24 research outputs found
Layout Optimisation of Wave Energy Converter Arrays
No full textThis paper proposes an optimisation strategy for the layout design of wave energy converter (WEC) arrays. Optimal layouts are sought so as to maximise the absorbed power given a minimum q-factor, the minimum distance between WECs, and an area of deployment. To guarantee an efficient optimisation, a four-parameter layout description is proposed. Three different optimisation algorithms are further compared in terms of performance and computational cost. These are the covariance matrix adaptation evolution strategy (CMA), a genetic algorithm (GA) and the glowworm swarm optimisation (GSO) algorithm. The results show slightly higher performances for the latter two algorithms; however, the first turns out to be significantly less computationally demanding
On the reliability of electrical cable and optimal design of ocean energy arrays
No full textPublisher Copyright: © European Wave and Tidal Energy Conference 2021.A clear relationship exists between component reliability, the need for maintenance operations, and the resulting levelised cost of energy (LCOE) of offshore renewable energy arrays. To model this relationship, complex combinations of low-level components can be captured to provide the reliability of higher-level sub-systems. The open source, ocean energy array modelling tool “DTOcean” uses reliability block diagrams to represent higher-level sub-systems as networks of low-level components. Subsequently, failures of the higher-level sub-systems, based on the combined reliability of their components, can be simulated, resulting in LCOE estimates which are highly responsive to changes in array configuration. The operating environment in which a sub-system is deployed may also impact on its reliability. Considering the electrical network, it has recently been reported that subsea cable reliability reduces with the length of the cable deployed. By modifying DTOcean to include failure rate adjustment factors that model the effects of cable length, this study investigates the impact of cable length on the reliability of the electrical network and the most economical design of ocean energy arrays. It was found that for an array of 20 tidal energy converters, using the adjustment factors did not reduce the LCOE of the optimal array, but did offer a broader “design envelope” and may reduce overestimation of environmental impact when fixed cable reliability values are used.The contribution of Sandia National Laboratories was funded by the U.S. Department of Energy’s Water Power Technologies Office. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.Peer reviewe
Techno-Economic Modelling of Tidal Energy Converter Arrays in the Tacoma Narrows
No full textHydrokinetic tidal energy converter (TEC) technology is yet to become cost competitive with other renewable energy sources. Understanding the interaction between energy production and the costs incurred harvesting that energy may unlock the economic potential of this technology. Although hydrodynamic simulation of TEC arrays has matured over time, including demonstration of how small and large arrays affect the resource, integration of cost modelling is often limited. The advanced ocean energy array techno-economic modelling tool ‘DTOcean’ enables designers to calculate and improve the levelised cost of energy (LCOE) of an array through parametric simulation