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At least 505 records · Page 28

A Vision for Spaceflight Reliability: NASA's Objectives Based Strategy

In defining the direction for a new Reliability and Maintainability standard, OSMA has extracted the essential objectives that our programs need, to undertake a reliable mission. These objectives have been structured to lead mission planning through construction of an objective hierarchy, which defines the critical approaches for achieving high reliability and maintainability (R M). Creating a hierarchy, as a basis for assurance implementation, is a proven approach; yet, it holds the opportunity to enable new directions, as NASA moves forward in tackling the challenges of space exploration.

Strategy↗

Spaceflight Reliability: An Objectives-Based Strategy

In defining the direction for a new Reliability and Maintainability standard, OSMA has extracted the essential objectives that our programs need, to undertake a reliable mission. These objectives have been structured to lead mission planning through construction of an objective hierarchy, which defines the critical approaches for achieving high reliability and maintainability (R M). Creating a hierarchy, as a basis for assurance implementation, is a proven approach; yet, it holds the opportunity to enable new directions, as NASA moves forward in tackling the challenges of space exploration.

Reliability and Maintainability↗

Verification of Triple Modular Redundancy Insertion for Reliable and Trusted Systems

If a system is required to be protected using triple modular redundancy (TMR), improper insertion can jeopardize the reliability and security of the system. Due to the complexity of the verification process and the complexity of digital designs, there are currently no available techniques that can provide complete and reliable confirmation of TMR insertion. We propose a method for TMR insertion verification that satisfies the process for reliable and trusted systems.

Verification↗

Challenges Regarding IP Core Functional Reliability

For many years, intellectual property (IP) cores have been incorporated into field programmable gate array (FPGA) and application specific integrated circuit (ASIC) design flows. However, the usage of large complex IP cores were limited within products that required a high level of reliability. This is no longer the case. IP core insertion has become mainstream including their use in highly reliable products. Due to limited visibility and control, challenges exist when using IP cores and subsequently compromise product reliability. We discuss challenges and suggest potential solutions to critical application IP insertion.

IP cores↗

Inclusion of Radiation Environment Variability for Reliability Estimates for SiC Power MOSFETs

Variability of the solar energetic particle environment is investigated for single-event-burnout reliability of silicon-carbide power metal-oxide-semiconductor field effect transistors. A probabilistic assessment of failure evaluates the benefits of de-rating voltage, shielding, and mission length. The Prediction of Solar particle Yields for Characterizing Integrating Circuits code is used to calculate a cumulative density function for the fluence of the environment. The lethal ion method is then used to determine what proportion of the environment will cause single-event-burnout. The operating voltage determines the lowest linear-energy-transfer particle that will cause single-event-burnout and that should be included in the environment distribution. The shielding and mission length also determine the final environment distribution of the mission fluence. Through calculating the reliability for different operating voltages, shielding, and mission length for a specific device, it is shown that shielding thickness and operating voltage have a large effect on reliability and can be traded off during the design.

Heavy ion↗

The Reliability Function

Mathematically, reliability is the probability of success. First, we will present the calculus needed to comprehend basic probability theory. Second, we will introduce The Reliability Function and its basic properties. Last, we will demonstrate The Reliability Function in a notional fatigue life example.

Reliability↗

Considerations for Qualifying Reliable Eddy Current Array Technique for Detection of Backwall Cracks

A reliable nondestructive evaluation (NDE) technique provides minimum 90% probability of detection(POD) with 95% confidence for detection of cracklike flaws of a qualified size. In this case, the flaws are on backside of material. Eddy current array (ECA) probe or a single sensor eddy current probe in c-scanning mode is used for the flaw detection. Here, two geometries are considered for the test specimens. The two geometries are, a flat plate, and tube or pipe. The probe is assumed to be on outer diameter (OD)surface and the flaw is assumed to be at the inner diameter (ID) surface for tube inspection. The flaw and probe are on opposite side of wall thickness for inspection of plate material. The application may be used for acreage inspection or just for inspection of butt weld and heat affected zone (HAZ) in a tube, cylinder, or plate. The proposed approach is based on developing an instrument standardization or calibration procedure. Decision threshold of inspection procedure is determined using empirical qualification and noise data. The work explores essential parameters that are required to meet certain conditions to ensure reliable flaw detection. Physics-based simulation of eddy current array flaw detection is used to understand effect of essential parameters on signal response (amplitude and phase),and therefore flaw detectability. Simulation data is used to justify choice of calibration reference standard requirements and the qualification approach. An ECA technique qualification model is provided. The paper gives brief description of tasks to be completed for qualifying ECA technique for reliable detection of cracklike flaws.

