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Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments

Publications associées (41)

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The efficiency of stochastic particle schemes for large scale simulations relies on the ability to preserve a uniform distribution of particles in the whole physical domain. While simple particle split and merge algorithms have been considered previously, ...

2019

Beyond R&D: the role of embodied technological change in affecting employment

Gabriele Pellegrino

In this work, we test the employment impact of distinct types of innovative investments using a representative sample of Spanish manufacturing firms over the period 2002-2013. Our GMM-SYS estimates generate various results, which are partially in contrast ...

SPRINGER2019

Residual hip dysplasia in children: osseous and cartilaginous acetabular angles to guide further treatment-a pilot study

Katarzyna Pierzchala

Purpose In case of residual hip dysplasia (RHD) in children, pelvic radiographs are sometimes insufficient to precisely evaluate the entire coverage of the femoral head, when trying to decide on the need for further reconstructive procedures. Methods This ...

BMC2019

The detection of two-component mixture alternatives

Daria Rukina

In this thesis, we deal with one of the facets of the statistical detection problem. We study a particular type of alternative, the mixture model. We consider testing where the null hypothesis corresponds to the absence of a signal, represented by some kno ...

EPFL2018

Energy and Reserve Dispatch with Distributionally Robust Joint Chance Constraints

Daniel Kuhn, Viet Anh Nguyen, Christos Ordoudis

We develop a two-stage stochastic program for energy and reserve dispatch, which ensures the safe operation of a power system with a high penetration of renewables and a strong interdependence with the natural gas system. Distributionally robust joint chan ...

2018

Quasi-random numbers for copula models

Mathieu Jacques David Cambou

The present work addresses the question how sampling algorithms for commonly applied copula models can be adapted to account for quasi-random numbers. Besides sampling methods such as the conditional distribution method (based on a one-to-one transformatio ...

Springer2017

Objectives: The frontal hemispheric asymmetry and error-related components, as measured by EEG, are often considered to be biological correlates or “indicators of risk” for psychopathology. Here, we performed a meta-analysis to define specific patterns of ...

2017

Bayesian Calibration of Thermal-Hydraulics Model with Time-Dependent Output

Andreas Pautz, Damar Canggih Wicaksono, Omar Zerkak

The currently adopted practice for uncertainty quantification of thermal-hydraulics code predictions is done through statistical sampling where the code is evaluated multiple times using different values of input parameters that are randomly generated acco ...

2016

Sampling-Based Nuclear Data Uncertainty Quantification for Continuous Energy Monte Carlo Codes

Ting Zhu

The goal of the present PhD research is to establish a methodology of nuclear data uncertainty quantification (NDUQ) for MCNPX, the continuous-energy Monte-Carlo (M-C) code. The high fidelity (continuous-energy treatment and flexible geometry modelling) of ...

EPFL2015

Extremal behavior of squared Bessel processes attracted by the Brown-Resnick process

Sebastian Engelke

The convergence of properly time-scaled and normalized maxima of independent standard Brownian motions to the Brown-Resnick process is well-known in the literature. In this paper, we study the extremal functional behavior of non-Gaussian processes, namely ...

Elsevier Science Bv2015