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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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NASA NTRS2010

Functional Fault Modeling of a Cryogenic System for Real-Time Fault Detection and Isolation

The purpose of this paper is to present the model development process used to create a Functional Fault Model (FFM) of a liquid hydrogen (L H2) system that will be used for realtime fault isolation in a Fault Detection, Isolation and Recover (FDIR) system. The paper explains th e steps in the model development process and the data products required at each step, including examples of how the steps were performed fo r the LH2 system. It also shows the relationship between the FDIR req uirements and steps in the model development process. The paper concl udes with a description of a demonstration of the LH2 model developed using the process and future steps for integrating the model in a live operational environment.

Ferrell, Bob↗

NASA NTRS1973

Video systems for real-time oil-spill detection

Three airborne television systems are being developed to evaluate techniques for oil-spill surveillance. These include a conventional TV camera, two cameras operating in a subtractive mode, and a field-sequential camera. False-color enhancement and wavelength and polarization filtering are also employed. The first of a series of flight tests indicates that an appropriately filtered conventional TV camera is a relatively inexpensive method of improving contrast between oil and water. False-color enhancement improves the contrast, but the problem caused by sun glint now limits the application to overcast days. Future effort will be aimed toward a one-camera system. Solving the sun-glint problem and developing the field-sequential camera into an operable system offers potential for color 'flagging' oil on water.

Millard, J. P.↗

DOE OSTI2025

AI-powered municipal solid waste management: a comprehensive review from generation to utilization

The accumulation of municipal solid waste (MSW) continues to rise due to burgeoning population, rapid global urbanization and economic growth, intensifying ecological concerns associated with landfills and greenhouse gas (GHG) emissions. Over the past 2 decades, global waste generation has surged by 50%, with one-third remaining uncollected and about 70% sent to landfills. This review examines the critical role of integrating emerging technologies, such as advanced sensors and artificial intelligence (AI), into end-to-end MSW management to alleviate landfill burdens. The suitability of various AI tools for different stages of MSW management is assessed, alongside the deployment of advanced sensors including hyperspectral cameras, computer vision systems, and internet of things (IoT) devices for material identification. Applications of genetic algorithms and reinforcement learning for optimizing collection routes, reducing costs, and lowering emissions are highlighted. Life cycle assessment (LCA) across all stages of MSW management is also reviewed, along with future trends in leveraging generative AI, natural language processing (NLP), and agent-based AI systems to analyze waste generation patterns and public sentiment. Efficient collection and handling can be enhanced through route optimization with geographic information systems and real-time bin-level monitoring. Furthermore, sensor-embedded, real-time object detection systems paired with robotics enable material characterization and automated sorting, thereby lowering costs and diverting waste from landfills into value-added products for diverse industrial sectors including packaging, chemicals, textiles, metals and glass, transportation, and electronics industries. Without intervention, global waste is projected to reach 4.54 billion tons by 2050, contributing direct economic costs of $\$$400 billion and roughly 2.38 billion tons of CO 2 -equivalent emissions annually. This review demonstrates how AI-driven, end-to-end solutions for MSW management can mitigate economic and environmental challenges, while directly supporting the United Nations Sustainable Development (UNDP) goals related to innovation and infrastructure (SDG 9), sustainable cities (SDG 11), responsible consumption and production (SDG 12), and climate action (SDG 13).

09 BIOMASS FUELS↗

NASA NTRS2004

A Real-Time Satellite-Based Icing Detection System

Aircraft icing is one of the most dangerous weather conditions for general aviation. Currently, model forecasts and pilot reports (PIREPS) constitute much of the database available to pilots for assessing the icing conditions in a particular area. Such data are often uncertain or sparsely available. Improvements in the temporal and areal coverage of icing diagnoses and prognoses would mark a substantial enhancement of aircraft safety in regions susceptible to heavy supercooled liquid water clouds. The use of 3.9 microns data from meteorological satellite imagers for diagnosing icing conditions has long been recognized (e.g., Ellrod and Nelson, 1996) but to date, no explicit physically based methods have been implemented. Recent advances in cloud detection and cloud property retrievals using operational satellite imagery open the door for real-time objective applications of those satellite datasets for a variety of weather phenomena. Because aircraft icing is related to cloud macro- and microphysical properties (e.g., Cober et al. 1995), it is logical that the cloud properties from satellite data would be useful for diagnosing icing conditions. This paper describes the a prototype realtime system for detecting aircraft icing from space.

