Development of an electric heat pump for domestic use

This thesis records the design and development of an electrically driven, air to water, vapour compression heat pump of nominally 6kW heat output, for residential space heating. The study was carried out on behalf of GEC Research Ltd through the Interdisciplinary Higher Degrees Scheme at Aston University. A computer based mathematical model of the vapour compression cycle was produced as a design aid, to enable the effects of component design changes or variations in operating conditions to be predicted. This model is supported by performance testing of the major components, which revealed that improvements in the compressor isentropic efficiency offer the greatest potential for further increases in cycle COPh. The evaporator was designed from first principles, and is based on wire-wound heat transfer tubing. Two evaporators, of air side area 10.27 and 16.24m2, were tested in a temperature and humidity controlled environment, demonstrating that the benefits of the large coil are greater heat pump heat output and lower noise levels. A systematic study of frost growth rates suggested that this problem is most severe at the conditions of saturated air at 0oC combined with low condenser water temperature. A dynamic simulation model was developed to predict the in-service performance of the heat pump. This study confirmed the importance of an adequate radiator area for heat pump installations. A prototype heat pump was designed and manufactured, consisting of a hermetic reciprocating compressor, a coaxial tube condenser and a helically coiled evaporator, using Refrigerant 22. The prototype was field tested in a domestic environment for one and a half years. The installation included a comprehensive monitoring system. Initial problems were encountered with defrosting and compressor noise, both of which were solved. The unit then operated throughout the 1985/86 heating season without further attention, producing a COPh of 2.34.

Tax implications of dividend policy

This study examines the tax-arbitrage possibilities on the Budapest Stock Exchange between 1995 and 2007. The theoretical possibility for the arbitrage is the different taxation for different stockholders, for the private investors and for the institutions: the institutions had higher taxation on capital gain while private persons in the whole period had tax-benefits on capital gains. The dynamic clientele model shows, that there is a range of the price drops after dividend payouts which guarantees a risk-free profit for both parties. The research is based on the turnover data from 97 companies listed on the Budapest Stock Exchange. We have tested the significant turnovers around the dividend-dates. The study presents clear evidence that investors continuously did take advantages on the different taxation.

Integal futures based on the paradigm approach

The study discusses the interpretation of integral futures in the context of paradigm. The dynamic matrix model of futures paradigm has been developed for carrying out meta-analysis of futures. As a result of meta-analysis integral futures and its new paradigms are defined by way of reconstructing futures paradigm history as responses to changing societal needs and through the outcomes of dynamic and comparative analysis of futures paradigms. The study sets the argument that integral futures: a) is entering a new phase in development of futures that responses to societal demands for sustainability, democratic participation and continuous knowledge production and integration, b) it is the phase of cooperation building between theoretical and practical futures, c) it is the complementary development of co-evolutionary and participatory paradigms, d) it unfolds further research perspectives for futures.

A decision support framework for infrastructure maintenance investment decision-making

Infrastructure management agencies are facing multiple challenges, including aging infrastructure, reduction in capacity of existing infrastructure, and availability of limited funds. Therefore, decision makers are required to think innovatively and develop inventive ways of using available funds. Maintenance investment decisions are generally made based on physical condition only. It is important to understand that spending money on public infrastructure is synonymous with spending money on people themselves. This also requires consideration of decision parameters, in addition to physical condition, such as strategic importance, socioeconomic contribution and infrastructure utilization. Consideration of multiple decision parameters for infrastructure maintenance investments can be beneficial in case of limited funding. Given this motivation, this dissertation presents a prototype decision support framework to evaluate trade-off, among competing infrastructures, that are candidates for infrastructure maintenance, repair and rehabilitation investments. Decision parameters' performances measured through various factors are combined to determine the integrated state of an infrastructure using Multi-Attribute Utility Theory (MAUT). The integrated state, cost and benefit estimates of probable maintenance actions are utilized alongside expert opinion to develop transition probability and reward matrices for each probable maintenance action for a particular candidate infrastructure. These matrices are then used as an input to the Markov Decision Process (MDP) for the finite-stage dynamic programming model to perform project (candidate)-level analysis to determine optimized maintenance strategies based on reward maximization. The outcomes of project (candidate)-level analysis are then utilized to perform network-level analysis taking the portfolio management approach to determine a suitable portfolio under budgetary constraints. The major decision support outcomes of the prototype framework include performance trend curves, decision logic maps, and a network-level maintenance investment plan for the upcoming years. The framework has been implemented with a set of bridges considered as a network with the assistance of the Pima County DOT, AZ. It is expected that the concept of this prototype framework can help infrastructure management agencies better manage their available funds for maintenance.

