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Research Papers

A Model for Quantifying System Evolvability Based on Excess and Capacity

[+] Author and Article Information
Morgan W. P. Tackett

Graduate Research Assistant
Department of Mechanical Engineering,
Brigham Young University,
Provo, UT 84602

Christopher A. Mattson

Associate Professor
Department of Mechanical Engineering,
Brigham Young University,
Provo, UT 84602
e-mail: mattson@byu.edu

Scott M. Ferguson

Assistant Professor
Department of Mechanical
and Aerospace Engineering,
North Carolina State University,
Raleigh, NC 27695

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received May 3, 2013; final manuscript received January 23, 2014; published online March 13, 2014. Assoc. Editor: Jonathan Cagan.

J. Mech. Des 136(5), 051002 (Mar 13, 2014) (11 pages) Paper No: MD-13-1202; doi: 10.1115/1.4026648 History: Received May 03, 2013; Revised January 23, 2014

An important factor in system longevity is service-phase evolvability, which is defined as the ability of a system to physically transform from one configuration to a more desirable configuration while in service. These transformations may or may not be known during the design process, and may or may not be reversible. In a different study, we examined 210 engineered systems and found that system excess and modularity allow a system to evolve while in service. Building on this observation, the present paper introduces mathematical relationships that map a system's excess to that system's ability to evolve. As introduced in this paper, this relationship is derived from elastic potential-energy theories. The use of the evolvability measure, and other related measures presented herein, are illustrated with simple examples and applied to the design of U.S. Navy nuclear aircraft carriers. Using these relationships, we show that the Navy's new Ford-class aircraft carrier is measurably more evolvable than the Nimitz-class carriers. While the ability for systems to evolve is based on excess and modularity, this paper is focused only on excess. The mapping between modularity and evolvability is the focus of another work by the authors.

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Figures

Grahic Jump Location
Fig. 1

System reconfigures once in (a) and evolves to needs in (b)

Grahic Jump Location
Fig. 2

A graphical representation of the change in capacity (C) and evolvability (E) with constant unit gain measures

Grahic Jump Location
Fig. 3

A graphical representation of the change in capacity (C) and evolvability (E) with nonconstant unit gain measures

Grahic Jump Location
Fig. 4

Nimitz-class nuclear aircraft carrier, USS John C. Stennis [39]

Grahic Jump Location
Fig. 5

Plot of service length as a function of displacement for all decommissioned Cruisers, Destroyers, Frigates, and Patrol Craft built after World War II. Adapted from Ref. [45]

Grahic Jump Location
Fig. 6

Histogram of gain results

Grahic Jump Location
Fig. 7

Histogram of capacity due to gain variability

Grahic Jump Location
Fig. 8

Histogram of evolvability due to gain variability

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