SEARCH · Search NASA

Results for “Advanced condition monitoring”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23

All sources NASA NTRS DOE OSTI

DOE OSTI2021

In-situ Investigations on Gold Nanoparticles Stabilization Mechanisms in Biological Environments Containing HSA

Nanoparticles (NPs) developments advance innovative biomedical applications. However, complex interactions and the low colloidal stability of NPs in biological media restrict their widespread utilization. The influence of NPs properties on the colloidal stability for gold NPs with 5 and 40 nm in diameter with two surface modifications, methoxy-polyethylene glycol-sulfhydryl (PEG) and citrate, in NaCl and human serum albumin (HSA) protein solution, is investigated. This study is based on small-angle X-ray scattering (SAXS) methods allowing the in-situ monitoring of interactions in physiological conditions. The PEG coating provides high colloidal stability for NPs of both sizes. For 5 nm NPs in NaCl solution, a stable 3D self-assembled body-centered cubic (BCC) arrangement is detected with an interparticle distance of 20.7 ± 0.1 nm. In protein solution, this distance increases to 21.9 ± 0.1 nm by protein penetration inside the ordered structure. For citrate-capped NPs, a different mechanism is observed. The protein particles attach to the NPs surfaces, and an appropriate concentration of proteins results in a stable suspension. Cryogenic transmission electron microscopy (Cryo-TEM), UV–visible spectroscopy, and dynamic light scattering (DLS) support the SAXS results. The findings will pave the way to design and synthesize NPs with controlled behaviors in biomedical applications.

36 MATERIALS SCIENCE↗

NASA NTRS2013

Autonomous Control of Space Nuclear Reactors

Nuclear reactors to support future robotic and manned missions impose new and innovative technological requirements for their control and protection instrumentation. Long-duration surface missions necessitate reliable autonomous operation, and manned missions impose added requirements for failsafe reactor protection. There is a need for an advanced instrumentation and control system for space-nuclear reactors that addresses both aspects of autonomous operation and safety. The Reactor Instrumentation and Control System (RICS) consists of two functionally independent systems: the Reactor Protection System (RPS) and the Supervision and Control System (SCS). Through these two systems, the RICS both supervises and controls a nuclear reactor during normal operational states, as well as monitors the operation of the reactor and, upon sensing a system anomaly, automatically takes the appropriate actions to prevent an unsafe or potentially unsafe condition from occurring. The RPS encompasses all electrical and mechanical devices and circuitry, from sensors to actuation device output terminals. The SCS contains a comprehensive data acquisition system to measure continuously different groups of variables consisting of primary measurement elements, transmitters, or conditioning modules. These reactor control variables can be categorized into two groups: those directly related to the behavior of the core (known as nuclear variables) and those related to secondary systems (known as process variables). Reliable closed-loop reactor control is achieved by processing the acquired variables and actuating the appropriate device drivers to maintain the reactor in a safe operating state. The SCS must prevent a deviation from the reactor nominal conditions by managing limitation functions in order to avoid RPS actions. The RICS has four identical redundancies that comply with physical separation, electrical isolation, and functional independence. This architecture complies with the safety requirements of a nuclear reactor and provides high availability to the host system. The RICS is intended to interface with a host computer (the computer of the spacecraft where the reactor is mounted). The RICS leverages the safety features inherent in Earth-based reactors and also integrates the wide range neutron detector (WRND). A neutron detector provides the input that allows the RICS to do its job. The RICS is based on proven technology currently in use at a nuclear research facility. In its most basic form, the RICS is a ruggedized, compact data-acquisition and control system that could be adapted to support a wide variety of harsh environments. As such, the RICS could be a useful instrument outside the scope of a nuclear reactor, including military applications where failsafe data acquisition and control is required with stringent size, weight, and power constraints.

