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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

STS-49 Endeavour/Compiled Video for Editors

Compiled footage includes shots taken of the rollout of Endeavour at Palmdale, CA, the departure and arrival of Endeavour for Kennedy Space Center (KSC), main engine three installation, solid rocket booster (SRB) segment lift and stack at the Vehicle Assembly Building (VAB), external tank mate to SRB, Intelsat rotation at the Vertical Processing Facility (VPF), Endeavour rollover from the Orbiter Processing Facility (OPF) to VAB, rollout to Pad B, and the flight readiness firing (FRF). The crew is seen during the Terminal Countdown and Demonstration Test (TCDT) training activities, at breakfast, suiting up, and exiting the Operations and Checkout (O&C) Building.

Source record↗
NASA NTRS2012

Miniaturized Laser Heterodyne Radiometer (LHR) for Measurements of Greenhouse Gases in the Atmospheric Column

This passive laser heterodyne radiometer (LHR) instrument simultaneously measures multiple trace gases in the atmospheric column including carbon dioxide (CO2) and methane (CH4), and resolves their concentrations at different altitudes. This instrument has been designed to operate in tandem with the passive aerosol sensor currently used in AERONET (an established network of more than 450 ground aerosol monitoring instruments worldwide). Because aerosols induce a radiative effect that influences terrestrial carbon exchange, simultaneous detection of aerosols with these key carbon cycle gases offers a uniquely comprehensive measurement approach. Laser heterodyne radiometry is a technique for detecting weak signals that was adapted from radio receiver technology. In a radio receiver, a weak input signal from a radio antenna is mixed with a stronger local oscillator signal. The mixed signal (beat note, or intermediate frequency) has a frequency equal to the difference between the input signal and the local oscillator. The intermediate frequency is amplified and sent to a detector that extracts the audio from the signal. In the LHR instrument described here, sunlight that has undergone absorption by the trace gas is mixed with laser light at a frequency matched to a trace gas absorption feature in the infrared (IR). Mixing results in a beat signal in the RF (radio frequency) region that can be related to the atmospheric concentration. For a one-second integration, the estimated column sensitivities are 0.1 ppmv for CO2, and <1 ppbv for CH4. In addition to producing a standalone ground measurement product, this instrument could be used to calibrate/validate four Earth observing missions: ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons), OCO-2 (Orbiting Carbon Observatory), OCO-3, and GOSAT (Greenhouse gases Observational SATellite). The only network that currently measures CO2 and CH4 in the atmospheric column is TCCON (Total Carbon Column Observing Network), and only two of its 16 operational sites are in the United States. TCCON data is used for validation of GOSAT data, and will be used for OCO-2 validation. While these Fourier-transform spectrometers (FTS) can measure the largest range of trace gases, the network is severely limited due to the high cost and extreme size of these instruments (these occupy small buildings and require personnel for operation). The LHR/AERONET instrument offers a significantly smaller (carry-on luggage size) autonomous instrument that can be incorporated into AERONET s much larger (450 instruments) global network.

