Literatura académica sobre el tema "Hybrid Twins"
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Artículos de revistas sobre el tema "Hybrid Twins"
Nespolo, Massimo. "Plesiotwinsversusdiperiodic twins". Acta Crystallographica Section A Foundations and Advances 74, n.º 4 (1 de julio de 2018): 332–44. http://dx.doi.org/10.1107/s2053273318005351.
Texto completoPignatelli, Isabella, Massimo Nespolo y Giovanni Ferraris. "A survey of hybrid twins in silicate minerals". European Journal of Mineralogy 23, n.º 5 (1 de diciembre de 2011): 779–94. http://dx.doi.org/10.1127/0935-1221/2011/0023-2142.
Texto completoFerraris, G. y M. Nespolo. "Hybrid twins in minerals". Acta Crystallographica Section A Foundations of Crystallography 64, a1 (23 de agosto de 2008): C491. http://dx.doi.org/10.1107/s0108767308084213.
Texto completoNespolo, Massimo y Giovanni Ferraris. "A survey of hybrid twins in non-silicate minerals". European Journal of Mineralogy 21, n.º 4 (31 de agosto de 2009): 673–90. http://dx.doi.org/10.1127/0935-1221/2009/0021-1937.
Texto completoMarzouki, Mohamed Amine, Bernd Souvignier y Massimo Nespolo. "The staurolite enigma solved". Acta Crystallographica Section A Foundations and Advances 70, n.º 4 (17 de mayo de 2014): 348–53. http://dx.doi.org/10.1107/s2053273314007335.
Texto completoEmir Isik, Gülbahar y Henri Hubertus Achten. "OPERATIONALISING CONCEPTS OF DIGITAL TWINS ON DIFFERENT MATURITY LEVELS (FOETAL, CHILD, ADULT) FOR THE ARCHITECTURAL DESIGN PROCESS". Proceedings of the Design Society 3 (19 de junio de 2023): 2825–34. http://dx.doi.org/10.1017/pds.2023.283.
Texto completoYun, Seong-Jin, Jin-Woo Kwon y Won-Tae Kim. "A Novel Digital Twin Architecture with Similarity-Based Hybrid Modeling for Supporting Dependable Disaster Management Systems". Sensors 22, n.º 13 (24 de junio de 2022): 4774. http://dx.doi.org/10.3390/s22134774.
Texto completoNespolo, Massimo y Giovanni Ferraris. "The derivation of twin laws in non-merohedric twins. Application to the analysis of hybrid twins". Acta Crystallographica Section A Foundations of Crystallography 62, n.º 5 (23 de agosto de 2006): 336–49. http://dx.doi.org/10.1107/s0108767306023774.
Texto completoKluge, Michelle L., Evan Graber, Kathryn Foley, Lynnette V. Hansen, Heidi L. Sellers, Dragana Milosevic, Kendall W. Cradic y Stefan K. Grebe. "Monozygotic twins discordant for congenital adrenal hyperplasia due to mosaicism". European Journal of Endocrinology 182, n.º 2 (febrero de 2020): K7—K13. http://dx.doi.org/10.1530/eje-19-0249.
Texto completoTorregrosa, Sergio, Victor Champaney, Amine Ammar, Vincent Herbert y Francisco Chinesta. "Hybrid twins based on optimal transport". Computers & Mathematics with Applications 127 (diciembre de 2022): 12–24. http://dx.doi.org/10.1016/j.camwa.2022.09.026.
Texto completoTesis sobre el tema "Hybrid Twins"
Torregrosa, jordan Sergio. "Approches Hybrides et Méthodes d'Intelligence Artificielle Basées sur la Simulation Numérique pour l'Optimisation des Systèmes Aérodynamiques Complexes". Electronic Thesis or Diss., Paris, HESAM, 2024. http://www.theses.fr/2024HESAE002.
