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63. May political parties refuse to govern? On integrity, compromise and responsibility.

Author

Wendt, Fabian

Subjects
POLITICAL parties, POLITICAL philosophy, COALITION governments, POLITICAL science, INTEGRITY, THEORY (Philosophy)
Abstract

After the parliamentary elections in Germany in September 2017, the Christian Democratic Union (CDU), the Christian Social Union (CSU), The Greens (Bündnis90/Die Grünen) and the Free Democratic Party (FDP) started to negotiate about forming a coalition government. But, surprising to many, the FDP decided to let these coalition talks collapse, and many commentators in Germany found it highly problematic for a political party to refuse to take responsibility in government. Interestingly, the question whether (or: when) democratic parties may legitimately refuse to govern has so far been neglected in political theory and political philosophy. The article develops a general answer by discussing several possible reasons for thinking that it is sometimes wrong to refuse to govern and thereby engages both democratic theory and the recent literature on compromise. The resulting view is that parties have an 'integrity prerogative' that allows them to refuse to govern, except when there is no reasonable and stable alternative government coalition available. [ABSTRACT FROM AUTHOR]

Published
2023
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65. An approach for shear-stress based scour prediction.

Author

Coe, Ryan Geoffrey, primary, Gillespie, Alice, additional, Chartrand, Chris Clayton, additional, Morrow, Mike, additional, Delos-Reyes, Mike, additional, Wendt, Fabian, additional, Yu, Yi-Hsiang, additional, Oskan-Haller, Tuba, additional, Lomanaco, Pedro, additional, Roberts, Jesse D., additional, Olson, Sterling, additional, and Jones, Craig, additional

Published
2019
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71. Validation of Numerical Models of the Offshore Wind Turbine from the Alpha Ventus Wind Farm against Full-Scale Measurements within OC5 Phase III

Author

Popko, Wojciech, Robertson, Amy, Jonkman, Jason, Wendt, Fabian, Thomas, Philipp, Müller, Kolja, Kretschmer, Matthias, Hagen, Torbjørn Ruud, Galinos, Christos, Le Dreff, Jean Baptiste, Gilbert, Philippe, Auriac, Bertrand, Oh, Sho, Qvist, Jacob, Sørum, Stian Høegh, Suja-Thauvin, Loup, Shin, Hyunkyoung, Molins, Climent, Trubat, Pau, Bonnet, Paul, Bergua, Roger, Wang, Kai, Fu, Pengcheng, Cai, Jifeng, Cai, Zhisong, Alexandre, Armando, Harries, Robert, Popko, Wojciech, Robertson, Amy, Jonkman, Jason, Wendt, Fabian, Thomas, Philipp, Müller, Kolja, Kretschmer, Matthias, Hagen, Torbjørn Ruud, Galinos, Christos, Le Dreff, Jean Baptiste, Gilbert, Philippe, Auriac, Bertrand, Oh, Sho, Qvist, Jacob, Sørum, Stian Høegh, Suja-Thauvin, Loup, Shin, Hyunkyoung, Molins, Climent, Trubat, Pau, Bonnet, Paul, Bergua, Roger, Wang, Kai, Fu, Pengcheng, Cai, Jifeng, Cai, Zhisong, Alexandre, Armando, and Harries, Robert

Abstract

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project validates OWT models against the measurements recorded on a Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. The following operating conditions of the wind turbine were chosen for the validation: (1) idling below the cut-in wind speed, (2) rotor-nacelle assembly (RNA) rotation maneuver below the cut-in wind speed, (3) power production below and above the rated wind speed, and (4) shutdown. A number of validation load cases were defined based on these operating conditions. The following measurements were used for validation: (1) strains and accelerations recorded on the support structure and (2) pitch, yaw, and azimuth angles, generator speed, and electrical power recorded from the RNA. Strains were not directly available from the majority of the OWT simulation tools; therefore, strains were calculated based on out-of-plane bending moments, axial forces, and cross-sectional properties of the structural members. The simulation results and measurements were compared in terms of time series, discrete Fourier transforms, power spectral densities, and probability density functions of strains and accelerometers. A good match was achieved between the measurements and models setup by OC5 Phase III participants.

