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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Compare Mechanistic Predictions for Doped UO 2 Mechanical Response and Other Properties with Empirical Models and Experimental Measurements

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program develops predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity, high resolution fuel performance tool at the engineering scale. As part of its development, additional modeling capabilities and improvements have been developed for relevant fuel forms. In this work, a fuel creep deformation model for Cr-doped fuel has been implemented into BISON, along with improvements to the empirical UO 2 fuel creep model based on experimental data and improvements to the radial power factor calculation for doped fuels. This work allows for more accurate simulation analyses for both UO 2 and doped-UO 2 fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

First Results of ELM Triggering With a Multichamber Lithium Granule Injector Into EAST Discharges

A critical challenge facing the basic long-pulse H-mode for ITER is to control edge-localized modes (ELMs). A new method using a multichamber lithium (Li) granule injector (LGI) for ELM triggering experiments has been developed in Experimental Advanced Superconducting Tokamak (EAST). First experimental results of the control of ELMs are obtained in EAST with a tungsten divertor. It is found that the injector has good capacities, i.e., allowing good flexibilities in granule size selection, injection rate, and injection velocity. In conclusion, LGI has successfully triggered ELMs during the H-mode. These results indicate the LGI would be a promising method to control ELMs in long-pulse steady-state tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Experimental Protocols for Studying Organic Non-aqueous Redox Flow Batteries

We report that Redox flow batteries (RFBs) are promising devices for grid-scale energy storage due to the decoupling of power and energy, which can be independently scaled by the electrode area and storage tank size, respectively. To date, only aqueous RFBs, such as the vanadium RFB, have been implemented commercially. Nevertheless, the limited energy densities and high-cost materials may preclude their wider market penetration. Organic non-aqueous redox-flow batteries (O-NRFBs), which utilize redox-active organic molecules (ROMs), have been offered as an attractive alternative. Many possible advantages include the use of earth-abundant elements (C, H, N, O, S, F), wherein the ROMs can be prepared from low-cost and sustainable materials. Additionally, a large variety of electroactive moieties are accessible as building blocks, providing a synthetic platform to tune the properties of ROMs through rational design. As a consequence, the development of novel ROMs has attracted researchers with diverse backgrounds, prompting remarkable innovations in the past decade. However, consistency in experimental protocols (e.g., electrochemical methods, cycling stability, experimental conditions) has not coincided with this uptick in research, leading to sometimes ambiguous and incomparable results. This is further convoluted by the complexity innate to battery development, such as cell design, detection, and characterization of reactions and active components. The O-NRFB application imposes stringent requirements on the physical or/and chemical processes involved in electrochemical cycling. Yet such considerations are often overlooked. Further, while quantum mechanical calculations provide a convenient tool for evaluating and selecting ROM candidates, this simulation is not always performed. Thus, in this Energy Focus, we detail a means to standardize experimental protocols for studies of O-NRFBs and suggest practices to facilitate fundamental understanding and development of ROMs.

25 ENERGY STORAGE↗
DOE OSTI2022

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.

Jiménez-Aparicio, Miguel (ORCID:000000016864461X)↗
DOE OSTI2024

Perovskite/Perovskite Tandem Photoelectrodes for Low-Cost Unassisted Photoelectrochemical Water Splitting

In this project, we aim to address the challenges of achieving efficient and cost-effective unassisted photoelectrochemical water splitting using perovskite/perovskite tandem photoelectrodes. We utilized the following unique approaches to advance our innovation. (1) We developed stable and efficient low-E g (1.2 – 1.4 eV) perovskites as the bottom electrodes. We demonstrated approaches to improve the photovoltaic performance and photothermal stability of low-E g Sn-Pb iodide perovskite solar cells. (2) We developed a low-temperature synthesis route to fabricate wide-E g (>1.8 eV) perovskite top electrodes. By combining theoretical and experimental investigation, we found methods to reduce the formation of defects and dislocations in the wide-E g mixed halide perovskites and suppress halide segregation. (3) We developed a robust metal oxide-based interconnecting layer to integrate two perovskite layers into tandem photoelectrodes. Our monolithically integrated tandem devices feature a high V OC of more than 2 V and a high J SC of more than 15 mA/cm 2 . We showed the new design of the tandem photoelectrodes that is critical to the stable operation of tandem photoelectrodes for unassisted PV/PEC water splitting. (4) We demonstrated a water-impermeable barrier of carbon paste/epoxy/metal foil composite, which can prevent photocorrosion and water ingress of perovskite active layers. This surface protection enabled the operation of perovskite photoelectrodes in water and significantly enhanced the long-term stability of our tandem devices. (5) We conducted standardized PEC characterization in collaboration with NREL and reported accurate determination of solar-to-hydrogen conversion efficiencies of perovskite/perovskite tandem photoelectrodes. At the end of the project, we demonstrated perovskite/perovskite tandem photoelectrodes with STH efficiencies of up to 18% and less than 20% efficiency loss after continuous operation for more than 500 hours in water. Our results demonstrate the potential to develop a low-cost, durable, and efficient water-splitting system that meets the DOE 2026 and 2031 cost targets for hydrogen production.

