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Results for “Short-Term Testing”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Advancing stream temperature prediction with a generalizable large-sample framework across CONUS river reaches

Accurately predicting stream temperature in ungauged basins remains a critical challenge for water resource management, thermoelectric power plant cooling, and ecosystem conservation. Large-sample machine learning models trained on hundreds of well-monitored river basins have shown remarkable performance; however, such models have yet to be developed solely using forcing data that can be readily extracted to simulate stream temperatures anywhere in the contiguous United States (CONUS). In this study, we present a scalable, large-sample deep learning framework using Long Short-Term Memory (LSTM) networks to simulate daily stream temperatures in ungauged basins across the CONUS. The framework leverages both modeled reanalysis of meteorological and streamflow inputs as well as static attributes available for all 2.7 million CONUS river reaches in the National Hydrography Dataset Plus (NHDPlusV2). By generating dynamical inputs from predefined thermally relevant upstream contributing areas, rather than the entire upstream basin, the model also offers improvements in very large basins where full-basin averaging can dilute the most important influences on stream temperature. Evaluated across 300 basins, the model achieves a median Mean Absolute Error (MAE) of 1.1 °C and a Nash-Sutcliffe Efficiency (NSE) of 0.95 on temporally and spatially distinct test folds—comparable to models trained exclusively using meteorological and streamflow observational data. The flexible, high-performing framework generalizes to any unmonitored river reach without significant regulation or unnatural thermal input immediately upstream, substantially expanding predictive capabilities in data-scarce regions.

Hydrology↗
NASA NTRS1979

Plasma volume during stress in man - Osmolality and red cell volume

The purpose was (1) to test the hypothesis that in man there is a range of plasma osmolality within which the red cell volume (RCV) and mean corpuscular volume (MCV) remain essentially constant and (2) to determine the upper limit of this range. During a variety of stresses - submaximal and maximal exercise, heat and altitude exposure, +Gz acceleration, and tilting - changes in plasma osmolality between -1 and +13 mosmol/kg resulted in essentially no change in the regression of percent change in plasma volume (PV) calculated from a change in hematocrit (Hct) on that calculated from a change in Hct + hemoglobin (Hb), i.e., the RCV and MCV were constant. Factors that do not influence RCV are the level of metabolism, heat exposure at rest, and short-term orthostasis (heat-to-foot acceleration). Factors that may influence RCV are exposure to high altitude and long-term orthostasis (head-up tilting). Factors that definitely influence RCV are prior dehydration and extended periods of stress. Thus, either the Hct or the Hct + Hb equations can be used to calculate percent changes in PV under short-term periods of stress when the change in plasma osmolality is less than 13 mosmol/kg.

Greenleaf, J. E.↗
NASA NTRS1977

Short-term variations of the galactic cosmic ray intensity - 1964-1967

A statistical analysis of time variations in ground-level nucleonic cosmic-ray intensity for the interval from 1964 to 1967 is presented which incorporates synoptic observations of the solar white-light corona as well as indices of photospheric and chromospheric activity. Correlation analysis of solar activity and short-term modulation reveals that all indices vary significantly on time scales near the solar rotation period and that the correlation function exhibits a quasi-sinusoidal variation that maximizes near zero lag. It is found that 27-day variations of the indices were most pronounced in 1966-1967, that recurrent cosmic-ray depressions occurred in conjunction with observed solar-wind disturbances, and that two categories of interplanetary disturbance are sufficient to account for the large recurrent cosmic-ray depressions in 1966-1967. It is suggested that flare-generated shocks were the main source of these recurrent cosmic-ray variations and that the contribution of corotating cosmic-ray disturbances to the observed recurrent modulation was probably very small. This hypothesis is tested against the correlation functions of solar and cosmic-ray indices.

Parker, G. D.↗
NASA NTRS1974

Helicopter derivative identification from analytic models and flight test data

Recent results of stability derivative identification from helicopter analytic models and flight test data are presented. Six and nine degree-of-freedom (DOF) linear models are identified from an analytic nonlinear helicopter simulation using a least square technique. The identified models are compared with the convectional partial differentiation method for obtaining derivatives to form the basis for interpretation of derivatives identified from flight data. Six degree-of-freedom models are identified from CH-53A and CH-54B flight data, using an extended Kalman filter modified to process several maneuvers simultaneously. The a priori derivative estimate is obtained by optimal filtering of the data and then using a least square method. The results demonstrate that a six DOF identified model is sufficient to determine the low frequency modes of motion, but a nine DOF rotor/body model is necessary for proper representation of short-term response.

