Results for “Calorimeters” — Page 62

NASA NTRS2022

Fermi Gamma-ray Space Telescope

The Fermi Gamma-ray Space Telescope, a key mission in multiwavelength and multimessenger studies, has been surveying the γ-ray sky from its low-Earth orbit since 2008. Its two scientific instruments, the Gamma-ray Burst Monitor (GBM) and the Large Area Telescope (LAT), cover 8 orders of magnitude in photon energy. The GBM consists of 12 Sodium Iodide detectors and 2 Bismuth Germinate detectors, covering the 10 keV - 40 MeV energy range, arrayed on two sides of the spacecraft so as to view the entire sky that is not occulted by the Earth. The LAT is a pair production telescope based on silicon strip trackers, a Cesium Iodide calorimeter, and a plastic scintillator anticoincidence system. It covers the energy range from about 20 MeV to more than 500 GeV, with a field of view of about 2.4 steradians. Thanks to their huge fields of view, the instruments can observe the entire sky with a cadence of about an hour for GBM and about three hours for LAT. All γ-ray data from Fermi become public immediately, enabling a broad range of multiwavelength and multimessenger research. Over 3000 γ-ray bursts (GRBs), including GRB 170817A associated with a neutron star merger detected in gravitational waves, and 5000 high-energy sources, including the blazar TXS 0506+056 associated with high-energy neutrinos, have been detected by the Fermi instruments. The Fermi Science Support Center provides a wide array of resources to enable scientific use of the data, including background models, source catalogs, analysis software, documentation, and a Help Desk.

gamma rays↗

NASA NTRS2022

Precision Measurement of the Nickel Spectrum in Cosmic Rays from 8.8 GeV/n to 240 GeV/n with CALET on the International Space Station

The relative abundance of nickel with respect to iron is by far larger than all other trans-iron elements, therefore it provides a favourable opportunity for a low background measurement of its spectrum. Since nickel, as well as iron, is one of the most stable nuclei, the nickel energy spectrum and its relative abundance with respect to iron provide important information to estimate the abundances at the source and to model the propagation of heavy nuclei. However, only a few direct measurements of cosmic-ray nickel at energy larger than∼3 GeV/n are available at present in the literature and they are affected by strong limitations in both energy reach and statistics. In this paper we present a measurement of the differential energy spectrum of nickel from 8.8 GeV/nto 240 GeV/n, carried out with unprecedented precision by the Calorimetric Electron1 Telescope(CALET) in operation on the International Space Station since 2015. The CALET instrument can identify individual nuclear species via a measurement of their electric charge with a dynamic range extending far beyond iron (up to atomic number Z = 40). The particle’s energy is measured by a homogeneous calorimeter (1.2 proton interaction lengths, 27 radiation lengths) preceded by a thin imaging section (3 radiation lengths) providing tracking and energy sampling. This paper follows our previous measurement of the iron spectrum [1] and it extends our investigation on the energy dependence of the spectral index of heavy elements. It reports the analysis of nickel data collected from November 2015 to May 2021 and a detailed assessment of the systematic uncertainties. In the region from 20 GeV/nto 240 GeV/n our present data are compatible within the errors with a single power law with spectral index−2.51±0.07.

O Adriani↗

NASA NTRSDate not supplied

On Characterization of Laminar to Turbulent Transitional Flow in the Truncated IHF Semi-Elliptical Nozzle

This paper reports computational analysis and experimental data to characterize the laminar to turbulent flow transition in a high-enthalpy panel test facility at NASA Ames Research Center. The recently developed facility configuration uses a truncated version of an existing semi-elliptical nozzle in the 60-MW Interaction Heating Facility, and it provides testing capability for panel test articles as large as 43.2 cm x 43.2 cm (17 in x 17 in). A water-cooled calibration plate, which is attached to the semi-elliptical nozzle bottom surface and instrumented with twenty Gardon-gage heat flux calorimeters and twelve pressure gages, is used to characterize the convective heating environment over the panel test articles. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, and the flowfields over panel test articles, and comparisons with the measured test data. Both laminar and turbulent simulations are performed. Constant current studies are conducted: the measured data are grouped at the same arc current levels with varying mass flow rates, and they are compared with corresponding computations. For all currents considered, these studies indicate that the semi-elliptical nozzle flow is transitional at relatively higher mass flow rates within the facility operating envelope. An approximate facility map for the transitional flow characterization is developed, showing laminar and transitional to turbulent flow regions.

