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A 4-Phase Flow Model for Methane Production from an Unconsolidated Hydrate Reservoir
Title
A 4-Phase Flow Model for Methane Production from an Unconsolidated Hydrate Reservoir
Creator
Hinz, Deniz
Date
2019
Description
Natural gas from hydrates is extremely abundant as an energy resource; US resource-grade hydrate deposits are estimated to be over 20 times...
Show moreNatural gas from hydrates is extremely abundant as an energy resource; US resource-grade hydrate deposits are estimated to be over 20 times the domestic proved natural gas resources, at approximately 7000 trillion cubic feet (tcf). The theoretical potential of hydrates is immense, but production testing and research remain lacking, which has led to the development of numerous hydrate production numerical simulators for consolidated porous media hydrate reservoirs. However, due to the onset of unconsolidated flow behavior upon significant hydrate dissociation, numerical models haven’t agreed well with the experimental data from the Mallik production tests. Hydrate contributes substantially to the strength of the sediment matrix, such that hydrate-bearing sediment ultimately falls apart exhibiting 4-phase unconsolidated flow behavior of gas, water, hydrate, and sand. In order to better capture the multiphase flow characteristics of gas, water, hydrate, and sand in an unconsolidated gas hydrate reservoir, we have developed a novel 4-phase flow model coupled with numerical simulation of the Mallik 2007/2008 production tests. The model is able to capture the coupled 4-phase hydrodynamics, mass transfer, and heat transfer physics inherent to the unconsolidated hydrate reservoir. Solid deformation is modeled by extending multiphase and granular flow theory to hydrate-bearing sediment. Constitutive models for the solid viscosity and solid pressure are developed to model the change in strength of the sediment as hydrate dissociates and the solid deforms. The solid viscosity is a composite of frictional contributions from the solid normal stress and cohesive contributions from the hydrate. The interphase momentum exchange between the fluid phases (gas and water) and solid phases (hydrate and sand) modeled based on a volume-averaged approach that considers the formation and closure of high-permeability volumes due to dilation and compaction of hydrate-bearing sediment as it deforms. By considering the deformation of solids and the subsequent effect on the permeability, the 4-phase simulations showed good agreement with the experimental data from the Mallik 2007/2008 production phases. The 4-phase modeling approach serves as a proof of concept for the application of granular flow theory to hydrate-bearing sediment. An unconsolidated hydrate reservoir with sustained sand production essentially behaves like a naturally fracking reservoir, exhibiting a dramatic increase in permeability induced solely by depressurization. Conversely, preventing sand production with a sand screen ultimately leads to significant throttling of the gas production rate due to the compaction and accumulation of sand at the sand screen.
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Economic and Computational Methods for the Control of Uncertain Systems
Title
Economic and Computational Methods for the Control of Uncertain Systems
Creator
Zhang, Jin
Date
2019
Description
The Economic Linear Optimal Control (ELOC) can improve the effective use of economic and dynamic information throughout the traditional...
Show moreThe Economic Linear Optimal Control (ELOC) can improve the effective use of economic and dynamic information throughout the traditional optimization and control hierarchy. This dissertation investigates the computational procedures used to obtain a global solution to the ELOC problem. The proposed method employs the Generalized Benders Decomposition (GBD) algorithm. Compared to the previous branch and bound approach, the application of GBD to the ELOC problem will greatly improve computational performance. A technological benefit of decomposing the problem into steady-state and dynamic parts is the ability to utilize nonlinear steady-state models, since the relaxed master problem is free of SDP type constraints and can be solved using any global nonlinear programming algorithm.In order to address the issue of model/plant mismatch, the dissertation will also investigate how to handle box-type uncertainties in ELOC. We consider two methods, a robust formulation for when the uncertainty is completely unknown and a Linear Parameter Varying formulation for when uncertainty can be measured in real time. In both cases, the infinite number of conditions that need to be satisfied are reduced to a finite set of constraints. The resulting problem formulations have a similar structure to the ELOC and can be solved globally by employing the generalized Benders decomposition.Despite a high-quality control law, the ultimate performance of closed-loop systems will be dictated by the quality and limitation of hardware element. Thus, hardware selection is also investigated in the dissertation. The cost-optimal hardware selection problem has been shown to be of the Mixed Integer Convex Programming (MICP) class. While such a formulation provides a route to global optimality, use of the branch and bound search procedure has limited application to fairly small systems. In this dissertation, we illustrate that a simple reformulation of the MICP and subsequent application of the GBD algorithm will result in massive reductions in computational effort.Finally, the problems of value-optimal sensor network design (SND) for steady-state and closed-loop systems are investigated. The value-optimal SND problem has been shown to be of the nonconvex mixed integer programming class. In the dissertation, it is demonstrated after transforming into an equivalent reformation, the application of GBD algorithm will significantly reduce the computational effort.
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ECONOMIC MPC-BASED DESIGN AND OPERATION OF GRID SCALE ENERGY STORAGE SYSTEMS
Title
ECONOMIC MPC-BASED DESIGN AND OPERATION OF GRID SCALE ENERGY STORAGE SYSTEMS
Creator
Adeodu, Oluwasanmi
Date
2019
Description
It is generally recognized that a higher penetration of renewable power on the electric grid, along with the attendant environmental benefits,...
