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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Improving Thermal Model Prediction Through Statistical Analysis of Irradiation and Post-Irradiation Data from AGR Experiments

As part of the High Temperature Reactors (HTR) R&D program, a series of irradiation tests, designated as Advanced Gas-cooled Reactor (AGR), have been defined to support development and qualification of fuel design, fabrication process, and fuel performance under normal operation and accident conditions. The AGR tests employ fuel compacts placed in a graphite cylinder shrouded by a steel capsule and instrumented with thermocouples (TC) embedded in graphite blocks enabling temperature control. While not possible to obtain by direct measurements in the tests, crucial fuel conditions (e.g., temperature, neutron fast fluence, and burnup) are calculated using core physics and thermal modeling codes. This paper is focused on AGR test fuel temperature predicted by the ABAQUS code's finite element-based thermal models. The work follows up on a previous study, in which several statistical analysis methods were adapted, implemented in the NGNP Data Management and Analysis System (NDMAS), and applied for qualification of AGR-1 thermocouple data. Abnormal trends in measured data revealed by the statistical analysis are traced to either measuring instrument deterioration or physical mechanisms in capsules that may have shifted the system thermal response. The main thrust of this work is to exploit the variety of data obtained in irradiation and post-irradiation examination (PIE) for assessment of modeling assumptions. As an example, the uneven reduction of the control gas gap in Capsule 5 found in the capsule metrology measurements in PIE helps identify mechanisms other than TC drift causing the decrease in TC readings. This suggests a more physics-based modification of the thermal model that leads to a better fit with experimental data, thus reducing model uncertainty and increasing confidence in the calculated fuel temperatures of the AGR-1 test.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Initial demonstration of automated fuel performance modeling with 1977 EBR-II metallic fuel pins using BISON code with FIPD and IMIS databases

Using the BISON fuel performance code, simulations were conducted using an automated process to read initial and operating conditions from the Fuels Irradiation and Physics Database (FIPD) and Integral Fast Reactor materials information system (IMIS) database, which contains metallic fuel data from the Experimental Breeder Reactor-II (EBR-II). This work demonstrates use of an integrated framework to access the vast majority of EBR-II experimental fuel pin data to support rapid development of fuel performance models for next-generation metallic fuel systems. With this capability, validation for fuel qualification can be performed rapidly. Between IMIS and FIPD, there is enough information to conduct 1977 unique EBR-II metallic fuel pin histories from 24 different experiments, at varying levels of detail between the two databases. Each of these histories includes a high-resolution power history, flux history, coolant channel flow rates, and coolant channel temperatures. Fission gas release (FGR), cumulative damage fraction (CDF), fuel axial swelling, cladding profilometry, and burnup were all simulated in BISON. The results were compared to post-irradiation examination (PIE) results for the initial demonstration of automated BISON modeling. BISON simulations conducted with IMIS and FIPD were in rough agreement with PIE measurements and calculations. Cladding profilometry, FGR, and fuel axial swelling were found to be in rough agreement with PIE measurements, depending on the physics used within the BISON input files. Here, the mechanical contact solver chosen was found to significantly impact axial fuel swelling and cladding strain predictions. CDF values were assessed to see whether pin failure may have been predicted (CDF ≥ 1). This work suggests that continued development of an automated tool for BISON should focus on inclusion of the Fast Flux Test Facility (FFTF) experimental data for a larger database for metallic fuel, improved physical models to better capture fuel performance, such as fuel-cladding interactions, and a more detailed comparison with available PIE data to further the BISON model development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Results of the AGR-5/6/7 UCO TRISO fuel irradiation test in the Advanced Test Reactor

