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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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25 records · Page 2

Open Power System Datasets and Open Simulation Engines: A Survey Toward Machine Learning Applications

A major factor behind the success of machine learning (ML) models in multiple domains is the availability and accessibility of large, labeled, and well-organized datasets for training and benchmarking. In comparison, power grid datasets face three major challenges: (i) real-world data is often restricted by regulatory constraints, privacy reasons, or security concerns, making it difficult to obtain and work with; (ii) synthetic datasets, which are created to address these limitations, often have incomplete information and are released using specialized tools, making them inaccessible to the broader community; and, (iii) input-output datasets are difficult to generate through simulation for non-experts because open-source simulators are not known outside the power system community. This survey addresses these challenges by serving as an entry point to publicly available datasets and simulators for researchers venturing in this area. We review the current landscape of open-source power network data, machine models, consumer demand profiles, renewable generation data, and inverter models. We also examine open-source power system simulators, which are crucial for generating high-quality, high-fidelity power grid datasets. We aim to provide a foundation for overcoming data scarcity and advance towards a structured web of datasets and simulators to support the development of ML for power systems.

42 ENGINEERING↗

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Kernel Adaptive Support Vector Machine for Scalable Predictive Maintenance

Application of data-driven solutions across an industry is challenging, since the data are often stored locally, and increasing privacy and security concerns restrict access to the data. In addition, it is highly unlikely that all potential data patterns are captured in a single data source. Because it is highly unlikely that all potential data patterns are captured in a single data source, machine learning (ML) models developed from a single source cannot be robust enough. An alternative is to train the ML model at each source and develop a distributed knowledge discovery and aggregation approach to build global knowledge. In this paper, we develop and demonstrate a distributed ML model, federated transfer learning (FTL), using a multi-kernel-based adaptive support vector machine (MK-A-SVM). For federated learning (FL), the multi-kernel (MK) approach enables feature-specific model aggregation under data heterogeneity; whereas for transfer learning (TL) the adaptive model enables utilization of an aggregated model from a different task. The proposed approach is validated using nuclear power plant (NPP) vertical motor-driven pump data to predict the health condition of vertical motor-driven pumps as an anomaly detection. The efficiency of the proposed approach is also quantified and compared with neural network.

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Studying information recurrence, gatekeeping, and the role of communities during internet outages in Venezuela

Many authoritarian regimes have taken to censoring internet access in order to stop the spread of misinformation, restrict citizens from discussing certain topics, and prevent mobilization, among other reasons. There are several theories about the effectiveness of censorship. Some suggest that censorship will effectively limit the flow of information, whereas others predict that a backlash will form, resulting in ultimately more discussion about the topic. In this work, we analyze the role of communities and gatekeepers during multiple internet outages in Venezuela in January 2019. First, we measure how critical information (e.g., entities and hashtags) spreads during outages focusing on information recurrence and burstiness within and across language and location communities. We discover that information bursts tend to cross both language and location community boundaries rather than being limited to a single community during several outages. Then we identify users who play central roles and propose a novel method to detect gatekeepers—users who prevent critical information from spreading across communities during outages. We show that bilingual and English-speaking users play more central roles compared to Spanish-speaking users, but users inside and outside Venezuela have similar distribution of centrality. Finally, we measure the differences in social network structure before and after each outage event and discuss its effect on how information spreads. We find that with each outage event social connections tend to get less connected with higher mean shortest path, indicating that the effect of censorship makes it harder for information to spread.

97 MATHEMATICS AND COMPUTING↗

Preshaping clear glass at low temperatures

Advances in available glass chemistries and glass processing methods have accompanied and enabled some of the biggest technology revolutions, from the development and mass production of light bulbs to low-loss fiber optics and durable smartphone touchscreens. An emerging generation of low-temperature processing technologies aims to continue this important trend and make a broader array of glass components mass producible. In the issue, Mader et al. (1) describe one such innovation in glass processing—the use of low-temperature injection molding to preshape silica particle–filled composites that can later be transformed into transparent fused silica glass objects. Traditionally, transparent glass objects are manufactured in high volume from molten or softened glass, which is floated, drawn, blown, cast, or blow-molded to a desired shape (see the figure, top). The glass composition and processing technique dictate the working temperature, which is usually quite high (near 1000°C) and often restricts the choice of compatible equipment or limits the choice of glass composition. Because geometry-specific capital investment is required for production, drastic or frequent component design changes or small batches may be cost prohibitive. Alternatively, transparent glass components can also be shaped at ambient temperature from solid glass by a series of subtractive processes, including cutting or multiple stages of grinding, followed by slower processing steps, such as polishing or etching. This approach is somewhat less amenable to mass production, and certain geometries containing tool-inaccessible regions cannot be fabricated in this way. Several emerging glass-shaping technologies aim to reduce the required manufacturing temperatures and still provide access to a broader range of glass compositions and component geometries (see the figure). These approaches use a three-step process. First, a desired shape is preformed at low temperature from a glass-forming, organic-inorganic composite. Next, the preform is dried, and organic materials used to bind particles are removed. Finally, the preform is heated (sintered) well below the glass-melting temperature to densify to transparent glass. Although the second and third steps do occur at increased temperatures, only standard, geometry-agnostic driers and furnaces are required. This strategy builds on the well-studied sol-gel approach to forming monolithic glass, where silica network–forming chemical solutions are poured into molds, slowly dried, and condensed into dense glass without melting (2). In a departure from the sol-gel process, these new technologies use solvents, cross-linkers, and polymers to formulate organic-inorganic composites tuned for compatibility with a particular shaping process, with formats ranging from photocurable liquids to shear-thickening pastes to solids. The composite inorganic loadings are also typically higher than those in the pure sol-gel approach, which drastically reduces shrinkage in comparison.

