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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 703 records · Page 39

Recent Progress on 2012 SAT for UVOIR Coatings

Astronomical observations in the Far Ultraviolet (FUV) spectral region are some of the more challenging due to the very distant and faint objects that are typically searched for in cosmic origin studies such as origin of large scale structure, the formation, evolution, and age of galaxies and the origin of stellar and planetary systems. These challenges are driving the need to improve the performance of optical coatings over a wide spectral range that would increase reflectance in mirrors and reduced absorption in dielectric filters used in optical telescope for FUV observations. This paper will present recent advances in reflectance performance for Al+MgF2 mirrors optimized for Lyman-alpha wavelength by performing the deposition of the MgF2 overcoat at elevated substrate temperatures. We will also present optical characterization of little studied rare-earth fluorides such as GdF3 and LuF3 that exhibit low-absorption over a wide wavelength range and could therefore be used as high refractive index alternatives fordielectric coatings at FUV wavelengths.

LiF↗

Advanced Modified High Performance Synthetic Jet Actuator with Curved Chamber

The advanced modified high performance synthetic jet actuator with optimized curvature shape chamber (ASJA-M) is a synthetic jet actuator (SJA) with a lower volume reservoir or chamber. A curved chamber is used, instead of the conventional cylinder chamber, to reduce the dead volume of the jet chamber and increase the efficiency of the synthetic jet actuator. The shape of the curvature corresponds to the maximum displacement (deformation) profile of the electroactive diaphragm. The jet velocity and mass flow rate for the ASJA-M will be several times higher than conventional piezoelectric actuators.

Xu, Tian-Bing↗

FUV Reflectance of Recently Prepared Al Protected with AlF3: COR Program Technology Development

Astronomical observations in the Far Ultraviolet (FUV) spectral region are some of the more challenging due to the very distant and faint objects that are typically searched for in cosmic origin studies such as origin of large scale structure, the formation, evolution, and age of galaxies and the origin of stellar and planetary systems. These challenges are driving the need to improve the performance of optical coatings over a wide spectral range that would increase reflectance in mirrors and reduced absorption in dielectric filters used in optical telescope for FUV observations. This paper will present recent advances in reflectance performance for Al+AlF3 mirrors optimized for Lyman-alpha wavelength by performing the deposition of the AlF3 overcoat at elevated substrate temperatures.

MOS"↗

Aerostructural Weight Estimation for a Transonic Truss-Braced Wing using the Higher-fidelity Conceptual Design and Structural Optimization Tool

Continued development and enhancements of the Higher-fidelity Conceptual Design and structural optimization (HCDstruct) tool has been driven largely by advanced aircraft concepts of interest to NASA. While previous versions of HCDstruct were limited to hybrid wing body (HWB) and generalized tube and wing (TW) aircraft concepts, the latest version of HCDstruct supports the analysis of Truss-Braced Wing (TBW) aircraft concepts, where users can model both high and low wing configurations as well as strut and jury geometries parametrically. Additionally, new methods for modeling advanced composite materials within HCDstruct have been implemented. These recent tool enhancements were demonstrated for an independent assessment of the NASA/Boeing SUGAR Phase VI Mach 0.8 Transonic Truss-Braced Wing (TTBW) concept.

Zachary D. Windous↗

Manufacturing, Characterization and Terrestrial Passive Radiative Cooling Performance of Nanofibrous PTFR-PEO Composite Thermal Coatings

Passive heat management is desirable in many applications since it can reduce the energy expended for cooling, for example, in buildings and automobiles. Specifically, materials with wavelength-dependent reflectance and emittance can manage incident solar fluxes while enabling passive radiative cooling by thermal emission. This study demonstrates the use of polymeric nanofibers, specifically polytetrafluoroethylene (PTFE) and polyethylene oxide (PEO) composite, as thermal coatings for passive temperature control. Employing the electrospinning fabrication process, we engineer nano and micro-scale fibrous structures, studying the influence of fabrication parameters, such as precursor material concentration and rotating collector speed, on fiber geometry and optical properties. To understand the role of material and fiber geometry on optical performance, we characterize various samples' spectral reflectance, absorptance, and transmittance using spectrophotometers interfaced with integrating spheres. The results show the potential of nanofabricated PTFE-PEO coatings as promising candidates for passive thermal control. We highlight their competitive edge by comparing their solar reflectance and emittance values to existing passive radiative thermal control materials. In essence, this study contributes to advancing passive heat management technologies, offering insights into optimizing material composition and fabrication techniques for enhanced performance in various applications.

