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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Working fluid selection for organic Rankine cycle power generation using hot produced supercritical CO 2 from a geothermal reservoir

Geothermal heat mining simulations using supercritical CO 2 (sCO 2 ) were performed in this research. Working fluid selection criteria for power generation using sCO 2 from a geothermal reservoir are then presented for subcritical, superheated and supercritical organic Rankine cycles (ORCs). Meanwhile, method of working fluid classification for ORC is proposed. To get the most feasible ORC design, this study introduces the concept of “turning point” for isentropic and dry working fluids, as well as minimum turbine inlet temperature for wet working fluids. A thermodynamic model was developed with capabilities to obtain the optimal working fluid mass flow rate, evaporation temperature, superheated temperature, and supercritical pressure, to evaluate the thermal performance of the three ORC approaches using hot produced sCO 2 . With this model, thirty potential working fluids with critical temperatures in the range from 50 to 225 °C were screened for utilizing hot produced sCO 2 considering physical properties, environmental and safety impacts, and thermodynamic performances. Finally, the thermodynamic results were compared for all possible working fluids.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Using AI to build a hydrobiogeochemical soil model

Soil water content is a function of inputs from precipitation and outputs via evaporation, transpiration, lateral flow, and vertical percolation, and is sensitive to biogeochemical processes. As such, soils serve as an ideal integrator of atmospheric, hydrological, and biogeochemical processes affecting the water cycle. In addition, soil water retention capacity, infiltration rates, and hydraulic conductivity can buffer or exacerbate the effects of extreme precipitation events (e.g., flooding, runoff, subsurface transport, erosion, greenhouse gas emissions) and mitigate the impact of droughts and heat waves on land systems (e.g., fire, crop failure). However, integrating water cycle measurements spanning different land atmosphere compartments across scales is a fundamental barrier for numerical model predictability. A significant challenge is that each domain (soil, hydrology, biology, and atmosphere) typically collects different sets of data at different temporal and spatial frequencies/scales, and even different dimensionalities (2D vs 3D). To implement soil as an integrator of the water cycle in land models, we suggest that novel machine learning (ML) tools can be developed to effectively simulate complex landscapes across various domains and scales, extended to regions with sparse or no data. The ultimate goals are to improve predictive understanding of land-atmosphere interactions and to extend the predictability of current Earth System Models (ESMs) through better integration of hydrological and biogeochemical data. We envision a framework in which: (1) ML-aided data reconstructions enable the merger of data sources into a unified geospatial product; (2) automated detection techniques are used to improve the knowledge of complex soil processes and interactions; and (3) this knowledge is leveraged and incorporated into models through AI-based emulators to distinctly connect the land and atmospheric compartments of the water cycle in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A New Mechanistic Model of Nucleation Site Density

The two-fluid model, which is a macroscopic formulation of nucleate boiling systems, still makes use of experimental data or empirical correlations for closure models. The use of empirical correlations outside the range of conditions where they have been developed is questionable, which limits the application of the two-fluid model in the design of new boiling systems. This paper proposes a mechanistic model of nucleation site density, which, along with bubble departure frequency and bubble departure diameter, are key factors in the accurate prediction of evaporation heat flux and vapor generation rate on the heated surface in the two-fluid model formulation. Nucleation originates from cavities on boiling surface. Griffith and Wallis proposed that a nucleation site becomes active when vapor is entrapped inside the cavity and the mouth radius is larger than the minimum cavity size corresponding to the wall superheat. Yang and Kim obtained the probability density function of the cavity mouth radius and the half cone angle through a statistical treatment based on the measured cavities by a scanning electron microscope and a differential interference contrast microscope. Hibiki and Ishii modified the distribution profiles of the size and cone angle of cavities present on the heater surface and proposed a new model which is valid over rather wide range of flow conditions. The existing nucleation site density models are not physically consistent at onset of nucleation, where no boiling occurs even though the models predict a high nucleation site density. The new model developed in this paper took into account the non-uniform temperature in liquid near the wall, which allows one to physically impart the onset of nucleation into the nucleation site density model. The new model was parametrically tested and showed physical consistency at the region near onset of nucleate boiling. The new model was also validated against selected experimental data and good agreement was reached.

