[pt] A determinação dos parâmetros hidráulicos não saturados em laboratório nem sempre representa efetivamente as situações observadas em campo, principalmente devido ao erro causado pelo efeito de escala. Nesse sentido, inúmeros ensaios de campo vêm sendo desenvolvidos, fazendo o uso de medidas de carga de pressão no tempo, para a determinação das propriedades hidráulicas não saturadas. No presente estudo, foi utilizado o ensaio de campo proposto por Velloso (2000), denominado Ensaio de Infiltração Monitorada (EIM). Neste ensaio é mantida uma carga constante, utilizando um permeâmetro tipo Gueplh, sendo monitorada, com o auxílio de um tensiômetro, a variação da sucção ocasionada pela frente de infiltração. Quando a variação da sucção no solo torna-se constante e próxima a zero, o ensaio atingiu, portanto, a condição de fluxo permanente, podendo-se assim finalizar o teste. Os parâmetros do solo e os respectivos parâmetros do modelo de Van Genuchten (1980), os quais descrevem a curva de saturação versus o potencial mátrico, são obtidos matematicamente, através da resolução do problema inverso. Nesse sentido, o objetivo principal do presente trabalho é realizar uma avaliação detalhada dos procedimentos numéricos e experimentais para uso no Ensaio de Infiltração Monitorada (EIM), seguindo as diretrizes e recomendações apontadas nos estudos anteriormente realizados. Desta forma, buscou-se um melhor entendimento do EIM, e para isto, foram realizadas: análises comparativas com resultados de ensaio de laboratório do tipo papel filtro; foi adicionado o monitoramento de umidade de solo durante o EIM; e foram utilizados diferentes métodos de estimativa de parâmetros. Os ensaios apresentados no presente estudo foram realizados em cinco áreas do Estado do Rio de Janeiro. / [en] The determination of unsaturated hydraulic parameters in laboratory tests is not always represents as observed on the field, especially because of the presence of errors caused by the scale factor. So, several field tests have been developed using suction measures with time for a determination of the unsaturated hydraulic properties. This research aims to use the field test proposed by Velloso (2000), called Monitored Infiltration Test (EIM) to determine the Soil Water Characteristic Curve. In this test the constant head is maintained, using a constant head permeameter and, at the same time, monitoring a variation of the suction caused by the infiltration front with a tensiometer. When a variation of the suction in the soil becomes constant and close to zero, then, the test reached a condition of permanent flow, being possible to finalize the procedure. In addition, the soil water characteristic curve (SWCC) and the respective Van Genuchten parameters, that describes a saturation curve versus the matric potential, are obtained mathematically by solving the inverse problem. In this context, the main objective of this research is to develop a detailed evaluation of the numerical and experimental procedures to use it in the Monitored Infiltration Test (EIM), following the guidelines and recommendations pointed out in previous studies in the area. Moreover, was sought a better understanding of EIM, and for this, comparative analyzes were performed with laboratory test results of the filter paper type. In addition, it was added the soil moisture monitoring during the EIM. Finally, was used many optimization methods for parameter estimation. The tests developed and presented in this research, were performed in five areas around the State of Rio de Janeiro.

