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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

A numerical study of global axisymmetric states and their stability to quasi-geostrophic disturbances

A steady, axisymmetric model of the general circulation is developed as a basis for climate stability studies. The model includes the effects of heating, rotation, and internal friction, but neglects topography. It is assumed that the axisymmetric flow may be modeled by making the Boussinesq and deep convection approximations. The hydrostatic assumption is not made, thus permitting the advective terms to be included in the vertical equation of motion. The initial set of five primitive equations is reduced to three equations in terms of the zonal velocity, meridional streamfunction, and the potential temperature perturbation. The application of the Boussinesq, deep convection, and quasi-geostrophic assumptions limits the ranges of the heating and rotation rates. For values not too far from typical atmospheric values, the model produces a stability boundary separating Hadley from Rossby flow. The boundary is characterized by a particular value of vertical wind shear, which suggests that baroclinic instability is the primary mechanism for the loss of stability. The initial growth rates are largest for longitudinal waves 4-7, also in agreement with studies of baroclinic instability.

Henderson, H. W.↗
DOE OSTI2025

NEAR: Neural Embeddings for Amino acid Relationships

Protein language models (PLMs) have recently demonstrated potential to supplant classical protein database search methods based on sequence alignment, but are slower than common alignment-based tools and appear to be prone to a high rate of false labeling. Here, we present NEAR, a method based on neural representation learning that is designed to improve both speed and accuracy of search for likely homologs in a large protein sequence database. NEAR’s ResNet embedding model is trained using contrastive learning guided by trusted sequence alignments. It computes per-residue embeddings for target and query protein sequences, and identifies alignment candidates with a pipeline consisting of residue-level k-NN search and a simple neighbor aggregation scheme. Tests on a benchmark consisting of trusted remote homologs and randomly shuffled decoy sequences reveal that NEAR substantially improves accuracy relative to state-of-the-art PLMs, with lower memory requirements and faster embedding and search speed. While these results suggest that the NEAR model may be useful for standalone homology detection with increased sensitivity over standard alignment-based methods, in this manuscript we focus on a more straightforward analysis of the model’s value as a high-speed pre-filter for sensitive annotation. In that context, NEAR is at least 5x faster than the pre-filter currently used in the widely-used profile hidden Markov model (pHMM) search tool HMMER3, and also outperforms the pre-filter used in our fast pHMM tool, nail.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1998

Titania and Oberon: Surface Composition from New Near-Infrared Observations and Reflectance Models

Here we report the combination of new near-ir spectra (1.45-2.48 micrometers), of Titania and Oberon obtained in September 1995 at a resolving power of approx. 800, with older near-ir observations (0.5- 1.44 micrometers), and recent UV (0.22-0.48 micrometers) observations obtained with HST. Previous interpretations suggest these surfaces are chiefly composed of water ice and varying amounts of spectrally neutral material. The new near-ir data provide the opportunity to search for absorption bands that could be attributable to surface materials other than water ice and because the combined spectra include such a broad wavelength region, to undertake improved models of water and neutral components on the surface. The calculated near-ir geometric albedos clearly exhibit three broad spectral features. Two (1.52- & 2.05 micrometer) have previously been used to demonstrate the presence of water ice on these satellites. The third (approx. 1.65 micrometer), suggests the presence of hexagonal water ice at low temperatures, and may provide a mechanism of estimating the surface temperature. There is no spectral evidence for ices of CO2, CO, NH3 or CH4. At UV wavelengths there is a broad absorption near 0.27-0.28 micrometer previously attributed to OH formed by magnetospheric-surface interactions and retained at the low surface temperatures of these satellites. Surface components used in a Hapke scattering models include values for a combination of irradiated water ice in the UV and hexagonal water ice at 100k in the near-ir (IR), amorphous carbon (AC), and tholins (T) (produced from gas and solid). Results of these models suggest the surfaces of Titania/Oberon are composed of IW (-77/52%) with AC the next most abundant component (approx. 19/52%) and finally T (approx. 4/7%).

