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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Small target detection for search and rescue operations using distributed deep learning and synthetic data generation

It is important to find the target as soon as possible for search and rescue operations. Surveillance camera systems and unmanned aerial vehicles (UAVs) are used to support search and rescue. Automatic object detection is important because a person cannot monitor multiple surveillance screens simultaneously for 24 hours. Also, the object is often too small to be recognized by the human eye on the surveillance screen. This study used UAVs around the Port of Houston and fixed surveillance cameras to build an automatic target detection system that supports the US Coast Guard (USCG) to help find targets (e.g., person overboard). We combined image segmentation, enhancement, and convolution neural networks to reduce detection time to detect small targets. We compared the performance between the auto-detection system and the human eye. Our system detected the target within 8 seconds, but the human eye detected the target within 25 seconds. Our systems also used synthetic data generation and data augmentation techniques to improve target detection accuracy. This solution may help the search and rescue operations of the first responders in a timely manner.

Chow, Edward↗
NASA NTRS2020

Texas Spectroscopic Search for Lyα Emission at the End of Reionization. III. The Lyα Equivalent-width Distribution and Ionized Structures at z > 7

Lyα emission from galaxies can be utilized to characterize the ionization state in the intergalactic medium (IGM). We report our search for Lyα emission at z > 7 using a comprehensive Keck/MOSFIRE near-infrared spectroscopic data set, as part of the Texas Spectroscopic Search for Lyα Emission at the End of Reionization Survey. We analyze data from 10 nights of MOSFIRE observations which together target 72 high-z candidate galaxies in the GOODS-N field, all with deep exposure times of 4.5–19 hr. Utilizing an improved automated emission-line search, we report 10 Lyα emission lines detected (>4σ) at z > 7, significantly increasing the spectroscopically confirmed sample. Our sample includes large equivalent-width (EW) Lyα emitters (>50 Å), and additional tentative Lyα emission lines detected at 3σ–4σ from five additional galaxies. We constrain the Lyα EW distribution at z ~ 7.6, finding a significant drop from z ≲ 6, suggesting an increasing fraction of neutral hydrogen (H I) in the IGM in this epoch. We estimate the Lyα transmission through the IGM (=EW(z)~7.6/EW(z~2–6)) and infer an IGM H I fraction (X(HI)) of 49 (+19,-19)% at z ~ 7.6, which is lower in modest tension (>1σ) with recent measurements at z ~ 7.6. The spatial distribution of the detected Lyα emitters implies the presence of a potential highly ionized region at z ~ 7.55, which hosts four Lyα emitters within a ∼40 cMpc spatial separation. The prominence of this ionized region in our data set could explain our lower inferred value of X(HI), though our analysis is also sensitive to the chosen reference Lyα EW distribution values and reionization models.

Intae Jung↗
NASA NTRS2019

Search for Transient Gravitational-wave Signals Associated with Magnetar Bursts during Advanced LIGO's Second Observing Run

We present the results of a search for short- and intermediate-duration gravitational-wave signals from four magnetar bursts in Advanced LIGO's second observing run. We find no evidence of a signal and set upper bounds on the root sum squared of the total dimensionless strain ( h rss ) from incoming intermediate-duration gravitational waves ranging from 1.1 × 10 −22 at 150 Hz to 4.4 × 10 −22 at 1550 Hz at 50% detection efficiency. From the known distance to the magnetar SGR 1806–20 (8.7 kpc), we can place upper bounds on the isotropic gravitational-wave energy of 3.4 × 10 44 erg at 150 Hz assuming optimal orientation. This represents an improvement of about a factor of 10 in strain sensitivity from the previous search for such signals, conducted during initial LIGO's sixth science run. The short-duration search yielded upper limits of 2.1 × 10 44 erg for short white noise bursts, and 2.3 × 10 47 erg for 100 ms long ringdowns at 1500 Hz, both at 50% detection efficiency.

