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Typical energy audits are sufficiently expensive and time-consuming that many owners and managers of buildings are not willing to invest the time and money required for a full audit. This dissertation provides a methodology to identify buildings with large potential energy savings using limited information, specifically, utility bills, total area and weather data. The methodology is developed based on the hypothesis: if a commercial building is properly designed, constructed, operated, and maintained, the measured energy consumption should approximately match the simulated value for a typical building of the same size with the most efficient HVAC system; otherwise, there may be potential for energy savings. There are four steps in the methodology: 1) testing to determine whether the utility bills include both weather-dependent and weatherindependent loads; 2) separating weather-dependent and weather-independent loads when both are present in the same data; 3) determining the main type of HVAC system; 4) estimating potential energy savings and recommending an energy audit if appropriate. The Flatness Index is selected to test whether the utility bills include both weatherdependent and weather-independent loads. An approach to separate the utility bills based on thermal balance is developed to separate utility bills into weather-dependent and weather-independent loads for facilities in hot and humid climates. The average relative error in estimated cooling consumption is only 1.1% for 40 buildings in Texas, whereas it is -54.8% using the traditional 3P method. An application of fuzzy logic is used to identify the main type of HVAC system in buildings from their 12-month weatherdependent energy consumption. When 40 buildings were tested, 18 systems were identified correctly, seven were incorrect and the HVAC system type cannot be identified in 15 cases. The estimated potential savings by the screening methodology in eight large commercial buildings were compared with audit estimated savings for the same buildings. The audit estimated savings are between 25% - 150% of the potential energy savings estimated by the screening procedure in seven cases. The other two cases are less accurate, indicating that further refinement of the method would be valuable. The data required are easily obtained; the procedure can be carried out automatically, so no experience is required. If the actual type of HVAC system, measured weather-dependent, and weather-independent energy consumption are known, the methodology should work better.

The objective of this project is to design a tool for moderate cross section reduction of bars that are deformed within a channel slider tool that is used for equal channel angular extrusion (ECAE). The bars that are deformed via ECAE have an initial square cross section with a nominal value of 1.00 in2 and aspect ratios (length/width) ranging between 4 and 6. A systems engineering design methodology is used to generate a topbottom approach in the development of the tool's design. This includes defining a need statement, which is the "Need for an area reduction extrusion tool to replace the current practices of machining ECAE processed billets". The system functions and requirements are defined next and used to generate three concepts that are compared to select the winning concept for further refinement. Major components of the selected tool are: a container, ram, base plate, punch plate, four die-inserts, four wedges and four flange locks. For materials, such as copper (C10100) and aluminum (Al6061-T6), that can be processed by this tool, the upper bound extrusion pressure, which is derived by limit analysis, is set at 192 ksi. The upper bound extrusion pressure is constrained by the buckling limit of the ram, which is 202 ksi. The maximum wall stress experienced by the container is 113 ksi. For materials with the same cross section and dimensions, fixed end conditions of the Ram support larger bucking loads when compared to other end conditions such as rounded ends or rounded-fixed ends. With the application of the upper bound method, an increase in the extrusion ratio of the tool causes a corresponding rise in the optimal cone angle of the die further translating to a rise in the extrusion pressure.

This thesis proposes an interactive software tool that can be used to compute complete sets of Proportional Integral Derivative (PID) Controllers from knowledge of the plant transfer function/frequency response data. This is based on research results and algorithms developed by Bhattacharyya and others. Until these research results were published, it was not known if a nominal system could be stabilized using PID Controllers, and current PID Controller designs are carried out using ad hoc tuning rules. By using simulations, engineers can best plan for and observe the stabilizing effect each of the variables has on system performance in a realistic environment. The software application developed calculates and optimizes complete stabilizing sets of PID Controllers for a rational Linear Time Invariant (LTI) system, and has been developed for analytical models of plants with and without time delay. Further, these PID Controller sets are optimized to project subsets simultaneously satisfying multiple performance index specifications. Sets of PID Controllers that stabilize a system are also calculated automatically from knowledge of the frequency response of the plant. It allows the user ease of design and the ability to customize the final solution while permitting full control over source parameters. This thesis includes an introduction to the algorithms that have been developed for plant stabilization, a complete description of the graphical user interface, the simulation of the algorithms performed using LabVIEW, and a summary of future work.

