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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

In-Pile Instrumentation (I2) (2018 Report)

Energy demand is growing exponentially, renewing interest in nuclear technology as a reliable, carbon-free energy source. In alignment with the U.S. Department of Energy (DOE), Idaho National Laboratory’s (INL’s) primary mission is to discover, demonstrate and secure innovative nuclear energy solutions. The capability to monitor the conditions inside nuclear reactors core is considered essential to this development process. To enable such capability, the InPile Instrumentation (I2) program was conceived in 2017 as an additional element to DOE Crosscutting Technology Development activities under the Nuclear Energy Enabling Technology (NEET) program. This document reports on the first year of implementation of research activities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Sigma Division Capability Strategy

Sigma Division maintains a unique manufacturing science capability at Los Alamos National Laboratory that has made substantial contributions to weapons component process development for more than 70 years. This mission requires the ability to handle a range of radiological and hazardous materials, work with a variety of metallic and non-metallic components, and process materials systems with elements spanning hydrogen to uranium. Today, Sigma serves as a national resource for uranium research and development, provides hardware for experimental campaigns, supports production by demonstrating modern fabrication technologies, and conducts manufacturing science research primarily for customers across the nuclear weapons complex, including the Department of Energy, National Nuclear Security Administration, and Office of Defense Programs.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Performance Criteria for Capture and/or Immobilization Technologies (Revision 1)

The capture and subsequent immobilization of regulated volatile radionuclides from the off-gas streams of a used nuclear fuel (UNF) reprocessing facility has been a topic of substantial research interest for the US Department of Energy and its international counterparts. Removal of specific radionuclides from the plant effluent streams before discharge to the environment is required to meet regulations set forth by the US Environmental Protection Agency. Upon removal, the radionuclides, as well as associated sorbents that cannot be regenerated in a cost-effective manner, are destined for conversion to a waste form. Research in separation and capture methodologies has included a wide range of technology types, and studies of waste forms are correspondingly diverse. In considering the future development and implementation of both sorbents and waste forms, it is necessary to identify benchmark measures of performance to objectively evaluate each sorbent system or waste form. Sets of performance criteria and associated metrics have been developed for sorbent and waste form evaluation. These criteria address physical, radiological, and chemical characteristics, technical practicality, technical maturity, cost, and, for sorbents, system performance. The criteria and metrics appear to be robust and should be applicable despite the eventual waste classification (as either high- or low-level waste). They are flexible enough to address both aqueous reprocessing and electrochemical reprocessing of UNF. These criteria sets can serve as tools to evaluate performance at multiple stages within the development process, and in this revision (Revision 1) they have been used to assess technologies relating to krypton/xenon separations and iodine capture from off-gas streams arising from UNF reprocessing. Assessment of krypton/xenon separations using engineered forms of two zeolite minerals (silver mordenite and hydrogen mordenite in a polyacrylonitrile-based binder [AgZ-PAN/HZ-PAN]) found that the zeolite-based separation is relatively advanced in its development, but several key issues require resolution. First, desorption processes for both krypton and xenon require refinement to provide an understanding of the product purity that can be achieved. Second, adsorption rate data is needed in order to calculate the bed depth required for effective separation. Finally, it is strongly recommended that a technical review of krypton/xenon separation by AgZ-PAN/HZ-PAN be performed to synergize available data and assess the cost savings and operational benefits that may be realized from implementation of this technology. Assessment of metal organic frameworks (MOFs) for their use in the separation of krypton/xenon found that the ideal separation would be performed using a single-column system with a MOF selective for krypton over xenon. A robust research effort should work to identify a krypton-selective MOF designed to operate at temperatures of approximately 0°C or higher, which could be preferred over cryogenic krypton/xenon capture for used fuel reprocessing off-gas streams. In the case of the CaSDB-MOF (the most well-understood xenon sorbent to date), two issues are judged of high importance. First, xenon breakthrough capacity for the CaSDB-MOF in prototypical conditions should be determined. Preliminary research indicates that breakthrough may be near immediate, presenting a substantial obstacle in separative system design. Second, development of desorption methodology should be performed to determine regeneration time, energy requirements, and the product stream composition. Silver-based sorbents (AgZ and AgAero) for use in iodine capture from the dissolver off-gas were evaluated against the established criteria. These sorbents are significantly better understood for this application as a result of research efforts over the past decade. The potential implementation of AgAero at a large scale is hindered by its physical degradation by components of the dissolver off-gas stream. Less is known about the adsorption of iodine by these sorbents from other off-gas streams in the plant. Initial experimental efforts have been closely coordinated in an effort to understand organic iodine (such as would be found in the vessel off-gas) adsorption by AgZ and AgAero. Future work should expand this experimental program, and analysis of other reprocessing facility off-gas streams such as the vitrification off-gas stream should be conducted to better understand other potential applications for iodine sorbents. A review of iodine waste form development shows that this area is diverse and that multiple promising waste forms have been identified for the immobilization of radioactive iodine. Efforts related to the direct conversion of iodine sorbents (including AgZ and AgAero) should be continued because of the advantages of direct conversion in a waste management strategy and other sorbents should continue to be advanced as merited.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

