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Improvements of sampling and scoring ( User Requirements: Scoring for event biasing options)

Improvements of sampling and scoring ( User Requirements: Scoring for event biasing options). Tsukasa Aso , Toyama National College of Maritime Technology, Japan. Contents. Objective Current scoring options Migration from geometry biasing scorer User requirements Summary. Objective.

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Improvements of sampling and scoring ( User Requirements: Scoring for event biasing options)

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  1. Improvements of sampling and scoring( User Requirements: Scoring for event biasing options) Tsukasa Aso,Toyama National College of Maritime Technology, Japan

  2. Contents • Objective • Current scoring options • Migration from geometry biasing scorer • User requirements • Summary

  3. Objective • The main goal of improvements of scoring is to provide a user with common sampling scheme under: • event biasing • Geometrical biasing • Physics process biasing • All the influences of these biasing will be reflected to the “particle weight” in order to keep a consistency of the result • parallel geometry • ParallelWorldScoringProcess has already been available • Geometrical biasing is migrated to using parallel geometry. (by Alex) • The geometry must be identified by the geometry number,i.e. copy number or replication number • Scorers must be applicable by same manner • in both of mass and parallel geometry • with or without event biasing

  4. Current scoring options • There are three kinds of scorers • Sensitive Detector • Users have to implement own detector class and hit class • MultiFunctional Detector with Primitive Scorer • Geant4 provides many scorers • Users can compose own scorer by combining those scorers • Keys of maps are redundant for scorers of same volume • More improvements are desirable for efficient scoring • Event biasing scorer • Useful quantities for checking geometrical biasing • Sampling at Entering/InVolume/Exiting is useful for users • Must work with geometrical event biasing • Event biasing process becomes more simple if the scorer is separated from geometrical biasing • By separating the role, we can make it simple • Process, Process Placer, Scorer

  5. Migration from event biasing scorer • Geant4 provides examples at example/extended/biasing/B01~B03 • B01 Mass geometry • B02 Parallel geometry, AIDA • B03 using Python • Test version of parallel geometry ( by Alex ) • B01_para Mass geometry • B02_para Parallel geometry

  6. 1 • Detail in event biasing scorer • default scoring quantities • Entering track G4PSTrackCounter • Population G4PSPopulation • Collision G4PSCollision • SL G4PSTrackLength • SLW G4PSTrackLength • SLWE G4PSTrackLength • SLWE_v G4PSTrackLength • SLW_v G4PSTrackLength • NumWGTedE = SLWE_v/SLW_v (Run) • FluxWGTedE = SLWE/SLW (Run) • Av.Tr.WGT = SLW/SL (Run) • Problem in event biasing scorer • Since the biasing has to access to the both of volume in geometrical boundary, Scoring in given function basically stores quantities for “poststep” volume. • It should be unified to the volume of “prestep” • ScoreAnExitingStep(aStep,pre_gCell) • ScoreAnEnteringStep(aStep,post_gCell) • ScoreAnInVolume(aStep, post_gCell) • To use the volume in “poststep” causes miss the sampling step information. • At the geometry boundary • At the world volume boundary=>This is mentioned in User’s manual. “Scoring cells must not share boundaries with the world volume.” 1 x

  7. B01 Mass geometry Importance / Scoring WorldVolume (shieldWorld) 18 slabs (cell_01 ~ cell_18) 1 slab for score (rest_rep) R=100cm 10 MeV neutron +-100cm

  8. For comparison, PS are created for reproducing the event biasing scorer. ( B01 )i.e. use “prestep/poststep” volume in some case. Completely same result Copy number of volumes are assigned for primitive scorer

  9. Regular scoring using prestep volume (B01_para) • Difference comes from • boundary identification of volumes • steps to the out of world volume. InVolume quantities are same. Boundary related quantities are different

  10. B02_para R=101cm R=100cm Z=+- 90cm Mass Para 10cm thick slab

  11. In parallel geometry • Importance/PS are attached to same parallel geometry Here I changed G4ParallelWorldScoringProcess:CopyStep(const G4Step) for settinggeometry boundary of PreStepPoint.

  12. Executed without serious problem But result are different each other by the choice of transportation, Transportation CoupledTransportation Executed but the result is not same as Mass-Mass combination. Exactly same result. But if the biasing scorer is turned off,the result of PS is changed. => This difference come from interaction??? See next slides.

  13. When turning off the biasing scorer, the result is changed by physics interaction?

  14. Question from biasing example • Every process for parallel world geometry checking and identifying the geometry boundary in parallel world • Is there any possibility to merge it?i.e. a process for giving step status for the parallel world.

  15. User requirements(1) ~Other MC~ Physics quantities Geometrical condition Elemental quantities Current Flux Fluence FLUKA MCNP4B Surface current Surface Flux Cell Flux Point Flux After MCNP4B Mesh Tally - Rectangular - Cylindrical - Spherical USRBDX (surface) USRYEILD SCORE (energy deposition of the volume) FM (read/store) After MCNP4B Mesh Tally - Track averaged (tracks, flux, dose) - Source (coincidence, anticoincidence) - Energy deposition (total, de/dx,…) - DXTRAN - Image projection - Point detector USRBIN (space) EVENTDAT USRTRACK EVENTBIN DETECT USRCOLL RESNUCLEi Time window Coincidence capture …

  16. User requirements(2)~scorer~ • The primitive scorer has been already provided interest physics quantities.(This is because we started from MCNP tally for primitive scorer development) • Current options does not involve any support to define scoring geometryTally = Geometry + Sampling + Scoring • Scorer needs to get differential distributionsEnergy distribution, Angular distribution,or double-differential distribution

  17. User Requirements(3)

  18. User Requirements(4)

  19. Summary • Migration from event biasing scorer to primitive scorer will be possible • Still we have to investigate the differences • The new scoring capabilities will be designed and implemented • The some of example using new scorer, event biasing, and parallel geometry will be presented

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