abstract: As the photovoltaic (PV) power plants age in the field, the PV modules degrade and generate visible and invisible defects. A defect and statistical degradation rate analysis of photovoltaic (PV) power plants is presented in two-part thesis. The first part of the thesis deals with the defect analysis and the second part of the thesis deals with the statistical degradation rate analysis. In the first part, a detailed analysis on the performance or financial risk related to each defect found in multiple PV power plants across various climatic regions of the USA is presented by assigning a risk priority number (RPN). The RPN for all the defects in each PV plant is determined based on two databases: degradation rate database; defect rate database. In this analysis it is determined that the RPN for each plant is dictated by the technology type (crystalline silicon or thin-film), climate and age. The PV modules aging between 3 and 19 years in four different climates of hot-dry, hot-humid, cold-dry and temperate are investigated in this study. In the second part, a statistical degradation analysis is performed to determine if the degradation rates are linear or not in the power plants exposed in a hot-dry climate for the crystalline silicon technologies. This linearity degradation analysis is performed using the data obtained through two methods: current-voltage method; metered kWh method. For the current-voltage method, the annual power degradation data of hundreds of individual modules in six crystalline silicon power plants of different ages is used. For the metered kWh method, a residual plot analysis using Winters’ statistical method is performed for two crystalline silicon plants of different ages. The metered kWh data typically consists of the signal and noise components. Smoothers remove the noise component from the data by taking the average of the current and the previous observations. Once this is done, a residual plot analysis of the error component is performed to determine the noise was successfully separated from the data by proving the noise is random. / Dissertation/Thesis / Masters Thesis Engineering 2016

Yes / Risk Management is one of the most relevant approaches and systematic application of strategies, procedures and practices management that have been introduced in literature to identifying and analysing risks which exist through the whole life of a product or a process. As a quality management tool, the novelty of this paper suggests a modified Failure Modes and Effect Analysis (FMEA) for understanding the non-technical risk comprehensively, and to attain a systemic methodology by decomposing the risk for nine risk categories including an appropriate 84 Risk Indicators (RI's) within all those categories through the Life Cycle (LC) stages of power plants. These risk categories have been identified as: economic risks, environmental and safety health risks, social risks, technological risks, customer/demand risks, supply chain risks, internal and operational business process risks, human resources risks and management risks. These indicators are collected from literatures. The enhanced FMEA has combined the exponential and the weighted geometric mean (WGM) to calculate the Exponential Weighted Geometric Mean-RPN (EWGM-RPN). The EWGM-RPN can be used to evaluate the risk level, after which the high-risk areas can be determined. Subsequently, effective actions either preventive or corrective can be taken in time to reduce the risk to an acceptable level. However, in this paper the FMEA will not adapt an action plan. Due to that, all RPN's will be considered depending on the point scale (1 to 5) afterward, the results will be combined and extended later with AHP. This developed methodology is able to boost effective decision- making about risks, improve the awareness towards the risk management at power plants, and assist the top management to have an acceptable and preferable understanding of the organisation than lower level managers do who are close to the day-to-day (tactical plan). Additionally, this will support the organisation to develop strategic plans which are for long term. And the essential part of applying this methodology is the economic benefit. Also, this paper includes developed sustainability perspective indicators with a new fourth pillar, which is the technological dimension. The results of the analysis show that the potential strategic makers should pay special attention to the environmental and internal and operational business process risks. The developed methodology will be applied and validated for different power plants in the Middle East. An expanded validation is required to completely prove drawbacks and benefits after completing the Analytical Hierarchy Process (AHP) model. / Hashemite University, Jordan

Rapporten är skriven för ett högskoleingenjörsexamensarbete på kungliga tekniska högskolan, inom programmet maskinteknik, med inriktning industriell ekonomi och produktion. Bakgrunden av detta arbete ska ge läsaren en grund för de olika modellerna, elbilar och vätgasbilar samt väcka ett intresse för att bevara säkerheten med valet av bil. Syftet och målet med denna studie har varit att presentera en jämförelsestudie, gällande elbilar och vätgasbilar, samt svara på frågeställningarna som arbetet tagit fram. Resultatet av arbetet bygger på både FMEA- analyser för vätgasbilar och elbilar, samt jämförelsematris som ger en förtydligad bild på skillnader mellan elbilar och vätgasbilar, ur vissa valda funktioner. En förtydligad bild av FMEA analysen har byggt, genom att tillämpa ett paretodiagram som beskriver de olika risker och prioritering som finns för respektive modell. Rekommendationer och ytterligare säkerhetsarbeten för att minimera dessa risker beskrivs i FMEA analysen, utifrån