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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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At least 919 records · Page 51

Robot for Investigations and Assessments of Nuclear Areas

RIANA is a remote controlled Robot dedicated for Investigations and Assessments of Nuclear Areas. The development of RIANA is motivated by the need to have at disposal a proven robot, tested in hot cells; a robot capable of remotely investigate and characterise the inside of nuclear facilities in order to collect efficiently all the required data in the shortest possible time. It is based on a wireless medium sized remote carrier that may carry a wide variety of interchangeable modules, sensors and tools. It is easily customised to match specific requirements and quickly configured depending on the mission and the operator's preferences. RIANA integrates localisation and navigation systems. The robot will be able to generate / update a 2D map of its surrounding and exploring areas. The position of the robot is given accurately on the map. Furthermore, the robot will be able to autonomously calculate, define and follow a trajectory between 2 points taking into account its environment and obstacles. The robot is configurable to manage obstacles and restrict access to forbidden areas. RIANA allows an advanced control of modules, sensors and tools; all collected data (radiological and measured data) are displayed in real time in different format (chart, on the generated map...) and stored in a single place so that may be exported in a convenient format for data processing. This modular design gives RIANA the flexibility to perform multiple investigation missions where humans cannot work such as: visual inspections, dynamic localization and 2D mapping, characterizations and nuclear measurements of floor and walls, non destructive testing, samples collection: solid and liquid. The benefits of using RIANA are: - reducing the personnel exposures by limiting the manual intervention time, - minimizing the time and reducing the cost of investigation operations, - providing critical inputs to set up and optimize cleanup and dismantling operations. (authors)

42 ENGINEERING↗

20-kW Bi-directional Wireless Power Transfer System with Energy Storage System Connectivity

The severity of the economic impact caused by grid outages has been the driving factor for creating innovative solutions that increases interest for the deployment of distributed energy resources to reduce the impact of grid outages. This study presents a novel way of providing export power using bi-directional wireless power transfer (WPT) systems for ac grid side power and mobile energy storage systems (ESSs) connectivity. The proposed concept here interfaces the EV batteries to the AC grid and also can redirect the power from the stationary ESS to grid, to EV batteries, or both simultaneously; providing the capabilities of an uninterrupted power supply (UPS). Results demonstrate the performance and the functionality of the system with overall efficiencies 93% to 97%, depending on the operating mode.

Onar, Omer↗

A Novel Bi-directional AC/DC - DC/AC Wireless Power Transfer System for Grid Support Applications

The severity of the economic impact caused by grid outages has been the driving factor for creating innovative solutions that increases interest for the deployment of distributed energy resources to reduce the impact of grid outages. This paper presents a novel topology for providing export power applications. Proposed topology can be used for grid (primary)-side of bi-directional wireless power transfer (WPT) systems, mobile energy storage systems (ESSs), and electric vehicle (EV) batteries. The proposed concept here achieves energy transfer between sources by using a hybrid frequency bi-directional ac/dc converter without an additional front-end converter stage compared to the conventional systems. Due to inherent merit of the proposed bi-directional ac/dc converter, ac input with 60 Hz grid frequency can be directly transferred through the wireless coils and can be directly converted to the dc. Results demonstrate the performance and the functionality of the single-phase bi-directional system with the input / output of 110 V ac,rms and 200 V dc at 1 kW power. Full paper will demonstrate the converter operation at 10 kW power level with additional features and control aspects.

Asa, Erdem↗

Recent Development of Frequency Estimation Methods for Future Smart Grid

The frequency estimated by the Phasor Measurement Unit (PMU) is a critical index of power system status and supports many smart grid applications. The future smart grid features high penetration of renewables and more fast-moving power electronics inverters but raises challenges to the reliable frequency estimation. This article presents three methods to address these challenges. First, an enhanced zero-crossing algorithm was developed to track the fast-changing frequency in system dynamics. Second, we propose a technology that can tolerate the system transient and suppress the outliers. Third, an algorithm was developed to export high time-resolution frequency estimations with minimum computational effort. All of the proposed methods are realized in hardware and compared with classical frequency estimation methods. The testing results indicate that the proposed methods have excellent performance. They can be used in future PMUs and provide reliable and high time resolution data for smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Grid-Forming Inverters for Stability Improvements in Bulk Power Systems with High Inverter-Based Resources Penetration

