In the current global climate of declining fossil fuel reserves and due to the impact of industry on the natural environment, industrial sustainability is becoming ever more important. However, sustainability is quite a vague concept for many, and there are a range of interpretations of the word. If the resource efficiency of a factory is taken as a measure of its sustainability, then the concept becomes better defined and quantifiable. In order to analyse the resource efficiency of a factory and suggest improvements, all flows through the manufacturing system need to be modelled. However the factory is a complex environment, there is a wide variation in the quality levels of energy as well as the composition of material flows in the system. The research presented in this thesis shows how the thermodynamics-based concept of ‘exergy’ can be used to quantify the resource efficiency of a factory. The factory is considered an ‘integrated system’, meaning it is composed of the building and the production processes, both interacting with each other. This is supported by three case studies in different industries that demonstrate the practical application of the approach. A review of literature identified that it was appropriate to develop a novel approach that combined exergy analysis with the integrated view of the factory. Such an approach would allow a ‘holistic’ assessment of resource efficiency for different technology options possibly employable. The development of the approach and its illustration through practical case studies is the main contribution of the work presented. Three case studies, when viewed together, illustrate all aspects of the novel exergy based resource accounting approach. The first case study is that of an engine production line, in which the resource efficiency of this part of the factory is analysed for different energy system options relating to heating ventilation and air conditioning. Firstly, the baseline is compared with the use of a solar photovoltaic array to generate electricity, and then a heat recovery unit is considered. Finally, both of these options were used together, and here it is found that the non-renewable exergy supply and exergy destruction are reduced by 51.6% and 49.2% respectively. The second case study is that of a jaggery (a sugar substitute) production line. The exergy efficiency of the process is calculated based on varying the operating temperature of the jaggery furnace. The case study describes the modelling of al flows through the jaggery process in terms of exergy. Since this is the first example of an exergy analysis of a jaggery process, it can be considered a minor contribution of the work. An imaginary secondary process that could utilize the waste heat from the jaggery process is considered in order to illustrate the application of the approach to industrial symbiosis. The non-renewable exergy supply and exergy destruction are determined for the baseline and the alternative option. The goal of this case study is not to present a thermally optimized design; rather it illustrates how the exergy concept can be used to assess the impact of changes to individual process operations on the overall efficiency in industrial symbiosis. When considering natural resource consumption in manufacturing, accounting for clean water consumption is increasingly important. Therefore, a holistic methodology for resource accounting in factories must be able to account for water efficiency as well. The third case study is that of a food production facility where the water supply and effluent are modelled in terms of exergy. A review of relevant literature shows that previously, the exergy content of only natural water bodies and urban wastewater had been quantified. To the author’s knowledge, this is the first example of applying this methodology of modelling water flows in a manufacturing context. The results show that due to a high amount of organic content in food process effluent, there is significant recoverable exergy in it. Therefore, a hypothetical water treatment process was assumed to estimate the possible savings in exergy consumption. The results show that at least a net 4.1% savings in terms of exergy could be possible if anaerobic digestion water treatment was employed. This result can be significant for the UK since the food sector forms a significant portion of the industry in the country. Towards the end of the thesis, a qualitative study is also presented that aims to evaluate the practical utility of the approach for the industry. A mixed method approach was used to acquire data from experts in the field and analyse their responses. The exergy based resource accounting method developed in this thesis was first presented to them before acquiring the responses. A unanimous view emerged that the developed exergy based factory resource accounting methodology has good potential to benefit industrial sustainability. However, they also agreed that exergy was too complex a concept to be currently widely applied in practice. To this effect, measures that could help overcome this barrier to its practical application were presented which form part of future work.

The aim of this work is to investigate the energy consumption of the servo drive at different control settings. First, the theoretical part describes the servo drive as a mechatronic system with subsequent disassembly in terms of losses and efficiency, where all the losses that occur in the servo drives are defined. Subsequently, the theoretical part concludes with a chapter on controllers, thanks to which it is possible to control servo drives and describes their influence on the resulting control. In the practical part, a model of a DC motor with a linear axis and regulation was first created in the Simulink program. Subsequently, the Matlab program defined motion with linear acceleration and motion using S-curves, which controlled the model. Then the model was measured at different settings of the controllers and the resulting waveforms together with the energy values were compared with each other. In the second half of the practical part of this work, a real servo drive was then measured with a subsequent comparison with the created model. In this comparison, the resulting waveforms and energy values were also compared. The result of this work is then to determine the effect of changes on the resulting control, which are made in the controller settings. The functional models can then be used to determine how the various servo drives will behave under the given control conditions.

No description available.