Steel, Emily↗
NASA NTRS2014

Use of Semi-Autonomous Tools for ISS Commanding and Monitoring

As the International Space Station (ISS) has moved into a utilization phase, operations have shifted to become more ground-based with fewer mission control personnel monitoring and commanding multiple ISS systems. This shift to fewer people monitoring more systems has prompted use of semi-autonomous console tools in the ISS Mission Control Center (MCC) to help flight controllers command and monitor the ISS. These console tools perform routine operational procedures while keeping the human operator "in the loop" to monitor and intervene when off-nominal events arise. Two such tools, the Pre-positioned Load (PPL) Loader and Automatic Operators Recorder Manager (AutoORM), are used by the ISS Communications RF Onboard Networks Utilization Specialist (CRONUS) flight control position. CRONUS is responsible for simultaneously commanding and monitoring the ISS Command & Data Handling (C&DH) and Communications and Tracking (C&T) systems. PPL Loader is used to uplink small pieces of frequently changed software data tables, called PPLs, to ISS computers to support different ISS operations. In order to uplink a PPL, a data load command must be built that contains multiple user-input fields. Next, a multiple step commanding and verification procedure must be performed to enable an onboard computer for software uplink, uplink the PPL, verify the PPL has incorporated correctly, and disable the computer for software uplink. PPL Loader provides different levels of automation in both building and uplinking these commands. In its manual mode, PPL Loader automatically builds the PPL data load commands but allows the flight controller to verify and save the commands for future uplink. In its auto mode, PPL Loader automatically builds the PPL data load commands for flight controller verification, but automatically performs the PPL uplink procedure by sending commands and performing verification checks while notifying CRONUS of procedure step completion. If an off-nominal condition occurs during procedure execution, PPL Loader notifies CRONUS through popup messages, allowing CRONUS to examine the situation and choose an option of how PPL loader should proceed with the procedure. The use of PPL Loader to perform frequent, routine PPL uplinks offloads CRONUS to better monitor two ISS systems. It also reduces procedure performance time and decreases risk of command errors. AutoORM identifies ISS communication outage periods and builds commands to lock, playback, and unlock ISS Operations Recorder files. Operation Recorder files are circular buffer files of continually recorded ISS telemetry data. Sections of these files can be locked from further writing, be played back to capture telemetry data that occurred during an ISS loss of signal (LOS) period, and then be unlocked for future recording use. Downlinked Operation Recorder files are used by mission support teams for data analysis, especially if failures occur during LOS. The commands to lock, playback, and unlock Operations Recorder files are encompassed in three different operational procedures and contain multiple user-input fields. AutoORM provides different levels of automation for building and uplinking the commands to lock, playback, and unlock Operations Recorder files. In its automatic mode, AutoORM automatically detects ISS LOS periods, then generates and uplinks the commands to lock, playback, and unlock Operations Recorder files when MCC regains signal with ISS. AutoORM also features semi-autonomous and manual modes which integrate CRONUS more into the command verification and uplink process. AutoORMs ability to automatically detect ISS LOS periods and build the necessary commands to preserve, playback, and release recorded telemetry data greatly offloads CRONUS to perform more high-level cognitive tasks, such as mission planning and anomaly troubleshooting. Additionally, since Operations Recorder commands contain numerical time input fields which are tedious for a human to manually build, AutoORM's ability to automatically build commands reduces operational command errors. PPL Loader and AutoORM demonstrate principles of semi-autonomous operational tools that will benefit future space mission operations. Both tools employ different levels of automation to perform simple and routine procedures, thereby offloading human operators to perform higher-level cognitive tasks. Because both tools provide procedure execution status and highlight off-nominal indications, the flight controller is able to intervene during procedure execution if needed. Semi-autonomous tools and systems that can perform routine procedures, yet keep human operators informed of execution, will be essential in future long-duration missions where the onboard crew will be solely responsible for spacecraft monitoring and control.

