what engineers know and how they know it summary by david e. goldberg university of illinois at...
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What Engineers Know and How They Know It
Summary by David E. Goldberg
University of Illinois at Urbana-Champaign
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Text
• Vincenti, W. G. (1990). What engineers know and how they know it: Analytical studies from aeronautical history. Baltimore, MD: Johns Hopkins University Press.
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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.
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Goal of Engineering: Design
• Normal design (by analogy to Kuhn’s normal science).
• Versus radical design.
• Design of artifacts as social activity
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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.
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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.
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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.