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Eskilsson, C. (2025). Verification & validation of CFD simulations of a fixed oscillating water column with one- and two-way absorption. In: Innovations in Renewable Energies Offshore - Proceedings of the 6th International Conference on Renewable Energies Offshore, RENEW 2024: . Paper presented at 6th International Conference on Renewable Energies Offshore, RENEW 2024. Lisbon. 19 November 2024 through 21 November 2024 (pp. 211-208). CRC Press/Balkema
Open this publication in new window or tab >>Verification & validation of CFD simulations of a fixed oscillating water column with one- and two-way absorption
2025 (English)In: Innovations in Renewable Energies Offshore - Proceedings of the 6th International Conference on Renewable Energies Offshore, RENEW 2024, CRC Press/Balkema , 2025, p. 211-208Conference paper, Published paper (Refereed)
Abstract [en]

This work focuses on the validation of the two-phase Navier-Stokes model interFoam, part of the OpenFOAM finite volume framework, applied to the case of a fixed oscillating water column. The model is validated against experimental results from the Technical University of Denmark. Both twoand one-way absorption, i.e. only the upor downstroke is used to drive the flow through the orifice, are investigated. For the one-way absorption cases a numerical one-way valve is employed. The results show a good fit to the experimental values for the two-way absorption, but for the one-way absorption the pressure, and subsequently power generation, is off. The reason is unresolved problems with the numerical one-way valve. Further, for the two-way absorption a formal solution verification was performed, showing the simulations had less than 7% numerical uncertainty arising from the spatial discretization

Place, publisher, year, edition, pages
CRC Press/Balkema, 2025
Keywords
Navier Stokes equations; CFD simulations; Downstrokes; Finite-volume; Flowthrough; Navier-Stokes model; OpenFOAM; Oscillating water column; Technical University of Denmark; Two phase; Two ways; Computational fluid dynamics
National Category
Mechanical Engineering
Identifiers
urn:nbn:se:ri:diva-76170 (URN)10.1201/9781003558859-24 (DOI)2-s2.0-85208568958 (Scopus ID)
Conference
6th International Conference on Renewable Energies Offshore, RENEW 2024. Lisbon. 19 November 2024 through 21 November 2024
Available from: 2024-11-22 Created: 2024-11-22 Last updated: 2024-11-22Bibliographically approved
Palm, J., Verao Fernandez, G. & Eskilsson, C. (2025). Verification of constrained multi-body motion in MoodyMarine. In: Innovations in Renewable Energies Offshore: Proceedings of the 6th International Conference on Renewable Energies Offshore, RENEW 2024. Paper presented at 6th International Conference on Renewable Energies Offshore, RENEW 2024. Lisbon. 19 November 2024 through 21 November 2024 (pp. 173-182). CRC Press, 14
Open this publication in new window or tab >>Verification of constrained multi-body motion in MoodyMarine
2025 (English)In: Innovations in Renewable Energies Offshore: Proceedings of the 6th International Conference on Renewable Energies Offshore, RENEW 2024, CRC Press, 2025, Vol. 14, p. 173-182Conference paper, Published paper (Refereed)
Abstract [en]

MoodyMarine is a weakly nonlinear potential flow model for wave-body and mooring  simulations with a graphical user interface. In this work we present the extension of the model to deal with constrained multi-body dynamics. By combining different translation and rotation constraints most joints can be modelled. As the constraints are imposed through springs and dampers in the explicit time-stepping algorithm, a slight manual tuning is required to make sure the bodies are constrained properly. Nevertheless, this tuning is shown not to influence the final results. In the paper we compare to existing test cases in literature as well as against experimental data. In all test cases there is a good agreement between the target solutions and MoodyMarine .

