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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 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Report detailing comparative analysis of results from high flux isotope reactor and national institute of standards technology small-angle neutron scattering experiments

The major issues regarding irradiation effects are discussed in [1-3] and have also been discussed in previous progress and milestone reports. As noted previously, of the many significant issues discussed, the issue considered to have the most impact on the current regulatory process is that associated with effects of neutron irradiation on RPV steels at high fluence, for long irradiation times, and as affected by neutron flux. It is clear that embrittlement of RPV steels is a critical issue that may limit LWR plant life extension. The primary objective of the LWRSP RPV task is to develop robust predictions of transition temperature shifts (TTS) at high fluence ( t) to at least 1020 n/cm 2 (>1 MeV) pertinent to plant operation of some pressurized water reactors (PWR) for 80 full power years. Correlations between the high flux test reactor results and low flux surveillance specimens must be established for proper RPV embrittlement predictions of the current nuclear power fleet. Additionally, a complete understanding of defect evolution for high nickel RPV steels is needed to characterize the embrittlement potential of Mn-Ni-enriched precipitates (MNPs), particularly for the high fluence regime. While understanding of copper-enriched precipitates (CRPs) have been fully developed, the recent discovery and experimental verification [4] of late blooming MNPs with little to no copper for nucleation has stimulated research efforts to understand the evolution of these phases. New and existing databases will be combined to support developing physically based models of TTS for high fluence-low flux ( < 10 11n/cm 2 -s) conditions, beyond the existing surveillance database, to neutron fluences of at least 1 1020 n/cm2 (>1 MeV). Moreover, large number of various RPV materials have been irradiated in ATR-2 experiment and will be jointly studied by University of California Santa Barbara (UCSB) and ORNL to address majority of microstructural characteristics discussed above, see Ref. [5] and [6] for details. UCSB has performed a large number of SANS experiments in the past at the National Institute of Standards and Technology (NIST) Center for Neutron Research (NCNR). These data are taken from RPV steels irradiated in a wide range of flux-fluence space and will be very useful in comparing to the upcoming UCSB ATR-2 irradiation characterization since most of the SANS experiments with ATR-2 materials will be performed at ORNL High Flux Isotope Reactor (HFIR). However in the previous report [7], some discrepancies were observed between HFIR and NCNR generated data. One of the hypotheses was that there was some kind of extra scattering occurring off the sample holders that results in the HFIR curves falling above the NCNR curves. To test this hypothesis, UCSB provided thermally aged samples that have been previously run at NCNR to ORNL for testing at HFIR while ORNL performed some improvements to experimental set up at HFIR. This report provides the status for the Level 3 Milestone (M3LW-15OR0402013), Complete report detailing comparative analysis of results from High Flux Isotope Reactor and National Institute of Standards and Technology small-angle neutron scattering experiments. This milestone is associated with small-angle neutron scattering characterization at the High Flux Isotope Reactor of various model alloys that had been previously characterized at NCNR by UCSB.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Hardening of A6111-T4 Aluminum Alloy at Large Strains and Its Effect on Sheet Forming Operations

In a number of sheet metal stamping and joining processes, the material undergoes large plastic deformation exceeding the range of plastic strain achievable in a standard tensile test prior to material plastic instability. In order to extend the range of effective strains, the multistep rolling process was employed which enabled prestraining of aluminum sheet above 2.0 of true strain. Tensile testing of rolled samples was used to identify the flow stress corresponding to the level of prestrain: By varying the prestrain level, several data points were obtained for the studied flow curve. The numerical simulation using Abaqus software for the cold rolling process of aluminum strips confirmed that majority of the strip is deformed in plane strain compression condition. Performed simulation of the LDH test determined that earlier fracture might occur if the curve obtained via rolling–tensile testing approach is used versus traditional power law approximation and Voce law approximation. The results of simulation for the multistep drawing of a cylindrical cup revealed possible wrinkling in the die entry area during redrawing stage of the process if the rolling–tensile testing flow curve is employed.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Air Conditioning Stall Phenomenon Testing, Model Development, and Simulation

Electric distribution systems are experiencing power quality issues of extended reduced voltage due to fault-induced delayed voltage recovery (FIDVR). FIDVR occurs in part because modern air conditioner (A/C) and heat pump compressor motors are much more susceptible to stalling during a voltage sag or dip such as a sub-transmission fault. They are more susceptible than older A/C compressor motors due to the low inertia of these newer and more energy efficient motors. There is a concern that these local reduced voltage events on the distribution system will become more frequent and prevalent and will combine over larger areas and challenge transmission system voltage and ultimately power grid reliability. The Distributed Energy Communications and Controls (DECC) Laboratory at Oak Ridge National Laboratory (ORNL) has been employed to (1) test, (2) characterize and (3) model the A/C stall phenomenon.

