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GRAS Validation and GEANT4 Electromagnetic Physics Parameters

GRAS Validation and GEANT4 Electromagnetic Physics Parameters. R. Lindberg, G. Santin; ronnie.lindberg@esa.int Space Environment and Effects Section, ESTEC. Presentation Outline. Introduction A few Words About GRAS and MULASSIS GRAS Internal Validation Comparison with MULASSIS

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GRAS Validation and GEANT4 Electromagnetic Physics Parameters

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  1. GRAS Validation and GEANT4 Electromagnetic Physics Parameters R. Lindberg, G. Santin; ronnie.lindberg@esa.int Space Environment and Effects Section, ESTEC

  2. Presentation Outline • Introduction • A few Words About GRAS and MULASSIS • GRAS Internal Validation • Comparison with MULASSIS • GEANT4 Electromagnetic Physics • Tuning the parameters in GRAS • GRAS applied to complex geometry: ConeXpress • Conclusions

  3. ConeXpress radiation analysis ESABASE Ray-tracing and SHIELDOSE-2 curve GEANT4 Ray-tracing (SSAT) and SHIELDOSE-2 curve Used following tools for comparison GRAS Developed by G. Santin and V. Ivantchenko Uses GDML geometry; modular physics Modular analysis driven via script Introduction • SSAT • Developed by Qinetiq • Ray-tracing (a.k.a sector shielding analysis) • MULASSIS • Developed by Qinetiq • 1D multi-layer geometry.

  4. ConeXpress Results • GEANT4 SSAT ray-tracing results agree with ESABASE • However, GEANT4 GRAS full Monte Carlo gives very different results (orders of magnitude) • Uses same geometry model as SSAT analysis • First validation attempt • GEANT4 internal comparison • GRAS ↔ MULASSIS • Shows discrepancy of ~20 % for a semi-infinite slab case • Greatest difference in lower energy range (≤ 2 MeV) for electrons

  5. Understanding the Problem (1/3) • The geometry setup used was the semi-infinite slab case • 2 mm Silicon target • 3 mm Aluminium shield • Dose in energies below 1.5 MeV comes from gamma radiation • e--contribution starts to dominate around 1.5 MeV 3

  6. Understanding the Problem (2/3) • GRAS analysis was inserted into MULASSIS to obtain e- and gamma cont. • Gamma contribution agrees well between the two. • Simulations show that there were differences in the e- contributions between GRAS and MULASSIS

  7. Understanding the Problem (3/3) • Dose from gamma-contribution is the same but... • …e- contribution differs and… • …statistical errors are small (<1%) compared to total dose value, so difference is not due to statistical error, furthermore… • …the difference in dose between GRAS and MULASSIS is largest at “threshold energy”, so… • …what’s the catch?

  8. Electron EM Processes and Fine Tuning • Same EM physics used in GRAS and MULASSIS • Cause of different results was due to “fine tuning” of the electromagnetic energy loss modelling • Several parameters influence the modelling of GEANT 4 EM: • facRange: • Maximum fraction of kinetic energy that particle can loose in a step • Integral: • If true, dE(step) is obtained with integral of dE/dx curve • Cuts: • Is the production cuts for secondary electrons • StepMax: • Is one of the most important. • Limits the maximum step length. • “Process” in GRAS. • This parameter is not available in MULASSIS

  9. Internal Validation Conclusion (1/2) • GRAS gives near perfect agreement with MULASSIS when using the same EM physics parameter • Integral set to true • facRange set to 1.0 • stepMax set to 100 mm (similar to not having stepMax at all)

  10. Internal Validation Conclusion (2/2) • Several runs were conducted to verify correlation • E.g. • Sphere case, • maxtheta=90, • protons and electrons, Notice the scale.

  11. EM Physics Tuning – Parametric Study • Parametric study to look at effects of different settings • Parameter ranges: • facRange: 0.2-1. • Integral: Boolean – true or false • Cuts: between 0.01100 mm • StepMax: between 0.01100 mm (100 mm ~ no step limiting)

  12. Parameter Comparison (1/2) Dose differs 2.5x depending on StepMax

  13. Parameter Comparison (2/2)

  14. Tuning Effect with Space Env. Spectra • Ran simulations in GRAS for different spectra and Al shielding thickness: • e- GTO • e- MEO (Galileo) • e- GEO • p+ GEO • MULASSIS simulated by using StepMax=100.00 mm and StepFunction=1.0

  15. Tuning Effect with Space Env. Spectra

  16. Next Step – Complex Geometry • Currently conducting analysis on complex geometry – ConeXpress • Use radiation spectra from SPENVIS • Run each particle spectra separate and combine to obtain total ionised dose. • Presents different problems than simple geometry • Number of simulated events has to be very high due to thick shielding generated by subsystems, especially for electrons

  17. Next Step – Complex Geometry GDML model of ConeXpress

  18. Conclusions • Internal validation (GRAS ↔ MULASSIS) successful • Earlier difference due to different physics parameters • GRAS Parametric study of EM physics parameters shows difference • Up to 30%, using a space environment spectra • Up to 2.5 times, using mono-energetic beam particle source • Tentative set of parameters chosen as • facRange to 0.2 • Integral set to true • Cuts around 0.01 mm • StepMax around 0.1 mm – trade-off between CPU time and small step size •  impacts radiation analyses results • Suggested implementation of StepMax and facRange in MULASSIS

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