Application of gas hydrate equilibria prediction in process engineering

Desde hace cerca de dos siglos, los hidratos de gas han ganado un rol importante en la ingeniería de procesos, debido a su impacto económico y ambiental en la industria -- Cada día, más compañías e ingenieros ganan interés en este tema, a medida que nuevos desafíos muestran a los hidratos de gas como un factor crucial, haciendo su estudio una solución para un futuro próximo -- Los gases de hidrato son estructuras similares al hielo, compuestos de moléculas huéspedes de agua conteniendo compuestos gaseosos -- Existen naturalmente en condiciones de presiones altas y bajas temperaturas, condiciones típicas de algunos procesos químicos y petroquímicos [1] -- Basado en el trabajo doctoral de Windmeier [2] y el trabajo doctoral the Rock [3], la descripción termodinámica de las fases de los hidratos de gas es implementada siguiendo el estado del arte de la ciencia y la tecnología -- Con ayuda del Dortmund Data Bank (DDB) y el paquete de software correspondiente (DDBSP) [26], el desempeño del método fue mejorado y comparado con una gran cantidad de datos publicados alrededor del mundo -- También, la aplicabilidad de la predicción de los hidratos de gas fue estudiada enfocada en la ingeniería de procesos, con un caso de estudio relacionado con la extracción, producción y transporte del gas natural -- Fue determinado que la predicción de los hidratos de gas es crucial en el diseño del proceso del gas natural -- Donde, en las etapas de tratamiento del gas y procesamiento de líquido no se presenta ninguna formación, en la etapa de deshidratación una temperatura mínima de 290.15 K es crítica y para la extracción y transporte el uso de inhibidores es esencial -- Una composición másica de 40% de etilenglicol fue encontrada apropiada para prevenir la formación de hidrato de gas en la extracción y una composición másica de 20% de metanol en el transporte

Prediction of Phosphorylation Sites from Protein Sequences

Phosphorylation is amongst the most crucial and well-studied post-translational modifications. It is involved in multiple cellular processes which makes phosphorylation prediction vital for understanding protein functions. However, wet-lab techniques are labour and time intensive. Thus, computational tools are required for efficiency. This project aims to provide a novel way to predict phosphorylation sites from protein sequences by adding flexibility and Sezerman Grouping amino acid similarity measure to previous methods, as discovering new protein sequences happens at a greater rate than determining protein structures. The predictor – NOPAY - relies on Support Vector Machines (SVMs) for classification. The features include amino acid encoding, amino acid grouping, predicted secondary structure, predicted protein disorder, predicted protein flexibility, solvent accessibility, hydrophobicity and volume. As a result, we have managed to improve phosphorylation prediction accuracy for Homo sapiens by 3% and 6.1% for Mus musculus. Sensitivity at 99% specificity was also increased by 6% for Homo sapiens and for Mus musculus by 5% on independent test sets. In this study, we have managed to increase phosphorylation prediction accuracy for Homo sapiens and Mus musculus. When there is enough data, future versions of the software may also be able to predict other organisms.

O papel do software educativo na aprendizagem da matemática

Tese de Doutoramento, Educação (Tecnologia Educativa), 26 de Julho de 2013, Universidade dos Açores.

Validação numérica de leis coesivas triangulares para previsão de resistência de juntas adesivas em tração e corte puros

As ligações adesivas surgiram pela necessidade de se encontrar formas de unir componentes, por vezes de materiais distintos, através de técnicas mais vantajosas. Atualmente, qualquer estrutura deve ser resistente, robusta e leve, o que amplificou o interesse industrial e investigação nas ligações adesivas, principalmente na melhoria das propriedades de resistência e fratura de materiais. Desta forma, nos últimos anos, a utilização de juntas adesivas em aplicações industriais tem aumentando gradualmente, substituindo alguns métodos de ligação tradicionais, por apresentarem vantagens, tais como redução de concentração de tensões, reduzido peso e facilidade de processamento/fabrico. Em qualquer área da indústria, a aplicação em larga escala de uma determinada técnica de ligação supõe que estão disponíveis ferramentas confiáveis para o projeto e previsão da rotura. Neste âmbito, os Modelos de Dano Coesivo (MDC) são uma ferramenta fundamental, apesar de ser necessário estimar as leis coesivas do adesivo à tração e corte para entrada nos modelos numéricos. Nesta dissertação o trabalho experimental consistiu no tratamento de dados com vista à obtenção de GIc e GIIc, com a devida comparação de diferentes métodos de redução, bem como potencialidades e limitações dos mesmos. É realizada uma comparação dos três adesivos: Araldite® AV138, Araldite® 2015 e SikaForce® 7752. Neste trabalho estudou-se também numericamente a adequação de leis coesivas triangulares na previsão no comportamento de juntas adesivas, nomeadamente nas curvas forçadeslocamento (P-) de ensaios Double-Cantilever Beam para caracterização à tração e ensaios End-Notched Flexure para caraterização ao corte. Os ensaios foram simulados numericamente pelo software ABAQUS®, recorrendo ao Método de Elementos Finitos (MEF) e um MDC triangular, com o intuito de estimar a lei coesiva de cada um dos adesivos. Para os adesivos Araldite®AV138 e Araldite®2015, à tração e ao corte, a lei triangular previu o comportamento do adesivo com alguma razoabilidade. Para a previsão da resistência do adesivo SikaForce® 7752, a lei triangular não se ajustou convenientemente nem à tração nem ao corte. Considera-se que, para este adesivo, uma lei trapezoidal é a que melhor se adequa, devido à ductilidade do mesmo.

