and games. In particular, the topics of scientific modeling and simulation, cyber and kinetic warfare, propaganda through games, and war gaming will be explored.
The increased power of computers arising from faster chips and memory, better bandwidth, better algorithms and architecture, and other improvements described in Chapter 2 means that increased levels of realism, accuracy, and fidelity can be included in models, whether a model is used for science and engineering or for games.
The level of detail included in a simulated model must be optimized for the complexity of the problem, the hardware platform that will be used to solve the model, the level of qualitative versus quantitative accuracy required, and the time one is willing to wait for the solution. As computer speed increases, the accuracy and fidelity of the solution can also increase while the time to solution decreases. In science, recent increases in computing hardware speeds and capabilities mean that more detailed underlying physics (e.g., fluid flow, thermodynamics, molecular interactions) can be considered within models of radar cross sections, airfoils, weather and climate, and materials, respectively, providing a greater level of predictive accuracy. There are particular fields in which huge breakthroughs in simulation capabilities are having a positive effect, as mentioned in the World Technology Evaluation Center report (Oden et al., 2006; WTEC, 2009). Examples include the life sciences and medicine, where the ability to perform simulations of complex biological molecules such as proteins on millisecond timescales with atomistic resolution is now possible.
Verification and validation (V&V) and uncertainty quantification (UQ) are essential elements of modeling and simulation and are critical for proper risk assessment. Despite this, systematic efforts to develop these elements and integrate them into scientific modeling and simulation are not yet prevalent in either academic research programs or industrial research efforts. The 1991 Army Science Board noted that the Army’s use of “unvalidated simulations” should end its use of M&S until V&V is addressed. The report claimed the Army had been overly focused on the “pretty graphics” and fast run time of the sim (Lynn et al., 1991). A more recent study (WTEC, 2009) found that the United States leads only marginally in V&V and UQ through the efforts of major Department of Energy programs (ASC/ASCI/PSAAP1). Progress in the ability to automate V&V and UQ for scientific simulation would likely show up in the typical academic literature, but may also be developed in-house as proprietary efforts, especially in industrial labs. General methods and strategies developed for V&V and UQ for a given scientific problem are expected to be transferable to some extent to other domains. Rapid progress in this area would give a major competitive edge to the level of predictability of simulation and the accurate assessment of risk. See Chart 4-1 for a representation of this scenario according to the technology warning methodology detailed in Appendix C.
The ability to include physics-based models in simulation can be exploited to increase the “realism” of games through increased detail and more accurate levels of fidelity of the models solved as part of the games program. Examples of real-world intersections between games and M&S are detailed as case studies in Boxes 4-1 and 4-2.
While the open-source movement is seen by many as critical for leveraging scientific, engineering, and business productivity code bases, there is still the inherit danger in free access to information by those with nefarious purposes. In fact, some individuals in the U.S. military, homeland security, and