Advanced biofuel production: Engineering metabolic pathways for butanol and propane biosynthesis.

Greenhouse gases emitted from energy production and transportation are dramatically changing the climate of Planet Earth. As a consequence, global warming is affecting the living conditions of numerous plant and animal species, including ours. Thus the development of sustainable and renewable liquid fuels is an essential global challenge in order to combat the climate change. In the past decades many technologies have been developed as alternatives to currently used petroleum fuels, such as bioethanol and biodiesel. However, even with gradually increasing production, the market penetration of these first generation biofuels is still relatively small compared to fossil fuels. Researchers have long ago realized that there is a need for advanced biofuels with improved physical and chemical properties compared to bioethanol and with biomass raw materials not competing with food production. Several target molecules have been identified as potential fuel candidates, such as alkanes, fatty acids, long carbon‐chain alcohols and isoprenoids. The current study focuses on the biosynthesis of butanol and propane as possible biofuels. The scope of this research was to investigate novel heterologous metabolic pathways and to identify bottlenecks for alcohol and alkane generation using Escherichia coli as a model host microorganism. The first theme of the work studied the pathways generating butyraldehyde, the common denominator for butanol and propane biosynthesis. Two ways of generating butyraldehyde were described, one via the bacterial fatty acid elongation machinery and the other via partial overexpression of the acetone‐butanol‐ethanol fermentation pathway found in Clostridium acetobutylicum. The second theme of the experimental work studied the reduction of butyraldehyde to butanol catalysed by various bacterial aldehyde‐reductase enzymes, whereas the final part of the work investigated the in vivo kinetics of the cyanobacterial aldehyde deformylating oxygenase (ADO) for the generation of hydrocarbons. The results showed that the novel butanol pathway, based on fatty acid biosynthesis consisting of an acyl‐ACP thioesterase and a carboxylic acid reductase, is tolerant to oxygen, thus being an efficient alternative to the previous Clostridial pathways. It was also shown that butanol can be produced from acetyl‐CoA using acetoacetyl CoA synthase (NphT7) or acetyl‐CoA acetyltransferase (AtoB) enzymes. The study also demonstrated, for the first time, that bacterial biosynthesis of propane is possible. The efficiency of the system is clearly limited by the poor kinetic properties of the ADO enzyme, and for proper function in vivo, the catalytic machinery requires a coupled electron relay system.

Modeling a Network of Heat Exchangers

This research work addresses the problem of building a mathematical model for the given system of heat exchangers and to determine the temperatures, pressures and velocities at the intermediate positions. Such model could be used in nding an optimal design for such a superstructure. To limit the size and computing time a reduced network model was used. The method can be generalized to larger network structures. A mathematical model which includes a system of non-linear equations has been built and solved according to the Newton-Raphson algorithm. The results obtained by the proposed mathematical model were compared with the results obtained by the Paterson approximation and Chen's Approximation. Results of this research work in collaboration with a current ongoing research at the department will optimize the valve positions and hence, minimize the pumping cost and maximize the heat transfer of the system of heat exchangers.

Enhancing business-to-business relationship through value co-creation in traditional business sector: A case of building services engineering

This study discusses the significance of having service as a business logic, and more specifically, how value co-creation can be seen as an enhancing phenomenon to business-to-business relationships in traditional business sector. The purpose of this study is to investigate how value cocreation can enhance a business-to-business relationship in the heating, ventilation and airconditioning (HVAC) industry of building services engineering, through three sub-objectives: to identify what is value in the industry, how value is co-created in the industry, and what is value in a business-to-business relationship in the industry. The theoretical part this study consists of academic knowledge and literature related to the concepts of value, value co-creation and business-to-business relationships. In order to research value co-creation and business-to-business relationships in HVAC industry of building services engineering both, metaphorical and conceptual thinking of service dominant (S-D) logic and more managerial approach of service logic (SL), contributed to the theoretical part of the study. The empirical research conducted for this study is based on seven semi-structured interviews, which constituted the holistic, qualitative single case study method chosen for the research. The data was collected in September 2014 from CEOs, managers and owners representing six building services engineering firms. The interviews were analysed with the help of transcriptions, role-ordered matrices and thematic networks. The findings of this study indicate that value in HVAC industry consists of client expertise and supplier expertise. The result of applying client expertise and supplier expertise to the business-to- business relationship is characterized as value-in-reputation, when continuity, interaction, learning and rapport of the business relationship are ensured. As a result, value co-creation in the industry consists of mutual and separate elements, which the client and the supplier apply in the process, in addition to proactive interaction. The findings of this study, together with the final framework, enhance the understanding of the connection existing between value co-creation and business-to-business relationship. The findings suggest that value in the HVAC industry is characterized by both value-in-use and value-inreputation. Value-in-reputation enhances the formation of value-in-use, and consequently, value cocreation enhances the business-to-business relationship. This study thus contributes to the existing knowledge on the concepts of value and value co-creation in business-to-business relationships.