B. P. Abbott↗
NASA NTRS2019

Search for Intermediate Mass Black Hole Binaries in the First and Second Observing Runs of the Advanced LIGO and VIRGO Network

Gravitational-wave astronomy has been firmly established with the detection of gravitational waves from the merger of ten stellar-mass binary black holes and a neutron star binary. This paper reports on the all-sky search for gravitational waves from intermediate mass black hole binaries in the first and second observing runs of the Advanced LIGO and Virgo network. The search uses three independent algorithms: two based on matched filtering of the data with waveform templates of gravitational-wave signals from compact binaries, and a third, model-independent algorithm that employs no signal model for the incoming signal. No intermediate mass black hole binary event is detected in this search. Consequently, we place upper limits on the merger rate density for a family of intermediate mass black hole binaries. In particular, we choose sources with total masses 𝑀=𝑚1+𝑚2∈[120,800] 𝑀⊙ and mass ratios 𝑞=𝑚2/𝑚1∈[0.1,1.0]. For the first time, this calculation is done using numerical relativity waveforms (which include higher modes) as models of the real emitted signal. We place a most stringent upper limit of 0.20 Gpc−3 yr−1 (in comoving units at the 90% confidence level) for equal-mass binaries with individual masses 𝑚1,2=100 𝑀⊙ and dimensionless spins 𝜒1,2=0.8 aligned with the orbital angular momentum of the binary. This improves by a factor of ∼5 that reported after Advanced LIGO’s first observing run.

B. P. Abbott↗
NASA NTRS2019

Search for Subsolar Mass Ultracompact Binaries in Advanced LIGO’s Second Observing Run

We present a search for subsolar mass ultracompact objects in data obtained during Advanced LIGO’s second observing run. In contrast to a previous search of Advanced LIGO data from the first observing run, this search includes the effects of component spin on the gravitational waveform. We identify no viable gravitational-wave candidates consistent with subsolar mass ultracompact binaries with at least one component between 0.2 𝑀 ⊙ –1.0 𝑀 ⊙ . We use the null result to constrain the binary merger rate of (0.2 𝑀 ⊙ , 0.2 𝑀 ⊙ ) binaries to be less than 3.7×10 5 Gpc −3 yr −1 and the binary merger rate of (1.0 𝑀 ⊙ , 1.0 𝑀 ⊙ ) binaries to be less than 5.2×10 3 Gpc −3 yr −1 . Subsolar mass ultracompact objects are not expected to form via known stellar evolution channels, though it has been suggested that primordial density fluctuations or particle dark matter with cooling mechanisms and/or nuclear interactions could form black holes with subsolar masses. Assuming a particular primordial black hole (PBH) formation model, we constrain a population of merging 0.2 𝑀 ⊙ black holes to account for less than 16% of the dark matter density and a population of merging 1.0 𝑀 ⊙ black holes to account for less than 2% of the dark matter density. We discuss how constraints on the merger rate and dark matter fraction may be extended to arbitrary black hole population models that predict subsolar mass binaries.

B. P. Abbott↗
NASA NTRSDate not supplied

Improving Earth Science Dataset Search with Publication

The NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) archives a large number of Earth observational datasets. Thousands of the publications are created each year based on these datasets. The content of these publications can be used for discovery of the datasets based on the characteristics of applicational research. We leverage the content of these publications to retrieve the information about phenomena and domains where measurements from the datasets were utilized through linking these publications and dataset in Knowledge Graph. We retrieve phenomena and domain information using SWEET ontology and produce the set of keywords that are linked to the datasets. Further, we evaluate this link strength according to the frequency of dataset usage in the papers mentioning these keywords. We demonstrate how this linkage can improve dataset search by comparing the search results obtained from Common Metadata Repository (CMR) search and the publications based data.

Kristina Stoyanova↗
NASA NTRS2021

Search for Gravitational Waves Associated with Gamma-Ray Bursts Detected by Fermi and Swift during the LIGO–Virgo Run O3a

We search for gravitational-wave transients associated with gamma-ray bursts (GRBs) detected by the Fermi and Swift satellites during the first part of the third observing run of Advanced LIGO and Advanced Virgo (2019 April 1 15:00 UTC–2019 October 1 15:00 UTC). A total of 105 GRBs were analyzed using a search for generic gravitational-wave transients; 32 GRBs were analyzed with a search that specifically targets neutron star binary mergers as short GRB progenitors. We find no significant evidence for gravitational-wave signals associated with the GRBs that we followed up, nor for a population of unidentified subthreshold signals. We consider several source types and signal morphologies, and report for these lower bounds on the distance to each GRB.

