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At least 127 records · Page 7

Digitizing Today’s Buildings in the Real World: Lessons from Field Demonstrations

Digital twins, created by generating a virtual replica of a building, enable safe evaluation of operational scenarios and applications like fault detection and diagnosis and advanced controls. However, a prerequisite is the creation of a machine-readable digital representation of a building, currently hindered by fragmented information scattered across mechanical drawings, point lists, and natural language sequences. As a result, digital twin development remains labor-intensive, error-prone, and difficult to validate. To address these challenges, two efforts from ASHRAE aim to support the digitalization of buildings. ASHRAE s223 establishes a semantic model of buildings, representing system components, configuration, and data sources. ASHRAE s231 defines a vendor-neutral programming language for expressing their control logic. As the industry evaluates implementing them in their products, understanding the challenges that vendors and implementers may face is crucial. In this paper, we present findings and lessons learned from field demonstrations in five buildings that implemented control applications using ASHRAE s223 and s231. The demonstrations highlight how semantic modeling and formalized control descriptions can significantly reduce software development time, manual point mapping, and hard-coding. Beyond time efficiency, they enable reliable automation by minimizing human interpretation and providing a means for consistency across projects. We describe the processes and best practices for model creation and model usage, from translating heterogeneous building documentation into semantic representations to implementing control logic in real-world systems. Finally, we discuss the challenges that persist, including integration with legacy software environments, gaps in interoperability, and the level of expertise still required to effectively leverage semantic models.

Prakash, Anand Krishnan↗

Establishing Models for Digital Twin of Hydropower Systems Using Probability Density Function Shaping

This paper introduces a digital twin modeling method for hydropower systems with Kaplan turbines using probability density function (PDF) shaping. We first use multilayer perceptron (MLP) model to build the discretized openloop Kaplan unit, where the MLP is trained by historical data. Then we use a proportional integral double derivative (PIDD) controller and a lead-lag exciter to test the obtained digital twin model in a closed-loop fashion. Simulation results show that the proposed digital twin modeling method can accurately capture the dynamics of the Kaplan hydropower unit. Finally, we show that the obtained digital twin can help to optimize the PIDD parameters. Compared with the original PIDD controller, the optimized one can achieve an over 90% improvement on the mean square tracking error.

Yin, Zhun [New York University]↗

Physics-Guided Machine Learning (PGML) for Improved Aerostructure Manufacturing

The Physics-Guided Machine Learning (PGML) for Improved Aerostructure Manufacturing project objective is to automatically tune machining parameter predictions from physics-based models using process data and Bayesian machine learning. The intent is to enable a step change in aerospace manufacturing by combining machine learning, physics-based process models, and sensors/data in a comprehensive digital environment that simultaneously considers the computer numerically controlled (CNC) machining center capabilities, the workpiece material and geometry, and the workpiece support (fixturing). The project hypothesis is that this combination will enable improved performance in machining operations.

42 ENGINEERING↗

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗

Mechanical Solutions Scan Report

Power lines, poles, and towers are the backbone of the United States (U.S.) electric-power grid. These transmission and distribution networks route electricity from generator to loads. The characteristics of these routes are rapidly changing -- trending towards decentralized renewable generation, electric heating, vehicle charging, and large data-center loads. Coupled with aging infrastructure and the increased frequency of extreme weather events, there is concern about the future reliability and transmission capacity of conductors and adjacent components. This scan report seeks to provide an overview of mechanical solutions to challenges caused by extreme weather events associated with components of transmission and distribution infrastructure, including conductor heat sag, ice accumulation, wind, and wildfire. Many options could increase transmission capacity or reliability, and these are at various stages of technological readiness. Some have only been lab tested, while some have been widely deployed in the U.S. or overseas for decades. The solution categories and providers featured in this report are intended to be comprehensive at the time of publication and to serve as a reference for decision-makers concerned about transmission and distribution reliability. There are two other categories of large, complex solutions, which are not covered in this report: replacing existing conductors with advanced conductors and implementing digital grid enhancing technologies. A separate scan report titled “Advanced Conductor Scan Report,” which discusses advanced carbon-core conductors, was published by the Idaho National Laboratory (INL) in 2023. Information on digital technologies, such as dynamic line ratings, power-flow controllers, and other power electronics and communications-based devices, can be found on the Grid- Enhancing Technologies landing page. Mechanical grid-enhancing technologies, or solutions covered in this report, often do not require full equipment replacement and do not rely on digital components. Mechanical technologies are overlooked because they may be older, simpler, or seemingly “more obvious” than digital or carbon-core technologies. However, it is wise to consider mechanical solutions in a thorough evaluation of grid enhancing technology solutions.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Field Insights: Strengthening Digital Assurance Through On-Site Network Monitoring

