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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Comparison of structurally diverse simulation models for prediction of epidemic outcomes caused by a long-distance dispersed pathogen

Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.

Dispersal kernel↗
NASA NTRS2019

Audibility of Multiple, Low-Frequency Tonal Signals in Noise

The main purpose of this study is to examine the audibility of multiple, low-frequency tones that are placed in distinct auditory channels. Three experiments are described, the goals of which are to determine if the presence of sound in multiple channels results in enhanced audibility and to assess the applicability of the Statistical Summation Model (SSM) to this frequency range. This model predicts that for the case of multiple signals that are in separate auditory channels, implying statistical independence, each with sensitivity value d prime of i, the resulting total sensitivity is given by the square root of the sum of the squares of the individual d prime of i values. In common with previous studies conducted at higher frequencies, the signals are pure tones and the maskers are broadband noise. The requirement that low frequency tones be placed in separate auditory filters limited the number of tones to a maximum of three. The first of the three experiments measured the change in masked thresholds for two- and three-tone signals relative to the level of the equally-detectable single tones. The multiple tone signals were composed of combinations of 55, 120 and 200 Hz tones. The measured changes in thresholds exceeded those predicted by the SSM, although they did not differ statistically from the model predictions. The second experiment employed the same overall approach but acquired more data and concentrated on the three-tone signal. Once again, the measured changes in masked threshold exceeded the model predictions, this time to a statistically-significant degree. Two issues were postulated with the potential to yield inflated changes in masked threshold: interaction between tones resulting in perceptible intermodulation/difference tones, and the assumption that the tones were in distinct auditory filters and statistically independent of one another. The third experiment used two sets of three-tone signals to address these latter concerns. The first set of three tones was composed of harmonically related tone frequencies of 55, 110 and 165 Hz, which was an attempt to reduce effects of intermodulation difference tones. The second set of three tones was chosen to be 110, 220 and 330 Hz, again reducing effects of difference tones, but also providing greater separation between tones. Results for the first set of three tones compared to those of the earlier experiments indicated that intermodulation was not an important effect. The second set of three tones (110, 220, 330 Hz) yielded changes in masked thresholds that, on average, were in good agreement with the SSM, although intersubject variability was large and prohibited a definitive conclusion regarding the concern that tone spacing was inadequate. The results of the three experiments showed that the masked threshold of sounds with multiple (two or three) equally-detectable low frequency tones was lower than those of the single tones. In other words, it is clear that audibility is enhanced by the presence of signals in multiple auditory filters. This finding is consistent with most previous research conducted at higher frequencies. In contrast with previous research, test subjects were, on average, able to detect multitone sounds at lower levels than those predicted using the SSM. Analyses that included Monte Carlo simulations showed that normally distributed errors in the single tone thresholds result in biased estimates of the thresholds of multitone sounds. This phenomenon is likely responsible for at least a substantial fraction of the unexpected deviation of measurements from SSM predictions.

Rafaelof, Menachem↗
NASA NTRS2012

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

MODIS aerosol retrievals↗
NASA NTRS2012

Model for Predicting the Performance of Planetary Suit Hip Bearing Designs

Designing a space suit is very complex and often requires difficult trade-offs between performance, cost, mass, and system complexity. During the development period of the suit numerous design iterations need to occur before the hardware meets human performance requirements. Using computer models early in the design phase of hardware development is advantageous, by allowing virtual prototyping to take place. A virtual design environment allows designers to think creatively, exhaust design possibilities, and study design impacts on suit and human performance. A model of the rigid components of the Mark III Technology Demonstrator Suit (planetary-type space suit) and a human manikin were created and tested in a virtual environment. The performance of the Mark III hip bearing model was first developed and evaluated virtually by comparing the differences in mobility performance between the nominal bearing configurations and modified bearing configurations. Suited human performance was then simulated with the model and compared to actual suited human performance data using the same bearing configurations. The Mark III hip bearing model was able to visually represent complex bearing rotations and the theoretical volumetric ranges of motion in three dimensions. The model was also able to predict suited human hip flexion and abduction maximums to within 10% of the actual suited human subject data, except for one modified bearing condition in hip flexion which was off by 24%. Differences between the model predictions and the human subject performance data were attributed to the lack of joint moment limits in the model, human subject fitting issues, and the limited suit experience of some of the subjects. The results demonstrate that modeling space suit rigid segments is a feasible design tool for evaluating and optimizing suited human performance. Keywords: space suit, design, modeling, performance

