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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

A high performance FDDI NIU for streaming voice, video, and data

A 100-Mbit/s FDDI network interface unit (NIU) is described that supports real-time data, voice and video. Its high-speed interrupt-driven hardware architecture efficiently manages stream and packet data transfers to the FDDI network. Other enhancements include modular single-mode laser-dioce fiber optic links to maximize node spacing, optic bypass switches for increased fault tolerance, and a hardware performance monitor to gather real-time network diagnostics.

Bergman, L. A.↗
NASA NTRS1993

Pattern classifier for health monitoring of helicopter gearboxes

The application of a newly developed diagnostic method to a helicopter gearbox is demonstrated. This method is a pattern classifier which uses a multi-valued influence matrix (MVIM) as its diagnostic model. The method benefits from a fast learning algorithm, based on error feedback, that enables it to estimate gearbox health from a small set of measurement-fault data. The MVIM method can also assess the diagnosability of the system and variability of the fault signatures as the basis to improve fault signatures. This method was tested on vibration signals reflecting various faults in an OH-58A main rotor transmission gearbox. The vibration signals were then digitized and processed by a vibration signal analyzer to enhance and extract various features of the vibration data. The parameters obtained from this analyzer were utilized to train and test the performance of the MVIM method in both detection and diagnosis. The results indicate that the MVIM method provided excellent detection results when the full range of faults effects on the measurements were included in training, and it had a correct diagnostic rate of 95 percent when the faults were included in training.

Chin, Hsinyung↗
NASA NTRS1998

Breaking the Wavelength Barrier

Under an SBIR (Small Business Innovative Research) contract with Goddard Space Flight Center, Focused Research, Inc. and New Focus, Inc., developed a single mode tunable diode laser from 1.9 to 4.0 microns. As an offshoot from this work, they were able to introduce a 2.0 micron diode laser into their commercial product line. These lasers are useful in trace gas detection, environmental monitoring, seeding of lidar systems, and medical diagnostic experiments.

Source record↗
NASA NTRS2004

High Sensitivity, Low Power Nano Sensors and Devices for Chemical Sensing

The chemical sensor market has been projected to grow to better than $40 billion dollars worldwide within the next 10 years. Some of the primary motivations to develop nanostructured chemical sensors are monitoring and control of environmental pollution; improved diagnostics for consumption; improvement in measurement precision and accuracy; and improved detection limits for Homeland security, battlefield environments, and process and quality control of industrial applications. In each of these applications, there is demand for sensitivity, selectivity and stability of environmental and biohazard detection and capture beyond what is currently commercially available. Nanotechnology offers the ability to work at the molecular level, atom by atom, to create large structures with fundamentally new molecular organization. It is essentially concerned with materials, devices, and systems whose structures and components exhibit novel and significantly improved physical, chemical and biological properties, phenomena, and process control due to their nanoscale size. One such nanotechnology-enabled chemical sensor has been developed at NASA Ames leveraging nanostructures, such as single walled carbon nanotubes (SWNTs) and metal oxide nanobelts or nanowires, as a sensing medium bridging a pair of interdigitated electrodes (IDE) realized through a silicon-based microfabrication and micromachining technique. The DE fingers are fabricated on a silicon substrate using standard photolithography and thin film metallization techniques. It is noteworthy that the fabrication techniques employed are not confined to the silicon substrate. Through spin casting and careful substrate selection (i.e. clothing, glass, polymer, etc.), additional degrees of freedom can be exploited to enhance sensitivity or to conform to unique applications. Both in-situ growth of nanostructured materials and casting of nanostructured dispersions were used to produce analogous chemical sensing devices.

Li, Jing↗
NASA NTRS2006

Inferring Gear Damage from Oil-Debris and Vibration Data

A system for real-time detection of surface-fatigue-pitting damage to gears for use in a helicopter transmission is based on fuzzy-logic used to fuse data from sensors that measure oil-borne debris, referred to as "oil debris" in the article, and vibration signatures. A system to detect helicopter-transmission gear damage is beneficial because the power train of a helicopter is essential for propulsion, lift, and maneuvering, hence, the integrity of the transmission is critical to helicopter safety. To enable detection of an impending transmission failure, an ideal diagnostic system should provide real-time monitoring of the "health" of the transmission, be capable of a high level of reliable detection (with minimization of false alarms), and provide human users with clear information on the health of the system without making it necessary for them to interpret large amounts of sensor data.

