Searched for: subject%3A%22data%255C-driven%255C+modeling%22
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Walker, J.M. (author), Coraddu, A. (author), Collu, Maurizio (author), Oneto, Luca (author)
The number of installed floating offshore wind turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system’s integrity, extending the...
journal article 2021
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Shang, Y. (author), Nogal Macho, M. (author), Wang, Haoyu (author), Wolfert, A.R.M. (author)
Performance evaluation and maintenance planning are gaining importance with ageing rail infrastructure and increasing demand on track safety and continuous availability. The discrete/point railway assets (e.g. bridges, level crossings) together with extended track sections constitute the main railway network infrastructure. The former has...
journal article 2021
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Huijing, Jasper P. (author), Dwight, R.P. (author), Schmelzer, M. (author)
In this short note we apply the recently proposed data-driven RANS closure modelling framework of Schmelzer et al.(2020) to fully three-dimensional, high Reynolds number flows: namely wall-mounted cubes and cuboids at Re=40,000, and a cylinder at Re=140,000. For each flow, a new RANS closure is generated using sparse symbolic regression based...
journal article 2021
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Walker, J.M. (author), Coraddu, A. (author), Oneto, Luca (author), Kilbourn, Stuart (author)
The number of installed Floating Offshore Wind Turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system's integrity, extending the...
conference paper 2021
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Eleftheroglou, N. (author)
Prognostics is an emerging field of research that enables the real-time health assessment of an engineering system and the prediction of its future state based on up-to-date information. This field integrates various scientific disciplines including physics/mechanics, computational statistics and probabilistic modeling, machine learning and...
doctoral thesis 2020
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Gnodde, Sjoerd (author)
The past decades, the increasing availability of data has paved the way for a new, data-driven generation of models. This research proposes a non-parametric Bayesian network (NPBN) to model hydrologic processes. The Bayesian network (BN) is a directed, acyclic graph in which the variables are represented by the nodes, and the conditional...
master thesis 2020
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Dong, Jianfei (author), Wang, T. (author)
Light therapies can be used to treat fungal infections. A general mechanism is attributed to the generation of cytotoxic reactive oxygen species (ROS) due to light stimulation. The effectiveness of these therapies has been widely studied in the literature via conducting biological experiments, where fungi are exposed to light with various...
journal article 2020
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Kramer, O.J.I. (author), de Moel, P.J. (author), Padding, J.T. (author), Baars, E.T. (author), El Hasadi, Yousef M.F. (author), Boek, E.S. (author), van der Hoek, J.P. (author)
In full-scale drinking water production plants in the Netherlands, central softening is widely used for reasons related to public health, client comfort, and economic and environmental benefits. Almost 500 million cubic meters of water is softened annually through seeded crystallisation in fluidised bed reactors. The societal call for a circular...
journal article 2020
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Mu, Li (author), Zheng, Feifei (author), Tao, Ruoling (author), Zhang, Qingzhou (author), Kapelan, Z. (author)
This case study uses a long short-term memory (LSTM)-based model to predict short-term urban water demands for the Hefei City of China. The performance of the LSTM-based model is compared with the autoregressive integrated moving average (ARIMA) model, the support vector regression (SVR) model, and the random forests (RF) model based on data...
journal article 2020
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Dembele, M. (author), Oriani, Fabio (author), Tumbulto, Jacob (author), Mariéthoz, Grégoire (author), Schaefli, Bettina (author)
Complete hydrological time series are necessary for water resources management and modeling. This can be challenging in data scarce environments where data gaps are ubiquitous. In many applications, repetitive gaps can have unfortunate consequences including ineffective model calibration, unreliable timing of peak flows, and biased statistics....
journal article 2019
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Amaranto, A. (author), Munoz-Arriola, F. (author), Solomatine, D.P. (author), Corzo, G. (author)
The aim of this paper is to improve semiseasonal forecast of groundwater availability in response to climate variables, surface water availability, groundwater level variations, and human water management using a two-step data-driven modeling approach. First, we implement an ensemble of artificial neural networks (ANNs) for the 300 wells...
journal article 2019
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Mozaffar, M. (author), Bostanabad, R. (author), Chen, W. (author), Ehmann, K. (author), Cao, J. (author), Bessa, M.A. (author)
Plasticity theory aims at describing the yield loci and work hardening of a material under general deformation states. Most of its complexity arises from the nontrivial dependence of the yield loci on the complete strain history of a material and its microstructure. This motivated 3 ingenious simplifications that underpinned a century of...
journal article 2019
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Tripathy, Navdeep (author)
In the thesis, the challenge of precisely developing a data-driven Linear Time Invariant MIMO Reticle Heating Induced Deformation Prediction (RHIDP) model for ASML's DUV systems is presented. The model is developed for two inputs, namely airflow temperature and dose for full field exposures. A reduced order data-driven based approach for...
master thesis 2018
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Zhu, Zhengqiu (author), Qiu, S. (author), Chen, Bin (author), Wang, Rongxiao (author), Qiu, Xiaogang (author)
The accurate prediction of hazardous gas dispersion process is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in a chemical cluster. Conventional Gaussian-based dispersion models can seldom give accurate predictions due to inaccurate input parameters and the computational errors. In order...
journal article 2018
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Bocovich, C. (author), Kanning, W. (author), Parekh, M. (author), Mooney, M. (author)
conference paper 2017
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Lievens, R.A. (author)
Marine contractors deal with processes that are understood qualitatively but are hard to quantify. The amount of data available for these processes is ever growing, and so too the intrinsic value that lies within this data. Several data driven model approaches can be used to analyse this process data, one being a Bayesian Network (BN) approach....
master thesis 2014
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Siek, M.B.L.A. (author)
Accurate predictions of storm surge are of importance in many coastal areas. This book focuses on data-driven modelling using methods of nonlinear dynamics and chaos theory for predicting storm surges. A number of new enhancements are presented: phase space dimensionality reduction, incomplete time series, phase error correction, finding true...
doctoral thesis 2011
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Hall, J. (author)
Task 20 has contributed to the methods and application of uncertainty analysis by targeting novel areas of uncertainty analysis and decision support. The research fell into four sub-tasks: 1) Development of an overall framework for uncertainty analysis in flood risk management decisions. 2) Development of new methods to deal with the uncertainty...
report 2009
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Kai, C. (author)
Coastal zones which are known as the interface between continents and oceans are vital and important to human beings because a majority of the world's population live in such zones (Nelson, 2007). Coastal systems are among the most dynamic and energetic environments on earth and they are continuously changing because of the dynamic interaction...
report 2009
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Wang, W. (author)
Abstract not available
doctoral thesis 2006
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