Em vista das mudanças ambientais em nível global, disponibilizar informações ecológicas e buscar uma melhor compreensão dos fatores e processos que moldam a distribuição de espécies, é uma iniciativa importante para o planejamento de ações de conservação. Neste contexto, a importância e carência de informações sobre a distribuição geográficas das espécies nos motivaram a predizer a distribuição potencial de arbustos e árvores das famílias Lauraceae e Myrtaceae na Floresta Atlântica, no sul do Brasil. Modelos lineares generalizados (GLM) foram usados para ajustar modelos preditivos com os registros de ocorrência de 88 espécies em função de variáveis ambientais. As variáveis preditoras foram selecionadas com base no menor critério de informação de Akaike corrigido. Nós avaliamos o desempenho dos modelos usando o método de validação cruzada (10-fold) para calcular a habilidade estatística verdadeira (TSS) e a área sob a curva característica do operador receptor (AUC). Nós usamos GLM para testar a influência da área de ocorrência estimada, do número de registros das espécies e da complexidade dos modelos sobre a TSS e a AUC. Nossos resultados mostraram que as variáveis climáticas governam amplamente a distribuição de espécies, mas as variáveis que captam as variações ambientais locais são relativamente importantes na área de estudo. A TSS foi significativamente influenciada pelo número de registros e complexidade dos modelos, enquanto a AUC sofreu com o efeito de todos os três fatores avaliados. A interação entre estes fatores é uma questão importante e a ser considerada em novas avaliações sobre ambas medidas e com diferentes técnicas de modelagem. Nossos resultados também mostraram que as distribuições de algumas espécies foram superestimadas e outras corresponderam bem com a ocorrência por nós conhecida. Efetivamente nossos resultados têm fundamentos para embasar novos levantamentos de campo, a avaliação de áreas prioritárias e planos de conservação, além de inferências dos efeitos de mudanças ambientais sobre as espécies da Mata Atlântica. / In view of environmental change on a global level, providing ecological information and getting a better understanding of the factors and processes that shape species distribution is an important initiative for planning conservation actions. In this context, the importance and lack of information about the geographical distribution of species motivated us to predict the potential species distribution of shrubs and trees of the family Lauraceae and Myrtaceae, in the Atlantic Forest in southern Brazil. Generalized linear models (GLM) were used to fit predictive models with records of occurrence of 88 species according to environmental variables. Predictor variables were selected based on the lowest corrected Akaike information criterion. We evaluate the performance of the models using the method of cross-validation (10-fold) to calculate the true skill statistic (TSS) and area under the receiver operator characteristic curve (AUC). We used GLM to test the influence of the area of occurrence estimated, the number of records of the species and the complexity of the models on the TSS and AUC. Our results show that climatic variables largely govern the distribution of species, but the variables that capture the local environmental variations are relatively important in the study area. The TSS was significantly influenced by the number of records and complexity of models while the AUC suffered from the effect of all three evaluated factors. The interaction between these factors is an important issue and be considered for new reviews on both measures and with different modeling techniques. Our results also showed that the distributions of some species were overestimated and other corresponded well with the occurrence known to us. Indeed our results have foundations to support new field surveys, assessment of priority areas and conservation plans, and inferences of the effects of environmental change on species of the Atlantic Forest.

Em vista das mudanças ambientais em nível global, disponibilizar informações ecológicas e buscar uma melhor compreensão dos fatores e processos que moldam a distribuição de espécies, é uma iniciativa importante para o planejamento de ações de conservação. Neste contexto, a importância e carência de informações sobre a distribuição geográficas das espécies nos motivaram a predizer a distribuição potencial de arbustos e árvores das famílias Lauraceae e Myrtaceae na Floresta Atlântica, no sul do Brasil. Modelos lineares generalizados (GLM) foram usados para ajustar modelos preditivos com os registros de ocorrência de 88 espécies em função de variáveis ambientais. As variáveis preditoras foram selecionadas com base no menor critério de informação de Akaike corrigido. Nós avaliamos o desempenho dos modelos usando o método de validação cruzada (10-fold) para calcular a habilidade estatística verdadeira (TSS) e a área sob a curva característica do operador receptor (AUC). Nós usamos GLM para testar a influência da área de ocorrência estimada, do número de registros das espécies e da complexidade dos modelos sobre a TSS e a AUC. Nossos resultados mostraram que as variáveis climáticas governam amplamente a distribuição de espécies, mas as variáveis que captam as variações ambientais locais são relativamente importantes na área de estudo. A TSS foi significativamente influenciada pelo número de registros e complexidade dos modelos, enquanto a AUC sofreu com o efeito de todos os três fatores avaliados. A interação entre estes fatores é uma questão importante e a ser considerada em novas avaliações sobre ambas medidas e com diferentes técnicas de modelagem. Nossos resultados também mostraram que as distribuições de algumas espécies foram superestimadas e outras corresponderam bem com a ocorrência por nós conhecida. Efetivamente nossos resultados têm fundamentos para embasar novos levantamentos de campo, a avaliação de áreas prioritárias e planos de conservação, além de inferências dos efeitos de