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DOE OSTI2016

Anisotropic phase segregation and migration of Pt in nanocrystals en route to nanoframe catalysts

Compositional heterogeneity in shaped, bimetallic nanocrystals offers additional variables to manoeuvre the functionality of the nanocrystal. However, understanding how to manipulate anisotropic elemental distributions in a nanocrystal is a great challenge in reaching higher tiers of nanocatalyst design. In this study, we present the evolutionary trajectory of phase segregation in Pt-Ni rhombic dodecahedra. The anisotropic growth of a Pt-rich phase along the $\langle$111$\rangle$ and $\langle$200$\rangle$ directions at the initial growth stage results in Pt segregation to the 14 axes of a rhombic dodecahedron, forming a highly branched, Pt-rich tetradecapod structure embedded in a Ni-rich shell. With longer growth time, the Pt-rich phase selectively migrates outwards through the 14 axes to the 24 edges such that the rhombic dodecahedron becomes a Pt-rich frame enclosing a Ni-rich interior phase. The revealed anisotropic phase segregation and migration mechanism offers a radically different approach to fabrication of nanocatalysts with desired compositional distributions and performance.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Defined PEG smears as an alternative approach to enhance the search for crystallization conditions and crystal-quality improvement in reduced screens

An alternative strategy for PEG sampling is suggested through the use of four newly defined PEG smears to enhance chemical space in reduced screens with a benefit towards protein crystallization. The quest for an optimal limited set of effective crystallization conditions remains a challenge in macromolecular crystallography, an issue that is complicated by the large number of chemicals which have been deemed to be suitable for promoting crystal growth. The lack of rational approaches towards the selection of successful chemical space and representative combinations has led to significant overlapping conditions, which are currently present in a multitude of commercially available crystallization screens. Here, an alternative approach to the sampling of widely used PEG precipitants is suggested through the use of PEG smears, which are mixtures of different PEGs with a requirement of either neutral or cooperatively positive effects of each component on crystal growth. Four newly defined smears were classified by molecular-weight groups and enabled the preservation of specific properties related to different polymer sizes. These smears not only allowed a wide coverage of properties of these polymers, but also reduced PEG variables, enabling greater sampling of other parameters such as buffers and additives. The efficiency of the smear-based screens was evaluated on more than 220 diverse recombinant human proteins, which overall revealed a good initial crystallization success rate of nearly 50%. In addition, in several cases successful crystallizations were only obtained using PEG smears, while various commercial screens failed to yield crystals. The defined smears therefore offer an alternative approach towards PEG sampling, which will benefit the design of crystallization screens sampling a wide chemical space of this key precipitant.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Foundational Principles for Large-Scale Inference: Illustrations Through Correlation Mining

When can reliable inference be drawn in the ‘‘Big Data’’ context? This article presents a framework for answering this fundamental question in the context of correlation mining, with implications for general large-scale inference. In large-scale data applications like genomics, connectomics, and eco-informatics, the data set is often variable rich but sample starved: a regime where the number n of acquired samples (statistical replicates) is far fewer than the number p of observed variables (genes, neurons, voxels, or chemical constituents). Much of recent work has focused on understanding the computational complexity of proposed methods for ‘‘Big Data.’’ Sample complexity, however, has received relatively less attention, especially in the setting when the sample size n is fixed, and the dimension p grows without bound. To address this gap, we develop a unified statistical framework that explicitly quantifies the sample complexity of various inferential tasks. Sampling regimes can be divided into several categories: 1) the classical asymptotic regime where the variable dimension is fixed and the sample size goes to infinity; 2) the mixed asymptotic regime where both variable dimension and sample size go to infinity at comparable rates; and 3) the purely high-dimensional asymptotic regime where the variable dimension goes to infinity and the sample size is fixed. Each regime has its niche but only the latter regime applies to exa-scale data dimension. We illustrate this high-dimensional framework for the problem of correlation mining, where it is the matrix of pairwise and partial correlations among the variables that are of interest. Correlation mining arises in numerous applications and subsumes the regression context as a special case. We demonstrate various regimes of correlation mining based on the unifying perspective of high-dimensional learning rates and sample complexity for different structured covariance models and different inference tasks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Feature Based Qualification of 17-4PH Stainless Steel to Evaluate Location-Specific Variability in Wire Arc Additive Manufacturing

