Three-Dimensional Multiscale Modeling of Dendritic Spacing Selection During Al-Si Directional Solidification
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The quantification of recharge and trans-valley underflow is needed in arid regions to estimate the impacts of new water withdrawals on the water table. However, for mountainous desert areas, such estimates are highly challenging, due to data scarcity, heterogeneous soils, and long residence times. Conventional assessment employs isolated groundwater models configured with simplified uniform estimates of recharge. Here, we employed a data-constrained surface-subsurface process model to provide an ensemble of spatially distributed recharge and underflow estimates using perturbed parameters. Then, the Model-Independent Parameter Estimation and Uncertainty Quantification (PEST) package was used to calibrate the aquifer hydraulic conductivity field in MODFLOW for this ensemble and reject implausible recharge values. This novel dual-model approach, broadly applicable to mountainous arid regions, was designed to maximally exploit available data sources. It can assimilate groundwater head observations, reject unrealistic parameters, and narrow the range of estimated drawdowns due to pumping. We applied this approach to the Chuckwalla basin in California, USA to determine natural recharge. Simulated recharge concentrates along alluvial fans at the mountain fronts and ephemeral washes where run-off water infiltrates. If an evenly distributed recharge was employed as in conventional studies, it would result in regional biases in estimated drawdown and larger uncertainty bounds. Here, we also note that the speed of groundwater recovery does not guarantee sustainability: heavy pumping induces large hydraulic gradients that initially recover quickly when pumping is halted, but the system may not ultimately recover to pre-pumping levels.
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Ceria is an important material for chemical conversion processes in catalysis. Its intrinsic properties as a reducible oxide can be exploited to achieve catalytic selectivity and activity. However, numerous phenomenological characteristics of ceria remain unknown and its active nature is ever slowly being unraveled. Well defined models of ceria (111) are an important way to systematically study these properties and take advantage of new in situ methods that require pristine materials that allow for the interrogation of the most fundamental traits of this material. The ceria-Ru(0001) model is now the most well studied model surface with numerous aspects of its preparation, atomic structure and reactivity studied by several groups. The preparation of CeO x structures oriented with a (111) surface termination can be achieved through molecular beam deposition, facilitating the growth of well-defined nanostructures, microparticles, and films on the Ru(0001) surface. The growth mechanism exploits the epitaxial relationship between CeOx and Ru to form a carpet mode of well oriented layers of Osingle bondCesingle bondO. These models can be studied to unravel the atomic structure and the oxidation state (Ce 4+ and Ce 3+ ), as prepared and under redox conditions (reduction/oxidation) or with reaction using reactants (e.g., H 2 , methanol). Here, we present a discussion of these most recent observations pertaining to the growth mode, arrangement of atoms on the surface, characteristic chemical state, and redox chemistry of the CeO x -Ru surface. As a result, with insights from these studies we propose new strategies to further unravel the chemistry of ceria.
A kinetic analysis of the H 2 reduction of a CuO-Fe 2 O 3 -Al 2 O 3 oxygen carrier in gas phase fueled Chemical Looping Combustion of synthesis gas was utilized to derive particle scale representation. An experimentally driven study was carried out to provide an array of operational data sets for kinetic modelling approaches. The impact of key operational variables on the kinetics of the novel oxygen carrier were examined, with emphasis on the application of reliable phenomena driven particle scale models to describe the reduction behavior. Due to the novel nature of the material, a series of experimental studies were carried out to provide a fundamental understanding of how the material changed as oxygen was depleted from the structure due to reduction with H 2 . This include quantification of the complex mixed metal oxide phase and changes due to lattice oxygen depletion. It was found that H 2 reduction occurs in a multistep process where CuFeAlO 4 → Cu 0+ + FeAl 2 O 4 → Cu 0+ + Fe 0+ + Al 2 O 3 as oxygen is depleted from the structure. This multistep process was successfully emulated through the use of a two interface Grainy pellet model in which reaction (kinetic) control was the main rate limiting step. This is validated through the examination of other potential rate limiting resistances. In conclusion, the model emulates changes in key operation variables with good accuracy.
