698 resultados para Lappeenranta University of Technology


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State-of-the-art predictions of atmospheric states rely on large-scale numerical models of chaotic systems. This dissertation studies numerical methods for state and parameter estimation in such systems. The motivation comes from weather and climate models and a methodological perspective is adopted. The dissertation comprises three sections: state estimation, parameter estimation and chemical data assimilation with real atmospheric satellite data. In the state estimation part of this dissertation, a new filtering technique based on a combination of ensemble and variational Kalman filtering approaches, is presented, experimented and discussed. This new filter is developed for large-scale Kalman filtering applications. In the parameter estimation part, three different techniques for parameter estimation in chaotic systems are considered. The methods are studied using the parameterized Lorenz 95 system, which is a benchmark model for data assimilation. In addition, a dilemma related to the uniqueness of weather and climate model closure parameters is discussed. In the data-oriented part of this dissertation, data from the Global Ozone Monitoring by Occultation of Stars (GOMOS) satellite instrument are considered and an alternative algorithm to retrieve atmospheric parameters from the measurements is presented. The validation study presents first global comparisons between two unique satellite-borne datasets of vertical profiles of nitrogen trioxide (NO3), retrieved using GOMOS and Stratospheric Aerosol and Gas Experiment III (SAGE III) satellite instruments. The GOMOS NO3 observations are also considered in a chemical state estimation study in order to retrieve stratospheric temperature profiles. The main result of this dissertation is the consideration of likelihood calculations via Kalman filtering outputs. The concept has previously been used together with stochastic differential equations and in time series analysis. In this work, the concept is applied to chaotic dynamical systems and used together with Markov chain Monte Carlo (MCMC) methods for statistical analysis. In particular, this methodology is advocated for use in numerical weather prediction (NWP) and climate model applications. In addition, the concept is shown to be useful in estimating the filter-specific parameters related, e.g., to model error covariance matrix parameters.

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In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.

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The tightening competition and increasing dynamism have created an emerging need for flexible asset management. This means that the changes of market demand should be responded to with adjustments in the amount of assets tied to the balance sheets of companies. On the other hand, industrial maintenance has recently experienced drastic changes, which have led to an increase in the number of maintenance networks (consisting of customer companies that buy maintenance services, as well as various supplier companies) and inter-organizational partnerships. However, the research on maintenance networks has not followed the changes in the industry. Instead, there is a growing need for new ways of collaboration between partnering companies to enhance the competitiveness of the whole maintenance network. In addition, it is more and more common for companies to pursue lean operations in their businesses. This thesis shows how flexible asset management can increase the profitability of maintenance companies and networks under dynamic operating conditions, and how the additional value can then be shared between the network partners. Firstly, I have conducted a systematic literature review to identify what kind of requirements for asset management models are set by the increasing dynamism. Then I have responded to these requirements by constructing an analytical model for flexible asset management, linking asset management to the profitability and financial state of a company. The thesis uses the model to show how flexible asset management can increase profitability in maintenance companies and networks, and how the created value can be shared in the networks to reach a win-win situation. The research indicates that the existing models for asset management are heterogeneous by nature due to the various definitions of ‘asset management’. I conclude that there is a need for practical asset management models which address assets comprehensively with an inter-organizational, strategic view. The comprehensive perspective, taking all kinds of asset types into account, is needed to integrate the research on asset management with the strategic management of companies and networks. I will show that maintenance companies can improve their profitability by increasing the flexibility of their assets. In maintenance networks, reorganizing the ownership of the assets among the different network partners can create additional value. Finally, I will introduce flexible asset management contracts for maintenance networks. These contracts address the value sharing related to reorganizing the ownership of assets according to the principles of win-win situations.

