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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Detection of Damage During Quasi-Static Loading of a Single Stringer Panel Using Passive Thermography and Acoustic Emission

The purpose of this paper is to describe the methodology of measuring damage onset and growth in a composite structure during quasi-static loading using passive thermography and acoustic emission. The early detection and measurement of damage progression is important to understand failure modes. A single stringer panel was subjected to quasi-static loading to induce deformation which resulted in the formation of damage between the stiffener flange and skin. The loading was stopped when damage growth was detected. Passive thermography and acoustic emission were used to detect damage in real-time as a function of the applied load. Of particular interest are the small transient thermographic signals resulting from damage formation which can be challenging to detect, as compared to the persistent passive thermography indications of cyclic fatigue loading. We describe a custom developed thermal inspection system for detection of composite damage during quasi-static loading. The thermal results are compared to a two-dimensional multi-layered thermal simulation based on the quadrupole method. Acoustic emission is used to further characterize the damage by comparing the acoustic emission events with the thermal imagery. Results are compared to ultrasonic measurements to document the damage through-the-thickness.

Zalameda, Joseph N.↗
NASA NTRS2013

Atom Interferometry for Detection of Gravitational Waves: NASA Institute for Advanced Concepts (NIAC) - Phase 1 Final Report

This report presents the results of the 2012-2013 NASA Institute for Advanced Concepts (NIAC) Phase 1 "Atom Interferometry for Detection of Gravitational Waves" project. The origin of this GW (Gravitational Wave) detection concept using atoms can be traced to theoretical work that first appeared in 2008 and also to a satellite mission-focused followup study that was done in 2011. The goal of the current project was to explore both theoretical and technical issues surrounding the implementation of this idea, as well as to begin performing proof-of-concept experiments to validate critical aspects of the proposal.The top level trade space for the detector design is driven by the strategy employed to mitigate laser frequency noise, which, if uncontrolled, can mask GW signatures. One of the advantages of the atom interferometric approach is the possibility of single baseline detection (Fig. 1.1), even in the presence of laser noise. This is enabled by the differential measurement between the two ensembles of atoms, which can result in substantial laser noise suppression. The details of this suppression depend on the atomic physics techniques used to implement the atom interferometry. Specifically, we considered the effect on noise suppression that results from using traditional two-photon Raman transitions (with alkali atoms) and also single-photon transitions (with alkaline earth-like atoms).The interferometers shown in Fig 1.1(b) take advantage of single-photon transitions (as opposed to traditional Raman transitions) because using light pulses from one direction at a time allows for near perfect common-mode cancellation of laser phase noise, even for long baselines. This calls for the use of atomic transitions with an (ideally large) optical energy level difference with a long (greater than 1 second) lifetime, such as high-transitions routinely used for optical atomic clocks in species like Sr, Ca and Yb. Notably, large momentum transfer (LMT) atom optics - and the sensitivity enhancement they confer – can still be realized by simply adding additional pairs of alternating pulses to each beam splitter process. Section 3 reports on the theoretical work we performed to justify this GW detection protocol using single-photon transitions. This approach represents a new method for GW detection using atoms that is distinct from the original proposal from 2008. At the system level, we evaluated three architectures, each of which implements a different solution to the laser frequency noise issue. The first two designs are based on two-photon Raman transitions with Rb atoms. One of these is a three-satellite, multiple baseline design while the other is a two-satellite, single baseline design. The third proposal is a two-satellite, single baseline design that uses single-photon transitions with Sr atoms. These three architectures are described in more detail in Section 2. There are a number of known technical issues that we have started to address using ground-based experiments. These issues include atom technology development needs such as, for example, lower ensemble temperature requirements and large momentum transfer (LMT) atom optics. To this end, we have built a 10-meter scale atom drop tower, where we can perform proof-of-principle demonstrations of the proposed AGIS detector in an environment that permits more than 2.5 seconds of free-fall time. This facility allows for demonstration of atom interferometry with long interrogation time (seconds) and large atom wavepacket

Saif, Babak N.↗
NASA NTRS2018

Methods for Passive Optical Detection and Relative Navigation for Rendezvous with a Non-Cooperative Object at Mars

Long-range passive optical detection of an orbiting inert sphere by a robotic Mars orbiter is investigated and trades are described in terms of detectability via reflected visible light in the presence of orbit uncertainty, gravitational perturbations, and camera electronics noise. A new approximate equation for signal-tonoise ratio (SNR) is developed to include most relevant camera imperfections, diffraction, and stray light from the Mars limb as relevant to this scenario. Using this method, a notional camera suite is designed to meet detection, navigation, and redundancy requirements for an example mission scenario. Results from a simulation tool demonstrate the long-range initial detection strategy in the presence of perturbations from various sources. Finally, navigation analysis shows that the information gathered using passive optical detection is sufficient to begin orbit matching.

