Searched for: subject%3A%22Bayesian%255C%2BOptimization%22
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Begall, Moritz J. (author), Schweidtmann, A.M. (author), Mhamdi, Adel (author), Mitsos, Alexander (author)
Computational Fluid Dynamics (CFD) is a powerful tool which can help with the geometry optimization of continuous milli-scale reactors, which often are highly complex devices. Attempting to perform this optimization by manually modifying and testing geometry configurations can however be tedious and computationally inefficient. Addressing...
journal article 2023
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Liang, M. (author), Schlangen, E. (author), Šavija, B. (author)
Stress evolution of restrained concrete is directly related to early-age cracking (EAC) potential of concrete, which is a tricky problem that often happens in engineering practice. Due to the global objective of carbon reduction, Ground granulated blast furnace slag (GGBFS) concrete has become a more promising binder comparing with Ordinary...
book chapter 2023
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Liang, M. (author), Chang, Z. (author), Wan, Z. (author), Gan, Y. (author), Schlangen, E. (author), Šavija, B. (author)
This study aims to provide an efficient and accurate machine learning (ML) approach for predicting the creep behavior of concrete. Three ensemble machine learning (EML) models are selected in this study: Random Forest (RF), Extreme Gradient Boosting Machine (XGBoost) and Light Gradient Boosting Machine (LGBM). Firstly, the creep data in...
journal article 2022
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Cicirello, A. (author), Giunta, F. (author)
Two non-intrusive uncertainty propagation approaches are proposed for the performance analysis of engineering systems described by expensive-to-evaluate deterministic computer models with parameters defined as interval variables. These approaches employ a machine learning based optimization strategy, the so-called Bayesian optimization, for...
journal article 2022
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Ashok, Aravind (author)
The advancement in the steering capabilities of fibre placement machines has improved the tailoring potential and therefore the design possibilities for composite structures. However, the larger design freedom leads to complex and non-convex design spaces. Finding the optimum solution thus becomes costly and challenging, specifically considering...
master thesis 2021
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D'Elia, Evelyn (author)
Designing controllers for complex robots is not an easy task. Often, researchers hand-tune controllers for humanoid robots, but this is a time-consuming approach that yields a single controller which cannot generalize well to varied tasks. This thesis presents a method which uses the NSGA-II multi-objective optimization (MOO) algorithm with...
master thesis 2021
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Basien, Henricus (author)
This MSc. thesis presents the extensive research conducted on designing neural networks capable of generating reactionary dance motions. The research was conducted in collaboration with Stichting Another kind of Blue (AKOB) and CompactCopters UG (CC). It is set within the industry context of the ’AI-man’ project, developed...
master thesis 2021
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Leenders, Nick (author)
In order to reduce the levelised cost of energy, the rotors of wind turbines are increasing in size. To increase the energy yield, wind turbine rotors need to have an innovative tip design; such as winglets. Winglets are used widely in aircraft design; however, they remain mostly absent in state-of-the-art wind turbine design. The low-fidelity...
master thesis 2021
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van Dam, Daniël (author)
Suspended microchannel resonators are a kind of mechanical resonator with an embedded microchannel inside. This is done as for some samples it is convenient or even necessary to put the sample into a fluid. The sample can then travel through the channel and its mass can be determined. The channel also simplifies placement of the samples compared...
master thesis 2021
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van der Knaap, Leon (author)
One of the planning problems encountered by the Dutch Railways (NS) at shunting yards is the train unit shunting problem (TUSP). This problem considers idle train units that have to be parked, be cleaned, undergo regular maintenance, and be reconfigured into the scheduled departing train compositions. A local search algorithm is being developed...
master thesis 2021
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Deen, Mitchell (author)
Recent years have shown a tremendous increase in the application of Artificial Intelligence to the field of radiology, often through the extraction and analysis of large numbers of quantitative features from medical images. These applications increase the demand for machine learning models to extract information from these images. To provide...
master thesis 2021
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Storm, Joep (author)
Designing engineering structures relies on accurate numerical simulations to predict the behaviour of a structure before its realization. In the design process, many variables influence the final structure. There is an incentive for optimizing the design based on the desire for cheaper structures and less material usage. Although a wide variety...
master thesis 2021
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Guvenir Torun, Su (author), Torun, Hakki M. (author), Hansen, Hendrik H.G. (author), Gandini, Giulia (author), Berselli, Irene (author), Codazzi, Veronica (author), de Korte, Chris L. (author), van der Steen, A.F.W. (author), Migliavacca, Francesco (author), Chiastra, Claudio (author), Akyildiz, A.C. (author)
Atherosclerotic plaque rupture in coronary arteries, an important trigger of myocardial infarction, is shown to correlate with high levels of pressure-induced mechanical stresses in plaques. Finite element (FE) analyses are commonly used for plaque stress assessment. However, the required information of heterogenous material properties of...
journal article 2021
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Hao, Zhimian (author), Caspari, Adrian (author), Schweidtmann, A.M. (author), Vaupel, Yannic (author), Lapkin, Alexei A. (author), Mhamdi, Adel (author)
Pressure swing adsorption (PSA) is an energy-efficient technology for gas separation, while the multiobjective optimization of PSA is a challenging task. To tackle this, we propose a hybrid optimization framework (TSEMO + DyOS), which integrates two steps. In the first step, a Bayesian stochastic multiobjective optimization algorithm (i.e.,...
journal article 2021
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Karlsson, R.K.A. (author), Bliek, L. (author), Verwer, S.E. (author), de Weerdt, M.M. (author)
One method to solve expensive black-box optimization problems is to use a surrogate model that approximates the objective based on previous observed evaluations. The surrogate, which is cheaper to evaluate, is optimized instead to find an approximate solution to the original problem. In the case of discrete problems, recent research has...
conference paper 2021
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Kasprzyk, Szymon (author)
Metamaterials are a relatively new group of materials whose behaviour strongly depends on the design of their internal structure. They can be employed in a wide range of applications, one of which is presented in this thesis. As cardiovascular diseases account for around 30% of deaths worldwide the research done in the field of Materials Science...
master thesis 2020
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Dev, Shikhar (author)
Hyperparameter optimization(HPO) forms a critical aspect for machine learning applications to attain superior performance. BOHB (Bayesian Optimization and HyperBand) is a state of the art HPO algorithm that approaches HPO in a multi-armed bandit strategy, augmented with Bayesian optimization to drive configuration sampling. However, BOHB...
master thesis 2020
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Turan, Taylan (author)
This research considers the offline training stage of the Reduced Order Models (ROM), that has been getting attention recently on the endeavor to come up with efficient solutions for the highly complex numerical models. In this work, a simply supported beam problem has been considered, for which a reduced basis creation has been investigated....
student report 2020
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Bliek, L. (author), Verwer, S.E. (author), de Weerdt, M.M. (author)
When a black-box optimization objective can only be evaluated with costly or noisy measurements, most standard optimization algorithms are unsuited to find the optimal solution. Specialized algorithms that deal with exactly this situation make use of surrogate models. These models are usually continuous and smooth, which is beneficial for...
journal article 2020
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Lago, Jesus (author), De Ridder, Fjo (author), Vrancx, Peter (author), De Schutter, B.H.K. (author)
Motivated by the increasing integration among electricity markets, in this paper we propose two different methods to incorporate market integration in electricity price forecasting and to improve the predictive performance. First, we propose a deep neural network that considers features from connected markets to improve the predictive...
journal article 2018
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