CBRN Assessment

NRL seeks more capability for CT-Analyst

19 April 2017
NRL's CT-Analyst models a hazardous airborne plume faster than many currently used systems. Seen here is a screen shot depicting plume movement in New York City, six minutes after an attack. Source: USN NRL

The US Naval Research Laboratory (NRL) is looking to add more features to its CT-Analyst real-time 3-D model that tracks how hazardous airborne plumes might disperse in an urban setting.

Features could include adding more data about the character of a chemical, biological, or radiological release. For example, whether the chemical agent that has been released is lighter or heavier than air, Adam Moses, a computer scientist at the NRL, told Jane's.

"If it is lighter than air it could affect more people as it drops to the ground. Maybe it is raining that day or snowing, maybe there is more chaos in terms of the air circulation, something you expect in late summer or fall," Moses explained. "We try to model something that is general because first responders do not have the time to do the characterisation.

A screen shot from NRL's CT-Analyst depicting a plume dispersion across New York City, 30 minutes after an attack. (USN NRL)A screen shot from NRL's CT-Analyst depicting a plume dispersion across New York City, 30 minutes after an attack. (USN NRL)

"But if you have better and better sensors able to give you more and more results you can rearrange the picture depending on sensor readings," he added.

Researchers would also like to expand CT-Analyst's ability to integrate into other modelling programs.

"The big problem is people are using a tool already. To learn something new is [a challenge] and to integrate it with their concept of operations is a problem," Moore said.

"If they can have [CT-Analyst] plug in to something they are already using it is a lot [easier for them]," he said.

Besides providing a 3-D model of how hazardous airborne plumes might disperse, CT-Analyst does it faster than many currently used systems.

"Most models wait to enter data on wind, buildings, or terrain. Then they run their calculations; but doing that causes you to wait minutes up to hours depending on the complexity of the calculation," Moses said.

"We have actually pre-computed [the data] so instead of waiting from time of the incident to actually do our modelling we pre-calculate the entire region," he said.

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