Active mission success estimation through functional modeling

Short, Ada-Rhodes; Hodge, Robert D. D.; Bossuyt, Douglas L. Van; DuPont, Bryony

doi:10.1007/s00163-018-0285-8

Cited by 4 publications

(7 citation statements)

References 40 publications

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“…This may help to identify “worst case scenarios” where completely unanticipated emergent system behaviors occur due to the SoI receiving several irrationality initiators at once. Recent research on external initiating events for autonomous robotic systems has indicated that unique emergent system behaviors not predicted by other research methods can be caused by several external initiating events simultaneously occurring and interacting with one another inside of an SoI …”

Section: Methodsmentioning

confidence: 99%

“…Recent research on external initiating events for autonomous robotic systems has indicated that unique emergent system behaviors not predicted by other research methods can be caused by several external initiating events simultaneously occurring and interacting with one another inside of an SoI. 59,89 We suggest that all possible irrationality initiator-dependent com- (1). Note that the formula intentionally subtracts 1 to acknowledge that the baseline case of no irrationality initiators being present in the SoI is assumed to have been previously assessed.…”

Section: Independent and Dependent Irrationality Initiatorsmentioning

confidence: 96%

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A method of identifying and analyzing irrational system behavior in a system of systems

Bossuyt

O’Halloran

Arlitt

2019

Systems Engineering

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System of interest (SoI) failures can sometimes be traced to an unexpected behavior occurring within another system that is a member of the system of systems (SoS) with the SoI. This article presents a method for use when designing an SoI that helps to analyze an SoS for unexpected behaviors from existing SoS members during the SoI's conceptual functional modeling phase of system architecture. The concept of irrationality initiators—unanticipated or unexpected failure flows emitted from one system that adversely impact an SoI, which appear to be impossible or irrational to engineers developing the new system—is introduced and implemented in a quantitative risk analysis method. The method is implemented in the failure flow identification and propagation framework to yield a probability distribution of failure paths through an SoI in the SoS. An example of a network of autonomous vehicles operating in a partially denied environment is presented to demonstrate the method. The method presented in this paper allows practitioners to more easily identify potential failure paths and prioritize fixing vulnerabilities in an SoI during functional modeling when significant changes can still be made with minimal impact to cost and schedule.

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Section: Methodsmentioning

confidence: 99%

Section: Independent and Dependent Irrationality Initiatorsmentioning

confidence: 96%

A method of identifying and analyzing irrational system behavior in a system of systems

Bossuyt

O’Halloran

Arlitt

2019

Systems Engineering

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“…This is done by propagating failures through the system and results in the system's functional health. This work has been extended is a variety of ways 62–70 . Work by O'Halloran et al.…”

Section: Related Researchmentioning

confidence: 99%

“…This work has been extended is a variety of ways. [62][63][64][65][66][67][68][69][70] Work by O'Halloran et al models failure propagation across uncoupled boundaries in early conceptual designs. 16 Related work by Jensen has been focused on functional failure propagation in FBDs and basic functional architectures.…”

Section: Related Researchmentioning

confidence: 99%

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

O’Halloran

Papakonstantinou

Giammarco

et al. 2021

Systems Engineering

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An 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).

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“…Routing and planning decisions are important especially in contexts where systems may be exposed to non-nominal conditions such as in a military context, a space exploration context, etc. because the decisions analyze several priority variables such as the potential for inclement weather and proximity of hazards that can impact the success of the mission [30][31][32][33]. Notably, the cost of time for employing resources against the risk of exposure to threats is a key criterion to consider.…”

Section: Mission Planningmentioning

confidence: 99%

Digital Twin-Enabled Decision Support in Mission Engineering and Route Planning

Lee

Bossuyt

Bickford

2021

Systems

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This article presents a Model-Based Systems Engineering (MBSE) methodology for the development of a Digital Twin (DT) for an Unmanned Aerial System (UAS) with the ability to demonstrate route selection capability with a Mission Engineering (ME) focus. It reviews the concept of ME and integrates ME with a MBSE framework for the development of the DT. The methodology is demonstrated through a case study where the UAS is deployed for a Last Mile Delivery (LMD) mission in a military context where adversaries are present, and a route optimization module recommends an optimal route to the user based on a variety of inputs including potential damage or destruction of the UAS by adversary action. The optimization module is based on Multiple Attribute Utility Theory (MAUT) which analyzes predefined criteria which the user assessed would enable the successful conduct of the UAS mission. The article demonstrates that the methodology can execute a ME analysis for route selection to support a user’s decision-making process. The discussion section highlights the key MBSE artifacts and also highlights the benefits of the methodology which standardizes the decision-making process thereby reducing the negative impact of human factors which may deviate from the predefined criteria.

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Active mission success estimation through functional modeling

Cited by 4 publications

References 40 publications

A method of identifying and analyzing irrational system behavior in a system of systems

A method of identifying and analyzing irrational system behavior in a system of systems

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

Digital Twin-Enabled Decision Support in Mission Engineering and Route Planning

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