Cost-Effective Assessment of System Reliability Using Data From Subsystem/Assembly Level
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Cost-Effective Assessment↗
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Reliability and Safety Assessment of Urban Air Mobility Concept Vehicles
The primary objective of this research effort is to identify failure modes and hazards associated with several configurations of multicopter concept vehicles supplied by NASA. Functional hazard analyses (FHA) and failure modes and effects criticality analyses (FMECA) are performed for each of the eight vehicle configurations under review. Conceptual design of notional powertrain configurations (turboshaft, electric, hybrid electric), notional thrust control systems (rpm control and collective control), and navigation control systems for the concept vehicles were to support the reliability and safety analysis and to assess whether a mission can be completed safely. Two kinds of analyses are performed: static safety analysis which enable the quantification of the likelihood of individual events, and dynamic safety analyses which allows the investigation of multiple time-dependent failures. Their objective is to quantify the likelihood of catastrophic failures.
Urban Air Mobility↗
System reliability and risk assessment task goals and status
The major focus for continued development of the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) codes is in support of system testing and certification of advanced propulsion systems. Propulsion system testing has evolved over the years from tests designed to show success, to tests designed to reveal reliability issues before service use. Such test conditions as performance envelope corners, high rotor imbalance, power dwells, and overspeed tests are designed to shake out problems that can be associated with low and high cycle fatigue, creep, and stress rupture, bearing durability, and the like. Subsystem testing supports system certification by standing as an early evaluation of the same durability and reliability concerns as for the entire system. The NESSUS software system is being further developed to support the definition of rigorous subsystem and system test definition and reliability certification. The principal technical issues are outlined which are related to system reliability, including key technology issues such as failure mode synergism, sequential failure mechanisms, and fault tree definition.
Cruse, T. A.↗
Risk-informed Graded Approach for Reliability and Performance Assessment of Sensor and Instrumentation Systems within Advanced Condition Monitoring Technologies
Advanced condition monitoring (ACM) technologies, such as digital twins, are innovative strategies designed to provide real-time health insights, including the remaining useful life of components. The primary goal of ACM is to predict and alert operators to potential functional failures before they occur. ACM systems achieve this by integrating predictive models with various sensor instrumentation, analog-to-digital converters, data warehouses, and data pre-processors. These sensor and instrumentation systems (SIS) are essential for forming a comprehensive understanding of component conditions and ensuring the predictive success of ACM programs. Introducing new technologies like ACM involves varying degrees of risk that can impact plant reliability. Therefore, risk mitigation should be commensurate with the performance and reliability of the developed technology, following a risk-informed graded approach (RIGA). Establishing a RIGA process requires a clear understanding of the hazards and reliability of all subsystems, including their interdependencies and potential impacts on the overall system. Given the critical role of SIS in ACM, this work reviews hazard identification and reliability quantification methods for SIS. It also considers these methods' implications when developing a RIGA process for ACM.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Constructing the "Best" Reliability Data for the Job
Modern business and technical decisions are based on the results of analyses. When considering assessments using "reliability data", the concern is how long a system will continue to operate as designed. Generally, the results are only as good as the data used. Ideally, a large set of pass/fail tests or observations to estimate the probability of failure of the item under test would produce the best data. However, this is a costly endeavor if used for every analysis and design. Developing specific data is costly and time consuming. Instead, analysts rely on available data to assess reliability. Finding data relevant to the specific use and environment for any project is difficult, if not impossible. Instead, we attempt to develop the "best" or composite analog data to support our assessments. One method used incorporates processes for reviewing existing data sources and identifying the available information based on similar equipment, then using that generic data to derive an analog composite. Dissimilarities in equipment descriptions, environment of intended use, quality and even failure modes impact the "best" data incorporated in an analog composite. Once developed, this composite analog data provides a "better" representation of the reliability of the equipment or component can be used to support early risk or reliability trade studies, or analytical models to establish the predicted reliability data points. Data that is more representative of reality and more project specific would provide more accurate analysis, and hopefully a better final decision.
DeMott, D. L.↗
Constructing the Best Reliability Data for the Job
Modern business and technical decisions are based on the results of analyses. When considering assessments using "reliability data", the concern is how long a system will continue to operate as designed. Generally, the results are only as good as the data used. Ideally, a large set of pass/fail tests or observations to estimate the probability of failure of the item under test would produce the best data. However, this is a costly endeavor if used for every analysis and design. Developing specific data is costly and time consuming. Instead, analysts rely on available data to assess reliability. Finding data relevant to the specific use and environment for any project is difficult, if not impossible. Instead, we attempt to develop the "best" or composite analog data to support our assessments. One method used incorporates processes for reviewing existing data sources and identifying the available information based on similar equipment, then using that generic data to derive an analog composite. Dissimilarities in equipment descriptions, environment of intended use, quality and even failure modes impact the "best" data incorporated in an analog composite. Once developed, this composite analog data provides a "better" representation of the reliability of the equipment or component can be used to support early risk or reliability trade studies, or analytical models to establish the predicted reliability data points. Data that is more representative of reality and more project specific would provide more accurate analysis, and hopefully a better final decision.
