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F H Froes - One of the best experts on this subject based on the ideXlab platform.
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superior superplastic behavior in fine grained ti 6al 4v sheet
Journal of Alloys and Compounds, 2002Co-Authors: S N Patankar, G A Salishchev, J P Escobedo, David P Field, R M Galeyev, O R Valiakhmetov, F H FroesAbstract:Abstract The superplastic behavior of extremely fine-grained (300 nm) Ti–6Al–4V was studied by performing elevated temperature uniaxial tensile tests in the temperature range of 700–900 °C. The strain rate was varied from 10 −5 to 10 −1 s −1 to estimate the value of the strain rate Sensitivity Coefficient, m . The ductility of the fine-grained Ti–6Al–4V specimens was compared with that of a control set of conventional superplastic Ti–6Al–4V specimens with an average grain size of 3 μm. The results obtained indicate that the fine grain sized materials should see application in commercial use, with the caveat that a 1-μm grain size is considered optimum in terms of the superplastic forming temperature and subsequent creep behavior at use temperature.
Christopher M Perfetti - One of the best experts on this subject based on the ideXlab platform.
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scale continuous energy eigenvalue Sensitivity Coefficient calculations
Nuclear Science and Engineering, 2016Co-Authors: Christopher M Perfetti, Bradley T Rearden, William R MartinAbstract:AbstractThe need to model geometrically complex systems with improved ease of use and fidelity and the desire to extend the Tools for Sensitivity and UNcertainty Analysis Methodology Implementation...
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scale continuous energy eigenvalue Sensitivity Coefficient calculations
Nuclear Science and Engineering, 2016Co-Authors: Christopher M Perfetti, Bradley T Rearden, William R MartinAbstract:Sensitivity Coefficients describe the fractional change in a system response that is induced by changes to system parameters and nuclear data. The Tools for Sensitivity and UNcertainty Analysis Methodology Implementation (TSUNAMI) code within the SCALE code system makes use of eigenvalue Sensitivity Coefficients for an extensive number of criticality safety applications, including quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different critical systems, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved fidelity and the desire to extend TSUNAMI analysis to advanced applications has motivated the development of a methodology for calculating Sensitivity Coefficients in continuous-energy (CE) Monte Carlo applications. The Contributon-Linked eigenvalue Sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) and Iterated Fission Probability (IFP) eigenvalue Sensitivity methods were recently implemented in the CE-KENO framework of the SCALE code system to enable TSUNAMI-3D to perform eigenvalue Sensitivity calculations using continuous-energy Monte Carlo methods. This work provides a detailed description of the theory behind the CLUTCH method and describes in detail its implementation. This work explores the improvements in eigenvalue Sensitivity Coefficient accuracy that can be gained through the use of continuous-energy Sensitivity methods and also compares severalmore » Sensitivity methods in terms of computational efficiency and memory requirements.« less
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development of a scale tool for continuous energy eigenvalue Sensitivity Coefficient calculations
International Conference on Supercomputing, 2014Co-Authors: Christopher M Perfetti, Bradley T ReardenAbstract:Two methods for calculating eigenvalue Sensitivity Coefficients in continuous-energy Monte Carlo applications were implemented in the KENO code within the SCALE code package. The methods were used to calculate Sensitivity Coefficients for several criticality safety problems and produced Sensitivity Coefficients that agreed well with both reference sensitivities and multigroup TSUNAMI-3D Sensitivity Coefficients. The newly developed CLUTCH method was observed to produce Sensitivity Coefficients with high figures of merit and low memory requirements, and both continuous-energy Sensitivity methods met or exceeded the accuracy of the multigroup TSUNAMI-3D calculations.