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The business logic in the manufacturing industry has changed in the 21st century. In the current industrial market, manufacturers are driven to provide more comprehensive offerings that go beyond the traditional product-orientation by providing capacity and availability for their customers. From incidental merchandise, services have become the core of manufacturers’ offerings with long-lasting service agreements over the life-cycles of their products. This change is driven both by the need of providers to grow and gain competitive advantage and by increased customer demand caused by customers’ outsourcing trends. The three key drivers for manufacturers’ service strategies are outsourcing trends, saturation of the installed base, and commoditization in product markets. Thus, manufacturers focus on providing industrial solutions which are delivered through relational processes with customers by using solution-driven business models. In the management of marketing activities, this can be regarded as closer customer relationships, service-dominant business logic, and collaboration in solving customers’ problems. However, there are few studies on comprehensive conceptualizations of a solution offering that include different elements and their roles, especially in the context of capital goods industry. Also the transition process needs further studies in a real life context. This study explores the transition process of an industrial company from product to solution business and, as an aid to managing the solution business, explicates the structure and management of an industrial solution offering. There are two themes, the industrial transition process and industrial solution offering. Regarding the industrial transition process, the aim is to understand the supplier view on the process and its execution and to determine the challenges related to the transition process. The industrial solution offering is discussed by its elements and characteristics, as well as management. Furthermore, a special type of build-own-operate-transfer business model is presented and its suitability in the industrial context analyzed. The study includes findings achieved by qualitative methods and from four case companies. Based on the results, it is tentatively suggested that in the industrial solution business, the transition from product to solution business is not a linear project but an evolving process that varies according to customer needs, which suggests that companies need to possess an ability to develop new business models for different customer needs. The industrial solution offering is dynamic as it evolves in collaboration according to the prevailing and latent customer needs, which suggest restructuring of the organization from a product-centric to a customer-centric one. Furthermore, based on the findings, the concept of industrial solutions is defined as an ongoing relational process to satisfy a customer’s particular business or operational requirements, and the concept of industrial solution offering as an entity comprising the customized goods, services, collaboration, and finance needed to fulfill the industrial solution. Finally, the study offers several managerial implications for industrial managers involved in the transition and management of the solution business and its offering.

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Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

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RENSOL (Regional Energy Solutions) project deals with the use of energy efficiency and renewable energy solutions in Kaliningrad Oblast to tackle climate change. Overall objective of the RENSOL work package 1 is to build awareness and knowledge on solutions for energy efficient buildings and street lightning applications. The project report describes available solutions to improve housing energy efficiency.

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RENSOL (Regional Energy Solutions) project deals with the use of energy efficiency and renewable energy solutions in Kaliningrad Oblast to tackle climate change. Overall objective of the RENSOL work package 1 is to build awareness and knowledge on solutions for energy efficient buildings and street lightning applications. This project report describes available solutions to improve housing energy efficiency.

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Fan systems are responsible for approximately 10% of the electricity consumption in industrial and municipal sectors, and it has been found that there is energy-saving potential in these systems. To this end, variable speed drives (VSDs) are used to enhance the efficiency of fan systems. Usually, fan system operation is optimized based on measurements of the system, but there are seldom readily installed meters in the system that can be used for the purpose. Thus, sensorless methods are needed for the optimization of fan system operation. In this thesis, methods for the fan operating point estimation with a variable speed drive are studied and discussed. These methods can be used for the energy efficient control of the fan system without additional measurements. The operation of these methods is validated by laboratory measurements and data from an industrial fan system. In addition to their energy consumption, condition monitoring of fan systems is a key issue as fans are an integral part of various production processes. Fan system condition monitoring is usually carried out with vibration measurements, which again increase the system complexity. However, variable speed drives can already be used for pumping system condition monitoring. Therefore, it would add to the usability of a variablespeed- driven fan system if the variable speed drive could be used as a condition monitoring device. In this thesis, sensorless detection methods for three lifetime-reducing phenomena are suggested: these are detection of the fan contamination build-up, the correct rotational direction, and the fan surge. The methods use the variable speed drive monitoring and control options for the detection along with simple signal processing methods, such as power spectrum density estimates. The methods have been validated by laboratory measurements. The key finding of this doctoral thesis is that a variable speed drive can be used on its own as a monitoring and control device for the fan system energy efficiency, and it can also be used in the detection of certain lifetime-reducing phenomena.

