Strategies For Process Systems Mapping And Control Based On Operability Analysis, Victor Manuel Cunha Alves

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation aims to develop strategies for process systems engineering (PSE) mapping using models, emerging tools and algorithms motivated by process operability analysis research. Such strategies will be employed to ensure simultaneous design and control of large-scale industrial systems. The emerging tools and techniques in this research include supervised machine learning-based (ML-based) operability mapping, automatic differentiation (AD) for implicit mapping, and the development of a systematic mapping approach for control structure selection using operability analysis. Thus far, the developed operability algorithms either recur to nonlinear programming (NLP) solutions which are computationally expensive or to linearizing the underlying modeling task at …

Characterization And Evaluation Of Various Biochar Types As Green Adsorbents For Rare Earth Element Recovery From Aqueous Solutions, Oluwaseun Victor Famobuwa

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rare earth elements (REEs) are members of the lanthanide family (atomic number 57 – 71). They are significantly important to the global economy due to their applications in renewable energy, defense, and medical industries. REEs are primarily derived from bastnaesite and monazite but may also be present in xenotime, cerite, alanite, and many other types of mineralization in lesser amounts. Due to the increasing demand for REEs and their criticality in the supply chain, the need to explore secondary sources of REEs has gained tremendous importance.

Secondary sources of REEs include but are not limited to acid mine drainage (AMD), …

Enhancing Pipeline Simulations Through Artificial Intelligence And Machine Learning: A Smart Proxy Modelling Approach, Afeez Shittu

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

Enhancing pipeline simulations is essential for improving operational efficiencies and effectively managing risks in the oil and gas industry. Traditional pipeline simulators, relying heavily on mathematical modeling assumptions, often face limitations due to their high energy and computational demands. This thesis addresses these challenges by introducing an innovative approach that integrates artificial intelligence (AI) and machine learning (ML) through a smart proxy model, offering a more efficient, cost-effective, and flexible alternative to conventional full-physics models used in pipeline simulation software.

The primary aim of this research is to develop and implement a smart proxy model capable of accurately predicting …

Application Of Predictive Control Strategies For Water-Gas Shift Membrane Reactors Using Data-Driven Models, Bernardo De Oliveira Vecchio

Graduate Theses, Dissertations, and Problem Reports (ETD)

As demand for more efficient processes keeps rising and more restrictive environmental legislation requires higher levels of both yield and purity, the process industry has now, more than ever, been looking for new ways to achieve these goals. One approach has been the implementation of Process Intensification (PI). PI aims to combine multiple unit operations into a single one, promoting efficiency gains on multiple levels. This combination, however, leads to complex process dynamics, and controlling such processes, particularly when setup as multi-input-multi-output (MIMO) systems, presents a great challenge due to highly interactive complex process dynamics and the imposition of many …

Development Of Probabilistic Dynamic Model Building And Bayesian Machine Learning Approaches, Samuel Oladayo Adeyemo

Graduate Theses, Dissertations, and Problem Reports (ETD)

Abstract

Development of Probabilistic Dynamic Model Building and Bayesian Machine Learning Approaches

Samuel Adeyemo

The recent years have seen a tremendous increase in the use of artificial intelligence (AI) and machine learning (ML) for the development of data-driven mathematical models needed for performing real-time optimization, model-based control, performance optimization, dynamic data reconciliation, and process performance monitoring. However, the development of data-driven models is faced with some challenges including lack of model interpretability, sensitivity of algorithm to noise in training data, limited extrapolation capabilities and violation of conservation laws. Drawing motivation from these existing gaps, this work aims to develop robust …

State Estimation And Economic Analysis For Electrochemical Sensor-Based Corrosion Monitoring, Chandra Sekhar Somayajula

Graduate Theses, Dissertations, and Problem Reports (ETD)

Coal is currently the third-largest source of electricity production in the U.S. However, renewables are projected to be the primary source of electricity production in the future. Though coal-fired power plants (CFPPs) are rapidly retiring in the U.S., many CFPPs worldwide are expected to stay operational for a while due to factors like easy and cheap access to comparatively inexpensive coal. Therefore, non-renewable sources like coal are still expected to be prevalent and be used to ensure the stability of the electric grid in the foreseeable future. The existing coal-fired power plants generally designed to operate at base-loaded conditions are …

Comparative Analysis Of Artificial Intelligence And Numerical Reservoir Simulation In Marcellus Shale Wells, Arya Maher Sattari

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation addresses the limitations of conventional numerical reservoir simulation techniques in the context of unconventional shale plays and proposes the use of data-driven artificial intelligence (AI) models as a promising alternative. Traditional methods, while providing valuable insights, often rely on simplifying assumptions and are constrained by time, resources, and data quality. The research leverages AI models to handle the complexities of shale behavior more effectively, facilitating accurate predictions and optimizations with less resource expenditure.

