The U.S. Army is transforming into a network-centric modular force. Developed by the Army Research Laboratory's Survivability/Lethality Analysis Directorate, in conjunction with New Mexico State University's Physical Science Laboratory, the System of Systems Survivability Simulation (S4) is a detailed, agent-based, Monte Carlo simulation designed to conduct survivability, lethality, and vulnerability assessments of military platforms connected via communications networks to other platforms on the battlefield. This thesis explores key parameters that make up S4's communications environment, using design of experiments and data farming tools to determine if any or all are having unintended interactions. This thesis concludes that the explored parameters generally perform as intended, decreasing or increasing communication performance as the environment becomes respectively more or less restrictive. However, the level of influence of the parameters varies greatly, questioning either the level of realism to how the parameters are modeled or their necessity to the simulation. In addition, the variation across input settings and replications demonstrates the value of being able to efficiently explore multiple factors and take many replications. As a pilot study, these results and methodology pave the way for enhanced analytical capability with S4 and its continued verification, validation, and accreditation.