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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Active Betweenness Cardinality: Algorithms and Applications

Centrality rankings such as degree, closeness, betweenness, Katz, PageRank, etc. are commonly used to identify critical nodes in a graph. These methods are based on two assumptions that restrict their wider applicability. First, they assume the exact topology of the network is available. Secondly, they do not take into account the activity over the network and only rely on its topology. However, in many applications, the network is autonomous, vast, and distributed, and it is hard to collect the exact topology. At the same time, the underlying pairwise activity between node pairs is not uniform and node criticality strongly depends on the activity on the underlying network. In this paper, we propose active betweenness cardinality, as a new measure, where the node criticalities are based on not the static structure, but the activity of the network. We show how this metric can be computed efficiently by using only local information for a given node and how we can find the most critical nodes starting from only a few nodes. We also show how this metric can be used to monitor a network and identify failed nodes. We present experimental results to show effectiveness by demonstrating how the failed nodes can be identified by measuring active betweenness cardinality of a few nodes in the system.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Detecting Hidden Failure Modes in Critical, Embedded Software

This experience report describes a method that has been used successfully to detect hidden failure modes in critical, embedded spacecraft software. The method is an adaptation of an earlier, controversial approach called failure modes and effects analysis. The adapted method was found to be well-suited to identifying latent software design weaknesses involving complex system interactions and dependencies in the two applications described here. This experience may be useful for other high-integrity software systems in which the possibility of hidden failure modes is a major concern.

detecting software failure design analysis↗
NASA NTRS2009

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Balaban, Edward↗
NASA NTRS1992

Underlying modal data issues for detecting damage in truss structures

The modal strain energy distribution and frequency and mode shape sensitivities to structural stiffness changes are studied in order to overcome the current limits of modal data limit measurements in damage location. It is established that damage detection is feasible for members significantly contributing to the strain energy of the measured modes; the modes that are most effective in detecting the damage of critical members are identifiable, and a relationship is formulated between the accuracy of the measured modes and frequencies and the probability of damage detection.

Kashangaki, Thomas A.-L.↗
NASA NTRS1992

Underlying modal data issues for detecting damage in truss structures

Independent of the modal identification techniques employed for damage detection, use of measured modal data limits the expectations for damage location. These limitations are examined using the distribution of modal strain energy and the sensitivity of the frequency and mode shapes to structural stiffness changes. For given measured modal information of specific accuracy, this examination reveals the following: (1) damage detection is feasible for members that contribute significantly to the strain energy of the measured modes, (2) the modes which are most effective in detecting damage to certain critical members can be identified, and (3) a relationship can be drawn between the accuracy of the measured modes and frequencies and damage detection feasibility.

Kashangaki, Thomas A-L.↗
DOE OSTI2022

Characterization of Advanced Imaging Systems for High-Resolution and Event-Mode Detection

Post-irradiation examination (PIE) is a continually growing field critical to the development of improved nuclear fuels. To characterize these materials, neutron imaging systems are employed and outfitted with, typically, CMOS or CCD cameras - complementary metal oxide semiconductor sensors and charge-couple devices. Imaging systems are a team-effort between the camera, scintillating materials, and object of interest, as a result of neutrons' inherent need to be converted to a detectable signal. High resolution imaging, flash radiography imaging, and event-mode detection systems are three systems undergoing development, construction, and characterization for improved spatial resolution and time-of-flight detection for PIE efforts.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Comparison of Approach-to-Critical Results in Current and Pulse Mode for Systems with High Starter Neutron Rates

Reactors and critical assemblies use a variety of detection systems to monitor the neutron population. The count rate is proportional to the neutron flux present at the location of the detector. When such systems are placed external to an assembly, it is often assumed that the relative leakage multiplication will be proportional to the detector count rate (assuming that the source term, system geometry, and detector placement have not changed). Such systems are often used in an approach-to-critical during reactor startup to ensure that the critical configuration is well predicted. Various types of detectors have been used during an approach-to-critical. These include 3 He, BF 3 , ion chambers, fission chambers, and fission foils. Any of these types of systems (or others) should work well when adequate counting statistics are available. These detector systems can be operated in either pulse or current mode. The National Criticality Experiments Research Center (NCERC) has two detection systems that are commonly used in critical assembly operations. The start-up (referred to as "SU" in this work) system is made up of 3 He proportional counters in pulse mode and the linear counter system (referred to as "LC" in this work) consists of compensated ion-chambers in current mode. Typically the SU system is used for approach-to-critical operations and the LC system is only used at/above delayed critical ( k eff = 1). This work investigates the use of the LC system for an approach-to-critical. It has been long hypothesized that such an approach would be feasible for systems with high starter neutron rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Improved galactic foreground removal for B-mode detection with clustering methods

