Valuation of marine and coastal ecosystems: The role of ecological-economic modeling

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Attracting investments from Germany to Portugal: A specific value-proposition for automotive suppliers

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Estruturas 3D porosas com gradiente de funcionalidade produzidas por Freeze-casting

Dissertação para obtenção do Grau de Mestre em Engenharia de Materiais

Computational modeling of prefrontal cortex circuits

Dissertation presented to obtain the Ph.D degree in Biology

Quality of process modeling using BPMN: a model-driven approach

Dissertação para obtenção do Grau de Doutor em Engenharia Informática

Novas utilizações das potencialidades BIM – produção de informação as-built e apoio à medição de trabalhos realizados com recurso a realidade aumentada

Dissertação para obtenção do Grau Mestre em Engenharia Civil – Perfil de Construção

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

Predictive analytical and numerical modeling for orthogonal cutting

In this thesis, a predictive analytical and numerical modeling approach for the orthogonal cutting process is proposed to calculate temperature distributions and subsequently, forces and stress distributions. The models proposed include a constitutive model for the material being cut based on the work of Weber, a model for the shear plane based on Merchants model, a model describing the contribution of friction based on Zorev’s approach, a model for the effect of wear on the tool based on the work of Waldorf, and a thermal model based on the works of Komanduri and Hou, with a fraction heat partition for a non-uniform distribution of the heat in the interfaces, but extended to encompass a set of contributions to the global temperature rise of chip, tool and work piece. The models proposed in this work, try to avoid from experimental based values or expressions, and simplifying assumptions or suppositions, as much as possible. On a thermo-physical point of view, the results were affected not only by the mechanical or cutting parameters chosen, but also by their coupling effects, instead of the simplifying way of modeling which is to contemplate only the direct effect of the variation of a parameter. The implementation of these models was performed using the MATLAB environment. Since it was possible to find in the literature all the parameters for AISI 1045 and AISI O2, these materials were used to run the simulations in order to avoid arbitrary assumption.

Writing/erasing 3D micro and nano wrinkles in flexible elastomers for volatile organic compounds sensor

Micro/nano wrinkled patterns on cross-linked urethane/urea polymeric flexible free standing films with two soft segments, polypropylene oxide and polybutadiene, can be induced by UV-irradiation. The ability to write/erase these 3D structures, in a controlled manner, is the main focus of this work. The imprinting of the wrinkled structures was accomplished by swelling in an appropriate solvent followed by drying the membranes after the cross-linking process and UV irradiation. The surface tailoring of the elastomeric membranes was imaged by optical microscopy, scanning electronic microscopy and by atomic force microscopy. To erase the wrinkled structures the elastomers were swollen. The swelling as well as the sol/gel fraction and the UV radiation were tuned in order to control the wrinkles characteristics. It was found that the wrinkles wavelength, in the order of microns (1±0,25μm), was stamped by the UV radiation intensity and exposure time while the wrinkles' amplitude, in the order of nanometers (150-450 nm), was highly dependent on the swelling and sol/gel fraction. A prototype for volatile organic compounds detection was developed taking advantage of the unique 3D micro/nano wrinkles features.

Ageing on commercial automotive catalysts, a structure reactivity study

Increasingly stringed regulations for diesel engine emissions have a significant impact on the required efficiency of DOC. Lowered DOC oxidation efficiency due to thermal aging effects influences the efficiency of the exhaust aftertreatment systems downstream of the DOC. In this work carried out in the Jean Le Rond d’Alembert Institute the effect of hydrothermal aging on the reactivity and structure of a commercial DOC was investigated. The characterization of the catalytic performance was carried out on a synthetic gas bench using carrots catalyst under conditions close to the realistic conditions i.e. using a synthetic gas mixture, representative of the exhaust gases from diesel engines. Different structural characterization techniques were performed: textural and morphological proprieties were analyzed by BET and TEM, the characterization of the presented crystallographic phases was performed by DRX and the determination of the number of reducible species was possible by TPR. TEM results shown, an increase of the metal particle size with the aging caused by the agglomeration of metal particles, revealing the presence of metal sintering. DRX results also suggest the presence of support sintering. Furthermore, DRX and BET results unexpectedly reveal that the most drastic aging conditions used actually activated the catalyst surface. As expected, the aging affected negatively the catalyst performance on the oxidation of methane and CO, however an improvement of the NO oxidation performance with the aging was observed. Nevertheless, for the aging conditions used, catalytic activity results show that the influence of aging in DOC performance was not significant, and therefore, more drastic aging conditions must be used.

Influence of Lean and Green on supply chain performance: an interpretive structural modelling model

This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Enhancement of an implemented rating model and impact on existing risk management processes: A hands-on approach from financial supplier risk management within the automotive industry

The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.

Flexible multivariate GARCH modeling with an application to international stock markets

This paper offers a new approach to estimating time-varying covariance matrices in the framework of the diagonal-vech version of the multivariate GARCH(1,1) model. Our method is numerically feasible for large-scale problems, produces positive semidefinite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the nev^ estimator with a number of existing ones.

Produção de matrizes porosas 3D baseadas em réplicas invertidas de cristais coloidais

A Engenharia de Tecidos surge da necessidade recorrente de regenerar ou recriar órgãos e tecidos danificados devido a vários tipos de trauma. A carência de funcionalidades resultante pode ser resolvida através da implantação de substitutos bio-sintéticos. O presente trabalho consiste na produção de matrizes porosas 3D baseadas em réplicas invertidas de cristais coloidais com futura aplicação em substituintes ósseos sintéticos para fraturas de não-união. O substituinte ósseo consiste numa estrutura denominada Inverse colloidal crystal (ICC), em que a sua organização singular resulta numa homogénea proliferação celular e num aumento das propriedades mecânicas, quando comparada com outros substituintes. O primeiro passo para a obtenção desta estrutura é a produção de microesferas de poliestireno, por uma técnica baseada em microfluídica. Posteriormente as microesferas são empacotadas resultando numa estrutura coesa com ligações entre microesferas vizinhas. O preenchimento dos espaços vazios entre microesferas pelo biomaterial pretendido e posterior remoção das microesferas dá origem à estrutura porosa do ICC. ICCs poliméricos (ϕCs = 1,00) e compósitos (ϕCs = 0,86 e ϕHA = 0,14; ϕCs = 0,67 e ϕHA = 0,33; ϕCs = ϕHA = 0,50) são produzidos e as suas propriedades mecânicas são testadas através de ensaios de compressão e comparadas com outros substituintes sintéticos. Para avaliação do comportamento dos materiais em contacto com meio biológico, foram realizados testes de citotoxicidade que revelaram uma viabilidade celular acima dos 80% em todos os ICCs.