of the energy extraction, design of the electrical network, moorings and foundations, and simulation of the installation and lifetime operations and maintenance of the array. This work presents a verification of DTOcean’s ability to simulate the techno-economic performance of TEC arrays by reproducing the hypothetical RM1 reference model, a semi-analytical model of a TEC array based in the Tacoma Narrows of Washington state, U.S.A. It is demonstrated that DTOcean can produce a reasonable estimate to the LCOE predicted by the reference model, giving (in Euro cents per kiloWatt hour) 36.69 ¢/kWh against the reference model’s 34.612 ¢/kWh for 10 TECs, while for 50 TECs, DTOcean calculated 20.34 ¢/kWh compared to 17.34 ¢/kWh for the reference model
Introducing primre’s mre software knowledge hub (February 2021)
No full textPublisher Copyright: © European Wave and Tidal Energy Conference 2021.This paper focuses on the role of the Marine Renewable Energy (MRE) Software Knowledge Hub on the Portal and Repository for Information on Marine Renewable Energy (PRIMRE). The MRE Software Knowledge Hub provides online services for MRE software users and developers, and seeks to develop assessments and recommendations for improving MRE software in the future. Online software discovery platforms, known as the Code Hub and the Code Catalog, are provided. The Code Hub is a collection of open-source MRE software that includes a landing page with search functionality, linked to files hosted on the MRE Code Hub GitHub organization. The Code Catalog is a searchable online platform for discovery of useful (open-source or commercial) software packages, tools, codes, and other software products. To gather information about the existing MRE software landscape, a software survey is being performed, the preliminary results of which are presented herein. Initially, the data collected in the MRE software survey will be used to populate the MRE Software knowledge hub on PRIMRE, and future work will use data from the survey to perform a gap analysis and develop a vision for future software development. Additionally, as one of PRIMRE’s roles is to support development of MRE software within project partners, a silo of knowledge relating to best practices has been gathered. An early draft of new guidance developed from this knowledge is presented.In conclusion, the Portal and Repository for Information on Marine Renewable Energy (PRIMRE) was developed to serve as a centralized access point that enhances the accessibility and discoverability of information relevant to Marine Renewable Energy (MRE). Launched in 2019, PRIMRE provides easy access to the Knowledge Hubs (refer to Figure 1), tools and codes, and other resources available within the MRE space. PRIMRE is funded by the U.S. Department of Energy (DOE) Water Power Technologies Office (WPTO) and is developed and maintained by a multi-lab team from Pacific Northwest National Laboratory, National Renewable Energy Laboratory, and Sandia National Laboratories. This work was supported by U.S. Department of Energy, Office of Energy Efficiency and RenewableEnergy (EERE), Water Power Technologies Office (WPTO). PRIMRE, the Portal and Repository for Information on Marine Renewable Energy project is a multi-lab project between Pacific Northwest National Laboratory, National Renewable Energy Laboratory, and Sandia National Laboratories. This research was funded by the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), Water Power Technologies Office (WPTO). Pacific Northwest National Laboratory is a multi-mission laboratory operated by Battelle Memorial Institute for the U.S. Department of Energy Office of Science under Contract Number DE-AC05-76RL01830. National Renewable Energy Laboratory is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC under Contract Number DE-AC36-08GO28308. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. The United States Government retains, and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The views expressed in the article do not necessarily represent the views of the U.S. Department of Energy or the United States Government. Paper ID 2178, ESP track. This work was supported by U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy (EERE), Water Power Technologies Office (WPTO).Peer reviewe
The limits of reduced order current energy converter modeling
No full textPublisher Copyright: © 2020, Offshore Technology Conference.Reduced-order models for mesoscale current energy converter (CEC) modeling allow for tractablecomputation times for investigations of array configurations on power performance and environmentaleffects to support design optimization. The CEC representation in these models take the form of actuatordiscs in codes such as SNL-Delft3D-CEC-FM treating the rotating CEC blades as momentum sinks. Inthe first-of-its-kind, whole-plant optimization software, DTOcean, the hydrodynamic modelling of CECsis reduced one step further by superimposing wake models based on normalized CFD simulations onto aset of pre-computed velocity fields, to provide power estimates. DTOcean is a new tool and the amountof verification and validation evidence gathered is presently limited. To gain additional confidence andindustry buy-in to the software penetration, this study investigated a primary component of levelized cost ofelectricity (LCOE) calculation, annual energy production (AEP), through an analytic calculation of powerusing the results of an identical simulation in SNL-Delt3D-CEC-FM. Three configurations of an 8-turbinearray are studied with DTOcean where two rows of 4-turbines are spaced (unstaggered) 5-, 10-, and 20-Diameters apart and the AEP was calculated; The energy calculation in SNL-Delft3D-CEC-FM were morecomputationally expensive for the mesoscale domain making the optimization of solely an arrays powerproduction using the wake superposition method implemented DTOcean attractive. The codes however arecomplementary as SNL-Delft3D-CEC-FM simultaneously investigates environmental effects of varyingarray configurations while DTOcean considers all aspects of array costs through its lifetime to optimizeLCOE from a whole-plant perspective.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.Peer reviewe
NEW DEVELOPMENTS AND CAPABILITIES WITHIN WEC-SIM
No full textPublisher Copyright: Copyright © 2023 by Sandia National Laboratories (SNL).WEC-Sim is an open-source software for simulating wave energy converters and has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory and Sandia National Laboratories within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with the latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim’s capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1, which spans a 2-year period from June 2020 to September 2022. New features described here include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.Sandia is managed and operated by NTESS under DOE NNSA contract DE-NA0003525. This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Water Power Technologies Office. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.Peer reviewe
