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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.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Measured and satellite-derived albedo data for estimating bifacial photovoltaic system performance

The albedo of the ground surface is an important factor in the cost-effectiveness of a bifacial photovoltaic (PV) system. To improve the availability of reliable albedo data, datasets of ground albedo and associated meteorological data were developed by using existing measurement network data and data measured by the PV industry. The measured datasets include time-series data as well as summary information of tabular monthly and yearly data and plots of monthly and hourly albedo values. Satellite-derived values of albedo are available from the National Solar Radiation Data Base (NSRDB). The NSRDB albedos were compared to the measured albedos for Surface Radiation budget (SURFRAD) network locations for the period 2001–2017, and the mean bias difference results were from -0.044 to +0.056. Overall, these differences are greater than the albedo measurement uncertainty of ±0.02; consequently, the NSRDB albedos should be used with caution for estimating the performance of bifacial PV systems. Differences between SURFRAD and NSRDB albedos are attributed to the NSRDB method for determining albedo and to the ground surfaces within the NSRDB 4 km spatial resolution pixel consisting of a mixture of surface types rather than just the single surface types viewed by the albedometers at the SURFRAD stations.

14 SOLAR ENERGY↗
DOE OSTI2024

Simulator Data Analysis to Inform Digitalized Environment Impacts on Human Reliability

The U.S. Nuclear Regulatory Commission (NRC) has developed a human reliability analysis (HRA) method, termed the Integrated Human Event Analysis System for Event and Condition Assessment (IDHEAS-ECA), in order to estimate human error probabilities (HEPs) in risk-informed regulatory applications. To update the quantification part of IDHEAS-ECA, the NRC required human performance and error data from fully digitalized main control rooms (MCRs); therefore, it requested that Idaho National Laboratory (INL) revisit previous data collection studies and investigate how the following three factors impact human reliability: self-checking, peer-checking, and automation. The HRA data collection studies revisited were the Human Reliability Data Extraction (HuREX) project, developed by the Korea Atomic Energy Research Institute (KAERI), and the Simplified Human Error Experimental Program (SHEEP), developed by INL. HuREX is a representative HRA data collection study that collects human reliability data from full-scope simulators staffed by licensed operators. SHEEP, on the other hand, has been proposed to complement such full-scope studies by collecting data via simplified simulators staffed by non-licensed student operators. In the HuREX study, KAERI collected HRA data from fully digitalized MCRs for the Advanced Power Reactor (APR)–1400. The SHEEP data were obtained from simplified simulators that partially mimicked the features of digitalized MCRs. The present report mainly discusses how the impacts of the aforementioned three factors on human errors were derived from these two data collection studies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Extracting Resilience Metrics From Distribution Utility Data Using Outage and Restore Process Statistics

Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. The formulas express the mean value of these metrics as a function of the number of outages in the event. We also give a formula for the variability of restore duration, which allows us to predict a maximum restore duration with 95% confidence. Overall, we give a simple and general way to decompose resilience curves into outage and restore processes and then show how to use these processes to extract resilience metrics from standard distribution system data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

G EANT 4 atomic relaxation data for transfermium nuclei (Z = 101–104)

Advanced theoretical methods can accurately calculate various atomic observables and predict electronic structure. Still, systematic computations of the radiative and non-radiative transition probabilities and energies are missing for the actinides and all the transfermium elements. However, these compilations are needed for comprehensive Monte-Carlo simulations (such as GEANT4) of the radioactive decay of transfermium nuclei. These simulations can forma basis for data analysis of experiments, especially with complex detection setups. Investigation of the transfermium nuclei is crucial for understanding the nature of the nuclear force. In this study, simulations based on data from the Jena Atomic Calculator (JAC) and the data from the Evaluated Atomic Data Library (EADL) present in GEANT4 were found compatible for the three elements Ba(Z = 56), U(Z = 92), and Fm(Z = 100), thus, validating the JAC calculations. For Z> 100, we also found sound agreement between simulations that used data generated with JAC and experimental results involving No(Z = 102) and Rf(Z = 104) isotopes. In conclusion, these results demonstrate that JAC can produce reliable atomic data sets for transfermium elements, which will assist in analyzing nuclear-decay-spectroscopy experiments.

