Sensitivity analysis of the efficiency of Compton camera to the detector parameters using the GEANT4 computer code

2021 ◽  
pp. 109883
Author(s):  
Mostafa Niknami ◽  
Seyed Abolfazl Hosseini ◽  
Mahdy Ebrahimi Loushab
Keyword(s):  
Sensitivity Analysis ◽  
Computer Code ◽  
Compton Camera

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.

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.

scholarly journals A method of assessing the sensitivity of the Cochran–Mantel–Haenszel test to an unobserved confounder

2008 ◽  
Vol 366 (1874) ◽  
pp. 2377-2388 ◽  
Author(s):  
Binbing Yu ◽  
Joseph L Gastwirth
Keyword(s):  
Sensitivity Analysis ◽  
Observational Studies ◽  
Control Design ◽  
Computer Code ◽  
Case Control ◽  
Low Birth Weight Infants ◽  
Erroneous Conclusion ◽  
Maternal Hypertension ◽  
Haenszel Test ◽  
Causal Variables

Observational studies, including the case-control design frequently used in epidemiology, are subject to a number of biases and possible confounding factors. Failure to adjust with them may lead to an erroneous conclusion about the existence of a causal relationship between exposure and disease. The Cochran–Mantel–Haenszel (CMH) test is widely used to measure the strength of the association between an exposure and disease or response, after stratifying on the observed covariates. Thus, observed confounders are accounted for in the analysis. In practice, there may be causal variables that are unknown or difficult to obtain. Hence, they are not incorporated into the analysis. Sensitivity analysis enables investigators to assess the robustness of the findings. A method for assessing the sensitivity of the CMH test to an omitted confounder is presented here. The technique is illustrated by re-examining two datasets: one concerns the effect of maternal hypertension as a risk factor for low birth weight infants and the other focuses on the risk of allopurinol on having a rash. The computer code performing the sensitivity analysis is provided in appendix A.

scholarly journals Thermal Efficiency Projections of a Simple-Cycle Gas Turbine in Biogas Power Generation

1996 ◽  
Author(s):  
David E. Yomogida ◽  
Ngo D. Thinh ◽  
Valentino M. Tiangco ◽  
Ying Lee
Keyword(s):  
Power Generation ◽  
Sensitivity Analysis ◽  
Gas Turbine ◽  
Thermal Efficiency ◽  
Gas Turbines ◽  
Design Parameter ◽  
Computer Code ◽  
Simple Cycle ◽  
Specific Work ◽  
Expected Values

The thermal efficiency of a 125 kW simple-cycle gas turbine for biogas power generation was estimated, using a computer code developed for simple-cycle gas turbines. The computer code can predict expected values for the thermal efficiency and specific work along with the expected temperatures and pressures at various stages in the gas turbine. For the 125 kW Solar Gas Turbine (Titan series), the projected thermal efficiency is about 14%. This paper additionally presents a sensitivity analysis oo the operating condition and design parameter which had the greatest impacts on the thermal efficiency. These results will assist the California Energy Commission in determining the type of combustion device most suitable for biogas power generation.

Design Sensitivity Analysis of Planar Mechanism and Machine Dynamics

1981 ◽  
Vol 103 (3) ◽  
pp. 560-570 ◽  
Author(s):  
E. J. Haug ◽  
R. Wehage ◽  
N. C. Barman
Keyword(s):  
Sensitivity Analysis ◽  
Equations Of Motion ◽  
Computer Code ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Algebraic Equations ◽  
Analysis And Design ◽  
Structural Design Optimization ◽  
Mixed Systems ◽  
Crank Mechanism

A method of formulating and automatically integrating the equations of motion of quite general constrained dynamic systems is presented. Design sensitivity analysis is carried out using a state space adjoint variable method that has been employed extensively in optimal control and structural design optimization. Both dynamic analysis and design sensitivity analysis formulations are automated and numerical solution of state and adjoint differential equations are carried out using a stiff numerical integration method that treats mixed systems of differential and algebraic equations. A computer code that implements the method is applied to two numerical examples. The first example concerns a relatively simple slider-crank mechanism. The second example treats a more complex agricultural trip plow that undergoes intermittent motion.

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