M&S Improvements
In this section, we describe some modeling improvements that reduce identified limitations to our current analytic capability. This discussion will start at the engagement-level and progress up the M&S conflict hierarchy, shown in Figure 2, to the enterprise level.
At the engagement-level, there are at least three major ongoing initiatives to improve our analysis capability. First, one of our primary engagement M&S programs for air combat is BRAWLER, a time-oriented simulation of few-on-few fighter engagements. We have started listing the requirements for a follow-on M&S tool. The Australian Defence Science and Technology Group is also considering replacing their engagement-level air combat model. Hence, we are comparing requirements to improve both our lists.
Second, the joint community supports the Cyber Joint Munitions Effectiveness Methods (JMEMs) effort led by the Director, Operational Test & Evaluation in OSD (OSD/DOT&E). We support JMEMs as a forum to exchange cyber related M&S approaches to calculate operational effectiveness of cyber operations. We propose that the cyber engineering-level analysis, which is often done under highly classified restraints, should produce planning factors or metadata at lower classification levels. These cyber effects could be incorporated into more traditional M&S for analytic studies that are attempting to account for the impact of cyber operations on warfighting scenarios.
Our third engagement-level initiative is to improve our capability to analyze the impacts of logistics. We constructed a Time-Phased Force Deployment Data (TPFDD) builder and evaluator. Our operational energy project models fuel consumption and electrical usage in warfighting scenarios. We have built a prototype model of aircraft availability that evaluates the ability of the various base-level logistic components to support flight operations; this model includes maintenance personnel, parts availability, along with failure and fix rates. We are developing a model to explore the impacts of adversary attacks on our bases and their infrastructure (fuel, runways, vehicles, maintenance facilities, etc.) and our ability to apply active and passive defenses to mitigate the impact of these attacks. We are constructing interfaces between several of our existing engagement models and simulations. With this suite of tools, analysts should be able to evaluate base resiliency to the impact of enemy attack on installations and their infrastructure. The goal is to inform analysis on the logistics capacity to generate support for flight operations.
We also have many initiatives to improve our mission-area-level M&S analysis. The Air Force is transitioning to two simulation frameworks or environments, both of which are government owned: the Extensible Architecture for the Analysis and Generation of Linked Simulations (EAAGLES) (Hodson 2006) and the Advanced Framework for Simulation, Integration and Modeling (AFSIM). EAAGLES is for time-oriented hardware-in-the-loop simulations. AFSIM, is a discrete-event simulation environment (Zeh 2014). The Simulation and Analysis Facility (SIMAF) is testing whether the same system models may be run in both AFSIM and EAAGLES. The Air Force Research Laboratory is leading the collaboration among the analytic community to build AFSIM applications (equivalent to stand-alone models, like EADSIM or SUPRESSOR) for integrated air defense systems (IADS) and fighter engagements. We have already incorporated satellites and their contributions into our AFSIM applications. These two frameworks greatly increase our ability for sharing and reuse of system models.
We are also improving our mission area analytic ability. We are enhancing the capabilities of our Combat Forces Assessment Model (CFAM). We are modifying this cost-constrained, mixed-integer force structure development/assessment tool to improve the fidelity of a number of interactions including air-to-air refueling, expected attrition, resource usage, logistics, and basing.
For Campaign-level M&S, we are pleased with our Synthetic Theater Operations Research Model (STORM) (Seymour 2014). However, we continue to improve its capabilities. A new initiative is to incorporate wide-area effects including nuclear detonations into STORM (Hefty, et al. 2014). We also intend to improve the modeling of collection and use of intelligence, surveillance, and reconnaissance (ISR) along with other satellite contributions into STORM.
As shown in Figure 2, I contend there is an enterprise-level that is more aggregate than the campaign level. The primary concept at the enterprise-level is to evaluate a force structure ability to conduct wars in more than one type of conflict and strategic environment. To assist our evaluation of enterprise-level force structure options, we are continuing to develop the Bayesian Enterprise Analysis Model (BEAM). The aggregation in BEAM is that only the quantities of unit types or platforms within a large geographic region, without any specific locations, are modeled. Our BEAM prototype demonstration was promising.
Many more model enhancements are underway. This list is biased to those at the headquarters because that is where I sit and see what is happening. Under renewed emphasis within the Air Force on developmental programing and experimentation, the Air Force is assessing and improving its analytic capability.
Conclusion
The Air Force has two thrusts to improve the effectiveness and efficiency of its analytic M&S capability. We are defining M&S along with wargames, the meaning of studies, analysis, and assessments, and establishing standards for organizational analytic capability. M&S governance and oversight is being implemented to improve overall analytic enterprise performance and efficiency. We are better planning and coordinating our M&S developments and enhancements. The Air Force is improving its analytic tools at all levels of the Conflict M&S Hierarchy.
Disclaimer
The opinions expressed herein are those of the author, and are not necessarily representative of those of the United States Air Force or the Department of Defense.
References
(DoD), Department of Defense. 2015. “M&S Glossary.”
Clark, Clinton R, and Timothy J. Cook. 2008. “A Practical Approach to Effects-Based Operational Assessment.”22.2 (2008): 82. Air and Space Power Journal 22 (2): 82-99.
Gallagher, Mark A, Cameron MacKenzie, David Blum, and Douglas Boerman. 2015. “Communicating Risk Assessments.”AF/A9 Working Paper.
Gallagher, Mark A, David J Caswell, Brian Hanlon, and Justin M Hill. 2014. “Rethinking the Hierarchy of Models and Simulations for Conflicts.”Military Operations Research19 (4): 15-24. doi:10.5711/1082598319415.
Hefty, Kiley, Thomas Dickey, Mark A Gallagher, and Frederick Garcia. 2014.Journal of Defense Modeling and Simulation. doi:1548512915588571.
Hodson, Douglas D., David P. Gehl, and Rusty O. Baldwin. 2006. “Building Distributed Simulations Utilizing the EAAGLES Framework.”Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC).
Institute for Operations Research and Managment Science (INFORMS). 2015. “What Analytics Is.” INFORMS. Accessed August 8, 2015. https://www.informs.org/Sites/Getting-Started-With-Analytics/What-Analytics-Is.
Perla, Peter P., and Darryl L. Branting. 1986.Wargames, Exercises, and Analysis.No. CRM-86-20., Alexandria, VA: Center for Naval Analyses, Opearations Division.
Pew, Richard W.; Mavor, Anne S.; Editors. 1998.Modeling Human and Organizational Behavior: Application to Military Simulations.National Research Council, National Academies Press. http://www.nap.edu/catalog/6173.html.
Seymour, Christian N. 2014.Capturing the full potential of the Synthetic Theater Operations Research Model (STORM). Master’s Thesis, Monterey, CA: Naval Postgraduate School. http://hdl.handle.net/10945/44000.
Zacharias, Greg L., Jean MacMillan, and Susan B Van Hemel. 2008.Behavioral Modeling and Simulations: From Individuals to Socieities.Washington, DC: National Academies Press.
Zeh, James and Brian Birkmire. 2014. “Advanced Framework For Simulation, Integration and Modeling (AFSIM) Version 1.8 Overview.” RQQD, Air Force Research Laboratory, Wright-Patterson Air Force Base.