This thesis investigates three major aspects of energy consumption rebound effects (RE) in three papers. More specifically, the issues addressed are (i) the magnitude of economy-wide rebound effect (ii) the role of energy policy instruments in mitigating it and (iii) its channels of impact. The research begins with the estimation of cross-country economy-wide rebound effects for a panel of 55 countries over the period 1980 to 2010. A two-stage approach is utilized in which energy efficiency is first estimated from a stochastic input distance frontier (SIDF). The estimated energy efficiency is then used in a second stage dynamic panel model to derive short-run and long-run RE for an array of developing and developed countries. The cross-country point estimates indicate substantial RE magnitudes across sampled countries during the period under consideration, although a positive and encouraging finding is the declining RE trend across most of the sampled countries during the study period. The second paper contains an RE benchmark for 19 EU countries, as well as an investigation of the effects of two energy policy instruments (energy taxes and ener-gy R&D) on RE performance over the period 1995 to 2010. The results indicate that RE performance improved over the sample period, reinforcing the results from paper one. In addition, there is also some evidence suggesting that binding market-based instruments such as energy taxes have been more effective in restricting RE than in-direct instruments such as energy R&D during the period under consideration. This is consistent across both estimated model specifications. An important observation from the first essay is the slightly larger average RE across the non-OECD countries. For this reason, the last empirical chapter evaluated the channels through which RE stimulated energy use across productive sectors of major developing/emerging economies, namely Brazil, Russia, India, Indonesia and China. To achieve this, the essay relied on duality theory to decompose changes in energy demand into substitution and output effects through the estimation of a trans-log cost function using data spanning 1995-2009. Findings reveal that energy use elasticities across sampled sectors/countries are dominated by substitution effects. One intriguing result that also emerges from this analysis is the role of economies of scale and factor accumulation, rather than technical progress, in giving rise to eco-nomic growth and energy consumption in these countries during the period under consideration.

To achieve agreed targets for reducing global carbon emissions, industry must become more resource-efficient. To this end, two viable strategies exist: energy efficiency and material efficiency. Despite their inherent interdependence, industry continues to treat these two strategies as isolated pursuits, providing in the process only a partial insight into the potential of resource efficiency. To resolve this disconnect, this thesis attempts to develop and apply tools that help integrate industrial energy and material efficiency analyses. Three areas of research are explored. The first is concerned with a fundamental component of industrial performance: efficiency benchmarks. No agreed-upon metric exists to measure the efficiency with which the sector trans- forms both energy and materials - that is, how resource-efficient they are. This thesis applies exergy - a well-established method to consolidate energy and materials into a single metric - to a case study of the global steel industry in 2010. Results show that this exergy-based metric provides a suitable proxy to capture the interactions between energy and materials. By comparing energy and material efficiency options on an equal footing, this metric encourages the recovery of material by-products - an intervention excluded from traditional energy efficiency metrics. To realise resource efficiency opportunities, individual industry firms must be able to identify them at actionable time-frames and scopes. Doing this hinges on understanding resources flows through entire systems, the most detailed knowledge of which resides in control data. No academic study was found to exploit control data to construct an integrated picture of resources that is representative of real operations. In the second research area, control data is extracted to track the resource flows and efficiency of a basic oxygen steel-making plant from TataSteel. This second case study highlights the plant's material efficiency options during operations. It does so by building close-to-real-time Sankey diagrams of resource flows (measured in units of exergy) for the entire plant and its constituent processes. Without the support of effective policies the new exergy approach is unlikely to be widely adopted in industry. By collating evidence from interviews and policy documents, the third area explores why the European Union's industrial energy and emissions policies do not incentivise material efficiency. Results suggest several contributing factors, including: the inadequacy of monitored indicators; an imposed policy lock-in; and the lack of a designated industry lobby and high-level political buy-in. Policy interventions are then proposed to help integrate material efficiency into energy and climate agendas. The European Union's limited agency stresses the need for Member States and industry to drive the move to a low-carbon industry in the short-term.

Philosophiae Doctor - PhD (Chemistry) / Renewable energy has become the centrepiece of research in resolving the energy crisis. One of the forms of renewable energy is solar energy. This form of energy is costly to develop. Organic molecules are promising materials for the construction of next generation photovoltaic cells considering their advantage of lower cost compared to crystalline silicon that is currently used in solar cells. This forms the basis of this research, which focused on the synthesis and characterisation of poly(3- hexylthiophene) P3HT, stannum (Sn) nanoparticles and stannum-based bimetallic stannum-titanium (SnTi), stannum-chromium (SnCr) and stannum-vanadium (SnV) nanoparticles for the application in the construction of heterojunction photovoltaic cells (PVCs).