42 ENGINEERING↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
DOE OSTI2018

Shallow-to-Deep Transition of Continental Moist Convection: Cold Pools, Surface Fluxes, and Mesoscale Organization

Large-eddy simulation is used to investigate the effects of cold pools driven by rain evaporation on the shallow-to-deep convection transition over land. The physically consistent methodologies are developed to obtain a time-dependent reference ensemble without cold pools and to apply interactive surface heat fluxes without modeling of surface energy and water budgets. Three different simulation ensembles are contrasted. The reference ensemble, in the spirit of one-dimensional single-column models, eliminates cold pools by horizontally homogenizing negative buoyancy production due to rain evaporation. The additional ensembles complement the reference cold-pool-free ensemble by including cold pools and by applying either interactive or prescribed surface fluxes. Contrasting these ensembles suggests possible improvements of convection parameterization in large-scale models of weather and climate. Without cold pools, the reference ensemble preserves key features of buoyancy-driven cellular convection associated with a field of convective plumes, as assumed in a typical convection parameterization. With cold pools, a significant enhancement of surface heat and moisture fluxes and about an hour delay of their daily maximum is simulated. Cold pools enhance near-surface temperature and moisture standard deviations as well as maxima of the near-surface updraft velocity. They also lead to the reduction of cloud lateral entrainment, deeper vertical development of the cloud layer, and a few-times-larger accumulated surface precipitation. Interactive surface fluxes provide a damping mechanism that noticeably suppresses all these effects. Perhaps surprisingly, cold pools do not significantly change the cloud-base convective mass flux that approximately follows the evolution of surface heat fluxes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Falling-film thermosyphons: Application to water harvesting from humid gas streams

Water harvesting from humid gas streams is central to fresh-water production, desalination, and particulate removal from combustion gas streams. Two-phase thermosyphons are well suited for these applications due to their very low thermal resistance, but have several operating limits at the high heat flows required for such applications. This work introduces the falling-film thermosyphon for large-scale condensation applications. Working fluid is pumped to the top of the evaporator to provide the evaporating liquid film on the inner tube wall, rather than by vapor condensation. The flooding, dry-out and pool-boiling limits are eliminated, resulting in significantly higher maximum heat fluxes for the same physical evaporator size. Furthermore, the condenser no longer needs to be located vertically above the evaporator, which allows for a standard steam condenser to be used. A model for the condensation process in humid air was developed that estimates the fluid and heat transfer and is confirmed experimentally. Further benefits include the use of a high-thermal-conductivity polymer material for the evaporator section to minimize corrosion, and the ability to impose a temperature boundary condition on the evaporator, which is made possible due to the elimination of a liquid pool.

42 ENGINEERING↗
DOE OSTI2022

Reconciling and Improving Formulations for Thermodynamics and Conservation Principles in Earth System Models (ESMs)

Abstract This paper provides a comprehensive derivation of the total energy equations for the atmospheric components of Earth System Models (ESMs). The assumptions and approximations made in this derivation are motivated and discussed. In particular, it is emphasized that closing the energy budget is conceptually challenging and hard to achieve in practice without resorting to ad hoc fixers. As a concrete example, the energy budget terms are diagnosed in a realistic climate simulation using a global atmosphere model. The largest total energy errors in this example are spurious dynamical core energy dissipation, thermodynamic inconsistencies (e.g., coupling parameterizations with the host model) and missing processes/terms associated with falling precipitation and evaporation (e.g., enthalpy flux between components). The latter two errors are not, in general, reduced by increasing horizontal resolution. They are due to incomplete thermodynamic and dynamic formulations. Future research directions are proposed to reconcile and improve thermodynamics formulations and conservation principles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

