Steady state, inter row measurements in multistage axial compressors are relevant to the current design process. The objective in obtaining such data is for evaluation of compressor blading as well as validation for the computer programmes used in compressor design. Multi-hole pressure probes are a reliable and economical method of collecting detailed flowfield data in compressors for these purposes. These probes are calibrated in a uniform flow in a wind tunnel prior to use, to determine their response to a range of flow angles and speeds. When the probe is subsequently used for measurements in the compressor, often the small inter row spacing means that the probe has to be close to the downstream stator passage and upstream rotor. The result is that the probe is no longer situated in the uniform flow in which it was calibrated, in terms of influences from both the upstream rotor and downstream stator. This project presents the investigation of these two effects on steady state pressure probe measurements. The effects of blockage on a probe positioned in front of a stator row in a high speed compressor were studied using CFD. This was also carried out on a large scale probe in a low speed compressor. It was found that the blockage effect caused a reduced mass flow in the downstream stator passage which in turn lead to an altered flow angle and a small reduction in measured total pressure. Experimental in rig calibrations showed that the change in flow angle was due to an angular offset of the pressure distribution about the probe. These calibrations also showed that the wind tunnel calibration was valid in the compressor within a small angular range. The influence of the upstream rotor passing was studied using an unsteady CFD model. Responses of the individual probe ports and the deduced flow angle and total pressure indicated that the steady state blockage effect is present throughout the wake passing. The wake passing was found to be a largely two dimensional effect in that the radial flow component changes in the low speed compressor wakes had little influence. The Total Technology thesis incorporates a management project on the relevant topic of project selection within companies. An existing project selection model was applied to a sample group of projects to determine the applicability of such models. The main findings were that these models can generate useful information for further selection decisions and that the applicability is towards lower budget projects where a structured approach is often not used.

Abstract This study was aimed at introducing multistage filtration (MSF) (a combination of slow-sand filtration (SSF) and pretreatment system - horizontal flow roughing filter (HRF)) as an alternative water treatment technology to the conventional one. A pilot- plant study was undertaken to achieve this goal. Evaluating the MSF performance vs. the existing conventional system in removing selected physical and chemical drinking water quality parameters together with the biological water quality improvement by the MSF without chemical use was done. Evaluation of the effectiveness of the MSF system utilizing locally available material, i.e. gravel, improved agricultural waste (charcoal maize cobs) and broken burnt bricks as pretreatment filter material was also done The benchmark was the Kenya Bureau of Standards (KEBS) values for the selected parameters. Results showed that with proper design specifications, MSF systems perform better than conventional systems under similar conditions of raw water quality and environmental conditions. The tested locally available materials can also be effectively used as pretreatment media with each allowing a filter run greater than 82 d and therefore could serve as alternatives where natural gravel is not readily available. With special reference to the bacteriological quality improvement, the MSF greatly improved the bacteriological quality of the water recording removal efficiencies of over 99% and 98% respectively for E. coli and total coliforms. Despite the observed performance, MSF should be complemented with chlorination as a final buffer against water-borne diseases. However, in this case, the dosing will be greatly reduced when compared to the conventional system.

A simulation study was carried out to assess the effects of using different testing frameworks and different statistical estimators in constructing a vertical scale. The adaptive multistage testing framework (MST) was comprised of five test forms which were administered across three testing occasions. The single form testing framework (SFT) was comprised of one form at each of the three testing occasions. Maximum likelihood estimation (MLE) and Bayesian Expected a-posteriori (EAP) estimators were used to estimate each simulee's ability at three "testing'' occasions. Item response theory (IRT) true scores, or domain scores, were used as the score scale. This was done to facilitate the use of growth scores between testing occasions. It was hypothesized that testing framework and estimation procedures would influence the recovery of the known domain score for each simulee across the three testing occasions and growth values between testing occasions. Average absolute deviation (AAD) values indicated that the MST framework offered a slight reduction in error when compared to the SFT framework in estimating IRT domain scores. The pattern of errors in estimation indicated that the MST framework provided more accurate estimates across the range of ability. The MST framework also offered a slight reduction in error when estimating IRT growth scores. Horizontal distances between test administrations indicted that EAP estimation produced uneven departures from known horizontal distances, but MLE did not. This was true for both the SFT and MST framework. Also, when the distributions of IRT domain scores were considered, the MLE estimation method was more consistent with the distribution of known domain scores.Overall, the MST framework performed better than did the SFT framework with respect to reduced estimation error and approximating the known IRT domain score.

