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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Pyrotechnic system failures: Causes and prevention

Although pyrotechnics have successfully accomplished many critical mechanical spacecraft functions, such as ignition, severance, jettisoning and valving (excluding propulsion), failures continue to occur. Provided is a listing of 84 failures of pyrotechnic hardware with completed design over a 23-year period, compiled informally by experts from every NASA Center, as well as the Air Force Space Division and the Naval Surface Warfare Center. Analyses are presented as to when and where these failures occurred, their technical source or cause, followed by the reasons why and how these kinds of failures persist. The major contributor is a fundamental lack of understanding of the functional mechanisms of pyrotechnic devices and systems, followed by not recognizing pyrotechnics as an engineering technology, insufficient manpower with hands-on experience, too few test facilities, and inadequate guidelines and specifications for design, development, qualification and acceptance. Recommendations are made on both a managerial and technical basis to prevent failures, increase reliability, improve existing and future designs, and develop the technology to meet future requirements.

Bement, Laurence J.↗
NASA NTRS2014

Effect of Preconditioning and Soldering on Failures of Chip Tantalum Capacitors

Soldering of molded case tantalum capacitors can result in damage to Ta205 dielectric and first turn-on failures due to thermo-mechanical stresses caused by CTE mismatch between materials used in the capacitors. It is also known that presence of moisture might cause damage to plastic cases due to the pop-corning effect. However, there are only scarce literature data on the effect of moisture content on the probability of post-soldering electrical failures. In this work, that is based on a case history, different groups of similar types of CWR tantalum capacitors from two lots were prepared for soldering by bake, moisture saturation, and longterm storage at room conditions. Results of the testing showed that both factors: initial quality of the lot, and preconditioning affect the probability of failures. Baking before soldering was shown to be effective to prevent failures even in lots susceptible to pop-corning damage. Mechanism of failures is discussed and recommendations for pre-soldering bake are suggested based on analysis of moisture characteristics of materials used in the capacitors' design.

multilayer ceramic capacitor (MLCC)↗
NASA NTRS1971

Establishment of design criteria for acceptable failure modes and fail safe considerations for the space shuttle structural system

The application of general design approaches for preventing failures due to repeated load cycles is briefly discussed. Program objective, mission requirements, and structural design criteria are summarized. Discrete structural elements and associated sections were selected for detailed strength, fatigue, and fracture mechanics investigations.

Westrup, R. W.↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Text-based information about past engineering failures presents one possible solution by facilitating the retrieval of information that can inform new designs. However, identifying documents containing relevant information and extracting required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing-based framework is proposed to discover relevant knowledge from documents containing failure-related design information. Documents containing usable information are filtered using sentiment analysis based on a custom lexicon specialized for engineering design and by filtering out documents containing only irrelevant topics. Next, from the identified usable documents, information relating to engineering failures, contributing factors that can be controlled at design time (“risk factors”), and recommended preventative actions are extracted. Semantic similarity is then used to group similar pieces of extracted information for improved generalizability. The proposed framework is applied to NASA’s Lessons Learned Information System (LLIS). The framework can be used to identify documents containing usable failure-related design information from other databases, extract relevant information from these documents, and generalize the acquired knowledge such that it can be applied to novel systems.

Sequoia R. Andrade↗
NASA NTRS2009

Case Study of Using High Performance Commercial Processors in a Space Environment

