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At least 37 records · Page 2

Real-Time High-Accuracy Digital Wireless Time, Frequency, and Phase Calibration for Coherent Distributed Antenna Arrays

his work presents a fully-digital high-accuracy real-time calibration procedure for frequency and time alignment of open-loop wirelessly coordinated coherent distributed antenna array (CDA) modems, enabling radio frequency (RF) phase coherence of spatially separated commercial off-the-shelf (COTS) software-defined radios (SDRs) without cables or external references such as the global navigation satellite system (GNSS). Building on previous work using high-accuracy spectrally-sparse time of arrival (ToA) waveforms and a multistep ToA refinement process, a high-accuracy two-way time transfer (TWTT)-based time–frequency coordination approach is demonstrated. Due to the two-way nature of the high-accuracy TWTT approach, the time and frequency estimates are Doppler and multipath tolerant, so long as the channel is reciprocal over the synchronization epoch. This technique is experimentally verified using COTS SDRs in a lab environment in static and dynamic scenarios and with significant multipath scatterers. Time, frequency, and phase stability were evaluated by beamforming over coaxial cables to an oscilloscope which achieved time and phase precisions of ~60– 70 ps , with median coherent gains above 99% using optimized coordination parameters, and a beamforming frequency root-mean-square error (RMSE) of 3.73 ppb in a dynamic scenario. Finally, experiments were conducted to compare the performance of this technique with previous works using an analog continuous-wave two-tone (CWTT) frequency reference technique in both static and dynamic settings.

Clock synchronization

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

GNSS-based Vegetation Optical Depth, Tree Sway, and Evapotranspiration data from the Niwot Ridge Subalpine Forest (US-NR1) AmeriFlux site

This data package contains data and information about Global Navigation Satellite System (GNSS)-based Vegetation Optical Depth (VOD), tree sway motion, and eddy-covariance evapotranspiration (ET) data collected at the Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1). The raw GNSS data were collected between May 2022 and August 2023. Other processed datasets such as tree sway motion and ET data are also included. The goal was to study the water content within a subalpine forest and, more specifically, examine the canopy evaporation process. This data archive includes all data that were used within the following Biogeosciences discussion paper that further summarizes the research objectives and conclusions:Burns, S.P., V. Humphrey, E.D. Gutmann, M.S. Raleigh, D.R. Bowling, and P.D. Blanken, 2025: Using GNSS-based vegetation optical depth, tree sway motion, and eddy-covariance to examine evaporation of canopy-intercepted rainfall in a subalpine forest. EGUsphere [preprint],https://doi.org/10.5194/egusphere-2025-1755This data archive also supplements the 30-min Lawrence Berkeley National Laboratory (LBNL) AmeriFlux dataset for US-NR1 (i.e., https://doi.org/10.17190/AMF/1246088) and updates what was in the 2020 ESS-DIVE US-NR1 archive (https://doi.org/10.15485/1671825) to include data from the years 2020-2025. More specifically, the following updates are provided: (i) five-minute statistics (means, variances, covariances) of all data measured by the US-NR1 data system between Sep 2020 and Jun 2025 in netCDF format, (ii) the electronic logbook of US-NR1 site visits, (iii) a web calendar (in HTML format) documenting activity at the site (a replica of https://urquell.colorado.edu/calendar/), (iv) photos taken at the site between years 2020 and present day (Aug 2025), and (v) several auxiliary datasets, primary related to trees near the site, soil properties, soil moisture and soil temperature, and subcanopy radiation data. The data package is setup so that the web calendar, photos, and electronic logbook can be easily accessed on a local computer using a web browser. The provided data files are in either BINEX or SBF format (for the raw GNSS data), netCDF, CSV, ASCII, or MATLAB format. To obtain a better understanding about the archive, please start by reading the following PDF which is included within the data archive:README_ESS_DIVE_USNR1_2025_readme_first.pdf.