AGR-5/6/7 was the last in a series of irradiation experiments sponsored by the U.S. Department of Energy in support of the development and qualification of TRISO coated particle fuel for use in a high-temperature gas-cooled reactor. This experiment was conducted to verify the performance of the reference-design TRISO-coated low-enriched UCO fuel for modular high-temperature gas-cooled reactor normal operating conditions and to explore fuel performance at temperatures substantially beyond those typical of normal operation. A total of 194 UCO fuel compacts in five capsules were irradiated in the Advanced Test Reactor for 360.9 effective full-power days, achieving final burnup ranging from 5.66% to 15.26% fissions per initial heavy metal atom and fast neutron fluence ranging from 1.62 × 10 25 to 5.55 × 10 25 n/m 2 (E > 0.18 MeV). Calculated time-averaged fuel temperatures ranged from 467 °C to 1432 °C, with a peak fuel temperature of 1536 °C. During the first five irradiation cycles (∼180 effective full-power days), 85m Kr fission gas release-rate-to-birth-rate ratios were 10 −7 –10 −6 , indicating no particle failures. Near the end of the sixth cycle, a substantial number of in-pile particle failures occurred in Capsule 1. The fission gas release from this capsule impacted the readings from the other four capsules and led to unreliable fission gas release measurements for all capsules during the last four cycles. A preliminary post-irradiation examination of Capsule 1 fuel and internal components revealed the in-pile particle failures resulted from operational issues with the capsule, not subpar performance of the fuel particles.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Inverted, Organic WORM Device Based on PEDOT:PSS with Very Low Turn-On Voltage

An organic Write-Once-Read-Many (WORM) device based on poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) as the active layer was fabricated with an inverted architecture. Insertion of an ultrathin layer of poly(methylmethacrylate) (PMMA) between the bottom electrode and the PEDOT:PSS resulted in a systematic and substantial decrease in turn-on voltage, from 7.0 V to less than 1.0 V. An optimal thickness of the PMMA layer was found to yield the lowest consistent turn-on voltage of ~0.8 V, with 0.5 V being the lowest value of all fabricated devices. The switching mechanism was attributed to filamentary doping of the PEDOT:PSS. Insertion of the PMMA acted to protect the underlying ZnO from being etched by the acidic PEDOT:PSS as well as to improve its wetting properties. Moreover, devices were demonstrated on both ITO and aluminum bottom electrodes, with aluminum yielding the highest ON/OFF ratios in the study. Owing to their inverted architecture, the devices demonstrated good stability, and the retention time of the ON-state was determined to be greater than twenty months while stored in air for devices with ITO bottom electrodes. Blade-coating was demonstrated as a viable processing technique for applications requiring rapid or large-area manufacturing in addition to deposition via spin-coating.

14 SOLAR ENERGY↗
DOE OSTI2019

A microbenchmark characterization of the Emu chick

The Emu Chick is a prototype system designed around the concept of migratory memory-side processing. Rather than transferring large amounts of data across power-hungry, high-latency interconnects, the Emu Chick moves lightweight thread contexts to near-memory cores before the beginning of each memory read. The current prototype hardware uses FPGAs to implement cache-less “Gossamer” cores for computational work and rely on a typical stationary core (PowerPC) to run basic operating system functions and migrate threads between nodes. In this multi-node characterization of the Emu Chick, we extend an earlier single-node investigation of the the memory bandwidth characteristics of the system through benchmarks like STREAM, pointer chasing, and sparse matrix-vector multiplication. Here, we compare the Emu Chick hardware to architectural simulation and an Intel Xeon-based platform. Our results demonstrate that for many basic operations the Emu Chick can use available memory bandwidth more efficiently than a more traditional, cache-based architecture although bandwidth usage suffers for computationally intensive workloads like SpMV. Moreover, the Emu Chick provides stable, predictable performance with up to 65% of the peak bandwidth utilization on a random-access pointer chasing benchmark with weak locality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Optimization of a low noise detection circuit for probing the structure of damage cascades with IBIC

Optimal detector / pre-amplifier combinations have been identified for the use of light ion IBIC (ion beam induced charge) to probe the physical structure of electrically active defects in damage cascades caused by heavy ion implantation. The ideal detector must have a sufficiently thin dead layer that incident ions will produce the majority of damage cascades in the depletion region of the detector rather than the dead layer. Detector and circuit noise must be low enough to detect the implantation of a single heavy ion as well as the decrease in the light ion IBIC signal caused by Shockley-Read-Hall recombination when the beam scans regions of the detector damaged by the heavy ion. The IBIC signals from three detectors irradiated with 750 keV He⁺ ions are measured with commercial and bespoke charge sensitive pre-amplifiers to identify the combination with the lowest noise.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