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A trade-off between return and risk plays a central role in financial economics. The intertemporal capital asset pricing model (ICAPM) proposed by Merton (1973) provides a neoclassical theory for expected returns on risky assets. The model assumes that risk-averse investors (seeking to maximize their expected utility of lifetime consumption) demand compensation for bearing systematic market risk and the risk of unfavorable shifts in the investment opportunity set. Although the ICAPM postulates a positive relation between the conditional expected market return and its conditional variance, the empirical evidence on the sign of the risk-return trade-off is conflicting. In contrast, autocorrelation in stock returns is one of the most consistent and robust findings in empirical finance. While autocorrelation is often interpreted as a violation of market efficiency, it can also reflect factors such as market microstructure or time-varying risk premia. This doctoral thesis investigates a relation between the mixed risk-return trade-off results and autocorrelation in stock returns. The results suggest that, in the case of the US stock market, the relative contribution of the risk-return trade-off and autocorrelation in explaining the aggregate return fluctuates with volatility. This effect is then shown to be even more pronounced in the case of emerging stock markets. During high-volatility periods, expected returns can be described using rational (intertemporal) investors acting to maximize their expected utility. During lowvolatility periods, market-wide persistence in returns increases, leading to a failure of traditional equilibrium-model descriptions for expected returns. Consistent with this finding, traditional models yield conflicting evidence concerning the sign of the risk-return trade-off. The changing relevance of the risk-return trade-off and autocorrelation can be explained by heterogeneous agents or, more generally, by the inadequacy of the neoclassical view on asset pricing with unboundedly rational investors and perfect market efficiency. In the latter case, the empirical results imply that the neoclassical view is valid only under certain market conditions. This offers an economic explanation as to why it has been so difficult to detect a positive tradeoff between the conditional mean and variance of the aggregate stock return. The results highlight the importance, especially in the case of emerging stock markets, of noting both the risk-return trade-off and autocorrelation in applications that require estimates for expected returns.

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Communications play a key role in modern smart grids. New functionalities that make the grids ‘smart’ require the communication network to function properly. Data transmission between intelligent electric devices (IEDs) in the rectifier and the customer-end inverters (CEIs) used for power conversion is also required in the smart grid concept of the low-voltage direct current (LVDC) distribution network. Smart grid applications, such as smart metering, demand side management (DSM), and grid protection applied with communications are all installed in the LVDC system. Thus, besides remote connection to the databases of the grid operators, a local communication network in the LVDC network is needed. One solution applied to implement the communication medium in power distribution grids is power line communication (PLC). There are power cables in the distribution grids, and hence, they may be applied as a communication channel for the distribution-level data. This doctoral thesis proposes an IP-based high-frequency (HF) band PLC data transmission concept for the LVDC network. A general method to implement the Ethernet-based PLC concept between the public distribution rectifier and the customerend inverters in the LVDC grid is introduced. Low-voltage cables are studied as the communication channel in the frequency band of 100 kHz–30 MHz. The communication channel characteristics and the noise in the channel are described. All individual components in the channel are presented in detail, and a channel model, comprising models for each channel component is developed and verified by measurements. The channel noise is also studied by measurements. Theoretical signalto- noise ratio (SNR) and channel capacity analyses and practical data transmission tests are carried out to evaluate the applicability of the PLC concept against the requirements set by the smart grid applications in the LVDC system. The main results concerning the applicability of the PLC concept and its limitations are presented, and suggestion for future research proposed.

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Organizational creativity is increasingly important for organizations aiming to survive and thrive in complex and unexpectedly changing environments. It is precondition of innovation and a driver of an organization’s performance success. Whereas innovation research increasingly promotes high-involvement and participatory innovation, the models of organizational creativity are still mainly based on an individual-creativity view. Likewise, the definitions of organizational creativity and innovation are somewhat equal, and they are used as interchangeable constructs, while on the other hand they are seen as different constructs. Creativity is seen as generation of novel and useful ideas, whereas innovation is seen as the implementation of these ideas. The research streams of innovation and organizational creativity seem to be advancing somewhat separately, although together they could provide many synergy advantages. Thereby, this study addresses three main research gaps. First, as the knowledge and knowing is being increasingly expertized and distributed in organizations, the conceptualization of organizational creativity needs to face that perspective, rather than relying on the individual-creativity view. Thus, the conceptualization of organizational creativity needs clarification, especially as an organizational-level phenomenon (i.e., creativity by an organization). Second, approaches to consciously build organizational creativity to increase the capacity of an organization to demonstrate novelty in its knowledgeable actions are rare. The current creativity techniques are mainly based on individual-creativity views, and they mainly focus on the occasional problem-solving cases among a limited number of individuals, whereas, the development of collective creativity and creativity by the organization lacks approaches. Third, in terms of organizational creativity as a collective phenomenon, the engagement, contributions, and participation of organizational members into activities of common meaning creation are more important than the individualcreativity skills. Therefore, the development approaches to foster creativity as social, emerging, embodied, and collective creativity are needed to complement the current creativity techniques. To address these gaps, the study takes a multiparadigm perspective to face the following three objectives. The first objective of this study is to clarify and extend the conceptualization of organizational creativity. The second is to study the development of organizational creativity. The third is to explore how an improvisational theater based approach fosters organizational creativity. The study consists of two parts comprising the introductory part (part I) and six publications (part II). Each publication addresses the research questions of the thesis through detailed subquestions. The study makes three main contributions to the research of organizational creativity. First, it contributes toward the conceptualization of organizational creativity by extending the current view of organizational creativity. This study views organizational creativity as a multilevel construct constituting both of individual and collective (group and organizational) creativity. In contrast to current views of organizational creativity, this study bases on organizational (collective) knowledge that is based on and demonstrated through the knowledgeable actions of an organization as a whole. The study defines organizational creativity as an overall ability of an organization to demonstrate novelty in its knowledgeable actions (through what it does and how it does what it does).Second, this study contributes toward the development of organizational creativity as multi-level phenomena, introducing developmental approaches that face two or more of these levels simultaneously. More specifically, the study presents the cross-level approaches to building organizational creativity, by using an approach based in improvisational theater and considering assessment of organizational renewal capability. Third, the study contributes on development of organizational creativity using an improvisational theater based approach as twofold meaning. First, it fosters individual and collective creativity simultaneously and builds space for creativity to occur. Second, it models collective and distributed creativity processes, thereby, contributing to the conceptualization of organizational creativity.

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Although the concept of multi-products biorefinery provides an opportunity to meet the future demands for biofuels, biomaterials or chemicals, it is not assured that its implementation would improve the profitability of kraft pulp mills. The attractiveness will depend on several factors such as mill age and location, government incentives, economy of scale, end user requirements, and how much value can be added to the new products. In addition, the effective integration of alternative technologies is not straightforward and has to be carefully studied. In this work, detailed balances were performed to evaluate possible impacts that lignin removal, hemicelluloses recovery prior to pulping, torrefaction and pyrolysis of wood residues cause on the conventional mill operation. The development of mill balances was based on theoretical fundamentals, practical experience, literature review, personal communication with technology suppliers and analysis of mill process data. Hemicelluloses recovery through pre-hydrolysis of chips leads to impacts in several stages of the kraft process. Effects can be observed on the pulping process, wood consumption, black liquor properties and, inevitably, on the pulp quality. When lignin is removed from black liquor, it will affect mostly the chemical recovery operation and steam generation rate. Since mineral acid is used to precipitate the lignin, impacts on the mill chemical balance are also expected. A great advantage of processing the wood residues for additional income results from the fact that the pulping process, pulp quality and sales are not harmfully affected. For pulp mills interested in implementing the concept of multi-products biorefinery, this work has indicated possible impacts to be considered in a technical feasibility study.

