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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 271 records · Page 15

A Search for Successful and Choked Jets in Nearby Broad-lined Type Ic Supernovae

The observational link between long gamma-ray bursts (GRBs) and broad-lined stripped-envelope core-collapse supernovae (SNe Ic-BL) is well established. Significant progress has been made in constraining what fraction of SNe Ic-BL may power high- or low-luminosity GRBs when viewed at small off-axis angles. However, the GRB–SN connection still lacks a complete understanding in the broader context of massive-star evolution and explosion physics. Models predict a continuum of outcomes for the fastest ejecta, from choked to ultrarelativistic jets, and observations from radio to X-rays are key to probing these scenarios across a range of viewing angles and velocities. Here, we present results from a coordinated radio-to-X-ray campaign targeting nearby (z ≲ 0.1) SNe Ic-BL designed to explore this diversity. With eight new radio-monitored events and updated data for one previously observed SN, we further tighten constraints on the fraction of SNe Ic-BL as relativistic as SN 1998bw (GRB 980425). We identify SN 2024rjw as a new radio-loud event likely powered by strong interaction with circumstellar material, and add evidence supporting a similar interpretation for SN 2020jqm. We also establish new limits on the properties of radio-emitting ejecta with velocities consistent with cocoons from choked jets, highlighting SN 2022xxf as a promising cocoon-dominated candidate. These results refine our understanding of the continuum linking ordinary SNe Ic-BL, engine-driven explosions, and GRBs, and contribute to building a sample that will inform future multimessenger searches for electromagnetic counterparts to high-energy neutrinos.

O’Dwyer, Tanner [Johns Hopkins Univ., Baltimore, M↗

The StarLight Space Interferometer

Two papers describe the StarLight space interferometer a Michelson interferometer that would be implemented by two spacecraft flying in formation. The StarLight formation flying interferometer project has been testing and demonstrating engineering concepts for a new generation of space interferometers that would be employed in a search for extrasolar planets and in astrophysical investigations. As described in the papers, the original StarLight concept called for three spacecraft, and the main innovation embodied is a modification that makes it possible to reduce complexity by eliminating the third spacecraft. The main features of the modification are (1) introduction of an optical delay line on one spacecraft and (2) controlling the flying formation such that the two spacecraft are located at two points along a specified parabola so as to define the required baseline of specified length (which could be varied up to 125 m) perpendicular to the axis of the parabola. One of the papers presents a detailed description of the optical layout and discusses computational modeling of the performance; the other paper presents an overview of the requirements for operation and design, the overall architecture, and subsystems.

Folkner, William↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗

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↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Diagnosis↗

A Flux-Tunable cavity for Dark matter detection

Developing a dark matter detector with wide mass tunability is an immensely desirable property, yet it is challenging due to maintaining strong sensitivity. Resonant cavities for dark matter detection have traditionally employed mechanical tuning, moving parts around to change electromagnetic boundary conditions. However, these cavities have proven challenging to operate in sub-Kelvin cryogenic environments due to differential thermal contraction, low heat capacities, and low thermal conductivities. Instead, we develop an electronically tunable cavity architecture by coupling a superconducting 3D microwave cavity with a DC flux tunable SQUID. With a flux delivery system engineered to maintain high coherence in the cavity, we perform a hidden-photon dark matter search below the quantum-limited threshold. A microwave photon counting technique is employed through repeated quantum non-demolition measurements using a transmon qubit. With this device, we perform a hidden-photon search and constrain the kinetic mixing angle to ${\varepsilon}< 8.2\times 10^{-15}$ in a tunable band from 5.672 GHz to 5.694 GHz. By coupling multimode tunable cavities to the transmon, wider hidden-photon searching ranges are possible.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Design synthesis of a boron/epoxy reinforced metal shear web.

An advanced composite shear web design concept has been developed for the Space Shuttle Orbiter main engine thrust beam structure. Various web concepts were synthesized by a computer-aided adaptive random search procedure. A practical concept is identified having a titanium-clad, boron/epoxy plate with vertical boron/epoxy reinforced stiffeners. Baseline composite and titanium shear resistant designs are compared; the composite concept is 28% lighter than the titanium web. Element test results show the metal cladding effectively reinforces critical composite load transfer and fastener hole areas making the composite web concept practical for other shear structure applications.-

Laakso, J. H.↗

Rocket ascent G-limited moment-balanced optimization program (RAGMOP)

This document describes the RAGMOP (Rocket Ascent G-limited Momentbalanced Optimization Program) computer program for parametric ascent trajectory optimization. RAGMOP computes optimum polynomial-form attitude control histories, launch azimuth, engine burn-time, and gross liftoff weight for space shuttle type vehicles using a search-accelerated, gradient projection parameter optimization technique. The trajectory model available in RAGMOP includes a rotating oblate earth model, the option of input wind tables, discrete and/or continuous throttling for the purposes of limiting the thrust acceleration and/or the maximum dynamic pressure, limitation of the structural load indicators (the product of dynamic pressure with angle-of-attack and sideslip angle), and a wide selection of intermediate and terminal equality constraints.

