Open TURNS: An industrial software for uncertainty quantification in simulation

The needs to assess robust performances for complex systems and to answer tighter regulatory processes (security, safety, environmental control, and health impacts, etc.) have led to the emergence of a new industrial simulation challenge: to take uncertainties into account when dealing with complex numerical simulation frameworks. Therefore, a generic methodology has emerged from the joint effort of several industrial companies and academic institutions. EDF R&D, Airbus Group and Phimeca Engineering started a collaboration at the beginning of 2005, joined by IMACS in 2014, for the development of an Open Source software platform dedicated to uncertainty propagation by probabilistic methods, named OpenTURNS for Open source Treatment of Uncertainty, Risk 'N Statistics. OpenTURNS addresses the specific industrial challenges attached to uncertainties, which are transparency, genericity, modularity and multi-accessibility. This paper focuses on OpenTURNS and presents its main features: openTURNS is an open source software under the LGPL license, that presents itself as a C++ library and a Python TUI, and which works under Linux and Windows environment. All the methodological tools are described in the different sections of this paper: uncertainty quantification, uncertainty propagation, sensitivity analysis and metamodeling. A section also explains the generic wrappers way to link openTURNS to any external code. The paper illustrates as much as possible the methodological tools on an educational example that simulates the height of a river and compares it to the height of a dyke that protects industrial facilities. At last, it gives an overview of the main developments planned for the next few years

Steering efficiency of a ultrarelativistic proton beam in a thin bent crystal

Crystals with small thickness along the beam exhibit top performance for steering particle beams through planar channeling. For such crystals, the effect of nuclear dechanneling plays an important role because it affects their efficiency. We addressed the problem through experimental work carried out with 400 GeV/c protons at fixed-target facilities of CERN-SPS. The dependence of efficiency vs. curvature radius has been investigated and compared favourably to the results of modeling. A realistic estimate of the performance of a crystal designed for LHC energy including nuclear dechanneling has been achieved.Comment: 16 pages, 6 figure

Transport properties in correlated systems: An analytical model

Several studies have so far investigated transport properties of strongly correlated systems. Interesting features of these materials are the lack of resistivity saturation well beyond the Mott-Ioffe-Regel limit and the scaling of the resistivity with the hole density in underdoped cuprates. Due to the strongly correlated nature of these materials, mainly numerical techniques have been employed. A key role in this regards is thought to be played by the continuous transfer of spectral weight from coherent to incoherent states. In this paper we employ a simple analytical expression for the electronic Green's function to evaluate both quasi-particle and transport properties in correlated systems. Our analytical approach permits to enlighten the specific role of the spectral transfer due to the correlation on different features. In particular we investigate the dependence of both quasi-particle and transport scattering rate on the correlation degree and the criterion for resistivity saturation. systems.Comment: 11 pages, 8 figures. New version correcting a mistake of the previous version and added figure

Thermooxidative stability of PMMA composites

Tato práce se zabývá studiem termooxidační stability kompozitů polymethylmethakrylátu (PMMA) plněného mikro a nanočásticemi siliky. V připravených vzorcích byly použity různé objemové zlomky a různé velikosti částic siliky. Studium stability bylo prováděno pomocí termogravimetrie, která umožňuje simulovat podmínky termooxidační degradace. Indukční perioda byla stanovena za použití různých rychlostí ohřevu a aplikací izokonverzních metod. Závislosti teplot degradací na rychlostech ohřevu sloužily pro určení parametrů odvozených ze čtyř různých teplotních funkcí, které dovolují předpověď stability materiálu (indukční periody) při zvoleném rozsahu teplot. Zjištěné výsledky ukazují, že větší částice siliky snižuji stabilitu PMMA, zatímco nanočástice v nízkých koncentracích ji nijak neovlivňují.In this work the thermooxidative stability of poly(methyl metacrylate) (PMMA) composites reinforced with silica micro and nanoparticles was studied. Different volume fractions and particles sizes of silica particles were used. PMMA/silica composites were analysed by thermogravimetry which simulated the conditions of thermooxidative degradation. The induction periods were determined using different heating rates and applying the isoconversional methods. The dependence of degradation temperatures on heating rates were used for the determination of adjustable parameters derived for four different temperature functions allowing the prediction of material stability (induction periods) at chosen temperatures. Results showed that the larger silica particles destabilized the PMMA structure while smallest nanoparticles at low concentration had no effect on the stability.

Uncertainties of size measurements in electron microscopy characterization of nanomaterials in foods

Electron microscopy is a recognized standard tool for nanomaterial characterization, and recommended by the European Food Safety Authority for the size measurement of nanomaterials in food. Despite this, little data have been published assessing the reliability of the method, especially for size measurement of nanomaterials characterized by a broad size distribution and/or added to food matrices. This study is a thorough investigation of the measurement uncertainty when applying electron microscopy for size measurement of engineered nanomaterials in foods. Our results show that the number of measured particles was only a minor source of measurement uncertainty for nanomaterials in food, compared to the combined influence of sampling, sample preparation prior to imaging and the image analysis. The main conclusion is that to improve the measurement reliability, care should be taken to consider replications and matrix removal prior to sample preparation

Physics-based large-signal sensitivity analysis of microwave circuits using technological parametric sensitivity from multidimensional semiconductor device models

The authors present an efficient approach to evaluate the large-signal (LS) parametric sensitivity of active semiconductor devices under quasi-periodic operation through accurate, multidimensional physics-based models. The proposed technique exploits efficient intermediate mathematical models to perform the link between physics-based analysis and circuit-oriented simulations, and only requires the evaluation of dc and ac small-signal (dc charge) sensitivities under general quasi-static conditions. To illustrate the technique, the authors discuss examples of sensitivity evaluation, statistical analysis, and doping profile optimization of an implanted MESFET to minimize intermodulation which makes use of LS parametric sensitivities under two-tone excitatio

Analysis of Green Computing Strategy in University: Analytic Network Process (ANP) Approach

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis do not provide an analytical means to determine the importance of the identified factors of green computing strategy and implementation. Although the SWOT analysis successfully explores the factors, individual factors are usually described very generally. For this reason, SWOT analysis possesses deficiencies in the measurement and evaluation of green computing steps. Even though the analytic hierarchy process (AHP) technique eliminates these deficiencies, it does not allow for measuring the possible dependencies among the individual factors. The AHP method assumes that the green computing factors presented in the hierarchical structure are independent; however, this assumption may be inappropriate in light of certain situation. Therefore, it is important to utilize a form of SWOT analysis that calculates and takes into account the possible dependency among the factors. This paper demonstrates a process for quantitative SWOT analysis of green computing implementation that can be performed even when there is dependence among strategic factors. The proposed algorithm uses the analytic network process (ANP), which allows measurement of the dependency among the green computing implementation factors, as well as AHP, which is based on the independence between the factors. There are four alternatives: campus awareness program, computer procurement, increase in heat removal requirement, and increase in equipment power density for improving the implementation of green computing in campus. Dependency among the SWOT factors is observed to effect the strategic and sub-factor weights, as well as to change the strategy priorities. Based on ANC method, the best alternative for this implementation is computer procurement