08 HYDROGEN↗
DOE OSTI2020

Computational Methods to Accelerate Development of Corrosion Resistant Coatings for Industrial Gas Turbines

Oxidation resistant overlay coatings protect the underlying superalloy component in industrial gas turbines from oxidation attack. Rate of depletion of the Al-rich β-phase in the bond coat governs the lifetime of these coatings. The applicability of a computational method in accelerating the development of corrosion resistant coatings and significantly reducing the extensive experimental effort to predict coating lifetimes and microstructural changes in three-coated Ni-based superalloys for real operational durations (20–40 kh) was undertaken in the present study. Scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and electron microprobe analysis (EPMA) were employed to characterize MCrAlY-coated superalloy substrates (1483, 247 and X4) after exposure at 900 °C in air + 10% H 2 O for up to 20,000 h. The model predicted the longest coating lifetime for the coating on X4 substrate. Precipitation of γ' in the coatings was correctly predicted for all three coating systems. Additionally, the model was able to predict the formation of topologically close packed (TCP)-phases in the investigated coating systems.

Pillai, Rishi R.↗
DOE OSTI2024

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗
DOE OSTI2018

Thermodynamic modeling of the La-Te system aided by first-principles calculations

A complete thermodynamic description of the La-Te binary system is developed by means of CALculation of PHAse Diagram (CALPHAD) method in combination with available experimental data in the literature and the present first-principles calculations based on density functional theory. The intermetallic phases with homogeneity ranges, La3-xTe4 and LaTe2-x, are modeled using a two-sublattice (La,Va)3(Te)4 model and a three-sublattice (La)1(Te)1(Te,Va)1 model based on their structure features, respectively. The intermetallic phases, LaTe and LaTe3, are treated as stoichiometric compounds. The thermodynamic properties of the intermetallic compounds and their corresponding end members at finite temperatures are predicted using first-principles quasi-harmonic approach. The associate solution model is used to describe the short-range ordering behavior of the liquid phase. The calculated phase diagram agrees well with the available phase equilibrium data in the literature.

Chemistry↗
DOE OSTI2025

Machine learning models for volumetric swelling in uranium nitride

Machine learning methods are applied to predict the volumetric swelling rate of the nuclear fuel uranium nitride (UN) over various temperatures, irradiation conditions, and power densities. Both kernel-based methods and symbolic regression models for UN swelling are developed and compared with multiple experimental datasets. We find that the UN pellet geometry and dimensions must be taken into account to accurately model swelling behavior. Strong agreement is observed between the developed machine learning models and the data. The predictive error generated by the machine learning models improves on empirical models taken from the literature. Sensitivity analysis is performed to determine which properties such as temperature, burnup, and power density, are most important in the swelling process. We find that machine learning can be used to quickly develop accurate swelling models for nuclear materials. In conclusion, the presented results illustrate the potential of machine learning to determine volumetric swelling in UN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

RF pulse shape control in the compact linear collider test facility

The Compact Linear Collider (CLIC) is a study for an electron–positron machine aiming at accelerating and colliding particles at the next energy frontier. The CLIC concept is based on the novel two-beam acceleration scheme, where a high-current low-energy drive beam generates RF in series of power extraction and transfer structures accelerating the low-current main beam. To compensate for the transient beam-loading and meet the energy spread specification requirements for the main linac, the RF pulse shape must be carefully optimized. This was recently modelled by varying the drive beam phase switch times in the sub-harmonic buncher so that, when combined, the drive beam modulation translates into the required voltage modulation of the accelerating pulse. In this paper, the control over the RF pulse shape with the phase switches, that is crucial for the success of the developed compensation model, is studied. The results on the experimental verification of this control method are presented and a good agreement with the numerical predictions is demonstrated. Implications for the CLIC beam-loading compensation model are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

