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Results for “Conditional rate functions”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Refinements to the Graves–Pitarka Kinematic Rupture Generator, Including a Dynamically Consistent Slip-Rate Function, Applied to the 2019 Mw 7.1 Ridgecrest Earthquake

The main objective of this study is to develop physics–based constraints on the spatiotemporal variation of the slip–rate function using a simplified dynamic rupture model. First, we performed dynamic rupture modeling of the 2019 M w 7.1 Ridgecrest, California, earthquake, to analyze the effects of depth–dependent stress and material friction on slip rate. Then, we used our modeling results to guide refinements to the slip–rate function that were implemented in the Graves–Pitarka kinematic rupture generation technique. The dynamic ruptures were computed on a surface–rupturing, planar strike–slip fault that includes a weak (negative to low–stress–drop) zone in the upper 4 km of the crust. Below the weak zone, we placed high–stress–drop patches designed to mirror the large–slip areas seen in various rupture model inversions of the event. The locations of the high–stress–drop patches and the hypocenter were varied in multiple realizations to investigate how changing the dynamic conditions affected the resulting rupture kinematics, in particular, the slip rate. From these simulations, we observed a systematic change in the shape of the slip–rate function from Kostrov type below the weak zone to a predominantly symmetric shape within the weak zone, along with a depth–dependent reduction of peak slip rate. We generalized these shallow rupture features into a depth–dependent parametric variation of the slip–rate function and implemented it in the Graves–Pitarka kinematic rupture model generator. The performance of the updated kinematic approach was then verified in 0–4 Hz simulations of the M w 7.1 Ridgecrest earthquake, which showed that incorporating the depth–dependent variation in the shape of the slip–rate function improves the fit to the observed near–fault ground motions in the 0.5–3 s period range.

58 GEOSCIENCES↗
DOE OSTI2014

Gasification Characteristics of Coal/Biomass Mixed Fuels

A research project was undertaken that had the overall objective of developing the models needed to accurately predict conversion rates of coal/biomass mixtures to synthesis gas under conditions relevant to a commercially-available coal gasification system configured to co-produce electric power as well as chemicals and liquid fuels. In our efforts to accomplish this goal, experiments were performed in an entrained flow reactor in order to produce coal and biomass chars at high heating rates and temperatures, typical of the heating rates and temperatures fuel particles experience in real systems. Mixed chars derived from coal/biomass mixtures containing up to 50% biomass and the chars of the pure coal and biomass components were subjected to a matrix of reactivity tests in a pressurized thermogravimetric analyzer (TGA) in order to obtain data on mass loss rates as functions of gas temperature, pressure and composition as well as to obtain information on the variations in mass specific surface area during char conversion under kinetically-limited conditions. The experimental data were used as targets when determining the unknown parameters in the chemical reactivity and specific surface area models developed. These parameters included rate coefficients for the reactions in the reaction mechanism, enthalpies of formation and absolute entropies of adsorbed species formed on the carbonaceous surfaces, and pore structure coefficients in the model used to describe how the mass specific surface area of the char varies with conversion. So that the reactivity models can be used at high temperatures when mass transport processes impact char conversion rates, Thiele modulus – effectiveness factor relations were also derived for the reaction mechanisms developed. In addition, the reactivity model and a mode of conversion model were combined in a char-particle gasification model that includes the effects of chemical reaction and diffusion of reactive gases through particle pores and energy exchange between the particle and its environment. This char-particle gasification model is capable of predicting the average mass loss rates, sizes, apparent densities, specific surface areas, and temperatures of the char particles produced when co-firing coal and biomass to the type environments established in entrained flow gasifiers operating at high temperatures and elevated pressures.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Pilgrim : A thermal rate constant calculator and a chemical kinetics simulator

