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NASA NTRS2020

Hawai'i Water Resources: Utilizing NASA Earth Observations to Assess Ocean Conditions Leading to the Spread of the Nuisance Red Algae (Chondria tumulosa) in Papahānaumokuākea Marine National Monument, Hawai’i

Chondria tumulosa, a newly discovered red alga, was observed in low abundance in 2016 but has since proliferated and is now smothering and decimating vast expanse of coral reefs in Manawai, located in Papahānaumokuākea Marine National Monument (PMNM). If the spread persists, the outbreak of this cryptogenic species could potentially cause region-wide ecosystem degradation. In coordination with the U.S. Fish and Wildlife Service, Marine National Monuments of the Pacific and the National Oceanographic and Atmospheric Administration (NOAA) Office of National Marine Sanctuaries’ Papahānaumokuākea Marine National Monument, this project created a tool to analyze oceanographic conditions (sea surface temperature (SST), chlorophyll-a, water velocity, salinity, turbidity) across the Monument that could potentially be driving the algal spread. The Google Earth Engine tool enabled the partners to visualize oceanographic conditions and gather time-series graphs utilizing Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-3 Ocean and Land Colour Instrument (OLCI), Hybrid Coordinate Ocean Model (HYCOM) and NOAA's Climate Data Record in a user-friendly interface. The team used in situ SST data from subsurface temperature recorders provided by the partners to validate the tool's accuracy. Preliminary statistical analysis of MODIS data found warming trends in SST in Manawai as well as increased chlorophyll-a levels during the summer months in contrast to the control (non-infected) Lalo atoll. The tool did not aim to classify algal presence due to limited availability of higher resolution satellite imagery but instead enabled PMNM managers to monitor conditions that may be conducive to algal growth around the monument to make informed decisions and mitigation practices.

DEVELOP Project Summary↗

DOE OSTI2024

Skeletal reaction models for methane combustion

A local-sensitivity-analysis technique is employed to generate new skeletal reaction models for methane combustion from the foundational fuel chemistry model (FFCM-1). Here, the sensitivities of the thermo-chemical variables with respect to the reaction rates are computed via the forced-optimally time dependent (f-OTD) methodology. In this methodology, the large sensitivity matrix containing all local sensitivities is modeled as a product of two low-rank time-dependent matrices. The evolution equations of these matrices are derived from the governing equations of the system. The modeled sensitivities are computed for the auto-ignition of methane at atmospheric and high pressures with different sets of initial temperatures, and equivalence ratios. These sensitivities are then analyzed to rank the most important (sensitive) species. A series of skeletal models with different number of species and levels of accuracy in reproducing the FFCM-1 results are suggested. The performances of the generated models are compared against FFCM-1 in predicting the ignition delay, the laminar flame speed, and the flame extinction. The results of this comparative assessment suggest the skeletal models with 24 and more species generate the FFCM-1 results with an excellent accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1999

Psychological changes in hundred-day remote Antarctic field groups

Psychological adaptation to extreme environments has been examined from several perspectives. In this study, two Australian teams, each consisting of six male crew members, completed computer-administered questionnaires twice weekly during 100-day traverses around the Lambert Glacier Basin, Antarctica. Only small trends were noted when data were aggregated at the group level, which is consistent with the findings of others. Data were then analyzed using pooled time-series regression. These analyses incorporated personality characteristics, environmental factors, and interpersonal factors as predictors of Group Tensions, Personal Morale, Emotional State, Cognitive Readiness, and the Team's Work Life. Most of the psychological discomfort and problems that occurred appeared to be within the individual or between individuals. They did not affect all members of the group equally.

NASA Discipline Space Human Factors↗

DOE OSTI2022

Crustal Strain Rates in the Western United States and Their Relationship with Earthquake Rates

