Simulação da produção de Paraxileno

O trabalho tem como objectivo a simulação e verificação do funcionamento de 3 colunas de destilação, a T-0303, a T-0306 e a T-0307, integrantes do processo de produção de p-xileno, baseado nos dados relativos ao ano de 2008, existente na refinaria da Galp no Porto. A abordagem consistiu em utilizar o AspenPlus quer para a simulação quer para a optimização, sendo esta última complementada com um planeamento experimental e optimização no Minitab15. O critério de optimização foi estabelecido a partir de uma análise ao processo actual, na qual se averiguou que se poderia, no limite: produzir mais 15,30ton.ano-1 de p-xileno no conjunto de colunas T-0306 e T-0307; remover mais 1,36ton.ano-1 de dessorvente na coluna T-0303 e diminuir a energia necessária para o processo. Da optimização à coluna T-0303, obteve-se uma melhoria de remoção de 0,34ton.ano-1 de dessorvente, e uma diminuição na energia necessária para 333,24.106kWh por ano. Para obter esta optimização houve necessidade de ultrapassar em 109,852kW a potência da bomba P0306A/S e alterou-se a razão de refluxo na base para 46,1. A optimização conjunta das colunas T-0306 e T-0307 apenas possibilita uma melhoria de p-xileno de 3,4ton.ano-1. De uma optimização individual da coluna T-0307, mantendo a coluna T-0306 nas condições actuais, obteve-se uma melhoria na produção de p-xileno de 14,62ton.ano-1. Neste ensaio as potências do condensador E-0314, do reebulidor E-0306 e da bomba P0314A/S excedem, as actuais em, respectivamente, 35,71kW, 35,74kW e 0,12kW. Enquanto para a situação actual o custo de p-xileno equivale a 722,17€.ton-1, para a optimização simultânea da coluna T-0303 e T-0307, é de 723,39€.ton-1 e para a optimização de apenas da coluna T-0307 é de 722,81€.ton-1. Perante um preço de venda actual de pxileno de 749,10€.ton-1 todas as situações são favoráveis. Em suma, é possível uma optimização processual mas o custo por tonelada de pxileno fica superior ao actual.

Electrochemical study of butylate: application to the analysis of water

The electroactivity of butylate (BTL) is studied by cyclic voltammetry (CV) and square wave voltammetry (SWV) at a glassy carbon electrode (GCE) and a hanging mercury drop electrode (HMDE). Britton–Robinson buffer solutions of pH 1.9–11.5 are used as supporting electrolyte. CV voltammograms using GCE show a single anodic peak regarding the oxidation of BTL at +1.7V versus AgCl/ Ag, an irreversible process controlled by diffusion. Using a HMDE, a single cathodic peak is observed, at 1.0V versus AgCl/Ag. The reduction of BTL is irreversible and controlled by adsorption. Mechanism proposals are presented for these redox transformations. Optimisation is carried out univaryingly. Linearity ranges were 0.10–0.50 mmol L-1 and 2.0–9.0 µmolL-1 for anodic and cathodic peaks, respectively. The proposed method is applied to the determination of BTL in waters. Analytical results compare well with those obtained by an HPLC method.

Sensing Cloud Optimization applied to a non-convex constrained economical dispatch

Conferência: 39th Annual Conference of the IEEE Industrial-Electronics-Society (IECON) - NOV 10-14, 2013

Rapid determination of tartaric acid in wines

A flow-spectrophotometric method is proposed for the routine determination of tartaric acid in wines. The reaction between tartaric acid and vanadate in acetic media is carried out in flowing conditions and the subsequent colored complex is monitored at 475 nm. The stability of the complex and the corresponding formation constant are presented. The effect of wavelength and pH was evaluated by batch experiments. The selected conditions were transposed to a flowinjection analytical system. Optimization of several flow parameters such as reactor lengths, flow-rate and injection volume was carried out. Using optimized conditions, a linear behavior was observed up to 1000 µg mL-1 tartaric acid, with a molar extinction coefficient of 450 L mg-1 cm-1 and ± 1 % repeatability. Sample throughput was 25 samples per hour. The flow-spectrophotometric method was satisfactorily applied to the quantification of tartaric acid (TA) in wines from different sources. Its accuracy was confirmed by statistical comparison to the conventional Rebelein procedure and to a certified analytical method carried out in a routine laboratory.