air conditioning stall↗
DOE OSTI2024

Multiple Beam Triode Driven RF Sources for Accelerator Applications Phase I Final Report

Calabazas Creek Research, Inc, (CCR), in collaboration with Microwave Power Products, Inc. (MPP), formerly Communications & Power Industries, LLC (CPI,) and JP Accelerator Works, Inc. (JPAW), embarked on a program to develop multiple beam triodes to produce RF power from 350 – 800 MHz with an average power exceeding 200 kW. The effort was motivated by the performance of a triode-based RF source which produces 25 kW of UHF power at 90% efficiency. The CCR effort focused on implementing this technology into a multiple beam device to increase the output power while retaining the low cost, compact size, and high efficiency. The program performed extensive simulations indicating that the goals could be achieved, and a prototype multiple beam triode was built, baked, and tested. Unfortunately, a grid to cathode short terminated the testing before the tube could generate RF power. Nevertheless, the effort demonstrated that a multiple beam triode could be designed, built, baked, and energized to high voltage. The multiple beam triode used oxide cathodes, which are only capable of pulsed operation. The multiple beam triode will be rebuilt using dispenser cathodes, which will allow high duty or continuous operation. The grids were also modified to be more robust to avoid previous issues. The MB triode will provide the beam power for RF generation. The RF is generated by surrounding the triode with input and output cavities to convert beam power to RF power. RF cavities to generate 200 kW CW at 350-450 MHz using the MB triode with dispenser cathodes was assembled during the program. The next Phase of this effort is to assemble the multiple beam triode using the subassemblies built in the Phase I program and test with the RF cavities. The Phase I program also initiated design of a higher frequency, higher power multiple beam triode. That design is forecast to produce approximately 500 kW CW from 350 - 500 MHz.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Evaluation of the Effectiveness of a New Technology for Extraction of Insoluble Impurities from Nuclear Power Plant Steam Generators with Purge Water

An experimental technology for the removal of insoluble impurities from a horizontal steam generator with purge water during planned shutdowns of the power generating unit is improved through a more representative determination of the concentration of impurities in the purge water ahead of the water cleanup facility and a more precise effective time for the duration of the purge process. Tests with the improved technique at power generating unit No. 1 of the Rostov Nuclear Power Plant show that the efficiency with which insoluble impurities are removed from the steam generator volume was more than two orders of magnitude greater than under the standard regulations.

42 ENGINEERING↗
DOE OSTI2016

Planck 2015 results: XVI. Isotropy and statistics of the CMB

In this paper, we test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect our studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The “Cold Spot” is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Finally, where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Dynamic System Scaling Application to Accelerated Nuclear Fuel Testing

The development of nuclear fuel and materials requires a continuous effort to investigate the acute and prolonged effects of irradiation, thermal-material stress, chemical change, or other conceivable damage mechanics acquired during normal operation or accident scenarios throughout its lifetime. As in-core fuel property measurement techniques advance to support in the real-time, non-invasive, and enhanced accuracy realm, it is the future of fuel development to pursue to higher degrees of control, predictability of integral test behavior via separate effects test (SET), and shorter test time intervals. The fuel development life cycle from initial concept to commercial licensing is approximated to be 20 years and current literature suggests by optimizing fuel performance codes with SETs, the process could possibly be compressed to 5 to 10 years. Recently, a research group in the Idaho National Laboratory (INL) is testing reduced scale fuel rods and increased power density to accelerate evolution of fuel phenomena in metallic fuels. In support of nuclear fuel rod development, compressing fuel test process, and accelerating fuel phenomena, it was the purpose of this study to investigate nuclear fuel performance phenomena via literature review and effectively scale the initial conditions, boundary conditions, and geometric properties to describe the time-dependent response including to fuel burnup, thermal and mechanical stress, transmutations and inter-diffusion, and other relevant observed phenomena. The study was based on BISON simulations of historic EBR-II metallic fuel experiments and Dynamical System Scaling (DSS) method are utilized to assess effects of scaling activity including fuel phenomena acceleration and calculations of time-dependent distortions. The research successfully scaled metallic fuel phenomena, accelerated fuel testing, and assessed the distortions for each scaled case derived.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

