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Data Sets George Bieberbach a , Paul E. Bieringer a , Andrzej - - PowerPoint PPT Presentation

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A Framework for Developing Synthetic Chemical and Biological Agent Release Data Sets George Bieberbach a , Paul E. Bieringer a , Andrzej Wyszogrodzki a , Jeffrey Weil a , Ryan Cabell a , Jonathan Hurst a , and John Hannan b a National Center for

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NCAR/RAL - National Security Applications Program

A Framework for Developing Synthetic Chemical and Biological Agent Release Data Sets

George Bieberbacha, Paul E. Bieringera, Andrzej Wyszogrodzkia, Jeffrey Weila, Ryan Cabella, Jonathan Hursta, and John Hannanb

aNational Center for Atmospheric Research bDefense Threat Reduction Agency

May 31st 2010

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Chemical and Biological (CB) Defense Systems Test and Evaluation (T&E)

  • Technology gap

– Insufficient field data for T&E – Economic and logistic limitations for chemical biological defense T&E

  • One solution

– Physically realistic virtual environments and synthetic

  • bservations

Best Solution Will be Derived from the use of Both Observations and Virtual Environment Data

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Virtual Testing Methodology

(Observation System Simulation Experiment)

Atmospheric Models Transport and Dispersion Models Models and Analysis Systems

Generation of Synthetic Environment Simulated Sensor Measurements Applications That Utilize Observations

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Real Sensor Data Characteristics

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Near-Field Dispersion Modeling

(Exterior CB Release and Atmospheric Environment)

  • Near-field dispersion characteristics

– Gaussian-based models capture the mean properties – Large-Eddy-Simulation (LES) based models are capable of capturing the near-instantaneous plume

From: Slade (1968)

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Diagnostic Met + Gaussian Puff

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Large Eddy Simulation + Lagrangian Particle Dispersion

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Outline

  • Motivation
  • Virtual Threat Response Emulation and Analysis Testbed

(VTHREAT)

– Overview – Synthetic Environment Generation Models – Evaluation

  • VTHREAT applications

– CB Field Test Design – CB Source Term Estimation (STE) Algorithm Development – CB Sensor Test and Evaluation

  • Future Work

– Aerosol Background Modeling

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VTHREAT Overview

CLIENT PC NCAR

Aerosol Background Model Atmospheric Aerosol Model EULAG/LPDM Simulations Synthetic Environment Repository EULAG/LPDM Synthetic Environment Generator Synthetic T&D Generator LPDM Chemical Sensors (ACADA) Synthetic CBR Sensor Emulators Synthetic Meteorology Sensor Emulators Radiosonde Windmill Anemometer Sonic Anemometer Doppler LIDAR Bio-Agent Sensor Radiological Current Capability Planned Capability

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Outline

  • Motivation
  • Virtual Threat Response Emulation and Analysis Testbed

(VTHREAT)

– Overview – Synthetic Environment Generation Models – Evaluation

  • VTHREAT applications

– CB Field Test Design – CB Source Term Estimation (STE) Algorithm Development – CB Sensor Test and Evaluation

  • Future Work

– Aerosol Background Modeling

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NCAR/RAL - National Security Applications Program Optional nonhydrostatic fluid equations: Anelastic or Compressible / incompressible Boussinesq, Optional modes for integrating fluid PDEs: Eulerian (flux form) or semi-Lagrangian (advective form) Applications: classical fluid dynamics, cloud turbulence, atmospheric flows from PBL to global and planetary scale, MHD, ocean flows, T&D aplications, flows over complex topography and buildings Numerical algorithms:

  • Nonoscillatory forward-in-time (NFT) advective transport (MPDATA)
  • Preconditioned non-symmetric Krylov-subspace elliptic solver GCR(k)
  • Generalized-coordinate formulation for grid adaptivity

Strategies of simulating turbulent dynamics:

  • Direct numerical simulation (DNS)
  • LES type turbulence closure (1 ½ order, prognostic tke), Smagorinsky or ILES model

T&D applications

  • Structured, time-dependent grids, “terrain-following” transformation (orographic flows) or

immersed boundary approach (urban flows)

  • Passive tracer to asses transport and dispersion of passive contaminants

EULAG

(EULerian/semi-LAGrangian Model for Fluid Flows)

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LPDM

(Lagrangian Particle Dispersion Model)

  • LPDM model driven by EULAG

meteorological solution

– Weil et al., 2004, J. Atmos. Sci.

