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DOE OSTI2020

Gaussian Process Optimization of Sensitivity-Based Similarity Metrics between New Nuclear Applications and New/Existing Benchmarks

Confidently designing safe, new nuclear criticality experiments requires expert judgement, which could take years of experience. Sensitivity/uncertainty (S/U) analysis can be utilized by less experienced individuals to conservatively estimate uncertainties in important parameters, such as k eff , in newly proposed nuclear applications. This type of analysis relies on matching new nuclear applications with existing benchmark experiments. The Whisper-1.1 software package included in MCNP6.2 ®1 contains more than 1,100 International Criticality Safety Benchmark Evaluation Project (ICSBEP) benchmarks. These benchmarks however rarely match new nuclear applications. The number of benchmarks available to match a given set of materials or geometric configurations varies significantly. Furthermore, recently performed benchmark experiments may not have had enough time to be properly documented and published. Benchmarks are vital for determining the accuracy of nuclear data and can assist nuclear physics and evaluators in improving nuclear data libraries. Exhaustively exploring the parameter space using simulations with software such as MCNP is too computationally expensive. In this work, Gaussian process optimization was implemented to reduce the number of simulations needed for optimization over multiple parameters. This optimization scheme was designed to selectively generate new benchmarks with high sensitivity-based similarity metrics to user-defined nuclear applications. Two benchmark models of spherically nested shells containing plutonium, uranium, tantalum, and water were used in the optimization to match an application containing plutonium plates, stacked in a tantalum reflector, surrounded by water.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Silicon nitride stress-optic microresonator modulator for optical control applications

Modulation-based control and locking of lasers, filters and other photonic components is a ubiquitous function across many applications that span the visible to infrared (IR), including atomic, molecular and optical (AMO), quantum sciences, fiber communications, metrology, and microwave photonics. Today, modulators used to realize these control functions consist of high-power bulk-optic components for tuning, sideband modulation, and phase and frequency shifting, while providing low optical insertion loss and operation from DC to 10s of MHz. In order to reduce the size, weight and cost of these applications and improve their scalability and reliability, modulation control functions need to be implemented in a low loss, wafer-scale CMOS-compatible photonic integration platform. The silicon nitride integration platform has been successful at realizing extremely low waveguide losses across the visible to infrared and components including high performance lasers, filters, resonators, stabilization cavities, and optical frequency combs. Yet, progress towards implementing low loss, low power modulators in the silicon nitride platform, while maintaining wafer-scale process compatibility has been limited. Here we report a significant advance in integration of a piezo-electric (PZT, lead zirconate titanate) actuated micro-ring modulation in a fully-planar, wafer-scale silicon nitride platform, that maintains low optical loss (0.03 dB/cm in a 625 µm resonator) at 1550 nm, with an order of magnitude increase in bandwidth (DC - 15 MHz 3-dB and DC - 25 MHz 6-dB) and order of magnitude lower power consumption of 20 nW improvement over prior PZT modulators. The modulator provides a >14 dB extinction ratio (ER) and 7.1 million quality-factor (Q) over the entire 4 GHz tuning range, a tuning efficiency of 162 MHz/V, and delivers the linearity required for control applications with 65.1 dB·Hz 2/3 and 73.8 dB·Hz 2/3 third-order intermodulation distortion (IMD3) spurious free dynamic range (SFDR) at 1 MHz and 10 MHz respectively. We demonstrate two control applications, laser stabilization in a Pound-Drever Hall (PDH) lock loop, reducing laser frequency noise by 40 dB, and as a laser carrier tracking filter. This PZT modulator design can be extended to the visible in the ultra-low loss silicon nitride platform with minor waveguide design changes. This integration of PZT modulation in the ultra-low loss silicon nitride waveguide platform enables modulator control functions in a wide range of visible to IR applications such as atomic and molecular transition locking for cooling, trapping and probing, controllable optical frequency combs, low-power external cavity tunable lasers, quantum computers, sensors and communications, atomic clocks, and tunable ultra-low linewidth lasers and ultra-low phase noise microwave synthesizers.