Published
2021

72. SCIM: universal single-cell matching with unpaired feature sets

Author

Stark, Stefan G, Ficek, Joanna, Locatello, Francesco, Bonilla, Ximena, Chevrier, Stéphane, Singer, Franziska, Aebersold, Rudolf, Al-Quaddoomi, Faisal S, Albinus, Jonas, Alborelli, Ilaria, Andani, Sonali, Attinger, Per-Olof, Bacac, Marina, Baumhoer, Daniel, Beck-Schimmer, Beatrice, Beerenwinkel, Niko, Beisel, Christian, Bernasconi, Lara, Bertolini, Anne, Bodenmiller, Bernd, Casanova, Ruben, Chicherova, Natalia, D'Costa, Maya, Danenberg, Esther, Davidson, Natalie, gan, Monica-Andreea Dră, Dummer, Reinhard, Engler, Stefanie, Erkens, Martin, Eschbach, Katja, Esposito, Cinzia, Fedier, André, Ferreira, Pedro, Frei, Anja L, Frey, Bruno, Goetze, Sandra, Grob, Linda, Gut, Gabriele, Günther, Detlef, Haberecker, Martina, Haeuptle, Pirmin, Heinzelmann-Schwarz, Viola, Herter, Sylvia, Holtackers, Rene, Huesser, Tamara, Irmisch, Anja, Jacob, Francis, Jacobs, Andrea, Jaeger, Tim M, Jahn, Katharina, James, Alva R, Jermann, Philip M, Kahles, André, Kahraman, Abdullah, Koelzer, Viktor H, Kuebler, Werner, Kuipers, Jack, Kunze, Christian P, Kurzeder, Christian, Lehmann, Kjong-Van, Levesque, Mitchell, Lugert, Sebastian, Maass, Gerd, Manz, Markus, Markolin, Philipp, Mena, Julien, Menzel, Ulrike, Metzler, Julian M, Miglino, Nicola, Milani, Emanuela S, Moch, Holger, Muenst, Simone, Murri, Riccardo, Ng, Charlotte KY, Nicolet, Stefan, Nowak, Marta, Pedrioli, Patrick GA, Pelkmans, Lucas, Piscuoglio, Salvatore, Prummer, Michael, Ritter, Mathilde, Rommel, Christian, Rosano-González, María L, Rätsch, Gunnar, Santacroce, Natascha, Castillo, Jacobo Sarabia del, Schlenker, Ramona, Schwalie, Petra C, Schwan, Severin, Schär, Tobias, Senti, Gabriela, Sivapatham, Sujana, Snijder, Berend, Sobottka, Bettina, Sreedharan, Vipin T, Stark, Stefan, Stekhoven, Daniel J, Theocharides, Alexandre PA, Thomas, Tinu M, Tolnay, Markus, Tosevski, Vinko, Toussaint, Nora C, Tuncel, Mustafa A, Tusup, Marina, Drogen, Audrey Van, Vetter, Marcus, Vlajnic, Tatjana, Weber, Sandra, Weber, Walter P, Wegmann, Rebekka, Weller, Michael, Wendt, Fabian, Wey, Norbert, Wicki, Andreas, Wollscheid, Bernd, Yu, Shuqing, Ziegler, Johanna, Zimmermann, Marc, Zoche, Martin, Zuend, Gregor, and University of Zurich

Subjects
Statistics and Probability, 1303 Biochemistry, AcademicSubjects/SCI01060, Computer science, 610 Medicine & health, computer.software_genre, Biochemistry, 03 medical and health sciences, 0302 clinical medicine, Text mining, 1312 Molecular Biology, 1706 Computer Science Applications, Humans, Profiling (information science), 2613 Statistics and Probability, Molecular Biology, 030304 developmental biology, Data, 0303 health sciences, Sequence Analysis, RNA, business.industry, Gene Expression Profiling, Autoencoder, Computer Science Applications, Computational Mathematics, Computational Theory and Mathematics, 10032 Clinic for Oncology and Hematology, Bipartite graph, Data mining, Single-Cell Analysis, business, computer, 2605 Computational Mathematics, Algorithms, Software, 030217 neurology & neurosurgery, Data integration, 1703 Computational Theory and Mathematics
Abstract

