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NASA NTRS2004

Estimations of the Global Distribution and Time Series of UV Noontime Irradiance (305, 310, 324, 380 nm, and Erythemal) from TOMS and SeaWiFS Data

The amount of UV irradiance reaching the Earth's surface is estimated from the measured cloud reflectivity, ozone, aerosol amounts, and surface reflectivity time series from 1980 to 1992 and 1997 to 2000 to estimate changes that have occurred over a 21-year period. Recent analysis of the TOMS data shows that there has been an apparent increase in reflectivity (decrease in W) in the Southern Hemisphere that is related to a calibration error in EP-TOMS. Data from the well-calibrated SeaWiFS satellite instrument have been used to correct the EP-TOMS reflectivity and UV time series. After correction, some of the local trend features seen in the N7 time series (1980 to 1992) have been continued in the combined time series, but the overall zonal average and global trends have changed. In addition to correcting the EP-TOMS radiance calibration, the use of SeaWiFS cloud data permits estimation of UV irradiance at higher spatial resolution (1 to 4 km) than is available from TOMS (100 km) under the assumption that ozone is slowly varying over a scale of 100 km. The key results include a continuing decrease in cloud cover over Europe and North America with a corresponding increase in UV and a decrease in UV irradiance near Antarctica.

Herman, J.↗

NASA NTRS1953

Investigation of a Related Series of Turbine-Blade Profiles in Cascade

An application of airfoil design methods was used to design series of related turbine-blade profiles to satisfy the conditions of inlet flow angle and turning angle encountered in the usual range of turbine operation. A series of blade profiles applicable to most turbine blading requirements and a secondary series with particular reference to impulse conditions were designed. Five blade sections from these series ranging in mean-line turning angles from 63 deg. to 120 deg. were tested in low-speed cascade tunnels. From low-speed test results optimum blade angles of attack were selected at each test condition. The induced angle and the deviation angle of the flow were determined from the low-speed data. If these angles are known for the solidity and inlet angle of an application, the necessary camber is specified. A method of predicting high-speed pressure distributions from low-speed cascade test results is presented to extend the usefulness of the low-speed data. Sample high-speed tests of two of the five blade sections were made at Mach numbers up to the critical value. The results indicated satisfactory flow conditions in all of the blade passages tested.

Dunavant, James C.↗

NASA NTRS2006

GEOSAT Follow-On (GFO) Altimeter Document Series, Volume 8: GFO Altimeter Engineering Assessment Report Update:The First 109 Cycles Since Acceptance November 29, 2000 to December 26, 2005

The purpose of this document is to present and document GFO performance analyses and results. This is the fifth Assessment Report since the initial report. This report extends the performance assessment since acceptance to 26 December 2005. The initial GFO Altimeter Engineering Assessment Report, March 2001 (NASA/TM-2001-209984/Ver.1/Vol.1) covered the GFO performance from Launch to Acceptance (10 February 1998 to 29 November 2000). The second of the series covered the performance from Acceptance to the end of Cycle 20 (29 November 2000 to 21 November 2001). The third of the series covered the performance from Acceptance to the end of Cycle 42 (29 November 2000 to 30 November 2002). The fourth of the series covered the performance from Acceptance to the end of Cycle 64 (29 November 2000 to 17 December 2003). The fifth of the series covered performance from Acceptance to the end of Cycle 86 (29 November 2000 to 17 December 2004). Since launch, we have performed a variety of GFO performance studies; an accumulative index of those studies is provided in Appendix A.

Conger, A. M.↗

NASA NTRS2008

High Speed Solution of Spacecraft Trajectory Problems Using Taylor Series Integration

Taylor series integration is implemented in a spacecraft trajectory analysis code-the Spacecraft N-body Analysis Program (SNAP) - and compared with the code s existing eighth-order Runge-Kutta Fehlberg time integration scheme. Nine trajectory problems, including near Earth, lunar, Mars and Europa missions, are analyzed. Head-to-head comparison at five different error tolerances shows that, on average, Taylor series is faster than Runge-Kutta Fehlberg by a factor of 15.8. Results further show that Taylor series has superior convergence properties. Taylor series integration proves that it can provide rapid, highly accurate solutions to spacecraft trajectory problems.

