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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Observing large-scale temporal variability of ocean currents by satellite altimetry - With application to the Antarctic circumpolar current

A new method is developed for studying large-scale temporal variability of ocean currents from satellite altimetric sea level measurements at intersections (crossovers) of ascending and descending orbit ground tracks. Using this method, sea level time series can be constructed from crossover sea level differences in small sample areas where altimetric crossovers are clustered. The method is applied to Seasat altimeter data to study the temporal evolution of the Antarctic Circumpolar Current (ACC) over the 3-month Seasat mission (July-October 1978). The results reveal a generally eastward acceleration of the ACC around the Southern Ocean with meridional disturbances which appear to be associated with bottom topographic features. This is the first direct observational evidence for large-scale coherence in the temporal variability of the ACC. It demonstrates the great potential of satellite altimetry for synoptic observation of temporal variability of the world ocean circulation.

Fu, L.-L.↗
DOE OSTI2025

Understanding and Mitigating Coherence and Frequency Fluctuations in Superconducting Transmon Qubits

Transmon qubits are a cornerstone of superconducting quantum computing platforms. However‚ their frequency and coherence properties exhibit temporal fluctuations‚ leading to performance degradation in quantum processors over time. A common mitigation approach involves frequent recalibration‚ which‚ while effective‚ results in increased system downtime. Enhancing the long-term stability of transmon qubits is therefore critical for scalable and reliable quantum computing. In this study‚ we develop novel techniques for understanding the underlying mechanisms driving frequency and coherence fluctuations in fixed-frequency transmon qubits. We further explore strategies to mitigate these instabilities‚ aiming to improve overall system robustness. Our findings provide insights into optimizing superconducting quantum hardware for practical applications.

Roy, Tanay [Fermilab]↗
DOE OSTI2021

Solid state core-exciton dynamics in NaCl observed by tabletop attosecond four-wave mixing spectroscopy

Nonlinear wave mixing in solids with ultrafast x-rays can provide insight into complex electronic dynamics of materials. Here, tabletop-based attosecond noncollinear four-wave mixing (FWM) spectroscopy using one extreme ultraviolet (XUV) pulse from high harmonic generation and two separately timed few-cycle near-infrared (NIR) pulses characterizes the dynamics of the Na + L 2,3 edge core-excitons in NaCl around 33.5 eV. An inhomogeneous distribution of core-excitons underlying the well-known doublet absorption of the Na+ Γ point core-exciton spectrum is deconvoluted by the resonance-enhanced nonlinear wave mixing spectroscopy. In addition, other dark excitonic states that are coupled to the XUV-allowed levels by the NIR pulses are characterized spectrally and temporally. Approximately <10fs coherence lifetimes of the core-exciton states are observed. Furthermore, the core-excitonic properties are discussed in the context of strong electron-hole exchange interactions, electron-electron correlation, and electron-phonon broadening. This investigation successfully indicates that tabletop attosecond FWM spectroscopies represent a viable technique for time-resolved solid state measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Step-patterned survivorship curves: Mortality and loss of equilibrium responses to high temperature and food restriction in juvenile rainbow trout ( Oncorhynchus mykiss )

While survivorship curves typically exhibit smooth declines over time, step-patterned curves can occur with multiple stressors within a life stage. To explore this process, we examined the effects of heat (24°C) and food restriction on juvenile rainbow trout (Oncorhynchus mykiss Walbaum) in challenge experiments. We observed step-patterned survivorship curves determined by mortality and loss of equilibrium (LOE) endpoints. To examine the cause of heterogeneity in the stress responses from early to late mortality and LOE, we measured indices of energetic reserves. The step transition in the survivorship curves, the peak mortality rates, and start of when individuals reached a critical energetic threshold (14% dry mass; 4.0 kJ∙g -1 energy) all occurred at around days 10–15 of the challenge. The coherence in these temporal patterns suggest heterogeneity in the cohort stress responses, in which an early subgroup died from heat stress and a late subgroup died from starvation. Thus, their endpoint sensitivities resulted in step-patterned survivorship curves. We discuss the implications of the study for understanding effects of multiple stressors on population heterogeneity and note the possible significance of stress response selection under climate change in which heat stress and food limitations occur in concert.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

Computerized X-ray reconstruction tomography in stereometric analysis of cardiovascular dynamics

A computerized technique is proposed for obtaining cross-sectional images of the dynamic spatial distribution of X-ray attenuation covering the entire anatomic extent of the thorax and its contents in living dogs with a resolution of 1 mm and at time intervals of 1/60 sec. Use is made of an X-ray imaging chain which is a new high-performance video-fluoroscopic system, unique in its design and construction and called SSDSR for single source dynamic spatial reconstructor. This dynamic spatial reconstruction system is shown to provide the temporally and spatially coherent multiple cross sections required to obtain the full three-dimensional anatomic and simultaneous hemodynamic information necessary for detailed quantitative analyses of regional cardiopulmonary and vascular functions in both basic investigations of animals and clinical diagnostic applications to patients. Numerous photographs supplement the text.

