Thesis (Ph. D.)--University of Sydney, 1996. / Title from title screen (viewed on February 3, 2009) Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the Dept. of Chemical Engineering. Degree awarded 1996, thesis submitted 1995. Includes bibliographical references. Also issued in print.

A dissertation submitted in fulfilment of the requirement for the degree of Master of Science in Engineering, to the Faculty of Engineering and the Built Environment, School of Chemical and Metallurgical Engineering, University of the Witwatersrand, Johannesburg, 2018 / The two hydrofluoric acid (HF) storage tanks used for holding 70% technical grade HF product at the HF plant at Necsa started leaking in March 2012. An evaluation of the failure was conducted in the form of a corrosion failure analysis. It was confirmed that a higher than usual nitric acid (HNO3) content in the technical grade HF stream changed the corrosion mechanisms typically experienced within the HF storage vessels, which then caused the tanks to fail. Immersion type corrosion experiments were done to safely simulate the corrosive environment experienced by the mild steel, stainless steel and nickel alloys used on site, and to predict the change in corrosion rates and characteristics associated with the HNO3 contamination in the HF production plant circuit. Since the corrosion resistance of mild steel in HF is heavily dependent on the thickness of the protective scale on the steel, a series of planned interval corrosion tests (PICTs) was done to reproduce and then examine the oxidefluoride barrier on mild steel coupons in pure 70% HF prior to corrosion tests. These shorter PICTs were also done on the stainless steel and nickel alloys and showed that the prepassivation step had a surface cleaning effect when exposed for only 24 h. Eleven day corrosion tests were conducted to establish the effect of HNO3 concentration and temperature on mild steel corrosion in 70% HF, and to determine the change in corrosion rates and mechanisms associated with HNO3 contamination (0.1-1% HNO3) of the downstream HF products. The corrosion was characterized by analysing the corroded coupons for mass loss, apparent corrosion rates, acid consumptions, visual observations of scale formation and pits, as well as depth profiles from scanning electron microscopy and energy dispersive spectroscopy analyses. Linear relationships were frequently observed when analysing mass losses for the coupons over time, making it possible to define corrosion rates in terms of first order reaction kinetics. The harshest corrosive condition for mild steel in HF was determined to be 1% HNO3 in 70% HF at a constant temperature of 25ºC. The corrosion characteristics of alloys used in the HF plant, as affected by HNO3 impurities (in the range 50–10000 ppm) in the final HF acid product (70% Technical grade) were successfully established. Normalized SA516 Grade 70 mild steel and Monel 400 were found not adequate for use as construction materials in a plant where HNO3 contamination was >100 ppm. However, the corrosion resistance of SS 904 L was suitable under these conditions and was recommended for applications in HF solutions where the presence of an oxygen-containing acid (e.g. HNO3) is consistent. It was recommended that Alloy 31, Alloy 33 or Nirosta 4565S, with higher chromium content (>20 wt% Cr), should be considered for construction material of the HF plant when HNO3 contamination becomes unavoidable. However, if the continued use of mild steel at the plant cannot be avoided, other inhibition strategies tailored to the selective consumption of HNO3 in the HF product stream need to be investigated. / XL2019

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This study investigated whether risk compensation behavior would occur during a chemistry experiment due to the presence of protective equipment. This study also examined whether a homeostatic regulating mechanism exists for risk-taking behavior. Risk compensation and a homeostatic regulating mechanism for risk-taking behavior are both encompassed within the Risk Homeostasis Theory, which states that people accurately perceive and fully compensate for changes in risk. Thirty-six subjects performed three trials of a short chemistry experiment either with protective equipment or without protective equipment during the first of two sessions. After the first session, half the subjects were required to switch from wearing protective equipment to not wearing protective equipment, or from not wearing protective equipment to wearing protective equipment. The time required to complete the task, the number of errors committed, and subtask measurement accuracy were tabulated. Between-subject analyses did not reveal risk compensation behavior. Moreover, within-subject comparisons failed to show a significant risk compensation effect or the presence of a homeostatic regulating mechanism for risk-taking behavior. The results suggested that the Risk Homeostasis Theory may not explain sufficiently changes in behavior due to increases (or decreases) in perceived risk. The limitations of the present study were discussed. Suggestions and examples for research on different aspects of the Risk Homeostasis Theory were also provided. / Master of Science