SRF Cavity Emulator for PIP-II LLRF Lab and Field Testing

There are many stages in the LLRF and RF system development process for any new accelerator that can take advantage of hardware emulation of the high-power RF system and RF cavities. LLRF development, bench testing, control system development and testing of installed systems must happen well before SRF cavities are available for test. The PIP-II Linac has three frequencies of SRF cavities, 162.5 MHz, 325 MHz and 650 MHz and a simple analog emulator design has been chosen that can meet the cavity bandwidth requirements, provide tuning errors to emulate Lorentz force detuning and microphonics for all cavity types. This emulator design utilizes a quartz crystal with a bandwidth of 65Hz at an IF of ~ 4 MHz, providing a Q of ~ 1.3 x 10^7 at 650MHz. This paper will discuss the design and test results of this emulator.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Development of Surface Treatment Solutions for Stamping Tools Fabricated via Additive Manufacturing

Oak Ridge National Laboratory (ORNL) and H.E.F. USA, Inc. (HEF) partnered to develop wear resistant surface treatment of additive manufactured steels for stamping die applications under CRADA agreement NFE-19-07909. This project aimed at evaluating the ARCOR® process, developed by HEF, to improve the surface behavior of 410SS (stainless steel), 410NiMo SS, 630 SS, and Maraging 250 steel coupons and demo components, fabricated via wire arc additive manufacturing (WAAM), with and without post print heat treatment. The peak hardness achieved was ~1000 HV and above (Up to 1300 HV) for all materials under proper processing parameters, and far exceeded the target hardness of 746 HV (60 HRC). Finally, stamping tools were printed and nitrocarburized with the optimum parameters, and then went through 500 fabrication cycles. Characterization of the used 17-4PH stamping tool discovered no crack or delamination in the nitrocarburized layer and the interface between the nitrocarburized layer and substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Representation of Modes of Variability in Six U.S. Climate Models

We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Highly selective Si 3 N 4 /SiO 2 etching using an NF 3 /N 2 /O 2 /H 2 remote plasma. II. Surface reaction mechanism

Developing processes for highly selective etching of silicon nitride (Si 3 N 4 ) with respect to silicon dioxide (SiO 2 ) is a major priority for semiconductor fabrication processing. In this paper and in Paper I [Volynets et al., J. Vac. Sci. Technol. A 38, 023007 (2020)], mechanisms are discussed for highly selective Si3N4 etching in a remote plasma based on experimental and theoretical investigations. The Si 3 N 4 /SiO 2 etch selectivity of up to 380 was experimentally produced using a remote plasma sustained in NF 3 /N 2 /O 2 /H 2 mixtures. A selectivity strongly depends on the flow rate of H 2 , an effect attributed to the formation of HF molecules in vibrationally excited states that accelerate etching reactions. Based on experimental measurements and zero-dimensional plasma simulations, an analytical etching model was developed for etch rates as a function of process parameters. Reaction rates and sticking coefficients were provided by quantum chemistry models and also fitted to the experimental results. Etch rates from the analytical model show good agreement with the experimental results and demonstrate why certain etchants accelerate or inhibit the etch process. In particular, the modeling shows the important role of HF molecules in the first vibrationally excited state [HF( v = 1)] in achieving high Si 3 N 4 /SiO 2 selectivity.

