Working fluid selection and design of small-scale waste heat recovery systems based on organic Rankine cycles

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.

Portfolio Selection via Composite Measure Analysis: Evidence from the U.S. Stock Market

The aim of this research is to examine the pricing anomalies existing in the U.S. market during 1986 to 2011. The sample of stocks is divided into decile portfolios based on seven individual valuation ratios (E/P, B/P, S/P, EBIT/EV, EVITDA/EV, D/P, and CE/P) and price momentum to investigate the efficiency of individual valuation ratio and their combinations as portfolio formation criteria. This is the first time in financial literature when CE/P is employed as a constituent of composite value measure. The combinations are based on median scaled composite value measures and TOPSIS method. During the sample period value portfolios significantly outperform both the market portfolio and comparable glamour portfolios. The results show the highest return for the value portfolio that was based on the combination of S/P & CE/P ratios. The outcome of this research will increase the understanding on the suitability of different methodologies for portfolio selection. It will help managers to take advantage of the results of different methodologies in order to gain returns above the market.

Green supplier selection via Multiple Criteria Data Envelopment Analysis

An appropriate supplier selection and its profound effects on increasing the competitive advantage of companies has been widely discussed in supply chain management (SCM) literature. By raising environmental awareness among companies and industries they attach more importance to sustainable and green activities in selection procedures of raw material providers. The current thesis benefits from data envelopment analysis (DEA) technique to evaluate the relative efficiency of suppliers in the presence of carbon dioxide (CO2) emission for green supplier selection. We incorporate the pollution of suppliers as an undesirable output into DEA. However, to do so, two conventional DEA model problems arise: the lack of the discrimination power among decision making units (DMUs) and flexibility of the inputs and outputs weights. To overcome these limitations, we use multiple criteria DEA (MCDEA) as one alternative. By applying MCDEA the number of suppliers which are identified as efficient will be decreased and will lead to a better ranking and selection of the suppliers. Besides, in order to compare the performance of the suppliers with an ideal supplier, a “virtual” best practice supplier is introduced. The presence of the ideal virtual supplier will also increase the discrimination power of the model for a better ranking of the suppliers. Therefore, a new MCDEA model is proposed to simultaneously handle undesirable outputs and virtual DMU. The developed model is applied for green supplier selection problem. A numerical example illustrates the applicability of the proposed model.

Alueellisen lämmitysjärjestelmän valinta hankesuunnitteluvaiheessa

Työn lähtökohtana oli tarkastella hankesuunnitteluvaiheen lämmitysjärjestelmän valintaa ja siihen vaikuttavia tekijöitä. Työssä käytettiin Case-tarkasteluna Espoon Finnoon aluetta. Rakennusosakeyhtiö Hartela voitti Espoon Finnoon ensimmäisen (Finnoo I) asemakaava-alueen suunnittelu ja toteuttamisen ideakilpailun vuoden 2012 lopussa. Finnoo I alueelle rakennettaan noin 155 000 kerrosmetriä eli huoneistot noin 4000 asukkaalle. Alueen ra-kennukset suunnitellaan energiatehokkaaksi, sekä lämmityksessä ja sähkössä on tarkoitus käyttää uusiutuvaa energiaa. Työssä käsiteltiin alueellista lämmitysjärjestelmää ja sen vaihtoehtoetoja. Työssä tutkittiin myös aurinkosähkön käytön mahdollisuutta alueella. Ensin työssä mitoitettiin rakennusten energiankulutuksen muodostuminen alustavien suunnitelmien ja arvioitujen ominaiskulu-tusten avulla. Sen jälkeen käytiin läpi mahdolliset lämmitysjärjestelmät, joita alueella voi-daan käyttää ja arvioitiin niiden aiheuttamat elinkaarikustannukset koko laskenta-ajan jak-solla. Elinkaarilaskentaan valittiin viisi toteutuskelpoisinta järjestelmää ja niistä laskettiin elinkaarikustannukset. Lisäksi laskettiin järjestelmien hiilidioksidipäästöt vuosittain. Työn tulosten pohjalta voidaan olettaa, että kokonaisvaltaisesti yhtä ainoata parasta lämmi-tysjärjestelmää alueelle ei ole, vaan kaukolämpöä, maalämpöä ja hybridijärjestelmiä tulisi käyttää alueella sekaisin. Lisäksi alue on mahdollista rakentaa niin, että alue käyttäisi nolla-lämpöalueen periaatetta, niin että rakennukset, jotka tuottavat lämpöä liikaa myisivät ne sitä rakennuksille jotka tarvitsevat sitä. Aurinkosähkön potentiaali alueella on hyvä ja sitä käyttämällä voidaan rakennusten E-lukua ja hiilidioksidipäästöjä laskea.