R. Abbott↗
NASA NTRSDate not supplied

Semantic Search with Sentence-BERT for Design Information Retrieval

Managing and referencing design knowledge is a critical activity in the design process. However, reliably retrieving useful knowledge can be a frustrating experience for users of knowledge management systems due to inherent limitations of standard keyword-based searches. In this research, we consider the task of retrieving relevant lessons learned from the NASA Lessons Learned Information System (LLIS). To this end, we apply a state-of-the-art natural language processing (NLP) technique for information retrieval (IR): semantic search with sentence-BERT, which is a modification of a Bidirectional Encoder Representations from Transformers (BERT) model that uses siamese and triplet network architectures to obtain semantically meaningful sentence embeddings. While the pre-trained sBERT model performs well out-of-the-box, we further fine-tune the model on data from the LLIS so that it learns on design engineering-relevant vocabulary. We quantify the improvement in query results using both standard sBERT and fine-tuned sBERT over a keyword search. Our use case throughout the paper is to use queries related to specific requirements from a NASA project. Fine tuning the sBERT model on LLIS data yields a mean average precision (MAP) of 0.807 on queries based on information needs from a real NASA project. Results indicate that applying state-of-the-art natural language processing techniques, especially when finetuned using engineering data, to design information retrieval tasks shows significant promise in modernizing design knowledge management systems.

Hannah S. Walsh↗
NASA NTRS2021

Using GPUs and the Parameterization Method for Rapid Search and Refinement of Connections between Tori in Periodically Perturbed Planar Circular Restricted 3-Body Problems

When the planar circular restricted 3-body problem is periodically perturbed, most unstable periodic orbits become invariant tori. However, 2D Poincare ́ sections no longer work to find their manifolds’ intersections; new methods are needed. In this study, we first review a method of restricting the intersection search to only certain manifold subsets. We then implement this search using Julia and OpenCL, representing the manifolds as triangular meshes and gaining a 30x speedup using GPUs. We finally show how to use manifold parametrizations to refine the ap- proximate connections found in the mesh search. We demonstrate the tools on the planar elliptic RTBP.

de la Llave, Rafael↗
NASA NTRSDate not supplied

The Search for Extant Life on Mars: A Human Exploration Objective

A search for evidence of extant life on Mars should be conducted prior to and as part of human exploration missions. Potentially habitable environments for modern life occur on Mars. Despite a vigorous campaign of exploration of the surface over the last 3 decades, no mission has attempted to search for signatures of extant life since the Viking landers in 1976. Finding an example of extant life beyond Earth would be one of the greatest scientific discoveries of all time. This is especially important because (once discovered) the biochemistry and metabolism of the life form can be studied. Earth and Mars exchange materials over geologic time because impacts eject rock and crustal materials into space that are eventually deposited on other planets and moons [1]. Therefore, Earth and Mars could share life with a common origin and similar biochemistry; if this is the case, life on Mars likely experienced billions of years of evolution in isolation from Earth. Alternatively, Mars may host a distinct genesis of life which could be evident from its different biochemistry. Either discovery would change our understanding of life in the solar system and beyond. The Mars 2020/Perseverance sample collection mission is not optimized for finding extant life because the site for sample collection, Jezero Crater, was chosen for its ancient habitability and likelihood to host fossil evidence of life. Furthermore, the samples collected will not be returned for at least a decade. Within that period, technology development for human exploration will likely be underway and it is possible that humans will land on Mars without an updated knowledge of extant life on Mars, which may pose a risk both to those mission crews and to Earth when they return. Thus, it is important to perform a search for extant life on Mars prior to humans landing at a site where life may persist. Salts and shallow ground ice are particularly important environments to evaluate for extant life prior to human missions because they may be encountered and interacted with by human crews.

C.R. Stoker↗
NASA NTRSDate not supplied

Utilizing Google Scholar as a Bibliographic Resource for Publications Search

This study focuses on the automated search for publication citations for the Earth Observing System Data and Information System (EOSDIS) datasets. The research investigates the feasibility of using automated search methods to gather published works from various bibliometric databases. A comparison is presented, highlighting the differences in citation counts obtained from Google Scholar compared to established bibliographic databases. The study also introduces a methodology and an open-source tool for getting publication citations from Google Scholar, utilizing dataset DOIs and keyword searches. The findings contribute to understanding the reliability and effectiveness of Google Scholar as a source for dataset citation retrieval and provide researchers with a valuable resource for obtaining comprehensive citation data.