GEANT4↗
DOE OSTI2021

SeismoGen: Seismic Waveform Synthesis Using GAN With Application to Seismic Data Augmentation

Abstract Detecting earthquake arrivals within seismic time series can be a challenging task. Visual, human detection has long been considered the gold standard but requires intensive manual labor that scales poorly to large data sets. In recent years, automatic detection methods based on machine learning have been developed to improve the accuracy and efficiency. However, the accuracy of those methods relies on access to a sufficient amount of high‐quality labeled training data, often tens of thousands of records or more. We aim to resolve this dilemma by answering two questions: (1) provided with a limited amount of reliable labeled data, can we use them to generate additional, realistic synthetic waveform data? and (2) can we use those synthetic data to further enrich the training set through data augmentation, thereby enhancing detection algorithms? To address these questions, we use a generative adversarial network (GAN), a type of machine learning model which has shown supreme capability in generating high‐quality synthetic samples in multiple domains. Once trained, our GAN model is capable of producing realistic seismic waveforms of multiple labels (noise and event classes). Applied to real Earth seismic data sets in Oklahoma, we show that data augmentation from our GAN‐generated synthetic waveforms can be used to improve earthquake detection algorithms in instances when only small amounts of labeled training data are available.

Wang, Tiantong↗
DOE OSTI2024

State Machine Operation of Complex Systems

Operation of complex systems which depend on one, or more, sub-systems with many process variables often operate in more than one state. For each state there may be a variety of parameters of interest, and for each of these, one may require different alarm limits, different archiving needs, and have different critical parameters. Relying on operators to reliably change 102-105 parameters for each system for each state is unreasonable. Not changing these parameters results in alarms being ignored or disabled, critical changes missed, and/or data archiving inefficiencies. To reliably manage the operation of complex systems, such as cryomodules (CMs), Fermilab is implementing state machines for each CM and an over-arching state machine for the PIP-II superconducting LINAC (SCL). The state machine transitions and operating parameters are stored/restored to/from a configuration database. Proper implementation of the state machines will not only ensure safe and reliable operation of the CMs, but will help ensure reliable data quality. A description of PIP-II SCL, details of the state machines, and plans for imminent use the state machines for CM testing will be discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Comparing Methods for Assessing Reliability Uncertainty Based on Pass/Fail Data Collected Over Time

In this paper, we compare statistical methods for analyzing pass/fail data collected over time; some methods are traditional and one (the RADAR or Rationale for Assessing Degradation Arriving at Random) was recently developed. These methods are used to provide uncertainty bounds on reliability. We make observations about the methods' assumptions and properties. Finally, we illustrate the differences between two traditional methods, logistic regression and Weibull failure time analysis, and the RADAR method using a numerical example.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Wave Energy Converter Design Load Case Study

This article presents an example by which design loads for a wave energy converter (WEC) might be estimated through the various stages of the WEC design process. Unlike previous studies, this study considers structural loads, for which, an accurate assessment is crucial to the optimization and survival of a WEC. Three levels of computational fidelity are considered. The first set of design load approximations are made using a potential flow frequency-domain boundary-element method with generalized body modes. The second set of design load approximations are made using a modified version of the linear-based time-domain code WEC-Sim. The final set of design load simulations are realized using computational fluid dynamics coupled with finite element analysis to evaluate the WEC’s loads in response to both regular and focused waves. This study demonstrates an efficient framework for evaluating loads through each of the design stages. In comparison with experimental and high-fidelity simulation results, the linear-based methods can roughly approximate the design loads and the sea states at which they occur. The high-fidelity simulations for regular wave responses correspond well with experimental data and appear to provide reliable design load data. The high-fidelity simulations of focused waves, however, result in highly nonlinear interactions that are not predicted by the linear-based most-likely extreme response design load method.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Characterization of Low-mass Companions to Kepler Objects of Interest Observed with APOGEE-N

