Search NASA⌕ Search

SEARCH · Search NASA

Results for “surface modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Synergistic Enhancement of Lead and Selenate Uptake at the Barite (001)–Water Interface

The interactions of heavy metals with minerals influence the mobility and bioavailability of toxic elements in natural aqueous environments. The sorption of heavy metals on covalently bonded minerals is generally well described by surface complexation models (SCMs). However, understanding sorption on sparingly soluble minerals is challenging because of the dynamically evolving chemistry of sorbent surfaces. The interpretation can be even more complicated when multiple metal ions compete for sorption. In the present study, we observed synergistically enhanced uptake of lead and selenate on the barite (001) surface through two sorption mechanisms: lattice incorporation that dominates at lower coverages and two-dimensional monolayer growth that dominates at higher coverages. Further, we also observed a systematic increase in the sorption affinity with increasing co-sorbed ion coverages, different from the assumption of invariant binding constants for individual adsorption processes in classical SCMs. Computational simulations showed thermodynamically favorable co-incorporation of lead and selenate by simultaneously substituting for barium and sulfate in neighboring sites, resulting in the formation of molecular clusters that locally match the net dimension of the substrate lattice. These results emphasize the importance of ion–ion interactions at mineral–water interfaces that control the fate and transport of contaminants in the environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Uniting Surface Properties With Hydrodynamic Roughness in Shallow Overland Flow Models

Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's n). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation-based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely-used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted values between 0.48 and 0.54, depending on the roughness scheme used. Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Confocal Raman Microscopy Investigation of Phospholipid Monolayers Deposited on Nitrile-Modified Surfaces in Porous Silica Particles

Phospholipid bilayers deposited on a variety of surfaces offer models for investigation of the lipid membrane structure and supports for biocompatible sensors. Hybrid-supported phospholipid bilayers (HSLBs) are stable membrane models for these investigations, typically prepared by self-assembly of a lipid monolayer over an n-alkane-modified surface. HSLBs have been prepared on n-alkyl chain-modified silica and used for lipophilicity-based chromatographic separations. The structure of these hybrid bilayers differs from vesicle membranes where the lipid head group spacing is greater due to interdigitation of the lipid acyl chains with the underlying n-alkyl chains bound to the silica surface. This interdigitated structure exhibits a broader melting transition at a higher temperature due to strong interactions between the lipid acyl chains and the immobile n-alkyl chains bound to silica. In the present work, we seek to reduce the interactions between a lipid monolayer and its supporting substrate by self-assembly of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) on porous silica functionalized with nitrile-terminated surface ligands. The frequency of Raman scattering of the surface -C≡N stretching mode at the lipid–nitrile interface is consistent with an n-alkane-like environment and insensitive to lipid head group charge, indicating that the lipid acyl chains are in contact with the surface nitrile groups. The head group area of this lipid monolayer was determined from the within-particle phospholipid concentration and silica specific surface area and found to be 54 ± 2 Å 2 , equivalent to the head group area of a DMPC vesicle bilayer. The structure of these nitrile-supported phospholipid monolayers was characterized below and above their melting transition by confocal Raman microscopy and found to be nearly identical to DMPC vesicle bilayers. Their narrow gel-to-fluid-phase melting transition is equivalent to dispersed DMPC vesicles, indicating that the acyl chain structure on the nitrile support mimics the outer leaflet structure of a vesicle membrane.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thermomechanical Stress and Creep-Fatigue Analysis of a High-Temperature Prototype Receiver for Heating Particles