Qualifying large-scale metal additive manufacturing (M-AM) technologies such as wire arc additive manufacturing (WAAM) can be challenging. This is especially significant in precipitation hardened martensitic stainless steels like SS 17-4PH, where thermal histories induce location-specific microstructural variability and property anisotropy. The Department of Defense (DOD) and the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center (GVSC) Ground Vehicle Materials Engineering (GVME) aim to build robust and qualified large-scale M-AM workflows that could reduce the time and cost through quick and informed evaluation, testing, and development of feedstock, processes, and parts. The report presents the findings from the collaborative efforts between Oak Ridge National Laboratory (ORNL) and the U.S. Army GVSC GVME. The aim of this project was to develop a geometric feature-based qualification framework for WAAM of SS 17-4PH components. This report outlines selection methodology of representative build geometries, optimization of WAAM process parameters, in-situ monitoring, microstructure-property evaluation, thermal simulations, as well as data visualization techniques incorporated in this project. The results from this project demonstrate a clear understanding of thermal history dependent phase evolution and consequent location-specific property variations in WAAM of SS 17-4PH. These results in conjunction with the data-driven methodologies used in this project are expected to reduce qualification timelines, improve predictability, and accelerate the development of reliable feature-based qualification strategies for part production via large-scale M-AM technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Quantifying Rates of Erosion Using Historical Aerial Photos - 19478

Erosion can play an important role in the fate and transport of waste at sites where disposal of long-lived waste is anticipated. The statistical characterization of key processes related to erosion is essential to the understanding of site stability through time. In this work multi-temporal historical aerial images are analyzed in conjunction with orthophotography and Lidar data to develop probability distributions for variables representing important erosion processes. Scans of photographic negatives were obtained for multiple photographs and several negatives were scanned with a calibrated photogrammetric scanner by Geomni (formerly Blue Skies Consulting) in Belen, New Mexico. Other negatives were provided by USDA or scanned on a high-resolution, large format media scanner in the United States National Archives Cartographic Research Room, College Park, Maryland (1939). An additional set of aerial photographs was obtained from the USGS EROS Data Center web site. For other years, photographic prints were available for aerial photography. Several prints were scanned with a large-format media scanner at 1200 dpi. Ground control points for selected digital images used in the stereoscopic analyses were identified in ArcMap. Ground control points were collected by matching features which could be identified in the aerial photography as well as the orthophotography or shaded relief imagery from the Lidar dataset. Such features included fence line intersections, road intersections, railroad bridges, and structures, depending on the age of the photography. Many old fence lines and abandoned roads remained visible in the shaded relief imagery while they were completely obscured by tree canopy in modern photography. Ground control elevations were sampled from the Lidar-based DEM or directly from point clouds. The image coordinates and matching three-dimensional projected coordinates of the ground control points were exported to IDL where parameters for a three-dimensional direct linear transformation (DLT) were obtained. Built-in singular value decomposition routines were used to solve an overdetermined set of equations for the eleven parameters of the DLT for a particular historical photograph. A solution to the DLT parameters was obtained for each historical aerial photograph in which features of interest were identified using the stereoscope. Ultimately, this process resulted in the identification of locations for features like gully heads using both the Lidar dataset and projection of the estimated location from the historical aerial photo under consideration back to the Lidar dataset. The distance between the estimate of the location from the historical image and that of the Lidar dataset was the estimated distance the feature has moved. This distance was then divided by the number of years between the Lidar dataset and the year of the historical aerial image of interest to get a rate of movement through time. This was done for several dozen points on each historical aerial image. There was inevitable uncertainty associated with the estimation of points from the historical aerial imagery. This includes estimation of changes in locations of features like gully heads through time. In this work a method to estimate the uncertainty associated with measurements of locations of features using the stereoscopic analysis is developed and applied. For features with locations in space that do not change (e.g., road intersections, etc.) the difference in measurements of locations from the Lidar dataset and that of the estimate from the historical aerial image provides an observation of the measurement error. These points used to estimate the measurement error are referred to as control points. For each of the historical aerial images, a different measurement error distribution is estimated using control points. These measurement errors are combined with the estimated distances from the stereoscopic analyses to produce distributions of gully retreat rates and hillslope erosion rates used along with output from Erosion Working Group (EWG) Landscape Evolution Models (LEMs) to provide statistical probability distributions for input into the PPA Model. Specifically, gully head retreat rate and gully widening rate were characterized using statistical probability distributions. The central limit theorem was then applied to develop rates that represent long-term averages that are used to inform a PPA Model built in GoldSim. The importance of these rates with respect to characterization of future risk can then assessed using sensitivity analyses. This provides an approach to determine if subsequent reduction of the uncertainty associated with the probability distributions of erosion rates will correspond to meaningful reduction in the estimation of future risk from the site. Ultimately this is a general method that utilizes historical aerial imagery to estimate rates of erosion with uncertainty. This information can be used to inform PPA models to project future risks from a given site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

