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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-1 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024 This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

COMPASS-FME Synoptic Sites Level 1 Sensor Data v1-2

This is the version 1-2 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our synoptic field sites. COMPASS-FME is studying sites in two distinct regions, the Chesapeake Bay and the Western Lake Erie Basin. We established the network at seven "synoptic" (observational) sites along the Chesapeake Bay and Lake Erie coastlines, collectively generating over three million observations per month, to track and comprehend environmental changes where land and water intersect. Additionally, the two regions provide an interesting contrast of saltwater and freshwater coasts that allow us to differentiate the impacts of inundation and coastal water chemistries in two nationally important coastal systems.L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds and out-of-service flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project**This dataset includes:- An overall dataset README file that describes the current version, gives citation and contact information, etc.- Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year.- Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, as well as a general description of the site.- Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v1-2 Synoptic L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1963

A SURVEY OF MASS AND LEVEL GAUGING TECHNIQUES FOR LIQUID HYDROGEN

Generally, liquid level sensors are used to determine the liquid mass or head in tank filling, holding, and propellant utilization systems for rocket vehicles, and also In storage Inventory and research applications. The latter two applications are so varied that they will not be discussed further. Tank filling and holding to a predetermined liquid mass require a flow control system that is maintained by a liquid level sensor. The sensor may be a continuous-reading type or a rake of point sensors located in the vicinity of the required level Propellant utilization systems control the relative flows of the liquid propellants so that, ideally, no propellant is left over at burnout. A liquid level sensing and control system monitors the liquid mass in each tank during outflow and corrects the relative propellant flows to obtain the desired result. The level sensor again may be either a continuous sensor or a rake of point sensors.

LIQUID HYDROGEN↗
DOE OSTI2022

Automated cryogenic refilling system

An improved system and method for the automated refilling of cryogenic helium is provided. In one embodiment, the system includes a dewar in fluid communication with a liquid helium cryostat through a cryogen transfer line. A controller regulates operation of a three-way valve to pre-cool the transfer line and to cause gaseous helium to flow to the dewar and force liquid helium through the transfer line into the cryostat. The controller is coupled to the output of a cryogenic level sensor, such that the controller regulates the helium liquid level within the cryostat. During filling cycles, the dewar liquid level is also monitored by the cryogenic level sensor and an alarm sounds if the dewar liquid level is undesirably low. Between filling cycles, the controller is operable to ventilate the dewar through a solenoid vent valve in fixed time intervals to ensure the dewar pressure is sufficiently low so as to not bleed liquid helium into the cryostat.

Ruiz-Rodriguez, Mariano M.↗
NASA NTRS2006

A Wireless Fluid-Level Measurement Technique

This paper presents the application of a recently developed wireless measurement acquisition system to fluid-level measurement. This type of fluid-level measurement system alleviates many shortcomings of fluid-level measurement methods currently being used, including limited applicability of any one fluid-level sensor design. Measurement acquisition shortcomings include the necessity for power to be supplied to each sensor and for the measurement to be extracted from each sensor via a physical connection to the sensor. Another shortcoming is existing measurement systems require that a data channel and signal conditioning electronics be dedicated to each sensor. Use of wires results in other shortcomings such as logistics needed to add or replace sensors, weight, potential for electrical arcing and wire degradations. The fluid level sensor design is a simple passive inductor-capacitor circuit that is not subject to mechanical failure that is possible when float and lever-arm systems are used. Methods are presented for using the sensor in caustic, acidic or cryogenic fluids. Oscillating magnetic fields are used to power the sensor. Once electrically excited, the sensor produces a magnetic field response. The response frequency corresponds to the amount to fluid within the capacitor s electric field. The sensor design can be modified for measuring the level of any fluid or fluent substance that can be stored in a non-conductive reservoir. The interrogation method for discerning changes in the sensor response frequency is also presented.

Woodard, Stanley E.↗
DOE OSTI2024

Conductive Spray Paint Fabricated Cylindrical Coplanar Waveguide for Noncontact Liquid-Level Sensing

A noncontact liquid-level sensor using a cylindrical coplanar waveguide (CCPW) is proposed. The concept is demonstrated using a prototype device made by directly spraying conductive paint on the outer surface of a glass cylinder. The position of the air–liquid interface is measured using the time-domain reflection (TDR) signal from the CCPW. The geometric parameters of the prototype sensor were optimized using a full-wave simulation tool. The experimental results show that the prototype CCPW-based liquid-level sensor has a resolution of 29.8μm over a range of 210 mm at the sweeping frequency bandwidth of 500 MHz–4 GHz. The tradeoff between the resolution and the measurement range was discussed. The proposed sensor provides a low-cost, easy-to-fabricate, and noncontact method for liquid-level measurement, which has potential applications in fuel storage, chemical production, and wastewater treatment.

