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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Description of real-time Ada software implementation of a power system monitor for the Space Station Freedom PMAD DC testbed

The authors describe the Ada language software developed to perform the electrical power system monitoring functions for the NASA Lewis Research Center's Power Management and Distribution (PMAD) DC testbed. The results of the effort to implement this monitor are presented. The PMAD DC testbed is a reduced-scale prototype of the electric power system to be used in Space Station Freedom. The power is controlled by smart switches known as power control components (or switchgear). The power control components are currently coordinated by five Compaq 386/20e computers connected through an 802.4 local area network. The power system monitor algorithm comprises several functions, including periodic data acquisition, data smoothing, system performance analysis, and status reporting. Data are collected from the switchgear sensors every 100 ms, then passed through a 2-Hz digital filter. System performance analysis includes power interruption and overcurrent detection. The system monitor required a hardware timer interrupt to activate the data acquisition function. The execution time of the code was optimized by using an assembly language routine. The routine allows direct vectoring of the processor to Ada language procedures that perform periodic control activities.

Ludwig, Kimberly↗
NASA NTRS2014

Monitoring of Thermal Protection Systems and MMOD using Robust Self-Organizing Optical Fiber Sensing Networks

The general aim of this work is to develop and demonstrate a prototype structural health monitoring system for thermal protection systems that incorporates piezoelectric acoustic emission (AE) sensors to detect the occurrence and location of damaging impacts, such as those from Micrometeoroid Orbital Debris (MMOD). The approach uses an optical fiber Bragg grating (FBG) sensor network to evaluate the effect of detected damage on the thermal conductivity of the TPS material. Following detection of an impact, the TPS would be exposed to a heat source, possibly the sun, and the temperature distribution on the inner surface in the vicinity of the impact measured by the FBG network. A similar procedure could also be carried out as a screening test immediately prior to re-entry. The implications of any detected anomalies in the measured temperature distribution will be evaluated for their significance in relation to the performance of the TPS during reentry. Such a robust TPS health monitoring system would ensure overall crew safety throughout the mission, especially during reentry.

Fiber Optic Sensors↗
NASA NTRS2002

Monitor and control software for ground systems in the Deep Space Network

Currently, the NMC is being utilized for 24/7 operations at the three main DSN complexes supporting all of the major spacecraft supported and managed by JPL. A portable version of NMC is being exercised in a Compatibility Test Trailer for off-site monitor and control. Remote monitoring of the three complexes at JPL is accomplished as part of the NMC infrastructure.

monitor and control infrastructure spacecraft oper↗
NASA NTRS2013

Distributed Prognostics and Health Management with a Wireless Network Architecture

A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the prognostics task is over, and after appropriate actions have been taken, all CEs return to their original default configuration. Wireless technology-based implementation would ensure more flexibility in terms of sensor placement. It would also allow more sensors to be deployed because the overhead related to weights of wired systems is not present. Distributed architectures are furthermore generally robust with regard to recovery from node failures.

Goebel, Kai↗
NASA NTRS2021

Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands

The Twente region in the east of the Netherlands has a network with twenty soil monitoring stations that has been utilized for validation of the Soil Moisture Active/Passive (SMAP) passive-only soil moisture products. Over the period from April 2015 until December 2018, seven stations covered by the SMAP reference pixels 15 have fairly complete data records. Spatially distributed soil moisture simulations with the Dutch national hydrological model have been utilized for the development of upscaling functions to translate the spatial mean of point measurements to the domain of the SMAP reference pixels. The native and upscaled spatial soil moisture means computed using the in-situ measurements have been adopted as references to assess the performance of the SMAP i) Single Channel Algorithm at Horizontal Polarization (SCA-H), ii) Single Channel Algorithm at Vertical Polarization (SCA-V), and iii) Dual Channel Algorithm (DCA) soil moisture estimates. In the case of the Twente network it was found that the SCA-V soil moisture retrieved SMAP observations collected in the afternoon had the best agreement with the native spatial mean leading to an unbiased Root Mean Squared Error (uRMSE) of 0.059 m3 m-3, whereas for the upscaled in-situ references primarily larger biases were found. These error levels are larger than the mission’s target accuracy of 0.04 m3 m-3, which can be attributed to large over- and underestimation errors (>0.08 m3 m-3) in particular at the end of dry spells and during freezing, respectively. The strong vertical dielectric gradients associated with rapid soil freezing and wetting causes the disparity in soil depth characterized by SMAP and in situ that leads to the large mismatches. Once filtered for frozen conditions and antecedent rainfall the uRMSE improves to 0.043 m3 m-3.

