965 resultados para OPTIMIZATION PROCESS
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It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation.
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As operações de separação por adsorção têm vindo a ganhar importância nos últimos anos, especialmente com o desenvolvimento de técnicas de simulação de leitos móveis em colunas, tal como a cromatografia de Leito Móvel Simulado (Simulated Moving Bed, SMB). Esta tecnologia foi desenvolvida no início dos anos 60 como método alternativo ao processo de Leito Móvel Verdadeiro (True Moving Bed, TMB), de modo a resolver vários dos problemas associados ao movimento da fase sólida, usuais nestes métodos de separação cromatográficos de contracorrente. A tecnologia de SMB tem sido amplamente utilizada em escala industrial principalmente nas indústrias petroquímica e de transformação de açúcares e, mais recentemente, na indústria farmacêutica e de química fina. Nas últimas décadas, o crescente interesse na tecnologia de SMB, fruto do alto rendimento e eficiente consumo de solvente, levou à formulação de diferentes modos de operação, ditos não convencionais, que conseguem unidades mais flexíveis, capazes de aumentar o desempenho de separação e alargar ainda mais a gama de aplicação da tecnologia. Um dos exemplos mais estudados e implementados é o caso do processo Varicol, no qual se procede a um movimento assíncrono de portas. Neste âmbito, o presente trabalho foca-se na simulação, análise e avaliação da tecnologia de SMB para dois casos de separação distintos: a separação de uma mistura de frutose-glucose e a separação de uma mistura racémica de pindolol. Para ambos os casos foram considerados e comparados dois modos de operação da unidade de SMB: o modo convencional e o modo Varicol. Desta forma, foi realizada a implementação e simulação de ambos os casos de separação no simulador de processos Aspen Chromatography, mediante a utilização de duas unidades de SMB distintas (SMB convencional e SMB Varicol). Para a separação da mistura frutose-glucose, no quediz respeito à modelização da unidade de SMB convencional, foram utilizadas duas abordagens: a de um leito móvel verdadeiro (modelo TMB) e a de um leito móvel simulado real (modelo SMB). Para a separação da mistura racémica de pindolol foi considerada apenas a modelização pelo modelo SMB. No caso da separação da mistura frutose-glucose, procedeu-se ainda à otimização de ambas as unidades de SMB convencional e Varicol, com o intuito do aumento das suas produtividades. A otimização foi realizada mediante a aplicação de um procedimento de planeamento experimental, onde as experiências foram planeadas, conduzidas e posteriormente analisadas através da análise de variância (ANOVA). A análise estatística permitiu selecionar os níveis dos fatores de controlo de modo a obter melhores resultados para ambas as unidades de SMB.
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Trabalho Final de Mestrado para obtenção do grau de Mestre Em Engenharia Química e Biológica Ramo de processos Químicos
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This paper proposes a stochastic mixed-integer linear approach to deal with a short-term unit commitment problem with uncertainty on a deregulated electricity market that includes day-ahead bidding and bilateral contracts. The proposed approach considers the typically operation constraints on the thermal units and a spinning reserve. The uncertainty is due to the electricity prices, which are modeled by a scenario set, allowing an acceptable computation. Moreover, emission allowances are considered in a manner to allow for the consideration of environmental constraints. A case study to illustrate the usefulness of the proposed approach is presented and an assessment of the cost for the spinning reserve is obtained by a comparison between the situation with and without spinning reserve.
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An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.
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In distributed soft real-time systems, maximizing the aggregate quality-of-service (QoS) is a typical system-wide goal, and addressing the problem through distributed optimization is challenging. Subtasks are subject to unpredictable failures in many practical environments, and this makes the problem much harder. In this paper, we present a robust optimization framework for maximizing the aggregate QoS in the presence of random failures. We introduce the notion of K-failure to bound the effect of random failures on schedulability. Using this notion we define the concept of K-robustness that quantifies the degree of robustness on QoS guarantee in a probabilistic sense. The parameter K helps to tradeoff achievable QoS versus robustness. The proposed robust framework produces optimal solutions through distributed computations on the basis of Lagrangian duality, and we present some implementation techniques. Our simulation results show that the proposed framework can probabilistically guarantee sub-optimal QoS which remains feasible even in the presence of random failures.