We report the characterization of 28 low-mass (0.02 M ⊙ ≤ M 2 ≤ 0.25 M ⊙ ) companions to Kepler objects of interest (KOIs), eight of which were previously designated confirmed planets. These objects were detected as transiting companions to Sunlike stars (G and F dwarfs) by the Kepler mission and are confirmed as single-lined spectroscopic binaries in the current work using the northern multiplexed Apache Point Observatory Galactic Evolution Experiment near-infrared spectrograph (APOGEE-N) as part of the third and fourth Sloan Digital Sky Surveys. We have observed hundreds of KOIs using APOGEE-N and collected a total of 43,175 spectra with a median of 19 visits and a median baseline of ~1.9 yr per target. We jointly model the Kepler photometry and APOGEE-N radial velocities to derive fundamental parameters for this subset of 28 transiting companions. The radii for most of these low-mass companions are overinflated (by ~10%) when compared to theoretical models. Tidally locked M dwarfs on short-period orbits show the largest amount of inflation, but inflation is also evident for companions that are well separated from the host star. We demonstrate that APOGEE-N data provide reliable radial velocities when compared to precise high-resolution spectrographs that enable detailed characterization of individual systems and the inference of orbital elements for faint (H > 12) KOIs. The data from the entire APOGEE-KOI program are public and present an opportunity to characterize an extensive subset of the binary population observed by Kepler.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Making machine learning a useful tool in the accelerated discovery of transition metal complexes

Abstract As machine learning (ML) has matured, it has opened a new frontier in theoretical and computational chemistry by offering the promise of simultaneous paradigm shifts in accuracy and efficiency. Nowhere is this advance more needed, but also more challenging to achieve, than in the discovery of open‐shell transition metal complexes. Here, localized d or f electrons exhibit variable bonding that is challenging to capture even with the most computationally demanding methods. Thus, despite great promise, clear obstacles remain in constructing ML models that can supplement or even replace explicit electronic structure calculations. In this article, I outline the recent advances in building ML models in transition metal chemistry, including the ability to approach sub‐kcal/mol accuracy on a range of properties with tailored representations, to discover and enumerate complexes in large chemical spaces, and to reveal opportunities for design through analysis of feature importance. I discuss unique considerations that have been essential to enabling ML in open‐shell transition metal chemistry, including (a) the relationship of data set size/diversity, model complexity, and representation choice, (b) the importance of quantitative assessments of both theory and model domain of applicability, and (c) the need to enable autonomous generation of reliable, large data sets both for ML model training and in active learning or discovery contexts. Finally, I summarize the next steps toward making ML a mainstream tool in the accelerated discovery of transition metal complexes. This article is categorized under: Electronic Structure Theory > Density Functional Theory Software > Molecular Modeling Computer and Information Science > Chemoinformatics

Kulik, Heather J.↗
DOE OSTI2023

State Machine Operation of Complex Systems

Operation of complex systems which depend on one or more other systems with many process variables often operate in more than one state. For each state there may be a variety of parameters of interest, and for each of these, one may require different alarm limits, different archiving needs, and have different critical parameters. Relying on operators to reliably change 10s-1000s of parameters for each system for each state is unreasonable. Not changing these parameters results in alarms being ignored or disabled, critical changes missed, and/or possible data archiving problems. To reliably manage the operation of complex systems, such as cryomodules (CMs), Fermilab is implementing state machines for each CM and an over-arching state machine for the PIP-II superconducting linac (SCL). The state machine transitions and operating parameters are stored/restored to/from a configuration database. Proper implementation of the state machines will not only ensure safe and reliable operation of the CMs, but will help ensure reliable data quality. A description of PIP-II SCL, details of the state machines, and lessons learned from limited use of the state machines in recent CM testing will be discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Poster — Thur Eve — 33: The Influence of a Modeled Treatment Couch on Dose Distributions During IMRT and RapidArc Treatment Delivery

