Inversão de funções do plano no plano aplicada ao cálculo de azeótropos

Azeotropia é um fenômeno termodinâmico onde um líquido em ebulição produz um vapor com composição idêntica. Esta situação é um desafio para a Engenharia de Separação, já que os processos de destilação exploram as diferenças entre as volatilidades relativas e, portanto, um azeótropo pode ser uma barreira para a separação. Em misturas binárias, o cálculo da azeotropia é caracterizado por um sistema não-linear do tipo 2 × 2. Um interessante e raro caso é o denominado azeotropia dupla, que pode ser verificado quando este sistema não-linear tem duas soluções, correspondendo a dois azeótropos distintos. Diferentes métodos tem sido utilizados na resolução de problemas desta natureza, como métodos estocásticos de otimização e as técnicas intervalares (do tipo Newton intervalar/bisseção generalizada). Nesta tese apresentamos a formulação do problema de azeotropia dupla e uma nova e robusta abordagem para a resolução dos sistemas não-lineares do tipo 2 × 2, que é a inversão de funções do plano no plano (MALTA; SALDANHA; TOMEI, 1996). No método proposto, as soluções são obtidas através de um conjunto de ações: obtenção de curvas críticas e de pré-imagens de pontos arbritários, inversão da função e por fim, as soluções esperadas para o problema de azeotropia. Esta metodologia foi desenvolvida para resolver sistemas não-lineares do tipo 2 × 2, tendo como objetivo dar uma visão global da função que modela o fenômeno em questão, além, é claro, de gerar as soluções esperadas. Serão apresentados resultados numéricos para o cálculo dos azeótropos no sistema benzeno + hexafluorobenzeno a baixas pressões por este método de inversão. Como ferramentas auxiliares, serão também apresentados aspectos numéricos usando aproximações clássicas, tais como métodos de Newton com técnicas de globalização e o algorítmo de otimização não-linear C-GRASP, para efeito de comparação.

Modeling the effect of snow on seasonal runoff within the Truckee River drainage basin

EXTRACT (SEE PDF FOR FULL ABSTRACT): We estimate monthly runoff for a 2-dimensional solution domain containing those areas tributary to Pyramid Lake, Nevada (the Truckee River drainage basin) at a 1-kilometer grid cell spacing. ... To calculate the effect of snow on the hydrologic system, we perform two experiments. In the first we assume that all precipitation falls as rain; in the second we assume that some precipitation falls as snow, thus available water is a combination of rain and snowmelt. We find that considering the effect of snow results in a more accurate representation of mean monthly flow rates, in particular the peak flow during the melt season in the Sierra Nevada. These preliminary results indicate that a relatively simple snow model can improve the representation of Truckee River basin hydrology, significantly reducing errors in modeled seasonal runoff.

Pipeline uplift response in thawed sandy backfills: Preliminary findings

Offshore and onshore buried pipelines under high operating temperature and pressures may lead to upheaval buckling (UHB) if sufficient soil cover is not present to prevent the upward movement of the pipeline. In regions where seasonal changes involve ground soil undergoing freezing-thawing cycles, the uplift resistance from soil cover may be minimum when the soil is undergoing thawing. This paper presents the results from 2 directly-comparable minidrum centrifuge tests conducted at the Schofield Centre, University of Cambridge, to investigate the difference in uplift resistance responses between fully-saturated and thawed sandy backfill conditions. Both tests were conducted drained at 30g using an 8.6 mm diameter aluminium model pipe, corresponding to a prototype pipe diameter of 258 mm. The soil cover/pipe diameter ratio, H/D, was kept at 1. Fraction E fine silica sand was used as the backfill. Preliminary experimental results indicated that the ultimate uplift resistance of a thawing sand backfill to be lower than that of a fully saturated sand backfill. This suggests that in regions where backfill soil undergoes freeze-thaw cycles, the thawing backfill may be more critical than fully saturated backfill for uplift resistance. The 2-dimensional displacement field during the experiment was accurately measured and analysed using the Particle Image Velocimetry technique. Copyright © 2011 by the International Society of Offshore and Polar Engineers (ISOPE).

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Enticing general engineering undergrads into signal processing with Photo-Editing and image search

The University of Cambridge is unusual in that its Department of Engineering is a single department which covers virtually all branches of engineering under one roof. In their first two years of study, our undergrads study the full breadth of engineering topics and then have to choose a specialization area for the final two years of study. Here we describe part of a course, given towards the end of their second year, which is designed to entice these students to specialize in signal processing and information engineering topics for years 3 and 4. The course is based around a photo editor and an image search application, and it requires no prior knowledge of the z-transform or of 2-dimensional signal processing. It does assume some knowledge of 1-D convolution and basic Fourier methods and some prior exposure to Matlab. The subject of this paper, the photo editor, is written in standard Matlab m-files which are fully visible to the students and help them to see how specific algorithms are implemented in detail. © 2011 IEEE.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Eliminating discharge imbalances in predicting shallow water flows with shocks

The shallow water equations are widely used in modelling environmental flows. Being a hyperbolic system of differential equations, they admit shocks that represent hydraulic jumps and bores. Although the water surface can be solved satisfactorily with the modern shock-capturing schemes, the predicted flow rate often suffers from imbalances where shocks occur, eg the mass conservation is violated by failing to maintain a constant discharge rate at every cross-section in a steady open channel flow. A total-variation-diminishing Lax-Wendroff scheme is developed, and used to demonstrate how to achieve an exact flux balance. The performance of the proposed methods is inspected through some test cases, which include 1- and 2-dimensional, flat and irregular bed scenarios. The proposed methods are shown to preserve the mass exactly, and can be easily extended to other shock-capturing models.

Ultrafast lasers mode-locked by nanotubes and graphene

Ultrafast lasers play an increasingly important role in many applications. Nanotubes and graphene have emerged as promising novel saturable absorbers for passive mode-locking. Here, we review recent progress on the exploitation of these two carbon nanomaterials in ultrafast photonics. © 2012 Elsevier B.V. All rights reserved.

500 fs wideband tunable fiber laser mode-locked by nanotubes

Sub-picosecond tunable ultrafast lasers are important tools for many applications. Here we present an ultrafast tunable fiber laser mode-locked by a nanotube based saturable absorber. The laser outputs ∼500fs pulses over a 33 nm range at 1.5μm. This outperforms the current achievable pulse duration from tunable nanotube mode-locked lasers. © 2012 Elsevier B.V. All rights reserved.