Wang, Jiawei (ORCID:0000000257965220)↗

DOE OSTI2021

Robust Molecular Predictive Methods for Novel Polymer Discovery and Applications

Polymeric materials are ubiquitous in modern society and they play an instrumental role in almost all industries, undoubtedly including the energy and environment sectors. Increased demand of energy and awareness to sustainability both necessitates the development of novel polymers with enhanced properties. Unfortunately, their structural and behavioral complexity render such discovery challenging and impeded. To address this problem, scientists are developing various computational modeling techniques and leveraging their power to depict the relationship between structural characteristics of polymers and their properties (such as rheological behaviors), and use such prediction to guide the design and syntheses of novel polymeric materials with enhanced performances. Unfortunately, predicting the relationships between polymer structure and composition with rheological properties via atomistic modeling is still a major challenge because of the extended time and length scales involved. Studying dynamic shear viscosity and linear viscoelasticity using molecular models requires capabilities that have been elusive, including representation of large molecular weight chains with an effective internal scale capable of describing entanglement, shear-rates that are in the s-1 scale with accurate quantitative stresses, and chemically-realistic combinations of both homogeneous and heterogeneous systems. Motivated by these unmet challenges, the overall technical objective of this DOE-STTR Phase II project is to develop robust molecular predictive methods for advanced polymer discovery and applications and especially for designing and demonstrating the “smart” polymer-based waterflooding enhanced oil recovery (EOR) process. In particular, we apply state-of-the-art molecular modeling methods developed by our academic partner, Materials Stimulation Center (MSC) at California Institute of Technology (Caltech), to facilitate and accelerate the experimental discovery processes. During the Phase I of this project, we had focused on development and demonstration of the molecular modeling methods to describe rheological properties of non-Newtonian polymer fluids, and to improve our fundamental understandings of shear-thickening mechanism and kinetics. In Phase II, we further apply the theoretical models to guide our experimental programs to improve our design of smart rheology modifier (SRM) polymers and their optimization for EOR. Specifically, we have three objectives in the Phase II study: (1) to further improve out computational modeling methods, coupling with the advanced machine learning algorithms; (2) to develop cost-effective and efficient SRM-flooding process suitable for EOR applications under typical reservoir conditions; and (3) to further explore the application of our molecular predictive models for innovative material discovery in other industrial applications. The recent development of our multiscale predictive framework allows the successful prediction of rheological properties from the chemical structure for polymers of experimentally relevant molecular weights, and provides an in-silico machine learning engine for screening novel compositions and structures with optimized non-Newtonian response, required for both shear-thinning and shear-thickening applications. Our framework provides: (1) procedures and tools for systematic coarsening from atomistic models and reverse mapping of coarse-grain models to atomistic, (2) unique ab initio methods to characterize the atomistic origin of colloidal and interfacial interactions and phenomena, (3) systematic structure and composition builders based on practical descriptors that drive rheological changes in polymer melts and diluted polymer mixtures, (4) a rheological properties engine capable of predicting viscosity in the zero-shear limit and under realistic dynamic conditions (for shear-rates commensurate with experiments) for large heterogeneous systems, (5) coarse-grain force fields with improved non-bond descriptions based on accurate quantum mechanics, (6) an in-silico screening machine learning engine that feeds from the systematic model builders to cover the descriptors search space, computes the rheological properties from converged trajectories spanning sub-milliseconds and ranks them for each structure/composition using an automated viscosity-vs-shear rate fitness function that can be tuned for shear-thickening, shear-thinning and other rheological responses.

02 PETROLEUM↗

DOE OSTI2021

HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017) (and subsequently titled) Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020) (Final Technical Report)

