Experimental assessment of communication delay's impact on connected automated vehicle speed volatility and energy consumption
Not Available
33 ADVANCED PROPULSION SYSTEMS↗
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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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Traffic Control via Connected and Automated Vehicles (CAVs): An Open-Road Field Experiment with 100 CAVs
The CIRCLES project aims to reduce instabilities in traffic flow, which are naturally occurring phenomena due to human driving behavior. Also called “phantom jams” or “stop-and-go waves,” these instabilities are a significant source of wasted energy. Toward this goal, the CIRCLES project designed a control system, referred to as the MegaController by the CIRCLES team, that could be deployed in real traffic. Our field experiment, the MegaVanderTest (MVT), leveraged a heterogeneous fleet of 100 longitudinally controlled vehicles as Lagrangian traffic actuators, each of which ran a controller with the architecture described in this article. The MegaController is a hierarchical control architecture that consists of two main layers. The upper layer is called the Speed Planner and is a centralized optimal control algorithm. It assigns speed targets to the vehicles, conveyed through the LTE cellular network. The lower layer is a control layer, running on each vehicle. It performs local actuation by overriding the stock adaptive cruise controller, using the stock onboard sensors. The Speed Planner ingests live data feeds provided by third parties as well as data from our own control vehicles and uses both to perform the speed assignment. The architecture of the Speed Planner allows for the modular use of standard control techniques, such as optimal control, model predictive control (MPC), kernel methods, and others. The architecture of the local controller allows for the flexible implementation of local controllers. Corresponding techniques include deep reinforcement learning (RL), MPC, and explicit controllers. Depending on the vehicle architecture, all onboard sensing data can be accessed by the local controllers or only some. Likewise, control inputs vary across different automakers, with inputs ranging from torque or acceleration requests for some cars to electronic selection of adaptive cruise control (ACC) setpoints in others. The proposed architecture technically allows for the combination of all possible settings proposed previously, that is {Speed Planner algorithms} × {local Vehicle Controller algorithms} × {full or partial sensing} × {torque or speed control}. As a result, most configurations were tested throughout the ramp up to the MegaVandertest (MVT).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Shunt-Connected FACTS and Synchronous Condensers
In recent years, the electric-transmission system has undergone a significant transformation marked by a greater integration of renewable-energy sources like wind and solar, the phasing out of thermal generation plants, and a concerted effort towards electrifying energy consumption. To keep pace with the integration of renewable-energy sources and the escalating demands of industries and households, it is imperative to expand and modernize the existing power infrastructure. These upgrades are essential to maintain grid stability, enhance power delivery, and boost overall efficiency of the system. However, challenges have emerged with the growing complexity of power grids, particularly in the realms of voltage control, transient stability, and power-quality management.
24 - POWER TRANSMISSION AND DISTRIBUTION↗
Connected Residential Communities with Enhanced Resiliency and both Customer and Utility Attributes (Final Technical Report)
This report is a compilation of information from Quarter Progress Reports submitted to the Department of Energy’s Office of Energy Efficiency Building Technologies Office (BTO) by SunPower Corporation. The report has been uploaded to OSTI by DOE as a substitute for the required Final Technical Report which was never received from the project recipient.
14 SOLAR ENERGY↗
GeoBridge: Connecting Communities to Geothermal Information and Opportunities: Preprint
The geothermal community is well established with long-standing events, organizations, and tools that are known across the geothermal community. But many of these tools and resources are located behind pay walls, require memberships, or are otherwise difficult to find, especially for people looking to join the geothermal community. These barriers to access can prevent outsiders from discovering valuable geothermal resources, limiting the geothermal community's potential for collaboration with other communities, such as clean energy entrepreneurs looking to expand into geothermal energy. The Department of Energy's (DOE) GeoBridge serves to bring these communities together by acting as a single, publicly accessible, searchable portal that facilitates easy access to available geothermal knowledge and information. It works to expand and diversify the pool of geothermal stakeholders by providing in-roads to geothermal information and community resources. It helps build a stronger geothermal community; one inclusive of individuals and groups from a variety of different backgrounds, including potential investors and start-up companies looking to accelerate innovation in geothermal technologies. By linking communities to geothermal information, analysis and expertise, GeoBridge serves as a launch point, directing interested parties to existing data and tools, events, educational resources, STEM programs, permitting and regulatory information, and other resources that can be used to evaluate, promote, and discover geothermal opportunities.
