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DOE OSTI2024

Computed entropy spectra for grain boundary segregation in polycrystals

Abstract Grain boundary solute segregation influences most bulk material properties, and understanding solute thermodynamics at grain boundaries is critical for engineering them. However, the vast grain boundary space in polycrystals is challenging to evaluate due to its size, especially for the intrinsically hard-to-compute segregation excess entropy. Here data science methods are used to generate a database of site-wise grain boundary segregation entropy spectra for 155 dilute binary alloys within the harmonic approximation. The spectral framework allows scale bridging between the calculated atomistic site-wise energy-entropy spectra and macroscopic segregation entropy estimates. The results affirm that macroscopic averaging is not sufficient: a spectral treatment of grain boundary segregation is needed to accurately model bulk temperature dependence of grain boundary solute segregation. The calculated spectral entropy database and thermodynamic framework can be applied for both understanding segregation experiments and alloy design exercises, paving the way to a finite-temperature grain boundary genome.

Chemistry↗

DOE OSTI2020

MPACT Verification With Magnox Reactor Neutronics Progression Problems

MPACT is a state-of-the-art core simulator designed to perform high-fidelity analysis using whole-core, three-dimensional, pin-resolved neutron transport calculations on modern parallel computing hardware. MPACT was originally developed to model light water reactors, and its capabilities are being extended to simulate gas-cooled, graphite-moderated cores such as Magnox reactors. To verify MPACT’s performance in this new application, the code is being formally benchmarked using representative problems. Progression problems are a series of example models that increase in complexity designed to test a code’s performance. The progression problems include both beginning-of-cycle and depletion calculations. Reference solutions for each progression problem have been generated using Serpent 2, a continuous-energy Monte Carlo reactor physics burnup calculation code.Using the neutron multiplication eigenvalue ke as a metric, MPACT’s performance is assessed on each of the progression problems. Initial results showed that MPACT’s multi-group cross section libraries, originally developed for pressurized water reactor problems, were not sufficient to accurately solve Magnox problems. MPACT’s improved performance on the progression problems is demonstrated using this new optimized cross section library.

Luciano, Nicholas↗

DOE OSTI2024

When in-memory computing meets spiking neural networks—A perspective on device-circuit-system-and-algorithm co-design

This review explores the intersection of bio-plausible artificial intelligence in the form of spiking neural networks (SNNs) with the analog in-memory computing (IMC) domain, highlighting their collective potential for low-power edge computing environments. Through detailed investigation at the device, circuit, and system levels, we highlight the pivotal synergies between SNNs and IMC architectures. Additionally, we emphasize the critical need for comprehensive system-level analyses, considering the inter-dependencies among algorithms, devices, circuit, and system parameters, crucial for optimal performance. An in-depth analysis leads to the identification of key system-level bottlenecks arising from device limitations, which can be addressed using SNN-specific algorithm–hardware co-design techniques. This review underscores the imperative for holistic device to system design-space co-exploration, highlighting the critical aspects of hardware and algorithm research endeavors for low-power neuromorphic solutions.

Physics↗

DOE OSTI2021

Analysis of Design Alternatives of Actively Cooled RF Window for MPEX

The Materials Plasma Exposure eXperiment (MPEX) has been designed as a linear plasma divertor simulator in order to address plasma material interaction (PMI) science for next-generation fusion devices. It will have the capability to test neutron irradiated samples with plasma fluxes of greater than 10 24 m -2 s -1 . It is expected to operate steady state for up to 10 6 s to consider PMI affects through reactor end of life. The conceptual design of MPEX was completed in 2019, with preliminary design having begun in 2020. The plasma source for MPEX is a helicon antenna, where the energized helical antenna sits outside of the vacuum in order to minimize impurities in the plasma. It is expected to receive up to 200 kW of continuous power, and so the antenna and the window must be actively cooled. The water-cooled copper antenna has been operated at full power on the Proto-MPEX device (which is a test facility to demonstrate the plasma source and heating systems). The water-cooled window, however, is a novel component that must meet numerous competing requirements. It requires a low dielectric loss to allow the Radio Frequency (RF) power to create the plasma within the vacuum boundary. It must be structurally robust to handle the significant heat flux from the plasma and any heat from dielectric coupling. It must be compatible with the coolant (preferably water). It requires a vacuum seal that minimizes impurities into the plasma and does not compromise the structural integrity of the window. Two window designs have been tested. Results from these tests, where temperatures are measured and heat fluxes inferred from infrared camera data, have been correlated with thermal-structural simulations. When these simulations are extrapolated to the full power steady-state heat fluxes that are expected in MPEX, the designs do not appear to have the necessary structural robustness. This study explores design alternatives for the MPEX helicon antenna window, presents analysis results for several of the alternatives, and shows a viable solution that satisfies the requirements for MPEX operation.

