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of 29
pro vyhledávání: '"Lorenzo Tamellini"'
When dealing with timber structures, the characteristic strength and stiffness of the material are made highly variable and uncertain by the unavoidable, yet hardly predictable, presence of knots and other defects. In this work we apply the sparse gr
Externí odkaz:
http://arxiv.org/abs/2211.04735
Autor:
Yueting Li, Claudia Zoccarato, Lorenzo Tamellini, Chiara Piazzola, Pablo Ezquerro, Guadalupe Bru, Carolina Guardiola‐Albert, Roberta Bonì, Pietro Teatini
Land subsidence is one of most severe geohazards caused by excessive groundwater pumping which has gained increasingly interest over the last decades. Various numerical models have been developed to address this mechanism and support the groundwater
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f72c92b10ea63ba690cc34c0652fa0a2
https://doi.org/10.5194/egusphere-egu23-8761
https://doi.org/10.5194/egusphere-egu23-8761
Autor:
Emily A. Baker, Sauro Manenti, Alessandro Reali, Giancarlo Sangalli, Lorenzo Tamellini, Sara Todeschini
Publikováno v:
GEM - International Journal on Geomathematics. 14
Groundwater flow modeling is commonly used to calculate groundwater heads, estimate groundwater flow paths and travel times, and provide insights into solute transport processes within an aquifer. However, the values of input parameters that drive gr
Autor:
John D. Jakeman, Sam Friedman, Michael S. Eldred, Lorenzo Tamellini, Alex A. Gorodetsky, Doug Allaire
Publikováno v:
International Journal for Numerical Methods in Engineering. 123:2760-2790
Publikováno v:
SIAM Journal on Numerical Analysis. 60:659-687
Convergence of an adaptive collocation method for the stationary parametric diffusion equation with finite-dimensional affine coefficient is shown. The adaptive algorithm relies on a recently introduced residual-based reliable a posteriori error esti
When dealing with timber structures, the characteristic strength and stiffness of the material are made highly variable and uncertain by the unavoidable, yet hardly predictable, presence of knots and other defects. In this work we apply the sparse gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::da4f2268adb4e4d10817bbff115dcef5
http://arxiv.org/abs/2211.04735
http://arxiv.org/abs/2211.04735
Autor:
Emily A. Baker, Alessandro Cappato, Sara Todeschini, Lorenzo Tamellini, Giancarlo Sangalli, Alessandro Reali, Sauro Manenti
Groundwater flow model accuracy is often limited by the uncertainty in model parameters that characterize aquifer properties and aquifer recharge. Aquifer properties such as hydraulic conductivity can have an uncertainty spanning orders of magnitude.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d0630d87f65a2bc7fd8696e260ade1f
http://arxiv.org/abs/2206.01990
http://arxiv.org/abs/2206.01990
Autor:
Lorenzo Tamellini, Doug Allaire, Michael S. Eldred, John D. Jakeman, Alex Gorodestky, Sam Friedman
Publikováno v:
Proposed for presentation at the IX International Conference on Coupled Problems in Science and Engineering held June 13-16, 2021..
Publikováno v:
Lecture Notes in Computational Science and Engineering ISBN: 9783030813611
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07dcfb4dd7742d0ff528bd59919ee73a
https://doi.org/10.1007/978-3-030-81362-8_1
https://doi.org/10.1007/978-3-030-81362-8_1
Publikováno v:
Mathematical Biosciences
Mathematical biosciences 332 (2021): 108514. doi:10.1016/j.mbs.2020.108514
info:cnr-pdr/source/autori:C. Piazzola, L. Tamellini, and R. Tempone/titolo:A note on tools for prediction under uncertainty and identifiability of SIR-like dynamical systems for epidemiology/doi:10.1016%2Fj.mbs.2020.108514/rivista:Mathematical biosciences/anno:2021/pagina_da:108514/pagina_a:/intervallo_pagine:108514/volume:332
Mathematical biosciences 332 (2021): 108514. doi:10.1016/j.mbs.2020.108514
info:cnr-pdr/source/autori:C. Piazzola, L. Tamellini, and R. Tempone/titolo:A note on tools for prediction under uncertainty and identifiability of SIR-like dynamical systems for epidemiology/doi:10.1016%2Fj.mbs.2020.108514/rivista:Mathematical biosciences/anno:2021/pagina_da:108514/pagina_a:/intervallo_pagine:108514/volume:332
We provide an overview of the methods that can be used for prediction under uncertainty and data fitting of dynamical systems, and of the fundamental challenges that arise in this context. The focus is on SIR-like models, that are being commonly used