Show moreIt is generally recognized that a higher penetration of renewable power on the electric grid, along with the attendant environmental benefits, is limited by its inherent high variability and intermittency. An approach to alleviating this issue is to install grid scale energy storage as buffer. However, the economic viability of such an endeavor is dependent on the optimal sizing and placement (OSP) of storage units, which in turn requires the specification of an appropriate storage management policy. While stochastic programming with recourse is recognized as the standard approach to stage-wise optimal decision-making under uncertainty, Economic Model Predictive Control (EMPC) is put forward as a deterministic simplification of the former and demonstrated to be a viable economic dispatch strategy for networks with a high proportion of renewable energy and storage. Then, a numerical, EMPC-based gradient search strategy is proposed to address the OSP problem. Since both the operating policy and OSP questions are invariably massive optimization problems in real systems, strong emphasis is laid on computational tractability. Therefore, the analytical nature of a surrogate stochastic control policy, Economic Linear Optimal Control (ELOC), is exploited to develop innovative modifications to both algorithms. The end products are (1), an Approximate Infinite Horizon EMPC (AIH-EMPC) strategy, a relatively low computational cost variant of EMPC and (2), a hybrid EMPC-ELOC OSP strategy that essentially sidesteps the inherent combinatorial complexity of the unit location problem.
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Development of multirate data-driven models for chemical and biological processes
Title
Development of multirate data-driven models for chemical and biological processes
Creator
Gan, Jingwei
Date
2019
Description
Monoclonal antibodies (MAbs) have extensive biomedical application and are produced in mammalian cell bioreactor at a variety of scales, with...
Show moreMonoclonal antibodies (MAbs) have extensive biomedical application and are produced in mammalian cell bioreactor at a variety of scales, with glucose and glutamine being the principle carbon and nitrogen sources required for cellular metabolism. Fed-batch operation has certain inherent advantage over batch culture for MAbs production. Design, optimization, scale-up, and control of bioreactor used for MAbs production requires reliable predictive empirical or mechanistic models for key cellular activity. The models used in prior studies have largely been the first principle based models (FPMs), although data-driven models are receiving increasing attention due to their certain inherent benefits and increasing information available about biological processes. The simpler and much less rigid structure of data-driven models facilitates frequent updating of parameters and prediction of process trajectories, increasing their utility in representation, monitoring and control of these processes.Multi-sampling rate recursive time series models are developed for representation of a mammalian cell culture, with process variables that are determinants of the performance of the culture being measured at different sampling frequencies. For this reason, a composite of an adaptive autoregressive moving average with exogenous input (ARMAX) model, a dual-rate adaptive autoregressive exogenous input (DR-ARX) model and a irregular-rate adaptive autoregressive exogenous input (IR-ARX) model is used. Appropriate parameter constraints have been imposed in parameter estimation algorithms and stability of these has been examined and is ensured. The data required of estimation of parameters are generated from simulation experiments using a well tested first principle-based kinetic model (FPM) considering random variations in manipulated inputs, kinetic parameters in the FPM, and measurement error for outputs. Glucose and glutamine being determinants of mammalian cell metabolism, their supply rates are considered to be inputs. The predictive ability of the data-driven model is examined and demonstrated over a broad range of prediction horizon.
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Structural Studies of Degradation Mechanism of Lithium Rich Manganese, Nickel, and Iron Based Cathodes
Title
Structural Studies of Degradation Mechanism of Lithium Rich Manganese, Nickel, and Iron Based Cathodes
Creator
Aryal, Shankar
Date
2018
Description
Layered oxide compounds are superior with respect to discharge voltage and discharge specific capacity compared to other families of cathodes....
Show moreLayered oxide compounds are superior with respect to discharge voltage and discharge specific capacity compared to other families of cathodes. Therefore, LiCoO2 and LiMnxNiyCozO2, are the most commonly used cathodes since the commercialization of lithium ion battery. Recently, Li rich Ni, Mn, and Co oxide composite cathodes have been introduced with some improvements. As Co is toxic and expensive, attempts have been made to replace Co with cheap and environmentally friendly Fe. This dissertation reports that comparable discharge specific capacity and discharge voltage can be achieved by replacing Co with Fe and optimizing the composition of Mn, Ni, and Fe. However, the capacity and voltage fading on cycling are still remaining challenges. Structural change on electrochemical cycling is the main reason behind this fading. X-ray absorption spectroscopy (XAS), the specific element probe technique to study local structure and X-ray diffraction (XRD) to study the crystallographic phase information are utilized to understand the degradation/aging mechanism. A series of Li rich Mn, Ni, and Fe oxide composite cathode materials Li1.2Mn(0.30+x)Ni(0.40-x)Fe0.10O2 for x = 0, 0.05, 0.10, 0.15, 0.20 and 0.25 were prepared using a sol-gel synthesis method. Rhombohedral and monoclinic crystal phases are found in Li rich Mn, Ni, and Fe composite oxide materials, but pure rhombohedral phase cannot be obtained without excess Li in the stoichiometric LiMO2 form. The pure monoclinic phase Li2MnO3 is also synthesized to confirm its presence in the composite oxide cathodes. Particle size and surface morphology are studied with scanning electron microscopy. The composite cathodes are cycled to over 100 cycles at 0.3C, for C = 250 mAhg-1 rate. XAS before and after 100 electrochemical cycles of Li rich Mn-Ni-Fe based cathodes is reported for the first time. The determination of fractional contents of monoclinic and rhombohedral phases in the composite oxide cathodes is not possible by powder XRD analysis, however, Li2MnO3 content decreases on decreasing Mn content and on increasing Ni content. The composition with higher Ni content has a higher degree of cation mixing. The synergistic effect of rhombohedral and monoclinic phases in Li rich Mn, Ni, and Fe based cathode is critical for stable electrochemical performance. The Li1.2Mn0.50Ni0.20Fe0.10O2 cathode showed the most stable cyclability performance (194 mAhg-1 first discharge capacity with 94 % capacity retention after 100 cycles at 0.3C rate) however, Li1.2Mn0.40Ni0.30Fe0.10O2 (220 mAhg-1 first discharge capacity with 57 % capacity retention) and Li1.2Mn0.55Ni0.15Fe0.10O2 (241 mAhg-1 first discharge capacity with 68 % capacity retention) cathodes showed higher 1st discharge capacity but poor cyclability under the same charge/discharge cycling.The XAS at Mn K-edge is used to explain the mechanism of Li2MnO3 activation for the improved electrochemical performance of Li rich Mn, Ni, and Fe oxide composite cathode, however Li2MnO3 contributed differently in different compositions. Synchrotron XRD and XAS measurements probed the lattice size expansion, which decreases the chemical potential of Li ions in the cathode on cycling leading to lower discharge voltage after cycling.