The design of robust and efficient high-temperature thermochemical reactors and determination of operating conditions are critical steps toward enabling high-efficiency long-duration solar energy storage. This work presents a computational model for the thermal reduction of a metal oxide material (Mg-Mn-O) up to 1450 °C and the coupled complex transport phenomena in a novel tubular thermal reactor design that features the capability for a high extent-of-reduction (high energy storage density) and inherent heat recuperation. A one-dimensional model coupling counter-current gas–solid flow, two-phase heat transfer, thermochemical redox reactions, and species transport in a moving-bed reactor is developed. Simplified versions of the model are validated with published results in the literature for packed beds with both inert and reactive particles; the fully coupled model is also validated with experimental measurements of a moving-bed reactor in terms of local temperatures and oxygen release at the exit. Detailed comparisons on the effects of different boundary conditions in the reaction zone (prescribed wall temperature vs. heat flux conditions) and formulations based on a simple uniform flow assumption vs. plug flow using Ergun equation for gas flow are investigated. The results are compared with experimental measurements, and for all cases, the energy flow components in the reactor system and the thermal to chemical conversion efficiency and overall system efficiency are computed. Finally, the predicted high thermal-to-chemical efficiency ~95% and system efficiency ~30% agree with experimental measurements.
The increasing interest in retrofitting of existing buildings is motivated by the need to make a major contribution to enhancing building energy efficiency and reducing energy consumption and CO2 emission by the built environment. This paper examines the relevance of calibration in model-based analysis to support decision-making for energy and carbon efficiency retrofits of individual buildings and portfolios of buildings. The authors formulate a set of real retrofit decision-making situations and evaluate the role of calibration by using a case study that compares predictions and decisions from an uncalibrated model with those of a calibrated model. The case study illustrates both the mechanics and outcomes of a practical alternative to the expert- and time-intense application of dynamic energy simulation models for large-scale retrofit decision-making under uncertainty.
The modified quasichemical model in the quadruplet approximation (MQMQA) considers the first- and the second-nearest-neighbor coordination and interactions, particularly useful in describing short-range ordering (SRO) in complex liquids such as molten salts, slag in metal processing, and electrolytic solutions. Here, the present work implements the MQMQA into the Python based open-source software PyCalphad for thermodynamic calculations. This endeavor facilitates the development of MQMQA-based thermodynamic database with uncertainty quantification (UQ) and propagation (UP) using the open-source software ESPEI. A new database structure based on Extensible Markup Language (XML) is proposed for ESPEI evaluation of MQMQA model parameters. Using the KF-NiF 2 , KCl-NaCl-MgCl 2 , and CaCl 2 -CaF 2 -LiCl-LiF salt systems as examples, we demonstrate the successful implementation of MQMQA in PyCalphad through thermodynamic calculations of Gibbs energy, equilibrium quadruplet fractions, and phase diagram, as well as database development with UQ and UP using ESPEI. Furthermore, as an application of the present implementation, both the LiF–TbF 3 and LiF-HoF 3 systems have been modeled by MQMQA for the first time, which are in good agreement with experiments. The present implementation hence offers an open-source capability for performing CALPHAD modeling for complex liquids with SRO using MQMQA plus a new XML database structure.
With a view to understanding ignition and combustion behaviours in diesel engines, this study investigates several aspects of ignition and combustion of an n-dodecane spray in a high pressure, high temperature chamber, known as Spray A, using data resulting from modelling using the transported probability density function (TPDF) method. The model has been validated comprehensively with good to excellent agreement in our previous work against all available experimental data including for mixture-fraction and velocity fields in non-reacting cases, and flame lift-off length and ignition delay in reacting cases. This good agreement encourages further investigation of the numerical model results to help understand the structure of this flame, which serves to complement the experimental information that is available, which is very limited due to the difficult experimental conditions in which this flame exists. For example, quantitative experimental measurements of local mixture-fraction, temperature, velocity gradients, etc. are not yet possible in reacting cases. Analysis of the model results shows that two-stage ignition is found to occur across the ambient temperature conditions considered: the first stage is rapidly initiated on the lean side where temperatures are high and sequentially moves to richer, cooler conditions. The first stage is extremely resilient to turbulence, occurring in a region of very low Damkohler number. The second stage of ignition occurs first in rich mixtures in a region behind the head of the fuel jet where mixture gradients are low, and appears to be influenced strongly by turbulence. Relative to a homogeneous reactor, it is delayed on the lean side but advanced on the rich side, suggesting entrainment and mixing from the early igniting lean regions into richer mixtures is an important moderator of the ignition process. The second-stage ignition front propagates at very high velocities initially, suggesting it is a sequential ignition moving according to gradients of ignition delay