Abstract We present a suite of strain rate models for the western United States based on geologic and geodetic data. The geologic data consist of Quaternary fault-slip rates and the geodetic data consists of a new compilation of Global Positioning System (GPS) velocities derived from continuous, semicontinuous, and campaign measurements. We remove postseismic deformation from the GPS time series in order for our geodetic strain rate model to best capture the interseismic strain accumulation rate. We present models based on either geologic or geodetic data, but also create a hybrid model. Although there are some differences between the models, the large-scale features are the same, with the noticeable exception for the Pacific Northwest where interseismic strain is naturally more distributed than the long-term strain release. We also present a map of earthquake rate densities based on mainshocks, and the result has similar spatial features similar to the strain rate models (at least in the southwestern United States). We perform a general correlation analysis between strain rate and seismicity rate (south of Cascadia) and find a change in linearity between seismicity and strain rates from slow to faster deforming areas with seismicity rates relatively lower for the latter. The extent of that change depends a bit on assumptions made on the declustering and completeness of the catalog, but the finding of a change in slope is robust across the different strain rate models. Linearity for all areas is only expected when Gutenberg–Richter parameters and parameters involved in the conversion from strain to moment rate are uniform across the study area. We discuss these qualifications, but find no single satisfactory explanation for our observation. Moreover, when considering a rather short time and space, theoretical considerations of sampling from a power-law distribution actually predict there to be a power law instead of a linear relationship, generally consistent with our observation.

Geochemistry & Geophysics↗

DOE OSTI2024

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

Burns, Kory (ORCID:0000000158019909)↗

DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗

DOE OSTI2020

Support of the Development of EPP Plus SMT Design Method (FY2020 Test Results)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) analysis and Simplified Model Test (SMT) design methodology continued in FY 2020. The previously developed single-bar SMT (SBSMT) technique was successfully extended to tubular shaped Alloy 617 specimens for evaluation of the effect of primary pressure load on SMT creep-fatigue (CF) properties at 950°C. A series of pressurized SMT tests were performed with various elastic follow-up factors and strain ranges. The results show that the primary pressure load reduces the SMT CF cycles. The reduction of SMT CF life due to primary load was found to be dependent on strain ranges, elastic follow up and test temperatures. These results are crucial for verification of the EPP strain range analysis in the EPP+SMT evaluation procedure. Additionally, hold time effect on the SMT CF life cycles is a determining factor for generating the EPP+SMT CF design curves. Lack of test data in the high cycle and low strain range region results in major uncertainty in developing the design curves. In FY2020, experiments were designed, and testing started on Alloy 617 at 950°C to fill the gap in experimental data. The on-going CF and additional SMT CF with elastic follow-up at low strain ranges will generate the information needed to verify the methods for extrapolation to long hold time and finalize the EPP+SMT design method.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1975

Design automation techniques for custom LSI arrays

The standard cell design automation technique is described as an approach for generating random logic PMOS, CMOS or CMOS/SOS custom large scale integration arrays with low initial nonrecurring costs and quick turnaround time or design cycle. The system is composed of predesigned circuit functions or cells and computer programs capable of automatic placement and interconnection of the cells in accordance with an input data net list. The program generates a set of instructions to drive an automatic precision artwork generator. A series of support design automation and simulation programs are described, including programs for verifying correctness of the logic on the arrays, performing dc and dynamic analysis of MOS devices, and generating test sequences.

Feller, A.↗

NASA NTRS1989

Reflectance characteristics and surface processes in stabilized dune environments

Analysis of multitemporal TM data for three environmentally related field areas yields information on the response characteristics of stabilized dunes and desert-fringe environments. The three field sites studied include dune fields in Egypt, Mali, and Botswana, ranging in climate from hyperarid to semiarid, and may be classed as an environmental series relating surface processes under Saharan, Sahelian, and Savanna conditions. Sites were field mapped and monitored with TM data for lengths of time up to a year. The complexity of spectral response characteristics is greatest where vegetation is dense and diverse, but study of the three environments together places constraints on the importance of vegetation to spectral response as well as to mechanisms of sand transport. In both Mali and Botswana, the Sahelian and Savanna environments, contrast reversals occur on dune crests and reflectance patterns change through the dry season to resemble the response curves of the hyperarid study site in Egypt. In these analyses, overall surface brightness is controlled by sand composition, while spectral features are controlled by vegetation dynamics.