Eddy current array inspection, nondestructive eval↗

Proposed Reliability-Based Damage Tolerance Guidelines for Space Systems

Deterministic damage tolerance guidelines for highly reusable and efficiently designed launch systems can be challenging to meet and result in overly conservative assessments for tightly controlled manufacturing processes. Deterministic approaches may be unconservative when the structure is workmanship sensitive and there is a wide spread in fracture properties. Reliability-based damage tolerance assessments targeting a component reliability over the service life commensurate to mission risk posture is a promising alternative. Low production rates, short fleets, and lack of standards or guidance has slowed down widespread adoption of this method. Guidance for the robust application of reliability-based damage tolerance for space systems are proposed. These guidelines cover the treatment of uncertainty in damage tolerance analysis, the collection of data to develop probabilistic distributions, uncertainty propagation methods, and types of hardware.

Reliability-Based Damage Tolerance↗

Improving Real-world Measurement-based Phase Identification in Power Distribution Feeders with a Novel Reliability Criteria Assessment

This paper is concerned with solving the phase identification problem in a real-world smart grid project; where there is only a few smart meters available on each of the five power distribution feeders in the test site in Riverside, CA. The main idea is to develop and use two reliability criteria that can identify the most reliable components in a broken-down phase identification analysis; thereby significantly improving the accuracy of phase identification. The proposed method consists of three steps. The results from field implementation reveal the accuracy and consistency of the proposed method in practice, in correctly and reliability identifying the phase connectivity.

Phase identification Data-driven method Sliding wi↗

Drivetrain Reliability Collaborative Update

Pitch bearings, main bearings, and gearboxes in conventional wind turbine drivetrains often do not meet their 20-year minimum specified lifetime, resulting in turbine downtime as well as expensive, time-consuming repairs or replacements. The dominant failure modes of the drivetrain components and the conditions that lead to their failure are not fully accounted for during product design or routinely modeled for life management. Drivetrain reliability improvements and O&M cost reductions remain top priorities for both land-based and offshore wind turbines, especially as wind turbines continue to be deployed in increasingly remote and offshore locations, continue to increase in size, and are becoming expected to be in service beyond their original design life, all of which correspond to an increase in the impact of any reliability issues on O&M costs. This presentation summarizes the most recent activities by NREL and ANL on drivetrain reliability.

bearing↗

Component Reliability R&D

A review of the work done on the hydrogen Component Reliability R&D project in the last year. The National Renewable Energy Laboratory's (NREL) Hydrogen Safety Research and Development (HSR&D) program in collaboration with the University of Maryland's Systems Risk and Reliability Analysis Laboratory (SyRRA) are working to improve reliability and reduce risk in hydrogen systems through the use of use quantitative data on component leaks and failures, together with Prognosis and Health Management (PHM), and Quantitative Risk Assessment (QRA).

component↗

Follow-Up from the Photovoltaic Reliability Workshop (PVRW): Cost Modeling Capabilities to Evaluate Trends in PV Technologies

NREL's Solar and Storage Techno-Economic Analysis (TEA) team reviews live polling results from the Photovoltaic Reliability Workshop (PVRW) related to module technology trends believed to have the greatest reliability impacts. Then, the team reviews the publicly available tools and inputs necessary for evaluating reliability tradeoffs between initial module and system costs, degradation profiles, and levelized cost of energy (LCOE). These tools include the online Detailed Cost Analysis Models (DCAM) and the DuraMAT LCOE calculator.

cost modeling↗

An Investigation of Time Distributions for Task Primitives to Support the HUNTER Dynamic Human Reliability Analysis

As an effort to support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method. GOMS-HRA was developed to provide cognition-based time and human error probability information for dynamic HRA calculation in the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework. HUNTER is a framework to support the dynamic modelling of human error in conjunction with other modelling tools. In this paper, we investigate time distributions using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which suggests an HRA data collection framework to complement full-scope simulator research as well as collect input data for dynamic HRA using simplified simulators such as the Rancor Microworld Simulator. In this study, time required for GOMS-HRA task primitives to satisfy thirteen statistical distributions is investigated. Then, the time distributions from student operators and professional operators are compared and discussed. As a result, this study identified several time distributions on five GOMS-HRA task primitives at a statistically significant level. According to analyses to date, a greater number of significant time distributions was found in abnormal or emergency operating procedures rather than standard operating procedures. In the future, it is expected that the result of this study can provide objective reference on elapsed time data for task primitives as well as help to realistically simulate scenarios within dynamic HRA.