The Limits of Reduced Order Current Energy Converter Modeling
No full textPublisher Copyright: © 2020, Offshore Technology Conference.Reduced-order models for mesoscale current energy converter (CEC) modeling allow for tractablecomputation times for investigations of array configurations on power performance and environmentaleffects to support design optimization. The CEC representation in these models take the form of actuatordiscs in codes such as SNL-Delft3D-CEC-FM treating the rotating CEC blades as momentum sinks. Inthe first-of-its-kind, whole-plant optimization software, DTOcean, the hydrodynamic modelling of CECsis reduced one step further by superimposing wake models based on normalized CFD simulations onto aset of pre-computed velocity fields, to provide power estimates. DTOcean is a new tool and the amountof verification and validation evidence gathered is presently limited. To gain additional confidence andindustry buy-in to the software penetration, this study investigated a primary component of levelized cost ofelectricity (LCOE) calculation, annual energy production (AEP), through an analytic calculation of powerusing the results of an identical simulation in SNL-Delt3D-CEC-FM. Three configurations of an 8-turbinearray are studied with DTOcean where two rows of 4-turbines are spaced (unstaggered) 5-, 10-, and 20-Diameters apart and the AEP was calculated; The energy calculation in SNL-Delft3D-CEC-FM were morecomputationally expensive for the mesoscale domain making the optimization of solely an arrays powerproduction using the wake superposition method implemented DTOcean attractive. The codes however arecomplementary as SNL-Delft3D-CEC-FM simultaneously investigates environmental effects of varyingarray configurations while DTOcean considers all aspects of array costs through its lifetime to optimizeLCOE from a whole-plant perspective.Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.Peer reviewe
Long-baseline neutrino oscillation physics potential of the DUNE experiment: DUNE Collaboration
No full text© 2020, The Author(s). Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. WSU authors: Meyer, H.; Muether, M.; Solomey, N. The complete list includes: Abi, B.; Acciarri, R.; Acero, M.A.; Adamov, G.; Adams, D.; Adinolfi, M.; Ahmad, Z.; Ahmed, J.; Alion, T.; Monsalve, S.A.; Alt, C.; Anderson, J.; Andreopoulos, C.; Andrews, M.P.; Andrianala, F.; Andringa, S.; Ankowski, A.; Antonova, M.; Antusch, S.; Aranda-Fernandez, A.; Ariga, A.; Arnold, L.O.; Arroyave, M.A.; Asaadi, J.; Aurisano, A.; Aushev, V.; Autiero, D.; Azfar, F.; Back, H.; Back, J.J.; Backhouse, C.; Baesso, P.; Bagby, L.; Bajou, R.; Balasubramanian, S.; Baldi, P.; Bambah, B.; Barao, F.; Barenboim, G.; Barker, G.J.; Barkhouse, W.; Barnes, C.; Barr, G.; Monarca, J.B.; Barros, N.; Barrow, J.L.; Bashyal, A.; Basque, V.; Bay, F.; Alba, J.L.B.; Beacom, J.F.; Bechetoille, E.; Behera, B.; Bellantoni, L.; Bellettini, G.; Bellini, V.; Beltramello, O.; Belver, D.; Benekos, N.; Neves, F.B.; Berger, J.; Berkman, S.; Bernardini, P.; Berner, R.M.; Berns, H.; Bertolucci, S.; Betancourt, M.; Bezawada, Y.; Bhattacharjee, M.; Bhuyan, B.; Biagi, S.; Bian, J.; Biassoni, M.; Biery, K.; Bilki, B.