42 ENGINEERING↗
DOE OSTI2022

Effect of nitriding on mechanical and microstructural properties of Direct Metal Laser Sintered 17-4PH stainless steel

In this work, the effect of the nitriding process on microstructure and mechanical properties of additively manufactured (AM) 17-4PH stainless steel is investigated. The nitriding was performed at 530 °C, 560 °C, and 580 °C for 2 h. The nitriding process improves the hardness and surface roughness of the AM 17-4PH steel. Detailed microstructural characterizations of both as-built and nitride samples are performed using an optical microscope, scanning electron microscope (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction technique. It reveals that the nitride layer thickness increases with nitriding temperature. A distinct transition layer between the substrate and nitride layer is observed in the 560 °C and 580 °C nitride samples. The nitriding process develops almost equiaxed grain microstructure with new secondary phase precipitates, whereas in the as-built material, the grains are primarily columnar along the AM process build direction. Specifically, the nitriding process introduces γ-Fe4N, ε-Fe3N, CrN, and Ni3N precipitates. The increase in Ni- and Cu-rich precipitates with the nitriding temperature explains the observed improvement in the hardness and surface roughness. Furthermore, the nitriding process does not alter the substrate's initial weak crystallographic texture.

17-4PH steel↗
DOE OSTI2020

Land Use Considerations for Large-Scale Solar

Energy development is the largest driver of land-use and land-cover change in the United States. Today, one of the leading forms of this new development is large-scale solar photovoltaic (PV) plants. This new issue brief is intended to educate local governments and community stakeholders interested in supporting solar development. Topics covered include: 1. Key challenges posed by storm water runoff and mitigation measures that can be incorporated into project development processes. 2. Vegetation Management concepts and their tactical application, including an Integrated Vegetation Management (IVM) strategy. Together, these strategies can help communities and local governments develop policies and guidelines on large-scale solar that can realize both environmental and economic benefits.

14 SOLAR ENERGY↗
DOE OSTI2020

Land Use Considerations For Large-Scale Solar

Energy development is the largest driver of land-use and land-cover change in the United States. Today, one of the leading forms of this new development is large-scale solar photovoltaic (PV) plants. This new issue brief is intended to educate local governments and community stakeholders interested in supporting solar development. Topics covered include: 1. Key challenges posed by storm water runoff and mitigation measures that can be incorporated into project development processes. 2. Vegetation Management concepts and their tactical application, including an Integrated Vegetation Management (IVM) strategy. Together, these strategies can help communities and local governments develop policies and guidelines on large-scale solar that can realize both environmental and economic benefits.

14 SOLAR ENERGY↗
DOE OSTI2023

Reducing warpage in a hybrid large-scale additive manufacturing and compression molding process

In recent years, a hybrid manufacturing process, developed by combining extrusion-based large-scale additive manufacturing (AM) and compression molding (CM) techniques, has shown promising outcomes for producing structurally functional parts. The process can be used with both short fiber-reinforced composites and neat polymers and hence, even multi-material parts can be manufactured easily. This process offers the advantages of structural enhancement by having a desired fiber orientation using a large-scale AM process, as well as rapid manufacturing capability using a CM process. In the large-scale AM process, the alignment of fibers in the deposition direction enables significant improvement in the mechanical properties of the manufactured parts. However, the anisotropy resulting from the directional arrangement of fibers also introduces challenges related to warpage in the produced parts. This study aims to identify the causes of warpage and propose strategies to mitigate it. The research involves the use of preforms manufactured through the large-scale AM, which are then combined with the neat resin for CM manufacturing. A finite element-based numerical simulation model is developed, employing a sequentially coupled thermomechanical approach. Through a parametric study using the simulation models, optimization of printing direction and preform geometry is performed to minimize warpage. This contributes to the advancement and wider adoption of AM/CM hybrid manufacturing to produce structurally functional parts.

