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

Penilaian Karya Ilmiah C-11

Recent experimental work has shown that variations in the confinement of <i>n</i>-butane at Brønsted acid sites due to changes in zeolite framework structure strongly affect the apparent and intrinsic enthalpy and entropy of activation for cracking and dehydrogenation. Quantum chemical calculations have provided good estimates of the intrinsic enthalpies and entropies of activation extracted from experimental rate data for MFI, but extending these calculations to less confining zeolites has proven challenging, particularly for activation entropies. Herein, we report our efforts to develop a theoretical model for the cracking and dehydrogenation of <i>n</i>-butane occurring in a series of zeolites containing 10-ring channels and differing in cavity size (TON, FER, -SVR, MFI, MEL, STF, and MWW). We combine a QM/MM approach to calculate intrinsic and apparent activation parameters, with thermal corrections to the apparent barriers obtained from configurational-bias Monte Carlo simulations, to account for configurational contributions due to global motions of the transition state. We obtain good agreement between theory and experiment for all activation parameters for central cracking in all zeolites. For terminal cracking and dehydrogenation, good agreement between theory and experiment is found only at the highest confinements. Experimental activation parameters, especially those for dehydrogenation, tend to increase with decreasing confinement. This trend is not captured by the theoretical calculations, such that deviations between theory and experiment increase as confinement decreases. We propose that, because transition states for dehydrogenation are later than those for cracking, relative movements between the fragments produced in the reaction become increasingly important in the less confining zeolites

Computing Mixture Adsorption in Porous Materials through Flat Histogram Monte Carlo Methods

Mixture adsorption properties of porous materials are critical to determine their potential as adsorbents in separation applications. Toward the discovery of optimal adsorbents, in silico screening studies typically employ the grand canonical Monte Carlo (GCMC) technique to compute adsorption properties of gas mixtures in materials of interest at a given condition (i.e., composition, total pressure, and temperature) or to compute their adsorption properties for each component, followed by utilizing methods to predict mixture adsorption isotherms. However, the former approach results in the need for repeated calculations when different conditions such as compositions are considered. For the latter, the predictions may involve uncertainties, sometimes originating from the fitting quality to the pure component isotherms, and repeated simulations may also be needed for different temperatures. To this end, this study demonstrates the potential of flat histogram Monte Carlo methods in addressing the abovementioned shortfalls. Specifically, the so-called NVT + W method, first reported by Smit and co-workers, is extended herein to determine the macrostate probability distribution (MPD) of binary mixtures in porous materials. The obtained MPD can be reweighted to any conditions, yielding accurate adsorption isotherms of any desired compositions and temperatures. This approach, denoted as 2D NVT + W, is also compared with the widely adopted ideal adsorbed solution theory (IAST) method, and the former is found to offer more reliable predictions. Overall, the 2D NVT + W approach represents an efficient and effective alternative to compute mixture adsorption isotherms for porous materials, and the obtained MPD can be conveniently reused by peer researchers. A user-friendly Python code is also provided along with this article to employ this method

Computing Mixture Adsorption in Porous Materials through Flat Histogram Monte Carlo Methods

Mixture adsorption properties of porous materials are critical to determine their potential as adsorbents in separation applications. Toward the discovery of optimal adsorbents, in silico screening studies typically employ the grand canonical Monte Carlo (GCMC) technique to compute adsorption properties of gas mixtures in materials of interest at a given condition (i.e., composition, total pressure, and temperature) or to compute their adsorption properties for each component, followed by utilizing methods to predict mixture adsorption isotherms. However, the former approach results in the need for repeated calculations when different conditions such as compositions are considered. For the latter, the predictions may involve uncertainties, sometimes originating from the fitting quality to the pure component isotherms, and repeated simulations may also be needed for different temperatures. To this end, this study demonstrates the potential of flat histogram Monte Carlo methods in addressing the abovementioned shortfalls. Specifically, the so-called NVT + W method, first reported by Smit and co-workers, is extended herein to determine the macrostate probability distribution (MPD) of binary mixtures in porous materials. The obtained MPD can be reweighted to any conditions, yielding accurate adsorption isotherms of any desired compositions and temperatures. This approach, denoted as 2D NVT + W, is also compared with the widely adopted ideal adsorbed solution theory (IAST) method, and the former is found to offer more reliable predictions. Overall, the 2D NVT + W approach represents an efficient and effective alternative to compute mixture adsorption isotherms for porous materials, and the obtained MPD can be conveniently reused by peer researchers. A user-friendly Python code is also provided along with this article to employ this method

Role of Structural Defects in the Water Adsorption Properties of MOF-801

The nanoporous and tunable nature of metal–organic frameworks (MOFs) has made them promising adsorbents for water adsorption applications such as water harvesting and adsorptive heat pumps. In these applications, water adsorption properties in MOFs play a crucial role. However, understanding their structural defects and how defects influence adsorption thermodynamics remains limited to date. In this work, by employing Monte Carlo techniques and first-principle density functional theory calculations, we investigate the effect of defects on the water adsorption properties in MOF-801 structures at an atomic level. Our calculations show that the adsorption isotherm in perfect MOF-801 (without defects) greatly deviates from that measured experimentally. With the introduction of defects with a high density, a reasonably good agreement can be achieved, suggesting that a high defect density in MOF-801 may be responsible for its hydrophilic adsorptive behaviors. Further, water adsorption properties in MOF-801 structures are found to depend on the spatial configuration of defects, and water condensation in nanoporous MOF-801 is identified to occur preferentially along the ⟨110⟩ direction. Detailed structural characteristics (accessible volume, etc.) of MOF-801 structures and the adsorption energetics of water in the frameworks are also studied and correlated with the computed adsorption isotherms. Our findings reveal important insights into the role of defects, offering a microscopic picture to help facilitate the rational design of better MOFs for water adsorption 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