54 ENVIRONMENTAL SCIENCES

CHESS 2025: Location data for field observations and sampling

This dataset represents geolocation data associated with field observations and sampling from the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Location data were collected using Trimble DA2 Global Navigation Satellite System (GNSS) receivers with Trimble Catalyst 2 centimeter (cm) positioning service and the Environmental Systems Research Institute (Esri) Field Maps mobile app. Files in this data package include meadow site polygons, shrub site polygons, tree site polygons and stem point locations, and Leaf Area Index (LAI) plot polygons (.geojson). The geojson files can be opened with open-source GIS software (e.g, QGIS). A csv file is also provided with point coordinates for all locations. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns

Center for Alternative Synchronization and Timing (CAST) Technical Bulletin #007: Holdover Experiment #1

Stable and accurate timing forms the foundation of many modern essential services. While Global Navigation Satellite Systems (GNSS) provide a cheap way to achieve extremely accurate timing, these systems are vulnerable to interference and complete outages, forcing systems that rely on them into a state of holdover. Testing and characterizing holdover performance is therefore essential for ensuring that these modern services do not go down when GNSS-based timing is unavailable.

24 POWER TRANSMISSION AND DISTRIBUTION

Center for Alternative Synchronization and Timing (CAST) Technical Bulletin #006: Holdover Experimental Summary

Stable and accurate timing forms the foundation of many modern essential services. While Global Navigation Satellite Systems (GNSS) provide a cheap way to achieve extremely accurate timing, these systems are vulnerable to interference and complete outages, forcing systems that rely on them into a state of holdover. Testing and characterizing holdover performance is therefore essential for ensuring that these modern services do not go down when GNSS-based timing is unavailable.

24 POWER TRANSMISSION AND DISTRIBUTION

Precision Time Protocol Performance Testing Over Optical Transport Network

The US Department of Energy Office of Electricity has partnered with Oak Ridge National Laboratory (ORNL) to find alternative precision timing solutions for the nation’s power grid. This effort is in response to the vulnerabilities identified in the Global Navigation Satellite System (GNSS), of which the US Global Positioning System (GPS) platform is a part. Additionally, Executive Order 139055 has highlighted the need for alternative or backup timing solutions. ORNL has established a Timing Lab and has been testing various technologies and timing devices as part of this effort. Precision Time Protocol (PTP), and the off-the-shelf timing devices and network connections that support it, are among the alternatives being tested. This work reports the accuracy of PTP over an Optical Transport Network (OTN) and is part of a series published by the Center for Alternative Synchronization and Timing (CAST).

24 POWER TRANSMISSION AND DISTRIBUTION

Enhanced Lighting Signals for Safety and Efficiency - Experiments With Addressable LEDs

For enhanced roadway safety, clear and immediate visual cues are essential for preventing accidents between drivers and pedestrians. At intersections, however, the line of sight to other roadway users may be obstructed by vehicles and infrastructure. Additionally, adverse conditions, including low visibility, poor weather, or inadequate lighting can increase the potential for collisions. Distracted drivers and pedestrians can further exacerbate the risk of accidents, particularly when using a smartphone, rather than focusing on roadway surroundings. These issues demonstrate the need for infrastructure upgrades that enhance visibility and awareness at crosswalks. A potential solution is through enhanced lighting signals integrated into the roadway infrastructure. One such example is the use of addressable LEDs, individually controllable lights that can change color and brightness instantaneously through programmable microcontrollers. They can be installed and integrated into crosswalks to maintain visibility in conditions where pedestrians may be difficult to see, while also offering peripheral cues to pedestrians who may be distracted by their phones or other objects rather than the road. Such a system (as one example) that is integrated into a traffic intersection digital twin that tracks all roadway users accurately, has the potential to enhance visibility of vulnerable road users, and thus enhance safety. This paper examines the potential implementation and feasibility of this technology, as well as the safety benefits it could provide. Laboratory experiments with addressable LEDs reveal the capabilities and challenges of this technology for roadway infrastructure safety. These findings could pave the way for more integrated lighting in infrastructure for vehicles and pedestrians at intersections, merge and diverge locations, and other areas where complex interactions present safety hazards. Such lighting solutions, enabled by modern computation and communications, could enhance safety and efficiency in our transportation system and improve overall mobility.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Enhanced Lighting Signals for Safety and Efficiency - Experiments with Addressable LEDs