mudanças ambientais sobre as espécies da Mata Atlântica. / In view of environmental change on a global level, providing ecological information and getting a better understanding of the factors and processes that shape species distribution is an important initiative for planning conservation actions. In this context, the importance and lack of information about the geographical distribution of species motivated us to predict the potential species distribution of shrubs and trees of the family Lauraceae and Myrtaceae, in the Atlantic Forest in southern Brazil. Generalized linear models (GLM) were used to fit predictive models with records of occurrence of 88 species according to environmental variables. Predictor variables were selected based on the lowest corrected Akaike information criterion. We evaluate the performance of the models using the method of cross-validation (10-fold) to calculate the true skill statistic (TSS) and area under the receiver operator characteristic curve (AUC). We used GLM to test the influence of the area of occurrence estimated, the number of records of the species and the complexity of the models on the TSS and AUC. Our results show that climatic variables largely govern the distribution of species, but the variables that capture the local environmental variations are relatively important in the study area. The TSS was significantly influenced by the number of records and complexity of models while the AUC suffered from the effect of all three evaluated factors. The interaction between these factors is an important issue and be considered for new reviews on both measures and with different modeling techniques. Our results also showed that the distributions of some species were overestimated and other corresponded well with the occurrence known to us. Indeed our results have foundations to support new field surveys, assessment of priority areas and conservation plans, and inferences of the effects of environmental change on species of the Atlantic Forest.

Em vista das mudanças ambientais em nível global, disponibilizar informações ecológicas e buscar uma melhor compreensão dos fatores e processos que moldam a distribuição de espécies, é uma iniciativa importante para o planejamento de ações de conservação. Neste contexto, a importância e carência de informações sobre a distribuição geográficas das espécies nos motivaram a predizer a distribuição potencial de arbustos e árvores das famílias Lauraceae e Myrtaceae na Floresta Atlântica, no sul do Brasil. Modelos lineares generalizados (GLM) foram usados para ajustar modelos preditivos com os registros de ocorrência de 88 espécies em função de variáveis ambientais. As variáveis preditoras foram selecionadas com base no menor critério de informação de Akaike corrigido. Nós avaliamos o desempenho dos modelos usando o método de validação cruzada (10-fold) para calcular a habilidade estatística verdadeira (TSS) e a área sob a curva característica do operador receptor (AUC). Nós usamos GLM para testar a influência da área de ocorrência estimada, do número de registros das espécies e da complexidade dos modelos sobre a TSS e a AUC. Nossos resultados mostraram que as variáveis climáticas governam amplamente a distribuição de espécies, mas as variáveis que captam as variações ambientais locais são relativamente importantes na área de estudo. A TSS foi significativamente influenciada pelo número de registros e complexidade dos modelos, enquanto a AUC sofreu com o efeito de todos os três fatores avaliados. A interação entre estes fatores é uma questão importante e a ser considerada em novas avaliações sobre ambas medidas e com diferentes técnicas de modelagem. Nossos resultados também mostraram que as distribuições de algumas espécies foram superestimadas e outras corresponderam bem com a ocorrência por nós conhecida. Efetivamente nossos resultados têm fundamentos para embasar novos levantamentos de campo, a avaliação de áreas prioritárias e planos de conservação, além de inferências dos efeitos de mudanças ambientais sobre as espécies da Mata Atlântica. / In view of environmental change on a global level, providing ecological information and getting a better understanding of the factors and processes that shape species distribution is an important initiative for planning conservation actions. In this context, the importance and lack of information about the geographical distribution of species motivated us to predict the potential species distribution of shrubs and trees of the family Lauraceae and Myrtaceae, in the Atlantic Forest in southern Brazil. Generalized linear models (GLM) were used to fit predictive models with records of occurrence of 88 species according to environmental variables. Predictor variables were selected based on the lowest corrected Akaike information criterion. We evaluate the performance of the models using the method of cross-validation (10-fold) to calculate the true skill statistic (TSS) and area under the receiver operator characteristic curve (AUC). We used GLM to test the influence of the area of occurrence estimated, the number of records of the species and the complexity of the models on the TSS and AUC. Our results show that climatic variables largely govern the distribution of species, but the variables that capture the local environmental variations are relatively important in the study area. The TSS was significantly influenced by the number of records and complexity of models while the AUC suffered from the effect of all three evaluated factors. The interaction between these factors is an important issue and be considered for new reviews on both measures and with different modeling techniques. Our results also showed that the distributions of some species were overestimated and other corresponded well with the occurrence known to us. Indeed our results have foundations to support new field surveys, assessment of priority areas and conservation plans, and inferences of the effects of environmental change on species of the Atlantic Forest.

