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DOE OSTI2022

Updates to Nek5000: RANS wall functions, NRC support, and documentation

As a key part of the U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program (NEAMS), the next generation of tools for nuclear reactor design are being developed. A primary metric for success of this program is the adoption of those tools by industry stakeholders. To help meet this metric for Nek5000, development efforts this year have focused on the expansion of the available Reynolds-averaged Navier-Stokes (RANS) turbulence models to include wall function models, continued support of the U.S. Nuclear Regulatory Commission in simulating a hydrogen mitigation benchmark experiment, and expansion of the Nek5000 documentation to enhance the code’s usability. The implementation of wall functions is intended to significantly decrease time to-solution for a wide range of problems and it has been identified as an important feature by stakeholders across the nuclear community. The initial implementation of standard and pressure corrected wall functions has been tested in Nek5000 on the classical problems of channel flow and a backward facing step. It has also been tested on a 2D molten salt fast reactor core and a T-junction. The recommended formulation of choosing y + = 30 as a boundary value combined with a Neumann-Neumann formulation of the boundary condition for k and τ produces the most consistent results compared to a wall resolved approach. The collaboration with the NRC is a continuing exercise that has been ongoing for multiple years. This year we have concluded investigations into appropriate inlet conditions, showing that fully developed turbulent conditions are adequate for the full PANDA domain. We have also concluded simulations for an unobstructed jet and are now refocusing to the original obstructed jet case. The expansion of the code documentation has also been an ongoing effort over the past few years to address feedback from the various stakeholders. The documentation now more fully covers many of the available features and closes identified SQA gaps. Finally we report on three training sessions that were offered over the past year in an effort to expand the Nek5000 user base.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Data Curation for Machine Learning Applied to Geothermal Power Plant Operational Data for GOOML: Geothermal Operational Optimization with Machine Learning: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach to physics-guided, data-centric machine learning. This framework has been used to develop digital twins that provide steamfield operators with operational environments to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management in real world applications. To create, test, and apply the GOOML framework, diverse time-series datasets spanning multiple years were sourced from various geothermal power plant components within several complex real-world geothermal operations. These operations are based in the United States and New Zealand and include a variety of technologies, end-uses and configurations, collectively covering nearly all relevant operating conditions for modern geothermal fields. Datasets were acquired from multiple sources to ensure that machine learning experiments generalized properly to various operating conditions. It was found that the data varied in quality, format, and completeness. To ensure consistency between the various datasets, a standardized data curation process was developed to reliably streamline data preparation. This paper will discuss best practices as learned from the GOOML data curation process which takes the following steps: 1) acquisition of large quantities of data from power plant operators, 2) digestion of data to gain an initial understanding of what is included, 3) data transformation, which includes converting the data into a standardized machine-readable format so that they can be visualized, quality checked, and cleaned, 4) quality assurance and quality control, involving identification of significant data gaps and apparent anomalies through mapping of data features to real world componentry via the GOOML historical model, followed by discussion with modelers and power plant operators to identify additional data needs and to resolve issues, 5) use in machine learning algorithms, and 6) repetition of steps one through five until all data needs are met and data are deemed suitable for producing trustworthy modeling results which may be disseminated, ideally along with the curated dataset. This iterative process is focused on improving the quality of the data rather than tuning machine learning model parameters and supports a shift towards data-centric AI as a means to improving real-world applicability of geothermal machine learning projects.

access↗

DOE OSTI2024

Dynamic flux surrogate-based partitioned methods for interface problems

Loosely coupled partitioned methods for multiphysics problems treat each subproblem as a separate entity and advance them independently in time. In so doing these methods enable code reuse, increase concurrency and provide a convenient framework for plug-and-play multiphysics simulations. However, mathematically loosely coupled schemes are equivalent to a single step of an iterative solution method, which can compromise their accuracy and stability. We present a new data-driven partitioned method for coupled parametric PDEs that can improve upon the accuracy of traditional loosely coupled methods without incurring a performance penalty. To that end, we replace conventional field transfers across the interface by a surrogate for the dynamics of the interface flux exchanged between the subdomains. To develop this surrogate we apply dynamic mode decomposition to a non-standard staggered-in-time state, comprising the interface flux and small solution patches near the interface. The new approach shifts the main computational burden to an offline training phase, whereas application of the surrogate in the online phase amounts to a single matrix–vector multiplication. In conclusion, we provide stability analysis of the surrogate-based partitioned scheme and include numerical results that demonstrate its potential.

