Results for “failure mode analysis” — Page 14

NASA NTRS1988

Independent Orbiter Assessment (IOA): Assessment of the reaction control system, volume 2

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA effort first completed an analysis of the aft and forward Reaction Control System (RCS) hardware and Electrical Power Distribution and Control (EPD and C), generating draft failure modes and potential critical items. The IOA results were then compared to the proposed Post 51-L NASA FMEA/CIL baseline. This report documents the results of that comparison for the Orbiter RCS hardware and EPD and C systems. Volume 2 continues the presentation of IOA worksheets.

Prust, Chet D.↗

NASA NTRS1988

Independent Orbiter Assessment (IOA): Assessment of the reaction control system, volume 3

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA effort first completed an analysis of the aft and forward Reaction Control System (RCS) hardware and Electrical Power Distribution and Control (EPD and C), generating draft failure modes and potential critical items. The IOA results were then compared to the proposed Post 51-L NASA FMEA/CIL baseline. This report documents the results of that comparison for the Orbiter RCS hardware and EPD and C systems. Volume 3 continues the presentation of IOA worksheets.

Prust, Chet D.↗

NASA NTRS1988

Independent Orbiter Assessment (IOA): Assessment of the reaction control system, volume 4

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA effort first completed an analysis of the aft and forward Reaction Control System (RCS) hardware and Electrical Power Distribution and Control (EPD and C), generating draft failure modes and potential critical items. The IOA results were then compared to the proposed Post 51-L NASA FMEA/CIL baseline. This report documents the results of that comparison for the Orbiter RCS hardware and EPD and C systems. Volume 4 continues the presentation of IOA worksheets and contains the potential critical items list.

Prust, Chet D.↗

DOE OSTI2023

Liquid hydrogen storage system for heavy duty trucks: Configuration, performance, cost, and safety

In this work, we investigate the potential of liquid hydrogen storage (LH 2 ) on-board Class-8 heavy duty trucks to resolve many of the range, weight, volume, refueling time and cost issues associated with 350 or 700-bar compressed H 2 storage in Type-3 or Type-4 composite tanks. We present and discuss conceptual storage system configurations capable of supplying H 2 to fuel cells at 5-bar with or without on-board LH 2 pumps. Structural aspects of storing LH 2 in double walled, vacuum insulated, and low-pressure Type-1 tanks are investigated. Structural materials and insulation methods are discussed for service at cryogenic temperatures and mitigation of heat leak to prevent LH 2 boiloff. Failure modes of the liner and shell are identified and analyzed using the regulatory codes and detailed finite element (FE) methods. The conceptual systems are subjected to a Failure modes and effects analysis (FMEA) and a safety, codes, and standards (SCS) review to rank failures and identify safety gaps. The results indicate that the conceptual systems can reach 19.6% usable gravimetric capacity, 40.9 g-H 2 /L usable volumetric capacity and $174-183/kg-H 2 cost (2016 USD) when manufactured 100,000 systems annually.

08 HYDROGEN↗

NASA NTRS2000

High Energy Flywheel Containment Evaluation

A flywheel testing facility is being constructed at the NASA Glenn Research Center. This facility is to be used for life cycle testing of various flywheel rotors. The lifecycle testing consists of spinning a rotor from a low rpm (approx. 20,000 ) to a high rpm (approx. 60,000) and then back to the low rpm. This spin cycle will model that which the rotor will see during use. To simulate the lifetime of the rotor, the spin cycle will be performed tens of thousands of times. A typical life cycle spin test is expected to last six months. During this time the rotor will be spun through a cycle every five minutes. The test will run continuously for the six month period barring a flywheel failure. Since it is not reasonable to have the surrounding area evacuated of personnel for the duration of the testing, the flywheel facility has to be designed to withstand a flywheel rotor failure and insure that there is no danger to any personnel in the adjacent buildings or surrounding areas. In order to determine if the facility can safely contain a flywheel rotor failure an analysis of the facility in conjunction with possible flywheel failure modes was performed. This analysis is intended as a worst case evaluation of the burst liner and vacuum tank's ability to contain a failure. The test chamber consists of a cylindrical stainless steel vacuum tank, two outer steel containment rings, and a stainless steel burst liner. The stainless steel used is annealed 302, which has an ultimate strength of 620 MPa (90,000 psi). A diagram of the vacuum tank configuration is shown. The vacuum tank and air turbine will be located below ground in a pit. The tank is secured in the pit with 0.3 m (12 in.) of cement along the base and the remaining portion of the tank is surrounded by gravel up to the access ports. A 590 kg (1300 lb.) bulkhead is placed on top of the pit during operation and the complete facility is housed within a concrete structure which has 7.5 cm (3 in.) thick walls. A cutaway of the facility is shown.