; Bishai, M.; Bitadze, A.; Blake, A.; Siffert, B.B.; Blaszczyk, F.D.M.; Blazey, G.C.; Blucher, E.; Boissevain, J.; Bolognesi, S.; Bolton, T.; Bonesini, M.; Bongrand, M.; Bonini, F.; Booth, A.; Booth, C.; Bordoni, S.; Borkum, A.; Boschi, T.; Bostan, N.; Bour, P.; Boyd, S.B.; Boyden, D.; Bracinik, J.; Braga, D.; Brailsford, D.; Brandt, A.; Bremer, J.; Brew, C.; Brianne, E.; Brice, S.J.; Brizzolari, C.; Bromberg, C.; Brooijmans, G.; Brooke, J.; Bross, A.; Brunetti, G.; Buchanan, N.; Budd, H.; Caiulo, D.; Calafiura, P.; Calcutt, J.; Calin, M.; Calvez, S.; Calvo, E.; Camilleri, L.; Caminata, A.; Campanelli, M.; Caratelli, D.; Carini, G.; Carlus, B.; Carniti, P.; Terrazas, I.C.; Carranza, H.; Castillo, A.; Castromonte, C.; Cattadori, C.; Cavalier, F.; Cavanna, F.; Centro, S.; Cerati, G.; Cervelli, A.; Villanueva, A.C.; Chalifour, M.; Chang, C.; Chardonnet, E.; Chatterjee, A.; Chattopadhyay, S.; Chaves, J.; Chen, H.; Chen, M.; Chen, Y.; Cherdack, D.; Chi, C.; Childress, S.; Chiriacescu, A.; Cho, K.; Choubey, S.; Christensen, A.; Christian, D.; Christodoulou, G.; Church, E.; Clarke, P.; Coan, T.E.; Cocco, A.G.; Coelho, J.A.B.; Conley, E.; Conrad, J.M.; Convery, M.; Corwin, L.; Cotte, P.; Cremaldi, L.; Cremonesi, L.; Crespo-Anadón, J.I.; Cristaldo, E.; Cross, R.; Cuesta, C.; Cui, Y.; Cussans, D.; Dabrowski, M.; Motta, H.; Da Silva Peres, L.; David, C.; David, Q.; Davies, G.S.; Davini, S.; Dawson, J.; De, K.; De Almeida, R.M.; Debbins, P.; De Bonis, I.; Decowski, M.P.; de Gouvêa, A.; De Holanda, P.C.; De Icaza Astiz, I.L.; Deisting, A.; De Jong, P.; Delbart, A.; Delepine, D.; Delgado, M.; Dell’Acqua, A.; De Lurgio, P.; de Mello Neto, J.R.T.; DeMuth, D.M.; Dennis, S.; Densham, C.; Deptuch, G.; De Roeck, A.; De Romeri, V.; De Vries, J.J.; Dharmapalan, R.; Dias, M.; Diaz, F.; Díaz, J.S.; Domizio, S.D.; Giulio, L.D.; Ding, P.; Noto, L.D.; Distefano, C.; Diurba, R.; Diwan, M.; Djurcic, Z.; Dokania, N.; Dolinski, M.J.; Domine, L.; Douglas, D.; Drielsma, F.; Duchesneau, D.; Duffy, K.; Dunne, P.; Durkin, T.; Duyang, H.; Dvornikov, O.; Dwyer, D.A.; Dyshkant, A.S.; Eads, M.; Edmunds, D.; Eisch, J.; Emery, S.; Ereditato, A.; Escobar, C.O.; Sanchez, L.E.; Evans, J.J.; Ewart, E.; Ezeribe, A.C.; Fahey, K.; Falcone, A.; Farnese, C.; Farzan, Y.; Felix, J.; Fernandez-Martinez, E.; Menendez, P.F.; Ferraro, F.; Fields, L.; Filkins, A.; Filthaut, F.; Fitzpatrick, R.S.; Flanagan, W.; Fleming, B.; Flight, R.; Fowler, J.; Fox, W.; Franc, J.; Francis, K.; Franco, D.; Freeman, J.; Freestone, J.; Fried, J.; Friedland, A.; Fuess, S.; Furic, I.; Furmanski, A.P.; Gago, A.; Gallagher, H.; Gallego-Ros, A.; Gallice, N.; Galymov, V.; Gamberini, E.; Gamble, T.; Gandhi, R.; Gandrajula, R.; Gao, S.; Garcia-Gamez, D.; García-Peris, M.Á.; Gardiner, S.; Gastler, D.; Ge, G.; Gelli, B.; Gendotti, A.; Gent, S.; Ghorbani-Moghaddam, Z.; Gibin, D.; Gil-Botella, I.; Girerd, C.; Giri, A.K.; Gnani, D.; Gogota, O.; Gold, M.; Gollapinni, S.; Gollwitzer, K.; Gomes, R.A.; Bermeo, L.V.G.; Fajardo, L.S.G.; Gonnella, F.; Gonzalez-Cuevas, J.A.; Goodman, M.C.; Goodwin, O.; Goswami, S.; Gotti, C.; Goudzovski, E.; Grace, C.; Graham, M.; Gramellini, E.; Gran, R.; Granados, E.; Grant, A.; Grant, C.; Gratieri, D.; Green, P.; Green, S.; Greenler, L.; Greenwood, M.; Greer, J.; Griffith, W.C.; Groh, M.; Grudzinski, J.; Grzelak, K.; Gu, W.; Guarino, V.; Guenette, R.; Guglielmi, A.; Guo, B.; Guthikonda, K.K.; Gutierrez, R.; Guzowski, P.; Guzzo, M.M.; Gwon, S.; Habig, A.; Hackenburg, A.; Hadavand, H.; Haenni, R.; Hahn, A.; Haigh, J.; Haiston, J.; Hamernik, T.; Hamilton, P.; Han, J.; Harder, K.; Harris, D.A.; Hartnell, J.; Hasegawa, T.; Hatcher, R.; Hazen, E.; Heavey, A.; Heeger, K.M.; Heise, J.; Hennessy, K.; Henry, S.; Morquecho, M.A.H.; Herner, K.; Hertel, L.; Hesam, A.S.; Hewes, J.; Higuera, A.; Hill, T.; Hillier, S.J.; Himmel, A.; Hoff, J.; Hohl, C.; Holin, A.; Hoppe, E.; Horton-Smith, G.A.; Hostert, M.; Hourlier, A.; Howard, B.; Howell, R.; Huang, J.; Huang, J.; Hugon, J.; Iles, G.; Ilic, N.; Iliescu, A.M.; Illingworth, R.; Ioannisian, A.; Itay, R.; Izmaylov, A.; James, E.; Jargowsky, B.; Jediny, F.; Jesùs-Valls, C.; Ji, X.; Jiang, L.; Jiménez, S.; Jipa, A.; Joglekar, A.; Johnson, C.; Johnson, R.; Jones, B.; Jones, S.; Jung, C.K.; Junk, T.; Jwa, Y.; Kabirnezhad, M.; Kaboth, A.; Kadenko, I.; Kamiya, F.; Karagiorgi, G.; Karcher, A.; Karolak, M.; Karyotakis, Y.; Kasai, S.; Kasetti, S.P.; Kashur, L.; Kazaryan, N.; Kearns, E.; Keener, P.; Kelly, K.J.; Kemp, E.; Ketchum, W.; Kettell, S.H.; Khabibullin, M.; Khotjantsev, A.; Khvedelidze, A.; Kim, D.; King, B.; Kirby, B.; Kirby, M.; Klein, J.; Koehler, K.; Koerner, L.W.; Kohn, S.; Koller, P.P.; Kordosky, M.; Kosc, T.; Kose, U.; Kostelecký, V.A.; Kothekar, K.; Krennrich, F.; Kreslo, I.; Kudenko, Y.; Kudryavtsev, V.A.; Kulagin, S.; Kumar, J.; Kumar, R.; Kuruppu, C.; Kus, V.; Kutter, T.; Lambert, A.; Lande, K.; Lane, C.E.; Lang, K.; Langford, T.; Lasorak, P.; Last, D.; Lastoria, C.; Laundrie, A.; Lawrence, A.; Lazanu, I.; LaZur, R.; Le, T.; Learned, J.; LeBrun, P.; Miotto, G.L.; Lehnert, R.; de Oliveira, M.A.L.; Leitner, M.; Leyton, M.; Li, L.; Li, S.; Li, S.W.; Li, T.; Li, Y.; Liao, H.; Lin, C.S.; Lin, S.; Lister, A.; Littlejohn, B.R.; Liu, J.; Lockwitz, S.; Loew, T.; Lokajicek, M.; Lomidze, I.; Long, K.; Loo, K.; Lorca, D.; Lord, T.; LoSecco, J.M.; Louis, W.C.; Luk, K.B.; Luo, X.; Lurkin, N.; Lux, T.; Luzio, V.P.; MacFarland, D.; Machado, A.A.; Machado, P.; Macias, C.T.; Macier, J.R.; Maddalena, A.; Madigan, P.; Magill, S.; Mahn, K.; Maio, A.; Maloney, J.A.; Mandrioli, G.; Maneira, J.; Manenti, L.; Manly, S.; Mann, A.; Manolopoulos, K.; Plata, M.M.; Marchionni, A.; Marciano, W.; Marfatia, D.; Mariani, C.; Maricic, J.; Marinho, F.; Marino, A.D.; Marshak, M.; Marshall, C.; Marshall, J.; Marteau, J.; Martin-Albo, J.; Martinez, N.; Caicedo, D.A.M.; Martynenko, S.; Mason, K.; Mastbaum, A.; Masud, M.; Matsuno, S.; Matthews, J.; Mauger, C.; Mauri, N.; Mavrokoridis, K.; Mazza, R.; Mazzacane, A.; Mazzucato, E.; McCluskey, E.; McConkey, N.; McFarland, K.S.; McGrew, C.; McNab, A.; Mefodiev, A.; Mehta, P.; Melas, P.; Mellinato, M.; Mena, O.; Menary, S.; Mendez, H.; Menegolli, A.; Meng, G.; Messier, M.D.; Metcalf, W.; Mewes, M.; Meyer, H.; Miao, T.; Michna, G.; Miedema, T.; Migenda, J.; Milincic, R.; Miller, W.; Mills, J.; Milne, C.; Mineev, O.; Miranda, O.G.; Miryala, S.; Mishra, C.S.; Mishra, S.R.; Mislivec, A.; Mladenov, D.; Mocioiu, I.; Moffat, K.; Moggi, N.; Mohanta, R.; Mohayai, T.A.; Mokhov, N.; Molina, J.; Bueno, L.M.; Montanari, A.; Montanari, C.; Montanari, D.; Zetina, L.M.M.; Moon, J.; Mooney, M.; Moor, A.; Moreno, D.; Morgan, B.; Morris, C.; Mossey, C.; Motuk, E.; Moura, C.A.; Mousseau, J.; Mu, W.; Mualem, L.; Mueller, J.; Muether, M.; Mufson, S.; Muheim, F.; Muir, A.; Mulhearn, M.; Muramatsu, H.; Murphy, S.; Musser, J.; Nachtman, J.; Nagu, S.; Nalbandyan, M.; Nandakumar, R.; Naples, D.; Narita, S.; Navas-Nicolás