3. Electronic Theses and Dissertations (ETDs) - All submissions
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Item Natural gas to methanol process flowsheet improvement via integration of ITM oxygen technology(2024) Fankomo, PhumzileCurrent industrial gas-to-liquids (GTL) processes suffer high energy penalties and associated carbon emissions caused by inefficient energy utilization and recovery. With the increasing demand for methanol and stricter regulations requiring reduced carbon intensity, there is a need to improve efficiencies of the existing process. This study analysed the existing large-scale natural gas to methanol flow sheet and investigated development of a new and improved flow sheet. In a conventional natural gas to methanol process, the air compressors in the cryogenic air separation unit (ASU) as well as the syngas compressor in the methanol synthesis unit are the most energy intensive and contribute significantly to the energy cost of large-scale syngas manufacture. The conventional autothermal reformer (ATR) process contributes the largest exergy losses as a result of the large temperature driving force used in the syngas cooler. The novel ion transport membrane (ITM) oxygen technology has the potential to replace the cryogenic air separation and reduce the large power demands associated with oxygen production. Its high temperature operation makes it suitable for process integration with syngas production. Integration of this ITM oxygen technology into a natural gas to methanol flow sheet was investigated. The pinch analysis method was used to evaluate flow sheet minimum energy requirements and identify opportunities for process heat integration to reduce utility requirements. Exergy analysis was conducted to identify areas of large exergy destruction and opportunities for improvement and, to quantify and compare exergy losses of the flow sheet cases. Power cycles were integrated to efficiently recover and convert process heat to power. Performance of the power cycles was measured by the cycles’ thermal efficiencies. The overall plant and process efficiency as well as the specific iv gas efficiency were evaluated to assess and compare energy efficiency of the process flow sheet cases. Replacing the cryogenic ASU with ITM and integrating ITM oxygen into the ATR process is a more efficient method to recover the high temperature syngas heat with reduced exergy losses. The ITM oxygen unit integrated with power cycles resulted in 47% more power production compared to the conventional case A. The exergy analysis results showed a decrease in overall exergy losses by 26% in this new flow sheet. The ITM oxygen power cycle was found to produce enough power to drive its own compressors and with excess power of 28 MW, whereas the cryogenic ASU in the conventional case has a power demand of 33 MW. This work shows that lower cost production of oxygen may be the feasible solution to reduce the high costs of large-scale syngas manufacture. The ITM oxygen presents such opportunities by substituting the energy intensive cryogenic ASU and combining oxygen, syngas and power production into a single thermally integrated unit. The methanol loop was found to have sufficient process heat for combined heat and power production. The Rankine medium pressure (MP) steam cycle produced enough power to drive the syngas compressor. Configuring the methanol process into a power production cycle results in an increase in the flow sheet excess power production by 68% compared to the conventional case. However, reduced methanol production rate caused by lower flash pressures as well as reduced process heat for feed preheat are the main challenges to consider. The specific gas efficiency improved by 6% while carbon dioxide emissions decreased by 40%. The overall thermal efficiencies of the cases were not optimized as this was not part of the study objectives. A further study can be conducted to investigate improving the thermal efficiencies of the power cycles in each case by performing a sensitivity analysis to impact parameters such as turbine and compressor inlet temperature and v pressure ratio. The specific parameters to assess can be determined from the airstandard model equation for a Brayton power cycle. The thermal efficiency improvement can result in higher power production and reduced equipment duties which is a benefit to both capital and operating costs.Item Towards a robust, universal predictor of gas hydrate equilibria through the means of a deep learning regression(2019) Landgrebe, M. K. B.Gas hydrate equilibria of natural gas mixtures has proven to be a highly non-linear, multimodal phenomenon, and extensive investment has been made over decades in order to understand and accurately predict natural gas hydrate equilibrium conditions. While most models applied toward predicting gas hydrate equilibria industrially are computerised thermodynamic models based on intrinsic molecular behaviour, these approaches are often limited in their capability to predict actual phenomena over a wide range of conditions due to the high degrees of non-linearity and complexities resulting from other factors which prove difficult to model explicitly. In this research, an artificial neural network was developed using publicly available experimental gas hydrate equilibrium data. A regression was achieved by means of a deep-learning multi-layer perceptron consisting of three hidden layers with a high neuron count, and an output layer comprised of a single neuron, corresponding with the predicted equilibrium pressure. 