ABSTRACT Characterizing the sub-mm Galactic emission has become increasingly critical especially in identifying and removing its polarized contribution from the one emitted by the cosmic microwave background (CMB). In this work, we present a parametric foreground removal performed on to sub-patches identified in the celestial sphere by means of spectral clustering. Our approach takes into account efficiently both the geometrical affinity and the similarity induced by the measurements and the accompanying errors. The optimal partition is then used to parametrically separate the Galactic emission encoding thermal dust and synchrotron from the CMB one applied on two nominal observations of forthcoming experiments from the ground and from the space. Moreover, the clustering is performed on tracers that are different from the data used for component separation, e.g. the spectral index maps of dust and synchrotron. Performing the parametric fit singularly on each of the clustering derived regions results in an overall improvement: both controlling the bias and the uncertainties in the CMB B-mode recovered maps. We finally apply this technique using the map of the number of clouds along the line of sight, $\mathcal {N}_c$, as estimated from H i emission data and perform parametric fitting on to patches derived by clustering on this map. We show that adopting the $\mathcal {N}_c$ map as a tracer for the patches related to the thermal dust emission, results in reducing the B-mode residuals post-component separation. The code is made publicly available https://github.com/giuspugl/fgcluster.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2017

A Numerical Study on the Edgewise Compression Strength of Sandwich Structures with Facesheet-Core Disbonds

Damage tolerant design approaches require determination of critical damage modes and flaw sizes in order to establish nondestructive evaluation detection requirements. A finite element model is developed to assess the effect of circular facesheet-core disbonds on the strength of sandwich specimens subjected to edgewise compressive loads for the purpose of predicting the critical flaw size for a variety of design parameters. Postbuckling analyses are conducted in which an initial imperfection is seeded using results from a linear buckling analysis. Both the virtual crack closure technique (VCCT) and cohesive elements are considered for modeling disbond growth. Predictions from analyses using the VCCT and analyses using cohesive elements are in good correlation. A series of parametric analyses are conducted to investigate the effect of core thickness and material, facesheet layup, facesheet-core interface properties, and curvature on the criticality of facesheet-core disbonds of various sizes. The results from these analyses provide a basis for determining the critical flaw size for facesheet-core disbonds subjected to edgewise compression loads and, therefore, nondestructive evaluation flaw detection requirements for this configuration.

Bergan, Andrew C.↗
NASA NTRS1978

Critical fault patterns determination in fault-tolerant computer systems

The method proposed tries to enumerate all the critical fault-patterns (successive occurrences of failures) without analyzing every single possible fault. The conditions for the system to be operating in a given mode can be expressed in terms of the static states. Thus, one can find all the system states that correspond to a given critical mode of operation. The next step consists in analyzing the fault-detection mechanisms, the diagnosis algorithm and the process of switch control. From them, one can find all the possible system configurations that can result from a failure occurrence. Thus, one can list all the characteristics, with respect to detection, diagnosis, and switch control, that failures must have to constitute critical fault-patterns. Such an enumeration of the critical fault-patterns can be directly used to evaluate the overall system tolerance to failures. Present research is focused on how to efficiently make use of these system-level characteristics to enumerate all the failures that verify these characteristics.

Mccluskey, E. J.↗
NASA NTRS2021

The Roman Space Telescope Coronagraph Technology Demonstration: Current Status and Relevance to Future Missions

The Nancy Grace Roman Space Telescope (formally WFIRST) will be launched in the mid-2020’s with an onboard coronagraph instrument which will serve as a technology demonstrator for exoplanet direct imaging. The Roman Coronagraph will be capable of detecting and characterizing exoplanets and circumstellar disks in visible light at an unprecedented contrast level of ~10-8 or lower. Such a contrast level, which is several magnitudes better than state-of-the-art visible or near-infrared coronagraphs, raises entirely new challenges that will be overcome using a combination of hardware, calibration and data processing. In particular, the Roman Coronagraph will be the first space-based coronagraphic instrument with real-time active wavefront control through the use of large format deformable mirrors, and its EMCCD detector will enable faint signal detection in photon-counting mode. The Roman Coronagraph passed its critical design review successfully in April 2021, and is now well on its path to demonstrate many core technologies at the levels required for future exo-Earth direct imaging missions.

Luchik, T.↗
NASA NTRS1990

Health management system for rocket engines

The functional framework of a failure detection algorithm for the Space Shuttle Main Engine (SSME) is developed. The basic algorithm is based only on existing SSME measurements. Supplemental measurements, expected to enhance failure detection effectiveness, are identified. To support the algorithm development, a figure of merit is defined to estimate the likelihood of SSME criticality 1 failure modes and the failure modes are ranked in order of likelihood of occurrence. Nine classes of failure detection strategies are evaluated and promising features are extracted as the basis for the failure detection algorithm. The failure detection algorithm provides early warning capabilities for a wide variety of SSME failure modes. Preliminary algorithm evaluation, using data from three SSME failures representing three different failure types, demonstrated indications of imminent catastrophic failure well in advance of redline cutoff in all three cases.