The grid-forming inverter (GFM) has been considered recently as a means to enhance grid stability in areas with Inverter-based Resources (IBRs) concentration. This paper assesses the potential improvements the GFM can bring to Bulk-power Systems (BPS) through two distinct studies. The first study was conducted on West Texas in ERCOT with presence of more than 35GW of IBRs, the Grid-Following (GFL) batteries were replaced with GFM batteries. The results demonstrate that the GFM significantly improved the voltage profile and active power injection during and after a fault. The second study focused on a local area within ERCOT grid. In this case, a battery operating as GFL within the local study area was replaced with a GFM battery. The findings clearly illustrate that GFM can strengthen the area and allow a higher IBRs power generation and a higher power export from the local study area.

Quedan, Amro↗

DC-Connected Solar Plus Storage Modeling and Analysis for Behind-the-Meter Systems in the System Advisor Model

A detailed model for PV plus DC-connected batteries was developed. This model was compared to an existing ACconnected battery model in the System Advisor Model (SAM) tool using a hypothetical Honolulu residence with a PV plus storage system. The stand-alone PV system was shown to provide the most value; however due to the increased difficulty of PV systems being approved for grid interconnection in Hawaii, it is valuable to install an AC or DC connected battery to enable full PV self-consumption under a less restrictive interconnection option. In that case both battery systems enabled full PV selfconsumption at the residence, requiring no power to be exported to the grid. The DC-connected battery system captured energy from the PV array which would have also been clipped due to inverter limitations. For a PV system with DC/AC ratio of 1.23, the battery configurations produced net-present values within 1% of each other, but when the DC/AC ratio increased to 1.85, the DC-connected system increased the net-present value by 13%.

14 SOLAR ENERGY↗

Dual Context: Leveraging Structured Application Context for Code Generation and Runtime Feature Activation via Chat Interfaces

Integrating artificial intelligence (AI) capabilities into software applications typically involves two common paths. For developers, AI assists in generating and documenting source code and other related software engineering efforts. For users, AI assists them through question-and-answer exchanges via chatbots. Both approaches have their value, but neither effectively leverages the modularity of component-based architectures that modern web application frameworks offer. We implement a proof of concept within a centralized suite of applications used for the Atmospheric Radiation Measurement (ARM) Data Center Operational Tools, where we introduce a third integration path through the ARM Context Engine (ACE). ACE is a context driven system that uses structured contextual specifications to enable Large Language Models (LLMs) to render interactive and feature-rich user interface (UI) components directly within chat responses, alongside or in place of conventional text outputs. These specifications serve two important purposes across what we call code context and UI context. Code context provides AI-assisted development tools with structured application knowledge beyond raw code, including component relationships, architectural patterns and schematic information, enabling the generation of consistent, well-structured code. UI context defines the rules for enabling and rendering component features at runtime based on the user's natural language input, allowing end users to activate capabilities such as data export, filtering, and pagination within chat responses, without requiring code changes or redeployment. We demonstrate, through a comparative evaluation against general-purpose AI chatbots, that context-driven component rendering provides interactive capabilities that text-based responses cannot replicate, including deterministic component behavior, application-consistent design language, and on-demand feature activation. A development effort comparison further shows that features that traditionally require multi-step development cycles can be activated with a single naturallanguage request. In this ongoing work, we present ACE as an emerging approach to AI integration that positions modular, well-documented software architecture as the foundation for AI-ready applications. ACE treats context as a shared resource across both development and user-facing AI, bringing cohesion to conventionally disconnected efforts, bridging developer tooling and end-user capabilities within a single framework.

Tadimeti, Vijay [ORNL]↗

Inter-IBR Oscillation Modes

This research addresses the following question: For a weak grid with multiple-IBRs, what is the nature of oscillation modes? The analysis of a system consisting of two identical IBRs offers a glimpse of the picture. It shows that the system has a weak-grid mode and an inter-IBR mode. For the weak-grid mode, two IBRs work as an aggregated one to interact with the grid. Furthermore, this mode is sensitive to IBR exporting power level and grid strength. For the inter-IBR mode, two IBRs oscillate against each other. This mode is less sensitive to grid strength and power level.