Colozza, Anthony J.↗

DOE OSTI2026

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗

DOE OSTI2024

Recommended Actions to Improve Adapter Safety

With the rapid advancement and acceleration in the electric vehicle (EV) industry within the United States, major automakers and EV charging companies are increasingly adopting the North American Charging Standard (NACS) connector style, now officially known as J3400. This shift is expected to enhance charging infrastructure, providing a better customer experience by making it easier for all EV drivers to access a wider network of direct-current (DC) fast chargers (DCFCs). However, the adoption of the J3400 standard presents challenges for many EVs already on the roads and some currently coming off production lines that are equipped with the Combined Charging System (CCS) connector, which this report will refer to as the North American standard, CCS1. These vehicles will need adapters to use new or existing J3400 infrastructure. During this transition, several issues have emerged. Firstly, there is a need to standardize the new connector type to ensure it is interoperable, safe, and reliable. Second, existing CCS EV drivers need a way to access the J3400 network, which will require electric vehicle supply equipment (EVSE) or sites with both connector types, driver-provided adapters to physically convert from CCS to J3400, or EVSE with retained adapters designed for use with the EVSE. Third, adapter standards will need to be written to specify how they will be designed and what evaluations will be needed to ensure safe and reliable performance. To address these challenges, adapters that support different types of charging connectors will be essential. These adapters will play a crucial role in supporting the transition and ensuring continued service for legacy EVs with CCS inlets as the J3400 standard becomes the predominant one in the United States. Consequently, the National Charging Experience (ChargeX) Consortium has investigated and performed a teardown analysis on the different adapter versions on the market. The aim is to create a failure mode and effects analysis (FMEA) on what are expected to be the most common adapter types used in this transition. In order to support this work, we executed an FMEA exercise with the main goal of identifying gaps in the existing adapters' performance and conformance to the most common safety requirements of high-power and high-voltage devices. This effort focused on adapters provided by the driver, as these may present the highest safety and reliability risks. The recommendations made here apply to both retained and driver-provided adapters.

25 ENERGY STORAGE↗

DOE OSTI2021

Data requirements for improving the Quantitative Risk Assessment of liquid hydrogen storage systems

Quantitative Risk Assessment (QRA) supports the development of risk-informed safety codes and standards which are employed to enable the safe deployment of hydrogen technologies essential to decarbonize the transportation sector. System reliability data is a necessary input for rigorous QRA. Here, the lack of reliability data for bulk liquid hydrogen (LH 2 ) storage systems located on site at fueling stations limits the use of QRAs. In turn, this hinders the ability to develop the necessary safety codes and standards that enable worldwide deployment of these stations. Through a QRA-based analysis of a LH 2 storage system, this work focuses on identifying relevant scenario and probability data currently available and ascertaining future data collection requirements regarding risks specific to liquid hydrogen releases. The work developed consists of the analysis of a general bulk LH 2 storage system design located at a hydrogen fueling station. Failure Mode and Effect Analysis (FMEA) and traditional QRA modeling tools such as Event Sequence Diagrams (ESD) and Fault Tree Analysis (FTA) are employed to identify, rank, and model risk scenarios related to the release of LH 2 . Based on this analysis, scenario and reliability data needs to add LH 2 -related components to QRA are identified with the purpose of improving the future safety and risk assessment of these systems.

08 HYDROGEN↗

NASA NTRS1990

A methodology for probabilistic prediction of structural failures of launch vehicle propulsion systems

A quantitative methodology for estimating the probability of occurrence of critical structural failure modes of launch vehicle propulsion systems during mission operation is presented. In this approach, engineering analysis models that characterize specific failure modes based on the physics and mechanics of the failure phenomenon are used in a prescribed probabalistic structure in which quantified uncertainty in the information used in the analysis and quantified uncertainty of the engineering analysis models themselves are both considered in estimating failure risk. The methodology is applicable to high cycle fatigue, low cycle fatigue, flaw propagation stress rupture, and other failure modes of launch vehicle propulsion systems and other space-flight systems. The probabalistic failure assessment presented provides the capability of performing quantitative analyses to rank options to improve reliability, thereby enabling limited financial resources of development and improvement programs to be more effectively allocated.