Woolley, Ryan C.↗
NASA NTRS2021

Sensor Calibration Impacts on Dust Detection Based On MODIS And VIIRS Thermal Emissive Bands

Dust detection using remotely sensed measurements has been one of the challenging problems encountered by atmospheric scientists. MODerate Resolution Imaging Spectroradiometer (MODIS) on the Terra (T)and Aqua (A) platforms have been a versatile sensor for well over 21 and 18 years respectively and have been extremely useful in the retrieval of aerosol information over the entire globe. The MODIS radiances from the Level1B in general are expected to be within 5% accuracy in the reflective wavelengths and within 1% in the thermal emissive wavelengths. In this paper, we evaluate the sensitivity of previously developed dust detection technique based on thermal emissive wavelengths, which correspond to MODIS bands 20, 29, 31, and 32 respectively. The Thermal Emissive Dust Index (TEDI) performed very comparably to the traditional Aerosol Optical Thickness (AOT) retrievals by MODIS reflective channels. Since the MODIS Thermal Emissive Bands (TEB) are well calibrated on-orbit using a BlackBody (BB) source, the calibration of these long wave infrared bands is quite robust. As A-MODIS continues to perform well beyond its designed lifetime of 6 years, the instrument has undergone various levels of degradation during its mission time. As a consequence, it is imperative to check the impacts of calibration on the higher-level retrievals. In this paper, we rigorously analyze the sensitivity of TEDI due to the impact of calibration by the afore-mentioned TEB. The perturbation of the dominant (linear) calibration term demonstrated the following: first, there was a correlation in the sensitivity of the TEDI due to the uncertainty in the linear calibration term. Based on a perturbation in the linear calibration term for all aforementioned bands over a range of ± 5 % yielded the TEDI sensitivity to vary from approximately -3.2 % to about -3.6 %. When considering the uncertainty in each individual band significant changes were observed. The least change was observed for the perturbation in the calibration of band 20 with the TEDI sensitivity and the largest sensitivity in TEDI was observed in the perturbation of band 31 calibration. Thus, in the case of TEDI, noticeable sensitivity due to calibration uncertainty was observed in bands 29, 31, and 32, reiterating the importance of the TEB calibration in these bands. Also, the dust detection scheme based on A-MODIS was successfully transferred to the follow-on sensors such as Suomi (SNPP) and NOAA 20 (N20) VIIRS. The results presented in this paper would be extremely helpful in understanding impacts of calibration on the higher-level products for both current and future missions based on the MODIS heritage. Finally, the work also identifies the importance of radiometric fidelity in maintaining the accuracy of the dust detection. Results presented will show drastic improvement of the Saharan dust detection after the reduction of the electronic crosstalk in the 8.5 μm channel of T-MODIS.

Sriharsha Madhavan↗
NASA NTRS2020

The Lowest-frequency Fast Radio Bursts: Sardinia Radio Telescope Detection of the Periodic FRB 180916 at 328 MHz