The objectives of this research were to 1) measure the extent to which water vapor movement results in water accumulation in freezing base materials; 2) evaluate the effect of soil stabilization on water vapor movement in freezing base materials; 3) determine if the corresponding changes in water content are sufficient to cause frost heave during winter; 4) determine if the corresponding changes in water content are sufficient to cause reductions in stiffness during spring; 5) evaluate relationships between selected material properties, freezing conditions, and the occurrence and impact of water vapor movement; and 6) numerically simulate heat and water movement in selected pavement design scenarios. The research involved extensive laboratory and field testing, statistical analyses, and numerical modeling. The results of the laboratory testing, which included gradations, Atterberg limits, soil classifications, specific gravity and absorption values, electrical conductivity values, moisture-density relationships, soil-water characteristic curves, moisture-stiffness curves, hydraulic conductivity values, and frost susceptibility assessments, were used to characterize each material and enable subsequent statistical analyses. Testing of both treated and untreated materials enabled investigation of a wide variety of material properties. The results of the field testing, which included temperature, moisture content, water potential, elevation, and stiffness data over time, provided the basis for comparing pavement sections with and without capillary barriers and established the framework for numerical modeling. In a pavement section with a capillary barrier underlying the base layer, water vapor movement from the subgrade through the capillary barrier may be expected to increase the water content of the base layer by 1 to 3 percent during a typical winter season in northern Utah for base materials similar to those studied in this research. During winter, cold temperatures create an ideal environment for water vapor to travel upward from the warm subgrade soil below the frost line, through the capillary barrier, and into the base material. Soil stabilization can lead to increased or decreased amounts of water vapor movement in freezing base materials depending on the properties of the stabilized soil, which may be affected by gradation, mineralogy, and stabilizer type and concentration. Accumulation of water from long-term water vapor movement into frost-susceptible base materials underlain by a capillary barrier can lead to frost heave of the base layer as it approaches saturation, as water available in the layer can be redistributed upwards to create ice lenses upon freezing. However, the incremental increase in total water content that may occur exclusively from water vapor movement during a single winter season in northern Utah would not be expected to cause measurable increases in thaw weakening of the base layer during spring. Because water in a base layer overlying a capillary barrier cannot drain until nearly reaching positive pore pressures, the base layer will remain indefinitely saturated or nearly saturated as demonstrated in this research. For materials similar to those studied in this research, potentially important material properties related to the occurrence of water vapor movement during freezing include dry density, percent of material finer than the No. 200 sieve, percent of material finer than 0.02 mm, apparent specific gravity, absorption, initial water content, porosity, degree of saturation, hydraulic conductivity, and electrical conductivity. The rate at which water vapor movement occurs is also dependent on the thermal gradient within the given material, where higher thermal gradients are associated with higher amounts of water vapor movement. The numerical modeling supported the field observations that the capillary barrier effectively trapped moisture in the overlying base material, causing it to remain saturated or nearly saturated throughout the monitoring period. Only non-frost-susceptible aggregate base materials should be specified for use in cold climates in conjunction with capillary barriers, and the base material in this case should be assumed to remain in a saturated or nearly saturated condition during the entire service life of the pavement. Further study is recommended on water vapor movement in freezing aggregate base materials.

