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Conceptual design of sacrificial sub-systems: failure flow decision functions

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Abstract

This paper presents a method to conceptually model sacrificing non-critical sub-systems, or components, in a failure scenario to protect critical system functionality through a functional failure modeling technique. Understanding the potential benefits and drawbacks of choosing how a failure is directed in a system away from critical sub-systems and toward sub-systems that can be sacrificed to maintain core functionality can help system designers to design systems that are more likely to complete primary mission objectives despite failure events. Functional modeling techniques are often used during the early stage of conceptual design for complex systems to provide a better understanding of system architecture. A family of methods exists that focuses on the modeling of failure initiation and propagation within a functional model of a system. Modeling failure flow provides an opportunity to understand system failure propagation and inform system design iteration for improved survivability and robustness. Currently, the ability to model failure flow decision-making is missing from the family of function failure and flow methodologies. The failure flow decision function (FFDF) methodology presented in this paper enables system designers to model failure flow decision-making problems where functions and flows that are critical to system operation are protected through the sacrifice of less critical functions and flow exports. The sacrifice of less critical system functions and flows allows for mission critical functionality to be preserved, leading to a higher rate of mission objective completion. An example of FFDF application in a physical design is a non-critical peripheral piece of electrical hardware being sacrificed during an electrical surge condition to protect critical electronics necessary for the core functionality of the system. In this paper, a case study of the FFDF method is presented based on a Sojourner class Mars Exploration Rover (MER) platform.

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Acknowledgements

This research was partially supported by United States Nuclear Regulatory Commission Grant No. 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 Van Bossuyt lab and specifically wish to thank the following students for their contributions: Alexis Humann, David Hodge, Zachary Mimlitz, and Robin Coleman. The authors wish to thank LeVar Burton, Fred Rogers, Gene Roddenberry, Carl Sagan, and their individual middle school and high school science and technical arts teachers who inspired them to pursue careers in the sciences and engineering, and instilled in them a sense of purpose and compassion.

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Correspondence to Douglas L. Van Bossuyt.

Appendices

Appendix 1

Appendix 2

Flow type

Probability of passing failure downstream

Probability of passing failure upstream

Collectable energy

0.10

0.00

Electrical energy

0.40

0.02

Digital signal

0.50

0.02

Control signal

0.50

0.02

Positional information

0.47

0.00

Visual information

0.47

0.00

Rotational work

0.50

0.15

Translational work

0.50

0.15

Alignment work

0.25

0.15

Function

Probability of accepting failure flow

 

Accumulate energy

0.50

 

Store energy

0.12

 

Distribute electrical

0.24

 

Control magnitude electrical

0.20

 

Convert electrical to rotation

0.16

 

Transmit rotation

0.16

 

Convert rotation to translation

0.16

 

Direct command

0.44

 

Process signal

0.01

 

Store data

0.01

 

Record position

0.22

 

Record visual

0.22

 

Transmit data

0.44

 

Appendix 3

Index

Flow type

  

f1

Collectable energy

  

f2

Electrical energy

  

f3

Digital signal

  

f4

Position information

  

f5

Visual information

  

f6

Rotational work

  

f7

Translation work

  

f8

Steering work

  

Index

Function type

Index

Function type

1

Operating environment

26

Convert electric-to-rotation 7

2

Accumulate energy 1

27

Convert electric-to-rotation 8

3

Accumulate energy 2

28

Convert electric-to-rotation 9

4

Accumulate energy 3

29

Convert electric-to-rotation 10

5

Accumulate energy 4

30

Transmit rotation 1

6

Accumulate energy 5

31

Transmit rotation 2

7

Accumulate energy 6

32

Transmit rotation 3

8

Accumulate energy 7

33

Transmit rotation 4

9

Accumulate energy 8

34

Convert rotation-to-translation 1

10

Accumulate energy 9

35

Convert Rotation-to-Translation 2

11

Accumulate energy 10

36

Convert rotation-to-translation 3

12

Accumulate energy 11

37

Convert rotation-to-translation 4

13

Accumulate energy 12

38

Convert rotation-to-translation 5

14

Accumulate energy 13

39

Convert rotation-to-translation 6

15

Store energy 1

40

Direct command

16

Store energy 2

41

Process signal

17

Store energy 3

42

Process signal (digital)

18

Distribute electricity

43

Store data 1

19

Control magnitude electrical

44

Store data 2

20

Convert electric-to-rotation 1

45

Store data 3

21

Convert electric-to-rotation 2

46

Record position

22

Convert electric-to-rotation 3

47

Record visual 1

23

Convert electric-to-rotation 4

48

Record visual 2

24

Convert electric-to-rotation 5

49

Record visual 3

25

Convert electric-to-rotation 6

50

Transmit data (analogue)

Appendix 4

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Short, AR., Lai, A.D. & Van Bossuyt, D.L. Conceptual design of sacrificial sub-systems: failure flow decision functions. Res Eng Design 29, 23–38 (2018). https://doi.org/10.1007/s00163-017-0258-3

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