Molusis, J. H.↗
NASA NTRS1984

The system design of a rubidium maser frequency standard

The Rubidium Maser Frequency Standard is a precision frequency source with excellent short-term stability. A type PBR-II Rb maser frequency standard was developed by the Beijing Institute of Radio Metrology and Measurement (BIRMM). The time-domain frequency stability (two-sample variance) of this frequency standard is less than 1/5 times 10 to the 13th power for t=10ms yields 1.0s, fh=1.0 KHz. Two PBR-II frequency standards were used as reference frequency sources in a frequency stability measurement system. Some important system characteristics for the PBR-II Rb maser frequency standard such as phase noise and frequency stability transfer characteristics are discussed. Furthermore, the design of the frequency standard for optimum frequency stability of the output signal; the choice of a voltage controlled crystal oscillator for the frequency standard; the design of the phase-locked loop; and the frequency stability test results on the PBR-II are discussed.

Xiong, C. X.↗
DOE OSTI2025

Enhancing 2D hydrodynamic flood models through machine learning and urban drainage integration

Two-dimensional hydrodynamic flood models are commonly employed for simulating flood extent and inundation depth. However, the influence of urban drainage network (UDN) is frequently overlooked in these models, potentially compromising their accuracy. Furthermore, the expensive computational costs and longer processing times make them challenging for large-scale hydrodynamic simulation. To address these challenges, this paper develops a machine learning (ML)-driven emulator for an open-source flood model, the Two-dimensional Runoff Inundation Toolkit for Operational Needs (TRITON). A TRITON-ML Emulator (TR-Emulator) that utilizes Convolutional Long Short-Term Memory is developed to capture the spatiotemporal features of flood events based on the outputs from TRITON. We further enhance the emulator by integrating UDN parameters (TR-UDN), such as the flow capacity of drainage pipes, pipe size, and pipe length, via an ML stacking technique to improve the water surface elevation (WSE) simulation. Hurricane Harvey 2017 in Houston, TX is used as the case study. We compare WSE results from TRITON, TR-Emulator, TR-UDN, and the United States Geological Survey (USGS) observations to evaluate the performance of these models. The results indicate that the TR-Emulator effectively replicates the WSE simulated by TRITON. Additionally, TR-UDN performs well in capturing WSE patterns and peak flows, aligning more closely with USGS observations, except in areas with milder slopes where conveyance discrepancies are observed. We further test the generalizability of our ML-based models using another smaller event. This paper shows that the TR-Emulator is effective for users and engineers to emulate a 2D hydrodynamic model, and the enhanced version of the TR-Emulator, TR-UDN, can be an efficient tool for predicting WSEs during urban flooding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Knowledge-guided graph machine learning for spatially distributed prediction of daily discharge and nitrogen export dynamics

Spatially distributed prediction of streamflow and nitrogen export dynamics is essential for precision management of agricultural watersheds. While temporal deep learning models such as Long Short-Term Memory (LSTM) have shown strong performance at basin scales, their ability to generalize spatially is limited by insufficient representation of spatial dependencies and flow paths, particularly under data-scarce conditions. To address this gap, we propose HydroGraphNet, a knowledge-guided graph machine learning framework that integrates process-based knowledge and explicit spatial learning into temporal modeling. This framework incorporates directed graph topology to encode watershed connectivity and upstream inflows, with mass balance constraints to improve physical consistency. To enhance generalization in sparsely monitored regions, HydroGraphNet is pretrained on synthetic data generated by the SWAT+ (Soil and Water Assessment Tool Plus) model. We evaluated HydroGraphNet in the Upper Sangamon River Basin (44 HUC-12 subwatersheds, 2001–2020) against two LSTM baselines: a lumped basin-level model and a distributed variant. When benchmarked on SWAT+ simulations in pretraining, HydroGraphNet improved test NSEs by 8.9% (discharge) and 13.7% (NO₃–N load) in temporal extrapolation, and by 27.1% and 34.7% in spatial extrapolation, relative to the Lumped LSTM baseline. After fine-tuning with USGS monitoring data, the model achieved mean test NSE (KGE) scores of 0.768 (0.861) for discharge and 0.626 (0.664) for NO₃–N load, substantially outperforming baselines. Attribution analysis further highlighted the importance of upstream inflow representation and graph-based spatial learning in capturing cross-subwatershed dependencies. The model also reproduced seasonal hydrological and biogeochemical patterns consistent with known processes, demonstrating its robustness and process fidelity for spatially distributed prediction. Altogether, HydroGraphNet advances the integration of physical knowledge and spatially explicit learning in hydrological modeling, offering a generalizable framework for distributed modeling to support spatially targeted water quality management in data-scarce watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Physics vs structure: A systematic benchmark of learning strategies for multi-zone building thermal dynamics

