Improving the temperature measurement in hydro-processing reactors

The world is going to replace renewable and green fuels with fossil fuels to reduce the environmental issues and global warming effects. Bio-based feedstock is a biological source to produce fuel and considered as an alternative that can supersede fossil-based resources in the future. Co-processing is a transition towards green fuel which through a mixture of fossil and bio-based feedstocks are processed. In co-processing, the biomass is blended with fossil-based feed and upgraded through hydro-treating in a catalytic reactor. Since biomass contains high amount of oxygen, the process is highly exothermic releasing heat and causing temperature rise inside the reactor. Hence, reactor temperature needs to be monitored properly to prevent serious accident and retain the required quality of the product. In petro-refineries, use of temperature measurement systems is a need and usually problematic in hydro-processing reactors. When introducing alternative or biomass feedstocks to the process, the problem will be more highlighted due to new reactants and different reactions. The following work has expounded the need for measuring temperature in exothermic reactions. Reactions and products, main hardware and equipment has been described to express the need for temperature monitoring systems. This thesis has considered different approaches and methods in measuring the temperature in reactors mentioning their advantages and disadvantages. Challenges stemmed from the new reactants and new reactions by introducing bio-based feedstocks were identified. The material selection is crucial as almost all available temperature measurement systems has direct contact with the reactants and catalyst. Some widely-used materials in oil and gas industry were compared to choose the proper one for the application. The possible solutions reducing the problematic issues were recommended for design, procurement and installation of the temperature measurement system

Modeling and Multi-objective Optimization of a Packed Bed Reactor for Sulfur Dioxide Removal by Magnesium Oxide Using Non-dominated Sorting Genetic Algorithm II

Nowadays, protecting the environment is of utmost importance worldwide, and sulfur dioxide is one of the main pollutants in the atmosphere. This work proposes a new method for simultaneous SO2 removal by MgO, and production of magnesium sulfate in a packed bed reactor for which breakthrough curves have been obtained. Furthermore, the effect of important operating parameters, including temperature, SO2 concentration, and gaseous flow rate was investigated. Experiments showed that increasing the temperature improved the breakthrough lifetime, but the increase in concentration and flow rate reduced the lifetime. The experimental results were predicted successfully by applying the Random Pore Model (RPM). Finally, the Non-dominated Sorting Genetic Algorithm II (NSGA II) that is a technique for multi-objective optimization, was employed to determine the best operating parameters for SO2 removal by magnesium oxide in the packed bed reactor. This work is licensed under a Creative Commons Attribution 4.0 International License

Market risk analysis of coal liquefaction

This study addresses the risks associated with coal liquefaction using a market risk simulation approach. The study can be divided into four phases: (i) identify the sources of risk, (ii) examine the relationships among different sources that cause the risk, (iii) estimate the risk level based on the sources of risk using statistical and financial method and (iv) provide conclusions and recommendations for risk analysis.;Market risk is considered the most important risk for commercial scale coal liquefaction projects and is one of the biggest obstacles to commercialization. This study analyses market risk and discusses methods to lower this type of risk. For a coal liquefaction project, the relationship between coal and oil prices has a critical influence on the project\u27s feasibility. This study also extends the relationship among different types of risks of coal liquefaction and provides guidelines for risk management.;In the risk assessment section, statistical and financial methods are applied to analyze the risk of a proposed coal liquefaction project in West Virginia. Granger Causality Tests are conducted to examine the relationship between coal and oil prices. Using the estimated standard errors, Monte Carlo simulations of NPV are performed to access the financial viability of the West Virginia coal liquefaction project. The results show that the project has a high probability of financial feasibility including a high expected net present value with an acceptable standard deviation. Conclusions and extended discussions are based on the simulation results

Hydrodynamics related performance evaluation of Upflow Moving Bed Hydrotreater reactor (MBR) using developed experimental methods and CFD simulation

Upflow Moving Bed Hydrotreater (MBR) reactor is used for hydrotreating resid crude oil. It is a two-phase upflow reactor having a catalyst bed with conical bottom, and plena. At industrial conditions the reactor is not performing at its best and encountering issues such as hot spots, catalyst agglomeration inside the catalyst bed leading to frequent shutdown of the reactor. The root cause of these problems are linked to the improper hydrodynamics inside the catalyst bed. To investigate this, the industrial scale MBR is scaled down to a pilot scale and indicative and key hydrodynamic parameters are investigated using developed experimental methods and CFD simulation. The local hydrodynamics is quantified using an experimental technique called two-tip optical probe (TTOP). Developed algorithms for TTOP to derive the local phase saturations, velocities, backmixing, maldistribution using the time series data of the probe. The results indicates high maldistribution zones inside the catalyst bed and found convincing evidence to link this to the conical design and plena of MBR. Overall Gas and Liquid dispersion/Mixing in the catalyst bed is investigated by tracer studies using a developed methodology based on residence time distribution (RTD), Convolution, Regression, and Catalyst Bed Models based on axial dispersion and wave model. Good gas/liquid dispersion is seen at the industrial scaled down operating condition. A CFD model is developed for the lower plenum of MBR and validated with gamma ray densitometry (GRD) for radial profile of line average phase volume fraction. The simulation indicates that the current design of lower plenum is enabling a dominant movement of phases only in the central region outlets of this plenum. A modification of the current design proves to perform better in terms of movement of phases along entire outlets of the lower plenum --Abstract, page iv

Investigation of the Activity of Composite Catalyst Beds for Hydrotreatment of a Coal-Derived Liquid

Chemical Engineerin