A Class of Sparse Johnson–Lindenstrauss Transforms and Analysis of their Extreme Singular Values

The Johnson–Lindenstrauss (JL) lemma is a powerful tool for dimensionality reduction in modern algorithm design. The lemma states that any set of high-dimensional points in a Euclidean space can be projected into lower dimensions while approximately preserving pairwise Euclidean distances. Random matrices satisfying this lemma are called JL transforms (JLTs). Inspired by existing $s$-hashing JLTs with exactly $s$ nonzero elements on each column, the present work introduces an ensemble of sparse matrices encompassing so-called $s$-hashing-like matrices whose expected number of nonzero elements on each column is $s$. The independence of the sub-Gaussian entries of these matrices and the knowledge of their exact distribution play an important role in their analyses. Using properties of independent sub-Gaussian random variables, these matrices are demonstrated to be JLTs, and their smallest nontrivial singular values and largest singular values are estimated nonasymptotically using a technique from geometric functional analysis. As the dimensions of the matrix grow to infinity, these singular values are proved to converge almost surely to fixed quantities (by using the universal Bai–Yin law) and in distribution to the Gaussian orthogonal ensemble Tracy–Widom law after proper rescalings. Understanding the behaviors of extreme singular values is important in general because they are often used to define a measure of stability of matrix algorithms. For example, JLTs were recently used in derivative-free optimization algorithmic frameworks to select random subspaces in which are constructed random models or poll directions to achieve scalability, and hence estimating their smallest singular value in particular helps determine the dimension of these subspaces.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Experimental Evaluation of Interference in 2.4 GHz Wireless Network

To attain automation across different applications, nuclear power plants are beginning to leverage advancements in wireless communication technologies. A “one-size-fits-all” solution cannot be applied since wireless technologies are selected according to application needs, quality of service requirements, and economic restrictions. To balance the trade-off between technical and economic requirements, a multi-band heterogeneous wireless network architecture is needed. Numerous wireless technologies including Wi-Fi, Zigbee, and Bluetooth share the 2.4 GHz industrial, scientific, and medical band. However, due to different channel access mechanisms and transmit power levels, and very importantly, uncoordinated use, coexistence of these devices in the same vicinity can cause interference and degradation in performance. This report provides the technical basis for understanding the coexistence of these wireless technologies through an experimental evaluation of their performance. This report investigates interactions encompassing variables such as transmission power level, distance between the devices, data rates, and the utilization of co-channel or adjacent channels. The results show that the operation of both Zigbee and Bluetooth is severely compromised when coexisting with Wi-Fi within the same frequency spectrum. On the other hand, the performance of Bluetooth is not impaired by Zigbee and vice versa unless there exists any external interference from Wi-Fi.