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The foresight and scenario building methods can be an interesting reference for social sciences, especially in terms of innovative methods for labour process analysis. A scenario – as a central concept for the prospective analysis – can be considered as a rich and detailed portrait of a plausible future world. It can be a useful tool for policy-makers to grasp problems clearly and comprehensively, and to better pinpoint challenges as well as opportunities in an overall framework. The features of the foresight methods are being used in some labour policy making experiences. Case studies developed in Portugal will be presented, and some conclusions will be drawn in order to organise a set of principles for foresight analysis applied to the European project WORKS on the work organisation re-structuring in the knowledge society, and on the work design methods for new management structures of virtual organisations.
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The discovery of X-rays was undoubtedly one of the greatest stimulus for improving the efficiency in the provision of healthcare services. The ability to view, non-invasively, inside the human body has greatly facilitated the work of professionals in diagnosis of diseases. The exclusive focus on image quality (IQ), without understanding how they are obtained, affect negatively the efficiency in diagnostic radiology. The equilibrium between the benefits and the risks are often forgotten. It is necessary to adopt optimization strategies to maximize the benefits (image quality) and minimize risk (dose to the patient) in radiological facilities. In radiology, the implementation of optimization strategies involves an understanding of images acquisition process. When a radiographer adopts a certain value of a parameter (tube potential [kVp], tube current-exposure time product [mAs] or additional filtration), it is essential to know its meaning and impact of their variation in dose and image quality. Without this, any optimization strategy will be a failure. Worldwide, data show that use of x-rays has been increasingly frequent. In Cabo Verde, we note an effort by healthcare institutions (e.g. Ministry of Health) in equipping radiological facilities and the recent installation of a telemedicine system requires purchase of new radiological equipment. In addition, the transition from screen-films to digital systems is characterized by a raise in patient exposure. Given that this transition is slower in less developed countries, as is the case of Cabo Verde, the need to adopt optimization strategies becomes increasingly necessary. This study was conducted as an attempt to answer that need. Although this work is about objective evaluation of image quality, and in medical practice the evaluation is usually subjective (visual evaluation of images by radiographer / radiologist), studies reported a correlation between these two types of evaluation (objective and subjective) [5-7] which accredits for conducting such studies. The purpose of this study is to evaluate the effect of exposure parameters (kVp and mAs) when using additional Cooper (Cu) filtration in dose and image quality in a Computed Radiography system.
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The foot and the ankle are small structures commonly affected by disorders, and their complex anatomy represent significant diagnostic challenges. SPECT/CT Image fusion can provide missing anatomical and bone structure information to functional imaging, which is particularly useful to increase diagnosis certainty of bone pathology. However, due to SPECT acquisition duration, patient’s involuntary movements may lead to misalignment between SPECT and CT images. Patient motion can be reduced using a dedicated patient support. We aimed at designing an ankle and foot immobilizing device and measuring its efficacy at improving image fusion. Methods: We enrolled 20 patients undergoing distal lower-limb SPECT/CT of the ankle and the foot with and without a foot holder. The misalignment between SPECT and CT images was computed by manually measuring 14 fiducial markers chosen among anatomical landmarks also visible on bone scintigraphy. Analysis of variance was performed for statistical analysis. Results: The obtained absolute average difference without and with support was 5.1±5.2 mm (mean±SD) and 3.1±2.7 mm, respectively, which is significant (p<0.001). Conclusion: The introduction of the foot holder significantly decreases misalignment between SPECT and CT images, which may have clinical influence in the precise localization of foot and ankle pathology.