The Drift Chamber for the Experiment to Study the Nature of the Confinement

The GlueX experiment was designed to search for hybrid mesons with exotic quantum numbers using a beam of linearly polarized photons incident on a liquid hydrogen target. The spectrum of these states and their mass splitting from normal mesons may yield information on confinement. The description of the GlueX spectrometer and Forward Drift Chambers (FDC) as a part of track reconstruction system is presented in the text. FDC‘s are multiwire chambers with cathode and anode read-out. The system allows reconstructing tracks of charged particles with ~200mkm accuracy with angles from 20° up to 1°. One of the detector features is 1.64% X 0 material amount in the active area. The cathode gain calibration procedure is presented. The results of such calibration using cosmic data and beam data are presented as well.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Parameter optimization for transitions between memory states in small arrays of Josephson junctions

Coupled arrays of Josephson junctions possess multiple stable zero voltage states. Such states can store information and consequently can be utilized for cryogenic memory applications. Basic memory operations can be implemented by sending a pulse to one of the junctions and studying transitions between the states. In order to be suitable for memory operations, such transitions between the states have to be fast and energy efficient. Here in this article we employed simulated annealing, a stochastic optimization algorithm, to study parameter optimization of array parameters which minimizes times and energies of transitions between specifically chosen states that can be utilized for memory operations (Read, Write, and Reset). Simulation results show that such transitions occur with access times on the order of 10–100 ps and access energies on the order of 10 -19 –5×10 -18 J. Numerical simulations are validated with approximate analytical results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The anomalous magnetic moment of the muon in the Standard Model

We review the present status of the Standard Model calculation of the anomalous magnetic moment of the muon. This is performed in a perturbative expansion in the fine-structure constant α and is broken down into pure QED, electroweak, and hadronic contributions. The pure QED contribution is by far the largest and has been evaluated up to and including O(α 5 ) with negligible numerical uncertainty. The electroweak contribution is suppressed by (m μ / M W ) 2 and only shows up at the level of the seventh significant digit. It has been evaluated up to two loops and is known to better than one percent. Hadronic contributions are the most difficult to calculate and are responsible for almost all of the theoretical uncertainty. The leading hadronic contribution appears at O(α 2 ) and is due to hadronic vacuum polarization, whereas at O(α 3 ) the hadronic light-by-light scattering contribution appears. Given the low characteristic scale of this observable, these contributions have to be calculated with nonperturbative methods, in particular, dispersion relations and the lattice approach to QCD. The largest part of this review is dedicated to a detailed account of recent efforts to improve the calculation of these two contributions with either a data-driven, dispersive approach, or a first- principle, lattice-QCD approach. The final result reads $a$$^{SM}_{μ}$ = 116 591 810(43) × 10 −11 and is smaller than the Brookhaven measurement by 3.7σ. The experimental uncertainty will soon be reduced by up to a factor four by the new experiment currently running at Fermilab, and also by the future J-PARC experiment. Furthermore, this and the prospects to further reduce the theoretical uncertainty in the near future – which are also discussed here – make this quantity one of the most promising places to look for evidence of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

The anomalous magnetic moment of the muon in the Standard Model: an update

We present the current Standard Model (SM) prediction for the muon anomalous magnetic moment, a μ , updating the first White Paper (WP20) [1]. The pure QED and electroweak contributions have been further consolidated, while hadronic contributions continue to be responsible for the bulk of the uncertainty of the SM prediction. Significant progress has been achieved in the hadronic light-by-light scattering contribution using both the data-driven dispersive approach as well as lattice-QCD calculations, leading to a reduction of the uncertainty by almost a factor of two. The most important development since WP20 is the change in the estimate of the leading-order hadronic-vacuum-polarization (LO HVP) contribution. A new measurement of the e + e - → π + π - cross section by CMD-3 has increased the tensions among data-driven dispersive evaluations of the LO HVP contribution to a level that makes it impossible to combine the results in a meaningful way. At the same time, the attainable precision of lattice-QCD calculations has increased substantially and allows for a consolidated lattice-QCD average of the LO HVP contribution with a precision of about 0.9%. Adopting the latter in this update has resulted in a major upward shift of the total SM prediction, which now reads $a^{SM}_{μ}$ = 116 592 033 (62) x $10^{-11}$ (530 ppb). When compared against the current experimental average based on the E821 experiment and runs 1–6 of E989 at Fermilab, one finds $a^{exp}_{μ} -a^{SM}_{μ}= 38 (63)$ x $10^{-11}$, which implies that there is no tension between the SM and experiment at the current level of precision. The final precision of E989 (127 ppb) is the target of future efforts by the Theory Initiative. The resolution of the tensions among data-driven dispersive evaluations of the LO HVP contribution will be a key element in this endeavor.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Development and assessment of a model predictive controller enabling anticipatory control strategies for a heat-pipe system