We report on the lowest-frequency detection to date of three bursts from the fast radio burst FRB 180916.J0158+65, observed at 328 MHz with the Sardinia Radio Telescope (SRT). The SRT observed the periodic repeater FRB 180916.J0158+65 for five days from 2020 February 20 to 24 during a time interval of active radio bursting, and detected the three bursts during the first hour of observations; no more bursts were detected during the remaining ∼30 hr. Simultaneous SRT observations at 1548 MHz did not detect any bursts. Burst fluences are in the range 37 to 13 Jy ms. No relevant scattering is observed for these bursts. We also present the results of the multiwavelength campaign we performed on FRB 180916.J0158+65, during the five days of the active window. Simultaneously with the SRT observations, others with different time spans were performed with the Northern Cross at 408 MHz, with XMM-Newton, NICER, INTEGRAL, AGILE, and with the TNG and two optical telescopes in Asiago, which are equipped with fast photometers. XMM-Newton obtained data simultaneously with the three bursts detected by the SRT, and determined a luminosity upper limit in the 0.3–10 keV energy range of ∼10(exp 45) erg/s for the burst emission. AGILE obtained data simultaneously with the first burst and determined a fluence upper limit in the MeV range for millisecond timescales of 10(exp -8) erg/sq.cm. Our results show that absorption from the circumburst medium does not significantly affect the emission from FRB 180916.J0158+65, thus limiting the possible presence of a superluminous supernova around the source, and indicate that a cutoff for the bursting mechanism, if present, must be at lower frequencies. Our multi-wavelength campaign sensitively constrains the broadband emission from FRB 180916.J0158+65, and provides the best limits so far for the electromagnetic response to the radio bursting of this remarkable source of fast radio bursts.

M. Pilia↗
NASA NTRS2019

An Automatic Light Rain Detection Algorithm on NASA MPLNET Lidar Observations in the Frame of WMO GALION Project

The water cycle strongly influences life on Earth. In particular, the precipitation modifies the atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially low-intensity precipitation) at global scale, bedsides improving our understanding of the hydrological cycle, it is crucial to reduce the associated uncertainty of the global climate models to correctly forecast future scenarios, i.e. to apply fast mitigation strategies. In this study we developed an algorithm to automatically detect precipitation from lidar measurements obtained by the National and Aeronautics Space Administration (NASA) Micropulse lidar network (MPLNET) permanent observational site in Goddard. The algorithm, once full operational, will deliver in Near Real Time (latency 1.5h) a new rain mask product that will be publicly available on MPLNET website as part of the new Version 3 Level 1.5 data. The methodology, based on an image processing technique, can detect only light precipitation events (defined by intensity and duration) as the morphological filters used through the detection process are applied on the lidar volume depolarization ratio range corrected composite images, i.e. heavy rain events are unusable as the lidar signal is completely extinguished after few meters in the precipitation or no signal detected because of the water accumulated on the receiver optics. Results from the algorithm, besides filling a gap in precipitation and virga detection by radars, are of particular interest for the scientific community because will help to better understand long-term aerosol-cloud interactions and aerosol atmospheric removal (scavenging effect) by rain as multi-year database being available for several MPLNET permanent observational sites across the globe. Moreover, we developed the automatic algorithm at Universitat Politecnica de Catalunya (UPC) Barcelona, the unique permanent observation station member of MPLNET and the European Aerosol Lidar Network (EARLINET) In the future the algorithm can be then easily applied to any other lidar and/or ceilometer network infrastructure in the frame of World Meteorological Organization (WMO) Global Aerosol Watch (GAW) aerosol lidar observation network (GALION)

Simone Lolli↗
NASA NTRS2021

Microwave Radiometer RFI Detection Using Deep Learning

Radio frequency interference (RFI) is a risk for microwave radiometers due to their requirement of very high sensitivity. The Soil Moisture Active Passive (SMAP) mission has an aggressive approach to RFI detection and filtering using dedicated spaceflight hardware and ground processing software. As more sensors push to observe at larger bandwidths in unprotected or shared spectrum, RFI detection continues to be essential. This article presents a deep learning approach to RFI detection using SMAP spectrogram data as input images. The study utilizes the benefits of transfer learning to evaluate the viability of this method for RFI detection in microwave radiometers. The well-known pretrained convolutional neural networks, AlexNet, GoogleNet, and ResNet-101 were investigated. ResNet-101 provided the highest accuracy with respect to validation data (99%), while AlexNet exhibited the highest agreement with SMAP detection (92%).

