Publications

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As Modeling and Simulation (M&S) tools have matured, their applicability and importance have increased across many national security challenges. In particular, they provide a way to test how something may behave without the need to do real world testing. However, current and future changes across several factors including capabilities, policy, and funding are driving a need for rapid response or evaluation in ways that many M&S tools cannot address. Issues around large data, computational requirements, delivery mechanisms, and analyst involvement already exist and pose significant challenges. Furthermore, rising expectations, rising input complexity, and increasing depth of analysis will only increase the difficulty of these challenges. In this study we examine whether innovations in M&S software coupled with advances in ''cloud'' computing and ''big-data'' methodologies can overcome many of these challenges. In particular, we propose a simple, horizontally-scalable distributed computing environment that could provide the foundation (i.e. ''cloud'') for next-generation M&S-based applications based on the notion of ''parallel multi-simulation''. In our context, the goal of parallel multi- simulation is to consider as many simultaneous paths of execution as possible. Therefore, with sufficient resources, the complexity is dominated by the cost of single scenario runs as opposed to the number of runs required. We show the feasibility of this architecture through a stable prototype implementation coupled with the Umbra Simulation Framework [6]. Finally, we highlight the utility through multiple novel analysis tools and by showing the performance improvement compared to existing tools.

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This Lab-Directed Research and Development (LDRD) sought to develop technology that enhances scenario construction speed, entity behavior robustness, and scalability in Live-Virtual-Constructive (LVC) simulation. We investigated issues in both simulation architecture and behavior modeling. We developed path-planning technology that improves the ability to express intent in the planning task while still permitting an efficient search algorithm. An LVC simulation demonstrated how this enables 'one-click' layout of squad tactical paths, as well as dynamic re-planning for simulated squads and for real and simulated mobile robots. We identified human response latencies that can be exploited in parallel/distributed architectures. We did an experimental study to determine where parallelization would be productive in Umbra-based force-on-force (FOF) simulations. We developed and implemented a data-driven simulation composition approach that solves entity class hierarchy issues and supports assurance of simulation fairness. Finally, we proposed a flexible framework to enable integration of multiple behavior modeling components that model working memory phenomena with different degrees of sophistication.

Network-centric systems that depend on mobile wireless ad hoc networks for their information exchange require detailed analysis to support their development. In many cases, this critical analysis is best provided with high-fidelity system simulations that include the effects of network architectures and protocols. In this research, we developed a high-fidelity system simulation capability using an HLA federation. The HLA federation, consisting of the Umbra system simulator and OPNET Modeler network simulator, provides a means for the system simulator to both affect, and be affected by, events in the network simulator. Advances are also made in increasing the fidelity of the wireless communication channel and reducing simulation run-time with a dead reckoning capability. A simulation experiment is included to demonstrate the developed modeling and simulation capability.

This report describes Umbra's High Level Architecture HLA library. This library serves as an interface to the Defense Simulation and Modeling Office's (DMSO) Run Time Infrastructure Next Generation Version 1.3 (RTI NG1.3) software library and enables Umbra-based models to be federated into HLA environments. The Umbra library was built to enable the modeling of robots for military and security system concept evaluation. A first application provides component technologies that ideally fit the US Army JPSD's Joint Virtual Battlespace (JVB) simulation framework for Objective Force concept analysis. In addition to describing the Umbra HLA library, the report describes general issues of integrating Umbra with RTI code and outlines ways of building models to support particular HLA simulation frameworks like the JVB.

Umbra is a new Sandia-developed modeling and simulation framework. The Umbra framework allows users to quickly build models and simulations for intelligent system development, analysis, experimentation, and control and supports tradeoff analyses of complex robotic systems, device, and component concepts. Umbra links together heterogeneous collections of modeling tools. The models in Umbra include 3D geometry and physics models of robots, devices and their environments. Model components can be built with varying levels of fidelity and readily switched to allow models built with low fidelity for conceptual analysis to be gradually converted to high fidelity models for later phase detailed analysis. Within control environments, the models can be readily replaced with actual control elements. This paper describes Umbra at a functional level and describes issues that Sandia uses Umbra to address.