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At least 667 records · Page 37

Local Ultrasonic Resonance Spectroscopy of Lithium Metal Batteries for Aerospace Applications

As next-generation aircraft and vehicles continue to develop, so do their associated energy demands. Lithium metal batteries are a leading candidate to fulfill this energy requirement, but these batteries are prone to internal dendrite defects that can lead to catastrophic thermal runaway events. Current battery management systems are capable of mitigating such risks, but are unable to detect such defects until thermal runaway has already begun. Various nondestructive evaluation (NDE) techniques, particularly ultrasonic NDE, can directly monitor internal battery parameters giving them the potential to detect critical defects prior to catastrophic failure. However, most of the current battery NDE research has focused on improved battery state-of-charge (SOC) and stateof- health (SOH) monitoring with little emphasis on critical defect detection. Thus, a measurement technique sensitive to subtle battery defects is needed. In addition, the complex mechanics of ultrasound in porous, thin, multilayered batteries prompt the use of physics-based simulation to guide inspections. In this work, an ultrasonic NDE technique has been developed utilizing frequency domain analysis of local battery resonances to detect the presence of battery defects. This technique is a practical extension of local ultrasonic resonance spectroscopy (LURS) – which previously required non-contact laser ultrasonics – to measurements with piezoelectric contact and immersion scan transducers. To extend the technique to work with piezoelectric transducers, ultrasonic battery measurements were compared to a sans-battery calibration measurement. Then, a linear systems deconvolution was used to eliminate the transfer functions of extraneous factors such as the transducer and electronics, leaving only the frequency-dependent battery reflection coefficient. The LURS technique was first validated on stainless steel and aluminum plates, producing reflection coefficients in line with analytical and numerical finite element modeling (FEM) results. Functioning Li-metal pouch cells were then seeded with lithium chip defects prior to LURS measurements. The presence of these defects is shown to cause a measurable shift in the battery’s through-thickness local resonances. 2D, frequency-domain poroelastic models of ultrasonic propagation in a single-cell lithium metal pouch battery were created and corroborated these findings. Thus, this work has both extended and proven the feasibility of the LURS technique in the detection of local battery defects.

Ultrasound↗

Material Property Estimation in Thin Battery Components Using Guided Wave Measurement, Experimental Dispersion Curve Extraction and Finite Element Modeling

At NASA, we are investigating nondestructive evaluation (NDE) and structural health monitoring (SHM) techniques to detect precursors of thermal runaway failure in lithium metal based lithium ion batteries (LIB). The approach is centered on computational simulation models to guide inspection and aid in interpretation of results. Since lithium metal LIBs have combinations of solid and fluid-filled porous materials, obtaining accurate material properties is both challenging and critical for successful simulation of battery inspection. To this end, we investigated a multi-verification approach for material characterization of thin battery components. First, a laser Doppler vibrometer (LDV) was used to measure guided wave fields in thin (microns-thick) battery components subject to broadband excitation. The time-space wavefield data was converted to frequency-wave number data to extract guided wave dispersion curves. A data visualization and post processing graphics user interface (GUI) was developed at NASA to aid the data exploration and analysis. Due to the thinness of the samples, low frequency-thickness-product plate wave approximations allowed for the calculation of closed-form solutions for material elastic property estimation. These approximations were then verified by calculating the Lamb wave solutions using the previously obtained material properties. Finally, the estimated elastic material properties were implemented in a COMSOL simulation model, and dispersion curves were extracted from simulation results. The dispersion curves and derived material properties were then compared to the analysis results from the experimental data. These comparisons informed on the accuracy of the measured material properties and helped demonstrate the accuracy of the finite element analysis (FEA) computational models. This assessment will prove vital when we start simulating more complex multi-layer components and poroelastic media. This paper gives a brief background of the problem space, outlines the workflow for data analysis and verification, shows results from the workflow, and gives an overview of future plans for simulation of lithium metal LIB inspection.