Minnis, Patrick↗

NASA NTRS1979

Low-level processing for real-time image analysis

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Eskenazi, R.↗

DOE OSTI2020

Supporting Cyber Security of Power Distribution Systems by Detecting Differences Between Real-time Micro-Synchrophasor Measurements and Cyber-Reported SCADA (Final Report)

As modern power grids tend towards greater levels of automation and communication, the challenges of identifying and mitigating vulnerabilities to cyber-attacks are ones that are increasingly demanding attention. Today’s power system has evolved to form the foundational bedrock of modern society, and an attack on this infrastructure could prove disastrous. In this project we were tasked to investigate the use of distribution synchrophasors as an independent isolated sensor network with which we can corroborate, or flag potentially spoofed,Supervisory Control And Data Acquisition (SCADA) data. We adapted an approach to marry the underlying physical properties of power systems with the network communications used by power systems in order to offer insights unattainable by either data stream isolation. While the concept of intrusion detection systems (IDS) is well understood for monitoring network traffic and traditional IT computing systems, the approach discussed in this report is motivated by several key notions: first, current SCADA communications alone presents an incomplete view of the grid. Second, the power grid, and the equipment controlling it, is grounded by laws of physics. Given this, we leverage high-frequency physical grid measurements to understand the physical condition of the grid, and combine this with SCADA. While high-frequency physical grid measurements and SCADA communication over Internet Protocol (IP) networks are fundamentally disparate information sources, when collectively examined through appropriate lenses, they offer a much more nuanced depiction of the grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Exploring AI/ML-based Real-time Anomaly Detection in DUNE for Supernova Burst Neutrinos

The Deep Underground Neutrino Experiment (DUNE) is currently under construction with far detectors consisting of 4 liquid argon time projection chamber (LArTPC) modules at SURF (South Dakota Underground Research Facility) and a near detector complex with neutrino beam production at Fermilab to unambiguously determine neutrino mass ordering, to discover and precisely measure Charge-Parity (CP) violation phase in leptonic sector, to search for Beyond Stand Model (BSM) physics, and to study solar and supernova burst neutrinos. Anomalies in this project are classified in three categories: new physics signals, supernova burst neutrinos, and detector malfunction. We report here on promising early studies toward an Artificial Intelligence/Machine Learning-based real-time anomaly detection system, using a prototype autoencoder model currently under development. Additionally, the current status of an improved model and its performance will be presented. The model will be evaluated not only for its sensitivity to supernova neutrinos, but also to BSM physics signals and detector malfunctions. We will also consider how such a real-time algorithm might be used in DUNE.

de Jonge, Anselm [Kirchhoff Inst. Phys.] (ORCID:00↗

DOE OSTI2020

Accessible Real-Time Surveillance Radar System for Object Detection

As unmanned ground and aerial vehicles become more accessible and their usage covers a wider area of application, including for threatening purposes which can cause connected catastrophe, a surveillance system for the public places is being considered more essential to respond to those possible threats. We propose an inexpensive, lighter, safer, and smaller radar system than military-grade radar systems while keeping reasonable capability for use in monitoring public places. The paper details the iterative process on the system design and improvements with experiments to realize the system used for surveillance. The experiments show the practical use of the system and configuration for a better understanding of using the system. Cyber-physical systems for outdoor environments can benefit from the system as a sensor for sensing objects as well as monitoring.

47 OTHER INSTRUMENTATION↗

NASA NTRS1996

A Leak Monitor for Industry

GenCorp Aerojet Industrial Products, Lewis Research Center, Marshall Space Flight Center, and Case Western Reserve University developed a gas leak detection system, originally for use with the Space Shuttle propulsion system and reusable launch vehicles. The Model HG200 Automated Gas Leak Detection System has miniaturized sensors that can identify extremely low concentrations of hydrogen without requiring oxygen. A microprocessor-based hardware/software system monitors the sensors and displays the source and magnitude of hydrogen leaks in real time. The system detects trace hydrogen around pipes, connectors, flanges and pressure tanks, and has been used by Ford Motor Company in the production of a natural gas-powered car.

