4 resultados para Data type converter

em Dalarna University College Electronic Archive


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Continuous casting is a casting process that produces steel slabs in a continuous manner with steel being poured at the top of the caster and a steel strand emerging from the mould below. Molten steel is transferred from the AOD converter to the caster using a ladle. The ladle is designed to be strong and insulated. Complete insulation is never achieved. Some of the heat is lost to the refractories by convection and conduction. Heat losses by radiation also occur. It is important to know the temperature of the melt during the process. For this reason, an online model was previously developed to simulate the steel and ladle wall temperatures during the ladle cycle. The model was developed as an ODE based model using grey box modeling technique. The model’s performance was acceptable and needed to be presented in a user friendly way. The aim of this thesis work was basically to design a GUI that presents steel and ladle wall temperatures calculated by the model and also allow the user to make adjustments to the model. This thesis work also discusses the sensitivity analysis of different parameters involved and their effects on different temperature estimations.

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This report describes a method how to perform measurements on boilers and stoves and how to identify parameters from the measurements for the boiler/stove-model TRNSYS Type 210. The model can be used for detailed annual system simulations using TRNSYS. Experience from measurements on three different pellet stoves and four boilers were used to develop this methodology. Recommendations for the set up of measurements are given and the re-quired combustion theory for the data evaluation and data preparation are given. The data evalua-tion showed that the uncertainties are quite large for the measured flue gas flow rate and for boilers and stoves with high fraction of energy going to the water jacket also the calculated heat rate to the room may have large uncertainties. A methodology for the parameter identification process and identified parameters for two different stoves and three boilers are given. Finally the identified models are compared with measured data showing that the model generally agreed well with meas-ured data during both stationary and dynamic conditions.

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The aim of this study was to investigate electricity supply solutions for an educationalcenter that is being built in Chonyonyo Tanzania. Off-grid power generation solutions andfurther optimization possibilities were studied for the case.The study was done for Engineers Without Borders in Sweden. Who are working withMavuno Project on the educational center. The school is set to start operating in year 2015with 40 girl students in the beginning. The educational center will help to improve genderequality by offering high quality education in a safe environment for girls in rural area.It is important for the system to be economically and environmentally sustainable. Thearea has great potential for photovoltaic power generation. Thus PV was considered as theprimary power generation and a diesel generator as a reliable backup. The system sizeoptimization was done with HOMER. For the simulations HOMER required componentdata, weather data and load data. Common components were chose with standardproperties, the loads were based on load estimations from year 2011 and the weather datawas acquired from NASA database. The system size optimization result for this base casewas a system with 26 kW PW; 5.5 kW diesel generator, 15 kW converter and 112 T-105batteries. The initial cost of the system was 55 875 €, the total net present cost 92 121 €and the levelized cost of electricity 0.264 €/kWh.In addition three optimization possibilities were studied. First it was studied how thesystem should be designed and how it would affect the system size to have night loads(security lights) use DC and could the system then be extended in blocks. As a result it wasfound out that the system size could be decreased as the inverter losses would be avoided.Also the system extension in blocks was found to be possible. The second study was aboutinverter stacking where multiple inverters can work as one unit. This type of connectionallows only the required number of inverters to run while shutting down the excess ones.This would allow the converter-unit to run with higher efficiency and lower powerconsumption could be achieved. In future with higher loads the system could be easilyextendable by connecting more inverters either in parallel or series depending on what isneeded. Multiple inverters would also offer higher reliability than using one centralizedinverter. The third study examined how the choice of location for a centralized powergeneration affects the cable sizing for the system. As a result it was found that centralizedpower generation should be located close to high loads in order to avoid long runs of thickcables. Future loads should also be considered when choosing the location. For theeducational center the potential locations for centralized power generation were found outto be close to the school buildings and close to the dormitories.

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This paper generalizes the HEGY-type test to detect seasonal unit roots in data at any frequency, based on the seasonal unit root tests in univariate time series by Hylleberg, Engle, Granger and Yoo (1990). We introduce the seasonal unit roots at first, and then derive the mechanism of the HEGY-type test for data with any frequency. Thereafter we provide the asymptotic distributions of our test statistics when different test regressions are employed. We find that the F-statistics for testing conjugation unit roots have the same asymptotic distributions. Then we compute the finite-sample and asymptotic critical values for daily and hourly data by a Monte Carlo method. The power and size properties of our test for hourly data is investigated, and we find that including lag augmentations in auxiliary regression without lag elimination have the smallest size distortion and tests with seasonal dummies included in auxiliary regression have more power than the tests without seasonal dummies. At last we apply the our test to hourly wind power production data in Sweden and shows there are no seasonal unit roots in the series.