indata och beskrivningar från tidigare rapporter, samt kunskap från studier. Resultatet från FMEA- analysen, paretodiagrammet, samt jämförelsematrisen visar att vätgasbilar är en säkrare modell och har en framtid eftersom utvecklingsmöjligheterna fortfarande finns, då dessa är nya på marknaden. Vätgasbilen är även mindre riskbenägen modell jämfört med elbilar, detta kan man visa med hjälp av RPN-talet, som är lägre för vätgasbilar, i jämförelse med elbilarnas RPN-tal. / The background of this thesis will give the reader the basis for the models of electric and hydrogen fueled vehicles. The purpose and goal of this study has been to present a comparative study regarding electric and hydrogen vehicles, and to answer the questions that the study has raised. The results of the work are based on both FMEA analysis for hydrogen and electric vehicles, as well as a comparison matrix that provides a clarified picture of the differences between electric vehicles and hydrogen vehicles, through certain selected factors. A clarified picture of the FMEA analysis results has been built by applying a pareto diagram that describes the different risks of each model and also what their priorities are. Recommendations and additional safety work to minimize these risks are suggested and described in the FMEA analysis, based on input data and descriptions from previous reports, as well as gained knowledge from studies. The results from the FMEA analysis, pareto-diagram and the comparison matrix shows that hydrogen vehicles are a less risk-prone model compared to electric vehicles and have a bright future as development opportunities still exist, this due to the fact that they are still new in the automotive industry. This can be proved with the help of the RPN number for hydrogen vehicles, which is lower compared to the RPN number of electric vehicles.

Offshore oil and gas exploitation is principally conducted using dry or wet tree systems, otherwise called the subsea Xmas tree system. Due to the shift to deeper waters, subsea production system (SPS) has come to be a preferred technology with attendant economic benefits. At the centre of the SPS is the subsea control module (SCM), responsible for the proper functioning and monitoring of the entire system. With increasing search for hydrocarbons in deep and ultra-deepwaters, the SCM system faces important environmental, safety and reliability challenges and little research has been done in this area. Analysis of the SCM reliability then becomes very fundamental due to the huge cost associated with failure. Several tools are available for this analysis, but the FMECA stands out due to its ability to not only provide failure data, but also showcase the system’s failure modes and mechanisms associated with the subsystems and components being evaluated. However, the technique has been heavily challenged in various literatures for several reasons. To close this gap, a novel multi-criteria approach is developed for the analysis and ranking of the SCM failures modes. This research specifically focusses on subsea tree-mounted electro-hydraulic (E-H) SCM responsible for the underwater control of oil and gas production. A risk identification of the subsea control module is conducted using industry experts. This is followed by a comprehensive component based FMECA analysis of the SCM conducted with the conventional RPN technique, which reveals the most critical failure modes for the SCM. A novel framework is developed using multi-criteria fuzzy TOPSIS methodology and applied to the most critical failure modes obtained from the FMECA evaluation using unconventional parameters. Finally, a validation of these results is performed using a stochastic input evaluation and SCM failure data obtained from the offshore industry standard reliability database, OREDA.

Offshore oil and gas exploitation is principally conducted using dry or wet tree systems, otherwise called the subsea Xmas tree system. Due to the shift to deeper waters, subsea production system (SPS) has come to be a preferred technology with attendant economic benefits. At the centre of the SPS is the subsea control module (SCM), responsible for the proper functioning and monitoring of the entire system. With increasing search for hydrocarbons in deep and ultra-deepwaters, the SCM system faces important environmental, safety and reliability challenges and little research has been done in this area. Analysis of the SCM reliability then becomes very fundamental due to the huge cost associated with failure. Several tools are available for this analysis, but the FMECA stands out due to its ability to not only provide failure data, but also showcase the system’s failure modes and mechanisms associated with the subsystems and components being evaluated. However, the technique has been heavily challenged in various literatures for several reasons. To close this gap, a novel multi-criteria approach is developed for the analysis and ranking of the SCM failures modes. This research specifically focusses on subsea tree-mounted electro-hydraulic (E-H) SCM responsible for the underwater control of oil and gas production. A risk identification of the subsea control module is conducted using industry experts. This is followed by a comprehensive component based FMECA analysis of the SCM conducted with the conventional RPN technique, which reveals the most critical failure modes for the SCM. A novel framework is developed using multi-criteria fuzzy TOPSIS methodology and applied to the most critical failure modes obtained from the FMECA evaluation using unconventional parameters. Finally, a validation of these results is performed using a stochastic input evaluation and SCM failure data obtained from the offshore industry standard reliability database, OREDA.

