A research team from the Department of Energy’s Sandia National Laboratories has developed modelling and simulation tools for assessing the threat and vulnerability of buildings to chemical and biological attacks. This includes looking at how agents move and deposit inside a building, developing and assessing mitigation strategies, guiding the use of detection methods, and examining the effectiveness of cleanup and decontamination efforts.
Sandia researcher Richard Griffith began working on the project following the 1995 sarin gas release in Tokyo’s subway system where it became apparent that chemical and biological attacks by terrorists could be a future trend.
Using Sandia-developed computer modelling and visualisation capabilities, he can reportedly simulate how various chemical and biological agents flow through a building and deposit on various surfaces.
‘We start by mapping out the building and creating a computational model from the electronic AutoCAD blueprints, including all the rooms and areas served by each air handler and all the air ducts,’ Griffith said. ‘Then we simulate the release of a chemical or biological agent directly into different parts of the building, or from the outside for exterior releases.’
The computer model, known as KCNBC, predicts where the agent will move as a function of time following its release, producing a movie that gives researchers a view of agent transport and concentration. Simulations include a variety of agent release scenarios using real properties for a number of chemical and biological materials.
The information produced by the computer simulations is said to be valuable in determining cost-effective mitigation strategies, figuring out where to put agent detection sensors, sensor performance requirements, and deciding on cleanup and decontamination tactics.
In the area of mitigation the simulations might provide insight as to whether some or all of the air handlers should be turned off in a contaminated building; if it would be effective to purge the contaminated air and pump in fresh air or if it might be possible to contain or isolate the agent using the HVAC system.
The modelling data could also guide the optimal placement and use of sensors for detecting chemical and biological agents.
‘These new sensors are expensive, and may have significant installation and maintenance costs,’ Griffith said. ‘If you can only have five or six of them to help protect a large building, you have to figure out the most effective places to put them.’
Cleanup and decontamination efforts could also benefit from computer modelling as models can predict agent deposition on floors, walls, ceilings, ducts, and other surfaces in every room of the building, providing information about where the agent could go and what areas of a building could be the most contaminated.
Finally, Griffith said, the modeling and analysis tools are critical technologies in creating a ‘smart building,’ which integrates sensor information and observations from human security to know what is happening in and around the building, and then uses predictive modeling and decision-making algorithms to chose the most effective responses to protect building occupants.
When sensors detect the presence of an agent, a ‘smart building’ would chose the best HVAC system response to create clear evacuation paths or areas of the building where occupants could take shelter, provide real-time instructions to occupants and minimise the amount of the building that was contaminated.
‘There are a lot of things we can do to better protect building occupants against chemical and biological contamination,’ Griffith said. ‘These modelling and analysis tools can play a key role.’