Project

In the national context, one of the most distinguished qualities of the Austrian Armed Forces is the capability for conducting missions under CBRN threats, that is, threats caused by chemical, biological or radiological agents and by attacks with nuclear weapons. Essential for such missions is the capability for predicting hazardous areas, for monitoring areas that are affected or at risk with appropriate sensor technology, and for estimating the source properties of unobserved incidents where only measurements indicate their existence.

At present, procedures applied by the Armed Forces are almost solely based on the analysis of observations reported by soldiers. Not all nuclear detonations with the potential to threat Austrian personnel can be expected to being sufficiently characterised through direct observations. One of the project’s goals is therefore to estimate the yield of the nuclear device based on the results of geophysical measuring methods (seismic, infra sound). The International Monitoring System of the CTBTO (Comprehensive Nuclear Test-Ban Treaty Organization) serves as the primary data source.

Covert attacks with CBR agents can only be detected by observation of their effects or by precautionary placed sensors. A rapidly placeable sensor network that consists of low-priced nodes, is safeguarded against tampering, and is connected to the Armed Force’s CBRN information system is an essential building block in such a scenario and a goal of the project ABC MAUS.

Estimating parameters that are relevant for hazard prediction – such as the date and time, the location, the type and trend of the release and the amount of released substance – as well as optimising the use of placeable sensors requires modern methods for modelling atmospheric dispersion in forward and backward direction. The models used at present by the Armed Force’s CBRN information system are based on analytic equations, which allows for obtaining results very fast after being notified of nuclear detonations near / on the surface or releases of CBR agents, but represents a simplification that neglects potentially relevant effects. As a result, zones requiring protective measures must be established in a very conservative way and thus tend to be much larger than needed. Making complex, state-of-the-art atmospheric dispersion models available for hazard prediction and including larger scales allows for a refinement of the CBRN situational picture and makes estimating incident source terms feasible. That is another goal of project ABC MAUS.