SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Presentation to the Legislative Energy Horizons Institute on grid reliability and renewable integration, including resource adequacy, flexibility, and distributed energy resource considerations.
The primary deliverable for this project will be to construct a power electronics package utilizing an organic electrically insulating substrate material with a direct chip-to-chip interconnect technology and demonstrate superior thermal performance and greater reliability under thermal cycling, thermal aging, vibration, power cycling, and electrical high-potential evaluation over traditional packages.
This presentation introduces INL's human reliability analysis data collection studies.
Many researchers have emphasized the importance of dynamic probabilistic safety assessment (PSA), which highlights the necessity of studies for dynamic human reliability analysis (HRA). Dynamic HRA concentrates on a dynamic account of human actions or how performance shaping factors (PSFs) can dynamically modify the human error probability (HEP) over time. In contrast, existing static HRA does not consider human actions as changes over time or event progressions. Accordingly, previous research on dynamic HRA conceptually suggested PSF lag and linger effects to treat dependence between operator actions in dynamic HRA versus existing approaches. As follow-up research, this study attempted to identify PSF lag and linger effects for dynamic HRA on the basis of experimental data. Firstly, mathematical models for PSF lag and linger effects were developed based on a literature survey in the field of biology. Secondly, we analyzed experimental scenarios from a control room study to identify operator actions considered in PSA. Lastly, based on the experimental data, the effect of the stress PSF with lag and linger effects was compared to that without PSF lag and linger effects. This paper concludes with an overall discussion of PSF lag and linger effects based on the relation between the stress PSF and error occurrence.
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.
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.
An overview of the National Renewable Energy Laboratories Component Reliability Project including the accomplishments for the previous year.
For many decades, PSA (Probabilistic Safety Assessment) or PRA (Probabilistic Risk Assessment) techniques have been used to enhance the operational safety of nuclear power plants (NPPs) based on the consideration of potential hazards that could result in an unexpected consequence. As human error is one of the potential hazards, diverse human reliability analysis (HRA) methods have been proposed to provide a systematic way to estimate the likelihood of human errors (i.e., human error probability, HEP) in specific task contexts. Accordingly, it is evident that the quality of HRA results strongly depends on the credibility of HEP estimations. This implies that, in terms of enhancing this credibility, the collection of raw information (HRA data) that is helpful for understating when and why human errors occur is a crucial issue. In order to address this issue, in this study, the feasibility of a framework to integrate HRA data obtained from different sources is investigated based on the complexity of proceduralized tasks.
High temperature operation of wide bandgap devices continue to be a challenge for the power electronics packages. Thermal performance and reliability are important factors that determine the viability of a bonded interface for operation at high temperatures. In this presentation, we present the technical approach and key results from the research on sintered silver, transient liquid phase alloy, and polymeric materials. A lifetime prediction model that incorporates the thermomechanical behavior of sintered silver at 200C was developed. The copper-aluminum transient alloy completed 350 thermal cycles from -40C to 200C and little increase in the defect level was observed. In addition to material research, we initiated a time-series analysis on the scanning acoustic microscope images of eutectic solder to explore statistical forecasting methods and machine learning techniques. Initial results that report the accuracy of a few different statistical models are presented.
Human-system interfaces (HSIs) play an important role in enabling operators to communicate with the nuclear power plant (NPP) side. Getting the information required to understand a NPP’s current status or perform necessary actions for responding to a given operational context are representative operator tasks performed using HSIs. To date, HSIs have been mainly evaluated in the context of human reliability analysis (HRA). However, the current HSI evaluation that occurs during HRA may be challengeable on two fronts: (1) reflecting the unique characteristics of HSI systems and (2) considering situations in which HSIs are poorly operated due to software/hardware malfunctions. Accordingly, this study proposes an approach for specifically evaluating HSIs for digital instrumentation and controls (DI&C) systems, using Redundancy-guided Systems-theoretic Hazard Analysis (RESHA) and HRA. RESHA is a method for analyzing DI&C systems with redundancy features. In this study, we investigate how HSIs are evaluated in existing HRA methods, and what challenges exist in the current approaches. To better evaluate HSIs for DI&C systems, this study modifies the existing HSI evaluation process by additionally modeling the HSI back- and front- ends. In this paper, a HSI fault tree for the APR1400 DI&C system is introduced through a piping and instrumentation diagram. It then touches upon what aspects of the suggested method must be further researched.