Rogier van der Velde↗
NASA NTRS2010

Antenna Controller Replacement Software

The Antenna Controller Replacement (ACR) software accurately points and monitors the Deep Space Network (DSN) 70-m and 34-m high-efficiency (HEF) ground-based antennas that are used to track primarily spacecraft and, periodically, celestial targets. To track a spacecraft, or other targets, the antenna must be accurately pointed at the spacecraft, which can be very far away with very weak signals. ACR s conical scanning capability collects the signal in a circular pattern around the target, calculates the location of the strongest signal, and adjusts the antenna pointing to point directly at the spacecraft. A real-time, closed-loop servo control algorithm performed every 0.02 second allows accurate positioning of the antenna in order to track these distant spacecraft. Additionally, this advanced servo control algorithm provides better antenna pointing performance in windy conditions. The ACR software provides high-level commands that provide a very easy user interface for the DSN operator. The operator only needs to enter two commands to start the antenna and subreflector, and Master Equatorial tracking. The most accurate antenna pointing is accomplished by aligning the antenna to the Master Equatorial, which because of its small size and sheltered location, has the most stable pointing. The antenna has hundreds of digital and analog monitor points. The ACR software provides compact displays to summarize the status of the antenna, subreflector, and the Master Equatorial. The ACR software has two major functions. First, it performs all of the steps required to accurately point the antenna (and subreflector and Master Equatorial) at the spacecraft (or celestial target). This involves controlling the antenna/ subreflector/Master-Equatorial hardware, initiating and monitoring the correct sequence of operations, calculating the position of the spacecraft relative to the antenna, executing the real-time servo control algorithm to maintain the correct position, and monitoring tracking performance.

Chao, Roger Y.↗
DOE OSTI2025

rmon (Resource monitor) [SWR-24-128]

The resource monitor application provides monitoring, collection, and visualization of resource utilization in compute nodes. This package contains utilities to monitor system resource utilization (CPU, memory, disk, network). Here are the ways you can use it: -Monitor resource utilization for a compute node for a given set of resource types and process IDs. -Start a process and monitor its resource utilization. -Monitor resource utilization for a compute node asynchronously with the ability to dynamically change the resource types and process IDs being monitored. -Produce JSON reports of aggregated metrics. -Produce interactive HTML plots of the statistics.

Thom, Daniel [National Renewable Energy Laboratory↗
DOE OSTI2024

Notice of Submittal – 2023 Radionuclide Air Emissions Report for Los Alamos National Laboratory

This report describes the emissions of airborne radionuclides from operations at Los Alamos National Laboratory (LANL) for calendar year 2023 and the resulting off-site dose from these emissions. This document fulfills the requirements established by the National Emissions Standards for Hazardous Air Pollutants in 40 CFR 61, Subpart H – Emissions of Radionuclides other than Radon from Department of Energy Facilities, commonly referred to as the Radionuclide NESHAP or Rad-NESHAP. Compliance with this regulation and preparation of this document is the responsibility of LANL’s Rad NESHAP compliance program, which is part of the Environmental Protection and Compliance (EPC) Division. The information in this report is required under the Clean Air Act and is being submitted to the U.S. Environmental Protection Agency (EPA) Headquarters and EPA Region 6. The highest effective dose equivalent (EDE) to an off-site member of the public was calculated using procedures specified by the EPA and described in this report. LANL’s EDE was 0.43 for 2023. The annual limit is 10 millirem per year, established by the EPA in 40 CFR 61 Subpart H. All measured air emissions are modeled to a single location, known as the Maximally Exposed Individual (MEI). During calendar year 2023, LANL continuously monitored radionuclide emissions at 28 “major” release points, or stacks. The Laboratory estimates emissions from an additional 59 “minor” release points using radionuclide usage source terms in lieu of stack monitoring. Also, LANL uses an EPA approved network of air samplers around the Laboratory perimeter to monitor ambient airborne levels of radionuclides. To provide data for dispersion modeling and dose assessment, LANL maintains and operates several meteorological monitoring towers. From these various systems, a comprehensive evaluation is conducted to calculate the MEI dose for the Laboratory. The MEI can be any member of the public at any off-site location where there is a residence, school, business, or office. In 2023, this MEI location was a business at 129 New Mexico State Road 4 (NM-4), located in the northern end of White Rock. The primary contributors to the off-site dose at this location are the ambient air data at that location combined with the collected potential emissions from unmonitored (minor) sources. Overall, the MEI dose in 2023 is similar to that which has been observed in recent years, and it remains well below the EPA’s 10 millirem per year limit. Doses reported to the EPA for the past 10 years are shown in Table E1.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Use of the Delay-Tolerant Networking Bundle Protocol from Space