Moore, N.↗

NASA NTRS2016

S&MA Internship to Support Orion and the European Service Module

As a University Space Research Association (USRA) intern for NASA Johnson Space Center (JSC) during the summer 2016 work term, I worked on three main projects for the Space Exploration Division (NC) of the Safety and Mission Assurance (S&MA) Directorate. I worked on all three projects concurrently. One of the projects involved facilitating the status and closure of technical actions that were created during European Service Module (ESM) safety reviews by the MPCV Safety & Engineering Review Panel (MSERP). The two main duties included accurately collecting and summarizing qualitative data, and communicating that information to the European Space Agency (ESA) and Airbus (ESA's prime contractor) in a clear, succinct and precise manner. This project also required that I create a report on the challenges and opportunities of international S&MA. With its heavy emphasis on soft skills, this project taught me how to communicate better, by showing me how to present and share information in an easy-to-read and understandable format, and by showing me how to cooperate with and culturally respect international partners on a technical project. The second project involved working with the Orion Thermal Protection System (TPS) Process Failure Modes and Effects Analysis (PFMEA) Working Group to create the first full version of the Orion TPS PFMEA. The Orion TPS PFMEA Working Group met twice a week to analyze the Avcoat block installation process for failure modes, the failure modes effects, and how such failure modes could be controlled. I was in charge of implementing changes that were discussed in meeting, but were not implemented real time. Another major task included creating a significant portion of the content alongside another team member outside the two weekly meetings. This project caused me to become knowledgeable about TPS, heatshields, space-rated manufacturing, and non-destructive evaluation (NDE). The project also helped me to become better at working with a small team and helped improved my technical communication skills. My main duty for the third project was creating a Safety Verification Tracking Log (SVTL) for the Orbital Maneuvering System Engine (OMS-E), and contacting subject matter experts to close Hazard Report (HR) control verifications. This project also required me to support other OMS-E safety process tasks, like monitoring OMS-E vibration testing for Quality Assurance (QA) purposes. This project helped me become even more proficient in Excel. Throughout the project, I gained knowledge about the OMS-E system and improved my understanding of pressure systems and propellant systems. In terms of education goals, this work term has affirmed my desire to take a few more space-related courses, like orbital mechanics, so that I can have a better understanding of human spaceflight and the industry surrounding it. However, the work term did not persuade me to pursue a master's degree. In terms of career goals, this work term has helped me clarify the direction I would like to head in the future. The perspective of three summer terms working for NASA in S&MA has allowed me to observe that most S&MA employees joined S&MA after working in other NASA directorates, such as Engineering or Flight Operations. It is my belief that it would be advantageous for both NASA and I for me to broaden my knowledge base and technical skill set by completing hands-on technical work on human spaceflight projects, and for me to integrate my safety experience directly into technical work in other directorates. The other significant advantage to this proposed situation is that if I were to eventually return to S&MA, I would be returning with a substantial set of hands-on technical experience and knowledge, which would be a significant resource for S&MA tasks and projects.

Hutcheson, Connor↗

NASA NTRS1995

Comprehension and retrieval of failure cases in airborne observatories

This paper describes research dealing with the computational problem of analyzing and repairing failures of electronic and mechanical systems of telescopes in NASA's airborne observatories, such as KAO (Kuiper Airborne Observatory) and SOFIA (Stratospheric Observatory for Infrared Astronomy). The research has resulted in the development of an experimental system that acquires knowledge of failure analysis from input text, and answers questions regarding failure detection and correction. The system's design builds upon previous work on text comprehension and question answering, including: knowledge representation for conceptual analysis of failure descriptions, strategies for mapping natural language into conceptual representations, case-based reasoning strategies for memory organization and indexing, and strategies for memory search and retrieval. These techniques have been combined into a model that accounts for: (a) how to build a knowledge base of system failures and repair procedures from descriptions that appear in telescope-operators' logbooks and FMEA (failure modes and effects analysis) manuals; and (b) how to use that knowledge base to search and retrieve answers to questions about causes and effects of failures, as well as diagnosis and repair procedures. This model has been implemented in FANSYS (Failure ANalysis SYStem), a prototype text comprehension and question answering program for failure analysis.