Place, publisher, year, edition, pages
CRC Press, 2025
National Category
Applied Mechanics
Identifiers
urn:nbn:se:ri:diva-76260 (URN)10.1201/9781003558859-20 (DOI)978-1-032-90557-0 (ISBN)
Conference
6th International Conference on Renewable Energies Offshore, RENEW 2024. Lisbon. 19 November 2024 through 21 November 2024
Funder
Swedish Energy Agency, 50196-1
Note

Support for this work was given by the Swedish Energy Agency through Grant No. 50196-1, by Hugo Hammar’s Fund for Maritime Research through project No. 322, and by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No.101068736.

Available from: 2024-12-09 Created: 2024-12-09 Last updated: 2024-12-10Bibliographically approved
Abedi, H. & Eskilsson, C. (2025). Wind Turbine Aerodynamics Simulation Using the Spectral/hp Element Framework Nektar++. Wind, 5, Article ID 5010006.
Open this publication in new window or tab >>Wind Turbine Aerodynamics Simulation Using the Spectral/hp Element Framework Nektar++
2025 (English)In: Wind, E-ISSN 2674-032X, Vol. 5, article id 5010006Article in journal (Refereed) Published
Abstract [en]

Wind power plays an increasingly vital role in sustainable energy development. However, accurately simulating wind turbine aerodynamics, particularly in offshore wind farms, remains challenging due to complex environmental factors such as the marine atmospheric boundary layer. This study investigates the integration and assessment of the Actuator Line Model (ALM) within the high-order spectral/hp element framework, Nektar++, for wind turbine aerodynamic simulations. The primary objective is to evaluate the implementation and effectiveness of the ALM by analyzing aerodynamic loads, wake behavior, and computational demands. A three-bladed NREL-5MW turbine is modeled using the ALM in Nektar++, with results compared against established computational fluid dynamics (CFD) tools, including SOWFA and AMR-Wind. The findings demonstrate that Nektar++ effectively captures velocity and vorticity fields in the turbine wake while providing aerodynamic load predictions that closely align with finite-volume CFD models. Furthermore, the spectral/hp element framework exhibits favorable scalability and computational efficiency, indicating that Nektar++ is a promising tool for high-fidelity wind turbine and wind farm aerodynamic research.

Keywords
actuator line model (ALM); Nektar++; spectral/hp element method; high-order simulation; wake characteristics; aerodynamic loads; computational fluid dynamics (CFD)
National Category
Fluid Mechanics
Identifiers
urn:nbn:se:ri:diva-77979 (URN)10.3390/wind5010006 (DOI)
Funder
Swedish Energy Agency, 2021-029520
Note

 This research was conducted within the framework of the VindEl program and received funding from the Swedish Energy Agency (Energimyndigheten) under the grant No. 2021-029520

Available from: 2025-02-24 Created: 2025-02-24 Last updated: 2025-04-01Bibliographically approved
Eskilsson, C., Fernandez, G. V., Andersen, J. & Palm, J. (2024). High-Fidelity Hydrodynamic Simulations of a Slack-Moored Floating Offshore Wind Turbine Platform. International Journal of Offshore and Polar Engineering, 34(3), 246-253
Open this publication in new window or tab >>High-Fidelity Hydrodynamic Simulations of a Slack-Moored Floating Offshore Wind Turbine Platform
2024 (English)In: International Journal of Offshore and Polar Engineering, ISSN 1053-5381, Vol. 34, no 3, p. 246-253Article in journal (Refereed) Published
Abstract [en]

We numerically simulate the hydrodynamic response of a floating offshore wind turbine (FOWT) using computational fluid dynamics. The FOWT under consideration is a slack-moored 1:70 scale model of the UMaine VolturnUS-S semi-submersible platform. The test cases under consideration are (i) static equilibrium load cases, (ii) free decay tests, and (iii) two focused wave cases of different wave steepness. The FOWT is modelled using a two-phase Navier-Stokes solver inside the OpenFOAM-v2006 framework. The catenary mooring is computed by dynamically solving the equations of motion for an elastic cable using the MoodyCore solver. The results are shown to be in good agreement with measurements.

