Development of an efficient method for simulating fixed-bed adsorption dynamics using Ideal Adsorbed Solution Theory

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016von M. Sc. Héctor Octavio Rubiera LandaLiteraturverzeichnis: Seite 195-22

Experimental and Theoretical Investigations in Solid Phase<br /> Reaction Kinetics and Noncovalent Interactions in Water

Factors affecting reaction rates in polystyrene beads used in solid phase organic synthesis have been studied. The role of diffusion and reagent partitioning has been examined theoretically and experimentally. Both of these factors have been found to influence the reaction kinetics of common solid phase organic synthesis reactions. A mathematical model to analyze a simple bimolecular reaction inside a bead has been developed and successfully applied to the experimental data to obtain quantitative information on the influence of diffusion and reagent partitioning on the reaction rates. The effects of diffusion generally increase with the size and decreased swelling of the beads. Under many common reaction conditions, however, these effects may not be very significant. General guidelines to identify these conditions have been developed. A water-soluble torsion balance to study noncovalent interactions in aqueous media has been synthesized. The folding energies of new balances were found to be higher in water than in organic solvents. This increase can be partially attributed to hydrophobic forces. Aggregation and micelle formation were found to increase folding in water, indicating differences between microscopic and mesoscopic hydrophobic effects. The experimental data have been analyzed in the context of the Lum, Chandler and Weeks theory of hydrophobicity and evidences in its favor have been found. The hydrophobic response of a fluoromethyl group was found to be similar to a methyl group in two complementary torsion balances.<br /

Mathematical analysis, scaling and simulation of flow and transport during immiscible two-phase flow

Fluid flow and transport in fractured geological formations is of fundamental socio-economic importance, with applications ranging from oil recovery from the largest remaining hydrocarbon reserves to bioremediation techniques. Two mechanisms are particularly relevant for flow and transport, namely spontaneous imbibition (SI) and hydrodynamic dispersion. This thesis investigates the influence of SI and dispersion on flow and transport during immiscible two-phase flow. We make four main contributions. Firstly, we derive general, exact analytic solutions for SI that are valid for arbitrary petrophysical properties. This should finalize the decades-long search for analytical solutions for SI. Secondly, we derive the first non-dimensional time for SI that incorporates the influence of all parameters present in the two-phase Darcy formulation - a problem that was open for more than 90 years. Thirdly, we show how the growth of the dispersive zone depends on the flow regime and on adsorption. To that end we derive the first known set of analytical solutions for transport that fully accounts for the effects of capillarity, viscous forces and dispersion. Finally, we provide numerical tools to investigate the influence of heterogeneity by extending the higher order finite-element finite-volume method on unstructured grids to the case of transport and two-phase flow

Surface Energy Heterogeneity Mapping of Pharmaceutical Solids by Inverse Gas Chromatography

The surface energetics of model pharmaceutical powders, were D-mannitol (Ph Eur Pearlitol® 160C, Roquette, France), Racemic Ibuprofen (2-(4-isobutylphenyl)propionic acid) (Shasun, London, U.K.), Aspirin (acetyl salicyclic acid) (Sigma-Aldrich, Poole, U.K.) and Paracetamol (p-hydroxyacetanilide) (98% Sigma-Aldrich, St. Louis, MO) were evaluated using a Finite Dilution Inverse Gas Chromatography FD-IGC technique. This yielded heterogeneous surface energy distributions, which provided a continuum of energies with surface coverage. These measurements were then analysed using novel computational methods of deconvolution, to better understand the effects of heterogeneity on the fundamental site contributions to surface energetics. The modelling approach developed branches into several components: Dispersive and Specific Energetics Modelling. The Dispersive component further expanded to Iterative and Analytical forms, with extensions to both. Physical mixtures of heterogeneous unsilanised and homogeneous Methyl-silane modified Mannitol, in both blended and unblended configurations, as well as blended mixtures of two homogeneous species, Methyl-silane and Fluoro-silane modified Mannitol, were measured to investigate the effect of mixing on surface energetics measured by FD-IGC. Mannitol was used as its functionalisation allowed for the production of markedly different energy profiles with a negligible effect on surface area and mechanical properties allowing for accurate knowledge of the amount of each surface used. The effect of mixed surface chemistry was also investigated to further understand the root cause of energetic heterogeneity measured by FD-IGC, this was achieved by the dual species silanisation of Mannitol using both Methyl- and Fluoro-Silane species, this was found to produce a heterogeneity distribution bound between the energies of the two silane species used in isolation. Further, this was investigated by the induction of a heterogeneity in a homogeneous polymeric material, Polyethylene, through surface modification with Sulfuric Acid. Finally the computational approaches developed were applied to the 3 polymorphic forms of a common pharmaceutical excipient Mannitol to investigate the effects of polymorphism on surface energetics. This showed that the different polymorphs exhibit extremely different energetic behaviour, further results for a mixed-polymorph suggest that it may be possible to infer energetic contributions of unknown quantities. Such information can be used to possibly screen for unwanted polymorphic contributions and also to find more appropriate polymorphic forms for pharmaceutic uses in terms of adhesive and dissolution properties as affected by surface energetics.Open Acces

Developing Multi-Scale Models for Water Quality Management in Drinking Water Distribution Systems

