Real-time digital simulation of electrical machines and drives is an efficient approach to evaluate the true behavior of newly designed machines and controllers before applying them in a real system. State-of-the-art real-time digital simulators aim to offer a precise replica for different parts of an electrical drive. By the aid of these powerful simulators and hardware-in-the-loop (HIL) simulation, design engineers are able to test their new controllers or machines against a virtual motor drive which has been previously modeled and tested off-line. Interaction between different parts of the electrical drive, especially under hazardous and abnormal conditions, can then be studied in a cost-effective manner. Although many studies about the optimized models of power electronic drives and digital controllers for real-time simulation have been done, the real-time models of electrical machines are still limited to the lumped parameter electric circuit models. This is mainly due to the complexity of a detailed electrical machine model which makes it computationally expensive. In this thesis geometrical real-time permeance network models (PNMs) of induction machines are developed which can accommodate the local phenomena inside an electric machine such as saturation and slotting. For this purpose, numerical methods inside the model are optimized to reduce the computation time. Novel nonlinear solution algorithms are also developed to address the problem of real-time simulation of nonlinear systems. Next, the proposed model is linked with other parts of an electric drive to develop a PNM-based real-time induction motor drive. A comparison of the results obtained through real-time simulation and experiment shows their agreement. / Power Engineering and Power Electronics

Thesis (M.S.)--University of Missouri-Columbia, 2006. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (February 23, 2006) Includes bibliographical references.

The purpose of this study was to evaluate variations of the Natural Resources Conservation Service (NRCS) curve number (CN) method for estimating near real-time runoff for naturalized flow, using high resolution radar rainfall data for watersheds in various agro-climatic regions of Texas. The CN method is an empirical method for calculating surface runoff which has been tested on various systems over a period of several years. Many of the findings of previous studies indicate the need to develop variations of this method to account for regional and seasonal changes in weather patterns and land cover that might affect runoff. This study seeks to address these issues, as well as the inherent spatial variability of rainfall, in order to develop a means of predicting runoff in near real-time for water resource management. In the past, raingauge networks have provided data for hydrologic models. However, these networks are generally unable to provide data in real-time or capture the spatial variability associated with rainfall. Radar networks, such as the Next Generation Weather Radar (NEXRAD) of the National Weather Service (NWS), which are widely available and continue to improve in quality and resolution, can accomplish these tasks. In general, a statistical comparison of the raingauge and NEXRAD data, where both were available, shows that the radar data is as representative of observed rainfall as raingauge data. In this study, watersheds of mostly homogenous land cover and naturalized flow were used as study areas. Findings indicate that the use of a dry antecedent moisture condition CN value and an initial abstraction (Ia) coefficient of 0.1 produced statistically significant results for eight out of the ten watersheds tested. The urban watershed used in this study produced more significant results with the use of the traditional 0.2 Ia coefficient. The predicted results before and during the growing season, in general, more closely agreed with the observed runoff than those after the growing season. The overall results can be further improved by altering the CN values to account for seasonal vegetation changes, conducting field verification of land cover condition, and using bias-corrected NEXRAD rainfall data.

In the first phase of this study, the diversity of methanogenic bacteria in avian ceca was found to be minimal. Based on 16S rDNA clone libraries, a common phylotype, designated CH101, ranged between 92.86 to 100 % of the total clones whereas less than 1% of the other phylotypes were found. On the basis of the sequence identity, all of the sequences, except sequence CH1270, are related from 98.97 to 99.45% to 16S rDNA Methanobrevibacter woesei GS. Sequence CH1270 is 97.62% homologous to the sequence identified to uncultured archaeon clone ConP1-11F. Clearly, the predominant methanogen found to reside in the chicken ceca was M. woesei. By using a MPN enumeration method, methanogen counts were found to be in the range of 6.38 to 8.23 log10 organisms per gram wet weight. The 16S rDNA copy number per gram wet weight in the samples was between log10 5.50 and 7.19. The second phase of the study was conducted to observe the effects of selected nitrocompounds and two different feedstuffs on in vitro methane production in chicken cecal contents and rumen fluid. Initially, one of the three nitrocompounds was added to incubations containing cecal contents from laying hens supplemented with either alfalfa or layer feed. Both feed materials influenced volatile fatty acids (VFA) production and also fostered methane production in the incubations although methane was lower (P < 0.05) in incubations with added nitrocompound, particularly nitroethane. Secondly, nitroethane was examined in incubations of bovine or ovine rumen fluid or cecal contents containing either alfalfa or layer feed. Unlike cecal contents, layer feed significantly (P < 0.05) supported in vitro methane production in incubations of both rumen fluids. The results show that nitroethane impedes methane production, especially in incubations of chicken cecal contents. The final phase of this study was carried out to determine the methanogenic establishment in the chicken ceca by the cultural method with the quantitative PCR. The results suggested that methanogens colonized in chicken ceca at a few days after birth. Litter and house flies could be potential sources for methanogenic colonization in broiler chicks.

No description available.

Player coordination is a key element in many multi-player real-time digital games and cooperative real-time multi-player modes are now common in many digital-game genres. Coordination is an important part of the design of these games for several reasons: coordination can change the game balance and the level of difficulty as different types and degrees of coordination can make the game easier or more difficult; coordination is an important part of ‘playing like a team’ which affects the quality of play; and coordination as a shared activity is a key to sociality that can add to the sociability of the game. Being able to exercise control over the design of these coordination requirements is an important part of developing successful games. However, it is currently difficult to understand, describe, analyze or design coordination requirements in game situations, because current frameworks and theories do not mesh with the realities of video game design. I developed a new framework (called PLATO) that can help game designers to understand, describe, design and manipulate coordination episodes. The framework deals with five atomic aspects of coordinated activity: Players, Locations, Actions, Time, and Objects. PLATO provides a vocabulary, methodology and diagram notation for describing and analyzing coordination. I demonstrate the framework’s utility by describing coordination situations from existing games, and by showing how PLATO can be used to understand and redesign coordination requirements.

