Research Papers: Design Theory and Methodology

The D3 Methodology: Bridging Science and Design for Bio-Based Product Development

[+] Author and Article Information
Paul Egan

Department of Mechanical and
Process Engineering,
Swiss Federal Institute of Technology
(ETH Zurich),
CLA F 34.1,
Tannenstrasse 3,
Zurich 8092, Switzerland
e-mail: pegan@ethz.ch

Jonathan Cagan

Department of Mechanical Engineering,
Carnegie Mellon University,
5000 Forbes Avenue,
Pittsburgh, PA 15213
e-mail: cagan@cmu.edu

Christian Schunn

Department of Psychology,
University of Pittsburgh,
4200 Fifth Avenue,
Pittsburgh, PA 15260
e-mail: schunn@pitt.edu

Felix Chiu

Department of Mechanical Engineering,
Carnegie Mellon University,
5000 Forbes Avenue,
Pittsburgh, PA 15213
e-mail: Felixchiu92@gmail.com

Jeffrey Moore

Department of Biological Sciences,
University of Massachusetts Lowell,
One University Avenue,
Lowell, MA 01854
e-mail: Jeffrey_Moore@uml.edu

Philip LeDuc

Department of Mechanical Engineering,
Carnegie Mellon University,
5000 Forbes Avenue,
Pittsburgh, PA 15213
e-mail: prl@andrew.cmu.edu

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received October 12, 2015; final manuscript received May 31, 2016; published online June 16, 2016. Assoc. Editor: Andy Dong.

J. Mech. Des 138(8), 081101 (Jun 16, 2016) (13 pages) Paper No: MD-15-1699; doi: 10.1115/1.4033751 History: Received October 12, 2015; Revised May 31, 2016

New opportunities in design surface with scientific advances: however, the rapid pace of scientific discoveries combined with the complexity of technical barriers often impedes new product development. Bio-based technologies, for instance, typically require decisions across complex multiscale system organizations that are difficult for humans to understand and formalize computationally. This paper addresses such challenges in science and design by weaving phases of empirical discovery, analytical description, and technological development in an integrative “D3 Methodology.” The phases are bridged with human-guided computational processes suitable for human-in-the-loop design approaches. Optimization of biolibraries, which are sets of standardized biological parts for adaptation into new products, is used as a characteristic design problem for demonstrating the methodology. Results from this test case suggest that biolibraries with synthetic biological components can promote the development of high-performance bio-based products. These new products motivate further scientific studies to characterize designed synthetic biological components, thus illustrating reciprocity among science and design. Successes in implementing each phase suggest the D3 Methodology is a feasible route for bio-based research and development and for driving the scientific inquiries of today toward the novel technologies of tomorrow.

Copyright © 2016 by ASME
Topics: Design
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Fig. 1

The D3 Methodology consisting of a Discover phase with generic steps for experiments and data analysis, a Describe phase with generic steps of modeling and validation, and a Develop phase with generic steps for conceptualization and optimization of new technologies; example inputs/outputs for each phase are presented in the context of myosin motor protein research and development

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Fig. 2

Schematic of a biolibrary with varied myosin designs, biosystem blocks consisting of myosins from the biolibrary, and nanotechnologies constructed from biosystem blocks. Illustrated nanotechnologies from top to bottom include a synthetic muscle, contractile material, and nano-actuator.

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Fig. 3

Automated and manual tracking of filaments propelled by myosins over time. The movement of select filaments is indicated by lines that trace each filament's location across frames. In the t = 0 s frame, all displayed objects are imaged filaments, since there are no tracking lines.

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Fig. 6

Binary strings of biolibraries and biosystem blocks. Darkly shaded boxes represent turned on bits in genes mapped to design inputs.

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Fig. 5

Measured and simulated data of average filament velocity for (a) chicken skeletal muscle myosin and (b) pig cardiac muscle myosin experiments when varied concentrations of alpha-actinin molecules are introduced

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Fig. 4

Agent-based model with (a) rules for simulated molecules and (b) renderings of myosin (one globular end) and alpha-actinin (two globular ends) molecules. Left-facing arrows are positive forces that propel the filament; right-facing arrows are negative forces.

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Fig. 7

Robustness of biolibraries that (a) consist of one of two natural isoforms and (b) up to eight synthetic isoforms




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