Two specific methodologies are investigated for this purpose: traditional numerical reservoir simulations using Computer Modelling Group's GEM reservoir simulation software, and an AI-based Shale Analytics …

The Effect Of Different Fracturing Fluids On The Productivity Of Multi-Staged Fractured Marcellus Shale Horizontal Wells, Vida Gyaubea Matey-Korley

Graduate Theses, Dissertations, and Problem Reports (ETD)

While hydraulic fracturing has undeniably improved the production from oil and gas reservoirs, this technology is not without limitations. The primary hurdles lie in the areas of proppant transport, fluid rheology, and stress management. Despite the extensive research conducted in this domain, there remains a considerable amount of work to be done for comprehensive solutions that account for the complex interactions among fracturing fluid, proppant distribution, and geomechanical conditions. Achieving this will then make room for a holistic and efficient hydraulic fracturing strategy.

This study addresses the above-mentioned problem by examining the impact of fluid type on proppant transport and …

Combustion Characteristics Of Methane, Ethane, Propane, And Butane Blends Under Conditions Relevant Of A Dual-Fuel Diesel And Natural Gas Engine, Christopher Joseph Ulishney

Graduate Theses, Dissertations, and Problem Reports (ETD)

As natural gas production infrastructure is already in place in most of the world and will continue expanding for the foreseeable future, natural gas is an alternative to traditional liquid petroleum fuels in heavy-duty engines. Dedicated natural gas or dual-fuel diesel-natural gas heavy-duty engines are alternatives to diesel-only power generation equipment. One challenge is the large variation in the natural gas composition available for such applications, which is known to significantly affect engine’s combustion characteristics and the emissions composition. As the literature on dual-fuel combustion under low load engine operating conditions that use more realistic natural gas mixtures (i.e., mixtures …

Modeling And Simulation Of A Process That Converts Ethane To Ethylene And Ethylene To Low Density Polyethylene, Ernest Bosire Mokaya

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ethylene is a critical feedstock and a major building block in the petrochemical industry that is used in synthesizing important products like polyethylene, ethanol, ethylene oxide, ethylene dichloride and ethylbenzene. With increasing demand of plastics, production of ethylene and subsequently polyethylene has increased globally. This thesis conducts the modeling and simulation of an integrated process that utilizes ethane as the primary feedstock to produce ethylene and the subsequent polymerization of ethylene to low-density polyethylene (LDPE). The process combines two different processes into one integrated process: (1) conversion of ethane to ethylene and (2) conversion of ethylene to LDPE. First, a …

Applying Thermal And Microwave Heating For Natural Gas Conversion To Value-Added Chemicals Over Zeolite-Supported Catalysts, Ashley Marie Caiola

Graduate Theses, Dissertations, and Problem Reports (ETD)

The world’s demand for natural gas has been consistently growing over the past few decades. Natural gas is considered a potential alternative to oil and coal because of its ability to burn cleaner. Although not completely emission-free, it has dominated the energy industry by providing a continuous supply of cheap fuel. Currently, natural gas makes up 41% of North American energy production. The conversion of natural gas to value-added chemicals typically involves the indirect production of synthesis gas (syngas) as an intermediate before the production of the desired product. Steam reforming and partial oxidation are two of the most common …

Synthesis Of Quasi-Freestanding Graphene Films Using Radical Species Formed In Cold Plasmas, Michael A. Mathews Jr.

Graduate Theses, Dissertations, and Problem Reports (ETD)

For over a decade, the Stinespring laboratory has investigated scalable, plasma assisted synthesis (PAS) methods for the growth of graphene films on silicon carbide (SiC). These typically utilized CF₄-based inductively coupled plasma (ICP) with reactive ion etching (RIE) to selectively etch silicon from the SiC lattice. This yielded a halogenated carbon-rich surface layer which was then annealed to produce the graphene layers. The thickness of the films was controlled by the plasma parameters, and overall, the process was readily scalable to the diameter of the SiC wafer.