Jo, Eonyeon↗
DOE OSTI2024

Assessing Historical Extreme Weather Event Impacts

Understanding how past extreme weather events have affected a site is an integral part of site-level resilience planning. Energy and water resilience planning has been a key priority for the federal government for many years and agencies look to develop processes for identifying and addressing critical resilience gaps at their facilities and across their sites. The purpose of this information paper is to help inform how organizations could begin structuring a comprehensive process for recording the impacts of extreme weather events in order to facilitate climate vulnerability assessments, and thus, resilience planning. The paper highlights current limitations for developing event history assessments and suggests a framework for more consistently capturing key data points.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

High Throughput Source-less Plasma Deposition of Structured Silicon Anodes for Lithium-Ion Batteries

Amprius developed a manufacturing solution for silicon nanowire anode that relies on an inexpensive, high throughput, and high gas precursor utilization plasma deposition method that uses the anode foils as electrodes for plasma generation. The capacitively couple plasma (CCP) method is used in semiconductor and photovoltaic industry and Amprius modified existing high throughput equipment to use anode foils and to deposit amorphous silicon. The equipment was installed ahead of the program at Amprius site. The rest of the tasks included foil handling and process development. The equipment passed site acceptance tests (SAT) and the process parameter mapping was completed, indicating that the target process window limits produce output materials at the rate and with yield and specifications that meet the manufacturing target criteria. Amprius has hired supporting personnel to optimize processes and run the equipment. A parallel task verified the baseline performance of the silicon anode material, to be used as reference for the new manufacturing method.

25 ENERGY STORAGE↗
DOE OSTI2022

Thermal Neutron Scattering Research at ORNL – ENDF File Validation [Slides]

ENDF File Validation is a process developed to simulate VISION experiments. This method showed significant differences in inelastic spectra compared to experimental measurements. Differential data should be incorporated into thermal neutron scattering evaluation process to ensure accurate TSL files. The Polyethylene Discrepancy Issue has been found and corrected. The resulting ENDF manual change has been submitted and is currently under review.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Real Time Predictive and Adaptive Hybrid Powertrain Control Development via Neuroevolution

The real-time application of powertrain-based predictive energy management (PrEM) brings the prospect of additional energy savings for hybrid powertrains. Torque split optimal control methodologies have been a focus in the automotive industry and academia for many years. Their real-time application in modern vehicles is, however, still lagging behind. While conventional exact and non-exact optimal control techniques such as Dynamic Programming and Model Predictive Control have been demonstrated, they suffer from the curse of dimensionality and quickly display limitations with high system complexity and highly stochastic environment operation. This paper demonstrates that Neuroevolution associated drive cycle classification algorithms can infer optimal control strategies for any system complexity and environment, hence streamlining and speeding up the control development process. Neuroevolution also circumvents the integration of low fidelity online plant models, further avoiding prohibitive embedded computing requirements and fidelity loss. This brings the prospect of optimal control to complex multi-physics system applications. The methodology presented here covers the development of the drive cycles used to train and validate the neurocontrollers and classifiers, as well as the application of the Neuroevolution process.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Cooperative Research and Development Agreement between National Energy Technology Laboratory and Princeton University (Abstract)

The National Energy Technology Laboratory (NETL) and Princeton University will collaborate in the development of microwave-plasma technology to convert methane into hydrogen and valuable solid carbon materials. The effort will combine NETL’s vast resources for microwave-enhanced process development, characterization, and design with Princeton University’s extensive expertise in the study of non-equilibrium plasmas employing supersonic nozzles. Lab-scale experiments will be conducted for different conditions to convert and compare their respective performance in hydrogen production. Computational modeling will be performed to verify results from experimental studies conducted in both labs.

08 HYDROGEN↗
DOE OSTI2025

Event Classifications on DNE2 Main Experiment Data using a Convolutional Neural Network Ensemble

The Dynamic Networks (DN) Experiment for FY24 (DNE2) is an experiment within DN with the goal of quantitatively evaluating the effectiveness of solutions developed so far by various researchers under the Low Yield Nuclear Monitoring (LYNM) program using a shared set of metrics and datasets. A key component of this experiment is the mimicking of a signature processing pipeline, and comparing currently accepted and standard-use processing methods to more state-of-the-art processes developed under DN. In this work, we focus specifically on the Event Characterization (EC) Focus Area (FA) of the pipeline, where a seismic event’s magnitude, yield and class are identified. We use Deep Learning (DL) to classify the type of events being processed as either earthquakes (EQs) or explosions (EXs) for three iterations of experiment datasets. The model is noticeably more confident and accurate in classifying explosions than earthquakes, reflecting a known shortcoming of the model, that being of a bias towards predicting explosions over earthquakes in the west coast due to training data biases.

97 MATHEMATICS AND COMPUTING↗