The society of today relies a lot on the industry and the automation of factory tasks is more prevalent than ever before. However, the machines taking on these tasks require maintenance to continue operating. This maintenance is typically given periodically and can be expensive while sometimes requiring expert knowledge. Thus it would be very beneficial if one could predict when a machine needs maintenance and only employ maintenance as necessary. One method to predict when maintenance is necessary is to collect sensor data from a machine and analyse it for anomalies. Anomalies are usually an indicator of unexpected behaviour and can therefore show when a machine needs maintenance. Due to concerns like privacy and security, it is often not allowed for the data to leave the local system. Hence it is necessary to perform this kind of anomaly detection in an online manner and in an edge environment. This environment imposes limitations on hardware and computational ability. In this thesis we consider four machine learning anomaly detection methods that can learn and detect anomalies in this kind of environment. These methods are LoOP, iForestASD, KitNet and xStream. We first evaluate the four anomaly detectors on the Skoltech Anomaly Benchmark using their suggested metrics as well as the Receiver Operating Characteristic curves. We also perform further evaluation on two data sets provided by the company Gebhardt. The experimental results are promising and indicate that the considered methods perform well at the task of anomaly detection. We finally propose some avenues for future work, such as implementing a dynamically changing anomaly threshold. / Dagens samhälle är väldigt beroende av industrin och automatiseringen av fabriksuppgifter är mer förekommande än någonsin. Dock kräver maskinerna som tar sig an dessa uppgifter underhåll för att forsätta arbeta. Detta underhåll ges typiskt periodvis och kan vara dyrt och samtidigt kräva expertkunskap. Därför skulle det vara väldigt fördelaktigt om det kunde förutsägas när en maskin behövde underhåll och endast göra detta när det är nödvändigt. En metod för att förutse när underhåll krävs är att samla in sensordata från en maskin och analysera det för att hitta anomalier. Anomalier fungerar ofta som en indikator av oväntat beteende, och kan därför visa att en maskin behöver underhåll. På grund av frågor som integritet och säkerhet är det ofta inte tillåtet att datan lämnar det lokala systemet. Därför är det nödvändigt att denna typ av anomalidetektering genomförs sekventiellt allt eftersom datan samlas in, och att detta sker på nätverkskanten. Miljön som detta sker i påtvingar begränsningar på både hårdvara och beräkningsförmåga. I denna avhandling så överväger vi fyra anomalidetektorer som med användning av maskininlärning lär sig och upptäcker anomalier i denna sorts miljö. Dessa metoder är LoOP, iForestASD, KitNet och xStream. Vi analyserar först de fyra anomalidetektorerna genom Skoltech Anomaly Benchmark där vi använder deras föreslagna mått samt ”Receiver Operating Characteristic”-kurvor. Vi genomför även vidare analys på två dataset som vi har tillhandhållit av företaget Gebhardt. De experimentella resultaten är lovande och indikerar att de övervägda metoderna presterar väl när det kommer till detektering av anomalier. Slutligen föreslår vi några idéer som kan utforskas för framtida arbete, som att implementera en tröskel för anomalidetektering som anpassar sig dynamiskt.

No description available.

