The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Bruno Sudret - One of the best experts on this subject based on the ideXlab platform.
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An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis
Structural Safety, 2018Co-Authors: Stefano Marelli, Bruno SudretAbstract:Polynomial chaos expansions (PCE) have seen widespread use in the context of uncertainty quantification. However, their application to structural reliability problems has been hindered by the limited performance of PCE in the tails of the Model Response and due to the lack of local metaModel error estimates. We propose a new method to provide local metaModel error estimates based on bootstrap resampling and sparse PCE. An initial experimental design is iteratively updated based on the current estimation of the limit-state surface in an active learning algorithm. The greedy algorithm uses the bootstrap-based local error estimates for the polynomial chaos predictor to identify the best candidate set of points to enrich the experimental design. We demonstrate the effectiveness of this approach on a well-known analytical benchmark representing a series system, on a truss structure and on a complex realistic frame structure problem.
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Efficient design of experiments for sensitivity analysis based on polynomial chaos expansions
Annals of Mathematics and Artificial Intelligence, 2017Co-Authors: Evgeny Burnaev, Ivan Panin, Bruno SudretAbstract:Global sensitivity analysis aims at quantifying respective effects of input random variables (or combinations thereof) onto variance of a physical or mathematical Model Response. Among the abundant literature on sensitivity measures, Sobol indices have received much attention since they provide accurate information for most of Models. We consider a problem of experimental design points selection for Sobol’ indices estimation. Based on the concept of D-optimality, we propose a method for constructing an adaptive design of experiments, effective for calculation of Sobol’ indices based on Polynomial Chaos Expansions. We provide a set of applications that demonstrate the efficiency of the proposed approach.
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Physical and Polynomial Response Surfaces
2012Co-Authors: Frédéric Duprat, Franck Schoefs, Bruno SudretAbstract:Generally, structural reliability analysis is based on the supply of mechanical and probabilistic Models and a limit state function. In this chapter, we first define a mechanical Model that describes structural behavior. In a general sense, the mathematical transfer function $M$ allows us to evaluate the influence of loading with the knowledge of input parameters (or stimuli) that describe the structure and its environment. These parameters constitute the vector $x$. The Model Response is denoted here as $y=\mathcal M (x)$.
Peter C. M. Molenaar - One of the best experts on this subject based on the ideXlab platform.
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On the relation between the mean and the variance of a diffusion Model Response time distribution
Journal of Mathematical Psychology, 2005Co-Authors: Eric-jan Wagenmakers, Raoul P. P. P. Grasman, Peter C. M. MolenaarAbstract:Abstract Almost every empirical psychological study finds that the variance of a Response time (RT) distribution increases with the mean. Here we present a theoretical analysis of the nature of the relationship between RT mean and RT variance, based on the assumption that a diffusion Model (e.g., Ratcliff (1978) Psychological Review , 85 , 59–108; Ratcliff (2002). Psychonomic Bulletin & Review , 9 , 278–291), adequately captures the shape of empirical RT distributions. We first derive closed-form analytic solutions for the mean and variance of a diffusion Model RT distribution. Next, we study how systematic differences in two important diffusion Model parameters simultaneously affect the mean and the variance of the diffusion Model RT distribution. Within the range of plausible values for the drift rate parameter, the relation between RT mean and RT standard deviation is approximately linear. Manipulation of the boundary separation parameter also leads to an approximately linear relation between RT mean and RT standard deviation, but only for low values of the drift rate parameter.
Eric-jan Wagenmakers - One of the best experts on this subject based on the ideXlab platform.
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On the relation between the mean and the variance of a diffusion Model Response time distribution
Journal of Mathematical Psychology, 2005Co-Authors: Eric-jan Wagenmakers, Raoul P. P. P. Grasman, Peter C. M. MolenaarAbstract:Abstract Almost every empirical psychological study finds that the variance of a Response time (RT) distribution increases with the mean. Here we present a theoretical analysis of the nature of the relationship between RT mean and RT variance, based on the assumption that a diffusion Model (e.g., Ratcliff (1978) Psychological Review , 85 , 59–108; Ratcliff (2002). Psychonomic Bulletin & Review , 9 , 278–291), adequately captures the shape of empirical RT distributions. We first derive closed-form analytic solutions for the mean and variance of a diffusion Model RT distribution. Next, we study how systematic differences in two important diffusion Model parameters simultaneously affect the mean and the variance of the diffusion Model RT distribution. Within the range of plausible values for the drift rate parameter, the relation between RT mean and RT standard deviation is approximately linear. Manipulation of the boundary separation parameter also leads to an approximately linear relation between RT mean and RT standard deviation, but only for low values of the drift rate parameter.
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Notes and comments On the relation between the mean and the variance of a diffusion Model Response time distribution
2005Co-Authors: Eric-jan WagenmakersAbstract:Almost every empirical psychological study finds that the variance of a Response time (RT) distribution increases with the mean. Here we present a theoretical analysis of the nature of the relationship between RT mean and RT variance, based on the assumption that a diffusion Model (e.g., Ratcliff (1978) Psychological Review, 85, 59–108; Ratcliff (2002). Psychonomic Bulletin & Review, 9, 278–291), adequately captures the shape of empirical RT distributions. We first derive closed-form analytic solutions for the mean and variance of a diffusion Model RT distribution. Next, we study how systematic differences in two important diffusion Model parameters simultaneously affect the mean and the variance of the diffusion Model RT distribution. Within the range of plausible values for the drift rate parameter, the relation between RT mean and RT standard deviation is approximately linear. Manipulation of the boundary separation parameter also leads to an approximately linear relation between RT mean and RT standard deviation, but only for low values of the drift rate parameter.