In most of non-safety NSSS (Nuclear Steam Supply System) control systems, a process input is composed of two channels for redundancy. In a normal situation, the average of both input channels is used in the control algorithm. If a failed channel is detected, the 'channel selection algorithm' chooses the remaining normal input channel. For a bumpless transition, many implemented control systems include the 'ramping rate' function, which makes it possible for the selected input to slowly approach the new input channel. However, it recently turned out that this function adopted for positive effects may result in unintended consequences for the related control system and the plant in certain cases. Due to a process transient in the plant according to a significant event, any related sensor input signal can rapidly change and finally exceed the pre-defined range for detecting an out-of-range event in a short time. During the process of channel conversion due to a rapid transient in the plant, the processed input from the redundant channels can be distorted if the ramping rate function is not properly implemented. As a result, it can result in a plant shutdown because the control system fails to perform the critical function to mitigate a plant transient. To solve these potential problems, we analyzed the overall causes and derived a proposed algorithm for improving reliability and performance of the control systems. (authors)
Lack of appropriate human performance data for the development of human reliability analysis (HRA) methods has been identified as a key issue contributing to the method-to-method variability among the HRA methods. The United States Nuclear Regulatory Commission (NRC) worked with domain experts to develop the Scenario Authoring, Characterization, and Debriefing Application (SACADA) system to collect nuclear power plants' licensed operator simulator training and examination data to inform HRA. In the past two decades, significant improvements in understanding and modelling human performance in HRA have affected the perspectives of the types of data to be collected for HRA. A significant change is that human performance is strongly dependent on the context of the tasks to be performed. To incorporate this understanding, the SACADA data taxonomy collects the context and actual performance information of the training objective elements (TOEs) in nuclear plant operator simulator training. This provides a framework consistent with HRA to use context to estimate human error probabilities. It is recognized that measuring crew performance is equally important as improving operator training. SACADA is designed to support the nuclear trainers in capturing this important information that is used to identify training weaknesses and drive continuous improvement. This paper discusses the SACADA taxonomy, the SACADA system's functions, and the supporting software design to enable the SACADA system to be practically implemented in the nuclear power plants' operator simulator training program to collect data for tracking operator performance and HRA analysis. (authors)
On August, 2001, the Korean government issued a severe accident policy statement. In this policy statement, a safety goal was proposed in a form of quantitative health objective(QHO) such that an additive risk of early fatality and cancer fatality caused by accident or operation of nuclear power plant(NPPs) should not exceed 0.1% of the sum of other accidents and cancer fatality risks resulting from all other causes, respectively. In accordance with the policy statement, probabilistic safety analysis(PSA) for all Korean NPPs was conducted to show each plant satisfies QHO. Given the increasing importance of PSA to assess the level of safety of NPPs, it is crucial that the quality of the PSA results should be assured. Compared to well-established PSA method used for domestic NPPs, there is consensus that human reliability analysis (HRA) has lack of consistency due to the different assumptions and different characteristics of the methods, which could possibly result in low quality of the PSA. To resolve the issues with lack of consistency of the HRA methods, there have been efforts to develop a standardized HRA method in Korea. However, quality of existing Korean HRA should be evaluated before developing a standardized method, since the results can be used for deriving requirements and give feedback and insights for developing the standardized method. In this study, literature review was performed to select an adequate method for evaluating the quality of the HRA, and the quality of the HRA is evaluated. Finally, results and insights of this study are shown in the conclusion. (authors)