Robb, R. A.↗
NASA NTRS1985

Comparison of horizontal winds from the LIMS satellite instrument with rocket measurements

Statistical results are given for a comparison between horizontal geostrophic winds computed from satellite height data and all available in situ rocket wind soundings during a 7-month period. The satellite data are the daily mapped fields from the Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) instrument, which extend from 100 to 0.1 mbar. Results indicate that in both the tropics and the extratropical Northern Hemisphere, the average zonal and meridional wind speeds agree to within 2-4 m/s throughout the stratosphere. The rms differences are much larger, with values of 5-10 m/s in the lower stratosphere, increasing to 20-40 m/s in the lower mesosphere. Time series show that LIMS and rocketsonde zonal wind speeds show coherent variations with temporal periods of 1-2 weeks and more, and both exhibit irregular variations on time scales of less than one week.

Smith, A. K.↗
NASA NTRS1989

A case study using kinematic quantities derived from a triangle of VHF Doppler wind profilers

Horizontal divergence, relative vorticity, kinematic vertical velocity, and geostrophic and ageostrophic winds are computed from Colorado profiler network data to investigate an upslope snowstorm in northeastern Colorado. Horizontal divergence and relative vorticity are computed using the Gauss and Stokes theorems, respectively. Kinematic vertical velocities are obtained from the surface to 9 km by vertically integrating the continuity equation. The geostrophic and ageostrophic winds are computed by applying a finite differencing technique to evaluate the derivatives in the horizontal equations of motion. Comparison of the synoptic-scale data with the profiler network data reveals that the two datasets are generally consistent. Also, the profiler-derived quantities exhibit coherent vertical and temporal patterns consistent with conceptual and theoretical flow fields of various meteorological phenomena. It is suggested that the profiler-derived quantities are of potential use to weather forecasters in that they enable the dynamic and kinematic interpretation of weather system structure to be made and thus have nowcasting and short-term forecasting value.

Carlson, Catherine A.↗
NASA NTRS1989

The annual and interannual variabilities of precipitable water, surface wind speed, and sea surface temperature over the tropical Pacific

The Nimbus-7 Scanning Multichannel Microwave Radiometer (SSMR) provided simultaneous measurements of three geophysical parameters, each of which describing a certain aspect of the evolution of the 1982-1983 ENSO: the sea-surface temperature (T), precipitable water (W), and surface-wind speed (U). In this paper, values derived from the SSMR were compared with in situ measurements from ships, research buoys, and operational island stations in the tropical Pacific between January 1980 and October 1983, demonstrating the temporal and spatial coherence of the SSMR measurements. The results show that the variabilities of the surface convergence, sea surface temperature, and precipitable water are related. It was found that W anomalies were not always colocated with T anomalies, and that W anomalies were often associated with negative U anomalies, interpreted as surface convergence.

Liu, W. Timothy↗
NASA NTRS1994

Surface temperatures in the polar regions from Nimbus 7 temperature humidity infrared radiometer

Monthly surface temperatures in the Arctic and Antarctic regions have been derived from the 11.5 micrometer thermal infrared channel of the Nimbus 7 temperature humidity infrared radiometer (THIR) for a whole year in 1979 and for a winter and a summer month from 1980 through 1985. The data set shows interannual variability and provides spatial details that allow identification of temperature patterns over sea ice and ice sheet surfaces. For example, the coldest spot in the southern hemisphere is observed to be consistently in the Antarctic plateau in the southern hemisphere, while that in the northern hemisphere is usually located in Greenland, or one of three other general areas: Siberia, the central Arctic, or the Canadian Archipelago. Also, in the southern hemisphere, the amplitude of the seasonal fluctuation of ice sheet temperatures is about 3 times that of sea ice, while in the northern hemisphere, the corresponding fluctuations for the two surfaces are about the same. The main sources of error in the retrieval are cloud and other atmospheric effects. These were minimized by first choosing the highest radiance value from the set of measurements during the day taken within a 30 km by 30 km grid of each daily map. Then the difference of daily maps was taken and where the difference is greater than a certain threshold (which in this case is 12 C), the data element is deleted. Overall, the monthly maps derived from the resulting daily maps are spatially and temporally consistent, are coherent with the topograph y of the Antarctic continent and the location of the sea ice edge, and are in qualitative agreement with climatological data. Quantitatively, THIR data are in good agreement with Antarctic ice sheet surface air temperature station data with a correlation coefficient of 0.997 and a standard deviation of 2.0 C. The absolute values are not as good over the sea ice edges, but a comparison with Russian 2-m drift station temperatures shows very high correlation (with correlation coefficient at 0.998) and a standard deviation of 1.1 C. Overall, the rms error is estimated to be from 1 to 2 C, depending on the surface, while the average bias when compared with in situ data is less than 2 C.