Digital microprocessor based relays are currently being utilized for safe, reliable and efficient operation of power systems. The overcurrent protection relay is the most extensively used component to safeguard power systems from the detrimental effects of faults. Wrong settings in overcurrent relay parameters can lead to false tripping or even bypassing fault conditions which can lead to a catastrophe. Therefore it is important to validate the settings of power protection equipment and to confirm its performance when subject to different fault conditions. This paper presents the modeling of an overcurrent relay in SimPowerSystems (\textsc {matlab}/Simulink). The overcurrent relay has the features of instantaneous, time definite and inverse  definite minimum time (IDMT) characteristics. A power system is modeled in SimPowerSystems and this overcurrent relay model is incorporated in the test case. The overall model is then simulated in real-time using Opal-RT's eMEGAsim real-time simulator to analyze the relay's performance when subjected to faults and with different characteristic settings in the relay model. Finally Hardware-in-the-Loop validation of the model is done by using the overcurrent protection feature in Schweitzer Engineering Laboratories Relay SEL-487E. The event reports generated by the SEL relays during Hardware-in-the-Loop testing are compared with the results obtained from the standalone testing and software model to validate the model. / <p>QC 20130215</p>

Tracking of an object's full six degree-of-freedom (6-dof) position and orientation (pose) would allow a robotic system to autonomously perform a variety of complex tasks, such as docking from any preferred angle, surveillance of moving subjects, etc. Computer vision has been commonly advocated as an effective tool for 3D (i.e., 6-dof) tracking Objects of Interest (OIs). However, the vast majority of vision-based 6-dof pose trackers reported in the literature require a model of the OI to be provided a priori. Finding/selecting the OI to track is also essential to autonomous operation. A problem that has often been neglected. This Thesis proposes a novel, real-time object-tracking system that solves all of the aforementioned problems. The tracking procedure begins with OI selection. Since what constitutes an OI is application dependent, selection is achieved via a customizable framework of Interest Filters (IFs) that highlight regions of interest within an image. The region of greatest interest becomes the selected OI. Next, an approximate visual 3D model of the selected OI is built on-line by a real-time modeller. Unlike previously proposed techniques, this modeller can build the model of the OI even in the presence of background clutter; an essential task for tracking one object amongst many. Once a model is built, a real-time 6-dof tracker (i.e., the third sub-component) performs the actual 6-dof object tracking via 3D model projection and optical flow. Performing simultaneous modelling and tracking presents several challenges requiring novel solutions. For example, a novel data-reduction scheme based on colour-gradient redundancy is proposed herein that facilitates using colour input images whilst still maintaining real-time performance on current computer hardware. Likewise, a per-pixel occlusion-rejection scheme is proposed which enables tracking in the presence of partial occlusions. Various other techniques have also been developed within the framework of this Thesis in order to achieve real-time efficiency, robustness to lighting variations, ability to cope with high OI speeds, etc. Extensive experiments with both synthetic and real-world motion sequences have demonstrated the ability of the proposed object-tracking system to track a priori unknown objects. The proposed algorithm has also been tested within two target applications: autonomous convoying, and dynamic camera reconfiguration.

Tracking of an object's full six degree-of-freedom (6-dof) position and orientation (pose) would allow a robotic system to autonomously perform a variety of complex tasks, such as docking from any preferred angle, surveillance of moving subjects, etc. Computer vision has been commonly advocated as an effective tool for 3D (i.e., 6-dof) tracking Objects of Interest (OIs). However, the vast majority of vision-based 6-dof pose trackers reported in the literature require a model of the OI to be provided a priori. Finding/selecting the OI to track is also essential to autonomous operation. A problem that has often been neglected. This Thesis proposes a novel, real-time object-tracking system that solves all of the aforementioned problems. The tracking procedure begins with OI selection. Since what constitutes an OI is application dependent, selection is achieved via a customizable framework of Interest Filters (IFs) that highlight regions of interest within an image. The region of greatest interest becomes the selected OI. Next, an approximate visual 3D model of the selected OI is built on-line by a real-time modeller. Unlike previously proposed techniques, this modeller can build the model of the OI even in the presence of background clutter; an essential task for tracking one object amongst many. Once a model is built, a real-time 6-dof tracker (i.e., the third sub-component) performs the actual 6-dof object tracking via 3D model projection and optical flow. Performing simultaneous modelling and tracking presents several challenges requiring novel solutions. For example, a novel data-reduction scheme based on colour-gradient redundancy is proposed herein that facilitates using colour input images whilst still maintaining real-time performance on current computer hardware. Likewise, a per-pixel occlusion-rejection scheme is proposed which enables tracking in the presence of partial occlusions. Various other techniques have also been developed within the framework of this Thesis in order to achieve real-time efficiency, robustness to lighting variations, ability to cope with high OI speeds, etc. Extensive experiments with both synthetic and real-world motion sequences have demonstrated the ability of the proposed object-tracking system to track a priori unknown objects. The proposed algorithm has also been tested within two target applications: autonomous convoying, and dynamic camera reconfiguration.

No description available.