2.4 GHz↗

DOE OSTI2025

Contributions of vegetation heterogeneity within tower footprint to CO 2 flux estimations through graph neural network modeling

Net ecosystem exchange of CO 2 (Fc) measured directly by eddy covariance towers is based on various assumptions, including large, flat and homogenous land cover type. In reality, often a tower site is not large enough for flux measurements, and landscapes consist of patches of different land cover types within the flux footprint. In addition, some portions of fluxes are contributed by different cover types when a footprint exceeds the size of the target ecosystem. The contributions of non-dominant patches to Fc are often ignored. Here, in this study, we propose a novel integrated modeling framework that combines random forest (RF) and XGBoost with a residual correction module based on a deep graph convolutional network (DeeperGCN) to simulate Fc for seven flux measurement sites in southwest Michigan. High-resolution remote sensing vegetation indices, soil properties, meteorological variables, and footprint-weighted spatial features were used as model inputs at three spatial resolutions (10 m, 20 m, 30 m), and their importance in predicting Fc with DeeperGCN was assessed. We found that residual correction using DeeperGCN significantly improved prediction accuracy, with the R 2 increasing from 0.9098 to 0.9479 for RF and from 0.9235 to 0.9433 for XGBoost. At site level, the maximum improvement in R 2 reached 0.1617. Paired t-tests confirmed that these improvements were statistically significant (p < 0.05). Among all predictors, leaf area index and incoming shortwave radiation emerged as the dominant drivers of spatial residual variation, followed by precipitation, relative humidity, and selected vegetation indices. The 20 m resolution yielded the best balance between model performance and computational efficiency. In conclusion, our modeling framework effectively captures both spatial heterogeneity and nonlinear interactions, offering a robust solution for spatially explicit flux modeling in structurally diverse ecosystems beyond the study sites.

footprint model↗

DOE OSTI2018

Impact of community engagement on public acceptance towards waste-to-energy incineration projects: Empirical evidence from China

Highlights: • How community engagement affects public acceptance towards WTE projects is studied. • Public acceptance is affected by demographic variables. • Public trust positively affects public acceptance both directly and indirectly. • Community engagement can effectively enhance public trust in WTE authorities. - Abstract: As one of the most popular methods for the treatment of municipal solid waste (MSW), waste-to-energy (WTE) incineration offers effective solutions to deal with the MSW surge and globe energy issues. Nevertheless, the construction of WTE facilities faces considerable and strong opposition from local communities due to the perceived potential risks. The present study aims to understand whether, and how, community engagement improves local residents’ public acceptance towards waste-to-energy (WTE) incineration facilities using a questionnaire survey conducted with nearby residents of two selected WTE incineration plants located in Zhejiang province, China. The results of data analysis using Structural Equation Modeling (SEM) reveal that firstly, a lower level of public acceptance exists among local residents of over the age of 35, of lower education levels, living within 3 km from the WTE Plant and from WTE incineration Plants which are under construction. Secondly, the public trust of local government and other authorities was positively associated with the public acceptance of the WTE incineration project, both directly and indirectly based on perceived risk. Thirdly, community engagement can effectively enhance public trust in local government and other authorities related to the WTE incineration project. The findings contribute to the literature on MSW treatment policy-making and potentially hazardous facility siting, by exploring the determinants of public acceptance towards WTE incineration projects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Design and Analysis of High Heat Flux Plasma-Facing Components for NSTX Upgrade

The National Spherical Tokamak Experiment (NSTX) upgrade (NSTX-U) requirements lead to enhanced heat loads on plasma-facing components (PFCs) especially in the divertor regions, where normal heat flux density can reach up to 8 MW/m 2 . For these high heat flux (HHF) regions, the PFCs were redesigned, to use castellations which relieved the thermal stresses associated with high incident heat flux. Another design feature of HHF PFCs is the absence of front face mounting holes which create localized areas of high temperature and thermal stress concentrations. Optimized shaping of the front face of the HHF PFCs eliminates regions where the front face is perpendicular to the heat flux direction during normal helicity operation and spreads the heat load. A unique mechanism was designed to connect PFC tiles to the NSTX-U center stack casing using locking features accessible from the low heat flux regions. Isotropic graphite was selected as the HHF PFC tile material. Initial tile design parameters were accessed using analytical expressions for pulsed heat flux loading. A working prototype of the locking mechanism was created during the initial stages of the design to prove the concept performance. This article presents an overview of the divertor HHF PFC design and the results of the thermal and structural analyses performed using ANSYS software. The results of the analyses cover normal operating conditions and disruptions which impose electromagnetic (EM) loads from eddy and halo currents. The 3-D, transient, nonlinear analyses took into account the temperature-dependent properties of the materials, friction interfaces between the parts, and variable electric properties of the parts and interfaces. The results confirm that the HHF PFC tiles remain within the allowable limits for the loads defined by the NSTX-U Recovery Project. In addition, tolerance stack up analyses were performed to ensure tile performance in the worst possible assembly configuration. Finally, the design process was completed successfully, and the NSTX HHF PFC tiles are currently in the production phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Development of Property Composition Models For RPP-WTP LAW Glasses (Final Report)