Merk, John↗

DOE OSTI2024

The Fuel Motion Monitoring System at TREAT - Current Status and Future Plans

An important component of the United States Nuclear Fuel Safety Transient Testing Program, the Fuel Motion Monitoring System (FMMS) at Idaho National Laboratory's Transient Reactor Test Facility (TREAT) is fast-neutron hodoscope capable of imaging the location, movement, and relocation of nuclear fuel experiments under simulated transient accident conditions. The FMMS was refurbished in parallel with the TREAT restart program starting in 2014, restoring 96-channels of fast-neutron detection. Since returning to operation in 2017 the FMMS has supported many fuel safety experiments supporting accident tolerant fuel development, light-water reactor safety, space thermal nuclear propulsion fuel development, and advanced reactor research and development. In Phase 2 of the FMMS restoration. work is now under way to expand the FMMS' field-of-view by adding an additional 96 channels of fast neutron detectors to the system's hodoscope, along with an expanded data acquisition system and associated transient timing electronics. An overview of the FMSS system and its fast-neutron detectors will be presented along with examples of current FMMS imaging performance and associated information.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2021

AGR 5/6/7 Data Qualification Report for ATR Cycles 162B through 168A

This report provides the qualification status of experimental data for the Advanced Gas Reactor (AGR) 5/6/7 fuel irradiation. AGR-5/6/7 was conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The objectives of the AGR-5/6/7 experiments are to: (i) irradiate reference-design fuel particles to support fuel qualification, (ii) establish operating margins for the fuel beyond normal operating conditions, and (iii) provide irradiated-fuel performance data and irradiated-fuel samples for post-irradiation examination (PIE) and safety testing. The test train contains five separate capsules that were independently controlled and monitored. Each capsule contains multiple 12.51-mm-long compacts filled with low enriched uranium carbide/oxide (UCO) TRISO fuel particles. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) is to verify successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions in support of plant design and licensing. AGR 5/6/7 will also provide irradiated-fuel performance data on fission-gas release from failed particles during irradiation. The AGR-5/6/7 capsules were irradiated in the ATR northeast flux trap location. The experiment began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of 360.9 effective full power days. The AGR 5/6/7 experiment was able to remain in the reactor core during all three Powered Axial Locator Mechanism (PALM) cycles (163A, 165A, and 167A) without overheating its fuel compacts. This report includes irradiation monitoring data from nine ATR Cycles: 162B, 163A, 164A, 164B, 165A, 166A, 166B, 167A, and 168A, as stored in the Nuclear Data Management and Analysis System (NDMAS). During irradiation, data records consisted of instantaneous measurements recorded every minute and provided by text files automatically every 2 hours. The AGR 5/6/7 data streams addressed in this report include thermocouple (TC) temperatures, sweep gas data (flow rates [capsule inlet, outlet, and downstream at detector], pressure, and moisture content), and Fission Product Monitoring System (FPMS) data (release rates and release to birth rate ratios [R/Bs]) for each of the five capsules. A total of 94,989,908 TC temperature and sweep gas data records were received and processed by NDMAS for AGR 5/6/7 irradiation. Of these records, 41,593,387 (or 43.7% of the total) met data collection and accuracy requirements and are labeled as Qualified. A total of 57,746,693 TC temperature readings were captured from 54 installed TCs. Among them, 10,034,676 TC temperature records (only 17.4%) were Qualified and 47,701,371 TC temperatures (or 82.6%) are Failed due to 48 TC failures (63.5%) and due to missing values (19.1%). To assess performance of the operational TCs, analysis of daily correlations between TCs found no evidence of virtual junction failure for any TCs. Analyses on control charts of TC temperature differences revealed trending in TC readings for TC2, 4, 5, and 13 in Capsule 3, but there is no conclusive indication of TC drift failure that caused those trends. Therefore, TC control charts are not used to disqualify TC data, but only for users’ consideration. For sweep gas flow rates, a total of 31,519,747 gas flow records (84.4%) are Qualified for use for AGR-5/6/7 experiment; 5,723,468 gas flow records (15.4%) are Failed due mostly to missing values; and 74,641 high sweep gas flow rates (0.2 %) are Trend. A large number of Failed missing TC temperature and gas flow values were caused by an error in the data output script that outputted a ‘NULL’ value when values were unchanged. This problem was fixed during the outage of Cycle 166B, which led to a substantially decreased number of missing values during the last three cycles. Nonetheless, a large amount of non-missing data remained because of the high data acquisition frequency (1-minute) and still provided sufficient data to effectively monitor the experiment as designed. For FPMS data, NDMAS received and processed fission product release and R/B data for nine ATR cycles, when ATR core reached full power during AGR 5/6/7 irradiation. These data consist of 110,388 release rate records and 110,388 R/B records for the twelve radionuclides (Kr 85m, Kr 87, Kr 88, Kr 89, Kr 90, Xe 131m, Xe 133, Xe 135, Xe 135m, Xe 137, Xe 138, and Xe 139) for each of the five capsules. Equivalent numbers of uncertainty records associated the release rates and R/B values were provided. To date, qualification status of the FPMS data stored in the NDMAS dat