Kleinhammer, R. K.↗
Open data sets for assessing photovoltaic system reliability
Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.
14 SOLAR ENERGY↗
Application of Thévenin equivalent sensitivity equations for reliable voltage stability assessment
In this paper, sensitivity equations for the Thévenin equivalent parameters, voltage and reactance, are derived using the duality between the Thévenin parameters from two consecutive PMU measurements. Using the sensitivity equation for the Thévenin reactance, a robust adaptive X-Th algorithm is developed aiming to extend a well-known adaptive E-Th approach by being able to accurately estimate the parameters for a wider range of loading conditions. In the performed case studies the resulting accuracy is evaluated when estimating the Thévenin parameters for large disturbances, for two sides with respect to a boundary bus, accommodating sensitivity to topology changes and nonlinearities in power systems. In conclusion, the results can be used for accurate voltage stability assessment using the Thévenin parameters.
42 ENGINEERING↗
Spatiotemporal Variability of Electric System Reliability Metrics
As urbanization continues to grow, urban density also rises, placing significant stress on critical infrastructure. Cities often face challenges in investing in new infrastructure or upgrading existing ones. One area of infrastructure that has come under strain is the electric grid, leading to prolonged power outages. According to data from the U.S. Energy Information Administration, the average duration of power outages has steadily doubled from 2013 to 2021, primarily due to extreme weather events. The IEEE has developed a series of reliability metrics to assess the reliability of the electric system. However, these metrics are only applied at the utility level, making it challenging to comprehend the variations in these indices at finer spatial resolutions and, consequently, evaluate reliability at the non-utility level. In this study, we leveraged electric outage data collected at 15-minute intervals at the county level to estimate electric system reliability over a six-year period using a novel data analysis approach. Our findings reveal a gradual decline in reliability in the U.S. Southwest compared to national averages. Furthermore, the duration of outages per customer per event has significantly decreased in large portions of California and Florida. These discoveries can be valuable for utility companies as they seek to pinpoint regional anomalies and plan for prioritized remediation efforts.
Singh, Nagendra↗
A Novel Framework for Performance Evaluation and Design Optimization of PCM Embedded Heat Exchangers for the Built Environment
This research sheds light on the performance evaluation and design optimization of PCM-HXs for the built environment, addressing several barriers to practical issues to PCM-HX commercialization such as modeling aspects (i.e., modeling expertise and computational / time investment, etc.), manufacturing aspects (i.e., at-scale manufacturing, cost assessments, etc.) and experimental performance assessment (i.e., reliable experimental data, assessment of multiple PCM-working fluid combinations, etc.). We present a novel, comprehensive, and experimentally-validated design optimization framework for PCM-HXs capable of simulating any PCM-HX geometry with reasonable accuracy and significant computational time savings when compared to traditional CFD-based design practices. The framework was validated for a wide range of PCM-HX configurations, including a design optimization for a domestic hot water heater application where TES partially replaces electrical heating input. The resulting PCM-HXs were found to deliver 34-68% of the total daily hot water supply with only 5-10% package volume increase from the water heater, thus within U.S. DOE targets for TES systems. To identify the most promising HXs for PCM applications, first-order geometry and cost analyses were conducted based on off-the-shelf HX products. As part of this work, 9 PCM-HX prototypes were manufactured using additive and conventional manufacturing methods. Detailed economy-of-scale assessments were conducted for the most promising PCM-HXs and were found to have a good outlook for the next 5-10 years. The PCM-HX design optimization framework was validated through comprehensive in-house experimental testing using newly-developed PCM-to-fluid test facilities. In total,10 total in-house component-level experiments were conducted using these prototypes, including 9 with water and 1 with refrigerant (R410A) as the working fluid. It was found that the framework can successfully predict experimental thermal-hydraulic performance within ±10-20% the first time without manual design changes, eliminating the need for time-consuming and expensive prototyping efforts as part of the design process. As part of this work, a publicly-available PCM web tool was released which includes a PCM property database (531 PCMs) and PCM-HX modeling tool to assist the design community on common PCM-HX use-cases, e.g., single/multiple flow path(s) fluid-to-PCM and air-to-fluid-to-PCM configurations (https://ceeeweb.umd.edu/pcmapp/). This work will accelerate the design and time to market for next generation PCM-HXs.
25 ENERGY STORAGE↗
Assessment of NDE reliability data
Twenty sets of relevant nondestructive test (NDT) reliability data were identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations was formulated, and a model to grade the quality and validity of the data sets was developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, were formulated for each NDE method. A comprehensive computer program was written and debugged to calculate the probability of flaw detection at several confidence limits by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. An example of the calculated reliability of crack detection in bolt holes by an automatic eddy current method is presented.
Yee, B. G. W.↗
Assessment of NDE Reliability Data
Twenty sets of relevant Nondestructive Evaluation (NDE) reliability data have been identified, collected, compiled, and categorized. A criterion for the selection of data for statistical analysis considerations has been formulated. A model to grade the quality and validity of the data sets has been developed. Data input formats, which record the pertinent parameters of the defect/specimen and inspection procedures, have been formulated for each NDE method. A comprehensive computer program has been written to calculate the probability of flaw detection at several confidence levels by the binomial distribution. This program also selects the desired data sets for pooling and tests the statistical pooling criteria before calculating the composite detection reliability. Probability of detection curves at 95 and 50 percent confidence levels have been plotted for individual sets of relevant data as well as for several sets of merged data with common sets of NDE parameters.
