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Steiner, J. (author)The Dutch energy strategy expects renewable energy sources like wind and solar to provide around 70% of the yearly electricity by 2030. In order to achieve these targets, models that efficiently and accurately capture the flow around wind turbines would be immensely helpful for both planning and operation of wind farms.<br/><br/>For wind turbine...doctoral thesis 2023
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Hosseini, A. (author), Hage, Johannes (author), Meijer, Koen (author), Offerman, S.E. (author), Yang, Y. (author)In this paper a CFD analysis of HIsarna off-gas system for post combustion of CO-H2-carbon particle mixture is presented to evaluate the effect of different sub-models and parameters on the accuracy of predictions and simulation time. The effects of different mesh type, mesh grid size, radiation models, turbulent models, kinetic mechanism,...journal article 2023
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Elsinga, G.E. (author), Ishihara, Takashi (author), Hunt, J.C.R. (author)Direct numerical simulations up to Reλ = 1445 show that the scaling exponents for the enstrophy and the dissipation rate extrema are different and depend on the Reynolds number. A similar Reynolds number dependence of the scaling exponents is observed for the moments of the dissipation rate, but not for the moments of the enstrophy. Significant...journal article 2023
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Grabe, Cornelia (author), Jäckel, Florian (author), Khurana, Parv (author), Dwight, R.P. (author)Purpose: This paper aims to improve Reynolds-averaged Navier Stokes (RANS) turbulence models using a data-driven approach based on machine learning (ML). A special focus is put on determining the optimal input features used for the ML model. Design/methodology/approach: The field inversion and machine learning (FIML) approach is applied to...journal article 2023
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Diez Sanhueza, R.G. (author), Smit, S.H.H.J. (author), Peeters, J.W.R. (author), Pecnik, Rene (author)This paper presents a machine learning methodology to improve the predictions of traditional RANS turbulence models in channel flows subject to strong variations in their thermophysical properties. The developed formulation contains several improvements over the existing Field Inversion Machine Learning (FIML) frameworks described in the...journal article 2023
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Fehrs, Michael (author), Ritter, Markus (author), Helm, Sebastian (author), Mertens, C. (author)The Pazy Wing test case is a benchmark for the investigation of aeroelastic effects at very large deflections. Tip deformations in the order of 50% span were measured in wind tunnel tests, which renders this model highly attractive for the validation of numerical aeroelastic methods and tools for geometrically nonlinear, large deflection...conference paper 2022
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Steiner, J. (author), Dwight, R.P. (author), Viré, A.C. (author)The state-of-the-art in wind-farm flow-physics modeling is Large Eddy Simulation (LES) which makes accurate predictions of most relevant physics, but requires extensive computational resources. The next-fidelity model types are Reynolds-Averaged Navier–Stokes (RANS) which are two orders of magnitude cheaper, but resolve only mean quantities...journal article 2022
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Xu, R. (author), Zhou, Xu Hui (author), Han, Jiequn (author), Dwight, R.P. (author), Xiao, Heng (author)In fluid dynamics, constitutive models are often used to describe the unresolved turbulence and to close the Reynolds averaged Navier–Stokes (RANS) equations. Traditional PDE-based constitutive models are usually too rigid to calibrate with a large set of high-fidelity data. Moreover, commonly used turbulence models are based on the weak...journal article 2022
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Modesti, D. (author), Pirozzoli, Sergio (author)We carry out direct numerical simulations (DNS) of flow in a turbulent square duct by focusing on heat transfer effects, considering the case of unit Prandtl number. Reynolds numbers up to are considered that are much higher than in previous studies, and that yield clear scale separation between inner- and outer-layer dynamics. Close...journal article 2022
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Ben Hassan Saïdi, Ismaïl (author), Schmelzer, M. (author), Cinnella, Paola (author), Grasso, Francesco (author)A CFD-driven deterministic symbolic identification algorithm for learning explicit algebraic Reynolds-stress models (EARSM) from high-fidelity data is developed building on the frozen-training SpaRTA algorithm of [1]. Corrections for the Reynolds stress tensor and the production of transported turbulent quantities of a baseline linear eddy...journal article 2022
