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Статті в журналах з теми "Real-time model order reduction"
SUZUKI, Katsuyuki, Masaru OKAYASU, and Ryuta OKADA. "1803 Real Time Large Deformation Simulation using Model Order Reduction." Proceedings of The Computational Mechanics Conference 2013.26 (2013): _1803–1_—_1803–3_. http://dx.doi.org/10.1299/jsmecmd.2013.26._1803-1_.
Повний текст джерелаDams, Dennis, Rob Gerth, Bart Knaack, and Ruurd Kuiper. "Partial-order Reduction Techniques for Real-time Model Checking." Formal Aspects of Computing 10, no. 5-6 (May 26, 1998): 469–82. http://dx.doi.org/10.1007/s001650050028.
Повний текст джерелаFrank, Tobias, Henrik Zeipel, Mark Wielitzka, Steffen Bosselmann, and Tobias Ortmaier. "Real-Time Prediction of Curing Processes using Model Order Reduction." IFAC-PapersOnLine 53, no. 2 (2020): 11132–37. http://dx.doi.org/10.1016/j.ifacol.2020.12.273.
Повний текст джерелаFar, Mehrnaz Farzam, Floran Martin, Anouar Belahcen, Paavo Rasilo, and Hafiz Asad Ali Awan. "Real-Time Control of an IPMSM Using Model Order Reduction." IEEE Transactions on Industrial Electronics 68, no. 3 (March 2021): 2005–14. http://dx.doi.org/10.1109/tie.2020.2973901.
Повний текст джерелаNasika, Christina, Pedro Díez, Pierre Gerard, Thierry J. Massart, and Sergio Zlotnik. "Towards real time assessment of earthfill dams via Model Order Reduction." Finite Elements in Analysis and Design 199 (February 2022): 103666. http://dx.doi.org/10.1016/j.finel.2021.103666.
Повний текст джерелаGonzález, David, Alberto Badías, Icíar Alfaro, Francisco Chinesta, and Elías Cueto. "Model order reduction for real-time data assimilation through Extended Kalman Filters." Computer Methods in Applied Mechanics and Engineering 326 (November 2017): 679–93. http://dx.doi.org/10.1016/j.cma.2017.08.041.
Повний текст джерелаVettermann, J., S. Sauerzapf, A. Naumann, M. Beitelschmidt, R. Herzog, P. Benner, and J. Saak. "MODEL ORDER REDUCTION METHODS FOR COUPLED MACHINE TOOL MODELS." MM Science Journal 2021, no. 3 (June 30, 2021): 4652–59. http://dx.doi.org/10.17973/mmsj.2021_7_2021072.
Повний текст джерелаKiss, Kristóf Levente, and Tamás Orosz. "Model Order Reduction Methods for Rotating Electrical Machines: A Review." Energies 17, no. 20 (October 16, 2024): 5145. http://dx.doi.org/10.3390/en17205145.
Повний текст джерелаSUZUKI, Katsuyuki, Masayuki WADA, and Masaru OKAYASU. "2304 Real Time Simulation of Dynamic Large Deformation Problem using Model Order Reduction." Proceedings of The Computational Mechanics Conference 2012.25 (2012): 571–73. http://dx.doi.org/10.1299/jsmecmd.2012.25.571.
Повний текст джерелаALDHAHERI, RABAH W. "Model order reduction via real Schur-form decomposition." International Journal of Control 53, no. 3 (March 1991): 709–16. http://dx.doi.org/10.1080/00207179108953642.
Повний текст джерелаДисертації з теми "Real-time model order reduction"
Quaranta, Giacomo. "Efficient simulation tools for real-time monitoring and control using model order reduction and data-driven techniques." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/667474.