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continuous energy eigenvalue Sensitivity Coefficient calculations in tsunami 3d
2013Co-Authors: Christopher M Perfetti, Bradley T ReardenAbstract:Two methods for calculating eigenvalue Sensitivity Coefficients in continuous-energy Monte Carlo applications were implemented in the KENO code within the SCALE code package. The methods were used to calculate Sensitivity Coefficients for several test problems and produced Sensitivity Coefficients that agreed well with both reference sensitivities and multigroup TSUNAMI-3D Sensitivity Coefficients. The newly developed CLUTCH method was observed to produce Sensitivity Coefficients with high figures of merit and a low memory footprint, and both continuous-energy Sensitivity methods met or exceeded the accuracy of the multigroup TSUNAMI-3D calculations. (authors)
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use of scale continuous energy monte carlo tools for eigenvalue Sensitivity Coefficient calculations
2013Co-Authors: Christopher M Perfetti, Bradley T ReardenAbstract:The TSUNAMI code within the SCALE code system makes use of eigenvalue Sensitivity Coefficients for an extensive number of criticality safety applications, such as quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different critical systems, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved fidelity and the desire to extend TSUNAMI analysis to advanced applications has motivated the development of a methodology for calculating Sensitivity Coefficients in continuous-energy (CE) Monte Carlo applications. The CLUTCH and Iterated Fission Probability (IFP) eigenvalue Sensitivity methods were recently implemented in the CE KENO framework to generate the capability for TSUNAMI-3D to perform eigenvalue Sensitivity calculations in continuous-energy applications. This work explores the improvements in accuracy that can be gained in eigenvalue and eigenvalue Sensitivity calculations through the use of the SCALE CE KENO and CE TSUNAMI continuous-energy Monte Carlo tools as compared to multigroup tools. The CE KENO and CE TSUNAMI tools were used to analyze two difficult models of critical benchmarks, and produced eigenvalue and eigenvalue Sensitivity Coefficient results that showed a marked improvement in accuracy. The CLUTCH Sensitivity method in particular excelled in terms of efficiency and computational memorymore » requirements.« less
Bradley T Rearden - One of the best experts on this subject based on the ideXlab platform.
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scale continuous energy eigenvalue Sensitivity Coefficient calculations
Nuclear Science and Engineering, 2016Co-Authors: Christopher M Perfetti, Bradley T Rearden, William R MartinAbstract:AbstractThe need to model geometrically complex systems with improved ease of use and fidelity and the desire to extend the Tools for Sensitivity and UNcertainty Analysis Methodology Implementation...
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scale continuous energy eigenvalue Sensitivity Coefficient calculations
Nuclear Science and Engineering, 2016Co-Authors: Christopher M Perfetti, Bradley T Rearden, William R MartinAbstract:Sensitivity Coefficients describe the fractional change in a system response that is induced by changes to system parameters and nuclear data. The Tools for Sensitivity and UNcertainty Analysis Methodology Implementation (TSUNAMI) code within the SCALE code system makes use of eigenvalue Sensitivity Coefficients for an extensive number of criticality safety applications, including quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different critical systems, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved fidelity and the desire to extend TSUNAMI analysis to advanced applications has motivated the development of a methodology for calculating Sensitivity Coefficients in continuous-energy (CE) Monte Carlo applications. The Contributon-Linked eigenvalue Sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) and Iterated Fission Probability (IFP) eigenvalue Sensitivity methods were recently implemented in the CE-KENO framework of the SCALE code system to enable TSUNAMI-3D to perform eigenvalue Sensitivity calculations using continuous-energy Monte Carlo methods. This work provides a detailed description of the theory behind the CLUTCH method and describes in detail its implementation. This work explores the improvements in eigenvalue Sensitivity Coefficient accuracy that can be gained through the use of continuous-energy Sensitivity methods and also compares severalmore » Sensitivity methods in terms of computational efficiency and memory requirements.« less
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development of a scale tool for continuous energy eigenvalue Sensitivity Coefficient calculations
International Conference on Supercomputing, 2014Co-Authors: Christopher M Perfetti, Bradley T ReardenAbstract:Two methods for calculating eigenvalue Sensitivity Coefficients in continuous-energy Monte Carlo applications were implemented in the KENO code within the SCALE code package. The methods were used to calculate Sensitivity Coefficients for several criticality safety problems and produced Sensitivity Coefficients that agreed well with both reference sensitivities and multigroup TSUNAMI-3D Sensitivity Coefficients. The newly developed CLUTCH method was observed to produce Sensitivity Coefficients with high figures of merit and low memory requirements, and both continuous-energy Sensitivity methods met or exceeded the accuracy of the multigroup TSUNAMI-3D calculations.
