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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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193 records · Page 11

BOPTEST as a Platform for Building Controls and Grid-Interactive Buildings Workforce Training

Building automation and controls are becoming increasingly complex with the emergence of Grid Integrated Efficient Buildings (GEBs) as well as new highly efficient sequences of operation and data-driven control schemes. However, there remains a significant gap in hands-on training opportunities for building operators and technicians to gain practical experience with advanced control systems in a low-risk environment. This paper presents BOPTEST (Building Optimization Performance Test) as a suitable platform for workforce training in building controls and GEB technologies. BOPTEST provides a suite of standardized building simulation test cases with a REST API, real-time control interfaces through BACnet, semantic models connecting users to building data, and built-in calculation of control metrics and performance indicators. The platform enables trainees to interact with virtual buildings using industry-standard protocols while learning how to implement and innovate control strategies. The training platform is designed to offer a structured and interactive learning experience for building engineers, helping them effectively develop, learn, and retain skills in fault identification, troubleshooting, and correction. The workflow is divided into three main phases: 1) Setup, 2) Exercise, and 3) Review, each comprising specific activities performed by either the instructor or the student. Initial pilot training sessions have yielded positive feedback from instructors and participants and demonstrates that BOPTEST effectively fills an industry need for a low-risk training resource via simulation of real building control systems, allowing trainees to gain practical experience before working in the field. The platform's ability to provide immediate performance feedback while maintaining familiar industry interfaces makes it particularly suitable for workforce development programs. This work provides a replicable model for leveraging building simulation in control education and training.

Paul, Lazlo↗

Alfalfa Virtual Building Service: Software Engineering Best Practices Applied to Runtime Interaction with Building Energy Models

Buildings are active participants in increasingly complex energy systems. Building Energy Modeling (BEM) has a key role to play in planning and de-risking an equitable energy transition, with BEM-backed "virtual buildings" critical path for diverse applications that include workforce training tools, Hardware-in-the-Loop (HIL) experimentation to study equipment performance under a range of conditions, Control-Hardware-in-the-Loop (CHIL) experimentation to de-risk commercial control implementations at equipment through grid orchestration levels, and integration of dynamic load profiles into grid modeling tools for energy system experimentation at the urban scale. Modeling requirements vary across these applications, but many software engineering tasks do not. The Alfalfa Virtual Building Service (AVBS, see https://github.com/NREL/alfalfa/wiki) is an open-source web service that solves these common tasks robustly in one place, providing a foundational platform for power users to bootstrap their own applications. AVBS abstracts the specifics of runtime interaction with OpenStudio, Modelica, and Spawn of EnergyPlus models behind a unified REST API. Additionally, AVBS provides resources for cloud deployment and scaling to 100s of parallel simulations, a growing library of modular Operational Technology (OT) integrations for emulation of real-world interfaces, and scripts to automate the population of communities of virtual buildings from URBANopt, ResStock and ComStock.

building automation↗

Adaptive Computing and Multi-Fidelity Strategies for Control, Design and Scale-Up of Renewable Energy Applications

We describe our ongoing research in adaptive computing and multi-fidelity modeling strategies. Our goal is to use a combination of low- and high-fidelity simulation models to enable computationally efficient optimization and uncertainty quantification. We develop optimization formulations that take into account the compute resources currently available, which act as a constraint with regards to the fidelity level simulation we can run while maximizing information gain. These strategies are being implemented into a software framework with a generalized API allowing its application to a broad range of applications, from power grid stability and buildings control to material synthesis and biofuels processing. We will discuss a few examples from these applications that can benefit from this approach, especially when considering challenges arising in scaling up experiments and simulations.

adaptive computing↗

Adoption of ROOT RNTuple for the next main event data storage technology in the ATLAS production framework Athena