Tipton Jr, Joseph↗

DOE OSTI2020

Model Validation and Demonstration of a Hydrogen Fuel Cell Parcel Delivery Truck

With an emphasis on reducing fossil fuel consumption and emissions, major delivery service corporations have begun deploying and operating Class 6 battery electric delivery vans. Fuel cell hybrid delivery vans offer a zero emissions solution with extended range and route planning flexibility. This paper follows a prior publication [1] on the vehicle modeling and design and presents demonstration data and a validation of the prior modeling and design effort. Here, the validation exercise shows that the modeling tools predict performance and energy efficiency within 5% for most of the routes, while the demonstration data shows that in service operation fuel economy was over 14 km/kg of hydrogen gas. In addition, results from a range test showed the vehicle design and onboard hydrogen storage was able to surpass the design target range of 200 km.

08 HYDROGEN↗

DOE OSTI2022

Online State Estimation for Time-Varying Systems

The paper investigates the problem of estimating the state of a time-varying system with a linear measurement model; in particular, the paper considers the case where the number of measurements available can be smaller than the number of states. In lieu of a batch linear least-squares (LS) approach well-suited for static networks, where a sufficient number of measurements could be collected to obtain a full-rank design matrix the paper proposes an online algorithm to estimate the possibly time-varying state by processing measurements as and when available. The design of the algorithm hinges on a generalized LS cost augmented with a proximal-point-type regularization. With the solution of the regularized LS problem available in closed-form, the online algorithm is written as a linear dynamical system where the state is updated based on the previous estimate and based on the new available measurements. Conditions under which the algorithmic steps are in fact a contractive mapping are shown, and bounds on the estimation error are derived for different noise models. Numerical simulations are provided to corroborate the analytical findings.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Community-Based Transactive Coordination Mechanism for Enabling Grid Edge Systems

The changing landscape of the electricity industry, characterized by a surge in distributed energy resources (DERs) and proactive customers, necessitates practical solutions for coordinated operations especially at the distribution-level. This paper introduces a community-based transactive coordination mechanism designed to incentivize customers for providing localized and system-level services reflected through real-time prices. The work presents a bidding approach for communities with DERs, such as solar photovoltaic (PV) and battery energy storage systems (BESS), to formulate their price-responsiveness for retail energy coordination, emphasizing a community-centric model. By sending bidding curves to a third-party, the mechanism enables customers with DER assets to actively participate in localized coordination with the load serving entity (LSE), thereby supplementing each other’s and even the utilities needs through a shared energy economy. The proposed transactive mechanism is implemented leveraging a co-simulation framework that integrates a distribution grid simulator and Python-based agents for performance evaluation. Collaboration with a local utility to access real distribution feeder models and consumption profiles yields simulation results demonstrating the potential to reduce costs by 12\% for communities with DERs like PV and BESS.

Community-based coordination, grid-edge systems, R↗

DOE OSTI2024

High-Throughput Computing: Case Study of Medical Image Processing Applications

HPC is designed for large-scale simulations using monolithic codes of tightly coupled processes highly optimized to deliver decreased time to solution. Medical image processing is not a traditional field of HPC. Similar to AI applications, medical image processing parses large datasets, typically multiple times, to support a variety of studies for classification, diagnosis or monitoring purposes. The convergence of AI, HPC and Big Data encouraged more fields using image processing to transition to HPC. However, not all applications benefit from the same optimizations. In this paper we focus on high throughput medical image processing applications that analyze a huge dataset of small MRI images and that require HPC systems to decrease the time of parsing the entire dataset and not individual MRIs. We show in this research the performance of running SLANT, an image processing application for a whole brain segmentation, on large-scale systems and highlight performance limitations. We present optimizations prioritizing throughput that exhibit a 3.5x speed-up on the Summit Supercomputer that can be used as a baseline for building a high-throughput execution framework for other HPC systems.

