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Multidisciplinary DSS as Preventive Tools in Case of CBRNe Dispersion and Diffusion: Part 1: A Brief Overview of the State of the Art and an Example – Review

  • Jean-François CiparisseEmail author
  • Roberto Melli
  • Riccardo Rossi
  • Enrico Sciubba
Chapter
Part of the Terrorism, Security, and Computation book series (TESECO)

Abstract

The paper addresses some important issues related to the need for a timely, reliable and accurate tool for the early warning in case of CBRNe events. The state-of-the-art of the currently available tools is briefly presented in the first part of the two-papers set. While the accurate calculation of the dispersion of both lighter- and heavier-than-air contaminants in complex three-dimensional domains is definitely possible with commercially available CFD packages, the time needed to obtain a reliable numerical solution, under the pertinent atmospheric conditions prevailing at the time of the attack, exceeds the requirements of a first-aid intervention. Therefore, it would be advisable to combine these CFD packages with some sort of “intelligent” Decision Support System that makes use of multidisciplinary knowledge base and of some kind of detection-diagnostic-prognostic Expert System. The DSS could be interfaced with some standard early detection tools and ought to include an enhanced diagnostic/prognostic utility based on a specific series of local CFD simulations of dispersion events. Its use ought to be relatively easy for trained personnel. Since the database for the CFD dispersion calculation is by definition “local”, detailed maps of the presumable target areas must be included in the database. The second part of this paper presents a detailed description and one example of application of such an Expert Assisted CFD dispersion calculation, named FAST-HELPS (Fast Hazard estimate of low-level particles spread).

Keywords

DSS simulation software CFD 

Nomenclature

ρ

Density

\( \overrightarrow{V} \)

Velocity vector

p

Pressure

μ

Molecular viscosity

μT

Turbulent viscosity

k

Turbulent kinetic energy

ε

Turbulent kinetic energy dissipation rate

Pk

Turbulent kinetic energy production term

Cε1, Cε2, Cμ

Turbulence model constants

υT

Turbulent kinematic viscosity

φd

Dispersed particles volume fraction

cd

Dispersed phase mass fraction

ρc

Continuous phase density

ρd

Dispersed phase density

dd

Dispersed phase particles diameter

\( {\overrightarrow{u}}_c \)

Continuous phase velocity vector

\( {\overrightarrow{u}}_d \)

Dispersed phase velocity vector

\( {\overrightarrow{U}}_{slip} \)

Slip velocity

\( \overrightarrow{g} \)

Gravity acceleration vector

φmax

Maximum particles volume fraction

Cd

Particles drag coefficient

Rep

Particle-based Reynolds number

Q

Breath volumetric flow rate

Nb

Number of spores in each endospores

nb

Number of spores per volume unit

ψ

Number of inhaled spores

ξ

Infection probability

l

Lethality of the infection

CBRNe

Chemical, Biological, Radiological, Nuclear, explosive

BWA

Biological Warfare Agents

CFD

Computational Fluid Dynamics

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jean-François Ciparisse
    • 1
    Email author
  • Roberto Melli
    • 2
  • Riccardo Rossi
    • 1
  • Enrico Sciubba
    • 2
  1. 1.Department of Industrial EngineeringUniversity of Rome “Tor Vergata”RomeItaly
  2. 2.Department of Mechanical and Aerospace EngineeringUniversity Roma SapienzaRomeItaly

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