Ensaios geomecânicos em rochas metassedimentares do maciço da Mina das Aveleiras (Mosteiro de Tibães): comparação, potencialidades e limitações

Mestrado em Engenharia Geotécnica e Geoambiente

Geotecnia dos túneis do maciço de Paranhos: avaliação hidrogeomecânica exploratória

As classificações geomecânicas são uma das abordagens mais reconhecidas para estimar a qualidade do maciço rochoso, face à sua simplicidade e competência para gerir incertezas. As incertezas geológicas e geotécnicas podem ser avaliadas de forma eficaz usando classificações adequadas. Este estudo pretende enfatizar a importância das classificações geomecânicas e índices geomecânicos, tais como a Rock Mass Rating (RMR), a Rock Tunnelling Quality Index (Qsystem), o Geological Strength Index (GSI) e o Hydro‐Potential (HP) Value, para ajuizar a qualidade do maciço rochoso granítico das galerias subterrâneas de Paranhos (setor de Carvalhido ‐ Burgães; área urbana do Porto). Em particular, o valor hidro‐potencial (HP‐value) é uma classificação semi‐quantitativa aplicada a maciços rochosos que permite estimar as infiltrações de água subterrânea em escavações de terrenos rochosos. Para esta avaliação foi compilada e integrada uma extensa base de dados geológico‐geotécnica e geomecânica, apoiada na técnica de amostragem linear de superfícies expostas descontinuidades. Para refinar o zonamento geotécnico do maciço rochoso granítico, previamente realizado em 2010, foram coletadas amostras de rocha em pontos‐chave, com o objetivo de avaliar a sua resistência através do Ensaio de Carga Pontual (PLT). A aplicação das classificações geomecânicas foi realizada de uma forma equilibrada, estabelecendo diferentes cenários e tendo sempre em conta o conhecimento das características do maciço in situ. Apresenta‐se uma proposta de zonamento hidrogeomecânico com o objetivo de compreender melhor a circulação geo‐hidráulica do maciço rochoso granítico. Pretende‐se com esta metodologia contribuir para aprofundar o conhecimento do substrato rochoso do Porto, nomeadamente no que diz respeito ao seu comportamento geomecânico.

Estudo da antiga mina de volfrâmio das Aveleiras (Mire de Tibães): cartografia geotécnica e avaliação geomecânica

Este trabalho tem como objetivo sublinhar a importância de um estudo geológico‐geotécnico para apoiar a cartografia geotécnica do maciço rochoso subterrâneo da antiga mina de volfrâmio das Aveleiras (Mosteiro de Tibães, Braga). Foi realizado um trabalho de campo sistemático, ao longo de uma rede de galerias subterrâneas com uma extensão aproximada de 155 m. Estas galerias são constituídas, principalmente, por rochas metassedimentares, embora aflorem rochas graníticas num pequeno trecho de uma das galerias. A técnica de amostragem linear de descontinuidades aplicada ao grau de compartimentação do maciço rochoso esteve na base de todos os dados geológicos, geotécnicos e geomecânicos. Além disso, foram coligidos e integrados os dados de campanhas de campo anteriores, realizadas entre 2006 e 2011. Foram igualmente descritos os métodos de avaliação dos dados de campo, bem como a análise estatística dos parâmetros geológico‐geotécnicos. O zonamento geotécnico do maciço rochoso das Aveleiras foi desenvolvido tendo em conta o comportamento do maciço rochoso in situ, e foi apoiado por ensaios laboratoriais de resistência do material‐rocha através do Ensaio de Carga Pontual. Apresenta‐se uma proposta preliminar de zonamento geomecânico com o objectivo de apoiar o projeto de engenharia de maciços rochosos.

Experimental characterization of the out-of-plane performance of regular stone masonry walls, including test setups and axial load influence

Stone masonry is one of the oldest and most worldwide used building techniques. Nevertheless, the structural response of masonry structures is complex and the effective knowledge about their mechanical behaviour is still limited. This fact is particularly notorious when dealing with the description of their out-of-plane behaviour under horizontal loadings, as is the case of the earthquake action. In this context, this paper describes an experimental program, conducted in laboratory environment, aiming at characterizing the out-of-plane behaviour of traditional unreinforced stone masonry walls. In the scope of this campaign, six full-scale sacco stone masonry specimens were fully characterised regarding their most important mechanic, geometric and dynamic features and were tested resorting to two different loading techniques under three distinct vertical pre-compression states; three of the specimens were subjected to an out-of-plane surface load by means of a system of airbags and the remaining were subjected to an out-of-plane horizontal line-load at the top. From the experiments it was possible to observe that both test setups were able to globally mobilize the out-of-plane response of the walls, which presented substantial displacement capacity, with ratios of ultimate displacement to the wall thickness ranging between 26 and 45 %, as well as good energy dissipation capacity. Finally, very interesting results were also obtained from a simple analytical model used herein to compute a set of experimental-based ratios, namely between the maximum stability displacement and the wall thickness for which a mean value of about 60 % was found.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