Arc-jets↗

NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-Segmentation Tasks

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D CNN architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization are described as well as the results of application to three separate arc jet data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation.

Machine learning↗

NASA NTRSDate not supplied

Investigating the Ability of Plastic Current Collectors to Isolate Internal Shorts

Metallized plastic current collectors in Li-ion cells reduce mass and reduce the internal short circuit hazard compared to aluminum and copper foils. Shorts induced by nail and by our internal short circuit device were performed on control 18650 cells and on cells with the collectors replaced with metallized polyester and aramid films. Tests were performed inside our fractional thermal runaway calorimeter to quantify the heat transferred and its distributions and those runs done at a synchrotron yielded fascinating very high speedX-ray videography. These show tolerance to nail penetration and activation of defect internal shorts and when thermally forced into thermal runaway, the heat output is significantly reduced. Very high resolutionCT scans, cross sections, and cell tear downs give insights into the thermal and mechanism for these plastic collectors.

Plastic Current Collectors↗

NASA NTRS2022

Passive Cooling in Aerogel-Based Insulation Systems for Liquid Hydrogen Upper Stage Launch Vehicle Tanks

Spray-On Foam Insulation (SOFI) is typically used to protect the windward-facing side of flight tanks for space launch vehicle liquid hydrogen (LH2) stages. SOFI is an excellent insulator in ambient pressure environments, however, its performance pales in comparison to reflective-type systems such as Multi-Layer Insulation in the thermal radiation dominated vacuum environment of space. If a windward insulation system employing radiation shields could be devised to replace or supplement SOFI, the on-orbit heat load could be drastically reduced, and the residual propellants could then be used to facilitate secondary missions. Such insulation systems, utilizing aerogel blanket insulation, have been explored by the Cryogenics Test Laboratory at NASA Kennedy Space Center. Owing to its nano-porous structure, aerogel is an excellent adsorbent as well as an insulator at cryogenic temperatures and will readily uptake condensable background gasses such as air when protecting a surface near LH2 temperatures. When an adsorbed blanket is rapidly exposed to a vacuum, such as during the ascent of a rocket, it will release the background gas, producing a passive cooling effect that could potentially reduce or eliminate the heat load on the propellant tank for a time. This work discusses the setup and results of a test program carried out to determine the effectiveness and impact of this cooling effect as it pertains to LH2 upper stage tanks. A vertical-cylindrical liquid nitrogen (LN2) calorimeter test instrument acted as the upper stage analog. The cold-mass was wrapped with two layers of 10 mm thick aerogel blanket material, with and without aluminum heat shields depending on the test, and interspersed with numerous thermocouple temperature sensors. Gaseous argon was used as a stand-in for air as the condensable background gas. The test procedure mimicked vehicle cryo-loading/stabilization, and ascent phases, with the ascent phase accomplished using parallel vacuum pumps. Results show that the desorption cooling effect was enough to not only eliminate the heat load on the LN2 cold-mass entirely, but further refrigerated the liquid below its boiling point.

A.M. Swanger↗

NASA NTRSDate not supplied

1d-Convolutional Neural Network Architecture for Generalized Time-Segmentation Tasks

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D CNN architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization are described as well as the results of application to three separate arc jet data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation.

Machine learning↗

NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-Segmentation Tasks

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization are described as well as the results of application to three separate arc jet data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation.

Machine learning↗

NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗

NASA NTRSDate not supplied

New Mission Concept: Compton Telescope with Coded Aperture Mask (GECCO) for MeV Gamma-ray Astronomy

The Galactic Explorer with a Coded Aperture Mask Compton Telescope (GECCO) is a novel Explorer-class concept for a next-generation telescope covering the poorly explored hard X-ray and soft gamma-ray energy regimes. The instrument is based on a novel CdZnTe imaging calorimeter and a deployable coded aperture mask, which enable it to reach 1 arcmin angular resolution and 1% energy resolution. GECCO will connect the arcminute angular resolution observations from X-ray telescopes to high-energy images of the Galactic plane provided by Fermi-LAT, and will focus on the exploration of heavily populated sky regions such as the Galactic Center and the Carina and Cygnus regions to decipher the nature of their emission. These measurements will probe with unprecedented capabilities the possible origin of this emission as dark matter, new types of sources, or currently unresolved populations of point sources. Uncoded observations with GECCO’s Compton telescope will provide wide field-of-view sky monitoring for transient events, synergizing with gravitational wave and high-energy neutrino facilities. In addition, GECCO will conduct a high-sensitivity search for the positron sources in the Galactic Center responsible for the enigmatic 511 keV positron annihilation line excess, will search for as-yet untested candidates for dark matter, will detect and identify high-redshift blazars with excellent angular resolution, and will explore Galactic chemical evolution and sites of explosive element synthesis.

