[HTML][HTML] Single and multigeneration Rankine cycles with aspects of thermodynamical modeling, energy and exergy analyses and optimization: A key review along with …
The energy crises caused by the rapidly increasing population density around the world and
the economic, environmental and health threats, that have reached significant dimensions …
the economic, environmental and health threats, that have reached significant dimensions …
[图书][B] Basics and trends in sensitivity analysis: Theory and practice in R
In many fields, such as environmental risk assessment, agronomic system behavior,
aerospace engineering, and nuclear safety, mathematical models turned into computer code …
aerospace engineering, and nuclear safety, mathematical models turned into computer code …
[PDF][PDF] Introduction to sensitivity analysis
B Iooss, A Saltelli - Handbook of uncertainty quantification, 2017 - uq.math.cnrs.fr
Titre de la présentation Page 1 Kolkata, December, 2018 Introduction to sensitivity analysis
Bertrand Iooss (EDF R&D & Institut de Mathématiques de Toulouse, France) Page 2 ➢ …
Bertrand Iooss (EDF R&D & Institut de Mathématiques de Toulouse, France) Page 2 ➢ …
Gradient-based dimension reduction of multivariate vector-valued functions
Multivariate functions encountered in high-dimensional uncertainty quantification problems
often vary most strongly along a few dominant directions in the input parameter space. We …
often vary most strongly along a few dominant directions in the input parameter space. We …
Efficient global sensitivity analysis for high-dimensional outputs combining data-driven probability models and dimensionality reduction
WH Jung, AA Taflanidis - Reliability Engineering & System Safety, 2023 - Elsevier
This paper examines the efficient variance-based global sensitivity analysis (GSA),
quantified by estimating first-/higher-order and total-effect Sobol'indices, for applications …
quantified by estimating first-/higher-order and total-effect Sobol'indices, for applications …
Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational …
Dynamical earth and environmental systems models are typically computationally intensive
and highly parameterized with many uncertain parameters. Together, these characteristics …
and highly parameterized with many uncertain parameters. Together, these characteristics …
Global sensitivity analysis: A novel generation of mighty estimators based on rank statistics
F Gamboa, P Gremaud, T Klein, A Lagnoux - Bernoulli, 2022 - projecteuclid.org
We propose a new statistical estimation framework for a large family of global sensitivity
analysis indices. Our approach is based on rank statistics and uses an empirical correlation …
analysis indices. Our approach is based on rank statistics and uses an empirical correlation …
Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty
G Sarazin, J Morio, A Lagnoux, M Balesdent… - Reliability Engineering & …, 2021 - Elsevier
Reliability assessment in presence of epistemic uncertainty leads to consider the failure
probability as a quantity depending on the state of knowledge about uncertain input …
probability as a quantity depending on the state of knowledge about uncertain input …
[HTML][HTML] Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression
Uncertainty quantification (UQ) tasks, such as sensitivity analysis and parameter estimation,
entail a huge computational complexity when dealing with input-output maps involving the …
entail a huge computational complexity when dealing with input-output maps involving the …
Principal component analysis and sparse polynomial chaos expansions for global sensitivity analysis and model calibration: Application to urban drainage simulation
This paper presents an efficient surrogate modeling strategy for the uncertainty
quantification and Bayesian calibration of a hydrological model. In particular, a process …
quantification and Bayesian calibration of a hydrological model. In particular, a process …