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At least 1,225 records · Page 68

Glass formulation and composition optimization with property models: A review

Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed.

Lu, Xiaonan↗

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation↗

Hydropower Geotechnical Foundations: Current Practice and Innovation Opportunities for Low-Head Applications

Hydropower is a renewable energy resource that produces electricity from flowing water under pressure. Engineered hydropower structures, such as dams, are used to create a hydraulic head, enabling a turbinegenerator unit to convert pressurized flow into electricity. While hydropower has been a source of renewable energy since antiquity, new development in the United States has slowed in recent decades. Based on recent resource assessments, the largest opportunity to expand hydropower in the United States is from new stream-reach development (i.e., new hydropower development along stream-reaches that do not currently have hydroelectric facilities or other forms of infrastructure, such as dams). Roughly 75% of identified new stream-reach development potential is from low-head sites (less than 30 ft of head), which typically suffer from smaller power densities and higher normalized costs, given economies of scale. Hydropower developers and other stakeholders are thus interested in strategies to reduce initial capital costs while practicing sustainable development to maximize environmental compatibility with minimal disruption to natural aquatic life, sediment, and water flows. Historically, civil works have represented a significant cost driver for new hydropower development, with the foundation system representing a major cost component and source of uncertainty. The foundation system is the collection of engineered structural features (e.g. cutoff trenches, walls, grouting, anchors) constructed at or below the preconstruction ground surface that interfaces between the overlying structures (superstructures) and the bed material below (subsurface). Development of a hydropower foundation system must consider the various characteristics of the surrounding stream environment and subsurface while adhering to the engineering requirements of the superstructure that it supports. The care of water, excavation, and other construction activities are important features of foundation design and construction. The design and construction cost of the foundation system is largely dependent on the site geology and riverbed composition and is influenced by the level of geotechnical assessment required and conducted. Thus, a hydropower facility’s geotechnical foundation is often highly site-specific, with proper site selection and assessment being important to project success. The foundation system is designed to provide structural stability (of the foundation and dam), limit seepage, ensure public safety, and maintain functionality for the project life, during both construction and facility operations. Inadequate foundation or dam design can result in dam failure and the uncontrolled release of significant volumes of water, which could cause a high number of casualties and extensive property damage downstream of the failure. According to the Association of State Dam Safety Officials, approximately 30% of all historical dam failures in the United States are attributed to foundation or abutment defects, and another 20% are attributed to piping or seepage through the embankment, foundation, or abutment. To ameliorate these safety considerations, foundations often require massive amounts of construction material (e.g., grout, concrete, engineered dam fill) and long construction times. Foundation design also requires significant analysis prior to construction because the initial in-stream and abutment subsurface conditions are site-specific, and sufficient data for them often are lacking. Current practice requires on-site assessment, using expensive drilling and invasive and non-invasive investigation methods, to determine the expected cost of foundation material and treatment. Additionally, foundation construction often requires site dewatering (and other care of water activities), which involves constructing temporary diversion structures upstream and often downstream, called cofferdams, and water diversion systems that route water around the construction site. Cofferdams and water diversion systems can drastically increase construction costs and contribute to environmental disruption, including modification of flow patterns and benthic habitats. Given the technical, economic, and environmental challenges associated with hydropower foundations, opportunities exist to improve the current state of practice and to develop new and innovative solutions to Hydropower is a renewable energy resource that produces electricity from flowing water under pressure. Engineered hydropower structures, such as dams, are used to create a hydraulic head, enabling a turbinegenerator unit to convert pressurized flow into electricity. While hydropower has been a source of renewable energy since antiquity, new development in the United States has slowed in recent decades. Based on recent resource assessments, the largest opportunity to expand hydropower in the United States is from new stream-reach development (i.e., new hydropower development along stream-reaches that do not currently have hydroelectric facilities or other forms of infrastructure, such as dams). Roughly 75% of identified new stream-reach development potential is from low-head sites (less than 30 ft of head), which typically suffer from smaller power densities and higher normalized costs, given economies of scale. Hydropower developers and other stakeholders are thus interested in strategies to reduce initial capital costs while practicing sustainable development to maximize environmental compatibility with minimal disruption to natural aquatic life, sediment, and water flows. Historically, civil