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"Impact of input variables on the seismic response of free-standing spent fuel racks" presented at IALCCE2018 by Alberto Gonzalez Merino


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Stochastic input data brings aleatoric and epistemic uncertainty to the rack seismic analysis. From the synthetic acceleration-time history of the earthquake to the heterogeneous features of the rack system, several sources of uncertainty exist. The manufacturing process itself may produce slight deviations in the dynamic properties and mass distribution of the rack units. Moreover, each unit is loaded with a different number of fuel elements according to the operation needs of the plant. Even the exact clearance spaces between units are hardly inspectable due to radioactive ambiance. Hence, all of these uncertainties propagate across the nonlinear transient analysis and affect the accuracy and robustness of the numerical outputs. This paper carries out a ‘one-factor-ata-time’ parametric analysis of five key input variables: acceleration time-history, rack mass, fuel loading, rack Eigen-frequencies and hydrodynamic masses. This technique examines the impact on the main transient outputs when an analysis parameter is systematically varied while the others remain at their nominal value. Numerical results are provided for a simple two-rack system as a source of insight into the uncertain seismic response of a real rack system. It is highlighted that the dispersion is much higher for the sliding displacements than for the maximal forces on support.

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"Impact of input variables on the seismic response of free-standing spent fuel racks" presented at IALCCE2018 by Alberto Gonzalez Merino

  1. 1. Reducing Uncertainty in Structural Safety Special Session SS6 Ghent, Belgium 28-31 October 2018
  2. 2. Alberto Gonzalez, Luis Costas and Arturo González Impact of input variables on the seismic response of free- standing spent fuel racks
  3. 3. Outline • Free-standing Spent Fuel Storage Racks • Current seismic analysis methodology • Uncertain variables • OFAT parametric analysis of the input variables • Conclusions (I) • Analysis of the Coefficients of Variation • Conclusions (II)
  4. 4. Free-standing Spent Fuel Racks Metallic structures designed to store spent fuel removed from the nuclear power reactor. Several units are installed together. • Slightly spaced by only a few centimeters, • free-standing conditions, • submerged in water. Spent Fuel Pool 6x4 racks Fuel storage rack unit ~4m ~12m Nuclear Fuel assemblies
  5. 5. RACK SYSTEM STRUCTURAL MODEL SEISMIC MODEL Soler, A.I., & Singh, K.O. (1982) FLUID MODEL Loads and displacements to • Calculate local stresses • Check instabilities SHELL63 MASS21 Current analysis methodology
  6. 6. Uncertain variables A. Data Input • Acceleration time-history • Rack mass & weight • Fuel mass & weight • Rack Eigen frequencies • Hydrodynamic mass matrix B. Modelling properties • FE mesh discretization • Rack-Pool friction coefficient • Rack-Pool contact stiffness • Fuel-Cell contact stiffness • Fuel-Cell gap • Fuel flexural rigidity C. Solution controls Time marching (‘DELTIM’) Equilibrium iterations (‘NEQIT’) Convergence criteria (‘CNVTOL’) Integration parameter (‘TINTP’) Mass proportional damping (‘BETAD’) Stiffness proportional damping (‘ALPHAD’)
  7. 7. Acceleration time-history
  8. 8. Acceleration time-history
  9. 9. Rack mass
  10. 10. Rack mass
  11. 11. Fuel mass
  12. 12. Fuel mass
  13. 13. Inertia of the rack body beam
  14. 14. Inertia of the rack body beam
  15. 15. Hydrodynamic added masses
  16. 16. Hydrodynamic added masses
  17. 17. Conclusions (I) Variable Sliding amplitude Reaction forces Comments Amplitude of the seismic loading Unclear Increase Strong accelerations cause rack rocking Rack mass None Decrease Heavy racks are more stable Fuel mass Unclear Increase Heavy loadings contribute to the rattling energy Rigidity of the rack body beam Larger Potential resonance Determines the energy exchanges between the fuel ratting and the rack supports Hydrodynamic masses Unclear Unclear Coupling action that affects the overall motion
  18. 18. Coefficient of Variation (CV) CV for a 10% variation in the variables 𝐶𝑉 = 𝜎 𝜇 CV for a 5% variation in the variables
  19. 19. Coefficient of Variation (CV) CV for a 10% variation in the variables 𝐶𝑉 = 𝜎 𝜇 CV for a 3% variation in the variables
  20. 20. Conclusions (II) • Dispersion is much higher for the sliding displacements (CVs up to 0.8) than for the maximal forces on support (CVs under 0.2). • No dependency is observed between the sampling of the input variables an the resulting Coefficients of Variation.
  21. 21. The TRUSS ITN project ( has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 642453 Thanks for your attention