scholarly journals Variable selection and sensitivity analysis using dynamic trees, with an application to computer code performance tuning

2013 ◽  
Vol 7 (1) ◽  
pp. 51-80 ◽  
Author(s):  
Robert B. Gramacy ◽  
Matt Taddy ◽  
Stefan M. Wild
Keyword(s):  
Sensitivity Analysis ◽  
Variable Selection ◽  
Computer Code ◽  
Performance Tuning ◽  
Code Performance ◽  
Dynamic Trees

Sobol′ Sensitivity Analysis Using a Neural Network Model of a LB-LOCA in the ZION Nuclear Power Plant With CATHARE-2 V2.5 Code

2013 ◽  
Author(s):  
Fabrice Fouet ◽  
Pierre Probst
Keyword(s):  
Neural Network ◽  
Sensitivity Analysis ◽  
Nuclear Power ◽  
Uncertainty Propagation ◽  
Correlation Coefficients ◽  
Computer Code ◽  
Numerical Application ◽  
Loss Of Coolant Accident ◽  
Input Parameters ◽  
Artificial Neural Network Ann

In nuclear safety, the Best-Estimate (BE) codes may be used in safety demonstration and licensing, provided that uncertainties are added to the relevant output parameters before comparing them with the acceptance criteria. The uncertainty of output parameters, which comes mainly from the lack of knowledge of the input parameters, is evaluated by estimating the 95% percentile with a high degree of confidence. IRSN, technical support of the French Safety Authority, developed a method of uncertainty propagation. This method has been tested with the BE code used is CATHARE-2 V2.5 in order to evaluate the Peak Cladding Temperature (PCT) of the fuel during a Large Break Loss Of Coolant Accident (LB-LOCA) event, starting from a large number of input parameters. A sensitivity analysis is needed in order to limit the number of input parameters and to quantify the influence of each one on the response variability of the numerical model. Generally, the Global Sensitivity Analysis (GSA) is done with linear correlation coefficients. This paper presents a new approach to perform a more accurate GSA to determine and to classify the main uncertain parameters: the Sobol′ methodology. The GSA requires simulating many sets of parameters to propagate uncertainties correctly, which makes of it a time-consuming approach. Therefore, it is natural to replace the complex computer code by an approximate mathematical model, called response surface or surrogate model. We have tested Artificial Neural Network (ANN) methodology for its construction and the Sobol′ methodology for the GSA. The paper presents a numerical application of the previously described methodology on the ZION reactor, a Westinghouse 4-loop PWR, which has been retained for the BEMUSE international problem [8]. The output is the first maximum PCT of the fuel which depends on 54 input parameters. This application outlined that the methodology could be applied to high-dimensional complex problems.

scholarly journals Applications of DEA

2019 ◽  
Vol 8 (12) ◽  
pp. 3337-3341
Keyword(s):  
Sensitivity Analysis ◽  
Data Envelopment Analysis ◽  
Variable Selection ◽  
Efficiency Measurement ◽  
Data Envelopment ◽  
Selection Methods ◽  
Seminal Paper ◽  
The Public ◽  
Methodological Aspects

Data Envelopment Analysis (DEA), an efficiency measurement and benchmarking technique originated in 1978 with the publication of the seminal paper of Charnes et al (1978) has evolved into an important technique over the years. This paper attempts to critically review the various methodological aspects of DEA for application in any domain in the public or private sectors. In specific it reviews some of the important literature available on a) variable selection methods in DEA, b) Sensitivity analysis and ranking of DMUs and c) some of the applications it has been put into over the last four decades. The focus is on specific practical aspects of applying DEA in any particular field.

scholarly journals Global Sensitivity Analysis for Optimization with Variable Selection

2019 ◽  
Vol 7 (2) ◽  
pp. 417-443 ◽  
Author(s):  
Adrien Spagnol ◽  
Rodolphe Le Riche ◽  
Sébastien Da Veiga
Keyword(s):  
Sensitivity Analysis ◽  
Variable Selection ◽  
Global Sensitivity Analysis ◽  
Global Sensitivity

