• DocumentCode
    708557
  • Title

    Comparative analysis of static and dynamic probabilistic risk assessment

  • Author

    Mattenberger, Chris ; Mathias, Donovan L. ; Go, Susie

  • Author_Institution
    NASA Ames Res. Center, Moffett Field, CA, USA
  • fYear
    2015
  • fDate
    26-29 Jan. 2015
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This study examines three different methodologies for producing loss-of-mission (LOM) and loss-of-crew (LOC) risks estimates for probabilistic risk assessments (PRA) of crewed spacecraft. The three bottom-up, component-based PRA approaches examined are a traditional static fault tree, a dynamic Monte Carlo simulation, and a fault tree hybrid that incorporates some dynamic elements. These approaches were used to model the reaction control system thruster pod of a generic crewed spacecraft and mission, and a comparative analysis of the methods is presented. The methodologies are assessed in terms of the process of modeling a system, the actionable information produced for the design team, and the overall fidelity of the quantitative risk evaluation generated. The system modeling process is compared in terms of the effort required to generate the initial model, update the model in response to design changes, and support mass-versus-risk trade studies. The results are compared by examining the top-level LOM/LOC estimates and the relative risk driver rankings at the failure mode level. The fidelity of each modeling methodology is discussed in terms of its capability to handle real-world system dynamics such as cold-sparing, changes in mission operations due to loss of redundancy, and common cause failure modes. The paper also discusses the applicability of each methodology to different phases of system development and shows that a single methodology may not be suitable for all of the many purposes of a spacecraft PRA. The fault tree hybrid approach is shown to be best suited to the needs of early assessments during conceptual design phases. As the design begins to mature, the level of detail represented in the risk model must go beyond redundancy and nominal mission operations to include dynamic, time- and state-dependent system responses as well as diverse system capabilities. This is best accomplished using the dynamic simulation approach, since these phenomena are no- easily captured by static methods. Ultimately, once the design has been finalized and the goal of the PRA is to provide design validation and requirement verification, more traditional, static fault tree approaches may become as appropriate as the simulation method.
  • Keywords
    Monte Carlo methods; fault trees; probability; risk management; space vehicles; LOC risk estimates; LOM; PRA spacecraft; conceptual design phases; dynamic Monte Carlo simulation; dynamic probabilistic risk assessment; dynamic simulation approach; failure mode level; fault tree hybrid approach; generic crewed spacecraft; loss-of-crew; loss-of-mission; quantitative risk evaluation; reaction control system thruster pod; real-world system dynamics; relative risk driver rankings; state-dependent system responses; static fault tree approach; static probabilistic risk assessment; system modeling process; three bottom-up component-based PRA approaches; Fault trees; Monte Carlo methods; Orbits; Space vehicles; Subspace constraints; Valves; Vehicle dynamics; Crewed Spacecraft; Dynamic PRA; Risk-Informed Design; Space Exploration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Reliability and Maintainability Symposium (RAMS), 2015 Annual
  • Conference_Location
    Palm Harbor, FL
  • Print_ISBN
    978-1-4799-6702-5
  • Type

    conf

  • DOI
    10.1109/RAMS.2015.7105120
  • Filename
    7105120