A bactéria Zymomonas mobilis atraiu considerável interesse nas últimas décadas devido ao seu metabolismo único e a suas eficientes características fermentativas na produção de etanol através de açúcares simples. Além disso, dependendo do substrato utilizado outros produtos podem ser obtidos como ácido lático, ácido acético, ácido fórmico, acetona, levana, e sorbitol. Na literatura, a Z. mobilis tem sido proposta como microrganismo mais promissor que a convencional levedura Sacharomyces cerevisiae para a produção industrial de etanol. Na fermentação em modo contínuo o microrganismo apresenta oscilações (i.e., bifurcações Hopf) em baixas taxas de diluição (Df < 0,1/h). Diversos modelos têm sido propostos para descrever a dinâmica oscilatória do cultivo contínuo de Z. mobilis. Entre tais está o modelo de Jöbses et al. (1986) que foi ajustado experimentalmente em baixas taxas de diluição (Df < 0,1/h) e concentrações médias de substrato alimentado (Cso = 150 kg/m³). Recentemente, o modelo foi extrapolado por Elnashaine et al. (2006) que encontrou uma região operacional muito mais rentável a altas taxas de diluição (Df < 2,0/h) e concentração de substrato (Cso = 200 kg/m³). Embora o modelo de Jöbses não tenha sido validado nesta região, nossa contribuição assumirá que esta extrapolação é aceitável e então uma estratégia de controle foi proposta para manter o sistema trabalhando nesta região operacional. Para uma aplicação industrial bem sucedida da Z. mobilis, é necessário uma estratégia de controle eficiente e simples. Esse trabalho analisa o problema de controle e otimização de um biorreator contínuo de biosíntese de etanol pela bactéria modelado por Jöbses et al. (1986). Esse sistema apresenta multiplicidade de equilíbrios em determinadas condições operacionais. A idéia é manter o processo próximo à região de maior produtividade, localizada nas proximidades de um conjunto de bifurcações sela (onde o sistema torna-se instável). Baseado em uma análise sistemática da controlabilidade do sistema usando o índicie não-linear RPN percebe-se que é possível controlar o processo usando um controlador linear. Finalmente o trabalho aborda algumas características importantes no sistema de controle como a utilização de uma transformada nas ações do controlador com vistas a manter o biorreator no ótimo operacional. / Zymomonas mobilis has attracted considerable interest over the past decades pursuant to its unique metabolism and ability to rapidly and efficiently produce ethanol from simple sugars. In addition to ethanol depending on the substrate other fermentation products can occur, such as lactic acid, acetic acid, formic acid, acetone, and sorbitol. In the literature, Zymomonas mobilis has been proposed as a more promising microorganism than conventional yeast Saccharomyces cerevisiae for industrial production of ethanol. The major drawback of this microorganism is that it exhibits sustained oscillations (i.e., Hopf bifurcation) for low dilution rates (i.e., ,Df <=0.1 h-1) when grown in continuous mode. This leads to decreased ethanol productivity and less efficient use of available substrate. Various models have been proposed to describe the oscillatory dynamics of continuous Zymomonas mobilis cultures. One of them is the Jöbses et al. (1986) model that was fitted to experimental data with low dilution rate (i.e.,Df <= 0.1 h-1) and middle inlet substrate concentration (i.e., Cso~=150 kg/m³). Later, it was extrapolated outside of this operating region by Elnashaie et al. (2006), who have found a much more profitable operating region at higher dilution rates (Df~= 2.0 h -¹) and inlet concentrations (Cso~= 200 kg/m³). Notwithstanding the Jöbses's models has not been validated at this region, our contribution will assume that this extrapolation is acceptable and we will propose a control strategy to maintain the system working at this more profitable operating region. For a successful application of any industrial Z. mobilis facility, it is necessary to have an efficient and simple control strategy. This work analyzes the control and optimization problem of a continuous Z. mobilis bioreactor modeled by Jöbses et al. (1986). This system has steady state multiplicity in part of the operating range. The idea is to maintain the process close to the manifold border where is achievable the highest ethanol production. Based on a systematically analysis of the operational controllability using the nonlinear RPN indices it is identified that the process can be controlled using a linear controller. Finally in this work is proposed a variable transformation that makes easy to maintain the bioreactor close to the optimum.