Motivation: Recent technological advances have led to an increase in the production and availability of single-cell data. The ability to integrate a set of multi-technology measurements would allow the identification of biologically or clinically meaningful observations through the unification of the perspectives afforded by each technology. In most cases, however, profiling technologies consume the used cells and thus pairwise correspondences between datasets are lost. Due to the sheer size single-cell datasets can acquire, scalable algorithms that are able to universally match single-cell measurements carried out in one cell to its corresponding sibling in another technology are needed. Results: We propose Single-Cell data Integration via Matching (SCIM), a scalable approach to recover such correspondences in two or more technologies. SCIM assumes that cells share a common (low-dimensional) underlying structure and that the underlying cell distribution is approximately constant across technologies. It constructs a technology-invariant latent space using an autoencoder framework with an adversarial objective. Multi-modal datasets are integrated by pairing cells across technologies using a bipartite matching scheme that operates on the low-dimensional latent representations. We evaluate SCIM on a simulated cellular branching process and show that the cell-to-cell matches derived by SCIM reflect the same pseudotime on the simulated dataset. Moreover, we apply our method to two real-world scenarios, a melanoma tumor sample and a human bone marrow sample, where we pair cells from a scRNA dataset to their sibling cells in a CyTOF dataset achieving 90% and 78% cell-matching accuracy for each one of the samples, respectively., Bioinformatics, 36 (S2), ISSN:1367-4803, ISSN:1460-2059

Published
2020

74. The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support

Author

Irmisch, Anja, primary, Bonilla, Ximena, additional, Chevrier, Stéphane, additional, Lehmann, Kjong-Van, additional, Singer, Franziska, additional, Toussaint, Nora C., additional, Esposito, Cinzia, additional, Mena, Julien, additional, Milani, Emanuela S., additional, Casanova, Ruben, additional, Stekhoven, Daniel J., additional, Wegmann, Rebekka, additional, Jacob, Francis, additional, Sobottka, Bettina, additional, Goetze, Sandra, additional, Kuipers, Jack, additional, Sarabia del Castillo, Jacobo, additional, Prummer, Michael, additional, Tuncel, Mustafa A., additional, Menzel, Ulrike, additional, Jacobs, Andrea, additional, Engler, Stefanie, additional, Sivapatham, Sujana, additional, Frei, Anja L., additional, Gut, Gabriele, additional, Ficek, Joanna, additional, Miglino, Nicola, additional, Aebersold, Rudolf, additional, Bacac, Marina, additional, Beerenwinkel, Niko, additional, Beisel, Christian, additional, Bodenmiller, Bernd, additional, Dummer, Reinhard, additional, Heinzelmann-Schwarz, Viola, additional, Koelzer, Viktor H., additional, Manz, Markus G., additional, Moch, Holger, additional, Pelkmans, Lucas, additional, Snijder, Berend, additional, Theocharides, Alexandre P.A., additional, Tolnay, Markus, additional, Wicki, Andreas, additional, Wollscheid, Bernd, additional, Rätsch, Gunnar, additional, Levesque, Mitchell P., additional, Ak, Melike, additional, Al-Quaddoomi, Faisal S., additional, Albinus, Jonas, additional, Alborelli, Ilaria, additional, Andani, Sonali, additional, Attinger, Per-Olof, additional, Baumhoer, Daniel, additional, Beck-Schimmer, Beatrice, additional, Bernasconi, Lara, additional, Bertolini, Anne, additional, Chicherova, Natalia, additional, D'Costa, Maya, additional, Danenberg, Esther, additional, Davidson, Natalie, additional, Drăgan, Monica-Andreea, additional, Erkens, Martin, additional, Eschbach, Katja, additional, Fedier, André, additional, Ferreira, Pedro, additional, Frey, Bruno, additional, Grob, Linda, additional, Günther, Detlef, additional, Haberecker, Martina, additional, Haeuptle, Pirmin, additional, Herter, Sylvia, additional, Holtackers, Rene, additional, Huesser, Tamara, additional, Jaeger, Tim M., additional, Jahn, Katharina, additional, James, Alva R., additional, Jermann, Philip M., additional, Kahles, André, additional, Kahraman, Abdullah, additional, Kuebler, Werner, additional, Kunze, Christian P., additional, Kurzeder, Christian, additional, Lugert, Sebastian, additional, Maass, Gerd, additional, Markolin, Philipp, additional, Metzler, Julian M., additional, Muenst, Simone, additional, Murri, Riccardo, additional, Ng, Charlotte K.Y., additional, Nicolet, Stefan, additional, Nowak, Marta, additional, Pedrioli, Patrick G.A., additional, Piscuoglio, Salvatore, additional, Ritter, Mathilde, additional, Rommel, Christian, additional, Rosano-González, María L., additional, Santacroce, Natascha, additional, Schlenker, Ramona, additional, Schwalie, Petra C., additional, Schwan, Severin, additional, Schär, Tobias, additional, Senti, Gabriela, additional, Sreedharan, Vipin T., additional, Stark, Stefan, additional, Thomas, Tinu M., additional, Tosevski, Vinko, additional, Tusup, Marina, additional, Van Drogen, Audrey, additional, Vetter, Marcus, additional, Vlajnic, Tatjana, additional, Weber, Sandra, additional, Weber, Walter P., additional, Weller, Michael, additional, Wendt, Fabian, additional, Wey, Norbert, additional, Wildschut, Mattheus H.E., additional, Yu, Shuqing, additional, Ziegler, Johanna, additional, Zimmermann, Marc, additional, Zoche, Martin, additional, and Zuend, Gregor, additional