This is the Final Technical Report for the DoE Measurement Innovation (previously Diagnostic Development) grant DE-SC0006077 titled HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017), and subsequently titled Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020). The grant was funded by the Office of Fusion Energy Sciences (FES) for the period 1 May 2011–17 July 2020. Work performed through the grant has resulted in diagnostic innovations and new measurement capabilities that will improve understanding of transport, magnetic equilibrium, and electric fields in magnetically confined plasmas. We have developed novel hardware and advanced techniques to expand beam-based diagnostic capabilities, and extend measurements to new operating regimes. Some have been realized using a Heavy Ion Beam Probe (HIBP) having traditional features, while other applications have joined our innovations with subsets of advantageous HIBP features. This work has established smaller, more economical detection systems and, in doing so, may enable substantial extension of scenarios in which beam-based diagnostics are deployed. Key Measurement Innovations include: Computer Models and Simulations of HIBP Applications-Computer modeling and simulating of HIBP applications is central to predicting interaction of beam particles with plasmas, designing diagnostic systems, and anticipating measurement characteristics. We have extended the capability and improved measurement fidelity of the HIBP diagnostic on the Madison Symmetric Torus (MST) reversed field pinch (RFP); simulated feasibility of HIBP operation in the Helically Symmetric eXperiment (HSX) optimized stellarator; and investigated the plausibility of HIBP measurements in the ASDEX Upgrade tokamak. We have also developed a new technique that uses ion optics to model a finite phase-space beam. It yields more realistic (than traditional method) estimates of sample volume characteristics, which influence measurement resolution and sensitivity. Extension of Diagnostic Capabilities and Measurements on the MST RFP-Capabilities have been extended using the first and only HIBP installation on an RFP. Challenges associated with operation of the diagnostic on MST include the three-dimensional nature of particle trajectories, temporal topology and amplitude changes in the plasma equilibrium, and strong particle and radiative emission from the plasma. We have addressed these challenges through development of detailed and higher precision diagnostic simulations, calibrated subtraction of noise to resolve secondary ion signals, and implementation of hardware that enables higher fidelity measurement of plasma fluctuations. Development of New Hardware and Measurement Techniques - We have advanced beam-based measurement capabilities via development of new detectors and techniques to determine the poloidal magnetic flux ψ in the plasma, and enable placement of detectors close to the plasma and thus allow a smaller and less expensive diagnostic. We have demonstrated measurement of ψ, an ability that was made possible by development of highly effective noise reduction techniques. We also modeled the effect of non-ideal and instrumentation effects by developing a virtual (simulated) diagnostic. Application of beam-based diagnostics on various devices and multiple magnetic configurations (e.g. stellarator, tokamak, and reversed field pinch) enables investigation of critical physics issues and measurements resulting in the broad parameter space data needed to test and validate theory & modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Boride-Carbon Hybrid Technology to Produce Ultra-Wear and Corrosion Resistant Surfaces for Applications in Harsh Conditions (Final Technical Report)

Engineered functional surfaces play an important role to enable new products and manufacturing processes that can endure harsh service conditions such as high impact and contact loads, highly abrasive wear, extreme temperatures, and corrosive environments. Engineered surfaces can also be instrumental to improving the efficient use of energy by reducing frictional losses and extending service life. The main objective of this project was to develop a hybrid surface engineering technology that combines the advantages of a novel ultrafast boriding process with the next generation of superhard carbon coatings. The hypothesis was that this hybrid process will offer an unprecedented combination of wear and corrosion resistance, low frictional losses and affordability for treated parts so that it can be utilized in many applications. During this project, a duplex process was developed that combines the advantages of ultra-fast electrochemical boriding with those of hard tetrahedral amorphous carbon coatings. Both technologies can be combined to form a hybrid technology that is characterized by low friction and wear properties combined with corrosion and fatigue resistance. Good adhesion of both layers to each other was one main goal of this project, that has been achieved with HF1 adhesion through the Rockwell-C adhesion test. In this project, the mechanical properties of the hybrid coating were modeled through a finite-element analysis approach. We can conclude that the FEA model resembles the actual samples and be utilized to predict mechanical behavior under impacts. Based on this model, application-oriented load conditions can be simulated for optimal layer design regarding thickness and mechanical properties. To exemplify, one conclusion that can be drawn from the nanoindentation model is a boride layer thickness of 50 µm is sufficient to effectively support the carbon coating on the identified AISI 1045 low carbon steel substrate material. The duplex treatment yields wear rates as low as 6 x 10 -8 mm 3 N -1 m -1 and a coefficient of friction of 0.14 when tested against a steel counter face in a ball-on-disk test setup. On the other hand, the wear rate of the only-borided AISI 1045 steel was 5 x 10 -5 mm 3 N -1 m -1 , about three orders of magnitude higher than the duplex coating. At the same time, duplex treated samples experience corrosion resistance, which could not be achieved with single-layer carbon coatings. The developed surface treatment withstands a 3-hour exposure to 15% HCl, while the only carbon coated counter sample shows severe delamination of the coating due to pin hole corrosion. The boride layer is chemically stable and pin hole free because it is formed through an electrochemical process under high current densities (700 mA/cm 2 ) and high temperature. Additionally, the hybrid coating led to at least 3x increase in fatigue strength of the steel substrate, which exceeds the target performance of 30% improvement. There are numerous potential applications for the duplex coatings. A representative application is bearing ball coatings for off-shore windmills. Compared to currently employed surface technologies in this field, the initial costs of applying our technology might be higher due to more process steps but the performance benefits lead to an increased life time of treated parts, which will lower the maintenance and replacement costs in the long-term. To validate the technology for this specific application, the team is currently investigating the process of white etching crack initiation of the duplex coating in collaboration with ANL. Overall, this project successfully validated that the boride-carbon hybrid technology can withstand harsh conditions. One possible approach to commercialization under consideration is to transfer the technology to a startup or an existing coatings company.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Application of NEAMS Codes to Capture MSR Phenomena