Scott, James R.↗

NASA NTRS2005

Series-Connected Buck Boost Regulators

A series-connected buck boost regulator (SCBBR) is an electronic circuit that bucks a power-supply voltage to a lower regulated value or boosts it to a higher regulated value. The concept of the SCBBR is a generalization of the concept of the SCBR, which was reported in "Series-Connected Boost Regulators" (LEW-15918), NASA Tech Briefs, Vol. 23, No. 7 (July 1997), page 42. Relative to prior DC-voltage-regulator concepts, the SCBBR concept can yield significant reductions in weight and increases in power-conversion efficiency in many applications in which input/output voltage ratios are relatively small and isolation is not required, as solar-array regulation or battery charging with DC-bus regulation. Usually, a DC voltage regulator is designed to include a DC-to-DC converter to reduce its power loss, size, and weight. Advances in components, increases in operating frequencies, and improved circuit topologies have led to continual increases in efficiency and/or decreases in the sizes and weights of DC voltage regulators. The primary source of inefficiency in the DC-to-DC converter portion of a voltage regulator is the conduction loss and, especially at high frequencies, the switching loss. Although improved components and topology can reduce the switching loss, the reduction is limited by the fact that the converter generally switches all the power being regulated. Like the SCBR concept, the SCBBR concept involves a circuit configuration in which only a fraction of the power is switched, so that the switching loss is reduced by an amount that is largely independent of the specific components and circuit topology used. In an SCBBR, the amount of power switched by the DC-to-DC converter is only the amount needed to make up the difference between the input and output bus voltage. The remaining majority of the power passes through the converter without being switched. The weight and power loss of a DC-to-DC converter are determined primarily by the amount of power processed. In the SCBBR, the unswitched majority of the power is passed through with very little power loss, and little if any increase in the sizes of the converter components is needed to enable the components to handle the unswitched power. As a result, the power-conversion efficiency of the regulator can be very high, as shown in the example of Figure 1. A basic SCBBR includes a DC-to-DC converter (see Figure 2). The switches and primary winding of a transformer in the converter is connected across the input bus, while the secondary winding and switches are connected in series with the output bus, so that the output voltage is the sum of the input voltage and the secondary voltage of the converter. In the breadboard SCBBR, the input voltage applied to the primary winding is switched by use of metal oxide/semiconductor field-effect transistors (MOSFETs) in a full bridge circuit; the secondary winding is center-tapped, with two MOSFET switches and diode rectifiers connected in opposed series in each leg. The sets of opposed switches and rectifiers are what enable operation in either a boost or a buck mode. In the boost mode, input voltage and current, and the output voltage and current are all positive; that is, the secondary voltage is added to the input voltage and the net output voltage can be regulated at a value equal or greater than the input voltage. In the buck mode, input voltage is still positive and the current still flows in the same direction in the secondary, but the switches are controlled such that some power flows from the secondary to the primary. The voltage across the secondary and the current into the primary are reversed. The result is that the output voltage is lower than the input voltage, and some power is recirculated from the converter secondary back to the input. Quantitatively, the advantage of an SCBBR is a direct function of the regulation range required. If, for example, a regulation range of 20 percent is required for a 500-W supply, th it suffices to design the DC-to-DC converter in the SCBBR for a power rating of only 100 W. The switching loss and size are much smaller than those of a conventional regulator that must be rated for switching of all 500 W. The reduction in size and the increase in efficiency are not directly proportional to switched-power ratio of 5:1 because the additional switches contribute some conduction loss and the input and output filters must be larger than those typically required for a 100-W converter. Nevertheless, the power loss and the size can be much smaller than those of a 500-W converter.