Dempsey, Paula↗
NASA NTRS2022

Lithium-ion Battery Strain Gauge Monitoring and Depth of Discharge Estimation

Lithium-ion battery diagnostics and prognostics rely on measurements of electrical impedance, capacity, and voltage to infer the internal state of the battery. Mechanical changes to the cell structure represent an additional measure of the battery’s state because these changes are related to the overall battery health. As lithium-ion batteries are charged and discharged, lithium ions are inserted or removed from the anode and cathode, a process called intercalation and de-intercalation. As lithium ions intercalate and de-intercalate, they can cause changes to the lattice of the electrode particles, resulting in volumetric changes. These volumetric changes cause mechanical stresses and strains on the lithium-ion battery electrodes, and subsequently, the whole cell’s thickness varies as it is charged and discharged. This paper presents a study on the use of surface-mounted strain gauges for in-situ measurement of structural changes to lithium-ion batteries, along with a characterization of the unit-to-unit differences in strain response. A neural network modeling structure is then used to predict the battery’s depth of discharge under dynamic discharge conditions.

Lithium-ion batteries, depth of discharge, strain ↗
NASA NTRS2006

Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis

A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.

Dempsey, Paula J.↗
DOE OSTI2023

Development of a Scalable Risk-informed Predictive Maintenance Cloud-based Strategy at Nuclear Power Plants

The fact that light-water reactor operation and maintenance costs are prohibitively expensive and contribute to the premature decommissioning of nuclear power plants is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology, as its low cost, computing and storage adaptability, and ability to host applications across numerous virtual infrastructures potentially make it a cost-effective alternative to onsite storage and diagnostics. In this paper, a technological assessment is carried out on a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. This cloud-based monitoring system would enable maintenance and diagnostic analysts and other authorized plant users to remotely monitor equipment functionality, thus enabling early fault detection and effective predictive maintenance practices. To provide data processing and storage, sensor device networking, and database management, the Microsoft Azure cloud platform is utilized as part of the proposed cloud architecture; however, this analysis could be extended to other cloud computing service providers as well. The focus of this paper is on application of cloud resources for enabling predictive maintenance, identification of technological hurdles associated with moving to a cloud-computing-based architecture, and potential benefits from moving to a centralized cloud system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Development of a Cloud-based Application to Enable a Scalable Risk-informed Predictive Maintenance Strategy at Nuclear Power Plants

Light-water reactor operations and maintenance (O&M) costs are prohibitively high, thus contributing to the premature decommissioning of nuclear power plants (NPPs). This is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology by virtue of its low costs, computing and storage adaptability, and ability to host applications over numerous types of virtual infrastructures. Cloud computing can be a cost-effective alternative to onsite storage and diagnostics. This paper conducts a techno-economic assessment of a provisional cloud deployment architecture for a NPP predictive monitoring (PdM) system. The cloud-based monitoring system would enable maintenance and diagnostics (M&D) analysts and other authorized plant users to remotely monitor equipment functionality so as to enable PdM practices and early detection of faults. The Microsoft Azure cloud platform is included in the proposed cloud architecture to provide data processing and storage, sensor device networking, and database management; however, this analysis could be extended to other cloud computing service providers as well. For the techno-economic assessment, technical feasibility is measured in terms of network performance metrics such as response time, latency, and throughput, whereas economic feasibility is measured in terms of operational costs and capital expenditures. Finally, this report covers certain regulatory and security aspects that may concern licensees looking to implement cloud computing. The report focuses on the integration of sensor database storage, the application of cloud resources to PdM, and the identification of technological and economic hurdles associated with moving to a cloud-computing-based architecture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Charge breeders: Development of diagnostic tools to probe the underlying physics

Charge breeders were developed more than 20 years ago in the context of radioactive ion beam (RIB) production. The main goal is to boost the charge state of a singly charged RIB to a higher value matching the A/Q of a post-accelerator. In that way, the RIB produced at some tens of keV can efficiently be accelerated to energies in a range of few MeV/u up to several tens of MeV/u, which is of interest for nuclear structure and nuclear astrophysics experiments. Two families of charge breeders have been developed: one based on Electron Cyclotron Resonance Ion Sources (ECRISs) suitable for Continuous Wave (CW) operation and another built around Electron Beam Ion Sources (EBISs) used for pulsed post-accelerators. For many years, experimental studies have been carried out to enhance the charge breeding process and improve the extracted beam quality, i.e., purity, intensity, emittance, and time structure. The evolution of the charge breeders is also closely related to the emergence of new facilities delivering even more exotic beams. Diagnostic tools, such as Faraday cups, beam profile monitors, and emittance scanners, are mandatory to tune the machines and evaluate their performances. However, to go beyond that, a better understanding of plasma physics (in ECRIS) and electron-ion interactions (in EBIS), as well as the 1+ beam characteristics, for instance, energy spread transverse emittance, is needed. Therefore, simulation codes modeling the physics phenomena in both type of charge breeders were developed to support the understanding of experimental outputs and to gain insights into non-observable parameters. Nevertheless, more sophisticated diagnostic tools are required to improve the charge breeding performance and to extend the potential applications toward new RIB facilities. This Review will present the two kinds of charge breeders and their technical evolutions. It will review the diagnostic tools and simulation codes employed for operation and evaluation of the internal physics processes.