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.

Permanent magnet synchronous generator design solution for large directdrive wind turbines: Thermal behavior of the LC DD-PMSG

Wind is one of the most compelling forms of indirect solar energy. Available now, the conversion of wind power into electricity is and will continue to be an important element of energy self-sufficiency planning. This paper is one in a series intended to report on the development of a new type of generator for wind energy; a compact, high-power, direct-drive permanent magnet synchronous generator (DD-PMSG) that uses direct liquid cooling (LC) of the stator windings to manage Joule heating losses. The main param-eters of the subject LC DD-PMSG are 8 MW, 3.3 kV, and 11 Hz. The stator winding is cooled directly by deionized water, which flows through the continuous hollow conductor of each stator tooth-coil winding. The design of the machine is to a large degree subordinate to the use of these solid-copper tooth-coils. Both steady-state and timedependent temperature distributions for LC DD-PMSG were examined with calculations based on a lumpedparameter thermal model, which makes it possible to account for uneven heat loss distribution in the stator conductors and the conductor cooling system. Transient calculations reveal the copper winding temperature distribution for an example duty cycle during variable-speed wind turbine operation. The cooling performance of the liquid cooled tooth-coil design was predicted via finite element analysis. An instrumented cooling loop featuring a pair of LC tooth-coils embedded in a lamination stack was built and laboratory tested to verify the analytical model. Predicted and measured results were in agreement, confirming the predicted satisfactory operation of the LC DD-PMSG cooling technology approach as a whole.

Simulation model of wind turbine gearbox and lubrication system

As increasing efficiency of a wind turbine gearbox, more power can be transferred from rotor blades to generator and less power is used to cause wear and heating in the gearbox. By using a simulation model, behavior of the gearbox can be studied before creating expensive prototypes. The objective of the thesis is to model a wind turbine gearbox and its lubrication system to study power losses and heat transfer inside the gearbox and to study the simulation methods of the used software. Software used to create the simulation model is Siemens LMS Imagine.Lab AMESim, which can be used to create one-dimensional mechatronic system simulation models from different fields of engineering. When combining components from different libraries it is possible to create a simulation model, which includes mechanical, thermal and hydraulic models of the gearbox. Results for mechanical, thermal, and hydraulic simulations are presented in the thesis. Due to the large scale of the wind turbine gearbox and the amount of power transmitted, power loss calculations from AMESim software are inaccurate and power losses are modelled as constant efficiency for each gear mesh. Starting values for simulation in thermal and hydraulic simulations were chosen from test measurements and from empirical study as compact and complex design of gearbox prevents accurate test measurements. In further studies to increase the accuracy of the simulation model, components used for power loss calculations needs to be modified and values for unknown variables are needed to be solved through accurate test measurements.

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.