Microwave radiometry↗
NASA NTRSDate not supplied

Bayesian Analysis of the Detection Performance of the Lightning Imaging Sensors

Identical Lightning Imaging Sensors aboard the Tropical Rainfall Measuring Mission satellite (TRMM LIS, 1998-2015) and International Space Station (ISS LIS, 2017-present) have collectively provided over two decades of lightning observations over the global tropics, with ISS LIS extending coverage into the mid-latitudes. Quantifying the detection performance of both LIS sensors is a necessary step toward generating a LIS climatological record and accurately combining LIS data with lightning detections from other sensors and networks. We compare lightning observations from both LIS sensors with reference sources including the Geostationary Lightning Mapper (GLM) and ground-based networks operated by Earth Networks (the Earth Networks Total Lightning Network [ENTLN] and Earth Networks Global Lightning Network [ENGLN]) and Vaisala (the National Lightning Detection Network [NLDN] and Global Lightning Dataset [GLD360]). Instead of a relative detection efficiency (RDE) approach that involves assuming perfect performance of the reference sensor, we employ a Bayesian approach to estimate the upper limit of the absolute detection efficiency (ADE) of each sensor being analyzed. The results of this Bayesian analysis illustrate the geographical pattern of ADE as well as its diurnal cycle and yearly evolution, reflecting the growth of the reference networks over time.

Katrina Virts↗
NASA NTRSDate not supplied

In-Lab Rapid Analytical Detection of Lunar Volatiles By Universal Gas Analyzer With Comparison to GC-MS System

Introduction: The curation of permanently shadowed regions (PSRs) [1] on the lunar surface is centered around studies based upon the observed volatiles from the LCROSS mission [2]. The rapid detection of important volatile gases and vapors present in planetary bodies and Astromaterials by a standalone analytical device is an area of intense research interest in our group and Planetary Exploration & Astromaterials Research Laboratory (PEARL) facility and this work is relevant to the future preparation of viable lunar simulants for testing curation efforts down the road. The groundbreaking results obtained from the LCROSS Mission [2] open the requirements for the direct detection of volatiles present in regolith materials collected from the lunar surface. The mass spectrometry of volatile chemicals is a general technique that utilizes a set of instruments that creates charged ions from a gaseous chemical species and measures the intensities vs. mass-to-charge ratio (m/z) [3]. In this context, we discuss in-lab experimental results and procedures for rapid qualitative analysis of main LCROSS volatiles (water, H2S, NH3, CO2, and CH3OH) by a Universal Gas Analyzer (UGA) instrument. Additionally, the instrument performance was evaluated by measuring the isotopic abundance ratio of atmospheric Ar-40 to Ar-36 present in room air since, argon is a relevant gas in planetary studies as it can provide an insight and reference point to isotope studies [4]. Additional, cross comparisons were attempted and made between the two instruments to develop a robust analytical technique by comparing mass spectral data for H2S headspace samples with a Trace-1310/ ISQ 7000 (ThermoFisher Scientific.) GC-MS system. Background: The benchtop UGA System is equipped with an SRS UGA 300 quadrupole mass spectrometer designed and built by Stanford Research Systems [5]. This system can be configured for several types of gaseous chemical analysis. The inlet line continuously samples gases at low flow rates (several milliliters per minute) through a capillary limiting the intake pressure making the instrument ideal for online analysis of select gases and/or room atmosphere. Moreover, in our current UGA system, a change in composition at the inlet can be detected in about 200 milliseconds and a complete spectrum is acquired (for a range of 1-100 amu) in under 45 sec with masses measured at rates up to 25 msec per point [5]. This system provides a quick upstream analytical data that we can then compare to results obtained by our GC-MS system. Sample Preparation: Small volume (2-4 mL) of analyte sample was taken in a 10 mL glass vial and sealed with a crimped cap and purged with pure Ar or N2 gas to displace air from the top. The headspace sample was scanned by the UGA instrument at analog, histogram, and pressure vs. time modes. The isotopic abundance ratio for 40Ar-to-36Ar was estimated by measuring partial pressure vs. time scans and setting the mass at 40 and 36 respectively. Results and Discussions: In this work, we have investigated the applicability of the UGA system by qualitative analysis of a series of LCROSS volatiles measured individually. Fig. 1 demonstrates a set of vertically offset spectra for the partial pressures measured as a function of mass-to-charge (m/z) ratios. The average acquisition time for each spectrum was less than a minute suggesting that the UGA system is ideal for quick analysis of geochemical volatiles. For the cross-comparison, we analyzed an H2S headspace sample by a Trace-1310/ISQ-7000 system and compared mass spectral data with previously measured UGA histogram scan data (Fig. 2). In both cases, major peak positions are the same, however, the intensities of fragment ions ([1H132S]+ and [32S]+) are higher for UGA suggesting that the fragment ionization process is stronger in UGA compared to that of GC-MS. To investigate how the integrated area under each chromatogram varies with the headspace sample volume, a set of five H2S headspace samples with increasing volumes was analyzed by the GC-MS system (Fig. 3, inset). A small volume (e.g., 200 to 1000 µL) of H2S/H2O vapor was withdrawn from a 20 mL stock sample vial containing ~5 mL of 0.4% H2S in water by a gas-tight syringe and added to another 20 mL vial filled with argon and analyzed by the GC-MS system. Finally, the UGA detector sensitivity was evaluated by calculating the atmospheric 40Ar-to-36Ar isotopic abundance ratio in room air by running a partial pressure vs. time scan with setting the atomic mass at 40, and 36. Fig. 4(a) shows a ~25 min duration “P vs. time” scan for 40Ar (plot for 36Ar is not shown). The partial pressure values (~100 points) were corrected by subtracting the corresponding background pressure value for 37Ar and utilized to calculate 40Ar-to-36Ar isotopic abundance ratios as shown by Fig. 4b. The average isotopic abundance ratio is ~306 with a 2*STDEV ~13. This abundance ratio is significantly close to the previously reported value of 298.56 [6] and the ratio obtained by our GC-MS system (303 for a UHP grade Ar sample). Conclusions: Our study strongly evidenced that the benchtop UGA system is a valuable analytical tool for the detection of major LCROSS volatiles. The rapid scanning capability, the inexpensiveness of the whole system, and impressive detection sensitivity prove its worthiness as an essential device for advanced geochemical applications. Moreover, cross comparisons with the GC-MS provide important bridges into advanced curatorial efforts into the future. References: [1] Bickel, V.T., et al. (2021) Nat Commun 12, 5607. [2] Colaprete, A., et al. (2010) Science, 330, 463-468. [3] Glavin, D. P. et al. (2012) 2012 IEEE Aerospace Conference, 1-11. [4] Willett, C. D., et al. (2022) Geochimica et Cosmochimica Acta 329, 119-134. [5] Operation Manual and Programming Reference. (2018) Universal gas Analyzers, Stanford Research Systems. [6] Lee, J. Y., et al. (2006) Geochimica et Cosmochimica Acta 70, 4507–4512. Notes: (4 figures are attached with text as shown by the attached file)