Alvarado, Sergio J.↗

NASA NTRS2019

Achieving Improved Reliability with Failure Analysis

Reliability is the ability of a product to properly function, within specified performance limits, for a specified period of time, under the life cycle application conditions. Failure analysis is a vital tool in the effort to ensure reliability of electronic products and systems throughout their product lifecycle. Today, organizations involved in activities within the electronics supply chain are facing new challenges, not just from complex assembly styles, harsher lifecycle environments, and sophisticated supply chains, but also from customers who are demanding a quicker turn-around. Unfortunately, root cause failure analysis is often performed incompletely, leading to a poor understanding of failure mechanisms and causes and, customer dissatisfaction due to recurring failures. The PDC (Professional Development Course) starts with an introduction to reliability concepts, physics of failure and an overview of failure mechanisms that affect PCBs (Printed Circuit Boards), PCBAs (Printed Circuit Board Assembly) and components. The PDC then dives into root cause hypothesizing techniques (Pareto, FMEA (Failure Modes and Effects Analysis), fishbone (Cause-And-Effect Diagram), FTA (Fault Tree Analysis)), non-destructive and destructive analysis and, materials characterization will be discussed. Numerous failure analysis case studies will be used to illustrate the techniques and analysis principles to arrive at the root cause(s) of field failures on printed circuit boards, active components, and assemblies. What Attendees will Learn: Topics include: Overview of Reliability Concepts Failure mechanisms of electronic products Root cause analysis Failure analysis techniques -Non-destructive techniques (optical, CSAM (Confocal Scanning Electron Microscopy) etc.) -Destructive analysis (DPA (Destructive Physical Analysis), Decap (Decapsulation), FIB (Focused Ion Beam) etc.) -Materials characterization (XRF (X-Ray Fluorescence) , EDS (Error Detection Sequential), TMA/DSC (Thermal Mechanical Analysis/Differential Scanning Calorimetry) etc.)

PCB quality↗

NASA NTRS2002

Human Factors Process Task Analysis: Liquid Oxygen Pump Acceptance Test Procedure at the Advanced Technology Development Center

This viewgraph presentation provides information on Human Factors Process Failure Modes and Effects Analysis (HF PFMEA). HF PFMEA includes the following 10 steps: Describe mission; Define System; Identify human-machine; List human actions; Identify potential errors; Identify factors that effect error; Determine likelihood of error; Determine potential effects of errors; Evaluate risk; Generate solutions (manage error). The presentation also describes how this analysis was applied to a liquid oxygen pump acceptance test.

Diorio, Kimberly A.↗

NASA NTRS1989

Model 0A wind turbine generator FMEA

The results of Failure Modes and Effects Analysis (FMEA) conducted for the Wind Turbine Generators are presented. The FMEA was performed for the functional modes of each system, subsystem, or component. The single-point failures were eliminated for most of the systems. The blade system was the only exception. The qualitative probability of a blade separating was estimated at level D-remote. Many changes were made to the hardware as a result of this analysis. The most significant change was the addition of the safety system. Operational experience and need to improve machine availability have resulted in subsequent changes to the various systems which are also reflected in this FMEA.

Klein, William E.↗

NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗

NASA NTRSDate not supplied

From BERTopic to SysML: Informing Model-Based Failure Analysis With Natural Language Processing for Complex Aerospace Systems

The development of emerging complex aerospace systems will require new approaches for capturing safety incident scenarios as early as possible in the design phase. However, for novel systems, relevant data available is limited. In this work, we propose a framework informing model-based mission assurance activities with historical incident reports, lessons learned, or other relevant engineering documents using natural language processing. In doing so, we investigate whether there is useful information in data sets that are relevant, if not identical, to the system under design and whether, through rigorous systems engineering practice, this information can be effectively leveraged through model-based failure analysis. In a worked case study, we apply state-of-the-art topic modeling techniques to two data sets, a mission relevant data set and a system relevant data set. The sets of topics are merged and interpreted to form a preliminary list of failure topics that can be used to inform the identification of off-nominal modes in the model-based failure modes and effects analysis development. Once data from the system in operation is available, it can be used to update the topics identified. By extracting information about likely failures from relevant historical data sets and utilizing model-based mission assurance to ensure relevance and rigor, unanticipated failures can be reduced, and projects can more effectively learn from past missions.

Failure Analysis↗

NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗

NASA NTRSDate not supplied

What Went Wrong: A Survey of Wildfire UAS Mishaps through Named Entity Recognition

Increasingly, unmanned aircraft systems (UAS) are being applied to wildfire incidents for tasks such as mapping, aerial ignition, and delivery. As a result, incident reporting systems for wildfires are beginning to accumulate data related to UAS mishaps in wildfire response. In this research, we apply state-of-the-art natural language processing (NLP) techniques to develop a custom Named Entity Recognition (NER) model which extracts a Failure Modes and Effects Analysis (FMEA)-style survey of wildfire UAS mishaps reported in SAFECOM. The custom NER model is built by fine-tuning an existing (BERT) model, resulting in a generalizable NER model that can extract engineering relevant entities including failure modes, causes, effects, control processes, and recommendations from any failure-relevant text. Similar mishaps are clustered and reported as single rows within the FMEA. For each cluster, frequency, severity, and overall risk are computed. The methodology can be applied as part of a broader safety management system to track trends in mishaps and discover knowledge that can be utilized to improve safety outcomes and system performance.

Machine Learning↗