Sensitivity analysis for reliable design verification of nuclear turbosets

In this paper, we present an application of sensitivity analysis for design verification of nuclear turbosets. Before the acquisition of a turbogenerator, energy power operators perform independent design assessment in order to assure safe operating conditions of the new machine in its environment. Variables of interest are related to the vibration behaviour of the machine: its eigenfrequencies and dynamic sensitivity to unbalance. In the framework of design verification, epistemic uncertainties are preponderant. This lack of knowledge is due to inexistent or imprecise information about the design as well as to interaction of the rotating machinery with supporting and sub-structures. Sensitivity analysis enables the analyst to rank sources of uncertainty with respect to their importance and, possibly, to screen out insignificant sources of uncertainty. Further studies, if necessary, can then focus on predominant parameters. In particular, the constructor can be asked for detailed information only about the most significant parameters.

[1]  Abdelali Gabih,et al.  An ε-Optimal Portfolio with Stochastic Volatility , 2005, Monte Carlo Methods Appl..

[2]  Shuangzhe Liu,et al.  Global Sensitivity Analysis: The Primer by Andrea Saltelli, Marco Ratto, Terry Andres, Francesca Campolongo, Jessica Cariboni, Debora Gatelli, Michaela Saisana, Stefano Tarantola , 2008 .

[3]  Evgeny Petrov Method for Sensitivity Analysis of Resonance Forced Response of Bladed Disks With Nonlinear Contact Interfaces , 2009 .

[4]  C Soize,et al.  Maximum entropy approach for modeling random uncertainties in transient elastodynamics. , 2001, The Journal of the Acoustical Society of America.

[5]  Paola Annoni,et al.  Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index , 2010, Comput. Phys. Commun..

[6]  A. Saltelli,et al.  Importance measures in global sensitivity analysis of nonlinear models , 1996 .

[7]  Andrea Saltelli,et al.  An effective screening design for sensitivity analysis of large models , 2007, Environ. Model. Softw..

[8]  Tarantola Stefano,et al.  Uncertainty in Industrial Practice - A Guide to Quantitative Uncertainty Management , 2008 .

[9]  A. Saltelli,et al.  A quantitative model-independent method for global sensitivity analysis of model output , 1999 .

[10]  Jon C. Helton,et al.  Survey of sampling-based methods for uncertainty and sensitivity analysis , 2006, Reliab. Eng. Syst. Saf..

[11]  Marco Ratto,et al.  Global Sensitivity Analysis , 2008 .

[12]  Jean Frene,et al.  Dynamic behaviour of elastic shaft supported by hydrodynamic bearings , 2000 .

[13]  Saltelli Andrea,et al.  Global Sensitivity Analysis: The Primer , 2008 .

[14]  Harvey M. Wagner,et al.  Global Sensitivity Analysis , 1995, Oper. Res..

[15]  Mnaouar Chouchane,et al.  Eigensensitivity computation of asymmetric damped systems using an algebraic approach , 2007 .

[16]  Stefano Tarantola,et al.  Reliable design verification of nuclear turboset using sensitivity analysis on exceedance probalities. , 2009 .

[17]  E. Borgonovo Measuring Uncertainty Importance: Investigation and Comparison of Alternative Approaches , 2006, Risk analysis : an official publication of the Society for Risk Analysis.

[18]  Sergei S. Kucherenko,et al.  On global sensitivity analysis of quasi-Monte Carlo algorithms , 2005, Monte Carlo Methods Appl..

[19]  J. N. Kapur,et al.  Entropy optimization principles with applications , 1992 .

[20]  Jyoti K. Sinha,et al.  Estimating unbalance and misalignment of a flexible rotating machine from a single run-down , 2004 .

[21]  Stefano Tarantola,et al.  Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models , 2004 .

[22]  Terje Aven,et al.  On the Need for Restricting the Probabilistic Analysis in Risk Assessments to Variability , 2010, Risk analysis : an official publication of the Society for Risk Analysis.

[23]  Jon C. Helton,et al.  Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal , 1993 .

[24]  E. Jaynes Information Theory and Statistical Mechanics , 1957 .

[25]  Max D. Morris,et al.  Factorial sampling plans for preliminary computational experiments , 1991 .

[26]  Stefano Tarantola,et al.  Sensitivity analysis practices: Strategies for model-based inference , 2006, Reliab. Eng. Syst. Saf..

[27]  Uwe Prells,et al.  MINIMISATION OF THE EFFECT OF UNCERTAINTY ON MODEL ESTIMATION , 1998 .

[28]  C. Guedes Soares,et al.  Reliability, Risk, and Safety: Theory and Applications , 2009 .