A bactéria Zymomonas mobilis atraiu considerável interesse nas últimas décadas devido ao seu metabolismo único e a suas eficientes características fermentativas na produção de etanol através de açúcares simples. Além disso, dependendo do substrato utilizado outros produtos podem ser obtidos como ácido lático, ácido acético, ácido fórmico, acetona, levana, e sorbitol. Na literatura, a Z. mobilis tem sido proposta como microrganismo mais promissor que a convencional levedura Sacharomyces cerevisiae para a produção industrial de etanol. Na fermentação em modo contínuo o microrganismo apresenta oscilações (i.e., bifurcações Hopf) em baixas taxas de diluição (Df < 0,1/h). Diversos modelos têm sido propostos para descrever a dinâmica oscilatória do cultivo contínuo de Z. mobilis. Entre tais está o modelo de Jöbses et al. (1986) que foi ajustado experimentalmente em baixas taxas de diluição (Df < 0,1/h) e concentrações médias de substrato alimentado (Cso = 150 kg/m³). Recentemente, o modelo foi extrapolado por Elnashaine et al. (2006) que encontrou uma região operacional muito mais rentável a altas taxas de diluição (Df < 2,0/h) e concentração de substrato (Cso = 200 kg/m³). Embora o modelo de Jöbses não tenha sido validado nesta região, nossa contribuição assumirá que esta extrapolação é aceitável e então uma estratégia de controle foi proposta para manter o sistema trabalhando nesta região operacional. Para uma aplicação industrial bem sucedida da Z. mobilis, é necessário uma estratégia de controle eficiente e simples. Esse trabalho analisa o problema de controle e otimização de um biorreator contínuo de biosíntese de etanol pela bactéria modelado por Jöbses et al. (1986). Esse sistema apresenta multiplicidade de equilíbrios em determinadas condições operacionais. A idéia é manter o processo próximo à região de maior produtividade, localizada nas proximidades de um conjunto de bifurcações sela (onde o sistema torna-se instável). Baseado em uma análise sistemática da controlabilidade do sistema usando o índicie não-linear RPN percebe-se que é possível controlar o processo usando um controlador linear. Finalmente o trabalho aborda algumas características importantes no sistema de controle como a utilização de uma transformada nas ações do controlador com vistas a manter o biorreator no ótimo operacional. / Zymomonas mobilis has attracted considerable interest over the past decades pursuant to its unique metabolism and ability to rapidly and efficiently produce ethanol from simple sugars. In addition to ethanol depending on the substrate other fermentation products can occur, such as lactic acid, acetic acid, formic acid, acetone, and sorbitol. In the literature, Zymomonas mobilis has been proposed as a more promising microorganism than conventional yeast Saccharomyces cerevisiae for industrial production of ethanol. The major drawback of this microorganism is that it exhibits sustained oscillations (i.e., Hopf bifurcation) for low dilution rates (i.e., ,Df <=0.1 h-1) when grown in continuous mode. This leads to decreased ethanol productivity and less efficient use of available substrate. Various models have been proposed to describe the oscillatory dynamics of continuous Zymomonas mobilis cultures. One of them is the Jöbses et al. (1986) model that was fitted to experimental data with low dilution rate (i.e.,Df <= 0.1 h-1) and middle inlet substrate concentration (i.e., Cso~=150 kg/m³). Later, it was extrapolated outside of this operating region by Elnashaie et al. (2006), who have found a much more profitable operating region at higher dilution rates (Df~= 2.0 h -¹) and inlet concentrations (Cso~= 200 kg/m³). Notwithstanding the Jöbses's models has not been validated at this region, our contribution will assume that this extrapolation is acceptable and we will propose a control strategy to maintain the system working at this more profitable operating region. For a successful application of any industrial Z. mobilis facility, it is necessary to have an efficient and simple control strategy. This work analyzes the control and optimization problem of a continuous Z. mobilis bioreactor modeled by Jöbses et al. (1986). This system has steady state multiplicity in part of the operating range. The idea is to maintain the process close to the manifold border where is achievable the highest ethanol production. Based on a systematically analysis of the operational controllability using the nonlinear RPN indices it is identified that the process can be controlled using a linear controller. Finally in this work is proposed a variable transformation that makes easy to maintain the bioreactor close to the optimum.