Roush, Ted L.↗
DOE OSTI2025

Dynamic Modeling of a Fast Spectrum Molten Salt Reactor Integrated Energy System

Liquid-fueled molten salt fast reactors and nuclear-powered integrated energy systems (IESs) have the potential to play a pivotal role in the green energy transition. However, these systems have little to no operating experience. There is therefore increased interest and value in modeling and simulating these systems. The IES dynamic model developed in this work utilizes a lumped-parameter control volume methodology to investigate the behavior of the IES in a variety of accident scenarios. The results provide initial evidence for the potential inherent safety of the advanced reactor because of temperature-dependent reactivity feedback and the efficiency of hydrogen and electricity production at the high temperatures provided by the advanced reactor.

MCFR↗
DOE OSTI2025

Dusty Gas Model for Solid Oxide Fuel Cell Fuel Electrode

This model applies the Dusty Gas Model simulate multi-component species transport in SOFC (solid oxide fuel cell) anodes which considers the pressure gradient across the fuel electrode. This studyhas been verified with the analytical solution for different fuel electrode thicknesses and with literature values. The model was developed using the VoronoiFVM platform in Julia which is a built in implicit and semi implicit solver that integrates electrochemical behavior, microstructural effects, and transient analysis for accurate prediction of species transport under varying conditions.

dusty gas model (DGM)↗
NASA NTRS1973

A radiation model for calculating atmospheric corrections to remotely sensed infrared measurements, version 2

A numerical model is developed which calculates the atmospheric corrections to infrared radiometric measurements due to absorption and emission by water vapor, carbon dioxide, and ozone. The corrections due to aerosols are not accounted for. The transmissions functions for water vapor, carbon dioxide, and water are given. The model requires as input the vertical distribution of temperature and water vapor as determined by a standard radiosonde. The vertical distribution of carbon dioxide is assumed to be constant. The vertical distribution of ozone is an average of observed values. The model also requires as input the spectral response function of the radiometer and the nadir angle at which the measurements were made. A listing of the FORTRAN program is given with details for its use and examples of input and output listings. Calculations for four model atmospheres are presented.

Boudreau, R. D.↗
DOE OSTI2025

Development of an Interactive Valuation Model for Distributed Energy Resource Value: Cooperative Research and Development (Final Report)

The Oklahoma Office of the Secretary of Energy and Environment (OSEE) seeks to address perceived challenges and barriers to the deployment of distributed energy generation resources (DERs), including solar and other technologies, in the state of Oklahoma. The Scope of Work (SOW) associated with CRD-18-762 covers two tasks: (1) Interactive Valuation Model Requirements Document and (2) Consumer Protection Assessment. Follow-on work was completed under a separate CRADA (CRD-19-00788).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1990

Verification of the naval oceanic vertical aerosol model during FIRE

The value of Naval Oceanic Vertical Aerosol Model (NOVAM) is illustrated for estimating the non-uniform and non-logarithmic extinction profiles, based on a severe test involving conditions close to and beyond the limits of applicability of NOVAM. A more comprehensive evaluation of NOVAM from the FIRE data is presented, which includes a clear-air case. For further evaluation more data are required on the vertical structure of the extinction in the marine atmospheric boundary layer (MABL), preferably for different meteorological conditions and in different geographic areas (e.g., ASTEX).

Davidson, K. L.↗
NASA NTRS2009

Neutralizer Hollow Cathode Simulations and Validation with Experiments

The fidelity of electric propulsion physics-based models depends largely on the validity of their predictions over a range of operating conditions and geometries. In general, increased complexity of the physics requires more extensive comparisons with laboratory data to identify the region(s) that lie outside the validity of the model assumptions and to quantify the uncertainties within its range of application. This paper presents numerical simulations of neutralizer hollow cathodes at various operating conditions and orifice sizes. The simulations were performed using a two-dimensional axisymmetric model that solves numerically a relatively extensive system of conservation laws for the partially-ionized gas in these devices. The results for the plasma are compared directly with Langmuir probe measurements. The computed keeper voltages are also compared with the observed values. Wherever model inputs and/or specific physics of the cathode discharge are uncertain, additional sensitivity calculations have been performed to quantify the uncertainties.

