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Development of high performance ODS alloys

This project aims to capitalize on insights developed from recent high-dose self-ion irradiation experiments in order to develop and test the next generation of optimized ODS alloys needed to meet the nuclear community's need for high strength, radiation-tolerant cladding and core components, especially with enhanced resistance to void swelling. Two of these insights are that ferrite grains swell earlier than tempered martensite grains, and oxide dispersions currently produced only in ferrite grains require a high level of uniformity and stability to be successful. An additional insight is that ODS particle stability is dependent on as-yet unidentified compositional combinations of dispersoid and alloy matrix, such as dispersoids are stable in MA957 to doses greater than 200 dpa but dissolve in MA956 at doses less than 200 dpa. These findings focus attention on candidate next-generation alloys which address these concerns. Collaboration with two Japanese groups provides this project with two sets of first-round candidate alloys that have already undergone extensive development and testing for unirradiated properties, but have not yet been evaluated for their irradiation performance. The first set of candidate alloys are dual phase (ferrite + martensite) ODS alloys with oxide particles uniformly distributed in both ferrite and martensite phases. The second set of candidate alloys are ODS alloys containing non-standard dispersoid compositions with controllable oxide particle sizes, phases and interfaces.

36 MATERIALS SCIENCE↗

DUNE in 10 Minutes [Slides]

The DUNE Science Collaboration is currently made up of over 1000 collaborators from 175 institutions (60% non-US) in 32 countries (35% of developing countries) plus CERN. The aim of this research program is to discover some of the greatest mysteries of the universe; origin of matter, unification of forces, black holes formation, among others. This project has a cooperative structure of consortia, working groups, task forces, boards and committees who have been working academically and administratively on the different key areas such as physics research, development of the detectors and prototypes, coordination of interfaces, and data analysis. One of the main objectives of this experiment is to motivate young people into science; leaders and members of the experiment, are very encouraging with younger members. On the other hand, this experiment goes beyond the experimental and practical outcomes in developing countries such as Colombia. This experiment is providing us with opportunities for doing science in our country, promoting progress, engaging new generations of Colombians and placing science on the political agenda.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The 2015 Nonlinear Mechanics and Dynamics Research Institute

The Nonlinear Mechanics and Dynamics (NOMAD) Research Institute is a six week long collaborative research program for graduate students from across the world. The 2015 NOMAD Research Institute was hosted jointly by Sandia National Laboratories and the University of New Mexico, and featured 24 graduate students working on seven different research projects. These projects included: developing experimental strategies for studying the dynamics of nonlinear systems, a numerical round robin for predicting the response of a jointed system, quantification of uncertainty in a lap joint, assessment of experimental substructuring methods, a study of stress waves propagating through jointed interfaces, structural design optimization with joints, and the nonlinear system identification of MEMS devices. This report details both the technical research and the programmatic organization of the 2015 NOMAD Research Institute.

42 ENGINEERING↗

Future SDN-HPON Control Plane Architecture and Protocol for On-Demand Terabit End-to-End Extreme-Scale Science Applications