and/or residence time. The flame stabilises however on the lean side in a region of much lower velocity, where turbulent velocity fluctuations are sufficiently high such that turbulent transport influences the propagation. It stabilises in a region of low Damkohler number which implies that a competition of chemistry versus micro-mixing might also be involved in stabilisation. The stabilisation mechanism is investigated by an analysis of the transport budgets, showing the flame is stabilised by autoignition but moderated by turbulent diffusion. Further analysis of the flame index supports this stabilisation mechanism, and demonstrates the simultaneous existence of non-premixed and premixed combustion modes in the same flame. Analysis of the flow fields also reveals that local entrainment and dilatation are important flow features near the flame base. (C) 2015 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
The proliferation of commercial development in U.S. gas-bearing shales helped to drive a twelve-fold increase in domestic gas production between 2000 and 2010, and the nation's gas production rates continue to grow. While shales have long been regarded as a desirable caprock for CCS operations because of their low permeability and porosity, there is increasing interest in the feasibility of injecting CO₂ into shales to enhance methane recovery and augment CO₂ storage. Laboratory work published in recent years observes that shales with adsorbed methane appear to exhibit a stronger affinity for CO₂ adsorption, offering the potential to drive additional CH₄ recovery beyond primary production and perhaps the potential to store a larger volume of CO₂ than the volume of methane displaced. Recent research by the authors on the revenues associated with CO₂-enhanced gas recovery (CO₂-EGR) in gas-bearing shales estimates that, based on a range of EGR response rates, the average revenue per ton of CO₂ for projects managed over both EGR and subsequent storage-only phases could range from $0.50 to $18/tCO₂. While perhaps not as profitable as EOR, for regions where lower-cost storage options may be limited, shales could represent another “early opportunity” storage option if proven feasible for reliable EGR and CO₂ storage. Significant storage potential exists in gas shales, with theoretical CO₂ storage resources estimated at approximately 30-50 GtCO₂. However, an analysis of the comprehensive cost competitiveness of these various options is necessary to understand the degree to which they might meaningfully impact U.S. CCS deployment or costs. This preliminary analysis shows that the degree to which EGR-based CO₂ storage could play a role in commercial-scale deployment is heavily dependent upon the offsetting revenues associated with incremental recovery; modeling the low revenue case resulted in only five shale-based projects, while under the high revenue case, shales accounted for as much as 20 percent of total U.S. storage in the first 20 years of deployment. Interestingly, even in this highest revenue case, there appear to be no negative-cost projects that would be profitable in a no-policy environment as modeled under the assumptions employed. While this reflects a very first look at the potential for shales, it is clear that more laboratory and experimental work are needed to reduce uncertainty in key variables and begin to differentiate and identify high-potential shales for early pilot study.
Water management remains a key challenge in polymer-electrolyte fuel cells. In this paper, a pseudo 3-D (1+2D) model is developed to account better for changes of water management along the channel, as well as verify the possibilities of using differential cells for data capture and translation to integral cell performance. An accurate 2-D membrane-electrode-assembly model is developed for differential cell modeling, which is combined with an along-the-channel stepping algorithm to account for down the channel changes in pressure, temperature, reactant concentration, and relative humidity. Variations in cell performance along the channel due to changes in operating conditions are characterized quantitatively and optimized, where drier feed conditions demonstratively require such an approach. In conclusion, the study identifies gaps between differential and integral cells including those related to flow velocity and highlights the need for better models to understand and link integral cell performance and water management.
In this study, the fire growth and suppression models in FireFOAM were validated for rack-storage commodities consisting of two solid fuels, namely corrugated cardboard boxes and hardwood pallets, which are referred to as Class 2 commodity. Validation experiments included two fire-growth and two fire-suppression configurations with different rack-storage array heights (3 and 5 tiers). In the suppression study, standard-response upright ceiling sprinklers (K-factor of 160 lpm/bar1/2) were used. The time-resolved chemical heat release rates obtained from the experiments were used to validate the fire growth model. The observed sprinkler activations and fire-spread patterns were used to validate the suppression model. This study identified that lateral flame spread is primarily enabled by flames impinging on the commodity's bottom surfaces. This study also showed that obstructions, such as wood pallets, can significantly impede convective and radiative heat transfer to the underside of the commodity, reducing the lateral flame spread rate. Fire-suppression modeling revealed that both surface water transport and lateral flame spread rates are important when predicting fire-suppression behavior. Therefore, as the rack-storage array height increases, so does the water transport time, which results in the fire becoming more difficult to control. Likewise, as the lateral spread rate increases, e.g., as occurs in the absence of wood pallets, fire-suppression also becomes more difficult.
