Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Surgical correction of scoliosis: Numerical analysis and optimization of the procedure

A previously developed model is used to numerically simulate real clinical cases of the surgical correction of scoliosis. This model consists of one-dimensional finite elements with spatial deformation in which (i) the column is represented by its axis; (ii) the vertebrae are assumed to be rigid; and (iii) the deformability of the column is concentrated in springs that connect the successive rigid elements. The metallic rods used for the surgical correction are modeled by beam elements with linear elastic behavior. To obtain the forces at the connections between the metallic rods and the vertebrae geometrically, non-linear finite element analyses are performed. The tightening sequence determines the magnitude of the forces applied to the patient column, and it is desirable to keep those forces as small as possible. In this study, a Genetic Algorithm optimization is applied to this model in order to determine the sequence that minimizes the corrective forces applied during the surgery. This amounts to find the optimal permutation of integers 1, ... , n, n being the number of vertebrae involved. As such, we are faced with a combinatorial optimization problem isomorph to the Traveling Salesman Problem. The fitness evaluation requires one computing intensive Finite Element Analysis per candidate solution and, thus, a parallel implementation of the Genetic Algorithm is developed.

Modelling real solar cell using PSCAD/MATLAB

This paper presents the development of a solar photovoltaic (PV) model based on PSCAD/EMTDC - Power System Computer Aided Design – including a mathematical model study. An additional algorithm has been implemented in MATLAB software in order to calculate several parameters required by the PSCAD developed model. All the simulation study has been performed in PSCAD/MATLAB software simulation tool. A real data base concerning irradiance, cell temperature and PV power generation was used in order to support the evaluation of the implemented PV model.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

Desenvolvimento de uma plataforma SIG para apoio ao controlo da segurança das grandes barragens portuguesas

Trabalho Final de Mestrado elaborado no Laboratório Nacional de Engenharia Civil (LNEC) para a obtenção do grau de Mestre em Engenharia Civil pelo Instituto Superior de Engenharia de Lisboa no âmbito do protocolo de cooperação entre o ISEL e o LNEC

Estudo económico das energias renováveis: o caso português

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Empreendedorismo e Internacionalização, sob orientação de Maria Clara Dias Pinto Ribeiro

Metodologia para otimização da manutenção

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia da Manutenção

Aplicação da filosofia Lean management:caso de estudo, aplicado à manutenção de edifícios

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia da Manutenção

Desenvolvimento de modelo de primeiros princípios para simulação dinâmica de uma coluna de destilação contínua

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Inserção de todos os consumidores no mercado liberalizado de energia elétrica: oportunidades e desafios

O processo de liberalização do setor elétrico em Portugal Continental seguiu uma metodologia idêntica à da maior parte dos países europeus, tendo a abertura de mercado sido efetuada de forma progressiva. Assim, no âmbito do acompanhamento do setor elétrico nacional, reveste-se de particular interesse caracterizar a evolução mais recente do mercado liberalizado, nomeadamente em relação ao preço da energia elétrica. A previsão do preço da energia elétrica é uma questão muito importante para todos os participantes do mercado de energia elétrica. Como se trata de um assunto de grande importância, a previsão do preço da energia elétrica tem sido alvo de diversos estudos e diversas metodologias têm sido propostas. Esta questão é abordada na presente dissertação recorrendo a técnicas de previsão, nomeadamente a métodos baseados no histórico da variável em estudo. As previsões são, segundo alguns especialistas, um dos inputs essenciais que os gestores desenvolvem para ajudar no processo de decisão. Virtualmente cada decisão relevante ao nível das operações depende de uma previsão. Para a realização do modelo de previsão de preço da energia elétrica foram utilizados os modelos Autorregressivos Integrados de Médias Móveis, Autoregressive / Integrated / Moving Average (ARIMA), que geram previsões através da informação contida na própria série temporal. Como se pretende avaliar a estrutura do preço da energia elétrica do mercado de energia, é importante identificar, deste conjunto de variáveis, quais as que estão mais relacionados com o preço. Neste sentido, é realizada em paralelo uma análise exploratória, através da correlação entre o preço da energia elétrica e outras variáveis de estudo, utilizando para esse efeito o coeficiente de correlação de Pearson. O coeficiente de correlação de Pearson é uma medida do grau e da direção de relação linear entre duas variáveis quantitativas. O modelo desenvolvido foi aplicado tendo por base o histórico de preço da eletricidade desde o inicio do mercado liberalizado e de modo a obter as previsões diária, mensal e anual do preço da eletricidade. A metodologia desenvolvida demonstrou ser eficiente na obtenção das soluções e ser suficientemente rápida para prever o valor do preço da energia elétrica em poucos segundos, servindo de apoio à decisão em ambiente de mercado.

Urban sprawl analysis and modeling in Asmara, Eritreia: Application of Geospatial Tools

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

A study on reducing digital piracy: an analytical network process approach with benefits, opportunities, costs and risks analysis

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Building a thinner gap in a gas-gap heat switch

25th International Cryogenic Engineering Conference and the International Cryogenic Materials Conference in 2014, ICEC 25–ICMC 2014

Study of Helium II heat transport phenomena in superconducting rutherford type cables

This thesis is a study of how heat is transported in non-steady-state conditions from a superconducting Rutherford cable to a bath of superfluid helium (He II). The same type of superconducting cable is used in the dipole magnets of the Large Hadron Collider (LHC). The dipole magnets of the LHC are immersed in a bath of He II at 1.9 K. At this temperature helium has an extremely high thermal conductivity. During operation, heat needs to be efficiently extracted from the dipole magnets to keep their superconducting state. The thermal stability of the magnets is crucial for the operation of the LHC, therefore it is necessary to understand how heat is transported from the superconducting cables to the He II bath. In He II the heat transfer can be described by the Landau regime or by the Gorter-Mellink regime, depending on the heat flux. In this thesis both measurements and numerical simulation have been performed to study the heat transfer in the two regimes. A temperature increase of 8 2 mK of the superconducting cables was successfully measured experimentally. A new numerical model that covers the two heat transfer regimes has been developed. The numerical model has been validated by comparison with existing experimental data. A comparison is made between the measurements and the numerical results obtained with the developed model.

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.