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Development of Mockups and Instrumentation for Spent Fuel Drying Tests

The purpose of this report is to provide updates on the experimental components, methodology, and instrumentation under development for use in advanced studies of realistic drying operations conducted on surrogate spent nuclear fuel. Validation of the extent of water removal in a dry spent nuclear fuel storage system based on drying procedures used at nuclear power plants is needed to close existing technical gaps. Operational conditions leading to incomplete drying may have potential impacts on the fuel, cladding, and other components in the system. Water remaining in canisters upon completion of drying procedures can lead to cladding corrosion, embrittlement, and breaching, as well as fuel degradation. Additional information is needed on the drying process efficacy to help evaluate the potential impacts of water retention on extended longterm dry storage. A general lack of data suitable for model validation of commercial nuclear canister drying processes necessitates additional, well-designed investigations. Smaller-scale tests that incorporate relevant physics and well-controlled boundary conditions are essential to provide insight and guidance to the simulation of prototypic systems undergoing drying processes. This report describes the implementation of moisture monitoring equipment on a pressurized, submersible system employing a single waterproof, electrically heated spent fuel rod simulator as a demonstration of analytical capabilities during a drying process. A mass spectrometer with specially designed inlets was used to monitor moisture and other gases at 150 kPa to 800 kPa for a test simulating a forced helium dehydration procedure and below 1 torr for tests mimicking a vacuum drying process. The dew point data from the mass spectrometer was found to be in good agreement with a solid-state moisture probe. A distinct advantage of the mass spectrometer system was the capability to directly sample from the hightemperature (>200 °C) head space expected in a prototypic scale experiment where a solid-state moisture probe would suffer considerable loss of accuracy or fail altogether. The operational and analytical experiences gained from this test series are poised to support an expansion to assembly-scale tests at prototypic length. These assemblies are designed to feature prototypic assembly hardware, advanced diagnostics for in situ internal rod pressure monitoring, and failed fuel rod simulators with engineered cladding defects to challenge the drying system with waterlogged fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Enabling the Next Generation of Smart Sensors in Coal Fired Power Plants using Cellular 5G Technology

An important need for coal fired power plants is the ability to monitor multiple systems with ease and accuracy. Common implementations of these monitoring systems come with drawbacks due to the nature of coal fired power plants. Harsh environments, High Temperatures, and lots of RF (Radio Frequency) noise can create issues for accurately recording and transmitting data across wireless signals. In addition, as renewable energy sources come online, existing fossil fueled plants will need to operate more flexibly with their maintenance schedules outside of standard conditions. Therefore, additional sensing and control mechanisms need placed in existing plants to provide operators with more information such that maintenance decisions can be made well in advance of failures. A solution to this problem is the Next Generation of Smart Sensors, which leverages the power of 5G cellular signals and machine learning to overcome the myriad of problems with current implementations

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS2010

Use of MODIS Terra Imagery to Estimate Surface Water Quality Standards, Using Lake Thonotosassa, Florida, as a Case Study