abstract: This is a two-part thesis: Part 1 characterizes soiling losses using various techniques to understand the effect of soiling on photovoltaic modules. The higher the angle of incidence (AOI), the lower will be the photovoltaic (PV) module performance. Our research group has already reported the AOI investigation for cleaned modules of five different technologies with air/glass interface. However, the modules that are installed in the field would invariably develop a soil layer with varying thickness depending on the site condition, rainfall and tilt angle. The soiled module will have the air/soil/glass interface rather than air/glass interface. This study investigates the AOI variations on soiled modules of five different PV technologies. It is demonstrated that AOI effect is inversely proportional to the soil density. In other words, the power or current loss between clean and soiled modules would be much higher at a higher AOI than at a lower AOI leading to excessive energy production loss of soiled modules on cloudy days, early morning hours and late afternoon hours. Similarly, the spectral influence of soil on the performance of the module was investigated through reflectance and transmittance measurements. It was observed that the reflectance and transmittances losses vary linearly with soil density variation and the 600-700 nm band was identified as an ideal band for soil density measurements. Part 2 of this thesis performs statistical risk analysis for a power plant through FMECA (Failure Mode, Effect, and Criticality Analysis) based on non-destructive field techniques and count data of the failure modes. Risk Priority Number is used for the grading guideline for criticality analysis. The analysis was done on a 19-year-old power plant in cold-dry climate to identify the most dominant failure and degradation modes. In addition, a comparison study was done on the current power plant (framed) along with another 18-year-old (frameless) from the same climate zone to understand the failure modes for cold-dry climatic condition. / Dissertation/Thesis / Masters Thesis Engineering 2015

A bactéria Zymomonas mobilis atraiu considerável interesse nas últimas décadas devido ao seu metabolismo único e a suas eficientes características fermentativas na produção de etanol através de açúcares simples. Além disso, dependendo do substrato utilizado outros produtos podem ser obtidos como ácido lático, ácido acético, ácido fórmico, acetona, levana, e sorbitol. Na literatura, a Z. mobilis tem sido proposta como microrganismo mais promissor que a convencional levedura Sacharomyces cerevisiae para a produção industrial de etanol. Na fermentação em modo contínuo o microrganismo apresenta oscilações (i.e., bifurcações Hopf) em baixas taxas de diluição (Df < 0,1/h). Diversos modelos têm sido propostos para descrever a dinâmica oscilatória do cultivo contínuo de Z. mobilis. Entre tais está o modelo de Jöbses et al. (1986) que foi ajustado experimentalmente em baixas taxas de diluição (Df < 0,1/h) e concentrações médias de substrato alimentado (Cso = 150 kg/m³). Recentemente, o modelo foi extrapolado por Elnashaine et al. (2006) que encontrou uma região operacional muito mais rentável a altas taxas de diluição (Df < 2,0/h) e concentração de substrato (Cso = 200 kg/m³). Embora o modelo de Jöbses não tenha sido validado nesta região, nossa contribuição assumirá que esta extrapolação é aceitável e então uma estratégia de controle foi proposta para manter o sistema trabalhando nesta região operacional. Para uma aplicação industrial bem sucedida da Z. mobilis, é necessário uma estratégia de controle eficiente e simples. Esse trabalho analisa o problema de controle e otimização de um biorreator contínuo de biosíntese de etanol pela bactéria modelado por Jöbses et al. (1986). Esse sistema apresenta multiplicidade de equilíbrios em determinadas condições operacionais. A idéia é manter o processo próximo à região de maior produtividade, localizada nas proximidades de um conjunto de bifurcações sela (onde o sistema torna-se instável). Baseado em uma análise sistemática da controlabilidade do sistema usando o índicie não-linear RPN percebe-se que é possível controlar o processo usando um controlador linear. Finalmente o trabalho aborda algumas características importantes no sistema de controle como a utilização de uma transformada nas ações do controlador com vistas a manter o biorreator no ótimo