Peter Juarez↗

TechEdSat-11: Prototyping Autonomous Communications in Orbit

Cognitive Engine 1 (CE-1) is a state-of-the-art automated system designed to manage routine operations and respond to adverse events without requiring human operator input. CE-1 will optimize scheduling capabilities, detect and react to link failures, and ensure data delivery deadlines are met efficiently. Seamless roaming between government and commercial providers will allow for a robust and cost-effective network. TechEdSat-11 will demonstrate two key components of CE-1: User Initiated Services (UIS) and Delay Tolerant Networking (DTN). The first phase of the experiment will use UIS to automate on-demand scheduling of a commercial S-band ground station. Later phases of the experiment will demonstrate DTN store-and-forward and space internetworking capabilities through the TechEdSat-11 S-band radio. This paper will discuss the CE-1 main components relevant to the experiment, the flight and ground software architecture, experiment concept of operations and preliminary results.

Rachel Dudukovich↗

Empirically based analysis of failures in software systems

An empirical analysis of software-system failures is used to study several specific issues in software testing, reliability analysis, and reuse. Failure data from a large software manufacturer and a NASA production environment were collected and analyzed. The systems ranged in size from 30,000 to over 100,000 lines. The results show that (1) the first 15 percent of the test cases detected 67 percent of the high-severity failures and 50 percent of all failures; (2) multiple fault-detection and testing phases may result in a significant increase in reliability or none at all; (3) composite measures of system reliability did not adequately reflect reliability at the function or component level; (4) developers were biased toward portions of systems that would be heavily tested; (5) fault-proneness of reused or modified components was 74 percent less than that of newly developed components; and (6) systems with more reused software had lower component development effort, but not lower component fault-proneness.

Selby, Richard W.↗

Failure Analysis of CCD Image Sensors Using SQUID and GMR Magnetic Current Imaging

During electrical testing of a Full Field CCD Image Senor, electrical shorts were detected on three of six devices. These failures occurred after the parts were soldered to the PCB. Failure analysis was performed to determine the cause and locations of these failures on the devices. After removing the fiber optic faceplate, optical inspection was performed on the CCDs to understand the design and package layout. Optical inspection revealed that the device had a light shield ringing the CCD array. This structure complicated the failure analysis. Alternate methods of analysis were considered, including liquid crystal, light and thermal emission, LT/A, TT/A SQUID, and MP. Of these, SQUID and MP techniques were pursued for further analysis. Also magnetoresistive current imaging technology is discussed and compared to SQUID.

Felt, Frederick S.↗

Ferrographic and spectrographic analysis of oil sampled before and after failure of a jet engine

An experimental gas turbine engine was destroyed as a result of the combustion of its titanium components. Several engine oil samples (before and after the failure) were analyzed with a Ferrograph as well as plasma, atomic absorption, and emission spectrometers. The analyses indicated that a lubrication system failure was not a causative factor in the engine failure. Neither an abnormal wear mechanism, nor a high level of wear debris was detected in the oil sample from the engine just prior to the test in which the failure occurred. However, low concentrations of titanium were evident in this sample and samples taken earlier. After the failure, higher titanium concentrations were detected in oil samples taken from different engine locations. Ferrographic analysis indicated that most of the titanium was contained in spherical metallic debris after the failure.

Jones, W. R., Jr.↗

Modeling of a bubble-memory organization with self-checking translators to achieve high reliability.

Study of the design and modeling of a highly reliable bubble-memory system that has the capabilities of: (1) correcting a single 16-adjacent bit-group error resulting from failures in a single basic storage module (BSM), and (2) detecting with a probability greater than 0.99 any double errors resulting from failures in BSM's. The results of the study justify the design philosophy adopted of employing memory data encoding and a translator to correct single group errors and detect double group errors to enhance the overall system reliability.

