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At least 577 records · Page 32

R&D to Ensure a Scientific Basis for Qualification Tests and Standards (Final Report)

Project return on investment in a photovoltaic (PV) system depends increasingly on maintaining high energy yields, and the system lifetime is a major factor in levelized cost of electricity (LCOE). Thus, the rate of PV deployment and the success of these assets depends upon reliable long-term power generation. The overarching objective of this program is to improve photovoltaic (PV) module reliability via development of tests and standards. Where reliability problems or risk are discovered, we can design tests to ensure that these liabilities don't affect future generations of products. Customers can use these tests to understand which products are susceptible to certain degradation mechanisms, and manufacturers can use the tests to design unwanted characteristics out of their products. The work under this program identifies PV reliability needs, performs characterization that provides scientific understanding of targeted degradation mechanisms, and translates those data into practical and predictive test protocols and standards. Major accomplishments include: A model for polarization-type potential induced degradation (PID-p) was developed and validated against experimental data. NREL is currently leading a new edition of IEC 62804-1 for PID detection. PID-p can cause large losses in current and voltage for some module designs on cloudy days. Finite element modeling (FEM) and experiment was used to determine when cells crack in a module. It was shown that cells in landscape orientation are much more likely to crack than those on portrait orientation. Shortly thereafter, the first products with portrait-oriented cells were introduced. Studies of how to test for light and elevated temperature degradation (LeTID) culminated with the publication of IEC TS 63342. Software to predict the progression of LeTID was developed, validated, and made publicly available. Field validated tests and international standards for durability of PV module coatings abrasion, backsheets, and encapsulants were developed. Examples are IEC 62788-1-1, IEC 62788-2 ED2, IEC TS 62788-7-2, IEC 62788-7-3 ED1, IEC 63209-2. NREL led the development a high-temperature testing technical specification, and published guidelines that enable installers to determine whether higher-temperature testing is needed, simply based on location and mounting configuration. In a number of our case studies, variations in the bills of materials or workmanship have been associated with variations in reliability. These observations emphasize the importance of quality assurance to reliability. A framework for criticality (i.e. Pareto) analysis was developed and published. The framework helps us and other researchers determine what problems should be addressed for reliability research to have the biggest industry impact. NREL continues to participate actively in international standards development and stakeholder engagement activities, including organizing an annual PV Reliability Workshop. These activities are important for ensuring we address issues that are relevant and timely, and that we convey our results to those who may benefit.

14 SOLAR ENERGY↗

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗

Asteroid spin-rate study using the intermediate palomar transient factory

Two dedicated asteroid rotation-period surveys have been carried out in the R band with ∼20 minute cadence using the intermediate Palomar Transient Factory (iPTF) during 2014 January 6–9 and February 20–23. The total survey area covered 174 deg{sup 2} in the ecliptic plane. Reliable rotation periods for 1438 asteroids are obtained from a larger data set of 6551 mostly main-belt asteroids, each with ⩾10 detections. Analysis of 1751, PTF-based, reliable rotation periods clearly shows the spin barrier at ∼2 hr for rubble-pile asteroids. We found a new large super-fast rotator, 2005 UW163, and another five candidates as well. For asteroids of 3<D<15 km, our spin-rate distribution shows a number decrease along with frequency after 5 rev day{sup −1}, which is consistent with the results of the Asteroid Light Curve Database. The discrepancy between our work and that of Pravec et al. (update 2014 April 20) comes mainly from asteroids with Δm<0.2 mag, which could be the result of different survey strategies. For asteroids with D<3 km, we see a significant number drop at f = 6 rev day{sup −1}. The relatively short YORP effect timescale for small asteroids could have spun up those elongated objects to reach their spin-rate limit resulting in breakup to create such a number deficiency. We also see that the C-type asteroids show a smaller spin-rate limit than the S-type, which agrees with the general impression that C-type asteroids have a lower bulk density than S-type asteroids.

