As the demand for energy worldwide increases, the oil and gas industry will need to increase recovery from unconventional gas reservoirs (UGR). UGRs include Tight Gas Sand (TGS), coalbed methane and gas shales. To economically produce UGRs, one must have adequate product price and one must use the most current technology. TGS reservoirs require stimulation as a part of the completion, so improvement of completion practices is very important. We did a thorough literature review to extract knowledge and experience about completion and stimulation technologies used in TGS reservoirs. We developed the principal design and two modules of a computer program called Tight Gas Sand Advisor (TGS Advisor), which can be used to assist engineers in making decisions while completing and stimulating TGS reservoirs. The modules include Perforation Selection and Proppant Selection. Based on input well/reservoir parameters these subroutines provide unambiguous recommendations concerning which perforation strategy(s) and what proppant(s) are applicable for a given well. The most crucial parameters from completion best-practices analyses and consultations with experts are built into TGS Advisor’s logic, which mimics human expert’s decision-making process. TGS Advisor’s recommended procedures for successful completions will facilitate TGS development and improve economical performance of TGS reservoirs.

Abstract Taiwan, which is located in the subtropics, is in need of air-conditioning system to provide its people with a more comfortableenvironment. Since apparatus is used frequently, equipments may break down easily. Often, we¡¦ll need a great amount of budget for mending these damaged equipments. Therefore, we have come up with an idea in order to overcome the difficulties. AI (artificial intelligence) related technology has been under research for several years. Due to the fact that people demand computers to become more intelligent, there are many new innovations to be developed within the field of AI. Expert system is one of the newest technologies that increase the benefits brought to us through AI. Different from the conventional program, the expert system has plenty of advantages which include graphical interface, inferring mechanism, and knowledge-base, which can store a lot of professional knowledge. Moreover, the program is almost a real expert for it could teach people by its dialogue function. Based on this advantage, the unit can save an amount of money from using the expert system. Prolog is a program language used to write expert systems. It was invented by Colmerauer and Roussel in 1972. Because of its powerful function, Japan uses it as a tool to create the Fifth Computer Generation System (FGCS). According to the plan, the system must contain many user-friendly functions, which enables it to receive information by listening to people¡¦s voice, and it can learn everything ¡V almost as much as human beings. As for the programming of the VII language, Prolog uses a special syntax. When the predicate matches the fact, the function would be executed. This special program syntax is good for describing things. From now on, Prolog will be much more welcomed because it works in a more acceptable way for people. Finally, we would like to promote the techniques to the field of air-conditioning in order to offer people a new solution to deal with the flaws.

The oil barge operation in Kaohsiung harbor is one of typical systems of resources allocation problems in a complex and dynamic environment. Such system is far more difficult to deal with than a static and deterministic system and often depends on experienced human experts for the oil barge assignment. One of the major dilemmas faced by the system is that decision makers do not know the managerial efficiency under the current dispatching mechanism. Besides, if the dispatching rules have been modified due to the resource variation in the future, how would the changes affect the system? The current research is trying to develop an evaluation system for oil barge assignment. The objective of the system is to evaluate the overall performances of the oil barge operation in Kaohsiung harbor. Both expert system and system simulation techniques would be applied for such analysis. To acquire the current heuristic of oil barge assignment and then transfer it to a rule-based knowledge in an expert system, the interview with the engineer, who is responsible for making such decision, is the crucial step. With the knowledge base and the reasoning mechanism available, it is possible to imitate the current oil barge assignment. To further evaluate the performance of such assignment rule, the current research has developed the system simulation model of oil barge operation. This model is able to quantify the service quality under various assignment scenarios. The results of simulation can further be presented to the decision makers with easy-understanding animations. The case study would focus on Kaohsiung harbor¡¦s oil barge operation. The integrity and suitability of the expert system and simulation model have been validated through extensive statistical analysis. At last, various scenario analysis based on such integrated models have been conducted to improve the current oil barge operation and to set the appropriate response plans confronted by the future development of Kaohsiung harbor as the Asia-Pacific transshipment center.

With load growth of distribution systems, it becomes very complicated for dispatchers to obtain restoration plan for unfaulted but out-of-service areas. In this thesis, a rule-based expert system with a colored Petri net (CPN) inference model is developed. The CPN models of distribution components such as four-way line switches are proposed to derive the proper switching operation plan for service restoration by applying reasoning in the CPN. After main transformer contingency has been identified and isolated, it is highly possible that the out of service customers can not be restored completely because of the shortage of capacity reserve. The feeders which serve more key customers with higher service priority will have better chance to be selected for restoration. With the system reconfiguration to cover the load change of service zones over a longer period, during the process of switching operation, the maximum load demand of out-of-service area over the restoration time is considered in the CPN. To prevent the over-unbalance tripping of distribution feeders during switching operation process, the maximum tolerable current unbalance between any two phases is also considered in the CPN model. To assure the restoration plan complying with the operation regulation, heuristic rules based on the standard operation procedures of Taipower distribution system are included in the best first search of the CPN. A Taipower distribution system with 67 feeders is selected for computer simulation in this thesis to demonstrate the effectiveness of the proposed methodology. It is found that the service restoration of distribution systems can be obtained very efficiently by applying the proposed CPN model.