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Entangled Polymer Rheology: Efficient Algorithms and Coarse-Graining of Slip-Link Model
Title
Entangled Polymer Rheology: Efficient Algorithms and Coarse-Graining of Slip-Link Model
Creator
Taletskiy, Konstantin
Date
2018
Description
This manuscript presents the work done with the Discrete Slip-Link model (DSM) and efforts to improve it through new theoretical derivations...
Show moreThis manuscript presents the work done with the Discrete Slip-Link model (DSM) and efforts to improve it through new theoretical derivations and computational algorithms. New results are presented for melts of broadly polydisperse linear chains as well as for monodisperse star-branched chains. Significant portion of this work is dedicated to the development of the new method for coarse-graining physical models and application of it to the problem of mechanical relaxation of star-branched polymers in DSM.
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Capillary Rise of Common Liquids and Nanofluids: Experiments and Modeling
Title
Capillary Rise of Common Liquids and Nanofluids: Experiments and Modeling
Creator
Wu, Pingkeng
Date
2018
Description
Capillary dynamics of common liquids and nanofluids is a ubiquitous everyday phenomenon. It has practical applications in diverse fields,...
Show moreCapillary dynamics of common liquids and nanofluids is a ubiquitous everyday phenomenon. It has practical applications in diverse fields, including ink-jet printing, lab-on-a-chip, biotechnology, and coating. Important as it is, this phenomenon has not been fully understood and requires tremendous effort in theoretical analysis and experimental investigations to gain further knowledge and guide the design of practical precesses whenever capillarity is essential.The rise of the main meniscus in rectangular capillaries is important in interpreting the phenomenon of fluid flow in porous media. This thesis presents an experimental study on the rise of the main meniscus in rectangular borosilicate glass and plastic (polystyrene) capillaries using three different liquids (water, ethanol, and hexadecane). A universal model (an extended two-wall model) based on the Laplace equation was developed to predict the equilibrium height of the main meniscus in rectangular capillaries. In capillary dynamics, it is crucial to understand the interaction between fluid molecules and a solid substrate (the wall) in molecular scale. Recent studies reveal that a layered molecularly thin wetting film (LMTWF) will develop ahead of the apparent three-phase contact line for the spreading of a wetting liquid on solid surfaces. Based on this fact, a novel molecular self-layering model is proposed to explain the dynamic wetting considering the role of the molecular shape on self-layering and its effect on the molecularly thin film viscosity in regards to the advancing (dynamic) contact angle. The proposed molecular self-layering model is then incorporated into the Lucas-Washburn-Rideal (LWR) equation to explain the capillary rise dynamics of fluids of spherical, cylindrical, and disk shape molecules in borosilicate glass capillaries. The abilities of the other popular dynamic contact angle models to correct the dynamic contact angle effect in the capillary rise process were also investigated. The LWR equation modified by molecular self-layering model predicts well the capillary rise of carbon tetrachloride, octamethylcyclotetrasiloxane and n-alkanes with the molecular diameter or measured solvation force data. The molecular self-layering model modified LWR equation also has good predictions on the capillary rise of silicone oils covering a wide range of bulk viscosities with the same key parameter W(0), which results from the molecular self-layering. Besides the open capillaries, the proposed molecular self-layering model is applied to explain the spontaneous rise of Newtonian liquids in closed-end capillaries. Contribution of the compressed air inside the closed capillaries is also modeled and experimentally verified. Finally, the research is extended to a liquid phase displacing another immiscible liquid in capillaries with the focus on surfactant solutions containing polymeric nanoparticles (nanofluids), which have been shown to have an improved wetting and spreading on solid surfaces. The polymeric nanoparticles can reduce the frictional coefficient by as much as four times by forming structured layers in the confined wedge film. The role of the interfacial tension on the frictional coefficient is also demonstrated.In summary, this thesis presents the physics of liquid rise in rectangular capillaries, effect of molecular self-layering in capillary dynamics in open and closed-end capillaries, and the contribution of nanofluids in the two-phase displacement dynamics.