47 OTHER INSTRUMENTATION↗
NASA NTRS1991

Knowledge-based Autonomous Test Engineer (KATE)

Mathematical models of system components have long been used to allow simulators to predict system behavior to various stimuli. Recent efforts to monitor, diagnose, and control real-time systems using component models have experienced similar success. NASA Kennedy is continuing the development of a tool for implementing real-time knowledge-based diagnostic and control systems called KATE (Knowledge based Autonomous Test Engineer). KATE is a model-based reasoning shell designed to provide autonomous control, monitoring, fault detection, and diagnostics for complex engineering systems by applying its reasoning techniques to an exchangeable quantitative model describing the structure and function of the various system components and their systemic behavior.

Parrish, Carrie L.↗
DOE OSTI2021

Monte Carlo Analysis of the Performance of the ITER Diagnostic Residual Gas Analyzer

The composition of exhausted gas is a key parameter in long-pulse plasma fusion experiments, and its evolution shall be monitored at timescales relevant to plasma dynamics and plasma-wall interactions. A diagnostic residual gas analyzer (DRGA) is a multisensor instrument particularly suited to these studies, and ITER will adopt DRGAs in the equatorial and in the divertor tokamak regions. In this work, we have revisited the design of the ITER divertor DRGA through simple vacuum analytical considerations supported by simulations conducted with Molflow+, a test particle Monte Carlo (TPMC) simulation code commonly used in the particle accelerator community. Here, starting with recommendations on the manufacturing of the vacuum piping of the DRGA, this work is followed by a complete vacuum characterization of the diagnostic vacuum setup (pressure profiles at base pressure and during sampling, orifice diameter, and length optimization), and finally, the in-vessel residence time of the most important gas species is simulated. These studies have allowed us to give insights into some experimental results recently found on the prototype DRGA installed in the Wendelstein W7-X stellarator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1981

Performance deterioration based on simulated aerodynamic loads test, JT9D jet engine diagnostics program

An engine was specially prepared with extensive instrumentation to monitor performance, case temperatures, and clearance changes. A special loading device was used to apply known loads on the engine by the use of cables placed around the flight inlet. These loads simulated the estimated aerodynamic pressure distributions that occur on the inlet in various segments of a typical airplane flight. Test results indicate that the engine lost 1.3 percent in take-off thrust specific fuel consumption (TSFC) during the course of the test effort. Permanent clearance changes due to the loads accounted for 1.1 percent; increase in low pressure compressor airfoil roughness and thermal distortion in the high pressure turbine accounted for 0.2 percent. Pretest predicted performance loss due to clearance changes was 0.9 percent in TSFC. Therefore, the agreement between measurement and prediction is considered to be excellent.

Stromberg, W. J.↗
NASA NTRS2014

Smart Sensors Gather Information for Machine Diagnostics

Stennis Space Center was interested in using smart sensors to monitor components on test stands and avert equipment failures. Partnering with St. Paul, Minnesota-based Lion Precision through a Cooperative Agreement, the team developed a smart sensor and the associated communication protocols. The same sensor is now commercially available for manufacturing.

Source record↗
NASA NTRS2005

Traffic-Light-Preemption Vehicle-Transponder Software Module

A prototype wireless data-communication and control system automatically modifies the switching of traffic lights to give priority to emergency vehicles. The system, which was reported in several NASA Tech Briefs articles at earlier stages of development, includes a transponder on each emergency vehicle, a monitoring and control unit (an intersection controller) at each intersection equipped with traffic lights, and a central monitoring subsystem. An essential component of the system is a software module executed by a microcontroller in each transponder. This module integrates and broadcasts data on the position, velocity, acceleration, and emergency status of the vehicle. The position, velocity, and acceleration data are derived partly from the Global Positioning System, partly from deductive reckoning, and partly from a diagnostic computer aboard the vehicle. The software module also monitors similar broadcasts from other vehicles and from intersection controllers, informs the driver of which intersections it controls, and generates visible and audible alerts to inform the driver of any other emergency vehicles that are close enough to create a potential hazard. The execution of the software module can be monitored remotely and the module can be upgraded remotely and, hence, automatically

Bachelder, Aaron↗
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 NTRS2010

Improved Signal Processing Technique Leads to More Robust Self Diagnostic Accelerometer System

The self diagnostic accelerometer (SDA) is a sensor system designed to actively monitor the health of an accelerometer. In this case an accelerometer is considered healthy if it can be determined that it is operating correctly and its measurements may be relied upon. The SDA system accomplishes this by actively monitoring the accelerometer for a variety of failure conditions including accelerometer structural damage, an electrical open circuit, and most importantly accelerometer detachment. In recent testing of the SDA system in emulated engine operating conditions it has been found that a more robust signal processing technique was necessary. An improved accelerometer diagnostic technique and test results of the SDA system utilizing this technique are presented here. Furthermore, the real time, autonomous capability of the SDA system to concurrently compensate for effects from real operating conditions such as temperature changes and mechanical noise, while monitoring the condition of the accelerometer health and attachment, will be demonstrated.

Tokars, Roger↗