The purpose of the Space Shuttle Cockpit Avionics Upgrade project was to reduce crew workload and improve situational awareness. The upgrade was to augment the Shuttle avionics system with new hardware and software. A major success of this project was the validation of the hardware architecture and software design. This was significant because the project incorporated new technology and approaches for the development of human rated space software. An early version of this system was tested at the Johnson Space Center for one month by teams of astronauts. The results were positive, but NASA eventually cancelled the project towards the end of the development cycle. The goal to reduce crew workload and improve situational awareness resulted in the need for high performance Central Processing Units (CPUs). The choice of CPU selected was the PowerPC family, which is a reduced instruction set computer (RISC) known for its high performance. However, the requirement for radiation tolerance resulted in the reevaluation of the selected family member of the PowerPC line. Radiation testing revealed that the original selected processor (PowerPC 7400) was too soft to meet mission objectives and an effort was established to perform trade studies and performance testing to determine a feasible candidate. At that time, the PowerPC RAD750s where radiation tolerant, but did not meet the required performance needs of the project. Thus, the final solution was to select the PowerPC 7455. This processor did not have a radiation tolerant version, but faired better than the 7400 in the ability to detect failures. However, its cache tags did not provide parity and thus the project incorporated a software strategy to detect radiation failures. The strategy was to incorporate dual paths for software generating commands to the legacy Space Shuttle avionics to prevent failures due to the softness of the upgraded avionics.

Ferguson, Roscoe C.↗
NASA NTRS2009

Case Study of Using High Performance Commercial Processors in Space

The purpose of the Space Shuttle Cockpit Avionics Upgrade project (1999 2004) was to reduce crew workload and improve situational awareness. The upgrade was to augment the Shuttle avionics system with new hardware and software. A major success of this project was the validation of the hardware architecture and software design. This was significant because the project incorporated new technology and approaches for the development of human rated space software. An early version of this system was tested at the Johnson Space Center for one month by teams of astronauts. The results were positive, but NASA eventually cancelled the project towards the end of the development cycle. The goal to reduce crew workload and improve situational awareness resulted in the need for high performance Central Processing Units (CPUs). The choice of CPU selected was the PowerPC family, which is a reduced instruction set computer (RISC) known for its high performance. However, the requirement for radiation tolerance resulted in the re-evaluation of the selected family member of the PowerPC line. Radiation testing revealed that the original selected processor (PowerPC 7400) was too soft to meet mission objectives and an effort was established to perform trade studies and performance testing to determine a feasible candidate. At that time, the PowerPC RAD750s were radiation tolerant, but did not meet the required performance needs of the project. Thus, the final solution was to select the PowerPC 7455. This processor did not have a radiation tolerant version, but had some ability to detect failures. However, its cache tags did not provide parity and thus the project incorporated a software strategy to detect radiation failures. The strategy was to incorporate dual paths for software generating commands to the legacy Space Shuttle avionics to prevent failures due to the softness of the upgraded avionics.

Ferguson, Roscoe C.↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗
NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗
NASA NTRS1989

Modeling growth of fatigue cracks which originate at rivet holes

When a structural component is subjected to repeated stress cycles, it can fail at stresses which are well below the tensile strength of the material. The processes leading to this failure are termed fatigue. Instances of fatigue failure in aircraft have become an increasing concern. The crack leading to failure often originate at rivet holes and then grow in response to stress cycles which occur during the operation of the aircraft. A necessary step to preventing failures in todays fleet of aging aircraft is to increase the frequency and quality of inspections; steps were already taken in this direction. There is also a need for modeling of fatigue crack growth in the aircraft structures so that improvements in design can be established and predictions of the life of the components can be made. The purpose is to provide a method to accurately predict the growth of fatigue cracks and to use this method to make predictions about the life of aircraft structural components. The method relies on the formulation and numerical solution of a singular integral equation(s) for an arbitrarily shaped crack(s) which propagate in response to the applied loading. Of special interest to the aging aircraft studies are cracks which originate at circular holes (i.e., rivet holes), but other crack geometries can be treated equally as well.

Mear, Mark E.↗
NASA NTRS1978

Quantitative ultrasonic evaluation of mechanical properties of engineering materials

Current progress in the application of ultrasonic techniques to nondestructive measurement of mechanical strength properties of engineering materials is reviewed. Even where conventional NDE techniques have shown that a part is free of overt defects, advanced NDE techniques should be available to confirm the material properties assumed in the part's design. There are many instances where metallic, composite, or ceramic parts may be free of critical defects while still being susceptible to failure under design loads due to inadequate or degraded mechanical strength. This must be considered in any failure prevention scheme that relies on fracture analysis. This review will discuss the availability of ultrasonic methods that can be applied to actual parts to assess their potential susceptibility to failure under design conditions.