Dynamic mode decomposition (DMD)↗

DOE OSTI2023

252 Cf yield calibration method for nuclear material accountancy and safeguards practitioners

Californium-252 is an isotope commonly encapsulated as a physically small but strong spontaneous fission neutron source for applications in industry, academia, and research. Within the nuclear safeguards community, a well-characterized 252 Cf source is often used as an accessible alternative for plutonium in calibrations measurements, which require the absolute source strength. Current methods of source strength quantification can provide an accurate estimate, approximately 1% uncertainty under optimal conditions, but are typically costly and time consuming. An alternative method was developed to determine 252 Cf source strength using passive neutron correlation counting (PNCC). The PNCC method enables institutions and facilities to perform 252 Cf source calibration measurements in-house using detection systems that are common within the nuclear safeguards community. This novel method was previously successfully demonstrated using neutron multiplicity well counters. However, the previous evaluation utilized detection systems with high neutron detection efficiencies, greater than 60%. The purpose of the current study is to extend the previous evaluation and demonstrate the feasibility of the PNCC 252 Cf calibration method for suite of coincidence counters with lower neutron detection efficiencies, between 15% and 35%, which are more commonly encountered in the field, as well as to provide a step-by-step guide to using the method. The neutron source used in this evaluation was previously certified by the National Institutes of Science and Technology (NIST), which provides a reference for the accuracy of the PNCC method. In conclusion, the present source yield calculations demonstrate excellent agreement with a NIST calibration technique and achieve a standard uncertainty below the target 1%.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

VitroJet: new features and case studies

Single-particle cryo-electron microscopy has become a widely adopted method in structural biology due to many recent technological advances in microscopes, detectors and image processing. Before being able to inspect a biological sample in an electron microscope, it needs to be deposited in a thin layer on a grid and rapidly frozen. The VitroJet was designed with this aim, as well as avoiding the delicate manual handling and transfer steps that occur during the conventional grid-preparation process. Since its creation, numerous technical developments have resulted in a device that is now widely utilized in multiple laboratories worldwide. It features plasma treatment, low-volume sample deposition through pin printing, optical ice-thickness measurement and cryofixation of pre-clipped Autogrids through jet vitrification. This paper presents recent technical improvements to the VitroJet and the benefits that it brings to the cryo-EM workflow. A wide variety of applications are shown: membrane proteins, nucleosomes, fatty-acid synthase, Tobacco mosaic virus, lipid nanoparticles, tick-borne encephalitis viruses and bacteriophages. These case studies illustrate the advancement of the VitroJet into an instrument that enables accurate control and reproducibility, demonstrating its suitability for time-efficient cryo-EM structure determination.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Guided construction of single cell reference for human and mouse lung

Accurate cell type identification is a key and rate-limiting step in single-cell data analysis. Single-cell references with comprehensive cell types, reproducible and functionally validated cell identities, and common nomenclatures are much needed by the research community for automated cell type annotation, data integration, and data sharing. Here, we develop a computational pipeline utilizing the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct LungMAP single-cell reference (CellRef) for both normal human and mouse lungs. CellRefs define 48 human and 40 mouse lung cell types catalogued from diverse anatomic locations and developmental time points. We demonstrate the accuracy and stability of LungMAP CellRefs and their utility for automated cell type annotation of both normal and diseased lungs using multiple independent methods and testing data. We develop user-friendly web interfaces for easy access and maximal utilization of the LungMAP CellRefs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Timeouts Best Practices