Alexander A Moiseev↗

NASA NTRSDate not supplied

X-Ray Missions Based on LTD Technologies

Microcalorimeter arrays used as imaging spectrometers will enable ground-breaking science in X-ray astrophysics. Their development has been one of the driving applications of the low temperature detector community since the early 1980s. While their application in space remains in relative infancy, we are on the verge of an era in which microcalorimeter spectrometers are likely to dominate instrumentation for high-energy astrophysics missions. NASA sounding rocket experiments such as the X-ray Quantum Calorimeter (XQC) and Micro-X have now paved the way for orbital observatories. JAXA’s Astro-H gave us a glimpse of this fantastic new capability before its unfortunate demise. The launch of XRISM later this year should finally demonstrate the sort of large suite of observations that X-ray microcalorimeter arrays will make major contributions to. In the mid-2030s, we will see the launch of ESA’s flagship Athena mission, that will further advance the imaging and spectroscopic capabilities for the high-energy X-ray community enormously. Numerous other potential new mission concepts using X-ray microcalorimeters have been studied in detail such as NASA’s Lynx and the Light Element Mapper (LEM), JAXA’s Super-DIOS, and China’s Hot Universe Baryon Surveyor (HUBS). In the first half of this presentation, I will review the development and desired requirements of the X-ray microcalorimeter missions and concepts, and describe the current progress and status missions being implemented and proposed. In the second half of this presentation, I will focus on The Line Emission Mapper (LEM) which is a probe-class mission concept under study by NASA that is designed to provide unprecedented insight into the physics of galaxy formation, including stellar and black-hole feedback and flows of baryonic matter into and out of galaxies. LEM incorporates a light-weight X-ray optic with 10” angular resolution and a large-format microcalorimeter array with a 15” pixel pitch over a 29’ field of view (FOV). The main microcalorimeter array and readout design takes advantage of mature technology that has been developed for Athena X-IFU. The central 7’ region of the array consists of ~ 800 transition-edge sensors (TESs), optimized for a bandpass of 0.3-2 keV and with an energy resolution of 1.2 eV at 1 keV. The rest of the FOV is covered by 4-pixel TES hydras with 2.5 eV energy resolution at 1 keV. Hydras are position-sensitive (‘thermally multiplexed’) detectors that enable extremely large numbers of effective pixels in an array, without a commensurate increase in the number of wires, bias circuit, and readout components. In total the array will have ~ 4k TESs with ~ 14k imaging elements on a 290 micron-pitch. The array will be read out with state-of-the-art time-division multiplexing (TDM), implement with 59 pixels (and 1 dark pixel) in each of the 69 TDM columns. Here we present a detailed overview of the baseline microcalorimeter detector design and present first results from both single pixel TESs and 4-pixel hydras. Our prototype LEM pixels utilize 15um x 50um Mo/Au TESs with a transition temperature of around 58 mK. These pixels incorporate high-fill-factor Au absorbers of thickness 0.54um. We have demonstrated an energy resolution of 0.90+/-0.02 eV and 1.90 +/-0.02 eV at 1.5 keV for single pixel and 4-pixel hydras, respectively, meeting the performance requirements of LEM. We show how the position discrimination in the hydra pixels can be achieved, down to energies of a few 100 eV, using the measured pulse rise-times. Finally, we will show that the properties of the LEM pixels are well optimized for the proposed TDM read out architecture.