Brzezinski, Amy S.↗
NASA NTRSDate not supplied

Near-Term Policy Considerations for Lunar Missions

Near-Term Policy Considerations for Lunar Missions. Therese Jones1, Gabriel Swiney,1 and Katie McBrayer,2 1NASA HQ, 300 Hidden Figures Way SW, Washington, D.C. 20546, 2NASA Langley Re-search Center, 1 NASA Drive, Hampton, VA, 23666. (Contact: therese.m.jones@nasa.gov) Introduction: More than two dozen lunar missions are planned prior to the Artemis III crewed lunar landing, from Russian, Chinese, Indian, Japanese and U.S. government orbiters and landers to Commercial Lunar Payload Ser-vices missions to commercial crewed flybys. While the Artemis Accords have established an international consortium of countries seeking to mitigate interference between operations on the Moon, a number of unaddressed policy issues remain that may be critical to lunar operations. In this lightning talk, we build upon NASA’s Of-fice of Technology, Policy, and Strategy’s Sep-tember 2022 Report “Lunar Landing and Oper-ations Policy Analysis” [1], to give an overview of policy questions that remain open, including: whether to prioritize certain landing locations or avoid certain scientifically valuable locations, design and coordination of safety zones, notifi-cation of other actors of potential dangers posed by landing, whether to avoid placing equipment in operationally valuable locations, and end-of-life disposal. We will also discuss how these policy implications could apply to planned missions.. References: [1] Swiney, G., and Hernandez, A. Lunar Landing and Operations Policy Analy-sis, NASA Office of Technology, Policy, and Strategy, September 30, 2022 https://www.nasa.gov/sites/default/files/atoms/files/nasa-otps-lunar-landing-and-operations-policy-analysis-final-report_2.pdf

Therese Jones↗
NASA NTRS1964

Study Program to Determine the Acceleration Environment Capability of the GG159C Gas- Bearing Spinmotor Final Report

The goal of this contract was to determine the g environment under which the GC159C Gas-Bearing Spinmotor (GBSM) could reliably operate. This was fulfilled by building and testing of four GBSM's, a test fixture, and a "dummy" gyro. The test program was divided into two phases when a gas bearing improvement was required to withstand JPL shock requirement of 200 g. Phase I determined existing g capabilities and performance of the GC159C GBSM and gimbal-case structure. Phase II increased GBSM capability to meet required JPL g environments. Life tests were run on two GBSM's which were shocked at a high level to obtain bearing contact while rotating at their operating speed of 23,000 rpm. A third (nonoperating) GBSM was exposed to JPL maximum shock levels, and a fourth (nonoperating) GBSM was exposed to random vibration. Both nonoperating GBSM's were then subjected to life testing.

SPIN↗
NASA NTRS2022

Simulating Mars: Enabling Testing of the Perseverance Rover Sampling and Caching Subsystem on Earth

The development of the Sampling and Caching Subsystem (SCS) on the JPL Perseverance Rover lies at the intersection of testing, robotics, and geology. The SCS team established three primary system test campaigns and venues to aid in the development of SCS through verification and validation testing – Qualification Model Dirty Testing (QMDT) to provide a venue for testing in a Martian environment, Vehicle System Testbed (VSTB) for testing while integrated with the mobility subsystem on Martian-like terrain, and the Flight Software Testbed (FSWTB) for conducting tests using the flight motor controllers and software system on a hexapod which had the ability to simulate rover tilt. Each venue contributed a vital piece to the SCS building blocks. However, the QMDT venue operating within a 10-ft diameter Thermal Vacuum chamber to simulate Martian environment provided a sui generis opportunity to fine tune the entire sampling and caching process while building the team’s knowledge base about rock drillability, system life, and target selection. On Earth, because Martian rocks are not readily available, the development team must utilize geoanalogs to the rocks and regolith on Mars. Geologists on the team helped establish a set of standard rock types to use for Mars missions, like Basalt, Sandstone, Mudstone, Gypsum, and other related geoanalogs. These geoanalogs are characterized with a standard suite of tests for density, compressibility, and other characteristics to categorize potential drillability. This concept of drillability is what links the geoanalogs on Earth to the samples we collect on Mars. With the simulant characteristics defined, these geoanalog rocks are ready to be drilled into as we do on the Martian surface. A key aspect of interacting with the surface on Mars is rock target identification and selection. The Perseverance robotic system uses the on-board cameras, instrumentation, and software to collect enough information to identify potential scientific targets. With the targets identified, SCS can place the Corer and abrade the surface or collect a sample. For a ground test activity like QMDT, the test team did not have all of the camera and instrumentation systems that the rover does, so the team developed ground test equivalents to process a rock, build a target map, and define the target. The team constructed a Rock Scanning Station to build a 3D point cloud of the rock. This point cloud was then processed and evaluated with predefined and programmed criteria in a Target Downselect Tool. A primary output of the Target Downselect Tool is a defined target that can be uploaded directly to the robotic software system to simulate and build the robotic sequences used in tests. With these insights and programmatic definition of targets, the QMDT test team was able to make the same decisions that the Perseverance surface operations team does. In addition, valuable lessons learned from developing the target selection ground tools and using them were implemented into the tools used for surface operations.