Texto completoThe industrial design of a component is a complex, time-consuming and costly process constrained to precise physical, styling and development specifications led by its future conditions and environment of use. Indeed, an industrial component is defined and characterized by many parameters which must be optimized to best satisfy all those specifications. However, the complexity of this multi-parametric constrained optimization problem is such that its analytical resolution is compromised.In the recent past, such a problem was solved experimentally, by trial and error, leading to expensive and time-consuming design processes. Since the mid-20th century, with the advancement and widespread access to increasingly powerful computing technologies, the ``virtual twins'', or physics-based numerical simulations, became an essential tool for research and development, significantly diminishing the need for experimental measurements. However, despite the computing power available today, ``virtual twins'' are still limited by the complexity of the problem solved and present some significant deviations from reality due to the ignorance of certain subjacent physics. In the late 20th century, the volume of data has surge enormously, massively spreading in the majority of fields and leading to a wide proliferation of Artificial Intelligence (AI) techniques, or ``digital twins'', partially substituting the ``virtual twins'' thanks to their lower intricacy. Nevertheless, they need an important training stage and can lead to some aversion since they operate as black boxes. Today, these technological evolutions have resulted in a framework where theory, experimentation, simulation and data can interact in synergy and reinforce each other.In this context, Stellantis aims to explore how AI can improve the design process of a complex aerodynamic system: an innovative cockpit air vent. To this purpose, the main goal of this thesis is to develop a parametric surrogate of the aerator geometry which outputs the norm of the velocity field at the pilot's face in order to explore the space of possible geometries while evaluating their performances in real time. The development of such a data-based metamodel entails several conceptual problems which can be addressed with AI.The use of classical regression techniques can lead to unphysical interpolation results in some domains such as fluid dynamics. Thus, the proposed parametric surrogate is based on Optimal Transport (OT) theory which offers a mathematical approach to measure distances and interpolate between general objects in a novel way.The success of a data-driven model relies on the quality of the training data. On the one hand, experimental data is considered as the most realistic but is extremely costly and time-consuming. On the other hand, numerical simulations are cheaper and faster but present a significant deviation from reality. Therefore, a Hybrid Twin approach is proposed based on Optimal Transport theory in order to bridge the ignorance gap between simulation and measurement.The sampling process of training data has become a central workload in the development process of a data-based model. Hence, an Active Learning methodology is proposed to iteratively and smartly select the training points, based on industrial objectives expected from the studied component, in order to minimize the number of needed samples. Thus, this sampling strategy maximizes the performance of the model while converging to the optimal solution of the industrial problem.The accuracy of a data-based model is usually the main concern of its training process. However, reality is complex and unpredictable leading to input parameters known with a certain degree of uncertainty. Therefore, a data-based Uncertainty Quantifcation methodology, based on Monte Carlo estimators and OT, is proposed to take into account the uncertainties propagation into the surrogate and to quantify their impact on its precision
Weißhuhn, J., T. Mark, M. Martin, P. Müller, A. Seifert y S. Spange. "Ternary organic–inorganic nanostructured hybrid materials by simultaneous twin polymerization". Universitätsbibliothek Chemnitz, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-220068.
Texto completoDieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich
Sass, Monica A. "Seeing Double: Marie de France's Use of Twins and Hybrids in her Lais". University of Toledo Honors Theses / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=uthonors1418907558.
Texto completoUSAI, VITTORIO. "Experimental Analysis and 1D Model Simulation of an Advanced Twin Stage Hybrid Boosting System". Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1094853.
Texto completoKitschke, Philipp, Marc Walter, Tobias Rüffer, Heinrich Lang, Maksym V. Kovalenko y Michael Mehring. "From molecular germanates to microporous Ge@C via twin polymerization". Universitätsbibliothek Chemnitz, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-200917.
Texto completoDieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich
DI, NAPOLI MARIA. "Modeling and experimental characterization of belt drive systems in micro-hybrid vehicles". Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2715955.
Texto completoMackey, Grant. "TWIN AND NARROW ROW WIDTH EFFECTS ON CORN (ZEA MAYS L.) YIELD AND WEED MANAGEMENT". UKnowledge, 2013. http://uknowledge.uky.edu/pss_etds/22.
Texto completoGregorio, Jean-Loup. "Contribution à la définition d'un jumeau numérique pour la maîtrise de la qualité géométrique des structures aéronautiques lors de leurs processus d'assemblage". Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASN008.
