Numerical Analysis of the Film Cooling Effectiveness on a Highly Loaded Low Pressure Turbine Blade in Conjunction with Endwall Effects

This thesis is a numerical investigation of the flow development of film coolant injected from a turbine blade with considerations to the effects of the passage vortex. By studying the film cooling effectiveness of a low pressure turbine blade subjected to film cooling parameters such as the compound angle injection, Density Ratio, and Blowing Ratio are varied to understand the impact that these parameters have on the passage vortex and film cooling effectiveness in the near endwall region where the passage vortex effects are most prominent. Film Cooling is important in this region as the passage vortex region of a blade is susceptible to high heat transfer and thermal stresses, which can greatly reduce the life cycle of a turbine blade. For this study, a special blade was designed that has a total of 605 holes distributed along 13 different rows on the blade surfaces. 6 rows cover the suction side, 6 other rows cover the pressure side and one last row feeds the leading edge. There are six coolant cavities inside the blade. Each cavity is connected to one row on either sides of the blade, except for the closest cavity to leading edge since it is connected to the leading edge row as well. By using ANSYS CFX, a RANS based solver as a computational platform, the study first compared to an experimental benchmark to understand the deficiencies of the numerical simulation, in that the velocity fluctuations were overpredicted in the boundary layer, thus effecting the prediction of mass, momentum, and energy transport. Secondly, in varying the different parameters the interaction of the film cooling vortices and passage vortex is studied. The development of the film cooling iii vortices with varying parameters and the effects due to the passage vortex in the near endwall region is identified for each parameter. Ultimately, the passage vortex, displaced coolant away from the endwall at the same rate as the vorticity magnitude and size of the passage vortex is much larger than that produced from film cooling

On the Equivalence of Schemes for Simulating Bilayers at Constant Surface Tension

Lipid bilayers are simulated using flexible simulation cells in order to allow for relaxations in area per lipid as bilayer content and temperature are varied. We develop a suite of Monte Carlo (MC) moves designed to generate constant surface tension γ and constant pressure <i>P</i> and find that the <i>NPT</i> partition function proposed by Attard [<i>J. Chem. Phys.</i> <b>1995</b>, <i>103</i>, 9884–9885] leads to an <i>NP</i>γ<i>T</i> partition function with a form invariant to choice of independent shape variables. We then compare this suite of MC moves to <i>NP</i>γ<i>T</i> MC moves previously employed in our group as well as a pair of MC moves designed to replicate the <i>NP</i>_∥<i>P</i>_⊥<i>T</i> “ensemble” often used in molecular dynamics simulations to yield zero surface tension and constant pressure. A detailed analysis of shape fluctuations in a small bilayer system reveals that the two latter MC move sets are different from one another as well as from our new suite of MC moves, as justified by careful analysis of the partition functions. However, the study of a larger bilayer system reveals that, for practical purposes for this system, all six MC move sets are comparable to one another

Ligand-Assisted Enhancement of CO₂ Capture in Metal–Organic Frameworks

Using density functional theory with a van der Waals-corrected functional, we elucidate how CO₂ binds to a novel “BTT-type” metal–organic framework (MOF) featuring open metal centers. We show that CO₂ binds most favorably to open metal cation sites, but with an adsorption energy that can be three times more sensitive to the choice of the bridging ligand than to metal cation choice. A strong, three-site interaction between CO₂ and the open-metal site is predicted, with the binding energy enhanced by up to a factor of 2, depending on the ligand. The CO₂-MOF binding can be attributed to a combination of electrostatics and vdW dispersive interactions, both of which are critically sensitive to the local environment, and both of which contribute nearly equally to the overall binding strength. We show that a judicious choice of the organic linker and the metal center allows the binding energy to be tuned from 34.8 kJ/mol (for CaBTTri) to a maximum of 64.5 kJ/mol (MgBTT)