The UC Davis team conducted architecture, algorithm and experimental studies for next generation ultra-high-bandwidth optical networks in support of extreme-scale science applications. In particular, over the course of this 3-year project, the UC Davis team achieved the following main accomplishments: Designed a network architecture for automated multi-domain service provisioning: Designed information exchange schemes between autonomous systems (domains) Designed application programming interfaces to orchestrate resource reservation in data centers, high performance computation facilities, and communication networks belonging to different autonomous systems Experimentally assessed the multi-domain network architecture in a distributed field trial set-up connecting premises in three continents Designed a broker-based orchestrated multi-domain optical networking framework supporting observe-analyze-act cycle based cognitive inter-domain service provisioning: Designed an inter-domain operation mechanism, e.g., topology abstraction, for the broker plane and domain managers to collaboratively accomplish inter-domain service provisioning while respecting the autonomy of each administrative domain Designed an alien wavelength monitoring scheme and an artificial neural network based optical signal-to-noise ratio estimator for quality-of-transmission aware inter-domain service provisioning Developed a deep neural network based multi-domain traffic predictor and a cognitive routing and spectrum assignment algorithm to realize knowledge-based autonomous traffic engineering in multi-domain networks Implemented an optical signal-to-noise ratio estimator and traffic predictor with Google’s Tensor flow and assessed their performance using experimental and synthetic data Demonstrated the benefits of the proposed cognitive schemes with experiments ona two-domain elastic optical network testbed and evaluations on a six-domain simulation framework Built a two-domain software-defined networking control plane testbed using the ONOS platform and demonstrated the workflow of broker and domain manager cooperation, including hierarchical performance monitoring, topology abstraction and cognitive resource allocation. Designed self-learning cognitive service provisioning schemes using advanced machine learning technologies: Designed a self-taught anomaly detection framework for optical networks, including an unsupervised data clustering module for pattern recognition, a supervised data regression and classification module for online anomaly detection, and the system operation principle Experimentally validated the effectiveness of the self-taught anomaly detection framework with various failure/anomaly scenarios. Designed a self-learning autonomic routing, modulation and spectrum assignment (RMSA) provisioning framework for elastic optical networks with deep reinforcement learning. Designed effective modeling and training mechanisms for the self-learning RMSA framework Conducted extensive numerical simulations with various traffic patterns and topologies to verify the advantage of the self-learning RMSA framework.

42 ENGINEERING↗

Cobalt-Free Cathodes for Next Generation Li-Ion Batteries

In this U.S. Department of Energy sponsored project Nexceris, in collaboration with project partners; The Ohio State University and Navitas Advanced Systems have advanced the technical maturity of a non-cobalt containing cathode for next-generation Li-ion batteries. The cathode is based on the lithium manganese nickel-titanium oxide, LiNi 0.5 Mn 1.5 TiO 4 (LNMTO) high voltage spinel. To address limitations with poor cycle and calendar life an microstucturally hierarchical LNMO/LNMTO core-shell cathode powder has been developed that enables the formation of a solid-electrolyte interface that effectively passivates the cathode surface. The microstructural enhancements of the cathode material focus on preferentially enriching the surface with titanium. In parallel, new, optimized binder and electrolyte chemistries have been incorporated to address degradation mechanisms associated with high-voltage systems. Single-layer pouch cell and large-format 2-Ah cell testing have shown that an optimized LNMO/LNMTO core-shell powder significantly improves initial cell capacity and cycle life compared to homogeneous LNMO powder. To support development and the fabrication of 2-Ah cells a novel Hybrid Alternative Wet-Chemical Synthesis (HAWCS) process have been developed. This low-cost, synthesis approach enables the excellent compositional and particle morphology control achieved with co-precipitation without the strict process controls and associated expensive process equipment.

25 ENERGY STORAGE↗

PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Finding relevant chemicals in the vast (known) chemical space is a major challenge for environmental and exposomics studies leveraging nontarget high resolution mass spectrometry (NT-HRMS) methods. Chemical databases now contain hundreds of millions of chemicals, yet many are not relevant. This article details an extensive collaborative, open science effort to provide a dynamic collection of chemicals for environmental, metabolomics, and exposomics research, along with supporting information about their relevance to assist researchers in the interpretation of candidate hits. The PubChemLite for Exposomics collection is compiled from ten annotation categories within PubChem, enhanced with patent, literature and annotation counts, predicted partition coefficient (logP) values, as well as predicted collision cross section (CCS) values using CCSbase. Monthly versions are archived on Zenodo under a CC-BY license, supporting reproducible research, and a new interface has been developed, including historical trends of patent and literature data, for researchers to browse the collection. This article details how PubChemLite can support researchers in environmental and exposomics studies, describes efforts to increase the availability of experimental CCS values, and explores known limitations and potential for future developments. The data and code behind these efforts are openly available.