14 SOLAR ENERGY↗

Quantifying the impact of microgrid location and behavior on transmission network congestion

This work presents a preliminary analysis considering impact of a grid-connected microgrid on network transmission of the power system. The locational marginal prices of the power system are used to strategically place the microgrid to avoid congestion problems. In addition, a Monte Carlo simulation approach is implemented to confirm that network congestion can be attenuated if appropriate price-based signals are set to define the import and export dynamic between the two systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Protistan community composition and metabolism in the North Pacific Subtropical Gyre: Influences of mesoscale eddies and depth

Abstract Marine protists and their metabolic activities are intricately tied to the cycling of nutrients and the flow of energy through microbial food webs. Physiochemical changes in the environment, such as those that result from mesoscale eddies, may impact protistan communities, but the effects that such changes have on protists are poorly known. A metatranscriptomic study was conducted to investigate how eddies affected protists at adjacent cyclonic and anticyclonic eddy sites in the oligotrophic ocean at four depths from 25 to 250 m. Eddy polarity impacted protists at all depths sampled, although the effects of eddy polarity were secondary to the impact of depth across the depth range. Eddy‐induced vertical shifts in the water column yielded differences in the cyclonic and anticyclonic eddy protistan communities, and these differences were the most pronounced at and just below the deep chlorophyll maximum. An analysis of transcripts associated with protistan nutritional physiology at 150 m revealed that cyclonic eddies may support a more heterotrophic community, while anticyclonic eddies promote a more phototrophic community. The results of this study indicate that eddies alter the metabolism of protists particularly in the lower euphotic zone and may therefore impact carbon export from the euphotic zone.

Microbiology↗

Opportunities to advance the synthesis of ecology and evolution

Despite decades of research on the interactions between ecology and evolution, opportunities still remain to further integrate the two disciplines, especially when considering multispecies systems. Here, we discuss two such opportunities. First, the traditional emphasis on the distinction between evolutionary and ecological processes should be further relaxed as it is particularly unhelpful in the study of microbial communities, where the very notion of species is hard to define. Second, key processes of evolutionary theory such as adaptation should be exported to hierarchical levels higher than populations to make sense of biodiversity dynamics. Together, we argue that broadening our perspective of eco-evolutionary dynamics to be more inclusive of all biodiversity, both phylogenetically and hierarchically, will open up fertile new research directions and help us to address one of the major scientific challenges of our time, that is, to understand and predict changes in biodiversity in the face of rapid environmental change.

54 ENVIRONMENTAL SCIENCES↗

High methane concentrations in tidal salt marsh soils: Where does the methane go?

Abstract Tidal salt marshes produce and emit CH 4 . Therefore, it is critical to understand the biogeochemical controls that regulate CH 4 spatial and temporal dynamics in wetlands. The prevailing paradigm assumes that acetoclastic methanogenesis is the dominant pathway for CH 4 production, and higher salinity concentrations inhibit CH 4 production in salt marshes. Recent evidence shows that CH 4 is produced within salt marshes via methylotrophic methanogenesis, a process not inhibited by sulfate reduction. To further explore this conundrum, we performed measurements of soil–atmosphere CH 4 and CO 2 fluxes coupled with depth profiles of soil CH 4 and CO 2 pore water gas concentrations, stable and radioisotopes, pore water chemistry, and microbial community composition to assess CH 4 production and fate within a temperate tidal salt marsh. We found unexpectedly high CH 4 concentrations up to 145,000 μmol mol −1 positively correlated with S 2− (salinity range: 6.6–14.5 ppt). Despite large CH 4 production within the soil, soil–atmosphere CH 4 fluxes were low but with higher emissions and extreme variability during plant senescence (84.3 ± 684.4 nmol m −2 s −1 ). CH 4 and CO 2 within the soil pore water were produced from young carbon, with most Δ 14 C‐CH 4 and Δ 14 C‐CO 2 values at or above modern. We found evidence that CH 4 within soils was produced by methylotrophic and hydrogenotrophic methanogenesis. Several pathways exist after CH 4 is produced, including diffusion into the atmosphere, CH 4 oxidation, and lateral export to adjacent tidal creeks; the latter being the most likely dominant flux. Our findings demonstrate that CH 4 production and fluxes are biogeochemically heterogeneous, with multiple processes and pathways that can co‐occur and vary in importance over the year. This study highlights the potential for high CH 4 production, the need to understand the underlying biogeochemical controls, and the challenges of evaluating CH 4 budgets and blue carbon in salt marshes.

