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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Charles River Watershed Water Resources: Assessing Flooding Vulnerability to Assist High Water Intervention and Urban Planning Programs in the Charles River Watershed

The Charles River watershed intersects 35 municipalities within the Boston Metropolitan Area and has a population of 1.2 million, making it one of the most densely populated watersheds in New England. In recent years, the watershed has observed higher rates of flood inundation, mainly due to increased development, extreme precipitation events, and increased surface runoff. As the frequency of flood events increases and a changing climate poses an ongoing threat to local communities, governments, and organizations in Massachusetts need accurate flood risk assessments. This project partnered with the Charles River Watershed Association, the Town of Natick’s Office of Sustainability, and the Massachusetts Audubon Society to assess the potential for watershed degradation, flood vulnerability, and flood susceptibility in the watershed. The team used Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-Band Synthetic Aperture Radar (C-SAR), and Sentinel-2 MultiSpectral Instrument (MSI) to assess the feasibility of identifying flood events using remote sensing. After identifying images that overlapped with the reported flood events, the team concluded that it was not feasible to use Earth observation data to detect localized flooding. Instead, the Federal Emergency Management Agency (FEMA) 100-year floodplain was used as a proxy for areas where flooding may occur. The team used statistical analysis and supervised classification to develop a flood susceptibility map, incorporating factors like soil drainage, height above nearest drainage, and topographic wetness index. This was overlaid with demographic and socioeconomic data to create a flood vulnerability map. The flood susceptibility map captured over 2/3 of reported flood events in the watershed, an improvement over the 1/3 of events captured by the FEMA 100-year and 500-year floodplain maps.

DEVELOP Project Summary↗
NASA NTRSDate not supplied

ISS EVA80 EMU Water in the Helmet Failure and Associated Analytical Response

On March 23rd, 2022, during Extra-Vehicular Activity (EVA) 80 aboard the International Space Station (ISS) crew identified an 8-10-inch diameter thin film of water in the pressure bubble of the suit during repress. This launched an investigation to determine the cause of the water in the helmet as well as short- and long-term mitigation efforts to enable return to EVA as quickly as possible. The investigation analysis efforts in combination with hardware inspection and testing determined the most likely cause of the water in the helmet to be sublimator carryover as a result of high latent loading put on the system. In parallel with this investigation, efforts were being made to mitigate any future water in the helmet events. The short-term mitigation strategy developed is to install absorbent material in the pressure bubble to capture water as it enters the helmet before it can impact the astronauts. This hardware is referred to as the Helmet Absorption Band (HAB) and Helmet Absorption Pad – Extender (HAP-E). Longer-term mitigation strategies include a device to capture small water events before entering the helmet by installing a water capture system in the vent loop of the Extravehicular Mobility Unit (EMU). This effort is coined the T2 Water Capture System. Additionally, developing an on-orbit sublimator challenge test which will be able to verify sublimator performance before and after EVAs. The sublimator is the hardware which condenses water vapor and removes it from the vent loop, and this hardware is referred to as the EMU Moisture Injection Test System (EMITS). Based on the investigation and short-term water capture solutions the ISS Program decided to return to nominal EVAs on October 7, 2022. With the addition of the long-term mitigation strategies, the team hopes to be able to prevent any future water in the helmet events.

Veronica Lee Pizor↗
DOE OSTI2025

Early events in G-quadruplex folding captured by time-resolved small-angle X-ray scattering

Abstract Time-resolved small-angle X-ray experiments are reported here that capture and quantify a previously unknown rapid collapse of the unfolded oligonucleotide as an early step in the folding of hybrid 1 and hybrid 2 telomeric G-quadruplex structures. The rapid collapse, initiated by a pH jump, is characterized by an exponential decrease in the radius of gyration from 24.3 to 12.6 Å. The collapse is monophasic and is complete in <600 ms. Additional hand-mixing pH-jump kinetic studies show that slower kinetic steps follow the collapse. The folded and unfolded states at equilibrium were further characterized by SAXS studies and other biophysical tools, showing that G4 unfolding was complete at alkaline pH, but not in LiCl solution as is often claimed. The SAXS Ensemble Optimization Method analysis reveals models of the unfolded state as a dynamic ensemble of flexible oligonucleotide chains with a variety of transient hairpin structures. These results suggest a G4 folding pathway in which a rapid collapse, analogous to molten globule formation seen in proteins, is followed by a confined conformational search within the collapsed particle to form the native contacts ultimately found in the stable folded form.