Повний текст джерелаLa simulación numérica, el uso de ordenadores para ejecutar un programa que implementa un modelo matemático de un sistema físico, es una parte importante del mundo tecnológico actual. En muchos campos de la ciencia y la ingeniería es necesario estudiar el comportamiento de sistemas cuyos modelos matemáticos son demasiado complejos para proporcionar soluciones analíticas, haciendo posible la evaluación virtual de las respuestas de los sistemas (gemelos virtuales). Esto reduce drásticamente el número de pruebas experimentales para los diseños precisos del sistema real que el modelo numérico representa. Sin embargo, estos gemelos virtuales, basados en métodos clásicos que hacen uso de una rica representación del sistema (por ejemplo, el método de elementos finitos), rara vez permiten la retroalimentación en tiempo real, incluso cuando se considera la computación en plataformas de alto rendimiento. En estas circunstancias, el rendimiento en tiempo real requerido en algunas aplicaciones se ve comprometido. En efecto, los gemelos virtuales son estáticos, es decir, se utilizan en el diseño de sistemas complejos y sus componentes, pero no se espera que acomoden o asimilen los datos para definir sistemas de aplicación dinámicos basados en datos. Además, se suelen apreciar desviaciones significativas entre la respuesta observada y la predicha por el modelo, debido a inexactitudes en los modelos empleados, en la determinación de los parámetros del modelo o en su evolución temporal. En esta tesis se proponen diferentes métodos para resolver estas limitaciones con el fin de realizar un seguimiento y un control en tiempo real. En la primera parte se utilizan técnicas de Reducción de Modelos para satisfacer las restricciones en tiempo real; estas técnicas calculan una buena aproximación de la solución simplificando el procedimiento de resolución en lugar del modelo. La precisión de la solución no se ve comprometida y se pueden realizar simulaciones efficientes (gemelos digitales). En la segunda parte se emplea la modelización basada en datos para llenar el vacío entre la solución paramétrica, calculada utilizando técnicas de reducción de modelos no intrusivas, y los campos medidos, con el fin de hacer posibles los sistemas de aplicación dinámicos basados en datos (gemelos híbridos).
La simulation numérique, c'est-à-dire l'utilisation des ordinateurs pour exécuter un programme qui met en oeuvre un modèle mathématique d'un système physique, est une partie importante du monde technologique actuel. Elle est nécessaire dans de nombreux domaines scientifiques et techniques pour étudier le comportement de systèmes dont les modèles mathématiques sont trop complexes pour fournir des solutions analytiques et elle rend possible l'évaluation virtuelle des réponses des systèmes (jumeaux virtuels). Cela réduit considérablement le nombre de tests expérimentaux nécessaires à la conception précise du système réel que le modèle numérique représente. Cependant, ces jumeaux virtuels, basés sur des méthodes classiques qui utilisent une représentation fine du système (ex. méthode des éléments finis), permettent rarement une rétroaction en temps réel, même dans un contexte de calcul haute performance, fonctionnant sur des plates-formes puissantes. Dans ces circonstances, les performances en temps réel requises dans certaines applications sont compromises. En effet, les jumeaux virtuels sont statiques, c'est-à-dire qu'ils sont utilisés dans la conception de systèmes complexes et de leurs composants, mais on ne s'attend pas à ce qu'ils prennent en compte ou assimilent des données afin de définir des systèmes d'application dynamiques pilotés par les données. De plus, des écarts significatifs entre la réponse observée et celle prévue par le modèle sont généralement constatés en raison de l'imprécision des modèles employés, de la détermination des paramètres du modèle ou de leur évolution dans le temps. Dans cette thèse, nous proposons di érentes méthodes pour résoudre ces handicaps afin d'effectuer une surveillance et un contrôle en temps réel. Dans la première partie, les techniques de Réduction de Modèles sont utilisées pour tenir compte des contraintes en temps réel ; elles calculent une bonne approximation de la solution en simplifiant la procédure de résolution plutôt que le modèle. La précision de la solution n'est pas compromise et des simulations e caces peuvent être réalisées (jumeaux numériquex). Dans la deuxième partie, la modélisation pilotée par les données est utilisée pour combler l'écart entre la solution paramétrique calculée, en utilisant des techniques de réduction de modèles non intrusives, et les champs mesurés, afin de rendre possibles des systèmes d'application dynamiques basés sur les données (jumeaux hybrides).
Wang, Xiang, and 王翔. "Model order reduction of time-delay systems with variational analysis." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46604236.
Повний текст джерелаHerath, Narmada Kumari. "Model order reduction for stochastic models of biomolecular systems with time-scale separation." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118083.
Повний текст джерелаCataloged from PDF version of thesis.
