Space to Air High-Altitude Region Adjoint Neutron Transport

Abstract

The goal of this work was to use the adjoint transport equation to characterize the energy spectrum of a neutron source located in the upper atmosphere using the time-energy fluence at the satellite. This adjoint approach directly solves for the source spectrum thereby potentially enabling device reconstruct ion. The adjoint method also could improve computational efficiency over the forward method. The adjoint transport equation was solved via Monte Carlo methods in a new program called SAHARA written in Python 3.7. A new adjoint source event estimator was developed to improve the computational efficiency. This work explores SAHARA's development, and its performance for mono-energetic and continuous energy sources. In general, the identified source spectra were shifted towards lower energies approximately five percent, but were able to capture the source spectrum shapes. Additionally, continuous energy sources still passed a 2-D Kolmogorov-Smirnov (K -S) test. Lastly, SAHARA was applied to the real-world neutron energy spectra of Fat Man and Little Boy. Although these spectra were also noticeably shifted towards lower energies, the spectral features are still recognizable and the spectra passed a 2-D K-S test. SAHARA provides a new tool for estimating the source spectrum from space- based neutron measurements.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2021
Accession Number
AD1145714

Entities

People

  • Zachary W. Lamere

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Boltzmann Equation
  • Computational Science
  • Data Science
  • Engineering
  • Equations
  • Estimators
  • Geometry
  • High Altitude
  • Information Science
  • Materials
  • Measurement
  • Monte Carlo Method
  • Scattering
  • Statistical Algorithms
  • Two Dimensional
  • United States

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Solar Physics
  • Statistical inference.

Technology Areas

  • Space