Advanced wastewater treatment plants must meet permit requirements for organics, solids, nutrients and indicator bacteria, while striving to do so in a cost effective manner. This requires meeting day-to-day fluctuations in climate, influent flows and pollutant loads as well as equipment availability with appropriate and effective process control measures. A study was carried out to assess performance and process control strategies at the Falkenburg Road Advanced Wastewater Treatment Plant in Hillsborough County, Florida. Three main areas for control of the wastewater treatment process are aeration, return and waste sludge flows, and addition of chemicals. The Falkenburg AWWTP uses oxidation ditches where both nitrification and denitrification take place simultaneously in a low dissolved oxygen, extended aeration environment. Anaerobic selectors before the oxidation ditches help control the growth of filamentous organisms and may also initiate biological phosphorus removal. The addition of aluminum sulfate for chemical phosphorus removal ensures phosphorus permit limits are met. Wasting is conducted by maintaining a desired mixed liquor suspended solids (MLSS) concentration in the oxidation ditches. For this study, activated sludge modeling was used to construct and calibrate a model of the plant. This required historical data to be collected and compiled, and supplemental sampling to be carried out. Kinetic parameters were adjusted in the model to achieve simultaneous nitrification-denitrification. A sensitivity analysis found maximum specific growth rates of nitrifying organisms and several half saturation constants to be influential to the model. Simulations were run with the calibrated model to observe relationships between sludge age, MLSS concentrations, influent loading, and effluent nitrogen concentrations. Although the case-study treatment plant is meeting discharge permit limits, there are several recommendations for improving operation performance and efficiency. Controlling wasting based on a target MLSS concentration causes wide swings in the sludge age of the system. Mixed liquor suspended solids concentration is a response variable to changes in sludge age and influent substrate. Chemical addition for phosphorus removal should also be optimized for cost savings. Finally, automation of aeration control using online analyzers will tighten control and reduce energy usage.

Obtaining a very high level of precision and sophistication in automated computer control is now available inexpensively from a variety of hardware and software sources. Applying this automated technology to an astronomical telescope broadens the scope of applications of the instrument, particularly in areas such as photo electrics, CCD imaging and remote control. The ultimate design goal of the UWS telescope was that of full roboticism, giving access of the facility to off campus clients both in Australia and overseas. The first phase towards full robotic control is automation of the required optical and mechanical parameters, providing precision targeting and object tracking. This thesis describes the mechanical aspects of the UWS telescope and the procedures and equipment involved in its automation, including the drive system, electro mechanical design and associated computer hardware and software. Sample performance test data shows that using a high percentage of inexpensive proprietary robotics components, a very sophisticated and accurate measuring device can be produced. / Master of Science (Hons.)

This thesis addresses research towards the development of an intelligent design for assembly evaluation system (IDFAES) based on the design for assembly (DFA) principels. The research project aimed to enhance the capability of existing DFA methodologies in order to support activities such as redesign, design modification and assembly planning during the product development cycle.

Co-rotating twin-screw extruders are unique and versatile machines that are used widely in the plastics and food processing industries. Due to the large number of operating variables and design parameters available for manipulation and the complex interactions between them, it cannot be claimed that these extruders are currently being optimally utilised. The most significant improvement to the field of twin-screw extrusion would be through the provision of a generally applicable dynamic process model that is both computationally inexpensive and accurate. This would enable product design, process optimisation and process controller design to be performed cheaply and more thoroughly on a computer than can currently be achieved through experimental trials. This thesis is divided into three parts: dynamic modelling, measurement and control. The first part outlines the development of a dynamic model of the extrusion process which satisfies the above mentioned criteria. The dynamic model predicts quasi-3D spatial profiles of the degree of fill, pressure, temperature, specific mechanical energy input and concentrations of inert and reacting species in the extruder. The individual material transport models which constitute the dynamic model are examined closely for their accuracy and computational efficiency by comparing candidate models amongst themselves and against full 3D finite volume flow models. Several new modelling approaches are proposed in the course of this investigation. The dynamic model achieves a high degree of simplicity and flexibility by assuming a slight compressibility in the process material, allowing the pressure to be calculated directly from the degree of over-fill in each model element using an equation of state. Comparison of the model predictions with dynamic temperature, pressure and residence time distribution data from an extrusion cooking process indicates a good predictive capability. The model can perform dynamic step-change calculations for typical screw configurations in approximately 30 seconds on a 600 MHz Pentium 3 personal computer. The second part of this thesis relates to the measurement of product quality attributes of extruded materials. A digital image processing technique for measuring the bubble size distribution in extruded foams from cross sectional images is presented. It is recognised that this is an important product quality attribute, though difficult to measure accurately with existing techniques. The present technique is demonstrated on several different products. A simulation study of the formation mechanism of polymer foams is also performed. The measurement of product quality attributes such as bulk density and hardness in a manner suitable for automatic control is also addressed. This is achieved through the development of an acoustic sensor for inferring product attributes using the sounds emanating from the product as it leaves the extruder. This method is found to have good prediction ability on unseen data. The third and final part of this thesis relates to the automatic control of product quality attributes using multivariable model predictive controllers based on both direct and indirect control strategies. In the given case study, indirect control strategies, which seek to regulate the product quality attributes through the control of secondary process indicators such as temperature and pressure, are found to cause greater deviations in product quality than taking no corrective control action at all. Conversely, direct control strategies are shown to give tight control over the product quality attributes, provided that appropriate product quality sensors or inferential estimation techniques are available.

