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Active mission success estimation through functional modeling

Research in Engineering Design volume 29, pages 565–588 (2018)Cite this article

Abstract

Through the application of statistical models, the active mission success estimation (AMSE) introduced in this paper can be performed during a rapidly developing unanticipated failure scenario to support decision making. AMSE allows for system operators to make informed management and control decisions by performing analyses on a nested system of functional models that requires low time and computational cost. Existing methods for analyses of mission success such as probabilistic risk assessment or worst case analysis have been applied in the analysis and planning of space missions since the mid-twentieth century. While these methods are effective in analyzing anticipated failure scenarios, they are built on computational models, logical structures, and statistical models that often are difficult and time-intensive to modify, and are computationally inefficient leading to very long calculation times and making their ability to respond to unanticipated or rapidly developing scenarios limited. To demonstrate AMSE, we present a case study of a generalized crewed Martian surface station mission. A crew of four astronauts must perform activities to achieve scientific objectives while surviving for 1070 Martian sols before returning to Earth. A second crew arrives at the same site to add to the settlement midway through the mission. AMSE uses functional models to represent all of the major environments, infrastructure, equipment, consumables, and critical systems of interest (astronauts in the case study presented) in a nested super system framework that is capable of providing rapidly reconfigurable and calculable analysis. This allows for AMSE to be used to make informed mission control decisions when facing rapidly developing or unanticipated scenarios. Additionally, AMSE provides a framework for the inclusion of humans into functional analysis through a systems approach. Application of AMSE is expected to produce informed decision making benefits in a variety of situations where humans and machines work together toward mission goals in uncertain and unpredictable conditions.

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Notes

  1. This assumes no self-sacrifice or other extreme solutions.

Abbreviations

AI:

Artificial intelligence

AMSE:

Active mission success estimation

CDF:

Cumulative distribution function

DRV:

Daily recommended value

EMU:

Extravehicular mobility units

EVA:

Extravehicular activity

FBED:

Functional basis for engineering design

FFD:

Referred to as functional flow diagrams

FFIP:

Failure flow identification and propagation

ISRU:

In situ resource utilization

IVA:

Intra-vehicular activities

PDM:

Prognostic-enabled decision making

PHM:

Prognostics and health management

PRA:

Probabilistic risk assessment

SEV:

Surface exploration vehicle

WCA:

Worst case analysis

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Acknowledgements

This research was partially supported by United States Nuclear Regulatory Commission Grant number NRC-HQ-84-14-G-0047. Any opinions or findings of this work are the responsibility of the authors, and do not necessarily reflect the views of the sponsors or collaborators. The authors wish to acknowledge the work of the undergraduate research assistants in the Robotics, Automation, and Design group at Colorado School of Mines.

Author information

Authors and Affiliations

  1. Oregon State University, Corvallis, OR, 97331, USA

    Ada-Rhodes Short & Bryony DuPont

  2. Colorado School of Mines, Golden, CO, 80401, USA

    Robert D. D. Hodge

  3. KTM Research, LLC, Tualatin, USA

    Douglas L. Van Bossuyt

Authors
  1. Ada-Rhodes Short
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  2. Robert D. D. Hodge
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  3. Douglas L. Van Bossuyt
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  4. Bryony DuPont
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Corresponding author

Correspondence to Bryony DuPont.

Appendices

Appendix 1

Task Duration (sec) Systems used System health factors Resources used Quantity
Sleeping 30,960 Habitat module Time inhabited 30,960 (s) Calories burned ~ 8.5 (kcal/kg) × Astronaut weight (kg)
Physical intensity 0.5/10
Eat food 7200 Habitat module Time inhabited 7200 (s) Calories burned ~ 2.8 (kcal/kg) × Astronaut Weight (kg)
Physical intensity 1.0/10 Food eaten 3025 (kcal) Gained
Exercise 7200 Habitat module Time inhabited 7200 (s) Calories burned ~ 17.4 (kcal/kg) × Astronaut weight (kg)
Physical intensity 9.5/10
Maintain farm 3600 Farm module Time inhabited 3600 (s) Calories burned ~ 4.4 (kcal/kg) × Astronaut Weight (kg)
Physical intensity 4.5/10 Water used ~ 20 (L/m2 of Crops Being Grown)
Food produced ~ 8.4 (kg/day) At full production
EVA 28,800 Air lock Uses 2 Calories burned ~ 25 (kcal/kg) × Astronaut weight (kg)
EMU Time inhabited 28,800 (s)
Physical intensity 3.0/10
SEV Time inhabited 3600 (s)
Physical intensity 1.7/10
IVA 10,800 Habitat module Time inhabited 10,800 (s) Calories burned ~ 5 (kcal/kg) × Astronaut weight (kg)
Physical intensity 1.3/10

