21 research outputs found
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 CO<sub>2</sub> Membrane Separations
We
have conducted large-scale screening of zeolite materials for
CO<sub>2</sub>/CH<sub>4</sub> and CO<sub>2</sub>/N<sub>2</sub> 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
CO<sub>2</sub> 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 CO<sub>2</sub> is retained while CH<sub>4</sub> or N<sub>2</sub> 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
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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 CO<sub>2</sub> Force Fields for Prediction of Adsorption Properties in All-Silica Zeolites
We
present a systematic and comprehensive investigation of available
CO<sub>2</sub> 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