The PAS process reproducibly yielded two- to three-layer thick graphene films …

Leveraging Artificial Intelligence And Geomechanical Data For Accurate Shear Stress Prediction In Co2 Sequestration Within Saline Aquifers (Smart Proxy Modeling), Munirah Alawadh

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research builds upon the success of a previous project that used a Smart Proxy Model (SPM) to predict pressure and saturation in Carbon Capture and Storage (CCS) operations into saline aquifers. The Smart Proxy Model is a data-driven machine learning model that can replicate the output of a sophisticated numerical simulation model for each time step in a short amount of time, using Artificial Intelligence (AI) and large volumes of subsurface data. This study aims to develop the Smart Proxy Model further by incorporating geomechanical datadriven techniques to predict shear stress by using a neural network, specifically through supervised …

Ambient Ammonia Synthesis Via Microwave-Catalytic Materials And Plasma Chemistry, Siobhan Brown

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ammonia is critical to supporting human life on earth because of its use as fertilizer. The Haber-Bosch process to produce ammonia has been practiced for over 100 years. This process operates at high pressure and temperature to overcome the thermodynamic and kinetic limitations of the ammonia synthesis reaction thus researchers have tried to overcome it for decades. At present this process represents 1% of global energy usage and 2.5% of global CO₂ emissions. The proposed chemical looping ammonia synthesis approach seeks to reduce the environmental impact of this critical process and to elucidate microwave-catalytic principles.

This research aims to …

Optimal Design And Operation Of Integrated Hydrogen Generation And Utilization Plants, Ijiwole Solomon Ijiyinka

Graduate Theses, Dissertations, and Problem Reports (ETD)

There are considerable efforts worldwide for reducing the use of fossil fuel for energy production. While renewable energy sources are being increasingly used, fossil fuel still contribute about 80% of the energy used worldwide. As a result, the level of CO₂ is still increasing fast in the atmosphere currently exceeding about 410 parts per million (ppm). For reducing CO₂ build up in the atmosphere, various approaches are being investigated. For the electric power generation sector, two key approaches are post-combustion CO₂ capture and use of hydrogen as a fuel for power generation. These two solutions can also …

State Estimation, Covariance Estimation, And Economic Optimization Of Semi-Batch Bioprocesses, Ronald Hunter Alexander

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the most critical aspects of any chemical process engineer is the ability to gather, analyze, and trust incoming process data as it is often required in control and process monitoring applications. In real processes, online data can be unreliable due to factors such as poor tuning, calibration drift, or mechanical drift. Outside of these sources of noise, it may not be economically viable to directly measure all process states of interest (e.g., component concentrations). While process models can help validate incoming process data, models are often subject to plant-model mismatches, unmodeled disturbances, or lack enough detail to track …

Dynamic Modeling, Data Reconciliation, Parameter Estimation, And Health Monitoring Of A Supercritical Power Plant, Katherine Grace Hedrick

Graduate Theses, Dissertations, and Problem Reports (ETD)

With the introduction of a larger portion of renewable sources of power coming onto the U.S. power grid in recent decades, the operational strategy of coal-fired power plants has changed significantly to focus more on flexibility in response to the changing energy market. This has naturally led to different operational challenges. Many of these challenges are focused on the boilers within these plants, as they are producing more emissions and experiencing increased damage during load-following, which in turn leads to increased costs from penalties for not achieving emission standards or maintenance costs as boilers accumulate damage from the cycling behavior. …

Nonlinear Dynamic Analysis And Control Of Chemical Processes Using Dynamic Operability, San Quan Dinh

Graduate Theses, Dissertations, and Problem Reports (ETD)

Nonlinear dynamic analysis serves an increasingly important role in process systems engineering research. Understanding the nonlinear dynamics from the mathematical model of a process helps to find the boundaries of all achievable process conditions and identify the system instabilities. The information on such boundaries is beneficial for optimizing the design and formulating a control structure. However, a systematic approach to analyzing nonlinear dynamics of chemical processes considering such boundaries in a quantifiable and adaptable way is yet to exist in the literature. The primary aim of this work is to formulate theoretical concepts for dynamic operability, as well as develop …

Techno-Economic Analysis And Optimization Of Hydrogen And Mechanical Energy Storage Systems, Pavitra Senthamilselvan Sengalani

Graduate Theses, Dissertations, and Problem Reports (ETD)