As the demand for energy worldwide increases, the oil and gas industry will need to increase recovery from unconventional gas reservoirs (UGR). UGRs include Tight Gas Sand (TGS), coalbed methane and gas shales. To economically produce UGRs, one must have adequate product price and one must use the most current technology. TGS reservoirs require stimulation as a part of the completion, so improvement of completion practices is very important. We did a thorough literature review to extract knowledge and experience about completion and stimulation technologies used in TGS reservoirs. We developed the principal design and two modules of a computer program called Tight Gas Sand Advisor (TGS Advisor), which can be used to assist engineers in making decisions while completing and stimulating TGS reservoirs. The modules include Perforation Selection and Proppant Selection. Based on input well/reservoir parameters these subroutines provide unambiguous recommendations concerning which perforation strategy(s) and what proppant(s) are applicable for a given well. The most crucial parameters from completion best-practices analyses and consultations with experts are built into TGS Advisor's logic, which mimics human expert's decision-making process. TGS Advisor's recommended procedures for successful completions will facilitate TGS development and improve economical performance of TGS reservoirs.

Autorotation maneuvers are required to perform a safe landing of a helicopter in cases of engine loss in a single engine vehicle and transmission or tail rotor malfunction. The rise of autonomous helicopter technology, and the pilot skill required to manually perform an autorotation, motivate the need for new autonomous autorotation control laws. Previous approaches to automatic control for this maneuver have relied on control law optimization based on a high-fidelity model of the helicopter, or have attempted to match recorded trajectories flown by an expert human pilot. In this paper, a new expert control system is proposed. The term “expert control system” is used because the system is intended to mimic the actions that a human pilot might take, does not require any iterative learning, model prediction, or optimization at runtime, and is based on an inference system that involves fuzzy logic, PID, and other conventional control techniques. The multi-stage control law drives the helicopter to a near-optimal steady-state descent and uses an estimate of the time to impact to safely flare and land the helicopter in the vast majority of flight conditions. The control law is validated using a full 6-degree-of-freedom simulation of both a full-size attack helicopter and a small hobby-class helicopter. The pro- posed control design is highly flexible and may be used to perform fully autonomous autorotation or to provide guidance to pilots during manual autorotation maneuvers.

This research programme was carried out in order to establish design methods and procedures for thermowells and implement these methods in a computer-based expert system. Thermowells are accessories for the temperature measurement instrumentation and they have to protect the temperature sensor from hazardous environments at high pressures and temperatures. The sensor also needs protection from the flow of the fluid it is immersed in as it can cause the sensor to vibrate and subsequently damage it. Thermowells have to be designed in such a way that they can resist the vibration caused by the flowing fluid, do not collapse due to the surrounding pressure and the thermowell's material has to be compatible with the fluid to avoid corrosion of the thermowell. At the same time they have to transfer the heat of the fluid to the sensor to enable the temperature measurement. A literature review was carried out to establish the available methods and procedures concerning thermowell design. The procedures that deal with the calculation of the natural frequency of thermowells, which is required to ensure the thermowell is not damaged by vibration, were verified using practical vibration analysis techniques. After establishing the appropriate procedures to determine the vibration, pressure, stress and thermal aspects concerning thermowell design, they were implemented in an expert system. The software package KAPPA-PC was used to develop the application. After careful testing and elimination of different errors encountered during the testing phase, an expert system was delivered that carries out the analysis of a given thermowell design and also designs a thermowell for a specified application.

The Virginia Integrated Pest Management Expert for Wheat was designed to combine the best available information regarding wheat pest management of disease pathogens, weeds, and insects into a decision support system that would provide potential outbreak risk and pest control information to the Comprehensive Resource Planning System (CROPS). In addition, the system stands alone as an educational tool for farmers and Extension personnel. This is a rule-based system developed on the Microsoft Windows platform. Knowledge about crops and pest management is represented in the form of IF/THEN rules, demons, and "when-changed" methods. The inference engine analyzes specific crop system information entered by the user to determine potential risks of outbreak for wheat crop pests common to Virginia. These potential outbreak risks are presented as low, medium, and high levels of risk and are presented for each of 15 pests of wheat in Virginia. The system was evaluated using thirty random cropping system scenarios. By comparing expert system output with output from human experts, it was shown that the expert system agreed with human expert opinions in 84 percent of the decisions made. Statistical analysis of the insect pest data showed that there was no significant statistical difference between the distribution of the human expert predictions and the expert system predictions. Statistical analysis of the disease pest data showed that there were some significant statistical differences between the distribution of the human expert predictions and the expert system predictions. / Master of Science

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