Regulation of the renal proximal tubule second sodium pump by angiotensins

For several years it was believed that angiotensin II (Ang II) alone mediated the effects of the renin-angiotensin system. However, it has been observed that other peptides of this system, such as angiotensin-(1-7) (Ang-(1-7)), present biological activity. The effect of Ang II and Ang-(1-7) on renal sodium excretion has been associated, at least in part, with modulation of proximal tubule sodium reabsorption. In the present review, we discuss the evidence for the involvement of Na+-ATPase, called the second sodium pump, as a target for the actions of these compounds in the regulation of proximal tubule sodium reabsorption.

Inhibition of the sarcoplasmic reticulum Ca2+ pump with thapsigargin to estimate the contribution of Na+-Ca2+ exchange to ventricular myocyte relaxation

Relaxation in the mammalian ventricle is initiated by Ca2+ removal from the cytosol, which is performed by three main transport systems: sarcoplasmic reticulum Ca2+-ATPase (SR-A), Na+-Ca2+ exchanger (NCX) and the so-called slow mechanisms (sarcolemmal Ca2+-ATPase and mitochondrial Ca2+ uptake). To estimate the relative contribution of each system to twitch relaxation, SR Ca2+ accumulation must be selectively inhibited, usually by the application of high caffeine concentrations. However, caffeine has been reported to often cause changes in membrane potential due to NCX-generated inward current, which compromises the reliability of its use. In the present study, we estimated integrated Ca2+ fluxes carried by SR-A, NCX and slow mechanisms during twitch relaxation, and compared the results when using caffeine application (Cf-NT) and an electrically evoked twitch after inhibition of SR-A with thapsigargin (TG-TW). Ca2+ transients were measured in 20 isolated adult rat ventricular myocytes with indo-1. For transients in which one or more transporters were inhibited, Ca2+ fluxes were estimated from the measured free Ca2+ concentration and myocardial Ca2+ buffering characteristics. NCX-mediated integrated Ca2+ flux was significantly higher with TG-TW than with Cf-NT (12 vs 7 µM), whereas SR-dependent flux was lower with TG-TW (77 vs 81 µM). The relative participations of NCX (12.5 vs 8% with TG-TW and Cf-NT, respectively) and SR-A (85 vs 89.5% with TG-TW and Cf-NT, respectively) in total relaxation-associated Ca2+ flux were also significantly different. We thus propose TG-TW as a reliable alternative to estimate NCX contribution to twitch relaxation in this kind of analysis.

Selection of patients for myocardial perfusion scintigraphy based on fuzzy sets theory applied to clinical-epidemiological data and treadmill test results

Coronary artery disease (CAD) is a worldwide leading cause of death. The standard method for evaluating critical partial occlusions is coronary arteriography, a catheterization technique which is invasive, time consuming, and costly. There are noninvasive approaches for the early detection of CAD. The basis for the noninvasive diagnosis of CAD has been laid in a sequential analysis of the risk factors, and the results of the treadmill test and myocardial perfusion scintigraphy (MPS). Many investigators have demonstrated that the diagnostic applications of MPS are appropriate for patients who have an intermediate likelihood of disease. Although this information is useful, it is only partially utilized in clinical practice due to the difficulty to properly classify the patients. Since the seminal work of Lotfi Zadeh, fuzzy logic has been applied in numerous areas. In the present study, we proposed and tested a model to select patients for MPS based on fuzzy sets theory. A group of 1053 patients was used to develop the model and another group of 1045 patients was used to test it. Receiver operating characteristic curves were used to compare the performance of the fuzzy model against expert physician opinions, and showed that the performance of the fuzzy model was equal or superior to that of the physicians. Therefore, we conclude that the fuzzy model could be a useful tool to assist the general practitioner in the selection of patients for MPS.

The Fluid Structure Interaction Analysis of a Peristaltic Pump

The thesis work models the squeezing of the tube and computes the fluid motion of a peristaltic pump. The simulations have been conducted by using COMSOL Multiphysics FSI module. The model is setup in axis symmetric with several simulation cases to have a clear understanding of the results. The model captures total displacement of the tube, velocity magnitude, and average pressure fluctuation of the fluid motion. A clear understanding and review of many mathematical and physical concepts are also discussed with their applications in real field. In order to solve the problems and work around the resource constraints, a thorough understanding of mass balance and momentum equations, finite element concepts, arbitrary Lagrangian-Eulerian method, one-way coupling method, two-way coupling method, and COMSOL Multiphysics simulation setup are understood and briefly narrated.

Service product internationalisation : market selection for new service products in a multinational financial service firm

The significance and impact of services in the modern global economy has become greater and there has been more demand for decades in the academic community of international business for further research into better understanding internationalisation of services. Theories based on the internationalisation of manufacturing firms have been long questioned for their applicability to services. This study aims at contributing to understanding internationalisation of services by examining how market selection decisions are made for new service products within the existing markets of a multinational financial service provider. The study focused on the factors influencing market selection and the study was conducted as a case study on a multinational financial service firm and two of its new service products. Two directors responsible for the development and internationalisation of the case service products were interviewed in guided semi-structured interviews based on themes adopted from the literature review and the outcome theoretical framework. The main empirical findings of the study suggest that the most significant factors influencing the market selection for new service products within a multinational financial service firm’s existing markets are: commitment to the new service products by both the management and the rest of the product related organisation; capability and competence by the local country organisations to adopt new services; market potential which combines market size, market structure and competitive environment; product fit to the market requirements; and enabling partnerships. Based on the empirical findings, this study suggests a framework of factors influencing market selection for new service products, and proposes further research issues and methods to test and extend the findings of this research.