Predescu, Maria↗

DOE OSTI2020

Holistic Measurement Driven Resilience: Combining Operational Fault and Failure Measurements and Fault Injection for Quantifying Fault Detection, Propagation and Impact. Final report

For HPC systems to date, application resilience to faults and failures has been accomplished by the brute- force method of checkpoint/restart, which allows an application to make forward progress in the face of system and application faults, errors, and failures independent of root cause or end result. It has remained the primary resilience mechanism because we lack a way to identify faults and anticipate consequences early enough to take meaningful mitigating action. However, checkpoint/restart implementations put a tremendous burden on system resources and on the applications themselves and is becoming less feasible at scale. Because we have not yet operated at scales at which checkpoint/restart fails to provide forward progress, despite increasing costs, vendors have had little motivation to provide the instrumentation necessary for early identification of faults and failures. However, as we move from petascale to exascale, component mean time to failure (MTTF) will render the existing techniques ineffectual and/or too expensive. Furthermore, fault recovery mechanisms such as failover and/or error correction introduce performance inconsistency. Instrumentation allowing early indication of problems and tools to enable use of such information by systems, operating systems, and applications offer an alternative, more scalable and less costly solution. In the HMDR project, we built on our experience and expertise developed and accumulated over years of research on design, monitoring, measurement, and assessment of resilient computing systems. Analysis of field data on the current and past generations of extreme-scale systems revealed several challenges that, if not addressed in increasingly larger and more complex systems, may hinder the effectiveness of future exascale computing systems. Specifically, i) file systems and interconnects in current-generation large-scale systems already operate at the margins of resiliency, including consistent performance, and may not scale to larger deployments; ii) automated, software-based failover mechanisms are frequently inadequate and can introduce wider failures, such that failures during recovery may lead to system/application failures, including system-wide outages; and iii) silent data corruption represents a critical fault mode and will require efficient detection mechanisms if next-generation applications are to take full advantage of exascale hardware. To address the above challenges, we assembled a team of world-renowned experts in resilient extreme- scale computing from the University of Illinois (Electrical and Computer Engineering, Computer Science, and NCSA), SNL, LANL, NERSC, and Cray. Our team includes representatives from centers that house many of the largest HPC resources in the world, both today and over the coming years. The team has a unique track record of research in i) system and application failure characterization based on the analysis of field data, ii) data-driven design of fault/error detection mechanisms, and iii) experimental characterization of system/application resiliency. The team includes system owners/operators who provide continuous data collection and access and ensure installation of appropriate analysis tools.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Status Report on ASME Code Development for Nonmetallic Core Components in 2020

The purpose of this report is to provide a status update on the progress and ongoing activities of the current ASME Boiler Pressure Vessel (BPV) Code Section III, Division 5, on nonmetallic core components and assemblies which includes the design rules for graphite and ceramic composite materials. Section III is concerned with the design and construction of nuclear reactor components and Division 5 focuses on high temperature reactors (HTR). The ASME Section III Committee’s function for nuclear items other than pressure-retaining components, is to establish rules of safety related to structural integrity. The term “construction” refers to the all-inclusive effort comprising of materials, design, fabrication, examination, inspection, testing, certification, and pressure relief. The Department of Energy (DOE) supports industry codes and standards development through focused research providing the technical basis for new or modified codes and standards and the participation of subject matter experts in codes and standards committees. The activities for the nonmetallic core components and assemblies committees are the pursuit of two working groups that meet quarterly during ASME BPV Code Week meetings. The two working groups are General Requirements for Graphite and Ceramic Composite Core Components and Assemblies (GR GCCCCA) and Nonmetallic Design and Materials (NDM). The rules on general requirements for nonmetallic core components are discussed in the articles of Subsection HA subpart B. Ceramic composites were recently incorporated within the rules, and the GR GCCCCA working group is now in the process of aligning the requirements with the subsections and articles of ASME BPV Code Section III NCA, the general requirements for Division 1 and 2 of the code. The NDM working group is concerned with the design rules for graphite and composite materials for core components and assemblies discussed in Subsection HH (Class SN Nonmetallic Core Components) subpart A and subpart B which reference graphite and composite materials respectively. The bulk of the progress and work is done within this working group. A significant undertaking, with discussion that started in 2015, is to gain endorsement of ASME Section III, Division 5, by the U.S. Nuclear Regulatory Commission (NRC). In June 2018, ASME formally recommended endorsement to the NRC. The NRC has since initiated the endorsement review process, which is to be concluded early in 2021. ASME task groups on metallic structures and components, as well as non-metallic core support structures, have been formed to define potential pathways and schedules for NRC endorsement of Division 5. NRC determined to perform a review on the 2017 edition of Section III Division 5 as a baseline. As a result, the use of graphite as nonmetallic core components formed part of the review, but it excluded composite materials (which were first introduced in the 2019 edition). This report documents progress in FY 2020 directed toward ASME’s efforts to develop design codes for graphite and composites. Progress includes a major code review by NRC, the first code enquiry, and its solution, an overhaul of the treatment of Weibull Statistics, and the addition of Nonmandatory Appendices to the composites code relating to carbon-carbon composite materials.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Empowering Energy Efficiency in Existing Big-Box Retail/Grocery Stores (Final Optimization Report)