Biochemistry & Molecular Biology↗
NASA NTRS1994

Purity and cleanness of aerogel as a cosmic dust capture medium

The capability for capturing micrometeoroids intact through laboratory simulations and in space in passive underdense silica aerogel offers a valuable tool for cosmic dust research. The integrity of the sample handling medium can substantially modify the integrity of the sample. Intact capture is a violent hypervelocity event: the integrity of the capturing medium can cause even greater modification of the sample. Doubts of the suitability of silica aerogel as a capture medium were raised at the 20th LPSC, and questions were raised again at the recent workshop on Particle Capture, Recovery, and Velocity Trajectory Measurement Technologies. Assessment of aerogel's volatile components and carbon contents have been made. We report the results of laboratory measurements of the purity and cleanliness of silica aerogel used for several Sample Return Experiments flown on the Get Away Special program.

Tsou, P.↗
NASA NTRS2003

Autonomous Science on the EO-1 Mission

In mid-2003, we will fly software to detect science events that will drive autonomous scene selectionon board the New Millennium Earth Observing 1 (EO-1) spacecraft. This software will demonstrate the potential for future space missions to use onboard decision-making to detect science events and respond autonomously to capture short-lived science events and to downlink only the highest value science data.

autonomous systems robust execution↗
NASA NTRS1994

Purity and Cleanness of Aeorgel as a Cosmic Dust Capture Medium

The capability for capturing micrometeoroids intact through laboratory simulations [Tsou 1988] and in space [Tsou 1993] in passive underdense silica aerogel offers a valuable tool for cosmic dust research. The integrity of the sample handling medium can substantially modify the integrity of the sample. Intact capture is a violent hypervelocity event: the integrity of the capturing medium can cause even greater modification of the sample.

micrometeoroids cosmic dust silica aerogel↗
NASA NTRS2016

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

anomaly detection↗
DOE OSTI2025

Historical Bolide Infrasound Dataset (1960–1972)

We present the first fully curated, publicly accessible archive of infrasonic records from ten large bolide events documented by the U.S. Air Force Technical Applications Center’s global microbarometer network between 1960 and 1972. Captured on analog strip-chart paper, these waveforms predate modern digital arrays and space-based sensors, making them a unique window on meteoroid activity in the mid-twentieth century. Prior studies drew important scientific conclusions from the records but released only limited artifacts, chiefly period–amplitude tables and unprocessed scans, leaving the underlying data inaccessible for independent study. The present release transforms those limited excerpts into a research-ready resource. By capturing ten large events in the mid-20th century, the dataset constitutes a critical reference point for assessing bolide activity before the advent of modern space-based and digital ground-based monitoring. The multi-year coverage and worldwide distribution of events provide a valuable reference for comparing past and more recent detections, facilitating assessments of long-term flux and the dynamics of acoustic wave propagation in Earth’s atmosphere. The dataset’s availability in a consolidated format ensures straightforward access to waveforms and derived measurements, supporting a wide range of scientific inquiries into bolide physics and infrasound monitoring. By preserving these historical acoustic observations, the collection maintains a significant record of mid-20th-century meteoroid entries. It thereby establishes a basis for further refinement of impact hazard evaluations, contributes to historical continuity in atmospheric observation, and enriches the study of meteoroid-generated infrasound signals on a global scale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Identifying and tracking bubbles and drops in simulations: A toolbox for obtaining sizes, lineages, and breakup and coalescence statistics

Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the background flow also drive the time evolution of these distributions. Accurate and robust identification and tracking algorithms for the dispersed phase are necessary to reliably measure this evolution and thereby quantify the underlying mechanisms in interface-resolving flow simulations. The identification of individual bubbles and drops traditionally relies on an algorithm used to identify connected regions. This traditional algorithm can be sensitive to the presence of spurious structures. A cost-effective refinement is proposed to maximize volume accuracy while minimizing the identification of spurious bubbles and drops. An accurate identification scheme is crucial for distinguishing bubble and drop pairs with large size ratios. The identified bubbles and drops need to be tracked in time to obtain breakup and coalescence statistics that characterize the evolution of the size distribution, including breakup and coalescence frequencies, and the probability distributions of parent and child bubble and drop sizes. An algorithm based on mass conservation is proposed to construct bubble and drop lineages using simulation snapshots that are not necessarily from consecutive time steps. These lineages are then used to detect breakup and coalescence events, and obtain the desired statistics. Accurate identification of large-size-ratio bubble and drop pairs enables accurate detection of breakup and coalescence events over a large size range. Accurate detection of successive breakup and coalescence events requires that the snapshot interval be an order of magnitude smaller than the characteristic breakup and coalescence times to capture these successive events while minimizing the identification of repeated confounding events. Together, these algorithms serve as a toolbox for detailed analysis of two-phase simulations, and enable insights into the mechanisms behind bubble and drop formation and evolution in flows of practical importance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory

Risk-sensitive reinforcement learning (RL) has garnered significant attention in recent years due to the growing interest in deploying RL agents in real-world scenarios. A critical aspect of risk awareness involves modelling highly rare risk events (rewards) that could potentially lead to catastrophic outcomes. These infrequent occurrences present a formidable challenge for data-driven methods aiming to capture such risky events accurately. While risk-aware RL techniques do exist, they suffer from high variance estimation due to the inherent data scarcity. Our work proposes to enhance the resilience of RL agents when faced with very rare and risky events by focusing on refining the predictions of the extreme values predicted by the state-action value distribution. To achieve this, we formulate the extreme values of the state-action value function distribution as parameterized distributions, drawing inspiration from the principles of extreme value theory (EVT). We propose an extreme value theory based actor-critic approach, namely, Extreme Valued Actor-Critic (EVAC) which effectively addresses the issue of infrequent occurrence by leveraging EVT-based parameterization. Importantly, we theoretically demonstrate the advantages of employing these parameterized distributions in contrast to other risk-averse algorithms. Our evaluations show that the proposed method outperforms other risk averse RL algorithms on a diverse range of benchmark tasks, each encompassing distinct risk scenarios.

Wang, Yu↗
DOE OSTI2020

Real-time damage characterization for GFRCs using high-speed synchrotron X-ray phase contrast imaging

Here, we report the application of high-speed synchrotron X-ray phase contrast imaging (PCI) in real-time damage characterization for glass fiber reinforced composites (GFRCs) subjected to dynamic loading. Dynamic single-edge notched bending (DSENB) experiments on pre-notched S-2 GFRCs were performed on a modified Kolsky compression bar. During loading, the synchrotron X-ray beam penetrated through the composite specimen from the side to detect damage evolution inside the material. Entire dynamic events were recorded by a high-speed camera as image sequences.0° and 90° unidirectional and cross-ply composites were investigated. An optical imaging technique was also employed to capture similar dynamic events in comparison with the radiographic imaging. It is demonstrated that high-speed X-ray PCI had sufficient phase contrast to characterize a crack initiation at a 20-μm spatial resolution within 920 ns and track the crack geometry during propagation, thereby providing reliable data to quantify the dynamic damage resistance of GFRCs. Furthermore, being capable of recognizing microscopic damage-related features at a sub-10-μm resolution, high-speed X-ray PCI provided fundamental material failure mechanisms to reveal the essential of macroscale structural failure of composites. It can also track the damage evolution inside and between individual plies of laminated composites. However, current high-speed X-ray PCI technique only supports in-situ observation and the high timing and spatial resolutions are limited within a field of view of ~2.5 mm in square, preventing its application in the three-dimensional and larger-area damage detection for GFRC structures.

42 ENGINEERING↗
NASA NTRS2021

Comparison of chemical lateral boundary conditions for air quality predictions over the contiguous United States during pollutant intrusion events

The National Air Quality Forecast Capability (NAQFC) operated in U.S.’s National Oceanic and Atmospheric Administration (NOAA) provides the operational forecast guidance for ozone and fine particulate matters with aerodynamic diameters less than 2.5μm (PM2.5) over the contiguous 48 U.S. states (CONUS) using the Community Multi-scale Air Quality (CMAQ) model. The existing NAQFC uses climatological chemical lateral boundary conditions ( CLBCs), which cannot capture pollutant intrusion events originating outside of the model domain. In this study, we developed a model framework to use dynamic CLBCs from the Goddard Earth Observing System Model, version 5 (GEOS) to drive NAQFC. A mapping of the GEOS chemical species to the CMAQ’s Carbon Bond 5 (CB05)-Aero6 species was developed. The utilization of the GEOS dynamic CLBCs in NAQFC showed the best overall performance in simulating the surface observations during the Saharan dust intrusion and Canadian wildfire events in summer 2015.The simulated PM2.5 was improved from 0.18 to 0.37 and the mean bias was reduced from -6.74 μg/m3 to -2.96 μg/m3 over CONUS. Although the effect of CLBCs on the PM2.5 correlation was mainly near the inflow boundary, its impact on the background concentrations reached further inside the domain. The CLBCs could affect background ozone concentrations through the inflows of ozone itself and its precursors, such as CO. It was further found that the aerosol optical thickness (AOT) from satellite retrievals correlated well with the column CO and elemental carbon from GEOS. The satellite-derived AOT CLBCs generally improved the model performance for the wildfire intrusion events during a summer 2018 case study, and demonstrated how satellite observations of atmospheric composition could be used as an alternative method to capture the air quality effects of intrusions when the global model CLBCs, such as GEOS CLBCs, are not available.