works have represented a significant cost driver for new hydropower development, with the foundation system representing a major cost component and source of uncertainty. The foundation system is the collection of engineered structural features (e.g. cutoff trenches, walls, grouting, anchors) constructed at or below the preconstruction ground surface that interfaces between the overlying structures (superstructures) and the bed material below (subsurface). Development of a hydropower foundation system must consider the various characteristics of the surrounding stream environment and subsurface while adhering to the engineering requirements of the superstructure that it supports. The care of water, excavation, and other construction activities are important features of foundation design and construction. The design and construction cost of the foundation system is largely dependent on the site geology and riverbed composition and is influenced by the level of geotechnical assessment required and conducted. Thus, a hydropower facility’s geotechnical foundation is often highly site-specific, with proper site selection and assessment being important to project success. The foundation system is designed to provide structural stability (of the foundation and dam), limit seepage, ensure public safety, and maintain functionality for the project life, during both construction and facility operations. Inadequate foundation or dam design can result in dam failure and the uncontrolled release of significant volumes of water, which could cause a high number of casualties and extensive property damage downstream of the failure. According to the Association of State Dam Safety Officials, approximately 30% of all historical dam failures in the United States are attributed to foundation or abutment defects, and another 20% are attributed to piping or seepage through the embankment, foundation, or abutment. To ameliorate these safety considerations, foundations often require massive amounts of construction material (e.g., grout, concrete, engineered dam fill) and long construction times. Foundation design also requires significant analysis prior to construction because the initial in-stream and abutment subsurface conditions are site-specific, and sufficient data for them often are lacking. Current practice requires on-site assessment, using expensive drilling and invasive and non-invasive investigation methods, to determine the expected cost of foundation material and treatment. Additionally, foundation construction often requires site dewatering (and other care of water activities), which involves constructing temporary diversion structures upstream and often downstream, called cofferdams, and water diversion systems that route water around the construction site. Cofferdams and water diversion systems can drastically increase construction costs and contribute to environmental disruption, including modification of flow patterns and benthic habitats. Given the technical, economic, and environmental challenges associated with hydropower foundations, opportunities exist to improve the current state of practice and to develop new and innovative solutions to challenges frequently encountered with traditional approaches. With this understanding, it is critically important to understand and document the current state of practice for hydropower geotechnical foundations, identify key challenges, and define opportunities for innovative solutions. To this end, this report documents the current state of practice across the three main phases of geotechnical foundation development: (1) geotechnical site assessment, (2) design, and (3) construction for hydropower systems. It also describes the major challenges with conventional approaches and identifies opportunities for innovation to reduce hydropower foundations costs, timelines, and risks. Key takeaways from this report include the following: Approximately 80% of available low-head sites are expected to have foundations on soil beds rather than rock beds, suggesting that rockfill and earthfill dams may be the most cost-effective conventional dam type for new projects.; Geotechnical and geologic investigation activities are time-consuming and expensive but are essential to define the parameters and criteria needed for foundation design.; Certain riverbed soil and bedrock types present significant technical challenges or require expensive foundation construction, which can prove financially prohibitive for low-head project development.; Modular hydropower design and prefabricated modular foundations represent a promising but unproven paradigm for new hydropower development. Design and construction approaches using optimized and highly repeatable, reliable components would benefit project cost, time, and risk but require additional research and development.; Temporary construction features for foundations, including cofferdams, water diversion, and water control systems, can prove costly and have inherent construction risk.; For economically viable development, hydropower geotechnical foundations should be limited to 4 to 15% of the project’s total initial capital costs. Many proposed projects have experienced cost overruns attributable to foundation difficulties or surprises during construction. These overruns may have been due to inadequate investigations, lack of adequate engineering effort to tailor the structures to site geology and topography, and/or contractual terms, among other considerations.; Challenges for hydropower foundations and opportunities for innovative technology solutions are identified in the following areas (consistent with the three main phases of foundation development): Geotechnical site assessment, Foundation design and materials, Construction methods and technology. Ultimately, this report aims to provide information about geotechnical foundations for low-head hydropower and to motivate transformative technologies to support hydropower growth.