36 MATERIALS SCIENCE↗

In situ Detection of Plasma Induced Surface Interaction based on Deep Learning based Visual Diagnostics (Technical Report)

It is characteristic for many plasma devices to undergo plasma-material interaction leading to surface erosion. These processes, often not easily detectable, lead to changes in device performance and lifespan. State-of-the-art lifetime tests and wear experiments require over 1000s hours. A self-consistent model for accurately predicting the erosion's effects is not available. In situ detection of these processes is not a trivial task since the surface variations at the early stages have a micron scale. Such limitations not only restrict testing and prediction capabilities but also slow the development of new thrusters and limit mission duration. To address these challenges, an in-situ diagnostic for real-time erosion assessment has been developed, aiming to expedite lifetime testing and broaden experimental campaigns. Several works were dedicated to real-time and in situ monitoring of material erosion during plasma exposure using laser holography, microscopy, and with telemicroscopes. However, the applicability of these approaches is limited due to complexity, cost and less flexibility as they often require placing diagnostic equipment inside the vacuum chamber. In collaboration with Princeton Collaborative Research Facility (PCRF), Princeton Plasma Physics Laboratory (PPPL), a new diagnostic approach is developed, where geometry modifications to the ceramic channel walls were introduced that would result in accelerated channel erosion. We employed Long-distance microscope (LDM) imagery, combined with Deep-Learning based Shape from focus or depth from focus (DFF or SFF) approach, that provides an accessible and cost-effective solution. LDM employs focus variation techniques to continuously capture multiple images of the target object at distinct focal planes. DFF, an optical focus variation method, generates a 3D topographical surface depth map from a sequence of variably focused images. Combined with the developed diagnostic, this approach offers a controllable means to study erosion under accelerated conditions. In this work, we develop Neural Network-based DFF algorithm applicable for LDM data to quantitatively evaluate plasma induced surface modification from LDM data. Next, we develop Deep Learning-based super-resolution depth map image reconstruction technique to increase the resolution of depth maps obtained from DFF algorithm to improve the accuracy of erosion measurements. Thirdly, we develop several image processing techniques to remove noise and improve the quality of depth map image. Here we report the results of initial tests for this approach. An experimental setup designed and built in PPPL was employed that consists of a 3-cm gridded ion source that produces a neutralized argon beam with energies up to 600 eV. A hexagonal boron nitride (h-BN) ceramic target, designed based on computational predictions, was used. Tests were conducted to reconstruct the complex geometry of the target under the lighting conditions of the operated ion source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation

Carbon capture, utilization, and storage (CCUS) technology has significant potential to reduce greenhouse gas (GHG) emissions and mitigate the impact of climate change, particularly in hard to decarbonize industrial and commercial sectors. CCUS involves capturing carbon dioxide (CO 2 ) from industrial processes or power generation and utilizing it for other purposes, such as enhanced oil recovery (EOR), or storing the captured CO 2 underground. CCUS technology can reduce the environmental impact of continued fossil fuel use while smoothing the transition to a low-carbon economy. CCUS can create new economic opportunities, such as the development of new industries and job creation, and can enhance energy security by diversifying energy sources. For these reasons, enabling CCUS has become a key objective of the Biden-Harris administration’s clean energy policy and has received bipartisan support. Despite its environmental and economic potential, CCUS faces multiple barriers to widespread deployment. One of the main challenges is the high cost and technical difficulty of implementing and operating large-scale CCUS infrastructure. CCUS remains a relatively expensive way to reduce carbon emissions (e.g., compared to solar photovoltaic technology’s displacement of coal generation). Additionally, financial incentives and supportive policies like those enacted to support solar photovoltaic development, especially at the state level, are inconsistent or nonexistent, which can discourage investment in CCUS projects. There are also technical challenges associated with safe and secure underground CO 2 storage and the development of new carbon utilization technologies. Public opposition to various aspects of CCUS technologies, ranging from concerns that CCUS will extend reliance on fossil fuels to CCUS infrastructure being sited in disadvantaged communities, is a growing challenge. This paper focuses on another significant barrier to broad CCUS deployment: the need for considerable expansion of the dedicated land-based CO 2 pipeline network in the United States to meet CCUS goals and the unique regulatory challenges to its development. To reach carbon emissions targets in the United States by 2050, CCUS technology will need to be supported by tens of thousands of miles of CO 2 pipelines. Estimates range from a minimum of roughly 29,000 pipeline miles (according to a 2020 Great Plains Institute study) to 66,000 pipeline miles (as per a 2021 Princeton University–led study). As of October 2022, however, the U.S. Department of Transportation (U.S. DOT) reports fewer than 5,400 miles of U.S. pipelines carrying CO 2 . This deficit—and what it means for the prospect of moving substantially larger quantities of CO 2 from source to use or storage—threatens to stifle the development of CCUS projects and technologies identified as an important tool to meet emissions targets. The current regulatory landscape facing CO 2 pipeline development can best be described as uncertain. At the federal level, the U.S. DOT Pipeline and Hazardous Materials Safety Administration (PHMSA) oversees safety regulation of pipelines transporting hazardous materials, including CO 2 upon commencement of operation. However, PHMSA’s definition of CO 2 as “a fluid consisting of more than 90 percent CO 2 molecules compressed to a supercritical state” has not been updated since its 1991 addition to the Federal Register. Because CO 2 can be transported in a gaseous, liquid, or supercritical state (indeed, the physical state of CO 2 can fluctuate within a single pipeline due to environmental changes), doubts persist about the extent of PHMSA’s purview—and raise questions about what, if anything, states should do to address this apparent gap. PHMSA has begun a major revision of its existing rules, but the agency does not expect a first draft before 2024. Economic oversight of CO 2 pipelines is even less clear. The Federal Energy Regulatory Commission (FERC) and Surface Transportation Board (STB)—which regulate the rates of interstate oil/natural gas and non-energy pipelines, respectively—have both declined jurisdiction over interstate CO 2 pipelines. This presumably leaves economic regulation to state and/or local governments, but few if any states have the laws or resources in place to oversee just and reasonable rates. Further, the interstate nature of CO 2 pipeline development creates questions around how different states should align their rate-making decisions. Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation Currently, regulatory responsibilities regarding CO 2 pipeline siting and permitting fall to state and local governments. The variety of laws and regulations across the country, however, creates a maze of requirements for pipeline developers to navigate. To secure necessary permits, most states require pipeline companies to be “common carriers” that provide transport service to the public at uniform rates. However, the specific definition of that term varies. Some states require clear evidence that a pipeline services the public, while others automatically deem any pipeline company transporting energy products or hazardous materials to be a “common carrier”—with little consideration for accessibility to third parties. Other states have eschewed common-carrier terminology entirely, placing private and publicly accessible pipelines on equal footing. Much like the variation in common-carrier requirements, laws governing eminent domain authority to secure rights-of-way (ROW) to commence construction on a planned pipeline route differ by state. Several states have no laws or rules governing CO 2 pipelines. In addition to creating questions about whether long-standing rules for other pipelines (e.g., natural gas or petroleum products) apply to CO 2 , this policy vacuum leaves local governments as the sole authority over sections of pipe within their boundaries. With dozens of counties along a given route, the probability of inconsistent regulation of the same pipeline is significant. Even in states with CO 2 pipeline laws in place, local regulatory attempts to address rising concerns over pipeline routing and safety have triggered lawsuits by pipeline companies seeking to delimit areas of federal, state, and local government responsibility. Meanwhile, legislators across the country have introduced bills to restrict the application of eminent domain to CO 2 pipeline projects, which could threaten a key means of securing ROW that companies cannot secure through negotiation with landowners. Taken separately, any of these regulatory issues—the narrow federal definition of CO 2 , FERC’s and STB’s decisions that CO 2 pipelines are not within their jurisdiction, and the considerable variation in state and local governments’ laws regulating CO 2 pipeline technologies—are extremely difficult to resolve. Adding the required scale of CO 2 pipeline expansion and the currently identified narrow window of time in which to reach climate target goals, the task becomes even more difficult—and raises a host of urgent questions for regulators. How should CO 2 be defined in federal regulations to ensure consistent safety standards across the country? What is the potential impact radius of a CO 2 pipeline rupture, and how should that inform local emergency response? In the absence of centralized federal oversight, what should state legislatures do to increase alignment for interstate CO 2 pipeline projects? This paper intends to serve as a primer for regulators and stakeholders who seek to better understand the regulatory challenges and opportunities facing this critical infrastructure.

42 ENGINEERING↗