Bouricius, W. G.↗

Develop advanced nonlinear signal analysis topographical mapping system

The SSME has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) Develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system. (2) Develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amounts of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. A high compression ratio can be achieved to allow the minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities. (3) Integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for a quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Jong, Jen-Yi↗

Develop advanced nonlinear signal analysis topographical mapping system

The Space Shuttle Main Engine (SSME) has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature, pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system; (2) develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amount of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. High compression ratio can be achieved to allow minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities; and (3) integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Source record↗

Defect Detection and Prevention

As NASA continues to impement its Faster, Better, Cheaper philosophy, new approaches for implementing Mission Assurance activities are being developed.

faster↗

Laboratory simulation of Venusian lightning

Evidence of lightning activity in the Venusian atmosphere has been obtained from the Venera 9, 11, and 12 spacecraft, and from the Pioneer Venus Orbiter (PVO). However, a search for optical pulses expected from Venusian lightning using the star sensor on the PVO did not detect any signals. It has been suggested that the star sensor did not detect lightning because Venusian lightning does not radiate in the 500- to 900-nm spectral region detected by the star sensor. In this paper, spectra obtained from a laboratory simulation of Venusian lightning are discussed. Both the laboratory spectrum and the results of a theoretical calculation of line intensities show that Venusian lightning can be expected to radiate strongly in the 600- to 900-nm spectral region. Hence, the failure of the star sensor to detect lightning must be caused by the low flashing rate or by the low intensity of Venusian lightning.

Borucki, W. J.↗

Ferrographic and spectrometer oil analysis from a failed gas turbine engine

An experimental gas turbine engine was destroyed as a result of the combustion of its titanium components. It was concluded that a severe surge may have caused interference between rotating and stationary compressor that either directly or indirectly ignited the titanium components. Several engine oil samples (before and after the failure) were analyzed with a Ferrograph, a plasma, an atomic absorption, and an emission spectrometer to see if this information would aid in the engine failure diagnosis. The analyses indicated that a lubrication system failure was not a causative factor in the engine failure. Neither an abnormal wear mechanism nor a high level of wear debris was detected in the engine oil sample taken just prior to the test in which the failure occurred. However, low concentrations (0.2 to 0.5 ppm) of titanium were evident in this sample and samples taken earlier. After the failure, higher titanium concentrations ( 2 ppm) were detected in oil samples taken from different engine locations. Ferrographic analysis indicated that most of the titanium was contained in spherical metallic debris after the failure. The oil analyses eliminated a lubrication system bearing or shaft seal failure as the cause of the engine failure.

Jones, W. R., Jr.↗

Ferrographic and spectrometer oil analysis from a failed gas turbine engine

An experimental gas turbine engine was destroyed as a result of the combustion of its titanium components. It was concluded that a severe surge may have caused interference between rotating and stationary compressor parts that either directly or indirectly ignited the titanium components. Several engine oil samples (before and after the failure) were analyzed with a Ferrograph, and with plasma, atomic absorption, and emission spectrometers to see if this information would aid in the engine failure diagnosis. The analyses indicated that a lubrication system failure was not a causative factor in the engine failure. Neither an abnormal wear mechanism nor a high level of wear debris was detected in the engine oil sample taken just prior to the test in which the failure occurred. However, low concentrations (0.2 to 0.5 ppm) of titanium were evident in this sample and samples taken earlier. After the failure, higher titanium concentrations (2 ppm) were detected in oil samples taken from different engine locations. Ferrographic analysis indicated that most of the titanium was contained in spherical metallic debris after the failure. The oil analyses eliminated a lubrication system bearing or shaft seal failure as the cause of the engine failure. Previously announced in STAR as N83-12433

Jones, W. R., Jr.↗

An experiment in software reliability

The results of a software reliability experiment conducted in a controlled laboratory setting are reported. The experiment was undertaken to gather data on software failures and is one in a series of experiments being pursued by the Fault Tolerant Systems Branch of NASA Langley Research Center to find a means of credibly performing reliability evaluations of flight control software. The experiment tests a small sample of implementations of radar tracking software having ultra-reliability requirements and uses n-version programming for error detection, and repetitive run modeling for failure and fault rate estimation. The experiment results agree with those of Nagel and Skrivan in that the program error rates suggest an approximate log-linear pattern and the individual faults occurred with significantly different error rates. Additional analysis of the experimental data raises new questions concerning the phenomenon of interacting faults. This phenomenon may provide one explanation for software reliability decay.