13 HYDRO ENERGY↗

H ∞ Control for Energy Dispatch in Autonomous Nanogrid With Communication Delays

This paper proposes an optimal controller and estimator for energy dispatch to balance the power supply and demand considering communication delays. The proposed algorithm involves modeling an autonomous nanogrid (ANG) consisting of distributed energy resources, energy storage systems, loads, an $H$ ∞ controller with a reference power modulation technique, and a state estimator. The ANG was developed to express the dynamic supply-demand energy balance of a nanogird system. Reference power modulation was designed to generate the desired ESS power based on the imbalanced energy. Random communication delays were modeled using a stochastic variable satisfying the Bernoulli random binary distribution. The optimal $H$ ∞ controller and estimator were developed using a linear matrix inequality approach to exponentially stabilize the closed-loop system. Simulations were performed using real daily demand forecasts obtained from the Korea Meteorological Administration to demonstrate the effectiveness of the proposed real-time optimization algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Scalable Technologies Achieving Risk-Informed Condition-Based Predictive Maintenance Enhancing the Economic Performance of Operating Nuclear Power Plants

The primary objective of the research presented in this report is to develop scalable technologies that are deployable across plant assets and across the nuclear fleet to achieve risk-informed predictive maintenance (PdM) strategies at commercial nuclear power plants (NPPs). Over the years, the nuclear fleet has relied on labor-intensive and time-consuming preventive maintenance (PM) programs, driving up operation and maintenance (O&M) costs to achieve high capacity factors. A well-constructed risk-informed PdM approach for an identified plant asset has been developed in this research, taking advantage of advancements in data analytics, machine learning (ML), artificial intelligence (AI), physics-informed modeling, and visualization. These technologies would allow commercial NPPs to reliably transition from current labor-intensive PM programs to a technology driven PdM program, eliminating unnecessary O&M costs. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report (1) reflects the results of work by LWRS Program researchers with PSEG, Nuclear LLC-owned Salem and Hope Creek Nuclear Power Plants; (2) presents utilization of circulating water system (CWS) heterogeneous data and fault modes from both the Salem and Hope Creek nuclear power plant sites to develop salient fault signatures associated with each fault mode; (3) describes the integration of component-level predictive models into a robust system-level model enabled by the federated-transfer learning; (4) describes the development of physics-informed model of circulating water pump and motor; (5) develops a scalable risk and economic model; and (6) outlines the development of a user-centric visualization application. The outcomes presented in this report lays the foundation and provides a much-needed technical basis to focus on explainability and trustworthiness of ML and AI-based technologies, as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Powers of magnetic graph matrix: Fourier spectrum, walk compression, and applications

Magnetic graphs, originally developed to model quantum systems under magnetic fields, have recently emerged as a powerful framework for analyzing complex directed networks. Existing research has primarily used the spectral properties of the magnetic graph matrix to study global and stationary network features. However, their capacity to model local, nonequilibrium behaviors, often described by matrix powers, remains largely unexplored. We present a combinatorial interpretation of the magnetic graph matrix powers through directed walk profiles—counts of graph walks indexed by the number of edge reversals. Crucially, we establish that walk profiles correspond to a Fourier transform of magnetic matrix powers. The connection allows exact reconstruction of walk profiles from magnetic matrix powers at multiple discrete potentials, and more importantly, an even smaller number of potentials often suffices for accurate approximate reconstruction in real networks. This shows the empirical compressibility of the information captured by the magnetic matrix. This fresh perspective suggests further applications; for example, we illustrate how powers of the magnetic matrix can identify frustrated directed cycles (e.g., feedforward loops) and can be effectively employed for link prediction by encoding local structural details in directed graphs.