Curation↗
NASA NTRSDate not supplied

Magma-Sediment Interaction Induced Alteration Mineralogy on Mars: Detectability and Analytical Method Comparison Using the Curtis Sandstone as A Terrestrial Analog

Basaltic magmatism is a ubiquitous feature of the Martian crust, and would have interacted with sediments and fluids through the geologic history of Mars to potentially produce higher temperature hydrothermal systems , and contact metamorphic rocks. On Earth, comparable hydrothermal systems represent habitable environments, which can be used as an analog for Mars. Nevertheless, evidence of aforementioned hydrothermal systems on Mars has remained elusive, despite the efforts of both orbital and in-situ analyses. Limited low grade metamorphic minerals typically indicative of hydrothermal systems (prehnite, zeolites, serpentine) have been detected in the Martian crust, though the detections are typically isolated occurrences, and do not necessarily indicate an in-place metamorphic sequence. It is possible that orbital spectroscopy alone is not capable of detecting such an alteration front, with higher resolution in-situ analyses being required to detect the changes in mineralogy and species of alteration minerals associated with magma-sediment interaction. To constrain this, we have investigated a terrestrial analog on the Colorado Plateau, USA, where a mafic dike intrudes a quartz areinite of the Jurassic Curtis Sandstone. The investigation was carried out using Mars relevant instruments: Visible to Near-Infrared (VNIR) spectroscopy analogous to orbital spectroscopy, and X-ray Diffraction (XRD) analogous to CheMin on Mars Sample Laboratory Curiosity. While quartz sandstones have not been, and are unlikely to be, detected on Mars, the relatively mineralogically uniform Curtis Sandstone serves as analog here as it avoids complications of multiple mineral systems or significant element exchange with the surrounding area.