Chieloka Ibekwe↗

Evaluating the Impact of Managed EV Charging for Reliable Operation of Bulk Power Systems with High Non-Dispatchable Generation

The growth of electric vehicles (EVs) and variable-generation (VG) sources introduces new challenges for power-system operations. This study introduces a modeling framework and evaluates five EV charging strategies under projected 2040 grid conditions in the Evergy service territory with high non-dispatchable generation. Using realistic EV behavior and generation models, their impacts on system peak demand, ramp rate, and reserve capacity are evaluated. Results show that only the peak-avoidance strategy effectively reduces system peak demand, while decentralized strategies-particularly cost based dynamic charging-can exacerbate peaks due to synchronized user behavior. However, ramp-rate minimization strategy significantly reduce the stress on dispatchable generation achieving the lowest maximum absolute ramp rate (MARR) (56.81 MW) and lowest reserve requirement (2.39 GW). In contrast, unmanaged and TOU random strategies increase the stress on dispatchable generation sources with increased MARR and reserve requirements. These findings highlight the importance of coordinated, system-aware managed charging strategies to ensure reliable and affordable grid operation in the presence of EVs and VG sources.

14 - SOLAR ENERGY↗

Design for Manufacturing Tool for Automated Fiber Placement Structures - Verification and Validation

A tool has been developed to address the growing Design for Manufacturing needs for composite structures, specifically those manufactured with automated fiber placement. This manufacturing approach presents unique challenges associated with puckers and wrinkling, tow overlaps and gaps, fiber deviation, and laminate strength. Achieving a satisfactory laminate design usually requires finding compromises between those four areas. The developed tool, dubbed the Central Optimizer, assists with the process of balancing competing design metrics in automated fiber placement. This tool was developed under the NASA Advanced Composites Consortium with input from industry partners. Under this program, the Central Optimizer has been exercised on three different structures to verify its functionality and validate ability to improve the design process for automated fiber placement structures.

August T Noevere↗

Airport Ground Support Equipment Infrastructure & Logistics Electrification Assessment Tool: 2025 Data Development, Modeling and Analysis for DFW

The aviation industry is increasingly turning to modernize freight facilities by integrating electric Ground Support Equipment (eGSE) to enhance operational efficiency of freight facility moving vehicles and equipment. Airports worldwide are adopting eGSE to streamline cargo movement, reduce fuel and maintenance costs, and improve logistics coordination.1 North America, with its advanced aviation infrastructure, leads this transition, leveraging Internet of things (IoT)-enabled automation and zero emission technologies to boost reliability and reduce human errors.2 Electrification of freight facility moving vehicles and equipment boosts turnaround times, improves equipment reliability, and optimizes logistics coordination, giving operators a competitive advantage. With rising fuel price volatility and the pressure to meet stringent performance benchmarks, airports are focusing on cost-effective, scalable solutions for long-term financial and operational gains. To further accelerate electrification, airports are integrating Zero Emission Vehicles (ZEVs) into rental car fleets and deploying electric baggage carts, requiring strategic investments in charging infrastructure. 3 The shift, however, presents challenges, such as limited technical expertise, high capital costs, and complex procurement processes. By forging strategic partnerships, leveraging advanced technologies, and optimizing infrastructure investments, airports can create a resilient, future-ready ecosystem that enhances the movement of people and goods through electrification-driven efficiency. Supported by the U.S. Department of Energy (DOE) Vehicle Technologies Office (VTO), this electrification effort provides a scalable, cost-effective solution to improve airport freight operations. Through targeted investments and innovation, airports enhance efficiency, reduce costs, and meet performance benchmarks while advancing toward a resilient, electrified future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