Recent advances in physics-informed and data-driven machine learning promise improved thermal models for advanced building control, yet there is limited quantitative evidence on when added physics structure and architectural complexity are beneficial. Here, this work presents a systematic benchmark of five representative system identification methods for modeling multi-zone building thermal dynamics: linear state-space models, multi-layer perceptrons, neural state-space models, neural ordinary differential equations, and physically-consistent neural networks. The methods are evaluated across multiple data regimes and zone coupling strategies. Using a high-fidelity multi-zone commercial building emulator, we examine short-term and long-term prediction accuracy, computational efficiency, and ease of development. Our results reveal critical trade-offs between prediction performance, model complexity, and physical consistency. We demonstrate that decoupled, nonlinear black-box models consistently outperform coupled physics-constrained architectures in both predictive accuracy and out-of-distribution robustness in majority of the test cases for the building type considered in the study. Our findings quantify the cost of complexity in building thermal modeling and provide concrete, actionable, scenario-based guidelines for selecting model classes for control-oriented applications.

Building thermal modeling↗
DOE OSTI2024

eCoral: How Electrolysis Could Restore Seawater Conditions Ideal for Coral Reefs

Coral reefs suffer from climate change, including long-term ocean acidification (OA) and warming and short-term bleaching, tropical storms, and pollution events, all of which are increasing in frequency and severity. It is urgent yet unclear how to intervene to save coral reefs. Reversal of the ocean pH to preindustrial levels could restore coral reefs to their preindustrial growth rates; however, strategies to reverse OA on environmentally relevant scales have not been established. Anecdotally, electrolysis seems to help coral reefs recover from acidification and short-term events, but few uncontrolled studies support such claims. Here, using two independent continuum simulation approaches (COMSOL and CrunchFlow), we show the effect of electrolysis on seawater chemistry relevant to coral reef survival and growth. We conclude that near the negative electrodes, the cathodes, seawater pH, supersaturation, and carbonate concentration all increase significantly. Electrolysis of seawater, therefore, can be used to restore preindustrial ocean conditions locally to save coral reefs, an approach termed eCoral here. We anticipate these simulation results to be the starting point for controlled experiments to test whether seawater electrolysis promotes coral reef growth and restoration, as these simulations predict.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Efficient Simulation of Cascading Outages Using an Energy Function-Embedded Quasi-Steady-State Model

Here, this paper proposed an energy function-embedded quasi-steady-state model for efficient simulation of cascading outages on a power grid while addressing transient stability concerns. Compared to quasi-steady-state models, the proposed model incorporates short-term dynamic simulation and an energy function method to efficiently evaluate the transient stability of a power grid together with outage propagation without transient stability simulation. Cascading outage simulation using the proposed model conducts three steps for each disturbance such as a line outage. First, it performs time-domain simulation for a short term to obtain a post-disturbance trajectory. Second, along the trajectory, the system state with the local maximum potential energy is found and used as the initial point to search for a relevant unstable equilibrium by Newton's method. Third, the transient energy margin is estimated based on this unstable equilibrium to predict an out-of-step condition with generators. The proposed energy function-embedded quasi-steady-state model is tested in terms of its accuracy and time performance on an NPCC 140-bus power system and compared to a quasi-steady-state model embedding transient stability simulation.