partially ionized gases↗
DOE OSTI2026

Using PyBioNetFit to leverage qualitative and quantitative data in biological model parameterization and uncertainty quantification

Data generated in studies of cellular regulatory systems are often qualitative. For example, measurements of signaling readouts in the presence and absence of mutations may reveal a rank ordering of responses across conditions but not the precise extents of mutation-induced differences. Qualitative data are often ignored by mathematical modelers or are considered in an ad hoc manner, as in the study of Kocieniewski and Lipniacki (2013) [Phys Biol 10: 035006], which was focused on the roles of MEK isoforms in ERK activation. In this earlier study, model parameter values were tuned manually to obtain consistency with a combination of qualitative and quantitative data. This approach is not reproducible, nor does it provide insights into parametric or prediction uncertainties. Here, starting from the same data and the same ordinary differential equation (ODE) model structure, we generate formalized statements of qualitative observations, making these observations more reusable, and we improve the model parameterization procedure by applying a systematic and automated approach enabled by the software package PyBioNetFit. We also demonstrate uncertainty quantification (UQ), which was absent in the original study. Our results show that PyBioNetFit enables qualitative data to be leveraged, together with quantitative data, in parameterization of systems biology models and facilitates UQ. These capabilities are important for reliable estimation of model parameters and model analyses in studies of cellular regulatory systems and reproducibility.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

GCSS Idealized Cirrus Model Comparison Project

The GCSS Working Group on Cirrus Cloud Systems (WG2) is conducting a systematic comparison and evaluation of cirrus cloud models. This fundamental activity seeks to support the improvement of models used for climate simulation and numerical weather prediction through assessment and improvement of the "process" models underlying parametric treatments of cirrus cloud processes in large-scale models. The WG2 Idealized Cirrus Model Comparison Project is an initial comparison of cirrus cloud simulations by a variety of cloud models for a series of idealized situations with relatively simple initial conditions and forcing. The models (16) represent the state-of-the-art and include 3-dimensional large eddy simulation (LES) models, two-dimensional cloud resolving models (CRMs), and single column model (SCM) versions of GCMs. The model microphysical components are similarly varied, ranging from single-moment bulk (relative humidity) schemes to fully size-resolved (bin) treatments where ice crystal growth is explicitly calculated. Radiative processes are included in the physics package of each model. The baseline simulations include "warm" and "cold" cirrus cases where cloud top initially occurs at about -47C and -66C, respectively. All simulations are for nighttime conditions (no solar radiation) where the cloud is generated in an ice supersaturated layer, about 1 km in depth, with an ice pseudoadiabatic thermal stratification (neutral). Continuing cloud formation is forced via an imposed diabatic cooling representing a 3 cm/s uplift over a 4-hour time span followed by a 2-hour dissipation stage with no cooling. Variations of these baseline cases include no-radiation and stable-thermal-stratification cases. Preliminary results indicated the great importance of ice crystal fallout in determining even the gross cloud characteristics, such as average vertically-integrated ice water path (IWP). Significant inter-model differences were found. Ice water fall speed is directly related to the shape of the particle size distribution and the habits of the ice crystal population, whether assumed or explicitly calculated. In order to isolate the fall speed effect from that of the associated ice crystal population, simulations were also performed where ice water fall speed was set to the same constant value everywhere in each model. Values of 20 and 60 cm/s were assumed. Current results of the project will be described and implications will be drawn. In particular, this exercise is found to strongly focus the definition of issues resulting in observed inter-model differences and to suggest possible strategies for observational validation of the models. The next step in this project is to perform similar comparisons for well observed case studies with sufficient high quality data to adequately define model initiation and forcing specifications and to support quantitative validation of the results.