On the reliability of microvariability tests in quasars

Microvariations probe the physics and internal structure of quasars. Unpredictability and small flux variations make this phenomenon elusive and difficult to detect. Variance-based probes such as the C and F tests, or a combination of both, are popular methods to compare the light curves of the quasar and a comparison star. Recently, detection claims in some studies have depended on the agreement of the results of the C and F tests, or of two instances of the F-test, for rejecting the non-variation null hypothesis. However, the C-test is a non-reliable statistical procedure, the F-test is not robust, and the combination of tests with concurrent results is anything but a straightforward methodology. A priori power analysis calculations and post hoc analysis of Monte Carlo simulations show excellent agreement for the analysis of variance test to detect microvariations as well as the limitations of the F-test. Additionally, the combined tests yield correlated probabilities that make the assessment of statistical significance unworkable. However, it is possible to include data from several field stars to enhance the power in a single F-test, increasing the reliability of the statistical analysis. This would be the preferred methodology when several comparison stars are available. An example using two stars and the enhanced F-test is presented. These results show the importance of using adequate methodologies and avoiding inappropriate procedures that can jeopardize microvariability detections. Power analysis and Monte Carlo simulations are useful tools for research planning, as they can demonstrate the robustness and reliability of different research approaches.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Validation of Advanced Photovoltaic Module Materials and Processes by Combined-Accelerated Stress Testing (C-AST)

Tessolar module technology was developed to allow the incorporation of 5 incremental module material innovations. Combined, these innovations may improve the efficiency and durability of the standard silicon cell module. The innovations evaluated are: electrically conductive adhesive (ECA) replacing soldering of tabbing ribbons, light-capturing ribbon (LCR), silicone encapsulant, 2 mm front glass with backsheet, and a polymer-composite module frame. Tessolar-constructed individually encapsulated cells incorporating the material innovations are used to assemble 60-cell modules. 2 x 2 cell mini-modules of the same materials were produced for combined-accelerated stress testing (C-AST). C-AST results demonstrate that the 2 x 2 cell mini-module of Tessolar construction out-performed mini-modules using both ECA with EVA and standard solder with EVA constructions in power production over 108 cycles of testing.

14 SOLAR ENERGY↗
DOE OSTI2022

Options for Subscale Maturation of Advanced Reactor Technologies Testing for Nuclear Thermal Propulsion

Several options could be implemented to establish an irradiation testing capability suitable for investigation of the performance of multiple nuclear thermal propulsion fuel elements at prototypic conditions. The prototypic conditions of interest are based on the current needs of the National Aeronautics and Space Administration’s Space Nuclear Power Program. The results of such testing are also intended to reduce the risks currently seen for any future subscale or full-scale ground testing of an engine-reactor system. The optimal solution is dependent upon several factors such as performance, cost, availability, schedule, technology readiness level, and plans for future testing in the SNP Program. Three options, based on different combinations of these factors, are considered in this report.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Uncertainty and Sensitivity Analysis of Reactivity Insertion Accidents using BISON Fuel Performance Code

The development of Accident Tolerant Fuels (ATF) has expanded into a considerable research program in the wake of the events at the Japanese Fukushima Daiichi nuclear power plant in 2011. The ATF goal is to insert a test assembly into a commercial reactor by 2022. To support this, testing of the ATF design under off-normal conditions is needed to assess the 'enhanced accident tolerance' capability of the fuel rod design over standard UO{sub 2}-Zircaloy concepts. Transient testing capabilities are necessary for off-normal testing of events such as loss of coolant accidents (LOCA) and reactivity insertion accidents (RIA). A transient testing program has been developed to support the testing of ATF designs. The Transient Reactor Test (TREAT) facility has been chosen as the site to perform the transient testing of the ATF designs. TREAT is a versatile test facility capable of subjecting fuel specimens to various off-normal conditions. Historic TREAT experiments were performed in a variety of experimental test vehicles including static environment capsules, once-through flowing systems, and also recirculating flowing systems. The planned TREAT experiments will be operated under PWR conditions. Therefore, a static capsule vehicle is under development to handle required temperatures and pressures. The static capsule, termed the Static Environment Rodlet Transient Test Apparatus (SERTTA), will be used for irradiation tests in TREAT to subject ATF fuel rodlets to a range of power pulse conditions and environments. To aid in the design and analysis of future tests in TREAT, the fuel performance code BISON is being used. Fuel performance codes capable of accident modeling have been developed for some time and they have shown an ability to reproduce experimental results with some degree of adequacy, but they still require extensive verification and validation. Future experiments in TREAT will add to a limited database of past transient tests performed in transient reactors to support LWR systems. These tests can be used for future verification and validation of fuel performance codes. Understanding the impact of the uncertainty of influential parameters is critical for not only analyzing the results of the experiment but also for modeling and validation of codes. For example, uncertainties associated with the initial manufactured state of the sample, instrument measurements, material property models, and planned experiment conditions can provide important insight into model performance, experimental data, and play an important role in experimental design. The objective of this work is to perform an uncertainty and sensitivity analysis on a simplified RIA case of a standard UO{sub 2}-Zircaloy sample using expected nominal conditions in the SERTTA capsule in TREAT. The BISON fuel performance code is used in conjunction with DAKOTA (Design Analysis Kit for Optimization and Tera-scale Applications) to perform the uncertainty and sensitivity analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Evaluation of VVER Reactivity Coefficients in Normal Operating Regimes with Change of External Load

The activity coefficients of a reactor facility with VVER in normal operating regimes associated with a change of the external load are studied. The model used to evaluate the reactivity coefficients in terms of the moderator density and fuel temperature aided by the connected KORSAR/GP code is described. A three-dimensional model of the neutron kinetics and a realistic model of the main regulators are used. Calculations of the reactivity coefficients for a regime with unloading of the turbogenerator and the regime of primary regulation of the power system frequency are studied as test problems. A physical analysis of the results is performed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Physics-informed Bayesian machine learning case study: Integral blade rotors

This paper provides a physics-informed Bayesian machine learning (PIBML) description and case study. The PIBML approach applies three physics-based models to establish the initial beliefs before testing to determine the probability of milling stability (or prior). These include: receptance coupling substructure analysis (RCSA) prediction for the tool tip frequency response functions; finite element software prediction of the mechanistic force model coefficients; and a spindle speed-dependent power law model for process damping. Testing was then performed to identify optimal stable machining conditions using an expected improvement in material removal rate criterion. The prior probability of stability was updated using the test results to determine the posterior probability of stability. The test results were compared to the parameter recommendations provided by the endmill manufacturer. A demonstration integral blade rotor was machined at the optimal stable machining conditions for 304 stainless steel and 6061-T6 aluminum. Finally, the disagreement between manufacturer recommendations and milling performance in both materials tested emphasizes the need for broad implementation of PIBML approaches to increase machining productivity and efficiency.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Determining the oxidation behavior of matrix graphite

This work presents the oxidation behavior of matrix graphite in air. Matrix graphite, graphite powder/flakes bonded by a small amount of non-graphitic carbon, surrounds coated fuel particles in order to form cylindrical fuel compacts (in prismatic core designs) or spheres (in pebble-bed reactor designs). This work focuses on oxidation tests conducted on two matrix graphite materials, one provided by Kairos Power and the other A3 matrix graphite. Some of the tests followed American Society for Testing and Materials (ASTM) oxidation testing standards using a vertical furnace system and others were performed in a thermogravimetric analyzer (TGA). It was determined that, at temperatures of 450 °C–700 °C, the oxidation rate of the Kairos matrix graphite follows the Arrhenius equation. In comparison with A3 matrix graphite, the Kairos matrix graphite shows better oxidation resistance at high temperatures (≥550 °C), but also a higher oxidation rate at low temperatures. Both the A3 matrix graphite and the Kairos matrix graphite materials may experience preferential oxidation of the partially graphitized binder. An oxygen penetration gradient was also observed when using the three characterization methods (i.e., optical microscope, x-ray tomography [XCT], and density profile by the lathe) enlisted in this research. In conclusion, the oxygen penetration depth increases with decreasing isothermal oxidation temperature, while the center of the oxidized samples (10% weight loss) remains almost untouched even at 500 °C.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

PERLE A ‘STEPPING STONE’ FOR THE NEXT GENERATION ERLS

PERLE (Powerful ERL for Experiments) is a novel Energy Recovery Linac (ERL) test facility, which has been designed to validate choices for a 50 GeV ERL foreseen in the design of the LHeC and the FCC-eh, and to later serve a set of dedicated nuclear and particle physics experiments. Its main thrust is to probe high current, continuous wave (CW), multi-pass operation with superconducting cavities at 802 MHz (and perhaps testing other frequencies of interest). With very high transient beam power (~10 MW), PERLE offers an opportunity for controllable study of every beam dynamic effect of interest in the next generation of ERL design and become a ?stepping stone? between present state-of-art 1 MW ERLs and future 100 MW scale applications. PERLE design features flexible momentum compaction lattice architecture for six vertically stacked return arcs and a high current, 7 MeV, photo-injector. With only one pair of four cavity cryomodules, 500 MeV beam energy can be reached in three re-circulation passes, with beam currents of about 20 mA. The beam is decelerated in three consecutive passes back to the injection energy. Work on the engineering design of PERLE has just begun.

Bogacz, S.↗