Comiso, Josefino C.↗
NASA NTRS2011

Chlorophyll-a Algorithms for Oligotrophic Oceans: A Novel Approach Based on Three-Band Reflectance Difference

A new empirical algorithm is proposed to estimate surface chlorophyll-a concentrations (Chl) in the global ocean for Chl less than or equal to 0.25 milligrams per cubic meters (approximately 77% of the global ocean area). The algorithm is based on a color index (CI), defined as the difference between remote sensing reflectance (R(sub rs), sr(sup -1) in the green and a reference formed linearly between R(sub rs) in the blue and red. For low Chl waters, in situ data showed a tighter (and therefore better) relationship between CI and Chl than between traditional band-ratios and Chl, which was further validated using global data collected concurrently by ship-borne and SeaWiFS satellite instruments. Model simulations showed that for low Chl waters, compared with the band-ratio algorithm, the CI-based algorithm (CIA) was more tolerant to changes in chlorophyll-specific backscattering coefficient, and performed similarly for different relative contributions of non-phytoplankton absorption. Simulations using existing atmospheric correction approaches further demonstrated that the CIA was much less sensitive than band-ratio algorithms to various errors induced by instrument noise and imperfect atmospheric correction (including sun glint and whitecap corrections). Image and time-series analyses of SeaWiFS and MODIS/Aqua data also showed improved performance in terms of reduced image noise, more coherent spatial and temporal patterns, and consistency between the two sensors. The reduction in noise and other errors is particularly useful to improve the detection of various ocean features such as eddies. Preliminary tests over MERIS and CZCS data indicate that the new approach should be generally applicable to all existing and future ocean color instruments.

Hu, Chuanmin↗
DOE OSTI2023

Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Missing Photovoltaic Data Imputation

The integration of the global Photovoltaic (PV) market with real time data-loggers has enabled large scale PV data analytical pipelines for power forecasting and long-term reliability assessment of PV fleets. Nevertheless, the performance of PV data analysis heavily depends on the quality of PV timeseries data. This paper proposes a novel Spatio-Temporal Denoising Graph Autoencoder (STD-GAE) framework to impute missing PV Power Data. STDGAE exploits temporal correlation, spatial coherence, and value dependencies from domain knowledge to recover missing data. It is empowered by two modules. (1) To cope with sparse yet various scenarios of missing data, STD-GAE incorporates a domain-knowledge aware data augmentation module that creates plausible variations of missing data patterns. This generalizes STD-GAE to robust imputation over different seasons and environment. (2) STD-GAE nontrivially integrates spatiotemporal graph convolution layers (to recover local missing data by observed “neighboring” PV plants) and denoising autoencoder (to recover corrupted data from augmented counterpart) to improve the accuracy of imputation accuracy at PV fleet level. We have evaluated our proposed model on two realworld PV datasets. Experimental results show that STD-GAE can achieve a gain of 43.14% in imputation accuracy and remains less sensitive to missing rate, different seasons, and missing scenarios, compared with state-of-the-art data imputation methods such as MIDA and LRTC-TNN.

Fan, Yangxin↗
NASA NTRS2004

Photon Dynamics in Coherently Coupled Optical Resonators

The temporal response of coupled resonators is investigated using a linear systems analysis and coupled mode theory. Damped Rabi oscillations, slow and fast light, and coherent photon transfer techniques are demonstrated in these systems.

Smith, David D.↗
NASA NTRS2020

Assessment Of Polsar And Insar Time-Series From The 2019 Nasa Am-Pm Campaign For Above-Ground Biomass Estimation

The forthcoming launch of the NASA-ISRO Synthetic ApertureRadar (NISAR) mission will open the path to a new typeof L-band measurements constituted by dense time-series ofpolarimetric backscatter and interferometric coherence withunprecedented spatial and temporal sampling. Here, we startthe development of a theoretical framework that links L-bandbackscatter time-series with interferometric coherence measurements.The water-cloud-model (WCM) and an extendedversion of the random-motion-over-ground (RMoG) modelare adopted to express radar measurements in terms of forestabove-ground biomass and tree height. Time-series datacollected during the 2019 UAVSAR AM-PM campaign inSoutheastern United States are used to evaluate the correlationof various PolSAR- and InSAR-derived parameters withfield-measured above-ground biomass.

