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At least 415 records · Page 23

Bridging the gap between experiments and simulations using machine learning

The physics of inertial confinement fusion is rich and complex. Simulation codes that are used to design experiments are computationally expensive and lack the predictive capability required for extensive parameter exploration in search of a high-performing design for laser direct drive. In this work we use deep learning to build a fast emulator of experiments. To facilitate the development of the deep-learning model, an autoencoder is used to reduce the dimensionality of the input space. Two deep learning models are developed. One model is trained on a vast array of simulation data and is subsequently calibrated to expensive and limited experimental data using a technique known as “transfer learning.” The other model is trained on a statistical model and is subsequently calibrated using experimental data. A comparative study of the two predictive models is carried out. The models potentially reproduce key experimental observables with high accuracy and unprecedented inference times relative to those achieved with simulation codes. These models facilitate rapid exploration of a high dimensional input parameter space.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Basic Design Layout of a Modular Pumped Hydro Teaching Unit

This work was originally completed in July 2015 as a proposal to Santa Fe Community College (SFCC) for their engineering program and a follow up to a feasibility study completed for the Community College the year earlier as indicated below. The work was ahead of its time and funding was hard to obtain to implement a project. This work is now being formally released for distribution to a wider audience based on the evolving circumstances in greater society that now favor this approach with funding more readily available. Due to the distribution outside of SFCC, specific architectural drawing sets of the pertinent buildings called out in the design have been removed. No changes to the design have been made. The design layout utilizing a building is not meant to limit the implementation of the design. The elevation difference required may be obtained with a building, a small hill, jacking up the upper tank, or similar means. The design presented is a basic design, identifying major components and how they are connected together. The user may change components under their own liability. All local applicable codes and standards must be followed when building an actual unit, under the authority of a responsible engineer or owner. Appropriate measures must be followed to protect people from hazards such as electricity, water pressure, and general construction. A leak test to verify water tightness of the system should be conducted prior to any operations. The vision of this design is to allow a class of 10 to 15 students to construct the assembly within a month or so time period, and then learn to operate the assembly at their school location under the guidance of their instructor. This will allow the students to learn about the practical concept of storing electricity with water, and gain a hands on experience of the real world challenges faced with full Modular Pumped Hydro Projects.

13 HYDRO ENERGY↗

CDL2PLC translator v0.1.0

The CDL-PLC translator aims at translating control sequences for building energy systems from the CDL CXF format to the PLCopen XML format. The CDL CXF developed at LBL within the OpenBuildingControl project, and now being standardized via ASHRAE Standard 231P, enables expressing control sequences developed in the simulation environment Modelica in a JSON format. The PLCopen XML is an existing exchange format standardized in IEC 61131-10 for Programmable Logic Controllers (PLCs) following the IEC 61131 standard as one target system of CDL among others. The translation from the CDL CXF to the PLCopen XML contributes to a seamless workflow from the model-based development of control sequences in simulation environments, which is not building practice today, and their digital implementation on building controllers, which replaces graphical and textual documents used for this purpose today. The translator is at a prototypical stage and enables, as a proof of concept, the translation of very simple control sequences composed of 4 selected function blocks out of 137 function blocks defined in CDL. The translation includes the connection of inputs and outputs of function blocks and the expression of a control function in CDL to the equivalent code in IEC 61131-3.

Walther, Karl↗

Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.

36 MATERIALS SCIENCE↗

Report Series: Evaluation, Finding of Effect, and Mitigation Documentation for the Main Gate (23-GS100), Mercury, Area 23, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE) National Nuclear Security Administration Nevada Field Office (NNSA/NFO) plans to replace the existing guard shack at the Main Gate (23-GS100, Nevada State Historic Preservation Office [SHPO] Resource No. S1758) to the Nevada National Security Site (NNSS) in Nye County, Nevada. The purpose of the project is to improve security. The project is considered an undertaking subject to review under Title 54 of United States Code (USC) § 306108, commonly known as Section 106 of the National Historic Preservation Act, Title 54 USC § 300101, et seq., and its implementing regulations, Title 36 of the Code of Federal Regulations (36 CFR) Part 800. In 2018, Desert Research Institute (DRI) completed an architectural survey of the town of Mercury. This effort resulted in the identification, recordation, and evaluation of the Mercury Historic District (MHD, SHPO Resource No. D230), including the identification of its contributing elements (Reno et al. 2018). The MHD was recommended eligible for listing in the National Register of Historic Places (NRHP, National Register) under the Secretary of the Interior’s (SOI) Significance Criteria A and C, as defined in 36 CFR Part 60.4, as a significant concentration of buildings and structures with a direct and important association with Cold War-era nuclear testing from 1951 through 1992. It has not been evaluated under Criteria B and D to date. As part of a larger modernization program for Mercury, the NNSA/NFO and the SHPO executed the 2018 Programmatic Agreement between the National Nuclear Security Administration Nevada Field Office and the Nevada State Historic Preservation Officer regarding Modernization and Operational Maintenance of the Nevada National Security Site, at Mercury in Nye County, Nevada (Mercury PA). The Mercury PA includes streamlined Section 106 procedures for undertakings in the MHD based on contributing element categories. The Main Gate is identified in Appendix C of the Mercury PA as a Category I contributing element, indicating that it might be individually eligible for the NRHP. It is a historic property for the purposes of Section 106 compliance and subject to the stipulations of the Mercury PA. Per Stipulation VI of the Mercury PA, when the Area of Potential Effect (APE) for an undertaking includes Category I elements, the NNSA/NFO must evaluate the Category I elements for individual NRHP eligibility under all of the SOI Significance Criteria, prior to initiating any activity that may affect the elements. Thus, the purpose of this report is to evaluate the Main Gate as a potential individually eligible historic property in fulfillment of Stipulation VI of the Mercury PA. The evaluation detailed herein concludes that the Main Gate is individually eligible for listing in the NRHP under SOI Significance Criterion A at the national level of significance for its direct, important association with Cold War-era nuclear testing from 1965 (the date the current Main Gate was constructed) through 1992 (when critical nuclear testing on the NNSS ceased).

23-GS100↗

Pacific Northwest National Laboratory Facility Radionuclide Emission Points and Sampling Systems

Battelle–Pacific Northwest Division operates numerous research and development laboratories in Washington State. The U.S. Department of Energy (DOE) contracts to Battelle at Richland facilities on both the DOE Hanford Site and the Pacific Northwest National Laboratory (PNNL) Richland campus. These facilities have the potential for radionuclide air emissions. The PNNL contract with DOE also includes operations at the PNNL-Sequim campus in Sequim, where there is also the potential for radionuclide air emissions. This document is a periodic update that describes current PNNL facility emission units and sampling systems. The National Emission Standard for Hazardous Air Pollutants (NESHAP [40 Code of Federal Regulations 61, Subpart H]) requires an assessment of all emission units that have the potential for radionuclide air emissions. Emission units are registered with the State of Washington. Potential emissions from emission units are assessed annually by PNNL staff. Sampling, monitoring, and other regulatory compliance requirements are designated based on the potential to-emit dose criteria, a graded approach to facility-identified potential impact categories, and regulatory requirements. The purpose of this document is to describe the facility radionuclide air emission sampling program and provide current and historical facility emission unit system performance, operation, and design information. For sampled emission units, the building, exhaust unit, control technologies, and sample extraction details are provided. Additionally, applicable configuration drawings, figures, and photographs are included. For non-sampled emission units, emission estimation and radionuclide source details are provided. Site-wide permits for the lowest potential impact category are described. Deregistered/transitioned emission unit details are also provided as necessary for at least 5 years post-closure/transition. Currently, five emission units are sampled continuously for particulate radionuclides at PNNL managed facilities on the PNNL-Richland campus (3 of the 5) and on the Hanford Site (2 of the 5). Four of these units have sampling systems that comply with the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1–2011 standard for sampling from stacks and ducts of nuclear facilities, and the fifth is grandfathered and compliant with the older ANSI N13.1–1969 standard. In addition, the PNNL-managed Hanford Site 325 Building EP 325-01-S stack is sampled continuously for emissions of tritium. No emissions sampling is required for the single licensed emission unit on the PNNL-Sequim campus.

54 ENVIRONMENTAL SCIENCES↗

Electric Vehicles at Scale (EVs@Scale) Laboratory Consortium Deep-Dive Technical Meetings: High Power Charging (HPC) Summary Report

Electric vehicle (EV) adoption will change the composition of EV charging load to higher-power charging as more medium- (MD) and heavy-duty (HD) applications are electrified, and as all vocations, including light-duty (LD) vehicles, are capable of faster charging. These shifts provide the opportunity for high-power charging (HPC) and facility equipment to evolve and improve efficiency, cost, and space. High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP) project designs and develops a high-power, interoperable charging experimental platform to research, develop, and demonstrate the integration approaches and technology solutions. The project addresses (1) interconnection and management of a grid-tied inverter; (2) development of a DC distribution system that is responsible for system energy management, interoperability, and DC protection; (3) modular DC/DC conversion for vehicle charging; (4) EV charging interface and DC/DC integration; and (5) smart charge control and vehicle-to-edge (vehicle-to-building [V2B], vehicle-to-everything [V2X]) capability. This summary presentation is the first technical progress output of the project. It provides insight for the first deep-dive technical meeting outputs in terms of research presentations and also includes summary of the discussions occurred in the follow-up breakout sessions. The summary presentation covers three technical areas: (1) HPC: State of the art power architectures and the design of the power electronics, (2) Modeling, energy management, and power control in the HPC station, and (3) Next Generation Profiles for high power charging characterization.

ADVANCED PROPULSION SYSTEMS↗

Stacked reverberation mapping of high-redshift quasars in DESI. I. Feasibility analysis

The broad-line region of quasars has long been probed by reverberation mapping techniques that measure time lags between continuum and broad emission-line variations. Stacked reverberation mapping has been proposed as a less observationally expensive alternative to traditional methods. This ensemble approach also reduces biases from small-number statistics. The Dark Energy Spectroscopic Instrument (DESI) is conducting the most extensive spectroscopic survey of quasars to date. We create mock light curves emulating expected DESI quasar observations at redshifts $1.48\lt z\lt 5.2$ and luminosities $44.68 \le \log \lambda L_{1350 \mathring{\rm A}{}} / \mathrm{erg\, s^{-1}} \le 45.99$ to test stacked reverberation mapping feasibility using sparse spectroscopic data paired with well-sampled photometric data. The pipeline, using the lag estimation code JAVELIN (Just Another Vehicle for Estimating Lags In Nuclei), successfully recovers the simulated C IV lags within 1σ of the true values using spectroscopic light curves composed of only a few spectral epochs (2–10) with irregular cadences. We investigate how observational factors, including C IV flux error magnitude, number of stacked quasars, and spectral epoch count, affect performance. This work motivates a pathway for future stacked reverberation mapping projects with large-scale spectroscopic surveys of quasars having $\ge 2$ spectroscopic observations. Our results suggest an economical alternative for constraining and extending the radius–luminosity relation to higher redshifts and luminosities. Subsequently, this relation can be employed more reliably in single-epoch black hole mass measurements and quasar cosmology in these distant regimes.

quasars: general, quasars: supermassive black hole↗

MATBOX, an Open-Source Microstructure Analysis Toolbox for Meshing, Generation, Segmentation, and Characterization of 3D Heterogenous Volumes

Battery performance is strongly correlated with electrode microstructural properties. To account for its impact, lithium-ion battery (LIB) models either abstract the microstructural heterogeneity of composite electrodes using effective macroscopic properties (macro- or meso- scale models) or directly solve the system of equations on the microstructure geometry or mesh (microstructure-scale models). Therefore, to be adequate, both families of models require information from the microstructure geometry, which can be provided by the numerical tool presented in this work. MATBOX is a MATLAB open-source application [1] developed by NREL for performing various microstructure-related tasks including microstructure numerical generation, image filtering and microstructure segmentation, microstructure characterization and correlation, visualization, and microstructure meshing. MATBOX was originally developed for the analysis of LIB electrode microstructures; however, the algorithms provided by the toolbox are widely applicable to other heterogeneous materials. The toolbox provides a user-friendly experience thanks to a Graphical-User Interface, requires no coding by the user, and is well documented. This presentation will illustrate various MATBOX features for the characterization of a LIB electrode, including a fully automated Representative Volume Element (RVE) analysis, the numerical generation of complex 'virtual' microstructure, including dual-layer electrodes and carbon-binder additive phase, and the meshing of a complex NMC/graphite full cell microstructure suitable for 3D finite-element modeling. Other modules (segmentation, visualization, and correlation) will be briefly presented. Thanks to its modular, open-source approach, MATBOX can easily incorporate third-party algorithms to eventually build a standard in the field that will benefit the whole scientific community. Effective diffusion coefficient [2], additive phase numerical generation [3], and meshing [4] third-party algorithms have been already integrated in the toolbox with more to come.

DIRECT ENERGY CONVERSION,MATHEMATICS AND COMPUTING↗

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances

Abstract A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool for measuring precise and accurate distances across a large redshift range and constraining cosmological parameters. We present an improved model framework, SALT3, which has several advantages over current models—including the leading SALT2 model (SALT2.4). While SALT3 has a similar philosophy, it differs from SALT2 by having improved estimation of uncertainties, better separation of color and light-curve stretch, and a publicly available training code. We present the application of our training method on a cross-calibrated compilation of 1083 SNe with 1207 spectra. Our compilation is 2.5× larger than the SALT2 training sample and has greatly reduced calibration uncertainties. The resulting trained SALT3.K21 model has an extended wavelength range 2000–11,000 Å (1800 Å redder) and reduced uncertainties compared to SALT2, enabling accurate use of low- z I and iz photometric bands. Including these previously discarded bands, SALT3.K21 reduces the Hubble scatter of the low- z Foundation and CfA3 samples by 15% and 10%, respectively. To check for potential systematic uncertainties, we compare distances of low (0.01 < z < 0.2) and high (0.4 < z < 0.6) redshift SNe in the training compilation, finding an insignificant 3 ± 14 mmag shift between SALT2.4 and SALT3.K21. While the SALT3.K21 model was trained on optical data, our method can be used to build a model for rest-frame NIR samples from the Roman Space Telescope. Our open-source training code, public training data, model, and documentation are available at https://saltshaker.readthedocs.io/en/latest/ , and the model is integrated into the sncosmo and SNANA software packages.

79 ASTRONOMY AND ASTROPHYSICS↗

Reaction dynamics of S( 3 P) with 1,3-butadiene and isoprene: crossed-beam scattering, low-temperature flow experiments, and high-level electronic structure calculations

Sulfur atoms serve as key players in diverse chemical processes, from astrochemistry at very low temperature to combustion at high temperature. Building upon our prior findings, showing cyclization to thiophenes following the reaction of ground-state sulfur atoms with dienes, we here extend this investigation to include many additional reaction products, guided by detailed theoretical predictions. The outcomes highlight the complex formation of products during intersystem crossing (ISC) to the singlet surfaces. Here, we employed crossed-beam velocity map imaging and high-level ab initio methods to explore the reaction of S( 3 P) with 1,3-butadiene and isoprene under single-collision conditions and in low-temperature flows. For the butadiene reaction, our experimental results show the formation of thiophene via H 2 loss, a 2H-thiophenyl radical through H loss, and thioketene through ethene loss at a slightly higher collision energy compared to previous observations. Complementary Chirped-Pulse Fourier-Transform mmWave spectroscopy (CP-FTmmW) measurements in a uniform flow confirmed the formation of thioketene in the reaction at 20 K. For the isoprene reaction, we observed analogous products along with the 2H-thiophenyl radical arising from methyl loss and C 3 H 4 S (loss of ethene or H 2 + acetylene). CP-FTmmW detected the formation of thioformaldehyde via loss of 1,3-butadiene, again in the 20 K flow. Coupled-cluster calculations on the pathways found by the automated kinetic workflow code KinBot support these findings and indicate ISC to the singlet surface, leading to the generation of various long-lived intermediates, including 5-membered heterocycles.

Lang, Jinxin↗

Converter-Interfaced CHP Plant for Improved Grid-Integration, Flexibility and Resiliency

GE Research and its partner GE Renewables have proposed the use of an interface converter solution to increase the penetration of small to medium-sized CHP (1MWe to 20MWe) into distribution grids and improve their flexibility and grid support capability. Indeed, the proposed interface converter solution thanks to presence of the grid-ready inverter, allows to streamline the compliance to grid codes requirements, reduce the interconnection delays and costs and ultimately one of the main barriers for CHP adoption by commercial and industrial facilities. An additional benefit provided by the interface converter is the use of the grid-ready inverter for reactive power which eliminates the need of sizing the generator for that capability. These two benefits highly favor the economic feasibility of converter-interfaced CHP. Five user cases, each in one of the leading U.S states for CHP potential reported by the DOE in its estimation of the U.S Technical Potential of CHP, were selected to compare the economic performances of converter-interfaced CHP as compared with directly-coupled. They include a college campus in California, a hospital in New York, a water reclamation plant in Texas, a hotel in Minnesota, and a large office building in Pennsylvania. Results showed that, the presence of the interface converter allows to increase the return on investment (ROI) by 0.5 to 2 percentage points in most of the cases (4 of 5). Indeed, the interface converter by shortening the interconnection process allows to accelerate revenues while reducing interconnection costs. Added to the reduced cost of the required generator these savings trade favorably the capital cost of the converter. The analysis also showed that the profitability of the converter-interfaced CHP is highly sensitive to the energy price, interconnection delay, and converter cost. However, it appears that if the interface converter can shorten the interconnection process by at least 6 months, adopting this solution will be more economically viable than directly-coupled configuration in almost all the +23,000 sites of the U.S Technical Potential CHP. The evaluation of the benefits of a converter-interfaced CHP also showed that it enables higher ROI when coupled with other distributed energy resources (DER) such as battery energy systems (BESS) or solar photovoltaic (PV). Indeed, in those scenario, the grid-ready inverter included in the interface converter eliminates the need of separate inverters if DC-coupling is used. On the technical performance, it has been verified that the presence of the interface converter allows to reduce by 70% to 80% the CHP short-circuit contribution to grid faults. This not only reduces the mechanical and thermal stresses exposed to the CHP electrical components but also increases the grid hosting capacity which ultimately enables higher penetrations CHP. Another key benefit of the interface converter validated with hardware-in-the-loop simulations and testing is its superior capability for reactive power support. Indeed, using a power hardware testbed with two +700kW inverters configured in back-to-back, a microgrid controller and actual facilities loads it was demonstrated that the presence of the interface converter can help maintain a power factor near ~1 or regulate the voltage to ~1.0pu at the point of common coupling. This benefit can be highly valuable if in the future, due to higher penetration of renewable distributed energy resources (DER), utilities start billing demand charge based on kVA instead of kW as currently. It was also validated that converter-interfaced CHP can dispatch heat and power commands and seamlessly switch between the two modes while consistently controlling the power factor or voltage at PCC. Indeed, the power hardware testing showed that grid-connected converter-interfaced CHP can follow either the power or heat demand while maintaining a unity power factor at converter output. This research proved that the adoption of an interface converter as the solution for interconnection of CHP system into the distribution grid can greatly improve the economic feasibility of small to medium-sized CHP as well as the plant power quality, flexibility and resiliency. Additionally, it allows increased penetrations of CHP into the distribution grid, extends their grid support capability, and facilitates the integration of BESS and PV DER by streamlining their collocation within the same facilities. This ultimately provides an opportunity for commercial and small industrial facilities in the U.S to accelerate their energy transition thanks to the high energy efficiency of CHP systems and its reliable, flexible, and resilient microgrid operation when interconnected with an interface converter.

24 POWER TRANSMISSION AND DISTRIBUTION↗

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

Materials for Advanced Ultra-Supercritical (A-USC) Steam Turbines --- A-USC Component Demonstration

The U.S. Advanced Ultra-Supercritical (A-USC) Consortium was formed in 2001 as a government/industry program, sponsored by the U.S. Department of Energy (DOE) and the Ohio Coal Development Office (OCDO) and cost shared by industrial and not-for-profit partners. The purpose of the consortium was to advance the state of the art for power generation by evaluating and developing materials that allow the use of advanced steam cycles in coal-based power plants. These advanced cycles, with steam temperatures up to 1400°F (760°C), can increase the efficiency of coal-fired boilers from an average of 35% (current U.S. fleet) to more than 45% higher heating value (HHV) (>49% lower heating value [LHV]). The increase in a plant’s efficiency is limited unless new materials able to withstand these higher operating temperatures and pressures are identified and approved for use. The A-USC Consortium identified these needed materials during earlier phases of the program. It developed the welding and joining techniques along with manufacturing processes for casting and wrought products made from these new high-nickel alloys. It subjected these materials to extensive laboratory and steam loop testing. It then obtained ASME code approval for their use in U.S. boiler systems. The program’s successes leave this last remaining activity (ComTest Phase 2) that the U.S. utility industry has recommended to be accomplished prior to commercialization. The focus of the activity is the evaluation and demonstration of commercial readiness for “full scale” components to be made from these nickel-based alloy materials and provided by a U.S. domestic supply chain that is new to working with these alloys. According to studies completed by the Electric Power Research Institute (EPRI), the cost of an A-USC plant is approximately 20% higher than a non-A-USC plant because of its use of nickel-based alloys needed for the high temperature operating conditions. However, CO 2 reductions of approximately 30% from the current fleet average provide a strong incentive for its consideration. The actual costs and perceived value for CO 2 abatement will determine whether new or retrofitted plants are undertaken, although decisions to build A-USC plants in India would indicate its economic feasibility while also being part of a global carbon emissions strategy. The work by the A-USC Consortium, prior to the start of the ComTest project, has included lab scale and pilot scale materials testing, both in air and oxy-combustion. This testing has included air-cooled and steam-cooled “loops” that were installed into existing operating utility boilers to gain exposure of these materials to realistic conditions of high temperature and corrosion caused by the constituents in the coal ash. The A-USC Consortium also gained ASME Code approval of the Inconel 740 material, has cast and extruded the largest high nickel precipitation hardened alloys, and developed unique welding techniques to avoid problems identified by the competing European program. However, as valuable as these material test loops and accomplishments have been for obtaining information, their scale is below that required to minimize the risk associated for a U.S. utility to build a multibillion-dollar A-USC power plant. To reduce the final identified risk barrier to full-scale commercialization of these advanced materials and systems, the A-USC Consortium (guided by a utility industry advisory committee) has identified the key areas of the technology they desire to see as being capable of full-scale manufacturing and/or fabrication from an identified, capable U.S. domestic supplier base. A significant amount of work was accomplished during Phase 1 to identity the components, as well as the component size, that would be manufactured from advanced alloys such as Inconel 740H or Haynes 282 alloys. Pathways to supply these components for ComTest have been identified, as well as any further development that would be required. The Phase 2 effort used Phase 1 findings for designing these key full-scale components for A-USC boilers and turbines to include large castings; extrusions, forgings, fabrication of water walls and steam loops with headers from advanced materials, raw material (such as pipe extrusion billets) are at the commercial readiness level to permit advancement to a demonstration project. The Phase 2 work scope was addressed by a diverse team, including government, industry, and not-for-profit partners. The work scope under Phase 2 addressed fabrication of components identified as being outside of the proven capabilities of the existing supply chain, including the following: Steam turbine rotor forging and Haynes 282 nozzle carrier casting Superheater and reheater header and tube assemblies Large-diameter pipe extrusions and forgings Test valve articles to support ASME Code approval. In addition, key fabrication steps were completed, including boiler weld overlays and simulated field repairs. Throughout, extensive inspection and quality assurance testing of the components were performed. The team worked to advance ASME Code approval for key components and processes. Although much of the focus of ComTest Phase 2 was the high-temperature nickel-based alloy materials, a broader range of materials were incorporated, which would be representative of the materials used in full-scale A-USC power plant applications and have cross-cutting applicability on other high-temperature power generation options, such as advanced nuclear, supercritical CO 2 cycles, and central solar receivers. This report that has been submitted is organized in the following manner: Section 1 contains an Executive Summary. Section 2 discusses the ComTest project background and organization. Section 3 discusses project management and reporting. Section 4 discusses the procurement of nickel-based alloy and other A-USC materials and components. Section 5 discusses the fabrication of procurement of nickel-based alloy and other A-USC materials and components. Section 6 discusses the fabrication of cast nickel-based A-USC steam turbine components. Section 7 discusses the fabrication of forged nickel-based A-USC steam turbine piping and steam pipe components. Section 8 discusses the qualification of pressure relieve valves (PRVs) for A-USC power plants. Section 9 discusses proposed plans for future evaluation of A-USC components. Section 10 contains the summary and conclusion.

01 COAL, LIGNITE, AND PEAT↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

A Data Processing Pipeline To Extract A Knowledge Graph From Sec Documents For Socio-technical Analysis Of Critical Infrastructure Influence

The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest (disk) expressed as a latitude/longitude point and distance, and a set of SEC form types from which to extract entities and relations. There are three main components to this pipeline as currently implemented: Social Network Extraction, Critical Infrastructure Network Extraction, and Inference and Fusion. First, Social Network Extraction, implemented as the `organizations_sec` component of the workflow graph queries the SEC EDGAR webservice using the list of initial companies from the configuration file. Given this, it extracts metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Second, the Critical Network Extraction component extracts entities and relations for a critical infrastructure sector. Currently, we focus on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Third, the Inference and Fusion component relates the social network graph to the critical infrastructure graph in order to understand the impact of a company within a geographic region. Relations include ownership of the EV Charging Station asset as well as maintenance/ownership of the EV payment networks. The fused network can be represented in many ways and currently we emit a knowledge graph.

Weaver, GabrielA.↗

Quantifying Dynamic Signal Spread in Real-Time High-Energy X-ray Diffraction

Abstract Measured intensity in high-energy monochromatic X-ray diffraction (HEXD) experiments provides information regarding the microstructure of the crystalline material under study. The location of intensity on an areal detector is determined by the lattice spacing and orientation of crystals so that changes in the heterogeneity of these quantities are reflected in the spreading of diffraction peaks over time. High temporal resolution of such dynamics can now be experimentally observed using technologies such as the mixed-mode pixel array detector (MM-PAD) which facilitates in situ dynamic HEXD experiments to study plasticity and its underlying mechanisms. In this paper, we define and demonstrate a feature computed directly from such diffraction time series data quantifying signal spread in a manner that is correlated with plastic deformation of the sample. A distinguishing characteristic of the analysis is the capability to describe the evolution from the distinct diffraction peaks of an undeformed alloy sample through to the non-uniform Debye–Scherrer rings developed upon significant plastic deformation. We build on our previous work modeling data using an overcomplete dictionary by treating temporal measurements jointly to improve signal spread recovery. We demonstrate our approach in simulations and on experimental HEXD measurements captured using the MM-PAD. Our method for characterizing the temporal evolution of signal spread is shown to provide an informative means of data analysis that adds to the capabilities of existing methods. Our work draws on ideas from convolutional sparse coding and requires solving a coupled convex optimization problem based on the alternating direction method of multipliers.

Engineering↗