This study investigates common timeouts encountered in the electric vehicle (EV) charging communications process. Many different timeouts are defined within the EV charging communications protocols. These timeouts can either be a fixed value or a defined range of values. In both cases, the timeout defines the duration of time for which one or both parties in the communications session are expected to wait for some action or process to complete before terminating the charge attempt. These timeout-based terminations are intended to prevent the charging process from becoming stuck indefinitely in any particular step. These terminations also enable a retry of the terminated charging session to begin. However, misaligned timeout values can have a significant negative impact on the user experience. Premature termination of charging sessions due to inappropriate timeout settings can lead to charging failures, causing inconvenience, wasted time, and frustration for users. These disruptions can degrade the overall user experience, making it essential to carefully manage and align timeout values with the relevant actions and processes to ensure reliable and satisfactory EV charging sessions. The core objective of this study is to boost reliability and enhance user experience by conducting a thorough review of timeout-based issues in EV charging and delivering a set of recommendations to modify these existing timeouts. These recommendations are informed by feedback gathered from multiple EV charging partners. This document is intended to inform electric vehicle supply equipment (EVSE) and EV manufacturers, EV charging infrastructure developers, and policymakers responsible for designing and implementing EV charging protocols and systems.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Towards Neutron Transformation Searches

To probe the origins of the baryon asymmetry, baryon number violation, the last unconfirmed Sakharov condition, must be definitively observed experimentally. Similarly, the nature of dark matter is currently unknown, and calls out for new candidates to be investigated. Each of these issues can be considered through the study of neutron transformations.Some rare baryon number violating processes, such as neutron-antineutron transformations, are expected to probe baryogenesis. Here, I show progress on this discovery target through construction of more accurate Monte Carlo models, the design of future detectors, creation of more complete atmospheric neutrino background simulations, and use of automated analysis techniques within the the NNBAR/HIBEAM experimental program at the European Spallation Source (ESS) and the Deep Underground Neutrino Experiment (DUNE). First simulation-based sensitivities for these experiments will be discussed. Modeling of rare neutron-antineutron transformation and subsequent annihilation will be discussed at length for multiple nuclei useful to these and other collaborations. To go along with this work, more comprehensive lepton-scattering nuclear models must be integrated into neutrino event generators for proper atmospheric neutrino background simulations. I discuss the first furnishing of these backgrounds for DUNE, and I highlight a potential path forward for the community in this vein using precisionmore » electron scattering modeling as a facsimile.Aspects of other potentially related neutron – mirror-neutron oscillations pertinent to dark matter and the neutron lifetime anomaly will also be considered for the ESS HIBEAM experiment. Here, I will present the first experimental sensitivity calculations for a broad range of modular experimental setups which will serve as research and design stepping stones toward NNBAR while producing a multitude of physics results over short time scales.« less

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Accelerated Creep Test Qualification of Creep-Resistance Using the Wilshire–Cano–Stewart Constitutive Model and Stepped Isostress Method

In this paper, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire–Cano–Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing is a long-term continuous process; in fact, the ASME B&PV III requires that 10,000+ h of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The SSM has been developed, which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750 °C and predictions are compared to conventional creep testing data. The WCS model has proven to make long-term predictions for stress-rupture, MCSR, creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are postaudit validated using the National Institute of Material Science database. Similarly, the MCSR predictions are compared from previous studies. Finally, the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and industrial gas turbines.

42 ENGINEERING↗

DOE OSTI2024

Characterization of the upgraded single-line-of-sight time-resolved x-ray imager using short-pulse visible and UV lasers

The single-line-of-sight time-resolved x-ray imager (SLOS-TRXI), a fast-gated x-ray imager used for capturing x-ray self-emission in inertial confinement fusion experiments on OMEGA, has been upgraded and characterized. SLOS-TRXI combines an electron-dilation imager and a hybrid complementary metal–oxide–semiconductor (hCMOS) sensor to capture multiple gated frames on a single line of sight with a temporal resolution of ~40 ps and a spatial resolution of 10 µm. The original hCMOS sensor with four frames was replaced with a newer-generation hCMOS sensor having eight frames. Gate characterizations of both the sensor and the entire SLOS-TRXI diagnostic were performed using ~10-ps FWHM visible (2ω) and UV (4ω) short-pulse lasers, respectively. A stepped echelon was used to generate a train of five UV laser pulses having an interpulse separation of 30 ± 3 ps. Characterization results of the hCMOS gating (2.28 ± 0.02-ns FWHM on average) and a temporal resolution of the upgraded SLOS-TRXI (34 ± 4-ps FWHM on average) are presented. A temporal magnification for the electron-dilation imager between 40 and 60 was inferred from the characterization results. Furthermore, the spatial resolution of the upgraded SLOS-TRXI remains the same in light of this work.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Intercomparison of Deep Learning Model Architectures for Atmospheric River Prediction