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THE EFFECTS OF PHYSICAL AND CHEMICAL PROPERTIES OF DOLOMITE ON DOLOMITE DECOMPOSITION
Title
THE EFFECTS OF PHYSICAL AND CHEMICAL PROPERTIES OF DOLOMITE ON DOLOMITE DECOMPOSITION
Creator
Huang, Hsiang-Jung
Date
2020
Description
Dolomite comprises approximately two percent of the Earth’s crust and has a widespread geological distribution throughout the world. It is an...
Show moreDolomite comprises approximately two percent of the Earth’s crust and has a widespread geological distribution throughout the world. It is an abundant, low cost, and promising raw base material for many applications in industry, such as sorbents for capturing CO2 from coal gas and a heterogeneous catalyst for reducing tar content in biomass gasification. Dolomite decomposition has been intensively studied over the past decades. However, to date, there is hardly any systematic literature available that addresses the effects of naturally occurring impurities on dolomite decomposition due to the difference in various experimental setups, sample size, particle size, and so on. Therefore, this research focuses on employing a systematic and comprehensive investigation to develop a better understanding of the effects of the physical and chemical properties of raw dolomites on dolomite decomposition. This study involves experimental, theoretical, and modeling work. There are several experimental techniques utilized for the exploration of the physical and chemical properties of dolomites from different sources, such as the Thermogravimetric analysis (TGA), the X-ray powder diffraction (XRD) and the Brunauer–Emmett–Teller theory (BET), respectively. In the study, it has been discovered that the excess weight loss of samples during thermal decomposition experiments was owing to the explosive disintegration of the nature of dolomite. The physical properties of dolomites are not the main factor affecting dolomite decomposition but thermodynamic properties and crystal structure. The initial equilibrium constant of dolomite which is dominated by the amount of silicate-based impurities plays a major role in the decomposition rate. A two-stage reaction model was developed that included a reversible reaction of uniform solid ordered-disordered crystal transformation of dolomite followed by a "Quasi-Shrinking Core" reaction of disordered dolomite decomposition. This model is capable of describing the reaction rate of half-calcination of dolomite with acceptable accuracy.
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Synthesis and Processing of NaSICON Membranes with High Ionic Conductivity and Good Mechanical Strength
Title
Synthesis and Processing of NaSICON Membranes with High Ionic Conductivity and Good Mechanical Strength
Creator
Chiang, Shan-Ju
Date
2019
Description
Natrium super ion conductors (NaSICONs), Na1+xZr2SixP3-xO12 (0 ≤ x ≤ 3) are compounds that commonly used as solid electrolytes and membranes...
Show moreNatrium super ion conductors (NaSICONs), Na1+xZr2SixP3-xO12 (0 ≤ x ≤ 3) are compounds that commonly used as solid electrolytes and membranes of sodium based batteries, or in gas sensors and fuel cells due to their high sodium ion conductivity, low thermal expansion, and ability to accommodate ions in the lattice. However, NaSICON with high relative density (> 97%) and minimum impurity phases is found to be very difficult to obtain. Furthermore, the cost of the general synthesis methods is a serious drawback. Multi-high-temperature heating procedures is often employed to increase the density and to attain the single phase NaSICON because the particle size and free ZrO2 are better reduced. This research explores the possibility of densification and synthesis of NaSICON in one high-temperature reaction through a novel process termed Integrated Mechanical and Thermal Activation (IMTA) and the co-sintering behavior as well as the NaSICON composite membranes from tape casting. The sintering temperature of NaSICON was decreased by mechanical activation at room temperature using high-energy ball milling. Sintered NaSICON-based materials showed highest total ionic conductivity of 1.45 × 10-3 S cm-1 at room temperature and high density of 3.155 g cm-3 (96.5%). An alternative to obtaining full densification (99%) of NaSICON ceramics was developed utilizing traditional solid-state reaction. This sintered NaSICON without any sintering aid exhibited the total conductivity, 6.59 × 10-4 S cm-1 at 25 °C, and the highest density of 3.238 g cm-3, a better than 2.6% enhancement from the original samples.The second part of the work has comprised of successful fabrication of NaSICON/polymer composite membranes and bi-layered NaSICON/stainless steel membranes to enhance the mechanical flexibility of pure NaSICON films. The effect of different particle sizes of stainless steel on the sintering behavior and shrinkage rate were studied systematically. The effect of solid content in the slurry was also studied to control the density of both support layer and NaSICON body. The affect structural ratios have on co-sintered tapes along with ionic conductivity was investigated using Electrochemical Impedance Spectroscopy (EIS). The co-sintered membrane exhibited a total conductivity as high as 4.580 × 10-4 S/cm at room temperature. EIS results showed the high Na-ions conductivity strongly depends on the feature of grain boundary and the high densification of NaSICON layer.
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A NEURAL NETWORK BASED MODEL FOR BIOMASS GASIFICATION IN FLUIDIZED BED
Title
A NEURAL NETWORK BASED MODEL FOR BIOMASS GASIFICATION IN FLUIDIZED BED
Creator
Dirbaz, Mohsen
Date
2020
Description
Biomass is a renewable energy resource and its utilization has received great attention due to its life cycle carbon-neutrality and the...