Yee, B. G. W.↗
Methods for assessing the structural reliability of brittle materials
Failure from contact-induced surface flaws is considered along with controlled indentation flaws for construction of toughness and fatigue master maps, fatigue properties of ceramics with natural and controlled flaws, and a statistical analysis of size and stress state effects on the strength of an alumina ceramic. Attention is also given to dynamic and static fatigue of a machinable glass ceramic, the effect of multiregion crack growth on proof testing, and a fracture mechanics analysis of defect sizes. Other topics explored are related to the effect of temperature and humidity on delayed failure of optical glass fibers, subthreshold indentation flaws in the study of fatigue properties of ultrahigh-strength glass, the lifetime prediction for hot-pressed silicon nitride at high temperatures, static fatigue in high-performance ceramics, and requirements for flexure testing of brittle materials.
Freiman, S. W.↗
Systems Safety, Reliability, and Risk Assessment. Task 4: Safety and Launch Vehicle Review Support
This report summarizes support provided by Science Applications International Corporation (SAIC) to the NASA/Marshall Space Flight Center (MSFC). Work under this contract was performed in support of the Advanced Space Transportation Program and the Second Generation RLV Program Office.
Source record↗
Cost Effective Assessment of System Reliability Using Data From Subsystem/Assembly Level Testing
The paper describes a simple method developed to use and combine subsystem or assembly level accelerated test results withthe system level test results to estimate achieved overall system reliability.
achieved↗
Space Shuttle Main Engine (SSME) Reliability and Analysis Evolution
The Space Shuttle Main Engine (SSME) is a large thrust class, reusable, staged combustion cycle rocket engine employing liquid hydrogen and liquid oxygen propellants. A cluster of three SSMEs is used on every space shuttle mission to propel the space shuttle orbiter vehicle into low earth orbit. Development of the SSME began in the early 70 s and the first flight of the space shuttle occurred in 1981. Today, the SSME has accrued over one million seconds of ground test and flight operational time, launching 129 space shuttle missions. Given that the SSME is used to launch a manned vehicle, its reliability must be commensurate for the task. At the same time, the SSME is a high performance, high power density engine which traditionally does not lend itself towards high reliability. Furthermore, throughout its history, the SSME operational envelope has been explored and expanded leading to several major test failures. Hence, assessing the reliability of the SSME throughout its history has been a challenging undertaking. This paper provides a review and discussion of SSME reliability assessment techniques and results over its history. Basic reliability drivers such as engine design, test program, major failures, redesigns and upgrades will also be discussed.
Stephens, Walter E.↗
An Approach to Dynamic Human Reliability Analysis using EMRALD Dynamic Risk Assessment Tool
Research for dynamic human reliability analysis (HRA) (a.k.a., simulation-based or computation-based HRA) has been required, as many researchers have emphasized the importance of dynamic approaches to probabilistic safety assessment (PSA). This study proposes the PRocedure-based Investigation Method of EMRALD Risk Assessment – Human Reliability Analysis (PRIMERA-HRA) method, which is an approach to dynamic HRA using the Event Modeling Risk Assessment using Linked Diagram (EMRALD) software developed by Idaho National Laboratory (INL). In this study, how to model human actions using the software and evaluate the error probabilities is suggested. The applicability of this approach will be also investigated through an extended loss of AC power (ELAP) scenario. Then, major insights from this dynamic HRA approach against the static one will be discussed in the paper.
99 GENERAL AND MISCELLANEOUS↗
Reliability Quantification of Advanced Stirling Convertor (ASC) Components
The Advanced Stirling Convertor, is intended to provide power for an unmanned planetary spacecraft and has an operational life requirement of 17 years. Over this 17 year mission, the ASC must provide power with desired performance and efficiency and require no corrective maintenance. Reliability demonstration testing for the ASC was found to be very limited due to schedule and resource constraints. Reliability demonstration must involve the application of analysis, system and component level testing, and simulation models, taken collectively. Therefore, computer simulation with limited test data verification is a viable approach to assess the reliability of ASC components. This approach is based on physics-of-failure mechanisms and involves the relationship among the design variables based on physics, mechanics, material behavior models, interaction of different components and their respective disciplines such as structures, materials, fluid, thermal, mechanical, electrical, etc. In addition, these models are based on the available test data, which can be updated, and analysis refined as more data and information becomes available. The failure mechanisms and causes of failure are included in the analysis, especially in light of the new information, in order to develop guidelines to improve design reliability and better operating controls to reduce the probability of failure. Quantified reliability assessment based on fundamental physical behavior of components and their relationship with other components has demonstrated itself to be a superior technique to conventional reliability approaches based on utilizing failure rates derived from similar equipment or simply expert judgment.
Shah, Ashwin R.↗