Mining the online social network data: Influence, summarization, and organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Um estudo sobre a variabilidade do vento no nordeste do Brasil através de métodos estatísticos e via modelos dinâmicos de meso e micro escala

The objective of this study was to determine the seasonal and interannual variability and calculate the trends of wind speed in NEB and then validate the mesoscale numerical model for after engage with the microscale numerical model in order to get the wind resource at some locations in the NEB. For this we use two data sets of wind speed (weather stations and anemometric towers) and two dynamic models; one of mesoscale and another of microscale. We use statistical tools to evaluate and validate the data obtained. The simulations of the dynamic mesoscale model were made using data assimilation methods (Newtonian Relaxation and Kalman filter). The main results show: (i) Five homogeneous groups of wind speed in the NEB with higher values in winter and spring and with lower in summer and fall; (ii) The interannual variability of the wind speed in some groups stood out with higher values; (iii) The large-scale circulation modified by the El Niño and La Niña intensified wind speed for the groups with higher values; (iv) The trend analysis showed more significant negative values for G3, G4 and G5 in all seasons and in the annual average; (v) The performance of dynamic mesoscale model showed smaller errors in the locations Paracuru and São João and major errors were observed in Triunfo; (vi) Application of the Kalman filter significantly reduce the systematic errors shown in the simulations of the dynamic mesoscale model; (vii) The wind resource indicate that Paracuru and Triunfo are favorable areas for the generation of energy, and the coupling technique after validation showed better results for Paracuru. We conclude that the objective was achieved, making it possible to identify trends in homogeneous groups of wind behavior, and to evaluate the quality of both simulations with the dynamic model of mesoscale and microscale to answer questions as necessary before planning research projects in Wind-Energy area in the NEB

Mining the Online Social Network Data: Influence, Summarization, and Organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Exploring the Success of Student Experiential Learning through Entrepreneurial Opportunities

Academic literature has increasingly recognized the value of non-traditional higher education learning environments that emphasize action-orientated experiential learning for the study of entrepreneurship (Gibb, 2002; Jones & English, 2004). Many entrepreneurship educators have accordingly adopted approaches based on Kolb’s (1984) experiential learning cycle to develop a dynamic, holistic model of an experience-based learning process. Jones and Iredale (2010) suggested that entrepreneurship education requires experiential learning styles and creative problem solving to effectively engage students. Support has also been expressed for learning-by-doing activities in group or network contexts (Rasmussen and Sorheim, 2006), and for student-led approaches (Fiet, 2001). This study will build on previous works by exploring the use of experiential learning in an applied setting to develop entrepreneurial attitudes and traits in students. Based on the above literature, a British higher education institution (HEI) implemented a new, entrepreneurially-focused curriculum during the 2013/14 academic year designed to support and develop students’ entrepreneurial attitudes and intentions. The approach actively involved students in small scale entrepreneurship activities by providing scaffolded opportunities for students to design and enact their own entrepreneurial concepts. Students were provided with the necessary resources and training to run small entrepreneurial ventures in three different working environments. During the course of the year, three applied entrepreneurial opportunities were provided for students, increasing in complexity, length, and profitability as the year progressed. For the first undertaking, the class was divided into small groups, and each group was given a time slot and venue to run a pop-up shop in a busy commercial shopping centre. Each group of students was supported by lectures and dedicated class time for group work, while receiving a set of objectives and recommended resources. For the second venture, groups of students were given the opportunity to utilize an on-campus bar/club for an evening and were asked to organize and run a profitable event, acting as an outside promoter. Students were supported with lectures and seminars, and groups were given a £250 budget to develop, plan, and market their unique event. The final event was optional and required initiative on the part of the students. Students were given the opportunity to develop and put forward business plans to be judged by the HEI and the supporting organizations, which selected the winning plan. The authors of the winning business plan received a £2000 budget and a six-week lease to a commercial retail unit within a shopping centre to run their business. Students received additional academic support upon request from the instructor, and one of the supporting organizations provided a training course offering advice on creating a budget and a business plan. Data from students taking part in each of the events was collected, in order to ascertain the learning benefits of the experiential learning, along with the successes and difficulties they faced. These responses have been collected and analyzed and will be presented at the conference along with the instructor’s conclusions and recommendations for the use of such programs in higher educations.

Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.

Essays in corporate finance

China has been growing rapidly over the last decades. The private sector is the driving force of this growth. This thesis focuses on firm-level investment and cash holdings in China, and the chapters are structured around the following issues. 1. Why do private firms grow so fast when they are more financially constrained? In Chapter 3, we use a panel of over 600,000 firms of different ownership types from 1998 to 2007 to find the link between investment opportunities and financial constraints. The main finding indicates that private firms, which are more likely to be financially constrained, have high investment-investment opportunity sensitivity. Furthermore, this sensitivity is relatively lower for state-owned firms in China. This shows that constrained firms value investment opportunities more than unconstrained firms. To better measure investment opportunities, we attempt to improve the Q model by considering supply and demand sides simultaneously. When we capture q from the supply side and the demand side, we find that various types of firms respond differently towards different opportunity shocks. 2. In China, there are many firms whose cash flow is far greater than their fixed capital investment. Why is their investment still sensitive to cash flow? To explain this, in Chapter 4, we attempt to introduce a new channel to find how cash flow affects firm-level investment. We use a dynamic structural model and take uncertainty and ambiguity aversion into consideration. We find that uncertainty and ambiguity aversion will make investment less sensitive to investment opportunities. However, investment-cash flow sensitivity will increase when uncertainty is high. This suggests that investment cash flow sensitivities could still be high even when the firms are not financially constrained. 3. Why do firms in China hold so much cash? How can managers’ confidence affect corporate cash holdings? In Chapter 5, we analyse corporate cash holdings in China. Firms hold cash for precautionary reasons, to hedge frictions such as financing constraints and uncertainty. In addition, firms may act differently if they are confident or not. In order to determine how confidence shocks affect precautionary savings, we develop a dynamic model taking financing constraints, uncertainty, adjustment costs and confidence shocks into consideration. We find that without confidence shocks, firms will save money in bad times and invest in good times to maximise their value. However, if managers lose their confidence, they tend to save money in good times to use in bad times, to hedge risks and financing constraint problems. This can help explain why people find different results on the cash flow sensitivity of cash. Empirically, we use a panel of Chinese listed firms. The results show that firms in China save more money in good times, and the confidence shock channel can significantly affect firms’ cash holdings policy.