This thesis describes the design and implementation of an integrated circuit and associated packaging to be used as the building block for the data routing network of a large scale shared memory multiprocessor system. A general purpose multiprocessor depends on high-bandwidth, low-latency communications between computing elements. This thesis describes the design and construction of RN1, a novel self-routing, enhanced crossbar switch as a CMOS VLSI chip. This chip provides the basic building block for a scalable pipelined routing network with byte-wide data channels. A series of RN1 chips can be cascaded with no additional internal network components to form a multistage fault-tolerant routing switch. The chip is designed to operate at clock frequencies up to 100Mhz using Hewlett-Packard's HP34 $1.2\\mu$ process. This aggressive performance goal demands that special attention be paid to optimization of the logic architecture and circuit design.

The multistage testing (MST) has drawn increasing attention as a balanced format of adaptive testing that takes advantages of both fully-adaptive computerized adaptive testing (CAT) and paper-and-pencil (P\&P) tests. Most previous studies on MST have focused on purely dichotomous or polytomous item formats although the mixture of two item types (i.e., mixed-format) provides desirable psychometric properties by combining the strength of both item types. Given the dearth of studies investigating the characteristics of mixed-format MST, the current study conducted a simulation to identify important design factors impacting the measurement precision of mixed-format MST. The study considered several factors-namely, total points (40 and 60), MST structures (1-2-2 and 1-3-3), the proportion of polytomous items (10%, 30%, 50% and 70%), and the routing module design (purely dichotomous and a mixture of dichotomous and polytomous items) resulting in 32 total conditions. A total of 100 replications were performed, and 1,000 normally distributed examinees were generated in each replication. The performance of MST was evaluated in terms of the precision of ability estimation across the wide range of the scale. The study found that the longer test produced greater measurement precision while the 1-3-3 structure performed better than 1-2-2 structure. In addition, a larger proportion of polytomous items resulted in lower measurement precision through the reduced test information during the test construction. The interaction between the large proportion of polytomous items and the purely dichotomous routing module design was identified. Overall, the two factors of test length and the MST structure impacted the ability estimation, whereas the impact of the proportion of polytomous items and routing module design mirrored the item pool characteristic. / text

This study experimentally quantified the structure-property relations with respect to fatigue of an extruded AZ61 magnesium alloy and captured the behavior with a microstructure-sensitive MultiStage Fatigue Model. Experiments were conducted in the extruded and transverse directions under low and high cycle strain control fatigue conditions. The cyclic behavior of this alloy displayed varying degrees of cyclic hardening depending on the strain amplitude and the specimen orientation. The fracture surfaces of the fatigued specimens were analyzed using a scanning electron microscope in order to quantify structure-property relations with respect to microstructural features. Correlations between particle size, nearest neighbor distance, and grain size as a function of failure cycles were quantified. Finally, a multistage fatigue model based on the structure-property relations quantified in this study was employed to capture the anisotropic fatigue damage of the AZ61 magnesium alloy.

