116 resultados para Second Building
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Kristiina Hormia-Poutasen esitys CBUC-konferenssissa Barcelonassa 12.4.2013.
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Kristiina Hormia-Poutasen esitys CBUC-konferenssissa Barcelonassa 12.4.2013.
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Kristiina Hormia-Poutasen esitys CBUC-konferenssissa Barcelonassa 12.4.2013.
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Kristiina Hormia-Poutasen esitys CBUC-konferenssissa 12.4.2013 Barcelonassa.
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Waste combustion has gone from being a volume reducing discarding-method to an energy recovery process for unwanted material that cannot be reused or recycled. Different fractions of waste are used as fuel today, such as; municipal solid waste, refuse derived fuel, and solid recovered fuel. Furthermore, industrial waste, normally a mixture between commercial waste and building and demolition waste, is common, either as separate fuels or mixed with, for example, municipal solid waste. Compared to fossil or biomass fuels, waste mixtures are extremely heterogeneous, making it a complicated fuel. Differences in calorific values, ash content, moisture content, and changing levels of elements, such as Cl and alkali metals, are common in waste fuel. Moreover, waste contains much higher levels of troublesome trace elements, such as Zn, which is thought to accelerate a corrosion process. Varying fuel quality can be strenuous on the boiler system and may cause fouling and corrosion of heat exchanger surfaces. This thesis examines waste fuels and waste combustion from different angles, with the objective of giving a better understanding of waste as an important fuel in today’s fuel economy. Several chemical characterisation campaigns of waste fuels over longer time periods (10-12 months) was used to determine the fossil content of Swedish waste fuels, to investigate possible seasonal variations, and to study the presence of Zn in waste. Data from the characterisation campaigns were used for thermodynamic equilibrium calculations to follow trends and determine the effect of changing concentrations of various elements. The thesis also includes a study of the thermal behaviour of Zn and a full—scale study of how the bed temperature affects the volatilisation of alkali metals and Zn from the fuel. As mixed waste fuel contains considerable amounts of fresh biomass, such as wood, food waste, paper etc. it would be wrong to classify it as a fossil fuel. When Sweden introduced waste combustion as a part of the European Union emission trading system in the beginning of 2013 there was a need for combustion plants to find a usable and reliable method to determine the fossil content. Four different methods were studied in full-scale of seven combustion plants; 14Canalysis of solid waste, 14C-analysis of flue gas, sorting analysis followed by calculations, and a patented balance method that is using a software program to calculate the fossil content based on parameters from the plant. The study showed that approximately one third of the coal in Swedish waste mixtures has fossil origins and presented the plants with information about the four different methods and their advantages and disadvantages. Characterisation campaigns also showed that industrial waste contain higher levels of trace elements, such as Zn. The content of Zn in Swedish waste fuels was determined to be approximately 800 mg kg-1 on average, based on 42 samples of solid waste from seven different plants with varying mixtures between municipal solid waste and industrial waste. A review study of the occurrence of Zn in fuels confirmed that the highest amounts of Zn are present in waste fuels rather than in fossil or biomass fuels. In tires, Zn is used as a vulcanizing agent and can reach concentration values of 9600-16800 mg kg-1. Waste Electrical and Electronic Equipment is the second Zn-richest fuel and even though on average Zn content is around 4000 mg kg-1, the values of over 19000 mg kg-1 were also reported. The increased amounts of Zn, 3000-4000 mg kg-1, are also found in municipal solid waste, sludge with over 2000 mg kg-1 on average (some exceptions up to 49000 mg kg-1), and other waste derived fuels (over 1000 mg kg-1). Zn is also found in fossil fuels. In coal, the average level of Zn is 100 mg kg-1, the higher amount of Zn was only reported for oil shale with values between 20-2680 mg kg-1. The content of Zn in biomass is basically determined by its natural occurrence and it is typically 10-100 mg kg-1. The thermal behaviour of Zn is of importance to understand the possible reactions taking place in the boiler. By using thermal analysis three common Zn-compounds were studied (ZnCl2, ZnSO4, and ZnO) and compared to phase diagrams produced with thermodynamic equilibrium calculations. The results of the study suggest that ZnCl2(s/l) cannot exist readily in the boiler due to its volatility at high temperatures and its conversion to ZnO in oxidising conditions. Also, ZnSO4 decomposes around 680°C, while ZnO is relatively stable in the temperature range prevailing in the boiler. Furthermore, by exposing ZnO to HCl in a hot environment (240-330°C) it was shown that chlorination of ZnO with HCl gas is possible. Waste fuel containing high levels of elements known to be corrosive, for example, Na and K in combination with Cl, and also significant amounts of trace elements, such as Zn, are demanding on the whole boiler system. A full-scale study of how the volatilisation of Na, K, and Zn is affected by the bed temperature in a fluidised bed boiler was performed parallel with a lab-scale study with the same conditions. The study showed that the fouling rate on deposit probes were decreased by 20 % when the bed temperature was decreased from 870°C to below 720°C. In addition, the lab-scale experiments clearly indicated that the amount of alkali metals and Zn volatilised depends on the reactor temperature.
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The goal of this thesis is to build a viral marketing management framework for a Finnish medium sized gaming company. This is achieved by first finding and building a theoretical five step management process framework based on literature, analyzing current model and giving recommendations for the case company to develop its own management process. In addition, viral marketing research is still in early stage resulting this study to propose its own take on the definition in the theory part. Empirical part is based on qualitative interviews, campaign material and secondary sources and is aimed to find out and analyze the case company’s current viral marketing state and to give recommendations to it. The final outcome of the study is a general, theoretical management framework for viral marketing campaigns and specified recommendations for the case company.
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An augmented reality (AR) device must know observer’s location and orientation, i.e. observer’s pose, to be able to correctly register the virtual content to observer’s view. One possible way to determine and continuously follow-up the pose is model-based visual tracking. It supposes that a 3D model of the surroundings is known and that there is a video camera that is fixed to the device. The pose is tracked by comparing the video camera image to the model. Each new pose estimate is usually based on the previous estimate. However, the first estimate must be found out without a prior estimate, i.e. the tracking must be initialized, which in practice means that some model features must be identified from the image and matched to model features. This is known in literature as model-to-image registration problem or simultaneous pose and correspondence problem. This report reviews visual tracking initialization methods that are suitable for visual tracking in ship building environment when the ship CAD model is available. The environment is complex, which makes the initialization non-trivial. The report has been done as part of MARIN project.
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In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Panel at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Panel at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014