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Researching, developing, and transitioning advances in separation architectures, model-based system engineering, and mathematical analysis.
- Safety & Security AnalysisAnalyze system models for gaps in safety and security compliance, and generate documentation to support certification requirements.
- Real-time Operating System SchedulingProvide end-to-end, system-wide schedulabilty analysis, and generate real-time operating system (RTOS) schedules and configuration information
- Embedded System Tradespace AnalysisSupport least-commitment design strategies by continuously evaluating embedded system design alternatives against diverse requirements.
- Isolation TechnologyEnable virtual security enclaves within a single physical server
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What’s next: Innovative research examining hard problems of national importance.
- Weird MachinesAnticipating vulnerabilities related to computer systems that employ artificial intelligence
- Education InnovationDelivering game-based education to adolescents and young adults
- Automated Behavior AnalysisDetecting vulnerabilities in embedded systems using timed automata (VOLTA)
- Code GenerationAutomating the integration of cyber-resilient components in complex systems
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Acquisition Research: Digital Engineering Effectiveness
Acquisition Research: Digital Engineering Effectiveness
Abstract
The 2018 release of the DoD’s Digital Engineering (DE) strategy and the success of applying DE methods in the mechanical and electrical engineering domains motivate application of DE methods in other product development workflows, such as systems and/or software engineering. The expected benefits of this are improved communication and traceability with reduced rework and risk. Organizations have demonstrated advantages of DE methods many times over by using model-based design and analysis methods, such as Finite Element Analysis (FEA) or SPICE (Simulation Program with Integrated Circuit Emphasis), to conduct detailed evaluations earlier in the process (i.e., shifting left). However, other domains such as embedded computing resources for cyber physical systems (CPS) have not yet effectively demonstrated how to incorporate relevant DE methods into their development workflows. Although there is broad support for SysML and there has been significant advancement in specific tools, e.g., MathWorks ®, ANSYS®, and Dassault tool offerings, and standards like Modelica and AADL, the DE benefits to CPS engineering have not been broadly realized. In this paper, we will explore why CPS developers have been slow to embrace DE, how DE methods should be tailored to achieve their stakeholders’ goals, and how to measure the effectiveness of DE-enabled workflows.
Year of Publication
2022
Source
Nineteenth Annual Acquisition Research Symposium