Texto completoAssembly operations of aerostructures are nowadays planned using the Digital Mock Up of the considered products. To allow a good realization of the aforementioned operations, the geometry of the physical product must remain as faithful as possible to the reference geometry contained in the Digital Mock Up. Because of the complexity of the considered products, unanticipated geometrical deviations may however appear. These geometrical deviations lead to longer cycle times and higher assembly costs.The increasing integration of data processing system gives new prospects on how to organize production systems. These prospects include the possibility to optimize the manufacturing and assembly operations in real time thanks to the use of digital twins of the manufactured products. In this work, we propose the implementation of a geometrical digital twin. This digital twin is capable of mirroring the geometry of the physical product being assembled and optimizing the geometry of some components remaining to be assembled.With this in mind, the initial Digital Mock Up is updated in order to obtain a hybrid representation of the product. This representation includes the different states of the components, which are called as-designed, as-built and interface. The as-built components are more particularly updated in order to mirror the geometry of the physical product being assembled. A method using digitized data is proposed. From there, the geometry of interface components is updated so that the final product complies with the functional requirements which were defined. A method is also proposed for this purpose.The feasibility of the approach as well as the proposed tools is evaluated through two application cases, one of which is directly representative of the industrial context of the works. The obtained results allow to consider enriching the proposed approach by considering non-geometrical constraints in order to optimize assembly operations
Göring, M., A. Seifert, K. Schreiter, P. Müller y S. Spange. "A non-aqueous procedure to synthesize amino group bearing nanostructured organic–inorganic hybrid materials". Universitätsbibliothek Chemnitz, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-152006.
Texto completoDieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich
An, Jeongki [Verfasser], Andreas [Akademischer Betreuer] Binder y Harald [Akademischer Betreuer] Neudorfer. "Design of a permanent magnet synchronous machine for hybrid electric vehicles with twin electric machines and a range extender / Jeongki An ; Andreas Binder, Harald Neudorfer". Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2020. http://d-nb.info/1213907667/34.
Texto completoLibros sobre el tema "Hybrid Twins"
Mehring, Michael, Stefan Spange, Alexander Auer, Matthias Birkner y Giovanni Bistoni. Twin Polymerization: New Strategy for Hybrid Material Synthesis. De Gruyter, Inc., 2018.
Buscar texto completoMehring, Michael, Stefan Spange, Alexander Auer, Matthias Birkner y Giovanni Bistoni. Twin Polymerization: New Strategy for Hybrid Materials Synthesis. de Gruyter GmbH, Walter, 2018.
Buscar texto completoMehring, Michael, Stefan Spange, Alexander Auer, Matthias Birkner y Giovanni Bistoni. Twin Polymerization: New Strategy for Hybrid Materials Synthesis. de Gruyter GmbH, Walter, 2018.
Buscar texto completoCapítulos de libros sobre el tema "Hybrid Twins"
Pohlkötter, Fabian J., Dominik Straubinger, Alexander M. Kuhn, Christian Imgrund y William Tekouo. "Unlocking the Potential of Digital Twins". En Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains, 190–99. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27933-1_18.
Texto completoAli, Muhammad A., Rehan Umer y Kamran A. Khan. "Experimental-Empirical Hybrid Approach". En CT Scan Generated Material Twins for Composites Manufacturing in Industry 4.0, 153–70. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8021-5_7.
Texto completoAli, Muhammad A., Rehan Umer y Kamran A. Khan. "Experimental-Numerical Hybrid Reinforcement Characterization Framework". En CT Scan Generated Material Twins for Composites Manufacturing in Industry 4.0, 73–94. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8021-5_4.
Texto completoBellavista, Paolo. "Enabling Distributed and Hybrid Digital Twins in the Industry5.0 Cloud Continuum". En Lecture Notes in Computer Science, 139–42. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-12429-7_10.
Texto completoJain, Rajat, Nikhil Bharat y P. Subhash Chandra Bose. "Digital Twins of Hybrid Additive and Subtractive Manufacturing Systems–A Review". En Lecture Notes in Mechanical Engineering, 173–83. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6094-1_18.
Texto completoPfeifer, Denis, Andreas Baumann, Marco Giani, Christian Scheifele y Jörg Fehr. "Hybrid Digital Twins Using FMUs to Increase the Validity and Domain of Virtual Commissioning Simulations". En Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains, 200–209. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27933-1_19.
Texto completoSchumann, Dorit, Marco Bleckmann y Peter Nyhuis. "Hybrid Production Structures as a Solution for Flexibility and Transformability for Longer Life Cycles of Production Systems". En Product Lifecycle Management. Leveraging Digital Twins, Circular Economy, and Knowledge Management for Sustainable Innovation, 289–99. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62582-4_26.