Pilgrim is a program written in Python and designed to use direct dynamics in the calculation of thermal rate constants of chemical reactions by the variational transition state theory (VTST), based on electronic structure calculations for the potential energy surface. Pilgrim can also simulate reaction mechanisms using kinetic Monte Carlo (KMC). For reaction processes with many elementary steps, the rate constant of each of these steps can be calculated by means of conventional transition state theory (TST) or by using VTST. In the current version, Pilgrim can evaluate thermal rates using the canonical version of reaction-path VTST, which requires the calculation of the minimum energy path (MEP) associated with each elementary step or transition structure. Multi-dimensional quantum effects can be incorporated through the small-curvature tunneling (SCT) approximation. These methodologies are available both for reactions involving a single structure of the reactants and the transition state and also for reactions involving flexible molecules with multiple conformations of the reactant and/or of the transition state. For systems with many conformers, the program can evaluate each of the elementary reaction rate constants by multipath canonical VTST or multi-structural VTST. Moreover, the reactant can be unimolecular or bimolecular. Torsional anharmonicity can be incorporated through either the MSTor or the Q2DTor programs. Dual-level calculations are also available in Pilgrim: automatic high-level single-point energies can be used to correct the energy of reactants, transition states, products, and MEP points using the interpolated single-point energies (ISPE) algorithm. When the rate constants of all the chemical processes of interest are known, by means of their calculation using Pilgrim or alternatively through analytical fits to the rate constants as functions of temperature, it is possible to simulate a multistep mechanism under specified laboratory conditions using KMC. Finally, this algorithm allows performing a kinetic simulation to monitor the evolution of each chemical species with time and obtain the product yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Chemical Durability and Dissolution Kinetics of Iodoapatite in Aqueous Solutions

Understanding the long-term release of radionuclides from nuclear waste to the environment is critical for public acceptance and sustainability of nuclear energy. Iodoapatite, a synthetic material similar to mineral vanadinite proposed for radioactive iodine-129 immobilization, is employed in this study as a model system for iodine waste forms and ceramic waste forms in general to understand its long-term chemical durability. Semidynamic leaching experiments were performed in cap-sealed Teflon vessels to evaluate the chemical durability at temperatures from 20 to 90 degrees C and pH values from 4 to 9 using deionized water and pH buffer solutions. The leachates were analyzed using inductively coupled plasma-mass spectrometry. The leached surfaces were examined by X-ray diffraction, scanning electron microscopy, and Raman spectroscopy. Effects of test variables including surface-to-volume ratio, leachant replacement interval, and environmental variables including temperature and pH on the dissolution rate were systematically investigated. The activation energy of the dissolution was 16.9 ± 1.5 kJ/mol for the matrix elements and 34.4 ± 3.9 kJ/mol for the diffusive iodine release. The order of the pH effect on the dissolution rate as a power law exponent was 0.87 ± 0.08. The effect of the surface-to-volume ratio and replacement interval was approximated by a single exponential function rise to maximum. Fully parametrized models were then combined to predict iodine release rate under various conditions. The result suggests that the long-term iodine release is controlled by iodide diffusion when the matrix dissolution rate is very low in near neutral pH solutions and by matrix dissolution when the dissolution rate is high at low pH. The present study demonstrates a mechanistic approach to parametrize models that can be used to evaluate the performance of nuclear waste forms under various disposal environments.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Minimal physical requirements for crystal growth self-poisoning

Self-poisoning is a kinetic trap that can impair or prevent crystal growth in a wide variety of physical settings. In this paper, we use dynamic mean-field theory and computer simulation to argue that poisoning is ubiquitous because its emergence requires only the notion that a molecule can bind in two (or more) ways to a crystal; that those ways are not energetically equivalent; and that the associated binding events occur with sufficiently unequal probability. If these conditions are met then the steady-state growth rate is in general a non-monotonic function of the thermodynamic driving force for crystal growth, which is the characteristic of poisoning. Finally, our results also indicate that relatively small changes of system parameters could be used to induce recovery from poisoning.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dependence of Convective Cloud Microphysical Properties on Environmental Conditions during the TRACER and ESCAPE Field Campaigns: A Synergistic Approach of Observations, Machine Learning and Parcel Models

The sensitivity of convective clouds to aerosols and their interactions with environment, combined with limited observational constraints in parameterizations, introduces significant uncertainties in atmospheric models. Here, this study investigates the dependence of convective cloud microphysical properties on environmental conditions using a synergistic approach that combines unique observations from the TRACER and ESCAPE field campaigns, machine learning techniques, and parcel model simulations with a super-droplet microphysics scheme. A random forest algorithm identifies in-situ vertical velocity (w), temperature (T), and surface fine-mode aerosol mass concentration as the three most important environmental conditions influencing cloud properties including liquid water content (LWC), number concentration for particles with D max < 50 μm (N c ,<50), 50 μm ≤ D max ≤ 3000 μm (N c,50–3000 ), and droplet effective diameter (D e ). Results show that LWC, N c,<50 , and N c,50–3000 significantly increase with w in updrafts. Across w bins, as T decreases, LWC, D e , and N c,50–3000 increase, while N c,<50 decreases, which are closely linked to the distance above cloud bases. Warmer cloud bases yield higher LWC, greater N c,50–3000 , and smaller N c,<50 , while polluted environments produce greater N c,<50 . Parcel model simulations successfully replicate these observed dependencies. The simulation results indicate that warmer cloud bases enhance condensation generating larger droplets, and differences in droplet sizes are then amplified through collision-coalescence, resulting in a greater N c,50–3000 . Polluted conditions result in a greater N c,<50 primarily due to enhanced cloud condensation nuclei activation despite increased collision-coalescence rates compared to pristine conditions. This study provides observed quantitative patterns characterizing cloud microphysical properties as a function of key environmental parameters, offering valuable constraints for improving physics parameterizations and numerical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Reactive transport modelling of cement paste leaching in brines