The increasing significance of renewable energy sources is thrusting the load cycling of fossil-fueled power plants (FFPP), designed to operate under nominal-load conditions. Integration of energy storage systems (ESS) with the FFPPs such as hydrogen energy storage (HES) and mechanical energy storage facility such as compressed air energy storage (CAES) shows the potential to minimize the levelized cost of electricity during high demand scenarios and also minimize the negative impacts of off-design FFPP operation. The deployment of energy storage facilities at the FFPP level have considerable potential advantages as they can be exploited within the existing equipment items and facilities …

Evaluating Electrification Of Fossil Fuel-Fired Boilers For Decarbonization Using Discrete Event Simulation, Nahian Ismail Chowdhury

Graduate Theses, Dissertations, and Problem Reports (ETD)

Decarbonizing fossil fuel usage is crucial in mitigating the impacts of climate change. CO2, which comprises the major portion of greenhouse gas, is emitted from burning fossil fuels. One of the significant sources of fossil fuel user is industrial process heating, and most of the heating in industrial processes is achieved through boilers. Electrification is a promising solution for decarbonizing these boilers, as it enables renewable energy sources to generate electricity, which can then be used to power the electric boilers. The electrification of boilers can reduce greenhouse gas emissions, improve air quality, and increase energy efficiency. However, it requires …

Modular Supply Network Optimization Of Renewable Ammonia And Methanol Co-Production, Benjamin Akoh

Graduate Theses, Dissertations, and Problem Reports (ETD)

To reduce the use of fossil fuels and other carbonaceous fuels, renewable energy sources such as solar, wind, geothermal energy have been suggested to be promising alternative energy that guarantee sustainable and clean environment. However, the availability of renewable energy has been limited due to its dependence on weather and geographical location. This challenge is intended to be solved by the utilization of the renewable energy in the production of chemical energy carriers. Hydrogen has been proposed as a potential renewable energy carrier, however, its chemical instability and high liquefaction energy makes researchers seek for other alternative energy carriers. Ammonia …

Machine Learning Assisted Framework For Advanced Subsurface Fracture Mapping And Well Interference Quantification, Mohammad Faiq Adenan

Graduate Theses, Dissertations, and Problem Reports (ETD)

The oil and gas industry has historically spent significant amount of capital to acquire large volumes of analog and digital data often left unused due to lack of digital awareness. It has instead relied on individual expertise and numerical modelling for reservoir development, characterization, and simulation, which is extremely time consuming and expensive and inevitably invites significant human bias and error into the equation. One of the major questions that has significant impact in unconventional reservoir development (e.g., completion design, production, and well spacing optimization), CO2 sequestration in geological formations (e.g., well and reservoir integrity), and engineered geothermal systems (e.g., …

An Artificial Neural Network Approach To Predicting Formation Stress In Multi-Stage Fractured Marcellus Shale Horizontal Wells Based On Drilling Operations Data, Moudhi Alawadh

Graduate Theses, Dissertations, and Problem Reports (ETD)

The distribution of the anisotropic minimum horizontal stress, both in horizontal and vertical directions, is necessary for effective hydraulic fracture treatment design in Marcellus Shale horizontal wells. Typically, the minimum horizontal stress can be estimated sonic logs. However, sonic log data is not commonly available for the horizontal Marcellus shale wells due to the complexity and cost. The objective of this research is to predict the anisotropic minimum horizontal stress by utilizing drilling parameters including depth, weight-on-bit (WOB), revolution per minute (RPM), standpipe pressure, torque, pump flow rate, and the rate of penetration (ROP). More specifically, artificial neural network (ANN) …

Microwave-Assisted Ammonia Synthesis Over Cs-Ru/Ceo2 Catalyst, Alazar Kesete Araia

Graduate Theses, Dissertations, and Problem Reports (ETD)

Ammonia synthesis is one of the greatest innovations of the 20^th century with extensive applications from fertilizers to intermediates for nitrogen-containing chemicals and pharmaceuticals. Annually, more than 242 million tons of ammonia is produced globally, supporting approximately 27% of the world’s population. One of the fast-growing applications for ammonia is as H₂ energy carrier due to its high energy storage capacity, considered to be a decarbonized energy source. The low volumetric energy density and incompressibility makes Hydrogen a non-preferable energy carrier; an alternative carrier becomes a requirement. Ammonia possesses unique property as an energy-dense carrier to store and …

Thermochemical Water-Splitting Using Novel High-Entropy Perovskite Oxides, Hector Alexis De Santiago Hernandez