complex networks↗

eMosaic: Electrification Mosaic Platform for Grid Informed Smart Charging Management (Final Scientific/Technical Report)

ABB (Prime Contractor), in collaboration with its partners at the Utah State University (USU), Idaho National Laboratory, Rocky Mountain Power (RMP), and Electric Power Engineers (EPE), have performed research, development, and wide scale demonstration of a scalable and resilient Electrification Mosaic (eMosaic) platform for Smart Charge Management (SCM) for Electric Vehicle Infrastructure. Work was completed under DE EE0009194, titled “eMosaic Electrification Mosaic Platform for Grid Informed Smart Charging Management”, funded by the US Department of Energy. The project members developed algorithms that provide localized and bulk grid services and that reduce and stabilize costs all the way down the supply chain to the PEV owner through SCM. This platform aggregates telemetry from multiple data sources as pieces of the larger picture including personal, private fleet or transportation EVs, fast chargers and other supply equipment, weather service information, and geographically distributed charging sites such as public lots, garage and retail, and private or shared usage depots. ABB and the project team designed, tested, and improved a charging management system at local/edge and cloud levels. The ultimate objective of the project was to convincingly demonstrate that the developed secure eMosaic plat-form can be readily and favorably adopted by diverse utilities and site owners at scale. This was achieved through a demonstration plan with field deployment at several physical sites across 4 states and additional scalable simulation from high fidelity charging models.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Model for Evaluating the Configuration and Dispatch of PV Plus Battery Power Plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Multi-facility analysis using metered power data to quantify MRI energy use and utility bill costs across scanner operating modes

This study quantifies the energy consumption of magnetic resonance imaging (MRI) scanners across discrete operating modes during routine clinical workflows, based solely on electrical power measurements. Although previous studies have investigated MRI energy consumption within single hospitals or specific clinical settings, this research provides a broader and more systematic analysis. Researchers analyzed electrical power data and applied a previously developed semi-automatic method for identifying MRI operating modes using load duration curves for 20 MRI scanners across four different U.S. healthcare facilities, encompassing outpatient, inpatient, and mixed-use clinical settings. A key innovation is the inclusion of localized hourly utility rates to estimate costs, a parameter absent in prior literature. Key findings indicate significant variability in energy and cost profiles between weekdays and weekends. Scanner characteristics, including magnet strength, manufacturer, vintage, location, and clinical setting, influenced average daily energy consumption and power thresholds for operating modes. Notably, the clinical setting of a scanner predominantly determines its energy use. For example, the scanners in outpatient facilities consumed more energy. The breakdown of energy usage and costs by operating modes showed scanners spend between 61% and 93% of their time in nonproductive modes, with one outlier spending 34%. Average daily energy use for the scanners in the study ranged from 160 to 1069 kWh, with energy costs ranging from $\$$9 to $\$$149. This study uses an existing framework to quantify MRI energy behavior, leading to insights that can enable improved performance and cost savings across different healthcare environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Development of novel dynamic machine learning-based optimization of a coal-fired power plant

The increasing fraction of intermittent renewable energy in the electrical grid is resulting in coal-fired boilers now routinely ramp up and down. The current state-of-the-art operation for such boilers is to apply steady-state, neural network-based optimization to make control decisions in real-time, and this report demonstrates the feasibility of extending this to dynamic, neural network-based optimization using a long short-term memory neural network. A simplified numerical simulation of a t-fired coal boiler and supporting equipment is used to represent a real plant subjected to both steady-state, neural network-based optimization and dynamic, neural network-based optimization. Using the same intervals and a particle swarm optimization algorithm, the dynamic optimization outperforms the steady-state optimization and realizes up to 4.58% improvement in thermal efficiency. Dynamic optimization with a long short-term memory neural network is shown to both be feasible and beneficial for operation of a coal-fired boiler under changing load.