Simon Richard Bandler↗

NASA NTRSDate not supplied

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗

NASA NTRSDate not supplied

On Characterization of Flow Disturbances in Arc-Jet Testing

This paper reports computational simulations and analysis of flow characterization tests in high enthalpy arc-jet facilities at NASA Ames Research Center. Flow disturbances and their characterization are presented through case studies, and their implications for testing are discussed. The case studies include free-jet test configurations from three different arc heaters and nozzles: the 60-MW IHF 30-inch conical nozzle, the 10-MW TP3 15-inch conical nozzle, and the 20-MW AHF 12-inch conical nozzle. For all cases, test articles are placed in the jet exiting the conical nozzle, and the existence of a flow disturbance is confirmed through flow survey data using pitot pressure and heat flux probes and accompanying analysis. The paper focuses on cases where the effects of the disturbances on test article surface quantities are important. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzles and test box, including the models tested. Comparisons of computations with the experimental measurements are presented. The computations that reproduce the probe sweep data approximately are essential to interpret the arc-jet test data accurately, while providing insights into several observed calorimeter anomalies caused by flow disturbances.

Arc-jet testing↗

NASA NTRSDate not supplied

On Characterization of Flow Disturbances in Arc-Jet Testing

This paper reports computational simulations and analysis of flow characterization tests in high enthalpy arc-jet facilities at NASA Ames Research Center. Flow disturbances and their characterization are presented through case studies, and their implications for testing are discussed. The case studies include free-jet test configurations from three different arc heaters and nozzles: the 60-MW IHF 30-inch conical nozzle, the 10-MW TP3 15-inch conical nozzle, and the 20-MW AHF 12-inch conical nozzle. For all cases, test articles are placed in the jet exiting the conical nozzle, and the existence of a flow disturbance is confirmed through flow survey data using pitot pressure and heat flux probes and accompanying analysis. The paper focuses on cases where the effects of the disturbances on test article surface quantities are important. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzles and test box, including the models tested. Comparisons of computations with the experimental measurements are presented. The computations that reproduce the probe sweep data approximately are essential to interpret the arc-jet test data accurately, while providing insights into several observed calorimeter anomalies caused by flow disturbances.

Arc-jet testing↗

NASA NTRSDate not supplied

CFD Simulations of the AEDC H3 Arc-Jet Flow: Mach 3.3 Nozzle, Flow Surveys, Wedge Models

This paper reports computational simulations and analysis of tests in a high enthalpy arc-jet facility at Arnold Engineering Development Center. These tests were conducted using wedge models placed in a free jet downstream of a 4.5-inch diameter contoured Mach 3.3 nozzle in the H3 facility. For calibration of test conditions, one wedge calibration plate instrumented with an array of pressure and coaxial thermocouple heat flux gages, one stagnation pressure probe and two null-point heat flux calorimeters were used. The pitot pressure and null-point probe measurements give experimental surveys of the test flow, providing assessment of the flow uniformity and valuable data for flow characterization. The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle, into the test box and over the wedge models, and comparisons with the experimental measurements. Several issues related to testing are considered: test flow characterization, prediction of surface quantities for three wedge models, effects of model shape change and test article recession, and prediction of surface quantities for the test articles with two circular cavities. These simulations take into account non-uniform total enthalpy profiles at the nozzle inlet as well as the expansion waves emanating from the nozzle exit and their effects on the wedge model flowfields.

Arc-jet testing↗

NASA NTRSDate not supplied

Validation of Artemis I Aerothermal Design Models Using Developmental Flight Instrumentation

The inaugural flight of the Space Launch System (SLS) Block 1 launch vehicle, Artemis I, occurred on November 16, 2022, and featured a full suite of Developmental Flight Instrumentation (DFI) that provided aerothermodynamic measurements to assess thermal design and substantiate aerothermodynamic models. The Block 1 launch vehicle aerothermal instrumentation consisted of approximately 277 aerothermal gauges mounted throughout the Orion Multi-Purpose Crew Vehicle (MPCV), Integrated Spacecraft and Payload Element (ISPE), Core Stage (CS) and Solid Rocket Boosters (SRB) and an additional 179 thermal gauges on the Orion Crew Module (CM). Instrumentation included calorimeters, radiometers, pressure transducers, gas temperature probes, and thermocouples. Data was collected from lift-off through CS Main Engine Cut-Off (MECO). The flight data was invaluable for determining aerothermal model performance and developing flight-derived aerothermal environments for flight reconstruction thermal analysis and future SLS aerothermal models. The data offered critical insights into the aerothermodynamic conditions experienced during the launch and ascent of the SLS vehicle. This study compares the flight derived environments to pre-existing design models. The aerothermal models were constructed using MINIVER, the aerothermal engineering code which predicts aerodynamic heating and acts as an integration tool for incorporating databases from computational fluid dynamics (CFD) simulations and wind tunnel test data. The comparisons reveal the fidelity of the design models, highlighting areas where the design models accurately predicted flight conditions and instances where deviations were observed. Preliminary results suggest that while the design models largely aligned with the observed flight data, there were unique observations that reflected needed areas of model refinement. Aerothermal flight data from Artemis I for the SLS Block 1 vehicle will be further utilized to enhance the accuracy of Block 1B and Block 2 aerothermal models, ensuring improved safety and performance for subsequent Artemis missions.