Cowley, Matthew S.↗
NASA NTRS2004

Analysis of Factors Affecting the Performance of RLV Thrust Cell Liners

The reusable launch vehicle (RLV) thrust cell liner, or thrust chamber, is a critical component of the Space Shuttle Main Engine (SSME). It is designed to operate in some of the most severe conditions seen in engineering practice. This requirement, in conjunction with experimentally observed 'dog-house' failure modes characterized by bulging and thinning of the cooling channel wall, provides the motivation to study the factors that influence RLV thrust cell liner performance. Factors or parameters believed to be directly related to the observed characteristic deformation modes leading to failure under in-service loading conditions are identified, and subsequently investigated using the cylindrical version of the higher-order theory for functionally graded materials in conjunction with the Robinson's unified viscoplasticity theory and the power-law creep model for modeling the response of the liner s constituents. Configurations are analyzed in which specific modifications in cooling channel wall thickness or constituent materials are made to determine the influence of these parameters on the deformations resulting in the observed failure modes in the outer walls of the cooling channel. The application of thermal barrier coatings and functional grading are also investigated within this context. Comparison of the higher-order theory results based on the Robinson and power-law creep model predictions has demonstrated that, using the available material parameters, the power-law creep model predicts more precisely the experimentally observed deformation leading to the 'dog-house' failure mode for multiple short cycles, while also providing much improved computational efficiency. However, for a single long cycle, both models predict virtually identical deformations. Increasing the power-law creep model coefficients produces appreciable deformations after just one long cycle that would normally be obtained after multiple cycles, thereby enhancing the efficiency of the analysis. This provides a basis for the development of an accelerated modeling procedure to further characterize dog-house deformation modes in RLV thrust cell liners. Additionally, the results presented herein have demonstrated that the mechanism responsible for deformation leading to 'dog-house' failure modes is driven by pressure, creep/relaxation and geometric effects.

Arnold, Steven M.↗
NASA NTRS1976

Autoignition - A liquid propellant explosive potential limiting phenomena

It has been thought that the unplanned mixing of the propellants of liquid launch vehicles could result in massive explosion and destruction. This paper presents results of NASA's attempt to develop a precise analytical theory and predictive model for liquid propellant explosives. Prediction model experiments involving a 'seven-chart' approach showing the relationship between yield function, mixing function, time dependence, chemical and physical reactant properties and quantity effects were used to establish a theory that autoignition takes place when propellants mix in a certain 'critical mass' or greater. An analytical confirmation of the theory has been carried out, with particular reference to possible autoignition in LOX/LH2 and LOX/RP-1 and Saturn V: it was confirmed that autoignition occurs and prevents the mixing of more than the 'critical mass' and therefore limits the explosive yield to several thousand pounds, which will disperse the remaining propellant and prohibit detonation of the total quantities otherwise suspected.

Boggs, W. H.↗
NASA NTRS1985

The Space Shuttle Orbiter molecular environment induced by the supplemental flash evaporator system

The water vapor environment of the Space Shuttle Orbiter induced by the supplemental flash evaporator during the on-orbit flight phase has been analyzed based on Space II model predictions and orbital flight measurements. Model data of local density, column density, and return flux are presented. Results of return flux measurements with a mass spectrometer during STS-2 and of direct flux measurements during STS-4 are discussed and compared with model predictions.

Ehlers, H. K. F.↗
NASA NTRS2008

Using an Informative Missing Data Model to Predict the Ability to Assess Recovery of Balance Control after Spaceflight

Astronauts show degraded balance control immediately after spaceflight. To assess this change, astronauts' ability to maintain a fixed stance under several challenging stimuli on a movable platform is quantified by "equilibrium" scores (EQs) on a scale of 0 to 100, where 100 represents perfect control (sway angle of 0) and 0 represents data loss where no sway angle is observed because the subject has to be restrained from falling. By comparing post- to pre-flight EQs for actual astronauts vs. controls, we built a classifier for deciding when an astronaut has recovered. Future diagnostic performance depends both on the sampling distribution of the classifier as well as the distribution of its input data. Taking this into consideration, we constructed a predictive ROC by simulation after modeling P(EQ = 0) in terms of a latent EQ-like beta-distributed random variable with random effects.

Feiveson, Alan H.↗
NASA NTRS1975

An elementary psychophysical model to predict ride comfort in the combined stress of multiple degrees of freedom

The quality of airplane rides probably will become increasingly important to passengers, particularly in terminal area operations and on short haul trips. The development of models to predict ride comfort is considered. An elementary model concept is presented herein and compared with subjective ride comfort response ratings measured on actual scheduled airline flights and simulated flights.

Stone, R. W., Jr.↗
NASA NTRS2013

Characterization of the 2012-044C Briz-M Upper Stage Breakup

The NASA breakup model prediction was close to the observed population for catalog objects. The NASA breakup model predicted a larger population than was observed for objects under 10 cm. The stare technique produces low observation counts, but is readily comparable to model predictions. Customized stare parameters (Az, El, Range) were effective to increase the opportunities for HAX to observe the debris cloud. Other techniques to increase observation count will be considered for future breakup events.

