What Engineers Know and How They Know It

1
What Engineers Know and How They Know It

• Summary by David E. Goldberg
• University of Illinois at Urbana-Champaign
• deg_at_uiuc.edu

2
Text

• Vincenti, W. G. (1990). What engineers know and
  how they know it Analytical studies from
  aeronautical history. Baltimore, MD Johns
  Hopkins University Press.

3
Engineering is Just Applied Science

• 1922 Aeroplanes are not designed by science,
  but by art in spite of some pretence and humbug
  to the contrary.
• Historians of technology have split off from
  historians of science
• View science and technology as two categories,
  related but distinguishable.

4
Goal of Engineering Design

• Normal design (by analogy to Kuhns normal
  science).
• Versus radical design.
• Design of artifacts as social activity

5
Design and Growth of Knowledge

• B-24 airfoil design
• Planform and airfoil
• Consolidated Aircraft Corp.
• Inventor David R. Davis.
• Adopted and credited with B-24 long range.
• Not in the main stream of airfoil thought.

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Air Foil Evolution of Knowledge

• Separation of planform and section.
• Geometry first
• Laminar v. turbulent boundary layer
• Prolong laminar BL
• Pressure distribution first
• Analytical calculations based on conformal
  mapping.

7
Drivers of Knowledge

• Decrease uncertainty
• Increased performance presumptive anomaly, when
  science indicates better result is possible
• Functional failure subjected to ever greater
  demands, applied in new situations.
• Process Selection and variation.

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Establishment of Design Requirements

• Problem Flying quality specification.
• Longitudinal stability
• What stability and control characteristics
  needed?
• How proportion aircraft to obtain?
• Early schools of thought
• Chauffeurs vs. airmen
• Inherent stability vs. active control.

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Early Aircraft

• Sopwith Camel, Curtis JN-4, Thomas Morse S-4C,
  longitudinally unstable.
• Qualitative description of early aircraft
  followed in end by detailed specs.

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7 Elements

• Familiarization with artifact and recognition of
  problem.
• ID of basic variables derivation of concepts
  and criteria.
• Development of instruments and technique.
• Growth of opinion regarding desirable
  qualitities.
• Development of practical scheme for research.
• Measurement of characteristics for cross section
  of artifacts.
• Assessment of results.

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Theoretical Tool for Design

• Example Control volume models.
• Bernoulli as forerunner.
• Karman Prandtl Modern usage.
• Useful to engineers not physicists.
• Creation of artifacts dictates different choice
  of tools.

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Engineering Science v. Science

• Similarities
• Conform to same natural laws.
• Diffuse by same mechanisms.
• Cumulative facts build on facts.
• Differences
• ES create artifacts. S understand nature
• Skolimowski technological progress pursuit of
  effectiveness in producing objects of given kind.

13
Data for Design

• Case Durand propeller tests at Stanford,
  1916-26.
• History
• Smeaton Waterwheel studies of 1759, systematic
  experiment scale models.
• Froude testing of ship hulls 1868-1874.
• Reynolds 1883.
• Dimensional analysis Fourier (early 1800s),
  Rayleigh (late 1800s)

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Parameter Variation

• Via experimental or theoretical means.
• Via experimental means is not peculiar to
  engineering.
• Immediate interest in data for design, longer
  term interest in establishing a theory.
• Produce data in absence of theory.
• Indispensable for creation of such data.
• Absence of theory a number of causes.
• Scale models not necessary.
• Optimization often part of the experimentation.

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Design and Production

• Case Invention of flush riveting.
• Innovation driven by aerodynamics.
• Caused changes in production.
• Bigger gains first (retractable gear, flaps).
• 160,000 to 400,000 rivets per plane.

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Dimpled Riveting

• Science played no role in the story.
• Each company pursued own program.
• Different types of knowledge
• Explicit
• Tacit

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Problems Within Technology

• Internal logic of technology
• Physical laws
• Practical requirements dictate solution of
  problems.
• Internal needs of design e.g. quality specs.
  design theory.
• Need for decreased uncertainty.

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Categorization of Engineering Design Knowledge

• Fundamental design concepts.
• Criteria and specifications.
• Theoretical tools.
• Quantitative data.
• Practical considerations.
• Design instrumentalities.

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Knowledge Generating Activities

• Transfer from science.
• Invention
• Theoretical engineering research
• Experimental engineering research
• Design practice
• Production
• Direct trial

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Evolutionary Model of Knowledge Growth

• Variation-Selection
• Consistent with GAs
• Not as detailed in its mechanisms.