J R Crandall↗
NASA NTRSDate not supplied

Cyber Resiliency and the Implementation of a Host-Based Intrusion Detection System in an Urban Air Mobility Environment

With the growth in urban air mobility systems and the increasing reliance on interconnected technologies, ensuring the security of these complex infrastructures has become critical. As cities evolve into smart urban centers, the vulnerability to cyber threats escalates, possibly endangering citizens’ safety and the efficiency of transportation networks. In response to these challenges, this paper presents a study on implementing a Host-Based Intrusion Detection System (HIDS) tailored explicitly to urban mobility environments’ unique demands. This study explores the design, development, and deployment of the proposed HIDS, focusing on its adaptability to monitor the hybrid nature of the urban mobility environment. Leveraging machine learning algorithms and anomaly detection techniques, the HIDS is equipped to continuously monitor and analyze the behavior of individual host systems, vehicles, and devices, thereby providing a proactive approach to threat detection. Implementing a HIDS is a pivotal strategy for enhancing cyber resiliency, as it gives an organization granular visibility into internal system activities, enables rapid detection and response to anomalous behavior and cyber threats, and fortifies the organization’s overall cybersecurity posture. In conclusion, this paper highlights the significance of host-based intrusion detection in urban mobility environments and underscores the necessity of tailored security solutions to safeguard against emerging cyber threats.

UAM↗
NASA NTRSDate not supplied

Cyber Resiliency and the Implementation of a Host-Based Intrusion Detection System in an Urban Air Mobility Environment

With the growth in Urban Air Mobility systems and the increasing reliance on interconnected technologies, ensuring the security of these complex components has become critical. As cities evolve into smart urban centers, the vulnerability to cyber threats escalates, possibly endangering citizens safety and the efficiency of transportation networks.In response to these challenges, this paper presents a study on the need for cyber resilient techniques within future air traffic environments. It will pay specific attention to the implementation of a Host-Based Intrusion Detection System (HIDS) utilizing Atomic OSSEC software, tailored specifically to a NASA simulation of an UrbanAirMobility environments’ unique demands. Further, this study seeks to outline the rational for NASA’s recommendation for a HIDS in such environments. It explores the design, development, and deployment of the proposed HIDS, focusing on its adaptability to monitor the hybrid nature of the Urban Air Mobility environment. Leveraging machine learning algorithms and anomaly detection techniques, the HIDS is equipped to continuously monitor and analyze the behavior of individual host systems, vehicles, and devices, thereby providing a proactive approach to threat detection. Implementing a HIDS is a pivotal strategy for enhancing cyber resiliency, as it gives an organization granular visibility into internal system activities, enables rapid detection and response to anomalous behavior and cyber threats, and fortifies the organizations overall cybersecurity posture. Finally, this study aims to provide recommendations and include learned takeaways that the Urban Air Mobility industry should consider. In brief, this paper highlights the significance of host-based intrusion detection in UrbanAirMobility environments and underscores the necessity of tailored security solutions to safeguard against emerging cyber threats.

UAM↗
NASA NTRS2024

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗
NASA NTRS2026

Timing the Flames: Geostationary Satellite Detection of Diurnally Shifting Stubble Burning in Northwestern India

Post-monsoon open-field stubble burning in northwestern (NW) India—a key agricultural region known as the “breadbasket”—is a longstanding practice used to clear fields. Satellite observations spanning over two decades have revealed significant upward trends in crop production, vegetative greenness, and the frequency of post-harvest fires, with this last contributing to hazardous air quality during the peak burning season (mid-October to mid-November). Since 2022, thermal anomaly data from Aqua-MODIS and SNPP-VIIRS sensors have shown a sharp decline in reported fire events—an observation that contrasts starkly with the concurrent rise in regional aerosol loading detected from space. This apparent discrepancy became particularly pronounced in 2024–2025, prompting a closer examination using high-temporal-resolution imagery from the Advanced Meteorological Imager (AMI) on the geostationary satellite GEO-KOMPSAT-2A. These observations revealed a clear spike in fire-related signals occurring around and after 4:00 p.m. local time, i.e., outside the typical noon to 2:00 p.m. detection window of the MODIS and VIIRS. A fire detection algorithm exploiting the fire-sensitive shortwave-infrared 3.8 μm signal and its contrast to 11.2 μm infrared observations is designed to adopt AMI observations and applied to its multi-year observations (2019–2025). The resulting fire dataset unambiguously shows a gradual shift in stubble burning activity toward the late afternoon hours beginning in 2022 which is underreported by polar-orbiting satellites. The orbital drift of NASA’s MODIS sensor on the Aqua platform allows detection of some of the gradually shifting fires during afternoon hours, but the MODIS still misses a large number of fires occurring around and after 4 p.m. The AMI’s relatively coarse spatial resolution (~4 km), a consequence of its slant viewing geometry over NW India, imposes inherent limitations on quantifying the full extent of fire occurrences. The operational air quality forecasting models currently assimilate satellite fire detections predominantly captured during early afternoon overpasses of the MODIS and VIIRS. The temporal shift in fire activity complicates such forecast, leading to a substantial underestimation of emissions. Intense stubble burning and the resulting air pollution highlight the need for effective crop residue management practices for mitigating the frequency of open biomass burning and thereby reducing episodic degradation of air quality and its associated public health and economic impacts.