Graduate Theses, Dissertations, and Problem Reports (ETD)

In this project, we designed, synthesized, and tested the transformative (La_0.8Sr_0.2)(Mn_[1-x]/3Fe_[1-x]/3Co_xAl_[1-x]/3)O₃ (0 ≤ x ≤ 1.0) high-entropy perovskite oxides (HEPOs) as redox active oxygen carriers for thermochemical hydrogen production with improved stability, kinetics, and H₂ yield. The developed HEPOs form an R3c (hexagonal) phase and were successfully synthesized using both the Pechini and solid-state reactions with the latter synthesis being the primary source for testing. These innovative perovskites demonstrated an improved kinetics with oxygen surface exchange coefficient, k, greater than 7.5 x 10^-4 cm/s, …

Application Of Artificial Intelligence For Co2 Storage In Saline Aquifer (Smart Proxy For Snap-Shot In Time), Marwan Mohammed Alnuaimi

Graduate Theses, Dissertations, and Problem Reports (ETD)

In recent years, artificial intelligence (AI) and machine learning (ML) technology have grown in popularity. Smart Proxy Models (SPM) are AI/ML based data-driven models which have proven to be quite crucial in petroleum engineering domain with abundant data, or operations in which large surface/ subsurface volume of data is generated. Climate change mitigation is one application of such technology to simulate and monitor CO2 injection into underground formations.

The goal of the SPM developed in this study is to replicate the results (in terms of pressure and saturation outputs) of the numerical reservoir simulation model (CMG) for CO2 injection into …

Hydrocarbon Pay Zone Prediction Using Ai Neural Network Modeling., Darren D. Guedon

Graduate Theses, Dissertations, and Problem Reports (ETD)

This paper captures the ability of AI neural network technology to analyze petrophysical datasets for pattern recognition and accurate prediction of the pay zone of a vertical well from the Santa Fe field in Kansas.

During this project, data from 10 completed wells in the Santa Fe field were gathered, resulting in a dataset with 25,580 records, ten predictors (logs data), and a single binary output (Yes or No) to identify the availability of Hydrocarbon over a half feet depth segment in the well. Several models composed of different predictors combinations were also tested to determine how impactful some logs …

Ethane Dehydrogenation For Light Olefins Production Over Stable Catalyst, Xiaoyan Wang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Accompanied by the development of modern industry, the demand for light olefins (e.g., ethylene, propylene, butene, butadiene) increases year by year. Light olefins are important intermediates in producing polymers (Polyethylene, Polypropylene, etc.) and rubber (Styrene Butadiene Rubber, Polybutadiene rubber, etc.). The primary process for the production of light olefins is steam cracking of petroleum liquids (naphtha and distillate fuel oil). It is an energy-intensive process, requiring high temperature (750-850℃) and pressure (1.0-4.5 MPa). Meanwhile, due to undesired side reactions, this process has lowered the efficiency of light olefins production and suffers from severe coking issues. Furthermore, as petroleum liquids become …

Design And Control Of Intensified Membrane Reactor Systems Through Module-Based Design Approach, Brent Bishop

Graduate Theses, Dissertations, and Problem Reports (ETD)

As interest in the modularization and intensification of chemical processes continues to grow, more research must be directed towards the modeling and analysis of intensified process units. Intensified process units such as membrane reactors pose unique challenges pertaining to design and operation that have not been fully addressed in the reported literature. This work aims to address the design and control challenges caused by the integration of phenomena and the loss of degrees of freedom (DOF) that occur in the intensification of modular membrane reactor units.

First, a novel first-principles approach for modeling membrane reactors is developed using the AVEVA …

Advanced Process Modeling And Optimization Of Amine-Based Carbon Capture Process, Paul Jide Terhemba Akula

Graduate Theses, Dissertations, and Problem Reports (ETD)

With the rise of carbondioxide (CO2) concentration in the atmosphere to more than 400 parts per million (ppm), research efforts have been focused on achieving net-zero carbon emission technologies. Post-combustion CO2 capture (PCC) is a key strategy in reducing CO2 emissions. Amine-based CO2 capture is the baseline technology for retrofitting existing power stations. However, the integration of amine-based PCC technology with power plants to reduce greenhouse gas emissions incurs a high energy penalty, decreasing a powerplant’s efficiency by about 23 percentage points. Understanding the capture plant dynamics plays an important role in its technical and economic performance. Rigorous models are …