To support the reliable and resilient operation of modular reactors and microreactors, anticipatory control strategies have been proposed for achieving faster-than-real-time predictions and decision-making capabilities in anticipation of potential anomalies, including setpoint changes and cyber incidents. Here this work presents how anticipatory control strategies can be implemented via model predictive control (MPC) of a single heat pipe’s temperature. Considering the uncertainty in developing and applying MPC, this work evaluates MPC performance given three different model forms: a linear response surface model, an artificial neural network (ANN), and an autoregressive model with exogenous input (ARX). This work also evaluates the impacts of different input biases and variance on MPC performance in order to account for potential sensor reading variations due to cyber incidents. We observe that nonparametric models such as the ANN and ARX result in more fluctuated control actions compared to the MPC applied to the linear response surface model. However, when the cyber incidents are of a large magnitude, the linear response surface model produces smaller feasible regions than the nonparametric models under identical constraints.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

StoreRush: An Application-Level Approach to Harvesting Idle Storage in a Best Effort Environment

For a production HPC system where storage devices are shared between multiple applications and managed in a best effort manner, contention is often a major problem leading to some storage devices being more loaded than others and causing a significant reduction in I/O throughput. In this paper, we describe our latest efforts StoreRush to resolve this practical issue at the application level without requiring modification to the file and storage system. The proposed scheme uses a two-level messaging system to harvest idle storage via re-routing I/O requests to a less congested storage location so that write performance is improved while limiting the impact on read by throttling re-routing if deemed too much. An analytical model is derived to guide the setup of optimal throttling factor. The proposed scheme is verified against production applications Pixie3D, XGC1 and QMCPack during production windows, which very well demonstrated the effectiveness (e.g., up to 1.8x improvement in write) and scalability of our approach (up to 131,072 cores).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees or reliability block diagrams) can effectively propagate reliability data from the asset to the system level in order to identify system critical points. However, employed asset reliability data are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers on the most critical assets. In addition, the propagation of quantitative health data from the asset to the system level is a challenge given the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, expected failure time). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating available health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Here, this paper is directly addressing these two goals by proposing a different approach for reliability modeling that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. The propagation of health data from the asset to the system level is performed through fault tree models not in probability terms, but in terms of margin where margin is the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of an undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical assets.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Quantification of gas concentrations in NO/NO 2 /C 3 H 8 /NH 3 mixtures using machine learning

We employ machine learning to decode the composition of unknown gas mixtures from the output of an array of four electrochemical sensors. The sensors use metal oxide electrodes paired with a ceramic electrolyte, yttria-stabilized zirconia (YSZ), to produce voltage responses to the presence of gases in complex mixtures. The voltages from the sensor array serve as inputs to a machine learning pipeline which first carries out multi-class classification of mixtures into types based on which gases are present at non-zero concentrations, and subsequently predicts gas concentrations given the mixture type. Thus, our model is able to take a single reading from the sensor array in response to gas mixtures involving NO, NO 2 , C 3 H 8 , and NH 3 , and output a highly accurate prediction of which gases are present in the mixture, along with the concentrations of each constituent gas. Of note, our computational framework can be easily expanded to include additional gases and additional mixture types, allowing it to be used in numerous automotive, industrial and environmental monitoring settings.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

MPLBM-UT: Multiphase LBM library for permeable media analysis

MPLBM-UT is a specialized lattice-Boltzmann library that makes running single- and two-phase flow simulations in porous media accessible to everyone. We provide a suite of tools to pre-process computational domains for simulation, to set up custom boundary conditions, to run simulations, to post-process simulation outputs, and to visualize simulation results and data. All of these tools are easily accessible to users through the mplbm_utils Python package included in and automatically installed with MPLBM-UT. The high-performance, highly parallel library Palabos is used as the solver backend. MPLBM-UT is easily deployed in a variety of systems, from laptops to supercomputer clusters. MPLBM-UT also features multiple examples and benchmark templates that allow for fast prototyping of different porous media problems. We also provide an interface for reading in different file types and downloading domains from the Digital Rocks Portal to perform simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Effects of post-deposition CdCl 2 annealing on electronic properties of CdTe solar cells