Lake Thonotosassa is a highly eutrophied lake located in an area with rapidly growing population in the Tampa Bay watershed, Florida. The Florida Administrative Code has designated its use for "recreation, propagation and maintenance of a healthy, well-balanced population of fish and wildlife." Although this lake has been the subject of efforts to improve water quality since 1970, overall water quality has remained below the acceptable state standards, and has a high concentration of nutrients. This condition is of great concern to public health since it has favored episodic blooms of Cyanobacteria. Some Cyanobacterial species release toxins that can reach humans through drinking water, fish consumption, and direct contact with contaminated water. The lake has been historically popular for fishing and water sports, and its overflow water drains into the Hillsborough River, the main supply of municipal water for the City of Tampa, this explains why it has being constantly monitored in situ for water quality by the Environmental Protection Commission of Hillsborough County (EPC). Advances in remote sensing technology, however, open the possibility of facilitating similar types of monitoring in this and similar lakes, further contributing to the implementation of surveillance systems that would benefit not just public health, but also tourism and ecosystems. Although traditional application of this technology to water quality has been focused on much larger coastal water bodies like bays and estuaries, this study evaluates the feasibility of its application on a 46.6 km2 freshwater lake. Using surface reflectance products from Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra, this study evaluates associations between remotely sensed data and in situ data from the EPC. The parameters analyzed are the surface water quality standards used by the State of Florida and general indicators of trophic status.

Moreno, Max J.↗

DOE OSTI2023

Preliminary Development of Heat Transfer Model-Based Control Algorithms of Liquid Sodium Purification System: Advanced Sensors and Instrumentation Advanced Controls

Monitoring the operation of sodium purification system is essential for efficient operation of sodium fast reactors. In this work, a heat transfer model has been developed for monitoring the plugging meter and cold trap systems at the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The model of the purification system was developed by treating the respective aspects of the cold trap purification loop and plugging meter diagnostic loop as two separate control volumes using information from the METL piping and instrumentation diagram (P&ID). A model predictive controller was designed using first order differential equations with the specified boundary conditions. The system behavior was studied with a tuned optimized procedure using the internal cold trap temperature and plugging meter outlet temperature as control variables, and the air blower temperature as an independent variable respectively. Results of computer simulations obtained in this study compared favorably with experimental data showing very good reference tracking response with negligible overshoot as both plugging meter and cold trap physical models approach the setpoint.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Embedded Sensing in Additive Manufacturing Metal and Polymer Parts: A Comparative Study of Integration Techniques and Structural Health Monitoring Performance

This study presents a comparative evaluation of post-process sensor integration in additively manufactured (AM) metal and the in-situ process for polymer structures for structural health monitoring (SHM), with an emphasis on embedded sensors. Geometrically identical specimens were fabricated using copper via metal fused filament fabrication (FFF) and PLA via polymer FFF, with piezoelectric transducers (PZTs) inserted into internal cavities to assess the influence of material and placement on sensing fidelity. Mechanical testing under compressive and point loads generated signals that were transformed into time–frequency spectrograms using a Short-Time Fourier Transform (STFT) framework. An engineered RGB representation was developed, combining global amplitude scaling with an amplitude-envelope encoding to enhance contrast and highlight subtle wave features. These spectrograms served as inputs to convolutional neural networks (CNNs) for classification of load conditions and detection of damage-related features. Results showed reliable recognition in both copper and PLA specimens, with CNN classification accuracies exceeding 95%. Embedded PZTs were especially effective in PLA, where signal damping and environmental sensitivity often hinder surface-mounted sensors. This work demonstrates the advantages of embedded sensing in AM structures, particularly when paired with spectrogram-based feature engineering and CNN modeling, advancing real-time SHM for aerospace, energy, and defense applications.

additive manufacturing↗

DOE OSTI2021

Mid Infra-Red Laser Sensor for Continuous Sulfur Trioxide Monitoring to Improve Coal-Fired Power Plant Performance during Flexible Operations