Aplicações de Ferramentas Lean em uma Indústria de Transformação de Papel

Esta dissertação foi desenvolvida no âmbito do 2º ano do Mestrado em Engenharia Mecânica – Ramo de Gestão Industrial no Instituto Superior de Engenharia do Porto. Este projeto realizou-se em ambiente industrial, nomeadamente na Tubembal, S.A. uma empresa localizada no concelho da Trofa, distrito do Porto. Esta empresa dedica-se à transformação de papel e comércio de embalagens, produz tubos e cantoneiras de cartão e é atualmente a maior empresa do sector na Península Ibérica. Esta dissertação baseia-se na aplicação de ferramentas Lean, numa perspetiva de melhoria de um ambiente produtivo industrial, melhorando o desempenho dos processos existentes e consequentemente a produtividade da empresa em estudo, com o objetivo de a tornar mais competitiva num ambiente global. A metodologia Lean tem como principal objetivo a eliminação de desperdício em toda a cadeia de valor e neste sentido surge como fundamental numa cultura de melhoria contínua e focalização no cliente, que se pretende instalar nesta empresa. Foi realizada uma análise profunda a toda a cadeia de valor como forma de identificar os maiores desperdícios e posteriormente apresentadas medidas para combater estes mesmos desperdícios, podendo assim reduzir custos. No projeto de melhoria apresentado à organização constam como principais ações, a implementação da metodologia 5S’s como ferramenta essencial para mudança de hábitos dos funcionários e integração e envolvimento de todos num mesmo projeto comum, na busca da melhoria contínua. Procedeu-se ainda à simulação de algumas propostas de reorganização do layout de forma a encontrar aquela que minimizasse os custos com movimentações e garantisse um fluxo controlado e em segurança dos produtos e pessoas dentro da fábrica. As propostas apresentadas mostram que a reorganização do layout da fábrica pode trazer ganhos significativos para a empresa, redução direta no tempo perdido em deslocações e maior disponibilidade dos meios e consequente direta redução dos custos. Todas as propostas apresentadas visam a adaptação da empresa a um modelo mais dinâmico de negócio, capaz de responder rápida e eficazmente aos seus clientes, adaptando-se ao mercado e garantindo a sua sustentabilidade num futuro próximo.

Determination of thresholds in marine molluscs as an alternative to the Environmental Quality Standards in marine water defined in the Water Framework Directive

The Water Framework Directive (WFD) establishes Environmental Quality Standards (EQS) in marine water for 34 priority substances. Among these substances, 25 are hydrophobic and bioaccumulable (2 metals and 23 organic compounds). For these 25 substances, monitoring in water matrix is not appropriate and an alternative matrix should be developed. Bivalve mollusks, particularly mussels (Mytilus edulis, Mytilus galloprovincialis), are used by Ifremer as a quantitative biological indicator since 1979 in France, to assess the marine water quality. This study has been carried out in order to determine thresholds in mussels at least as protective as EQS in marine water laid down by the WFD. Three steps are defined: - Provide an overview of knowledges about the relations between the concentrations of contaminants in the marine water and mussels through bioaccumulation factor (BAF) and bioconcentration factor (BCF). This allows to examine how a BCF or a BAF can be determined: BCF can be determined experimentally (according to US EPA or ASTM standards), or by Quantitative Activity-Structure Relationship models (QSAR): four equations can be used for mussels. BAF can be determined by field experiment; but none standards exists. It could be determined by using QSAR but this method is considered as invalid for mussels, or by using existing model: Dynamic Budget Model, but this is complex to use. - Collect concentrations data in marine water (Cwater) in bibliography for those 25 substances; and compare them with concentration in mussels (Cmussels) obtained through French monitoring network of chemicals contaminants (ROCCH) and biological integrator network RINBIO. According to available data, this leads to determine the BAF or the BCF (Cmussels /Cwater) with field data. - Compare BAF and BCF values (when available) obtained with various methods for these substances: BCF (stemming from the bibliography, using experimental process), BCF calculated by QSAR and BAF determined using field data. This study points out that experimental BCF data are available for 3 substances (Chlorpyrifos, HCH, Pentachlorobenzene). BCF by QSAR can be calculated for 20 substances. The use of field data allows to evaluate 4 BAF for organic compounds and 2 BAF for metals. Using these BAF or BCF value, thresholds in shellfish can be determined as an alternative to EQS in marine water.

