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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Cavitation Effects on the Structural Dynamics of Turbomachinery Components

The structural integrity of inducer and impeller blades in rocket engine turbo machinery must be evaluated in the face of complex excitation mechanisms including fluctuating pressures due to cavitation. Cavitation occurs when the local fluid pressure drops below the vapor pressure, causing the formation of vapor-filled bubbles. Cavitation can exist to various extents within the typical operating range of rocket engine turbo pumps. Despite recent progress towards reducing uncertainties in structural dynamic models of turbo machinery components, the extent to which pump cavitation affects the structural dynamic properties (i.e., natural frequencies, damping, and mode shapes) of inducer and impeller blades remains largely unknown. To study the structural dynamic effects of cavitating flows, experiments are conducted in a high-speed water tunnel. The test article is a low aspect ratio cantilevered plate, thus mimicing a single inducer blade that is unwrapped from its hub. The test article is oriented at zero angle of attack and has a triangular trip at its leading edge to induce cavitation. To change the extent of cavitation, the static pressure of the water tunnel is controlled. A high-speed camera is used to quantify the coverage of the cavitation sheet.

Structural Dynamics↗
DOE OSTI2025

Data and scripts from: “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”

This data package includes data and scripts from the manuscript “Denoising autoencoder for reconstructing sensor observation data and predicting evapotranspiration: noisy and missing values repair and uncertainty quantification”.The study addressed common challenges faced in environmental sensing and modeling, including uncertain input data, missing sensor observations, and high-dimensional datasets with interrelated but redundant variables. Point-scaled meteorological and soil sensor observations were perturbed with noises and missing values, and denoising autoencoder (DAE) neural networks were developed to reconstruct the perturbed data and further predict evapotranspiration. This study concluded that (1) the reconstruction quality of each variable depends on its cross-correlation and alignment to the underlying data structure, (2) uncertainties from the models were overall stronger than those from the data corruption, and (3) there was a tradeoff between reducing bias and reducing variance when evaluating the uncertainty of the machine learning models.This package includes:(1) Four ipython scripts (.ipynb): “DAE_train.ipynb” trains and evaluates DAE neural networks, “DAE_predict.ipynb” makes predictions from the trained DAE models, “ET_train.ipynb” trains and evaluates ET prediction neural networks, and “ET_predict.ipynb” makes predictions from trained ET models.(2) One python file (.py): “methods.py” includes all user-defined functions and python codes used in the ipython scripts.(3) A “sub_models” folder that includes five trained DAE neural networks (in pytorch format, .pt), which could be used to ingest input data before being fed to the downstream ET models in ‘ET_train.ipynb” or ‘ET_predict.ipynb’.(4) Two data files (.csv). Daily meteorological, vegetation, and soil data is in “df_data.csv”, where “df_meta.csv” contains the location and time information of “df_data.csv”. Each row (index) in “df_meta.csv” corresponds to each row in “df_data.csv”. These data files are formatted to follow the data structure requirements and be directly used in the ipython scripts, and they have been shuffled chronologically to train machine learning models. The meteorological and soil data was collected using point sensors between 2019-2023 at(4.a) Three shrub-dominated field sites in East River, Colorado (named “ph1”, “ph2” and “sg5” in “df_meta.csv”, where “ph1” and “ph2” were located at PumpHouse Hillslopes, and “sg5” was at Snodgrass Mountain meadow) and(4.b) One outdoor, mesoscale, and herbaceous-dominated experiment in Berkeley, California (named “tb” in “df_meta.csv”, short for Smartsoils Testbed at Lawrence Berkeley National Lab).- See "df_data_dd.csv" and "df_meta_dd.csv" for variable descriptions and the Methods section for additional data processing steps. See "flmd.csv" and "README.txt" for brief file descriptions.- All ipython scripts and python files are written in and require PYTHON language software.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Observer-based robust-H-infinity control laws for uncertain linear systems

Based on the algebraic Riccati equation approach, this paper presents a simple and flexible method for designing observer-based robust-H-infinity control laws for linear systems with structured parameter uncertainty. The observer-based robust-H-infinity output-feedback control law, obtained by solving three augmented algebraic Riccati equations, provides both robust stability and disturbance attenuation with H-infinity-norm bound for the closed-loop uncertain linear system. Several tuning parameters are embedded into the augmented algebraic Riccati equations so that flexibility in finding the symmetric positive-definite solutions (and hence, the robust-H-infinity control laws) is significantly increased. A benchmark problem associated with a mass-spring system, which approximates the dynamics of a flexible structure, is used to illustrate the design methodologies, and simulation results are presented.