A low concentration of ouabain (0.18 µg/kg) enhances hypertension in spontaneously hypertensive rats by inhibiting the Na+ pump and activating the renin-angiotensin system

We investigated the effects of low ouabain concentrations on systolic (SAP) and diastolic (DAP) arterial pressures and on pressor reactivity in 3-month-old male spontaneously hypertensive rats (SHR). Arterial blood pressure (BP) and pressor reactivity to phenylephrine (PHE) were investigated before and after 0.18 μg/kg ouabain administration (N = 6). The influence of hexamethonium (N = 6), canrenone (N = 6), enalapril (N = 6), and losartan (N = 6) on ouabain actions was evaluated. Ouabain increased BP (SAP: 137 ± 5.1 to 150 ± 4.7; DAP: 93.7 ± 7.7 to 116 ± 3.5 mmHg; P<0.05) but did not change PHE pressor reactivity. Hexamethonium reduced basal BP in control but not in ouabain-treated rats. However, hexamethonium + ouabain increased DAP sensitivity to PHE. Canrenone did not affect basal BP but blocked ouabain effects on SAP. However, after canrenone + ouabain administration, DAP pressor reactivity to PHE still increased. Enalapril and losartan reduced BP and abolished SAP and DAP responses to ouabain. Enalapril + ouabain reduced DAP reactivity to PHE, while losartan + ouabain reduced SAP and DAP reactivity to PHE. In conclusion, a small dose of ouabain administered to SHR increased BP without altering PHE pressor reactivity. Although the renin-angiotensin system (RAS), Na+ pump and autonomic reflexes are involved in the effects of ouabain on PHE reactivity, central mechanisms might blunt the actions of ouabain on PHE pressor reactivity. The effect of ouabain on SAP seems to depend on the inhibition of both Na+ pump and RAS, whereas the effect on DAP seems to depend only on RAS.

Comparison of Model-Based Flow Rate Estimation Methods in Frequency-Converter-Driven Pumps and Fans

Fluid handling systems such as pump and fan systems are found to have a significant potential for energy efficiency improvements. To deliver the energy saving potential, there is a need for easily implementable methods to monitor the system output. This is because information is needed to identify inefficient operation of the fluid handling system and to control the output of the pumping system according to process needs. Model-based pump or fan monitoring methods implemented in variable speed drives have proven to be able to give information on the system output without additional metering; however, the current model-based methods may not be usable or sufficiently accurate in the whole operation range of the fluid handling device. To apply model-based system monitoring in a wider selection of systems and to improve the accuracy of the monitoring, this paper proposes a new method for pump and fan output monitoring with variable-speed drives. The method uses a combination of already known operating point estimation methods. Laboratory measurements are used to verify the benefits and applicability of the improved estimation method, and the new method is compared with five previously introduced model-based estimation methods. According to the laboratory measurements, the new estimation method is the most accurate and reliable of the model-based estimation methods.

Scalable Feature Selection Applications for Genome-Wide Association Studies of Complex Diseases

Personalized medicine will revolutionize our capabilities to combat disease. Working toward this goal, a fundamental task is the deciphering of geneticvariants that are predictive of complex diseases. Modern studies, in the formof genome-wide association studies (GWAS) have afforded researchers with the opportunity to reveal new genotype-phenotype relationships through the extensive scanning of genetic variants. These studies typically contain over half a million genetic features for thousands of individuals. Examining this with methods other than univariate statistics is a challenging task requiring advanced algorithms that are scalable to the genome-wide level. In the future, next-generation sequencing studies (NGS) will contain an even larger number of common and rare variants. Machine learning-based feature selection algorithms have been shown to have the ability to effectively create predictive models for various genotype-phenotype relationships. This work explores the problem of selecting genetic variant subsets that are the most predictive of complex disease phenotypes through various feature selection methodologies, including filter, wrapper and embedded algorithms. The examined machine learning algorithms were demonstrated to not only be effective at predicting the disease phenotypes, but also doing so efficiently through the use of computational shortcuts. While much of the work was able to be run on high-end desktops, some work was further extended so that it could be implemented on parallel computers helping to assure that they will also scale to the NGS data sets. Further, these studies analyzed the relationships between various feature selection methods and demonstrated the need for careful testing when selecting an algorithm. It was shown that there is no universally optimal algorithm for variant selection in GWAS, but rather methodologies need to be selected based on the desired outcome, such as the number of features to be included in the prediction model. It was also demonstrated that without proper model validation, for example using nested cross-validation, the models can result in overly-optimistic prediction accuracies and decreased generalization ability. It is through the implementation and application of machine learning methods that one can extract predictive genotype–phenotype relationships and biological insights from genetic data sets.

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.