Several studies have demonstrated that point-of-choice prompts modestly increase stair use (i.e., incidental physical activity) in many public places, but evidence of effectiveness in airport settings is weak. Furthermore, evaluating the effects of past physical activity on stair use and on point-of-choice prompts to increase stair use is lacking. The purpose of this study was to evaluate the influence of sign prompts and participant factors including past physical activity on stair ascent in an airport setting. We used a quasi-experimental design, systematically introducing and removing sign prompts daily across 22 days at the San Diego International Airport. Intercept interviewers recruited stair and escalator ascenders (N=1091; 33.0% interview refusal rate) of the only stairs/escalators providing access to Terminal 1 from the parking lot. A 13-item questionnaire about demographics, physical activity, health behavior, and contextual factors provided data not available in nearly all other stair use studies. We examined the effects of signs and self-reported covariates using multivariable logistic regression analyses, and tested whether physical activity and other covariates modified the intervention effect. Adjusting for all significant covariates, prompts increased the odds of stair use (odds ratio=3.67; p<.001). Past participation in vigorous physical activity increased the odds of stair use by 1.62 (p=0.001). None of the covariates moderated the intervention effect. In conclusion, vigorous physical activity and correlates of physical activity were related to stair use in expected directions, but did not modify the effect of the intervention. This indicates that the effects of point-of-choice prompts are independent of past physical activity, making them effective interventions for active adults and the higher risk population of inactive adults. Signs can prompt stair use in an airport setting and might be employed at most public stairs to increase rates of incidental physical activity and contribute to overall improvements in population health.

As interest in the modularization and intensification of chemical processes continues to grow, more research must be directed towards the modeling and analysis of these units. Intensified process units such as polymer membrane reactors pose unique challenges pertaining to design and operation that have not been fully addressed. In this work, a novel approach for modeling membrane reactors is developed in AVEVA’s Simcentral Simulation Platform. The produced model allows for the simulation of polymer membrane reactors under nonisothermal and countercurrent operation for the first time. This model is then applied to generate an operability mapping to study how operating points translate to overall unit performance. This work demonstrates how operability analyses can be used to identify areas of improvement in membrane reactor design, other than just using operability mapping studies to identify optimal input conditions. The performed analysis enables the quantification of the Pareto frontier that ultimately leads to design improvements that both increase overall performance and decreases the cost of the unit.

No abstract

This work aims to address the design and control challenges caused by the integration of phenomena and the loss of degrees of freedom (DOF) that occur in the intensification of membrane reactor units. First, a novel approach to designing membrane reactor units is proposed. This approach consists of designing smaller modules based on specific phenomena such as heat exchange, reactions, and mass transport and combining them in series to produce the final modular membrane-based unit. This approach to designing membrane reactors is then assessed using a process operability analysis for the first time to maximize the operability index, as a way of quantifying the operational performance of intensified processes. This work demonstrates that by designing membrane reactors in this way, the operability of the original membrane reactor design can be significantly improved, translating to an improvement in achievability for a potential control structure implementation.

The growing interest in intensified process units that improve efficiency by combining several phenomena into one unit, has led to a loss in degrees of freedom when addressing the control scheme of these units. Previous work demonstrated that a novel module-based design approach to membrane reactors could improve the operability index of membrane reactor systems. This approach sought to decouple the phenomena to regain some degrees of freedom for the control system. However, the computational time to determine such an optimal module design made this class of design problems intractable to solve in a reasonable amount of time. This work proposes a set of design heuristics for a new module-based design approach for membrane reactors. These heuristics are used in combination with a genetic algorithm formulation to produce a novel, two-staged algorithm for the design and control of membrane reactor systems. This algorithm is developed in Python and uses rigorous membrane reactor models built in AVEVA Process Simulation. The proposed algorithm solves the original non-polynomial (NP) complexity problem in polynomial time (P), while still being able to find the optimal designs discovered in previous work through exhaustive methods.