The effects of post-deposition CdCl 2 annealing temperature on the electronic properties of CdTe solar cells were investigated. CdTe devices incorporate Mg doped ZnO as a buffer layer and selenization using a CdSe interlayer for reducing the buffer/absorber interface recombination and increasing solar energy absorption respectively. The post-deposition CdCl 2 annealing treatments were done under separate, inert atmospheres of nitrogen and helium across the temperature range 380 to 430 °C. Electrical characterization of devices is carried out including temperature dependent current-voltage characteristics, admittance spectroscopy, and Shockley-Read-Hall recombination analysis. Here, the best improvements in device efficiency are obtained upon annealing at temperature 410 °C. This anneal correlated with reduced back contact barrier in CdTe and reduced grain-boundary barrier height which is beneficial for enhanced charge transport.

14 SOLAR ENERGY↗
DOE OSTI2023

pvlib iotools—Open-source Python functions for seamless access to solar irradiance data

Access to accurate solar resource data is critical for numerous applications, including estimating the yield of solar energy systems, developing radiation models, and validating irradiance datasets. However, lack of standardization in data formats and access interfaces across providers constitutes a major barrier to entry for new users. pvlib python’s iotools subpackage aims to solve this issue by providing standardized Python functions for reading local files and retrieving data from external providers. All functions follow a uniform pattern and return convenient data outputs, allowing users to seamlessly switch between data providers and explore alternative datasets. The pvlib package is community-developed on GitHub: https://github.com/pvlib/pvlib-python. As of pvlib python version 0.9.5, the iotools subpackage supports 12 different datasets, including ground measurement, reanalysis, and satellite-derived irradiance data. The supported ground measurement networks include the Baseline Surface Radiation Network (BSRN), NREL MIDC, SRML, SOLRAD, SURFRAD, and the US Climate Reference Network (CRN). Additionally, satellite-derived and reanalysis irradiance data from the following sources are supported: PVGIS (SARAH & ERA5), NSRDB PSM3, and CAMS Radiation Service (including McClear clear-sky irradiance).

14 SOLAR ENERGY↗
DOE OSTI2014

Molecular cloning and functional characterization of a rainbow trout liver Oatp

Cyanobacterial blooms have an impact on the aquatic ecosystem due to the production of toxins (e.g. microcystins, MCs), which constrain fish health or even cause fish death. However the toxicokinetics of the most abundant toxin, microcystin-LR (MC-LR), are not yet fully understood. To investigate the uptake mechanism, the novel Oatp1d1 in rainbow trout (rtOatp1d1) was cloned, identified and characterized. The cDNA isolated from a clone library consisted of 2772 bp containing a 2115 bp open reading frame coding for a 705 aa protein with an approximate molecular mass of 80 kDa. This fish specific transporter belongs to the OATP1 family and has most likely evolved from a common ancestor of OATP1C1. Real time PCR analysis showed that rtOatp1d1 is predominantly expressed in the liver, followed by the brain while expression in other organs was not detectable. Transient transfection in HEK293 cells was used for further characterization. Like its human homologues OATP1A1, OATP1B1 and OATP1B3, rtOatp1d1 displayed multi-specific transport including endogenous and xenobiotic substrates. Kinetic analyses revealed a K{sub m} value of 13.9 μM and 13.4 μM for estrone-3-sulfate and methotrexate, respectively and a rather low affinity for taurocholate with a K{sub m} value of 103 μM. Furthermore, it was confirmed that rtOatp1d1 is a MC-LR transporter and therefore most likely plays a key role in the susceptibility of rainbow trout to MC intoxications. - Highlights: • A new Oatp1d1 in rainbow trout (rtOatp1d1) was cloned, identified and characterized. • rtOatp1d1 is predominantly expressed in the liver. • rtOatp1d1 displays multi-specific transport of endogenous and xenobiotic substrates. • rtOatp1d1 is a homologue of the OATP1A1, OATP1B1 and OATP1B3. • rtOatp1d1 is a microcystin (MC) transporter.

60 APPLIED LIFE SCIENCES↗