Atomistic Understanding of Zeolite Nanosheets for Water Desalination

Reverse osmosis constitutes a large portion of currently operating commercial water desalination systems. Employing membranes with large water fluxes while maintaining high salt rejection is of central importance in decreasing the associated energy consumption and costs. The ultrathin-film nature of zeolite nanosheets and their versatile pore structures provides great opportunities in desalination. To push forward the development of zeolite nanosheets for water desalination, nonequilibrium molecular dynamics simulations were carried out to systematically study zeolites as RO membranes and establish fundamental structure-performance relationships. We have identified that zeolite nanosheets can achieve a high salt rejection rate close to 100% while allowing nearly 2 orders of magnitude higher water permeability than currently available membranes. Moreover, the effects of the pore density, inclusion of cages, and free energy barrier on water permeability and salt rejection are unraveled, leading to important insights toward the rational design of novel zeolite membranes

Atomistic Investigations of the Effects of Si/Al Ratio and Al Distribution on the Adsorption Selectivity of <i>n</i>‑Alkanes in Brønsted-Acid Zeolites

The adsorption of <i>n</i>-alkanes onto Brønsted-acid sites is a key step in the catalytic cracking of alkanes. Employing configurational-bias Monte Carlo simulations, we have investigated how the ratio of equilibrium adsorption constants for central C–C bonds relative to terminal bonds of <i>n</i>-alkanes (i.e., the adsorption selectivity ratio) in Brønsted-acid zeolites is influenced by the Si/Al ratio and the Al distribution. A new computational approach was implemented, and the developed force field was validated by a comprehensive comparison between simulation results and experimental data for a number of Brønsted-acid zeolites. While the adsorption selectivity seems to be relatively insensitive to the Si/Al ratio, our results reveal that the Al distribution plays a crucial role in determining the adsorption selectivity. Changes in the Al distribution result in a change of as much as 2-fold in the adsorption selectivity ratio for <i>n</i>-hexane. The selectivity generally shows larger variations with respect to Al distribution in zeolites with a larger Si/Al ratio. The two factors identified by this work that substantially influence the selectivity ratio are the siting of Al atoms among T-sites and their spatial proximity, and an atomic-level understanding of each of these effects was achieved. The siting of Al atoms at more or less selective T-sites significantly influences the overall selectivity ratio, and Al atoms in close proximity can synergistically enhance the adsorption of central C–C bonds, leading to a higher selectivity ratio relative to isolated Al atoms. We anticipate that these results will have important implications for future large-scale computational screenings and the development of advanced synthesis approaches to target certain Al distributions in zeolites

Rational Design of Two-Dimensional Hydrocarbon Polymer as Ultrathin-Film Nanoporous Membranes for Water Desalination

Membrane-based water desalination has drawn considerable attention for its potential in addressing the increasingly limited water resources, but progress remains limited due to the inherent constraints of conventional membrane materials. In this work, by employing state-of-the-art molecular simulation techniques, we demonstrated that two-dimensional hydrocarbon polymer membranes, materials that possess intrinsic and tunable nanopores, can provide opportunities as molecular sieves for producing drinkable water from saline sources. Moreover, we identified a unique relationship between the permeation and selectivity for membranes with elliptical pores, which breaks the commonly known trade-off between the pore size and desalination performance. Specifically, increase in the area of elliptical pores with a controlled minor diameter can offer an improved water flux without compromising the ability to reject salts. Water distributions and water dynamics at atomic levels with the potential of mean force profiles for water and ions were also analyzed to understand the dependence of permeation and selectivity on the pore geometry. The outcomes of this work are instrumental to the future development of ultrathin-film reverse osmosis membranes and provide guidelines for the design of membranes with more effective and efficient pore structures

Transferability of CO₂ Force Fields for Prediction of Adsorption Properties in All-Silica Zeolites

We present a systematic and comprehensive investigation of available CO₂ force fields for their predictions of adsorption properties in 156 geometrically diverse zeolite structures. The comparison reveals that a large discrepancy in the predicted properties, by more than 2 orders of magnitude, may exist. Especially, variation predicted by different force fields appears to be more pronounced for zeolites with more confined pore features, which can be attributed to the repulsive characteristics of force fields. The discrepancy especially impacts zeolites that are deemed to be the best materials for carbon capture and sequestration (CCS), indicating that the predictions on the best materials can drastically differ, based on the choice of force fields. To develop accurate and fully transferable force fields, in this work, we show that the inclusion of adsorption uptake at a high-pressure region (or saturation loading), as well as the diffusion coefficient, can be of utmost importance. These properties can be used as indicators for the repulsive behaviors between gas molecules and the framework. Mixture isotherms have also been identified to be potentially useful for the same purpose. Moreover, we have also demonstrated that interaction energies computed by ab initio methods can be useful references to ensure a newly developed force field is capable of describing the energy surface at an atomic level. Overall, the outcomes of this study will be instrumental to the future development of accurate and transferrable force fields, which is critical for future large-scale computational studies