This work presents a three-dimensional (3D) thermomechanical model of a prototype-scale enclosed light trapping solar receiver for heating particles. Results of the thermoelastic model are used to estimate receiver lifetime under maximum flux conditions. A computational fluid dynamics (CFD) model is first developed to predict the temperature fields in a multi-panel assembly under steady operating conditions. Solar flux distributions on the receiver are obtained from the software package SolTrace and applied to the 3D thermal model. The subsequent particle heating is captured through a simplified 1D energy balance. Panel reradiation is considered through a surface-to-surface radiation model and natural convection loss to the surrounding air is captured in a representative fluid domain surrounding the receiver. The resulting temperature fields from the CFD analysis are used as inputs for a thermoelastic mechanical model with representative boundary conditions. With the resultant temperature and stress fields, a creep-fatigue damage and lifetime analysis is performed using the linear damage accumulation (LDA) theory. The Manson-Coffin formula and Larson Miller correlation are used to calculate the fatigue and creep, respectively. A maximum damage (corresponding to a 30-year service life) is defined for design assessment. The model was first developed and verified in detail by comparing with published results in the literature (temperature and stress profiles and distributions, and creep/fatigue damage fractions) for tubular solar receivers with supercritical carbon dioxide as the working fluid. It was then implemented to model a planar-cavity receiver with various design parameters. Specifically, three different design geometries are considered, and the results show that a maximum temperature of approximately 1200 K could be reached for each design with the given incident solar flux, with the main difference being the distribution of these temperatures. Preliminary resulting stresses for the small-scale prototype without design optimization vary from 20 MPa to 250 MPa for each design, with the maximum stresses occurring on the front face and concave geometry on the side of the panel. In future work, the developed methodology shown here will be applied to analyze a full-scale (50-150 MWth) receiver.

concentrated solar power↗
DOE OSTI2021

Fixed Bit Rotary Drilling Failure Criteria Effect on Drilling Vibration

Polycrystalline diamond compact (PDC) bit use has been expanded to geothermal drilling applications due to their improved performance in drilling compared to roller cone bits. Multiple vibration models have been developed yet and there are limited use of field data to study the ability of numerical vibration model to predict recorded vibration in the field. The objective of this paper is to evaluate the capabilities of two different rock-bit interaction models with two different ROP formulations for predicting the actual behavior seen in the field. The first model (Model-I) considers the rock-bit interaction, incorporating the effect of subsurface formation characteristics. The second model (Model-II) is a PDC bit model that uses calculated threshold weight-on-cutter (WOCt) to study the interaction of the bit with the rock surface. The models, which couple the drill stem axial and torsional motions, are solved numerically using the fourth-order Runge-Kutta method and compared with recorded downhole drilling data from the Chocolate Mountain Aerial Gunnery Range (CMAGR) geothermal well located in California. An 8–½" PDC bit with 8 blades was modeled and vibration simulation was performed to investigate stick-slip vibrations at 1400 ft. depth. Simulation results using field data indicate that Model-II encounters a low range of stick-slip severity (SSV) as compared to Model-I, which is in the moderate range. Comparison with the field value for SSV shows Model-II is the best representative of the field case for this depth. The sensitivity analysis shows that results are sensitive to model constants making prediction of SSV from models uncertain.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

2-D moving mesh modeling of lithium dryout in open surface liquid metal flow applications

Liquid lithium displays increasing promise as a replacement for solid plasma facing components (PFCs) in fusion device applications. The Liquid Metal Infused Trench (LiMIT) system, developed at the University of Illinois (UIUC), has demonstrated how thermoelectric magnetohydrodynamics (TEMHD) can be harnessed to drive liquid lithium flow in an open surface PFC. However, in the highest heat flux applications, large local acceleration is created via TEMHD, and the sudden increase in velocity can cause the liquid level to expose the underlying solid, eliminating the protective benefits of the lithium. In order to study potential mitigation strategies, a 2-D COMSOL Multiphysics model was developed using the moving mesh module to capture free surface flow. The model depicts the development of the dryout phenomenon for 2 test cases – slow (1 cm/s) and medium (10 cm/s) flow in 5 mm deep trenches – including the liquid level reduction under the high heat flux and the pileup of slower flow both upstream and downstream of the heat stripe. The effectiveness of trench shaping dryout mitigation strategies is examined. For the slow flow case, it is shown that a 1.8 mm ledge placed under the heat stripe will stop dryout, and for the medium flow case, a 2.7 mm ledge is required to mitigate the effect. This model can be used to identify strategies for increasing the viable heat load for open surface liquid lithium PFCs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Gravitation and Mesh Adaption