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Nas últimas décadas, teorias têm sido formuladas para interpretar o comportamento de solos não saturados e estas têm se mostrado coerentes com resultados experimentais. Paralelamente, várias técnicas de campo e de laboratório têm sido desenvolvidas. No entanto, a determinação experimental dos parâmetros dos solos não saturados é cara, morosa, exige equipamentos especiais e técnicos experientes. Como resultado, essas teorias têm aplicação limitada a pesquisas acadêmicas e são pouco utilizados na prática da engenharia. Para superar este problema, vários pesquisadores propuseram equações para representar matematicamente o comportamento de solos não saturados. Estas proposições são baseadas em índices físicos, caracterização do solo, em ensaios convencionais ou simplesmente em ajustes de curvas. A relação entre a umidade e a sucção matricial, convencionalmente denominada curva característica de sucção do solo (SWCC) é também uma ferramenta útil na previsão do comportamento de engenharia de solos não saturados. Existem muitas equações para representar matematicamente a SWCC. Algumas são baseadas no pressuposto de que sua forma está diretamente relacionada com a distribuição dos poros e, portanto, com a granulometria. Nestas proposições, os parâmetros são calibrados pelo ajuste da curva de dados experimentais. Outros métodos supõem que a curva pode ser estimada diretamente a partir de propriedades físicas dos solos. Estas propostas são simples e conveniente para a utilização prática, mas são substancialmente incorretas, uma vez que ignoram a influência do teor de umidade, nível de tensões, estrutura do solo e mineralogia. Como resultado, a maioria tem sucesso limitado, dependendo do tipo de solo. Algumas tentativas têm sido feitas para prever a variação da resistência ao cisalhamento com relação a sucção matricial. Estes procedimentos usam, como uma ferramenta, direta ou indiretamente, a SWCC em conjunto com os parâmetros efetivos de resistência c e . Este trabalho discute a aplicabilidade de três equações para previsão da SWCC (Gardner, 1958; van Genuchten, 1980; Fredlund; Xing, 1994) para vinte e quatro amostras de solos residuais brasileiros. A adequação do uso da curva característica normalizada, proposta por Camapum de Carvalho e Leroueil (2004), também foi investigada. Os parâmetros dos modelos foram determinados por ajuste de curva, utilizando técnicas de problema inverso; dois métodos foram usados: algoritmo genético (AG) e Levenberq-Marquardt. Vários parâmetros que influênciam o comportamento da SWCC são discutidos. A relação entre a sucção matricial e resistência ao cisalhamento foi avaliada através de ajuste de curva utilizando as equações propostas por Öberg (1995); Sällfors (1997), Vanapalli et al., (1996), Vilar (2007); Futai (2002); oito resultados experimentais foram analisados. Os vários parâmetros que influênciam a forma da SWCC e a parcela não saturadas da resistência ao cisalhamento são discutidos. / In the last decades, theories have been formulated to interpret the behavior of unsaturated soils and found to be consistent with the experimental response. Besides, several techniques for field and laboratory testing have been developed, as well. However, the experimental determination of unsaturated soil parameters is costly, time-consuming, requires particular test equipments and experienced technicians. As a result, these theories application are limited to academic researches and are barely used in engineering practice. To overcome this issue, several researchers proposed equations to mathematically represent the experimental behavior unsaturated soils. These propositions are based on physical indexes, soil characterization, and current laboratory tests or simply curve fitting. The relationship of soil-water content and matric suction, conventionally referred to as the soil-water characteristic curve (SWCC) is also useful tool in the prediction of the engineering behavior of unsaturated soils. There are many equations to mathematically represent SWCC. Some are based on the assumption that its shape is directly related to the pore distribution, and, therefore, the grain size distribution. In these propositions the parameters are calibrated by curve adjustment of the experimental data. Others assume that the curve can be directly estimated from physical properties of soils. These proposals are simple and convenient for practical use, but are substantially incorrect since they disregard the influence of moisture content, stress level, soil structure and mineralogy. As a result, most of them have limited success depending on soil types. Some attempts have also been made to predict the variation of the shear strength with respect to matric suction. These procedures use SWCC as a tool either directly or indirectly along with the saturated strength parameters c and . This work discusses the applicability of three SWCC equations (Gardner, 1958; van Genuchten, 1980; and Fredlund and Xing, 1994) for twenty four residual soils from Brazil. The suitability of the normalized soil-water characteristic curve, proposed by Camapum de Carvalho and Leroueil (2004), was also investigated. Models parameters were determined by curve fitting, using inverse problem techniques; two optimization methods were used: Genetic Algorithm (GA) and Levenberq-Marquardt method. Several parameters that influence the SWCC behavior are discussed, as well. The relationship between matric suction and shear strength was evaluated by curve fitting using the equations proposed by Öberg and Sällfors (1995, 1997), Vanapalli et al., (1996), Vilar (2007) and Futai (2002); eight experimental results were analyzed. Several parameters that influence the SWCC behavior and the unsaturated shear strength are discussed, as well.