Katja Matthes - One of the best experts on this subject based on the ideXlab platform.
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Modeling the whole atmosphere Response to solar cycle changes in radiative and geomagnetic forcing
Journal of Geophysical Research, 2007Co-Authors: Daniel R Marsh, Stanley C. Solomon, Rolando R Garcia, Douglas E Kinnison, Byron A Boville, Fabrizio Sassi, Katja MatthesAbstract:The NCAR Whole Atmosphere Community Climate Model, version 3 (WACCM3), is used to study the atmospheric Response from the surface to the lower thermosphere to changes in solar and geomagnetic forcing over the 11-year solar cycle. WACCM3 is a general circulation Model that incorporates interactive chemistry that solves for both neutral and ion species. Energy inputs include solar radiation and energetic particles, which vary significantly over the solar cycle. This paper presents a comparison of simulations for solar cycle maximum and solar cycle minimum conditions. Changes in composition and dynamical variables are clearly seen in the middle and upper atmosphere, and these in turn affect terms in the energy budget. Generally good agreement is found between the Model Response and that derived from satellite observations, although significant differences remain. A small but statistically significant Response is predicted in tropospheric winds and temperatures which is consistent with signals observed in reanalysis data sets.
E.c. Gaucher - One of the best experts on this subject based on the ideXlab platform.
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Uncertainty in the reactive transport Model Response to analkaline perturbation in a clay formation
2006Co-Authors: A. Burnol, P. Blanc, N. Spycher, E.c. GaucherAbstract:The mineral alteration in the concrete barrier and in the clay formation around long-lived intermediate-level radioactive waste in the French deep geological disposal concept is evaluated using numerical Modeling. There are concerns that the mineralogical composition of the surrounded clay will not be stable under the high alkaline pore fluid conditions caused by concrete (pH {approx} 12). Conversely, the infiltration of CO{sub 2}-rich groundwater from the clay formation into initially unsaturated concrete, at the high temperature (T {approx} 70 C) produced from the decay of radionuclides, could cause carbonation, thereby potentially affecting critical performance functions of this barrier. This could also lead to significant changes in porosity, which would affect aqueous diffusive transport of long-lived radionuclides. All these processes are therefore intimately coupled and advanced reactive transport Models are required for long-term performance assessment. The uncertainty in predictions of these Models is one major question that must be answered. A mass-transfer Model Response to an alkaline perturbation in clay with standard Model values is first simulated using the two-phase non-isothermal reactive transport code TOUGHREACT. The selection of input parameters is thereafter designed to sample uncertainties in a wide range of physico-chemical processes without making a priori assumptions about the relative importance of different feedbacks. This 'base-case' simulation is perturbed by setting a parameter to a minimum, intermediate or maximum value or by switching on/off a process. This sensitivity analysis is conducted using grid computing facilities of BRGM (http://iggi.imag.fr). Our evaluation of the preliminary results suggests that the resaturation and the heating of the near-field will be of long enough duration to cause a limited carbonation through all the width of the concrete barrier. Another prediction is the possibility of self-sealing at the concrete/clay interface. Further research is however required to discuss the effect of such evolution on the desirable performance function of both barriers.
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UNCERTAINTY IN THE REACTIVE TRANSPORT Model Response TO AN ALKALINE PERTURBATION IN A CLAY FORMATION
Lawrence Berkeley National Laboratory, 2006Co-Authors: A. Burnol, P. Blanc, N. Spycher, E.c. GaucherAbstract:The mineral alteration in the concrete barrier and in the clay formation around long-lived intermediatelevel radioactive waste in the French deep geological disposal concept is evaluated using numerical Modeling. There are concerns that the mineralogical composition of the surrounded clay will not be stable under the high alkaline pore fluid conditions caused by concrete (pH~12). Conversely, the infiltration of CO2-rich groundwater from the clay formation into initially unsaturated concrete, at the high temperature (T~70°C) produced from the decay of radionuclides, could cause carbonation, thereby potentially affecting critical performance functions of this barrier. This could also lead to significant changes in porosity, which would affect aqueous diffusive transport of long-lived radionuclides. All these processes are therefore intimately coupled and advanced reactive transport Models are required for long-term performance assessment. The uncertainty in predictions of these Models is one major question that must be answered. A mass-transfer Model Response to an alkaline perturbation in clay with standard Model values is first simulated using the two-phase nonisothermal reactive transport code TOUGHREACT. The selection of input parameters is thereafter designed to sample uncertainties in a wide range of physico-chemical processes without making a priori assumptions about the relative importance of different feedbacks. This “base-case” simulation is perturbed by setting a parameter to a minimum, intermediate or maximum value or by switching on/off a process. This sensitivity analysis is conducted using grid computing facilities of BRGM (http://iggi.imag.fr). Our evaluation of the preliminary results suggests that the resaturation and the heating of the near-field will be of long enough duration to cause a limited carbonation through all the width of the concrete barrier. Another prediction is the possibility of selfsealing at the concrete/clay interface. Further research is however required to discuss the effect of such evolution on the desirable performance function of both barriers.