Essays on Financial Constraints, R&D Investments, and Competition

This dissertation consists of two chapters of theoretical studies that investigate the effect of financial constraints and market competition on research and development (R&D) investments. In the first chapter, I explore the impact of financial constraints on two different types of R&D investments. In the second chapter, I examine the impact of market competition on the relationship between financial constraints and R&D investments. In the first chapter, I develop a dynamic monopoly model to study a firm’s R&D strategy. Contrary to intuition, I show that a financially constrained firm may invest more aggressively in R&D projects than an unconstrained firm. Financial constraints introduce a risk that a firm may run out of money before its project bears fruit, which leads to involuntary termination on an otherwise positive-NPV project. For a company that relies on cash flow from assets in place to keep its R&D project alive, early success can be relatively important. I find that when the discovery process can be expedited by heavier investment (“accelerable” projects), a financially constrained company may find it optimal to “over”-invest in order to raise the probability of project survival. The over-investment will not happen if the project is only “scalable” (investment scales up payoffs). The model generates several testable implications regarding over-investment and project values. In the second chapter, I study the effects of competition on R&D investments in a duopoly framework. Using a homogeneous duopoly model where two unconstrained firms compete head to head in an R&D race, I find that competition has no effect on R&D investment if the project is not accelerable, and the competing firms are not constrained. In a heterogeneous duopoly model where a financially constrained firm competes against an unconstrained firm, I discover interesting strategic interactions that lead to preemption by the constrained firm in equilibrium. The unconstrained competitor responds to its constrained rival’s investment in an inverted-U shape fashion. When the constrained competitor has high cash flow risk, it accelerates the innovation in equilibrium, while the unconstrained firm invests less aggressively and waits for its rival to quit the race due to shortage of funds.

Translation Studies on an Annular Field Reversed Configuration Device for Space Propulsion

This research investigated annular field reversed configuration (AFRC)devices for high power electric propulsion by demonstrating the acceleration of these plasmoids using an experimental prototype and measuring the plasmoid's velocity, impulse, and energy efficiency. The AFRC plasmoid translation experiment was design and constructed with the aid of a dynamic circuit model. Two versions of the experiment were built, using underdamped RLC circuits at 10 kHz and 20 kHz. Input energies were varied from 100 J/pulse to 1000 J/pulse for the 10 kHz bank and 100 J/pulse for the 20 kHz bank. The plasmoids were formed in static gas fill of argon, from 1 mTorr to 50 mTorr. The translation of the plasmoid was accomplished by incorporating a small taper into the outer coil, with a half angle of 2°. Magnetic field diagnostics, plasma probes, and single-frame imaging were used to measure the plasmoid's velocity and to diagnose plasmoid behavior. Full details of the device design, construction, and diagnostics are provided in this dissertation. The results from the experiment demonstrated that a repeatable AFRC plasmoid was produced between the coils, yet failed to translate for all tested conditions. The data revealed the plasmoid was limited in lifetime to only a few (4-10) μs, too short for translation at low energy. A global stability study showed that the plasma suffered a radial collapse onto the inner wall early in its lifecycle. The radial collapse was traced to a magnetic pressure imbalance. A correction made to the circuit was successful in restoring an equilibrium pressure balance and prolonging radial stability by an additional 2.5 μs. The equilibrium state was sufficient to confirm that the plasmoid current in an AFRC reaches a steady-state prior to the peak of the coil currents. This implies that the plasmoid will always be driven to the inner wall, unless it translates from the coils prior to peak coil currents. However, ejection of the plasmoid before the peak coil currents results in severe efficiency losses. These results demonstrate the difficulty in designing an AFRC experiment for translation as balancing the different requirements for stability, balance, and efficient translation can have competing consequences.

Essays on employment / education, investment in education and student achievement

Méthodologie: Modèle de régression quantile de variable instrumentale pour données de Panel utilisant la fonction de production partielle