Lyons, J. T.↗

Evaluation of a metal shear web selectively reinforced with filamentary composites for space shuttle application. Phase 1 summary report: Shear web design development

An advanced composite shear web design concept was developed for the Space Shuttle orbiter main engine thrust beam structure. Various web concepts were synthesized by a computer-aided adaptive random search procedure. A practical concept is identified having a titanium-clad + or - 45 deg boron/epoxy web plate with vertical boron/epoxy reinforced aluminum stiffeners. The boron-epoxy laminate contributes to the strength and stiffness efficiency of the basic web section. The titanium-cladding functions to protect the polymeric laminate parts from damaging environments and is chem-milled to provide reinforcement in selected areas. Detailed design drawings are presented for both boron/epoxy reinforced and all-metal shear webs. The weight saving offered is 24% relative to all-metal construction at an attractive cost per pound of weight saved, based on the detailed designs. Small scale element tests substantiate the boron/epoxy reinforced design details in critical areas. The results show that the titanium-cladding reliably reinforces the web laminate in critical edge load transfer and stiffener fastener hole areas.

Laakso, J. H.↗

Multiwavelength Blazar Studies

The present report concerns the following projects 'High energy emission from hot accretion disks from active galactic nuclei'; 'OSSE spectral timing and monitoring observations of Cygnus X- 1'; 'OSSE observations of blazars'; and 'Search for correlated time variations of bright EGRET blazars'. The most favored model for the central engine inAGNs is the supermassive black hole hypothesis (Rees 1978). The observed luminosities range from approx. 10 logical and 44-45 erg /s for objects such as Mk 421 and Seyferts to as much as approx. 10logical and 47 for powerful QSOs such as 3C 273 and 3C 279, a large fraction of the observed bolometric luminosity being, in all likelihood, beamed. As such, these objects are strong X-ray emitters (cf. Makino et al. 1987) and often undergo gamma-ray flaring detected at the EGRET range (Hartman et al. 1992) and in the case of one of two known nearby BL Lacs, Mk 421, at TeV energies as well (Punch et al. 1992, Macomb et al. 1995). Previous campaigns emphasizing radio through X-ray and even gamma-ray observations have generally found that the multiwavelength spectrum is adequately fit by a standard synchrotron self-Compton (SSC-cf. Jones et al. 1974) model of a relativistic jet (e.g. Makino et al. 1987 and Macomb et al. 1995 for the BL Lac object Mk 421) or inhomogeneous relativistic jet (Mufson et al 1990). It also was examined the gamma-gamma transperency constraints inblazars.

Kafatos, Menas↗

Using Web 2.0 Techniques in NASA's Ares Engineering Operations Network (AEON) Environment - First Impressions

The Mission Operations Laboratory (MOL) at Marshall Space Flight Center (MSFC) is responsible for Engineering Support capability for NASA s Ares rocket development and operations. In pursuit of this, MOL is building the Ares Engineering and Operations Network (AEON), a web-based portal to support and simplify two critical activities: Access and analyze Ares manufacturing, test, and flight performance data, with access to Shuttle data for comparison Establish and maintain collaborative communities within the Ares teams/subteams and with other projects, e.g., Space Shuttle, International Space Station (ISS). AEON seeks to provide a seamless interface to a) locally developed engineering applications and b) a Commercial-Off-The-Shelf (COTS) collaborative environment that includes Web 2.0 capabilities, e.g., blogging, wikis, and social networking. This paper discusses how Web 2.0 might be applied to the typically conservative engineering support arena, based on feedback from Integration, Verification, and Validation (IV&V) testing and on searching for their use in similar environments.

Scott, David W.↗

The Science Discovery Engine: Connecting Heterogeneous Scientific Data and Information

Transformative science often occurs at the boundaries of different disciplines. Making interdisciplinary science data, software and documentation discoverable and accessible is essential to enabling transformative science. However, connecting this diverse and heterogeneous information is often a challenge due to several factors including the dispersed and sometimes isolated nature of data and the semantic differences between topical areas. NASA’s Science Discovery Engine (SDE) has developed several approaches to tackling these challenges. The SDE is a unified, insightful search experience that enables discovery of NASA’s open science data across five topical areas: astrophysics, biological and physical sciences, Earth science, heliophysics and planetary science. In this presentation, we will discuss our efforts to develop a systematic scientific curation workflow to integrate diverse content into a single search environment. We will also share lessons learned from our work to create a metadata crosswalk across the five disciplines.

Kaylin Bugbee↗

GRIP: Constraint-based Explanation of Missing Answers for Graph Queries

Abstract: A useful feature in graph query engines is to clarify “Why certain entities (nodes, attribute values or edges) are missing” in query answers. This task is even more challenging when the relevant data is already missing in the underlying data source. Missing data, on the other hand, can be inferred by enforcing data constraints for graphs. We demonstrate GRIP, a system that exploits data constraints to clarify missing answers for graph queries. (1) Constraint-based ex- planation. Given a desired yet missing entity in the query answer, GRIP ensures to generate finite and minimal sequences of data con- strains (an “explanation”) that should be consecutively enforced to ?? to ensure its occurrence for the same query. (2) Answering “why” and“how” questions. Users can query GRIP with both“Why”(“Why” the element is missing) and “How” questions (“How” to refine the graph to include the missing answer). GRIP engine supports run- time generation of explanations by incrementally maintaining a set of bi-directional search trees. (3) Interactive exploration. GRIP provides a user-friendly GUI to support interactive ad visual exploration of explanations, including both automated generation and step-by-step inspection of graph manipulations.

graphs↗

Scintillating Bubble Chambers for Rare Event Searches

The Scintillating Bubble Chamber (SBC) collaboration is developing liquid-noble bubble chambers for the detection of sub-keV nuclear recoils. These detectors benefit from the electron recoil rejection inherent in moderately-superheated bubble chambers with the addition of energy reconstruction provided from the scintillation signal. The ability to measure low-energy nuclear recoils allows the search for GeV-scale dark matter and the measurement of coherent elastic neutrino-nucleus scattering on argon from MeV-scale reactor antineutrinos. The first physics-scale detector, SBC-LAr10, is in the commissioning phase at Fermilab, where extensive engineering and calibration studies will be performed. In parallel, a functionally identical low-background version, SBC-SNOLAB, is being built for a dark matter search underground at SNOLAB. SBC-SNOLAB, with a 10 kg-yr exposure, will have sensitivity to a dark matter–nucleon cross section of 2×10 –42 cm 2 at 1 GeV/c 2 dark matter mass, and future detectors could reach the boundary of the argon neutrino fog with a tonne-yr exposure. In addition, the deployment of an SBC detector at a nuclear reactor could enable neutrino physics investigations including measurements of the weak mixing angle and searches for sterile neutrinos, the neutrino magnetic moment, and the light Z’ gauge boson.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA Tech Briefs, March 2007

Topics include: Advanced Systems for Monitoring Underwater Sounds; Wireless Data-Acquisition System for Testing Rocket Engines; Processing Raw HST Data With Up-to-Date Calibration Data; Mobile Collection and Automated Interpretation of EEG Data; System for Secure Integration of Aviation Data; Servomotor and Controller Having Large Dynamic Range; Digital Multicasting of Multiple Audio Streams; Translator for Optimizing Fluid-Handling Components; AIRSAR Web-Based Data Processing; Pattern Matcher for Trees Constructed From Lists; Reducing a Knowledge-Base Search Space When Data Are Missing; Ground-Based Correction of Remote-Sensing Spectral Imagery; State-Chart Autocoder; Pointing History Engine for the Spitzer Space Telescope; Low-Friction, High-Stiffness Joint for Uniaxial Load Cell; Magnet-Based System for Docking of Miniature Spacecraft; Electromechanically Actuated Valve for Controlling Flow Rate; Plumbing Fixture for a Microfluidic Cartridge; Camera Mount for a Head-Up Display; Core-Cutoff Tool; Recirculation of Laser Power in an Atomic Fountain; Simplified Generation of High-Angular-Momentum Light Beams; Imaging Spectrometer on a Chip; Interferometric Quantum-Nondemolition Single-Photon Detectors; Ring-Down Spectroscopy for Characterizing a CW Raman Laser; Complex Type-II Interband Cascade MQW Photodetectors; Single-Point Access to Data Distributed on Many Processors; Estimating Dust and Water Ice Content of the Martian Atmosphere From THEMIS Data; Computing a Stability Spectrum by Use of the HHT; Theoretical Studies of Routes to Synthesis of Tetrahedral N4; Estimation Filter for Alignment of the Spitzer Space Telescope; Antenna for Measuring Electric Fields Within the Inner Heliosphere; Improved High-Voltage Gas Isolator for Ion Thruster; and Hybrid Mobile Communication Networks for Planetary Exploration.

Source record↗

A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence

In the present study, we investigate different data-driven parameterizations for large eddy simulation of two-dimensional turbulence in the a priori settings. These models utilize resolved flow field variables on the coarser grid to estimate the subgrid-scale stresses. We use data-driven closure models based on localized learning that employs a multilayer feedforward artificial neural network with point-to-point mapping and neighboring stencil data mapping, and convolutional neural network fed by data snapshots of the whole domain. The performance of these data-driven closure models is measured through a probability density function and is compared with the dynamic Smagorinksy model (DSM). The quantitative performance is evaluated using the cross-correlation coefficient between the true and predicted stresses. We analyze different frameworks in terms of the amount of training data, selection of input and output features, their characteristics in modeling with accuracy, and training and deployment computational time. We also demonstrate computational gain that can be achieved using the intelligent eddy viscosity model that learns eddy viscosity computed by the DSM instead of subgrid-scale stresses. Here, we detail the hyperparameters optimization of these models using the grid search algorithm.

42 ENGINEERING↗