operacional. / Zymomonas mobilis has attracted considerable interest over the past decades pursuant to its unique metabolism and ability to rapidly and efficiently produce ethanol from simple sugars. In addition to ethanol depending on the substrate other fermentation products can occur, such as lactic acid, acetic acid, formic acid, acetone, and sorbitol. In the literature, Zymomonas mobilis has been proposed as a more promising microorganism than conventional yeast Saccharomyces cerevisiae for industrial production of ethanol. The major drawback of this microorganism is that it exhibits sustained oscillations (i.e., Hopf bifurcation) for low dilution rates (i.e., ,Df <=0.1 h-1) when grown in continuous mode. This leads to decreased ethanol productivity and less efficient use of available substrate. Various models have been proposed to describe the oscillatory dynamics of continuous Zymomonas mobilis cultures. One of them is the Jöbses et al. (1986) model that was fitted to experimental data with low dilution rate (i.e.,Df <= 0.1 h-1) and middle inlet substrate concentration (i.e., Cso~=150 kg/m³). Later, it was extrapolated outside of this operating region by Elnashaie et al. (2006), who have found a much more profitable operating region at higher dilution rates (Df~= 2.0 h -¹) and inlet concentrations (Cso~= 200 kg/m³). Notwithstanding the Jöbses's models has not been validated at this region, our contribution will assume that this extrapolation is acceptable and we will propose a control strategy to maintain the system working at this more profitable operating region. For a successful application of any industrial Z. mobilis facility, it is necessary to have an efficient and simple control strategy. This work analyzes the control and optimization problem of a continuous Z. mobilis bioreactor modeled by Jöbses et al. (1986). This system has steady state multiplicity in part of the operating range. The idea is to maintain the process close to the manifold border where is achievable the highest ethanol production. Based on a systematically analysis of the operational controllability using the nonlinear RPN indices it is identified that the process can be controlled using a linear controller. Finally in this work is proposed a variable transformation that makes easy to maintain the bioreactor close to the optimum.

Locating and extracting useful data from images is a task that has been revolutionized in the last decade as computing power has risen to such a level to use deep neural networks with success. A type of neural network that uses the convolutional operation called convolutional neural network (CNN) is suited for image related tasks. Using the convolution operation creates opportunities for the network to learn their own filters, that previously had to be hand engineered. For locating objects in an image the state-of-the-art Faster R-CNN model predicts objects in two parts. Firstly, the region proposal network (RPN) extracts regions from the picture where it is likely to find an object. Secondly, a detector verifies the likelihood of an object being in that region.For this thesis, we review the current literature on artificial neural networks, object detection methods, proposal methods and present our new way of generating proposals. By replacing the RPN with our network, the multiscale proposal network (MPN), we increase the average precision (AP) with 12% and reduce the computation time per image by 10%. / Lokalisering av användbar data från bilder är något som har revolutionerats under det senaste decenniet när datorkraften har ökat till en nivå då man kan använda artificiella neurala nätverk i praktiken. En typ av ett neuralt nätverk som använder faltning passar utmärkt till bilder eftersom det ger möjlighet för nätverket att skapa sina egna filter som tidigare skapades för hand. För lokalisering av objekt i bilder används huvudsakligen Faster R-CNN arkitekturen. Den fungerar i två steg, först skapar RPN boxar som innehåller regioner där nätverket tror det är störst sannolikhet att hitta ett objekt. Sedan är det en detektor som verifierar om boxen är på ett objekt .I denna uppsats går vi igenom den nuvarande litteraturen i artificiella neurala nätverk, objektdektektering, förslags metoder och presenterar ett nytt förslag att generera förslag på regioner. Vi visar att genom att byta ut RPN med vår metod (MPN) ökar vi precisionen med 12% och reducerar tiden med 10%.