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continuous energy eigenvalue Sensitivity Coefficient calculations in tsunami 3d
2013Co-Authors: Christopher M Perfetti, Bradley T ReardenAbstract:Two methods for calculating eigenvalue Sensitivity Coefficients in continuous-energy Monte Carlo applications were implemented in the KENO code within the SCALE code package. The methods were used to calculate Sensitivity Coefficients for several test problems and produced Sensitivity Coefficients that agreed well with both reference sensitivities and multigroup TSUNAMI-3D Sensitivity Coefficients. The newly developed CLUTCH method was observed to produce Sensitivity Coefficients with high figures of merit and a low memory footprint, and both continuous-energy Sensitivity methods met or exceeded the accuracy of the multigroup TSUNAMI-3D calculations. (authors)
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use of scale continuous energy monte carlo tools for eigenvalue Sensitivity Coefficient calculations
2013Co-Authors: Christopher M Perfetti, Bradley T ReardenAbstract:The TSUNAMI code within the SCALE code system makes use of eigenvalue Sensitivity Coefficients for an extensive number of criticality safety applications, such as quantifying the data-induced uncertainty in the eigenvalue of critical systems, assessing the neutronic similarity between different critical systems, and guiding nuclear data adjustment studies. The need to model geometrically complex systems with improved fidelity and the desire to extend TSUNAMI analysis to advanced applications has motivated the development of a methodology for calculating Sensitivity Coefficients in continuous-energy (CE) Monte Carlo applications. The CLUTCH and Iterated Fission Probability (IFP) eigenvalue Sensitivity methods were recently implemented in the CE KENO framework to generate the capability for TSUNAMI-3D to perform eigenvalue Sensitivity calculations in continuous-energy applications. This work explores the improvements in accuracy that can be gained in eigenvalue and eigenvalue Sensitivity calculations through the use of the SCALE CE KENO and CE TSUNAMI continuous-energy Monte Carlo tools as compared to multigroup tools. The CE KENO and CE TSUNAMI tools were used to analyze two difficult models of critical benchmarks, and produced eigenvalue and eigenvalue Sensitivity Coefficient results that showed a marked improvement in accuracy. The CLUTCH Sensitivity method in particular excelled in terms of efficiency and computational memorymore » requirements.« less
Andre Bardow - One of the best experts on this subject based on the ideXlab platform.
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Sensitivity Coefficient based uncertainty analysis for multi functionality in lca
International Journal of Life Cycle Assessment, 2014Co-Authors: Johannes Jung, Niklas Von Der Assen, Andre BardowAbstract:In LCA, a multi-functionality problem exists whenever the environmental impacts of a multi-functional process have to be allocated between its multiple functions. Methods for fixing this multi-functionality problem are controversially discussed because the methods include ambiguous choices. To study the influence of these choices, the ISO standard requires a Sensitivity analysis. This work presents an analytical method for analyzing sensitivities and uncertainties of LCA results with respect to the choices made when a multi-functionality problem is fixed. The existing matrix algebra for LCA is expanded by explicit equations for methods that fix multi-functionality problems: allocation and avoided burden. For allocation, choices exist between alternative allocation factors. The expanded equations allow calculating LCA results as a function of allocation factors. For avoided burden, choices exist in selecting an avoided burden process from multiple candidates. This choice is represented by so-called aggregation factors. For avoided burden, the expanded equations calculate LCA results as a function of aggregation factors. The expanded equations are used to derive Sensitivity Coefficients for LCA results with respect to allocation factors and aggregation factors. Based on the Sensitivity Coefficients, uncertainties due to fixing a multi-functionality problem by allocation or avoided burden are analytically propagated. The method is illustrated using a virtual numerical example. The presented approach rigorously quantifies sensitivities of LCA results with respect to the choices made when multi-functionality problems are fixed with allocation and avoided burden. The uncertainties due to fixing multi-functionality problems are analytically propagated to uncertainties in LCA results using a first-order approximation. For uncertainties in allocation factors, the first-order approximation is exact if no loops of the allocated functional flows exist. The contribution of uncertainties due to fixing multi-functionality problems can be directly compared to the uncertainty contributions induced by uncertain process data or characterization factors. The presented method allows the computationally efficient study of uncertainties due to fixing multi-functionality problems and could be automated in software tools. This work provides a systematic method for the Sensitivity analysis required by the ISO standard in case choices between alternative allocation procedures exist. The resulting analytical approach includes contributions of uncertainties in process data, characterization factors, and—in extension to existing methods—uncertainties due to fixing multi-functionality problems in a unifying rigorous framework. Based on the uncertainty contributions, LCA practitioners can select fields for data refinement to decrease the overall uncertainty in LCA results.
Takanori Kitada - One of the best experts on this subject based on the ideXlab platform.
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simple method based on Sensitivity Coefficient for stochastic uncertainty analysis in probabilistic risk assessment
Reliability Engineering & System Safety, 2021Co-Authors: Satoshi Takeda, Takanori KitadaAbstract:Abstract For the analysis of stochastic uncertainty in probabilistic risk assessment, a simple method based on the Sensitivity Coefficient was developed. The Sensitivity Coefficient can be defined as the importance of the parameter included in the risk assessment model to the output such as the probability of the target event. When the contribution of the parameter to the output is assumed to be linear, the Sensitivity Coefficient equals Fussell-Vesely importance. The present method does not require a lot of calculation cost and can treat the covariance of the parameters included in the risk assessment directly. The result obtained by the present method was compared with that obtained by other methods such as the Monte Carlo method in the analysis of the simple fault tree model. The results of the present method agree well with Monte Carlo method in the analysis of the fault tree model with β factor method and that with the Multiple Greek Letter method.