Shieh, Leang S.↗
NASA NTRS1990

Methods for evaluating the predictive accuracy of structural dynamic models

Uncertainty of frequency response using the fuzzy set method and on-orbit response prediction using laboratory test data to refine an analytical model are emphasized with respect to large space structures. Two aspects of the fuzzy set approach were investigated relative to its application to large structural dynamics problems: (1) minimizing the number of parameters involved in computing possible intervals; and (2) the treatment of extrema which may occur in the parameter space enclosed by all possible combinations of the important parameters of the model. Extensive printer graphics were added to the SSID code to help facilitate model verification, and an application of this code to the LaRC Ten Bay Truss is included in the appendix to illustrate this graphics capability.

Hasselman, T. K.↗
DOE OSTI2023

Multi-fidelity Uncertainty Quantification for Homogenization Problems in Structure-Property Relationships from Crystal Plasticity Finite Elements

Crystal plasticity finite element method (CPFEM) has been an integrated computational materials engineering (ICME) workhorse to study materials behaviors and structure-property relationships for the last few decades. These relations are mappings from the microstructure space to the materials properties space. Due to the stochastic and random nature of microstructures, there is always some uncertainty associated with materials properties, for example, in homogenized stress-strain curves. For critical applications with strong reliability needs, it is often desirable to quantify the microstructure-induced uncertainty in the context of structure-property relationships. However, this uncertainty quantification (UQ) problem often incurs a large computational cost because many statistically equivalent representative volume elements (SERVEs) are needed. In this article, we apply a multi-level Monte Carlo (MLMC) method to CPFEM to study the uncertainty in stress-strain curves, given an ensemble of SERVEs at multiple mesh resolutions. By using the information at coarse meshes, we show that it is possible to approximate the response at fine meshes with a much reduced computational cost. We focus on problems where the model output is multi-dimensional, which requires us to track multiple quantities of interest (QoIs) at the same time. In conclusion, our numerical results show that MLMC can accelerate UQ tasks around 2.23x, compared to the classical Monte Carlo (MC) method, which is widely known as ensemble average in the CPFEM literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey. II. Anisotropic Large-scale Coherence in Hot Gas, Galaxies, and Dark Matter

Statistics that capture the directional dependence of the baryon distribution in the cosmic web enable unique tests of cosmology and astrophysical feedback. We use constrained oriented stacking of thermal Sunyaev–Zel’dovich (tSZ) maps to measure the anisotropic distribution of hot gas 2.5–40 Mpc away from galaxy clusters embedded in massive filaments and superclusters. The cluster selection and orientation (at a scale of ∼15 Mpc) use Dark Energy Survey (DES) Year 3 data, while expanded tSZ maps from the Atacama Cosmology Telescope Data Release 6 enable a ∼3× more significant measurement of the extended gas compared to the technique’s proof-of-concept. Decomposing stacks into cosine multipoles of order m , we detect a dipole ( m = 1) and quadrupole ( m = 2) at 8σ–10σ, as well as evidence for m = 4 signal at up to 6σ, indicating sensitivity to late-time non-Gaussianity. We compare to Cardinal simulations with spherical gas models pasted onto dark matter halos. The fiducial tSZ data can discriminate between two models that deplete pressure differently in low-mass halos (mimicking astrophysical feedback), preferring higher average pressure in extended structures. However, uncertainty in the amount of cosmic infrared background contamination reduces the constraining power. Additionally, we apply the technique to DES galaxy density and weak lensing to study for the first time their oriented relationships with tSZ. In the tSZ-to-lensing relation, averaged on 7.5 Mpc (transverse) scales, we observe dependence on redshift but not shape or radial distance. Thus, on large scales, the superclustering of gas pressure, galaxies, and total matter is coherent in shape and extent.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