54 ENVIRONMENTAL SCIENCES↗

HIV influences clustering and intracellular replication of hepatitis C virus

We report HCV and HIV coinfection is common and HIV leads to increased HCV viraemia and accelerated disease progression. However, the biological basis of this interaction remains poorly understood and little is known about the impact of HIV on HCV replication at the cellular level. We analysed HCV RNA, based on single-cell laser-capture microdissection, in liver biopsies from monoinfected (n = 4) and HCV/HIV-coinfected (n = 5) participants. HCV RNA was assayed in 3200 hepatocytes with information of spatial position. We compared HCV RNA levels and clustering properties of infection between mono- and coinfected participants, and developed a mathematical model of infection. Although the median plasma HCV RNA level and the fraction of infected cells were comparable in monoinfected (7.0 log 10 IU/mL and ~ 30%) and coinfected (7.3 log 10 IU/mL and ~ 40%) participants, the median HCV RNA per infected hepatocyte in monoinfected (2.8IU) was significantly lower than in coinfected (8.2IU) participants (p = .03). Clustering of infected cells was more prominent in monoinfected participants (91% of samples) than in coinfected participants (~48%), p = .0045, suggesting that spatial spread may be influenced by HIV coinfection. Interestingly, when clustering does occur, the size of clusters is similar in both types of infection. A mathematical model of infection suggested that HIV allows higher intracellular accumulation of HCV RNA by impeding the export of HCV RNA. Our observations show that HIV coinfection impacts intracellular accumulation of HCV RNA and the clustering of HCV-infected cells, but to a less extent the fraction of HCV-infected cells.

59 BASIC BIOLOGICAL SCIENCES↗

Reduced global plant respiration due to the acclimation of leaf dark respiration coupled with photosynthesis

Summary Leaf dark respiration ( R d ) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models. We hypothesized that R d and Rubisco carboxylation capacity ( V cmax ) at 25°C ( R d,25 , V cmax,25 ) are coordinated so that R d,25 variations support V cmax,25 at a level allowing full light use, with V cmax,25 reflecting daytime conditions (for photosynthesis), and R d,25 / V cmax,25 reflecting night‐time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5‐yr warming experiment, and spatially using an extensive field‐measurement data set. We compared the results to three published alternatives: R d,25 declines linearly with daily average prior temperature; R d at average prior night temperatures tends towards a constant value; and R d,25 / V cmax,25 is constant. Our hypothesis accounted for more variation in observed R d,25 over time ( R 2 = 0.74) and space ( R 2 = 0.68) than the alternatives. Night‐time temperature dominated the seasonal time‐course of R d , with an apparent response time scale of c. 2 wk. V cmax dominated the spatial patterns. Our acclimation hypothesis results in a smaller increase in global R d in response to rising CO 2 and warming than is projected by the two of three alternative hypotheses, and by current models.

Plant Sciences↗

Technoeconomic Design of a Geothermal-Enabled Cold Climate Zero Energy Community

Development of a zero energy community is more costly in northern cold climates than in moderate regions. Building energy loads are higher, thanks to the colder weather, and site solar photovoltaics (PV) are less productive due to lower solar incidence and misalignment with the buildings’ energy needs (summer production, winter demands). Geothermal energy production can support a zero energy community through application of energy efficiency (demand design), geothermal production (supply design), and asset dispatch as an integrated techno-economic package. This article presents the process used to explore geothermal system integration, our findings, and technical challenges for community-scale adoption of geothermal as an electric and thermal resource. We show that under a wide range of conditions, community-scale geothermal electric power and direct-use thermal energy is economically competitive with “business-as-usual” design and construction practices for zero energy communities. Furthermore, geothermal-produced energy will be self-consumed to a much greater extent than PV, resulting in significant reductions in site energy import and export. We conclude that under appropriate conditions, community-scale geothermal can be the most economically favorable energy resource for northern-climate zero energy community developments. Ongoing geothermal research and development to improve performance and reduce costs will further enhance the value proposition for community-scale geothermal technologies. We expect that including geothermal power and thermal energy in zero energy community design can improve its cost-effectiveness and therefore enhance the benefits of zero energy in more northern climates.