Show moreBiomass is a renewable energy resource and its utilization has received great attention due to its life cycle carbon-neutrality and the potential to substitute fossil fuel to produce a variety of energy-related products. Thermochemical gasification is an important route for conversion of biomass that results in a product gas mainly consisting of H2, CO, CO2, CH4 and other light hydrocarbons that can be used as fuel gas to generate power, or as well as raw material to produce a variety of chemicals. Among the existing gasifiers, fluidized beds (FB) offer many advantages such as high conversion efficiency and great flexibility over types of feedstock.More than 200 data sets of biomass gasification in fluidized bed were collected featuring a wide range of operating condition and fuel types. An axiom-based reasoning was used to develop a multiphase statistical pathway needed as a precondition to effectively quantify the entanglements of different important factors in the process.Specifically, by creating an interconnected chain of analysis based on trigonometric functions, geometric projections, and design of a statistical inference tool utilizing neural network units, multiple partial measures of associations between biomass constituents, and operating condition were effectively consolidated and embedded in a single characteristic matrix that consequently led to detection of monotonic relationships for prediction of carbon conversion efficiency and product gas yield. The black box model in comparison to three different models showed better accuracy in predicting four major components of product gas, over the largest applicable range of all the influential parameters of the process, namely, temperature, air equivalent ratio, steam to biomass ratio, and type of fuel. In part of our methodology, we introduce a novel technique for obtaining a dynamical property value for stationary objects, based on a “specific computational time” of an “abstract mechanical operation on characteristics matrices”. The specific computational time (sct) showed excellent capability in capturing the non-equilibrium factor of the process which itself was function of several interrelated variables.
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USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
Title
USING COMPUTATIONAL MOLECULAR MODELING TO STUDY TRANSPORT PROCESSES OF INTEREST IN SEPARATIONS
Creator
Wang, Xiaoyu
Date
2020
Description
Separation processes are widely used in chemical productions. The further development of membrane-based separation processes, compared with...
Show moreSeparation processes are widely used in chemical productions. The further development of membrane-based separation processes, compared with thermal separations, can lead to significant energy savings in chemical process industries. However, the main obstacle of experiments is that many separation processes are not well understood at the fundamental molecular level. In this dissertation, we use computational molecular modeling tools, mainly classical molecular dynamics (MD), to clarify molecular forces and provide detail at a molecular level, which can aid in the understanding of transport process and designing materials for a proposed application.In the first study, we investigated separation of water/alcohol vapor using zeolite membranes. Experimentally, the separation of water/isopropanol (IPA) mixtures shows a dramatic decrease in selectivity due to increase of IPA flux as the feed water concentration decrease when using the sodium A zeolite membrane. We used molecular dynamics simulations to help our experimental collaborators understand these puzzling results. The MD results reveal that the water molecules gather around the defect pores on the zeolite membrane, which stops the IPA from going through the membrane and has a positive effect on separation.Then, we studied the HPLC used to separate chiral drug mixtures. One popular chiral stationary phase, amylose tris(3,5-dimethylphenyl carbamate) (ADMPC), has been investigated using both experimental and computational methods; however, the dynamic nature of the interaction between enantiomers and ADMPC, as well as the solvent effects on the ADMPC-enantiomer interaction, are currently absent from the chiral recognition mechanism. We used MD simulations to model the ADMPC in different solvents to elucidate the chiral recognition mechanism from a new dynamic perspective. The ADMPC is found to hold the left-handed helical structure in both methanol and heptane/IPA (90/10); however, the ADMPC has a more extended average structure in heptane/IPA. We developed a model where the ADMPC atoms were restricted in the MD simulation. To better understand the molecular dynamic chiral recognition that provides the retention factor and the elution order in HPLC, we examined hydrogen bonding lifetimes, and mapped out ring-ring interactions between the drugs and the ADMPC. We discover several MD metrics related to hydrogen-bonding lifetimes and correlate them with HPLC results. One metric provides a prediction of the correct elution order 90%, and the ratios of these quantities for the enantiomers provide linear correlation (0.85 coefficient) with experimental retention factors.In the following study, we presented an improved model wherein multiple ADMPC polymer strands are coated on an amorphous silica slab. Using various MD techniques, we successfully coated ADMPCs onto the surface without losing the structural character of the backbone in the solvent. This model provides more opportunities for chiral molecules interacting with ADMPC, resulting in a better agreement compared with experiment when using the overall average metric. The new model also provides the possibility for drug molecules to interact with two polymer strands simultaneously, which is not possible in the previous single-strand model. For a better understanding of why some metrics are better predictors than others, we used charts of the distribution of hydrogen bonding lifetimes to display the information for various donor-acceptor pairs. The results are more consistent than the previous models and resolves the problematic cases of thalidomide and valsartan.Besides the membrane-based separations, immiscible liquid-liquid equilibrium states were also studied. We successfully predicted results based on MD simulations and showed comparable accuracy with experimental data. This method has applications in liquid-liquid extraction which is widely used in industrial separation process.
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An adaptive personalized multivariable, multimodule artificial pancreas system based on a plasma insulin cognizant model predictive control
Title
An adaptive personalized multivariable, multimodule artificial pancreas system based on a plasma insulin cognizant model predictive control
Creator
Hajizadeh, Iman
Date
2019
Description
An adaptive and personalized multivariable artificial pancreas system is proposed for effective glycemic control and disturbance rejection...