Six thinking hats for electricity markets simulation: adapting meeting tools to agent decision

In almost all industrialized countries, the energy sector has suffered a severe restructuring that originated a greater complexity in market players’ interactions. The complexity that these changes brought made way for the creation of decision support tools that facilitate the study and understanding of these markets. MASCEM – “Multiagent Simulator for Competitive Electricity Markets” arose in this context providing a framework for evaluating new rules, new behaviour, and new participants in deregulated electricity markets. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. ALBidS is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This tool’s goal is to force the thinker to move outside his habitual thinking style. It was developed to be used mainly at meetings in order to “run better meetings, make faster decisions”. This dissertation presents a study about the applicability of the Six Thinking Hats technique in Decision Support Systems, particularly with the multiagent paradigm like the MASCEM simulator. As such this work’s proposal is of a new agent, a meta-learner based on STH technique that organizes several different ALBidS’ strategies and combines the distinct answers into a single one that, expectedly, out-performs any of them.

New insights on integer-programming models for the kidney exchange problem

In recent years several countries have set up policies that allow exchange of kidneys between two or more incompatible patient–donor pairs. These policies lead to what is commonly known as kidney exchange programs. The underlying optimization problems can be formulated as integer programming models. Previously proposed models for kidney exchange programs have exponential numbers of constraints or variables, which makes them fairly difficult to solve when the problem size is large. In this work we propose two compact formulations for the problem, explain how these formulations can be adapted to address some problem variants, and provide results on the dominance of some models over others. Finally we present a systematic comparison between our models and two previously proposed ones via thorough computational analysis. Results show that compact formulations have advantages over non-compact ones when the problem size is large.

Leilões combinados

Mestrado em Controlo de Gestão e dos Negócios

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

A survey in Portuguese X-ray fluoroscopy equipment: dose rates and image quality

X-ray fluoroscopy is essential in both diagnosis and medical intervention, although it may contribute to significant radiation doses to patients that have to be optimised and justified. Therefore, it is crucial to the patient to be exposed to the lowest achievable dose without compromising the image quality. The purpose of this study was to perform an analysis of the quality control measurements, particularly dose rates, contrast and spatial resolution of Portuguese fluoroscopy equipment and also to provide a contribution to the establishment of reference levels for the equipment performance parameters. Measurements carried out between 2007 and 2013 on 143 fluoroscopy equipment distributed by 34 nationwide health units were analysed. The measurements suggest that image quality and dose rates of Portuguese equipment are congruent with other studies, and in general, they are as per the Portuguese law. However, there is still a possibility of improvements intending optimisation at a national level.

Constraint solving over multi-valued logics - application to digital circuits

Due to usage conditions, hazardous environments or intentional causes, physical and virtual systems are subject to faults in their components, which may affect their overall behaviour. In a ‘black-box’ agent modelled by a set of propositional logic rules, in which just a subset of components is externally visible, such faults may only be recognised by examining some output function of the agent. A (fault-free) model of the agent’s system provides the expected output given some input. If the real output differs from that predicted output, then the system is faulty. However, some faults may only become apparent in the system output when appropriate inputs are given. A number of problems regarding both testing and diagnosis thus arise, such as testing a fault, testing the whole system, finding possible faults and differentiating them to locate the correct one. The corresponding optimisation problems of finding solutions that require minimum resources are also very relevant in industry, as is minimal diagnosis. In this dissertation we use a well established set of benchmark circuits to address such diagnostic related problems and propose and develop models with different logics that we formalise and generalise as much as possible. We also prove that all techniques generalise to agents and to multiple faults. The developed multi-valued logics extend the usual Boolean logic (suitable for faultfree models) by encoding values with some dependency (usually on faults). Such logics thus allow modelling an arbitrary number of diagnostic theories. Each problem is subsequently solved with CLP solvers that we implement and discuss, together with a new efficient search technique that we present. We compare our results with other approaches such as SAT (that require substantial duplication of circuits), showing the effectiveness of constraints over multi-valued logics, and also the adequacy of a general set constraint solver (with special inferences over set functions such as cardinality) on other problems. In addition, for an optimisation problem, we integrate local search with a constructive approach (branch-and-bound) using a variety of logics to improve an existing efficient tool based on SAT and ILP.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