Published
2021
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75. SCIM: Universal Single-Cell Matching with Unpaired Feature Sets

Author

Stark, Stefan, Ficek, Joanna, Locatello, Francesco, Bonilla Bustillo, Ximena, Chicherova, Natalia, Singer, Franziska, Tumor Profiler Consortium, Aebersold, Rudolf, Beerenwinkel, Niko, Al-Quaddoomi, Faisal S., Albinus, Jonas, Beisel, Christian, Bertolini, Anne, Davidson, Natalie, Eschbach, Katja, Ferreira, Pedro, Goetze, Sandra, Grob, Linda, Günther, Detlef, Jahn, Katharina, James, Alva R., Kahles, André, Kuipers, Jack, Lehmann, Kjong-Van, Mena, Julien, Menzel, Ulrike, Milani, Emanuela S., Pedrioli, Patrick G.A., Prummer, Michael, Rosano-Gonzalez, Maria L., Rätsch, Gunnar, Schär, Tobias, Snijder, Berend, Thankam Sreedharan, Vipin, Stekhoven, Daniel J., Thomas, Tinu M., Toussaint, Nora C., Tuncel, Mustafa, van Drogen, Audrey, Wegmann, Rebekka, Wendt, Fabian, Wollscheid, Bernd, Yu, Shuqing, and Zimmermann, Marc

Abstract

Motivation Recent technological advances have led to an increase in the production and availability of single-cell data. The ability to integrate a set of multi-technology measurements would allow the identification of biologically or clinically meaningful observations through the unification of the perspectives afforded by each technology. In most cases, however, profiling technologies consume the used cells and thus pairwise correspondences between datasets are lost. Due to the sheer size single-cell datasets can acquire, scalable algorithms that are able to universally match single-cell measurements carried out in one cell to its corresponding sibling in another technology are needed. Results We propose Single-Cell data Integration via Matching (SCIM), a scalable approach to recover such correspondences in two or more technologies. SCIM assumes that cells share a common (low-dimensional) underlying structure and that the underlying cell distribution is approximately constant across technologies. It constructs a technology-invariant latent space using an auto-encoder framework with an adversarial objective. Multi-modal datasets are integrated by pairing cells across technologies using a bipartite matching scheme that operates on the low-dimensional latent representations. We evaluate SCIM on a simulated cellular branching process and show that the cell-to-cell matches derived by SCIM reflect the same pseudotime on the simulated dataset. Moreover, we apply our method to two real-world scenarios, a melanoma tumor sample and a human bone marrow sample, where we pair cells from a scRNA dataset to their sibling cells in a CyTOF dataset achieving 93% and 84% cell-matching accuracy for each one of the samples respectively. Availability https://github.com/ratschlab/scim, bioRxiv