Hamilton, Joseph A.↗
DOE OSTI2026

Learning earthquake ground motions via conditional generative modeling

Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake locations, while physics-based methods are computationally intensive and require accurate representations of Earth structures and earthquake sources. We propose an artificial intelligence (AI) spectrogram generator, Conditional Generative Modeling for Ground Motion (CGM-GM). CGM-GM leverages earthquake magnitudes and geographic coordinates of earthquakes and sensors as inputs, when postprocessed with phase information, capturing spatially continuous Fourier amplitude spectra (FAS) as well as properties such as P and S arrivals, and waveform durations, without explicit physics constraints. This is achieved through a probabilistic autoencoder that extracts latent distributions in the time-frequency domain and variational sequential models for prior and posterior distributions. We evaluate the performance of CGM-GM using small-magnitude earthquake records from the San Francisco Bay Area, a region with high seismic risks. Here, we report that CGM-GM demonstrates potential for complementing physics-based simulations and non-ergodic empirical ground motion models, as well as shows promise in seismology and beyond.

geophysics↗
DOE OSTI2024

Regional climate change: consensus, discrepancies, and ways forward

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗
DOE OSTI2025

Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely-varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of four in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). Further, in addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

A 3D Model to Predict Explicit Morphologies and Volume Fraction of Lack-of-Fusion Pores Generated in Selective Laser Melting Processes

The performance of an additively manufactured (AM) component is dependent on the distribution of process-induced defects in addition to the complex microstructure of the material, surface roughness of the component and the process-induced residual stresses. For instance, it has been well demonstrated that lack-of-fusion (LoF) pores produced in the selective laser melting (SLM) AM process can significantly limit the fatigue performance of the material. Although two-dimensional (2D) models exist to predict the 2D profiles of LoF pores, the 2D pore profiles cannot be directly inserted into a three-dimensional (3D) microstructure domain that is output from several prevailing process simulation packages. A few commercial packages that simulate the SLM process can predict LoF pores in a 3D domain, but the morphologies of LoF pores are voxelated and hence do not capture sharp corners of the pores, thereby obviating their use in fatigue crack initiation studies. In order to address the aforementioned gaps, a high-fidelity model that predicts not only the volume fraction, but also the explicit 3D morphologies and spatial distributions of LoF pores has been developed using a computer aided design-based environment. The model has been partially validated for Ti-6Al-4V alloy by comparing the predictions of the volume fraction of LoF pores predicted by the model with experimental data obtained from the literature. Absolute error in predicted volume fraction of LoF pores varied between 5.16% and 1.87% for energy density values between 13 J/mm3 and 45 J/mm3 where a significant amount (over 3% volume fraction) of LoF porosity was measured. The absolute error was within 1.87% for energy density values greater than 45 J/mm3.

Saikumar R. Yeratapally↗
NASA NTRS2013

The Mars Science Laboratory (MSL) MMRTG In-Flight: A Power Update

The MSL Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) was fueled on October 28, 2008 by the Department Of Energy (DOE) in preparation for a late 2009 launch. Shortly after, the MSL launch was delayed approximately 2 years until 2011. The fueled MMRTG was placed in storage to await the new date for liftoff. Occasional measurements of the MMRTG's power output were taken and compared with power predictions that pre-dated fueling. An error in the predictive models was quickly recognized and remedied. The resultant predictions, while improved, carried significant uncertainty. This uncertainty did not deter the launch of MSL, but did alter the planned mission on the surface of Mars. Once launched, the MSL spacecraft provided a hi-fidelity telemetry stream measuring the generator's electrical and thermal performance. These data were used to update the predictive models and a new prediction of the performance of the MMRTG on the surface of Mars was run just before Entry, Descent, and Landing (EDL) at Mars. The MSL MMRTG is working extremely well, providing power above predictions and operating within its flight allowable temperature limits. The generator was producing approximately 114 W at the beginning of the surface mission. This paper will elaborate on power modeling for the MSL MMRTG along with a review of some of the data recorded from the MSL cruise to Mars, EDL, and the early days of the surface mission.

thermoelectric↗
NASA NTRS1990

A study of turbulence models for prediction of transitional boundary layers

Calculations of two-dimensional transitional boundary layer flows in zero and favorable pressure gradients are presented. The major focus is on the evaluation of current turbulence models to predict quantities such as skin-friction and heat transfer coefficients. Three turbulence models using the mixing length concept along with a one-equation model are considered. These models are tested by comparison with the experiments of Blair and Werle, who investigated flows over a heated flat plate for various levels of free-stream turbulence.

Abid, Ridha↗
NASA NTRS1992

AMTEC system performance studies using the detailed electrode kinetic and transport model

A detailed electrochemical model of the alkali metal thermoelectric converter (AMTEC) electrode and current collector grid has been developed recently. Comparative evaluations of the resulting differences in model predictions reveal that the new detailed model predicts up to 50 percent higher electrode power densities at condenser operating temperatures above 600 K. The new model, with experimentally determined parameters, was used to recalculate the projected system performance of previously reported 1- and 100-kWe AMTEC space power systems that had incorporated earlier electrolyte/electrode models. It was found that when the detailed model was used to determine the electrode power densities, enhanced specific power and efficiencies are predicted.

Sievers, Robert K.↗