Thick Section Laser Beam Welding of Structural Steels: Methods for Improving Welding Efficiency

Laser beam welding (LBW) is applicable for a wide range of industrial sectors and has a history of fifty years. However, it is considered an unusual method with applications typically limited to welding of thin sheet metal. With a new generation of high power lasers there has been a renewed interest in thick section LBW (also known as keyhole laser welding). There was a growing body of publications during 2001-2011 that indicates an increasing interest in laser welding for many industrial applications, and in last ten years, an increasing number of studies have examined the ways to increase the efficiency of the process. Expanding the thickness range and efficiency of LBW makes the process a possibility for industrial applications dealing with thick metal welding: shipbuilding, offshore structures, pipelines, power plants and other industries. The advantages provided by LBW, such as high process speed, high productivity, and low heat input, may revolutionize these industries and significantly reduce the process costs. The research to date has focused on either increasing the efficiency via optimizing process parameters, or on the process fundamentals, rather than on process and workpiece modifications. The argument of this thesis is that the efficiency of the laser beam process can be increased in a straightforward way in the workshop conditions. Throughout this dissertation, the term “efficiency” is used to refer to welding process efficiency, specifically, an increase in efficiency refers an increase in weld’s penetration depth without increasing laser power level or decreasing welding speed. These methods are: modifications of the workpiece – edge surface roughness and air gap between the joining plates; modification of the ambient conditions – local reduction of the pressure in the welding zone; modification of the welding process – preheating of the welding zone. Approaches to improve the efficiency are analyzed and compared both separately and combined. These experimentally proven methods confirm previous findings and contribute additional evidence which expand the opportunities for laser beam welding applications. The focus of this research was primarily on the effects of edge surface roughness preparation and pre-set air gap between the plates on weld quality and penetration depth. To date, there has been no reliable evidence that such modifications of the workpiece give a positive effect on the welding efficiency. Other methods were tested in combination with the two methods mentioned above. The most promising - combining with reduced pressure method - resulted in at least 100% increase in efficiency. The results of this thesis support the idea that joining those methods in one modified process will provide the modern engineering with a sufficient tool for many novel applications with potential benefits to a range of industries.

Effects of Fin Parameters on Gas-Side Heat Transfer Performance of H-Type Finned Tube Bundle in a Waste Heat Recovery Boiler

Alfa Laval Aalborg Oy designs and manufactures waste heat recovery systems utilizing extended surfaces. The waste heat recovery boiler considered in this thesis is a water-tube boiler where exhaust gas is used as the convective heat transfer medium and water or steam flowing inside the tubes is subject to cross-flow. This thesis aims to contribute to the design of waste heat recovery boiler unit by developing a numerical model of the H-type finned tube bundle currently used by Alfa Laval Aalborg Oy to evaluate the gas-side heat transfer performance. The main objective is to identify weaknesses and potential areas of development in the current H-type finned tube design. In addition, numerical simulations for a total of 15 cases with varying geometric parameters are conducted to investigate the heat transfer and pressure drop performance dependent on H-type fin geometry. The investigated geometric parameters include fin width and height, fin spacing, and fin thickness. Comparison between single and double tube type configuration is also conducted. Based on the simulation results, the local heat transfer and flow behaviour of the H-type finned tube is presented including boundary layer development between the fins, the formation of recirculation zone behind the tubes, and the local variations of flow velocity and temperature within the tube bundle and on the fin surface. Moreover, an evaluation of the effects of various fin parameters on heat transfer and pressure drop performance of H-type finned tube bundle has been provided. It was concluded that from the studied parameters fin spacing and fin width had the most significant effect on tube bundle performance and the effect of fin thickness was the least important. Furthermore, the results suggested that the heat transfer performance would increase due to enhanced turbulence if the current double tube configuration is replaced with single tube configuration, but further investigation and experimental measurements are required in order to validate the results.

Optimizing the Performance of a Heat Exchanger Network

This research is the continuation and a joint work with a master thesis that has been done in this department recently by Hemamali Chathurangani Yashika Jayathunga. The mathematical system of the equations in the designed Heat Exchanger Network synthesis has been extended by adding a number of equipment; such as heat exchangers, mixers and dividers. The solutions of the system is obtained and the optimal setting of the valves (Each divider contains a valve) is calculated by introducing grid-based optimization. Finding the best position of the valves will lead to maximization of the transferred heat in the hot stream and minimization of the pressure drop in the cold stream. The aim of the following thesis will be achieved by practicing the cost optimization to model an optimized network.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.