Hazardous Material Source Term Estimation

BACKGROUND

Figure 1.  Conceptual framework of the VIRSA system.
Figure 1.  Conceptual framework of the VIRSA system.

Atmospheric releases of hazardous materials, either accidental or intentional, continue to pose a threat to United States citizens and to troops abroad and at home.  To counter this threat, RAL is actively supporting research and the development of novel techniques and systems that  can be used to more accurately simulate the atmospheric state and evolution of the released material in both time and space, for planning, real-time response, and forensic purposes.

Hazardous Material Source Term Estimation

In addition to needing a representative description of the atmospheric state (past, present, and future), atmospheric transport-and-dispersion (AT&D) modeling systems also require precise specifications of the material release characteristics (e.g., location, time, and quantity).  For most real-time response scenarios, the specifics of the material release will be unknown, with only ancillary concentration measurements available.

Algorithms and techniques to characterize the source and material are actively being developed in RAL to quickly reconstruct and estimate the source release using these limited sensor observations.  In particular, RAL is actively developing a tailored source-term-estimation (STE) and hazard-refinement system, called the Variational Iterative Refinement STE Algorithm (VIRSA).  VIRSA is a source-term-estimation algorithm that requires minimal input from the user to produce an accurate STE quickly. A Gaussian static plume model is used to calculate a “first guess” source estimate based on available hazardous-material-sensor and meteorological observations.  The adjoint model is then used to iteratively refine the "first guess" source using variational minimization techniques.

A rebuilt version of VIRSA has been tested on data from three different field campaigns: Humble Jasmine 1, Fusion Field Trials 2007 (FFT-07), and Jackrabbit II (Fig. 2). Results have been presented at George Mason University and the International Technical Meeting on Air Pollution Modeling this year. The new system features a streamlined and faster approach that can also run on a standard laptop without a large amount of dependencies. 

Figure 2. Jackrabbit II field trial 6 results. FG is the First Guess, VIRSA is the refined solution, and Real is the actual amount released.
Figure 2. Jackrabbit II field trial 6 results. FG is the First Guess, VIRSA is the refined solution, and Real is the actual amount released.

Specific accomplishments since the last reporting period and plans for next fiscal year are summarized below.

ACCOMPLISHMENTS IN FY2019

  • Verification and validation of VIRSA with Fusion Field Trial 2007 (FFT-07), Jackrabbit II, and Humble Jasmine 1 field campaigns
  • Rebuilt code and workflow using Fortran and R statistical package
  • Improvements to the STE minimization algorithm to improve efficiency and accuracy
  • Additional verification and validation using FFT-07 and Jackrabbit field campaign data
  • Further development of a stand-alone VIRSA implementation, per sponsor and end-user requirements

PLANS FOR FY2020

Refinement of automatic evolution of error covariance parameters