15 GEOTHERMAL ENERGY↗

Development of a Method for Shape Optimization for a Gas Turbine Fuel Injector Design Using Metal-Additive Manufacturing

Adjoint shape optimization has enabled physics-based optimal designs for aerodynamic surfaces. Additive manufacturing (AM) makes it possible to manufacture complex shapes. However, there has been a gap between optimal and manufacturable surfaces due to the inherent limitations of commercial computational fluid dynamics (CFD) codes to implement geometric constraints during adjoint computation. In such cases, the design sensitivities are exported and used to perform constrained shape modifications using parametric information stored in computer aided design (CAD) files to satisfy manufacturability constraints. However, modifying the design using adjoint methods in CFD solvers and performing constrained shape modification in CAD can lead to inconsistencies due to different shape parameterization schemes. This paper describes a method to enable the simultaneous optimization of the fluid domain and impose AM manufacturability constraints, resolving one of the key issues of geometry definition for isogeometric analysis. Similar to a grid convergence study, the proposed method verifies the consistencies between shape parameterization techniques present within commercial CAD and CFD software during mesh movement as a part of the adjoint shape optimization routine. By identifying the appropriate parameters essential to a shape optimization study, the error metric between the different parameterization techniques converges to demonstrate sufficient consistencies for justifiable exchange of data between CAD and CFD. For the identified shape optimization parameters, the error metric to measure the deviation between the two parameterization schemes lies within the AM laser-powder bed fusion (L-PBF) process tolerance. Additionally, comparison for subsequent objective function calculations between iterations of the optimization loop showed acceptable differences within 1% variation between the modified geometries obtained using the two parameterization schemes. This method provides justification for the use of multiphysics guided adjoint design sensitivities computed in CFD software to perform shape modifications in CAD to incorporate AM manufacturability constraints during the shape optimization loop such that optimal designs are also additively manufacturable.

33 ADVANCED PROPULSION SYSTEMS↗

Demonstrating SolarPILOT’s Python API Through Heliostat Optimal Aimpoint Strategy Use Case

SolarPILOT is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s1 System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This paper presents a new, full-featured, Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT’s capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instance with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layouts; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying solar field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating solar field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux distribution; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot’s functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize power tower CSP research. This enables CSP researchers to perform analysis that was previously not possible through SolarPILOT’s existing interfaces. This paper discusses the capabilities of CoPylot and presents a use case wherein we demonstrate optimal solar field aiming strategies.

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

Techno-Economic Analysis of Green Hydrogen Energy Storage in a Cryogenic Flux Capacitor

Abstract The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH2) storage and liquid hydrogen (LH2) region near the normal boiling point. Hydrogen storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (∼1,000 m2/g) allows its storage performance to easily exceed capacities of high-pressure GH2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 36% over a simple tank filled with GH2 at the same operating temperature and pressure. For LH2 conditions, the CFC is shown to operate at improved densities, but testing is ongoing. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce green GH2. The TEA compares pure hydrogen produced at a small scale for a 25 MW power system and at a large scale in a 500 MW power system. The system allowed for hydrogen imports and exports at a set price with a tank sized for 10 hours of power production. The two power producing technologies are a combined cycle gas turbine (CCGT) and hydrogen fuel cells. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH), and levelized cost of storage (LCOS) are developed based on the capital cost and operating cost of the systems. The results are shown for current costs using a 2021 benchmark and DOE projections for cost improvements by 2030. The TEA showed that onsite hydrogen generation from SMR has an LCOH of about 1.4 to 2 USD per kg over the life of the plant and the PV hydrogen production LCOH is about 5.2 to 5.5 USD per kg. The LCOS of conventional GH2 systems is estimated to be $210/MWh and cost of storage for LH2 systems is $205/MWh for fuel cell systems and $249/MWh for CCGT systems. CFC improved the LCOS of all these systems to $198/MWh, $191/MWh and $233/MWh respectively. The LCOE also improved with conventional systems between $171/MWh and $228/MWh improved by CFC to between $167/MWh and $212/MWh. Using projections for improvement in costs following DOE’s goals by 2030, green hydrogen improved to as low as $78/MWh LCOS and LCOE for conventional cases. CFC improved over conventional storage with the lowest LCOS being $62/MWh and the lowest LCOE being $73/MWh. These results correspond to an LCOH of $2/kg. Finally, the TEA shows how LCOE is improved for hydrogen conditioning and storage over conventional systems and caverns in the 10 to 50 hour range.

08 HYDROGEN↗