Community Multi-scale Air Quality (CMAQ) model↗
NASA NTRS2011

Drop Shapes Versus Fall Velocities in Rain: 2 Contrasting Examples

Rainfall retrievals from polarimetric radar measurements require the knowledge of four fundamental rain microstructure parameters, namely, drop size distribution, drop shape distribution, canting angles and drop fall velocities. Some recent measurements of all four parameters in natural rain are summarized in [1]. In this paper, we perform an in-depth analysis of two events, using two co-located 2D video disdrometers (2DVD; see [2]) both with high calibration accuracy, and a C-band polarimetric radar [3], located 15 km away. The two events, which occurred 7 days apart (on the 18th and the 25th of Dec 2009), had moderate-to-intense rainfall rates, but the second event had an embedded convection line within the storm. The line had passed over the 2DVD site, thus enabling the shapes and fall velocities to be determined as the line crossed the site. The first event was also captured in a similar manner by both the 2DVDs as well as the C-band radar. Drop fall velocity measurements for, say, the 3 mm drops show noticeable differences between the two events. Whereas for the first event, the velocity distribution showed a narrow and symmetric distribution, with a mode at the expected value (7.95 m/s, as given by the formula in [4]), the second event produced a wider distribution with a significant skewness towards lower velocities (although its mode too was close to the expected value). Moreover, the slower 3 mm drops in the second event occurred when the convection line was directly over the 2DVD site (03:35-03:45 utc), and not before nor after. A similar trend was observed in terms of the horizontal dimensions of the 3 mm drops, i.e. large fluctuations during the same time period, but not outside the period. Vertical dimensions of the drops also fluctuated but not to the same extent. Interestingly, the horizontal dimensions tended towards larger values during the 10-minute period, implying an increase in drop oblateness, which in turn indicates the possibility of the horizontal mode oscillation, one of the three fundamental modes of drop oscillations [5], albeit the most difficult one to excite.

Thurai, M.↗
NASA NTRS2018

Sub-Seasonal Forecasting of the Stratospheric Wave Events, Sudden Stratospheric Warmings, and Their Influence on the Troposphere

Stratospheric wave events and major sudden stratospheric warming (SSW) events are well captured in high-resolution global forecasts out to 10 days. Tropospheric influences of SSW include statistically significant shifts in the storm tracks and associated surface temperature and precipitation pattern changes. Since these events can in turn influence the troposphere on time scales of 30-60 days the ability to predict these events and the subsequent long-term response on time scales beyond 10 days is of interest. Here we examine the prediction of stratospheric wave events and their evolution using the NASA GMAO (Global Modeling and Assimilation Office) Sub-Seasonal to Seasonal (S2S) system. This is a recently released subseasonal to seasonal forecast system, GEOS-S2S version 2.1. Compared to GMAO's previous system, the new version runs at higher atmospheric resolution (approximately 1/2 degree globally), contains a substantially improved model of the cryosphere, includes additional interactive aerosol model components, and the ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter. Results are based on a comprehensive series of hindcasts starting from the year 2000. They show that while the S2S system is not as accurate at 10 days in forecasting major SSW events as the NASA GMAO Forward Processing system, it can usefully predict stratospheric anomalies out to 20 days and the subsequent stratospheric/tropospheric evolution beyond 30 days.

Coy, L.↗
DOE OSTI2022

Solar Irradiance Ramp Forecasting Based on All-Sky Imagers

Solar forecasting constitutes a critical tool for operating, producing and storing generated power from solar farms. In the framework of the International Energy Agency’s Photovoltaic Power Systems Program Task 16, the solar irradiance nowcast algorithms, based on five all-sky imagers (ASIs), are used to investigate the feasibility of ASIs to foresee ramp events. ASIs 1–2 and ASIs 3–5 can capture the true ramp events by 26.0–51.0% and 49.0–92.0% of the cases, respectively. ASIs 1–2 provided the lowest (<10.0%) falsely documented ramp events while ASIs 3–5 recorded false ramp events up to 85.0%. On the other hand, ASIs 3–5 revealed the lowest falsely documented no ramp events (8.0–51.0%). ASIs 1–2 are developed to provide spatial solar irradiance forecasts and have been delimited only to a small area for the purposes of this benchmark, which penalizes these approaches. These findings show that ASI-based nowcasts could be considered as a valuable tool for predicting solar irradiance ramp events for a variety of solar energy technologies. The combination of physical and deep learning-based methods is identified as a potential approach to further improve the ramp event forecasts.