During project execution, the status of the project is periodically evaluated, using traditional methods or standard practices. However, these traditional methods or standard practices may not adequately identify certain issues, such as lack of sufficient identification of warning signs that predict potential project failure. Current methods may lack the ability to provide real time indications of emerging problems that impact project outcomes in a timely manner. To address this problem, the Construction Industry Institute (CII) formed a research team to develop a new tool that can forecast the potential risk of not meeting specific project outcomes based on assessing leading indicators. Thus, the leading indicators were identified and then the new tool was developed and validated. A screening process was conducted through industry surveys after identifying potential leading indicators. Each time, industry professionals were asked to evaluate the negative impact of leading indicators on project outcomes that were identified to measure the impact of leading indicators on project health. Through this process, forty-three leading indicators were acquired finally. Using descriptive statistics, the amount of negative impact of each leading indicator on project outcomes was identified after the analysis of the survey results. Based on these impacts, the tool development was initiated. The tool concept is that no indication of problems based on assessing leading indicators results in the tool output score high. To comply with this concept, specific weights were assigned to each leading indicator to reflect the impact on each project outcome. By this procedure, the Project Health Indicator (PHI) tool was developed. The validation process of the PHI tool was conducted using completed projects and finally negative correlation was observed between project outcomes and health scores generated by the PHI tool.

<p>Enterprise Modelling (EM) tools are an important part ofevery EM application project. Continuous evolution of modellingmethods therefore requires efficient EM tool support. Extensiveefforts have been devoted to developing new EM tools andmodelling techniques. Considerably less attention has been paidto the aspects of acquiring and introducing EM tools inorganisations. Our grounded theory study shows that thisprocess is far from simple. It is determined by theorganisation's intentions regarding EM and by the situation inthe EM user organisation. As a contribution to this, we presentan EM tool acquisition process, which focuses on selecting anappropriate EM tool acquisition scenario for an organisation.This process has the following stages - assessing theorganisation, choosing an EM tool acquisition strategy, andfollowing the EM tool acquisition strategy. We support theprocess of evaluating the situation at hand by providingguidelines for assessing intentional and situational factorsthat influence the use of EM tools.</p><p>We also outline EM itself, along with its applicationprocess, and describe possible sources for gathering therequirements for an EM tool-set. Major requirements categoriesare discussed and analysed with respect to the goals andproblems regarding EM tools. Each category of requirements canbe satisfied to a certain degree, depending on theorganisational needs and various situational factors.</p><p>This grounded theory study provides two main contributions.Firstly, it proposes a systematic approach for EM toolacquisition supported by a set of guidelines.The approachenables an organisation to assess its needs of EM tools and itsown appropriateness for EM tool usage. As a result, an EM userorganisation is able to choose an EM tool acquisition strategythat meets the situation it faces. This is a contribution tothe overall success of practical use of EM methods and tools.Secondly, it provides an important baseline for future researchand theory building within the area of EM tool adoption andapplication. It also gives valuable information andrequirements for development of new EM tools and relatedservices.</p>

Thesis--Ph. D., University of Hong Kong, 1977.

When performing web searches, users manually open a web browser, direct it to a search engine, input keywords, and finally manually filter and select relevant results. This repetitive task can negatively impact the user's experience, something the automation and personalization of web search can address. This thesis presents PALTask, an Instant Messaging (IM) application that exploits context of both the user and their conversation in order to automate and personalize related web tasks such as web searches relevant to the conversation. PALTask dynamically gathers context and provides feedback from the user and the system at runtime including keywords from the conversation and running them through various search services such as YouTube and Google to retrieve relevant results. This thesis also explores various natural language processing (NLP) tasks such as keyword extraction, sentiment analysis, and stemming. These NLP tasks help in the collection of dynamic context at runtime, identifying personalized context, and analyzing it to improve the user's experience. We also present our keyword ranking algorithm which aims to improve accuracy when retrieving web resources. / Graduate