PubChem↗

Planning and Analyses Performed to Install Halden’s Advanced Control Room Concept in the Human Systems Simulation Laboratory

The United States (U.S.) Department of Energy (DOE) sponsors the Light Water Reactor Sustainability (LWRS) Program, which has the goal of sustaining U.S. nuclear assets through conducting high-quality, value-added research and development (R&D) that provides the technical bases to extend the operating life of commercial NPPs. One area in the LWRS program is the Plant Modernization pathway, which includes human factors R&D, human factors engineering (HFE), and ergonomics, conducts targeted R&D to address aging and reliability concerns with the legacy instrumentation and control (I&C) and related information systems in NPPs. LWRS program researchers have been conducting R&D that enables the modernization of the I&C technologies in NPP main control rooms and have authored numerous reports on those research activities. Interestingly, however, virtually all of the control room modernization activities that have been researched in collaboration with various U.S. utility partners has been on upgrades that are the first steps to position these legacy control rooms for further full nuclear plant modernization. So, while many nuclear utility owners and operators have taken the first steps toward the digitalization of the control room I&C, LWRS program researchers are not aware of what any utility’s end-state vision is for full control room modernization. Thus, the purpose of this LWRS R&D activity is to start developing an advanced control room interface concept for legacy NPPs and to demonstrate it in the Human Systems Simulation Laboratory (HSSL) at Idaho National Laboratory (INL) so that utility partners can see what a potential end state is for their control room upgrade activities. The end state shows what a fully modernized control room looks like and how it works, and is the result of HFE and I&C work to transition the existing control room and its concept of operations to a new advanced control room configuration. This report documents the planning and analyses performed to install an advanced control room concept in the HSSL. Future LWRS reports will document the process to set up the HSSL and the gPWR with the HSI developed in Halden, and then document how LWRS program researchers at INL and Halden are supporting the capability to conduct future studies by creating additional HSIs that support control room modernization.

99 GENERAL AND MISCELLANEOUS↗

Development of a Fleet-Level Human Factors Engineering Program to Support the Digital Modernization of Multiple Turbine Control Systems

A number of years ago, Duke Energy and the United States (U.S.) Department of Energy (DOE) entered into a collaboration to support Duke’s digital upgrade activities for the main control rooms at three of their commercial nuclear power stations. The collaboration specifically focused on the human factors engineering (HFE) aspects of Duke’s plans to upgrade the legacy turbine control systems (TCS) at their Brunswick, Robinson, and Harris plants. This TSC upgrade involved installing a common digital control system (DCS), or distributed instrumentation and control (I&C) system platform, which multiple digital plant control systems can be integrated onto as the control rooms are modernized over time. Given the breadth and depth of the scope of this upgrade, DOE researchers at Idaho National Laboratory (INL) with expertise in human factors collaborated with Duke throughout the entire HFE life cycle to help ensure the upgrade was performed in a manner consistent with regulatory human factors review criteria, such as the U.S. Nuclear Regulatory Commission’s (NRC) Human Factors Engineering Program Review Model (NUREG 0711, 2012). This paper describes the HFE researchers performed through the early and middle phases of these TCS upgrades. Specific HFE activities include: 1) the development of a human factors program management plan, 2) performing an operational experience review, 3) evaluating the design human system interface while it was still in the early stages of development, and 4) developing a framework to help map these HFE activities to NUREG-0711 to help understand and catalog the value of different types and phases of human performance data collection. These four HFE activities are described in more detail below.

99 GENERAL AND MISCELLANEOUS↗

A Statistical Testing Approach for Quantifying Software Reliability; Application to an Example System