This report documents work completed in FY21 under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program’s Molten Salt Reactor (MSR) Application Drivers activity at Argonne. The common focus was on identifying the modeling and simulation functional requirements for designing, licensing, and operating MSRs and applying those capabilities already developed in NEAMS tools to example problems of interest. The four main parts of this report each focuses on a specific area of simulation physics as it relates to MSR phenomena: fuel evolution, chemistry, computational fluid dynamics (CFD), and systems analysis. In terms of fuel evolution, which includes depletion, decay, on-line separations, and transmutation, the current state of computational capabilities for modeling this behavior in liquid-fueled molten salt reactor is discussed. Some of the functional requirements to accomplish the various applications of MSR fuel depletion modeling are highlighted, followed by a summary of recent approaches and code development activities. The chemistry functional requirements were discussed in the context of several applications of high importance for MSRs, such as corrosion, salt chemistry, and species transport. Each of these types of chemistry modeling have considerable impact on various aspects of reactor applications, including informing on reactor designs, improving operational efficiencies, analyzing safety and reactivity concerns, and estimating the mechanistic source term of the reactor. A brief overview is also provided on code development activities ongoing under NEAMS relevant to chemistry modeling of MSRs. In terms of CFD applications, the state-of-the-art spectral element code, Nek5000 was used to model the fluid dynamics within a full core of the Molten Salt Fast Reactor (MSFR) concept designed as part of the Euratom EVOL project. This concept was selected as the challenge problem because of its similar features to several U.S. industry concepts. The goal was to model some of the fast MSR design challenges, including potential large internal re-circulations, the need of accurate tracking of delayed neutron precursors (DNP), and the lack of relevant thermal-hydraulics models/correlations, etc. Therefore, a series of CFD models were created for the MSFR core cavity using a k – τ model two-equation model for the turbulence. These first full core results demonstrated that any potential recirculation zones could be properly identified with the current NEAMS CFD capabilities. The development of these models will also set the stage for future testing of Nek5000’s functionalities to model other MSR thermal-fluid phenomena. Lastly, the validation of SAM against experimental data from the Molten Salt Reactor Experiment, which started in FY19, continues with the inclusion of modeling the reactivity insertion tests. This involved using SAM and its point kinetics model for flowing fuel salt to recreate the time dependent power changes and response after positive reactivity insertions at the 1, 5, and 8 MWt power levels. Through these exercises, several code modifications were suggested to the SAM development team and accommodated to enable closer agreement with solid technical and physical justifications. These include adding a moderator reactivity feedback coefficient as an available input and modifying the solution approach for the point kinetics model. Additional SAM development suggestions for flowing fuel MSRs include adding the capability to allow the moderator power change proportionally with the reactor power and enabling specification of the power and DNP distributions separately.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Assessment of Cold Spray Technology for Nuclear Power Applications

This report provides an overview of cold spray (CS) technology as it relates to repair and fabrication of metal alloys in the nuclear power industry. CS is a relatively new technology with applications established in other industries (e.g., aerospace, defense), and greater use of CS is anticipated within the nuclear power industry. This report is prepared in support of the United States Nuclear Regulatory Commission (NRC) Action Plan for Advanced Manufacturing Technologies (AMTs) Rev. 1, which includes objectives to identify the AMTs most likely to be used for nuclear power applications that require NRC approval, and to prepare NRC staff to review regulatory submittals containing components manufacturing using AMTs. In addition to providing an overview of CS technology, this report highlights engineering and scientific knowledge gaps of CS and rates the size of the knowledge gaps. It also assesses importance rankings of the knowledge gaps as they relate to several application categories. The application categories considered in this exercise include factory-applied CS for chloride induced stress corrosion cracking (CISCC) mitigation, field CISCC repair, light water reactor (LWR) factory structural fabrication, and LWR field dimensional restoration and corrosion protection. The combination of a knowledge gap size rating and importance ranking for an application can be used to prioritize additional data or information gathering efforts.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Design Guidelines for Deployable Wind Turbines for Military Operational Energy Applications