Includes bibliographical references (pages 177-183).
Biomolecular systems often involve reactions that take place on different time-scales, giving rise to 'slow' and 'fast' system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In deterministic systems, methods to obtain such reduced-order models are well defined by the singular perturbation or averaging techniques. However, model reduction of stochastic systems remains an ongoing area of research. In particular, existing model reduction methods for stochastic models of biomolecular systems lack rigorous error quantifications between the full and reduced dynamics. Furthermore, they only provide approximations for the slow variable dynamics, making the application of such methods to biomolecular systems difficult since the variables of interest are typically mixed (i.e., they encompass both fast and slow variables). In this thesis, we consider biomolecular systems modeled using the chemical Langevin equation (CLE) and the Linear Noise Approximation (LNA). Specifically, we consider biomolecular systems with linear propensity functions modeled by the CLE and systems with arbitrary propensity functions modeled by the LNA. For these systems, we obtain reduced-order models that approximate both the slow and fast variables under time-scale separation conditions. In particular, with suitable assumptions, we prove that the moments of the reduced-order models converge to those of the full systems as the time-scale separation becomes large. Our results further provide a rigorous justification for the accuracy of the stochastic total quasi-steady state approximation (tQSSA). We then consider two applications of these reduced-order models. In the first application, we analyze the trade-offs between modularity and signal noise in biomolecular networks. In the second application, we consider the application of the reduced-order LNA developed in this work to obtain reduced-order stochastic models for gene-regulatory networks.
by Narmada Kumari Herath.
Ph. D.
Muhirwa, Luc N. [Verfasser]. "Model Order Reduction of Linear Time Delay Systrems / Luc N. Muhirwa." München : Verlag Dr. Hut, 2016. http://d-nb.info/1120763312/34.
Повний текст джерелаGoury, Olivier. "Computational time savings in multiscale fracture mechanics using model order reduction." Thesis, Cardiff University, 2015. http://orca.cf.ac.uk/70925/.
Повний текст джерелаZhang, Zheng, and 张政. "Passivity assessment and model order reduction for linear time-invariant descriptor systems in VLSI circuit simulation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44909056.
Повний текст джерелаpublished_or_final_version
Electrical and Electronic Engineering
Master
Master of Philosophy
Bhattacharyya, Mainak. "A model reduction approach in space and time for fatigue damage simulation." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLN019/document.
Повний текст джерелаThe motivation of the research project is to predict the life time of mechanical components that are subjected to cyclic fatigue phenomena. The idea herein is to develop an innovative numerical scheme to predict failure of structures under such loading. The model is based on classical continuum damage mechanics introducing internal variables which describe the damage evolution. The challenge lies in the treatment of large number of load cycles for the life time prediction, particularly the residual life time for existing structures.Traditional approaches for fatigue analysis are based on phenomenological methods and deal with the usage of empirical relations. Such methods consider simplistic approximations and are unable to take into account complex geometries, and complicated loadings which occur in real-life engineering problems. A thermodynamically consistent continuum-based approach is therefore used for modelling the fatigue behaviour. This allows to consider complicated geometries and loads quite efficiently and the deterioration of the material properties due to fatigue can be quantified using internal variables. However, this approach can be computationally expensive and hence sophisticated numerical frameworks should be used.The numerical strategy used in this project is different when compared to regular time incremental schemes used for solving elasto-(visco)plastic-damage problems in continuum framework. This numerical strategy is called Large Time Increment (LATIN) method, which is a non-incremental method and builds the solution iteratively for the complete space-time domain. An important feature of the LATIN method is to incorporate an on-the-fly model reduction strategy to reduce drastically the numerical cost. Proper generalised decomposition (PGD), being a priori a model reduction strategy, separates the quantities of interest with respect to space and time, and computes iteratively the spatial and temporal approximations. LATIN-PGD framework has been effectively used over the years to solve elasto-(visco)plastic problems. Herein, the first effort is to solve continuum damage problems using LATIN-PGD techniques. Although, usage of PGD reduces the numerical cost, the benefit is not enough to solve problems involving large number of load cycles and computational time can be severely high, making simulations of fatigue problems infeasible. This can be overcome by using a multi-time scale approach, that takes into account the rapid evolution of the quantities of interest within a load cycle and their slow evolution along the load cycles. A finite element like description with respect to time is proposed, where the whole time domain is discretised into time elements, and only the nodal cycles, which form the boundary of the time elements, are calculated using LATIN-PGD technique. Thereby, classical shape functions are used to interpolate within the time element. This two-scale LATIN-PGD strategy enables the reduction of the computational cost remarkably, and can be used to simulate damage evolution in a structure under fatigue loading for a very large number of cycles
Espinoza-Cuadros, Anelit, Marcavillaca Miriam Criollo, Pablo Mendoza-Vargas, and Jose Alvarez. "Production model for the reduction of order delivery time in a peruvian metalworking company based on the six sigma dmaic methodology." Universidad Peruana de Ciencias Aplicadas (UPC), 2021. http://hdl.handle.net/10757/656015.