Guo, Zhenping [Univ. of Tennessee, Knoxville, TN (↗
DOE OSTI2025

Surface heat flux and its association with the MJO in the tropical western Pacific using ARM observations

The Madden-Julian oscillation (MJO) is a major atmospheric phenomenon in the tropics that moves eastward every 20 to 100 days. It brings heavy rain and strong winds, influencing extreme weather events far beyond the tropics – including flooding, hurricanes, tornadoes and heavy snow in the United States. Therefore, an improved understanding of the MJO is critical for enhancing weather forecasts and supporting better decision-making for communities, emergency managers, and the private sector. Past studies, based on short-term observations or long-term model data, have emphasized the dominant role of atmospheric humidity in driving the MJO. Our research, using long-term observations (2000-2014) from three U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) sites in the tropical western Pacific (Manus, Nauru, and Darwin) confirms those past findings. However, we also show that atmospheric temperature, especially in the mid and upper troposphere, also plays a key role in the MJO’s evolution from its quiet (suppressed) to convective (active) phase. These findings provide valuable insights into how the MJO evolves and may help evaluate and improve weather and climate models. Our study also examined how the exchange of heat between the Earth's surface and the atmosphere, called surface heat flux, interacts with the MJO. This flux includes components such as latent heat (related to evaporation), sensible heat (related to temperature difference between surface and atmosphere), and radiation. We found that modulation in MJO convection is well connected to surface heat flux over the tropical western Pacific. One surface heat flux component often overlooked is the sensible heat flux due to precipitation (Q P ). Since falling raindrops are typically cooler than the land or ocean surface, they can cool the surface and affect local weather. To test the impact of Q P on convection during MJO, we incorporated it into a weather model, and ran simulations for two periods: April 2009 (when the MJO was active) and June 2006 (when it was not). Including Q P reduced errors in simulating the daily peak of rainfall—by 83% during the strong MJO and 23% during the inactive phase. It also improved the timing of peak daily rainfall and reduced the overall precipitation error by about 10%. These improvements were especially noticeable during periods of heavy rainfall. Our results suggest that even small heat exchanges from rainfall can play a significant role in shaping local weather. Accounting for these effects, particularly in regions like the tropical islands, can lead to more accurate simulations of the MJO-associated precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment

Distributed wind projects, which are connected at the distribution level of an electricity system or in off-grid applications to serve specific or local energy needs, often rely solely on wind resource models to establish wind speed and energy generation expectations. Historically, anemometer loan programs have provided an affordable avenue for more accurate onsite wind resource assessment, and the lowering cost of lidar systems has shown similar advantages for more recent assessments. While a full 12 months of onsite wind measurement is the standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities that drive expedient deployment of distributed wind projects. Much literature exists to quantify the performance of correcting long-term wind speed estimates with 1 or more years of observational data, but few studies explore the impacts of correcting with months-long observational periods. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to model-based long-term wind speed estimates. Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. On average, correction with even 1 month of observations provides significant improvement over the baseline ERA5 wind speed estimates and produces median bias magnitudes and relative errors within 0.22 m s −1 and 4 percentage points of the median bias magnitudes and relative errors achieved using the standard 12 months of data for correction. However, in cases when the shortest observational periods (1 to 2 months) used for correction are not well correlated with the overlapping ERA5 reference, the resultant long-term wind speed errors are worse than those produced using ERA5 without correction. Summer months, which are characterized by weaker relative wind speeds and standard deviations for most of the evaluation sites, tend to produce the worst results for long-term correction using months-long observations. The three tested algorithms perform similarly for long-term wind speed bias; however, regression trees perform notably worse than multivariable linear regression and adaptive regression splines in terms of correlation when using 6 months or less of observational data for correction. Translating the analysis to wind energy, median relative errors in the capacity factor are on average within 10 % using 1 month of training. If the observation period used for correction is not well correlated with the reference data, however, misrepresentation of the observed capacity factor can be substantial. The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. In the worst-correlation scenarios, the median capacity factor relative errors from using 1, 3, and 6 months are within 47 %, 26 %, and 16 %, respectively.

