Evaluation of optimisation techniques and control variable formulations for a batch cooling crystallization process

The mathematical optimisation of a batch cooling crystallization process is considered in this work. The objective is to minimize the standard deviation of the final crystal size distribution (CSD), which is an important feature in many industrial processes. The results with the problem written as a nonlinear programming and solved with the successive quadratic programming (SQP) coupled with the discretization of the control variable are compared with those obtained when SQP coupled with the parameterisation of the control variable is applied. Also it is proposed the implementation of the genetic algorithm (GA) coupled with parameterisation of the control variable. Extensive evaluations show that the SQP method is sensitive both to the parameterisation formulation and to the initial estimate. The solution with GA provided the control variable profile that leads to the minimum standard deviation of the final CSD. Nevertheless, it is a very time-consuming technique, which hampers its utilization in real time applications. However, its feature of global searching suggests its suitability in solving offline problems, in order to provide initial setup profiles. Bearing this in mind, it is proposed an algorithm which allows for the implementation of GA solution in a real time fashion, taking advantage of its robustness to find out the optimal solution.     

Off-line optimization and control for real time integration of a three-phase hydrogenation catalytic reactor

In order to develop and test the integration procedure, in this paper a real time process integration involving the optimization and control of the process is presented, in this case, with the two-layer approach. The used optimization algorithms were Levenberg–Marquardt and SQP that solve a non-linear least square problem subject to bounds on the variables. The two-layer approach is a hierarchical control structure where an optimization layer calculates the set points and manipulated variables to the advanced controller, which is based on the dynamic matrix control with constraints (QDMC). The non-isothermal dynamic model of the three-phase slurry catalytic reactor with appropriate solution procedure was utilized in this work (Vasco de Toledo, E. C., Santana, P. L., Maciel, M. R. W., & Maciel Filho, R. (2001). Dynamic modeling of a three-phase catalytic slurry reactor. Chemical Engineering Science, 56, 6055–6061). The model consists on mass and heat balance equations for the catalyst particles as well as for the bulk phases of gas and liquid. The model was used to describe the dynamic behavior of hydrogenation reaction of o-cresol to obtain 2-methil-cyclohexanol, in the presence of a catalyst Ni/SiO₂.     

The "Heart Area" of Juan Canalejo Hospital Complex. A new approach to clinical management

The present work describes the process by which the pilot project of clinical management of the Hospital Complex Juan Canalejo, designated as "Heart Area", was implemented. In the first section, the needs and reasons that led to the undertaking of this project are explained. The project's objectives and operative strategies are listed. In the Material and Methods section, three basic aspects of the "Heart Area" are described: selection criteria of the "Area", its structure and function, and its foundation and development. In the Results section, we compare the activity undertaken in the "Area" to the situation present prior to its implementation, in relation to quality and costs. Finally, in the Conclusions, we comment on the important implications that our project can have within the Hospital Complex Juan Canalejo as well as in the health care field in general.     

A semi-automatic strategy for achieving learning content and practice repurposing

The development of instructional content using Information Technologies is an expensive, time-consuming and complex process that requires new methodologies. It was in this context that the concept of Learning Objects (LOs) was proposed in order to promote reuse. However, this goal is not yet fully attained and new contributions to increase reuse are still welcome. Besides, if content is conveyed in LOs that are easier to reuse, they must be combined and sequenced in order to build more elaborated and complex content. This paper presents a strategy to deal with these problems based on the definition of small LOs here called Component Objects (COs). These COs are structured and combined according to a conceptual metamodel, which is the basis for the definition of conceptual schemas representing the existing material, including not only content but also practice. This strategy for searching, extracting, and sequencing COs, supports a teacher to better control the implementation of complex content, reducing errors in the authoring process. This approach includes a specification language and an algorithm for semi-automatic sequencing learning content and practice. Finally, a case study that shows the proposed approach and some results of using the algorithm are presented.     

Constructive learning neural network applied to identification and control of a fuel-ethanol fermentation process

In the present work, a constructive learning algorithm was employed to design a near-optimal one-hidden layer neural network structure that best approximates the dynamic behavior of a bioprocess. The method determines not only a proper number of hidden neurons but also the particular shape of the activation function for each node. Here, the projection pursuit technique was applied in association with the optimization of the solvability condition, giving rise to a more efficient and accurate computational learning algorithm. As each activation function of a hidden neuron is defined according to the peculiarities of each approximation problem, better rates of convergence are achieved, guiding to parsimonious neural network architectures. The proposed constructive learning algorithm was successfully applied to identify a MIMO bioprocess, providing a multivariable model that was able to describe the complex process dynamics, even in long-range horizon predictions. The resulting identification model was considered as part of a model-based predictive control strategy, producing high-quality performance in closed-loop experiments.     

Morphology and intersections of crazes in polystyrene films

Craze network with interconnecting crazes was produced in thin (~60nm) polystyrene films by using a spherical stretching method. For 30% and 45% radial strain, the average mesh size, defined as the square root of average non-crazed areas enclosed by crazes, decreased from about 28m to 4.6 and 2.7m, respectively, as the molecular weight increased from 46 900 to 1 350 000. At a molecular weight of about 10⁶, the interactions between crazes became evident by the split and change of directions at the end of their propagation. Two types of intersection appeared to exist in parallel. The first type showed void formation at the intersections with no apparent fibril displacement effect. The second type showed that the fibrils at the intersection of two perpendicular crazes reoriented to a new direction which seemed to be determined by the relative displacements of the two crazes at the intersections. This observation suggests that the craze fibrils can be displaced and further stretched by a second crazing process.     

Effect of cooling rate on Ti–Cu eutectoid alloy microstructure

Titanium alloys present a combination of properties that makes them suitable materials for various medical applications, and there is special interest in Ti–Cu alloys for the fabrication of dental prostheses. The addition of Cu to Ti lowers the melting point of the alloy, as well as leading to the development of desirable mechanical properties. In this study a eutectoid alloy was prepared and heat treated, then cooled at various cooling rates. The eutectoid structure (α + Ti₂Cu) was observed for all cooling rates used, and evidence of α′ martensite was found for cooling rate higher than 9 °C s^–1. Lower cooling rates resulted in higher modulus values. This was attributed to the volume fraction of the α and Ti₂Cu phases. Higher cooling rates produced structures with lower modulus values and greater hardness, a result attributed mainly to the development of a martensitic structure.