, D.; Nayak, N.; Nebot-Guinot, M.; Necib, L.; Negishi, K.; Nelson, J.K.; Nesbit, J.; Nessi, M.; Newbold, D.; Newcomer, M.; Newhart, D.; Nichol, R.; Niner, E.; Nishimura, K.; Norman, A.; Norrick, A.; Northrop, R.; Novella, P.; Nowak, J.A.; Oberling, M.; Campo, A.O.D.; Olivier, A.; Onel, Y.; Onishchuk, Y.; Ott, J.; Pagani, L.; Pakvasa, S.; Palamara, O.; Palestini, S.; Paley, J.M.; Pallavicini, M.; Palomares, C.; Pantic, E.; Paolone, V.; Papadimitriou, V.; Papaleo, R.; Papanestis, A.; Paramesvaran, S.; Parke, S.; Parsa, Z.; Parvu, M.; Pascoli, S.; Pasqualini, L.; Pasternak, J.; Pater, J.; Patrick, C.; Patrizii, L.; Patterson, R.B.; Patton, S.J.; Patzak, T.; Paudel, A.; Paulos, B.; Paulucci, L.; Pavlovic, Z.; Pawloski, G.; Payne, D.; Pec, V.; Peeters, S.J.M.; Penichot, Y.; Pennacchio, E.; Penzo, A.; Peres, O.L.G.; Perry, J.; Pershey, D.; Pessina, G.; Petrillo, G.; Petta, C.; Petti, R.; Piastra, F.; Pickering, L.; Pietropaolo, F.; Pillow, J.; Pinzino, J.; Plunkett, R.; Poling, R.; Pons, X.; • Poonthottathil, N.; Pordes, S.; Potekhin, M.; Potenza, R.; Potukuchi, B.V.K.S.; Pozimski, J.; Pozzato, M.; Prakash, S.; Prakash, T.; Prince, S.; Prior, G.; Pugnere, D.; Qi, K.; Qian, X.; Raaf, J.L.; Raboanary, R.; Radeka, V.; Rademacker, J.; Radics, B.; Rafique, A.; Raguzin, E.; Rai, M.; Rajaoalisoa, M.; Rakhno, I.; Rakotondramanana, H.T.; Rakotondravohitra, L.; Ramachers, Y.A.; Rameika, R.; Delgado, M.A.R.; Ramson, B.; Rappoldi, A.; Raselli, G.; Ratoff, P.; Ravat, S.; Razafinime, H.; Real, J.S.; Rebel, B.; Redondo, D.; Reggiani-Guzzo, M.; Rehak, T.; Reichenbacher, J.; Reitzner, S.D.; Renshaw, A.; Rescia, S.; Resnati, F.; Reynolds, A.; Riccobene, G.; Rice, L.C.J.; Rielage, K.; Rigaut, Y.; Rivera, D.; Rochester, L.; Roda, M.; Rodrigues, P.; Alonso, M.J.R.; Rondon, J.R.; Roeth, A.J.; Rogers, H.; Rosauro-Alcaraz, S.; Rossella, M.; Rout, J.; Roy, S.; Rubbia, A.; Rubbia, C.; Russell, B.; Russell, J.; Ruterbories, D.; Saakyan, R.; Sacerdoti, S.; Safford, T.; Sahu, N.; Sala, P.; Samios, N.; Sanchez, M.C.; Sanders, D.A.; Sankey, D.; Santana, S.; Santos-Maldonado, M.; Saoulidou, N.; Sapienza, P.; Sarasty, C.; Sarcevic, I.; 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Wang, J.; Wang, Y.; Wang, Y.; Warburton, K.; Warner, D.; Wascko, M.; Waters, D.; Watson, A.; Weatherly, P.; Weber, A.; Weber, M.; Wei, H.; Weinstein, A.; Wenman, D.; Wetstein, M.; While, M.R.; White, A.; Whitehead, L.H.; Whittington, D.; Wilking, M.J.; Wilkinson, C.; Williams, Z.; Wilson, F.; Wilson, R.J.; Wolcott, J.; Wongjirad, T.; Wood, K.; Wood, L.; Worcester, E.; Worcester, M.; Wret, C.; Wu, W.; Wu, W.; Xiao, Y.; Yang, G.; Yang, T.; Yershov, N.; Yonehara, K.; Young, T.; Yu, B.; Yu, J.; Zaki, R.; Zalesak, J.; Zambelli, L.; Zamorano, B.; Zani, A.; Zazueta, L.; Zeller, G.P.; Zennamo, J.; Zeug, K.; Zhang, C.; Zhao, M.; Zhivun, E.; Zhu, G.; Zimmerman, E.D.; Zito, M.; Zucchelli, S.; Zuklin, J.; Zutshi, V.; Zwaska, R.The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and a full simulation and parameterized analysis of the near detector. Detailed uncertainties due to the flux prediction, neutrino interaction model, and detector effects are included. DUNE will resolve the neutrino mass hierarchy to a precision of 5, for all values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3 (5) after an exposure of 5 (10) years, for 50\% of all values. It will also make precise measurements of other parameters governing long-baseline neutrino oscillation, and after an exposure of 15 years will achieve a similar sensitivity to to current reactor experiments.This work was supported by CNPq, FAPERJ, FAPEG and FAPESP, Brazil; CFI, IPP and NSERC, Canada; CERN; MŠMT, Czech Republic; ERDF, H2020-EU and MSCA, European Union; CNRS/IN2P3 and CEA, France; INFN, Italy; FCT, Portugal; NRF, South Korea; CAM, Fundación “La Caixa” and MICINN, Spain; SERI and SNSF, Switzerland; TÜBİTAK, Turkey; The Royal Society and UKRI/STFC, UK; DOE and NSF, United States of America. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231
Reducing variability in the cost of energy of ocean energy arrays
No full textThe research leading to this publication is part of the DTOceanPlus project which has received funding from the EuropeanUnion's Horizon 2020 research and innovation programme under grant agreement No 785921. Funding was also received from the European Community's Seventh Framework Programme for the DTOcean Project (grant agreement No. 608597). The contribution of Sandia National Laboratories was funded by the U.S. Department of Energy's Water Power Technologies Office. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. The image of the RM3 device, in Fig. 7, was reproduced with the permission of Sandia National LaboratoriesVariability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial decisions. This paper provides the unique contribution of quantifying variability in the predicted cost of energy and introduces a framework for investigating reduction of variability through investment in components. Following review of existing methodologies for parametric analysis of ocean energy array design, the development of the DTOcean software tool is presented. DTOcean can quantify variability by simulating the design, deployment and operation of arrays with higher complexity than previous models, designing sub-systems at component level. A case study of a theoretical floating wave energy converter array is used to demonstrate that the variability in levelised cost of energy (LCOE) can be greatest for the smallest arrays and that investment in improved component reliability can reduce both the variability and most likely value of LCOE. A hypothetical study of improved electrical cables and connectors shows reductions in LCOE up to 2.51% and reductions in the variability of LCOE of over 50%; these minima occur for different combinations of components.Peer reviewe
Aspects of the fantastic grotesque in the works of V. Mayakovsky, M. Bulgakov and E. Schwartz
No full textThe grotesque in Soviet literature ls a field of study whlch has been neglected both in the Soviet Union and the West. In the Soviet Union interest in the grotesque reached a high point in the formalist criticism of the twenties, since the grotesque is one of the most clearly expressed devices of defamiliarisation. After a long period of taboo a revival takes place in the sixties. An attempt has been made in thls thesis to define the grotesque and to apply this definition to the works of V. Mayakovaky, M. Bulgakoy and E. Schwartz. We are primarily concerned with the structural features of their grotesque and the relationshlp of these to comedy and tragedy. While very similar in its structure and its use of comedy devices, the grotesque of all three writers differs substantially in its nature. We have attempted to establish the reasons for the differences and to define the function of their grotesque