Im Zuge dieser Arbeit wurden die für die Dosimetrie mit BeO-OSL-Detektoren wichtigen Größen Energieansprechvermögen und Nachweiseffizienz experimentell ermittelt. Anschließend konnten die Ergebnisse genutzt werden, um ein Modell der lokalen Sättigung zur Berechnung der Effizienz für unterschiedlichste Bestrahlungsbedingungen zu generieren. Mit Hilfe des Modells lassen sich Vorhersagen zur Nachweiseffizienz für Photonen und Elektronen in dem in der Personen- und Ortsdosimetrie gängigen Energiebereich von 10 keV bis zu mehreren MeV treffen. Dabei nimmt die Effizienz für Elektronen mit sinkenden Energien kontinuierlich ab. Photonen zeigen einen ähnlichen Effekt, jedoch kommt es bei Energien im Bereich von 40-80 keV zu einem kurzen Anstieg der Effizienz mit fallender Energie, welcher sich durch die Wechselwirkungseigenschaften der Photonen erklären lässt. Die experimentellen und modellierten Nachweiseffizienzen können genutzt werden, um die Anzeige eines BeO-OSL-Detektor aus mit Strahlungstransportprogrammen ermittelten Dosiswerten zu berechnen. Auf experimentell gestützte Optimierungen von Bestrahlungsgeometrien kann so größtenteils verzichtet werden. Als Beispiel für die Anwendung der Nachweiseffizienz werden das Energieansprechvermögen für Beta-Strahler, des iBeOx-Personendosimeters sowie die Konzeption eines OSL-Ortsdosimeters aufgeführt.:1 Einleitung 2 Theoretische Grundlagen 2.1 Grundlagen zur Dosimetrie ionisierender Strahlung 2.2 Optisch Stimulierte Lumineszenz 2.3 Dosimetrie mit Hilfe der Optisch Stimulierten Lumineszenz 3 Material und Methoden 3.1 Berylliumoxiddetektoren und Dosimeter 3.2 Auswerteverfahren 3.3 Bestrahlungsmöglichkeiten 3.4 Strahlungstransportberechnungen 4 Experimentelle Ergebnisse 4.1 Rechnerisches Ansprechvermögen für BeO-OSL-Detektoren 4.2 Experimentelles Ansprechvermögen für BeO-OSL-Detektoren 4.3 Vergleich von rechnerischem und experimentellem ASV für BeO- Detektoren 4.4 Effizienz für BeO-OSL-Detektoren 5 Modellierung der Effizienz von BeO-OSL-Detektoren 5.1 Target-Modell 5.2 Berechnung der Effizienz auf Grundlage des Modells der lokalen Sättigung 5.3 Ergebnisse der Modellierung 6 Anwendungen 6.1 Ansprechvermögen für Beta-Strahler 6.2 Energieansprechvermögen des iBeOx-Personendosimeters 6.3 Konzeption eines Ortsdosimeters auf Basis des iBeOx-Dosimetriesystems 7 Zusammenfassung 8 Literaturverzeichnis A Anhang A.1 Theorie A.2 Messdaten und Ergebnisse A.3 Effizienzen für unterschiedliche Bestrahlungsgeometrien / In the course of this work, the experimental detection efficiency for BeO-OSL-detectors was determined for different radiation qualities. Subsequently the results were used to generate a model of local saturation for calculating the efficiency for different irradiation conditions. With the help of the model predictions for the detection efficiency for photons and electrons in the common energy range for personal and environmental dosimetry, reaching from 10 keV up to some MeV, are possible. The efficiency for electrons decreases with falling energy continuously. Photons show a similar effect, but for energies ranging from 40-80 keV the efficiency increases with decreasing energy. This can be explained by the interaction effects of the photons with the detector material. The experimental and modelled detection efficiencies can be used to calculate the display of a BeO-OSL detector from dose values determined with radiation transport programs. Three examples, the energy dependence for beta emitters, for the iBeOx personal dosimeters and the development of an environmental OSL-dosimeter are listed.:1 Einleitung 2 Theoretische Grundlagen 2.1 Grundlagen zur Dosimetrie ionisierender Strahlung 2.2 Optisch Stimulierte Lumineszenz 2.3 Dosimetrie mit Hilfe der Optisch Stimulierten Lumineszenz 3 Material und Methoden 3.1 Berylliumoxiddetektoren und Dosimeter 3.2 Auswerteverfahren 3.3 Bestrahlungsmöglichkeiten 3.4 Strahlungstransportberechnungen 4 Experimentelle Ergebnisse 4.1 Rechnerisches Ansprechvermögen für BeO-OSL-Detektoren 4.2 Experimentelles Ansprechvermögen für BeO-OSL-Detektoren 4.3 Vergleich von rechnerischem und experimentellem ASV für BeO- Detektoren 4.4 Effizienz für BeO-OSL-Detektoren 5 Modellierung der Effizienz von BeO-OSL-Detektoren 5.1 Target-Modell 5.2 Berechnung der Effizienz auf Grundlage des Modells der lokalen Sättigung 5.3 Ergebnisse der Modellierung 6 Anwendungen 6.1 Ansprechvermögen für Beta-Strahler 6.2 Energieansprechvermögen des iBeOx-Personendosimeters 6.3 Konzeption eines Ortsdosimeters auf Basis des iBeOx-Dosimetriesystems 7 Zusammenfassung 8 Literaturverzeichnis A Anhang A.1 Theorie A.2 Messdaten und Ergebnisse A.3 Effizienzen für unterschiedliche Bestrahlungsgeometrien