Numerical prediction of thermal and dynamic characteristics of a fireinduced ceiling-jet

The aim of this thesis is to test the ability of some correlative models such as Alpert correlations on 1972 and re-examined on 2011, the investigation of Heskestad and Delichatsios in 1978, the correlations produced by Cooper in 1982, to define both dynamic and thermal characteristics of a fire induced ceiling-jet flow. The flow occurs when the fire plume impinges the ceiling and develops in the radial direction of the fire axis. Both temperature and velocity predictions are decisive for sprinklers positioning, fire alarms positions, detectors (heat, smoke) positions and activation times and back-layering predictions. These correlative models will be compared with a 3D numerical simulation software CFAST. For the results comparison of temperature and velocity near the ceiling. These results are also compared with a Computational Fluid Dynamics (CFD) analysis, using ANSYS FLUENT.

Appraisal of open software for finite element simulation of 2D metal sheet laser cut.

FEA simulation of thermal metal cutting is central to interactive design and manufacturing. It is therefore relevant to assess the applicability of FEA open software to simulate 2D heat transfer in metal sheet laser cuts. Application of open source code (e.g. FreeFem++, FEniCS, MOOSE) makes possible additional scenarios (e.g. parallel, CUDA, etc.), with lower costs. However, a precise assessment is required on the scenarios in which open software can be a sound alternative to a commercial one. This article contributes in this regard, by presenting a comparison of the aforementioned freeware FEM software for the simulation of heat transfer in thin (i.e. 2D) sheets, subject to a gliding laser point source. We use the commercial ABAQUS software as the reference to compare such open software. A convective linear thin sheet heat transfer model, with and without material removal is used. This article does not intend a full design of computer experiments. Our partial assessment shows that the thin sheet approximation turns to be adequate in terms of the relative error for linear alumina sheets. Under mesh resolutions better than 10e−5 m , the open and reference software temperature differ in at most 1 % of the temperature prediction. Ongoing work includes adaptive re-meshing, nonlinearities, sheet stress analysis and Mach (also called ‘relativistic’) effects.

Protein expression of Myt272-3 recombinant clone and in silico prediction of a possible vaccine candidate against Mycobacterium tuberculosis

Purpose: To investigate the expression of Myt272-3 recombinant protein and also to predict a possible protein vaccine candidate against Mycobacterium tuberculosis . Methods: Myt272-3 protein was expressed in pET30a+-Myt272-3 clone. The purity of the protein was determined using Dynabeads® His-Tag Isolation & Pulldown. Protein sequence was analysed in silico using bioinformatics software for the prediction of allergenicity, antigenicity, MHC-I and MHC-II binding, and B-cell epitope binding. Results: The candidate protein was a non-allergen with 15.19 % positive predictive value. It was also predicted to be antigenic, with binding affinity to MHC-I and MHC-II, as well as B-cell epitope binding. Conclusion: The predicted results obtained in this study provide a guide for practical design of a new tuberculosis vaccine.

The Performance and Service Life Prediction of High Performance Concrete in Sulfate and Acidic Environments

Concrete substructures are often subjected to environmental deterioration, such as sulfate and acid attack, which leads to severe damage and causes structure degradation or even failure. In order to improve the durability of concrete, the High Performance Concrete (HPC) has become widely used by partially replacing cement with pozzolanic materials. However, HPC degradation mechanisms in sulfate and acidic environments are not completely understood. It is therefore important to evaluate the performance of the HPC in such conditions and predict concrete service life by establishing degradation models. This study began with a review of available environmental data in the State of Florida. A total of seven bridges have been inspected. Concrete cores were taken from these bridge piles and were subjected for microstructural analysis using Scanning Electron Microscope (SEM). Ettringite is found to be the products of sulfate attack in sulfate and acidic condition. In order to quantitatively analyze concrete deterioration level, an image processing program is designed using Matlab to obtain quantitative data. Crack percentage (Acrack/Asurface) is used to evaluate concrete deterioration. Thereafter, correlation analysis was performed to find the correlation between five related variables and concrete deterioration. Environmental sulfate concentration and bridge age were found to be positively correlated, while environmental pH level was found to be negatively correlated. Besides environmental conditions, concrete property factor was also included in the equation. It was derived from laboratory testing data. Experimental tests were carried out implementing accelerated expansion test under controlled environment. Specimens of eight different mix designs were prepared. The effect of pozzolanic replacement rate was taken into consideration in the empirical equation. And the empirical equation was validated with existing bridges. Results show that the proposed equations compared well with field test results with a maximum deviation of ± 20%. Two examples showing how to use the proposed equations are provided to guide the practical implementation. In conclusion, the proposed approach of relating microcracks to deterioration is a better method than existing diffusion and sorption models since sulfate attack cause cracking in concrete. Imaging technique provided in this study can also be used to quantitatively analyze concrete samples.

