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At least 91 records · Page 5

Reliability analysis of Skylab ATM solar cell modules

A detailed reliability analysis was performed on both types of Skylab Apollo telescope mount solar cell modules. Failure rates used were based on testing of several modules of each type for over 4000 thermal cycles. The analysis delineated several important differences between the failure modes of the two differently designed solar cell modules, and, more importantly, showed that the modules can be expected to meet all mission requirements.

Jones, G. M.↗

Human Reliability Analysis for Digital Human-Machine Interfaces

This paper addresses the fact that existing human reliability analysis (HRA) methods do not provide guidance on digital human-machine interfaces (HMIs). Digital HMIs are becoming ubiquitous in nuclear power operations, whether through control room modernization or new-build control rooms. Legacy analog technologies like instrumentation and control (I&C) systems are costly to support, and vendors no longer develop or support analog technology, which is considered technologically obsolete. Yet, despite the inevitability of digital HMI, no current HRA method provides guidance on how to treat human reliability considerations for digital technologies.

99 GENERAL AND MISCELLANEOUS↗

INVESTIGATION OF HUMAN RELIABILITY ANALYSIS METHODS FOR ANALYZING PRE-INITIATORS

As a type of human actions defined in human reliability analysis (HRA), pre-initiator refers to the human actions that may lead to the unavailability of systems, typically committed during maintenance, test, or calibration. This paper investigates representative HRA methods used for analyzing pre-initiators. The HRA methods are Technique for Human Error Rate Prediction (THERP), Korean Standard HRA (K-HRA) and Standard Plant Risk HRA (SPAR-H). In this paper, characteristics of each HRA method are compared for qualitative and quantification aspects. Two pre-initiators, i.e., a calibration task and a valve restoration task, are analyzed using the HRA methods to compare human error probabilities. Then, insights from the analysis and additional research requirements are discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗

INVESTIGATION OF HUMAN RELIABILITY ANALYSIS METHODS FOR ANALYZING PRE-INITIATORS

As a type of human actions defined in human reliability analysis (HRA), pre-initiator refers to the human actions that may lead to the unavailability of systems, typically committed during maintenance, test, or calibration. This paper investigates representative HRA methods used for analyzing pre-initiators. The HRA methods are Technique for Human Error Rate Prediction (THERP), Korean Standard HRA (K-HRA) and Standard Plant Risk HRA (SPAR-H). In this paper, characteristics of each HRA method are compared for qualitative and quantification aspects. Two pre-initiators, i.e., a calibration task and a valve restoration task, are analyzed using the HRA methods to compare human error probabilities. Then, insights from the analysis and additional research requirements are discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗

An Approach to Dependence Assessment in Human Reliability Analysis: Application of Lag and Linger Effects

Dependence assessment refers to an approach used in human reliability analysis (HRA) to adjust a human error probability (HEP) for the following action by considering the impact of the preceding action. It has been known to significantly affect the overall results of probabilistic safety assessment (PSA). If the dependence assessment is not adequate, the result could be unconvincing for explaining the operator failures in the context of PSA. To date, several methods and some recent research have identified suggestions for treating dependence issues in HRA; however, these are still exclusively based on the intrinsic approach of the Technique for Human Error Rate Prediction (THERP), an HRA method. THERP inevitably has a challenge with the subjectivity of expert evaluation as well as the requirement for PSA and HRA expertise with resource-intensive and time-consuming processes. This paper suggests an approach to dependence assessment that could not only minimize the influence of expert judgment, but also saves time to perform the analysis with reasonable manpower. It modifies existing HRA methods with considering lag and linger effects to apply dependence effects for them. Based on a representative HRA method, i.e., Standardized Plant Analysis Risk - HRA (SPAR-H), guidance for how to apply lag and linger effects for the HRA method is suggested. Then, an investigation is carried out to compare quantification results of the revised HRA method with that of the original approach based on experimental data.

