Life-cycle performance of structures: combining expert judgment and results of inspection

Life-Cycle Civil Engineering – Biondini & Frangopol

The monitoring of rammed earth experimental walls and characterization of rammed earth samples

RESTAPIA 2012 - Int. Conf. on Rammed Earth Conservation, Valencia, 21-23 June 2012

Lightweight monitoring of transactional memory programs

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Robustness of timber structures in seismic areas

Some of the properties sought in seismic design of buildings are also considered fundamental to guarantee structural robustness. Moreover, some key concepts are common to both seismic and robustness design. In fact, both analyses consider events with a very small probability of occurrence, and consequently, a significant level of damage is admissible. As very rare events,in both cases, the actions are extremely hard to quantify. The acceptance of limited damage requires a system based analysis of structures, rather than an element by element methodology, as employed for other load cases. As for robustness analysis, in seismic design the main objective is to guarantee that the structure survives an earthquake, without extensive damage. In the case of seismic design, this is achieved by guaranteeing the dissipation of energy through plastic hinges distributed in the structure. For this to be possible, some key properties must be assured, in particular ductility and redundancy. The same properties could be fundamental in robustness design, as a structure can only sustain significant damage if capable of distributing stresses to parts of the structure unaffected by the triggering event. Timber is often used for primary load‐bearing elements in single storey long‐span structures for public buildings and arenas, where severe consequences can be expected if one or more of the primary load bearing elements fail. The structural system used for these structures consists of main frames, secondary elements and bracing elements. The main frame, composed by columns and beams, can be seen as key elements in the system and should be designed with high safety against failure and under strict quality control. The main frames may sometimes be designed with moment resisting joints between columns and beams. Scenarios, where one or more of these key elements, fail should be considered at least for high consequence buildings. Two alternative strategies may be applied: isolation of collapsing sections and, provision of alternate load paths [1]. The first one is relatively straightforward to provide by deliberately designing the secondary structural system less strong and stiff. Alternatively, the secondary structural system and the bracing system can be design so that loss of capacity in the main frame does not lead to the collapse. A case study has been selected aiming to assess the consequences of these two different strategies, in particular, under seismic loads.

A framework for robustness assessment in the context of corroded RC structures

Structural robustness is an emergent concept related to the structural response to damage. At the present time, robustness is not well defined and much controversy still remains around this subject. Even if robustness has seen growing interest as a consequence of catastrophic consequences due to extreme events, the fact is that the concept can also be very useful when considered on more probable exposure scenarios such as deterioration, among others. This paper intends to be a contribution to the definition of structural robustness, especially in the analysis of reinforced concrete structures subjected to corrosion. To achieve this, first of all, several proposed robustness definitions and indicators and misunderstood concepts will be analyzed and compared. From this point and regarding a concept that could be applied to most type of structures and dam-age scenarios, a robustness definition is proposed. To illustrate the proposed concept, an example of corroded reinforced concrete structures will be analyzed using nonlinear analysis numerical methods based on a contin-uum strong discontinuities approach and isotropic damage models for concrete. Finally the robustness of the presented example will be assessed.

Robustness of corroded reinforced concrete structures

Short Term Scienti c Mission, COST ACTION TU-0601

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Monitoring chlorophyll-a with remote sensing techniques in the Tagus Estuary

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Gestão e Sistemas Ambientais

The contribution of multitemporal information from multispectral satellite images for automatic land cover classification at the national scale

Thesis submitted to the Instituto Superior de Estatística e Gestão de Informação da Universidade Nova de Lisboa in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Information Management – Geographic Information Systems

Primary bioreceptivity of limestones from the mediterranean basin to phototrophic microorganisms

Dissertação apresentada para a obtenção do grau de Doutor em Conservação e Restauro pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Design and implementation of an autonomous, proactive, and reactive software infrastructure to help improving the management level of projects

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Earthquakes and robustness for timber structures

Workshop of COST Actions TU0601 and E55 September 21-22 2009, Ljubljana, Slovenia

Cidadão e comunidade : que relevância no processo de contratualizaç

RESUMO - Nas últimas décadas, a especialização dos cuidados médicos tem conduzido a uma fragmentação do sistema de prestação, que, associada a uma deficiente coordenação entre serviços, cuidados e prestadores, torna a navegabilidade dos utentes nos sistemas de saúde uma tarefa complexa. Um novo modelo de organização, assente na procura de valor para os cidadãos, deve adoptar uma abordagem sistémica, que tenha subjacente uma coordenação integrada de serviços, numa perspectiva de ciclo de cuidados. Reorientar a prestação de cuidados para a obtenção de resultados e valor em saúde, exige uma reengenharia em torno da estrutura, organização e avaliação1 dos cuidados, requerendo, nomeadamente: i) instrumentos e ferramentas que auxiliem e estruturem este novo modelo; ii) assumpção dos papéis definidos para cada um dos actores do sistema, nomeadamente ao nível da coordenação; iii) encorajamento à adopção de modelos de contratualização, pagamento e competição, que responsabilizem os actores envolvidos não só pela prática que desenvolvem, mas pelos resultados em saúde. Estes mecanismos constituem uma oportunidade para expandir e sustentar abordagens, programas e intervenções integradas. Investir num sistema de pagamento por valor em saúde — P4V — payment for value, traduz uma aposta na relação entre diagnóstico, tratamento, resultados clínicos e custos, enquanto estratégia para assegurar ganhos em qualidade dos cuidados, eficiência dos processos e valor em saúde para o cidadão. Neste contexto, a gestão da doença enquanto modelo direccionado para o reforço da perspectiva e participação activa do cidadão, e avaliação compreensiva de novas formas de organização e gestão do sistema de prestação, constitui um instrumento para informar e sustentar esse processo de reengenharia do sistema. Um modelo que procura assegurar o encontro entre o estado da arte na prestação de cuidados e um nível óptimo, garantindo a qualidade de vida expectável para a pessoa com doença crónica. ----------------- ---------ABSTRACT – In the last decades advanced medical sciences trend to specialized care and fragmented health systems, leaving patients with a challenge on navigating services and care, requiring them to see a sequence of specialists each delivering discrete interventions. To overcome these challenges, every health system must redefine health care delivery to use its resources more efficiently and improve quality of care through an organization of the system as a whole. A system currently organized around value for patients, entails a framework that comprises the entire set of activities needed to address a patient´s medical condition, over the full cycle of care. Value- based care delivery therefore requires an integrated practice, both across services and time, and implies a movement through new structures, organization models, evaluation efforts and payment systems that enables, catalyze and reinforces the extension and sustainability of the steps needed to the change required. A shift from a payment for performance to a payment for value focuses attention on maximizing the overall value of care, and encourages coordination and integration between components of care that extends from screening, diagnoses, all the way through treatment, outcomes and costs, and ensuring an incentive for potentially high value types of care as well as innovation. These leave the actors of the system with the task of best allocating and valuing components of care. Disease management as a model designed to structure patient engagement and involvement in their care, and assure a comprehensive evaluation and monitoring of new organization and care delivery strategies align an opportunity as a source of information and sustainability for the progress of a growing number of likeminded efforts now underway across care delivery for chronic diseases. This framework will allow the fulfillment of the gap between sta

Environmental Decision-making utilizing a Web GIS to Monitor Hazardous Industrial Emissions in the Valencian community of Spain

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