This report describes the development of property-composition models for low-activity waste (LAW) glasses for the River Protection Project Waste Treatment Plant (RPP-WTP) at the Hanford site. The RPP-WTP will separate Hanford tank wastes into LAW and high-level waste (HLW) streams and each stream will be vitrified separately. The development of LAW and HLW glass formulations for the RPP-WTP has been reported previously and is an ongoing activity. Acceptable formulations must meet a variety of processability, product quality, and waste loading requirements that are dictated either by the RPP-WTP contract or by the characteristics of the particular treatment processes that have been selected. These requirements amount to constraints on the acceptable ranges of certain glass properties. These properties are determined first and foremost by the composition of the glass or glass melt. Thus, while there is no direct way of controlling the glass properties of interest during production, there are simple and extremely effective methods of achieving the same result by instead controlling the glass composition. This basic principle is no different from that used to produce enormous volumes of commercial glass to meet exacting product specifications. An essential difference in waste vitrification, however, is that one of the raw materials (the waste itself) can be subject to considerable compositional uncertainty and variability. Thus, waste vitrification facilities and associated process control systems (of which, the operating envelope in glass formulation space is a key part) must, of course, be designed to be robust with respect to such variations. The determination of quantitative relationships between the glass properties that must be controlled and the glass composition can play an important role in the development of such facilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

Clustering Method and Representative Feeder Selection for the California Solar Initiative

The screening process for DG interconnection procedures needs to be improved in order to increase the PV deployment level on the distribution grid. A significant improvement in the current screening process could be achieved by finding a method to classify the feeders in a utility service territory and determine the sensitivity of particular groups of distribution feeders to the impacts of high PV deployment levels. This report describes the utility distribution feeder characteristics in California for a large dataset of 8,163 feeders and summarizes the California feeder population including the range of characteristics identified and most important to hosting capacity. The report describes the set of feeders that are identified for modeling and analysis as well as feeders identified for the control group. The report presents a method for separating a utility's distribution feeders into unique clusters using the k-means clustering algorithm. An approach for determining the feeder variables of interest for use in a clustering algorithm is also described. The report presents an approach for choosing the feeder variables to be utilized in the clustering process and a method is identified for determining the optimal number of representative clusters.

14 SOLAR ENERGY↗

DOE OSTI2018

A study of Ni/La-Al 2 O 3 catalysts: A competitive system for CO 2 methanation

Ni/La-γ-Al 2 O 3 samples containing 13.6 wt.% Ni and a variable amount of lanthana (0, 4, 14 and 37 wt.%) were prepared by incipient wetness impregnation, using silica-free γ-Al 2 O 3 support. The materials were characterized, as such or after reaction, with XRD, H 2 -TPR, IR, UV–vis-NIR, XPS and FE-SEM techniques. They were tested as catalysts for CO 2 methanation at atmospheric pressure at GHSV 55000 h –1 . The reaction is under kinetic control at T < 650–673 K, while the product mixture is under thermodynamic control above this temperature range. Lanthanum addition strongly increases the activity of Ni/γ-Al 2 O 3 for CO 2 methanation. Methane selectivity is increased to nearly 100% at low temperatures (T < 650 K). The CO 2 methanation reaction on La-doped Ni/γ-Al 2 O 3 occurs with similar activation energies (80 kJ/mol), and with slightly higher reaction order for hydrogen and lower reaction order for CO 2 than those observed for undoped Ni/γ-Al 2 O 3 . Lanthanum acts as a promoter because of the stronger basicity of the lanthana-alumina support allowing stronger adsorption of CO 2 as surface carbonates that can be act as “reactant reservoirs”. Finally, the Ni/La-alumina catalysts studied here are similarly effective as Ru/alumina catalysts for the selective CO 2 methanation at low temperature and atmospheric pressure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Intrinsic Kinetics of Polyethylene Terephthalate Pyrolysis via Micropyrolysis and Multivariate Chromatographic Analysis