Повний текст джерелаThe present research work has as objective the application of Six Sigma DMAIC methodology in the production’s processes, the results will be manifested in increasing the efficiency of the production system and in reducing the delay in order delivery. In a metal mechanic company dedicated to the manufacture of electrical boards which focus is the terraced boards there was presented a fulfillment rate failure to deliver on time 46%. On the other hand, the delivery delay is generated because the current productivity does not supply what is required by the customer, therefore a minimum 394 units per month is needed to meet the requirements but currently only produce 226 units per month. For solve this problem it was proposed that Production model that merges the painting and baking areas and that generates an impact on the entire painting operation.
Guillet, Jérôme. "Etude et réduction d'ordre de modèles linéraires structurés : application à la dynamique du véhicule." Phd thesis, Université de Haute Alsace - Mulhouse, 2011. http://tel.archives-ouvertes.fr/tel-00807199.
Повний текст джерелаLauzeral, Nathan. "Reduced order and sparse representations for patient-specific modeling in computational surgery." Thesis, Ecole centrale de Nantes, 2019. http://www.theses.fr/2019ECDN0062.
Повний текст джерелаThis thesis investigates the use of model order reduction methods based on sparsity-related techniques for the development of real-time biophysical modeling. In particular, it focuses on the embedding of interactive biophysical simulation into patient-specific models of tissues and organs to enhance medical images and assist the clinician in the process of informed decision making. In this context, three fundamental bottlenecks arise. The first lies in the embedding of the shape parametrization into the parametric reduced order model to faithfully represent the patient’s anatomy. A non-intrusive approach relying on a sparse sampling of the space of anatomical features is introduced and validated. Then, we tackle the problem of data completion and image reconstruction from partial or incomplete datasets based on physical priors. The proposed solution has the potential to perform scene registration in the context of augmented reality for laparoscopy. Quasi-real-time computations are reached by using a new hyperreduction approach based on a sparsity promoting technique. Finally, the third challenge concerns the representation of biophysical systems under uncertainty of the underlying parameters. It is shown that traditional model order reduction approaches are not always successful in producing a low dimensional representation of a model, in particular in the case of electrosurgery simulation. An alternative is proposed using a metamodeling approach. To this end, we successfully extend the use of sparse regression methods to the case of systems with stochastic parameters
Книги з теми "Real-time model order reduction"
Lawford, Mark Stephen. Model reduction of discrete real-time systems. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1997.
Знайти повний текст джерелаBacior, Stanisław. Optymalizacja wiejskich układów gruntowych – badania eksperymentalne. Publishing House of the University of Agriculture in Krakow, 2019. http://dx.doi.org/10.15576/978-83-66602-37-3.
Повний текст джерелаGalderisi, Maurizio, and Sergio Mondillo. Assessment of diastolic function. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780199599639.003.0009.
Повний текст джерелаQueloz, Matthieu. The Practical Origins of Ideas. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780198868705.001.0001.
Повний текст джерелаDe Laurentis, Giacomo, Eugenio Alaio, Elisa Corsi, Emanuelemaria Giusti, Marco Guairo, Carlo Palego, Luca Paulicelli, et al. Rischio di credito 2.0. AIFIRM, 2021. http://dx.doi.org/10.47473/2016ppa00030.