DESI peculiar velocity survey – Fundamental Plane

The Dark Energy Spectroscopic Instrument (DESI) peculiar velocity survey aims to measure the peculiar velocities of early- and late-type galaxies within the DESI footprint using both the Fundamental Plane and optical Tully–Fisher relations. Direct measurements of peculiar velocities can significantly improve constraints on the growth rate of structure, reducing uncertainty by a factor of approximately 2.5 at redshift 0.1 compared to the DESI Bright Galaxy Survey’s redshift space distortion measurements alone. We assess the quality of stellar velocity dispersion measurements from DESI spectroscopic data. These measurements, along with photometric data from the Legacy Survey, establish the Fundamental Plane relation and determine distances and peculiar velocities of early-type galaxies. During survey validation, we obtain spectra for 6698 unique early-type galaxies, up to a photometric redshift of 0.15. 64 per cent of observed galaxies (4267) have relative velocity dispersion errors below 10 per cent. This percentage increases to 75 per cent if we restrict our sample to galaxies with spectroscopic redshifts below 0.1. We use the measured central velocity dispersion, along with photometry from the DESI Legacy Imaging Surveys, to fit the Fundamental Plane parameters using a 3D Gaussian maximum likelihood algorithm that accounts for measurement uncertainties and selection cuts. In addition, we conduct zero-point calibration using the absolute distance measurements to the Coma cluster, leading to a value of the Hubble constant, H 0 = 76.05 ± 0.35 (statistical) ±0.49 (systematic Fundamental Plane) ±4.86 (statistical due to calibration) km s –1 Mpc –1 ⁠. This H 0 value is within 2σ of Planck cosmic microwave background results and within 1σ of other low-redshift distance indicator-based measurements.

cosmological parameters↗
DOE OSTI2021

Probabilistic learning on manifolds constrained by nonlinear partial differential equations for small datasets

A novel extension of the Probabilistic Learning on Manifolds (PLoM) is presented. It makes it possible to synthesize solutions to a wide range of nonlinear stochastic boundary value problems described by partial differential equations (PDEs) for which a stochastic computational model (SCM) is available and which depend on a vector-valued random control parameter. The cost of a single numerical evaluation of this SCM is assumed to be such that only a limited number of points can be computed for constructing the training dataset (small data). Each point of the training dataset is made up of realizations from a vector-valued stochastic process (the stochastic solution) and the associated random control parameter on which it depends. The presented PLoM constrained by PDE allows for generating a large number of learned realizations of the stochastic process and its corresponding random control parameter. These learned realizations are generated so as to minimize the vector-valued random residual of the PDE in the mean-square sense. Appropriate novel methods are developed to solve this challenging problem. Three applications are presented. The first one is a simple uncertain nonlinear dynamical system with a nonstationary stochastic excitation. The second one concerns the 2D nonlinear unsteady Navier–Stokes equations for incompressible flows in which the Reynolds number is the random control parameter. Here, the last one deals with the nonlinear dynamics of a 3D elastic structure with uncertainties. The results obtained make it possible to validate the PLoM constrained by stochastic PDE but also provide further validation of the PLoM without constraint.

Machine learning↗
DOE OSTI2025

A critical verification of beam and shell models of wind turbine blades

Ever-increasing wind turbine size has challenged predictive capabilities on several fronts. Here, to address part of the blade structural modeling uncertainty, a systematic model fidelity comparison study was conducted on commonly used finite elements. pyNuMAD was utilized to create beam, shell, and solid models of a 100 m long blade undergoing large static deflections. The solid model avoided the use of layered-solid elements by resolving core and facesheet layers. An unprecedented model with 73.7 million elements revealed insights that have never been possible from prior experimental and numerical studies. As compared to the solid element model, the tip deflection from the shell and beam model was found to be about 2% and 4.3% too low, respectively. The twist from the beam model was found to be about 5.6% too high, while the twist from shell model was 24% too low, though improvement was demonstrated with mesh refinement. The beam model adhesive stresses were more accurate than the shell model. Out-of-plane stresses were of great significance near geometric and material discontinuities, and neither the shell nor beam model captured these effects well. Failure predictions from beam, shell, or layered-solid models are unlikely to be reliable at trailing edges, adhesives, ply-drops, spar-cap boundaries.

17 WIND ENERGY↗
DOE OSTI2026

ROADRUNNER uranium nitride MiniFuel: Experimental design, fabrication and pre-irradiation baseline characterization for accelerated burnup testing