Show moreAn adaptive and personalized multivariable artificial pancreas system is proposed for effective glycemic control and disturbance rejection without manual user announcements for meals and exercise. Adaptive models identified through system identification techniques are integrated with a physiological compartment model to characterize the time-varying glucose-insulin dynamics. The real-time estimation of plasma insulin concentration to quantify the insulin in the bloodstream in patients with type 1 diabetes mellitus is presented. The identified time-varying models are employed for the design of an adaptive model predictive control formulation that is cognizant of the plasma insulin concentration. A feature extraction method based on glucose measurements is used to detect rapid deviations from the desired set-point caused by significant disturbances and subsequently modify the constraints of the optimization problem for negotiating between the aggressiveness and robustness of the controller to suggest the required amount of insulin. A predictive hypoglycemia module with carbohydrate suggestion is also designed to prevent any potential hypoglycemia events. A controller performance assessment algorithm is developed to analyze the closed-loop behavior and modify the parameters of the artificial pancreas control system. To this end, various performance indices are defined to quantitatively evaluate the controller efficacy in real-time. The controller assessment and modification module also incorporates on-line learning from historical data to anticipate impending disturbances and proactively counteract their effects.
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MULTIVARIABLE SIMULATION PLATFORM FOR TYPE 1 DIABETES AND AUTOMATIC MEAL HANDLING IN ARTIFICIAL PANCREAS SYSTEMS
Title
MULTIVARIABLE SIMULATION PLATFORM FOR TYPE 1 DIABETES AND AUTOMATIC MEAL HANDLING IN ARTIFICIAL PANCREAS SYSTEMS
Creator
Samadi, Sediqeh
Date
2019
Description
Artificial pancreas (AP) systems are designed to automate the glucose control in type 1 diabetes mellitus (T1DM). Multivariable artificial...
Show moreArtificial pancreas (AP) systems are designed to automate the glucose control in type 1 diabetes mellitus (T1DM). Multivariable artificial pancreas systems have evolved to incorporate various additional physiological measurements beyond the conventional continuous glucose monitoring measurements to better integrate information on the metabolic state of the patients affecting the glycemic dynamics. The changes in the physiological measurements such as heart rate, energy expenditure, skin temperature, and skin conductance measured by wearable devices are indicative of the changes in the metabolic state. The controller receives the physiological measurements in the feed forward manner which accelerates the remedy control decision in response to the disturbances. Although various AP systems are proposed in the literature to accommodate these additional sources of information, the testing and evaluation of these advanced multivariable AP systems are hindered by the requirements of conducting time-consuming and expensive clinical trials. Development of a simulation platform for rapid prototyping and iterative development of AP systems is one of the main contributions of this study. Simulation platform for T1DM includes a compartmental model generating glucose concentration in response to physical activity in addition to meals and infused insulin. The proposed exercise-glucose-insulin model is an extension of the previously developed glucose-insulin model to derive transient variations in glycemic dynamics caused by physical activity and to improve the glucose prediction accuracy. Physiological variables affected by physical activity, such as heart rate, skin temperature, and blood volume pulse are generated in addition to the glucose concentration in the simulator. The simulation platform includes several virtual patients providing a reliable platform for in silico evaluation of different algorithms proposed for automation of glucose control in T1DM. The multivariable simulator will accelerate the development of next-generation artificial pancreas systems.The development of a disturbance detection algorithm is the other contribution of this study. Meals are major disturbances to the glucose homeostasis, and automated detection of meal consumption and carbohydrate estimation of the consumed meal are critical for fully automated artificial pancreas control systems. In this study, a detection algorithm integrating fuzzy logic classification and qualitative analysis is proposed. A fuzzy logic system estimates the carbohydrate content of the meal.
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Establishing Bisphenol A Degradation and Enhancing Microbial Fuel Cell Performance by Biofilm Optimization of Shewanella Oneidensis MR1
Title
Establishing Bisphenol A Degradation and Enhancing Microbial Fuel Cell Performance by Biofilm Optimization of Shewanella Oneidensis MR1
Creator
Zhou, Jiacheng
Date
2023
Description
Bisphenol A (BPA) has been widely used as a plasticizer in the production of synthetic polymers, such as those used in food storage containers...
Show moreBisphenol A (BPA) has been widely used as a plasticizer in the production of synthetic polymers, such as those used in food storage containers and bottles. However, BPA interferes with endocrine systems, causing carcinogenicity, immunotoxicity, and embryotoxicity. Biological water treatment processes scarcely remove BPA, owing to the poor BPA degradability and efficiency of the applied microorganisms. Shewanella oneidensis has been studied and used for the biodegradation process in wastewater treatment because of its excellent extracellular electron transfer properties. In this work, we engineered S. oneidensis MR1 to enable BPA degradation by producing ferredoxin (Fdbisd) and cytochrome P450 (P450bisd) originating from Sphingomonas bisphenolicum AO1. The engineered S. oneidensis exhibited a higher BPA degradation efficiency than that of Escherichia coli producing the same enzymes. The endogenous ferredoxin and ferredoxin reductase of S. oneidensis participated in BPA degradation, and overexpression of mtrC, omcA, and So0521, which encode S. oneidensis cytochromes, decreased BPA. We developed BPA-degrading S. oneidensis biofilms. We measured these optimized BPA-degrading S. oneidensis biofilm in a single chamber microbial fuel cell formed on different carbon electrodes by morphology. Cyclic voltammetry and electrochemical impedance spectroscopy were measured to analyze the biofilm-electrode performance. The biofilm colonization was also measured by confocal laser scanning microscope and scanning electron microscope. And the developed microbial fuel cell was used to degrade BPA and the biofilm developed on different type of carbon anodes was identified. This study provides insights into biocatalyst utilization for the biological degradation of toxic organic compounds.