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Otero Rodriguez, G.J. (author)The global temperature rise, which directly results from greenhouse gases emitted by burning fossil fuels, requires humanity to harness renewable energy sources at an increased rate. However, renewable energy sources are either highly intermittent, such as wind and solar radiation, or available at low temperatures leading to low efficiencies of...doctoral thesis 2021
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Laskari, A. (author), McKeon, Beverley J. (author)The probability density function (p.d.f.) of the streamwise velocity has been shown to indicate the presence of uniform momentum zones in wall-bounded turbulent flows. Most studies on the topic have focused on the instantaneous characteristics of this p.d.f. In this work, we show how the use of time-resolved particle image velocimetry data...journal article 2021
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Sciacchitano, A. (author), Arpino, F. (author), Cortellessa, G. (author)We present an experimental benchmark database for the transitional cavity flow. The database is obtained by planar Particle Image Velocimetry measurements at the median plane of the cavity model, for Reynolds numbers between 6300 and 19,000 based on the cavity height. A detailed uncertainty analysis of the experimental results is performed...journal article 2021
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Zou, P. (author), Bricker, J.D. (author), Uijttewaal, W.S.J. (author)Concepts of a submerged floating tunnel (SFT) for novel sea-crossings have been researched in recent years. An SFT tube should be moored afloat by tensioned mooring systems to maintain the tube position under complex hydrodynamic loads. In-line force is amongst the dominant hydrodynamic parameters in the SFT cross-section design and the...journal article 2021
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Zhang, Yu (author), Dwight, R.P. (author), Schmelzer, M. (author), Gómez, Javier F. (author), Han, Zhong hua (author), Hickel, S. (author)Multi-fidelity optimization methods promise a high-fidelity optimum at a cost only slightly greater than a low-fidelity optimization. This promise is seldom achieved in practice, due to the requirement that low- and high-fidelity models correlate well. In this article, we propose an efficient bi-fidelity shape optimization method for...journal article 2021
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Kaandorp, Mikael L.A. (author), Dwight, R.P. (author)A novel machine learning algorithm is presented, serving as a data-driven turbulence modeling tool for Reynolds Averaged Navier-Stokes (RANS) simulations. This machine learning algorithm, called the Tensor Basis Random Forest (TBRF), is used to predict the Reynolds-stress anisotropy tensor, while guaranteeing Galilean invariance by making use...journal article 2020
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Piscaer, P.J. (author), Soloviev, O.A. (author), Verhaegen, M.H.G. (author)This paper discusses various practical problems arising in the design and simulation of predictive control methods for adaptive optics. Although there has been increased attention towards optimal prediction and control methods for AO systems, they are often tested in simplified simulation environments. The use of advanced AO simulators...conference paper 2020
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Schmelzer, M. (author), Dwight, R.P. (author), Cinnella, Paola (author)In this work recent advancements are presented in utilising deterministic symbolic regression to infer algebraic models for turbulent stress-strain relation with sparsity-promoting regression techniques. The goal is to build a functional expression from a set of candidate functions in order to represent the target data most accurately....conference paper 2020
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Tiberga, M. (author), Hennink, A. (author), Kloosterman, J.L. (author), Lathouwers, D. (author)Accurate methods to solve the Reynolds-Averaged Navier-Stokes (RANS) equations coupled to turbulence models are still of great interest, as this is often the only computationally feasible approach to simulate complex turbulent flows in large engineering applications. In this work, we present a novel discontinuous Galerkin (DG) solver for the...journal article 2020
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Schmelzer, M. (author), Dwight, R.P. (author), Cinnella, Paola (author)A novel deterministic symbolic regression method SpaRTA (Sparse Regression of Turbulent Stress Anisotropy) is introduced to infer algebraic stress models for the closure of RANS equations directly from high-fidelity LES or DNS data. The models are written as tensor polynomials and are built from a library of candidate functions. The machine...journal article 2019