The accelerating deployment of digital energy infrastructure, ranging from inverter-based resources (IBRs), battery energy storage systems (BESS), to advanced grid control platforms, has brought unprecedented visibility, flexibility, and efficiency to the electric grid. However, this digital transformation also introduces new cybersecurity challenges, particularly in the form of supply chain risks and operational blind spots at the grid edge. Over the past year, the Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER), through its Rapid Risk Assessment initiative, along with the Grid Deployment Office (GDO), through its Technical Assistance for Digital Assurance (TADA) initiative, have supported a series of on-site network engagements led by Idaho National Laboratory (INL). These engagements, conducted in partnership with asset owners across the country, have focused on identifying real-world vulnerabilities and misconfigurations in operational environments, many of which are not detectable through remote assessments or traditional compliance audits. The goal of this report is to distill key findings and lessons learned during network hunt engagements from INL’s fiscal year (FY) 2024 - 2025. It is intended to help asset owners—regardless of their participation in the program—better understand the evolving threat landscape and adopt practical measures to secure their digital energy infrastructure.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Strategy to Develop a Control Scheme for Core Thermal Performance Optimization

This report outlines a three-year research plan for optimizing reactor core thermal performance through use of a Digital Twin (DT) model and a set of neutron detectors to correspondingly adapt the reactor control strategy. It identifies reactor features and achievable neutron measurements that factor into this optimization task. It considers spatial effects that are important and how they can be managed by a real-time algorithm that controls reactivity actuators. The report presents a set of tasks, along with corresponding methods, for accomplishing this objective. The final task in this set is to validate the combined optimization procedure in the Purdue University’s PUR-1 reactor, for which we have an agreement of understanding. Additionally, we describe an alternative approach for overcoming some of the limitations inherent in the above approach, which includes the computational costs of high-fidelity simulations and achievable integration of neutron measurements into the DT. The proposed algorithms lower the technology readiness level (TRL) of the overall approach as some additional analysis and the development of a new neutron detector concept are necessary. In particular, a sensor measuring the gradient of the neutron flux is required, and the prototype is expected to be validated in the PUR-1 reactor. The potential benefits and the opportunity to significantly push forward the state-of-the-art make this approach worthy of further exploration in the upcoming years.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling for a Digital Twin-Based Remote Operation System Framework

New reactor designs and technologies are being developed to grow and advance the nuclear industry. Microreactors are one of the many new concepts for advancing the industry. Microreactors are very small reactors generally designed to have an operating power of 20 MWth or less. They are ideal for many applications in which it would not be feasible to have a large-scale reactor, such as powering remote communities, military bases, and mining sites. Many of these applications currently rely on diesel generators for power, and replacing those generators with the carbon-free energy of a microreactor is a major driving factor for microreactor development. However, most of the use cases for microreactors are in isolated locations where construction and labor costs are much higher. Microreactors will need to be comparable to other energy production methods for their deployment to be successful. Remotely operating the microreactor has a great potential to benefit the economics and make it more cost competitive. With remote operations, the operation facility location could be strategically chosen based on factors such as construction costs, workforce size, etc. The benefits of remote operations could be leveraged even more if the remote operation system is semi-autonomous. If the remote operation system is semi-autonomous, more microreactors could be operated and monitored from one remote operation facility. Additionally, with the system handling some tasks for the human operator, it could reduce the number of operating staff necessary for the microreactor. Digital twins can be used to introduce a level of automation to the remote operation system. Digital twins are capable of component monitoring, system operation and control, and predictive performance [1]. All of those features are important for a successful semi-autonomous remote operation system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Subvoxel Control of Fiber Orientation via Multidirectional Shearing in 3D Printing

Anisotropy, the characteristic of materials exhibiting different properties based on their direction, is widespread in nature. Conventional manufacturing techniques often fall short in recreating such complex anisotropy. While 3D printing allows for precise fiber deposition in anisotropic composites, previous studies have only achieved bulk reorientation of fibers at the voxel level in two dimensions. This limits the replication of localized 3D anisotropies found in natural materials. To address this, a novel 3D printing technique is presented that enables subvoxel control of fiber orientation in all three directions using multidirectional shearing via nozzle rotation and inclination. The fiber orientation control in these experimental tests is driven by a numerical model, enabling a fully digital approach to program microstructures within a strand. This programmability is demonstrated through mechanical and thermal tests, illustrating a localized and controllable response to external stimuli. Achieving such complex anisotropy holds potential across several fields, including wearables and biomedical implants, lightweight composite structures, and energy storage technologies such as batteries and supercapacitors.