Starr, David OC.↗
NASA NTRSDate not supplied

Comparison of Entry Descent and Landing Aerodynamic Databases with Uncertainty Quantification Developed Using Machine Learning Techniques

When developing the aerodynamic databases for use in trajectory simulations, it is important to develop a system of metrics to qualify which aerodynamic models are best to use. Since aerodynamics are just one input into trajectory simulations, the results of these simulations do not reflect on the quality of the aerodynamic database used. This means that aerodynamic database comparisons must be done offline. While traditional metrics that focus on mean/nominal predictions are a good first step, more robust estimates of the prediction interval become important as more focused uncertainty models are developed. We explore the limitations of evaluating aerodynamic models based purely on nominal-centered response surfaces. Before elaborating and evaluating metrics based on distributed models, the value of evaluating prediction interval and confidence interval are discussed to conclude that prediction intervals are more relevant to the use of trajectory analysis. Several metrics to evaluate the prediction interval are introduced with a focus on the standard calibration metric. Finally, we compare candidate models using both mean and distributed metrics. A finalized candidate model developed using state of the art machine learning methods is compared to a baseline model developed using traditional aerodynamic database modeling techniques.

Aerodynamic Database↗
NASA NTRS1993

A multidimensional model of the effect of gravity on the spatial orientation of the monkey

A "sensory conflict" model of spatial orientation was developed. This mathematical model was based on concepts derived from observer theory, optimal observer theory, and the mathematical properties of coordinate rotations. The primary hypothesis is that the central nervous system of the squirrel monkey incorporates information about body dynamics and sensory dynamics to develop an internal model. The output of this central model (expected sensory afference) is compared to the actual sensory afference, with the difference defined as "sensory conflict." The sensory conflict information is, in turn, used to drive central estimates of angular velocity ("velocity storage"), gravity ("gravity storage"), and linear acceleration ("acceleration storage") toward more accurate values. The model successfully predicts "velocity storage" during rotation about an earth-vertical axis. The model also successfully predicts that the time constant of the horizontal vestibulo-ocular reflex is reduced and that the axis of eye rotation shifts toward alignment with gravity following postrotatory tilt. Finally, the model predicts the bias, modulation, and decay components that have been observed during off-vertical axis rotations (OVAR).

NASA Discipline Neuroscience↗
DOE OSTI2025

Prediction of Redox Potentials for Different Oxidation States of U, Np, Pu, and Am in Alkaline Aqueous Solution

The redox potentials for U, Np, Pu, and Am for oxidation states +III up to +VIII in alkaline aqueous solutions were predicted using density functional theory (DFT) and small-core pseudopotentials and their basis sets, with a hybrid explicit/implicit solvent model using SHE = 4.28 V. For each oxidation state, various oxo/hydroxo complexes were evaluated resulting in a variety of one-electron redox pathways. For An(VIII/VII) couples, the predicted redox potentials for the [An(VIII)O 5 (OH)] -3 /[An(VII)O 4 (OH) 2 ] -3 , or [An(VIII)O 4 (OH) 2 ] -2 /[An(VII)O 4 (OH) 2 ] -3 couples are in good agreement with existing estimates. For An(VII/VI) redox couples, all couples, particularly [An(VII)O 4 (OH) 2 ] -3 /[An(VI)O 2 (OH) 4 ] -2 , were in agreement with experimental values for U, Np, and Pu, but the results for Am showed larger differences from the estimated potentials. The An(VI/V) couples were consistent with experiment for dioxo/tetrahydroxo couples, and the An(V/IV) couples showed acceptable agreement based on actinide-specific couples, with neutral hydroxides often favored in the +IV state. The An(IV/III) couples were consistent with literature values when modeled as soluble neutral hydroxides. The use of our approach yielded calculated redox potentials that were within ±0.2 V from experimental or estimated values consistent with our prior calculations on redox potentials of actinides from Ac to Am in acidic aqueous solutions. Finally, as a result, this supports the robustness of our DFT-based methodology for predicting actinide redox potentials, offering valuable insights for actinide chemistry in aqueous solutions.