99 GENERAL AND MISCELLANEOUS↗

Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems

In recent years, the field of data-driven neural network-based machine learning (ML) algorithms has grown significantly and spurred research in its applicability to instrumentation and control systems. While they are promising in operational contexts, the trustworthiness of such algorithms is not adequately assessed. Failures of ML-integrated systems are poorly understood; the lack of comprehensive risk modeling can degrade the trustworthiness of these systems. In recent reports by the National Institute for Standards and Technology, trustworthiness in ML is a critical barrier to adoption and will play a vital role in intelligent systems' safe and accountable operation. Thus, in this work, we demonstrate a real-time model-agnostic method to evaluate the relative reliability of ML predictions by incorporating out-of-distribution detection on the training dataset. It is well documented that ML algorithms excel at interpolation (or near-interpolation) tasks but significantly degrade at extrapolation. This occurs when new samples are "far" from training samples. The method, referred to as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets, which is used to calculate a prediction's relative reliability. LADDR is demonstrated on a feedforward neural network-based model used to predict safety significant factors during different loss-of-flow transients. LADDR is intended as a "data supervisor" and determines the appropriateness of well-trained ML models in the context of operational conditions. Ultimately, LADDR illustrates how training data can be used as evidence to support the trustworthiness of ML predictions when utilized for conventional interpolation tasks.

97 MATHEMATICS AND COMPUTING↗

Efficient Reliability Analysis using Generalized Multifidelity Modeling and Explainable Active Learning

To assess the reliability of critical technologies like nuclear plants and infrastructure systems and improve the robustness of design, engineers have to quantify the uncertainties surrounding the system behavior accurately. However, the complexity of the problem can make standard reliability analysis algorithms prohibitively expensive, primarily due to the high computational cost of estimating the system response at each iteration. This cost can be greatly reduced by using multi-fidelity modeling and machine learning to build a surrogate model to replace the expensive response function. We propose a general and robust method for building surrogates from multiple Low Fidelity (LF) models coupled with machine learning to retain accuracy. Our framework first constructs “Corrected Low Fidelity models” (CLFs) by coupling a High Fidelity (HF) model inferred Gaussian Process correction term with each of the LF models. It then uses the correction terms to assign model probabilities to each of these CLFs in an explainable way before using them to assemble the final surrogate. No assumptions are made about the type of the LF models or their correlation with the HF model. The proposed surrogate modeling framework is used within the subset simulation algorithm (a variance-reduced MCMC-based reliability analysis algorithm) for enhanced efficiency. Additionally, an active learning step is added to the algorithm to adaptively decide when the surrogate is not sufficiently accurate, at which point the HF model is called and used to refine the surrogate. Through a frame buckling example, our method is shown to be highly efficient at reducing the expensive HF model calls while accurately estimating the failure probability.

97 MATHEMATICS AND COMPUTING↗

Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety reliability for hydrogen facilities by integrating risk reduction methodologies and component reliability data taxonomies that support hydrogen infrastructure failure rate analysis.

availability↗

ON THE LANGUAGE OF RELIABILITY: A SYSTEM ENGINEER PERSPECTIVE

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences and how likely is it to occur. While this definition makes sense in a regulatory based framework to estimate risk associated to power plants (in terms of core damage frequency and large early release frequency), this approach does not provide a useful snapshot of the health of the plant. A possible alternate path can start by redefining the word “risk” to a broader meaning that better reflects the needs of a system health and asset management decision making process. Rather than asking how likely an event can occur (in probabilistic terms), we can ask how far this event is from occurring. We will show how, given the data available from plant equipment reliability and monitoring/diagnostic/prognostic centers, a margin can be described and determined for all type of maintenance approaches (e.g., corrective or predictive maintenance). We will show how to link SSC margin-based reliability models to system reliability models (i.e., fault trees) in order to assess system/plant health and how to perform margin-based system calculations. These calculations are not solved using classical probabilistic calculations applied to sets (as performed by any PRA code) but, instead, through metric spaces operations (i.e., distance/margin based approach).

97 - MATHEMATICS AND COMPUTING↗

Reliability and Integrity Management Program Implementation Approach

Nuclear energy is the most reliable and environmentally sustainable energy source available today. In the United States, nuclear-generated power accounts for approximately 20% of total electricity and over 55% of clean energy. New advanced reactors have enormous potential to help further decarbonize the energy market, enhance grid resiliency, create new jobs, and build a stronger economy. More than 50 new reactors are being developed in the United States, and the federal government realizes an urgent need to deploy nuclear technologies to meet the country’s energy, environmental, and national security goals. As such, the U.S. Department of Energy launched multiple programs to support advanced reactor deployment. The research described in this paper explores implementation strategies for the Reliability and Integrity Management Program that directly supports the U.S. Department of Energy goal to enable the near-term deployment of the advanced reactor technologies. The project is conducted under the Regulatory Development Program for advanced reactors sponsored by the U.S. Department of Energy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