79 ASTRONOMY AND ASTROPHYSICS↗

Development and Validation of a Lifecycle-based Prognostics Architecture with Test Bed Validation

On-line monitoring and tracking of nuclear plant system and component degradation is being investigated as a method for improving the safety, reliability, and maintainability of aging nuclear power plants. Accurate prediction of the current degradation state of system components and structures is important for accurate estimates of their remaining useful life (RUL). The correct quantification and propagation of both the measurement uncertainty and model uncertainty is necessary for quantifying the uncertainty of the RUL prediction. This research project developed and validated methods to perform RUL estimation throughout the lifecycle of plant components. Prognostic methods should seamlessly operate from beginning of component life (BOL) to end of component life (EOL). We term this "Lifecycle Prognostics." When a component is put into use, the only information available may be past failure times of similar components used in similar conditions, and the predicted failure distribution can be estimated with reliability methods such as Weibull Analysis (Type I Prognostics). As the component operates, it begins to degrade and consume its available life. This life consumption may be a function of system stresses, and the failure distribution should be updated to account for the system operational stress levels (Type II Prognostics). When degradation becomes apparent, this information can be used to again improve the RUL estimate (Type III Prognostics). This research focused on developing prognostics algorithms for the three types of prognostics, developing uncertainty quantification methods for each of the algorithms, and, most importantly, developing a framework using Bayesian methods to transition between prognostic model types and update failure distribution estimates as new information becomes available. The developed methods were then validated on a range of accelerated degradation test beds. The ultimate goal of prognostics is to provide an accurate assessment for RUL predictions, with as little uncertainty as possible. From a reliability and maintenance standpoint, there would be improved safety by avoiding all failures. Calculated risk would decrease, saving money by avoiding unnecessary maintenance. One major bottleneck for data-driven prognostics is the availability of run-to-failure degradation data. Without enough degradation data leading to failure, prognostic models can yield RUL distributions with large uncertainty or mathematically unsound predictions. To address these issues a "Lifecycle Prognostics" method was developed to create RUL distributions from Beginning of Life (BOL) to End of Life (EOL). This employs established Type I, II, and III prognostic methods, and Bayesian transitioning between each Type. Bayesian methods, as opposed to classical frequency statistics, show how an expected value, a priori, changes with new data to form a posterior distribution. For example, when you purchase a component you have a prior belief, or estimation, of how long it will operate before failing. As you operate it, you may collect information related to its condition that will allow you to update your estimated failure time. Bayesian methods are best used when limited data are available. The use of a prior also means that information is conserved when new data are available. The weightings of the prior belief and information contained in the sampled data are dependent on the variance (uncertainty) of the prior, the variance (uncertainty) of the data, and the amount of measured data (number of samples). If the variance of the prior is small compared to the uncertainty of the data, the prior will be weighed more heavily. However, as more data are collected, the data will be weighted more heavily and will eventually swamp out the prior in calculating the posterior distribution of model parameters. Fundamentally Bayesian analysis updates a prior belief with new data to get a posterior belief. The general approach to applying the Bayesian method to lifecycle prognostics consisted of identifying the prior, which is the RUL estimate and uncertainty from the previous prognostics type, and combining it with observational data related to the newer prognostics type. The resulting lifecycle prognostics algorithm uses all available information throughout the component lifecycle.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Excess Capacity in China’s Power Systems: A Regional Analysis

This paper examines China’s regional electricity grids using a reliability perspective, which is commonly measured in terms of a reserve margin. Our analysis shows that at the end of 2014, the average reserve margin for China as a whole was roughly 28%, almost twice as high as a typical planning reserve margin in the U.S. However, this national average masks huge variations in reserve margins across major regional power grid areas: the northeastern region has the highest reserve margin of over 60%, followed by the northwestern region at 49%, and the southern grid area at 35%. In this analysis, we also examined future reserve margins for regional electricity grids in China under two scenarios: 1) a low scenario of national annual electricity consumption growth rates of 1.5% between 2015 and 2020 and 1.0% between 2020 and 2025, and 2) a high scenario of annual average growth rates of 3.0% and 2.0%, respectively. Both scenarios suggest that the northeastern, northwestern, and southern regions have significant excess generation capacity, and that this excess capacity situation will continue over the next decade without regulatory intervention. The northern and central regions could have sufficient generation capacity to 2020, but may require additional resources in a higher growth scenario. The eastern region requires new resources by 2020 in both scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Developing a Vorticity-Velocity-Based Off-Body Solver to Perform Multifidelity Simulations of Wind Farms