Jacobberger, P. A.↗

NASA NTRS1999

Optical Properties of Aerosols from Long Term Ground-Based Aeronet Measurements

AERONET is an optical ground-based aerosol monitoring network and data archive supported by NASA's Earth Observing System and expanded by federation with many non-NASA institutions including AEROCAN (AERONET CANada) and PHOTON (PHOtometrie pour le Traiteinent Operatonnel de Normalisation Satellitaire). The network hardware consists of identical automatic sun-sky scanning spectral radiometers owned by national agencies and universities purchased for their own monitoring and research objectives. Data are transmitted hourly through the data collection system (DCS) on board the geostationary meteorological satellites GMS, GOES and METEOSAT and received in a common archive for daily processing utilizing a peer reviewed series of algorithms thus imposing a standardization and quality control of the product data base. Data from this collaboration provides globally distributed near real time observations of aerosol spectral optical depths, aerosol size distributions, and precipitable water in diverse aerosol regimes. Access to the AERONET data base has shifted from the interactive program 'demonstrat' (reserved for PI's) to the AERONET homepage allowing faster access and greater development for GIS object oriented retrievals and analysis with companion geocoded data sets from satellites, LIDAR and solar flux measurements for example. We feel that a significant yet under utilized component of the AERONET data base are inversion products made from hourly principal plane and almucanter measurements. The current inversions have been shown to retrieve aerosol volume size distributions. A significant enhancement to the inversion code has been developed and is presented in these proceedings.

Holben, B. N.↗

NASA NTRS2004

Interannual Variations in Earth's Low-Degree Gravity Field and the Connections With Geophysical/Climatic Changes

Long-wavelength time-variable gravity recently derived from satellite laser ranging (SLR) analysis have focused to a large extent on the effects of the recent (since 1998) large anomalous change in J2, or the Earth's oblateness, and the potential causes. However, it is relatively more difficult to determine whether there are corresponding signals in the shorter wavelength zonal harmonics from the existing SLR-derived time variable gravity results, although it appears that geophysical fluid mass transport is being observed. For example, the recovered J3 time series shows remarkable agreement with NCEP-derived estimates of atmospheric gravity variations. Likewise, some of the non-zonal spherical harmonic components have significant interannual signal that appears to be related to mass transport. The non-zonal degree-2 components show reasonable temporal correlation with atmospheric signals, as well as climatic effects such as El Nino Southern Oscillation. We will present recent updates on the J2 evolution, as well as a look at other low-degree components of the interannual variations of gravity, complete through degree 4. We will examine the possible geophysical and climatic causes of these low-degree time-variable gravity related to oceanic and hydrological mass transports, for example some anomalous but prominent signals found in the extratropic Pacific ocean related to the Pacific Decadal Oscillation.

Chao, Benjamin F.↗

NASA NTRS2017

Kepler Planet Detection Metrics: Per-Target Flux-Level Transit Injection Tests of TPS for Data Release 25

Quantifying the ability of a transiting planet survey to recover transit signals has commonly been accomplished through Monte-Carlo injection of transit signals into the observed data and subsequent running of the signal search algorithm (Gilliland et al., 2000; Weldrake et al., 2005; Burke et al., 2006). In order to characterize the performance of the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017) on a sample of over 200,000 stars, two complementary injection and recovery tests are utilized:1. Injection of a single transit signal per target into the image or pixel-level data, hereafter referred to as pixel-level transit injection (PLTI), with subsequent processing through the Photometric Analysis (PA), Presearch Data Conditioning (PDC), Transiting Planet Search (TPS), and Data Validation (DV) modules of the Kepler pipeline. The PLTI quantification of the Kepler pipeline's completeness has been described previously by Christiansen et al. (2015, 2016); the completeness of the final SOC 9.3 Kepler pipeline acting on the Data Release 25 (DR25) light curves is described by Christiansen (2017).2. Injection of multiple transit signals per target into the normalized flux time series data with a subsequent transit search using a stream-lined version of the Transiting Planet Search (TPS) module. This test, hereafter referred to as flux-level transit injection (FLTI), is the subject of this document. By running a heavily modified version of TPS, FLTI is able to perform many injections on selected targets and determine in some detail which injected signals are recoverable. Significant numerical efficiency gains are enabled by precomputing the data conditioning steps at the onset of TPS and limiting the search parameter space (i.e., orbital period, transit duration, and ephemeris zero-point) to a small region around each injected transit signal.The PLTI test has the advantage that it follows transit signals through all processing steps of the Kepler pipeline, and the recovered signals can be further classified as planet candidates or false positives in the exact same manner as detections from the nominal (i.e., observed) pipeline run (Twicken et al., 2016, Thompson et al., in preparation). To date, the PLTI test has been the standard means of measuring pipeline completeness averaged over large samples of targets (Christiansen et al., 2015, 2016; Christiansen, 2017). However, since the PLTI test uses only one injection per target, it does not elucidate individual-target variations in pipeline completeness due to differences in stellar properties or astrophysical variability. Thus, we developed the FLTI test to provide a numerically efficient way to fully map individual targets and explore the performance of the pipeline in greater detail. The FLTI tests thereby allow a thorough validation of the pipeline completeness models (such as window function (Burke and Catanzarite, 2017a), detection efficiency (Burke Catanzarite, 2017b), etc.) across the spectrum of Kepler targets (i.e., various astrophysical phenomena and differences in instrumental noise). Tests during development of the FLTI capability revealed that there are significant target-to-target variations in the detection efficiency.