14 SOLAR ENERGY↗
DOE OSTI2021

Updated weather model captures subtleties of cold-air pool events

Imagine cold air building up inside a valley or other topographic basin, like a cold swimming pool in the atmosphere. Known in meteorology as cold-air pools, or simply cold pools, these events affect wind plant power production in two key ways. Because they are associated with stagnant air and low winds near the ground, cold pools can severely limit wind energy output over periods of hours to days. Then, when cold pools dissolve, known as cold pool “erosion,” increased wind speeds allow wind power production to recover.

Energy↗
NASA NTRS2019

Influence of Land Cover and Soil Moisture based Brown Ocean Effect on an Extreme Rainfall Event from a Louisiana Gulf Coast Tropical System

Extreme flooding over southern Louisiana in mid-August of 2016 resulted from an unusual tropical low that formed and intensified over land. We used numerical experiments to highlight the role of ‘Brown Ocean’ effect (where saturated soils function similar to a warm ocean surface) on intensification and it’s modulation by land cover change. A numerical modeling experiment that successfully captured the flood event (control) was modified to alter moisture availability by converting wetlands to open water, wet croplands, and dry croplands. Storm evolution in the control experiment with wet antecedent soils most resembles tropical lows that form and intensify over oceans. Irrespective of soil moisture conditions, conversion of wetlands to croplands reduced storm intensity, and also, non-saturated soils reduced rain by 20% and caused shorter durations of high intensity wind conditions. Developing agricultural croplands and more so restoring wetlands and not converting them into open water can impede intensification of tropical systems that affect the area.

Udaysankar S Nair↗
NASA NTRS2014

Very Large Rain Drops from 2D Video Disdrometers and Concomitant Polarimetric Radar Observations

Drop size distribution (DSD) measurements using ground-based disdrometers (point measurements) have often been used to derive equations to relate radar observations to the integral rainfall parameters (Atlas et al. 1999, Bringi et al., 2003, Kozu et al., 2006, Tokay and Short, 1996, Ajayi and Owolabi, 1987, Battan, 1973). Disdrometers such as JWD, MRR and several others have a major limitation in measuring drops with equi-volume diameters (D(sub eq)) larger than 5 mm because they often rely on the velocity-diameter relationship which plateaus beyond this diameter range (Atlas et al., 1973, Gunn & Kinzer, 1949). Other disdrometers such as Parsivel also lack accuracy beyond this diameter range. The 2D video disdrometer (2DVD: Schönhuber et al., 2008) on the other hand gives drop-shape contours and velocities for each individual drop/hydrometeor falling through its sensor area; this provides a unique opportunity to study the role of very-large drops on radar measurements in particular those with polarimetric radar capability where DSDs with a significant component of very large drops may require special consideration given that the differential reflectivity and other polarimetric radar parameters including attenuation-correction methods will be sensitive to the concentrations of these large drops. A recent study on the occurrence of large drops by Gatlin et al. (2014) has compiled a large and diverse set of measurements made with the 2D video disdrometers from many locations around the globe. Some of the largest drops found in this study were 9 mm D(sub eq) and larger, and in this paper, we report on three such events, with maximum D(sub eq's) of 9.0, 9.1 and 9.7 mm, which occurred in Colorado, Northern Alabama, and Oklahoma, respectively. Detailed examination of the 2DVD data - in terms of shapes and fall velocities - has confirmed that these are fully-melted hydrometeors, although for the last case in Oklahoma, a bigger and non-fully-melted hydrometeor was also observed. All three events were also captured by polarimetric radars, namely the S-band CHILL radar operated by Colorado State University (Brunkow et al., 2000), the C-band ARMOR radar (Petersen et al., 2007) operated by University of Alabama in Huntsville, and NEXRADKVNX, operated by the US National Weather Service, respectively. For the last event, several other radar observations were also made, including two X-band radars operated by the US Dept. of Energy. Analyses of 2DVD data in conjunction with the corresponding radar observations are presented, along with some discussion on sampling issues related to the measurements of such large rain drops. The latter is addressed using maximum diameter D(sub max) measurements from 1-minute DSDs using two collocated 2DVDs for 37 events in Huntsville.

Thurai, Merhala↗