post-monsoon stubble burning; northwestern India;↗
DOE OSTI2014

Design and Implementation of Real-Time Off-Grid Detection Tool Based on FNET/GridEye

Real-time situational awareness tools are of critical importance to power system operators, especially during emergencies. The availability of electric power has become a linchpin of most post disaster response efforts as it is the primary dependency for public and private sector services, as well as individuals. Knowledge of the scope and extent of facilities impacted, as well as the duration of their dependence on backup power, enables emergency response officials to plan for contingencies and provide better overall response. Based on real-time data acquired by Frequency Disturbance Recorders (FDRs) deployed in the North American power grid, a real-time detection method is proposed. This method monitors critical electrical loads and detects the transition of these loads from an on-grid state, where the loads are fed by the power grid to an off-grid state, where the loads are fed by an Uninterrupted Power Supply (UPS) or a backup generation system. The details of the proposed detection algorithm are presented, and some case studies and off-grid detection scenarios are also provided to verify the effectiveness and robustness. Meanwhile, the algorithm has already been implemented based on the Grid Solutions Framework (GSF) and has effectively detected several off-grid situations.

Guo, Jiahui↗
DOE OSTI2014

Methodology for fast detection of false sharing in threaded scientific codes

A profiling tool identifies a code region with a false sharing potential. A static analysis tool classifies variables and arrays in the identified code region. A mapping detection library correlates memory access instructions in the identified code region with variables and arrays in the identified code region while a processor is running the identified code region. The mapping detection library identifies one or more instructions at risk, in the identified code region, which are subject to an analysis by a false sharing detection library. A false sharing detection library performs a run-time analysis of the one or more instructions at risk while the processor is re-running the identified code region. The false sharing detection library determines, based on the performed run-time analysis, whether two different portions of the cache memory line are accessed by the generated binary code.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Transistor-based particle detection systems and methods

Transistor-based particle detection systems and methods may be configured to detect charged and non-charged particles. Such systems may include a supporting structure contacting a gate of a transistor and separating the gate from a dielectric of the transistor, and the transistor may have a near pull-in bias and a sub-threshold region bias to facilitate particle detection. The transistor may be configured to change current flow through the transistor in response to a change in stiffness of the gate caused by securing of a particle to the gate, and the transistor-based particle detection system may configured to detect the non-charged particle at least from the change in current flow.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Kaluza-Klein Dark Matter: Direct Detection vis-a-vis LHC (2013 update)

We present updated results on the complementarity between high-energy colliders and dark matter direct detection experiments in the context of Universal Extra Dimensions (UED). In models with relatively small mass splittings between the dark matter candidate and the rest of the (colored) spectrum, the collider sensitivity is diminished, but direct detection rates are enhanced. UED provide a natural framework to study such mass degeneracies. We discuss the detection prospects for the KK photon $\gamma_1$ and the KK $Z$-boson $Z_1$, combining the expected LHC reach with cosmological constraints from WMAP/Planck, and the sensitivity of current or planned direct detection experiments. Allowing for general mass splittings, neither colliders, nor direct detection experiments by themselves can explore all of the relevant KK dark matter parameter space. Nevertheless, they probe different parameter space regions, and the combination of the two types of constraints can be quite powerful.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