DR25↗

NASA NTRS2019

Applicability of Spectral Decomposition by Varimax-Rotated, Principal Component Analysis to the Surface Biology and Geology (SBG) VNIR Mission Concept

Cyanobacterial and Harmful Algal Blooms (CyanoHABs) are a growing concern in coastal and inland waters. But, spectral interference from multiple constituents in optically complex waters can hamper application of remote sensing using traditional image processing methods. The Kent State University (KSU) spectral decomposition method can be applied to multispectral and hyperspectral remote sensing images (e.g. HICO and the NASA Glenn HSI2) to partition and identify signals related to cyanobacteria, algae, pigment degradation products and suspended sediment in each pixel. Fundamental to the use of remote sensing data is the ability to extract independent signals from correlated hyperspectral VNIR data cubes. The Kent State University varimax-rotated, principal component analysis method (VPCA) is important to integrate into the SBG VNIR mission concept because it provides greater specificity, a software-based SNR boost relative to hardware performance, and can assist with Cal/Val, Modeling and Applications. We present examples of the hyperspectral application of the KSU VPCA method with relevance to SBG. The information extracted by VPCA can be validated spectrally or spatially with laboratory and/or in situ sensors, which capture spatial or time series of information at discrete points within remote sensing images. Comparisons show hyperspectral sensors extract more components than multispectral ones, but more independent information can be extracted from multispectral sensors by VPCA than traditional band ratio approaches. The spectral decomposition method is capable of enhancing the signal to noise ratio (SNR) of the NASA Glenn, second-generation hyperspectral imager by a factor of 7x to 20x, with a spectral reproducibility of ±3%. The spectral decomposition method, when compared against existing remote sensing monitoring methods exhibits both greater specificity and a lower detection limit. The method has been validated with multispectral images in Lake Erie to quantify the Microcystis CyanoHAB and from the Indian River Lagoon, Florida to quantify the Brown Tide resulting from A. lagunesnsis. Field operations in the Western Basin of Lake Erie were conducted using a bbe Fluoroprobe to collect vertical profiles and horizontal tows along a transect from the Toledo to the Detroit Lighthouse during coincident satellite overpasses. Extraction of pixel values from the MODIS Aqua sensor yields agreement between in situ field and lab-based measures of cyanobacterial, cryptophyte, diatoms and green algae, suspended sediment and pigment degradation products with R2>0.8.

hyperspectral↗

DOE OSTI2023

Probing the Mechanical Performance of Micro-architected Porous Structures Through In Situ Characterization and Analysis

Micropores play critical roles in both natural and man-made materials. Such pores take on a variety of shapes and sizes ranging from spherical to irregular sphere-like voids with diameters spanning from the nanometer to millimeter scales. When porous structures are mechanically loaded, the pores direct the stress around their free surfaces, altering the material’s mechanical response relative to fully dense materials. In this study, for the first time, we create micro-architected porous samples using nanolithography and investigate the role of pore morphology by conducting a series of in situ micropillar compression tests in scanning electron microscopy. The findings demonstrate that porosity is the primary factor influencing the mechanical response of these micro-architected materials, as often seen on a macroscopic level. Additionally, we observed that pore geometry had a significant impact on Young’s modulus, yield stress, and strain energy density as a secondary parameter. Then, the extracted Young’s modulus was compared to macroscopic empirical models and determined the analytical models sufficiently described the impact of porosity in the microscopic scale but failed to capture the impact of second-order parameters. Furthermore, these results suggest how porous materials can be tailored to achieve desired mechanical properties based on the engineering applications of interest.

36 MATERIALS SCIENCE↗

NASA NTRS1973

Time dependent worldwide distribution of atmospheric neutrons and of their products. I, II, III.