<p>Metal wire deposition by means of robotized laser welding offers great saving potentials, i.e. reduced costs and reduced lead times, in many different applications, such as fabrication of complex components, repair or modification of high-value components, rapid prototyping and low volume production, especially if the process can be automated. Metal deposition is a layered manufacturing technique that builds metal structures by melting metal wire into beads which are deposited side by side and layer upon layer. This thesis presents a system for on-line monitoring and control of robotized laser metal wire deposition (RLMwD). The task is to ensure a stable deposition process with correct geometrical profile of the resulting geometry and sound metallurgical properties. Issues regarding sensor calibration, system identification and control design are discussed. The suggested controller maintains a constant bead height and width throughout the deposition process. It is evaluated through real experiments, however, limited to straight line deposition experiments. Solutions towards a more general controller, i.e. one that can handle different deposition paths, are suggested.</p><p>A method is also proposed on how an operator can use different sensor information for process understanding, process development and for manual on-line control. The strategies are evaluated through different deposition tasks and considered materials are tool steel and Ti-6Al-4V. The developed monitoring system enables an operator to control the process at a safe distance from the hazardous laser beam.</p><p>The results obtained in this work indicate promising steps towards full automation of the RLMwD process, i.e. without human intervention and for arbitrary deposition paths.</p> / RMS

by J. Kimemia, S.B. Gershwin. / Bibliography: leaf 6. / Caption title. / Supported by the National Science Foundation under Grant APR76-12036 National Science Foundation Grant DAR 78-17826

Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 130-135).

The use of solar cells for energy production has indeed a bright future. Reduction of cost for fabrication along with increased efficiency are key features for a market boom, both achieved as a result of increased knowledge of the technology. Especially the thin film solar cell technology with absorbers made of Cu(In,Ga)Se2 (CIGS) is promising since it has proven high power conversion efficiency in combination with a true potential for low cost fabrication. In this thesis different recipes for fabrication of the Cu(In,Ga)Se2 absorber layer have been studied. The deposition technique used has been co-evaporation from elemental sources. For all depositions the substrate has been heated to a constant temperature of 500 ºC in order for the growing absorber to form a chalcopyrite phase, necessary for the photovoltaic functionality. The selenium has been evaporated such to always be in excess during depositions whereas the metal ratio Cu/(In+Ga) has been varied according to different recipes but always to be less than one at the end of the process. In the work emphasis has been on the radiative properties of the CIGS film during growth. The substrate heater has been temperature controlled to maintain the constant set temperature of the substrate, regardless of varying emitted power caused by changing surface emissivity. Depending on the growth conditions the emissivity of the growing film is changing, leading to a readable variation in the electrical power to the substrate heater. Since the thermal radiation from the substrate during growth has been of central focus, this has been studied in detail. For this reason the substrate has been treated as an optical stack composed of glass/Mo/Cu(In,Ga)Se2/CuxSe which determine the thermally radiated power by its emissivity. An optical model has been adopted to simulate the emissivity of the stack. In order to use the model, the optical constants for Cu(In,Ga)Se2 and CuxSe have been derived for the wavelength interval 2 μm to 20 μm. The simulation of the emissivity of the stack during CIGS growth agreed well with what has been seen for actual growth. Features of the OP-signal could hereby be explained as a result of film thickness of Cu(In,Ga)Se2 and CuxSe respectively. This is an important knowledge for an efficient fabrication in large scale.

Metal wire deposition by means of robotized laser welding offers great saving potentials, i.e. reduced costs and reduced lead times, in many different applications, such as fabrication of complex components, repair or modification of high-value components, rapid prototyping and low volume production, especially if the process can be automated. Metal deposition is a layered manufacturing technique that builds metal structures by melting metal wire into beads which are deposited side by side and layer upon layer. This thesis presents a system for on-line monitoring and control of robotized laser metal wire deposition (RLMwD). The task is to ensure a stable deposition process with correct geometrical profile of the resulting geometry and sound metallurgical properties. Issues regarding sensor calibration, system identification and control design are discussed. The suggested controller maintains a constant bead height and width throughout the deposition process. It is evaluated through real experiments, however, limited to straight line deposition experiments. Solutions towards a more general controller, i.e. one that can handle different deposition paths, are suggested. A method is also proposed on how an operator can use different sensor information for process understanding, process development and for manual on-line control. The strategies are evaluated through different deposition tasks and considered materials are tool steel and Ti-6Al-4V. The developed monitoring system enables an operator to control the process at a safe distance from the hazardous laser beam. The results obtained in this work indicate promising steps towards full automation of the RLMwD process, i.e. without human intervention and for arbitrary deposition paths. / RMS

This research work focuses at first on the intelligent model development for process state (special for fault) detection, behavior prediction and process control for complex industrial processes. In the model architecture, Fuzzy Neural Networks (FNNs) are employed as process state classifiers for process state (fault) detection; other (different) Neural Networks (NNs) models are applied for system identification of process characteristics in different process states. The model detects process states (faults) and predicts process behavior according to process input and historical behaviors, whose combination of influences generates the final results of process state (fault) detection and quantitative prediction. The whole model is constructed based on Fuzzy TS NARX models. Secondly, an optimal model is designed to two purposes, one is for optimal process diagnosis and another is for optimal prediction. To time varying processes, an adaptive strategy and algorithm, applying the Least Squares algorithm, has been developed for model adaptability to cover time depending process changes. Thirdly, a specific state space equation of discrete time varying system is being derived from the model. In the state space equation, the state transition matrix A is determined by the fuzzy degree of process state classification produced by process historical behavior in time t instant, and the input transition matrix B by process real input in time t instant. The state observer vector H is determined by optimization results generated by model adaptive or optimal scheme. Finally, to confirm the validity of the theoretical results from above, an application case has been studied for supply forecasting. The study and application results indicate that the model not only has good performance for fault detection, but also provides excellent quantitative prediction of process output. It can be applied in process state (fault) detection, diagnosis and prediction for process behavior, as well as fault predictive control.