Dunham, J. R.↗

Detection of lack of fusion using opaque additives

Reliable nondestructive inspection for incomplete weldment penetration and rapid oxidation of aluminum surfaces when exposed to the atmosphere are currently two major problems in welded aluminum spacecraft structure. Incomplete-penetration defects are extremely difficult to detect and can lead to catastrophic failure of the structure. The moisture absorbed by aluminum oxide on the surface can cause weldment porosity if the surface is not cleaned before welding. The approach employed in this program to solve both problems was to employ copper as a coating to prevent oxidation of the aluminum. Also, copper was used as an opaque additive in the weldment to enhance X-ray detection in the event of incomplete penetration.

Cook, J. L.↗

Nondestructive Detection of Cracks in Ceramics Using Vicinal Illumination

Cracks and other defects in ceramic materials can be difficult or impossible to examine and photograph due to the extreme lack of contrast. A method for inspecting translucent ceramics using scattered light, also known as vicinal illumination, will be described. This method has been known in the ceramics industry for quite some time, but is not well known in the testing and failure analysis community. Electronics applications include substrates, packages, multilayer capacitors, and thin film resistors. Ceramic materials are used in electronic applications as microcircuit packages and substrates which carry signals and power between microcircuits. Fine cracks in ceramic materials can result in mechanical failures, electrical failures, and loss of hermeticity. Often, fine cracks are difficult or impossible to detect using standard nondestructive inspection techniques such as visual inspection, ultrasonic inspection, or vapor crack detection. Dye penetrant inspection is usually effective, but contaminates the part, which is unacceptable for space flight hardware. One effective nondestructive inspection method of detecting cracks involves examining the way in which light scatters through the ceramic material when viewed with a standard bright field reflected light microscope. This method, termed vicinal illumination, has been used for detecting cracks during failure analyses of several part types, and screening of space flight hardware. The technique has proven effective on several different types of ceramic materials as well. A related method for use with dark field equipment has also been used to successfully locate otherwise invisible cracks.

Hull, Scott M.↗

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

Coffin, Thomas↗

Automated Monitoring with a BCP Fault-Decision Test

The Bayesian conditional probability (BCP) technique is a statistical fault-decision technique that is suitable as the mathematical basis of the fault-manager module in the automated-monitoring system and method described in the immediately preceding article. Within the automated-monitoring system, the fault-manager module operates in conjunction with the fault-detector module, which can be based on any one of several fault-detection techniques; examples include a threshold-limit-comparison technique or the BSP or SPRT technique mentioned in the preceding article. The present BCP technique is used to evaluate a series of one or more fault-detection events for the purpose of filtering out occasional false alarms produced by many types of statistical fault-detection procedures. The BCP technique increases the probability that an automated monitoring system produces a correct decision regarding the presence or absence of a fault. Because occasional false alarms are an inevitable consequence of the SPRT, BSP, or any other statistically based fault-detection test, there is a need for a logical procedure to distinguish between true and false alarms. Heretofore, it has been common practice to make a fault decision on an ad hoc basis for example by following a multiple-observation voting strategy in which a signal is declared to be indicative of a fault if m of the last n observations produced a fault-detection alarm. The BCP technique was developed to obtain results more reliable than those afforded by a voting strategy. The BCP technique involves a test in which one applies Bayesian inference techniques to a series of one or more single-observation alarms produced by a fault-detection test. One considers the last n decisions generated by a fault-detection test in order to evaluate the conditional probability that a failure is indicated (see figure). Each new decision reached by a fault-detection test is treated as a new piece of evidence about the state of the monitored asset, and the conditional probability of failure for the system is updated on the basis of this new evidence. The conditional probability of failure is compared with a predefined limit. For a probability below the limit, the asset is declared to be healthy. For a probability above the limit, the asset is declared to be faulty.

Bickford, Randall L.↗