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This research is an analysis of the value and content of local service offerings that enable longer periods of living at home for elderly people. Mobile health care and new distribution services have provided an interesting solution in this context. The research aim to shed light on the research question, ‘How do we bundle services based on different customer needs?’ A research process consisting of three main phases was applied for this purpose. During this process, elderly customers were segmented, the importance of services was rated and service offerings were defined. Value creation and service offering provides theoretical framework for the research. The target group is South Karelia’s 60 to 90-year old individuals and the data has been acquired via a postal questionnaire. Research has been conducted as exploratory research utilizing the methods of quantitative and social network analysis. The main results of the report are identified customer segments and service packages that fits to the segments’ needs. The results indicate the needs of customers and the results are additionally analysed from the producer’s point of view. In addition to the empirical results, the used theory framework has been developed further in order for the service-related theories to be seen from the customer’s point of view and not just from the producer’s point of view.

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Ion mobility spectrometry (IMS) is a straightforward, low cost method for fast and sensitive determination of organic and inorganic analytes. Originally this portable technique was applied to the determination of gas phase compounds in security and military use. Nowadays, IMS has received increasing attention in environmental and biological analysis, and in food quality determination. This thesis consists of literature review of suitable sample preparation and introduction methods for liquid matrices applicable to IMS from its early development stages to date. Thermal desorption, solid phase microextraction (SPME) and membrane extraction were examined in experimental investigations of hazardous aquatic pollutants and potential pollutants. Also the effect of different natural waters on the extraction efficiency was studied, and the utilised IMS data processing methods are discussed. Parameters such as extraction and desorption temperatures, extraction time, SPME fibre depth, SPME fibre type and salt addition were examined for the studied sample preparation and introduction methods. The observed critical parameters were extracting material and temperature. The extraction methods showed time and cost effectiveness because sampling could be performed in single step procedures and from different natural water matrices within a few minutes. Based on these experimental and theoretical studies, the most suitable method to test in the automated monitoring system is membrane extraction. In future an IMS based early warning system for monitoring water pollutants could ensure the safe supply of drinking water. IMS can also be utilised for monitoring natural waters in cases of environmental leakage or chemical accidents. When combined with sophisticated sample introduction methods, IMS possesses the potential for both on-line and on-site identification of analytes in different water matrices.

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Lappeenrannan teknilliselle yliopistolle on rakennettu ISO14001-mukaista ympäristöjärjestelmää. Tässä diplomityössä tarkastellaan rakentamisen vaiheita sekä etsitään ratkaisuja rakentamisen aikana ilmeneviin haasteisiin. Teoriaosassa keskitytään ympäristö- ja kestävän kehityksen toimintaan yliopistoissa sekä ISO14001-standardin mukaisiin ympäristöjärjestelmiin. Ympäristöjärjestelmää rakennettaessa luodaan ympäristöpolitiikka sekä arvioidaan ja valitaan yliopiston merkittävimmät ympäristönäkökohdat. Näkökohdille luodaan päämäärät, tavoitteet ja ohjelmat. Lisäksi työssä tarkastellaan lakisääteisiä vaatimuksia ja luodaan menetelmiä dokumentointiin, koulutukseen, poikkeamien havainnointiin ja sisäiseen auditointiin. Yliopistolle on mahdollista rakentaa toimiva ympäristöjärjestelmä, mutta se vaatii aika- ja taloudellisten resurssien lisäksi myös vahvan tuen ylimmältä johdolta sekä halua ajaa muutos organisaatioon.