This study provides an in-depth investigation of the primary decomposition of polyethylene terephthalate (PET) via pyrolysis, employing an experimental-analytic workflow that integrates design of experiments (DoE), micropyrolysis coupled with comprehensive two-dimensional gas chromatography (GC×GC), and multivariate data analysis to verify intrinsic kinetic conditions and elucidate evolving product distributions for mapping key reaction pathways. Peaks that could not be identified using commercial spectral libraries were assigned using Mass Frontier simulations, enabling the identification of divinyl terephthalate, ethyl vinyl terephthalate, and 2-(benzoyloxy)ethyl vinyl terephthalate. A polar×polar (non-orthogonal) column set tailored for the detection of carboxylic acids enhanced the quantification of benzoic acid, 4-vinylbenzoic acid, 4-ethylbenzoic acid, and methylbenzoic acid by up to 6-fold relative to an orthogonal column combination (non-polar×mid-polar). Moreover, pyrolysis variables were systematically evaluated using a Box- Behnken design (BBD), encompassing pyrolysis temperature (500−600 °C), sample weight (50−150 μg), and carrier gas flow rate (100−300 mL min −1 ). Among these, pyrolysis temperature was the only statistically significant factor influencing product yields, ranging from 58.78 to 84.26 wt %. In contrast, neither the sample weight nor the carrier gas flow rate had a significant effect on product yields within the evaluated experimental space. At 600 °C, the major pyrolysis products were benzoic acid (up to 20.20 ± 1.46 wt %) and CO 2 (up to 21.28 ± 1.46 wt %), which can be produced through decarboxylation reactions. These findings underscore the critical importance of selecting appropriate analytical columns for the accurate quantification of heteroatomcontaining products such as carboxylic acids, which may otherwise be underestimated or undetected due to their reactivity with the stationary phase of non-polar and mid-polar columns, as well as other GC components. They also highlight the importance of selecting pyrolysis conditions for investigating the primary decomposition of PET under an isothermal kinetically limited regime.

aromatic compounds↗

DOE OSTI2017

Taxonomic and functional shifts in the beech rhizosphere microbiome across a natural soil toposequence

It has been rarely questioned as to whether the enrichment of specific bacterial taxa found in the rhizosphere of a given plant species changes with different soil types under field conditions and under similar climatic conditions. Understanding tree microbiome interactions is essential because, in contrast to annual plants, tree species require decades to grow and strongly depend on the nutritive resources of the soil. In this context, we tested using a natural toposequence the hypothesis that beech trees select specific taxa and functions in their rhizosphere based on the soil conditions and their nutritive requirements. Our 16S rRNA gene pyrosequencing analyses revealed that the soil type determines the taxa colonizing the beech rhizosphere. A rhizosphere effect was observed in each soil type, but a stronger effect was observed in the nutrient-poor soils. Although the communities varied significantly across the toposequence, we identified a core beech rhizosphere microbiome. Functionally, GeoChip analyses showed a functional redundancy across the toposequence, with genes related to nutrient cycling and to the bacterial immune system being significantly enriched in the rhizosphere. Altogether, the data suggest that, regardless of the soil conditions, trees enrich variable bacterial communities to maintain the functions necessary for their nutrition.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

RELAP-7 Application and Enhancement for FLEX Strategies and ATF Behavior under Extended Loss of AC Power Conditions