3D printing↗

Development of an FGPA-Based Cavity Simulator for Testing RF Controls

LLRF is used to precisely control the amplitude and phase of the RF field in cavities. Often times, access to test the control algorithms with RF equipment, especially in the presence of beam, is limited or beyond reach. In such cases, testing must be done through computer modeling or simulations. Computer modeling is often too slow and difficult to interface with the LLRF hardware. Analog or digital cavity simulators are preferred as they allow for interaction with the LLRF controls platform in real-time, and compared to their analog counterparts, FPGA-based digital cavity simulators allow for a more adjustable and sophisticated implementation. The newly developed FPGA-based cavity simulator includes the cavity electrical model, the cavity mechanical model including Lorentz Force Detuning and microphonics, an amplifier model which can simulate real amplifier nonlinearities, and a beam model. The simulator has been validated using measurements from BNL’s CeC 704 MHz 5-cell SRF cryomodule.

43 PARTICLE ACCELERATORS↗

Hardware-Based Demonstration of Temperature Control Functions for Reactor Systems

Establishing autonomy in reactor control systems has become essential for the expansion of nuclear technologies. Thermal regulation in particular remains crucial for maintaining stable operation and ensuring the integrity of fuel. To alleviate public skepticism of the safety of nuclear reactors, demonstrating control over this key factor is pivotal. Utilizing electric heat pads to simulate the heat released in a reactor core, thermocouples for temperature monitoring, and an Arduino micro programmable logic controller (PLC) for control, a hardware-based demonstration of a reactor heating system validates the efficacy of reactor control over this key parameter. To improve precision, a proportional-integral-derivative (PID) algorithm was implemented in the heating control loop to ensure meticulous control of reactor functions. In addition, the integration of this physical system with a digital simulator tool such as RELAP5-3D establishes a foundation for a comprehensive testing environment. This allows for a refinement of temperature control under various simulated reactor conditions, bringing another layer of reliability to the operation of the system. By facilitating a physical demonstration of reactor thermal management and control strategies, this project provides a foundation for expanded testing and educational outreach. Ultimately, this system advances the broader goal of demonstrating the safety and viability of autonomous reactor operations, contributing to public trust and future reactor deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Broad-range tuning of ferroelectric switching of La x Bi 1−x FeO 3 epitaxial films via digital doping using off-axis co-sputtering

To investigate the scope of ferroelectric behavior in La-substituted BiFeO 3 films, La x Bi 1−x FeO 3 epitaxial films were synthesized using off-axis co-sputtering on SrTiO 3 (001) and DyScO 3 (110) substrates with a SrRuO 3 bottom electrode layer. A digital-doping deposition method was used to enable precise control and continuous tuning of La concentration in high-quality LaxBi 1−x FeO 3 films across a wide range of x = 0.05–0.60, which was systematically investigated using piezoresponse force microscopy. Robust and reversible out-of-plane ferroelectric switching has been observed up to x = 0.35, while films with x ≥ 0.37 exhibit no measurable ferroelectric behavior, indicating a sharp ferroelectric-to-paraelectric phase transition between x = 0.35 and 0.37. This represents the highest reported La concentration in LaxBi 1−x FeO 3 films that retains ferroelectric ordering, highlighting opportunities to engineer ferroelectric and multiferroic properties in complex oxide heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗

Calibration of the analog beam-signal hardware for the credited engineered beam power limit system at the Proton Power Upgrade Project at the Spallation Neutron Source

A programmable signal processor-based credited safety control that calculates pulsed beam power based on beam kinetic energy and charge was designed as part of the Proton Power Upgrade (PPU) project at the Spallation Neutron Source (SNS). The system must reliably shut off the beam if the average power exceeds 2.145 MW averaging over 60 seconds. System calibration requires pedigree in measurements, calibration setup, and calculations. This paper discusses the calibration of the analog beam signal components up to and including the Analog Digital Convertors (ADCs) for implementation into the Safety Programmable Logic Controllers (PLCs) and Field Programmable Gate Arrays (FPGAs).