The primary goals of this project are identifying hidden geothermal resources in the USA and designing profitable enhanced geothermal systems (EGS). Many non-obvious processes and parameters could characterize geothermal resources and could control the ultimate energy potential of geothermal fields. Diverse datasets (e.g., geology, geochemistry, geophysics, satellite, airborne geophysics) are available to help characterize geothermal resources, but this data is sparse and multi-scale. This has hindered attempts to leverage the datasets for geothermal exploration and profitable EGS design. Recent advancements in machine learning (ML) give promise to overcome these issues. Modern ML methods and tools can (1) analyze large datasets, (2) assimilate model ensembles that include a multitude of inputs and outputs, (3) process sparse datasets, (4) perform transfer learning between sites with different data quality, (5) extract hidden geothermal signatures from field and simulation data, (6) label geothermal resources and processes, (7) identify high-value data acquisition targets, and (8) guide geothermal exploration and production by selecting optimal exploration, production, and drilling strategies. In this work, we implement ML-based geothermal exploration and an enhanced geothermal systems (EGS) design tool to achieve the above goals. Our exploration tool is GeoThermalCloud (GTC) EGS design tool is GeoDT-ML. GTC (github.com/SmartTensors/GeoThermalCloud.jl) utilizes a LANL unsupervised ML platform called SmartTensors (https://tensors.lanl.gov/) to automate data analyses and interpretations by extracting hidden signatures to identify geothermal prospects. It enables the identification of critical measurements needed to identify geothermal resource signatures. GeoDT-ML (github.com/SmartTensors/GeoThermalCloud.jl/tree/master/) adds coupling to GeoDT (https://github.com/GeoDesignTool/GeoDT.git) for stochastic EGS design optimization and performance prediction. GeoDT-ML leverages recent advances in deep learning and high-performance computing. Contributors to this effort include LANL, PNNL, Google, Stanford, and Julia Computing.

15 GEOTHERMAL ENERGY↗

Apollo Lightcraft Project

This second year of the NASA/USRA-sponsored Advanced Aeronautical Design effort focused on systems integration and analysis of the Apollo Lightcraft. This beam-powered, single-stage-to-orbit vehicle is envisioned as the shuttlecraft of the 21st century. The five person vehicle was inspired largely by the Apollo Command Module, then reconfigured to include a new front seat with dual cockpit controls for the pilot and co-pilot, while still retaining the 3-abreast crew accommodations in the rear seat. The gross liftoff mass is 5550 kg, of which 500 kg is the payload and 300 kg is the LH2 propellant. The round trip cost to orbit is projected to be three orders of magnitude lower than the current space shuttle orbiter. The advanced laser-driven 5-speed combined-cycle engine has shiftpoints at Mach 1, 5, 11 and 25+. The Apollo Lightcraft can climb into low Earth orbit in three minutes, or fly to any spot on the globe in less than 45 minutes. Detailed investigations of the Apollo Lightcraft Project this second year further evolved the propulsion system design, while focusing on the following areas: (1) man/machine interface; (2) flight control systems; (3) power beaming system architecture; (4) re-entry aerodynamics; (5) shroud structural dynamics; and (6) optimal trajectory analysis. The principal new findings are documented. Advanced design efforts for the next academic year (1988/1989) will center on a one meter+ diameter spacecraft: the Lightcraft Technology Demonstrator (LTD). Detailed engineering design and analyses, as well as critical proof-of-concept experiments, will be carried out on this small, near-term machine. As presently conceived, the LTD could be constructed using state of the art components derived from existing liquid chemical rocket engine technology, advanced composite materials, and high power laser optics.

Myrabo, Leik N.↗

Scalable Unit Commitment with Security Constrained AC Power Flow via ADMM and Hybrid Modeling Strategies

This research introduces a more efficient way to optimize power grid operations, breaking the problem into manageable steps and using advanced mathematical techniques to speed up calculations. By incorporating smart heuristics, improved preprocessing, and contingency analysis, the approach allows operators to make better decisions faster. These innovations enhance our understanding of how to optimize energy generation, making it possible to anticipate failures before they happen, reduce system costs, and improve overall grid performance. Ultimately, this research helps bridge the gap between theoretical models and real-world applications, paving the way for a smarter, more resilient power grid. This research directly benefits the public by making electricity more affordable, reliable, and sustainable. By improving how power grids schedule and distribute electricity, the project helps energy providers reduce operational costs, which can lead to lower electricity prices for consumers. Additionally, the ability to predict and prevent power system failures enhances grid reliability, reducing the likelihood of blackouts that can disrupt homes, businesses, and critical infrastructure such as hospitals. From an environmental perspective, optimizing power generation reduces energy waste and lowers carbon emissions, contributing to cleaner air and a more sustainable energy system. Furthermore, with extreme weather events becoming more frequent, these advancements make the power grid more resilient, ensuring communities are better prepared for emergencies and natural disasters. By strengthening the nation's energy infrastructure, this research plays a crucial role in improving economic stability, public safety, and environmental sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Predicting Fuel Properties and Emissions for Advanced Biofuels for Diesel Engines (CRADA Final Report)