This report summarizes the results of a three-year research project sponsored by the U.S. Department of Energy (DOE) Nuclear Energy University Program (NEUP) to enhance and apply the RELAP-7 code by adding and improving several important components (e.g., a mechanistic Reactor Core Isolation Cooling (RCIC) system model) for thermal hydraulic studies of LWRs under ELAP conditions and evaluating the time available for transition to portable FLEX equipment. The project team included University of Massachusetts–Lowell, The Ohio State University, Texas A&M University, Idaho National Laboratory and Oak Ridge National Laboratory. In the Fukushima accident, it was found that the RCIC system played a crucial role in delaying core meltdown by almost three days in Fukushima Daiichi Unit 2, because of self-regulated operation of the steam driven RCIC turbine-pump injection system. Steam flow in the convergent-divergent nozzles of the RCIC Terry turbine is two-phase non-equilibrium transonic flow with homogenous nucleation condensation. To more accurately predict the dynamic process and behavior of the transonic compressible steam flow, a one-dimensional transient two-phase analytical model is presented. A simplified four-fluid model was employed in the present work with the consideration of four separate fluid fields: vapor, liquid film, entrained droplets and condensed droplets. The mass, momentum and energy interactions between the fluids were considered and modeled. An extended seven-equation non-equilibrium critical flow model was developed to obtain the critical pressure and velocities of each phase at the nozzle throat. To predict the wetness in the divergent section, a mechanistic nucleation condensation model was integrated in the nozzle analysis model, considering the generation and consequent growth of droplets. The governing differential equations on a staggered grid were discretized using the second-order Lax-Wendroff scheme with a flux limiter, and the Semi-Implicit Method for Pressure-Linked Equation (SIMPLE) algorithm was employed to solve the discrete linear system. To demonstrate the predictability and reliability of the physical models and the numerical method proposed in the present work, three representative nozzles were modeled and simulated. The results show good agreement with the available experimental data, even for condensation shock. Then, the 1D nozzle model was employed to obtain nozzle flow tables of the Terry turbine nozzle for different working pressures which can cover the operation pressure range of the RCIC system. A mechanistic RCIC turbine-pump system model was developed and implemented in the system code TRACE to simulate dynamic responses of the RCIC system under Beyond Design Basis Accident (BDBA) conditions. The turbine-pump governing equations are based on the control volume approach of the angular momentum balance. The physics based mechanistic RCIC model was developed using the TRACE control system components (i.e., signal variables, control blocks, and tables), and incorporated into a TRACE boiling water reactor (BWR) model. The TRACE model in this report has a detailed nodalization of the reactor pressure vessel (RPV), and all of the major flow paths and system components, including the safety relief valves (SRVs) and the containment suppression pool and drywell. Based on the nozzle flow tables generated from the 1D nozzle model developed, the turbine drive torque can be calculated from table lookup. Since the detailed specifications of the RCIC pump are unavailable, the homologous curves for a Bingham pump were used in the current pump component. A station black-out (SBO) accident test problem was selected to demonstrate the TRACE RCIC model. The short-term SBO simulations were performed for two cladding materials: Zircaloy and FeCrAl, to demonstrate the effect of the accident tolerant fuel cladding on fuel heat-up under BDBA accident conditions. The wetwell plays a vital safety role in SBO and other BWR accident scenarios in that it can reduce containment pressure and supply additional core make-up water. The suppression pool temperature distribution has a very large impact on both RPV and containment pressure. Thus, another novel contribution of the project comes mainly from an improved, systems-level wetwell model which can capture buoyancy-induced thermal stratification effects due to steam injection and condensation. A two-zone stratified wetwell model has been implemented in RELAP-7 and some results from that model are presented. This wetwell model is capable of simulating thermal stratification due to a low steam mass injection rate. With a low mass flow rate, the model assumes that all the steam condenses within the pipe and the resulting plume can be approximated with a purely buoyant, heat-source driven model. The wetwell model developed with these assumptions is adequate to simulate slow transients such as extended SBO transients.

