Searched for: subject%3A%22data%255C-driven%255C%2Bmodeling%22
(1 - 20 of 38)

Pages

document
Gökalan, Emre (author)
Greenhouses offer the promise to mitigate the challenges faced by traditional open field agri- culture. Operating these systems on a commercial scale demands effective control and forecast models. This thesis contributes to the increasing field of research that applies methods from systems and control to greenhouse systems. The primary objective...
master thesis 2024
document
Dziarnowska, Weronika (author)
Researchers have been interested in studying the connection between emotion and memory for decades but much remains unknown due to the elusive nature of the human brain. Furthering our understanding of the phenomenon is crucial for improving the treatment of neurological disorders associated with emotion dysregulation, as well as for enhancing...
master thesis 2023
document
Krijnen, Rogier (author)
This thesis investigates the ability of Bayesian EUCLID to retrieve a predictive approximate material model for the myocardium in the presence of heterogeneous deformation fields due to simulated biaxial stretch tests. The Holzapfel-Ogden material model is used as the ground-truth material model of the simulation, since it is capable of...
master thesis 2023
document
van Laarhoven, Menno (author)
<br/>We expand on the framework by Korda and Mezic (2020) to construct eigenfunctions directly from data by exploiting the eigenfunction PDE, guaranteeing closure and eliminating the need for a prior data dictionary. <br/>The constructed models are extended to forced systems through the multi-step prediction error of a linear state-space model....
master thesis 2023
document
de Boer, Jens (author)
A significant decrease in greenhouse gas emissions can be achieved by including a prediction of future power consumption in the control of ships’ power plants during transits. Moreover, including a prediction of power consumption in the Energy Management System (EMS) during Dynamic Positioning (DP) operations can also contribute to a reduction...
master thesis 2023
document
Cademartori, Giulia (author), Oneto, Luca (author), Valdenazzi, Federica (author), Coraddu, A. (author), Gambino, Andrea (author), Anguita, Davide (author)
The prediction of ship motions and quiescent periods, is of paramount importance for the maritime industry. The capability to predict these events sufficiently in advance has the potential to improve the safety and efficiency of several marine operations, such as landing and take-off on aircraft carriers, transfer of cargo, and mating...
review 2023
document
Dekhovich, A. (author), Turan, O.T. (author), Jiaxiang, Y. (author), Bessa, M.A. (author)
Data-driven modeling in mechanics is evolving rapidly based on recent machine learning advances, especially on artificial neural networks. As the field matures, new data and models created by different groups become available, opening possibilities for cooperative modeling. However, artificial neural networks suffer from catastrophic...
journal article 2023
document
Pini, M. (author), Giuffré, A. (author), Cappiello, A. (author), Majer, M. (author), Bunschoten, E.C. (author)
Modeling non-ideal compressible flows in the context of computational fluid-dynamics (CFD) requires the calculation of thermodynamic state properties at each step of the iterative solution process. To this purpose, the use of a built-in fundamental equation of state (EoS) in entropic form, i.e., s= s(e, ρ), can be particularly cost-effective,...
book chapter 2023
document
Valchev, Iliya (author), Coraddu, A. (author), Kalikatzarakis, Miltiadis (author), Geertsma, R.D. (author), Oneto, Luca (author)
Monitoring and evaluating the biofouling state and its effects on the vessel's hull and propeller performance is a crucial problem that attracts the attention of both academy and industry. Effective and reliable tools to address this would allow a timely cleaning procedure able to trade off costs, efficiency, and environmental impacts. In...
review 2022
document
Forouzandeh Shahraki, N. (author), Zomorodian, Zahra Sadat (author), Tahsildoost, Mohammad (author), Shaghaghian, Zohreh (author)
Recent studies have focused on data-driven methods for building energy efficiency, by using simulated or empirical data, for energy-based design assessment rather than the common physics-based techniques, which are mostly time-consuming. In this paper, the feasibility of using seven different Machine Learning models, including three single...
journal article 2022
document
Tian, X. (author), Voskov, D.V. (author)
In this paper, we describe adjoint gradient formulation for the Operator-Based Linearization modeling approach. Adjoint gradients are implemented in Delft Advanced Research Terra Simulator (DARTS) framework and applied for history matching using a proxy methodology. Due to the application of adjoint gradients, the computational efficiency of...
journal article 2022
document
Valchev, I. (author), Coraddu, A. (author), Oneto, L. (author), Kalikatzarakis, M. (author), Tiddens, W. (author), Geertsma, R.D. (author)
Deterministic models based on the laws of physics, as well as data-driven models, are often used to assess the current state of vessels and their systems, as well as predict their future behaviour. Predictive maintenance methodologies (i.e., Condition Based Maintenance), and advanced control strategies (i.e., Model Predictive Control), are built...
journal article 2022
document
Coraddu, A. (author), Kalikatzarakis, Miltiadis (author), Theotokatos, Gerasimos (author), Geertsma, R.D. (author), Oneto, Luca (author)
Accurate, reliable, and computationally inexpensive models of the dynamic state of combustion engines are a fundamental tool to investigate new engine designs, develop optimal control strategies, and monitor their performance. The use of those models would allow to improve the engine cost-efficiency trade-off, operational robustness, and...
book chapter 2022
document
Asadiesfahani, MAHDI (author)
Evaluating an adequate computer model representing the characteristics of a subsurface reservoir is of great importance in the oil and gas industry. With recent data acquisition developments, high-resolution geological models can be generated for the subsurface reservoirs; however, uncertainties of geological data and too many details in the...
master thesis 2021
document
Borghi, Alessandro (author)
The ability to compute models that correctly predict the trajectories of a nonlinear system can become a significant challenge in systems and control. The introduction of Koopman operator theory helped to deal with this challenge. The Koopman operator is a composition operator that globally describes a nonlinear system in an infinite-dimensional...
master thesis 2021
document
Kramer, O.J.I. (author)
In drinking water treatment plants, multiphase flows are a frequent phenomenon. Examples of such flows are pellet-softening and filter backwashing where liquid-solid fluidisation is applied. A better grasp of these fluidisation processes is needed to be able to determine optimal hydraulic states. In this research, models were developed, and...
doctoral thesis 2021
document
Enthoven, Maarten (author)
At the Center for Ultrasound and Brain imaging at Erasmus MC in Rotterdam, a mouse's visual cortex had been imaged using the fUS technique. The mouse had been exposed to different visual stimuli. The stimuli varied in position, size, and shape. We investigate how the measured task-based fUS signals differ depending on the visual stimuli...
master thesis 2021
document
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
document
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
document
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
Searched for: subject%3A%22data%255C-driven%255C%2Bmodeling%22
(1 - 20 of 38)

Pages