The U.S. Nuclear Regulatory Commission (NRC) encourages the use of probabilistic risk assessment (PRA) technology in all regulatory matters, to the extent supported by the state-of-the-art in PRA methods and data. Although much has been accomplished in the area of risk-informed regulation, risk assessment for digital systems has not been fully developed. The NRC established a plan for research on digital systems to identify and develop methods, analytical tools, and regulatory guidance for (1) including models of digital systems in the PRA's of nuclear power plants (NPPs), and, (2) incorporating digital systems in the NRC's risk-informed licensing and oversight activities. Under NRC's sponsorship, Brookhaven National Laboratory (BNL) explored approaches for addressing the failures of digital instrumentation and control (I and C) systems in the current NPP PRA framework. Specific areas investigated included PRA modeling digital hardware , development of a philosophical basis for defining software failure , and identification of desirable attributes of quantitative software reliability methods . Based on the earlier research, statistical testing is considered a promising method for quantifying software reliability. It is widely recognized that software failures are due to the triggering of pre-existing defects by the software's operational environment. Software defects can arise from errors made in user requirements or coding errors introduced during the developmental process. The software's operational environment includes factors such as the time history of digital system inputs, communication interfaces, the internal state of the digital system, and external conditions. Thus, software reliability is a function of both the number of pre-existing defects and the presence of a triggering condition caused by the manner in which the software is used. In this paper, we describe a statistical software-testing approach for quantifying software reliability and applied it to the loop-operating control system (LOCS) of an experimental loop of the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). The work involved collaboration between BNL and INL. The objectives of the study include: (1) Development of a statistical testing approach for estimating software failure probability on demand, the results of which are suitable for including in a probabilistic risk assessment (PRA); and, (2) Application of the approach to the LOCS to estimate its failure probability, and obtain insights into the feasibility, practicality, and usefulness of the estimation in models of digital systems for inclusion in nuclear power plants' PRAs. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Holography, Gravity and Condensed Matter

Over the five years of funding from this grant, I produced 26 publications. These include a book-long monograph on "Holographic Quantum Matter" that is currently in press with MIT press. The remainder were mostly published in Physical Review Letters, the Journal of High Energy Physics, Nature Physics, Classical and Quantum Gravity and Physical Review B. Over this period, the field of holography applied to condensed matter physics developed from a promising theoretical approach to a mature conceptual and practical edifice, whose ideas were realized in experiments. My own work played a central role in this development. In particular, in the final year of this grant, I co-authored two experimental papers in which ideas that I had developed in earlier years were shown to usefully describe transport in strongly correlated materials — these papers were published in Science and in the Proceedings of the National Academy of Sciences (obviously my contribution to these papers was theoretical). My theoretical work in this period developed several new directions of research that have proven to be influential. These include (i) The construction of highly inhomogeneous black hole event horizons, realizing disordered fixed points and describing new regimes of classical gravity, (ii) The conjecture of a bound on diffusivities that could underpin transport in strongly interacting media — an idea which may be proven in the near future and has turned out to be intimately connected to studies of quantum chaos in black holes and strongly correlated media, (iii) The characterization of new forms of hydrodynamic transport, e.g. with phase-disordered order parameters. These studies pertain to key open questions in our understanding of how non-quasiparticle, intrinsically strongly interacting systems can behave. In addition to the interface between holography and strongly interacting condensed matter systems, I made several advances on understanding the role of entanglement in quantum gravity. These included the first computation of holographic entanglement beyond the bulk classical limit as well understanding short distance entanglement in the emergent spacetime of the c=1 matrix quantum mechanics. The objective here is ultimately to understanding how a priori non-local degrees of freedom can re-arrange themselves quantum mechanically to support emergent local dynamics. Much of work funded by this grant involved collaboration with postdocs and graduate students, several of which were directly funded by the grant. These students have now successfully graduated to postdoctoral positions and in one case to high tech industry. The ideas developed in this work have directly fed into my current research in which I am aiming to prove fundamental bounds on entropy production and transport from quantum mechanics and statistical physics. As often, as with much of my previous work, black hole physics can be an inspiration for extreme dynamics such as fundamental bounds, but ultimately one hopes to prove them using more general tools of quantum field theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive complex nanocomposite alloys for burning plasma-material interface tunability (Final Report)

The focus of this program is discovery and development of novel self-healing and adaptive materials for the PMI (plasma-material interface) envisioned for future plasma-burning extreme environments in thermonuclear fusion reactors that can provide enhanced radiation-tolerance or resistance. This program was conceived and stems from the PI’s DOE Early Career Award work on harnessing nanotechnology and mesoscale materials design in refractory metals to address gaps in PMI research. These gaps pertain to the lack of understanding of multi-scale interactions at the plasma-material interface and the development of novel material interfaces that can be designed to adapt to extreme fusion reactor conditions. The final report is separated into two primary sections: The first section consists of the program’s first two years (FY16-FY17) performance period. The second section consists of FY18 to FY19 period, where the FY19 period was a supplemental addition to support the completion of a PhD thesis and continuation of another. This work consists of an excellent team consisting of a co-PI, one postdoctoral researcher, two graduate students, two undergraduate students and collaborators both domestic and abroad.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗

Electric Vehicle Charging Demand in the Chicago Metropolitan Area through 2030

This report outlines the collaborative efforts between Argonne National Laboratory and Exelon in advancing the Agent-Based Transportation Energy Analysis Model (ATEAM). Aligning with ComEd’s beneficial electrification plan, this study developed eight scenarios to access the temporal and spatial distribution of charging load and demand stemming from the widespread adoption of battery electric vehicles (BEV) adoption, augmented public charging infrastructure deployment, and increased multi-unit dwelling (MUD) charging availability. Enhancements to the ATEAM model encompassed the simulation of multiple days of travel behavior, estimation of total public charging infrastructure needs, user interface refinements, and output tracking at both vehicle and charging station levels. The total electricity consumption for residential and public charging to support over 800,000 BEVs in Chicago in 2029 is projected at approximately 10.2 GWh. Enhanced MUD home charging accessibility (70%) amplifies the home charging load in the study area by 1.5% compared to the baseline scenario (10%). The widespread adoption of BEVs reduces peak charging loads, owing to their inclusion across households with diverse income levels, thus fostering a more dispersed charging activity pattern. However, widespread BEV adoption increases the peak home charging load in areas with lower median household incomes, reflecting a higher BEV concentration in these locales and, subsequently, heightened peak charging demands. In the Widespread BEV adoption scenario, fewer census tracts exhibit elevated peak loads for combined home and public charging, indicating a more even distribution of charging demand across the study area. Predominantly, peak loads for combined charging—both home and public— occur between 2 p.m. and 10 p.m. across all scenarios, encompassing the majority of census tracts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Casing Annulus Monitoring of CO 2 Injection Using Wireless Autonomous Distributed Sensor Networks

Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.

47 OTHER INSTRUMENTATION↗

2024 Electric Vehicles at Scale Semiannual Stakeholder Meeting

The U.S. Department of Energy (DOE) Electric Vehicles at Scale Lab Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. This network will be critical to support tens of millions of light-, medium-, and heavy-duty EVs on American roads by 2030. The EVs@Scale Lab Consortium brings together national laboratories and key stakeholders to conduct infrastructure research and development (R&D) that advances innovations in, and sets unified standards for, high-power and wireless charging. The effort will also develop technologies to integrate vehicle charging with the power grid, and develop cybersecurity measures to protect drivers, vehicles, equipment, and the grid. The first hybrid EVs@Scale Lab Consortium Semiannual Stakeholder Meeting was held at ANL on September 27-28, 2023, to identify research, development, and deployment needs to accelerate technology development for electric vehicles at scale and explore opportunities for collaboration across government, academia, and industry.

advanced charging and grid interface technologies↗

XPRESS: eXascale PRogramming Environment and System Software

The XPRESS project is the research and development of a complete software architecture for Exascale computing. The four major R&D thrusts include: 1) an Exascale lightweight kernel operating system (LXK), based on the Kitten operating system (OS), to manage billion way hardware parallelism, management of faults and power, management of global virtual name space, and other features of future system architectures; 2) a runtime system (HPX-5), co-designed with LXK, based on the ParalleX execution model that supports dynamic resource management and task scheduling; 3) system interfaces for interoperability between the runtime system and both the OS and the runtime system (RIOS); 4) compilation strategies and systems to translate MPI and OpenMP legacy codes to a form that can be run with performance at least as good as a native code implementation. The software architecture development has been driven by performance evaluation of mini-applications developed at Department of Energy Co-Design Centers as well as ancillary in-house developed applications and benchmarks. Research on the ParalleX execution model has been driven by the development of formal semantics and model checkers for the execution model. The major components of the software architecture are: ParalleX execution model – guiding principles for co-design of components of the system stack with advances in locality management and task prioritization through introspection; HPX runtime system – support of application dynamic adaptive resource management, task scheduling, and introspective control policies; LXK operating system – lightweight kernel operating system for order-constant scalability and low/no noise to manage resources; RIOS – a realm of Exascale system operation unique in the XPRESS project that includes the relationship between the new generation of lightweight kernel operating systems and runtime system software; XPI advanced programming model – intermediate form and low-level (readable) programming interface reflecting the ParalleX model, providing a target for source-to- source high level parallel language translation, and supporting early direct programming experimentation and measurement; Performance models & metrics – providing parameters and their mutual sensitivities to guide co-design and quantify operational behavior; Legacy migration – ensuring seamless transition of legacy codes and programming methods to the future generation of ParalleX-based Exascale systems; . Experiments and evaluation – critical to determining degree of effectiveness and likelihood of ultimate success as well as guiding corrective design changes to achieve DOE objectives; and Applications – collaborations with Co-Design Centers and other mission critical codes. The exemplar implementation of the ParalleX execution model, HPX-5, has been released along with five fully ported applications (LULESH, HPCG, SSSP, WAMR, and DASHMM) and multiple microbenchmarks. Using these applications, the system architecture demonstrated dynamic load balancing through active migration, legacy code migration, and data-driven approaches to for graph-like applications. Crucially for Exascale and billion way parallelism, the needs and patterns of irregular applications in HPX-5 were addressed using local flow control rather than relying on globally synchronized data structures.