Ligand-Assisted Enhancement of CO₂ Capture in Metal–Organic Frameworks

Using density functional theory with a van der Waals-corrected functional, we elucidate how CO₂ binds to a novel “BTT-type” metal–organic framework (MOF) featuring open metal centers. We show that CO₂ binds most favorably to open metal cation sites, but with an adsorption energy that can be three times more sensitive to the choice of the bridging ligand than to metal cation choice. A strong, three-site interaction between CO₂ and the open-metal site is predicted, with the binding energy enhanced by up to a factor of 2, depending on the ligand. The CO₂-MOF binding can be attributed to a combination of electrostatics and vdW dispersive interactions, both of which are critically sensitive to the local environment, and both of which contribute nearly equally to the overall binding strength. We show that a judicious choice of the organic linker and the metal center allows the binding energy to be tuned from 34.8 kJ/mol (for CaBTTri) to a maximum of 64.5 kJ/mol (MgBTT)

Molecular Simulation Study of the Competitive Adsorption of H₂O and CO₂ in Zeolite 13X

The presence of H₂O in postcombustion gas streams is an important technical issue for deploying CO₂-selective adsorbents. Because of its permanent dipole, H₂O can interact strongly with materials where the selectivity for CO₂ is a consequence of its quadrupole interacting with charges in the material. We performed molecular simulations to model the adsorption of pure H₂O and CO₂ as well as H₂O/CO₂ mixtures in 13X, a popular zeolite for CO₂ capture processes that is commercially available. The simulations show that H₂O reduces the capacity of these materials for adsorbing CO₂ by an order of magnitude and that at the partial pressures of H₂O relevant for postcombustion capture, 13X will be essentially saturated with H₂O

CO₂ Capture by Metal–Organic Frameworks with van der Waals Density Functionals

We use density functional theory calculations with van der Waals corrections to study the role of dispersive interactions on the structure and binding of CO₂ within two distinct metal–organic frameworks (MOFs): Mg-MOF74 and Ca-BTT. For both classes of MOFs, we report calculations with standard gradient-corrected (PBE) and five van der Waals density functionals (vdW-DFs), also comparing with semiempirical pairwise corrections. The vdW-DFs explored here yield a large spread in CO₂–MOF binding energies, about 50% (around 20 kJ/mol), depending on the choice of exchange functional, which is significantly larger than our computed zero-point energies and thermal contributions (around 5 kJ/mol). However, two specific vdW-DFs result in excellent agreement with experiments within a few kilojoules per mole, at a reduced computational cost compared to quantum chemistry or many-body approaches. For Mg-MOF74, PBE underestimates adsorption enthalpies by about 50%, but enthalpies computed with vdW-DF, PBE+D2, and vdW-DF2 (40.5, 38.5, and 37.4 kJ/mol, respectively) compare extremely well with the experimental value of 40 kJ/mol. vdW-DF and vdW-DF2 CO₂–MOF bond lengths are in the best agreement with experiments, while vdW-C09_x results in the best agreement with lattice parameters. On the basis of the similar behavior of the reduced density gradients around CO₂ for the two MOFs studied, comparable results can be expected for CO₂ adsorption in BTT-type MOFs. Our work demonstrates for this broad class of molecular adsorbate-periodic MOF systems that parameter-free and computationally efficient vdW-DF and vdW-DF2 approaches can predict adsorption enthalpies with chemical accuracy

Addressing Challenges of Identifying Geometrically Diverse Sets of Crystalline Porous Materials