An evaluation of SAFIRE’s potential to reduce the dose received by paediatric patients undergoing CT: a narrative review

Introduction: The purpose of this review is to gather and analyse current research publications to evaluate Sinogram-Affirmed Iterative Reconstruction (SAFIRE). The aim of this review is to investigate whether this algorithm is capable of reducing the dose delivered during CT imaging while maintaining image quality. Recent research shows that children have a greater risk per unit dose due to increased radiosensitivity and longer life expectancies, which means it is particularly important to reduce the radiation dose received by children. Discussion: Recent publications suggest that SAFIRE is capable of reducing image noise in CT images, thereby enabling the potential to reduce dose. Some publications suggest a decrease in dose, by up to 64% compared to filtered back projection, can be accomplished without a change in image quality. However, literature suggests that using a higher SAFIRE strength may alter the image texture, creating an overly ‘smoothed’ image that lacks contrast. Some literature reports SAFIRE gives decreased low contrast detectability as well as spatial resolution. Publications tend to agree that SAFIRE strength three is optimal for an acceptable level of visual image quality, but more research is required. The importance of creating a balance between dose reduction and image quality is stressed. In this literature review most of the publications were completed using adults or phantoms, and a distinct lack of literature for paediatric patients is noted. Conclusion: It is necessary to find an optimal way to balance dose reduction and image quality. More research relating to SAFIRE and paediatric patients is required to fully investigate dose reduction potential in this population, for a range of different SAFIRE strengths.

In-situ X-ray diffraction studies during growth of Ni-Ti shape memory alloy films and their complementary ex-situ characterization

Shape Memory Alloy (SMA) Ni-Ti films have attracted much interest as functional and smart materials due to their unique properties. However, there are still important issues unresolved like formation of film texture and its control as well as substrate effects. Thus, the main challenge is not only the control of the microstructure, including stoichiometry and precipitates, but also the identification and control of the preferential orientation since it is a crucial factor in determining the shape memory behaviour. The aim of this PhD thesis is to study the optimisation of the deposition conditions of films of Ni-Ti in order to obtain the material fully crystallized at the end of the deposition, and to establish a clear relationship between the substrates and texture development. In order to achieve this objective, a two-magnetron sputter deposition chamber has been used allowing to heat and to apply a bias voltage to the substrate. It can be mounted into the six-circle diffractometer of the Rossendorf Beamline (ROBL) at the European Synchrotron Radiation Facility (ESRF), Grenoble, France, enabling an in-situ characterization by X-ray diffraction(XRD) of the films during their growth and annealing. The in-situ studies enable us to identify the different steps of the structural evolution during deposition with a set of parameters as well as to evaluate the effect of changing parameters on the structural characteristics of the deposited film. Besides the in-situ studies, other complementary ex-situ characterization techniques such as XRD at a laboratory source, Rutherford backscattering spectroscopy(RBS), Auger electron spectroscopy (AES), cross-sectional transmission electron microscopy (X-TEM), scanning electron microscopy (SEM), and electrical resistivity (ER) measurements during temperature cycling have been used for a fine structural characterization. In this study, mainly naturally and thermally oxidized Si(100) substrates, TiN buffer layers with different thicknesses (i.e. the TiN topmost layer crystallographic orientation is thickness dependent) and MgO(100) single crystals were used as substrates. The chosen experimental procedure led to a controlled composition and preferential orientation of the films. The type of substrate plays an important role for the texture of the sputtered Ni-Ti films and according to the ER results, the distinct crystallographic orientations of the Ni-Ti films influence their phase transformation characteristics.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.