With a rapid surge in the application of machine learning (ML) for a diverse range of tasks in climate science, the present study addresses a challenge for climate scientists when selecting the optimal ML or deep learning (DL) architecture for a given application. In particular, a DL intercomparison study was performed with a focus on forecasting the position of atmospheric rivers (ARs) on short-range time scales (up to 5-day lead times). AR predictions from multiple DL architectures, including various types of convolutional autoencoders and a vision transformer (ViT), were compared against ECMWF ERA5 reanalysis and hindcasts from a global climate model. DL models with similar trainable parameters were trained on ERA5 reanalysis data and AR positions derived from a thresholding algorithm to ensure a fair comparison among the DL models. Each model’s performance and accuracy in forecasting AR location and key input fields within a 5-day window were assessed using metrics of root-mean-square error, anomaly correlation, and mean intersection over union. The ViT architecture outperformed other autoencoder models in most of the metrics. Incorporating additional meteorological fields only yielded slight improvements in forecasting certain fields at longer lead times. The results also suggest that a smaller number of input time steps or smaller number of autoregressive steps can achieve better prediction skills, while also improving the overall computational efficiency. This research offers valuable insights into the strengths and weaknesses of different DL techniques for AR forecasting, hopefully guiding the development of improved models for forecasting this phenomenon.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Modular Linear Thermoviscoelastic Model

Time-dependent, viscoelastic responses of materials like polymers and glasses have long been studied. As such, a variety of models have been put forth to describe the behavior including simple rheological models (e.g. Maxwell, Kelvin), linear "fading memory" theories, and hereditary integral based linear thermal viscoelastic approaches as well as more recent nonlinear theories that are either integral, fictive temperature, or differential internal state variable based. The current work details a new LINEAR_THERMOVISCOELASTIC model that has been added to LAME. This formulation represents a viscoelastic theory that neglects some of the phenomenological details of the PEC/SPEC models in favor of efficiency and simplicity. Furthermore, this new model is a first step towards developing "modular" viscoelastic capabilities akin to those available with hardening descriptions for plasticity models in LAME. Specifically, multiple different (including user-defined) shift-factor forms are implemented with each being easily selected via parameter specification rather than requiring distinct material models.

36 MATERIALS SCIENCE↗

DOE OSTI2023

The Historical Development of Large‐Scale Paleoclimate Field Reconstructions Over the Common Era

Abstract Climate field reconstructions (CFRs) combine modern observational data with paleoclimatic proxies to estimate climate variables over spatiotemporal grids during time periods when widespread observations of climatic conditions do not exist. The Common Era (CE) has been a period over which many seasonally‐ and annually‐resolved CFRs have been produced on regional to global scales. CFRs over the CE were first produced in the 1970s using dendroclimatic records and linear regression‐based approaches. Since that time, many new CFRs have been produced using a wide range of proxy data sets and reconstruction techniques. We assess the early history of research on CFRs for the CE, which provides context for our review of advances in CFR research over the last two decades. We review efforts to derive gridded hydroclimatic CFRs over continental regions using networks of tree‐ring proxies. We subsequently explore work to produce hemispheric‐ and global‐scale CFRs of surface temperature using multi‐proxy data sets, before specifically reviewing recently‐developed data assimilation techniques and how they have been used to produce simultaneous reconstructions of multiple climatic fields globally. We then review efforts to develop standardized and digitized databases of proxy networks for use in CFR research, before concluding with some thoughts on important next steps for CFR development.

Smerdon, Jason E.↗

DOE OSTI2021

Symbolic pregression: Discovering physical laws from distorted video

In this work, we present a method for unsupervised learning of equations of motion for objects in raw and optionally distorted unlabeled synthetic video (or, more generally, for discovering and modeling predictable features in time-series data). We first train an autoencoder that maps each video frame into a low-dimensional latent space where the laws of motion are as simple as possible, by minimizing a combination of nonlinearity, acceleration, and prediction error. Differential equations describing the motion are then discovered using Pareto-optimal symbolic regression. We find that our pre-regression (“pregression”) step is able to rediscover Cartesian coordinates of unlabeled moving objects even when the video is distorted by a generalized lens. Using intuition from multidimensional knot theory, we find that the pregression step is facilitated by first adding extra latent space dimensions to avoid topological problems during training and then removing these extra dimensions via principal component analysis. An inertial frame is autodiscovered by minimizing the combined equation complexity for multiple experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Dynamic Catalysis Fundamentals: I. Fast calculation of limit cycles in dynamic catalysis