42 ENGINEERING↗

DOE OSTI2024

Performance Testing of an Integrated Magnetic Power Take-Off

A wave energy converter (WEC) and the power take-off (PTO) generator system can be represented by using a mass-spring-dampener model. By incorporating a negative stiffness spring within the PTO, the overall stiffness of the PTO can be lowered allowing the impedance of the PTO to be more closely matched with the WEC. By designing for impedance matching the WEC can greatly enhance its power generation capability. This project has involved the design, fabrication and testing of a new type of linear-stroke length and rotary stroke length adjustable negative stiffness magnetic springs for use within a wave energy converter (WEC). The magnetic springs were studied by using 3-D finite element analysis with the objective of creating high energy density and a long linear stroke length. After the construction and testing of both a proof-of-principle adjustable linear and rotary magnetic spring prototype the rotary (torsional) magnetic spring was selected for scaling up analysis. The selected scaled-up proof-of-principle magnetic spring had a peak torque of 850 Nm with a ±45 degree stroke length. By translating the inner rotor relative to the outer rotor, the stiffness could be adjusted to be either negative or positive stiffness. During this project a magnetic lead screw was also studied, and it was shown that by combining the magnetic lead screw with a linearly translating magnetic spring a very long rotary stroke length could be attained. However, as the magnetic lead screw increased complexity and reduced overall energy density relative to a rotary (torsional) spring, this design approach was not further pursed. Dynamometer testing of the variable stiffness magnetic springs was first completed by Portland State University and following this the magnetic spring performance was independently verified by Sandia National Laboratory (Sandia). A WEC analysis when using a variable stiffness magnetic spring was completed by using the WecOptTool. WecOptTool is an open-source WEC optimization software developed by Sandia that supports efficient power take-off (PTO) and control optimization. Wave condition data from the Oregon PacWave test-site was used in this study. The analysis showed that a WEC with a tunable stiffness value could consistently achieve about 80% of its maximum theoretical power production. The use of a tunable stiffness WEC, rather than zero-stiffness or a constant stiffness WEC was also shown to lead to a smaller maximum PTO force requirement. The variable stiffness magnetic spring was integrated into an experimental WEC developed by Sandia, called a Wave-Bot. Sandia successfully completed water-tank testing of the Wave-Bot at the Navy’s Carderock, Maryland, wave-basin test site. The wave-basin testing helped to experimentally demonstrate the operating capabilities and increased power generation capability of a WEC containing an integrated variable stiffness magnetic spring. A WEC capacity factor analysis was also completed. The capacity factor was defined as the ratio of annual average WEC generator power to the maximum (RMS) generated power. This capacity factor provided a means of identifying the ratio of potential revenue to cost. It was calculated that if a tunable variable stiffness magnetic spring has RMS constraints it could operate with a capacity factor above 30%. This is comparable to a wind turbine’s capacity factor.

16 TIDAL AND WAVE POWER↗

DOE OSTI2017

Real-time phase evolution of Selective Laser Melted (SLM) Inconel 718 with temperature through synchrotron X-rays

Selective laser melting (SLM) is an additive manufacturing process that uses laser scanning to achieve melting and solidification of a metal powder bed. This process, when applied to develop high temperature material systems, holds great promise for more efficient manufacturing of turbine components that withstand extreme temperatures, heat fluxes, and high mechanical stresses associated with engine environments. These extreme operational conditions demand stringent tolerances and an understanding of the material evolution under thermal loading. This work presents a real-time approach to elucidating the evolution of precipitate phases in SLM Inconel 718 (IN718) under high temperatures using high-energy synchrotron x-ray diffraction. Four representative samples (taken along variable build height) were studied in room temperature conditions. Two samples were studied as-processed (samples 1 and 4) and two samples after different thermal treatments (samples 2 and 3). The as-processed samples were found to contain greater amounts of weakening phase, δ. Precipitation hardening of Sample 2 reduced the detectable volume of δ, while also promoting growth of γ00 in the γ matrix. Inversely, solution treatment of Sample 3 produced an overall decrease in precipitate phases. High-temperature, in-situ synchrotron scans during ramp-up, hold, and cool down of two different thermal cycles show the development of precipitate phases. Sample 1 was held at 870°C and subsequently ramped up to 1100°C, during which the high temperature instability of strengthening precipitate, γ00, was seen. γ00 dissolution occurred after 15 minutes at 870°C and was followed by an increase of δ-phase. Sample 4 was held at 800°C and exhibited growth of γ00 after 20 minutes at this temperature. These experiments use in-situ observations to understand the intrinsic thermal effect of the SLM process and the use of heat treatment to manipulate the phase composition of SLM IN718.

Sarley, Brooke A.↗