42 ENGINEERING↗
NASA NTRS2010

A Safe, Self-Calibrating, Wireless System for Measuring Volume of Any Fuel at Non-Horizontal Orientation

A system for wirelessly measuring the volume of fluid in tanks at non-horizontal orientation is predicated upon two technologies developed at Langley Research Center. The first is a magnetic field response recorder that powers and interrogates magnetic field response sensors [ Magnetic Field Response Measurement Acquisition System, (LAR-16908), NASA Tech Briefs, Vol. 30, No. 6 (June 2006), page 28]. Magnetic field response sensors are a class of sensors that are powered via oscillating magnetic fields and when electrically active respond with their own magnetic fields whose attributes are dependent upon the magnitude of the physical quantity being measured. The response recorder facilitates the use of the second technology, which is a magnetic field response fluid-level sensor ["Wireless Fluid- Level Sensors for Harsh Environments," (LAR-17155), NASA Tech Briefs, Vol. 33, No. 4 (April 2009), page 30]. The method for powering and interrogating the sensors allows them to be completely encased in materials (Fig. 1) that are chemically resilient to the fluid being measured, thereby facilitating measurement of substances (e.g., acids, petroleum, cryogenic, caustic, and the like) that would normally destroy electronic circuitry. When the sensors are encapsulated, no fluid (or fluid vapor) is exposed to any electrical component of the measurement system. There is no direct electrical line from the vehicle or plant power into a fuel container. The means of interrogating and powering the sensors can be completely physically and electrically isolated from the fuel and vapors by placing the sensor on the other side of an electrically non-conductive bulkhead (Fig. 2). These features prevent the interrogation system and its electrical components from becoming an ignition source.

Woodward, Stanley E.↗
NASA NTRS2012

Measuring Air Leaks into the Vacuum Space of Large Liquid Hydrogen Tanks

Large cryogenic liquid hydrogen tanks are composed of inner and outer shells. The outer shell is exposed to the ambient environment while the inner shell holds the liquid hydrogen. The region between these two shells is evacuated and typically filled with a powderlike insulation to minimize radiative coupling between the two shells. A technique was developed for detecting the presence of an air leak from the outside environment into this evacuated region. These tanks are roughly 70 ft (approx. equal 21 m) in diameter (outer shell) and the inner shell is roughly 62 ft (approx. equal 19 m) in diameter, so the evacuated region is about 4 ft (approx. equal 1 m) wide. A small leak's primary effect is to increase the boil-off of the tank. It was preferable to install a more accurate fill level sensor than to implement a boil-off meter. The fill level sensor would be composed of an accurate pair of pressure transducers that would essentially weigh the remaining liquid hydrogen. This upgrade, allowing boil-off data to be obtained weekly instead of over several months, is ongoing, and will then provide a relatively rapid indication of the presence of a leak.

Youngquist, Robert↗
NASA NTRS1972

A reliable liquid helium detector

Detector and indicator system, utilizing commercial perforated germanium cryogenic thermometer as level sensor containing adjustable level discriminator with indicators, operates reliably over pressure range from 50 to 900 mm Hg without electronic adjustments.

Krawczonek, W. M.↗
NASA NTRS2012

A Brief Overview of NASA Glenn Research Center Sensor and Electronics Activities

Aerospace applications require a range of sensing technologies. There is a range of sensor and sensor system technologies being developed using microfabrication and micromachining technology to form smart sensor systems and intelligent microsystems. Drive system intelligence to the local (sensor) level -- distributed smart sensor systems. Sensor and sensor system development examples: (1) Thin-film physical sensors (2) High temperature electronics and wireless (3) "lick and stick" technology. NASA GRC is a world leader in aerospace sensor technology with a broad range of development and application experience. Core microsystems technology applicable to a range of application environmentS.

Hunter, Gary W.↗
NASA NTRS2008

Smart Networked Elements in Support of ISHM

At the core of ISHM is the ability to extract information and knowledge from raw data. Conventional data acquisition systems sample and convert physical measurements to engineering units, which higher-level systems use to derive health and information about processes and systems. Although health management is essential at the top level, there are considerable advantages to implementing health-related functions at the sensor level. The distribution of processing to lower levels reduces bandwidth requirements, enhances data fusion, and improves the resolution for detection and isolation of failures in a system, subsystem, component, or process. The Smart Networked Element (SNE) has been developed to implement intelligent functions and algorithms at the sensor level in support of ISHM.

Oostdyk, Rebecca↗
DOE OSTI2024

Warrick Conductivity Level Controllers Series 3H

This is my internship poster. In the poster I talk about the level controllers that I wired together and installed to support electrolysis testing systems in efforts to make the systems more efficient and run based on the communication between devices to ensure a closed loop system that can run on its own in a safe and controlled manner. I included pictures of some of the wiring as well as the level sensor devices and relays. I also included pictures of the tanks that will be filled at different heights with deionized water based on where the level sensors are.

