Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 41 for “"ensemble Kalman filter"”.
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Carbon Data Assimilation Using an Ensemble Kalman Filter
As a first step to build an ensemble data assimilation and source inversion system for atmospheric carbon, I implemented column-integrated carbon monoxide (CO) mixing ratio assimilation capability in an ensemble Kalman filter (EnKF) data assimilation system with the Weather Research and Forecasting …
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Strategies for Coupling Global and Limited-Area Ensemble Kalman Filter Assimilation
… All four strategies are formulated in the Local Ensemble Transform Kalman Filter (LETKF) framework. Numerical experiments are carried out with the model component of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) and the NCEP Regional Spectral Model (RSM). …
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Continuous reservoir model updating by ensemble Kalman filter on Grid computing architectures
… uncertainty are up-to-date for optimization. The ensemble Kalman filter (EnKF), a Bayesian approach for model updating, uses Monte Carlo statistics for fusing observation data with forecasts from simulations to estimate a range of plausible models. The ensemble of updated models can be used for …
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Continuous reservoir modeling updating by integrating experimental data using an ensemble Kalman Filter
The continuous researvoir model updating is widely used to calibrate reservoir simulation models to production data, but many challenges remain. First, few real field data are available to test the new history matching method, and most of the data sets are synthetic cases. Second, computational …
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Localization Performance Improvement of a Low-Resolution Robotic System using an Electro-Permanent Magnetic Interface and an Ensemble Kalman Filter
… end effector. On the state estimation side, an Ensemble Kalman Filter is implemented, along with a scaling system to prevent FASER Lab hardware from becoming stuck due to hardware limitations. Overall, the three modifications improved the test robot's autonomous convergence error by 98.5%, …
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Study on the Intensity and Track Prediction of Typhoon Yagi (2024) Based on Ensemble Kalman Filter Assimilation of Satellite and Radar Data
… assimilating satellite and radar data using the Ensemble Kalman Filter (EnKF) on the prediction of Typhoon Yagi (2024). Based on the Weather Research and Forecasting (WRF) model and the EnKF method, a series of sensitivity experiments with different assimilated observational data types were …
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Algorithms for Tomographic Reconstruction: Fast Back Projection and Cardiac Computed Tomography
… present a reconstruction algorithm based on the ensemble Kalman filter. The algorithm reconstructs a movie of the moving heart that is free of the motion artifacts of conventional methods.
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Estimating post-disaster traffic conditions using real-time data streams
… given traffic sensor measurements using an ensemble Kalman filter. The proposed algorithm is tested through numerical experiments and the results show that integrating the seismic hazard and bridge fragility model with the traffic model and traffic sensor data improves the post-disaster …
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Dynamic Magnetic Resonance Imaging
… imaging (MRI). The proposed imaging method, the ensemble Kalman filter, is a Monte Carlo approximation to the Kalman filter with reduced computational cost. The technique reconstructs images of snapshots taken during a cardiac cycle from a low number of measurements that can be obtained during …
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Investigation of sensitivity of surface deformation to subsurface properties and reservoir operations
… serve as the input of future inversions with the Ensemble Kalman Filter (EnKF).
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Design, evaluation, and validation of a naval ship structural health monitoring tool
… for structural health monitoring using nonlinear Kalman Filter methodologies such as the Extended Kalman Filter and the Ensemble Kalman Filter to identify damage within a structural model. Through the observation of structural responses and the formulation of a Kalman Filter, it is possible to …
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Particle filtering with Lagrangian data in a point vortex model
Particle filtering is a technique used for state estimation from noisy measurements. In fluid dynamics, a popular problem called Lagrangian data assimilation (LaDA) uses Lagrangian measurements in the form of tracer positions to learn about the changing flow field. Particle filtering can be applied …
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Validating Forecasting Strategies of Simple Epidemic Models on the 2015-2016 Zika Epidemic
… We employed the Parametric Bootstrapping and Ensemble Kalman Filter methods to assimilate data and then generated 14-day-ahead forecasts throughout the epidemic across five case studies. We visualized each forecast to show the training/testing split in data and associated prediction intervals. …
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A state-space approach to dynamic tomography
… characterization of the convergence of the ensemble Kalman filter, a new method for ensemble Kalman smoothing and theory regarding its convergence, the first four-dimensional reconstruction of electron density in the solar atmosphere, a new method for dynamic tomography called the …
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Real-time data assimilation in nonlinear dynamical systems
… models and data. First, we develop a Bayesian ensemble data assimilation method for a low-order model to self-adapt and self-correct any time that reference data become available. We apply the methodology to infer the thermoacoustic states and heat release parameters on the fly without storing …
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Modeling volcanic unrest by data assimilation
… data, I optimize a data assimilation technique, Ensemble Kalman Filter (EnKF), to improve its performance in forecasting volcanic unrests with multiple geodetic observations. Then, the robustness of the EnKF is confirmed in application to the unrest and 2009 eruption of Kerinci volcano, …
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Hydrologic data assimilation of multi-resolution microwave radiometer and radar measurements using ensemble smoothing
Previously, the ensemble Kalman filter (EnKF) has been used to estimate soil moisture and related fluxes by merging noisy low frequency microwave observations with forecasts from a conventional though uncertain land surface model (LSM). Here it is argued that soil moisture estimation is a …
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Data Assimilation and Applications in Forecasting
… by data assimilationand specifically the ensemble Kalman filter (EnKF). The first explores how spatial localization, an important method commonly used in the EnKF, can be extended to multiscale problems. Rather than using a single length scale when localizing, we construct a localized …
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Evaluating the 3D EnKF - VAR Hybrid Data Assimilation in GSI for Surface and Upper Level Analyses
… 3 dimensional analysis produced using the Hybrid Ensemble Kalman Filter (EnKF) Variational (VAR) Data Assimilation in the Gridpoint Statistical Interpolation (GSI) System. The data assimilation ingests the 1 hour forecast High-Resolution Rapid Refresh (HRRR) and The Global Ensemble Forecast …
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Improving the temporal consistency of satellite-based contrail detections using ensemble Kalman filtering
… by post-processing the model’s outputs with an ensemble Kalman filter. We create a hand-labeled dataset of 73 contrails tracked over a 2-hour time series which we use to quantify performance. We find that by adding temporal correlations, we are able to recover 53.25% of contrail pixels on an …
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