Nemeth, Edward↗
NASA NTRS2009

Dynamic Structural Fault Detection and Identification

Aircraft structures are designed to guarantee safety of flight in some required operational envelope. When the aircraft becomes structurally impaired, safety of flight may not be guaranteed within that previously safe operational envelope. In this case the safe operational envelope must be redefined in-flight and a means to prevent excursion from this new envelope must be implemented. A specific structural failure mode that may result in a reduced safe operating envelope, the exceedance of which could lead to catastrophic structural failure of the aircraft, will be addressed. The goal of the DFEAP program is the detection of this failure mode coupled with flight controls adaptation to limit critical loads in the damaged aircraft structure. The DFEAP program is working with an F/A-18 aircraft model. The composite wing skins are bonded to metallic spars in the wing substructure. Over time, it is possible that this bonding can deteriorate due to fatigue. In this case, the ability of the wing spar to transfer loading between the wing skins is reduced. This failure mode can translate to a reduced allowable compressive strain on the wing skin and could lead to catastrophic wing buckling if load limiting of the wing structure is not applied. The DFEAP program will make use of a simplified wing strain model for the healthy aircraft. The outputs of this model will be compared in real-time to onboard strain measurements at several locations on the aircraft wing. A damage condition is declared at a given location when the strain measurements differ sufficiently from the strain model. Parameter identification of the damaged structure wing strain parameters will be employed to provide load limiting control adaptation for the aircraft. This paper will discuss the simplified strain models used in the implementation and their interaction with the strain sensor measurements. Also discussed will be the damage detection and identification schemes employed and the means by which the damaged aircraft parameters will be used to provide load limiting that keeps the aircraft within the safe operational envelope.

Smith, Timothy↗
NASA NTRS1991

On-orbit damage detection and health monitoring of large space trusses - Status and critical issues

The literature in the fields of structural identification, mode shape expansion and orthogonalization, and on-orbit damage location of large space trusses is reviewed. The use of a Dynamic Scale Model Technology (DSMT) hybrid scale model for damage location research and as a universal test bed for other damage location methods is proposed as a means of comparing and evaluating existing and newly developed methods in the named areas. Issues concerning on-orbit data acquisition, data accuracy, and data quality relevant to structural dynamic system identification which require extensive research are identified.

Kashangaki, Thomas A.-L.↗
DOE OSTI2021

Determination of X-ray detection limit and applications in perovskite X-ray detectors

X-ray detection limit and sensitivity are important figure of merits for perovskite X-ray detectors, but literatures lack a valid mathematic expression for determining the lower limit of detection for a perovskite X-ray detector. In this work, we present a thorough analysis and new method for X-ray detection limit determination based on a statistical model that correlates the dark current and the X-ray induced photocurrent with the detection limit. The detection limit can be calculated through the measurement of dark current and sensitivity with an easy-to-follow practice. Alternatively, the detection limit may also be obtained by the measurement of dark current and photocurrent when repeatedly lowering the X-ray dose rate. While the material quality is critical, we show that the device architecture and working mode also have a significant influence on the sensitivity and the detection limit. Our work establishes a fair comparison metrics for material and detector development.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

SSME Propellant Path Leak Detection

The complicated high-pressure cycle of the space shuttle main engine (SSME) propellant path provides many opportunities for external propellant path leaks while the engine is running. This mode of engine failure may be detected and analyzed with sufficient speed to save critical engine test hardware from destruction. The leaks indicate hardware failures which will damage or destroy an engine if undetected; therefore, detection of both cryogenic and hot gas leaks is the objective of this investigation. The primary objective of this phase of the investigation is the experimental validation of techniques for detecting and analyzing propellant path external leaks which have a high probability of occurring on the SSME. The selection of candidate detection methods requires a good analytic model for leak plumes which would develop from external leaks and an understanding of radiation transfer through the leak plume. One advanced propellant path leak detection technique is obtained by using state-of-the-art technology infrared (IR) thermal imaging systems combined with computer, digital image processing, and expert systems for the engine protection. The feasibility of IR leak plume detection is evaluated on subscale simulated laboratory plumes to determine sensitivity, signal to noise, and general suitability for the application.

Roger Crawford↗
DOE OSTI2025

Accurate and rapid acoustic damage characterization in complex structures using sparse sensor networks and deep learning models

Damage diagnosis in critical components is essential for ensuring the safety and reliability of operations across industries, spanning manufacturing, aerospace, and energy. Traditional acoustic nondestructive testing methods primarily focus on detecting defects through the direct scattering of single-mode incident waves from the damage, which limit their applicability to simple structures and small inspection areas. Our earlier research demonstrated that machine learning algorithms combined with sparse sensor networks can identify critical defect signatures even from multiply scattered, multi-mode acoustic signals, indicating the potential for improved defect inspection in complex, real-world structures. In this work, we demonstrate the successful implementation of this approach in a fixed sensor configuration to rapidly and accurately detect simulated defects in a geometrically complex, real-world structure, a brake rotor hub. Three different types of defects were physically simulated on the surface of the hub, and the collected data were used to train an autoencoder-based deep learning model. Two models were tested, one using single measurements and the other using multiple measurements taking advantage of the spatial distribution of the sensor network. After training, the multi-measurement model achieved 100 % accuracy in identifying, classifying, and locating unseen, unique damages. This work illustrates the potential of the proposed method for a wide range of industrial applications.

36 MATERIALS SCIENCE↗
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↗