Review of the experimental results obtained in a series of measurements of the fast neutron cosmic ray spectrum by means of high-altitude balloons and aircraft. These results serve as a basis for checking a Monte Carlo calculation of the entire neutron distribution and its products. A calculation of neutron production and transport in the earth's atmosphere is then discussed for the purpose of providing a detailed description of the morphology of secondary neutron components. Finally, an analysis of neutron observations during solar particle events is presented. The Monte Carlo output is used to estimate the contribution of flare particles to fluctuations in the steady state neutron distributions.

Merker, M.↗

DOE OSTI2023

How Climate and Data Quality Impact Photovoltaic Performance Loss Rate Estimations

Different data pipelines and statistical methods are applied to photovoltaic (PV) performance datasets to quantify the performance loss rate (PLR). Since the real values of PLR are unknown, a variety of unvalidated values are reported. As such, the PV industry commonly assumes PLR based on statistically extracted ranges from the literature. However, the accuracy and uncertainty of PLR depend on several parameters including seasonality, local climatic conditions, and the response of a particular PV technology. In addition, the specific data pipeline and statistical method used affect the accuracy and uncertainty. To provide insights, a framework of (≈200 million) synthetic simulations of PV performance datasets using data from different climates is developed. Time series with known PLR and data quality are synthesized, and large parametric studies are conducted to examine the accuracy and uncertainty of different statistical approaches over the contiguous US, with an emphasis on the publicly available and “standardized” library, RdTools . In the results, it is confirmed that PLRs from RdTools are unbiased on average, but the accuracy and uncertainty of individual PLR estimates vary with climate zone, data quality, PV technology, and choice of analysis workflow. Best practices and improvement recommendations based on the findings of this study are provided.

14 SOLAR ENERGY↗

NASA NTRS1988

Creep rupture analysis of a beam resting on high temperature foundation

A simplified uniaxial strain controlled creep damage law is deduced with the use of experimental observation from a more complex strain dependent law. This creep damage law correlates the creep damage, which is interpreted as the density variation in the material, directly with the accumulated creep strain. Based on the deduced uniaxial strain controlled creep damage law, a continuum mechanical creep rupture analysis is carried out for a beam resting on a high temperature elastic (Winkler) foundation. The analysis includes the determination of the nondimensional time for initial rupture, the propagation of the rupture front with the associated thinning of the beam, and the influence of creep damage on the deflection of the beam. Creep damage starts accumulating in the beam as soon as the load is applied, and a creep rupture front develops at and propagates from the point at which the creep damage first reaches its critical value. By introducing a series of fundamental assumptions within the framework of technical Euler-Bernoulli type beam theory, a governing set of integro-differential equations is derived in terms of the nondimensional bending moment and the deflection. These governing equations are subjected to a set of interface conditions at the propagating rupture front. A numerical technique is developed to solve the governing equations together with the interface equations, and the computed results are presented and discussed in detail.

Gu, Randy J.↗

NASA NTRS2003

The Rondonia Lightning Detection Network: Network Description, Science Objectives, Data Processing Archival/Methodology, and Results

A four station Advanced Lightning Direction Finder (ALDF) network was established in the state of Rondonia in western Brazil in 1999 through a collaboration of U.S. and Brazilian participants from NASA, INPE, INMET, and various universities. The network utilizes ALDF IMPACT (Improved Accuracy from Combined Technology) sensors to provide cloud-to-ground lightning observations (i.e., stroke/flash locations, signal amplitude, and polarity) using both time-of- arrival and magnetic direction finding techniques. The observations are collected, processed and archived at a central site in Brasilia and at the NASA/Marshall Space Flight Center in Huntsville, Alabama. Initial, non-quality assured quick-look results are made available in near real-time over the Internet. The network, which is still operational, was deployed to provide ground truth data for the Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite that was launched in November 1997. The measurements are also being used to investigate the relationship between the electrical, microphysical and kinematic properties of tropical convection. In addition, the long-time series observations produced by this network will help establish a regional lightning climatological database, supplementing other databases in Brazil that already exist or may soon be implemented. Analytic inversion algorithms developed at the NASA/Marshall Space Flight Center have been applied to the Rondonian ALDF lightning observations to obtain site error corrections and improved location retrievals. The data will also be corrected for the network detection efficiency. The processing methodology and the results from the analysis of four years of network operations will be presented.

Blakeslee, R. J.↗