Повний текст джерелаSobczyk, Eugeniusz Jacek. Uciążliwość eksploatacji złóż węgla kamiennego wynikająca z warunków geologicznych i górniczych. Instytut Gospodarki Surowcami Mineralnymi i Energią PAN, 2022. http://dx.doi.org/10.33223/onermin/0222.
Повний текст джерелаJohansen, Bruce, and Adebowale Akande, eds. Nationalism: Past as Prologue. Nova Science Publishers, Inc., 2021. http://dx.doi.org/10.52305/aief3847.
Повний текст джерелаЧастини книг з теми "Real-time model order reduction"
Ge, Y., L. T. Watson, E. G. Collins, and L. D. Davis. "Computationally Efficient Homotopies for the H 2 Model order Reduction Problem." In Linear Algebra for Large Scale and Real-Time Applications, 385–86. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-015-8196-7_36.
Повний текст джерелаBaumann, Michael, Dominik Hamann, and Peter Eberhard. "Time-Dependent Parametric Model Order Reduction for Material Removal Simulations." In Model Reduction of Parametrized Systems, 491–504. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58786-8_30.
Повний текст джерелаBaur, Ulrike, Peter Benner, Bernard Haasdonk, Christian Himpe, Immanuel Martini, and Mario Ohlberger. "Chapter 9: Comparison of Methods for Parametric Model Order Reduction of Time-Dependent Problems." In Model Reduction and Approximation, 377–407. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2017. http://dx.doi.org/10.1137/1.9781611974829.ch9.
Повний текст джерелаNaderi Lordejani, Sajad, Bart Besselink, Antoine Chaillet, and Nathan van de Wouw. "On Extended Model Order Reduction for Linear Time Delay Systems." In Model Reduction of Complex Dynamical Systems, 191–215. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72983-7_9.
Повний текст джерелаKumar, Mahendra, Aman, and Siyaram Yadav. "Model Order Reduction of Time Interval System: A Survey." In Advances in Intelligent Systems and Computing, 265–77. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1768-8_25.
Повний текст джерелаAumann, Quirin, Peter Benner, Jens Saak, and Julia Vettermann. "Model Order Reduction Strategies for the Computation of Compact Machine Tool Models." In Lecture Notes in Production Engineering, 132–45. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-34486-2_10.
Повний текст джерелаBradde, Tommaso, Alessandro Zanco, and Stefano Grivet-Talocia. "Data-Driven Model Order Reduction of Parameterized Dissipative Linear Time-Invariant Systems." In Scientific Computing in Electrical Engineering, 152–58. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54517-7_17.
Повний текст джерелаThiem, Xaver, Holger Rudolph, Robert Krahn, Steffen Ihlenfeldt, Christof Fetzer, and Jens Müller. "Adaptive Thermal Model for Structure Model Based Correction." In Lecture Notes in Production Engineering, 67–82. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-34486-2_6.
Повний текст джерелаMichiels, Wim, Gijs Hilhorst, Goele Pipeleers, and Jan Swevers. "Model Order Reduction for Time-Delay Systems, with Application to Fixed-Order $$\mathscr {H}_2$$ H 2 Optimal Controller Design." In Recent Results on Time-Delay Systems, 45–66. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26369-4_3.
Повний текст джерелаStanisławski, Rafał, Marek Rydel, and Krzysztof J. Latawiec. "New Implementation of Discrete-Time Fractional-Order PI Controller by Use of Model Order Reduction Methods." In Advances in Intelligent Systems and Computing, 1199–209. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50936-1_100.
Повний текст джерелаТези доповідей конференцій з теми "Real-time model order reduction"
Tang, Man, and Zhi-Hua Xiao. "Model order reduction of linear time-varying systems via shifted Legendre polynomials." In 2024 43rd Chinese Control Conference (CCC), 1340–45. IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10662255.
Повний текст джерелаMelendez, Nander, Jack Cruz, and Cesar Salas. "MAS4CHICKEN: Multi-Agent Systems based order service model for waiting time reduction at rotisserie chicken restaurants in Lima - Peru." In 2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI), 193–98. IEEE, 2024. https://doi.org/10.1109/iscmi63661.2024.10851627.