Kim, Junggon↗
NASA NTRS1992

High-resolution terrain map from multiple sensor data

The authors present 3-D vision techniques for incrementally building an accurate 3-D representation of rugged terrain using multiple sensors. They have developed the locus method to model the rugged terrain. The locus method exploits sensor geometry to efficiently build a terrain representation from multiple sensor data. The locus method is used to estimate the vehicle position in the digital elevation map (DEM) by matching a sequence of range images with the DEM. Experimental results from large-scale real and synthetic terrains demonstrate the feasibility and power of the 3-D mapping techniques for rugged terrain. In real world experiments, a composite terrain map was built by merging 125 real range images. Using synthetic range images, a composite map of 150 m was produced from 159 images. With the proposed system, mobile robots operating in rugged environments can build accurate terrain models from multiple sensor data.

Kweon, In S.↗
NASA NTRS1976

Experimental solar heating-cooling system model tests of a full-scale building system

An experimental solar heating and cooling system model has been built and operated, combining elements that are programmable - heating and/or cooling load of a building, collected solar energy - with experimental equipment. The system model was based on the loads and components used in the Solar Building Test Facility (SBTF) which includes a 1394 square meter solar collector field, at NASA-Langley. Operations covered 5 continuous days under summer conditions. For the system model, up to 55% of the simulated collected solar energy was used for the building load. This amount constituted 35% of the building cooling load. Heat loss was significant. If tank heat loss were eliminated, 75% of the collected solar energy would be used. This amount would supply approximately 50% of the building cooling load.

Namkoong, D.↗
NASA NTRS2010

Analysis of Possible Explosions at Kennedy Space Center Due to Spontaneous Ignition of Hypergolic Propellants

NASA's Constellation Program plan currently calls for the replacement of the Space Shuttle with the ARES I & V spacecraft and booster vehicles to send astronauts to the moon and beyond. Part of the ARES spacecraft is the Orion Crew Exploration Vehicle (CEV), which includes the Crew Module (CM) and Service Module (SM). The Orion CM's main propulsion system and supplies are provided by the SM. The SM is to be processed off line and moved to the Vehicle Assembly Building (V AB) for stacking to the first stage booster motors prior to ARES move to the launch pad. The new Constellation Program philosophy to process in this manner has created a major task for the KSC infrastructure in that conventional QD calculations are no longer viable because of the location of surrounding facilities near the VAB and the Multi Purpose Processing Facility (MPPF), where the SM will be serviced with nearly 18,000 pounds of hypergolic propellants. The Multi-Payload Processing Facility (MPPF) complex, constructed by NASA in 1994, is located just off E Avenue south of the Operations and Checkout (O&C) building in the Kennedy Space Center industrial area. The MPPF includes a high bay and a low bay. The MPPF high bay is 40.2 m (132 ft) long x 18.9 m (60 ft) wide with a ceiling height of 18.9 m (62 ft). The low bay is a 10.4 m (34 ft) long x 10.4 m (34 ft) wide processing area and has a ceiling height of6.1 m (20 ft). The MPPF is currently used to process non-hazardous payloads. Engineering Analysis Inc. (EAI), under contract with ASRC Aerospace, Inc. in conjunction with the Explosive Safety Office, NASA, Kennedy Space Center (KSC), has carried out an analysis of the effects of explosions at KSC in or near various facilities produced by the spontaneous ignition ofhypergolic fuel stored in the CEV SM. The facilities considered included (1) Vehicle Assembly Building (VAB) (2) Multi-Payload Processing Facility (MPPF) (3) Canister Rotation Facility (CRF) Subsequent discussion deals with the MPPF analysis. Figure 1 provides a view of the MPPF from the northwest. An interior view ofthe facility is shown in Figure 2. The study was concerned with both blast hazards and hazardous fragments which exceed existing safety standards, as described in Section 2.0. The analysis included both blast and fragmentation effects and was divided into three parts as follows: (1) blast (2) primary fragmentation (3) secondary fragmentation Blast effects are summarized in Section 3.0, primary fragmentation in Section 4.0, and secondary fragmentation (internal and external) in Section 5.0. Conclusions are provided in Section 6.0, while references cited are included in Section 7.0. A more detailed description of the entire study is available in a separate document.