Power and cooling costs are some of the highest costs in data centers today, which make improvement in energy efficiency crucial. Energy efficiency is also a major design point for chips that power whole ranges of computing devices. One important goal in this area is energy proportionality, arguing that the system's power consumption should be proportional to its performance. Currently, a major trend among server processors, which stems from the design of chips for mobile devices, is the inclusion of advanced power management techniques, such as dynamic voltage-frequency scaling, clock gating, and turbo modes. A lot of recent work on energy efficiency of database management systems is focused on coarse-grained power management at the granularity of multiple machines and whole queries. These techniques, however, cannot efficiently adapt to the frequently fluctuating behavior of contemporary workloads. In this paper, we argue that databases should employ a fine-grained approach by dynamically scheduling tasks using precise hardware models. These models can be produced by calibrating operators under different combinations of scheduling policies, parallelism, and memory access strategies. The models can be employed at run-time for dynamic scheduling and power management in order to improve the overall energy efficiency. We experimentally show that energy efficiency can be improved by up to 4x for fundamental memory-intensive database operations, such as scans.

No description available.

The UK building stock accounts for about half of all energy consumed in the UK. A large portion of the energy is consumed by nondomestic buildings. Offices and retail are the most energy intensive typologies within the nondomestic building sector, typically accounting for over 50% of the nondomestic buildings’ total energy consumption. Heating, ventilating and air conditioning (HVAC) systems are the largest energy end use in the nondomestic sector, with energy consumption close to 50% of total energy consumption. Different HVAC systems have different energy requirements when responding to the same building heating and cooling demands. On the other hand, building heating and cooling demands depend on various parameters such as building fabrics, glazing ratio, building form, occupancy pattern, and many others. HVAC system energy requirements and building energy demands can be determined by mathematical modelling. A widely accepted approach among building professionals is to use building energy simulation tools such as EnergyPlus, IES, DOE2, etc. which can analyse in detail building energy consumption. However, preparing and running simulations in such tools is usually very complicated, time consuming and costly. Their complexity has been identified as the biggest obstacle. Adequate alternatives to complex building energy simulation tools are regression models which can provide results in an easier and faster way. This research deals with the development of regression models that enable the selection of HVAC systems for office buildings. In addition, the models are able to predict annual heating, cooling and auxiliary energy requirements of different HVAC systems as a function of office building heating and cooling demands. For the first part of the data set development used for the regression analysis, a data set of office building simulation archetypes was developed. The four most typical built forms (open plan sidelit, cellular sidelit, artificially lit open plan and composite sidelit cellular around artificially lit open plan built form) were coupled with five types of building fabric and three levels of glazing ratio. Furthermore, two measures of reducing solar heat gains were considered as well as implementation of daylight control. Also, building orientation was included in the analysis. In total 3840 different office buildings were then further coupled with five different HVAC systems: variable air volume system; constant air volume system; fan coil system with dedicated air; chilled ceiling system with embedded pipes, dedicated air and radiator heating; and chilled ceiling system with exposed aluminium panels, dedicated air and radiator heating. The total number of models simulated in EnergyPlus, in order to develop the input database for regression analysis, was 23,040. The results clearly indicate that it is possible to form a reliable judgement about each different HVAC system’s heating, cooling and auxiliary energy requirements based only on office building heating and cooling demands. High coefficients of determination of the proposed regression models show that HVAC system requirements can be predicted with high accuracy. The lowest coefficient of determination among cooling regression models was 0.94 in the case of the CAV system. HVAC system heating energy requirement regression models had a coefficient of determination above 0.96. The auxiliary energy requirement models had a coefficient of determination above 0.95, except in the case of chilled ceiling systems where the coefficient of determination was around 0.87. This research demonstrates that simplified regression models can be used to provide design decisions for the office building HVAC systems studied. Such models allow more rapid determination of HVAC systems energy requirements without the need for time-consuming (hence expensive) reconfigurations and runs of the simulation program.