17 WIND ENERGY↗
NASA NTRS1970

Multispectral sensing of moisture stress

Laboratory reflectance data, and field tests with multispectral remote sensors provide support for this hypotheses that differences in moisture content and water deficits are closely related to foliar reflectance from woody plants. When these relationships are taken into account, automatic recognition techniques become more powerful than when they are ignored. Evidence is increasing that moisture relationships inside plant foliage are much more closely related to foliar reflectance characteristics than are external variables such as soil moisture, wind, and air temperature. Short term changes in water deficits seem to have little influence on foliar reflectance, however. This is in distinct contrast to significant short-term changes in foliar emittance from the same plants with changing wind, air temperature, incident radiation, or water deficit conditions.

Olson, C. E., Jr.↗
NASA NTRS1974

A new approach to lightweight radar altimeters

Test results and key principles are given for a radar altimeter designed for meteorological balloons. The instrument, which weighs 160 g and consumes 0.7 W, will fill a gap in meteorological sensing using balloons - an area where pressure altitude was formerly the prevailing reference. The instrument is basically a delay-lock radar utilizing a superregenerative RF stage. Long-term absolute accuracy of plus or minus 10 m and short-term stability of better than 2 m rms were measured at altitudes of 20 km.

Levanon, N.↗
NASA NTRS1978

Internally and externally caused climate change

A numerical climate model is used to simulate climate change forced only by random fluctuations of the atmospheric heat transport. This short-term natural variability of the atmosphere is shown to be a possible 'cause' not only of the variability of the annual world average temperature about its mean, but also long-term excursions from the mean. Various external causes of climate change are also tested with the model and the results compared with observations for the past 100 years. Volcanic dust is shown to have been an important cause of climate change, while the effects of sunspot-related solar constant variation and anthropogenic forcing are not evident.

Robock, A.↗
NASA NTRS1980

CF6-6D engine short-term performance deterioration

Studies conducted as part of the NASA-Lewis CF6 jet engine diagnostics program are summarized. An 82-engine sample of DC-10-10 aircraft engine checkout data that were gathered to define the extent and magnitude of CF6-6D short term performance deterioration were analyzed. These data are substantiated by the performance testing and analytical teardown of CF6-6D short term deterioration engine serial number (ESN) 451507.

Kramer, W. H.↗
NASA NTRS1982

A direct-measurement technique for estimating discharge-chamber lifetime

The use of short-term measurement techniques for predicting the wearout of ion thrusters resulting from sputter-erosion damage is investigated. The laminar-thin-film technique is found to provide high precision erosion-rate data, although the erosion rates are generally substantially higher than those found during long-term erosion tests, so that the results must be interpreted in a relative sense. A technique for obtaining absolute measurements is developed using a masked-substrate arrangement. This new technique provides a means for estimating the lifetimes of critical discharge-chamber components based on direct measurements of sputter-erosion depths obtained during short-duration (approximately 1 hr) tests. Results obtained using the direct-measurement technique are shown to agree with sputter-erosion depths calculated for the plasma conditions of the test. The direct-measurement approach is found to be applicable to both mercury and argon discharge-plasma environments and will be useful for estimating the lifetimes of inert gas and extended performance mercury ion thrusters currently under development.

Beattie, J. R.↗
NASA NTRS1983

Transducers for ultrasonic limb plethysmography

The design, construction, and performance characteristics of ultasonic transducers suitable for limb plethysmography are presented. Both 3-mm-diameter flat-plate and 12-mm-diameter hemispheric ceramic transducers operating at 2 MHz were fitted in 1-mm thick epoxy-resin lens/acoustic-coupling structures and mounted in exercie-EKG electrode housings for placement on the calf using adhesive collars. The effects of transducer directional characteristics on performance under off-axis rotation and the electrical impedances of the transducers were measured: The flat transducer was found to be sensitive to rotation and have an impedance of 800 ohms; the hemispheric transducer, to be unaffected by rotation and have an impedance of 80 ohms. The use of hemispheric transducers as both transmitter and receiver, or of a flat transducer as transmitter and a hemispheric transducer as receiver, was found to produce adequate dimensional measurements, with minimum care in transducer placement, in short-term physiological experiments and long-term (up to 7-day) attachment tests.

Nickell, W. T.↗