Since the start of LHC in 2008, the ATLAS experiment has relied on ROOT to provide storage technology for all its processed event data. Internally, ROOT files are organized around TTree structures that are capable of storing complex C++ objects. The capabilities of TTrees developed over the years and are now offering support for advanced concepts like polymorphism, schema evolution and user defined collections and ATLAS makes use of these features to handle its EDM. But some original TTrees concepts, like the POSIX file model and sequential writing, remain unchanged since the beginning and could be an obstacle to achieving the performance required for High Luminosity LHC. With the HL-LHC performance goals in mind, the ROOT project developed a new storage format - the RNTuple. RNTuple, with its accompanying user API, is now in the final development stage and is planned to be production-ready at the end of 2024. Soon after that, the TTree will become a legacy format. ATLAS intends to have its main Event processing framework Athena ready to use RNTuple in the production environment as early as possible. The work on adopting RNTuple as another ROOT storage technology in Athena started already in 2021 and is now nearly complete. Although the initial goal was to focus on derived-AOD products (PHYS and PHYSLITE), with a little added effort all ATLAS data products: RDO, HITS, ESD, AOD and DAOD can be now stored in RNTuple format and transparently read back. In this paper we will describe the current state of RNTuple adoption in the Athena framework and explain the ATLAS EDM requirements that had to be met on the ROOT side to successfully integrate both environments. We will demonstrate the ability to run standard ATLAS production workflows, based on RNTuple as the Event data storage technology, and point out key advantages of the new format.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

FLAW STABILITY ANALYSIS OF SURFACE CRACKS IN DOE STANDARD CANISTERS UNDER OPERATION LOADS AND WELDING RESIDUAL STRESSES

There are over 3000 commercial spent nuclear fuel (SNF) storage canisters that are made of stainless steel and planned for multi-purpose functions of SNF handling: interim storage, transportation, and ultimate disposal at a future SNF disposition location. To date, many multi-purpose canisters (MPC) are located in coastal regions for long-term storage. The canisters are fabricated by welding, and post-welding heat treatment is not required for relieving welding residual stresses (WRS). As a result, these canisters may be susceptible to chloride induced stress corrosion cracking (CISCC) due to the chloride-bearing marine salts. The flaw stability analysis of MPC canisters was performed at SRNL (i.e., PVP2016-4935 and PVP2016-63887) for through-wall flaws and for surface flaws respectively, where WRS was considered, and the failure assessment diagram (FAD)-based fracture mechanics method codified by API 579-1/ASME FFS-1-2007 Edition was adopted.

DOE standard canister↗

Data Centers and Digital Assurance Workshop 2 – Prioritizing Digital Assurance Challenges, Session 2

The second session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 10, 2025, focused on prioritizing digital assurance challenges at the intersection of data centers and the electric grid. Building on the foundational concepts introduced in Workshop 1, this session deepened the application of the Threat–Vulnerability–Consequence (TVC) framework and emphasized the urgency of addressing cybersecurity, supply chain integrity, and operational reliability. Participants explored the growing convergence of digital and physical systems, the expanding attack surface due to global supply chain dependencies, and the implications of AI-driven load behavior. Real-world incidents—including the Volt Typhoon campaign and vulnerabilities in Solarman and Deye platforms—were analyzed to illustrate the risks of unpatched systems, insecure APIs, and inadequate vendor oversight. Key themes included architecture and interface weaknesses, governance gaps, and human and procedural shortcomings. The workshop also examined the evolving regulatory landscape, highlighting new federal mandates around Foreign Entity of Concern (FEOC) compliance and large-load reliability standards. Through interactive exercises, stakeholders ranked and mapped digital assurance risks from their respective perspectives—utilities, operators, and vendors—laying the groundwork for mitigation strategies and shared accountability models to be developed in Workshop 3. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

A Brief Survey on High Performance Computing Systems Power Management

This paper provides a survey of software-based power management techniques in High Performance Computing (HPC) systems. Seven existing power management and monitoring tools and frameworks are discussed. These are: Variorum, dynamic energy-performance optimizer (DEPO), Powersched, Bull Dynamic Power Optimizer (BDPO), Energy Aware Runtime (EAR), Global Extensible Open Power Manager (GEOPM), and PoLiMEr. Each of these tools is evaluated based on hardware abstraction, optimization methods, usability, and experimental validation. This survey highlights the diversity of approaches in managing energy efficiency, from vendor-neutral APIs to algorithm-driven power capping, and dynamic frequency adjustments. Given that energy requirements for large computational systems is increasing quickly, the importance of integrating these tools into existing HPC environments and the need for further research in this rapidly evolving field is also discussed.