Place, publisher, year, edition, pages
International Society of Offshore and Polar Engineers, 2024
Keywords
Computational fluid dynamics; Hydrodynamics; Mooring; Offshore wind turbines; Computational fluid; Floating offshore wind turbines; Fluid-dynamics; High-fidelity; Hydrodynamic response; Hydrodynamic simulation; Scale-model; Static equilibrium; Submersible platforms; Test case; computational fluid dynamics; floating structure; hydrodynamics; mooring system; simulation; wind turbine; wind wave; Navier Stokes equations
National Category
Fluid Mechanics
Identifiers
urn:nbn:se:ri:diva-76043 (URN)10.17736/ijope.2024.sv15 (DOI)2-s2.0-85205431465 (Scopus ID)
Funder
Swedish Energy Agency, 44423-2EU, Horizon Europe, 101068736Swedish Research Council, 2018-05973,
Note

Support for this work was given by the Swedish Energy Agency through Grant No. 44423-2 and EU Horizon through the MSCA-PF Grant No. 101068736. Computations were performed on resources at (i) the National Supercomputer Centre provided by NAISS, partially funded by the Swedish Research Council through Grant Agreement No. 2018-05973, and (ii) LUMI though DeiC National HPC Grant Agreement No. DeiC-AAU-N3-2023017.

Available from: 2024-10-30 Created: 2024-10-30 Last updated: 2025-02-09Bibliographically approved
Palm, J., Fernandez, G. V. & Eskilsson, C. (2024). Verification of constrained multi-body motion in MoodyMarine. In: Innovations in Renewable Energies Offshore - Proceedings of the 6th International Conference on Renewable Energies Offshore, RENEW 2024: . Paper presented at 6th International Conference on Renewable Energies Offshore, RENEW 2024. Lisbon, Portugal. 19 November 2024 through 21 November 2024 (pp. 173-181). CRC Press/Balkema
Open this publication in new window or tab >>Verification of constrained multi-body motion in MoodyMarine
2024 (English)In: Innovations in Renewable Energies Offshore - Proceedings of the 6th International Conference on Renewable Energies Offshore, RENEW 2024, CRC Press/Balkema , 2024, p. 173-181Conference paper, Published paper (Refereed)
Abstract [en]

MoodyMarine is a weakly nonlinear potential flow model for wave-body and mooring simulations with a graphical user interface. In this work we present the extension of the model to deal with constrained multi-body dynamics. By combining different translation and rotation constraints most joints can be modelled. As the constraints are imposed through springs and dampers in the explicit time-stepping algorithm, a slight manual tuning is required to make sure the bodies are constrained properly. Nevertheless, this tuning is shown not to influence the final results. In the paper we compare to existing test cases in literature as well as against experimental data. In all test cases there is a good agreement between the target solutions and MoodyMarine.

Place, publisher, year, edition, pages
CRC Press/Balkema, 2024
Keywords
Flow simulation; Nonlinear simulations; User interfaces; Body motions; Manual tuning; Multi-body; Multibody dynamic (MBD); Nonlinear potential; Potential flow model; Target solution; Test case; Time stepping algorithms; Weakly non-linear; Mooring
National Category
Environmental Engineering
Identifiers
urn:nbn:se:ri:diva-76121 (URN)10.1201/9781003558859-20 (DOI)2-s2.0-85208533034 (Scopus ID)9781003558859 (ISBN)
Conference
6th International Conference on Renewable Energies Offshore, RENEW 2024. Lisbon, Portugal. 19 November 2024 through 21 November 2024
Available from: 2025-01-07 Created: 2025-01-07 Last updated: 2025-01-07Bibliographically approved
Eskilsson, C. & Engsig-Karup, A. P. (2024). Water wave simulations using fully nonlinear potential flow: Spectral/hp element models implemented in Nektar++. In: Proceedings from the 26th Numerical Towing Tank Symposium NuTTS'24: . Paper presented at 26th Numerical Towing Tank Symposium NuTTS'24, 23-25 October 2024, Mulheim/Ruhr, Germany.
Open this publication in new window or tab >>Water wave simulations using fully nonlinear potential flow: Spectral/hp element models implemented in Nektar++
2024 (English)In: Proceedings from the 26th Numerical Towing Tank Symposium NuTTS'24, 2024Conference paper, Published paper (Other academic)
National Category
Water Engineering
Identifiers
urn:nbn:se:ri:diva-76261 (URN)
Conference
26th Numerical Towing Tank Symposium NuTTS'24, 23-25 October 2024, Mulheim/Ruhr, Germany
Funder
Swedish Energy Agency, 51388-1
Note

