Searched for: subject:"data%5C+assimilation"
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Wang, Z. (author)
This dissertation's ultimate goal is to provide solutions to two problems that the promising data assimilation method, called the Particle Filter, has when applied to high dimensional non-linear models, such as those often used in hydrological research and forecasting. Two local particle filters have been proposed to overcome three major issues....
doctoral thesis 2021
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Belligoli, Z. (author)
The continuous increase in the number of flights in the last decades caused a steepgrowth of aviation-related pollution to the point that the aviation sector is responsible for3% of the global greenhouse gas emissions. Regulators have been slow at catching up withthis problem, and stringent emission targets have been put in place only very...
doctoral thesis 2021
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Xiao, C. (author)
In the community of petroleum engineering, the use of surrogate modelling techniques have recently gained more and more popularity to improve the efficiency of history matching. However, it is still not possible to fully utilize their potential in realistic applications. One of the challenges is to retain high accuracy while increasing the...
doctoral thesis 2021
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Lopez Restrepo, S. (author), Nino-Ruiz, Elias D. (author), Guzman-Reyes, Luis G. (author), Yarce, Andres (author), Quintero, O. L. (author), Pinel, Nicolas (author), Segers, Arjo (author), Heemink, A.W. (author)
In this paper, we propose an efficient and practical implementation of the ensemble Kalman filter via shrinkage covariance matrix estimation. Our filter implementation combines information brought by an ensemble of model realizations, and that based on our prior knowledge about the dynamical system of interest. We perform the combination of...
journal article 2021
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Xiao, C. (author), Leeuwenburgh, O. (author), Lin, H.X. (author), Heemink, A.W. (author)
Imaging-type monitoring techniques are used in monitoring dynamic processes in many domains, including medicine, engineering, and geophysics. This paper aims to propose an efficient workflow for application of such data for the conditioning of simulation models. Such applications are very common in e.g. the geosciences, where large-scale...
journal article 2021
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Saredi, E. (author), Tumuluru Ramesh, Nikhilesh (author), Sciacchitano, A. (author), Scarano, F. (author)
State observer techniques are investigated for the assimilation of three-dimensional velocity measurements into computational fluid dynamics simulations based on Reynolds-averaged Navier–Stokes (RANS) equations. The method relies on a forcing term, or observer, in the momentum equation, stemming from the difference between the computed velocity...
journal article 2021
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Çakir, Bora (author)
Closure of Collar's triangle represents a complete framework of fluid-structure interactions (FSI) enabling the comprehensive understanding of different design elements compromising aeronautical applications. Experimental methods such as tomographic particle image velocimetry (Tomo-PIV) are proven to provide accurate acquisition opportunities of...
master thesis 2020
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de Hoon, N.H.L.C. (author)
Heart and vessel diseases, or cardiovascular diseases (CVDs), are globally the main cause of mortality and morbidity. The blood flow plays an important role in their occurrence and progression. Therefore, knowledge of the blood flow is of key importance to reduce and threat these diseases. This knowledge requires both high-quality data and an...
doctoral thesis 2020
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Zijlker, Tammo (author)
This study aims to improve estimates of NOx emission strengths by assimilation of TROPOMI satellite retrievals in the LOTOS-EUROS chemical transport model. Nitrogen oxides (NO and NO2) play a pivotal role in atmospheric chemistry, are an important source of air pollution and contribute to nitrogen deposition over vulnerable natural areas....
master thesis 2020
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Bode, Danielle (author)
Predictions of the morphology of coastal areas are used to make decisions on coastal defence and nature conservation. To predict this morphology, simulations made by morphological models are used. To base decisions on this morphology predictions, we want the uncertainties in these predictions to be small. The goal of this research is to get a...
master thesis 2020
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Nino-Ruiz, Elias David (author), Mancilla-Herrera, Alfonso (author), Lopez Restrepo, S. (author), Quintero-Montoya, Olga (author)
This paper proposes an efficient and practical implementation of the Maximum Likelihood Ensemble Filter via a Modified Cholesky decomposition (MLEF-MC). The method works as follows: via an ensemble of model realizations, a well-conditioned and full-rank square-root approximation of the background error covariance matrix is obtained. This...
journal article 2020
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Tangdamrongsub, Natthachet (author), Han, Shin Chan (author), Yeo, In Young (author), Dong, Jianzhi (author), Steele-Dunne, S.C. (author), Willgoose, Garry (author), Walker, Jeffrey P. (author)
Assimilating remote sensing observations into land surface models has become common practice to improve the accuracy of terrestrial water storage (TWS) estimates such as soil moisture and groundwater, for understanding the land surface interaction with the climate system, as well as assessing regional and global water resources. Such remote...
journal article 2020
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Allaerts, D.J.N. (author), Quon, Eliot (author), Draxl, Caroline (author), Churchfield, Matthew (author)
Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal...
journal article 2020
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Cho, Y. (author), Huang, Yilin (author), Verbraeck, A. (author)
Dynamic data-driven simulation (DDDS) incorporates real-time measurement data to improve simulation models during model run-time. Data assimilation (DA) methods aim to best approximate model states with imperfect measurements, where particle Filters (PFs) are commonly used with discrete-event simulations. In this paper, we study three critical...
conference paper 2020
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Lu, Y. (author), Steele-Dunne, S.C. (author), De Lannoy, Gabriëlle J.M. (author)
Surface heat fluxes are vital to hydrological and environmental studies, but mapping them accurately over a large area remains a problem. In this study, brightness temperature (TB) observations or soil moisture retrievals from the NASA Soil Moisture Active Passive (SMAP) mission and land surface temperature (LST) product from the...
journal article 2020
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Wang, Z. (author), Hut, R.W. (author), van de Giesen, N.C. (author)
Particle filters are non-Gaussian filters, which means that the assumption that the error distribution of the ensemble should be Gaussian is unnecessary. Like the ensemble Kalman filter, particle filters are based on the Monte Carlo approximation to represent the distribution of model states. It requires a substantial number of particles to...
journal article 2020
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Jesus de Moraes, R. (author), Hajibeygi, H. (author), Jansen, J.D. (author)
In data assimilation problems, various types of data are naturally linked to different spatial resolutions (e.g., seismic and electromagnetic data), and these scales are usually not coincident to the subsurface simulation model scale. Alternatives like upscaling/downscaling of the data and/or the simulation model can be used, but with...
journal article 2020
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Jin, J. (author)
Severe dust storms present great threats to the environment, property and human health over the areas in the downwind of arid regions. Several dynamical dust models have been developed to predict the dust concentrations in the atmosphere. Currently, the accuracy of these models is limited mainly due to the imperfect modeling of dust emissions....
doctoral thesis 2019
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Terleth, Niels (author)
Due to their powerful approximation capabilities, artificial neural networks have seen a wide interest in various fields. A particular application is the use of an artificial neural network to predict solutions of the governing equations for fluid flow i.e. the Navier-Stokes equations. This is done by taking the space and time variables as the...
master thesis 2019
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Tumuluru Ramesh, Nikhilesh (author)
Experimental fluid dynamics and computational fluid dynamics have traditionally been treated as disparate fields of study. However, each field has its own unique set of advantages and disadvantages. Data assimilation is a field that can be used to leverage some of the advantages each field offers to help compensate mutual<br/>weaknesses. In this...
master thesis 2019
Searched for: subject:"data%5C+assimilation"
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