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The aim of this paper is to evaluate the influence of the crushing process used to obtain recycled concrete aggregates on the performance of concrete made with those aggregates. Two crushing methods were considered: primary crushing, using a jaw crusher, and primary plus secondary crushing (PSC), using a jaw crusher followed by a hammer mill. Besides natural aggregates (NA), these two processes were also used to crush three types of concrete made in laboratory (L20, L45 e L65) and three more others from the precast industry (P20, P45 e P65). The coarse natural aggregates were totally replaced by coarse recycled concrete aggregates. The recycled aggregates concrete mixes were compared with reference concrete mixes made using only NA, and the following properties related to the mechanical and durability performance were tested: compressive strength; splitting tensile strength; modulus of elasticity; carbonation resistance; chloride penetration resistance; water absorption by capillarity; water absorption by immersion; and shrinkage. The results show that the PSC process leads to better performances, especially in the durability properties. © 2014 RILEM
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Mestrado Integrado em Engenharia Química e Bioquímica
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Waste oil recycling companies play a very important role in our society. Competition among companies is tough and process optimization is essential for survival. By equipping oil containers with a level monitoring system that periodically reports the level and alerts when it reaches the preset threshold, the oil recycling companies are able to streamline the oil collection process and, thus, reduce the operation costs while maintaining the quality of service. This paper describes the development of this level monitoring system by a team of four students from different engineering backgrounds and nationalities. The team conducted a study of the state of the art, draw marketing and sustainable development plans and, finally, designed and implemented a prototype that continuously measures the container content level and sends an alert message as soon as it reaches the preset capacity.
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With the current complexity of communication protocols, implementing its layers totally in the kernel of the operating system is too cumbersome, and it does not allow use of the capabilities only available in user space processes. However, building protocols as user space processes must not impair the responsiveness of the communication. Therefore, in this paper we present a layer of a communication protocol, which, due to its complexity, was implemented in a user space process. Lower layers of the protocol are, for responsiveness issues, implemented in the kernel. This protocol was developed to support large-scale power-line communication (PLC) with timing requirements.
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Penalty and Barrier methods are normally used to solve Nonlinear Optimization Problems constrained problems. The problems appear in areas such as engineering and are often characterised by the fact that involved functions (objective and constraints) are non-smooth and/or their derivatives are not know. This means that optimization methods based on derivatives cannot net used. A Java based API was implemented, including only derivative-free optimizationmethods, to solve both constrained and unconstrained problems, which includes Penalty and Barriers methods. In this work a new penalty function, based on Fuzzy Logic, is presented. This function imposes a progressive penalization to solutions that violate the constraints. This means that the function imposes a low penalization when the violation of the constraints is low and a heavy penalisation when the violation is high. The value of the penalization is not known in beforehand, it is the outcome of a fuzzy inference engine. Numerical results comparing the proposed function with two of the classic penalty/barrier functions are presented. Regarding the presented results one can conclude that the prosed penalty function besides being very robust also exhibits a very good performance.
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Search Optimization methods are needed to solve optimization problems where the objective function and/or constraints functions might be non differentiable, non convex or might not be possible to determine its analytical expressions either due to its complexity or its cost (monetary, computational, time,...). Many optimization problems in engineering and other fields have these characteristics, because functions values can result from experimental or simulation processes, can be modelled by functions with complex expressions or by noise functions and it is impossible or very difficult to calculate their derivatives. Direct Search Optimization methods only use function values and do not need any derivatives or approximations of them. In this work we present a Java API that including several methods and algorithms, that do not use derivatives, to solve constrained and unconstrained optimization problems. Traditional API access, by installing it on the developer and/or user computer, and remote API access to it, using Web Services, are also presented. Remote access to the API has the advantage of always allow the access to the latest version of the API. For users that simply want to have a tool to solve Nonlinear Optimization Problems and do not want to integrate these methods in applications, also two applications were developed. One is a standalone Java application and the other a Web-based application, both using the developed API.