematics in NVSS, we can safely use most of the information contained in this survey. We then make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP 7 year and NVSS maps with 1.8$^\circ$ resolution, the best-fit model has a cosmological constant of approximatively 70% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).
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an Optimal Estimator for the cmb lss angular power spectrum and its application to wmap and nvss data
Monthly Notices of the Royal Astronomical Society, 2012Co-Authors: F. Schiavon, Fabio Finelli, Alessandro Gruppuso, P. Vielva, Robert Crittenden, R. B. Barreiro, A Marcoscaballero, E MartinezgonzalezAbstract:We use a quadratic maximum likelihood (QML) method to estimate the angular power spectrum of the cross-correlation between cosmic microwave background and large-scale structure maps as well as their individual auto-spectra. We describe our implementation of this method and demonstrate its accuracy on simulated maps. We apply this Optimal Estimator to Wilkinson Microwave Anisotropy Probe (WMAP) 7-yr and National Radio Astronomical Observatory (NRAO) Very Large Array Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. With the correction of the declination systematics in NVSS, we can safely use most of the information contained in this survey. We then make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat Λ cold dark matter model by different likelihood prescriptions. When using just the cross-correlation between WMAP 7-yr and NVSS maps with 1°.8 resolution, the best-fitting model has a cosmological constant of approximately 70 per cent of the total energy density, disfavouring an Einstein–de sitter universe at more than 2σ confidence level.
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An Optimal Estimator for the correlation of CMB anisotropies with Large Scale Structures and its application to WMAP-7year and NVSS
2012Co-Authors: F. SchiavonAbstract:In the thesis we present the implementation of the quadratic maximum likelihood (QML) method, ideal to estimate the angular power spectrum of the cross-correlation between cosmic microwave background (CMB) and large scale structure (LSS) maps as well as their individual auto-spectra. Such a tool is an Optimal method (unbiased and with minimum variance) in pixel space and goes beyond all the previous harmonic analysis present in the literature. We describe the implementation of the QML method in the {\it BolISW} code and demonstrate its accuracy on simulated maps throughout a Monte Carlo. We apply this Optimal Estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. Taking into account the shot noise and one of the systematics (declination correction) in NVSS, we can safely use most of the information contained in this survey. On the contrary we neglect the noise in temperature since WMAP is already cosmic variance dominated on the large scales. Because of a discrepancy in the galaxy auto spectrum between the estimates and the theoretical model, we use two different galaxy distributions: the first one with a constant bias $b$ and the second one with a redshift dependent bias $b(z)$. Finally, we make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP7 and NVSS maps with 1.8° resolution, we show that $\Omega_\Lambda$ is about the 70\% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).
Yannick Fabre - One of the best experts on this subject based on the ideXlab platform.
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Development of a new dynamic procedure for the Clark model of the subgrid-scale scalar flux using the concept of Optimal Estimator
Physics of Fluids, 2011Co-Authors: Yannick Fabre, Guillaume BalaracAbstract:Accurate prediction of a scalar advected by a turbulent flow is needed for various applications. In the framework of large-eddy simulation (LES), an accurate subgrid-scale (SGS) model for the subgrid-scale scalar flux has to be used. In this work, the performance of various dynamic SGS models is first evaluated by a priori tests through the concept of Optimal Estimator. Direct numerical simulation (DNS) in homogeneous isotropic turbulence is performed on 5123 grid points. Filtered quantities are extracted from the DNS data using a box or a spectral cut-off filter. The models' accuracy is then evaluated in term of structural and functional performances, i.e., the model capacity to locally approximate the SGS unknown term and to reproduce its energetic action, respectively. It is shown that the Clark model has the best set of parameters to describe the SGS scalar flux. However, the classic dynamic procedure usually applied to compute the model coefficient leads to a large error. A new dynamic procedure is thus proposed to reduce this error. The results show that the new dynamic model leads to a good accuracy, which is not expectable from a model based only on the parameters of the classic dynamic Smagorinsky model. To better evaluate the improvement of the new dynamic procedure, a posteriori (large-eddy simulation) tests are performed for three different Schmidt numbers. It is shown that the new model allows to improve substantially the prediction of various scalar statistics.
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Development of a new dynamic procedure for the Clark model of the subgrid-scale scalar flux using the concept of Optimal Estimator
Physics of Fluids, 2011Co-Authors: Yannick Fabre, Guillaume BalaracAbstract:Accurate prediction of a scalar advected by a turbulent flow is needed for various applications. In the framework of large-eddy simulation (LES), an accurate subgrid-scale (SGS) model for the subgrid-scale scalar flux has to be used. In this work, the performance of various dynamic SGS models is first evaluated by a priori tests through the concept of Optimal Estimator. Direct numerical simulation (DNS) in homogeneous isotropic turbulence is performed on 5123 grid points. Filtered quantities are extracted from the DNS data using a box or a spectral cut-off filter. The models’ accuracy is then evaluated in term of structural and functional performances, i.e., the model capacity to locally approximate the SGS unknown term and to reproduce its energetic action, respectively. It is shown that the Clark model has the best set of parameters to describe the SGS scalar flux. However, the classic dynamic procedure usually applied to compute the model coefficient leads to a large error. A new dynamic procedure is t...
Pini Gurfil - One of the best experts on this subject based on the ideXlab platform.
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Two-step Optimal Estimator for three dimensional target tracking
IEEE Transactions on Aerospace and Electronic Systems, 2005Co-Authors: Pini Gurfil, N.j. KasdinAbstract:This study presents an adaptation of a novel estimation methodology to the general nonlinear three-dimensional problem of tracking a maneuvering target. The two-step Optimal Estimator (TSE) suggests an attractive alternative to the standard extended Kalman filter (EKF). A superior performance is accomplished by dividing the estimation problem into two steps: a linear first step and a nonlinear second step. The target tracking performance of the TSE is shown to be better than an EKF implemented in either inertial or modified spherical coordinates. In the passive case, where bearing/elevation angles only are measured, the TSE yields excellent range and target acceleration estimates. In the active case, where range measurement is available as well, a homing missile employing closed-loop Optimal guidance based on the TSE state estimates obtains smaller miss distances than with either versions of the EKF.
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Two-step Optimal Estimator for three dimensional target tracking
Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 1Co-Authors: Pini Gurfil, N.j. KasdinAbstract:This study presents an adaptation of a novel estimation methodology to the general nonlinear three-dimensional problem of tracking a maneuvering target. The two-step Optimal Estimator (TSE) suggests an attractive alternative to the standard extended Kalman filter (EKF). A superior performance is accomplished by dividing the estimation problem into two steps: a linear first step and a nonlinear second step. The target tracking performance of the TSE is shown to be better than the EKF implemented in either inertial or modified spherical coordinates.