Syftet med denna studie var att undersöka unga idrottares upplevelser i en topprestation. Studiens frågeställningar var: ·        Vilka upplevelser har unga idrottare i en topprestation? ·        Upplever unga idrottare flow i en topprestation? ·        Vilka faktorer ligger bakom en topprestation hos unga idrottare?  Utifrån syfte och frågeställningar valdes mätinstrumentet Flow State Scale-2 (FSS-2). FSS-2 består av ett påståendeformulär som mäter den totala upplevelsen av flow samt var och en av de nio dimensionerna av flow. Kontakt togs via telefon och mail med ansvariga tränare vid idrottsgymnasier för att finna unga idrottare med ett tydligt minne av en topprestation. Undersökningsgruppen blev 51 stycken unga idrottare, män och kvinnor i åldrarna16-20 år som utövat fotboll, ishockey eller orientering på elitnivå. Litteratursökning gjordes i bibliotekskatalogen tillhörande Umeå Universitet. Den funna relevanta litteraturen och artiklarna har legat till grund för denna studies bakgrundsdel.  Påståendeformuläret FSS-2 visar att undersökningspersonerna, i sin topprestation, hade en stark upplevelse av inre tillfredsställelse, tydliga mål, koncentration på uppgiften, känsla av kontroll och balans mellan skicklighet och utmaning. Vidare upplevde de att handlingar och tankar kunde utföras automatiskt, tydlig återkoppling av resultatet i prestationen och avsaknad av osäkerhet. Undersökningsgruppen upplevde en viss förändrad tidsuppfattning i sin topprestation. Resultatet av studien visar att undersökningspersonerna upplevde en hög grad av flow i sina topprestationer. Bakomliggande faktorer till de unga idrottarnas topprestationer är kroppsliga dimensioner, fysiologiska faktorer, motoriska faktorer, psykologiska faktorer och sociologiska faktorer.  En slutsats av denna studie är att oavsett kön eller typ av idrott framkommer följande karaktäristiska faktorer när de upplevt en topprestation; trygg, säker, automatiserad, fokuserad och en känsla av kontroll. Dessa faktorer sammantaget tycks skapa en tydlig upplevelse av tillfredsställelse och glädje.

ABSTRACT The aim of this dissertation is to fabricate an optical transceiver based on Si-bench technology for light peak application. The transceivers are composed of hybrid integration of the vertical cavity surface-emitting lasers (VCSEL), photo diodes and multi-mode fibers (MMF) on the Si optical bench using V-groove and U-groove structures. We are able to passively align VCSEL to MMF and photo diode to MMF because of the accurately-aligned characteristic of V-groove. The 45-degree-angled fibers with mirror coating are used to bend the directions of both the incoming and outgoing lights to the photodiode and the MMF. The simulations showed that the optical losses of the transceiver are less than 10 dB when the distance between VCSEL and MMF is 250£gm.The measured optical losses between transmitting module and receiving module are less than 12 dB. Key words: Light Peak¡Boptical transceiver¡BSi-bench¡Baccurately-aligned

Thermal energy storage(TES) air-conditioning system is a electrical load management technology with great potential to shift load from peak to off-peak utility periods. TES is now in widespread use for electric rate structures and energy policies and becomes a great contribution to energy conservation. However, TES is more complicated than conventional air-conditioning system in design and control strategies. According to practical field operation, the control of dynamic characters is especially difficult, and so are storage capacity design , discharging rate and charging capacity selection. This study set an example how to improve the energy performance of a retrofitted thermal energy storage air-conditioning system of a marine museum. Through full-scale experiment, historical air-conditioning operation data and computer simulation, the solution is provided on condition of unchanging major water pipe and equipment. This example can be a good demonstration for upping performance of TES. After testing and recording data for one year, this case indicates the investigation is effective and valuable to electric power management and green technology.

This work presents a novel slack management technique, the Service Rate Based Slack Distribution Technique, for dynamic real-time distributed embedded systems targeting the reduction and management of energy consumption. Energy minimization is critical for devices such as laptop computers, PCS telephones, PDAs and other mobile and embedded computing systems simply because it leads to extended battery lifetime. Such systems being power hungry rely greatly upon the system design and algorithms for processing, slack and power management. This work presents an effcient dynamic slack management scheme for an energy aware design of such systems. The proposed Service Rate Based Slack Distribution Technique has been considered with two static(FCFS, WRR) and two dynamic(EDF, RBS) scheduling schemes used most commonly in distributed systems. A fault tolerance mechanism has also been incorporated into the proposed technique inorder to use the available dynamic slack to maintain checkpoints and provide for rollbacks on faults. Results show that in comparion to contemporary techniques, the proposed Service Rate Based Slack Distribution Technique provides for about 29% more perfor-mance/overhead savings when validated with real world and random benchmarks.