The Disaster Monitoring Constellation (DMC), constructed by Survey Satellite Technology Ltd (SSTL), is a multisatellite Earth-imaging low-Earth-orbit sensor network where captured image swaths are stored onboard each satellite and later downloaded from the satellite payloads to a ground station. Store-and-forward of images with capture and later download gives each satellite the characteristics of a node in a Delay/Disruption Tolerant Network (DTN). Originally developed for the Interplanetary Internet, DTNs are now under investigation in an Internet Research Task Force (IRTF) DTN research group (RG), which has developed a bundle architecture and protocol. The DMC is currently unique in its adoption of the Internet Protocol (IP) for its imaging payloads and for satellite command and control, based around reuse of commercial networking and link protocols. These satellites use of IP has enabled earlier experiments with the Cisco router in Low Earth Orbit (CLEO) onboard the constellation's UK-DMC satellite. Earth images are downloaded from the satellites using a custom IPbased high-speed transfer protocol developed by SSTL, Saratoga, which tolerates unusual link environments. Saratoga has been documented in the Internet Engineering Task Force (IETF) for wider adoption. We experiment with use of DTNRG bundle concepts onboard the UKDMC satellite, by examining how Saratoga can be used as a DTN convergence layer to carry the DTNRG Bundle Protocol, so that sensor images can be delivered to ground stations and beyond as bundles. This is the first successful use of the DTNRG Bundle Protocol in a space environment. We use our practical experience to examine the strengths and weaknesses of the Bundle Protocol for DTN use, paying attention to fragmentation, custody transfer, and reliability issues.

Wood, Lloyd↗
DOE OSTI2026

Optimizing infrasound observations for sample return capsule re-entry: Insights from OSIRIS-REx and Hayabusa2

The atmospheric entry of meteoroids presents a rare and unpredictable phenomenon, posing challenges for systematic observation and detailed characterization. Such events are nonetheless critical for advancing understanding of acoustic wave propagation, atmospheric structure, and entry dynamics. In contrast, sample return capsules (SRCs) from space missions follow well constrained re-entry trajectories, enabling planned observations of shock wave generation and propagation under controlled conditions. This study compares two SRC atmospheric entries, Hayabusa2 in 2020 and OSIRIS-REx in 2023, to assess how different infrasound array configurations influence shock wave detection and trajectory validation. Hayabusa2’s re-entry was monitored using a distributed network of 28 portable infrasound sensors across seven arrays in Woomera, Australia, permitting three-dimensional reconstruction of the trajectory and analysis of wave characteristics. For OSIRIS-REx, a compact four-sensor array deployed near Eureka Airport provided trajectory confirmation through arrival-time differences and back-azimuth estimates. Spectral and waveform analyses revealed differences in signal properties associated with variations in entry angle and velocity. The results illustrate both the strengths and the limitations of the deployed array configurations. The dense and distributed arrays during Hayabusa2’s re-entry enabled detailed trajectory reconstruction, whereas the compact array at Eureka primarily provided confirmation of signal coherence and back-azimuth consistency. These case studies highlight that even relatively small arrays, if located close to the predicted ground track, can still capture useful information on arrival direction and timing. Such insights provide practical guidance for planning future observational campaigns of SRC returns and other controlled atmospheric entries, and may also inform approaches to opportunistic observations of meteoroid events and other atmospheric acoustic phenomena.

celestial mechanics: orbit determination↗
DOE OSTI2026

Spot-Checking for Reliable Quantum Communications

We demonstrate a spot-checking approach for real-time drift estimation and mitigation in continuously operating quantum links. Using polarization-entangled photon pairs, we achieve stable 16-hour operation, validating efficient, minimally invasive monitoring of quantum-network performance.

Zhang, Yanbao [ORNL] (ORCID:0000000245530561)↗
DOE OSTI2024

LYNM PE1 Shot A Meteorology Team Technical Report

Weather support for Shot A was done by NOAA’s Air Resources Laboratory (ARL) / Special Operations and Research Division (SORD) and Lawrence Livermore National Laboratory (LLNL). Weather support activities included wind and precipitation forecasting, maintaining and monitoring PE1 meteorology towers MT02-11, maintaining and monitoring the ARL/SORD tower on Aqueduct Mesa (A12AI, also called MT01), maintaining and monitoring the Blackbrush energy flux tower, radiosonde preparation and launch, providing weather conditions on shot day for go/no-go criteria, and quality control and submission of the datasets. ARL/SORD additionally maintains and monitors the meteorological tower network (Mesonet) and sodar (at Desert Rock) for NNSS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Considering Multiple Realizations: Application to the Illinois Basin-Decatur Carbon Sequestration Project

We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site. Unlike the previous work, this study incorporates the impact of spatial heterogeneity using multiple realizations. In the proposed workflow, a neural network model utilizes available monitoring data such as downhole pressure measurements as input and predicts the propagating pressure ‘front’ using the diffusive time of flight (DTOF) map which is considered as representative reservoir image of the flow field. The DTOF is the arrival time of pressure front propagation, which can be computed by the Fast Marching Method rapidly without flow simulations. Reservoir model calibration can be implemented by selecting the training data samples that describe the predicted DTOF map based on observed data. The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project.

