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Grid Enabled Surrogate Modeling [PDF]
, 2009 The simulation and optimization of complex systems is a very time consuming and computationally intensive task. Therefore, global surrogate modeling methods are often used for the efficient exploration of the design space, as they reduce the number of simulations needed.
Gorissen, Dirk +3 more
openaire +3 more sources
A Surrogate Model of Gravitational Waveforms from Numerical Relativity Simulations of Precessing Binary Black Hole Mergers [PDF]
, 2017 We present the first surrogate model for gravitational waveforms from the coalescence of precessing binary black holes. We call this surrogate model NRSur4d2s. Our methodology significantly extends recently introduced reduced-order and surrogate modeling
Blackman, Jonathan +6 more
core +3 more sources
Fuel, 2022 Green methanol production, based on intermittent renewable energy sources, requires a more flexible operation mode and close integration with other sections, such as, the electrical grid and electrolysis processes.
Xiaoti Cui, S. Kær, M. Nielsen
semanticscholar +1 more source
Engineering Applications of Computational Fluid Mechanics, 2022 Extremely complex flow channels and multi-parameter, highly nonlinear thermal fluid–structure interactions are the main factors restricting the exploration mechanism and optimal design of explosion-proof valves.
Chaoyong Zong +6 more
doaj +1 more source
Influence of diesel surrogates on the behavior of simplified spray models [PDF]
, 2012 Numerous experimental investigations make use of diesel surrogates to make the computational time reasonable. In the few studies where measured (surrogate and real diesel) and computed (surrogate only) results have been compared, the selection ...
F Battin-Leclerc +6 more
core +2 more sources
Surrogate Modeling of Nonlinear Dynamic Systems: A Comparative Study
Journal of Computing and Information Science in Engineering, 2022 Surrogate models play a vital role in overcoming the computational challenge in designing and analyzing nonlinear dynamic systems, especially in the presence of uncertainty.
Ying Zhao +4 more
semanticscholar +1 more source
, 2020 Bayesian inverse modeling is important for a better understanding of hydrological processes. However, this approach can be computationally demanding, as it usually requires a large number of model evaluations.
Chen, Dingjiang +4 more
core +1 more source
GTApprox: Surrogate modeling for industrial design [PDF]
Advances in Engineering Software, 2016 31 pages, 11 ...
Mikhail Belyaev +6 more
openaire +2 more sources
IEEE Access, 2020 This paper presents an innovative modeling strategy for the construction of efficient and compact surrogate models for the uncertainty quantification of time-domain responses of digital links. The proposed approach relies on a two-step methodology. First,
Paolo Manfredi, Riccardo Trinchero
doaj +1 more source
Active learning to understand infectious disease models and improve policy making. [PDF]
PLoS Computational Biology, 2014 Modeling plays a major role in policy making, especially for infectious disease interventions but such models can be complex and computationally intensive. A more systematic exploration is needed to gain a thorough systems understanding.
Lander Willem +5 more
doaj +1 more source