A5029573210- Meteorological Phenomena and Simulations
- Model Reduction and Neural Networks
- Advanced Numerical Methods in Computational Mathematics
- Climate variability and models
- Computational Fluid Dynamics and Aerodynamics
- Fluid Dynamics and Vibration Analysis
- Probabilistic and Robust Engineering Design
- Lattice Boltzmann Simulation Studies
- Oceanographic and Atmospheric Processes
- Fluid Dynamics and Turbulent Flows
- Geophysics and Gravity Measurements
- Nuclear physics research studies
- Wind and Air Flow Studies
- Reservoir Engineering and Simulation Methods
- Numerical methods for differential equations
- Nuclear Engineering Thermal-Hydraulics
- Differential Equations and Numerical Methods
- Particle physics theoretical and experimental studies
- Quantum Chromodynamics and Particle Interactions
- Atmospheric and Environmental Gas Dynamics
- Tropical and Extratropical Cyclones Research
- Advanced Mathematical Modeling in Engineering
- Advanced Optimization Algorithms Research
- Nuclear Physics and Applications
- Numerical methods in inverse problems
Florida State University
2015-2024
The University of Texas at Austin
2017-2024
Imperial College London
2021
Tel Aviv University
1979-2004
Goddard Space Flight Center
1984-2003
NOAA National Centers for Environmental Prediction
2001
Dubna State University
2000
Massachusetts Institute of Technology
1995
NOAA Geophysical Fluid Dynamics Laboratory
1992
Stanford University
1991
Variational four-dimensional (4D) data assimilation is performed using an adiabatic version of the National Meteorological Center (NMC) baroclinic spectral primitive equation model with operationally analyzed fields as well simulated datasets. Two limited-memory quasi-Newton minimization techniques were used to iteratively find minimum a cost function, NMC forecast constraint. The function consists weighted square sum differences between and observations over time interval. In all...
The cross section for true absorption of pions in nuclei was obtained from experiments at 85, 125, 165, 205, 245, and 315 MeV positive 125 165 negative pions. results are compared with theoretical calculations. inclusive pion scattering angular distribution also measured, the indicate that quasifree plays an important role backward scattering. total pion-nucleus is decomposed into its major channels: elastic scattering, inelastic absorption, single charge exchange, as a function energy...
Abstract Four‐dimensional variational data assimilation (4DVAR) is a powerful tool for in meteorology and oceanography. However, major hurdle use of 4DVAR realistic general circulation models the dimension control space (generally equal to size model state variable typically order 10 7 –10 8 ) high computational cost computing function its gradient that require integration adjoint model. In this paper, we propose approach based on proper orthogonal decomposition (POD). POD an efficient way...
During the last few years new meteorological variational analysis methods have evolved, requiring large-scale minimization of a nonlinear objective function described in terms discrete variables. The conjugate-gradient method was found to represent good compromise convergence rates and computer memory requirements between simpler more complex optimization. In this study different available algorithms are presented with aim assessing their use typical problems meteorology. Computational...
A novel non-intrusive reduced order model (NIROM) for fluid–structure interaction (FSI) has been developed. The is based on proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation method. method independent of the governing equations, therefore, it does not require modifications to source code. This first time that a NIROM was constructed FSI phenomena using POD RBF Another novelty this work implementation under framework an unstructured mesh finite element...
Summary We propose an improved framework for dynamic mode decomposition (DMD) of 2‐D flows problems originating from meteorology when a large time step acts like filter in obtaining the significant Koopman modes, therefore, classic DMD method is not effective. This study motivated by need to further clarify connection between modes and proper orthogonal (POD) modes. apply POD derive reduced order models (ROM) shallow water equations. Key innovations DMD‐based ROM introduced this paper are...
Summary This paper focuses on a new framework for obtaining nonintrusive (i.e., not requiring projecting of the governing equations onto reduced basis modes) order model two‐dimensional fluid problems. To overcome shortcomings intrusive reduction usually derived by combining Proper Orthogonal Decomposition and Galerkin projection methods, we developed novel technique randomized dynamic mode decomposition (DMD) as fast accurate option in reduction. Our approach utilizes an adaptive DMD to...
Abstract This paper presents a new nonlinear non‐intrusive reduced‐order model (NL‐NIROM) that outperforms traditional proper orthogonal decomposition (POD)‐based reduced order (ROM). improvement is achieved through the use of auto‐encoder (AE) and self‐attention based deep learning methods. The novelty this work it uses stacked (SAE) network to project original high‐dimensional dynamical systems onto low dimensional subspace predict fluid dynamics using an method. introduces reduction...
In variational data assimilation (VDA) for meteorological and/or oceanic models, the assimilated fields are deduced by combining model and gradient of a cost functional measuring discrepancy between solution observation, via first-order optimality system. However, existence uniqueness VDA problem along with convergence algorithms its implementation depend on convexity function. Properties local can be studying Hessian function in vicinity optimum. This shows necessity second-order...
Abstract A new optimal nudging dynamical relaxation technique is tested in the framework of 4‐dimensional variational data assimilation, applied to an adiabatic T40 version National Meteorological Center (NMC) spectral model with 18 vertical layers. Several experiments are performed using NMC operationally analysed data. assimilation algorithm also employed a parameter‐estimation mode determine vector coefficients. Results data‐assimilation involving estimated nudging, and compared. Issues...
We studied the 12C(p,2p+n) reaction at beam momenta of 5.9, 8.0, and 9.0 GeV/c. For quasielastic (p,2p) events p(f), momentum knocked-out proton before reaction, was compared (event by event) with p(n), coincident neutron momentum. |p(n)|>k(F)=0.220 GeV/c (the Fermi momentum) a strong back-to-back directional correlation between p(f) p(n) observed, indicative short-range n-p correlations. From we constructed distributions c.m. relative motion in longitudinal direction for correlated pairs....