On-line Inductively Coupled Plasma Mass Spectrometry Reveals Material Degradation Dynamics of Au and Cu Catalysts during Electrochemical CO 2 Reduction

A significant challenge in commercializing electrochemical CO 2 reduction (CO 2 R) is achieving catalyst durability. Here, in this study, online inductively coupled mass spectrometry (ICP–MS) was used to investigate catalyst degradation via nanoparticle detachment and/or dissolution into metal ions under CO 2 R operating conditions in 0.1 M KHCO 3 . We developed an experimental framework with ex situ characterization to validate the online ICP–MS method for in situ evaluation of degradation from metal foils. By varying the applied potential and microenvironment (CO 2 vs N 2 -saturated electrolyte), we gained insights into the degradation of Au and Cu foils under CO 2 R and hydrogen evolution reaction (HER) conditions. While both Au and Cu foils were observed to be stable to dissolution in these regimes, degradation via nanoparticle detachment from the foil surface at the femtogram scale was observed as a function of reaction conditions, providing new insights into material degradation mechanisms. When applying potential steps at −0.1 and −1.0 V vs the reversible hydrogen electrode (RHE), Au was found to degrade via nanoparticle detachment under CO 2 R operating conditions more than under HER conditions, while Cu was found to degrade via nanoparticle detachment in similar amounts during both reactions. Au lost ∼1.8× more mass and ∼7.5× more nanoparticles than Cu under CO 2 R operating conditions. This study demonstrates the use of online ICP–MS to gain insight into the degradation of Au and Cu, the importance of studying unconventional degradation mechanisms such as nanoparticle detachment, and that online ICP–MS can be further utilized to gain fundamental understanding of catalyst durability for a variety of reaction systems.

Yan, Katherine [Stanford Univ., CA (United States)↗
DOE OSTI2021

Tuning the electronic structure of Ag-Pd alloys to enhance performance for alkaline oxygen reduction

Alloying is a powerful tool that can improve the electrocatalytic performance and viability of diverse electrochemical renewable energy technologies. Herein, we enhance the activity of Pd-based electrocatalysts via Ag-Pd alloying while simultaneously lowering precious metal content in a broad-range compositional study focusing on highly comparable Ag-Pd thin films synthesized systematically via electron-beam physical vapor co-deposition. Cyclic voltammetry in 0.1 M KOH shows enhancements across a wide range of alloys; even slight alloying with Ag (e.g. Ag 0.1 Pd 0.9 ) leads to intrinsic activity enhancements up to 5-fold at 0.9 V vs. RHE compared to pure Pd. Based on density functional theory and x-ray absorption, we hypothesize that these enhancements arise mainly from ligand effects that optimize adsorbate–metal binding energies with enhanced Ag-Pd hybridization. This work shows the versatility of coupled experimental-theoretical methods in designing materials with specific and tunable properties and aids the development of highly active electrocatalysts with decreased precious-metal content.

25 ENERGY STORAGE↗
DOE OSTI2017

Suppression of Alfven Modes on the National Spherical Torus Experiment Upgrade with Outboard Beam Injection [Suppression of Alfven Modes on the NSTX-U with Outboard Beam Injection]

In this paper we present data from experiments on the National Spherical Torus Experiment Upgrade, where it is shown for the first time that small amounts of high pitch-angle beam ions can strongly suppress the counterpropagating global Alfven eigenmodes (GAE). GAE have been implicated in the redistribution of fast ions and modification of the electron power balance in previous experiments on NSTX. The ability to predict the stability of Alfven modes, and developing methods to control them, is important for fusion reactors like the International Tokamak Experimental Reactor, which are heated by a large population of nonthermal, super-Alfvenic ions consisting of fusion generated alpha's and beam ions injected for current profile control. We present a qualitative interpretation of these observations using an analytic model of the Doppler-shifted ion-cyclotron resonance drive responsible for GAE instability which has an important dependence on k(perpendicular to rho L). A quantitative analysis of this data with the HYM stability code predicts both the frequencies and instability of the GAE prior to, and suppression of the GAE after the injection of high pitch-angle beam ions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Empirical Evaluation of GPS Clock Accuracy for Isochronous Droop-based Inverters