Residential buildings in the United States are responsible for the consumption of 38% of electricity, and for much of the fluctuations in the power demands on the electric grid, particularly in hot climates. Residential buildings are also where occupants spend nearly 69% of their time. As “smart” technologies, including electric grid-connected devices and home energy management systems are increasingly available and installed in buildings, this research focuses on the use of these technologies combined with available energy use data in accomplishing three main objectives. The research aims to: (a) better understand how residential buildings currently use electricity, (b) evaluate the use of these smart technologies and data to reduce buildings’ electricity use and their contribution to peak loads, and (c) develop a methodology to assess the impacts of these operational changes on occupant thermal comfort. Specifically this study focuses on two of the most significant electricity consumers in residential buildings: large appliances, including refrigerators, clothes washers, clothes dryers and dishwashers, and heating, ventilation and air conditioning (HVAC) systems. First, to develop an improved understanding of current electricity use patterns of large appliances and residential HVAC systems, this research analyzes a large set of field-collected data. This dataset includes highly granular electricity consumption information for residential buildings located in a hot and humid climate. The results show that refrigerators have the most reliable and consistent use, while the three user-dependent appliances varied more greatly among houses and by time-of-day. In addition, the daily use patterns of appliances vary in shape depending on a number of factors, particularly whether or not the occupants work from home, which contrasts with common residential building energy modeling assumptions. For the all-air central HVAC systems studied, the average annual HVAC duty cycle was found to be approximately 20%, and varied significantly depending on the season, time of day, and type of residential building. Duty cycle was also correlated to monthly energy use. This information provides an improvement to previously assumed values in indoor air modeling studies. Overall, the work presented here enhances the knowledge of how the largest consumers of residential buildings, large appliances and HVAC, operate and use energy, and identifies influential factors that affect these use patterns. The methodologies developed can be applied to determine use patterns for other energy consuming devices and types of buildings, to further expand the body of knowledge in this area. Expanding on this knowledge of current energy use, smart large appliances and residential HVAC systems are investigated for use in reducing peak electric grid loads, and building energy use, respectively. This includes a combination of laboratory testing, field-collected data, and modeling. For appliance peak load reduction, refrigerators are found to have a good demand response potential, in part due to the nearly 100% of residential buildings that have one or more of these appliances, and the predictability of their energy consumption behavior. Dryers provide less consistent energy use across all homes, but have a higher individual peak power demand during afternoon and evening peak use times. These characteristics also make dryers also a good candidate for demand response. The study of continuous commissioning of HVAC systems using energy data found that both runtime and energy use are increased, and cooling capacity and efficiency are reduced due to the presence of faults or inefficiencies. The correction of these faults have an estimated 1.4% to 5.7% annual impact on a residential building’s electricity use in a cooling-dominated climate such as the one studied. Overall, appliance peak load reduction results are useful for utility companies and policy makers in identifying what smart appliance may provide the most peak energy reduction potential through demand response programs. The results of the HVAC study provides a methodology that can be used with energy use data, to determine if an HVAC system has the characteristics implying an inefficiency may be present, and to quantify the annual savings resulting from its correction. The final aspect of this research focuses on the development of a tool to enable an assessment the effect of operational changes of a building associated with energy and peak load reduction on occupant comfort. This is accomplished by developing a methodology that uses the response surface methodology (RSM), combined with building performance data as input, and uncertainly analysis. A second-order RSM model constructed using a full-factorial design was generally found to provide strong agreement to in and out-of-sample building simulation data when evaluating the Average Percent of People Dissatisfied (PPD[subscript avg]). This 5-step methodology was applied to assess occupant thermal comfort in a residential building due to a 1-hour demand response event and a time-of-use pricing rate schedule for a variety of residential building characteristics. This methodology provides a model that can quickly assess, over a continuous range of values for each of the studied design variables, the effect on occupant comfort. This may be useful for building designers and operators who wish to quickly assess the effect of a change in building operations on occupants. / text