Birchenough, Arthur G.↗

NASA NTRS2010

High-Speed Solution of Spacecraft Trajectory Problems Using Taylor Series Integration

It has been known for some time that Taylor series (TS) integration is among the most efficient and accurate numerical methods in solving differential equations. However, the full benefit of the method has yet to be realized in calculating spacecraft trajectories, for two main reasons. First, most applications of Taylor series to trajectory propagation have focused on relatively simple problems of orbital motion or on specific problems and have not provided general applicability. Second, applications that have been more general have required use of a preprocessor, which inevitably imposes constraints on computational efficiency. The latter approach includes the work of Berryman et al., who solved the planetary n-body problem with relativistic effects. Their work specifically noted the computational inefficiencies arising from use of a preprocessor and pointed out the potential benefit of manually coding derivative routines. In this Engineering Note, we report on a systematic effort to directly implement Taylor series integration in an operational trajectory propagation code: the Spacecraft N-Body Analysis Program (SNAP). The present Taylor series implementation is unique in that it applies to spacecraft virtually anywhere in the solar system and can be used interchangeably with another integration method. SNAP is a high-fidelity trajectory propagator that includes force models for central body gravitation with N X N harmonics, other body gravitation with N X N harmonics, solar radiation pressure, atmospheric drag (for Earth orbits), and spacecraft thrusting (including shadowing). The governing equations are solved using an eighth-order Runge-Kutta Fehlberg (RKF) single-step method with variable step size control. In the present effort, TS is implemented by way of highly integrated subroutines that can be used interchangeably with RKF. This makes it possible to turn TS on or off during various phases of a mission. Current TS force models include central body gravitation with the J2 spherical harmonic, other body gravitation, thrust, constant atmospheric drag from Earth's atmosphere, and solar radiation pressure for a sphere under constant illumination. The purpose of this Engineering Note is to demonstrate the performance of TS integration in an operational trajectory analysis code and to compare it with a standard method, eighth-order RKF. Results show that TS is 16.6 times faster on average and is more accurate in 87.5% of the cases presented.

Scott, James R.↗

NASA NTRS2012

The Re-Analysis of Ozone Profile Data from a 41-Year Series of SBUV Instruments

In this study we present the validation of ozone profiles from a number of Solar Back Scattered Ultra Violet (SBUV) and SBUV/2 instruments that were recently reprocessed using an updated (Version 8.6) algorithm. The SBUV dataset provides the longest available record of global ozone profiles, spanning a 41-year period from 1970 to 2011 (except a 5-year gap in the 1970s) and includes ozone profile records obtained from the Nimbus-4 BUV and Nimbus-7 SBUV instruments, and a series of SBUV(/2) instruments launched on NOAA operational satellites (NOAA 09, 11, 14, 16, 17, 18, 19). Although modifications in instrument design were made in the evolution from the BUV instrument to the modern SBUV(/2) model, the basic principles of the measurement technique and retrieval algorithm remain the same. The long term SBUV data record allows us to create a consistent, calibrated dataset of ozone profiles that can be used for climate studies and trend analyses. In particular, we focus on estimating the various sources of error in the SBUV profile ozone retrievals using independent observations and analysis of the algorithm itself. For the first time we include in the metadata a quantitative estimate of the smoothing error, defined as the error due to profile variability that the SBUV observing system cannot inherently measure. The magnitude of the smoothing error varies with altitude, latitude, season and solar zenith angle. Between 10 and 1 hPa the smoothing errors for the SBUV monthly zonal mean retrievals are of the order of 1 %, but start to increase above and below this layer. The largest smoothing errors, as large as 15-20%, were detected in in the troposphere. The SBUV averaging kernels, provided with the ozone profiles in version 8.6, help to eliminate the smoothing effect when comparing the SBUV profiles with high vertical resolution measurements, and make it convenient to use the SBUV ozone profiles for data assimilation and model validation purposes. The smoothing error can also be minimized by combining layers of data, and we will discuss recommendations for this approach as well. The SBUV ozone profiles have been intensively validated against satellite profile measurements obtained from the Microwave Limb Sounders (MLS) (on board the UARS and AURA satellites), Stratospheric Aerosol and Gas Experiment (SAGE) and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Also, we compare coincident and collocated SBUV ozone retrievals with observations made by ground-based instruments, such as microwave spectrometers, lidars, Umkehr instruments and balloon-borne ozonosondes. Finally, we compare the SBUV ozone profiles with output from the NASA GSFC GEOS-CCM model. In the stratosphere between 25 and 1 hPa the mean biases and standard deviations are within 5% for monthly mean ozone profiles. Above and below this layer the vertical resolution of the SBUV algorithm decreases and the effects of vertical smoothing should be taken into account. Though the SBUV algorithm has a coarser vertical resolution in the lower stratosphere and troposphere, it is capable of precisely estimating the integrated ozone column between the surface and 25 hPa. The time series of the tropospheric - lower stratospheric ozone column derived from SBUV agrees within 5% with the corresponding values observed by an ensemble of ozone sonde stations in North Hemisphere. Drift of the ozone time series obtained from each SBUV(/2) instrument relative to ground based and satellite measurements are evaluated and some features of individual SBUV(l2) instruments are discussed. In addition to evaluating individual instruments against independent observations, we also focus on the instrument to instrument consistency in the series. Overall, Version 8.6 ozone profiles obtained from two different SBUV(l2) instruments compare within a couple of percent during overlap periods and are consistently varying in time, with some exceptions. Some of the noted discrepancies might bssociated with ozone diurnal variations, since the difference in the local time of the observations for a pair of SBUV(l2) instruments could be several hours. Other issues include the potential short-term drift in measurements as the instrument orbit drifts, and measurements are obtained at high solar zenith angles (>85 ). Based on the results of the validation, a consistent, calibrated dataset of SBUV ozone profiles has been created based on internal calibration only.