This work is supported by the Swedish Energy Agency through grant no. 51388-1 obtained by CE. This work issupported by the Danish COWIFONDEN through project no. A-165.19 obtained by APEK. 

Available from: 2024-12-09 Created: 2024-12-09 Last updated: 2024-12-10Bibliographically approved
Eskilsson, C., Pashami, S., Holst, A. & Palm, J. (2023). A hybrid linear potential flow - machine learning model for enhanced prediction of WEC performance. In: Proceedings of the 15th European Wave and Tidal Energy Conference: . Paper presented at The 15th European Wave and Tidal Energy Conference.
Open this publication in new window or tab >>A hybrid linear potential flow - machine learning model for enhanced prediction of WEC performance
2023 (English)In: Proceedings of the 15th European Wave and Tidal Energy Conference, 2023Conference paper, Published paper (Refereed)
Abstract [en]

Linear potential flow (LPF) models remain the tools-of-the trade in marine and ocean engineering despite their well-known assumptions of small amplitude waves and motions. As of now, nonlinear simulation tools are still too computationally demanding to be used in the entire design loop, especially when it comes to the evaluation of numerous irregular sea states. In this paper we aim to enhance the performance of the LPF models by introducing a hybrid LPF-ML (machine learning) approach, based on identification of nonlinear force corrections. The corrections are defined as the difference in hydrodynamic force (vis- cous and pressure-based) between high-fidelity CFD and LPF models. Using prescribed chirp motions with different amplitudes, we train a long short-term memory (LSTM) network to predict the corrections. The LSTM network is then linked to the MoodyMarine LPF model to provide the nonlinear correction force at every time-step, based on the dynamic state of the body and the corresponding forces from the LPF model. The method is illustrated for the case of a heaving sphere in decay, regular and irregular waves – including passive control. The hybrid LPF-model is shown to give significant improvements compared to the baseline LPF model, even though the training is quite generic.

Keywords
Linear potential flow, machine learning, recurrent neural network, floating bodies, wave energy
National Category
Marine Engineering
Identifiers
urn:nbn:se:ri:diva-72107 (URN)10.36688/ewtec-2023-321 (DOI)
Conference
The 15th European Wave and Tidal Energy Conference
Funder
Swedish Energy Agency, 50196-1
Available from: 2024-03-02 Created: 2024-03-02 Last updated: 2025-02-10Bibliographically approved
Andersen, J. & Eskilsson, C. (2023). Detached-Eddy Simulation of Normal Flow past Flat Plates: The Influence from Corner Curvature. International Journal of Offshore and Polar Engineering, 33(4), 359-366
Open this publication in new window or tab >>Detached-Eddy Simulation of Normal Flow past Flat Plates: The Influence from Corner Curvature
2023 (English)In: International Journal of Offshore and Polar Engineering, ISSN 1053-5381, Vol. 33, no 4, p. 359-366Article in journal (Refereed) Published
Place, publisher, year, edition, pages
International Society of Offshore and Polar Engineers, 2023
National Category
Marine Engineering
Identifiers
urn:nbn:se:ri:diva-72115 (URN)10.17736/ijope.2023.jc912 (DOI)
Available from: 2024-03-02 Created: 2024-03-02 Last updated: 2025-02-10Bibliographically approved
Eskilsson, C., Pashami, S., Holst, A. & Palm, J. (2023). Estimation of nonlinear forces acting on floating bodies using machine learning. In: J. W. Ringsberg, C. Guedes Soares (Ed.), Advances in the Analysis and Design of Marine Structures: (pp. 63-72). Boca Raton: CRC Press
Open this publication in new window or tab >>Estimation of nonlinear forces acting on floating bodies using machine learning
2023 (English)In: Advances in the Analysis and Design of Marine Structures / [ed] J. W. Ringsberg, C. Guedes Soares, Boca Raton: CRC Press, 2023, p. 63-72Chapter in book (Other academic)
Abstract [en]