The Gravitation and Mesh Adaptation (GaMA) toolbox consists of a set of Matlab classes for modeling the environment around asteroids and comets. A variety of gravitational models and supporting algorithms from are consolidated alongside a custom meshing utility tailored for the application. This allows the user to work within a single streamlined environment to import and manipulate surface definitions, probe the dynamical environment, integrate trajectories, and post-process results. For other applications, modified surface meshes can be exported. Gravity Models: 1) Werner's analytic polyhedron model 2) Mascon model 3) Gottlieb's spherical harmonic model 4) Approximate polyhedron models 5) Curvilinear surface models 6) Custom composite models Meshing Features: 1) Array-based half-edge data structure 2) Supports curvilinear surface definitions up to degree 4 3) Ray-tracing 4) Coarsening 5) Feature-based refinement 6) Projection 7) Smoothing 8) Mesh quality validity tests 9) Mesh repair Additional Features: 1) Solar radiation pressure model 2) Distant 3rd body model 3) Collision detection 4) Trajectory integration and post-processing 5) Visualization of surface fields

Pearl, Jason↗
DOE OSTI2024

Insights into the interaction of nitrobenzene and the Ag(111) surface: A DFT study

Here, this study explores the potential of nitrobenzene as an anolyte material for nonaqueous redox flow batteries (RFBs) by theoretically examining its low-coverage adsorption behavior on neutral and charged Ag(111) model electrode surfaces. At the low coverage limit, DFT calculations show a preference for nitrobenzene to adsorb parallel to the surface, with the benzene ring and nitro group centered over HCP sites. Interactions between nitrobenzene and the surface were analyzed using induced charge density analysis, Bader charge analysis, and projected density of states (PDOS). It was found that nitrobenzene adsorbs primarily through van der Waals interactions with the surface. As nitrobenzene accumulates negative charge, the strength of adsorption diminishes. Understanding the electrode-electrolyte interface is crucial for enhancing RFB electrochemical performance, and this study sheds light on nitrobenzene's interaction with a model Ag electrode.

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

Human-induced changes to the global ocean water masses and their time of emergence

The World Ocean is rapidly changing, with global and regional modification of temperature and salinity, resulting in widespread and irreversible impacts. While the most pronounced observed temperature and salinity changes are located in the upper ocean, changes in water masses at depth have been identified and will probably strengthen in the future. In this study, using 11 climate models, we define when anthropogenic temperature and salinity changes are expected to emerge from natural variability in the ocean interior along density surfaces. The models predict that in 2020, 20–55% of the Atlantic, Pacific and Indian basins have an emergent anthropogenic signal; reaching 40–65% in 2050 and 55–80% in 2080. The well-ventilated Southern Ocean water masses emerge very rapidly, as early as the 1980–1990s, while the Northern Hemisphere water masses emerge in the 2010–2030s. Our results highlight the importance of maintaining and augmenting an ocean observing system capable of detecting and monitoring persistent anthropogenic changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Surface Termination of CsPbBr 3 Perovskite Quantum Dots Determined by Solid-State NMR Spectroscopy

Cesium lead halide perovskite quantum dots (QDs) have gained significant attention as next-generation optoelectronic materials; however, their properties are highly dependent on their surface chemistry. The surfaces of cuboidal CsPbBr 3 QDs have been intensively studied by both theoretical and experimental techniques, but fundamental questions still remain about the atomic termination of the QDs. The surface binding sites and modes of ligands at the surface remain unproven. Herein, we demonstrate that solid-state NMR spectroscopy allows the unambiguous assignment of organic surface ligands via 1 H, 13 C, and 31 P NMR. Surface-selective 133 Cs solid-state NMR spectra show the presence of an additional 133 Cs NMR signal with a unique chemical shift that is attributed to Cs atoms terminating the surface of the particle and which are likely coordinated by carboxylate ligands. Dipolar dephasing curves that report on the distance between the surface ammonium ligands and Cs and Pb were recorded using double resonance 1 H{ 133 Cs} and 1 H{ 207 Pb} RESPDOR experiments. Model QD surface slabs with different possible surface terminations were generated from the CsPbBr 3 crystal structure and theoretical RESPDOR dipolar dephasing curves considering all possible 1 H- 133 Cs/ 207 Pb spin pairs were then calculated. Comparison of the calculated and experimental RESPDOR curves indicates the particles are CsBr terminated (not PbBr 2 terminated) with alkylammonium ligands substituting into some surface Cs sites, consistent with the surface-selective 133 Cs NMR experiments. Lastly, these results highlight the utility of high-resolution solid-state NMR spectroscopy for studying ligand binding and the surface structure of nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Power-Law Entanglement and Hilbert Space Fragmentation in Nonreciprocal Quantum Circuits