Grid-forming inverters rely upon an internal reference to regulate the grid 's voltage and frequency. Without a reliable reference, issues such as loss of synchronism, frequency instability, and unequal power sharing can occur. One proposed internal phase reference for grid-forming inverters is generated by the controller's clock, but this is affected by nonidealities in the crystal oscillator leading to time drift in the phase reference. To improve the controller's clock accuracy, the Global Positioning System (GPS) can be used to calibrate the internal clock. Previously, GPS-based clock calibration was explored theoretically and various methods were developed for mitigating frequency/phase drift at the power system level. This paper experimentally validates the direct performance of GPS time-calibration at the controller level and justifies its use in maintaining an accurate phase reference for droop-based grid-forming inverters.

clock drift↗
DOE OSTI2017

Suppression of Alfvén modes on NSTX-U with outboard beam injection

In this paper we present data from experiments on NSTX-U where it is shown for the first time that small amounts of high pitch-angle beam ions can strongly suppress the counter-propagating Global Alfvén Eigenmodes (GAE). GAE have been implicated in the redistribution of fast ions and modification of the electron power balance in previous experiments on NSTX. The ability to predict the stability of Alfvén modes, and developing methods to control them, is important for fusion reactor like the International Tokamak Experimental Reactor (ITER) which are heated by a large population of non-thermal, super-Alfvénic ions consisting of fusion generated alphas and beam ions injected for current profile control. We present a qualitative interpretation of these observations using an analytic model of the Doppler-shifted ion-cyclotron resonance drive responsible for GAE instability which has an important dependence on k⊥ρL. A quantitative analysis of this data with the HYM stability code predicts both the frequencies and instability of the GAE prior to, and suppression of the GAE after the injection of high pitch-angle beam ions.

Energetic particles↗
DOE OSTI2022

The importance of phonon spectrum measurements for accurate prediction of thermal scattering laws [Slides]

Although approximate phonon spectra (e.g. Debye model) are sufficient to reproduce integral quantities (e.g. total INS cross section) in reasonable agreement with the measured data, more accurate phonon spectra are needed to achieve agreement with the differential data. SANS component is essential for reproducing the total scattering cross section; this is the case for nanodiamonds and other materials where SANS components are present (such as porous materials like nuclear graphite). A format proposal for SANS data in ENDF or GNDS is needed. Therefore, differential (e.g. phonon spectrum) and integral (e.g. total cross section) measurements are necessary in the process of creating an ENDF evaluation. We have successfully developed a method by which ENDF evaluations can be directly compared to the relevant experimentally measured quantities. INS experiments at SNS, ILL, ISIS, and, in the future, ESS, as well as total cross section measurements at the VESUVIO instrument at ISIS, are accessible through user programs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Empirical Evaluation of GPS Clock Accuracy for Isochronous Droop-Based Inverters: Preprint

Grid-forming inverters rely upon an internal reference to regulate the grid’s voltage and frequency. Without a reliable reference, issues such as loss of synchronism, frequency instability, and unequal power sharing can occur. One proposed internal phase reference for grid-forming inverters is generated by the controller’s clock, but this is affected by nonidealities in the crystal oscillator leading to time drift in the phase reference. To improve the controller’s clock accuracy, the Global Positioning System (GPS) can be used to calibrate the internal clock. Previously, GPS-based clock calibration was explored theoretically and various methods were developed for mitigating frequency/phase drift at the power system level. This paper experimentally validates the direct performance of GPS time-calibration at the controller level and justifies its use in maintaining an accurate phase reference for droop-based grid-forming inverters.

clock drift↗
DOE OSTI2016

Application of Jacobian-free Newton–Krylov method in implicitly solving two-fluid six-equation two-phase flow problems: Implementation, validation and benchmark

This work represents a first-of-its-kind successful application to employ advanced numerical methods in solving realistic two-phase flow problems with two-fluid six-equation two-phase flow model. These advanced numerical methods include high-resolution spatial discretization scheme with staggered grids (high-order) fully implicit time integration schemes, and Jacobian-free Newton–Krylov (JFNK) method as the nonlinear solver. The computer code developed in this work has been extensively validated with existing experimental flow boiling data in vertical pipes and rod bundles, which cover wide ranges of experimental conditions, such as pressure, inlet mass flux, wall heat flux and exit void fraction. Additional code-to-code benchmark with the RELAP5-3D code further verifies the correct code implementation. The combined methods employed in this work exhibit strong robustness in solving two-phase flow problems even when phase appearance (boiling) and realistic discrete flow regimes are considered. Transitional flow regimes used in existing system analysis codes, normally introduced to overcome numerical difficulty, were completely removed in this work. As a result, this in turn provides the possibility to utilize more sophisticated flow regime maps in the future to further improve simulation accuracy.

42 ENGINEERING↗