Effect of heat input on the mechanical properties of welded joints in high strength steels

Experiments were carried out to determine the properties of the welded joints in 8mm thick high-strength steels produced by quenching and tempering and thermomechanical rolling with accelerated cooling (tensile strength 821–835 MPa). The dependence of the strength, elongation, hardness, impact energy and crack opening displacement on the heat input in the range 1.0–0.7 kJ mm21 was determined. The results show that the dependence of the strength of the welded joints decreases and that of the elongation increases. The heat input has only a slight effect on the impact energy and crack opening displacement in the heat-affected zone.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

Luonnonkiertovirtauksen kääntyminen pystyhöyrystimen lämmönvaihtoputkissa

Diplomityössä tutkitaan virtauksen kääntymistä Lappeenrannan teknillisen yliopiston PWR PACTEL –koelaitteiston pystyhöyrystimen lämmönvaihtoputkissa käyttäen APROS–prosessisimulointiohjelmaa. Työn teoriaosassa esitellään pystyhöyrystimillä varustettuja koelaitteistoja, erityisesti PWR PACTEL ja sen höyrystin. Lisäksi esitellään virtauksen kääntymisestä tehtyjä havaintoja ja käsitellään kääntymistä teoreettisesta näkökulmasta. Simulointiosan alussa esitellään työssä käytetty APROS –prosessisimulointiohjelma, sekä sen avulla höyrystimestä luodut mallit. Työssä on tutkittu virtauksen käännöstapahtumaa simuloimalla useita eri transienttitilanteita pienillä primäärimassavirroilla. Simulaatiotapauksissa havaittiin virtauksen kääntyvän höyrystimen eripituisissa lämmönvaihtoputkissa, tilanteesta riippuen pääosin lyhimmissä tai toisiksi lyhimmissä lämmönvaihtoputkissa. Transienttien eri vaiheiden, ts. primäärimassavirran muutos- ja tasaantumisvaiheiden pituuden havaittiin vaikuttavan siihen, minkä pituisissa putkissa kääntyminen tapahtuu ja missä järjestyksessä.

Benefits of gas driven ground source heat pump systems

This thesis studies energy efficiencies and technical properties of gas driven ground source heat pumps and pump systems. The research focuses on two technologies: gas engine driven compressor heat pump and thermally driven gas absorption heat pump. System consist of a gas driven compressor or absorption ground source heat pump and a gas condensing boiler, which covers peak load. The reference system is a standard electrically powered compressor heat pump with electric heating elements for peak load. The systems are compared through primary energy ratios. Coefficient of performances of different heat pump technologies are also compared. At heat pump level, gas driven heat pumps are having lower coefficient of performances as compared with corresponding electric driven heat pump. However, gas heat pumps are competitive when primary energy ratios, where electricity production losses are counted in, are compared. Technically, gas heat pumps can potentially achieve a slightly higher temperatures with greater total energy efficiency as compared to the electric driven heat pump. The primary energy ratios of gas heat pump systems in relation to EHP-system improves when the share of peak load increases. Electric heat pump system's overall energy efficiency is heavily dependent on the electricity production efficiency. Economy as well as CO2-emissions were not examined in this thesis, which however, would be good topics for further study.