Kramarova, Natalya↗

NASA NTRS2014

An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data

Forests contain a majority of the aboveground carbon (C) found in ecosystems, and understanding biomass lost from disturbance is essential to improve our C-cycle knowledge. Our study region in the Wisconsin and Minnesota Laurentian Forest had a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 2007, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometer (AVHRR). To understand the potential role of disturbances in the terrestrial C-cycle, we developed an algorithm to map forest disturbances from either harvest or insect outbreak for Landsat time-series stacks. We merged two image analysis approaches into one algorithm to monitor forest change that included: (1) multiple disturbance index thresholds to capture clear-cut harvest; and (2) a spectral trajectory-based image analysis with multiple confidence interval thresholds to map insect outbreak. We produced 20 maps and evaluated classification accuracy with air-photos and insect air-survey data to understand the performance of our algorithm. We achieved overall accuracies ranging from 65% to 75%, with an average accuracy of 72%. The producer's and user's accuracy ranged from a maximum of 32% to 70% for insect disturbance, 60% to 76% for insect mortality and 82% to 88% for harvested forest, which was the dominant disturbance agent. Forest disturbances accounted for 22% of total forested area (7349 km2). Our algorithm provides a basic approach to map disturbance history where large impacts to forest stands have occurred and highlights the limited spectral sensitivity of Landsat time-series to outbreaks of defoliating insects. We found that only harvest and insect mortality events can be mapped with adequate accuracy with a non-annual Landsat time-series. This limited our land cover understanding of NDVI decline drivers. We demonstrate that to capture more subtle disturbances with spectral trajectories, future observations must be temporally dense to distinguish between type and frequency in heterogeneous landscapes.

Forest↗

NASA NTRS2016

Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

A global, monthly averaged time series of Sun-induced Fluorescence (SiF), spanning January 2007 to June 2015, was derived from Metop-A Global Ozone Monitoring Experiment 2 (GOME-2) spectral measurements. Far-red SiF was retrieved using the filling-in of deep solar Fraunhofer lines and atmospheric absorption bands based on the general methodology described by Joiner et al, AMT, 2013. A Principal Component (PC) analysis of spectra over non-vegetated areas was performed to describe the effects of atmospheric absorption. Our implementation (SiF KNMI) is an independent algorithm and differs from the latest implementation of Joiner et al, AMT, 2013 (SiF NASA, v26), because we used desert reference areas for determining PCs (as opposed to cloudy ocean and some desert) and a wider fit window that covers water vapour and oxygen absorption bands (as opposed to only Fraunhofer lines). As a consequence, more PCs were needed (35 as opposed to 12). The two time series (SiF KNMI and SiF NASA, v26) correlate well (overall R of 0.78) except for tropical rain forests. Sensitivity experiments suggest the strong impact of the water vapour absorption band on retrieved SiF values. Furthermore, we evaluated the SiF time series with Gross Primary Productivity (GPP) derived from twelve flux towers in Australia. Correlations for individual towers range from 0.37 to 0.84. They are particularly high for managed biome types. In the de-seasonalized Australian SiF time series, the break of the Millennium Drought during local summer of 2010/2011 is clearly observed.