Dynamic catalysis—the forced oscillation of catalytic reaction coordinate potential energy surfaces (PES)—has recently emerged as a promising method for the acceleration of heterogeneously-catalyzed reactions. Theoretical study of enhancement of rates and supra-equilibrium product yield via dynamic catalysis has, to-date, been severely limited by onerous computational demands of forward integration of stiff, coupled ordinary differential equations (ODEs) that are necessary to quantitatively describe periodic cycling between PESs. Here, we establish a new approach that reduces, by ≳108×, the computational cost of finding the time-averaged rate at dynamic steady state (i.e. the limit cycle for linear and nonlinear systems of kinetic equations). Our developments are motivated by and conceived from physical and mathematical insight drawn from examination of a simple, didactic case study for which closed-form solutions of rate enhancement are derived in explicit terms of periods of oscillation and elementary step rate constants. Generalization of such closed-form solutions to more complex catalytic systems is achieved by introducing a periodic boundary condition requiring the dynamic steady state solution to have the same periodicity as the kinetic oscillations and solving the corresponding differential equations by linear algebra or Newton-Raphson-based approaches. The methodology is well-suited to extension to non-linear systems for which we detail the potential for multiple solutions or solutions with different periodicities. For linear and non-linear systems alike, the acute decrement in computational expense enables rapid optimization of oscillation waveforms and, consequently, accelerates understanding of the key catalyst properties that enable maximization of reaction rates, conversions, and selectivities during dynamic catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study: Preprint

Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2022

Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study

Langner, Rois↗

DOE OSTI2022

Status Update on the Development of Transducers and Bonding Techniques for Enabling Acoustic Measurements of Damage in Microreactor Components

This report provides an overview of potential sensors and sensor-bonding techniques to enable the online acoustic interrogation of microreactor components and enhance structural health monitoring capabilities. The report focuses primarily on optical fiber–based acoustic sensors and describes initial experimental progress toward the deployment of these sensors for microreactor applications. The general approach is to monitor the resonant frequencies of microreactor components and search for evidence of structural defects that could indicate imminent failure. If properly identified, then the components could be repaired during the next reactor outage to prevent costly unplanned shutdowns. The ability to monitor the structural health of components could also reduce the need for time-consuming visual inspections and reduce staffing to improve microreactor economic viability. Increased sensor density is also one of the first steps to moving toward eventual semiautonomous operation. The expected microreactor conditions in which acoustic sensors must survive are characterized, including temperatures, neutron fluences, thermomechanical strains, and vibrational frequencies. Optical fiber–based acoustic sensors are identified as an attractive candidate for acoustic monitoring because of their high accuracy, immunity to electromagnetic interference, and resiliency in high-temperature, high-radiation environments. Optical fiber–based intrinsic sensors, such as type-II fiber-Bragg gratings and Fabry-Pérot Cavities (FPCs), are particularly attractive for a microreactor environment because of their high temperature stability, and FPCs also enable higher frequency interrogation with a lower sensitivity to radiation-induced drift. This report describes multiple interrogation systems, but the best interrogation system for a given situation will depend on the specific microreactor application, including the desired acoustic vibrational amplitudes, modes, and resonant frequencies. Initial experiments included fabricating three FPCs, tack-welding these FPCs to stainless-steel pipes or rods and performing room-temperature acoustic sensing tests to capture the vibrational frequency content. Peaks were identified in the measured frequency spectra and compared with the theoretical fundamental frequencies obtained from Euler-Bernoulli beam theory. Two of the three FPCs measured vibrational frequencies that generally matched those obtained from theory. Future work will include similar testing on pipes or other microreactor components with intentional flaws to evaluate the ability to determine changes in resonant frequencies. Finally, these tests will be repeated at high temperatures, potentially with an applied thermomechanical stress, to include environmental conditions similar to those for a microreactor application.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