There is presently no wildfire model developed for Swedish conditions, only a fire danger rating system (FWI) has been developed for Swedish conditions. The demand for a wildfire model has not been great in the past in Sweden but the climate changes now taking place increases the risk of large and intensive wildfires in Sweden. The need for additional and better tools for sizing-up wildfires will be in great demand in the future. This pre-study is aimed at: - Presenting what has been done in the wildfire modeling field during the years and mainly the last twenty years. - Giving recommendations on the continued work with developing a Swedish wildfire model. The method that was used was literature and article survey. The study also looks into the required input data for a wildfire model and the input data available at the moment. This issue is highly crucial as the quality of the output of a wildfire model is depending upon the quality of the input data. During the study, a primitive wildfire model was constructed and refined in order to get an insight in the complexities and problems with developing an operational model. The following characterization of wildfire models was used during the study: - Statistical models: based primarily on statistics from earlier or experimental fires. They do not explicitly consider the controlling physical processes. - Semi-empirical models: based on physical laws, but enhanced with some empirical factors, often by lumping all physical mechanisms for heat transfer together. - Physical models: based on physical principles and distinguishing between physical mechanisms for heat transfer. The statistical models make no attempt to involve physical processes, as they are merely a statistical description of test fires. Thus the lack of a physical basis means that statistical models must be used carefully outside the test conditions. Semi-empirical models are often based on conservation of energy principles but do not make any difference between conduction, convection and radiation heat transfer. The semi-empirical model has low computational requirements and includes variables that are generally easy to measure in the field. So despite the issue with limited accuracy, the speed and simplicity of these models make them useful for operational use. Physical models have the advantage that they are based on known relationships and thus facilitating their scaling. Thus we can expect that physical models would provide the most accurate predictions and have the widest applicability. But the work on physical models is suffering of for example the lack of understanding of several processes, such as the characterization of the chemical processes taking place during combustion, the resulting flame characteristics and the isolation and quantification of physical processes governing heat transfer. The input data available today are generally not detailed enough for physical models. As a result, a very detailed physical model will still only give imprecise predictions. As better and more detailed input will be available, the use of physical models will be more justified. A semi-empirical model is recommended being developed in Sweden. This conclusion is based upon the following factors: - The accuracy of a semi-empirical model is generally much better than for a statistical model, also the use of a semi-empirical model is much wider than the use of a statistical model. - The amount of work required for developing a semi-empirical model will not differ much from the amount of work required for a statistical model. In both cases a number of test fires will have to be conducted to define and calibrate a number of fuel models representative of Sweden. - Presently the performance and application of physical models is not at an acceptable level (due to for example the complexity which they are to model and the computational capabilities of the PC’s of today) for operational use. The semi-empirical model for Sweden is recommended to be built upon Swedish conditions (i.e. built upon the type of vegetation found in Sweden) instead of trying to retrofit the local Swedish conditions into an existing model. This would most likely give the best output for Swedish conditions. A system for better input data - weather and fuel data – should be worked on as well. This could for example take advantage of the results of the very promising “Alarm”-project that is being conducted in western part of Sweden. Regarding the issue on better fuel data, new technology for satellite images or aerial photos and image classification techniques must be monitored as one major problem to be solved is distinguishing between the canopy fuel and the ground fuel. For more specific conclusions and reflections, please see the analysis and discussion, and conclusions sections of this report.

 This research is concerned with the transformation Mould and Die (MD) manufacturing industry from the traditional manufacturing paradigm into service-oriented manufacturing (SOM) in collaboration with leading manufacturers in the sector. It investigates how the new concept of Production Service System (PnSS) can be used and extended to integrate distributed manufacturing-oriented services (MOSs) so that all participants could efficiently and effectively collaborate in response to market opportunities. In the PnSS model, MD manufacturers become more specialized in providing certain types of MD products and components while outsourcing other components or related services as MOSs from MOS providers (MOSPs). The main objective of this research is to develop an information and collaboration platform for PnSS (iPnSS) to utilize MOSs and support the implementation of PnSS strategy for MD industry. The proposed iPnSS is developed based on the SOA (Service-oriented Architecture) paradigm, which aims to encapsulate MOSs as Software as a Service so that MOSs can be advertised, searched, and utilized by stakeholders in PnSS. Several core MOSs have been developed as the core components of iPnSS to meet the urgent requirements of participants in new business model, including Ontology-based Dynamic Alliance Service (ODAS) for forming PnSS alliance, Real-time Order Progress Kanban Service (RT-OPKS) for collaborative project tracking and coordinating, and Hybrid Flow Shop Assembly Scheduling Service (HFS-ASS) for production planning and scheduling which is specified for MD production. The research makes several key contributions. First, this research investigates the characteristics and challenges of MD industry, and develops the PnSS business model to transform the traditional manufacturing into service-oriented manufacturing for MD industry. An information and collaboration platform called iPnSS is developed to provide related IT solutions for integrating distributed MOSs to facilitate the practical usage of PnSS. Second, Ontology-based Dynamic Alliance Service is developed to enable participants to form alliance and take advantage of SOM. This service provides a systematic and integrated supplier selection approach in PnSS, being responsible for the major stages in the life cycle of a service-enabled manufacturing process, including service provision and consumption as well as service evaluation and organization respectively. Third, Real-time Order Progress Kanban Service with the support of Radio Frequency Identification (RFID) technology is developed to support the efficient knowledge feedback for shop floor visibility and traceability. This service provides a set of mechanisms to monitor, evaluate and coordinate the manufacturing execution during the process of collaborative manufacturing after the formation of alliance. Finally, Hybrid Flow Shop Assembly Scheduling Service is developed to deal with scheduling problem for manufacturing one-of-a-kind products, which is based on real-life study with MD industrial collaborators. For each order in MD manufacturing is assembled after the required components have been produced, the service firstly considers the production simultaneity of components of the same product for final assembly. The service automatically generates scheduling results for PnSS user. / published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy