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DOE OSTI2023

DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets

Graph neural networks (GNNs) are a class of Deep Learning models used in designing atomistic materials for effective screening of large chemical spaces. To ensure robust prediction, GNN models must be trained on large volumes of atomistic data on leadership class supercomputers. Even with the advent of modern architectures that consist of multiple storage layers that include node-local NVMe devices in addition to device memory for caching large datasets, extreme-scale model training faces I/O challenges at scale.We present DDStore, an in-memory distributed data store designed for GNN training on large-scale graph data. DDStore provides a hierarchical, distributed, data caching technique that combines data chunking, replication, low-latency random access, and high throughput communication. DDStore achieves near-linear scaling for training a GNN model using up to 1000 GPUs on the Summit and Perlmutter supercomputers, and reaches up to a 6.15x reduction in GNN training time compared to state-of-the-art methodologies.

Choi, Jong Youl↗

DOE OSTI2021

Cavern Leaching Monitoring CY18 And CY19

The U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system run by the U.S. Department of Energy (DOE). The reserve consists of 60 active storage caverns spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR began executing U.S. congressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 MMB, requires raw water to be used instead of saturated brine for oil withdrawals such as for sales. All sales will produce leaching within the caverns used for oil delivery. Thirty-six caverns had a combined total of over 29 MMB of water injected from CY18-CY19 for mandatory sales. Leaching effects were monitored in these caverns to understand how the sales operations may impact the long-term integrity of the caverns. While frequent sonars are the best way to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An intermediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code (SANSMIC). The results indicate that leaching induced features are not of concern in the majority of the caverns, 32 of 36. Four caverns, BH-107, BH-108, BH-114 and WH-114 have features that may grow with additional leaching and should be monitored as leaching continues in those caverns. Six caverns had post sale sonars which were compared with SANSMIC results. SANSMIC was able to capture the leaching well. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results suggest SANSMIC is a useful tool for monitoring changes in cavern shape due to leaching effects related to sales and exchanges.

02 PETROLEUM↗

DOE OSTI2021

Strong and Efficient Consistency with Consistency-aware Durability

We introduce consistency-aware durability or C ad , a new approach to durability in distributed storage that enables strong consistency while delivering high performance. We demonstrate the efficacy of this approach by designing cross-client monotonic reads , a novel and strong consistency property that provides monotonic reads across failures and sessions in leader-based systems; such a property can be particularly beneficial in geo-distributed and edge-computing scenarios. We build O rca , a modified version of ZooKeeper that implements C ad and cross-client monotonic reads. We experimentally show that O rca provides strong consistency while closely matching the performance of weakly consistent ZooKeeper. Compared to strongly consistent ZooKeeper, O rca provides significantly higher throughput (1.8--3.3×) and notably reduces latency, sometimes by an order of magnitude in geo-distributed settings. We also implement C ad in Redis and show that the performance benefits are similar to that of C ad ’s implementation in ZooKeeper.

Computer Science↗

DOE OSTI2021

Numerical and experimental evaluation of mechanical performance of the multifunctional energy storage composites

This work presents numerical simulation methods to model the mechanical behavior of the multifunctional energy storage composites (MESCs), which consist of a stack of multiple thin battery layers reinforced with through-the-hole polymer rivets and embedded inside carbon fiber composite laminates. MESC has been demonstrated through earlier experiments on its exceptional behavior as a structural element as well as a battery. However, the inherent complex infrastructure of the MESC design has created significant challenges in simulation and modeling. A novel homogenization technique was adopted to characterize the multi-layer properties of battery material using physics-based constitutive equations combined with nonlinear deformation theories to handle the interface between the battery layers. Second, mechanical damage and failure modes among battery materials, polymer reinforcements, and carbon fiber-polymer interfaces were characterized through appropriate models and experiments. The model of MESCs has been implemented in a commercial finite element code in ABAQUS. A comparison of structural response and failure modes from numerical simulations and experimental tests are presented. The results of the study showed that the predictions of elastic and damage responses of MESCs at various loading conditions agreed well with the experimental data. © 2021

Materials Science↗

DOE OSTI2021

SIRIUS: Science-Driven Data Management for Multi-Tiered Storage

The data sets being generated by large applications on very large-scale systems are increasing in both size and complexity. At the same time, there are new ways available to store and access these data sets. The goal in this project is to develop software that applications can use to make use of new and existing storage technologies in more sophisticated ways. One challenge in scientific data management is handling ‘hot’ vs ‘cold’ data. Data that is hot is data that is needed (or will be needed soon) in order for the program to continue progressing, while cold data is either output (and so will not be need further during the life of the program) or will not be needed until significantly later in the program’s run. Hot data should be stored in a way that allows fast access. On most systems, economic factors lead to an inverse relationship between storage performance and storage capacity and so fast access storage is limited. This makes it important to correctly place hot and cold data and avoid cold data unnecessarily consuming precious resources. In this reporting period, we addressed this challenge in various ways and at various levels. Data management frameworks offer only limited control to applications in how data is stored. We have added software capabilities for seamlessly moving data between layers of the storage technology using promote and demote functions to existing software frameworks. This gives direct control to applications in deciding what priority data receives. Additionally, we integrated different storage layer management frameworks in order to allow data to be exchanged and moved between storage layers in a consistent way across the application. Further, applications are not always able to directly decide what storage level makes sense for a given piece of data without an understanding of the underlying storage technologies. Data storage frameworks are often positioned to make these sorts of decisions in service of the application. We have added machine-learning based capabilities to data staging frameworks in order to make intelligent decisions about where data should be stored given learning about patterns in previous usage of similar data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Stretchable electrochemical energy storage devices

The increasingly intimate contact between electronics and the human body necessitates the development of stretchable energy storage devices that can conform and adapt to the skin. Therefore, the development of stretchable batteries and supercapacitors has received significant attention in recent years. This review provides an overview of the general operating principles of batteries and supercapacitors and the requirements to make these devices stretchable. The following sections provide an in-depth analysis of different strategies to convert the conventionally rigid electrochemical energy storage materials into stretchable form factors. Namely, the strategies of strain engineering, rigid island geometry, fiber-like geometry, and intrinsic stretchability are discussed. A wide range of materials are covered for each strategy, including polymers, metals, and ceramics. By comparing the achieved electrochemical performance and strain capability of these different materials strategies, we allow for a side-by-side comparison of the most promising strategies for enabling stretchable electrochemical energy storage. The final section consists of an outlook for future developments and challenges for stretchable supercapacitors and batteries.

25 ENERGY STORAGE↗

DOE OSTI2026

Powdermet CRADA for VELOCITI Voucher (CRADA Final Report)

NLR shall develop a model of an electric thermal energy storage (ETES) system in the System Advisor Model (SAM) framework that uses a salt and particle slurry developed by PowderMet as the thermal energy storage medium. The ETES shall consist of a recuperated sCO 2 Brayton cycle using 2-tank indirect thermal energy storage and an electric heater for heat input. The salt slurry uses chloride salt and operates at a maximum temperature of 500-720°C. The ETES uses dry air cooling. The salt slurry will be modeled as a sensible heat storage medium and as a latent heat storage medium. NLR will use the model to do parametric analysis of the factors affecting the performance (ex., round trip efficiency) of the ETES system. NLR will work with PowderMet to estimate the costs of system components and total system costs, with the levelized cost of electricity (LCOE) as the primary cost metric.

14 SOLAR ENERGY↗

DOE OSTI2020

CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) User’s Manual

This user’s manual guides the use of the National Energy Technology Laboratory’s (NETL) CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) tool, which was developed to aid users screening geologic formations for prospective CO₂ storage resources. This manual is specific to the CO₂-SCREEN 4.0 version which is based in Python. CO₂-SCREEN applies U.S. Department of Energy (DOE) methods and equations for estimating prospective CO₂ storage resources for saline formations, shale formations, and residual oil zones (ROZ). CO₂-SCREEN was developed to be substantive and user-friendly and provide a consistent method for calculating prospective CO₂ storage resources. CO₂-SCREEN uses a Java based graphical user interface for data inputs and uses Python to calculate prospective CO₂ storage resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Analysis and Control of a Three-Port Converter with High-Frequency AC Link for Hybrid Unmanned/Autonomous Aerial Vehicles

In this study, a three-port resonant converter with a high-frequency isolation link for hybrid unmanned/autonomous aerial vehicle (UAV/AAV) applications is analyzed. The rectified engine-generator set output supplies the first input ports while the other is connected to a battery energy storage system. Input ports consist of half-bridge high-frequency inverters, whereas output port utilizes a semi-bridgeless active rectifier. This rectifier is formed by replacing rectifier low-side diodes with active switching devices. A phase-shift duty-cycle control is implemented for switching signals to regulate the power share and flow between ports. The proposed control system implemented achieves zero voltage switching (ZVS), reduces switching losses, and minimum current flow optimization ensures regulation in a wide range of output power. Compared to the existing bidirectional pulse width modulation (PWM) converters, the proposed system decreases the number of power conversion stages and provides centralized control without needing communications between the ports. The proposed control technique operating in closed-loop control achieves the power flow between ports under various load conditions. Finally, theoretical analysis demonstrates the proposed converter’s viability and laboratory experimental validations at 500 W full power.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

CO2-SCREEN

CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) is a tool which was developed by the Department of Energy’s National Energy Technology Laboratory (DOE-NETL) to screen saline formations for prospective CO2 storage resources. CO2-SCREEN applies U.S. DOE methods and equations for estimating prospective CO2 storage resources for saline formations. This provides a dependable method for calculating prospective CO2 storage resources which allows for consistent comparison of results between different research efforts. CO2-SCREEN latest version (v5.0) is a python application that utilizes a Java front end user interface. The 3.0 version consists of an Excel spreadsheet containing geologic inputs and outputs, linked to a GoldSim Player model that calculates prospective CO2 storage resources via Monte Carlo simulation. https://www.youtube.com/watch?v=lhakk-HYfOI

CO2 Storage Resource,Prospective Storage,Screening↗

DOE OSTI2023

Verification of Spent Fuel Inside Dry Storage Casks by Cask Top Fast Neutron Mapping (FY2023 Mid-Year Report)

This project is developing a prototype scanner array verification system for detection of missing fuel assemblies in spent-fuel storage casks. The prototype consists of six fast-neutron scintillator detectors mounted to a linear actuator frame that is placed on the top of a spent fuel cask to scan across all fuel assembly positions. The scanner array was assembled and tested at LLNL in FY2022. A field test schedule has been requested at the Idaho National Laboratory (INL) Cask Farm site for FY2023. Note that the Cask Farm contractor determines this scheduling and not INL directly. Further system automation will be designed and implemented with the goal of obtaining a level of system operation that meets IAEA needs. This includes integration of the scanner array and data-acquisition control software into a single interface for operator use. In addition, commercial operators and the IAEA may have special requirements for portability, shipping, lifting, and installation. Prior to the Field Test at INL, the system will be operated at LLNL to exercise lifting procedure and linear actuators, monitor stability of detector energy and pulse-shape discrimination calibration, and test system software integration efforts. Following the Field Test, we will present results and discuss the technology with the IAEA. We will incorporate additional improvements to the system based on lessons learned from the field test and feedback from the IAEA. If successful, the technology can be transferred to the IAEA or other stakeholders for assessment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

FY2024 Mid-Year Report: Verification of Spent Fuel Inside Dry Storage Casks by Cask Top Fast Neutron Mapping

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps

In situ computation of Lagrangian flow maps to enable post hoc time-varying vector field analysis has recently become an active area of research. However, the current literature is largely limited to theoretical settings and lacks a solution to address scalability of the technique in distributed memory. To improve scalability, we propose and evaluate the benefits and limitations of a simple, yet novel, performance optimization. Our proposed optimization is a communication-free model resulting in local Lagrangian flow maps, requiring no message passing or synchronization between processes, intrinsically improving scalability, and thereby reducing overall execution time and alleviating the encumbrance placed on simulation codes from communication overheads. To evaluate our approach, we computed Lagrangian flow maps for four time-varying simulation vector fields and investigated how execution time and reconstruction accuracy are impacted by the number of GPUs per compute node, the total number of compute nodes, particles per rank, and storage intervals. Our study consisted of experiments computing Lagrangian flow maps with up to 67M particle trajectories over 500 cycles and used as many as 2048 GPUs across 512 compute nodes. In all, our study contributes an evaluation of a communication-free model as well as a scalability study of computing distributed Lagrangian flow maps at scale using in situ infrastructure on a modern supercomputer.

Sane, Sudhanshu↗

DOE OSTI2020

Commissioning plan for LCLS II 2 K cold box

Commissioning of the LCLS II cryogenic plant has been planned with respect to electrical and mechanical systems checkout, equipment cleanup, cool-down, and individual performance evaluation. This plant consists of warm and cold storage, helium compressors, 4.5 K and 2 K cold boxes, and all auxiliaries typical for helium refrigeration processes. The 2 K cold box, consisting of five cold compressors in series to produce the flow and pressures necessary for 2K operation, will be the last equipment installed and, along with an additional 10,000 L helium dewar, will allow the entire plant to be commissioned as a single entity. The pre-commissioning stages, commissioning plan for 2 K cold box without connecting to the LCLS II LINAC, additional test equipment needed to simulate the loads, all process studies and associated results are described herein.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development of Remote Cutting Tools for use at ATR - 20438

As a result of years of operations of the Advanced Test Reactor (ATR) at the Idaho National Lab (INL), the ATR canal has become congested due to the storage of materials including waste consisting of highly irradiated remote handled (RH) metals. In order to support its continuing nuclear mission the ATR requires canal space to support fuel storage and future core internal change out (CIC) components. INL staff determined that the canal must be cleaned out and waste removed to efficiently utilize the valuable canal floor space. It was determined that a methodology for processing, packaging, characterizing, and removing current and future irradiated hardware from the ATR canal is needed. Orano Federal Services (OFS) and its subcontractor Babcock Services Inc. (BSI) were selected to provide remote tooling in order to safely and efficiently size reduce the material currently stored in the ATR canal. INL developed detailed requirements that established the design and performance requirements for the tooling. Orano TN and BSI had recently successfully completed similar tasks in clearing highly activated materials from spent fuel pools and canals at commercial nuclear plants. That experience directly translated into a proven approach that could be used at the ATR thereby saving time and money and lowering risks. Based on BSI's demonstrated proficiency in the design and deployment of remote size reduction specialty tooling at comparable commercial facilities, Orano Federal Services was confident that a solution to INL's requirements could be delivered. The tooling had to be designed to be compatible with the operational requirements of the ATR canal as well as the functionality needed by the facility operators that will use the equipment. Some of the major design requirements and functions of the equipment included remote operations, capability to shear highly irradiated sections of aluminum and steel tubing, pipe, and components ranging in size from 0.6 cm to 16.5 cm diameter into 1.5 m -1.8 m lengths, utilizing buoyancy compensation to assist with underwater operations, and use commercially available existing technology and components as much as practical. The design team evaluated and selected commercially available equipment that could be modified to meet the design and performance specifications. In addition, a waste sizing table (WST) was designed and fabricated to further ensure the size reduction equipment would perform as expected and give the facility operators a stable and usable remote, underwater work platform. After successful development of the tooling, a mock up test and operator training was conducted to ensure the tooling performed as expected and met the requirements of INL. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

The fixed probe storage ring magnetometer for the Muon g-2 experiment at Fermi National Accelerator Laboratory

The goal of the FNAL E989 experiment is to measure the muon magnetic anomaly to unprecedented accuracy and precision at the Fermi National Accelerator Laboratory. To meet this goal, the time and space averaged magnetic environment in the muon storage volume must be known to better than 70 ppb. A new pulsed proton nuclear magnetic resonance (NMR) magnetometer was designed and built at the University of Washington, Seattle to track the temporal stability of the 1.45 T magnetic field in the muon storage ring at this precision. It consists of an array of 378 petroleum jelly based NMR probes that are embedded in the walls of muon storage ring vacuum chambers and custom electronics built with readily available modular radio frequency (RF) components. We give NMR probe construction details and describe the functions of the custom electronic subsystems. The excellent performance metrics of the magnetometer are discussed, where after 8 years of operation the median single shot resolution of the array of probes remains at 650 ppb.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Exploring the Future Energy Value of Long-Duration Energy Storage

Long-duration energy storage is commonly viewed as a key technology for providing flexibility to the grid and broader energy systems over a multidecadal time frame. However, prior work has typically used present-day grid infrastructures to characterize the relationship between the duration and arbitrage value of storage in electricity markets. This study leverages established National Renewable Energy Laboratory grid planning and operations tools, analysis, and data to execute a price-taker model of an energy storage system for several 8760 h price series representative of current and future contiguous United States grid infrastructures with varying shares of variable renewable energy (VRE). We find that the total value of energy storage typically increases with VRE shares, but any increase in the relative value of longer storage durations over time depends on the region and grid mix. Some regions see incremental value increasing notably, up to 20–40 h in 2050, while others do not. The negative effect of lower roundtrip efficiency on value is also found to be scenario-dependent, with the energy value in higher VRE scenarios being less sensitive to roundtrip efficiency and more supportive of longer storage durations. Long-duration storage value and deployment potential are a function of evolving electricity sector infrastructure, markets, and policy, making it critical to consistently revisit potential long-duration storage contributions to the grid.

14 SOLAR ENERGY↗

DOE OSTI2021

Injection data analysis using material balance time for CO 2 storage capacity estimation in deep closed saline aquifers

Estimating the ultimate storage capacity of deep saline aquifers is important to address the formation potential to store the envisioned large volumes of CO 2 . Injection data (i.e. injection rate, bottomhole pressure, and cumulative injected volume of CO 2 ) are routinely recorded during storage operations. These data contain valuable information on the subsurface (e.g. the reservoir pore volume and the formation storage capacity) that can be extracted. In this paper, we present a two-step graphical technique to infer the pore volume and the ultimate storage capacity of closed saline aquifers by analyzing the available injection data. First, the pore volume is inferred through adapting the concept of the material balance time. Material balance time is an approximate superposition time function developed to interpret production data from oil and gas wells operating at variable pressure/rate conditions during the boundary-dominated flow period. Using material balance techniques, the ultimate storage capacity is then estimated through linear extrapolation of the average pressure trend to the maximum allowable pressure the formation can withstand. The average pressure is not available in practice, but is can be obtained from the injection data. Two approaches are presented in this study to calculate the average pressure; namely the rigorous and the approximate approaches. Unlike the rigorous approach, the approximate approach does not require a prior knowledge of some reservoir properties (e.g. relative permeability, absolute permeability, formation porosity and thickness) to calculate the average pressure. To investigate its potential and reliability in analyzing CO 2 injection data, the proposed technique is applied to four synthetic cases representing different well operating conditions. Results indicate that the approximate approach consistently overestimates the actual (simulated) storage capacity as compared to the rigorous approach. The agreement - between the inferred and the simulated reservoir pore volume, and between the analytical and numerical estimates of storage capacity - validates the potential application of the technique to CO 2 storage in closed saline aquifers. The technique is further substantiated through application to a field data set utilized from a commercial-scale geological storage (CGS) project. Finally, field data interpretation shows that the proposed technique can be utilized to identify the degree of hydraulic continuity and reservoir compartmentalization within a target formation by interpreting the corresponding pressure and rate responses.

02 PETROLEUM↗