Treatment couches have been known to perturb dose delivery in patients. This effect is most pronounced in techniques such as IMRT and RapidArc. Although modern treatment planning systems (TPS) include data for a “default” treatment couch, actual couches are not manufactured identically. Thus, variations in their Hounsfield Unit (HU) values may exist. This study demonstrates a practical and simple method of acquiring reliable HU data for any treatment couch. We also investigate the effects of both the default and modeled treatment couches on absorbed dose. Experimental verifications show that by neglecting to incorporate the treatment couch in the TPS, dose differences of up to 9.5% and 7.3% were present for 4 MV and 10 MV photon beams, respectively. Furthermore, a clinical study based on a cohort of 20 RapidArc and IMRT (brain, pelvis and abdominal) cases is performed. 2D dose distributions show that without the couch in the planning phase, differences ≤ 4.6% and 5.9% for RapidArc and IMRT cases are present for the same cases that the default couch was added to. Additionally, in comparison to the default couch, employing the modeled couch in the calculation process influences dose distributions by ≤ 2.7% and 8% for RapidArc and IMRT cases, respectively. This result was found to be site specific; where an accurate couch proves to be preferable for IMRT brain plans. As such, adding the couch during dose calculation decreases dose calculation errors, and a precisely modeled treatment couch offers higher dose delivery accuracy for brain treatment using IMRT.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Data Quality-Aware Framework to Reliably Forecast Photovoltaic Generation and Consumer Load for an Improved Resilience of Microgrids

Photovoltaic (PV) power and consumer load forecasting plays a critical role to ensure operational resilience of the electric grid. Most data-driven forecasting algorithms rely heavily on the continuous availability of good quality data for periodic training and validation. When deployed at the grid’s edge, prolonged disruptions to communications during extreme events degrade data quality. Factors such as missing observations, epistemic uncertainties, data drift, and concept drift are manifestations of data quality that impact the generalization of such field-deployed forecasting models. Currently, there exists no mechanism in the literature to dynamically switch between models under varying degrees of data quality as quantified by certain metrics for each factor highlighted above. This paper addresses this shortcoming by conceptually introducing a data qualityaware framework for reliable PV generation and consumer load forecasting. The framework’s design incorporates components of missing values, divergence tests, and continuous monitoring of generalization performance to detect changes in data quality caused by communications disruptions and trigger specific classes of forecasting models grouped under three use cases (UC1- UC3). As a first step towards validating this framework, real data collected from an actual field microgrid system is used to demonstrate the viability of the three use cases. Results show that the performance is the best in UC1 with an unadjusted R-square value of 0.954, followed by 0.939 for UC2 and 0.757 for UC3.

Sundararajan, Aditya↗
DOE OSTI2015

Calculated fission-fragment yield systematics in the region 74 <=Z <= 94 and 90 <=N <= 150

Background: In the seminal experiment by Schmidt et al . [Nucl. Phys. A 665 , 221 (2000)] in which fission-fragment charge distributions were obtained for 70 nuclides, asymmetric distributions were seen above nucleon number A ≈ 226 and symmetric ones below. Because asymmetric fission had often loosely been explained as a preference for the nucleus to always exploit the extra binding of fragments near ¹³²Sn it was assumed that all systems below A ≈ 226 would fission symmetrically because available isotopes do not have a proton-to-neutron Z/N ratio that allows division into fragments near ¹³²Sn. But the finding by Andreyev et al . [Phys. Rev. Lett. 105 , 252502 (2010)] did not conform to this expectation because the compound system ¹⁸⁰Hg was shown to fission asymmetrically. It was suggested that this was a new type of asymmetric fission, because no strong shell effects occur for any possible fragment division. Purpose: We calculate a reference database for fission-fragment mass yields for a large region of the nuclear chart comprising 987 nuclides. A particular aim is to establish whether ¹⁸⁰Hg is part of a contiguous region of asymmetric fission, and if so, its extent, or if not, in contrast to the actinides, there are scattered smaller groups of nuclei that fission asymmetrically in this area of the nuclear chart. Methods: We use the by now well benchmarked Brownian shape-motion method and perform random walks on the previously calculated five-dimensional potential-energy surfaces. The calculated shell corrections are damped out with energy according to a prescription developed earlier. Results: We have obtained a theoretical reference database of fission-fragment mass yields for 987 nuclides. These results show an extended region of asymmetric fission with approximate extension 74 ≤ Z ≤ 85 and 100 ≤ N ≤ 120. The calculated yields are highly variable. We show 20 representative plots of these variable features and summarize the main aspects of our results in terms of “nuclear-chart” plots showing calculated degrees of asymmetry versus N and Z. Conclusions: Experimental data in this region are rare: only ten or so yield distributions have been measured, some with very limited statistics. We agree with several measurements with higher statistics. Regions where there might be differences between our calculated results and measurements lie near the calculated transition line between symmetric and asymmetric fission. To draw more definite conclusions about the accuracy of the present implementation of the Brownian shape-motion approach in this region experimental data, with reliable statistics, for a fair number of suitably located additional nuclides are clearly needed. Because the nuclear potential-energy structure is so different in this region compared to the actinide region, additional experimental data together with fission theory studies that incorporate additional, dynamical aspects should provide much new insight.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Experimental determination of the complex stiffness tensor and Euler angles in anisotropic media using ultrasonic waves