This document aims to provide guidance on the design and operation of deployable wind systems that provide maximum value to missions in defense and disaster relief. Common characteristics of these missions are shorter planning and execution time horizons and a global scope of potential locations. Compared to conventional wind turbine applications, defense and disaster response applications place a premium on rapid shipping and installation, short-duration operation (days to months), and quick teardown upon mission completion. Furthermore, defense and disaster response applications are less concerned with cost of energy than conventional wind turbine applications. These factors impart design drivers that depart from the features found in conventional distributed wind turbines, thus necessitating unique design guidance. The supporting information for this guidance comes from available relevant references, technical analyses, and input from industry and military stakeholders. This document is not intended to be a comprehensive, prescriptive design specification. This document is intended to serve as a written record of an ongoing discussion of stakeholders about the best currently available design guidance for deployable wind turbines to help facilitate the effective development and acquisition of technology solutions to support mission success. The document is generally organized to provide high-level, focused guidance in the main body, with more extensive supporting details available in the referenced appendices. Section 2 begins with a brief qualitative description of the design guidelines being considered for the deployable wind turbines. Section 3 provides an overview of the characteristics of the mobile power systems commonly used in U.S. military missions. Section 4 covers current military and industry standards and specifications that are relevant to a deployable wind turbine design. Section 5 presents the deployable turbine design guidelines for the application cases.

17 WIND ENERGY↗

DOE OSTI2024

Offline Power Systems Applications Enabled by Phasor Measurement Units: Technical Assistance to the Power Sectors of Southeast Asia

This report provides a brief overview of several offline (non-real-time) applications facilitated by high-resolution time-synchronized measurements recorded by phasor measurement units (PMUs). The high reporting rate and time-synchronization of PMU records provide a detailed view of power system dynamics, enabling electric utilities to obtain a better understanding of their systems. In this report, the following applications have been reviewed: Power plant model validation, System model validation, Ringdown oscillation analysis, Frequency response analysis, Postmortem analysis of disturbance events Along with a brief technical background of the applications above, applicable North American Electric Reliability Corporation (NERC) standards have been discussed, and examples of implementation in North American organizations have been provided. Implementing several of the discussed applications may need a preliminary stage of data gathering from multiple entities, and several frameworks and process flows have been formulated by organizations around the world for this purpose. However, the data-gathering stage has not been considered in the scope of the present report.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Connecting Minds: AI Use Cases to Bridge Power Systems and Large Language Models for Practical Applications

Recent advances in artificial intelligence (AI) and development of large language models (LLMs) present the opportunity to develop a new generation of power systems applications. In contrast with early power system AI applications based on structured numerical data, LLMs offer unique capabilities to perform logical reasoning using text documents, unstructured data, and application programming interface (API) calls to computational software. This paper seeks to bridge the knowledge gap between power systems engineers and LLM developers through a crosscutting explanation of use cases, characteristics, requirements, practical considerations from the perspectives of both LLM capabilities and industry needs. Specific focus is given to applications that can be realistically deployed by electric utilities. After introducing the architecture of LLMs and unique challenges of the power systems domain, this paper proposes twenty representative LLM applications grouped into categories of 1) power system operations, 2) asset management, 3) system planning and analytics, and 4) energy management and protection systems. Five use cases are presented within each category with descriptions of the motivation, objectives, approaches, example inputs / outputs, and benefits of each use case.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

High-Temperature Active Magnetic Bearing Development for Supercritical CO 2 Machinery Applications