Повний текст джерелаLubkowski, Grzegorz, Radosław Piesiewicz, and Werner John. "Time Domain Modeling of Interconnected Integrated Circuits Based on Black Box Approach and Model Order Reduction for Signal Integrity Applications." In 2004_Wroclaw, 1–6. IEEE, 2004. https://doi.org/10.23919/emc.2004.10844155.
Повний текст джерелаMcGahan, Paul, Cedric Rouaud, and Michael Booker. "A Comparison of Model Order Reduction Techniques for Real-Time Battery Thermal Modelling." In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2019. http://dx.doi.org/10.4271/2019-01-0503.
Повний текст джерелаNguyen, Ngoc-Hien, Karen Willcox, and Boo Cheong Khoo. "Model Order Reduction for Stochastic Optimal Control." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82061.
Повний текст джерелаKahng, Sungtek, and Raj Mittra. "Equivalent circuit model order reduction by real-coefficient AFS." In 2011 IEEE International Symposium on Electromagnetic Compatibility - EMC 2011. IEEE, 2011. http://dx.doi.org/10.1109/isemc.2011.6038439.
Повний текст джерелаGosea, Ion Victor, Igor Pontes Duff, Peter Benner, and Athanasios C. Antoulas. "Model order reduction of bilinear time-delay systems." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8796085.
Повний текст джерелаGupta, Shivam, Somica Pathak, Saurabh Singh, Satyam Singh, and Ujjwal Yadav. "Model Order Reduction of Linear Time Invarient System." In 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE). IEEE, 2024. http://dx.doi.org/10.1109/ic3se62002.2024.10593493.
Повний текст джерелаGao, Baofeng, and Lamei Shang. "Research on Real-time Simulation Method of Vascular Interventional Surgery Based on Model Order Reduction." In 2020 IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, 2020. http://dx.doi.org/10.1109/icma49215.2020.9233617.
Повний текст джерелаXuanzeng, Lihong Feng, Yangfeng Su, Wei Cai, D. Zhou, and C. Chiang. "Time Domain Model Order Reduction by Wavelet Collocation Method." In 2006 Design, Automation and Test in Europe. IEEE, 2006. http://dx.doi.org/10.1109/date.2006.243963.
Повний текст джерелаЗвіти організацій з теми "Real-time model order reduction"
Carlberg, Kevin Thomas, Martin Drohmann, Raymond S. Tuminaro, Paul T. Boggs, Jaideep Ray, and Bart Gustaaf van Bloemen Waanders. Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction. Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1323654.
Повний текст джерелаGómez Loscos, Ana, Miguel Ángel González Simón, and Matías José Pacce. Short-term real-time forecasting model for spanish GDP (Spain-STING): new specification and reassessment of its predictive power. Madrid: Banco de España, March 2024. http://dx.doi.org/10.53479/36137.
Повний текст джерелаVelghe, Ineke, Bart Buffel, Veerle Vandeginste, Wim Thielemans, and Frederik Desplentere. Modelling hydrolytic, thermal, and mechanical degradation of PLA during single-screw extrusion. Universidad de los Andes, December 2024. https://doi.org/10.51573/andes.pps39.ss.dbc.1.
Повний текст джерелаZhang, Renduo, and David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, November 2004. http://dx.doi.org/10.32747/2004.7587220.bard.
Повний текст джерелаIanchovichina, Elena. GTAP-DD: A Model for Analyzing Trade Reforms in the Presence of Duty Drawbacks. GTAP Technical Paper, March 2004. http://dx.doi.org/10.21642/gtap.tp21.
Повний текст джерелаHanda, Avtar K., Yuval Eshdat, Avichai Perl, Bruce A. Watkins, Doron Holland, and David Levy. Enhancing Quality Attributes of Potato and Tomato by Modifying and Controlling their Oxidative Stress Outcome. United States Department of Agriculture, May 2004. http://dx.doi.org/10.32747/2004.7586532.bard.
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Повний текст джерелаBrydie, Dr James, Dr Alireza Jafari, and Stephanie Trottier. PR-487-143727-R01 Modelling and Simulation of Subsurface Fluid Migration from Small Pipeline Leaks. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), May 2017. http://dx.doi.org/10.55274/r0011025.
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