Vary, A.↗
DOE OSTI2023

Locating Partial Discharges in Power Transformers with Convolutional Iterative Filtering

The most common source of transformer failure is in the insulation, and the most prevalent warning signal for insulation weakness is partial discharge (PD). Locating the positions of these partial discharges would help repair the transformer to prevent failures. This work investigates algorithms that could be deployed to locate the position of a PD event using data from ultra-high frequency (UHF) sensors inside the transformer. These algorithms typically proceed in two steps: first determining the signal arrival time, and then locating the position based on time differences. This paper reviews available methods for each task and then propose new algorithms: a convolutional iterative filter with thresholding (CIFT) to determine the signal arrival time and a reference table of travel times to resolve the source location. The effectiveness of these algorithms are tested with a set of laboratory-triggered PD events and two sets of simulated PD events inside transformers in production use. Tests show the new approach provides more accurate locations than the best-known data analysis algorithms, and the difference is particularly large, 3.7X, when the signal sources are far from sensors.

47 OTHER INSTRUMENTATION↗
NASA NTRS1950

Calibration of Instruments for Measuring Wind Velocity and Direction

Signal Corps wind equipment AN/GMQ-1 consisting of a 3-cup anemometer and wind vane was calibrated for wind velocities from 1 to 200 miles per hour. Cup-shaft failure prevented calibration at higher wind velocities. The action of the wind vane was checked and found to have very poor directional accuracy below a velocity of 8 miles per hour. After shaft failure was reported to the Signal Corps, the cup rotors were redesigned by strengthening the shafts for better operation at high velocities. The anemometer with the redesigned cup rotors was recalibrated, but cup-shaft failure occurred again at a wind velocity of approximately 220 miles per hour. In the course of this calibration two standard generators were checked for signal output variation, and a wind-speed meter was calibrated for use with each of the redesigned cup rotors. The variation of pressure coefficient with air-flow direction at four orifices on a disk-shaped pitot head was obtained for wind velocities of 37.79 53.6, and 98.9 miles per hour. A pitot-static tube mounted in the nose of a vane was calibrated up to a dynamic pressure of 155 pounds per square foot, or approximately 256 miles per hour,

Vogler, Raymond D.↗
NASA NTRS2021

Effect of Soldering on Polymer and MnO2 Tantalum Capacitors

Soldering might have a strong effect on performance and reliability of most surface mount technology components, including tantalum capacitors. High quality tantalum capacitors are likely the only type of components where soldering simulation is the first step during screening. Nevertheless, post-soldering failures of tantalum capacitors happen and require additional analysis. Popcorning is a well-known effect in plastic encapsulated microcircuits (PEM) and it occurs also in chip tantalum capacitors. The sensitivity of parts to the presence of moisture during soldering is characterized by the moisture sensitivity level (MSL); however, contrary to PEMs, there is no standard procedure for establishing MSL for tantalum capacitors. The effect of absorbed moisture on soldering related degradation and failures in tantalum capacitors have not been studied properly yet, and there is no sufficient information regarding the difference in the sensitivity to soldering between polymer and MnO2 tantalum capacitors. In this work, 16 types of polymer and 9 types of MnO2 cathodes tantalum capacitors with different moisture content have been tested before and after reflow soldering. The level of moisture release after soldering has been estimated and thermo-mechanical analysis used to assess deformation of capacitors during soldering simulations. Results show that moisture uptake in similar parts is approximately two times greater in polymer than in MnO2 capacitors. Cracking of the case and degradation of parameters can occur in both types of parts, but MnO2 capacitors are much more likely to fail catastrophically with a short circuit and possible ignition during the first power-on cycle. This type of failure in MnO2 capacitors is lot-related, can occur even at derated voltages and relatively low levels of moisture sorption corresponding to room conditions. Baking before soldering is an effective measure to prevent failures even in lots susceptible to popcorning damage. Recommendations for baking and testing to establish MSL are suggested.