On the dynamics of non-relativistic flavor-mixed particles

Evolution of a system of interacting non-relativistic quantum flavor-mixed particles is considered both theoretically and numerically. It was shown that collisions of mixed particles not only scatter them elastically, but can also change their mass eigenstates thus affecting particles' flavor composition and kinetic energy. The mass eigenstate conversions and elastic scattering are related but different processes, hence the conversion S-matrix elements can be arbitrarily large even when the elastic scattering S-matrix elements vanish. The conversions are efficient when the mass eigenstates are well-separated in space but suppressed if their wave-packets overlap; the suppression is most severe for mass-degenerate eigenstates in flat space-time. The mass eigenstate conversions can lead to an interesting process, called ''quantum evaporation'', in which mixed particles, initially confined deep inside a gravitational potential well and scattering only off each other, can escape from it without extra energy supply leaving nothing behind inside the potential at t → ∞. Implications for the cosmic neutrino background and the two-component dark matter model are discussed and a prediction for the direct detection dark matter experiments is made.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Energy and exergy analysis of a novel multiple-effect vapor chamber distillation system for high-salinity wastewater treatment

A novel modular thermally-driven multiple-effect vapor chamber distillation (MVCD) system is presented for compact and portable desalination applications. The MVCD system consists of several vapor chambers connected in series with the condenser section of the upstream vapor chambers serving as the evaporator section of the following effect. A heat transfer model accounting for the major thermal resistances was developed to predict the heat transfer and distilled water production rates. A mass transfer analysis was performed to evaluate the effect of the accumulation of the non-condensable gasses within the chambers. An exergy analysis was also conducted to quantify the efficiency of the system from the viewpoint of the second law of thermodynamics. It was found that for a fixed number of effects, increasing the hot-end temperature increased the distillation rate and decreased the second law efficiency. On the other hand, increasing the number of effects at a fixed hot-end temperature resulted in increased distillation rate and second law efficiency. The increased salinity of the feed water resulted in smaller distillation rates and greater second law efficiency. For all the cases, it was found that sensible heat recovery from the discharging fluids could improve the gained output ratio (GOR) and the second law efficiency by about 10%. Here, the quantitatively, at a hot-end temperature of 70°C, feed water salinity of 35 ppt and recovery ratio of 36%, the MVCD system with six effects and energy recovery from the discharging fluids yielded a GOR of 5.0 and a second law efficiency of 3.8%.

42 ENGINEERING↗
DOE OSTI2018

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains

Abstract Many Numerical Weather Prediction (NWP) and climate models exhibit too warm lower tropospheres near the midlatitude continents. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in nine model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor, and aerosols are quantified, using an array of radiation measurement stations near the Atmospheric Radiation Measurement Southern Great Plains site. Furthermore, an in‐depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although nonnegligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud radiative effects dominate in the cloud‐related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

FY24: LEMMs: Long-term, Electrochemical Materials degradation Models

FY24 progress for LEMMs: Long-term, Electrochemical Materials degradation Models LDRD project are presented. Significant progress toward creating validated corrosion models was made in this FY paving success in future FY’s for success with battery model development and validation. Specifically, models for various forms of corrosion were probed for sensitivities showing a significant influence of reactive transport parameters for hydroxide species on the run time of the models. Further, cryo-genic time-of-flight secondary ion mass spectroscopy was utilized to map ions in a frozen corrosion droplet showing the precipitates/precipitate species near corroding locations. Additionally, a realistic corrosion droplet was created that accounted for evaporation and condensation coupled with corrosion. This pushes the boundary of corrosion modeling and will be validated in future FY’s.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Computational Investigation of Melt Pool Process Dynamics and Pore Formation in Laser Powder Bed Fusion

In the laser powder bed fusion additive manufacturing process, the presence of porosity may result in cracks and significantly affects the part performance. A comprehensive understanding of the melt pool process dynamics and porosity evolution can help to improve build quality. In this study, a novel multi-physics computational fluid dynamics (CFD) model has been applied to investigate the fluid dynamics in melt pools and resultant pore defects. To accurately capture the melting and solidification process, major process physics, such as the surface tension, evaporation as well as laser multi-reflection, have been considered in the model. A discrete element method is utilized to model the generation of powder spreading upon build plate by additional numerical simulations. Multiple single track experiments have been performed to obtain the melt pool shape and cross-sectional dimension information. The predicted melt pool dimensions were found to have a reasonable agreement with experimental measurements, e.g., the errors are in the range of 1.3 to 10.6% for melt pool width, while they are between 1.4 and 15.9% for melt depth. Pores are captured by both CFD simulation and x-ray computed tomography measurement for the case with a laser power of 350 W and laser speed of 100 mm/s. The formation of keyholes maybe related to the melt pool front wall angle, and it is found that the front wall angle increases with the increase in laser line energy density. In addition, a larger laser power or smaller scanning speed can help to generate keyhole-induced pores; they also contribute to produce larger sized pores.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Projecting Large Fires in the Western US With an Interpretable and Accurate Hybrid Machine Learning Method