For enhanced roadway safety, clear and immediate visual cues are essential for preventing accidents between drivers and pedestrians. At intersections, however, the line of sight to other roadway users may be obstructed by vehicles and infrastructure. Additionally, adverse conditions, including low visibility, poor weather, or inadequate lighting can increase the potential for collisions. Distracted drivers and pedestrians can further exacerbate the risk of accidents, particularly when using a smartphone, rather than focusing on roadway surroundings. These issues demonstrate the need for infrastructure upgrades that enhance visibility and awareness at crosswalks. A potential solution is through enhanced lighting signals integrated into the roadway infrastructure. One such example is the use of addressable LEDs, individually controllable lights that can change color and brightness instantaneously through programmable microcontrollers. They can be installed and integrated into crosswalks to maintain visibility in conditions where pedestrians may be difficult to see, while also offering peripheral cues to pedestrians who may be distracted by their phones or other objects rather than the road. Such a system (as one example) that is integrated into a traffic intersection digital twin that tracks all roadway users accurately, has the potential to enhance visibility of vulnerable road users, and thus enhance safety. This paper examines the potential implementation and feasibility of this technology, as well as the safety benefits it could provide. Laboratory experiments with addressable LEDs reveal the capabilities and challenges of this technology for roadway infrastructure safety. These findings could pave the way for more integrated lighting in infrastructure for vehicles and pedestrians at intersections, merge and diverge locations, and other areas where complex interactions present safety hazards. Such lighting solutions, enabled by modern computation and communications, could enhance safety and efficiency in our transportation system and improve overall mobility.

24 POWER TRANSMISSION AND DISTRIBUTION

202508 HAIIC IR Images with Attitude Data at BNF

This campaign aims to collect infrared imagery using a custom data acquisition system to improve and validate a previously developed attitude estimation algorithm, with a focus on ensuring reliable performance at higher altitudes. The system integrates a Boson+320 infrared camera, a VN-200 IMU for recording attitude data synchronized with image acquisition, and a Raspberry Pi 4B+ for onboard processing and storage. Image orientation was controlled using a Gremsy T7 gimbal. The primary dataset spans roll angles from −40° to 40° and pitch angles from −20° to 40°, sampled at 1° increments. Additional, smaller datasets were also collected at 2.5° angular intervals.

Boson+320

RAG for FLAG: AI Assistance for a Physics Code

Artificial intelligence (AI) has quickly become an important tool in scientific research, where significant efforts are underway to develop tools that will expedite the research process. One area of particular impact is scientific software, which can be particularly complex, and therefore time consuming to learn and use effectively. AI assistants are increasingly helping to streamline the process by performing tasks such as interactively answering user questions or suggesting solutions. Los Alamos National Laboratory (LANL) develops several advanced scientific codes, such as FLAG, which can be used to run multiphysics simulations. With this study, our goal was to develop an AI assistant for FLAG that could help make the process of understanding the software and running physics simulations more efficient. To develop an AI assistant for FLAG, we used a method called retrieval-augmented generation (RAG), which is a technique that uses information from relevant data sources to enhance the accuracy of large language models (LLMs). We used the FLAG user manual and other FLAG documentation as the knowledge base for the RAG system. When a user provides a query, RAG retrieves relevant sections from the knowledge base in response, then uses those excerpts to generate grounded and contextually rich answers. We found that our AI assistant was able to provide context aware answers and source references to user queries. To evaluate performance, we developed a set of 40 benchmark questions and compared the accuracy of the responses to those of two standard LLMs without retrieval. Our AI assistant significantly outperformed the standard LLMs at answering FLAG-related questions, with an 82.5% accuracy rate, compared to 47.5% for both of the standard LLMs. This has the potential to make the process of learning and using FLAG much easier, especially for new users. Ultimately, it supports LANL’s broader mission by empowering scientists and engineers to focus more on discovery and analysis rather than on navigating complex software systems.