Wind power has become a key player in satisfying the global energy needs. With increased market penetration, unanticipated unsteady loading induced failures, installation related reductions in power generation, and significant maintenance costs have underscored the need to predict the unsteady fluid-structure interactions related to turbine layout and off-design wind conditions. Contemporary turbine design tools are incapable of accounting for such loadings. As a result, researchers have started utilizing high-Performance-Computing (HPC) based Computational Fluid Dynamics (CFD) solvers, such as the U.S. Department of Energy sponsored ExaWind software package, to investigate these phenomena. Unfortunately, such HPC tools are computationally expensive for routine industrial use, often because of the sheer number of cells required to resolve the wake flowfield. This paper describes a preliminary effort to address this issue by developing a vorticity-velocity based CFD off-body solver, VorTran-M2-AMReX, that integrates directly with DOE's ExaWind wind turbine analysis system to perform accurate and reliable simulations of wind turbine/farm at a lower computational cost than ExaWind alone. This article summarizes work undertaken to date concerning the assembly of the proposed analysis tool, and provides preliminary validation and verification of the VorTran-M2-AMReX off-body solver.

adaptive mesh refinement↗

Potential applications of industrial wireless technologies in the future HTR - 18505

High Temperature Reactor (HTR) is a kind of promising nuclear reactor for supplying electricity and heat with inherent safety. The High Temperature Reactor-Pebble bed Modular reactor (HTR-PM) in China is equipped with the Distributed Control System (DCS) where wired network is applied mainly based on fiber. Considering the difficulty and cost of implementation, the flexibility of network configuration and maintenance, the industrial wireless network might be potential for some cases in the network of the next generation of HTR. Nowadays, there are several technologies available for choice, such as wireless HART, WIA-PA and ZigBee. Characteristics of these technologies are introduced. The most important factors for choice of the technology of network are the required reliability and latency tolerance of communication. Analysis and classification of the communications needed in the network of the HTR are carried out, and a comparison of popular industrial wireless technologies, including the reliability, the latency, the communication distance, and the difficulty and cost of implementation is made. Generally speaking, considering the low latency, high reliability and the compatibility with HART devices, wireless HART is promising. WIA-PA could be applied if redundant gateway is required. ZigBee might show its advantages in power consumption and cost. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Systematic search for tidal features around nearby galaxies: I. Enhanced SDSS imaging of the Local Volume

In hierarchical models of galaxy formation, stellar tidal streams are expected around most, if not all, galaxies. Although these features may provide useful diagnostics of the Λ CDM model, their observational properties remain poorly constrained because they are challenging to detect and interpret and have been studied in detail for only a sparse sampling of galaxy population. More quantitative, systematic approaches are required. We advocate statistical analysis of the counts and properties of such features in archival wide-field imaging surveys for a direct comparison against results from numerical simulations. We aim to study systematically the frequency of occurrence and other observational properties of tidal features around nearby galaxies. The sample we construct will act as a foundational dataset for statistical comparison with cosmological models of galaxy formation. Our approach is based on a visual classification of diffuse features around a volume-limited sample of nearby galaxies, using a post-processing of Sloan Digital Syk Survey (SDSS) imaging optimized for the detection of stellar structure with low surface brightness. At a limiting surface brightness of 28 mag arcsec –2 , 14% of the galaxies in our sample exhibit evidence of diffuse features likely to have arisen from minor merging events. Our technique recovers all previously known streams in our sample and yields a number of new candidates. Consistent with previous studies, coherent arc-like features and shells are the most common type of tidal structures found in this study. Here, we conclude that although some detections are ambiguous and could be corroborated or refuted with deeper imaging, our technique provides a reliable foundation for the statistical analysis of diffuse circumgalactic features in wide-area imaging surveys, and for the identification of targets for follow-up studies.

79 ASTRONOMY AND ASTROPHYSICS↗

Multilevel probabilistic approach to evaluate manufacturing defect in composite aircraft structures

In this work it is developed a reliable approach and its feasibility to the design and analysis of a composite structures. The metric is compared the robustness and reliability designs versus the traditional design, to demonstrate the gain that can be achieved with a probabilistic approach. The use of the stochastic approach of the uncertain parameteters in combination with the multi-scale levels analysis is the main objective of this paper. The work is dedicated to analyze the uncertainties in the design, tests, manufacturing process, and key gates such as materials characteristic.