Published
2020

76. Hurricane Resilient Wind Plant Concept Study Final Report

Author

Dibra, Besart, primary, Finucane, Zachary, additional, Foley, Benjamin, additional, Hall, Rudy, additional, Damiani, Rick, additional, Maples, Benjamin, additional, Parker, Zachary, additional, Robertson, Amy, additional, Scott, George, additional, Stehly, Tyler, additional, Wendt, Fabian, additional, Andersen, Mads Boel Overgaard, additional, Standish, Kevin, additional, Lee, Ken, additional, Raina, Amool, additional, Wetzel, Kyle, additional, Musial, Walter, additional, and Schreck, Scott, additional

Published
2016
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79. Validation of Numerical Models of the Offshore Wind Turbine From the Alpha Ventus Wind Farm Against Full-Scale Measurements Within OC5 Phase III

Author

Popko, Wojciech, primary, Robertson, Amy, additional, Jonkman, Jason, additional, Wendt, Fabian, additional, Thomas, Philipp, additional, Müller, Kolja, additional, Kretschmer, Matthias, additional, Hagen, Torbjørn Ruud, additional, Galinos, Christos, additional, Le Dreff, Jean-Baptiste, additional, Gilbert, Philippe, additional, Auriac, Bertrand, additional, Oh, Sho, additional, Qvist, Jacob, additional, Sørum, Stian Høegh, additional, Suja-Thauvin, Loup, additional, Shin, Hyunkyoung, additional, Molins, Climent, additional, Trubat, Pau, additional, Bonnet, Paul, additional, Bergua, Roger, additional, Wang, Kai, additional, Fu, Pengcheng, additional, Cai, Jifeng, additional, Cai, Zhisong, additional, Alexandre, Armando, additional, and Harries, Robert, additional

Published
2020
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80. Ocean Energy Systems Wave Energy Modelling Task : Modelling, Verification and Validation of Wave Energy Converters

Author

Wendt, Fabian, Nielsen, Kim, Hoffman, Johan, Jansson, Johan, Leoni, Massimiliano, Yasutaka, Imai, Wendt, Fabian, Nielsen, Kim, Hoffman, Johan, Jansson, Johan, Leoni, Massimiliano, and Yasutaka, Imai

Abstract

The International Energy Agency Technology Collaboration Programme for Ocean Energy Systems (OES) initiated the OES Wave Energy Conversion Modelling Task, which focused on the verification and validation of numerical models for simulating wave energy converters (WECs). The long-term goal is to assess the accuracy of and establish confidence in the use of numerical models used in design as well as power performance assessment of WECs. To establish this confidence, the authors used different existing computational modelling tools to simulate given tasks to identify uncertainties related to simulation methodologies: (i) linear potential flow methods; (ii) weakly nonlinear Froude-Krylov methods; and (iii) fully nonlinear methods (fully nonlinear potential flow and Navier-Stokes models). This article summarizes the code-to-code task and code-to-experiment task that have been performed so far in this project, with a focus on investigating the impact of different levels of nonlinearities in the numerical models. Two different WECs were studied and simulated. The first was a heaving semi-submerged sphere, where free-decay tests and both regular and irregular wave cases were investigated in a code-to-code comparison. The second case was a heaving float corresponding to a physical model tested in a wave tank. We considered radiation, diffraction, and regular wave cases and compared quantities, such as the WEC motion, power output and hydrodynamic loading., QC 20200103

Published
2019
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83. Verification of Numerical Offshore Wind Turbine Models Based on Full Scale Alpha Ventus Data within OC5 Phase III