Model predictive control has become a standard for most control strategies in modern process plants. It relies heavily on process models, which might not always be fundamentally available, but can be obtained from time series analysis. The first step in any control strategy is to identify or detect changes in the system, if present. The detection of such changes, known as dynamic changes, is the main objective of this study. In the literature a wide range of change detection methods has been developed and documented. Most of these methods assume some prior knowledge of the system, which is not the case in this study. Furthermore a large number of change detection methods based on process history data assume a linear relationship between process variables with some stochastic influence from the environment. These methods are well developed, but fail when applied to nonlinear dynamic systems, which is focused on in this study. A large number of the methods designed for nonlinear systems make use of statistics defined in phase space, which led to the method proposed in this study. The correlation dimension is an invariant measure defined in phase space that is sensitive to dynamic change in the system. The proposed method uses the correlation dimension as test statistic with and moving window approach to detect dynamic changes in nonlinear systems. The proposed method together with two dynamic change detection methods with different approaches was applied to simulated time series data. The first method considered was a change-point algorithm that is based on singular spectrum analysis. The second method applied to the data was mutual cross prediction, which utilises the prediction error from a multilayer perceptron network. After the proposed method was applied to the data the three methods’ performance were evaluated. Time series data were obtained from simulating three systems with mathematical equations and observing one real process, the electrochemical noise produced by a corroding system. The three simulated systems considered in this study are the Belousov-Zhabotinsky reaction, an autocatalytic process and a predatory-prey model. The time series obtained from observing a single variable was considered as the only information available from the systems. Before the change detection methods were applied to the time series data the phase spaces of the systems were reconstructed with time delay embedding. All three the methods were able to do identify the change in dynamics of the time series data. The change-point detection algorithm did however produce a haphazard behaviour of its detection statistic, which led to multiple false alarms being encountered. This behaviour was probably due to the distribution of the time series data not being normal. The haphazard behaviour reduces the ability of the method to detect changes, which is aggravated by the presence of chaos and instrumental or measurement noise. Mutual cross prediction is a very successful method of detecting dynamic changes and is quite robust against measurement noise. It did however require the training of a multilayer perceptron network and additional calculations that were time consuming. The proposed algorithm using the correlation dimension as test statistic with a moving window approach is very useful in detecting dynamic changes. It produced the best results on the systems considered in this study with quick and reliable detection of dynamic changes, even in then presence of some instrumental noise. The proposed method with the correlation dimension as test statistic was the only method applied to the real time series data. Here the method was successful in distinguishing between two different corrosion phenomena. The proposed method with the correlation dimension as test statistic appears to be a promising approach to the detection of dynamic change in nonlinear systems.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1970. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (M.Eng.(Control Engineering))--University of Pretoria, 2008. / Summary in English. Includes bibliographical references.

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Made available in DSpace on 2014-10-09T12:52:33Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:02:23Z (GMT). No. of bitstreams: 0 / Os acidentes causados pelo efeito dominó são dos mais graves ocorridos na indústria química e de processo. Mesmo sendo o potencial destrutivo desses eventos acidentais bastante conhecido, pouca atenção tem sido dada a este problema pela literatura técnica e uma metodologia completa e aprovada para a avaliação quantitativa da contribuição do efeito dominó ao risco industrial ainda não está plenamente desenvolvida. O presente estudo propõe um procedimento sistemático para a avaliação quantitativa do efeito dominó em plantas químicas do ciclo do combustível nuclear. O trabalho é baseado em avanços recentes feitos na modelagem de danos a equipamentos de processo causados por incêndios e explosões devido aos vetores de propagação (radiação de calor, sobrepressão e projeção de fragmentos). Dados disponíveis na literatura técnica e novos modelos de vulnerabilidade deduzidos para diversas categorias de equipamentos de processo foram utilizados no presente trabalho. O procedimento proposto é aplicado a uma área de tancagem típica de uma planta de reconversão situada em um sítio que abriga varias outras instalações do ciclo do combustível nuclear. São analisados os vários eventos iniciadores, seus vetores de propagação, as conseqüências desses eventos e as freqüências associadas ao efeito dominó. / Dissertação (Mestrado) / IPEN/D / Instituto de Pesquisas Energeticas e Nucleares - IPEN/CNEN-SP