Crystalline porous materials have a variety of uses, such as for catalysis and separations. Identifying suitable materials for a given application can, in principle, be done by screening material databases. Such a screening requires automated high-throughput analysis tools that calculate topological and geometrical parameters describing pores. These descriptors can be used to compare, select, group, and classify materials. Here, we present a descriptor that captures shape and geometry characteristics of pores. Together with proposed similarity measures, it can be used to perform diversity selection on a set of porous materials. Our representations are histogram encodings of the probe-accessible fragment of the Voronoi network representing the void space of a material. We discuss and demonstrate the application of our approach on the International Zeolite Association (IZA) database of zeolite frameworks and the Deem database of hypothetical zeolites, as well as zeolitic imidazolate frameworks constructed from IZA zeolite structures. The diverse structures retrieved by our method are complementary to those expected by emphasizing diversity in existing one-dimensional descriptors, e.g., surface area, and similar to those obtainable by a (subjective) manual selection based on materials’ visual representations. Our technique allows for reduction of large sets of structures and thus enables the material researcher to focus efforts on maximally dissimilar structures

Predicting Local Transport Coefficients at Solid–Gas Interfaces

The regular nanoporous structure make zeolite membranes attractive candidates for separating molecules on the basis of differences in transport rates (diffusion). Since improvements in synthesis have led to membranes as thin as several hundred nanometers by now, the slow transport in the boundary layer separating bulk gas and core of the nanoporous membrane is becoming increasingly important. Therefore, we investigate the predictability of the coefficient quantifying this local process, the surface permeability α, by means of a two-scale simulation approach. Methane tracer-release from the one-dimensional nanopores of an AFI-type zeolite is employed. Besides a pitfall in determining α on the basis of tracer exchange, we, importantly, present an accurate prediction of the surface permeability using readily available information from molecular simulations. Moreover, we show that the prediction is strongly influenced by the degree of detail with which the boundary region is modeled. It turns out that not accounting for the fact that molecules aiming to escape the host structure must indeed overcome two boundary regions yields too large a permeability by a factor of 1.7–3.3, depending on the temperature. Finally, our results have far-reaching implications for the design of future membrane applications

Predicting Local Transport Coefficients at Solid–Gas Interfaces

The regular nanoporous structure make zeolite membranes attractive candidates for separating molecules on the basis of differences in transport rates (diffusion). Since improvements in synthesis have led to membranes as thin as several hundred nanometers by now, the slow transport in the boundary layer separating bulk gas and core of the nanoporous membrane is becoming increasingly important. Therefore, we investigate the predictability of the coefficient quantifying this local process, the surface permeability α, by means of a two-scale simulation approach. Methane tracer-release from the one-dimensional nanopores of an AFI-type zeolite is employed. Besides a pitfall in determining α on the basis of tracer exchange, we, importantly, present an accurate prediction of the surface permeability using readily available information from molecular simulations. Moreover, we show that the prediction is strongly influenced by the degree of detail with which the boundary region is modeled. It turns out that not accounting for the fact that molecules aiming to escape the host structure must indeed overcome two boundary regions yields too large a permeability by a factor of 1.7–3.3, depending on the temperature. Finally, our results have far-reaching implications for the design of future membrane applications

Large-Scale Screening of Zeolite Structures for CO₂ Membrane Separations

We have conducted large-scale screening of zeolite materials for CO₂/CH₄ and CO₂/N₂ membrane separation applications using the free energy landscape of the guest molecules inside these porous materials. We show how advanced molecular simulations can be integrated with the design of a simple separation process to arrive at a metric to rank performance of over 87 000 different zeolite structures, including the known IZA zeolite structures. Our novel, efficient algorithm using graphics processing units can accurately characterize both the adsorption and diffusion properties of a given structure in just a few seconds and accordingly find a set of optimal structures for different desired purity of separated gases from a large database of porous materials in reasonable wall time. Our analysis reveals that the optimal structures for separations usually consist of channels with adsorption sites spread relatively uniformly across the entire channel such that they feature well-balanced CO₂ adsorption and diffusion properties. Our screening also shows that the top structures in the predicted zeolite database outperform the best known zeolite by a factor of 4–7. Finally, we have identified a completely different optimal set of zeolite structures that are suitable for an inverse process, in which the CO₂ is retained while CH₄ or N₂ is passed through a membrane