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COMPUTATIONAL FLUID DYNAMICS SIMULATION OF CARBON CAPTURE UNIT USING AN AMINE-BASED SOLID SORBENT
Title
COMPUTATIONAL FLUID DYNAMICS SIMULATION OF CARBON CAPTURE UNIT USING AN AMINE-BASED SOLID SORBENT
Creator
Esmaeili Rad, Farnaz
Date
2021
Description
Carbon capture and sequestration (CCS) is one of the key technologies to reduce the emission of carbon dioxide, including that from exiting...
Show moreCarbon capture and sequestration (CCS) is one of the key technologies to reduce the emission of carbon dioxide, including that from exiting flue gas of fossil fuel-fired power plants. The goal of this project is the development of a computational fluid dynamics (CFD) model to predict the extent of CO2 capture in a circulating fluidized bed carbon capture unit using novel amine-based solid sorbents.In this study, first the hydrodynamics of the carbonation section of the carbon capture unit was investigated. Then, the performance of the amine-based solid sorbents toward capturing carbon dioxide from flue gas and the extent of CO2 adsorption in the carbonation section were studied. At the second stage of the study, the regeneration of the sorbents and desorption of carbon dioxide from carbonated solid sorbents in the regeneration section of the carbon capture unit was investigated. At the third stage of the study, the hydrodynamics of the entire loop of the integrated carbonation and regeneration sections were simulated. Two-dimensional non-reactive CFD simulations of the entire loop, including the carbonator, regenerator, and two loop-seal fluidized beds, were performed to study the details of the solid circulation in the system in a stable operational condition. At the fourth stage of the study, the effect of the carbonated solids’ residence time in the regeneration section was investigated by extending the regenerator fluidized bed height and adding to the volume of the system. Heated surfaces, which resembled heating coils in the regenerator cylinder, were also added to the system to investigate the effect of the temperature. The heated surface of the immersed coils in the bed provided sufficient energy for the endothermic regeneration reaction to keep the temperature of the bed at the desired temperature. Finally, the verified models of the carbonation section, the regenerations section, and non-reactive simulation of the CFB loop were used to simulate the entire circulating fluidized bed carbon capture unit, with an integrated carbonator and regenerator system using amine-based solid sorbents. The extent of CO2 capture in the carbonation section and desorption of carbon dioxide in the regeneration section were predicted. Our study showed the potential of continuous carbon capture by amine-based solid sorbents through the circulating fluidized bed CO2 capture unit.
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DEVELOPMENT OF FULLY BIOCOMPATIBLE HYDROGEL NANOPARTICLE FORMULATIONS FOR CONTROLLED-RELEASE DELIVERY OF A WIDE VARIETY OF BIOMOLECULES
Title
DEVELOPMENT OF FULLY BIOCOMPATIBLE HYDROGEL NANOPARTICLE FORMULATIONS FOR CONTROLLED-RELEASE DELIVERY OF A WIDE VARIETY OF BIOMOLECULES
Creator
Borges, Fernando Tancredo Pereira
Date
2020
Description
In recent years, our group has focused on the production of PEGDA-based hydrogel scaffolds and nanoparticles for drug delivery of small...
Show moreIn recent years, our group has focused on the production of PEGDA-based hydrogel scaffolds and nanoparticles for drug delivery of small molecules. However, with recent advances in modern therapeutic treatments, such as protein and genetic engineering, there is an increasing need for the development of drug delivery devices that would be able encapsulate larger molecules. Therefore, the goal of this thesis work was to develop a systematic way to produce fully biocompatible PEGDA-based hydrogel nanoparticle formulations that would be able to encapsulate any size molecule, ranging from small ionic molecules, to peptides and proteins, all the way to large nucleic acids, and deliver it in a controlled manner.The first of part of this work consisted of developing a stable and reproducible process for the production of hydrogel PPi-NPs. Initial studies were done in order to assess the influence of phosphate salts in the polymerization system and it was found that both monophosphate and polyphosphate salts significantly damper the NVP homo-polymerization kinetics, but do not affect the co-polymerization of NVP and PEGDA. Then, emulsion stability studies were done to determine whether phosphate salts affected the stability of the minimeulsion system used in the production of the nanoparticles. Cloud point measurements and droplet size screening measurements showed that by transitioning from a Pi-loaded emulsion system to a PPi-loaded emulsion system, the required HLB of the emulsion shifts by 1.5 points. Upon correction for that shift, a reproducible process for production of PPi-loaded nanoparticles was obtained. A parametric study was then performed to see how the different process parameters affected the different properties of the produced particles. The second part of the work consisted in developing a platform for encapsulation of large to very-large molecules within these hydrogel systems. A new set of equations was developed for better estimation of the interstitial space, available for encapsulation of molecules, of crosslinked polymers that used very high molecular weight crosslinkers and/or high amounts of crosslinker. Upon development of this new set of equations, hydrogel discs were made via photopolymerization in order to validate the equations. By introducing a third monomer, EGA, and varying the molecular weight and concentration of the crosslinker, hydrogels with a wide range of mesh dimensions from 25 to 700 were achieved. These gels were then used to encapsulate 4 different sample molecules of varying molecular weights and size. A new heuristic was developed for encapsulation of non-spherical molecules, where the aspect ratios of the molecule and of the polymer network are considered. By varying the size of the ratios of the dimensions of the hydrogel network to the dimensions of the molecule, significantly different release profiles of small molecules, peptides and oligonucleotides were obtained. Finally, in order to explore different administration routes, the process was transitioning into being fully biocompatible. The organic solvent previously used in the emulsion system was replaced by soybean oil and the surfactants were replaced by a food-grade surfactant, PGPR, to form Bio-Compatible Nanoparticle Emulsions (BCNEs). Qualitative release from the BCNEs was shown. A new method for quantitative measuring of release from BCNE was developed. Release from QK-BCNE was observed up to 46 days, which is unprecedented for sustained-release and revolutionary for the field. A BCNE spreadable ointment formulation was also developed.