Texto completoAbhilash, P. M., Jibin Boban, Afzaal Ahmed y Xichun Luo. "Digital twin-driven additive manufacturing". En Hybrid Metal Additive Manufacturing, 196–221. Boca Raton: CRC Press, 2023. http://dx.doi.org/10.1201/9781003406488-12.
Texto completoChinesta, Francisco, Fouad El Khaldi y Elias Cueto. "Hybrid Twin: An Intimate Alliance of Knowledge and Data". En The Digital Twin, 279–98. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-21343-4_11.
Texto completoBadawy, Ibrahim, A. M. Bassiuny, Rania Darwish y A. S. Tolba. "A Digital Twin of a Remote Real-Time Accessible Labs". En Towards a Hybrid, Flexible and Socially Engaged Higher Education, 200–212. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-52667-1_21.
Texto completoActas de conferencias sobre el tema "Hybrid Twins"
Lin, Yu-Wen, Tsz Ling Elaine Tang y Costas J. Spanos. "Hybrid Approach for Digital Twins in the Built Environment". En e-Energy '21: The Twelfth ACM International Conference on Future Energy Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3447555.3466585.
Texto completoNafors, Daniel, Bjorn Johansson, Per Gullander y Sven Erixon. "Simulation in Hybrid Digital Twins for Factory Layout Planning". En 2020 Winter Simulation Conference (WSC). IEEE, 2020. http://dx.doi.org/10.1109/wsc48552.2020.9384075.
Texto completoAbburu, Sailesh, Arne J. Berre, Michael Jacoby, Dumitru Roman, Ljiljana Stojanovic y Nenad Stojanovic. "COGNITWIN – Hybrid and Cognitive Digital Twins for the Process Industry". En 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE, 2020. http://dx.doi.org/10.1109/ice/itmc49519.2020.9198403.
Texto completoZhang, Guobin y Xinying Wang. "Digital Twin Modeling for Photovoltaic Panels Based on Hybrid Neural Network". En 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI). IEEE, 2021. http://dx.doi.org/10.1109/dtpi52967.2021.9540210.
Texto completoThummerer, Tobias, Artem Kolesnikov, Julia Gundermann, Denis Ritz y Lars Mikelsons. "Paving the way for Hybrid Twins using Neural Functional Mock-Up Units". En 15th International Modelica Conference 2023, Aachen, October 9-11. Linköping University Electronic Press, 2023. http://dx.doi.org/10.3384/ecp204141.
Texto completoWang, Yuxiao, Xingyuan Dai, Kara Wang, Hub Ali y Fenghua Zhu. "Embed Trajectory Imitation in Reinforcement Learning: A Hybrid Method for Autonomous Vehicle Planning". En 2023 IEEE 3rd International Conference on Digital Twins and Parallel Intelligence (DTPI). IEEE, 2023. http://dx.doi.org/10.1109/dtpi59677.2023.10365415.
Texto completoGrimmeisen, Philipp, Yuliang Ma, Mihai A. Diaconeasa y Andrey Morozov. "Automated Generation of Hybrid Probabilistic Risk Models From SysML V2 Models of Software-Defined Manufacturing Systems". En ASME 2022 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/imece2022-95433.
Texto completoSemenkov, Kirill, Vitaly Promyslov y Alexey Poletykin. "Verification of Large Scale Control Systems with Hybrid Digital Models and Digital Twins". En 2020 International Russian Automation Conference (RusAutoCon). IEEE, 2020. http://dx.doi.org/10.1109/rusautocon49822.2020.9208167.
Texto completoMustafee, Navonil, Alison Harper y Joe Viana. "Hybrid Models with Real-time Data: Characterising Real-time Simulation and Digital Twins". En SW23 The OR Society Simulation Workshop. Operational Research Society, 2023. http://dx.doi.org/10.36819/sw23.031.
Texto completoChenxi, Hu, Yang Qiliang, Xing Jianchun, Qin Xia, Li Suliang y Jia Haining. "A Hybrid Knowledge-Data Model to Driving the Self-Evolution of Building Digital Twins". En 2022 34th Chinese Control and Decision Conference (CCDC). IEEE, 2022. http://dx.doi.org/10.1109/ccdc55256.2022.10034336.
Texto completoInformes sobre el tema "Hybrid Twins"
Mohanty, Subhasish. Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction. Office of Scientific and Technical Information (OSTI), junio de 2022. http://dx.doi.org/10.2172/1874565.
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