access↗
GeoBridge: Connecting Communities to Geothermal Information and Opportunities
The geothermal community is well established with long-standing events, organizations, and tools that are known across the geothermal community. But many of these tools and resources are located behind pay walls, require memberships, or are otherwise difficult to find, especially for people looking to join the geothermal community. These barriers to access can prevent outsiders from discovering valuable geothermal resources, limiting the geothermal community's potential for collaboration with other communities, such as clean energy entrepreneurs looking to expand into geothermal energy. The Department of Energy's (DOE) GeoBridge serves to bring these communities together by acting as a single, publicly accessible, searchable portal that facilitates easy access to available geothermal knowledge and information. It works to expand and diversify the pool of geothermal stakeholders by providing in-roads to geothermal information and community resources. It helps build a stronger geothermal community; one inclusive of individuals and groups from a variety of different backgrounds, including potential investors and start-up companies looking to accelerate innovation in geothermal technologies. By linking communities to geothermal information, analysis and expertise, GeoBridge serves as a launch point, directing interested parties to existing data and tools, events, educational resources, STEM programs, permitting and regulatory information, and other resources that can be used to evaluate, promote, and discover geothermal opportunities.
access↗
Twin networks in hexagonal close-packed metals: Morphology, connectivity, and incompatibilities
Not Available
36 MATERIALS SCIENCE↗
Towards gradient multimaterial toolpath generation for direct ink writing with connected fermat spirals
This work describes advances towards a reproducible, parametrically defined algorithm for generating graded multimaterial toolpaths for direct ink writing. Expanding on the existing Fermat space-filling algorithm and coupling with image-driven processing techniques, we demonstrate the fabrication of multimaterial structures. Here, material composition is encoded within toolpaths by parsing hue values from a multi-colored image. By performing dynamic velocity compensation based on local curvature and Euclidean distance filtering, internal voids are mitigated while optimizing print fidelity. Here, the work opens new avenues for designing complex toolpaths with locally programmable composition.
3D Printing↗
Constraining Galaxy-Halo connection using machine learning
We investigate the potential of machine learning (ML) methods to model small-scale galaxy clustering for constraining Halo Occupation Distribution (HOD) parameters. Our analysis reveals that while many ML algorithms report good statistical fits, they often yield likelihood contours that are significantly biased in both mean values and variances relative to the true model parameters. This highlights the importance of careful data processing and algorithm selection in ML applications for galaxy clustering, as even seemingly robust methods can lead to biased results if not applied correctly. ML tools offer a promising approach to exploring the HOD parameter space with significantly reduced computational costs compared to traditional brute-force methods if their robustness is established. Using our ANN-based pipeline, we successfully recreate some standard results from recent literature. Properly restricting the HOD parameter space, transforming the training data, and carefully selecting ML algorithms are essential for achieving unbiased and robust predictions. Among the methods tested, artificial neural networks (ANNs) outperform random forests (RF) and ridge regression in predicting clustering statistics, when the HOD prior space is appropriately restricted. We demonstrate these findings using the projected two-point correlation function (w p (r p )), angular multipoles of the correlation function (ξ ℓ (r)), and the void probability function (VPF) of Luminous Red Galaxies from Dark Energy Spectroscopic Instrument mocks. Our results show that while combining w p (r p ) and VPF improves parameter constraints, adding the multipoles ξ 0 , ξ 2 , and ξ 4 to w p (r p ) does not significantly improve the constraints.
cosmology↗
Providing for occupant experience in optimized connected energy communities - A critical review
Not Available
Ramsey, Philip↗
The connection between the chromatic numbers of a hypergraph and its 1-intersection graph
A well known problem from an excellent book of Lovász states that any hypergraph with the property that no pair of hyperedges intersect in exactly one vertex can be properly 2-colored. Motivated by this as well as recent works of Keszegh and of Gyárfás et al. we study the 1-intersection graph of a hypergraph. The 1-intersection graph encodes those pairs of hyperedges in a hypergraph that intersect in exactly one vertex. We prove for k ϵ {2, 4} that all hypergraphs whose 1-intersection graph is k-partite can be properly k-colored.
