An Exploration of Risk, Information, and Model Validity in Engineering Design

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The research activities to be conducted for this project focus on investigating principal questions that must be resolved if Decision Based Design (DBD) is to gain currency within the community of design researchers. DBD is a controversial conjecture that asserts that engineering design is a decision making process and thus can be framed within well-established tenets of decision theory. This conjecture is founded on the premise that the practice of engineering design is directly analogous to rational economic behavior. As yet, however, DBD is not a viable normative theory in that its axiomatic foundation has not lead to the development of subsequent analytical methods. While researchers can pose numerous questions regarding designing under uncertainty, this project will focus first on examining whether it is possible, and subsequently practical, to map spaces of design alternatives into a domain that satisfies the axioms of DBD. To answer the question, tasks will include the investigation of constructing probability spaces that capture design alternatives (both design parameters and design configurations). This question must be addressed to assess model validity; as the research team holds that validity is more than simply satisfying axioms of rationality. The expected impact of the results attained from this effort will be to establish a valid logical connection between constructs of a basic probability space associated with engineering models and the expected utility theorem. Such a result will offer direct analytical characterization of elements of uncertainty within a valid engineering design space. The researchers will also explore a collaborative research activity with a group of faculty at the University of Texas at Austin. This collaboration will investigate possible connections between this work in probability modeling of design spaces with the characterization of uncertainties arising in the empirical similitude research being conducted at the University of Texas.