97 - MATHEMATICS AND COMPUTING↗

Advanced Transmission Technologies – GETs and HPCs Session 2: Advanced Power Flow Control and Transmission Topology Optimization

The INL TADA GETs Cohort Session 2, held on November 7, 2025, conducted in collaboration with ScottMadden, focused on two core Advanced Transmission Technologies (ATTs): Advanced Power Flow Control (APFC) and Transmission Topology Optimization (TTO). These technologies are pivotal in enhancing grid flexibility, reliability, and cybersecurity resilience. APFC, particularly through modular FACTS devices like Modular Static Synchronous Series Compensators (M-SSSCs), enables dynamic voltage injection to reroute power flows. The session highlighted the deployment benefits of APFC, such as rapid installation, minimal civil works, and re-deployability. Regulatory drivers like FERC Order 2023 mandate the inclusion of Grid-Enhancing Technologies (GETs) in interconnection studies. Case studies from Central Hudson, CAISO, and National Grid (UK) demonstrated APFC’s effectiveness in congestion relief and cost savings. The session also addressed cybersecurity concerns, including firmware vulnerabilities, SCADA integration risks, and supply chain dependencies. Participants engaged in interactive exercises to rank cybersecurity and supply chain risks, emphasizing the need for robust digital assurance strategies. TTO involves software-based reconfiguration of transmission networks to optimize power flow without new infrastructure. The session showcased its operational value, with examples from SPP, PJM, and MISO showing significant congestion cost reductions. Cybersecurity vulnerabilities were discussed, particularly in API security and software supply chains, referencing incidents like SolarWinds and attacks on Danish utilities. Digital assurance exercises explored worst-case scenarios, attack paths, and mitigation responsibilities between vendors and utilities. Reliability challenges such as algorithm stability, vendor dependency, and operator trust were also examined. Cross-cutting themes emphasized the importance of digital assurance tools, including Software Bills of Materials (SBOMs) and hardware-in-loop testing. Human performance, training, and operational confidence were identified as critical enablers of technology adoption. The session concluded with a preview of Session 3, which will focus on High Performance Conductors (HPCs) and risk-based cybersecurity tools. Session 2 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

LeWRON: Agentic Analysis of Electroweak Phase Transitions

The electroweak phase transition (EWPT) is a central topic in particle physics and cosmology, connecting collider phenomenology, baryogenesis, and gravitational-wave observatories. Its analysis requires a technically demanding, convention-sensitive, and model-dependent pipeline, from constructing the finite-temperature effective potential to tracking thermal histories, computing bubble nucleation rates, and predicting gravitational-wave spectra. We present LeWRON (Learning ElectroWeak phase tRansitiON), an agentic framework that orchestrates this pipeline starting from an input Lagrangian. LeWRON combines audited toolbox construction with an Explorer module that uses the generated model-specific code for further analysis, including scans and plots. Intermediate analytic outputs are checked by auditor agents and stored as structured artifacts, enabling reproducible human inspection and downstream use through both a command-line interface and a public Python API. The framework supports a reproduction mode, which infers conventions from the literature and reproduces published results, and a discovery mode, which guides users through structured checkpoints for new models. We demonstrate LeWRON across representative beyond-the-Standard-Model scenarios and release the code on GitHub.

Wang, Isaac R. [Fermilab] (ORCID:000000030789218X)↗

Latency Analysis of the Nexus Digital Twin Framework

Real-time digital catalogs are increasingly relied upon to track metadata and connect disparate data sources for cloud-based data integration efforts. One such tool, Deeplynx Nexus is supporting real-time digital twin efforts through event-driven data integration and time-series queries. Nexus’s usefulness for these applications depends critically on how quickly individual records can be uploaded and downloaded, since delays directly affect the responsiveness of any system built on top of it. However, the actual latency a user should expect from Nexus has not been systematically measured before, particularly for the small, frequent transactions typical of live sensor feeds. Here we show that single-record round-trip latency is 61.1 ms on a local Nexus instance and 391.7 ms on the hosted production infrastructure, a roughly 6.4x difference driven primarily by fixed per-request overhead rather than data volume. This overhead dominates at small scale: comparing single-record and ten-record trials suggests approximately 56 ms of each single-record request is fixed connection and authentication cost rather than data-transfer time, meaning batching even a handful of records is substantially more efficient than transmitting them individually. At large batch sizes, this pattern reverses for uploads, which converge to near parity between local and hosted environments by 25,000-50,000 records, while download latency remains persistently 5.7-6.4x slower on hosted infrastructure even at scale. These results suggest that Nexus deployments intended for real-time digital twin applications should prioritize record batching over single-record transactions, and that download-path optimization on hosted infrastructure offers the largest remaining opportunity to reduce latency at scale. We anticipate these baseline measurements will serve as a reference point for future digital twin projects evaluating whether Nexus’s latency profile meets their real-time requirements, and as a benchmark for tracking the effect of future infrastructure or API changes.

