Preventing xenon oscillations in Monte Carlo burnup calculations by forcing equilibrium

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Preventing xenon oscillations in Monte Carlo burnup calculations by forcing equilibrium Aarno Isotaloa), Jaakko Leppänenb), Jan Dufekcc) a) Aalto University, Finland b) VTT Technical Research Centrte of Finland c) Royal Institute of Technology, Sweden

Xenon oscillations Physical xenon oscillations Numerical xenon oscillations Result from time discretization and the resulting delay in feedback from Xe-135 concentration Traditional geometries Result from the delayed production of Xe-135 z Geometry dimensions ~ Migration length Spatial oscillations impossible Large geometries (+ detailed discretization) Dimensions >> Migration-length Prior studies: All old methods appear to suffer from numerical xenon oscillations [1,2] Flux 2 / 14

Test case Higher enrichment (or equal) 1 2 3 Lower enrichment (or equal) 4 5 6 4m 0.5 m 4 m PWR pin cell 8 axial segments Reflective boundary conditions Average enrichment 3.1 % 8.2 mm Enrichment increased in one end, reduced in the other Average enrichment not changed 9.5 mm 12.6 mm 8 7 3 / 14

Results with normal steps 1-120 day steps Numerical xenon oscillations New methods of Serpent 2 are also affected Oscillations between predictor and corrector Results look stable In less extreme cases these oscillations might be difficult to notice 4 / 14

Results with very short steps (1) 15 min steps physical xenon oscillations Reducing step length improves accuracy, nothing else The results are accurate (for the model being solved) The model describes an oscillating system No temperature feedback or reactor control system Flux and xenon concentration in segment 1 with 0.1 pp enrichment difference and 15 min steps. Four runs with different random number sequences. 5 / 14

Results with very short steps (2) Flux and xenon concentration in segment 1 with different enrichment differences and 15 min steps. Spatial distribution of the flux and xenon concentration at the extremes of the oscillations with 0.4 and 0.8 pp enrichment differences and 15 min steps. 6 / 14

Results with very short steps (3) Special case: no enrichment difference Initial state is symmetric The correct solution must be symmetric Statistical variation breaks symmetry oscillations Easily handled by using the symmetry (2D geometry) Flux and xenon concentration in segment 1 with 0 pp enrichment difference and 15 min steps. Four runs with different random number sequences. 7 / 14

Results with very short steps (4) The existing methods do work Short enough steps correct solution (to the model being solved) Steps longer than the timescale of the solution a mess What else would you expect... The root of the instability problem is the model being solved 3h steps give a half-decent representation Adding temperature feedback and control models should help What we really want is stable results for the simple models Force equilibrium Represents the stabilizing effect of e.g. control system Xenon-flux equilibrium at each neutronics solution Xe-135 concentration calculated in the equilibrium calculation, not the deplation calculation. 8 / 14

Equilibrium xenon Deterministic codes: another layer of wrapper to iterate equilibrium Multiplies transport calculations required per step Would be very slow with MC neutronics MC neutronics: possible to integrate equilibrium xenon calculation Algorithms already exist (developed for other purposes) Equilibrium xenon concentration and flux in one transport simulation Only a minor slowdown Can be used with any depletion algorithm and coupling scheme The equilibrium algorithm of Serpent After each source cycle, xenon concentrations are set to saturated levels corresponding to the cross-sections collected during that cycle. 9 / 14

Equilibrium xenon results (1) Flux and U-235 concentration with 0.4 pp enrichment difference and 16 day steps without equilibrium xenon Flux and U-235 concentration with 0.4 pp enrichment difference and 16 day steps with equilibrium xenon 10 / 14

Equilibrium xenon results (2) There is no exact or universal limit for how large a difference indicates instability! 11 / 14

Equilibrium xenon results (3) 30 day steps: oscillations disappear 60 day steps: numerical oscillations driven by fuel depletion Similar results with all coupling schemes available in Serpent 2 Exception: LE becomes unstable at 30 day steps Xenon is always forced to saturated level Limit depends on the problem being solved Cannot be prevented with a similar approach Not applicable when non-saturated behavior is relevant The equilibrium algorithm of Serpent Bias of the xenon concentration estimate might become a problem Solution: Unbiased estimator. [3] The algorithm of MC21 could be used instead. [4] 12 / 14

Equilibrium xenon results (4) Average standard deviations of segment-wise fluxes in stand-alone transport calculation with various initial enrichment differences and burnup of 0 or 9.1 MWd/kgHM. The values are percent of mean global flux. The constant feedback from the equilibrium xenon calculation appears to improve convergence. 13 / 14

Conclusions Spatial stability is a real issue in large geometries Oscillations may be difficult to notice from usual results The simulation models themselves are unstable Forcing flux and xenon concentration to remain in equilibrium helps MUTUAL equilibrium, not just normal flux + saturated xenon level Simple, lightweight, accurate (Can use any coupling scheme) Step length limited by instability driven by other nuclides The method is available in Serpent (1 and 2) set xenon 1 Prefer large neutron cycles There are other stabilizing schemes Gadolinium related instability might be harder to solve... 14 / 14

References [1] Dufek, J., Hoogenboom, J.E. Numerical Stability of Existing Monte Carlo Burnup Codes in Cycle Calculations of Critical Reactors. Nucl. Sci. Eng. 162, 307311. (2009) [2] Dufek, J., Kotlyar, D., Shwageraus, E., Leppänen, J. Numerical Stability of the PredictorCorrector Method in Monte Carlo Burnup Calculations of Critical Reactors. Ann. Nucl. Energy 56, 3438. (2013) [3] Dumonteil, E., Diop, M.C. Biases and Statistical Errors in Monte Carlo Burnup Calculations: An Unbiased Stochastic Scheme to Solve Boltzmann/Bateman Coupled Equations. Nucl. Sci. Eng. 167, 165170. (2011) [4] Griesheimer D.P. In-Line Xenon Convergence Algorithm for Monte Carlo Reactor Calculations. PHYSOR 2010. Pittsburgh, Pennsylvania, USA, May 9-14, 2010. On CD-ROM, ISBN 978-089448-079-9. (2010) For a more detailed overview of the work presented here see Isotalo A.E., Leppänen, J., Dufek, J. Preventing xenon oscillations in Monte Carlo burnup calculations by forcing equilibrium. Ann. Nucl. Energy 60, 7885. (2013) 15 / 14

Thank you for your attention Questions?