We propose and analyse a unified reactive transport model for leaching of cement paste in brines, with and without CO{sub 2}. We investigate the impact of the boundary conditions on the rate of propagation of the reaction. In agreement with experiments, we observe distinct mechanisms as a function of the pH and the CO{sub 2} concentration of the leaching brine. In particular, clogging is observed at intermediate concentration of CO{sub 2} while higher concentration accelerates the reaction. In addition, we leverage the flexibility of the simulator to explore the impact of different models on the simulations. In particular, aqueous species, phase assemblage and diffusion coefficient model are varied. We demonstrate that in order to be able to obtain quantitative predictions, it is important to accurately capture the feedback between chemical reactions, microstructure and macroscopic transport parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Upscaling Calcite Growth Rates from the Mesoscale to the Macroscale

Quantitative prediction of mineral reaction rates in the subsurface remains a daunting task partly because a key parameter for macroscopic models, the reactive site density, is poorly constrained. Here we report atomic force microscopy (AFM) measurements on the calcite surface of monomolecular step densities, treated as equivalent to the reactive site density, as a function of aqueous calcium-to-carbonate ratio and saturation index. Data for the obtuse step orientation are combined with existing step velocity measurements to generate a model that predicts overall macroscopic calcite growth rates. The model is quantitatively consistent with several published macroscopic rates under a range of alkaline solution conditions, particularly for two of the most comprehensive data sets without the need for additional fit parameters. The model reproduces peak growth rates and its functional form is simple enough to be incorporated into reactive transport or other macroscopic models designed for predictions in porous media. However, it currently cannot model equilibrium, pH effects, and may overestimate rates at high aqueous calcium-to-carbonate ratios. The discrepancies in rates at high calcium-to-carbonate ratios may be due to differences in pre-treatment, such as exposing the seed material to SI 1.0 to generate/develop growth hillocks, or other factors.

Bracco, Jacquelyn N.↗
DOE OSTI2012

Mathematical modeling of cold cap

The ultimate goal of studies of cold cap behavior in glass melters is to increase the rate of glass processing in an energy-efficient manner. Regrettably, mathematical models, which are ideal tools for assessing the responses of melters to process parameters, have not paid adequate attention to the cold cap. In this study, we consider a cold cap resting on a pool of molten glass from which it receives a steady heat flux while temperature, velocity, and extent of conversion are functions of the position along the vertical coordinate. A one-dimensional (1D) mathematical model simulates this process by solving the differential equations for mass and energy balances with appropriate boundary conditions and constitutive relationships for material properties. The sensitivity analyses on the effects of incoming heat fluxes to the cold cap through its lower and upper boundaries show that the cold cap thickness increases as the heat flux from above increases, and decreases as the total heat flux increases. We also discuss the effects of foam, originating from batch reactions and from redox reactions in molten glass and argue that models must represent the foam layer to achieve a reliable prediction of the melting rate as a function of feed properties and melter conditions.

Pokorny, Richard↗
DOE OSTI2011

PHOTON-INDUCED EVOLUTIONARY RATES OF LiHe{sup +} ({sup 1}{Sigma}{sup +}) IN EARLY UNIVERSE FROM ACCURATE QUANTUM COMPUTATIONS

The radiative association rates for the formation of LiHe{sup +} molecules in their ground electronic state have been calculated employing an accurate ab initio potential energy curve and the dipole moment function. The enhancement of this rate, which may arise from stabilizing emissions stimulated by the cosmic background radiation field, has also been calculated and analyzed in the context of early universe conditions. Direct photodissociation processes have also been studied using local thermal equilibrium cross sections and rates are reported for temperatures between 600 and 9000 K. These photochemical processes are in turn analyzed and discussed as a function of the redshift z that is expected to operate in the early universe chemical kinetics. All data suggest very low residual abundances of this molecule and therefore its marginal role within early universe chemistry.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2016