The project will investigate variations in biofuel composition and optimize performance in combustion for conventional and future compression ignition engines. It will evaluate a variety of bio-derived molecules in the diesel range that can be produced using technology in ExxonMobil’s portfolio as well as fuels that cover the range of potential molecular structures for robust model development. Changes in fuel/air premixing and stratification in advanced engines could alter the relationship between fuel properties and performance in comparison to current generation spray combustion approaches. NREL experience in fuel and combustion modeling will enable development of general rules for predicting performance of a wide range of biofuel options.

33 ADVANCED PROPULSION SYSTEMS↗

Surpassing millisecond coherence in on chip superconducting quantum memories by optimizing materials and circuit design

The performance of superconducting quantum circuits for quantum computing has advanced tremendously in recent decades; however, a comprehensive understanding of relaxation mechanisms does not yet exist. In this work, we utilize a multimode approach to characterizing energy losses in superconducting quantum circuits, with the goals of predicting device performance and improving coherence through materials, process, and circuit design optimization. Using this approach, we measure significant reductions in surface and bulk dielectric losses by employing a tantalum-based materials platform and annealed sapphire substrates. With this knowledge we predict the relaxation times of aluminum- and tantalum-based transmon qubits, and find that they are consistent with experimental results. We additionally optimize device geometry to maximize coherence within a coaxial tunnel architecture, and realize on-chip quantum memories with single-photon Ramsey times of 2.0 – 2.7 ms, limited by their energy relaxation times of 1.0 – 1.4 ms. These results demonstrate an advancement towards a more modular and compact coaxial circuit architecture for bosonic qubits with reproducibly high coherence.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Development of a Digital Twin for Hydrogen Dispersion and Safety Assessment in an Electrolyzer Based Hydrogen Production Facility

Digital twin models are virtual representations of physical systems that use real-time data to simulate and optimize performance. This study presents the development and initial implementation of a digital twin (DT) for the electrolyzer-based hydrogen production facility at NREL's Advanced Research on Integrated Energy Systems (ARIES), focused on enhancing safety and optimizing sensor placement through physics-based simulations and metadata integration. The DT incorporates detailed facility-specific information, including component layout, leak locations, and controlled release parameters, to model hydrogen dispersion under varying environmental conditions. Using steady-state computational fluid dynamics (CFD) simulations informed by real meteorological data, such as wind speed, direction, and vertical wind profiles, the DT enables visualization of hydrogen plume behavior and spatial concentration distributions. Comparative analysis between high and low wind speed scenarios illustrates the significant influence of wind dynamics on plume shape and extent, with horizontal momentum dominating dispersion at higher speeds, while buoyancy effects become more prominent under low wind conditions. These simulations generate a rich dataset embedded within the DT, allowing users to assess potential leak outcomes and identify optimal sensor locations based on concentration thresholds. The model supports scenario-based analysis to guide safety strategies and equipment deployment for open-area hydrogen infrastructure. The digital twin thus serves as a dynamic platform for virtual prototyping, providing predictive insight into hydrogen behavior and enhancing risk-informed decision-making. This initial phase establishes a validated foundation for future integration of transient, uncontrolled leak scenarios and real-time sensor feedback, positioning the DT as a critical tool for safety design, operational planning, and adaptive monitoring in hydrogen systems. Overall, the approach demonstrates the value of combining environmental data with digital simulations to inform safer and more efficient deployment of hydrogen technologies.