Quantum circuits utilizing measurement to evolve a quantum wave function offer a new and rich playground to engineer unconventional entanglement dynamics. Here, in this work, we introduce a hybrid, nonreciprocal setup featuring a quantum circuit, whose updates are conditioned on the state of a classical dynamical agent. In our example the circuit is represented by a Majorana quantum chain controlled by a classical N-state Potts chain undergoing pair flips. The local orientation of the classical spins controls whether randomly drawn local measurements on the quantum chain are allowed or not. This imposes a dynamical kinetic constraint on the entanglement growth, described by the transfer matrix of an N-colored loop model. It yields an equivalent description of the circuit by an SU(N)-symmetric Temperley-Lieb Hamiltonian or by a kinetically constrained surface growth model for an N-component height field. For N = 2, we find a diffusive growth of the half-chain entanglement toward a stationary profile S(L) ~ L 1/2 for L sites. For N ≥ 3, the kinetic constraints impose Hilbert space fragmentation, yielding subdiffusive growth toward S(L) ~ L 0.57 . This showcases how the control by a classical dynamical agent can enrich the entanglement dynamics in quantum circuits, paving a route toward novel entanglement dynamics in nonreciprocal hybrid circuit architectures.

1-dimensional spin chains↗
DOE OSTI2020

Mathematical Model for Li-S Cell with Shuttling-Induced Capacity Loss Approximation

Lithium sulfur (Li-S) batteries have the potential to outperform the current lithium ion batteries and transform the technology of the future. However, dissolution, diffusion, and shuttling of the dissolved polysulfides result in parasitic reactions and substantial capacity loss. To provide a better understanding of the shuttling process, a 1D porous electrode mathematical model has been developed in this paper. An approximation method is used to account for the shuttling-induced capacity loss by adding an extra source/sink term in the material balance equations for the species involved in the parasitic reactions. Shuttling constants used in the source terms can be determined by fitting the model predictions to the experimental measurements. Here, the results showed that by including the approximation method, the model was able to predict the active material loss and the continuous decrease of volume fractions of Li 2 S on the cathode surface. The model sheds light on the capacity loss mechanism occurring inside the cell as a result of the shuttling of polysulfides.

25 ENERGY STORAGE↗
DOE OSTI2021

Efimov-like states and quantum funneling effects on synthetic hyperbolic surfaces

Engineering lattice models with tailored inter-site tunnelings and onsite energies could synthesize essentially arbitrary Riemannian surfaces with highly tunable local curvatures. Here, we point out that discrete synthetic Poincaré half-planes and Poincaré disks, which are created by lattices in flat planes, support infinitely degenerate eigenstates for any nonzero eigenenergies. Such Efimov-like states exhibit a discrete scaling symmetry and imply an unprecedented apparatus for studying quantum anomaly using hyperbolic surfaces. Furthermore, all eigenstates are exponentially localized in the hyperbolic coordinates, signifying the first example of quantum funneling effects in Hermitian systems. As such, any initial wave packet travels towards the edge of the Poincaré half-plane or its equivalent on the Poincaré disk, delivering an efficient scheme to harvest light and atoms in two dimensions. Furthermore, our findings unfold the intriguing properties of hyperbolic spaces and suggest that Efimov states may be regarded as a projection from a curved space with an extra dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Machine Learning Assisted Gap-Filled Discharge Data for the East River Community Watershed, Colorado, for Water Years 2014-2021

This dataset contains a collection of machine learning assisted gap-filled discharge data created for all discharge stations across the East River Watershed, Colorado. This data was generated by using raw discharge data collected by Rosemary Carroll, and conducting a random forest machine learning analysis to gap-fill discharge data across all years at the hourly time level. Discharge data with gaps creates problems for analysis of measured and modeled fluxes of carbon and nitrogen exported out of each sub-watershed. Gap-filled data is also required as an input to surface water models, which helps to address our main research question related to how snowmelt timing impacts the timing and magnitude of nitrogen exports. Data is provided in one csv file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Pairing instability on a Luttinger surface: A non-Fermi liquid to superconductor transition and its Sachdev-Ye-Kitaev dual