99 GENERAL AND MISCELLANEOUS↗

Reliability analysis of structures under periodic proof tests in service

A reliability analysis of structures subjected to random service loads and periodic proof tests treats gust loads and maneuver loads as random processes. Crack initiation, crack propagation, and strength degradation are treated as the fatigue process. The time to fatigue crack initiation and ultimate strength are random variables. Residual strength decreases during crack propagation, so that failure rate increases with time. When a structure fails under periodic proof testing, a new structure is built and proof-tested. The probability of structural failure in service is derived from treatment of all the random variables, strength degradations, service loads, proof tests, and the renewal of failed structures. Some numerical examples are worked out.

Yang, J.-N.↗

SURE reliability analysis: Program and mathematics

The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The computational methods on which the program is based provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

Butler, Ricky W.↗

Space Mission Human Reliability Analysis (HRA) Project

The purpose of the Space Mission Human Reliability Analysis (HRA) Project is to extend current ground-based HRA risk prediction techniques to a long-duration, space-based tool. Ground-based HRA methodology has been shown to be a reasonable tool for short-duration space missions, such as Space Shuttle and lunar fly-bys. However, longer-duration deep-space missions, such as asteroid and Mars missions, will require the crew to be in space for as long as 400 to 900 day missions with periods of extended autonomy and self-sufficiency. Current indications show higher risk due to fatigue, physiological effects due to extended low gravity environments, and others, may impact HRA predictions. For this project, Safety & Mission Assurance (S&MA) will work with Human Health & Performance (HH&P) to establish what is currently used to assess human reliabiilty for human space programs, identify human performance factors that may be sensitive to long duration space flight, collect available historical data, and update current tools to account for performance shaping factors believed to be important to such missions. This effort will also contribute data to the Human Performance Data Repository and influence the Space Human Factors Engineering research risks and gaps (part of the HRP Program). An accurate risk predictor mitigates Loss of Crew (LOC) and Loss of Mission (LOM).The end result will be an updated HRA model that can effectively predict risk on long-duration missions.

Boyer, Roger↗

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. In this paper, how we have developed one of the HUNTER modules, the individual module for evaluating performance shaping factors (PSFs), is introduced. The PSF refers to any factor that influences human performance such as workload or complexity. It has been used for highlighting human errors and adjusting the error probabilities in the existing HRA. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, which is the representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also design the individual module composed of the two functions: 1) the PSF qualification function that automatically or manually evaluates a PSF level, and 2) the PSF quantification function that dynamically or statically determines the PSF multiplier values and integrate them to adjust human error probabilities (HEPs). How each function works with the SPAR-H PSFs and how the PSFs adjust the HEPs are investigated through literature and discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗

A framework to collect human reliability analysis data for nuclear power plants using a simplified simulator and student operators

Data scarcity in human reliability analysis (HRA) has been a major challenge in the quantification process. Many institutes have collected HRA data through experiments using full-scope simulators with actual operators. Nevertheless, there are still some limitations to relying solely on full-scope studies. This paper aims to propose how full-scope data collection studies can be supported through the Simplified Human Error Experimental Program (SHEEP). The SHEEP framework was developed by Idaho National Laboratory (INL) to collect HRA data through a simplified simulator and student operators. This paper introduces the major tasks in the SHEEP framework, with a particular focus on differences that arise due to participant type (i.e., student vs. actual operator), based on experiments using a simplified simulator (i.e., the Rancor Microworld). This paper also describes whether the data collected via this approach could support a representative full-scope data collection study (i.e., the HuREX study) based on the experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Transient Reliability Analysis Capability Developed for CARES/Life