More frequent and widespread large fires are occurring in the western United States (US), yet reliable methods for predicting these fires, particularly with extended lead times and a high spatial resolution, remain challenging. In this study, we proposed an interpretable and accurate hybrid machine learning (ML) model, that explicitly represented the controls of fuel flammability, fuel availability, and human suppression effects on fires. The model demonstrated notable accuracy with a F 1 -score of 0.846 ± 0.012, surpassing process-driven fire danger indices and four commonly used ML models by up to 40% and 9%, respectively. More importantly, the ML model showed remarkably higher interpretability relative to other ML models. Specifically, by demystifying the “black box” of each ML model using the explainable AI techniques, we identified substantial structural differences across ML fire models, even among those with similar accuracy. The relationships between fires and their drivers, identified by our model, were aligned closer with established fire physical principles. The ML structural discrepancy led to diverse fire predictions and our model predictions exhibited greater consistency with actual fire occurrence. With the highly interpretable and accurate model, we revealed the strong compound effects from multiple climate variables related to evaporative demand, energy release component, temperature, and wind speed, on the dynamics of large fires and megafires in the western US. Our findings highlight the importance of assessing the structural integrity of models in addition to their accuracy. They also underscore the critical need to address the rise in compound climate extremes linked to large wildfires.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Numerical Simulations of Supernova Remnant Evolution in a Cloudy Interstellar Medium

The mixed morphology class of supernova remnants has centrally peaked X-ray emission along with a shell-like morphology in radio emission. White and Long proposed that these remnants are evolving in a cloudy medium wherein the clouds are evaporated via thermal conduction once being overrun by the expanding shock. Their analytical model made detailed predictions regarding temperature, density, and emission profiles as well as shock evolution. We present numerical hydrodynamical models in 2D and 3D including thermal conduction, testing the White and Long model and presenting results for the evolution and emission from remnants evolving in a cloudy medium. We find that, while certain general results of the White and Long model hold, such as the way the remnants expand and the flattening of the X-ray surface brightness distribution, in detail there are substantial differences. In particular we find that the X-ray luminosity is dominated by emission from shocked cloud gas early on, leading to a bright peak, which then declines and flattens as evaporation becomes more important. In addition, the effects of thermal conduction on the intercloud gas, which is not included in the White and Long model, are important and lead to further flattening of the X-ray brightness profile as well as lower X-ray emission temperatures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Determination of dispersive optical constants of nanocrystalline CdSe (nc-CdSe) thin films

Highlights: ► nc-CdSe thin films are prepared by thermal vacuum evaporation technique. ► TEM analysis shows NCs are spherical in shape. ► XRD reveals the hexagonal (wurtzite) crystal structure of nc-CdSe thin films. ► The direct optical bandgap of nc-CdSe is 2.25 eV in contrast to bulk (1.7 eV). ► Dispersion of refractive index is discussed in terms of Wemple–DiDomenico single oscillator model. -- Abstract: The nanocrystalline thin films of CdSe are prepared by thermal evaporation technique at room temperature. These thin films are characterized by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX), X-ray diffraction (XRD) and photoluminescence spectroscopy (PL). The transmission spectra are recorded in the transmission range 400–3300 nm for nc-CdSe thin films. Transmittance measurements are used to calculate the refractive index (n) and absorption coefficient (α) using Swanepoel's method. The optical band gap (E{sub g}{sup opt}) has been determined from the absorption coefficient values using Tauc's procedure. The optical constants such as extinction coefficient (k), real (ε{sub 1}) and imaginary (ε{sub 2}) dielectric constants, dielectric loss (tan δ), optical conductivity (σ{sub opt}), Urbach energy (E{sub u}) and steepness parameter (σ) are also calculated for nc-CdSe thin films. The normal dispersion of refractive index is described using Wemple–DiDomenico single-oscillator model. Refractive index dispersion is further analysed to calculate lattice dielectric constant (ε{sub L}).