36 MATERIALS SCIENCE↗

Idling Reduction for Long-Haul Trucks: An Economic Comparison of On-Board and Wayside Technologies

Reducing the idling of long-haul heavy-duty trucks has long been recognized as a particularly low-hanging fruit of fuel efficiency and emissions reduction. The displacement of about 10 hours of diesel idling every day, for most days of the year, for as many as a million long-haul trucks has very clear benefits. This report considers the costs and return on investment (ROI) for idling reduction (IR) equipment for both truck owners and electrified parking space (EPS) equipment owners. For the truck owners, the key variables examined are idling hours to be displaced (generally 1,000 to 2,000 hours per year) and the price of fuel ($0 to $5/gal). The ideal IR option would provide complete services in varied climates in any location and offer the best ROI on trucks that log many idling hours. For trucks that have fewer idling hours, options with a fixed cost per hour (i.e., EPS) might be most attractive if they were available to all, or even most, truck drivers. EPS, however, is particularly cost effective for trucks on prescribed routes with a need for regular, extended stops at terminals. (EPS is also called truck stop electrification, or TSE.) The analysis shows that all IR options save money when fuel costs more than $2/gal. For trucks requiring bunk heat, a simple heater (plug-in or diesel) is almost always the most costeffective way to provide heat, even if the truck is equipped with an auxiliary power unit (APU) or is parked at a single-system EPS location. For trucks requiring bunk air-conditioning, the use of single-system EPS is most cost effective for those logging fewer idling hours. Even for trucks with higher idling hours, the cost of EPS may be about the same as that for on-board air-conditioning. Clearly, trucks’ locations and seasonal factors—and the availability of EPS— are significant in the choice of “best fit” IR equipment for truck owners. This report also considers costs and payback for owners of EPS infrastructure. An industry that 5 years ago had at least five players has been narrowed to two companies—one in single-system EPS (IdleAir) and the other in dual-system EPS (Shorepower Technologies). Use of EPS by truck drivers has not met initial expectations for a variety of reasons. One area where EPS has particular promise, however, is in the cost-effective provision of reliable air-conditioning. This analysis is focused strictly on cost and fuel savings; it does not consider the important benefits of reduced emissions (i.e., greenhouse gases and criteria pollutants). It is important to note that all IR options provide some emissions benefits. Even where an IR option may not have a rapid ROI, the emissions-reduction benefit may be considerable. Finally, as the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA) set stricter standards to reduce greenhouse gas emissions and improve the fuel efficiency of medium- and heavy-duty vehicles, the emissions benefits of IR strategies will become increasingly important.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Structural Reliability Evaluation of Thermoelectric Generator Modules: Influence of End Conditions, Leg Geometry, Metallization, and Processing Temperatures

Structural reliability of thermoelectric generators (TEGs) in medium to high temperature applications still remains a challenge. Currently there are no established standards for evaluating the thermomechanical reliability of TEGs during new material and module development phases in the industry. In this work we implemented a procedure for evaluating the reliability of brittle TE materials based on the common practice in the ceramics industry. The probabilistic thermomechanical reliability of TEG couples and modules is evaluated using Weibull analysis. Finite element simulations were carried out to study the influence of TEG couple parameters such as element geometry, dimensions, spacing, metallization thickness, and processing conditions on the stresses, and the structural reliability evaluations are conducted based on the TE element stresses. We report results showed that the boundary conditions and processing temperatures have significant influence on the element and metallization stresses and overall device reliability. The external compressive load significantly enhanced structural reliability. Results also showed that among geometrical parameters the element length has a dominating influence on the element stresses compared to the leg cross-sectional shapes. The cross-section geometry of legs showed considerable effect at shorter lengths and the influence diminished with increased lengths. The proposed approach for evaluating the structural reliability could be integrated with performance optimization techniques for developing optimal and reliable TEG devices.