Brown, Stephen↗
NASA NTRS1975

Building a computer-aided design capability using a standard time share operating system

The paper describes how an integrated system of engineering computer programs can be built using a standard commercially available operating system. The discussion opens with an outline of the auxiliary functions that an operating system can perform for a team of engineers involved in a large and complex task. An example of a specific integrated system is provided to explain how the standard operating system features can be used to organize the programs into a simple and inexpensive but effective system. Applications to an aircraft structural design study are discussed to illustrate the use of an integrated system as a flexible and efficient engineering tool. The discussion concludes with an engineer's assessment of an operating system's capabilities and desirable improvements.

Sobieszczanski, J.↗
NASA NTRS2020

2019 Corrective Measures Implementation and Intermim Measures Annual Status Report: Summary of Biosparge System Operation and Maintenance, and Interim Groundwater Monitoring Mobile Launch Platform / Vehicle Assembly Building Area (SWMU 056) Kennedy Space Center, Florida

This report presents a summary of the Corrective Measures Implementation (CMI) and Interim Measure (IM) implementation activities that occurred from May 2019 through December 2019 at the Mobile Launch Platform/Vehicle Assembly Building (MLPV) Area, Solid Waste Management Unit 056 (SWMU 056), located at the John F. Kennedy Space Center, Florida.

MOBILE LAUNCH PLATFORM / VEHICLE ASSEMBLY BUILDING↗
NASA NTRSDate not supplied

Imagery Analysis for Space Operations

The purpose of this project is to build a prototype camera system that utilizes artificial intelligence/machine learning and computer vision to track an object in 2D and recreate it in 3D.The goal is to improve image analysis and photogrammetry function for Pad 39B operations

Robotics↗
NASA NTRSDate not supplied

Imagery Analysis for Space Operations

The purpose of this project is to build a prototype camera system that utilizes artificial intelligence/machine learning and computer vision to track an object in 2D and recreate it in 3D.The goal is to improve image analysis and photogrammetry function for Pad 39B operations.

Computer Programming↗
NASA NTRS2024

Computing Proximity to Threat Along Uncertain Trajectory to Support Urban Air Mobility

Many airspace threats affect the selection of a flight route, such as terrain, physical obstacles, adverse weather, and special-use airspace, among others. Threat avoidance during Urban Air Mobility (UAM) and Low Altitude Mobility (LAM) flights is especially challenging due to their lower cruising altitudes. These operations may be exposed to buildings, towers, trees, terrain undulations, etc., along much of their flight route. Moreover, these low-altitude flights in urban environments are expected to encounter very busy airspace, increasing the workload associated with threat avoidance. The Proximity to Threat (PtT) function aims to support onboard or remote pilots by computing the risk from geospatial threats in the airspace along an aircraft’s flight path. The threats are both static entities and dynamic airspace restrictions that have been modeled and stored in geo-referenced mapping databases. The flight path may be specified by waypoints, airways, or similar discrete route elements or by a time series of closely spaced position and altitude points. Flight path uncertainty can also be taken into account by assuming both the position and altitude to be sampled from two normal distributions, each being specified by a mean and variance. PtT uses this additional information to verify that the flight path remains clear of threats along a wider path or if a position is reached earlier or later than anticipated, assuring the pilot or operator that there will be an available safety margin even if the aircraft deviates due to one or more occurrences of unexpected wind gusts, mechanical failures, airspeed changes, collision avoidance maneuvers, etc. The client can specify an uncertainty confidence level to bound the set of trajectories evaluated for threats so that the confidence level corresponds to the client’s risk tolerance under the expected conditions. PtT can be used as a pre-flight planning tool to determine a safe route through known threats and in-flight to avoid emerging or changing threats. In this report, we present the PtT function, discuss how the trajectory uncertainty is incorporated into the PtT function, and describe the use of this PtT function in a representative scenario.