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The basin factor is a hydrologic parameter that represents the overall impedance to flow of a watershed in the PC-Hydro peak discharge model for small ( < 10 mi2) semi-arid watersheds in Pima County, Arizona. To improve peak discharge estimates and provide validation of the basin factor as a physically-based parameter, basin factor values were "back-calculated" for return period and observed events on six undeveloped rangeland watersheds and correlated with Manning's n roughness coefficients, rainfall intensities, and hydraulic radii. Observed basin factor values displayed a positive trend with observed peak discharge. The results suggest that the correlated variables can predict the basin factor on small undeveloped sub-basins in Pima County and the basin factor is measurable as a physical parameter. Empirical models for basin factor prediction are proposed. The study may also be useful for estimating hydraulic roughness in hydrologic methods such as the kinematic wave time of concentration equation.

As many variable pricing projects are still in the implementation stage, long-run driver responses to the variable tolls are largely unknown. This research examined the long-run changes in driver behavior in an existing variable pricing project in Lee County, Florida. Using empirical evidence, it was found that over time the price elasticities of demand on the Lee County toll bridges have decreased from -0.42 to - 0.11 (Midpoint Memorial Bridge) and from -0.31 to -0.06 (Cape Coral Bridge) during the early morning discount period. The elasticities have decreased, but to a lesser extent, during the late morning and early afternoon discount periods. A discount period volume spreading ratio was also developed to analyze these changes. The results from this analysis confirmed the elasticity results. In addition to the empirical analysis of travel patterns discussed above, a telephone survey of drivers was conducted. The survey results indicated that certain driver characteristics such as higher frequency of trips, commute trip purpose, full-time employment status, more people in the household, higher education, and age between 25-34 years, were all indicators that the participant may increase his or her variable pricing usage over time. Other characteristics, including being retired and having a household income less than $16,000, were indicators that the driver may not increase variable pricing participation. Binary logit and semiparametric models were also developed to examine socio-economic and commute characteristics that may influence a driver increasing his or her participation in a variable pricing program. The results from these two variable toll bridges in Lee County indicated a decrease in variable toll price elasticity over time. However, these results may not be typical for variable pricing projects. Factors such as alternative routes, different traveler demographics, traffic congestion levels, and size of the toll discount may influence the results obtained from other variable pricing projects. However, the methodology developed in this research can be applied to other projects in order to determine those toll price elasticities of demand.

Renewable energy integration will become a significant issue as renewable penetration levels increase, and will require new generation support infrastructure; Energy storage provides one solution to this issue. Specifically, battery technologies offer a wide range of energy and power output abilities, making them ideal for a variety of integration applications. Distributed energy storage on distribution grids may be required in many areas of Canada where renewables will be installed. Peak shaving using distributed small (residential) energy storage can provide a reduction in peak loads and help renewable energy integration. To this end, a peak shaving model was developed for typical houses in several regions in Canada which provided sizing and performance results. An experimental battery bank and cycling apparatus was designed and constructed using these sizing results. This battery bank and cycling apparatus was then used to calibrate and validate a lithium iron phosphate battery energy storage system model.

This thesis employs a case study approach to investigate local implications of globally restricted mobility by examining Queenstown’s vulnerability to peak oil and climate change. Qualitative research methods are the principal means of inquiry. The research findings suggest that Queenstown is particularly vulnerable to peak oil and climate change at a broad scale because of its dependence on tourism and heavy reliance on air transport. However, Queenstown has fortuitously built up resilience to peak oil and climate change through tourism industry diversity, comparative advantage and an increasing proportion of short-haul visitors. A selection of key Queenstown tourism stakeholders interviewed as part of the research demonstrated some grasp of peak oil and climate change issues but lacked in-depth understanding. They generally considered the issues as being beyond their control although several suggested ways that Queenstown could strengthen resilience to peak oil and climate change. In terms of solutions, this research identifies three potential strategies. The first involves investing in a low carbon local transport system to increase destination level resilience to peak oil and climate change and enhance the uniqueness of the Queenstown brand. The second involves Queenstown promoters targeting the high-end niche tourism market in order to create a more resilient visitor profile. And the third involves the creation of new and expansion of existing industries not tied to tourism – preferably industries that are not excessively oil dependent and carbon intensive. But in order to successfully tackle the problem, it is imperative to first raise awareness. The research recommends implementing a framework that ensures an inclusive community-wide open dialogue process as the most effective way to achieve this.