Uranium nitride (UN) is a promising fuel candidate for advanced reactor systems owing to its high uranium density and thermal conductivity; however, its qualification remains constrained by the scarcity of well-controlled irradiation performance data. Here, to address this limitation, the ROADRUNNER (Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments) campaign employs the MiniFuel platform in the High Flux Isotope Reactor (HFIR) to enable accelerated burnup irradiation testing under tightly controlled and largely isothermal conditions. This paper presents the experimental design, fuel fabrication, and pre-irradiation baseline characterization of the ROADRUNNER UN MiniFuel campaign. Thirty-six UN minidisc specimens were fabricated with systematically varied as-fabricated density (86–96% of theoretical density), carbon impurity content (961–5240 ppm), oxygen content (≤ ∼2000 ppm), and grain size (2.5–24 μm). The irradiation matrix spans nominal fuel temperatures of 873 K, 1173 K, and 1473 K and target burnups of 3.75%, 6.0%, and 7.5% fissions per initial metal atom (FIMA). Neutronic and thermal analyses were performed to define specimen-specific burnup accumulation and temperature histories, establishing the boundary conditions for subsequent in-pile behavior. Comprehensive pre-irradiation characterization—including dimensional metrology, density verification, impurity analysis, X-ray diffraction, Raman spectroscopy, scanning electron microscopy, X-ray computed tomography, and confocal profilometry—provides a detailed baseline for post-irradiation examination. Pre-irradiation data were further used to generate predictive estimates of fission gas release and swelling using existing empirical correlations. This quantitative comparison reveals substantial inter-model divergence at intermediate and elevated temperatures that exceeds propagated input uncertainties, highlighting structural gaps in the historical irradiation database. The ROADRUNNER irradiation campaign is currently underway in HFIR, with initial firs cycle completed in late 2025 and remaining targets scheduled through 2027. The experimental design and baseline dataset presented here establish the framework needed to interpret forthcoming post-irradiation measurements and to provide discriminating data for the validation and refinement of physics-based UN fuel performance models.

Lopes, Denise Adorno [Oak Ridge National Laborator↗
DOE OSTI2025

Impacts of irrigation expansion on moist-heat stress based on IRRMIP results

Irrigation rapidly expanded during the 20 th century, affecting climate via water, energy, and biogeochemical changes. Previous assessments of these effects predominantly relied on a single Earth System Model, and therefore suffered from structural model uncertainties. Here we quantify the impacts of historical irrigation expansion on climate by analysing simulation results from six Earth system models participating in the Irrigation Model Intercomparison Project (IRRMIP). Results show that irrigation expansion causes a rapid increase in irrigation water withdrawal, which leads to less frequent 2-meter air temperature heat extremes across heavily irrigated areas (≥4 times less likely). However, due to the irrigation-induced increase in air humidity, the cooling effect of irrigation expansion on moist-heat stress is less pronounced or even reversed, depending on the heat stress metric. In summary, this study indicates that irrigation deployment is not an efficient adaptation measure to escalating human heat stress under climate change, calling for carefully dealing with the increased exposure of local people to moist-heat stress.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Ground-based thermal IR images of Comet Tempel 2

The 10.8-micron images of Comet Tempel 2 obtained on the four days from September 21 to 24, 1988, indicate that the dust coma contributed about half of the nuclear pixel brightness. The nuclear condensation brightness exhibited a temporal variability slightly larger than observational uncertainty. The structure of the observed extended dust emission is interpretable as (1) a large grain tail primarily generated by cm-scaled particles, (2) the result of an outburst near 2.5-3.0 AU perihelion, and (3) a sunward emission of dust in a fanlike pattern.

Campins, Humberto↗
NASA NTRS1991

A vision-based end-point control for a two-link flexible manipulator

The measurement and control of the end-effector position of a large two-link flexible manipulator are investigated. The system implementation is described and an initial algorithm for static end-point positioning is discussed. Most existing robots are controlled through independent joint controllers, while the end-effector position is estimated from the joint positions using a kinematic relation. End-point position feedback can be used to compensate for uncertainty and structural deflections. Such feedback is especially important for flexible robots. Computer vision is utilized to obtain end-point position measurements. A look-and-move control structure alleviates the disadvantages of the slow and variable computer vision sampling frequency. This control structure consists of an inner joint-based loop and an outer vision-based loop. A static positioning algorithm was implemented and experimentally verified. This algorithm utilizes the manipulator Jacobian to transform a tip position error to a joint error. The joint error is then used to give a new reference input to the joint controller. The convergence of the algorithm is demonstrated experimentally under payload variation. A Landmark Tracking System (Dickerson, et al 1990) is used for vision-based end-point measurements. This system was modified and tested. A real-time control system was implemented on a PC and interfaced with the vision system and the robot.

Obergfell, Klaus↗
NASA NTRS1988

Uncertainties in large space systems

Uncertainties of a large space system (LSS) can be deterministic or stochastic in nature. The former may result in, for example, an energy spillover problem by which the interaction between unmodeled modes and controls may cause system instability. The stochastic uncertainties are responsible for mode localization and estimation errors, etc. We will address the effects of uncertainties on structural model formulation, use of available test data to verify and modify analytical models before orbiting, and how the system model can be further improved in the on-orbit environment.