Pressure dependence of carbonate exchange with [NpO 2 (CO 3 ) 3 ] 4– in aqueous solutions

Here, the rates of ligand exchange into the geochemically important [NpO 2 (CO 3 ) 3 ] 4– aqueous complex are measured as a function of pressure in order to complement existing data on the isostructural [UO 2 (CO 3 ) 3 ] 4– complex. Experiments are conducted at pH conditions where the rate of exchange is independent of the proton concentration. Unexpectedly, the experiments show a distinct difference in the pressure dependencies of rates of exchange for the uranyl and neptunyl complexes.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2018

Fluid Flow, Dissolution, and Mixing Phenomena in Argon-Stirred Steel Ladles

In the current study, the multiphase fluid flow in argon-stirred steel ladles is simulated using an Eulerian–Lagrangian two-phase approach. The momentum source and the turbulent kinetic energy source due to the motion of the bubble are considered for the liquid phase. Argon bubbles are treated as discrete phase particles, and the interfacial forces between the bubbles and the liquid phase; the dependence of the gas density and the bubble diameter on the temperature and the static pressure; and the bubble size distribution are considered. When the fluid flow reaches the quasi-steady state, the ferroalloy melting and mixing phenomena is also modeled. The melting time and the trajectory length of each ferroalloy particle are recorded using a user-defined function (UDF). Local mixing time is predicted in the entire computational domain by checking the mixing criteria in every cell. The effects of gas flow rate, porous plug location, and separation angle of two porous plugs on the fluid flow and the mixing phenomena are investigated. The results show that the flow intensity increases, and the mixing time decreases with the increasing gas flow rate. The optimal porous plug’s radial position with one porous plug is 0.50R for its best mixing condition. When two porous plugs are adopted, the separation angle of 90 deg is recommended to improve the flow field and mixing phenomena.

42 ENGINEERING↗
DOE OSTI2015

Impact of deposition conditions on the crystallization kinetics of amorphous GeTe films

The speed at which phase change memory devices can operate depends strongly on the crystallization kinetics of the amorphous phase. To better understand factors that affect the crystallization rate, we have investigated in this paper crystallization of GeTe films as a function of their deposition temperatures and deposition rates, using X-ray synchrotron radiation and Raman spectroscopy. As-deposited films were found to be fully amorphous under all conditions, even though films deposited at higher temperatures and lower rates experienced lower effective quench rates. Non-isothermal transformation curves show that the apparent crystallization temperature of GeTe films decreases with increasing deposition temperature and decreasing deposition rate. It was found that this correlates with a decrease in the activation energy for nucleation (calculated using Kissinger’s analysis), while the activation energy for crystal growth remained unaffected. Finally, from Raman spectroscopy measurements, it was found that increasing the deposition temperature or decreasing the deposition rate, and therefore the effective quench rate, reduces the number of homopolar Te–Te bonds and thereby reduces the barrier to crystal nucleation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Multiscale modeling of fission gas behavior in U 3 Si 2 under LWR conditions

In this work, we present a model of fission gas behavior in U 3 Si 2 under light water reactor (LWR) conditions for application in engineering fuel performance codes. The model includes components for intra-granular and inter-granular behavior of fission gases. The intra-granular component is based on cluster dynamics and computes the evolution of intra-granular fission gas bubbles and swelling coupled to gas diffusion to grain boundaries. The inter-granular component describes the evolution of grain-boundary fission gas bubbles coupled to fission gas release. Given the lack of experimental data for U 3 Si 2 under LWR conditions, the model is informed with parameters calculated via atomistic simulations. In particular, we derive fission gas diffusivities through density functional theory calculations, and the re-solution rate of fission gas atoms from intra-granular bubbles through binary collision approximation calculations. Further, the developed model is applied to the simulation of an experiment for U 3 Si 2 irradiated under LWR conditions available from the literature. Results point out a credible representation of fission gas swelling and release in U 3 Si 2 . Finally, we perform a sensitivity analysis for the various model parameters. Based on the sensitivity analysis, indications are derived that can help in addressing future research on the characterization of the physical parameters relative to fission gas behavior in U 3 Si 2 . The developed model is intended to provide a suitable infrastructure for the engineering scale calculation of fission gas behavior in U 3 Si 2 that exploits a multiscale approach to fill the experimental data gap and can be progressively improved as new lower-length scale calculations and validation data become available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Performance Analysis and Limiting Parameters of Cross-flow Membrane-based Liquid-desiccant Air Dehumidifiers