36 MATERIALS SCIENCE↗

Artifact-Free Coring Procedures for Removing Samples from Photovoltaic Modules for Microscopic Analysis

An important step in producing more reliable and efficient photovoltaic modules is to establish a relationship between the microscopic properties of modules deployed in the field for many years and efficiency-related parameters. The first step in accomplishing this task is to be able to identify and remove small areas from these modules without causing any damage to these samples. In this work, we will describe two different procedures to core small areas of deployed and stressed solar panels produced with different materials (Si, CIGS, and CdTe), and we will prove that these processes did not damage the cored material. We will also show that the coring procedure changes for different types of photovoltaic modules.

14 SOLAR ENERGY↗

Progress in the RAMI analysis of a conceptual LHCD system for DEMO

Reliability, Availability, Maintainability and Inspectability (RAMI) concepts and techniques, that acquired great importance during the first manned space missions, have been progressively extended to industrial, scientific and consumer equipments to assure them satisfactory performances and lifetimes. In the design of experimental facilities, like tokamaks, mainly aimed at demonstrating validity and feasibility of scientific theories, RAMI analysis has been often left aside. DEMO, the future prototype fusion reactors, will be instead designed for steadily delivering electrical energy to commercial grids, so that the RAMI aspects will assume an absolute relevance since their initial design phases. A preliminary RAMI analysis of the LHCD system for the conceptual EU DEMO reactor is given in the paper.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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↗

Aeroelastic Analysis Using Deforming Cartesian Grids

Ongoing work in air-vehicle design illustrates the potential of advanced concepts to provide significant improvements in efficiency; but with their incorporation of lightweight flexible structures, such configurations may require active control systems to ensure reliability and safety. However, many contemporary analysis methods are inefficient for aeroelastic analysis and design of such configurations. This paper describes the development of a new approach that automates the geometry setup, mesh generation, and assembly of fluid–structural coupling interfaces to enable efficient aeroelastic and aeroservoelastic analysis of advanced concepts. The core elements for this approach are a cut-cell Cartesian grid-based computational fluid dynamics solver, a nonlinear beam element structural model, a conservative fluid–structural interface treatment, and the formulation and implementation of a new deforming grid capability within the cut-cell Cartesian grid solver. In this paper, emphasis is on this latter component with detailed description given of the mesh motion strategy, evaluation of fluxes and structural loads at the surface, and computation of geometrical properties such as cell volume, directed face areas, centroids, and motion-induced fluxes for deforming Cartesian grids required to advance the flow states. Aeroelastic simulations exercising the capability show favorable agreement with data and predictions in the literature for subsonic and supersonic applications.

97 MATHEMATICS AND COMPUTING↗

Geometry Optimization for Structural Reliability and Performance of a Thermoelectric Generator

The opposing requirements for the performance and reliability of a thermoelectric generator (TEG) are investigated with numerical finite element analysis simulations. The parameters that significantly influence the operational performance and structural reliability of a TEG are considered for simultaneous optimization. The design of experiments (DOE) based response surface optimization methodology in conjunction with results from finite element analysis was employed to identify optimal parameters from the structural reliability and performance (power output and efficiency) perspectives. A high temperature bismuth telluride based TEG couple was used in the studies to demonstrate the general applicability of the methodology. The response surface methodology is found to be a robust technique that can expedite the process of geometry optimization of a TE device during the research and development phase of TEG devices fabricated from new thermoelectric materials.

Karri, Naveen K.↗

Cell degradation quantification—a performance metric-based approach

A safe and reliable battery operation needs effective diagnostic tools. A quantitative failure analysis (FA) to enable cell qualification and quantify its effectiveness for reliable and safe operation of rechargeable Li batteries (RLB) is shown here. The method can identify and quantify potential failure based on the state of charge (SOC) under any operating conditions. A precise and accurate electrochemical analytic diagnosis (eCAD) of 14 rechargeable Li || NMC622 cells of the same build are used as an example. The FA by eCAD can quantitatively decipher good, bad and ugly cells in cycle aging. The cell qualification is based on thermodynamic SOC, not experimental conditions. The method provides a quantitative failure mode and effect analysis (FMEA) to reveal diverse “dead Li” formation that affects the reversibility of the Li anode and charge retention in the cell. This cell qualification method highlights the potential to improve cell quality for safe operation, with strong implications for early fault detection, FA, risk mitigation, state estimation and life prediction for reliable and safe RLB operations

25 ENERGY STORAGE↗