The aim of this work is to measure the complex elastic tensor and Euler angles in very complex anisotropic media like austenitic steel welds, by inverse problem resolution from experimental data. The obtained experimental characteristics of the anisotropic material will be injected in a FE code developed by EDF enabling the simulation of an actual ultrasonic NDE of welds. The present work aims to provide reliable input data to the 3D future development of the code. In particular, this complex elastic tensor will allow to predict by modeling beam skewing ant attenuation in an austenitic weld. The investigation of such anisotropic media is very complex because of the directional dependency of the elastic stiffness tensor. Then we will discuss the use of a hybrid genetic algorithm to overcome this difficulty. The identification method is based on waveforms spectra reconstruction associated to a physical model describing wave propagation in plates, during underwater measurements. The entire procedure is qualified and validated using simulated data. Moreover, a comparison of the estimated elastic coefficients with literature values and ultrasonic measurements obtained in transmission is also given, at the end of the paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Fault-tolerant bandwidth reservation strategies for data transfers in high-performance networks

Many next-generation e-science applications need fast and reliable transfer of large volumes of data with guaranteed performance, which is typically enabled by the bandwidth reservation service in high-performance networks. One prominent issue in such network environments with large footprints is that node and link failures are inevitable, hence potentially degrading the quality of data transfer. We consider two generic types of bandwidth reservation requests (BRRs) concerning data transfer reliability: (i) to achieve the highest data transfer reliability under a given data transfer deadline, and (ii) to achieve the earliest data transfer completion time while satisfying a given data transfer reliability requirement. We propose two periodic bandwidth reservation algorithms with rigorous optimality proofs to optimize the scheduling of individual BRRs within BRR batches. The efficacy of the proposed algorithms is illustrated through extensive simulations in comparison with scheduling algorithms widely adopted in production networks in terms of various performance metrics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

UK-US Collaboration on Fossil Energy R&D: Steam Side Oxidation

In recent years, interest in increasing the efficiency of power plants based on steam generation has led to the need to develop and qualify materials capable of operating at steam temperatures and pressures significantly higher than those employed in current power plants. The overall focus of this international program is on using ferritic-martensitic steels to the maximum possible temperature, before switching to austenitic steels and/or Ni-based alloys. The relatively low Cr content of these alloys raises concerns regarding their resistance to steam oxidation at these higher temperatures. Earlier work in this collaboration addressed the reliability of data from atmospheric pressure, laboratory-based steam oxidation tests. This raised issues regarding how representative the laboratory-grown oxides were compared to those formed on service-exposed material and how the tests could be made more reliable by introducing added complexity. In general laboratory-scale exposures are conducted under isothermal conditions at ambient or slightly elevated pressure, using a relatively low flow rate of steam. The coupons used in these tests are normally flat cuboids which have been ground to homogenise the surface and remove any pre-existing features. However, there is a concern that these samples and exposures are not representative of service conditions, and so it is necessary to quantify the influence of transient conditions, such as heat flux, pressure and sample geometry/surface conditions. To address such concerns a new collaborative program of work was initiated to determine the influence of these added features on oxidation kinetics and oxide scale morphology. The overall aim was to improve the understanding of alloy performance in ultrasupercritical (USC) steam conditions and qualify suitable test procedures.

20 FOSSIL-FUELED POWER PLANTS↗