97 MATHEMATICS AND COMPUTING

Navigating United States Standards and Regulation for Digital Energy Systems

This report provides an analysis of the U.S. standards and regulatory landscape for digital energy systems, focusing on cybersecurity, safety, and reliability requirements. It examines the interplay between federal mandates, state regulations, voluntary industry standards, and utility-specific policies, highlighting critical gaps between compliance and real-world risk mitigation. While NERC CIP standards enforce cybersecurity for Bulk Electric System assets, distribution-level infrastructure and emerging technologies often fall outside mandatory oversight, creating vulnerabilities. The report identifies systemic challenges such as reliance on self-attestation, uneven state adoption of safety codes, and lagging standards for advanced technologies like battery energy storage and inverter-based resources. Through a detailed gap analysis, it underscores the urgency of proactive risk-based approaches, independent verification, and strategic engagement with state and federal entities. Recommendations include adopting tiered security frameworks, strengthening procurement practices, and addressing emerging technology risks to ensure resilient and secure digital energy infrastructure. This guidance is intended for utilities, regulators, and stakeholders navigating compliance obligations and seeking to enhance cybersecurity and safety beyond minimum standards.

24 - POWER TRANSMISSION AND DISTRIBUTION

Robotics for HVAC applications: A critical review and future perspectives

Recent advances in artificial intelligence (AI), enhanced computational capabilities, and innovations in sensors and hardware have driven the increasing development and application of robots in heating, ventilation, and air conditioning (HVAC) systems. We selected and reviewed 101 studies published between 2005 and 2025, sourced from IEEE Xplore, Scopus, Web of Science, and the ACM Digital Library. To analyze these works, we developed a five-dimensional analytical framework (morphology, sensing, navigation, task execution, and system integration), inspired by the Springer Handbook of Robotics and tailored specifically for robotic applications in HVAC. Based on the reviewed studies, six distinct tasks spanning the entire HVAC lifecycle have been identified. Among the six tasks, inspection and maintenance dominate (59 %), followed by indoor monitoring and auditing (21 %), whereas leakage detection, comfort support, and installation/retrofit remain less explored. To address the identified gaps, this review proposes future research directions including investigating robot-aware HVAC design principles, developing multimodal HVAC sensing and data fusion techniques, enhancing robot training and hardware capabilities, and expanding robotic applications beyond Maintenance and Operations (M&O). The findings from this review inform future robotics research for HVAC applications and ultimately enhance system affordability, energy efficiency, resilience or reliability, and occupant environmental comfort. Moreover, it seeks to inspire researchers to explore the intersections of robotics, computer science, building science, and HVAC engineering fostering advancements in this multidisciplinary field.

AI

A Behavioral Robotics Approach to Radiation Mapping Using Adaptive Sampling

Radiation mapping is a desirable task to automate because of the inherent risks involved and its tedious nature. A novel system was designed to address this by combining various existing technologies, utilizing behavior-based robotics and Bayesian optimization. The system uses a quadruped robot equipped with a manipulator and gamma detector to take measurements at locations that are selected based on the uncertainty of a surrogate model used to estimate the true radiation field. The robot uses input from the world with depth cameras to avoid collisions with the robot’s body, and unreachable points for the end effector are addressed by both allowing for a soft collision with the environment to occur, prompting the system to abandon that point, and varying the exploration tendency of the optimization based on consecutive collisions. This approach provides unique traversability and adaptability over other strategies in the literature. Experiments were performed by placing a Cesium-137 source on the ground and varying geometric setups and an optimization parameter demonstrating the adaptability to diverse environments and the increased robustness resulting from the designed behavior. The results additionally demonstrate that dynamically adjusting the optimization algorithm’s exploration tendency based on the arm’s collision history improves the system’s ability to navigate cluttered environments and construct accurate radiation maps without getting stuck in unreachable areas.

Adams, Joel

Toward particle accelerator machine state embeddings as a modality for large language models

Understanding and diagnosing the state of a particle accelerator requires navigating high-dimensional control system data, often involving hundreds of interdependent parameters. We propose a novel multimodal embedding framework that jointly learns representations of machine states from both numerical control system readouts and natural language descriptions. This enables the translation of complex machine conditions into human-readable summaries while maintaining fidelity to the underlying physical system. The obtained embeddings are subsequently adapted to an open-weights large language model via cross-attention conditioning. We demonstrate a first implementation trained on European XFEL machine state data. This work covers the embedding model architecture, training methodology, and presents initial examples demonstrating the model's capabilities in action. Due to the general concept of machine state, the model can be easily adapted to other facilities and control system environments.

Accelerator Physics

Utility-Scale Operational Consequences for Solar Grid Services

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

14 SOLAR ENERGY