Mission Scenario Generation and Characterization to Support Acquisition Decisions for Long Range Precision Fires-Maritime (LRPF-M)

NPS NRP Executive SummaryMission Scenario Generation and Characterization to Support Acquisition Decisions for Long Range Precision Fires-Maritime (LRPF-M)Naval Surface Warfare Center (NSWC), Division DahlgrenThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Mission Scenario Generation and Characterization to Support Acquisition Decisions for Long Range Precision Fires-Maritime (LRPF-M)

NPS NRP Project PresentationMission Scenario Generation and Characterization to Support Acquisition Decisions for Long Range Precision Fires-Maritime (LRPF-M)Naval Surface Warfare Center (NSWC), Division DahlgrenThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Mission Scenario Generation and Characterization to Support Acquisition Decisions for Long Range Precision Fires-Maritime (LRPF-M)

NPS NRP Project PosterMission Scenario Generation and Characterization to Support Acquisition Decisions for Long Range Precision Fires-Maritime (LRPF-M)Naval Surface Warfare Center (NSWC), Division DahlgrenThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

A Fuzzy Evaluation Method for System of Systems Meta-architectures

A method is proposed for evaluating a range of System of Systems (SoS) meta-architecture alternatives. SoS are composed through combination of existing, fully functioning Systems, possibly with minor functional changes, but certainly by using the combined Systems to achieve a new capability, not available from the Systems alone. The meta-architecture describes how all possible subsets of Systems can be combined to create an SoS. The fitness of a realizable SoS architecture may be characterized by terms such as unacceptable, marginal, above average, or excellent. While these terms provide little information about the SoS when used alone and informally, they readily fit into fuzzy membership sets that overlap at their boundaries. More descriptive attributes such as “ease of use,” which might depend on individual user and a set of conditions, “mission effectiveness” over a particular suite of missions, and “affordability,” which may change over time with changing business climate, etc., lend themselves readily to fuzzy evaluation as well. An approach to defining the fuzzy concepts and establishing rule sets to provide an overall SoS evaluation for many sets of participating individual Systems represented by the meta-architecture is discussed. An application of the method is discussed within the framework of developing and evaluating a hypothetical Intelligence, Surveillance and Reconnaissance (ISR) SoS capability

A Graph Theory Approach to Functional Failure Propagation in Early Complex Cyber-Physical Systems (CCPSs)

27th Annual INCOSE International Symposium (IS 2017) Adelaide, Australia, July 15-20, 2017This paper presents a framework to quantify failure propagation potential for complex, cyber-physical systems (CCPSs) during the conceptual stages of design. This method is referred to as the Function Failure Propagation Potential Methodology (FFPPM). This research is motivated by recent trends in engineering design. As systems become increasingly connected, an open area of research for CCPSs is to move reliability and failure assessments earlier in the engineering design process. This allows practitioners to make decisions at a point in the design process where the decision has a high impact and a low cost. Standard methods are limited by the availability of data and often rely on detailed representations of the system. As such, they have not addressed failure propagation in the functional design prior to selecting candidate architectures. To develop the metrics, graph theory is used to model and quantify the connectedness of the functional block diagram (FBD). These metrics quantify (1) the summation of the reachability matrix and (2) the summation of the number of paths between nodes (functions within system models) i and j for all i and j. From a practical standpoint, these metrics quantify the reachability between functions in the graph and the number of paths between functions defines the failure propagation potential of that failure. The unique contribution of this research is to quantify failure propagation potential during conceptual design prior to selecting candidate architectures. The goal of these metrics is to produce derived system requirements, based on an analysis, that focus on minimizing the impact of failures

A graph theory approach to predicting functional failure propagation during conceptual systems design

The article of record as published may be found at https://doi.org/10.1002/sys.21569An open area of research for complex, cyber-physical systems is how to adequately support decision making using reliability and failure data early in the systems engineering process. Having meaningful reliability and failure data available early offers information to decision makers at a point in the design process where decisions have a high impact to cost ratio. When applied to conceptual system design, widely used methods such as probabilistic risk analysis (PRA) and failure modes effects and criticality analysis (FMECA) are limited by the availability of data and often rely on detailed representations of the system. Further, existing methods for system reliability and failure methods have not addressed failure propagation in conceptual system design prior to selecting candidate architectures. Consideration given to failure propagation primarily focuses on the basic representation where failures propagate forward. In order to address the shortcomings of existing reliability and failure methods, this paper presents the function failure propagation potential methodology (FFPPM) to formalize the types of failure propagation and quantify failure propagation potential for complex, cyber-physical systems during the conceptual stage of system design. Graph theory is leveraged to model and quantify the connectedness of the functional block diagram (FBD) to develop the metrics used in FFPPM. The FFPPM metrics include (i) the summation of the reachability matrix, (ii) the summation of the number of paths between nodes (i.e., functions) i and j for all i and j, and (iii) the degree and degree distribution. In plain English, these metrics quantify the reachability between functions in the graph, the number of paths between functions, and the connectedness of each node. The FFPPM metrics can then be used to make candidate architecture selection decisions and be used as early indicators for risk. The unique contribution of this research is to quantify failure propagation potential during conceptual system design of complex, cyber-physical systems prior to selecting candidate architectures. FFPPM has been demonstrated using the example of an emergency core cooling system (ECCS) system in a pressurized water reactor (PWR).Naval Postgraduate School (NPS) and United States Nuclear Regulatory CommissionNaval Postgraduate School (NPS) and United States Nuclear Regulatory Commission Grant Number NRC-HQ- 84-14-G-004