Lavalle, Marco↗
DOE OSTI2026

TLS characterization using multilevel decay of a fixed-frequency transmon

Transmon qubits are a cornerstone of superconducting quantum computing platforms, yet their coherence times often exhibit temporal fluctuations that degrade processor performance. These variations are commonly attributed to shifts in the resonance frequencies of individual two-level systems (TLSs) near the qubit transition. In this study, we monitor the lifetimes of multiple energy levels of a fixed-frequency transmon and examine their temporal correlations. Our measurements reveal that one or more TLSs—detuned by more than 100 MHz from the qubit transition—can still significantly influence coherence. The proposed method provides a powerful tool for TLS spectroscopy without the need to tune the transmon frequency, either via a flux-tunable inductor or AC-Stark shifts.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗
DOE OSTI2026

TLS characterization using multilevel decay of a fixed-frequency transmon

Transmon qubits are a cornerstone of superconducting quantum computing platforms, yet their coherence times often exhibit temporal fluctuations that degrade processor performance. These variations are commonly attributed to shifts in the resonance frequencies of individual two-level systems (TLSs) near the qubit transition. In this study, we monitor the lifetimes of multiple energy levels of a fixed-frequency transmon and examine their temporal correlations. Our measurements reveal that one or more TLSs—detuned by more than 100 MHz from the qubit transition—can still significantly influence coherence. The proposed method provides a powerful tool for TLS spectroscopy without the need to tune the transmon frequency, either via a flux-tunable inductor or AC-Stark shifts.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗
DOE OSTI2025

Tracing Long-Lived Atomic Coherences Generated via Molecular Conical Intersections

Accessing coherences is key to fully understand and control ultrafast dynamics of complex quantum systems like molecules. Most photochemical processes are mediated by conical intersections, which generate coherences between electronic states in molecules. We show with accurate calculations performed on gas-phase methyl iodide that electronic coherences of spin-orbit-split states persist in atomic iodine after dissociation. Our simulation predicts a maximum magnitude of vibronic coherence in the molecular regime of 0.75% of the initially photoexcited state population. Upon dissociation, one-third of this coherence magnitude is transferred to a long-lived atomic coherence where vibrational decoherence can no longer occur. To trace these dynamics, we propose a tabletop experimental approach—heterodyned attosecond four-wave-mixing spectroscopy. This technique can temporally resolve small electronic coherence magnitudes and reconstruct the full complex coherence function via phase cycling. Hence, heterodyned attosecond four-wave-mixing spectroscopy leads the way to a complete understanding and optimal control of spin-orbit-coupled electronic states in photochemistry.

Chemical Physics↗
DOE OSTI2024

Using spatio-temporal graph neural networks to estimate fleet-wide photovoltaic performance degradation patterns

Accurate estimation of photovoltaic (PV) system performance is crucial for determining its feasibility as a power generation technology and financial asset. PV-based energy solutions offer a viable alternative to traditional energy resources due to their superior Levelized Cost of Energy (LCOE). A significant challenge in assessing the LCOE of PV systems lies in understanding the Performance Loss Rate (PLR) for large fleets of PV systems. Estimating the PLR of PV systems becomes increasingly important in the rapidly growing PV industry. Precise PLR estimation benefits PV users by providing real-time monitoring of PV module performance, while explainable PLR estimation assists PV manufacturers in studying and enhancing the performance of their products. However, traditional PLR estimation methods based on statistical models have notable drawbacks. Firstly, they require user knowledge and decision-making. Secondly, they fail to leverage spatial coherence for fleet-level analysis. Additionally, these methods inherently assume the linearity of degradation, which is not representative of real world degradation. To overcome these challenges, we propose a novel graph deep learning-based decomposition method called the Spatio-Temporal Graph Neural Network for fleet-level PLR estimation (PV-stGNN-PLR). PV-stGNN-PLR decomposes the power timeseries data into aging and fluctuation components, utilizing the aging component to estimate PLR. PV-stGNN-PLR exploits spatial and temporal coherence to derive PLR estimation for all systems in a fleet and imposes flatness and smoothness regularization in loss function to ensure the successful disentanglement between aging and fluctuation. We have evaluated PV-stGNN-PLR on three simulated PV datasets consisting of 100 inverters from 5 sites. Experimental results show that PV-stGNN-PLR obtains a reduction of 33.9% and 35.1% on average in Mean Absolute Percent Error (MAPE) and Euclidean Distance (ED) in PLR degradation pattern estimation compared to the state-of-the-art PLR estimation methods.

14 SOLAR ENERGY↗