Methods for Modeling and Analyzing Concurrent Software

Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.

Meshfree Method for Prediction of Thermal Properties of Porous Ceramic Materials

In the presented thesis work, meshfree method with distance fields is applied to create a novel computational approach which enables inclusion of the realistic geometric models of the microstructure and liberates Finite Element Analysis(FEA) from thedependance on and limitations of meshing of fine microstructural feature such as splats and porosity.Manufacturing processes of ceramics produce materials with complex porosity microstructure.Geometry of pores, their size and location substantially affect macro scale physical properties of the material. Complex structure and geometry of the pores severely limit application of modern Finite Element Analysis methods because they require construction of spatial grids (meshes) that conform to the geometric shape of the structure. As a result, there are virtually no effective tools available for predicting overall mechanical and thermal properties of porous materials based on their microstructure. This thesis is a separate handling and controls of geometric and physical computational models that are seamlessly combined at solution run time. Using the proposedapproach we will determine the effective thermal conductivity tensor of real porous ceramic materials featuring both isotropic and anisotropic thermal properties. This work involved development and implementation of numerical algorithms, data structure, and software.

A pro-active and dynamic prediction assistance using BaranC framework

Monitoring user interaction activities provides the basis for creating a user model that can be used to predict user behaviour and enable user assistant services. The BaranC framework provides components that perform UI monitoring (and collect all associated context data), builds a user model, and supports services that make use of the user model. In this case study, a Next-App prediction service is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic; it is dynamic both in responding to the current context, and also in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

A next application prediction service using the BaranC framework

Predicting user behaviour enables user assistant services provide personalized services to the users. This requires a comprehensive user model that can be created by monitoring user interactions and activities. BaranC is a framework that performs user interface (UI) monitoring (and collects all associated context data), builds a user model, and supports services that make use of the user model. A prediction service, Next-App, is built to demonstrate the use of the framework and to evaluate the usefulness of such a prediction service. Next-App analyses a user's data, learns patterns, makes a model for a user, and finally predicts, based on the user model and current context, what application(s) the user is likely to want to use. The prediction is pro-active and dynamic, reflecting the current context, and is also dynamic in that it responds to changes in the user model, as might occur over time as a user's habits change. Initial evaluation of Next-App indicates a high-level of satisfaction with the service.

An Analysis of the Early Prediction of Highway Construction Project Completion using the Contract Status Report

History has shown that projects move in and out of poor status through the life of the project. Predicting the success or failure of a project to complete on time because of its recent history on the contract status report could provide our project managers another tool for monitoring contract progress. In many instances, poor contract progress results in the loss of contract time and late completion of projects. This research evaluates the combinations of work type, point in time physical work begins, recent poor status, and contract bid amount as indicators of late project completion.

Modelos estocásticos de crescimento individual e desenvolvimento de software de estimação e previsão

Os modelos de crescimento individual são geralmente adaptações de modelos de crescimento de populações. Inicialmente estes modelos eram apenas determinísticos, isto é, não incorporavam as flutuações aleatórias do ambiente. Com o desenvolvimento da teoria do cálculo estocástico podemos adicionar um termo estocástico, que representa a aleatoriedade ambiental que influencia o processo em estudo. Actualmente, o estudo do crescimento individual em ambiente aleatório é cada vez mais importante, não apenas pela vertente financeira, mas também devido às suas aplicações nas áreas da saúde e da pecuária, entre outras. Problemas como o ajustamento de modelos de crescimento individual, estimação de parâmetros e previsão de tamanhos futuros são tratados neste trabalho. São apresentadas novas aplicações do modelo estocástico monomolecular generalizado e um novo software de aplicação deste e de outros modelos. ABSTRACT: Individual growth models are usually adaptations of growth population models. Initially these models were only deterministic, that is, they did not incorporate the random fluctuations of the environment. With the development of the theory of stochastic calculus, we can add a stochastic term that represents the random environmental influences in the process under study. Currently, the study of individual growth in a random environment is increasingly important, not only by the financial scope but also because of its applications in health care and livestock production, among others. Problems such as adjustment of an individual growth model, estimation of parameters and prediction of future sizes are treated in this work. New applications of the generalized stochastic monomolecular model and a new software applied to this and other models are presented.