Recently, pattern recognition/classification has received a considerable attention in diverse engineering fields such as biomedical imaging, speaker identification, fingerprint recognition, etc. In most of these applications, it is desirable to maintain the classification accuracy in the presence of corrupted and/or incomplete data. The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distortion. Some classification techniques that are introduced in the literature are described in Chapter one. In this dissertation, a pattern recognition approach that can be designed to have evolutionary learning by developing the features and selecting the criteria that are best suited for the recognition problem under consideration is proposed. Chapter two presents some of the features used in developing the set of criteria employed by the system to recognize different types of signals. It also presents some of the preprocessing techniques used by the system. The system operates in two modes, namely, the learning (training) mode, and the running mode. In the learning mode, the original and preprocessed signals are projected into different transform domains. The technique automatically tests many criteria over the range of parameters for each criterion. A large number of criteria are developed from the features extracted from these domains. The optimum set of criteria, satisfying specific conditions, is selected. This set of criteria is employed by the system to recognize the original or noisy signals in the running mode. The modes of operation and the classification structures employed by the system are described in details in Chapter three. The proposed pattern recognition system is capable of recognizing an enormously large number of patterns by virtue of the fact that it analyzes the signal in different domains and explores the distinguishing characteristics in each of these domains. In other words, this approach uses available information and extracts more characteristics from the signals, for classification purposes, by projecting the signal in different domains. Some experimental results are given in Chapter four showing the effect of using mathematical transforms in conjunction with preprocessing techniques on the classification accuracy. A comparison between some of the classification approaches, in terms of classification rate in case of distortion, is also given. A sample of experimental implementations is presented in chapter 5 and chapter 6 to illustrate the performance of the proposed pattern recognition system. Preliminary results given confirm the superior performance of the proposed technique relative to the single transform neural network and multi-input neural network approaches for image classification in the presence of additive noise.

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Multistage tests (MSTs) have received renewed interest in recent years as an effective compromise between fixed-length linear tests and computerized adaptive test. Most MSTs studies scored the assessments based on item response theory (IRT) methods. Many assessments are currently being developed as mixed-format assessments that administer both standalone items and clusters of items associated with a common stimulus called testlets. By the nature of a testlet, a natural dependency occurs between the items within the testlet that violates the local independence of items. Local independence is a fundamental assumption of the IRT models. Using dichotomous IRT methods on a mixed-format testlet-based assessment knowingly violates local independence. By combining the score points within a testlet, researchers have successfully applied polytomous IRT models. However, the use of such models loses information by not using the unique response patterns provided by each item within a testlet. The three-parameter logistic testlet response theory (3PL-TRT) model is a measurement model developed to retain the uniqueness in response patterns of each item, while accounting for the local dependency exhibited by a testlet, or testlet effect. Because few studies have examined mixed-format MSTs administration under the 3PL-TRT model, the dissertation performed a simulation to investigate the administration of a mixed-format testlet based MSTs under the 3PL-TRT model. Simulee responses were generated based on the 3PL-TRT calibrated item parameters from a real large-scale passage based standardized assessment. The manipulated testing conditions considered four panel designs, two test lengths, three routing procedures, and three conditions of local item dependence. The study found functionally no bias across testing conditions. All conditions showed adequate measurement properties, but a few differences did occur between some of the testing conditions. The measurement precision was impacted by panel design, test length and the magnitude of local item dependence. The three-stage MSTs consistently illustrated slightly lower measurement precision than the two-stage MSTs. As expected, the longer test length conditions had better measurement precision than the shorter test length conditions. Conditions with the largest magnitude of local item dependency showed the worst measurement precision. The routing procedure had little impact on the measurement effectiveness. / text

The main function of a pyroscrubber in petroleum coke calcining process is to oxidize the carbonaceous contents, including hydrocarbon volatiles, of the exhaust gas from the calcination kiln, so as to leave no more than small traces of unburned volatiles, solid carbon, ashes, or emissions (e.g. CO, NOx and SOx) in the flue gas finally discharged. To maximize the energy recovery and reduce pollutant emission from the pyroscrubber, 3-D computational models are developed using FLUENT to simulate the combustion and thermal-flow phenomena inside the pyroscrubber. The results show the 3-D behavior of the flow, the reaction inside the pyroscrubber, effect of different amounts of air injection with respect to combustion efficiency, energy output and NOx emission. A multistage burning strategy is introduced and studied and results show it successfully cuts emission without compromising energy output. A particle combustion model with the homogeneous gas combustion model is also developed and incorporated to investigate CO emission.