08 HYDROGEN↗
NASA NTRS2003

Capacitive Sensors for Measuring Masses of Cryogenic Fluids

An effort is under way to develop capacitive sensors for measuring the masses of cryogenic fluids in tanks. These sensors are intended to function in both microgravitational and normal gravitational settings, and should not be confused with level sensors, including capacitive ones. A sensor of this type is conceptually simple in the sense that (1) it includes only one capacitor and (2) if properly designed, its single capacitance reading should be readily convertible to a close approximation of the mass of the cryogenic fluid in the tank. Consider a pair of electrically insulated electrodes used as a simple capacitive sensor. In general, the capacitance is proportional to the permittivity of the dielectric medium (in this case, a cryogenic fluid) between the electrodes. The success of design and operation of a sensor of the present type depends on the accuracy of the assumption that to a close approximation, the permittivity of the cryogenic fluid varies linearly with the density of the fluid. Data on liquid nitrogen, liquid oxygen, and liquid hydrogen, reported by the National Institute of Standards and Technology, indicate that the permittivities and densities of these fluids are, indeed, linearly related to within a few tenths of a percent over the pressure and temperature regions of interest. Hence, ignoring geometric effects for the moment, the capacitance between two electrodes immersed in the fluid should vary linearly with the density, and, hence, with the mass of the fluid. Of course, it is necessary to take account of the tank geometry. Because most cryogenic tanks do not have uniform cross sections, the readings of level sensors, including capacitive ones, are not linearly correlated with the masses of fluids in the tanks. In a sensor of the present type, the capacitor electrodes are shaped so that at a given height, the capacitance per unit height is approximately proportional to the cross-sectional area of the tank in the horizontal plane at that height (see figure).

Nurge, Mark↗
DOE OSTI2024

Mechanisms Underlying a Quantum Superposition Microscope Based on THz-Driven Coherent Oscillations in a Two-Level Molecular Sensor

Here we report pump-probe measurements of a hydrogen molecule (H 2 ) in the tunnel junction of a scanning tunneling microscope (STM) coupled to ultrashort terahertz (THz) pulses. The coherent oscillation of the THz induced DC tunneling current at a frequency of ~0.5 THz fingerprints the absorption by H 2 as a two-level system (TLS). Two components of the oscillatory signal are observed and point to both photon and field aspects of the THz pulses. A few loosely bound states with similar energies for the upper state of the TLS are evidenced by the coherent revival of oscillatory signal. Furthermore, the comparison of spectroscopic features of H 2 with different tips provides an understanding of the TLS for H 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2021

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗
NASA NTRS2009

NASA Tech Briefs, April 2009

Topics covered include: Direct-Solve Image-Based Wavefront Sensing; Use of UV Sources for Detection and Identification of Explosives; Using Fluorescent Viruses for Detecting Bacteria in Water; Gradiometer Using Middle Loops as Sensing Elements in a Low-Field SQUID MRI System; Volcano Monitor: Autonomous Triggering of In-Situ Sensors; Wireless Fluid-Level Sensors for Harsh Environments; Interference-Detection Module in a Digital Radar Receiver; Modal Vibration Analysis of Large Castings; Structural/Radiation-Shielding Epoxies; Integrated Multilayer Insulation; Apparatus for Screening Multiple Oxygen-Reduction Catalysts; Determining Aliasing in Isolated Signal Conditioning Modules; Composite Bipolar Plate for Unitized Fuel Cell/Electrolyzer Systems; Spectrum Analyzers Incorporating Tunable WGM Resonators; Quantum-Well Thermophotovoltaic Cells; Bounded-Angle Iterative Decoding of LDPC Codes; Conversion from Tree to Graph Representation of Requirements; Parallel Hybrid Vehicle Optimal Storage System; and Anaerobic Digestion in a Flooded Densified Leachbed.

Source record↗
NASA NTRS2012

Coincident Observation of Lightning using Spaceborne Spectrophotometer and Ground-Level Electromagnetic Sensors

The present study aims at assessing a possible new way to reveal the properties of lightning flash, using spectrophotometric data obtained by FORMOSAT-2/ISUAL which is the first spaceborne multicolor lightning detector. The ISUAL data was analyzed in conjunction with ground ]based electromagnetic data obtained by Duke magnetic field sensors, NLDN, North Alabama Lightning Mapping Array (LMA), and Kennedy Space Center (KSC) electric field antennas. We first classified the observed events into cloud ]to ]ground (CG) and intra ]cloud (IC) lightning based on the Duke and NLDN measurements and analyzed ISUAL data to clarify their optical characteristics. It was found that the ISUAL optical waveform of CG lightning was strongly correlated with the current moment waveform, suggesting that it is possible to evaluate the electrical properties of lightning from satellite optical measurement to some extent. The ISUAL data also indicated that the color of CG lightning turned to red at the time of return stroke while the color of IC pulses remained unchanged. Furthermore, in one CG event which was simultaneously detected by ISUAL and LMA, the observed optical emissions slowly turned red as the altitude of optical source gradually decreased. All of these results indicate that the color of lightning flash depends on the source altitude and suggest that spaceborne optical measurement could be a new tool to discriminate CG and IC lightning. In the presentation, we will also show results on the comparison between the ISUAL and KSC electric field data to clarify characteristics of each lightning process such as preliminary breakdown, return stroke, and subsequent upward illumination.

Adachi, Toru↗