Searched for: subject%3A%22Surrogate%255C%2Bmodelling%22
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De Bosscher, Benjamin (author)
Airport terminals are complex sociotechnical systems, in which humans interact with diverse technical systems. A natural way to represent them is through agent-based modeling. However, this method has two drawbacks: it entails a heavy computational burden and the emergent properties are often difficult to analyze. The purpose of our research is...
master thesis 2023
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de Bruin, Bram (author)
Over the years, aero engines have evolved into the efficient turbofans present on commercial airliners today. Although these engines are very reliable, they still experience degradations in performance and reductions in component health. The degradation affects the operation of the engine, which can be measured using the pressure, temperature,...
master thesis 2022
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Niessen, Lex (author)
In the past decade, the application of Neural Networks (NNs) has received increasing interest due to the growth in computing power. In the field of computational mechanics, this has led to numerous publications presenting surrogate models to assist or replace conventional simulation methods. A subset of these networks, referred to as Graph...
master thesis 2022
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Holstvoogd, Jorijn (author)
Under the current climate change projections, droughts and extreme rainfall events are becoming more common and intense. During sustained droughts, soil cracks can develop in the topsoil of a dike. These soil cracks can enhance the infiltration and drainage of the dike, affecting the dike stability. This study’s main objective is to better...
master thesis 2022
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Wilkens, Laurent (author)
This work sets out the creation, verification and demonstration of an automated end-to-end tool for the multi-point fluid-dynamic optimization of turbomachinery. Taking into account multiple operating conditions during optimization aims to benefit the overall performance of turbomachines which are characterized by off-design operation and to...
master thesis 2022
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Restrepo Botero, Miguel (author)
Understanding the fatigue load history of wind turbines is critical for taking decisions regarding the lifetime of a project. However, direct measurement of fatigue loads at each turbine in a wind farm is unfeasible. For this reason, surrogate models offer a useful alternative. In this thesis, a methodology for creating surrogate models for...
master thesis 2022
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Andrade Castanheira, Francisco (author)
The optimization of interplanetary, low-­thrust trajectories is a computationally expensive aspect of preliminary mission design. To reduce the computational burden associated with it, surrogate models can be used as cheap approximations of the original fitness function. Training the surrogate models in a fully online manner can be done to...
master thesis 2022
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Star, Quinten (author)
Perforated monopiles show promise in providing a better alternative to the commonly used jacket-like substructures used in intermediate water depths in the range of 30 to 120 m. By introducing perforations near the vicinity of the splash zone the wave loads on the monopile can be mitigated and the fatigue damage reduced, which is the main...
master thesis 2022
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Martinez Colan, Andres (author)
Bayesian system identification has been extensively adopted in Structural Health Monitoring as a way to probabilistically infer unobservable parameters of the physical model of a structure using measurement data. Combining the Bayesian approach with distributed optic fibre sensors can potentially improve the accuracy and reduce the uncertainty...
master thesis 2022
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Lyons, Jeff (author)
In light of worsening climate change and an increased interest in adapting infrastructure to cope with its effects, model-based decision support has become an essential tool for policy makers. In conditions of deep uncertainty, models may be used to explore a large space of possible system behaviours and so encourage a wider consideration of the...
master thesis 2022
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Kamphuis, Arian (author)
Climatic conditions in uence peak discharges in rivers and change sea levels; therefore, attention to the safety of dikes is of ever growing importance. Macro instability is one of the dike failure mechanisms that can inundate the hinterland. Soil heterogeneity plays an important role in assessing dike safety, especially for slope stability,...
master thesis 2022
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Kaaij, Otto (author)
Machine learning models are being used extensively in many high impact scenarios. Many of these models are ‘black boxes’, which are almost impossible to interpret. Successful implementations have been limited by this lack of interpretability. One approach to increasing interpretability is to use imitation learning to extract a more interpretable...
bachelor thesis 2022
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Kaseb, Z. (author), Montazeri, H. (author)
Metamodels are developed and used for aerodynamic optimization of a ducted opening integrated into a high-rise building to maximize the amplification factor within the duct. The duct consists of a nozzle, a throat, and a diffuser. 211 high-resolution 3D RANS CFD simulations are performed to generate training and testing datasets. The space...
journal article 2022
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Ngo, Q.H. (author), Ranasinghe, Roshanka (author), Zevenbergen, C. (author), Kirezci, Ebru (author), Maheng, M.D. (author), Radhakrishnan, Mohanasundar (author), Pathirana, Assela (author)
Risk-informed flood risk management requires a comprehensive and quantitative risk assessment, which often demands multiple (thousands of) river and flood model simulations. Performing such a large number of model simulations is a challenge, especially for large, complex river systems (e.g., Mekong) due to the associated computational and...
journal article 2022
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Wang, Y. (author), Yu, Rongjie (author), Qiu, Shuhan (author), SUN, J. (author), Farah, H. (author)
Highly automated vehicles (HAVs) have been introduced to the transportation system for the purpose of providing safer mobility. Considering the expected long co-existence period of HAVs and human-driven vehicles (HDVs), the safety operation of HAVs interacting with HDVs needs to be verified. To achieve this, HAVs' Operational Design Domain ...
journal article 2022
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Sharifnia, E. (author), Tindemans, Simon H. (author)
Monte Carlo simulation is often used for the reliability assessment of power systems, but it converges slowly when the system is complex. Multilevel Monte Carlo (MLMC) can be applied to speed up computation without compromises on model complexity and accuracy that are limiting real-world effectiveness. In MLMC, models with different complexity...
conference paper 2022
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Garzón Díaz, J.A. (author), Kapelan, Z. (author), Langeveld, J.G. (author), Taormina, R. (author)
Surrogate models replace computationally expensive simulations of physically-based models to obtain accurate results at a fraction of the time. These surrogate models, also known as metamodels, have been employed for analysis, control, and optimization of water distribution and urban drainage systems. With the advent of machine learning (ML),...
review 2022
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Lin, Chaoning (author), Li, Tongchun (author), Chen, Siyu (author), Yuan, Li (author), van Gelder, P.H.A.J.M. (author), Yorke-Smith, N. (author)
Dam safety monitoring has become an important topic and is critical for evaluating a dam's safety status. This study focuses on identifying the mechanical properties of a concrete dam from long-term viscoelastic deformation monitoring data. A novel inversion framework is proposed in which a surrogate model, instead of the finite element model...
journal article 2022
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Milanoski, Dimitrios (author), Galanopoulos, Georgios (author), Zarouchas, D. (author), Loutas, Theodoros (author)
In this study, a multi-level Structural Health Monitoring methodology for stiffened composite panels is introduced. A digital twin (DT), that is, a three-dimensional finite element (FE) model, representing the pristine state baseline of the test article, is developed and verified for compressive loading in the post-buckling regime. The...
journal article 2022
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Kumthekar, A. (author), Ponnusami, Sathiskumar A. (author), van der Zwaag, S. (author), Turteltaub, S.R. (author)
Computationally-efficient surrogate models based on a Polynomial Chaos Expansion (PCE) are developed to quantify the uncertainties in the fracture behavior and lifetime of a self-healing thermal barrier coating system (SH-TBC) and a benchmark conventional TBC system. The surrogate models are built using deterministic information from...
journal article 2022
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