As knock is one of the main factors limiting the efficiency of spark-ignition engines, the introduction of alcohol blends could help to mitigate knock concerns due to the elevated knock resistance of these blends. A model that can accurately predict their autoignition behavior would be of great value to engine designers. The current work aims to develop such a model for alcohol–gasoline blends. First, a mixing rule for the autoignition delay time of alcohol–gasoline blends is proposed. Subsequently, this mixing rule is used together with an autoignition delay time correlation of gasoline and an autoignition delay time cor-relation of methanol in a knock integral model that is implemented in a two-zone engine code. The pre-dictive performance of the resulting model is validated through comparison against experimental measurements on a CFR engine for a range of gasoline–methanol blends. The knock limited spark advance, the knock intensity, the knock onset crank angle and the value of the knock integral at the experimental knock onset have been simulated and compared to the experimental values derived from in-cylinder pressure measurements.
Abstract not provided
Hight-resolved observations of vertical winds remain nearly non-existing over the Himalayas, despite of anticipated crucial role of vertical motions in transporting pollution across the Himalayan hms. The present study analyze the vertical wind observations from surface to 1 km above ground level over Manora Peak (29.4° N; 79.5° E; 1958 m ams!) in the Himalaya performed using a Doppler Lidar during the Ganges Valley Aerosol Experiment (GVAX). Vertical wind exhibited a pronounced diurnal variability at Manora Peak comprising of upward motions during the daytime (05-10 UT) and downward motions during nighttime typical of a mountainvalley system. Mean vertical wind speeds are observed to be varying from -0.8 to +0.8 ms- 1 during the study period with a variance of 0.1-1.5 m2s·2, which is attributed to the thermally driven turbulence. Mean vertical winds are observed to be stronger in the Doppler Lidar profiles above Manora Peak (-0_8 to 0.8 ms- 1) as compared to near surface measurements at this station using an ultrasonic anemometer ( -0.4 to 0.4 ms - 1 ), and low altitude stations in India. Daytime vertical wind speeds are observed to be higher during pre-monsoon (0.81 ms- 1), as compared to post-monsoon (0.24 ms- 1) and winter (0.33 ms- 1)_ Average Black Carbon (BC) concentrations are significantly higher during strong upward vertical winds, which indicates efficient transport of polluted air mass from low-altitude regions to the Himalaya. Weather Research and Forecasting (WRF) model reproduces the observed diurnal pattern in the vertical wind at the observation site however the model underestimates the variability.
The Consortium for the Advanced Simulation of Light Water Reactors (CASL), the first Energy Innovation Hub of the Department of Energy, was established in 2010 with the goal of providing modeling and simulation (M&S) capabilities that support and accelerate the improvement of nuclear energy's economic competitiveness and the reduction of spent nuclear fuel volume per unit energy, and all while assuring nuclear safety. To accomplish this requires advances in M&S capabilities in radiation transport, thermal-hydraulics, fuel performance and corrosion chemistry. To focus CASL's R&D, industry challenge problems have been defined, which equate with long standing issues of the nuclear power industry that M&S can assist in addressing. To date CASL has developed a multi-physics “core simulator” based upon pin-resolved radiation transport and subchannel (within fuel assembly) thermal-hydraulics, capitalizing on the capabilities of high performance computing. CASL's fuel performance M&S capability can also be optionally integrated into the core simulator, yielding a coupled multi-physics capability with untapped predictive potential. Material models have been developed to enhance predictive capabilities of fuel clad creep and growth, along with deeper understanding of zirconium alloy clad oxidation and hydrogen pickup. Understanding of corrosion chemistry (e.g., CRUD formation) has evolved at all scales: micro, meso and macro. CFD R&D has focused on improvement in closure models for subcooled boiling and bubbly flow, and the formulation of robust numerical solution algorithms. For multiphysics integration, several iterative acceleration methods have been assessed, illuminating areas where further research is needed. Finally, uncertainty quantification and data assimilation techniques, based upon sampling approaches, have been made more feasible for practicing nuclear engineers via R&D on dimensional reduction and biased sampling. Industry adoption of CASL's evolving M&S capabilities, which is in progress, will assist in addressing long-standing and future operational and safety challenges of the nuclear industry. - Highlights: • Complexity of physics based modeling of light water reactor cores being addressed. • Capability developed to help address problems that have challenged the nuclear power industry. • Simulation capabilities that take advantage of high performance computing developed.
We present an efficient implicit incompressible smoothed particle hydrodynamics (I2SPH) discretization of Navier-Stokes, Poisson-Boltzmann, and advection-diffusion equations subject to Dirichlet or Robin boundary conditions. It is applied to model various two and three dimensional electrokinetic flows in simple or complex geometries. The I2SPH's accuracy and convergence are examined via comparison with analytical solutions, grid-based numerical solutions, or empirical models. The new method provides a framework to explore broader applications of SPH in microfluidics and complex fluids with charged objects, such as colloids and biomolecules, in arbitrary complex geometries.
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