We report that to dehumidify a humid air stream, existing air conditioning (AC) systems substantially overcool the outdoor humid air below its dew point, thereby significantly reducing energy efficiency. Directly capturing humidity, membrane-based liquid-desiccant dehumidification systems separate sensible and latent cooling (SSLC) loads and thus offer a promising pathway for a high-performance AC solution. Design of an energy-efficient SSLC-AC system, however, rests largely on detailed understating of the dehumidification process. While some studies have identified the dehumidification process mainly depends on membrane characteristics, other studies have argued that the process is limited by desiccant liquid or alternatively air thermo-hydraulic physics for typical humid climate conditions. The present study examines performance and physics of the membrane-based liquid-desiccant dehumidification process over a wide range of climate conditions through a novel 3D, two-phase, multi-species CFD model. Decoupling the thermodynamic and hydraulic effects, the study reveals that the dehumidification rate is a linear function of the water vapor pressure potential ($J=α ΔP$) summarizing the system's thermodynamic state. The slope of the curve (i.e., α) depends on hydraulic transport characteristics of the membrane pores, air stream, and desiccant solution. More importantly, it was found that the air dehumidification process is mainly limited by the air-side transport physics for thin liquid-desiccant films and commonly used porous superhydrophobic membranes. Additionally, results show that, depending on ambient/desiccant conditions and physical dehumidifier characteristics, energy effectiveness and dehumidification rate vary from 13 to 34% and from 0.13 to 1.4 g m -2 s -1 , respectively. Therefore, the present study allows to efficiently design future SSLC-based AC systems exhibiting high performance energy metrics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Small-scale flow topologies in decaying isotropic turbulence laden with finite-size droplets

The topology of the fine-scale motions in decaying isotropic turbulence laden with droplets of super-Kolmogorov size is investigated using results from direct numerical simulations. The invariants of the velocity-gradient, rate-of-strain, and rate-of-rotation tensors are computed in the carrier phase. The joint probability density functions of the invariants are calculated and conditioned on different distances from the droplet surface. The results show that outside the viscous region near the interface, the flow topologies favor stable focus/stretching and unstable node/saddle/saddle structures, which is in agreement with those found in canonical homogeneous isotropic turbulence. Inside the viscous layer at the droplet surface, the flow topologies shift from a preference for high-enstrophy/low-dissipation motions to favoring low-enstrophy/high-dissipation. At the droplet surface, there is a strong tendency for boundary-layer-like and vortex-sheet flow topologies in which the strain and rotation rates are positively correlated. Furthermore, an interesting observation is that the shapes of the invariant distributions at the droplet surface are remarkably similar to those reported in the viscous sublayer of turbulent wall-bounded flows. Also, the results show that the smallest hydrodynamic length scale of the carrier fluid turbulence is located at the droplet interface and that this length scale is two to three times smaller than that of the surrounding bulk flow. From a computational viewpoint, this suggests a more stringent spatial resolution requirement for the direct numerical simulation of finite-size droplets in isotropic turbulence than its single-phase counterpart.

42 ENGINEERING↗
DOE OSTI2019

Metalearners for estimating heterogeneous treatment effects using machine learning

There is growing interest in estimating and analyzing heterogeneous treatment effects in experimental and observational studies. We describe a number of metaalgorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate the conditional average treatment effect (CATE) function. Metaalgorithms build on base algorithms—such as random forests (RFs), Bayesian additive regression trees (BARTs), or neural networks—to estimate the CATE, a function that the base algorithms are not designed to estimate directly. We introduce a metaalgorithm, the X-learner, that is provably efficient when the number of units in one treatment group is much larger than in the other and can exploit structural properties of the CATE function. For example, if the CATE function is linear and the response functions in treatment and control are Lipschitz-continuous, the X-learner can still achieve the parametric rate under regularity conditions. We then introduce versions of the X-learner that use RF and BART as base learners. In extensive simulation studies, the X-learner performs favorably, although none of the metalearners is uniformly the best. In two persuasion field experiments from political science, we demonstrate how our X-learner can be used to target treatment regimes and to shed light on underlying mechanisms. A software package is provided that implements our methods.

42 ENGINEERING↗