Optimizing the Placement of Biological and Chemical Weapon Sensors

Daniel L. Schafer
Thomas Jefferson High School for Science and Technology

Defense Threat Reduction Agency TDOA OR
Mentor: George D. Gunn

Purpose of the Experiment
Although tools exist to simulate biological and chemical attacks, the detailed 
approach taken by these programs made optimization runs on such tools take 
unfeasibly large amounts of time.  The development of a new tool that can both 
quickly simulate such attacks and optimize the placement of sensors to detect 
those attacks was needed for practical sensor optimization purposes.

Procedures Used
An existing C++ program, which would run a Monte Carlo simulation of a biological
attack on a base, was modified and converted to Java.  Additional evaluation 
functions were programmed, to allow varying sensor grid comparisons.   Two 
optimization algorithms were added to the program, one which would find the best
distribution of a limited number of sensors, and the other which could determine
the fewest number of sensors needed to meet a specified performance threshold.
Mathematical models were also created to perform numerical analysis on the 
effectiveness of different sensor grids.

Observation/Data/Results
The results found not only verified the mathematical models created, but also 
were in agreement with previous analysis.  Additionally, the program is quite fast,
as it takes between 1 and 5 minutes to complete an entire optimization run.

Conclusions
The final version of the program both can quickly and easily determine how best
to distribute a limited amount of sensors, or decide how many sensors need to be
allocated to other bases to ensure a certain level of protection.  The 
functionality offered by this tool should ensure that military and civilian 
facilities can be better protected from any potential biological or chemical 
threat.