During the course of this project, we performed exhaustive research and development of SO3/H2SO4 sensing technology for coal-fired power plant applications (Figure 1). The development culminated in a successful field campaign of a prototype continuous real-time H2SO4 monitor at a coal-fired power plant (TRL 6) accomplishing the primary goal of the project. The developed sensors utilize tunable laser absorption spectroscopy (TLAS) operating in the mid-infrared (Mid-IR) wavelength region, which is the so-called “molecular fingerprint” region. Systems operating in the Mid-IR have orders of magnitude more sensitivity than systems operating at shorter wavelengths, such as near-infrared (NIR). However, NIR systems are more widespread due to more mature supporting technology (e.g., fiber optics, optical components, etc.). In this project, we not only produced a specific Mid-IR sensor, we also advanced Mid-IR sensor technology in general through the development and demonstration of such supporting technology. In this project, we also developed proprietary broad tuning lasers enabling the ability to effectively measure SO3, H2SO4, H2O, and SO2. Different molecular species have unique spectral signatures that can be probed with lasers operating at different wavelengths. Standard TLAS uses relatively narrow wavelength tuning distributed feedback (DFB) lasers, which can typically only target a single species with narrow features, and are not appropriate for species with broad features, such as SO3 or H2SO4. In contrast, by developing unique, broad-tuning laser technology, we were able to measure these species, as well as SO2 and H2O simultaneously. Furthermore, to enable real-time analysis at a power plant, we modified a commercially available heated gas cell to operate in the Mid-IR wavelength range and fiber coupled the lasers to enable remote delivery of the beams. To generate reference data (library spectra), our collaborators at the University of California Irvine (UCI) developed a catalytic SO3 generation facility. It is worth mentioning that representative H2SO4 and SO3 Mid-IR spectra are not a part of any publicly available database and the data generated under this project is a valuable resource in and of itself. In addition, based on the UCI study we determined that detection of SO3 is complicated by the very strong SO2 absorption. For that reason, we concentrated on H2SO4 detection. Since SO3 and H2SO4 exist in a flue gas in a state of equilibrium, which depends on temperature and humidity, by measuring water concentration and controlling the temperature of the gas cell, we developed an approach to determine SO3 concentration from the H2SO4 measurement. During the development phase of the project, we performed three testing campaigns at our collaborator’s FERCo flue gas facility with conditions representative of the coal-fired power plant (~ 40ppm SO3, 1700ppm to 2800 ppm SO2, 10% water) with the exception of particulate matter. After three test campaigns at FERCo we performed field testing at Harrison Power Station. The final system was mounted on a duct and measured H2SO4, SO2 and water. The tests were highly successful with a demonstrated real-time H2SO4 precision of 1 ppm with a 1 second update. Our collaborators at EPRI conducted an industry survey and determined that there is a very high interest for the SO3/H2SO4 monitoring in the power generation industry as well as in heavy industries in general. Furthermore, work performed by OptoKnowledge beyond the scope of this project under a synergistic DOE SBIR determined another approach to SO3 detection. We applied for Phase II on this SBIR for development a of versatile SO3/H2SO4 sensor but were not selected. We are currently looking for another opportunity to leverage all the technological advancements produced by this project including but not limited to the flue gas facility at UCI, the hardware and software developed, and relationships with FERCo, EPRI CEMTEK, and Harrison Station.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Photovoltaic System Health-State Architecture for Data-Driven Failure Detection

The timely detection of photovoltaic (PV) system failures is important for maintaining optimal performance and lifetime reliability. A main challenge remains the lack of a unified health-state architecture for the uninterrupted monitoring and predictive performance of PV systems. To this end, existing failure detection models are strongly dependent on the availability and quality of site-specific historic data. The scope of this work is to address these fundamental challenges by presenting a health-state architecture for advanced PV system monitoring. The proposed architecture comprises of a machine learning model for PV performance modeling and accurate failure diagnosis. The predictive model is optimally trained on low amounts of on-site data using minimal features and coupled to functional routines for data quality verification, whereas the classifier is trained under an enhanced supervised learning regime. The results demonstrated high accuracies for the implemented predictive model, exhibiting normalized root mean square errors lower than 3.40% even when trained with low data shares. The classification results provided evidence that fault conditions can be detected with a sensitivity of 83.91% for synthetic power-loss events (power reduction of 5%) and of 97.99% for field-emulated failures in the test-bench PV system. Finally, this work provides insights on how to construct an accurate PV system with predictive and classification models for the timely detection of faults and uninterrupted monitoring of PV systems, regardless of historic data availability and quality. Such guidelines and insights on the development of accurate health-state architectures for PV plants can have positive implications in operation and maintenance and monitoring strategies, thus improving the system’s performance.

photovoltaics↗

NASA NTRS1982

The pilot's role in manned space flight

The present investigation regarding the pilot's role in manned space flight takes into account space missions conducted with the Mercury capsule, Gemini, Apollo, Skylab, and the Shuttle. It is concluded that advancements in digital systems and automation technology have made many of the space pilot's tasks easier. However, these advancements have also made the space pilot's training more complicated. He must be familiar with the interrelated failure effects in highly complex vehicle systems. The nominal performance of the Shuttle fly-by-wire entry control system depends, for instance, on nominal electrical power from three fuel cells, nominal performance of three hydraulic auxiliary power units, five computers, other equipment, and microwave landing systems. The pilot must monitor and manage failures in these systems, and, in addition, must be prepared to intervene if an abort situation creates off-nominal conditions.

