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A space radiation transport method development.

J W Wilson1, R K Tripathi, G D Qualls

  • 1NASA Langley Research Center, Hampton, VA 23681-2199, USA. john.w.wilson@nasa.gov

Advances in Space Research : the Official Journal of the Committee on Space Research (COSPAR)
|May 11, 2005
PubMed
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This study introduces a fast, 3D deterministic code for spacecraft radiation shielding analysis. It enables efficient design optimization by integrating radiation constraints early in the process.

Area of Science:

  • Spacecraft engineering
  • Radiation physics
  • Computational methods

Background:

  • Effective spacecraft shielding design necessitates early integration of radiation constraints to optimize performance and reduce costs.
  • Current methods face limitations in analyzing complex geometries, hindering efficient design optimization.

Purpose of the Study:

  • To present progress on a computationally efficient, three-dimensional deterministic code for spacecraft radiation shield analysis.
  • To enable rapid shield analysis from preliminary concepts to final design stages.

Main Methods:

  • Development of a deterministic code, an advancement over the current HZETRN code which evaluates the lowest-order asymptotic term.
  • Utilizing standard finite element method (FEM) geometry for International Space Station (ISS) models.
Keywords:
NASA Center JSCNASA Center LaRCNASA Discipline Radiation Health

Related Experiment Videos

  • Demonstrating field mapping within ISS FEM geometry in tens of minutes.

    • Main Results:

    • The developed deterministic code provides a solution to the Boltzmann equation.
    • Enables shield analysis in tens of minutes, significantly faster than traditional methods for complex geometries.
    • A single ray trace in ISS FEM geometry takes 14 ms, highlighting limitations for Monte Carlo methods.

    Conclusions:

    • The new deterministic code facilitates integrated multidisciplinary design optimization for spacecraft shielding.
    • Offers a viable alternative to computationally intensive Monte Carlo methods for engineering models.
    • Re-configurable computing may enhance Monte Carlo efficiency for final design verification.