Infometrics↗
NASA NTRS2021

Monte Carlo Tree Search Methods for the Earth-Observing Satellite Scheduling Problem

This work explores on-board planning for the single spacecraft, multiple ground station Earth-observing satellite scheduling problem through artificial neural network function approximation of state–action value estimates generated by Monte Carlo tree search (MCTS). An extensive hyperparameter search is conducted for MCTS on the basis of performance, safety, and downlink opportunity utilization to determine the best hyperparameter combination for data generation. A hyperparameter search is also conducted on neural network architectures. The learned behavior of each network is explored, and each network architecture’s robustness to orbits and epochs outside of the training distributions is investigated. Furthermore, each algorithm is compared with a genetic algorithm, which serves to provide a baseline for optimality. MCTS is shown to compute near-optimal solutions in comparison to the genetic algorithm. The state–action value networks are shown to match or exceed the performance of MCTS in six orders of magnitude less execution time, showing promise for execution on board spacecraft.

Adam P. Herrmann↗
NASA NTRS2024

Future of the Search for Life: Workshop Report

The 2-week, virtual Future of the Search for Life science and engineering workshop brought together more than 100 scientists, engineers, and technologists in March and April 2022 to provide their expert opinion on the interconnections between life-detection science and technology. Participants identified the advances in measurement and sampling technologies they believed to be necessary to perform in situ searches for life elsewhere in our Solar System, 20 years or more in the future. Among suggested measurements for these searches, those pertaining to three potential indicators of life termed “dynamic disequilibrium,” “catalysis,” and “informational polymers” were identified as particularly promising avenues for further exploration. For these three indicators, small breakout groups of participants identified measurement needs and knowledge gaps, along with corresponding constraints on sample handling (acquisition and processing) approaches for a variety of environments on Enceladus, Europa, Mars, and Titan. Despite the diversity of these environments, sample processing approaches all tend to be more complex than those that have been implemented on missions or envisioned for mission concepts to date. The approaches considered by workshop breakout groups progress from nondestructive to destructive measurement techniques, and most involve the need for fluid (especially liquid) sample processing. Sample processing needs were identified as technology gaps. These gaps include technology and associated sampling strategies that allow the preservation of the thermal, mechanical, and chemical integrity of the samples upon acquisition; and to optimize the sample information obtained by operating suites of instruments on common samples. Crucially, the interplay between science-driven life-detection strategies and their technological implementation highlights the need for an unprecedented level of payload integration and extensive collaboration between scientists and engineers, starting from concept formulation through mission deployment of life-detection instruments and sample processing systems.

Marc Neveu↗
NASA NTRSDate not supplied

Monte Carlo Tree Search for Integrated Planning, Learning, and Execution in Nondeterministic Python

We present a novel use of Monte Carlo Tree Search (MCTS),adapted to explore a search space produced by the choice points embedded in Python code. The choice points are non-deterministic assignment statements and subroutine calls. We present MCTS extensions required for doing tree search in this context which includes control constructs like hierarchical decomposition (subroutine calls), iterative while loops and conditional statements. We demonstrate how the system works in a simulated rideshare scenario in an urban setting, and present preliminary experiments as a proof of concept.

Automatic planning↗
NASA NTRS2024

Search Technology for Optimal Rescue Missions (STORM)

Natural disasters, such as earthquakes, hurricanes, and wildfires are responsible for the deaths of 60,000 to 90,000 people per year. Today, search and rescue (SAR) operations heavily rely on humans to find and deliver life-saving supplies to those affected by these disasters. However, these operations have limits in visibility, navigation, communication systems, and data availability in the area affected, as well as endangering the SAR personnel. Search Technology for Optimal Rescue Missions (STORM) discusses a new system for SAR teams using autonomous drones able to find and deliver supplies to people, without risking more lives in the process. The concept includes the use of two drone types, STORM Search and STORM Rescue, which will survey and locate survivors and be able to drop equipment to the survivors identified, respectively. These two types of drones were optimized in drone design and durability (such as the use of dihedral wings and a toroidal propeller), detection and navigation systems (sturdy thermal and Light Detection and Ranging [LiDAR] cameras), automation and system design (Machine Learning and Computer Vision), server-drone communication (Meshnets), weight, and cost. Once implemented, the STORM concept is expected to improve, ease, and speed up SAR operations, and most important of all, rescue lives that would have never been currently possible to find.

