The maritime industry is critical to Singapore's survival. In 2019, the Ministry of Defence found that the maritime industry accounted for 7% of Singapore's GDP and supplied more than 90% of Singapore's food consumption in 2018. To protect the maritime trade, one of the many threats Singapore has to defend against is naval mines. Effective mine countermeasures (MCM) using unmanned systems would enhance safety and reduce the reliance on human involvement. This thesis uses agent-based simulation, cutting-edge design of experiments, and data analysis tools to explore the performance of different MCM concept of operations (CONOPS). The scenario is a defensive MCM mission where unmanned surface vehicles are deployed around the clock to neutralize naval mines along operational sea lines of communications. Results from 60,000 simulated MCM missions reveal that overlapping sensor range and path deviation are the main factors influencing kill probability. The main driving factors for risk are detector speed, revisit rate, and sectorization of neutralizers. Sectorization of neutralizers increases the risk to transiting vessels and has little impact on kill probability. It is recommended that decision makers focus on increasing the speed of detectors, optimizing the length of overlap for sensor range, and using strategies to reduce path deviation when improving a CONOPS for the MCM scenario presented in this thesis.

Distribution Statement A. Approved for public release: Distribution is unlimited.

Civilian, DSO National Laboratories, Singapore

Outstanding Thesis