Alexander Teverovsky↗
NASA NTRS2021

Effect of Preconditioning on Post-Soldering Failures in Tantalum Capacitors

Soldering have a strong effect on performance and reliability of most surface mount technology components, including tantalum capacitors. High quality tantalum capacitors are likely the only type of components where soldering simulation is the first step during screening. Nevertheless, post-soldering failures of tantalum capacitors do happen and require additional analysis. Popcorning is a well-known effect in plastic encapsulated microcircuits (PEM) and it occurs also in chip tantalum capacitors. The sensitivity of parts to the presence of moisture during soldering is characterized by the moisture sensitivity level (MSL); however, contrary to PEMs, there is no standard procedure for establishing MSL for tantalum capacitors, and standard J-STD-020 is applicable partially only. In this work, the effect of absorbed moisture on soldering related degradation and failures in tantalum capacitors have been studied using 22 types of polymer and 11 types of MnO2 cathodes tantalum capacitors including single and multianode parts. The amount of moisture released during soldering has been estimated by measurements of mass and capacitance variations. Results show that moisture uptake in similar parts is approximately two times greater in polymer than in MnO2 capacitors. Cracking of the case and degradation of parameters can occur in both types of parts, but MnO2 capacitors are much more susceptible to catastrophic short circuit failures and their ignition is possible during the first power-on cycle. This type of failure in MnO2 capacitors is lot-related, can occur even at derated voltages and relatively low levels of moisture sorption corresponding to room conditions. Baking before soldering is an effective measure to prevent failures even in lots susceptible to popcorning damage. Recommendations for testing to establish MSL and for baking to reduce the probability of failures are suggested.

tantalum polymer capacitors↗
NASA NTRS2020

Popcorning Failures in Polymer and MnO2 Tantalum Capacitors

Popcorning is a well-known effect in plastic encapsulated microcircuits (PEM) and it occurs in chip tantalum capacitors. The sensitivity of components to the presence of moisture during soldering is characterized by the moisture sensitivity level (MSL); however, contrary to PEMs, there is no standard procedure for establishing MSL for tantalum capacitors.The effect of absorbed moisture on soldering related degradation and failures in tantalum capacitors have not been studied properly yet, and there is no sufficient information regarding the difference in the sensitivity to soldering between polymer and MnO2 capacitors. In this work, 16 types of polymer and 9 types of MnO2 tantalum capacitors with different moisture content have been tested before and after reflow soldering. The level of moisture release during soldering has been estimated and thermo-mechanical analysis used to assess deformation of capacitorsduring soldering simulations. Results show that moisture uptake in similar parts is approximately two times greater in polymer than in MnO2 capacitors. Cracking of the case and degradation of parameters can occur in both types of parts, but MnO2 capacitors are much more likely to fail catastrophically with a short circuit and possible ignition during the first power-on cycle. This type of failure in MnO2 capacitors is lot-related, can occur even at derated voltages and relatively low levels of moisture sorption that corresponds to room conditions. Baking before soldering is an effective measure to prevent failures even in lots susceptible to popcorning damage.

Capacitor↗
NASA NTRS2018

The Effects of Fiber Orientation and Adhesives on Tensile Properties of Carbon Fiber Reinforced Polymer Matrix Composite with Embedded Nickel-Titanium Shape Memory Alloys

Tensile tests of Nickel-titanium (NiTi) shape memory alloys (SMA) embedded within carbon fiber reinforced polymer matrix composite (CFRP/PMC) laminates were evaluated with simultaneous monitoring of modal acoustic emissions (MAE). Three different layup configurations utilizing two different thin film adhesives were applied to bond the materials. Ultimate tensile strengths, strains, and moduli were obtained along with cumulative AE energy of events and specimen failure location. Scanning electron microscopy was used to examine the break areas of the specimens post-test. Microscopy was used to validate failure locations revealed from MAE analysis. A unique finding within this research showed that 90° plies in the outer ply gave the strongest acoustic signals as well as the cleanest fracture of the specimens tested. Overlapping 0° ply layers surrounding the SMA was found to be the best scenario to prevent failure of the specimen itself.

Derek Quade↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