According to the U.S Energy Information Administration (EIA), the U.S fossil fuel share of energy consumption in 2015 was 67%. Furthermore, the Ecotricity UK report based on the CIA World Factbook states that with the current rate of consumption of fossil fuels, petroleum would run out by 2052, natural gas by 2060, and coal by 2088. No fossil fuel will remain by the next century. Besides the limited reserves of fossil fuel, massive consumption of fossil fuel also raises concerns about global warming and pollution. Therefore, there has been a growing interest in reducing fossil fuel consumption in the energy structure and in increasing the proportion of clean energy. Renewable energy (e.g. wind, solar) has the potential for distributed generation. However, the availability for renewable energy fluctuates and is uncontrollable. Therefore, additional energy sources need to be coupled with renewable energy to produce a stable electricity generation profile. Nuclear energy can serve this purpose as it is a clean energy source, has low greenhouse gas emission and possesses high power density and baseload power supply with low fuel cost. It is desirable to develop a hybrid energy system that combines both renewable energy and nuclear energy to meet low carbon emission goals and to utilize renewable energy. Such a nuclear hybrid energy system, consisting of different energy subsystems such as nuclear, solar, and wind, involves frequent switching between different energy subsystems. Since the primary loop in a nuclear power plant generates constant heat, the turbine bypass line in the secondary loop is required to switch frequently to meet the gap in the energy demand and that generated by the renewables. The increased usage of the turbine bypass system is considered to be the major difference between a nuclear hybrid energy system and a traditional nuclear power plant. Reliability analysis for designing such a complex system involves both high level fault propagation analysis at the conceptual design stage and low level failure prediction for specific components. The main focus of this summary to derive a degradation model of hardware components which can later help in the high level fault propagation analysis. The degradation model is a low level failure mode model that combines the effects of natural aging and frequent switching. The model can be used for predicting components' failure due to specific failure modes. The results can serve as indicators for conducting repair actions and maintenance to minimize Operation and Maintenance (O and M) costs. (authors)
Slides for an external presentation at a reliability workshop.
Challenging climates for Photovoltaics are usually based on climate classification. However, extreme weather events such as high wind, flooding, large hail, extreme snow etc. have become more ubiquitous globally. To study the impact of extraordinary weather events on PV reliability we used two of the largest databases in the USA. First, the National Oceanic and Atmospheric Administration (NOAA) database on extreme weather and secondly, the PV Fleet Data Initiative where we have collected high-resolution PV performance data of more than 8 gigawatts or about 6-7% of all commercial and utility systems in the USA. We analyzed almost 200 systems between 2008-20022 that were immediately impacted by these weather events. The immediate impact (outages) was determined to be about 1% of or a median of approximately 3 days of annual lost production. However, the risk these events pose is exemplified by a long tail where 0.4 % of all systems lost more than 2 weeks annual production. We also found a threshold for high wind (90 km/hr) and hail (25mm), above which we observed significantly higher degradation implying long-term damage to the systems. In addition, we are using satellite imagery to quantify visible damage to PV plants. Finally, we share module, design and installation lessons from some observed case studies to improve extreme weather resilience for PV power systems.
The need for reliable bonded interface materials is critical to realize the performance benefits of wide-bandgap devices in power electronic modules, especially in operating temperatures greater than 150 degrees Celsius. In this paper, we investigate the thermomechanical performance of sintered copper (Cu) as a large-area attachment, bonded between Cu baseplates and active-metal-bonded substrates, under accelerated thermal shock (-40 degrees Celsius to 200 degrees Celsius) conditions. In the fabrication phase of the samples, we used different stencil patterns and found out that the grid and stripe patterns resulted in a better outgassing of the residual organics during the sintering process, thereby ensuring a substantially improved bond quality than a full-area print. The paste consisted of Cu microflakes and we performed sintering using a Budatec SP300 sintering press at 275 degrees Celsius with 15 MPa of bonding pressure for 5 minutes in a nitrogen atmosphere. Under accelerated experiments, we monitored the degradation of the sintered Cu bond in the samples through C-mode scanning acoustic microscope (C-SAM) images. To quantify the defect percentage in C-SAM images, we investigated image denoising techniques to exclude the pattern prints. Finally, we cross-sectioned a sample and obtained digital microscope images, which revealed adhesive fracture as the dominant failure mechanism.
This presentation is to guide interactive discussion by posing questions to workshop participants. Topic is reliability, maintenance cost, and performance risk associated with failure of PV connectors which make electrial connections between components.