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Investigating anti-biofilm and anti-persister activities of natural compounds and antimicrobial proteins
Title
Investigating anti-biofilm and anti-persister activities of natural compounds and antimicrobial proteins
Creator
Jin, Xing
Date
2020
Description
Bacterial biofilm formation is frequently involved in the development of chronic infectious diseases. Inhibiting biofilms is challenging due...
Show moreBacterial biofilm formation is frequently involved in the development of chronic infectious diseases. Inhibiting biofilms is challenging due to their tolerance against conventional antibiotics which are not effective to penetrating biofilm matrix to kill the cells residing in biofilms. Metabolically dormant cells known as persisters are also not eradicated by antibiotic treatment. Therefore, novel antimicrobial drugs that can kill non-growing persisters or inhibit biofilms are needed urgently. Here, we investigate the anti-biofilm and anti-persister activities of new drug candidates including plant extracts, fatty acids and colicins. We firstly screened 50 different plant extracts on enterohemorrhagic E. coli and Listeria monocytogenes, and identified Cancavalia ensiformis-derived lectin Concanavalin A (ConA) inhibits biofilm formation of enterohemorrhagic E. coli and Listeria monocytogenes by binding to carbohydrates on bacterial cell surface. Biofilm results support that ConA lectin can be applied for developing anti-adherent and anti-biofilm agents to control biofilms. Also, fatty acids may be promising candidates as anti-persister or anti-biofilm agents, because some fatty acids exhibit antimicrobial effects. We screened a fatty acid library consisting of 65 different fatty acid molecules for altered persister formation. We found that undecanoic acid, lauric acid, and N-tridecanoic acid inhibited E. coli persister cell formation including enterohemorrhagic E. coli EDL933. These fatty acids were all medium chain saturated forms. Furthermore, the fatty acids repressed EHEC biofilm formation (for example, by 8-fold for lauric acid) without having antimicrobial activity. This study demonstrates that medium chain saturated fatty acids can serve as anti-persister and anti-biofilm agents that may be applied to treat bacterial infections. Colicins, a type of antimicrobial bacteriocins, are considered as a viable alternative of conventional antibiotics due to their unique cell killing mechanisms that can damage cells by pore-forming on the cell membrane, nuclease activity, and cell wall synthesis inhibition. In this study, we utilized cell-free protein synthesis to produce colicins with different modes of action. We optimized the production yield and activity of colicins in cell-free system. Also, we tested effect of cell-free produced colicins on persister cell formation and biofilm formation. We illustrated that colicins kill persister cells and biofilm cells. Moreover, colicins produced from the engineered probiotic E. coli cells, which can be used as a living medicine, specifically and significantly eradicate target biofilms without affecting other bacterial population. Colicins have great potential to be an antibiotic alternative, and engineered probiotic E. coli is a potential candidate for engineered bacterial therapeutics.
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Developing Advanced Materials for Carbon Dioxide Electroreduction to Value-Added Chemicals and Fuels
Title
Developing Advanced Materials for Carbon Dioxide Electroreduction to Value-Added Chemicals and Fuels
Creator
Esmaeilirad, Mohammadreza
Date
2023
Description
Developing highly efficient electrocatalysts for the carbon dioxide reductionreaction (CO2RR) to value-added fuels and chemicals offers a...
Show moreDeveloping highly efficient electrocatalysts for the carbon dioxide reductionreaction (CO2RR) to value-added fuels and chemicals offers a feasible pathway for renewable energy storage and could help mitigate the ever-increasing carbon dioxide (CO2) emissions from human activities. Different catalysts are known to catalyze CO2RR in aqueous solutions. Most known catalysts are only capable of transferring 2 electrons with needed protons to CO2 producing either carbon monoxide (CO) or formic acid (HCOOH). Copper (Cu) is the only electrocatalytic material that converts CO2 into different types of hydrocarbon products. Additionally, owing to Cu’s natural abundance and low cost, it has been intensively studied for CO2RR for decades. However, the required high input energy (overpotential), low product selectivity towards valuable fuel products, and the lack of long-term stability remain major challenges for Cu-based catalysts. This work aims to develop new materials that produce hydrocarbons at lower overpotentials with higher rates and greater selectivity than current copper catalysts. By implementing a process referred to as the electrocatalyst discovery cycle iterations between predications, catalyst testing, and active site characterization allow for the rational design and discovery of new and improved electrocatalysts for CO2RR. This methodology led to the discovery of different heteroatomic catalysts as low overpotential catalysts for electroreduction of CO2 high energy density hydrocarbon products.
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