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Titlebook: The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I; Overcoming the Curse Dan Gabriel Cacuci Book 2022 Springer

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書目名稱The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I
副標題Overcoming the Curse
編輯Dan Gabriel Cacuci
視頻videohttp://file.papertrans.cn/923/922542/922542.mp4
概述Describes the innovative C-ASAM methodology, framework, implementation and application.Presents separate frameworks for finite (algebraic) and infinite-dimensional (operator) spaces.Describes represen
圖書封面Titlebook: The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I; Overcoming the Curse Dan Gabriel Cacuci Book 2022 Springer
描述.The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties underlying the respective model. The functional derivatives (also called “sensitivities”) of results (also called “responses”) produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing “reduced-order modeling” by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing “model validation,” by comparing computations to experiments to address the question “does the modelrepresent reality?” (v) prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward “predictive modeling” to obtain best-estimate predicted results wit
出版日期Book 2022
關(guān)鍵詞finite-dimensional (matrix) systems; linear finite-dimensional systems; linear infinite-dimensional sy
版次1
doihttps://doi.org/10.1007/978-3-030-96364-4
isbn_softcover978-3-030-96366-8
isbn_ebook978-3-030-96364-4
copyrightSpringer Nature Switzerland AG 2022
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