Astha Ingole↗
DOE OSTI2020

A Search for Neutron-Antineutron Oscillation in the NOvA Experiment

This dissertation presents the search for neutron-antineutron oscillation using the data collected in the Far Detector of the NOvA experiment. Searching for neutron anti-neutron oscillation is becoming an active research direction that promises immense values for the field of particle physics and cosmology. Experimental observation of the phenomenon would offer the possibility of new physics associated with anomalous $B$ and $B-L$ violating processes. This work is opening with a general introduction of the neutron-antineutron oscillation, its theoretical motivations, and recent empirical results related to the topic. The data-driven trigger that allows the NOvA experiment to collect the signal-like events constitutes a significant work of this study and will be described in detail. Following the discussion of the trigger, the thesis focuses on the development of a selection method to further classify collected events into the signal candidates and the background. This search chooses an analysis approach in which the real data is partially unblinded to assist the development and evaluation of the event selection. Because this is an ongoing work and essential aspects of the analysis have not been all finalized, this thesis closes out with a sensitivity study. By analyzing the data from 4 months of Far Detector exposure, a 90\% C.L. sensitivity limit of $4\times10^{30}$\,years is placed on the oscillation lifetime of bound neutrons inside the $^{12}$C targets. This limit is equivalent to a sensitivity of $0.57\times10^{8}$\,s placed on the oscillation lifetime of free neutrons. The NOvA's sensitivity is a factor of 5 below the most stringent limit of $2.7\times10^8$\,s set by the Super-Kamiokande experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Search for Higgs Portal Scalars and Heavy Neutral Leptons Decaying in the MicroBooNE Detector

This thesis presents a search for Higgs Portal Scalars (HPS) and Heavy Neutral Leptons (HNL) decaying in the MicroBooNE liquid argon time projection chamber (LArTPC). The measurement was performed using data collected in-time with the Neutrino at the Main Injector (NuMI) beam with a total exposure corresponding to $7.01 \times 10^{20}$ protons on target. Mono-energetic HPS and HNL would be produced from kaons decaying at rest in the NuMI hadron absorber, before travelling ${\sim}100$~m to the MicroBooNE detector where they decay. A single selection and search strategy is used to target decays of HPS to $\mu\mu$ pairs and HNL to $\mu\pi$ pairs. The results are expressed as limits, at the $90\%$ confidence level, on the mixing angles that control the rates of production and decay for each new particle. For the HNL model, upper limits are set on the mixing parameter $\mumix$ in the range [$12.9 \times 10^{-8}$, $0.54 \times 10^{-8}$] for HNL with masses in the region $246$--$385$~MeV. % This represents an order of magnitude increase in sensitivity to the previous MicroBooNE HNL result. For the HPS model, limits on the scalar-Higgs mixing angle $\theta^2$ are set, excluding a region with a lower boundary between [$31.3 \times10^{-9}$, $1.09 \times 10^{-9}$] and an upper boundary between [$2.50 \times 10^{-5}$, $5.05 \times 10^{-9}$] for scalars with a mass of $212$--$275$ MeV. These results set the first constraints in this region of parameter space from a dedicated experimental search for HPS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Search for Higgs Portal Scalars and Heavy Neutral Leptons Decaying in the MicroBooNE Detector

This thesis presents a search for Higgs Portal Scalars (HPS) and Heavy Neutral Leptons (HNL) decaying in the MicroBooNE liquid argon time projection chamber (LArTPC). The measurement was performed using data collected in-time with the Neutrino at the Main Injector (NuMI) beam with a total exposure corresponding to 7.01x10^20 protons on target. Mono-energetic HPS and HNL would be produced from kaons decaying at rest in the NuMI hadron absorber, before travelling ~100 m to the MicroBooNE detector where they decay. A single selection and search strategy is used to target decays of HPS to muon-muon pairs and HNL to muon-pion pairs. The results are expressed as limits, at the 90% confidence level, on the mixing angles that control the rates of production and decay for each new particle. For the HNL model, upper limits are set on the mixing parameter |U\mu4|^2 in the range [12.9 x 10^-8, 0.54 x 10^-8] for HNL with masses in the region 246 - 385 MeV. For the HPS model, limits on the scalar-Higgs mixing angle \theta^2 are set, excluding a region with a lower boundary between [31.3 x 10^-9, 1.09 x 10^-9] and an upper boundary between [2.50 x 10^-5, 5.05 x 10^-9] for scalars with a mass of 212-275 MeV. These results set the first constraints in this region of parameter space from a dedicated experimental search for HPS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