Actinides↗
DOE OSTI2026

Scaling open-weight large language models for hydropower regulatory information extraction: A systematic analysis

Information extraction from regulatory and technical documents using large language models (LLMs) involves practical trade-offs between extraction quality and computational cost. We evaluate eight open-weight LLMs spanning 0.6B–70B parameters on hydropower licensing documents and report deployment-oriented evidence under a unified extraction schema and evaluation protocol. Across the model set, we observe clear scale-dependent trends in both baseline extraction quality and the effectiveness of reflective reasoning (self-checking) under our fixed-prompt, no-augmentation setting. Mid-scale models often provide a favorable balance of accuracy and efficiency, whereas the smallest models show limited or inconsistent gains from the reasoning variants tested. Larger models achieve the highest overall F1 scores but incur substantially greater compute and infrastructure requirements. We further find that reliability failure modes can distort conventional metrics in this domain: in particular, high recall can coincide with systematic extraction errors when models fabricate values for fields that are absent from the source text, underscoring the importance of conservative null handling and evidence-grounded evaluation. Overall, our study provides a reproducible resource–performance comparison for open-weight LLM-based extraction in hydropower regulatory documentation and offers practical guidance for model selection under different deployment constraints.

Evaluation protocol↗
NASA NTRS1971

A control-theory model for human decision-making

A model for human decision making is an adaptation of an optimal control model for pilot/vehicle systems. The models for decision and control both contain concepts of time delay, observation noise, optimal prediction, and optimal estimation. The decision making model was intended for situations in which the human bases his decision on his estimate of the state of a linear plant. Experiments are described for the following task situations: (a) single decision tasks, (b) two-decision tasks, and (c) simultaneous manual control and decision making. Using fixed values for model parameters, single-task and two-task decision performance can be predicted to within an accuracy of 10 percent. Agreement is less good for the simultaneous decision and control situation.

Levison, W. H.↗
NASA NTRS1973

Effect of blockage ratio on drag and pressure distributions for bodies of revolution at transonic speeds

Experimental data were obtained in two wind tunnels for 13 models over a Mach number range from 0.70 to 1.02. Effects of increasing test-section blockage ratio in the transonic region near a Mach number of 1.0 included change in the shape of the drag curves, premature drag creep, delayed drag divergence, and a positive increment of pressures on the model afterbodies. Effects of wall interference were apparent in the data even for a change in blockage ratio from a very low 0.000343 to an even lower 0.000170. Therefore, models having values of blockage ratio of 0.0003 - an order of magnitude below the previously considered safe value of 0.0050 - had significant errors in the drag-coefficient values obtained at speeds near a Mach number of 1.0. Furthermore, the flow relief afforded by slots or perforations in test-section walls - designed according to previously accepted criteria for interference-free subsonic flow - does not appear to be sufficient to avoid significant interference of the walls with the model flow field for Mach numbers very close to 1.0.

Couch, L. M.↗
NASA NTRS1986

Dynamic remapping decisions in multi-phase parallel computations

The effectiveness of any given mapping of workload to processors in a parallel system is dependent on the stochastic behavior of the workload. Program behavior is often characterized by a sequence of phases, with phase changes occurring unpredictably. During a phase, the behavior is fairly stable, but may become quite different during the next phase. Thus a workload assignment generated for one phase may hinder performance during the next phase. We consider the problem of deciding whether to remap a paralled computation in the face of uncertainty in remapping's utility. Fundamentally, it is necessary to balance the expected remapping performance gain against the delay cost of remapping. This paper treats this problem formally by constructing a probabilistic model of a computation with at most two phases. We use stochastic dynamic programming to show that the remapping decision policy which minimizes the expected running time of the computation has an extremely simple structure: the optimal decision at any step is followed by comparing the probability of remapping gain against a threshold. This theoretical result stresses the importance of detecting a phase change, and assessing the possibility of gain from remapping. We also empirically study the sensitivity of optimal performance to imprecise decision threshold. Under a wide range of model parameter values, we find nearly optimal performance if remapping is chosen simply when the gain probability is high. These results strongly suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change; precise quantification of the decision model parameters is not necessary.

Nicol, D. M.↗