Hermetic machinery utilizing gas bearings for MW-scale supercritical CO 2 (sCO 2 ) machinery applications can have significantly lower power loss and enable improved cycle efficiency compared to conventional machinery with oil-lubricated bearings. Active magnetic bearings (AMBs) are another option anticipated to have similar power loss and load capacity to gas bearings as well as offering larger mechanical tolerances, the ability to tune properties, and high reliability due to lack of mechanical wear. AMBs also have proven commercial experience at MW-scale, though environments for high-temperature sCO 2 power cycle machinery conditions are novel. Besides the potential impact of AMBs for sCO 2 turbomachinery, the technology also offers promising benefits for steam and gas turbines for power generation, compressors and expanders for industrial heat and power, and in other oil and gas and space applications. The goals of this project were to conceptual design an AMB and perform material testing. Conceptual designs for radial and thrust AMBs were produced based on a hermetically-sealed sCO 2 machinery waste-heat recovery (WHR) application for sizing and loads, and choosing a target design temperature of 540°C useful for high-temperature sCO 2 turbines for concentrating solar power (CSP) applications. Conceptual designs were initially developed for multiple radial and thrust AMBs with spreadsheet-based calculations before selecting one of each to develop further using higher-fidelity design methods for magnetic and structural performance. It was found that the radial AMB at 540°C was feasible, but the thrust AMB needed to be limited to 315°C for high-speed operation. The decision for a reduced-temperature thrust AMB was the result of several significant conclusions: 1) Hiperco 50A, originally chosen for good magnetic performance at high temperature, had insufficient strength for high-speed operation, so it was replaced with 17-4 PH. 2) The reduced magnetic performance from 17-4 PH yielded a larger bearing size, reducing the strength margin. 3) This ultimately led to a creative design implementing a more-compact E-core topology, compared to the original (conventional) C-core, and an integral shaft-disk with Hirth joint connection. These conceptual designs are unique for the size and temperature in CO 2 , relevant for MW-scale CSP applications. Long term, high temperature test data was generated for several materials, filling a void in the current body of literature. Corrosion and magnetic performance measurements were produced for PM materials (Alnico 5-7C, Alnico 9C, and SmCo) with and without nickel-coating for environments of high-temperature CO 2 up to 550°C at atmospheric pressure and 450°C at 103 bar for up to 6,000 hours. Corrosion measurements were also produced for Hiperco 50, a SM material relevant for AMB laminations, with and without C5 coating. Comparisons were also made for 450°C and 550°C, atmospheric pressure air exposures up to 5,000 hours. Results generally show that coatings can be effective at improving oxidation resistance of the bare materials, and Alnicos generally outperformed SmCo after high-temperature exposure. In addition to technical feasibility demonstrated by the design, economic feasibility was demonstrated by updating the TEA from the reference machine, re-evaluating it with CAPEX and OPEX to reflect estimated changes from process-lubricated bearings to AMBs. AMBs were shown to be comparable in performance to process-lubricated bearings, still showing a notable improvement over conventional machinery architecture with oil-lubricated bearings.

42 ENGINEERING↗

DOE OSTI2025

Redesign of the Timeline Generator at Fermilab using a web-based Flutter Application, GraphQL API and an IOC

Redesign of the Timeline Generator at Fermilab using a web-based Flutter application, GraphQL API and an IOC ABSTRACT = The control system at Fermilab is undergoing an evolution with a shift towards web-based applications with connections to the EPICS infrastructure. The Timeline Generator (TLG) is an application that serves to coordinate events across the lab using different timing links. These links include the Tevatron clock (TCLK), a 10 MHz serial link with events encoded at 20Hz and Ma-chine Data (MDAT), a communication link with states encoded at 720Hz. This paper covers the redesign of the major components of the TLG. This includes a web-based Flutter application for building timelines. A placement service is in use that has a GraphQL interface and uses a timeline input to compute a schedule of events and states. The Flutter application sends this computed schedule to the TLG IOC via a GraphQL interface to the Data Pool Manager (DPM). The TLG IOC runs on an Arria FPGA, the Accelerator Clock Generator (ACLK-GEN), which is responsible for writing the events and states on to the different timing links.