99 - GENERAL AND MISCELLANEOUS↗

Optimal Operation of Residential High Performance Water Heater for Reduction of Electricity Cost and Peak Demand Through Field Validation

Water heating accounts for about 18% of a typical US home’s energy use. Modern water heaters have enabled control options through APIs, offering customers the opportunity to reduce their energy cost and peak demand by dynamically adjusting settings. A water heater’s capacity to store energy using its storage tank makes it an asset for peak demand reduction and energy cost savings. For this reason, a mixed-integer linear programming model is proposed to minimize the energy cost of a high-performance water heater while also reducing the peak demand of the residential household under a time-of-use utility rate by dynamically changing the water heater’s running mode. Specifically, a multi-objective optimization model is formulated to determine the mode settings of the water heater considering hot water use, time-of-use rate, and peak demand limit of the residential household. The mode settings are associated with different dead bands of water temperature for triggering on/off action of the heat pump and heating element. A 66-gal hybrid electric high performance water heater was used for numerical simulation and practical experiments. The simulation results were well aligned with measurements of practical experiments, validating the soundness of the thermodynamic model. In addition, reductions of energy cost, enabling affordability, and reducing peak demand are demonstrated. The research team also developed a software framework with dashboards to automatically and continuously monitor and manage devices.

Liu, Guodong [ORNL] (ORCID:0000000213498608)↗

MontePy: a Python library for reading, editing, and writing MCNP input files.

The Monte Carlo N-Particle (MCNP) radiation transport code is a highly capable and accurate code with a long legacy. MCNP uses the Monte Carlo simulation process to simulate the path of particles (e.g., neutrons, photons, charged particles, etc.), and their interaction with materials. It is widely used in nuclear engineering, high-energy physics, and other fields. Its origins in the mid-twentieth century predate many modern software conventions. MCNP users provide an input file to MCNP, which it then uses to create an internal representation of the simulation problem. These input files originally had to be stored as punchcard decks, and the user manual still uses the terminology of cards and decks, despite moving beyond punchcards. MCNP predates nearly all modern human readable markup or data serialization languages, such as the extensible Markup Language (XML), the Standard Generalized Markup Language (SGML), YAML (YAML Ain’t Markup Language), and Javascript Object Notation (JSON). Due to this, MCNP uses an entirely custom defined syntax language for its input, making off-the-shelf libraries for XML, YAML, and JSON impossible to use for scripting various operations on MCNP input files (Kulesza et al., 2022).

97 - MATHEMATICS AND COMPUTING↗

Intrinsic Bonding and Reactivity of Actinide Clusters Poster

The effect of electronic structure on chemical bonding and reactivity is one of the most important questions in the field of chemistry. Insight into chemical bond formation involving elements that contain f electrons (i.e., the lanthanides and actinides) is critical for solving specific technical challenges, such as development of advanced nuclear fuel cycles and efficient rare earth separations, as well as a broader understanding of bonding across the entire periodic table. The primary technique for studying the fundamentals of lanthanide and actinide bonding is crystallization of metal-ligand compounds followed by structural determination with X-rays and comparison to theory with computational chemistry. While this procedure has yielded significant insights for a wide variety of elements, it is challenging to apply to the heavier trans-uranic actinides such as berkelium and californium because of limited material availability, significant radioactivity, and poorly understood chemical reactivity of these elements. We hypothesize that by forming actinide-ligand clusters in a mass spectrometer and probing their reactivity in the gas-phase, many of the challenges associated with studying the heavier trans-uranic elements can be circumvented. This project will develop a capability to address a wide range of actinide bonding and reactivity phenomena, increasing Idaho National Laboratory’s capability to address fundamental questions at the forefront of heavy element chemical and molecular science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