Superconductivity results from an instability of the Fermi surface—contour of poles of the single-particle propagator—to an infinitesimally small attraction between electrons. Here, we instead discuss the analogous problem on a model Luttinger surface, or contour of zeros of the Green function. At zero temperature ($β → \infty$) and a critical interaction strength ($u_{c∞}$) characterized by the residue of self-energy pole, we find that the pair susceptibility diverges leading to a superconducting instability. We evaluate the pair fluctuation partition function and find that the spectral density in the normal state has an interaction-driven, power-law $\frac{1}{\sqrt{ω}}$ type, van-Hove singularity (vHS), indicating non-Fermi liquid (NFL) physics. Crucially, in the strong coupling limit ($βu \gg 1$), the leading-order fluctuation free-energy terms in the normal state of this NFL-SC transition resembles the equivalent [$\textit{O}(1)$] terms of the Sachdev-Ye-Kitaev (SYK) model. This free-energy contribution takes a simple form $–βF = βu_{c∞} – γ \text{ln}(βu_{c∞}$), where $\gamma$ is a constant equal to $\frac{1}{2}$. Weak impurity scattering ($τ \gg β^{–1}$) leaves the low-energy spectral density unaffected but leads to an interaction-driven enhancement of superconductivity. Our results in this work shed light on the role played by order-parameter fluctuations in providing the key missing link between Mott physics and strongly coupled toy models exhibiting gravity duals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

The influence of cloud cover on the reliability of satellite-based solar resource data

Satellite-based solar resource data are often developed and validated by using binary cloudiness categories: clear sky or overcast cloudy sky. To investigate the reliability of solar resource data in partially cloudy conditions, we estimate cloud fraction using two distinct algorithms: a physical retrieval model using surface observed global horizontal irradiance (GHI) and direct normal irradiance (DNI) and a temporal average of cloud mask data estimated by the observed DNI. Our analysis reveals a significant presence of scattered clouds, broken clouds, and mismatches between satellite- and surface-based cloud data at 17 surface sites across the contiguous United States, though confidently clear and cloudy conditions collectively account for more than 70 % of the data. Solar radiation is computed using the National Solar Radiation Database (NSRDB) algorithm and validated using surface observations. Here, our findings suggest that, in the presence of scattered clouds, NSRDB data for clear-sky conditions can be subject to significant overestimation. In cloudy-sky conditions classified by satellite data, DNI computed by the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) can be underestimated when limited clouds are detected by surface observations. The bias observed in several cloudiness categories indicates that the NSRDB is exceptionally accurate in confidently clear conditions. However, clear-sky conditions with scattered clouds and mismatched cloud data contribute significantly to the overall uncertainties in the NSRDB. Therefore, future improvements in solar resource data should involve development and implementation of satellite-derived cloud fraction and should consider a novel radiative transfer model accounting for amplified cloud reflection. The evaluation within cloudiness categories also provides a physical rationale for the superior performance of FARMS-DNI compared to the Direct Insolation Simulation Code (DISC) in both cloudy-sky and all-sky conditions.

14 SOLAR ENERGY↗
DOE OSTI2026

Aperture and roughness govern iron oxide passivation in olivine fractures during carbon mineralization

Efficient carbon dioxide mineralization in silicate-rich formations depends on reaction rates within fracture networks, yet the role of fracture microstructure remains poorly constrained. We investigated how fracture aperture and surface roughness influence mineralization by reacting synthetic forsteritic olivine fractures with controlled apertures (0.5–1.6 millimeters) and roughness (6–16 micrometers) with supercritical carbon dioxide at 13.7 megapascals and 185 degrees Celsius. Optical microscopy and Raman spectroscopy showed that rougher fracture surfaces promoted iron oxide precipitation, which passivated olivine surfaces, limiting magnesium availability for carbonate formation while removing iron as a reactant. These effects were more pronounced in smaller-aperture fractures. A geochemical model incorporating surface topography and passivation reproduced the observed trends, confirming that increased roughness can reduce reactivity despite greater surface area. Our results demonstrate that fracture microstructure strongly influences iron oxide passivation and carbon dioxide mineralization, with important implications for predicting long-term performance of engineered carbon dioxide storage systems.

54 ENVIRONMENTAL SCIENCES↗