36 MATERIALS SCIENCE↗
DOE OSTI2019

Numerical Analysis of Molten Pool Behavior and Spatter Formation with Evaporation During Selective Laser Melting of 316L Stainless Steel

During the selective laser-melting process, material evaporation and resultant spatter are common phenomena that bring about many defects. However, the underlying physical phenomena such as molten pool behavior and spatter formation, as evaporation occurred, are sparsely understood and difficult to observe during the process. Thus, a three–dimensional powder-scale model was established to investigate the thermal and flow behavior of the molten pool, the morphology evolution of the molten pool and keyhole, and the spatter formation with evaporation in the selective laser-melting processing of 316L stainless steel. Phase transitions and variations in interfacial force were taken into account in this model. The modified phase-field method was applied to trace the melt–gas interface. The results showed that keyhole formed in molten pool under recoil pressure, and that there were some differences in the temperature distribution and flow behavior inside and outside the keyhole. In addition, the dimension and surface morphology of the molten pool and keyhole depth altered and gradually stabilized during the process. Moreover, droplet spatter formation at rear of molten pool proceeded roughly as follows: the backward ejection of melt vapor would induce a depression in molten pool and a bump on the molten pool surface, the bump moved backward and subsequently a liquid column formed, then the liquid column formed a neck and gradually pinched off, resulting in the droplet spatter. Furthermore, the characteristic morphology of the scan track and dimension of the molten pool were obtained through experiments, which showed good agreement with the simulation results.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Computational study of the ECN spray C via one-way coupling of internal nozzle flow and ensuing spray

Here, in this study, computational fluid dynamics simulations of the Engine Combustion Network Spray C injector were performed to investigate the effect of the internal nozzle flow on the development of the ensuing spray in automotive fuel injectors. A set of simulation best practices was first developed to achieve an accurate representation of the internal nozzle flow. Detailed, spatiotemporally defined information was extracted at the injector’s orifice exit and stored in maps that were subsequently employed to initialize a Lagrangian spray by means of a static, one-way coupling (OWC) approach. To highlight the impact of the in-nozzle flow on the spray, the OWC approach was compared with the conventional rate-of-injection (ROI) approach, for which the spray parcels are commonly initialized using a blob injection model. The results indicated that, using the ROI approach, considerable evaporation was observed within the plume in the near-nozzle region. On the other hand, the OWC approach showed evidence of evaporation farther downstream and at the plume periphery. The different behavior observed with the two approaches was mostly due to substantial differences in fuel mass distribution. The liquid fuel concentration predicted by the OWC approach matched well with X-ray tomography measurements of projected fuel mass per unit volume, in terms of both magnitude and distribution. In contrast, an unphysical distribution of fuel mass characterized by an extremely low liquid concentration was predicted by the ROI approach. In the far-field, the effect of the in-nozzle flow was found to be weaker as the spray penetrated and interacted with the ambient gas. In this region, the OWC and ROI approaches provided similar predictions of vapor penetration, spray morphology, and mixing-related characteristics.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Phase Diagram and Structure Map of Binary Nanoparticle Superlattices from a Lennard-Jones Model

A first-principles prediction of the binary nanoparticle phase diagram assembled by solvent evaporation has eluded theoretical approaches. In this paper, we show that a binary system interacting through the Lennard-Jones (LJ) potential contains all experimental phases in which nanoparticles are effectively described as quasi hard spheres. We report a phase diagram consisting of 53 equilibrium phases, whose stability is quite insensitive to the microscopic details of the potentials, thus giving rise to some type of universality. Furthermore, we show that binary lattices may be understood as consisting of certain particle clusters, i.e., motifs, that provide a generalization of the four conventional Frank–Kasper polyhedral units. Our results show that metastable phases share the very same motifs as equilibrium phases. Finally, we discuss the connection with packing models, phase diagrams with repulsive potentials, and the prediction of likely experimental superlattices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