– Provides a very detailed T&D solution – Flexible solution for producing synthetic T&D from numerous sources – Lower computational costs – Evaluated relative to laboratory and field data

v(x0,t) = uRES(xp,t) + uSGS(xp,t) uRES = resolved LES velocity uSGS = stochastic sub-grid-scale (SGS) velocity Thomson’s (1987) stochastic model for uSGS Concentrations: Cy = Q ∫p1(x - xs,z - zs,td) dtd td = t - tem

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Outline

  • Motivation
  • Virtual Threat Response Emulation and Analysis Testbed

(VTHREAT)

– Overview – Synthetic Environment Generation Models – Evaluation

  • VTHREAT applications

– CB Field Test Design – CB Source Term Estimation (STE) Algorithm Development – CB Sensor Test and Evaluation

  • Future Work

– Aerosol Background Modeling

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VTHREAT Validation

Crosswind-Integrated Concentration Mean Height

Scaled Downwind Distance Scaled Downwind Distance Scaled Mean Height Scaled Concentration Scaled Downwind Distance = w*x/(Uzi) Scaled Concentration = CyUzi/Q Scaled Mean Height = zp/zi

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VTHREAT Evaluation

(Assessing the Suitability for the CB T&E Application)

  • Virtual CB T&E tool requirements

– Realistic agent mean lateral/vertical and downwind dispersion – Realistic agent concentration and wind fluctuations – Realistic background interference signals

Scaled Downwind Distance Scaled Concentration

Crosswind-Integrated Concentration

VTHREAT Wind Observation

Surface Wind Fluctuations

U - Wind Speed (m/s) V - Wind Speed (m/s)

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Outline

  • Motivation
  • Virtual Threat Response Emulation and Analysis Testbed

(VTHREAT)

– Overview – Synthetic Environment Generation Models – Evaluation

  • VTHREAT applications

– CB Field Test Design – CB Source Term Estimation (STE) Algorithm Development – CB Sensor Test and Evaluation

  • Future Work

– Aerosol Background Modeling

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CB Field Test Design

Sensor Grid Detection Sensitivity Plume Coverage Detection Sensitivity to Release Concentration

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Outline

  • Motivation
  • Virtual Threat Response Emulation and Analysis Testbed

(VTHREAT)

– Overview – Synthetic Environment Generation Models – Evaluation

  • VTHREAT applications

– CB Field Test Design – CB Source Term Estimation (STE) Algorithm Development – CB Sensor Test and Evaluation

  • Future Work

– Aerosol Background Modeling

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Incorporation of Relevant Background Fields

  • Realistic background signals physically consistent with agent

release

– Aerosol background for biological sensors – Ambient chemical interference fields for chemical agent sensors

  • Implementation plans

– Utilize aerosol background information from PD TESS program – DTRA-JSTO funded DSTL aerosol background model – Couple aerosol concentration with the EULAG LES model

DSTL Aerosol Background Model VTHREAT LIDAR Emulation EULAG/LPDM Model

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CB Release and Relevant Background Fields

(Preliminary Demonstration)

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Summary

  • The problem

– A capability gap exists for evaluating CB sensors in a more robust way. – “Virtual” testing can be used to fill this gap

  • One solution

– Generation of synthetic test environments

  • Model validation

– Turbulent dispersion characteristics are being validated against a range of experimental and laboratory datasets

  • Applications

– Support field test design – Sensor data algorithm development – CB sensor test and evaluation.

  • Looking ahead

– Simulated chemical dispersion imbedded within a background interferent signals

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Questions?

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Incorporation of Relevant Background Fields

  • Realistic background signals physically consistent with agent

release

– Aerosol background for biological sensors – Ambient chemical interference fields for chemical agent sensors

  • Implementation plans

– Utilize aerosol background information from PD TESS program – DTRA-JSTO funded DSTL aerosol background model – Couple aerosol concentration with the EULAG LES model

DSTL Aerosol Background Model VTHREAT LIDAR Emulation EULAG/LPDM Model