97 MATHEMATICS AND COMPUTING↗

Advancements in Development and Testing of Thermal Power Dispatch Simulators

Flexible plant operations and generation (FPOG) offer nuclear power plants (NPPs) the chance to leverage alternative, non-electric revenue streams while ensuring their continued role as reliable, clean, and constant sources of baseload electrical power. The excess thermal energy generated from NPPs during periods of low electricity demand can be channeled as raw materials to numerous industrial processes via a thermal power dispatch (TPD) system. Hydrogen production via high-temperature steam electrolysis (HTSE) is an optimal use case based on technical and economic feasibility. Researchers at Idaho National Laboratory (INL) have conducted previous works that developed and implemented TPD system models within the GSE Solutions Generic Pressurized Water Reactor (GPWR) simulator to support human-in-the-loop (HITL) scenario-based evaluations. The first part of this report documents modifications made to the GPWR TPD model and HMI from the previous iteration in line with a new Sargent and Lundy (S&L) TPD design with an automatic control system. The was done in collaboration with Westinghouse using their three-loop pressurizer water reactor (W3LPWR) simulator which contains an industrial grade automatic control system for the TPD. This was installed in the Human Systems Simulation Laboratory (HSSL) at INL. The second part of the report documents findings from an all-hands-on-deck integration and verification workshop that was conducted in the HSSL over several days. The research team comprised INL human factors and TPD experts, a nuclear engineer from GSE Solutions who implemented the revised TPD model for GPWR, the human-machine interface (HMI) prototyping and human factors team from the University of Idaho, and personnel with operations experience with pressurized water reactors. The workshop provided time and expertise to conduct the final activities to bring the operations, HMI, and simulator into a functional state. The goals of the integration and verification workshop were: 1. to install the revised GPWR TPD model into the HSSL 2. verify the TPD HMI prototype was functional 3. integrate the HTSE Simulink model to GPWR. 3. Issues were identified for resolution, but overall the workshop accomplished its goal to integrated and verify the majority of the intended functional. Future work will resolve the identified issues and use the integrated simulation to support an evaluation and demonstration in the next fiscal year.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Next Generation Sensor Development (CRADA Final Report)

B. Project Scope This was a collaborative effort between Lawrence Livermore National Security, LLC (LLNS), as manager and operator of Lawrence Livermore National Laboratory (LLNL) and The Federal Reserve Bank of San Francisco ("FRBSF" or "Participant"), to research and develop advanced processing techniques to measure the fitness and authenticity of U.S. currency. The FRBSF previously partnered with LLNL to evaluate end-of-life predictions, review sensor requirements, develop communications protocols, and perform thermal analysis. These Strategic Partnership Projects (SPP) included SPP No. L20960 - Federal Reserve Currency Technology Office Studies, SPP No. L15900 - Development of a Common Detector Interface (CDI 2.0) Specification and Hardware Simulators, and SPP No. L15610 - Limited Design Review of a Second-Generation E-Material Authentication Sensor (EMAS2).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