Σκοπός αυτής της διπλωματικής εργασίας είναι να εμβαθύνουμε στη λειτουργία φωτοβολταϊκού πλαισίου μονοκρυσταλλικού πυριτίου και μέσα από τα αριθμητικά δεδομένα των μετρήσεων και των υπολογισμών, να αποφανθούμε πώς η λειτουργία σε πραγματικές συνθήκες μπορεί να επηρεάσει την παραγόμενη ισχύ του. Στα πλαίσια αυτά, πραγματοποιήθηκαν μετρήσεις ρεύματος και τάσης, στο χώρο του τμήματος των Ηλεκτρολόγων Μηχανικών και Τεχνολογίας Υπολογιστών, με φωτοβολταϊκό πλαίσιο μονοκρυσταλλικού πυριτίου ισχύος αιχμής 80 W. Οι μετρήσεις γίνονταν μια φορά την εβδομάδα κατά τη διάρκεια ενός έτους περίπου (2008-2009) και στόχος ήταν να διεξαχθούν μετρήσεις υπό διάφορες συνθήκες ακτινοβολίας και θερμοκρασίας και για αρκετές γωνίες κλίσης ώστε να αποκτήσουμε μια ολοκληρωμένη εικόνα της ενεργειακής του συμπεριφοράς. Στη διάρκεια των μετρήσεων αλλάζαμε την τιμή ενός μεταβλητού φορτίου, για να πάρουμε τη χαρακτηριστική ρεύματος τάσης του συγκεκριμένου πλαισίου και επιπλέον σημειώναμε την ακτινοβολία, τη θερμοκρασία του περιβάλλοντος, του κυττάρου και της πίσω όψης του, καθώς και της κλίσης τοποθέτησης. Ακόμα ελέγχαμε πώς επηρεάζει τη χαρακτηριστική καμπύλη I-V, και κατά συνέπεια την απόδοση, τυχόν φυσική σκίαση από παρακείμενο αντικείμενο. Ο προσανατολισμός των πλαισίων ήταν πάντα προς το Νότο, ώστε να έχουμε περισσότερες ώρες ηλιοφάνειας, μίας και η Ελλάδα είναι χώρα του βόρειου ημισφαιρίου. Κατά την επεξεργασία των μετρήσεων καταλήξαμε στην βέλτιστη κλίση τοποθέτησης του πλαισίου ανά εποχή και είδαμε πως η ακτινοβολία επιδρά θετικά στην απόδοση του σε αντίθεση με τη θερμοκρασία του κυττάρου που τη μειώνει όταν αυτή αυξάνεται. Τέλος, έγινε μια σύγκριση των τιμών που δίνει ο κατασκευαστής σε εργαστηριακό περιβάλλον με τις τιμές των μετρήσεων για να διαπιστώσουμε τις απώλειες που έχουμε όταν το μονοκρυσταλλικό πλαίσιο λειτουργεί σε πραγματικές συνθήκες. / The aim of this diploma thesis is to take a better look at the operation of a monocrystalline silicon photovoltaic module and through the numerical data of measurements and the calculations, to come to a conclusion about how the operation in real conditions can influence his produced power. Measurements of current and tendency have been made in the area of the department of Electrical and Computer Engineering using a monocrystalline silicon photovoltaic module of peak power 80 W. The measurements took place once a week for about a year (2008-2009) and our goal was to obtain measurements under various conditions of radiation and temperature and for some angles of bent so that we acquire a completed picture of its energy behavior. During the measurements we changed a variable load, in order to form the characteristic curve of current and tendency of the module and we also noted down the radiation, the environmental, the cell and the back side temperature of the module, as well as the bent of placement. Moreover, we checked how a possible natural shading from an adjacent object influences the characteristic I-V curve, and as a result the efficiency of the module. The orientation of the module was always South, in order to gain more hours of sunlight, since Greece is a country of the northern hemisphere. While processing the measurements, we found the optimal bent of placement per season for the module and we saw that the radiation affects positively its efficiency contrary to the cell temperature that decreases the efficiency when increased. Finally, we compare the electrical specifications in laboratorial environment that the constructor gives, with the measurements in order to realise the losses that we have when the monocrystalline module functions in real conditions.