The Center for Sustainable Energy (CSE), in partnership with the National Renewable Energy Laboratory (NREL), TRC Energy Services, P2S Engineering Inc, Walmart, and five innovative technology providers, are to demonstrate the impact of an integrated suite of pre-commercial energy efficiency (EE) technologies in a large, existing, retail building located within an inland disadvantaged community. Proposed technology packages include three categories of advanced EE solutions: heating, ventilating, air-conditioning, and refrigerating (HVAC/R); lighting; and integrated system and building level controls. The project is designed to impact Walmart’s future store specifications, which can be replicated and deployed in other buildings across California with similar end-use and system characteristics. The following lists the technologies considered for this project: DualCool (HVAC evaporative cooling); Software Motor Company (SMC) (HVAC and refrigeration fan motor); I2S: DC LED lighting; LocBit: building energy management and optimization; Saya: water monitoring.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

A Quantum Analog Coprocessor for Correlated Electron Systems Simulation

Analog quantum simulation is an approach for studying physical systems that might otherwise be computationally intractable to simulate on classical high-performance computing (HPC) systems. The key idea behind analog quantum simulation is the realization of a physical system with a low-energy effective Hamiltonian that is the same as the low-energy effective Hamiltonian of some target system to be studied. Purpose-built nanoelectronic devices are a natural candidate for implementing the analog quantum simulation of strongly correlated materials that are otherwise challenging to study using classical HPC systems. However, realizing devices that are sufficiently large to study the properties of a non-trivial material system (e.g., those described by a Fermi-Hubbard model) will eventually require the fabrication, control, and measurement of at least 0(10) quantum dots, or other engineered quantum impurities. As a step toward large-scale analog or digital quantum simulation platforms based on nanoelectronic devices, we propose a new approach to analog quantum simulation that makes use of the large Hilbert space dimension of the electronic baths that are used to adjust the occupancy of one or a few engineered quantum impurities. This approach to analog quantum simulation allows us to study a wide array of quantum impurity models. We can further augment the computational power of such an approach by combining it with a classical computer to facilitate dynamical mean-field theory (DMFT) calculations. DMFT replaces the solution of a lattice impurity problem with the solution of a family of localized impurity problems with bath couplings that are adjusted to satisfy a self-consistency condition between the two models. In DMFT, the computationally challenging task is the high-accuracy solution of an instance of a quantum impurity model that is determined self-consistently in coordination with a mean-field calculation. We propose using one or a few engineered quantum impurities with adjustable couplings to baths to realize an analog quantum coprocessor that effects the solution of such a model through measurements of a physical quantum impurity, operating in coordination with a classical computer to achieve a self-consistent solution to a DMFT calculation. We focus on implementation details relevant to a number of technologies for which Sandia has design, fabrication, and measurement expertise. The primary technical advances outlined in this report concern the development of a supporting modeling capability. As with all analog quantum simulation platforms, the successful design and operation of individual devices depends critically on one's ability to predict the effective low-energy Hamiltonian governing its dynamics Our project has made this possible and lays the foundation for future experimental implementations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Exceedance Response Action (ERA) Level 2 (Technical Report)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Scorpius Injector Solenoid Magnet Alignment and Characterization

The Scorpius project consists of a linear induction accelerator (LIA) that will be built in the coming few years at the Nevada test site. Large radius solenoid magnets are used to focus and transport the electron beam through the injector of Scorpius. Typically, solenoid magnets are wrapped directly around the beam pipe. They have an inner radius of about 8 cm and weight approximately 170 lbs. The magnets for the Scorpius injector are much larger, the largest of which extends to an inner radius of 45 cm with a weight of 709 lbs. In addition, the magnet measurement effort is typically time-consuming, taking several months to complete. With 5 different designs of 52 solenoid magnets to measure in under a year, this is a challenging undertaking that requires a systems solution. Due to the size, variability, and quantity of solenoid magnets, as well as the compressed schedule, the process of measuring the solenoid magnets before integrating them into their respective assemblies and shipping them to Nevada is a challenging problem. There is a need for the injector magnets to be characterized and aligned in preparation for the commissioning of Scorpius. This will ensure that the injector magnet installation meets requirements.