Australia↗

NASA NTRS2017

MELDI2 Do No Harm Test Series

Mars 2020 will fly the Mars Entry, Descent, and Landing Instrumentation II (MEDLI2) sensor suite consisting of a total of seventeen instrumented thermal sensor plugs, eight pressure transducers, two heat flux sensors, and one radiometer embedded in the thermal protection system (TPS). Of the MEDLI2 instrumentation, eleven instrumented thermal plugs and seven pressure transducers will be installed on the heatshield of the Mars 2020 vehicle while the rest will be installed on the backshell. The goal of the MEDLI2 instrumentation is to directly inform the large performance uncertainties that contribute to the design and validation of a Mars entry system. A better understanding of the entry environment and TPS performance could lead to reduced design margins enabling a greater payload mass-fraction and smaller landing ellipses. To prove that the MEDLI2 system will not degrade the performance of the Mars 2020 TPS, an Aerothermal Do No Harm (DNH) test series was designed and conducted. Like Mars 2020's predecessor, Mars Science Laboratory (MSL), the heatshield material will be Phenolic Impregnated Carbon Ablator (PICA); the Mars 2020 entry conditions are enveloped by the MSL design environments, therefore the development and qualification testing performed during MEDLI is sufficient to show that the similar MEDLI2 heatshield instrumentation will not degrade PICA performance. However, given that MEDLI did not include any backshell instrumentation, the MEDLI2 team was required to design and execute a DNH test series utilizing the backshell TPS material (SLA-561V) with the intended flight sensor suite. To meet the requirements handed down from Mars 2020, the MEDLI2 DNH test series emphasized the interaction between the MEDLI2 sensors and sensing locations with the surrounding backshell TPS and substrucutre. These interactions were characterized by performing environmental testing of four 12" by 12" test panels, which mimicked the construction of the backshell TPS and the integration of the MEDLI2 sensors as seen in Figure 1. The testing included thermal vacuum/ cycling, random vibration, shock, and arc jet testing. The test panels were fabricated by Lockheed Martin, establishing techniques that will be utilized during the Mars 2020 vehicle installation. Each test panel included one thermal sensor plug (two embedded thermocouples), one heat flux sensor, and multiple pressure port holes for evaluation. This presentation will discuss the planning and execution of the MEDLI2 DNH test series. Selected highlights and results of each environmental test will be presented, and lessons learned will be addressed that will feed forward into the planning for the MEDLI2 flight system certification testing.

Heatshield↗

NASA NTRS2017

Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series

Long-term observations of vegetation phenology can be used to monitor the response of terrestrial ecosystems to climate change. Satellite remote sensing provides the most efficient means to observe phenological events through time series analysis of vegetation indices such as the Normalized Difference Vegetation Index (NDVI). This study investigates the potential of a Photochemical Reflectance Index (PRI), which has been linked to vegetation light use efficiency, to improve the accuracy of MODIS-based estimates of phenology in an evergreen conifer forest. Timings of the start and end of the growing season (SGS and EGS) were derived from a 13-year-long time series of PRI and NDVI based on a MAIAC (multi-angle implementation of atmospheric correction) processed MODIS dataset and standard MODIS NDVI product data. The derived dates were validated with phenology estimates from ground-based flux tower measurements of ecosystem productivity. Significant correlations were found between the MAIAC time series and ground-estimated SGS (R (sup 2) equals 0.36-0.8), which is remarkable since previous studies have found it difficult to observe inter-annual phenological variations in evergreen vegetation from satellite data. The considerably noisier NDVI product could not accurately predict SGS, and EGS could not be derived successfully from any of the time series. While the strongest relationship overall was found between SGS derived from the ground data and PRI, MAIAC NDVI exhibited high correlations with SGS more consistently (R (sup 2) is greater than 0.6 in all cases). The results suggest that PRI can serve as an effective indicator of spring seasonal transitions, however, additional work is necessary to confirm the relationships observed and to further explore the usefulness of MODIS PRI for detecting phenology.