Carmichael, Linden [Fermilab]↗

DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗

DOE OSTI2023

Nuclear fuel irradiation testbed for nuclear security applications

The nuclear security community has long been interested in the identification and quantification of nuclear material signatures to understand a material’s provenance, use, and ultimate application. New forensics signatures and methods intended for non-traditional or advanced nuclear fuel applications require fuel irradiation experiments to demonstrate viability and validity. Integral fuel irradiations have historically required significant costs and long timelines to design, irradiate, and characterize. This paper describes how a recently developed nuclear fuel irradiation testbed can be used to provide a low cost, rapid turnaround, modular test environment for irradiation and evaluation of nuclear fuel specimens for nuclear security applications. The irradiation testbed houses six small ‘MiniFuel’ samples within hermetically sealed capsules inside targets that can be removed in between each ∼25-day operating cycle of the High Flux Isotope Reactor (HFIR). As many as nine targets can be irradiated using a single irradiation position (reflector region) in HFIR, allowing for varying irradiation temperatures and burnups. A suite of hot cell capabilities have been established to perform post-irradiation examination for measuring performance (e.g., fuel swelling, fission gas release) and facilitating experiment disassembly for subsequent property measurements, microstructural analysis, or chemical assay. This new testbed allows fuel irradiations to be conducted on an accelerated timeframe to enable rapid proof of concept testing and to provide reference material for nuclear fuel security applications. Recent applications using this testbed include the testing of isotopic taggants in UO 2 fuel (intentional forensics), testing of U-10Mo fuel for down-conversion of highly enriched uranium–fueled reactors, and the production of irradiated UO 2 fuel material for signature analysis of its isotopic composition (plutonium, fission gases, etc.).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2025

Nuclear Data Adjustment for Nonlinear Applications in the OECD/NEA WPNCS SG14 Benchmark -- A Bayesian Inverse UQ-based Approach for Data Assimilation

The Organization for Economic Cooperation and Development (OECD) Working Party on Nuclear Criticality Safety (WPNCS) proposed a benchmark exercise to assess the performance of current nuclear data adjustment techniques applied to nonlinear applications and experiments with low correlation to applications. This work introduces Bayesian Inverse Uncertainty Quantification (IUQ) as a method for nuclear data adjustments in this benchmark, and compares IUQ to the more traditional methods of Generalized Linear Least Squares (GLLS) and Monte Carlo Bayes (MOCABA). Posterior predictions from IUQ showed agreement with GLLS and MOCABA for linear applications. When comparing GLLS, MOCABA, and IUQ posterior predictions to computed model responses using adjusted parameters, we observe that GLLS predictions fail to replicate computed response distributions for nonlinear applications, while MOCABA shows near agreement, and IUQ uses computed model responses directly. We also discuss observations on why experiments with low correlation to applications can be informative to nuclear data adjustments and identify some properties useful in selecting experiments for inclusion in nuclear data adjustment. Performance in this benchmark indicates potential for Bayesian IUQ in nuclear data adjustments.

FOS: Computer and information sciences↗

NASA NTRS1972

Applications analysis of high energy lasers

An analysis and comparison of laser technology with competing technologies were made to determine possible laser applications. The analysis was undertaken as follows: (1) possible applications were listed and categorized; (2) required components were enumerated and the characteristics of these components were extrapolated; (3) complete system characteristics were calculated parametrically for selected applications using the postulated component characteristics; and (4) where possible and appropriate, comparisons were made with competing systems. It was found that any large scale replacement of existing systems and methods by lasers requires many technological advances in laser and associated systems. However, several applications appear feasible, such as low orbit drag make-up, orbit changing, communications, and illumination applications.

Arno, R. D.↗

NASA NTRS1970

Potentially efficient forest and range applications of remote sensing using earth orbital space craft, circa 1980

Sixteen remote sensing applications or groups of related applications judged to be most important of any in the forestry and range disciplines were evaluated. In one application, major land classification, large amounts of useful data are anticipated to be contributed by space sensors in 1980. In four applications moderate amounts are anticipated to be so contributed. These are timber inventory, range inventory, fire weather forecasting, and monitoring snowfields. In the following seven applications small but significant amounts of data are anticipated to be contributed by space sensors: (1) detailed land classification; (2) inventory of wildlife habitat; (3) recreation resource inventory; (4) detecting stresses on the vegetation (5) monitoring air pollution caused by wildfires and prescribed burning; (6) monitoring water cycle, (7) pollution and erosion; and (8) evaluating damage to forests and ranges.

Wilson, R. C.↗

NASA NTRS1973

Applications of aerospace technology in biology and medicine

The results are reported of the medically related activities of the NASA Application Team Program at the Research Triangle Institute. Fourteen medical organizations are presently participating in the RTI Application Team Program: The accomplishments of the Research Triangle Institute Application Team during the reporting period were as follows: The team identified 21 new problems for investigation, accomplished 4 technology applications and 3 potential technology applications, closed 21 old problems, and on February 28, 1973, had a total of 57 problems under active investigation.

Source record↗