Source record↗

NASA NTRS2006

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Adler, Robert F.↗

DOE OSTI2024

A portable and reusable sensor system based on graphene for real-time and sensitive detection of lead ions in water

Long-term exposure to Pb 2+ can cause irreversible damage to the nervous, cardiovascular, and reproductive systems. Therefore, developing a fast and sensitive detection system capable of monitoring minuscule concentrations of Pb 2+ is essential. In this study, we demonstrated a fully portable sensor system enabling rapid, sensitive, and real-time monitoring of Pb 2+ . The sensor system adopted the remote-gate field-effect transistor (RGFET) detection scheme and was easy to operate, even for non-experts. The sensor system comprised two printed circuit boards (PCBs): a sensor PCB with a remote-gate electrode and an analyzer PCB with a metal-oxide-semiconductor field-effect transistor (MOSFET) transducer and peripheral electronics to manage sensor signals. To achieve a high sensitivity for Pb 2+ , we utilized graphene ink drop-casted on the sensor PCB as a sensing membrane. The graphene film was easy to deposit and remove, enabling the sensor PCB to be reused multiple times. The sensor system was further linked to a smartphone application that instantly monitors the sensor response, allowing for rapid point-of-use detection. The sensor exhibited a high sensitivity of 21.7% when the limit of detection (LOD) value of 1 nM (∼0.2 ppb) was detected, and the typical detection time for each sample was approximately 60 seconds. This portable sensor system advances sensing technologies and could potentially supplement expensive, laborious conventional sensing equipment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Cybersecurity Challenges in Low-Inertia Power-Electronics-Dominated Grids

Here, the low inertia characteristics of the power electronics dominated grid (PEDG) introduces challenges while restoring voltage and frequency to their nominal values. These stability challenges create new cybersecurity vulnerabilities that are not thoroughly discussed in the literature. Cyber events such as false data injection (FDI), denial of service (DoS), man-in-the-middle attacks, stealthy attacks, and advanced persistent threats target PEDG to disrupt grid stability or gain financial benefits. The low inertia of PEDG (< 2s) compared to traditional grids (~10s) exacerbates these vulnerabilities. In response to stealthy attacks on state variables that supervisory layers cannot detect until significant harm occurs, the low inertia characteristics of PEDG offer substantial stealthy attack surfaces. To counteract such threats, PEDG must be equipped with ultra-fast real-time anomaly detection system and trajectory prediction mechanism to achieve effective cyberattack resiliency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1978

Spaceborne ranging system

A spaceborne laser ranging system is described that could survey a large network of ground reflectors, and provide their relative locations to a precision of + or - 1 cm. This performance is believed realizable for networks covering up to 10 to 6th power square kilometers and from only a few days of observations. This system could be used to monitor crustal movements in many areas of the world and has the potential to provide an almost real-time system for detecting precursory ground motions before large earthquakes.

Smith, D. E.↗

NASA NTRS1981

RAMP - A fault tolerant distributed microcomputer structure for aircraft navigation and control

Design methodologies for realizing future high authority autoflight control systems are being investigated, taking into account also the study of distributed microcomputer architectures. Attention is given to the redundant asynchronous microprocessor (RAMP) structure. RAMP comprises a connected network of microcomputers which has as input command and sensor information, and which generates servo information to drive actuators, and thrust linkages. Tolerance to hardware failures is achieved by static redundancy. Results of a failed microcomputer are simply rejected. This is done in lieu of dynamic redundancy wherein the distributed computer system performs real time fault detection and reconfiguration of the system. Attention is given to the RAMP network structure and operation, flight control with parallel asynchronous computers, and intermittent fault tolerance.

Dunn, W. R.↗

NASA NTRS1998

The Intensity Distribution of Faint Gamma-Ray Bursts Detected with BATSE

We have recently completed a search of 6 years of archival Burst and Transient Source Experiment (BATSE) data for gamma-ray bursts (GRBS) that were too faint to activate the real-time burst detection system running onboard the spacecraft. These "non-triggered" bursts can be combined with the "triggered" bursts detected onboard to produce a GRB intensity distribution that reaches peak fluxes a factor of approximately 2 lower than could be studied previously. The value of the (V/V(max)) statistic (in Euclidean space) for the bursts we detect is 0.177 +/- 0.006. This surprisingly low value is obtained because we detected very few bursts on the 4.096 s and 8.192 s time scales (where most bursts have their highest signal-to-noise ratio) that were not already detected on the 1.024 s time scale. If allowance is made for a power-law distribution of intrinsic peak luminosities, the extended peak flux distribution is consistent with models in which the redshift distribution of the gamma-ray burst rate approximately traces the star formation history of the Universe. We argue that this class of models is preferred over those in which the burst rate is independent of redshift. These results lend support to the conclusions of previous studies predicting that relatively few faint bursts are waiting to be found below the BATSE onboard detection threshold.