The CARES/Life software developed at the NASA Glenn Research Center provides a general-purpose design tool that predicts the probability of the failure of a ceramic component as a function of its time in service. This award-winning software has been widely used by U.S. industry to establish the reliability and life of a brittle material (e.g., ceramic, intermetallic, and graphite) structures in a wide variety of 21st century applications.Present capabilities of the NASA CARES/Life code include probabilistic life prediction of ceramic components subjected to fast fracture, slow crack growth (stress corrosion), and cyclic fatigue failure modes. Currently, this code can compute the time-dependent reliability of ceramic structures subjected to simple time-dependent loading. For example, in slow crack growth failure conditions CARES/Life can handle sustained and linearly increasing time-dependent loads, whereas in cyclic fatigue applications various types of repetitive constant-amplitude loads can be accounted for. However, in real applications applied loads are rarely that simple but vary with time in more complex ways such as engine startup, shutdown, and dynamic and vibrational loads. In addition, when a given component is subjected to transient environmental and or thermal conditions, the material properties also vary with time. A methodology has now been developed to allow the CARES/Life computer code to perform reliability analysis of ceramic components undergoing transient thermal and mechanical loading. This means that CARES/Life will be able to analyze finite element models of ceramic components that simulate dynamic engine operating conditions. The methodology developed is generalized to account for material property variation (on strength distribution and fatigue) as a function of temperature. This allows CARES/Life to analyze components undergoing rapid temperature change in other words, components undergoing thermal shock. In addition, the capability has been developed to perform reliability analysis for components that undergo proof testing involving transient loads. This methodology was developed for environmentally assisted crack growth (crack growth as a function of time and loading), but it will be extended to account for cyclic fatigue (crack growth as a function of load cycles) as well.

Nemeth, Noel N.↗

The HUNTER Dynamic Human Reliability Analysis Tool: Development of a Module for Performance Shaping Factors

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) in communication with a variety of methods and tools. This paper explores how we developed one of the HUNTER modules: namely, the Individual module for evaluating performance shaping factors (PSFs). A PSF is any factor that influences human performance (e.g., workload or complexity). In the existing HRA, they are used to highlight human errors and adjust error probabilities. We consider the eight PSFs suggested in the Standardized Plant Analysis Risk-HRA (SPAR-H) method, a representative HRA method widely used in the nuclear field. To support our dynamic modeling using the eight SPAR-H PSFs, we reviewed the human performance literature and developed data-based mathematical models to rate and quantify PSFs in the context of dynamic HRA. We also designed the Individual module to consist of two functions: (1) the PSF qualification function for automatically or manually evaluating PSF levels, and (2) the PSF quantification function for dynamically or statically determining PSF multiplier values and integrating them to adjust human error probabilities (HEPs). How each function works in regard to the SPAR-H PSFs, and how the PSFs serve to adjust the HEPs, were investigated via literature review and are discussed in this paper.

99 GENERAL AND MISCELLANEOUS↗

Probabilistic Grid Reliability Analysis with Energy Storage Systems

SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nguyen, Tu↗

Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Production Facility System Reliability Analysis Report

This document describes the reliability, maintainability, and availability (RMA) modeling of the Los Alamos National Laboratory (LANL) design for the Closed Loop Helium Cooling System (CLHCS) planned for the NorthStar accelerator-based 99 Mo production facility. The current analysis incorporates a conceptual helium recovery system, beam diagnostics, and prototype control system into the reliability analysis. The results from the 1000 hr blower test are addressed.

Accelerator Design, Technology, and Operations↗

Hierarchical modeling for reliability analysis using Markov models

Markov models represent an extremely attractive tool for the reliability analysis of many systems. However, Markov model state space grows exponentially with the number of components in a given system. Thus, for very large systems Markov modeling techniques alone become intractable in both memory and CPU time. Often a particular subsystem can be found within some larger system where the dependence of the larger system on the subsystem is of a particularly simple form. This simple dependence can be used to decompose such a system into one or more subsystems. A hierarchical technique is presented which can be used to evaluate these subsystems in such a way that their reliabilities can be combined to obtain the reliability for the full system. This hierarchical approach is unique in that it allows the subsystem model to pass multiple aggregate state information to the higher level model, allowing more general systems to be evaluated. Guidelines are developed to assist in the system decomposition. An appropriate method for determining subsystem reliability is also developed. This method gives rise to some interesting numerical issues. Numerical error due to roundoff and integration are discussed at length. Once a decomposition is chosen, the remaining analysis is straightforward but tedious. However, an approach is developed for simplifying the recombination of subsystem reliabilities. Finally, a real world system is used to illustrate the use of this technique in a more practical context.

Fagundo, Arturo↗