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
Part of the Terrorism, Security, and Computation book series (TESECO)


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).


DSS simulation software CFD 




\( \overrightarrow{V} \)

Velocity vector




Molecular viscosity


Turbulent viscosity


Turbulent kinetic energy


Turbulent kinetic energy dissipation rate


Turbulent kinetic energy production term

Cε1, Cε2, Cμ

Turbulence model constants


Turbulent kinematic viscosity


Dispersed particles volume fraction


Dispersed phase mass fraction


Continuous phase density


Dispersed phase density


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


Maximum particles volume fraction


Particles drag coefficient


Particle-based Reynolds number


Breath volumetric flow rate


Number of spores in each endospores


Number of spores per volume unit


Number of inhaled spores


Infection probability


Lethality of the infection


Chemical, Biological, Radiological, Nuclear, explosive


Biological Warfare Agents


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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