De La Torre Quintana, Luis F.
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Publication Restricted Modelo de simulación y visualización del proceso de mezclas ultrasónico para la producción de biodiésel(2004) De La Torre Quintana, Luis F.; Portnoy, Arturo; College of Arts and Sciences - Sciences; Bollman, Dorothy; Gooransarab, Haedeh; Department of Mathematics; Orama Exclusa, Lionel R.Biodiesel is an “environmental” and renewable alternative to fuel diesel engines. In the production process of Biodiesel, it is necessary to mix inmiscible oils and alcohols. This production process needs fast, effective and viable methods. Thus, in the search to optimize the process an alternative mixing method has been developed by means of ultrasound, which promises to be faster, and more efficient and viable than traditional methods. This method generates cavities or bubbles that implode generating local ''jets'' that mix. Starting for the study of a single bubble that receives an ultrasonic stimulation, we will be able to find an approximation of the energy released by it and its lifetime, and thus have a model for the bubble. The model that we propose is based on the lattice in R3 space, in which each point is used as reference for the possible appearance of a cavity and depending on the location and the influence of the other bubbles a possible variation in the ultrasonic stimulate that if will receive is calculated. Then the model for a single bubble is used to obtain the lifetime and the energy emitted by the cavity. This will give the moment and the amount of mass that needs to be moved around this. We develop a visual model that allows us to see with clarity which happens during the mixing process. It is hoped that the model obtained will reflect the essence of the process, and will give a virtual laboratory where simulations can be made and design decisions can be taken at a very low cost. This promises to be a very attractive alternative for reactor design.Publication Restricted Scheduling divisible tasks under production or utilization constraints(2009) De La Torre Quintana, Luis F.; Rodríguez Rodríguez, Domingo; College of Engineering; Lu, Kejie; Rodríguez Martínez, Manuel; Seguel, Jaime; Department of Electrical and Computer Engineering; Sharma, Anand D.Several problems in science and engineering admit algorithmic solutions that demand a large amount of computing time. Among these applications are genotype sequencing, gene sequence comparison, protein folding, quantum chemistry, computational uid dynamics, and Earth simulation. In most of these cases, a single computer does not provide enough computing power to satisfy these needs, and therefore, the design of parallel methods is of crucial importance. It has been observe in practice that many of these algorithmic solutions acquire the form of a master-worker algorithm. Due to their availability and low cost, heterogeneous networks of computers are becoming a popular alternative for these implementations. One problem, frequently faced by implementers is how to divide and distribute the parallel segments of computing tasks among the computers. This is the essence of the so-called task scheduling problem. Efficiently managing the computations is a difficult and challenging problem. This efficiency depends on the number of rounds of computation, the sizes of the data chunks sent in a round, and the number and the activation sequence of the participating workers. In this dissertation variants and extensions of ideas related to the scheduling of master-worker tasks on heterogeneous star networks are introduced. Some of these ideas were previously discussed in the form of theoretical frameworks for steadystate scheduling or as a divisible load theory. This dissertation combines some elements of these previous works to construct a new framework, and from it, an efficient algorithm (SCOW) for identifying a deterministic scheduler for clusters of workers. SCOW produces the parameters of a periodic user-level scheduler for a single-program multiple-data implementation of a master-worker parallel solution. SCOW minimizes the job make-span under either maximal production per period, or perfect worker utilization. The eficiency of the scheduler identified by SCOW is demonstrated through comparison with other schedulers, including those derived from the above mentioned theoretical frameworks. As shown in the simulation an actual computer runs, the scheduler identified by SCOW outperform in most cases those produced by the previous frameworks.