Ulsig, Laura↗

NASA NTRS2017

Mars2020 Entry, Descent, and Landing Instrumentation 2 (MEDLI2) Do No Harm Test Series

A total of seventeen instrumented thermal sensor plugs, eight pressure transducers, two heat flux sensors, and one radiometer are planned to be utilized on the Mars 2020 missions thermal protection system (TPS) as part of the Mars Entry, Descent, and Landing Instrumentation II (MEDLI2) project. Of the MEDLI2 instrumentation, eleven instrumented thermal plugs and seven pressure transducers will be installed on the heatshield of the Mars 2020 vehicle while the rest will be installed on the backshell. The goal of the MEDLI2 instrumentation is to directly inform the large performance uncertainties that contribute to the design and validation of a Mars entry system. A better understanding of the entry environment and TPS performance could lead to reduced design margins enabling a greater payload mass-fraction and smaller landing ellipses. To prove that the MEDLI2 system will not degrade the performance of the Mars 2020 TPS, an Aerothermal Do No Harm (DNH) test series was designed and conducted. Like Mars 2020s predecessor, Mars Science Laboratory (MSL), the heatshield material will be Phenolic Impregnated Carbon Ablator (PICA); the Mars 2020 entry conditions are enveloped by the MSL design environments, therefore the development and qualification testing performed during MEDLI is sufficient to show that the similar MEDLI2 heatshield instrumentation will not degrade PICA performance. However, given that MEDLI did not include any backshell instrumentation, the MEDLI2 team was required to design and execute a DNH test series utilizing the backshell TPS material (SLA-561V) with the intended flight sensor suite. To meet the requirements handed down from Mars 2020, the MEDLI2 DNH test series emphasized the interaction between the MEDLI2 sensors and sensing locations with the surrounding backshell TPS and substrucutre. These interactions were characterized by performing environmental testing of four 12 by 12 test panels, which mimicked the construction of the backshell TPS and the integration of the MEDLI2 sensors as seen in Figure 1. The testing included thermal vacuumcycling, random vibration, shock, and arc jet testing. The test panels were fabricated by Lockheed Martin, establishing techniques that will be utilized during the Mars 2020 vehicle installation. Each test panel included one thermal sensor plug (two embedded thermocouples), one heat flux sensor, and multiple pressure port holes for evaluation.This presentation will discuss the planning and execution of the MEDLI2 DNH test series. Selected highlights and results of each environmental test will be presented, and lessons learned will be addressed that will feed forward into the planning for the MEDLI2 flight system certification testing.

backshell↗

NASA NTRS2020

UAS Integration in the NAS Project: Overview of Flight Test Series 6

The National Aeronautics and Space Administration (NASA) Unmanned Aircraft Systems Integration in the National Airspace System (UAS-NAS) Project has conducted a series of flight test campaigns intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration (FAA). The 2019 Flight Test Series 6 (FT6) campaign furthered this path and supported three test configurations: 1) Radar Characterization, 2) Scripted Encounters and 3) Full Mission. Radar Characterization assessed the performance of Honeywell’s low size, weight, and power (low SWaP) radar system; Scripted Encounters investigated the timing of Detect and Avoid (DAA) alerting thresholds using a Department of Defense (DoD) Group 3 unmanned aircraft system (UAS) equipped with low SWaP sensors and three different live intruder aircraft flown at varying encounter geometries; and Full Mission validated human-in-the-loop simulations by collecting pilot performance data from a ground control station while controlling a live unmanned aircraft on a mission in both virtual and live air traffic controlled airspace. The subject pilot observed a research display that presented DAA advisories to maintain separation from live and virtual aircraft. The test was conducted over a twenty-week period within the R-2508 special use airspace located near Edwards Air Force Base (EAFB), CA. Over 240 encounters were flown during the test series and FT6 proved to be invaluable for the purposes of planning, managing, and executing this type of integrated flight test in both live and virtual environments. Data collected from FT6 was provided to the RTCA Special Committee 228 (SC-228) to help inform the Phase 2 Minimum Operational Performance Standards (MOPS). FT6 was the final test series for the UAS-NAS project that began in 2012. This paper provides an overview of FT6 and its success can be directly attributed to the diligent work of the men and women who supported this effort.