Fuh, Jon-Shen↗
NASA NTRS2001

Space Shuttle RTOS Bayesian Network

With shrinking budgets and the requirements to increase reliability and operational life of the existing orbiter fleet, NASA has proposed various upgrades for the Space Shuttle that are consistent with national space policy. The cockpit avionics upgrade (CAU), a high priority item, has been selected as the next major upgrade. The primary functions of cockpit avionics include flight control, guidance and navigation, communication, and orbiter landing support. Secondary functions include the provision of operational services for non-avionics systems such as data handling for the payloads and caution and warning alerts to the crew. Recently, a process to selection the optimal commercial-off-the-shelf (COTS) real-time operating system (RTOS) for the CAU was conducted by United Space Alliance (USA) Corporation, which is a joint venture between Boeing and Lockheed Martin, the prime contractor for space shuttle operations. In order to independently assess the RTOS selection, NASA has used the Bayesian network-based scoring methodology described in this paper. Our two-stage methodology addresses the issue of RTOS acceptability by incorporating functional, performance and non-functional software measures related to reliability, interoperability, certifiability, efficiency, correctness, business, legal, product history, cost and life cycle. The first stage of the methodology involves obtaining scores for the various measures using a Bayesian network. The Bayesian network incorporates the causal relationships between the various and often competing measures of interest while also assisting the inherently complex decision analysis process with its ability to reason under uncertainty. The structure and selection of prior probabilities for the network is extracted from experts in the field of real-time operating systems. Scores for the various measures are computed using Bayesian probability. In the second stage, multi-criteria trade-off analyses are performed between the scores. Using a prioritization of measures from the decision-maker, trade-offs between the scores are used to rank order the available set of RTOS candidates.

Morris, A. Terry↗
NASA NTRSDate not supplied

A Framework for Evaluating Climate Model Performance Metrics

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables?e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to overproduce precipitation, this result could indicate that the metric is effective in identifying models which simulate more realistic precipitation. Ultimately, the goal of the framework is to identify performance metrics for advising better methods for ensemble averaging models and create better climate predictions.

Noel C Baker↗
DOE OSTI2021

A General Strategy for Batch Development of High-Performance and Cost-Effective Sodium Layered Cathodes

High-performance and low-cost transition metal (TM) layered oxides using earth abundant elements are promising cathodes for Na-ion batteries. However, it is challenging to obtain desired materials because the large Na size, different Na occupations and various layer stacking sequences multiply the complication in determining the structure of a given composition and exacerbate uncertainty to the structure-property correlation. In this work, we use the attainment of desired NaxMnyNiZTM1-y-zO2-based cathode materials as an example to demonstrate a general roadmap for batch development of sodium layered cathodes towards practical applications. A synthesis phase diagram of NaxMnyNi1-yO2 was created for pre-screening and rational selection of the platform material of P2/O3-structured Na0.85Mn0.6Ni0.4O2. Cationic potential was leveraged in elemental substitution to further promote the material structural stability and electrochemical performance. Several cost-effective O3 and P2/O3 hybrid cathode materials have been obtained, all of which demonstrate excellent performance. In particular, the Na0.85Mn0.5Ni0.4Ti0.1O2 delivers a high specific capacity of ~130 mAh/g between 2-4 V and 91% retention after 500 cycles. The work discovers multiple materials as high-performance and cost-effective Na-ion battery cathodes and offers critical guidance to the rational design of future layered cathode materials.

Xiao, Biwei↗
NASA NTRS1990

Robust tracking of a flexible spacecraft subject to induced disturbances and parametric uncertainties

A variable structure control technique combined with an operator spline for bilinear systems is implemented to a fast moving deformable structure for purposes of achieving robust tracking performance. The control torque applied to the structure is based on estimates of the structure parameters and on upper bounds of the model errors. For a rapid rotation of the deformable structure, the elastic response can be modeled by oscillators driven by angular acceleration, where stiffness and damping coefficients are also angular velocity and acceleration dependent. By transforming this 'slew-driven' elastic dynamics into a bilinear form, an operator spline can be constructed, that gives a low order estimate of the induced disturbance. An upper bound between the estimated deformation and the unknown exact deformation is also generated, which can be used where required in the sliding control correction.

Karray, Fakhreddine↗