Numerical models used in the design of floating bodies routinely rely on linear hydrodynamics. Extensions for hydrodynamic nonlinearities can be approximated using e.g. Morison type drag and nonlinear Froude-Krylov forces. This paper aims to improve the approximation of nonlinear forces acting on floating bodies by using machine learning (ML). Many ML models are general function approximators and therefore suitable for representing such nonlinear correction terms. A hierarchical modelling approach is used to build mappings between higher-fidelity simulations and the linear method. The ML corrections are built up for FNPF, Euler and RANS simulations. Results for decay tests of a sphere in model scale using recurrent neural networks (RNN) are presented. The RNN algorithm is shown to satisfactory predict the correction terms if the most nonlinear case is used as training data. No difference in the performance of the RNN model is seen for the different hydrodynamic models.

Place, publisher, year, edition, pages
Boca Raton: CRC Press, 2023
National Category
Marine Engineering
Identifiers
urn:nbn:se:ri:diva-72114 (URN)10.1201/9781003399759 (DOI)9781003399759 (ISBN)
Funder
Swedish Energy Agency, 50196-1
Available from: 2024-03-02 Created: 2024-03-02 Last updated: 2025-02-17Bibliographically approved
Eskilsson, C., Pashami, S., Holst, A. & Palm, J. (2023). Hierarchical Approaches to Train Recurrent Neural Networks for Wave-Body Interaction Problems. In: The Proceedings of the 33rd International Ocean and Polar Engineering Conference: . Paper presented at The 33rd International Ocean and Polar Engineering Conference. , 33, Article ID 307.
Open this publication in new window or tab >>Hierarchical Approaches to Train Recurrent Neural Networks for Wave-Body Interaction Problems
2023 (English)In: The Proceedings of the 33rd International Ocean and Polar Engineering Conference, 2023, Vol. 33, article id 307Conference paper, Published paper (Refereed)
Abstract [en]

We present a hybrid linear potential flow - machine learning (LPF-ML) model for simulating weakly nonlinear wave-body interaction problems. In this paper we focus on using hierarchical modelling for generating training data to be used with recurrent neural networks (RNNs) in order to derive nonlinear correction forces. Three different approaches are investigated: (i) a baseline method where data from a Reynolds averaged Navier Stokes (RANS) model is directly linked to data from a LPF model to generate nonlinear corrections; (ii) an approach in which we start from high-fidelity RANS simulations and build the nonlinear corrections by stepping down in the fidelity hierarchy; and (iii) a method starting from low-fidelity, successively moving up the fidelity staircase. The three approaches are evaluated for the simple test case of a heaving sphere. The results show that the baseline model performs best, as expected for this simple test case. Stepping up in the fidelity hierarchy very easily introduce errors that propagate through the hierarchical modelling via the correction forces. The baseline method was found to accurately predict the motion of the heaving sphere. The hierarchical approaches struggled with the task, with the approach that steps down in fidelity performing somewhat better of the two.

Keywords
Wave-body interaction; hierarchical modelling; linear potential flow; hybrid modeling; machine learning; recurrent neural net- work.
National Category
Marine Engineering
Identifiers
urn:nbn:se:ri:diva-72110 (URN)
Conference
The 33rd International Ocean and Polar Engineering Conference
Funder
Swedish Energy Agency, 50196-1
Available from: 2024-03-02 Created: 2024-03-02 Last updated: 2025-02-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6934-634x

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