08 HYDROGEN↗

Advances and trends in structures and dynamics; Proceedings of the Symposium, Washington, DC, October 22-25, 1984

Among the topics discussed are developments in structural engineering hardware and software, computation for fracture mechanics, trends in numerical analysis and parallel algorithms, mechanics of materials, advances in finite element methods, composite materials and structures, determinations of random motion and dynamic response, optimization theory, automotive tire modeling methods and contact problems, the damping and control of aircraft structures, and advanced structural applications. Specific topics covered include structural design expert systems, the evaluation of finite element system architectures, systolic arrays for finite element analyses, nonlinear finite element computations, hierarchical boundary elements, adaptive substructuring techniques in elastoplastic finite element analyses, automatic tracking of crack propagation, a theory of rate-dependent plasticity, the torsional stability of nonlinear eccentric structures, a computation method for fluid-structure interaction, the seismic analysis of three-dimensional soil-structure interaction, a stress analysis for a composite sandwich panel, toughness criterion identification for unidirectional composite laminates, the modeling of submerged cable dynamics, and damping synthesis for flexible spacecraft structures.

Noor, A. K.↗

ASEAN Technical Exchange Workshop for System Operators, Regulators, and Policymakers

This presentation provides an in-depth exploration of power system planning, cross-border electricity trading, and battery energy storage systems (BESS), offering actionable insights for system operators, regulators, and policymakers. The first section delves into power system planning and analysis, focusing on capacity expansion models and resource adequacy studies, including their role in optimizing system efficiency, managing emissions, and addressing system reliability risks. Key considerations, such as integration of transmission into generation planning and the forecasting versus optimization of customer distributed energy resources (DER) technologies, are explored. The session highlights critical trade-offs in spatial granularity and model runtimes, as well as the feasibility of aligning distribution investments with capacity expansion efforts. The second section examines cross-border electricity trading, with an emphasis on resource adequacy concepts such as reliability targets, loss of load expectation (LOLE), and planning reserve margins (PRM). Case studies on reserve market design and coordination across US regions provide insights into improving reserve deliverability and managing interregional power balance and congestion. This section also addresses market-to-market congestion management, including advanced strategies for high-voltage direct current (HVDC) optimization and ancillary service delivery. Finally, the presentation covers the rapid evolution of Battery Energy Storage Systems (BESS), highlighting their operational growth, regulatory frameworks, and use cases in grid flexibility, energy storage, and reliability. The discussion focuses on the benefits of BESS for system stability, resilience, and integration of renewable energy, offering insights into its role as a vital component in the transition toward a more sustainable and flexible grid. Key performance parameters, such as throughput, round-trip efficiency, and state of charge, are also examined.

25 ENERGY STORAGE↗

Orbit transfer vehicle engine study, phase A, extension 1: Volume 2: Study results

Because of the advantage of the Advanced Expander Cycle Engine brought out in initial studies, further design optimization and comparative analyses were undertaken. The major results and conclusion derived are summarized. The primary areas covered are (1) thrust chamber geometry optimization, (2) expander cycle optimization, (3) alternate low thrust capability, (4) safety and reliability, (5) development risk comparison, and (6) cost comparisons. All of the results obtained were used to baseline the initial design concept for the OTV Advanced Expander Cycle Engine Point Design Study.

Mellish, J. A.↗

Experimental Validation of Advanced Dispersed Fringe Sensing (ADFS) Algorithm Using Advanced Wavefront Sensing and Correction Testbed (AWCT)

Large aperture telescope commonly features segment mirrors and a coarse phasing step is needed to bring these individual segments into the fine phasing capture range. Dispersed Fringe Sensing (DFS) is a powerful coarse phasing technique and its alteration is currently being used for JWST.An Advanced Dispersed Fringe Sensing (ADFS) algorithm is recently developed to improve the performance and robustness of previous DFS algorithms with better accuracy and unique solution. The first part of the paper introduces the basic ideas and the essential features of the ADFS algorithm and presents the some algorithm sensitivity study results. The second part of the paper describes the full details of algorithm validation process through the advanced wavefront sensing and correction testbed (AWCT): first, the optimization of the DFS hardware of AWCT to ensure the data accuracy and reliability is illustrated. Then, a few carefully designed algorithm validation experiments are implemented, and the corresponding data analysis results are shown. Finally the fiducial calibration using Range-Gate-Metrology technique is carried out and a <10nm or <1% algorithm accuracy is demonstrated.

Dispersed Fringe Sensing (DFS)↗