aerothermodynamics↗

NASA NTRSDate not supplied

Validation of Artemis I Aerothermal Design Models Using Developmental Flight Instrumentation

The inaugural flight of the Space Launch System (SLS) Block 1 launch vehicle, Artemis I, occurred on November 16, 2022, and featured a full suite of Developmental Flight Instrumentation (DFI) that provided aerothermodynamic measurements to assess thermal design and substantiate aerothermodynamic models. The Block 1 launch vehicle aerothermal instrumentation consisted of approximately 277 aerothermal gauges mounted throughout the Orion Multi-Purpose Crew Vehicle (MPCV), Integrated Spacecraft and Payload Element (ISPE), Core Stage (CS) and Solid Rocket Boosters (SRB) and an additional 179 thermal gauges on the Orion Crew Module (CM). Instrumentation included calorimeters, radiometers, pressure transducers, gas temperature probes, and thermocouples. Data was collected from lift-off through CS Main Engine Cut-Off (MECO). The flight data was invaluable for determining aerothermal model performance and developing flight-derived aerothermal environments for flight reconstruction thermal analysis and future SLS aerothermal models. The data offered critical insights into the aerothermodynamic conditions experienced during the launch and ascent of the SLS vehicle. This study compares the flight derived environments to pre-existing design models. The aerothermal models were constructed using MINIVER, the aerothermal engineering code which predicts aerodynamic heating and acts as an integration tool for incorporating databases from computational fluid dynamics (CFD) simulations and wind tunnel test data. The comparisons reveal the fidelity of the design models, highlighting areas where the design models accurately predicted flight conditions and instances where deviations were observed. Preliminary results suggest that while the design models largely aligned with the observed flight data, there were unique observations that reflected needed areas of model refinement. Aerothermal flight data from Artemis I for the SLS Block 1 vehicle will be further utilized to enhance the accuracy of Block 1B and Block 2 aerothermal models, ensuring improved safety and performance for subsequent Artemis missions.

aerothermodynamics↗

NASA NTRSDate not supplied

Heat Transfer Measurements of NASA Liquid Kerosene/Oxygen Rotating Detonation Rocket Engine

The RDRE has been identified as a viable high performance propulsion system with numerous advantages over the state-of-the-art (SOA) liquid rocket engine. NASA has been investigating this combustion device for applications ranging from lander, upper stage, thruster, and hypersonics. All of the activities funded to date have been focused on closing major technology gaps preventing the RDRE from being used more broadly by industry. One of those gaps include the prediction and management of heat transfer to the walls from the extreme combustion environment. This work overviews the heat transfer measurements made using new and existing hardware. A liquid oxygen / liquid RP-1 RDRE was tested utilizing a calorimeter outer body and outer body nozzle extension. An actively cooled inner body with axial running cooling channels was also used. A bimetallic GRCop-42 / Monel K500 injector was developed and demonstrated to be a viable technology for RDRE environments. Trends in bulk heat loads are discussed along with a direct comparison to constant pressure theory predictions of wall heat transfer. The experimental data obtained in this investigation showed similar heat fluxes to constant pressure theory indicating deflagration may have dominated the flow field. Only a single detonation wave was observed in all tests which imparted a significant dynamic load (vibration) on the test article making measurement of combustor performances extremely challenging. Both accelerometer and load cell data corroborate the extreme G-forces measured. The single wave mode yielded relatively low performances compared with other hot fire test data sets available. This leads to the conclusion that a single detonation wave in this geometry is not sufficient for high performance. Wave multiplicity, or rather, a specific number of waves may yield higher performances.

Thomas Teasley↗