urban air mobility↗
NASA NTRS2024

Performance of Two Battery Prognostic Applications used by Two Octocopters for Safe Low Altitude Autonomous Flight Operations

This paper addresses the problem of building trust in online predictions of the remaining available flying time for two different electric Unmanned Aerial Vehicles (eUAVs) powered by lithium-ion-polymer batteries. Flight tests for various automation research missions for the two vehicles were monitored using two on-board battery health management applications to make predictions of the remaining flying time (RFT) for each eUAV and to predict the state of the battery. Playback of the voltage, current and temperature profiles of the battery discharge were used to assess the accuracy of the estimation of the voltage and the charge states of the models as well as the estimate of the RFT. The reference ground truth values were the observed landing time and the measured battery pack resting pack voltage 20 minutes after the flight. The predicted RFT, state of charge (SoC), and state of energy (SoE) were compared with the observed results. Noise values of one standard deviation from the mean values of the internal charge states of the battery model during a reference run were used to vary the states during simulation. One application used an equivalent circuit model of the electrical dynamics of the battery pack, and the other application used a reduced-order electrochemistry model. The variation of the model state components was compared to the variation in the estimate of the RFT and the variation in the SoE to estimate a confidence factor. Variation in the estimates caused by factors affecting the off-line laboratory parameter identification experiments is considered. Variation in the estimates due to environmental factors are discussed.

Assurance↗
NASA NTRS1971

Layered 'recognition cone' networks that pre-process, classify, and describe.

A sequence of six types of pattern recognition system is examined. A program is described to illustrate some of the features developed. The first type (similar to many of the programs currently used) preprocesses by applying layers of local averaging and differencing transforms to smooth, fill in gaps and heighten contours, curves, and angles. It then applies a set of characterizers, each of which implies a set of names. The program chooses the single most high implied name. The second type combines the preprocessing transforms and the characterizers into a single operation of general type. Transforms build up a next representation of the input, while the characterizers imply the output name. The third type erases the distinction between a transform and an implication. Now all outputs are stored in the next transform layer. As the program averages information, its layers shrink, so that the system builds a cone of layers. When the program reaches the apex (a layer of only one cell that contains all the information), it chooses the single name with which it classifies the input. The fourth type is capable of choosing more than one name and, therefore, can both describe and classify the scene. The fifth type examines the interrelations among the set of names chosen. The sixth step can be taken to converse about the scene, developing an appropriate description in response to suggestions and queries. This allows the program to perform more computations and to look again on demand.

Uhr, L.↗
NASA NTRS1972

Development of an engineering model traveling wave tube amplifier for space communication systems

A design has been made of a 100 watt traveling-wave tube amplifier for use in space communication applications. The features of very high overall efficiency and heat rejection of waste heat at low thermal densities were predominant in the design concept. The design concept was proven by building a series of tubes, operating at efficiencies up to 50%. These tubes utilized heat pipe cooling and heat distribution such that 150 watts of waste heat was rejected at a density of less than 1.5 watts per square inch. A power supply to convert a 28 volt primary line of the needs of the TWT was built and operated at 85% efficiency.

Eallonardo, C. M.↗