42 ENGINEERING↗

DOE OSTI2023

Exceedance Response Action (ERA) Level 2 Technical Report Update

The Sandia National Laboratories, California (SNL/CA) site comprises approximately 410 acres and is located in the eastern portion of Livermore, Alameda County, California. The property is owned by the United States Department of Energy/National Nuclear Security Administration (DOE/NNSA) and is being managed and operated by National Technology & Engineering Solutions of Sandia, LLC (NTESS). Operations at the SNL/CA facility consist of DOE statutory responsibilities for nuclear weapon research and design, development of energy technologies, and basic scientific research. Specific industrial activities occur in discrete buildings and include electroplating or anodizing, machine shop, permitted hazardous waste treatment, storage and disposal facility (TSDF), and a scrap yard. This report provides an update to the ERA Level 2 Technical Report Update previously submitted in June 2022 (2022 ERA L2 Technical Report Update) for iron, aluminum, and pH. In accordance with the California’s General Permit for Discharges of Storm Water Associated with Industrial Activities (IGP) Section XII.D.3.c, an ERA Level 2 Technical Report update is to be submitted with the annual report when a facility utilizing an Industrial Activity Best Management Practice (BMP) Demonstration (IABMPD) experiences additional exceedances of the numeric action levels.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Microgrid Design Toolkit (MDT) User Guide: Software v1.4

The MDT is a decision support software that can provide the information needed to identify optimal microgrid designs in the early stages of the design process. MDT searches the trade space of alternative microgrid designs in terms of user-defined objectives, such as performance, reliability, and cost. It produces a Pareto frontier of solutions embodying the efficient tradeoffs amongst multiple user-defined objectives.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Schema Elements for Granta Annual Report: FY2024

Granta: Materials Intelligence (Granta: MI) is a commercial database software distributed by Ansys, Inc. that is utilized by the Nuclear Security Enterprise (NSE) to organize and store relevant materials data. Lack of standard and well-documented database schema is the primary obstacle to an NSE materials data management solution, so the objective of this project is to create and document such a schema. In FY21, an approach for designing, documenting, and managing a standard database schema was described based on the creation of schema elements (collections of attributes used to describe particular aspects of the data) to be used as building blocks for creating various database tables without duplication. In FY22, these methods were applied through a multi-site collaboration to create and document the schema elements necessary to build a thermogravimetric analysis (TGA) testing table. In FY23 the schema was expanded to include elements for a differential scanning calorimetry (DSC) table, along with schema for supporting metadata tables including Instruments, Projects, Documents, and Testing Series. In FY24 the following progress was made, again through multi-site collaboration: • The existing schema elements were modified to accommodate thermomechanical analysis (TMA) data, and a table, Test Data: TMA, was created for managing TMA data. • The elements necessary for the following additive manufacturing (AM) data tables (directed at data specific to selective laser sintering AM technology) were created: • AM Builds • AM Processes • AM Part Designs • Built AM Parts • AM Feedstock Materials • AM Feedstock Material Batches • The elements necessary for creating a Calibrated Material Models table were created, and the Calibrated Material Models table was created. In FY25 the existing schema will be deployed on the production enterprise Granta instance on the enterprise secure network. Schema elements will be appended, and new elements created as necessary, to allow the creation of tables specifically to support materials testing, AM process development, and design and analysis for modernization programs.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Atomic Layer Deposition (ALD) of Metal and Metal Oxide Films: A Surface Science Study (Final Report)

This is the final report for this project. The long-term objective of our project is to develop a general molecular-level picture of the surface chemistry associated with ALD processes. Our central hypothesis is that the chemistry of ALD precursors can differ significantly from that seen in solution. Awareness of such differences should provide general guidelines on what to watch for when synthesizing new ALD precursors and designing and optimizing new ALD processes, especially in terms of minimizing the incorporation of impurities in the growing films and of carrying out depositions under mild pressure and temperature conditions. The main objective of our research project has been to advance the fundamental knowledge of the surface chemistry of ALD precursors needed for the design and optimization of film deposition processes. A modern surface-science approach has been implemented to both elucidate the mechanism of the reactions of the precursors on the surface and characterize the composition and morphology of the growing films.

36 MATERIALS SCIENCE↗