Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions.

Mathematical programming model for heat exchanger design through optimization of partial objectives

Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature.

Mathematical modelling of the lower urinary tract

The lower urinary tract is one of the most complex biological systems of the human body as it involved hydrodynamic properties of urine and muscle. Moreover, its complexity is increased to be managed by voluntary and involuntary neural systems. In this paper, a mathematical model of the lower urinary tract it is proposed as a preliminary study to better understand its functioning. Furthermore, another goal of that mathematical model proposal is to provide a basis for developing artificial control systems. Lower urinary tract is comprised of two interacting systems: the mechanical system and the neural regulator. The latter has the function of controlling the mechanical system to perform the voiding process. The results of the tests reproduce experimental data with high degree of accuracy. Also, these results indicate that simulations not only with healthy patients but also of patients with dysfunctions with neurological etiology present urodynamic curves very similar to those obtained in clinical studies.

Robust Solutions of MultiObjective Linear Semi-Infinite Programs under Constraint Data Uncertainty

The multiobjective optimization model studied in this paper deals with simultaneous minimization of finitely many linear functions subject to an arbitrary number of uncertain linear constraints. We first provide a radius of robust feasibility guaranteeing the feasibility of the robust counterpart under affine data parametrization. We then establish dual characterizations of robust solutions of our model that are immunized against data uncertainty by way of characterizing corresponding solutions of robust counterpart of the model. Consequently, we present robust duality theorems relating the value of the robust model with the corresponding value of its dual problem.

Spanish Nursing Students' Practical Experience of Computer Applications in Nursing

This study aimed to determine the level of computer practical experience in a sample of Spanish nursing students. Each student was given a Spanish language questionnaire, modified from an original used previously with medical students at the Medical School of North Carolina University (USA) and also at the Education Unit of Hospital General Universitario del Mar (Spain). The 10-item self-report questionnaire probed for information about practical experience with computers. A total of 126 students made up the sample. The majority were female (80.2%; n=101). The results showed that just over half (57.1%, n=72) of the students had used a computer game (three or more times before), and that only one third (37.3%, n=47) had the experience of using a word processing package. Moreover, other applications and IT-based facilities (e.g. statistical packages, e-mail, databases, CD-ROM searches, programming languages and computer-assisted learning) had never been used by the majority of students. The student nurses' practical experience was less than that reported for medical students in previous studies.

Robust solutions to multi-objective linear programs with uncertain data

In this paper we examine multi-objective linear programming problems in the face of data uncertainty both in the objective function and the constraints. First, we derive a formula for the radius of robust feasibility guaranteeing constraint feasibility for all possible scenarios within a specified uncertainty set under affine data parametrization. We then present numerically tractable optimality conditions for minmax robust weakly efficient solutions, i.e., the weakly efficient solutions of the robust counterpart. We also consider highly robust weakly efficient solutions, i.e., robust feasible solutions which are weakly efficient for any possible instance of the objective matrix within a specified uncertainty set, providing lower bounds for the radius of highly robust efficiency guaranteeing the existence of this type of solutions under affine and rank-1 objective data uncertainty. Finally, we provide numerically tractable optimality conditions for highly robust weakly efficient solutions.

Youth Sport Programs: An Avenue to Foster Positive Youth Development

Concern about the growth in adolescent problem behaviours (e.g. delinquency, drug use) has led to increased interest in positive youth development, and a surge in funding for ‘after school programs.’ We evaluate the potential of youth sport programs to foster positive development, while decreasing the risk of problem behaviours. Literature on the positive and negative outcomes of youth sport is presented. We propose that youth sport programs actively work to assure positive outcomes through developmentally appropriate designs and supportive child–adult (parent/coach) relationships. We also highlight the importance of sport programs built on developmental assets (Benson, 1997 ) and appropriate setting features (National Research Council and Institute of Medicine, 2002 ) in bringing about the five ‘C’s of positive development (competence, confidence, character, connections, and compassion/caring: Lerner et al., 2000 ). An applied sport-programming model, which highlights the important roles of policy-makers, sport organizations, coaches and parents in fostering positive youth development is presented as a starting point for further applied and theoretical research.

Polymorphism in the Spotlight: Studying its Prevalence in Java and Smalltalk

Subtype polymorphism is a cornerstone of object-oriented programming. By hiding variability in behavior behind a uniform interface, polymorphism decouples clients from providers and thus enables genericity, modularity and extensi- bility. At the same time, however, it scatters the implementation of the behavior over multiple classes thus potentially hampering program comprehension. The extent to which polymorphism is used in real programs and the impact of polymorphism on program comprehension are not very well understood. We report on a preliminary study of the prevalence of polymorphism in several hundred open source software systems written in Smalltalk, one of the oldest object-oriented programming languages, and in Java, one of the most widespread ones. Although a large portion of the call sites in these systems are polymorphic, a majority have a small number of potential candidates. Smalltalk uses polymorphism to a much greater extent than Java. We discuss how these findings can be used as input for more detailed studies in program comprehension and for better developer support in the IDE.

Effects of acid precipitation on soil leachate quality : computer calculations /

Mode of access: Internet.

Libraries enhance student learning : a guidebook of innovative library programs for youth /

Mode of access: Internet.

Computer cost models for potable water treatment plants /

Mode of access: Internet.

Cost-benefit, cost-effectiveness research of drug abuse prevention : implications for programming and policy /

Shipping list no.: 99-0004-P.

The general deterrence of driving while intoxicated, volume 1, system analysis and computer-based simulation. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Tools for embedded computing systems software.

"Preprint for a workshop sponsored by NASA Langley Research Center, Hampton, Virginia, and the American Institute of Aeronautics and Astronautics, New York, and held in Hampton, Virginia, November 7-8, 1978."