Author

Popko, Wojciech, Huhn, Matthias L., Robertson, Amy N., Jonkman, Jason M., Wendt, Fabian, Müller, Kolja, Kretschmer, Matthias L., Vorpahl, Fabian, Hagen, Torbjørn Ruud, Galinos, Christos, Dreff, Jean-Baptiste Le, Gilbert, Philippe, Auriac, Bertrand, Villora, Francisco Navarro, Schünemann, Paul, Bayati, Ilmas, Oh, Sho, Totsuka, Yoshitaka, Qvist, Jacob, Bachynski, Erin Elizabeth, Sørum, Stian Høegh, Thomassen, Paul Edgar, Shin, Hyun Kyoung, Vittori, Felipe, Galvan, Josean, Molins, Climent, Bonnet, Paul, Zee, Tjeerd van der, Bergua, Roger, Wang, Kai, Fu, Pengcheng, and Cai, Jifeng

Abstract

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project, is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project analyzes the Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. This paper shows results of the verification of the OWT models (code-to-code comparison). A subsequent publication will focus on their validation (comparison of simulated results to measured physical system response data). Based on the available data, the participants of Phase III set up numerical models of the OWT in their simulation tools. It was necessary to verify and to tune these models. The verification and tuning were performed against an OWT model available at the University of Stuttgart – Stuttgart Wind Energy (SWE) and documentation provided by Senvion and OWEC Tower. A very good match was achieved between the results from the reference SWE model and models set up by OC5 Phase III participants. Copyright © 2018 by ASME

Published
2018

85. Validation of Numerical Models of the Offshore Wind Turbine From the Alpha Ventus Wind Farm Against Full-Scale Measurements Within OC5 Phase III

Author

Popko, Wojciech, primary, Robertson, Amy, additional, Jonkman, Jason, additional, Wendt, Fabian, additional, Thomas, Philipp, additional, Müller, Kolja, additional, Kretschmer, Matthias, additional, Ruud Hagen, Torbjørn, additional, Galinos, Christos, additional, Le Dreff, Jean-Baptiste, additional, Gilbert, Philippe, additional, Auriac, Bertrand, additional, Oh, Sho, additional, Qvist, Jacob, additional, Sørum, Stian Høegh, additional, Suja-Thauvin, Loup, additional, Shin, Hyunkyoung, additional, Molins, Climent, additional, Trubat, Pau, additional, Bonnet, Paul, additional, Bergua, Roger, additional, Wang, Kai, additional, Fu, Pengcheng, additional, Cai, Jifeng, additional, Cai, Zhisong, additional, Alexandre, Armando, additional, and Harries, Robert, additional

Published
2019
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91. Verification of a Numerical Model of the Offshore Wind Turbine From the Alpha Ventus Wind Farm Within OC5 Phase III

Author

Popko, Wojciech, Huhn, Matthias L., Robertson, Amy, Jonkman, Jason M., Wendt, Fabian, Müller, Kolja, Kretschmer, Matthias, Vorpahl, Fabian, Hagen, Torbjørn Ruud, Galinos, Christos, Le Dreff, Jean-Baptiste, Gilbert, Philippe, Auriac, Bertrand, Víllora, Francisco Navarro, Schünemann, Paul, Bayati, Ilmas, Belloli, Marco, Oh, Sho, Totsuka, Yoshitaka, Qvist, Jacob, Bachynski, Erin E., Sørum, Stian Høegh, Thomassen, Paul, Shin, Hyunkyoung, Vittori, Felipe, Galvan, Josean, Molins, Climent, Bonnet, Paul, van der Zee, Tjeerd, Bergua, Roger, Wang, Kai, Pengcheng, Fu, Cai, Jifeng, Popko, Wojciech, Huhn, Matthias L., Robertson, Amy, Jonkman, Jason M., Wendt, Fabian, Müller, Kolja, Kretschmer, Matthias, Vorpahl, Fabian, Hagen, Torbjørn Ruud, Galinos, Christos, Le Dreff, Jean-Baptiste, Gilbert, Philippe, Auriac, Bertrand, Víllora, Francisco Navarro, Schünemann, Paul, Bayati, Ilmas, Belloli, Marco, Oh, Sho, Totsuka, Yoshitaka, Qvist, Jacob, Bachynski, Erin E., Sørum, Stian Høegh, Thomassen, Paul, Shin, Hyunkyoung, Vittori, Felipe, Galvan, Josean, Molins, Climent, Bonnet, Paul, van der Zee, Tjeerd, Bergua, Roger, Wang, Kai, Pengcheng, Fu, and Cai, Jifeng