Drinking water supply systems belong to the group of critical infrastructure systems that support the socioeconomic development of our modern societies. In addition, drinking water infrastructure plays a key role in the protection of public health by providing a common access to clean and safe water for all our municipal, industrial, and firefighting purposes. Yet, in the United States, much of our national water infrastructure is now approaching the end of its useful life while investments in its replacement and rehabilitation have been consistently inadequate. Furthermore, the aging water infrastructure has often been operated empirically, and the embracement of modern technologies in infrastructure monitoring and management has been limited. Deterioration of the water infrastructure and poor water quality management practices both have serious impacts on public health due to the increased likelihood of contamination events and waterborne disease outbreaks. Water quality reaching the consumers’ taps is largely dependent on a group of physical, chemical, and biological interactions that take place as the water transports through the pipes of the distribution system and inside premise plumbing. These interactions include the decay of disinfectant residuals, the formation of disinfection by-products (DBPs), the corrosion of pipe materials, and the growth and accumulation of microbial species. In addition, the highly dynamic nature of the system’s hydraulics adds another layer of complexity as they control the fate and transport of the various constituents. On the other hand, the huge scale of water distribution systems contributes dramatically to this deterioration mainly due to the long transport times between treatment and consumption points. Hence, utilities face a considerable challenge to efficiently manage the water quality in their aging distribution systems, and to stay in compliance with all regulatory standards. By integrating on-line monitoring with real-time simulation and control, smart water networks offer a promising paradigm shift to the way utilities manage water quality in their systems. Yet, multiple scientific gaps and engineering challenges still stand in the way towards the successful implementation of such advanced systems. In general, a fundamental understanding of the different physical, chemical, and biological processes that control the water quality is a crucial first step towards developing useful modeling tools. Furthermore, water quality models need to be accurate; to properly simulate the concentrations of the different constituents at the points of consumption, and fast; to allow their implementation in real-time optimization algorithms that sample different operational scenarios in real-time. On-line water quality monitoring tools need be both reliable and inexpensive to enable the ubiquitous surveillance of the system at all times. The main objective of this dissertation is to create advanced computational tools for water quality management in water distribution systems through the development and application of a multi-scale modeling framework. Since the above-mentioned interactions take place at different length and time scales, this work aims at developing computational models that are capable of providing the best description of each of the processes of interest by properly simulating each of its underlying phenomena at its appropriate scale of resolution. Molecular scale modeling using tools of ab-initio quantum chemical calculations and molecular dynamics simulations is employed to provide detailed descriptions of the chemical reactions happening at the atomistic level with the aim of investigating reaction mechanisms and developing novel materials for environmental sensing. Continuum scale reactive-transport models are developed for simulating the spatial and temporal distributions of the different compounds at the pipe level considering the effects of the dynamic hydraulics in the system driven by the spatiotemporal variability in water demands. System scale models are designed to optimize the operation of the different elements of the system by performing large-scale simulations coupled with optimization algorithms to identify the optimal operational strategies as a basis for accurate decision-making and superior water quality management. In conclusion, the computational models developed in this study can either be implemented as stand-alone tools for simulating the fundamental processes dictating the water quality at different scales of resolution, or be integrated into a unified framework in which information from the small scale models are propagated into the larger scale models to render a high fidelity representation of these processes

Advances in Model-based Downstream Process Development

This thesis consists of nine publications and manuscripts that focus on different aspects of chromatography modeling, model calibration and model-based process development. The first four manuscripts present results generated with novel computational methods, the following five are case studies of model-calibration and process optimization

Modeling single-phase flow and solute transport across scales

textFlow and transport phenomena in the subsurface often span a wide range of length (nanometers to kilometers) and time (nanoseconds to years) scales, and frequently arise in applications of CO₂ sequestration, pollutant transport, and near-well acid stimulation. Reliable field-scale predictions depend on our predictive capacity at each individual scale as well as our ability to accurately propagate information across scales. Pore-scale modeling (coupled with experiments) has assumed an important role in improving our fundamental understanding at the small scale, and is frequently used to inform/guide modeling efforts at larger scales. Among the various methods, there often exists a trade-off between computational efficiency/simplicity and accuracy. While high-resolution methods are very accurate, they are computationally limited to relatively small domains. Since macroscopic properties of a porous medium are statistically representative only when sample sizes are sufficiently large, simple and efficient pore-scale methods are more attractive. In this work, two Eulerian pore-network models for simulating single-phase flow and solute transport are developed. The models focus on capturing two key pore-level mechanisms: a) partial mixing within pores (large void volumes), and b) shear dispersion within throats (narrow constrictions connecting the pores), which are shown to have a substantial impact on transverse and longitudinal dispersion coefficients at the macro scale. The models are verified with high-resolution pore-scale methods and validated against micromodel experiments as well as experimental data from the literature. Studies regarding the significance of different pore-level mixing assumptions (perfect mixing vs. partial mixing) in disordered media, as well as the predictive capacity of network modeling as a whole for ordered media are conducted. A mortar domain decomposition framework is additionally developed, under which efficient and accurate simulations on even larger and highly heterogeneous pore-scale domains are feasible. The mortar methods are verified and parallel scalability is demonstrated. It is shown that they can be used as “hybrid” methods for coupling localized pore-scale inclusions to a surrounding continuum (when insufficient scale separation exists). The framework further permits multi-model simulations within the same computational domain. An application of the methods studying “emergent” behavior during calcite precipitation in the context of geologic CO₂ sequestration is provided.Petroleum and Geosystems Engineerin