North, W. J.↗

NASA NTRS2010

Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

Bolten, John D.↗

NASA NTRSDate not supplied

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

As part of its research, NASA investigates concepts, aircraft, and operations related to Advanced Air Mobility (AAM). One of the most challenging scenarios for AAM will be enabling safe routine access near densely populated urban centers. AAM flight operations over a regional area require a moderately high-fidelity simulation capability to develop and evaluate autonomy technologies in the urban environment. This paper aims to describe a system to simulate flight operations around regions such as the San Francisco-Oakland Bay area at a moderately-high scale (tens to hundreds of flights) that incorporates detailed vehicle models and control necessary to support research in airborne autonomy. The flight vehicle utilizes NASA AAM concept vehicle dynamics integrated with a custom flight management system and flight control system to simulate all flight phases accurately. The simulation incorporates a detailed simulated urban environment and includes glass cockpit displays to monitor aircraft operations. Simulation models integrate to simulate air and ground-based sensors, such as Radar and LiDAR. As a commercially available rendering engine, X-Plane 11 is used as the renderer to simulate vision-based sensors (such as onboard and ground-based cameras) with a detailed graphical model of a city at different times of the day and weather conditions. This paper presents the simulation and software architecture used for simulating AAM traffic over this urban region. This system enables the evaluation of NASA research concepts in autonomy for urban AAM operations on the path toward flight test evaluation.

distributed sensing↗

NASA NTRSDate not supplied

A Simulation Architecture for Air Traffic Over Urban Environments Supporting Autonomy Research in Advanced Air Mobility

Distributed sensing↗

NASA NTRS1990

Cardiac Imaging System

Although not available to all patients with narrowed arteries, balloon angioplasty has expanded dramatically since its introduction with an estimated further growth to 562,000 procedures in the U.S. alone by 1992. Growth has fueled demand for higher quality imaging systems that allow the cardiologist to be more accurate and increase the chances of a successful procedure. A major advance is the Digital Cardiac Imaging (DCI) System designed by Philips Medical Systems International, Best, The Netherlands and marketed in the U.S. by Philips Medical Systems North America Company. The key benefit is significantly improved real-time imaging and the ability to employ image enhancement techniques to bring out added details. Using a cordless control unit, the cardiologist can manipulate images to make immediate assessment, compare live x-ray and roadmap images by placing them side-by-side on monitor screens, or compare pre-procedure and post procedure conditions. The Philips DCI improves the cardiologist's precision by expanding the information available to him.

Source record↗

NASA NTRS2015

Towards Real-Time, On-Board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respond to uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from the NASA Swift UAS.

Unmanned Aerial System↗

NASA NTRS1993

Man-machine cooperation in advanced teleoperation

Teleoperation experiments at JPL have shown that advanced features in a telerobotic system are a necessary condition for good results, but that they are not sufficient to assure consistently good performance by the operators. Two or three operators are normally used during training and experiments to maintain the desired performance. An alternative to this multi-operator control station is a man-machine interface embedding computer programs that can perform some of the operator's functions. In this paper we present our first experiments with these concepts, in which we focused on the areas of real-time task monitoring and interactive path planning. In the first case, when performing a known task, the operator has an automatic aid for setting control parameters and camera views. In the second case, an interactive path planner will rank different path alternatives so that the operator will make the correct control decision. The monitoring function has been implemented with a neural network doing the real-time task segmentation. The interactive path planner was implemented for redundant manipulators to specify arm configurations across the desired path and satisfy geometric, task, and performance constraints.

Fiorini, Paolo↗