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Background: Professionals who pursue a doctorate after significant post-baccalaureate work experience, a group we refer to as returners, represent an important but understudied group of engineering doctoral students. Returners are well situated to leverage their applied work experiences in their advanced engineering training. Purpose/Hypothesis: We drew on results from the Graduate Student Experiences and Motivations Survey to explore the dimensionality of our scales measuring value and cost constructs. We used these scales, as well as measures of student expectancy of success, to compare returners with direct-pathway students. Design/Method: We surveyed 179 returners and 297 direct-pathway domestic engineering doctoral students. We first conducted Exploratory Factor Analysis on our cost and value measures. We then used both Ordinary Least Squares and Ordinal Regression Model analyses to assess the relationships of various student characteristics and experiences (including returner status) with student expectancy of success and the emergent cost and values factors associated with doctoral study in engineering. Results: Factor analysis revealed three categories of values (interest, attainment, and career utility) that were largely consistent with those in Eccles' expectancy-value framework. A similar analysis identified three categories of costs (balance, financial, and academic) associated with pursuing a PhD. Returners felt significantly less confident in their ability to complete their degrees prior to enrolling and perceived higher levels of all cost types than direct-pathway students. Conclusions: Given the differences between returning and direct-pathway students, it is important to consider how universities might best recruit and retain returners. Tracking returner status could be critical in better supporting these students.

Probabilistic design optimization addresses the presence of uncertainty in design problems. Extensive studies on reliability-based design optimization, i.e., problems with random variables and probabilistic constraints, have focused on improving computational efficiency of estimating values for the probabilistic functions. In the presence of many probabilistic inequality constraints, computational costs can be reduced if probabilistic values are computed only for constraints that are known to be active or likely active. This article presents an extension of monotonicity analysis concepts from deterministic problems to probabilistic ones, based on the fact that several probability metrics are monotonic transformations. These concepts can be used to construct active set strategies that reduce the computational cost associated with handling inequality constraints, similarly to the deterministic case. Such a strategy is presented as part of a sequential linear programming algorithm along with numerical examples. [DOI: 10.1115/1.2202887] Keywords: monotonicity, active set strategy, RBDO, probabilistic design, optimization under uncertainty

Recent environmental legislation, such as the European Union Directive on End-of-Life Vehicles and the Japanese Home Electric Appliances Recycling law, has had a major influence on product design from both an engineering and an economic perspective. This article presents a methodology for studying the effects of automobile fuel efficiency and emission policies on the long-term design decisions of profit-seeking automobile producers competing in an oligopoly market. Mathematical models of engineering performance, consumer demand, and manufacturing costs are developed for a specific market segment, and game theory is utilized to simulate competition among firms to predict design choices of producers at market equilibrium. Several policy scenarios are evaluated for the small car market, including corporate average fuel economy (CAFE) standards, carbon dioxide (C[O.sub.2]) emissions taxes, and diesel technology quotas. The results indicate that leveraging C[O.sub.2] taxes on producers for expected life cycle emissions yields diminishing returns on fuel efficiency improvement per regulatory dollar as the taxes increase, while CAFE standards achieve higher average fuel efficiency per regulatory dollar. Results also indicate that increasing penalties for violation of CAFE standards can result in lower cost to producers and consumers because of the effects of competition, and penalties based on fuel economy or emissions alone may not be sufficient incentive for producers to bring more costly alternative fuel vehicles into the market. The ability to compare regulations and achieve realistic trends suggests that including engineering design and performance considerations in policy analysis can yield useful predictive insight into the impact of government regulations on industry, consumers, and the environment. [DOI: 10.1115/1.1804195] Keywords: Environmental Policy; Optimal Design; Game Theory; Oligopoly; Emissions; CAFE; Discrete Choice Analysis; Econometrics; Logit; Green Engineering

This paper discusses the development of a mechanistic model that describes the rate of flow reduction (i.e., flux decline) for a semi-synthetic metalworking fluid (MWF) during the application of microfiltration for extended MWF reuse and recycling. For the transport of unused semi-synthetic MWF through microfiltration membranes ranging in pore size from 0.2 to 5.0 micrometers, Environmental Scanning Electron Microscopy (ESEM) and Confocal Scanning Laser Microscopy (CSLM) are used to identify three interdependent and sequential mechanisms of flux decline: pore constriction, pore blockage, and surface film retardation. These mechanisms are modeled together mathematically as a four-parameter model that quantitatively describes flux decline versus time for semi-synthetic MWF as a function of membrane pore size and transmembrane pressure. The four parameters of the model are the rate constants for pore constriction and pore blocking, the steady-state effective internal pore constriction, and the specific surface film resistance. Independent experimental observations confirmed both the existence of the three stages of flux decline, and the physical interpretation of the model parameters across the pore size range of polycarbonate membranes investigated. It was also found that the mechanistic model fit experimental flux data over time with low error and that the magnitudes and trends of the model parameters closely fit direct microscopic observations and expected behavior of fouled membrane surfaces. Consequently, the mechanistic model enables quantitative modeling of microscopic phenomena at the membrane surface using only macroscale flux observations. This will enable a better understanding of the relationship between MWF formulation and membrane transport in novel MWF recycling applications. [DOI: 10.111511.1763187]

Microfiltration is capable of reducing health hazards and environmental pollution associated with metalworking fluids (MWFs) by enabling recycling and microbial removal. This paper investigates chemical characteristics of MWFs that can lead to flux decline during microfiltration using aluminum oxide membranes by studying the family of polyoxyalkylene diblock copolymers comprised of ethylene oxide and propylene oxide. These copolymers are commonly used as lubricant additives in metalworking fluids and serve as a model for beginning to understand the relationship between metalworking fluid formulation and microfiltration flux. It is found that increasing the hydrophobic content of the copolymers can lead to reduced flux. Anionic modification and increasing molecular weight of the copolymers can also lead to reduced flux. Insufficient cleaning of anionic copolymers from the membrane leads to pH-dependent flux of deionized water during subsequent filtration. The pH-dependence of flux arises due to swelling caused by electrostatic repulsions between the aluminum oxide surface and anionic copolymers that remain adsorbed to the surface of the membrane. This swelling serves to resist permeate flow above the isoelectric point of aluminum oxide. This phenomenon is observed directly using Field Emission Environmental Scanning Electron Microscopy (FE-ESEM). [DOI: 10.1115/1.1392993]