1-intersection graph of hypergraphs↗
Techno-economic feasibility of borehole thermal energy storage system connected to geothermal heat pumps for seasonal heating load of two buildings in Fairbanks, Alaska
Borehole thermal energy storage (BTES) is an effective solution for managing imbalanced heating and cooling loads in cold regions. This study evaluated the long-term feasibility of a BTES system in the Fairbanks area, Alaska, through building energy modeling, resource characterization, and numerical modeling. The system was designed to store waste heat from a nearby coal power plant during summer and provide thermal energy during winter to geothermal heat pumps supplying heating loads in two buildings. Heating load profiles were modeled for the buildings using EnergyPlus, and the results indicated the annual heating load was 5.6 times greater than the cooling load. 40 borehole heat exchangers were pre-designed approximately 100 m away from the two buildings in terms of land availability and regulatorily optimized depth. The 20-year performance of the designed BTES system under two operational scenarios—one with a 5-year preheating period and one without—was numerically modeled using subsurface temperature and properties characterized through the literature review and thermal response tests. Both scenarios demonstrated that the BTES has the capacity to fully cover the heating loads in the two buildings throughout the 20-year lifetime. Production temperatures at central wells were 33 % higher on average than at outer wells in both scenarios. The 5-year preheating period increased subsurface and extraction temperatures, and correspondingly annual average and total thermal energy production was higher for 8 years than in the scenario without the preheating period. These results highlight the long-term reliability and sustainability of the BTES system in meeting heating demands over its lifetime, with the preheating period offering potential performance improvements. Implementing the BTES system in cold regions with high heating demand, such as Fairbanks, Alaska, could provide a long-term, sustainable energy solution for managing imbalanced heating and cooling loads.
15 GEOTHERMAL ENERGY↗
Connecting ambient toxicity testing with community-level responses of benthic macroinvertebrates in an impacted stream in East Tennessee, USA
Single-species laboratory toxicity tests are a standard tool for evaluating potential impairment of freshwater systems; however, it remains uncertain how well they reflect community-level impacts in natural environments. This study presents a multi-decadal dataset (2005-2025) pairing ambient toxicity testing with macroinvertebrate surveys along Bear Creek on the Oak Ridge Reservation (Tennessee, USA) downstream of an industrial complex to assess the ability of laboratory tests using stream water to track community-level effects. Biannual three-brood Ceriodaphnia dubia tests from 2005 to 2025 often showed reduced reproduction at select sites. Integrating water quality data showed strong positive correlations between sublethal toxicity and specific conductance. Macroinvertebrate diversity metrics, family-level occurrence, and densities were also associated with conductance and contemporaneous C. dubia responses. Laboratory-measured sublethal toxicity was a stronger indicator of macroinvertebrate change than conductance alone, although responses varied among sites and seasons. At the site with the highest diversity, densities and richness of Ephemeroptera, Plecoptera, Trichoptera (EPT) and non-EPT taxa were significantly related to C. dubia reproduction, with greater toxicity corresponding to lower diversity. At the family level, some pollution-tolerant taxa were more prevalent and at higher densities during periods of sublethal toxicity, while some sensitive families were absent or reduced. These patterns may reflect site-specific mixtures of acute and chronic stressors, with laboratory toxicity tests more effectively capturing short-term impacts. Overall, these multi-decadal observations suggest that laboratory toxicity tests can help track water-quality changes linked to shifts in aquatic community diversity, despite variable responses reflecting the complexity of dynamic stressors in this impacted freshwater system.
Stevenson, Louise [ORNL] (ORCID:0000000349679897)↗
Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning
The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.
54 ENVIRONMENTAL SCIENCES↗
Unraveling the connection of electronic and phononic structure with mechanical properties of commercial AZ80 alloy
Not Available
Sharma, Prince (ORCID:0000000218338785)↗