42 ENGINEERING↗

Develop a weather-aware climate model to understand and predict extremes and associated power outages and renewable energy shortages with uncertainty-aware and physics-informed machine learning

Focal Area(s): The focus area is predictive modeling through the use of AI techniques and AI-derived model components with a particular emphasis on extreme weather in Atmospheric Science and power outages and shortages in Energy Science. Science Challenge: Predicting weather extremes (e.g., heavy precipitation, strong wind, and large hailstones), and weather-related power system outages and shortages can mitigate economic losses, save lives, support renewables integration, and improve power system resiliency. However, currently, the poor reliability and large uncertainty associated with the weather extreme prediction in the current climate models make the problem intractable. The key challenges are: (1) physical factors like green-house gases (GHGs), aerosols, and land use and land cover (LULC) can significantly impact extreme storms, but the understanding of these impacts is limited, particularly globally; (2) the convective permitting resolutions needed to model severe convective storms and their impacts are computationally prohibitive with global climate models (GCMs); (3) interactions between weather extremes and power system outages are complex and subject to great uncertainty. Current outage prediction models are short lead (~ 3 days), which do not allow for long-time planning of energy production and distribution. Moreover, we have limited capacity to predict weather events leading to sustained shortages in a renewable-energy-dominated power system. These challenges drive motivation for mechanistic understanding and reliable and efficient predictive modeling of extremes and their impacts from the sub-seasonal to long term projections.

54 ENVIRONMENTAL SCIENCES↗

Secure NTP Implementation for Power System Synchronization

Network Time Protocol (NTP), originally developed in the 1980s, remains one of the most widely adopted protocols for synchronizing clocks over Internet Protocol (IP)-based networks. It distributes time with millisecond-level accuracy across Ethernet-based systems and continues to be a standard in both enterprise and operational technology environments.

97 MATHEMATICS AND COMPUTING↗

Energy Efficient, Cost-Effective Power and Co-Generation Technologies: Techno-Environmental Analysis

Development of energy solutions for addressing grid resiliency and energy efficiency while lowering greenhouse gas emissions is critical in today’s energy scenario. Chemical energy provides on demand power. Cogeneration technologies offer numerous benefits in meeting the growing energy demand while lowering the impact on environment. Utilization of waste heat from prime movers in conjunction with energy efficient heat pumps and renewable photovoltaics is an attractive approach. Efficient utilization of available resources to support current and future building energy needs targeting grid resiliency, energy and environmental security via co-generation approaches is the focus of this study. A detailed techno-environmental analysis of hybrid system configurations consisting of conventional and emerging technologies utilizing natural gas, electric grid, and renewable power resources along with heat recovery systems and heat pump technologies are analyzed and presented. The key objective is to present integrated system configurations and thermodynamic analysis of various co-generation systems suitable for providing building energy. Design solutions targeting low carbon footprint and high energy efficiency are presented.

Cheekatamarla, Praveen↗

AlGaInAs/InP semiconductor lasers with an ultra-narrow waveguide and an increased electron barrier

Semiconductor lasers based on AlGaInAs/InP heterostructures with an ultra-narrow waveguide and an increased electron barrier layer are developed. It is shown that the use of this waveguide in conjunction with profiled doping ensures a balance between internal optical losses and heat resistance. Additional use of strained wide-bandgap layers as blocking barriers limiting electron leakage from the active region makes it possible to increase the output power at the same pump current. The developed lasers with a stripe contact 100 μm wide demonstrate at room temperature an output optical power of 4.0 – 4.4 W (pump current 14 A) in a continuous-wave regime and 15 – 17 W (100 A) in a pulsed regime (100 ns, 1 kHz) at wavelengths of 1450 – 1500 nm. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