Bobrek, Miljko↗

Advanced Transmission Technologies –GETs and HPCs Session 3: HPCs and Building Actions Plans to Digital Assurance Risks

The third session of the Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program, held on November 11, 2025, centered on High Performance Conductors (HPCs) and the formulation of action plans to address digital assurance risks associated with Grid-Enhancing Technologies (GETs). This session convened experts from utilities, vendors, and government agencies to examine the technical, operational, and cybersecurity aspects of HPC deployment. Discussions highlighted the benefits of HPCs, such as their ability to rapidly increase transmission capacity using existing corridors, improve grid resilience, reduce system losses, and align with FERC Orders 2023 and 1920. Participants evaluated supply chain and digital assurance risks, including reliance on imported materials, limited domestic manufacturing capacity, workforce shortages, and traceability issues. The session also emphasized the importance of digital trust, integration-layer cybersecurity, and unified risk frameworks, introducing tools like intrusion detection systems, encryption, zero trust networking, and firmware integrity. Recaps of earlier workshops on Dynamic Line Ratings (DLRs), Advanced Power Flow Control (APFC), and Transmission Topology Optimization (TTO) underscored institutional barriers and integration challenges. Action plans were proposed to mitigate issues such as inconsistent cybersecurity practices, SBOM usage, supply chain visibility, operator trust, and misaligned incentives. Additionally, INL presented its supply chain risk management tools and Cyber-Informed Engineering (CIE) principles to support secure procurement and system design. The session concluded with a commitment to share key takeaways, incorporate cohort feedback into future policy development, and continue collaborative engagement through upcoming pilot activities. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Complex surface topographic changes from explosive experiments at the Dry Alluvium Geology site, southern Nevada, United States

Understanding the surface topographic change that results from underground explosions is important for global security. Current techniques to relate the surface change to underground explosion characteristics usually involve assuming the earth has homogenous properties, leading to highly variable interpretations. Here we use an unoccupied aerial platform and a digital single lens reflex camera along with 200+ ground control points surveyed with a real-time kinematic global navigation satellite system to measure the surface topographic change resulting from two underground explosions at the Dry Alluvium Geology site in Yucca Flat, Nevada National Security Site, southern Nevada, United States. We find areas of 5–7 cm of subsidence that are not directly above the explosion source but rather 200–300 m away. For experiment DAG2, this zone is located south and west of the explosion, while for DAG4, there is a zone of subsidence located northeast of the explosion. In addition, late-time measurements show as much as 5 cm of horizontal change without measurable associated vertical change in the weeks following DAG4 but not DAG2. These indicate that the deformation resulting from underground chemical explosions can be very complex and bear little to no resemblance to predictions using half-space models. It is likely the tectonic environment plays a significant role in controlling the surface change, but the details are not fully understood.

58 GEOSCIENCES↗

Implementing a Laser Stabilization System for Trapping Ca+ Ions: an Internship Reflection

At Lawrence Livermore National Laboratory, I contributed to a project developing 3D printed micro ion traps for quantum computing. I designed, implemented, and assessed a laser stabilization system that locked lasers to the frequencies required for calibrating our High Finesse WS8-10 wavelength meter and for laser cooling and trapping of Ca+ ions. I also programmed a Python interface for hardware communication, data collection, and statistical analysis. Additionally, I optimized and aligned laser beam paths, and I implemented a closed digital feedback loop using Proportional, Integral, and Derivative (PID) control parameters. I analyzed both the long-term and short-term behavior of our locked lasers and adjusted PID parameters to enhance performance. Furthermore, I used COMSOL to simulate the capacitance of a linear Paul trap design and predict our trap’s performance. The procedures I developed for the interface, analysis, and simulations will continue to support the ion trapping experiment after my appointment. I strengthened my skills in data analysis, Python coding, and optical alignment for laser systems. My confidence as a researcher grew, particularly in communicating my research. This experience taught me the importance of careful planning and consideration in research and solidified my desire to continue exploring novel quantum technology as an undergraduate

42 ENGINEERING↗

Adaptive control for hybrid manufacturing

The primary objective of the technical collaboration is to validate and implement adaptive feed rate control, tool wear monitoring, and anomaly detection for the finish machining of additive components. Most additively manufactured components need finish machining to achieve surface finish and tolerance requirements. Distortions and surface roughness of additively manufactured components can result in high forces and tool breakage or excessive tool wear during post-additive finish machining, which can result in rework or part scrap. In this collaboration, methods, and models for feed rate control, tool wear monitoring, and anomaly detection via a digital twin will be evaluated and validated.

99 GENERAL AND MISCELLANEOUS↗