Kommers, Jefferson↗

NASA NTRS2000

The Intensity Distribution of Faint Gamma-Ray Bursts Detected with BATSE

We have recently completed a search of 6 years of archival BATSE data for gamma-ray bursts (GRBS) that were too faint to activate the real-time burst detection system running on board the spacecraft. These "nontriggered" bursts can be combined with the "triggered" bursts detected on board to produce a GRB intensity distribution that reaches peak fluxes a factor of approximately 2 lower than could be studied previously. The value of the statistic (in Euclidean space) for the bursts we detect is 0.177 plus or minus 0.006. This surprisingly low value is obtained because we detected very few bursts on the 4.096 s and 8.192 s timescales (where most bursts have their highest signal-to-noise ratio) that were not already detected on the 1.024 s timescale. If allowance is made for a power-law distribution of intrinsic peak luminosities, the extended peak flux distribution is consistent with models in which the redshift distribution of the gamma-ray burst rate approximately traces the star formation history of the universe. We argue that this class of models is preferred over those in which the burst rate is independent of redshift. We use the peak flux distribution to derive a limit of 10% (99% confidence) on the fraction of the total burst rate that could be contributed by a spatially homogeneous (in Euclidean space) subpopulation of burst sources, such as type lb/c supernovae. These results lend support to the conclusions of previous studies predicting that relatively few faint "classical" GRBs will be found below the BATSE onboard detection threshold.

Kommers, Jefferson M.↗

NASA NTRS2000

The Intensity Distribution of Faint Gamma-Ray Bursts Detected with BATSE

We have recently completed a search of six years of archival Burst and Transient Source Experiment (BATSE) data for gamma-ray bursts (GRBs) that were too faint to activate the real-time burst detection system running on board the spacecraft. These 'nontriggered' bursts can be combined with the 'triggered' bursts detected on board to produce a GRB intensity distribution that reaches peak fluxes a factor of approximately two lower than could be studied previously. The value of the statistic (in Euclidean space) for the bursts we detect is 0.177 +/- 0.006. This surprisingly low value is obtained because we detected very few bursts on the 4.096 s and 8.192 s timescales (where most bursts have their highest signal-to-noise ratio) that were not already detected on the 1.024 s timescale. If allowance is made for a power-law distribution of intrinsic peak luminosities, the extended peak flux distribution is consistent with models in which the redshift distribution of the gamma-ray burst rate approximately traces the star formation history of the universe. We argue that this class of models is preferred over those in which the burst rate is independent of redshift. We use the peak flux distribution to derive a limit of 10% (99% confidence) on the fraction of the total burst rate that could be contributed by a spatially homogeneous (in Euclidean space) subpopulation of burst sources, such as type Ib/c supernovae. These results lend support to the conclusions of previous studies predicting that relatively few faint 'classical' GRBs will be found below the BATSE onboard detection threshold.

Kommers, Jefferson M.↗

NASA NTRS2008

Reconfigurable Processing for Satellite On-Board Automatic Cloud Cover Assessment (ACCA)

Clouds have a critical role in many studies such as weather- and climate-related investigations. However, they represent a source of errors in many applications, and the presence of cloud contamination can hinder the use of satellite data. In addition, sending cloudy data to ground stations can result in an inefficient utilization of the communication bandwidth. This requires satellite on-board cloud detection capability to mask out cloudy pixels from further processing. Remote sensing satellite missions have always required smaller size, lower cost, more flexibility, and higher computational power. Reconfigurable Computers (RCs) combine the flexibility of traditional microprocessors with the power of Field Programmable Gate Arrays (FPGAs). Therefore, RCs are a promising candidate for on-board preprocessing. This paper presents the design and implementation of an RC-based real-time cloud detection system. We investigate the potential of using RCs for on-board preprocessing by prototyping the Landsat 7 ETM+ ACCA algorithm on one of the state-of-the-art reconfigurable platforms, SRC-6. It will be shown that our work provides higher detection accuracy and over one order of magnitude improvement in performance when compared to previously reported investigations.

El-Araby, Esam↗