Reconfiguration of Uniprocessor Sporadic Real-Time Systems

2011 ◽  
pp. 167-189 ◽  
Author(s):  
Laurent George ◽  
Pierre Courbin
Keyword(s):  
Sensitivity Analysis ◽  
Real Time ◽  
Performance Tuning ◽  
Real Time Systems ◽  
Software Faults ◽  
Worst Case ◽  
Task Model ◽  
Worst Case Execution Time ◽  
On Line ◽  
Time Systems

In this chapter the authors focus on the problem of reconfiguring embedded real-time systems. Such reconfiguration can be decided either off-line to determine if a given application can be run on a different platform, while preserving the timeliness constraints imposed by the application, or on-line, where a reconfiguration should be done to adapt the system to the context of execution or to handle hardware or software faults. The task model considered in this chapter is the classical sporadic task model defined by a Worst Case Execution Time (WCET), a minimum inter-arrival time (also denoted the minimum Period) and a late termination deadline. The authors consider two preemptive scheduling strategies: Fixed Priority highest priority first (FP) and Earliest Deadline First (EDF). They propose a sensitivity analysis to handle reconfiguration issues. Sensitivity analysis aims at determining acceptable deviations from the specifications of a problem due to evolutions in system characteristics (reconfiguration or performance tuning). They present a state of the art for sensitivity analysis in the case of WCETs, Periods and Deadlines reconfigurations and study to what extent sensitivity analysis can be used to decide on the possibility of reconfiguring a system.

Supercomputer-Based Sensitivity Analysis of Constrained Dynamic Systems

1987 ◽  
Author(s):  
P. Krishnaswami ◽  
S. Ramaswamy
Keyword(s):  
Sensitivity Analysis ◽  
Dynamic Systems ◽  
Large Scale ◽  
Computing Time ◽  
Computer Code ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Dramatic Reduction ◽  
Computational Performance ◽  
Computationally Intensive

Abstract Generalized design sensitivity analysis of constrained dynamic systems is a computationally intensive process that is well-suited for implementation on a modern supercomputer. A matrix oriented method for design sensitivity analysis, based on direct differentiation, is developed. An algorithm based on this development was implemented in a computer code which was then run on a Cray X-MP supercomputer. The implementation attempts to make full use of the vectorization capabilities of this machine. The numerical examples that were run on this implementation were compared with results presented in the literature in order to verify the program and to assess its computational performance. The results show that the use of supercomputers for performing design sensitivity analysis of dynamic systems using this method produces a dramatic reduction in the computing time; it is anticipated that this will make the optimization of very large-scale dynamic systems computationally viable.

Sensitivity Analysis by the Use of a Surrogate Model During Large Break LOCA on ZION Nuclear Power Plant With CATHARE-2 V2.5 Code

2009 ◽  
Author(s):  
Fabrice Fouet ◽  
Pierre Probst
Keyword(s):  
Sensitivity Analysis ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Surrogate Model ◽  
Nuclear Power ◽  
Uncertainty Propagation ◽  
Correlation Coefficients ◽  
General Rule ◽  
Computer Code ◽  
Input Parameters

In nuclear safety, the Best-Estimate (BE) codes may be used in demonstration and licensing, provided that uncertainties are added to the relevant output parameters before comparing them with the acceptance criteria. The uncertainty of output parameters, which comes mainly from the lack of knowledge of the input parameters, is evaluated by estimating the 95% percentile with a high degree of confidence. IRSN, technical support of the French Safety Authority, develop a method of uncertainty propagation and chose to apply it to the calculation of the Peak Cladding Temperature (PCT) with CATHARE-2 V2.5 code during a Large Break (LB) LOCA event for ZION, a 4-loop PWR of Westinghouse design. As a general rule the Global Sensitivity Analysis (GSA) is done with linear correlation coefficients. This paper presents a new approach to perform a more accurate GSA to determine and to classify the main uncertain parameters: the SOBOL methodology. This technique requires simulating many sets of parameters to propagate uncertainties correctly, which makes of it a time-consuming approach. Therefore, it is natural to replace the complex computer code by an approximate mathematical model, called response surface or surrogate model. Kriging methodology (with simulated annealing optimization) for its construction and the SOBOL methodology for the GSA are used. The paper presents the application of the previously described methodology on a LB-LOCA scenario in ZION reactor, associated with 54 input parameters. The output is the first maximum peak cladding temperature of the fuel. Results show that the methodology could be applied to both high-dimensional complex problems and real nuclear power plant calculations.

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