CO2 plume imaging↗
DOE OSTI2026

Firmware Tampering Detection in Heavy-Duty Vehicles through J1939 CAN Analysis

Modern heavy-duty vehicles rely on complex networks of Electronic Control Units (ECUs) that communicate using the J1939 protocol. While this system makes it easier to update and configure vehicle components, it also opens the door to serious cybersecurity risks if not properly secured. This work investigates the potential for firmware tampering through the J1939 communication protocol, which enables ECU configuration and reprogramming over the Controller Area Network (CAN) bus. By monitoring CAN traffic during legitimate maintenance operations and reverse-engineering OEM diagnostic software, we identified common and proprietary J1939 message identifiers, authentication patterns, and vulnerabilities within Unified Diagnostic Services (UDS). These findings demonstrate that inadequate authentication mechanisms can allow malicious actors to alter ECU firmware or disable safety functions, posing severe operational and safety risks. Our analysis contributes to the development of vehicle intrusion detection systems capable of recognizing abnormal reprogramming activity and future firmware fingerprinting methods to verify software integrity across ECUs. This work highlights the importance of standardizing secure firmware authentication across manufacturers to strengthen cyber resilience in heavy-duty vehicle systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Monitoring of Liquid Metal Reactor Heater Zones with Recurrent Neural Network Learning of Temperature Time Series

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F 1 score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F 1 scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively.

gated recurrent unit↗
NASA NTRS1973

ERTS Applications in earthquake research and mineral exploration in California

Examples that ERTS imagery can be effectively utilized to identify, locate, and map faults which show geomorphic evidence of geologically recent breakage are presented. Several important faults not previously known have been identified. By plotting epicenters of historic earthquakes in parts of California, Sonora, Mexico, Arizona, and Nevada, we found that areas known for historic seismicity are often characterized by abundant evidence of recent fault and crustal movements. There are many examples of seismically quiet areas where outstanding evidence of recent fault movements is observed. One application is clear: ERTS-1 imagery could be effectively utilized to delineate areas susceptible to earthquake recurrence which, on the basis of seismic data alone, may be misleadingly considered safe. ERTS data can also be utilized in planning new sites in the geophysical network of fault movement monitoring and strain and tilt measurements.

Abdel-Gawad, M.↗
NASA NTRS1977

Launch processing system transition from development to operation

The Launch Processing System has been under development at Kennedy Space Center since 1973. A prototype system was developed and delivered to Marshall Space Flight Center for Solid Rocket Booster checkout in July 1976. The first production hardware arrived in late 1976. The System uses a distributed computer network for command and monitoring and is supported by a dual large scale computer system for 'off line' processing. A high level of automation is anticipated for Shuttle and Payload testing and launch operations to gain the advantages of short turnaround capability, repeatability of operations, and minimization of operations and maintenance (O&M) manpower. Learning how to efficiently apply the system is our current problem. We are searching for more effective ways to convey LPS system performance characteristics from the designer to a large number of users. Once we have done this, we can realize the advantages of LPS system design.

Paul, H. C.↗
NASA NTRS1977

Application of remotely sensed land-use information to improve estimates of streamflow characteristics, volume 8

The author has identified the following significant results. Land use data derived from high altitude photography and satellite imagery were studied for 49 basins in Delaware, and eastern Maryland and Virginia. Applying multiple regression techniques to a network of gaging stations monitoring runoff from 39 of the basins, demonstrated that land use data from high altitude photography provided an effective means of significantly improving estimates of stream flow. Forty stream flow characteristic equations for incorporating remotely sensed land use information, were compared with a control set of equations using map derived land cover. Significant improvement was detected in six equations where level 1 data was added and in five equations where level 2 information was utilized. Only four equations were improved significantly using land use data derived from LANDSAT imagery. Significant losses in accuracy due to the use of remotely sensed land use information were detected only in estimates of flood peaks. Losses in accuracy for flood peaks were probably due to land cover changes associated with temporal differences among the primary land use data sources.

Pluhowski, E. J.↗