9 model features are present in the input layer, consisting of the temperature and the molar fractions of methane, ethane, propane, iso-butane, n-butane, carbon dioxide, nitrogen and a lumped fraction of organic molecules consisting of at least five carbon atoms. Models have been evaluated according to the ability to predict a wide range of data, multicomponent prediction accuracy, and dependency on individual sources of data. 670 multicomponent experimental equilibrium data samples have been obtained from literature. Due to the limited amount of multicomponent equilibrium data published, the incorporation of pure and binary methane mixtures into a second dataset including multicomponent data has proven imperative to achieve the best possible model. The complete dataset consists of 1209 equilibrium data samples. To ensure multicomponent data is accurately modelled, several models have been developed using both datasets to prove that the pure and binary inclusive dataset models do not simply inflate results through inclusion of easily predicted data. Regression scoring was assessed using the coefficient of determination, the R2 score. Cross-validation and hold-out validation have been employed in conjunction to assess the model’s ability to predict unseen data, while facilitating parameter optimization and yielding the bias and variance associated with the model. Cross-validation has been implemented by means of 10-fold validation, with a randomized 70%-30% train-test split performed to determine the test indices for each fold. Hold-out validation has been achieved by means of a 10% stratified-split, whereby the proportion of data from each independent source is held approximately constant across training and hold-out validation sets with the purpose of ensuring a wide range of conditions are tested. A cross validation R2 score of 0.9860 is achieved with a standard deviation of 0.0035. Hold-out validation yields an R2 of 0.9926. Results indicate a sufficiently accurate model has been achieved with a low enough variance to consider the model universal over the range of equilibrium data included in this investigation. The dependency on individual experimental data sources is of concern due to the limited amount of multicomponent equilibrium data available, and the age of equilibrium measurement practices for many sources and time frames associated with hydrate equilibrium measurements. However, the inclusion of pure methane and methane binary compounds does assist in reducing the susceptibility of the model to these errors. Dependency on individual data sources has been assessed by means of grouped cross-validation being performed on neural network models. Grouping results do indicate a lack of independently obtained data covering certain ranges of conditions, however binary inclusive models are shown to present a damping effect on the magnitude of experimental or measurement error on the model at large. Due to a lack of independent experimental studies covering a wide range of conditions, hydrogen sulphide could not be included as a feature in model development. As such, the developed model is noted to be applicable to sweet natural gas flow systems, where hydrate structures I or II are exhibited.Item Enhancing linkages in oil and gas in Qatar(2018) Al-Showaikh, JenanQatar’s economy is mainly dependent on oil and gas, making it vulnerable to global economic shifts and in need of diversification. Qatar’s state has always depended on Western consultancies, which largely advance a neoliberal agenda and so do not consider the long-term needs of Qatar’s economy. While a small body of academic literature has criticized Qatar’s economic strategy, this research provides an alternative strategy for diversification, recommending building linkages directed towards industrialisation. The study takes into account the needs of Qatar’s economy, focusing on diversification carried out in a stable way that creates employment, as well as other factors. The study finds that Qatar’s local content policies lack transparency, clarity, and monitoring institutions, as well as penalties and incentives to enforce the rules. Thus, there has been limited progress in forming the backward linkages knowledge linkages that would enable Qatar’s economic diversification.Item Synthesis of dimethyl ether using natural gas as a feed via the C-H-O ternary diagram(2017) Masindi, AndisaniIn this research, the C, H and O bond equivalent diagram was used to design processes for DME synthesis using natural gas as a feed. This research proposes alternative ways of producing DME using natural gas (a cleaner gas) compared to the traditional routes. The different feed combinations were assessed for the production of syngas. The crucial step is the H2:CO ratio in each feed which determines the DME synthesis process route and yield. The syngas process was developed under equilibrium and non-equilibrium conditions (assuming 100% methane conversion). The region of operation on the ternary bond diagram was limited by mass and energy balance and carbon deposition boundaries. The feed composition was as follows, (1) Feed 1: methane, steam and oxygen (2) Feed 2: methane, oxygen and carbon dioxide (3) Feed 3: methane, oxygen, carbon dioxide and water. Feed (2) had the highest DME yield. The most optimal reaction route produced DME via the JFE reaction route (H2:CO =1). The yield of DME was 0.67 moles of DME per mole methane processed under non-equilibrium conditions. The proposed route does not emit CO2, excess CO2 is recycled back to the reforming reactor. Under equilibrium, the yield of DME was 0.25 mole DME per mole methane processed. The results indicate that a combination of partial oxidation and dry reforming produces a syngas composition which results in a high DME yield compared to (1) and (3).