Appendix 2

Sol Hour Radiation Temperature Starvation Exhaustion Injury
0 8.6 1.53E−06 5.09E−80 7.48E−12 9.87E−10 1.00E−09
0 9.6 1.53E−06 6.02E−10 1.25E−08 1.37E−07 8.00E−06
0 13.6 1.53E−06 1.32E−37 1.56E−08 2.33E−07 7.20E−06
0 15.6 1.53E−06 3.63E−19 1.64E−08 1.74E−06 1.00E−08
0 19.6 1.53E−06 1.32E−37 2.04E−08 4.50E−06 7.20E−06
0 24.6 1.53E−06 2.19E−28 1.24E−08 2.67E−05 1.00E−08
1 33.2 1.53E−06 5.09E−80 8.49E−12 9.87E−10 1.00E−09
1 36.2 1.53E−06 6.02E−10 7.96E−09 1.37E−07 1.00E−05
1 37.2 1.53E−06 6.02E−10 8.51E−09 2.33E−07 1.00E−05
1 38.2 1.53E−06 6.02E−10 9.10E−09 3.91E−07 1.00E−05
1 39.2 1.53E−06 6.02E−10 9.73E−09 6.49E−07 1.00E−05
1 40.2 1.53E−06 6.02E−10 1.04E−08 1.07E−06 1.00E−05
1 41.2 1.53E−06 6.02E−10 1.11E−08 1.74E−06 1.00E−05
1 42.2 1.53E−06 6.02E−10 1.19E−08 2.81E−06 1.00E−05
1 43.2 1.53E−06 6.02E−10 1.27E−08 4.50E−06 1.00E−05
1 47.2 1.53E−06 1.32E−37 1.41E−08 7.12E−06 1.00E−08
1 49.2 1.53E−06 3.63E−19 1.82E−08 4.07E−05 2.00E−05
2 57.8 1.53E−06 5.09E−80 1.38E−11 9.87E−10 1.00E−09
2 60.8 1.53E−06 6.02E−10 1.17E−08 1.37E−07 1.00E−05
2 61.8 1.53E−06 6.02E−10 1.25E−08 2.33E−07 1.00E−05
2 62.8 1.53E−06 6.02E−10 1.33E−08 3.91E−07 1.00E−05
2 63.8 1.53E−06 6.02E−10 1.42E−08 6.49E−07 1.00E−05
2 64.8 1.53E−06 6.02E−10 1.52E−08 1.07E−06 1.00E−05
2 65.8 1.53E−06 6.02E−10 1.62E−08 1.74E−06 1.00E−05
2 66.8 1.53E−06 6.02E−10 1.73E−08 2.81E−06 1.00E−05
2 67.8 1.53E−06 6.02E−10 1.85E−08 4.50E−06 1.00E−05
2 71.8 1.53E−06 1.32E−37 2.05E−08 7.12E−06 1.00E−08
2 73.8 1.53E−06 3.63E−19 2.64E−08 4.07E−05 2.00E−05

Appendix 3

Mission Plan

  • Sol-770

    • Crew Alpha Equipment Arrives on Planet

  • Sol 0

    • Crew Alpha Arrives on the Surface

    • Perform EVAs and IVAs to verify critical Martian Surface Habitat functionality

    • Unpack transit vehicle

    • Set up habitat module

  • Sol 1–5

    • Perform EVAs to validate external less critical functions

    • Begin Setup for experimentation and

    • Start farm

  • Sol 6-130

    • Tend to farm

      • Sol 55: Soybeans mature

      • Sol 67: Wheat mature

      • Sol 75: Potatoes mature

      • Sol 125: Sweet potatoes mature

      • Sol 130: Peanuts mature

      • Sol 130: Self-sufficient food source achieved

    • Perform EVAs on regular schedule

    • Perform IVAs on regular schedule

    • Perform Exercise on regular schedule

  • Sol 131–615

    • Perform EVAs on regular schedule

    • Perform IVAs on regular schedule

    • Perform Exercise on regular schedule

  • Sol 616–620

    • Begin verification of Beta Martian Surface Habitat during EVAs

    • Perform IVAs on regular schedule

    • Perform Exercise on regular schedule

  • Sol 621–769

    • Sol 621

      • Begin Farm Beta

    • Tend to Farm Beta

      • Sol 671: Soybeans mature

      • Sol 688: Wheat mature

      • Sol 696: Potatoes mature

      • Sol 746: Sweet potatoes mature

      • Sol 751: Peanuts mature

      • Sol 751: Self-sufficient food source achieved

    • Perform EVAs on regular schedule

    • Perform IVAs on regular schedule

    • Perform Exercise on regular schedule

  • Sol 770

    • Crew Beta Arrives on surface

      • Perform EVAs and IVAs to verify critical habitat functionality

      • Unpack transit vehicle

      • Set up habitat module

  • Sol 771–775

    • Crew Alpha

      • Perform EVAs on regular schedule

      • Perform IVAs on regular schedule

      • Perform Exercise on regular schedule

    • Crew Beta

      • Perform EVAs to validate external less critical functions

      • Begin Setup for experimentation and

  • Sols 776–1050

    • Crew Alpha

      • Perform EVAs on regular schedule

      • Perform IVAs on regular schedule

      • Perform Exercise on regular schedule

    • Crew Beta

      • Perform EVAs on regular schedule

      • Perform IVAs on regular schedule

      • Perform Exercise on regular schedule

  • Sols 1051–1069

    • Crew Alpha

      • Begin Prep for departure

      • Wrap up experiments

      • Perform EVAs to hand off tasks to Beta

      • Prepare habitat Alpha for vacancy

      • Will be used by Crew Gamma

    • Crew Beta

      • Perform EVAs on regular schedule

      • Perform IVAs on regular schedule

      • Perform Exercise on regular schedule

  • Sol 1070

    • Crew Alpha Departs from Martian Surface

    • End AMSE analysis

  • Sol 1540

    • Crew Gamma arrives and moves into habitat Alpha

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Short, AR., Hodge, R.D.D., Van Bossuyt, D.L. et al. Active mission success estimation through functional modeling. Res Eng Design 29, 565–588 (2018). https://doi.org/10.1007/s00163-018-0285-8

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Keywords

  • Risk
  • Functional modeling
  • Decision making
  • Mission success