Abstract

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project, is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project analyzes the Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. This paper shows results of the verification of the OWT models (code-to-code comparison). A subsequent publication will focus on their validation (comparison of simulated results to measured physical system response data). Based on the available data, the participants of Phase III set up numerical models of the OWT in their simulation tools. It was necessary to verify and to tune these models. The verification and tuning were performed against an OWT model available at the University of Stuttgart – Stuttgart Wind Energy (SWE) and documentation provided by Senvion and OWEC Tower. A very good match was achieved between the results from the reference SWE model and models set up by OC5 Phase III participants.

Published
2018

95. Verification of a Numerical Model of the Offshore Wind Turbine From the Alpha Ventus Wind Farm Within OC5 Phase III

Author

Popko, Wojciech, primary, Huhn, Matthias L., additional, Robertson, Amy, additional, Jonkman, Jason, additional, Wendt, Fabian, additional, Müller, Kolja, additional, Kretschmer, Matthias, additional, Vorpahl, Fabian, additional, Hagen, Torbjørn Ruud, additional, Galinos, Christos, additional, Le Dreff, Jean-Baptiste, additional, Gilbert, Philippe, additional, Auriac, Bertrand, additional, Víllora, Francisco Navarro, additional, Schünemann, Paul, additional, Bayati, Ilmas, additional, Belloli, Marco, additional, Oh, Sho, additional, Totsuka, Yoshitaka, additional, Qvist, Jacob, additional, Bachynski, Erin, additional, Sørum, Stian Høegh, additional, Thomassen, Paul E., additional, Shin, Hyunkyoung, additional, Vittori, Felipe, additional, Galván, Josean, additional, Molins, Climent, additional, Bonnet, Paul, additional, van der Zee, Tjeerd, additional, Bergua, Roger, additional, Wang, Kai, additional, Fu, Pengcheng, additional, and Cai, Jifeng, additional

Published
2018
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98. International Energy Agency Ocean Energy Systems Task 10 Wave Energy Converter Modeling Verification and Validation

Author

Wendt, Fabian F, Yu, Yi-Hsiang, Nielsen, Kim, Ruehl, Kelley, Bunnik, Tim, Touzon, Imanol, Nam, Bo Woo, Kim, Jeong Seok, Kim, Kyong-Hwan, Janson, Carl Erik, Jansson, Johan, Hoffman, Johan, et al., Wendt, Fabian F, Yu, Yi-Hsiang, Nielsen, Kim, Ruehl, Kelley, Bunnik, Tim, Touzon, Imanol, Nam, Bo Woo, Kim, Jeong Seok, Kim, Kyong-Hwan, Janson, Carl Erik, Jansson, Johan, Hoffman, Johan, and et al.

Abstract

QC 20180104

Published
2017

100. Verification and Validation of the New Dynamic Mooring Modules Available in FAST v8

Author

Wendt, Fabian F., Andersen, Morten Thøtt, Robertson, Amy N., Jonkman, Jason M., Chung, Jin S., Muskulus, Michael, Kokkinis, Ted, and Wang, Alan M.

Subjects
Floating offshore wind turbine, Validation, Modeling, Verification, FAST, MoorDyn, Mooring dynamics, FEAMooring
Abstract

The open-source, aero-hydro-servo-elastic wind turbine simulation software FAST v8 (created by the National Renewable Energy Laboratory) was recently coupled to two newly developed mooring dynamics modules: MoorDyn and FEAMooring. MoorDyn is a lumped-mass-based mooring dynamics module developed by the University of Maine, and FEAMooring is a finite-element-based mooring dynamics module developed by Texas A&M University. This paper summarizes the work performed to verify and validate these modules compared to other mooring models and measured test data to assess their reliability and accuracy. The quality of the fairlead load predictions by the open-source mooring modules MoorDyn and FEAMooring appears to be largely equivalent to that predicted by the commercial tool OrcaFlex. Both mooring dynamic model predictions agree well with the experimental data considering the given limitations in the accuracy of the platform hydrodynamic load calculation and the quality of the measurement data.

Published
2016

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