Mismatch negativity in childhood temporal lobe epilepsy: a proposed paradigm for testing central auditory processing

Background: Temporal lobe epilepsy (TLE) is a neurological disorder that directly affects cortical areas responsible for auditory processing. The resulting abnormalities can be assessed using event-related potentials (ERP), which have high temporal resolution. However, little is known about TLE in terms of dysfunction of early sensory memory encoding or possible correlations between EEGs, linguistic deficits, and seizures. Mismatch negativity (MMN) is an ERP component – elicited by introducing a deviant stimulus while the subject is attending to a repetitive behavioural task – which reflects pre-attentive sensory memory function and reflects neuronal auditory discrimination and perceptional accuracy. Hypothesis: We propose an MMN protocol for future clinical application and research based on the hypothesis that children with TLE may have abnormal MMN for speech and non-speech stimuli. The MMN can be elicited with a passive auditory oddball paradigm, and the abnormalities might be associated with the location and frequency of epileptic seizures. Significance: The suggested protocol might contribute to a better understanding of the neuropsychophysiological basis of MMN. We suggest that in TLE central sound representation may be decreased for speech and non-speech stimuli. Discussion: MMN arises from a difference to speech and non-speech stimuli across electrode sites. TLE in childhood might be a good model for studying topographic and functional auditory processing and its neurodevelopment, pointing to MMN as a possible clinical tool for prognosis, evaluation, follow-up, and rehabilitation for TLE.

Contribution of hospital effluents to the load of pharmaceuticals in urban wastewaters: Identification of ecologically relevant pharmaceuticals

The impact of effluent wastewaters from four different hospitals: a university (1456 beds), a general (350 beds), a pediatric (110 beds) and a maternity hospital (96 beds), which are conveyed to the same wastewater treatment plant (WWTP), was evaluated in the receiving urban wastewaters. The occurrence of 78 pharmaceuticals belonging to several therapeutic classes was assessed in hospital effluents and WWTP wastewaters (influent and effluent) as well as the contribution of each hospital in WWTP influent in terms of pharmaceutical load. Results indicate that pharmaceuticals are widespread pollutants in both hospital and urban wastewaters. The contribution of hospitals to the input of pharmaceuticals in urban wastewaters widely varies, according to their dimension. The estimated total mass loadings were 306 g d− 1 for the university hospital, 155 g d− 1 for the general one, 14 g d− 1 for the pediatric hospital and 1.5 g d− 1 for the maternity hospital, showing that the biggest hospitals have a greater contribution to the total mass load of pharmaceuticals. Furthermore, analysis of individual contributions of each therapeutic group showed that NSAIDs, analgesics and antibiotics are among the groups with the highest inputs. Removal efficiency can go from over 90% for pharmaceuticals like acetaminophen and ibuprofen to not removal for β-blockers and salbutamol. Total mass load of pharmaceuticals into receiving surface waters was estimated between 5 and 14 g/d/1000 inhabitants. Finally, the environmental risk posed by pharmaceuticals detected in hospital and WWTP effluents was assessed by means of hazard quotients toward different trophic levels (algae, daphnids and fish). Several pharmaceuticals present in the different matrices were identified as potentially hazardous to aquatic organisms, showing that especial attention should be paid to antibiotics such as ciprofloxacin, ofloxacin, sulfamethoxazole, azithromycin and clarithromycin, since their hazard quotients in WWTP effluent revealed that they could pose an ecotoxicological risk to algae.

Tensile behaviour of a structural adhesive at high temperatures by the extended finite element method

Component joining is typically performed by welding, fastening, or adhesive-bonding. For bonded aerospace applications, adhesives must withstand high-temperatures (200°C or above, depending on the application), which implies their mechanical characterization under identical conditions. The extended finite element method (XFEM) is an enhancement of the finite element method (FEM) that can be used for the strength prediction of bonded structures. This work proposes and validates damage laws for a thin layer of an epoxy adhesive at room temperature (RT), 100, 150, and 200°C using the XFEM. The fracture toughness (G Ic ) and maximum load ( ); in pure tensile loading were defined by testing double-cantilever beam (DCB) and bulk tensile specimens, respectively, which permitted building the damage laws for each temperature. The bulk test results revealed that decreased gradually with the temperature. On the other hand, the value of G Ic of the adhesive, extracted from the DCB data, was shown to be relatively insensitive to temperature up to the glass transition temperature (T g ), while above T g (at 200°C) a great reduction took place. The output of the DCB numerical simulations for the various temperatures showed a good agreement with the experimental results, which validated the obtained data for strength prediction of bonded joints in tension. By the obtained results, the XFEM proved to be an alternative for the accurate strength prediction of bonded structures.