UAS in the NAS↗

NASA NTRS2020

JWST Noise Floor. I. Random Error Sources in JWST NIRCam Time Series

James Webb Space Telescope (JWST) transmission and emission spectra will provide invaluable glimpses of transiting exoplanet atmospheres, including possible biosignatures. This promising science from JWST, however, will require exquisite precision and understanding of systematic errors that can impact the time series of planets crossing in front of and behind their host stars. Here, we provide estimates of the random noise sources affecting JWST Near-Infrared Camera (NIRCam) time-series data on the integration-to-integration level. We find that 1/ f noise can limit the precision of grism time series for two groups (230–1000 ppm depending on the extraction method and extraction parameters) but will average down like the square root of N frames/reads. The current NIRCam grism time-series mode is especially affected by 1/ f noise because its GRISMR dispersion direction is parallel to the detector fast-read direction, but could be alleviated in the GRISMC direction. Care should be taken to include as many frames as possible per visit to reduce this 1/ f noise source: thus, we recommend the smallest detector subarray sizes one can tolerate, four output channels, and readout modes that minimize the number of skipped frames (RAPID or BRIGHT2). We also describe a covariance-weighting scheme that can significantly lower the contributions from 1/ f noise as compared to sum extraction. We evaluate the noise introduced by preamplifier offsets, random telegraph noise, and high dark current resistor capacitor (RC) pixels and find that these are correctable below 10 ppm once background subtraction and pixel masking are performed. We explore systematic error sources in a companion paper.

Exoplanet atmospheres↗

DOE OSTI2024

Machine-learned closure of URANS for stably stratified turbulence: connecting physical timescales & data hyperparameters of deep time-series models

Stably stratified turbulence (SST), a model that is representative of the turbulence found in the oceans and atmosphere, is strongly affected by fine balances between forces and becomes more anisotropic in time for decaying scenarios. Moreover, there is a limited understanding of the physical phenomena described by some of the terms in the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations—used to numerically simulate approximate solutions for such turbulent flows. Rather than attempting to model each term in URANS separately, it is attractive to explore the capability of machine learning (ML) to model groups of terms, i.e. to directly model the force balances. We develop deep time-series ML for closure modeling of the URANS equations applied to SST. We consider decaying SST which are homogeneous and stably stratified by a uniform density gradient, enabling dimensionality reduction. We consider two time-series ML models: long short-term memory and neural ordinary differential equation. Both models perform accurately and are numerically stable in a posteriori (online) tests. Furthermore, we explore the data requirements of the time-series ML models by extracting physically relevant timescales of the complex system. We find that the ratio of the timescales of the minimum information required by the ML models to accurately capture the dynamics of the SST corresponds to the Reynolds number of the flow. The current framework provides the backbone to explore the capability of such models to capture the dynamics of high-dimensional complex dynamical system like SST flows.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗

DOE OSTI2026

System-Level Efficiency Study of Modular DC/DC and Fuel Cell Stack Series–Parallel Configurations

This paper presents a system-level efficiency study of modular DC/DC converter and fuel cell stack configurations under series, parallel, and series–parallel connections. The investigation considers selected DC/DC converter topologies, including isolated and non-isolated architectures, boost, non-inverting buck-boost, and resonant converters, integrated with commercially available fuel cell stacks, including the Accelera FCE150, Ballard FCgen-HPS, and Toyota TFCM2. DC/DC converter modules are evaluated in modular configurations rated at 60 kW and 90 kW and two distinct output voltage ranges, specifically 580–730V and 780–930V, examining how different interconnection schemes impact overall system efficiency. The converters are evaluated under full load (100%), partial load (66%), and light load (33%) conditions, providing a comprehensive assessment of efficiency and operational characteristics across varying power demands. Approximately two-thousand efficiency data points are obtained from laboratory prototype–level component measurements and validated design evaluations across multiple converter topologies, modular configurations, voltage ranges, and load conditions, providing a robust dataset for comparative system-level efficiency analysis. The results highlight the effects of modularity and topology selection on system-level efficiency, offering a “playbook” framework for designers to select appropriate DC/DC converter arrangements and fuel cell stack connections for series, parallel, or hybrid configurations based on efficiency considerations.

DC/DC↗

NASA NTRS2017

Interpretable Categorization of Heterogeneous Time Series Data

We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

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