54 resultados para Halley’s and Euler-Chebyshev’s Methods


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Demand for the use of energy systems, entailing high efficiency as well as availability to harness renewable energy sources, is a key issue in order to tackling the threat of global warming and saving natural resources. Organic Rankine cycle (ORC) technology has been identified as one of the most promising technologies in recovering low-grade heat sources and in harnessing renewable energy sources that cannot be efficiently utilized by means of more conventional power systems. The ORC is based on the working principle of Rankine process, but an organic working fluid is adopted in the cycle instead of steam. This thesis presents numerical and experimental results of the study on the design of small-scale ORCs. Two main applications were selected for the thesis: waste heat re- covery from small-scale diesel engines concentrating on the utilization of the exhaust gas heat and waste heat recovery in large industrial-scale engine power plants considering the utilization of both the high and low temperature heat sources. The main objective of this work was to identify suitable working fluid candidates and to study the process and turbine design methods that can be applied when power plants based on the use of non-conventional working fluids are considered. The computational work included the use of thermodynamic analysis methods and turbine design methods that were based on the use of highly accurate fluid properties. In addition, the design and loss mechanisms in supersonic ORC turbines were studied by means of computational fluid dynamics. The results indicated that the design of ORC is highly influenced by the selection of the working fluid and cycle operational conditions. The results for the turbine designs in- dicated that the working fluid selection should not be based only on the thermodynamic analysis, but requires also considerations on the turbine design. The turbines tend to be fast rotating, entailing small blade heights at the turbine rotor inlet and highly supersonic flow in the turbine flow passages, especially when power systems with low power outputs are designed. The results indicated that the ORC is a potential solution in utilizing waste heat streams both at high and low temperatures and both in micro and larger scale appli- cations.

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The objective of this thesis is to examine distribution network designs and modeling practices and create a framework to identify best possible distribution network structure for the case company. The main research question therefore is: How to optimize case company’s distribution network in terms of customer needs and costs? Theory chapters introduce the basic building blocks of the distribution network design and needed calculation methods and models. Framework for the distribution network projects was created based on the theory and the case study was carried out by following the defined framework. Distribution network calculations were based on the company’s sales plan for the years 2014 - 2020. Main conclusions and recommendations were that the new Asian business strategy requires high investments in logistics and the first step is to open new satellite DC in China as soon as possible to support sales and second possible step is to open regional DC in Asia within 2 - 4 years.

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Työn tarkoitus oli tutkia eläinrasvan puhdistusta biodieselin valmistusta varten. Eläinrasvaa syntyy elintarviketeollisuuden sivutuotteena ja sitä saadaan myös myymättä jääneistä elintarvikkeista. Rasva sisältää epäpuhtauksia, jotka on poistettava ennen biodieselprosessia. Tässä työssä tutkittavat epäpuhtaudet ovat typpi, fosfori, rauta, natrium, kalsium ja magnesium. Puhdistusmenetelminä käytettiin saostamista sitruunahapolla sekä adsorbointia kahdella eri adsorbentilla. Tavoitteena oli selvittää riittävä määrä happoa ja adsorbenttia sekä tutkia puhdistuksen mekanismia. Lisäksi tarkasteltiin lämpötilan vaikutusta adsorption aikana.

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This thesis considers optimization problems arising in printed circuit board assembly. Especially, the case in which the electronic components of a single circuit board are placed using a single placement machine is studied. Although there is a large number of different placement machines, the use of collect-and-place -type gantry machines is discussed because of their flexibility and increasing popularity in the industry. Instead of solving the entire control optimization problem of a collect-andplace machine with a single application, the problem is divided into multiple subproblems because of its hard combinatorial nature. This dividing technique is called hierarchical decomposition. All the subproblems of the one PCB - one machine -context are described, classified and reviewed. The derived subproblems are then either solved with exact methods or new heuristic algorithms are developed and applied. The exact methods include, for example, a greedy algorithm and a solution based on dynamic programming. Some of the proposed heuristics contain constructive parts while others utilize local search or are based on frequency calculations. For the heuristics, it is made sure with comprehensive experimental tests that they are applicable and feasible. A number of quality functions will be proposed for evaluation and applied to the subproblems. In the experimental tests, artificially generated data from Markov-models and data from real-world PCB production are used. The thesis consists of an introduction and of five publications where the developed and used solution methods are described in their full detail. For all the problems stated in this thesis, the methods proposed are efficient enough to be used in the PCB assembly production in practice and are readily applicable in the PCB manufacturing industry.

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SStrong evidence suggests that the climate is changing and that these changes are largely caused by human activities. A consensus exists among researchers that human activity is causing global warming and that actions to mitigate global warming need to be taken swiftly. The transportation sector, which relies heavily on fossil fuel burning and primarily oil, is one of the big contributors to air pollution problems at local, regional and global levels. It is the fastest growing source of greenhouse gas emissions and is estimated to be responsible for nearly a quarter of global energyrelated carbon dioxide emissions. Car sharing is a mobility solution encouraging its users to decrease private car usage in favour of communal transit and environmental goals. The idea of car sharing originates from the aspiration to decrease personal car ownership and to reduce vehicle distance travelled. This thesis seeks to complement the understanding of Finnish car sharing users and their usage through better categorization. Through better categorization and segmentation of Finnish car sharing users the thesis seeks to provide information for improved marketing insight. Research is done on the demographic and behavioural characteristics of Finnish car sharing users and they are compared with international findings about the characteristics of International car sharing users. The main research problem is Are Finnish car sharing users similar to international ones? A theoretical research framework on the determinants of individual car sharing usage is built based on international research about demographic and behaviouristic characteristics. After this a quantitative survey is performed to the customers of a Finnish car sharing organization. The data analysed in the thesis consist out of 532 answers received from the car sharing organizations customers. The data is analysed with descriptive and other exploratory methods, which create an understanding of Finnish car sharing users. At the end of the analysis the demographic and behavioural characteristics of Finnish car sharing users are compared with international ones. The research findings of the thesis indicate that the demographic and behavioural characteristics of Finnish car sharing usage largely follow those of their international counterparts. Thanks to the thesis results the car sharing organization is able to better target their customers through improved marketing insight.

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The aim of this thesis is to define effects of lignin separation process on Pulp mill chemical balance especially on sodium/sulphur-balance. The objective is to develop a simulation model with WinGEMS Process Simulator and use that model to simulate the chemical balances and process changes. The literature part explains what lignin is and how kraft pulp is produced. It also introduces to the methods that can be used to extract lignin from black liquor stream and how those methods affect the pulping process. In experimental part seven different cases are simulated with the created simulation model. The simulations are based on selected reference mill that produces 500 000 tons of bleached air-dried (90 %) pulp per year. The simulations include the chemical balance calculation and the estimated production increase. Based on the simulations the heat load of the recovery boiler can be reduced and the pulp production increased when lignin is extracted. The simulations showed that decreasing the waste acid stream intake from the chlorine dioxide plant is an effective method to control the sulphidity level when about 10 % of lignin is extracted. With higher lignin removal rates the in-mill sulphuric acid production has been discovered to be a better alternative to the sulphidity control.

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The strongest wish of the customer concerning chemical pulp features is consistent, uniform quality. Variation may be controlled and reduced by using statistical methods. However, studies addressing the application and benefits of statistical methods in forest product sector are scarce. Thus, the customer wish is the root cause of the motivation behind this dissertation. The research problem addressed by this dissertation is that companies in the chemical forest product sector require new knowledge for improving their utilization of statistical methods. To gain this new knowledge, the research problem is studied from five complementary viewpoints – challenges and success factors, organizational learning, problem solving, economic benefit, and statistical methods as management tools. The five research questions generated on the basis of these viewpoints are answered in four research papers, which are case studies based on empirical data collection. This research as a whole complements the literature dealing with the use of statistical methods in the forest products industry. Practical examples of the application of statistical process control, case-based reasoning, the cross-industry standard process for data mining, and performance measurement methods in the context of chemical forest products manufacturing are brought to the public knowledge of the scientific community. The benefit of the application of these methods is estimated or demonstrated. The purpose of this dissertation is to find pragmatic ideas for companies in the chemical forest product sector in order for them to improve their utilization of statistical methods. The main practical implications of this doctoral dissertation can be summarized in four points: 1. It is beneficial to reduce variation in chemical forest product manufacturing processes 2. Statistical tools can be used to reduce this variation 3. Problem-solving in chemical forest product manufacturing processes can be intensified through the use of statistical methods 4. There are certain success factors and challenges that need to be addressed when implementing statistical methods

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Intelligence from a human source, that is falsely thought to be true, is potentially more harmful than a total lack of it. The veracity assessment of the gathered intelligence is one of the most important phases of the intelligence process. Lie detection and veracity assessment methods have been studied widely but a comprehensive analysis of these methods’ applicability is lacking. There are some problems related to the efficacy of lie detection and veracity assessment. According to a conventional belief an almighty lie detection method, that is almost 100% accurate and suitable for any social encounter, exists. However, scientific studies have shown that this is not the case, and popular approaches are often over simplified. The main research question of this study was: What is the applicability of veracity assessment methods, which are reliable and are based on scientific proof, in terms of the following criteria? o Accuracy, i.e. probability of detecting deception successfully o Ease of Use, i.e. easiness to apply the method correctly o Time Required to apply the method reliably o No Need for Special Equipment o Unobtrusiveness of the method In order to get an answer to the main research question, the following supporting research questions were answered first: What kinds of interviewing and interrogation techniques exist and how could they be used in the intelligence interview context, what kinds of lie detection and veracity assessment methods exist that are reliable and are based on scientific proof and what kind of uncertainty and other limitations are included in these methods? Two major databases, Google Scholar and Science Direct, were used to search and collect existing topic related studies and other papers. After the search phase, the understanding of the existing lie detection and veracity assessment methods was established through a meta-analysis. Multi Criteria Analysis utilizing Analytic Hierarchy Process was conducted to compare scientifically valid lie detection and veracity assessment methods in terms of the assessment criteria. In addition, a field study was arranged to get a firsthand experience of the applicability of different lie detection and veracity assessment methods. The Studied Features of Discourse and the Studied Features of Nonverbal Communication gained the highest ranking in overall applicability. They were assessed to be the easiest and fastest to apply, and to have required temporal and contextual sensitivity. The Plausibility and Inner Logic of the Statement, the Method for Assessing the Credibility of Evidence and the Criteria Based Content Analysis were also found to be useful, but with some limitations. The Discourse Analysis and the Polygraph were assessed to be the least applicable. Results from the field study support these findings. However, it was also discovered that the most applicable methods are not entirely troublefree either. In addition, this study highlighted that three channels of information, Content, Discourse and Nonverbal Communication, can be subjected to veracity assessment methods that are scientifically defensible. There is at least one reliable and applicable veracity assessment method for each of the three channels. All of the methods require disciplined application and a scientific working approach. There are no quick gains if high accuracy and reliability is desired. Since most of the current lie detection studies are concentrated around a scenario, where roughly half of the assessed people are totally truthful and the other half are liars who present a well prepared cover story, it is proposed that in future studies lie detection and veracity assessment methods are tested against partially truthful human sources. This kind of test setup would highlight new challenges and opportunities for the use of existing and widely studied lie detection methods, as well as for the modern ones that are still under development.

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For advanced devices in the application fields of data storage, solar cell and biosensing, one of the major challenges to achieve high efficiency is the fabrication of nanopatterned metal oxide surfaces. Such surfaces often require both precise structure at the nanometer scale and controllable patterned structure at the macro scale. Nowadays, the dominating candidates to fabricate nanopatterned surfaces are the lithographic technique and block-copolymer masks, most of which are unfortunately costly and inefficient. An alternative bottom-up approach, which involves organic/inorganic self-assembly and dip-coating deposition, has been studied intensively in recent years and has proven to be an effective technique for the fabrication of nanoperforated metal oxide thin films. The overall objective of this work was to optimize the synthesis conditions of nanoperforated TiO2 (NP-TiO2) thin films, especially to be compatible with mixed metal oxide systems. Another goal was to develop fabrication and processing of NP-TiO2 thin films towards largescale production and seek new applications for solar cells and biosensing. Besides the traditional dip-coating and drop-casting methods, inkjet printing was used to prepare thin films of metal oxides, with the advantage of depositing the ink onto target areas, further enabling cost-effective fabrication of micro-patterned nanoperforated metal oxide thin films. The films were characterized by water contact angle determination, Atomic Force Microscopy, Scanning Electron Microscopy, X-ray Photoelectron Spectroscopy and Grazing Incidence XRay Diffraction. In this study, well-ordered zinc titanate nanoperforated thin films with different Zn/Ti ratios were produced successfully with zinc precursor content up to 50 mol%, and the dominating phase was Zn2Ti3O8. NP-TiO2 structures were also obtained by a cost-efficient means, namely inkjet printing, at both ambient temperature and 60 °C. To further explore new biosensing applications of nanoperforated oxide thin films, inkjet printing was used for the fabrication of both continuous and patterned polymeric films onto NP-TiO2 and perfluorinated phosphate functionalized NP-TiO2 substrates, respectively. The NP-TiO2 films can be also functionalized with a fluoroalkylsilane, resulting in hydrophobic surfaces on both titania and silica. The surface energy contrast in the nanoperforations can be tuned by irradiating the films with UV light, which provides ideal model systems for wettability studies.