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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Spin-transparent storage rings for quantum computing

Spin-transparent storage rings, where any spin direction repeats after one full turn, can be used in conjunction with ion traps as a new quantum computing platform [1]. Advantages of spin-transparent rings for quantum computing include: large numbers of stored qubits; long quantum coherence times of up to several hours; long storage lifetimes; and room temperature operation. These exceptional qualities mean rings could provide a scalable way to implement algorithms with deep complexity requiring many quantum operations while simultaneously providing a large number of qubits. This new platform where the qubit has long quantum coherence time can also be used as a quantum sensor or a part of a quantum memory.

Accelerator Physics↗
DOE OSTI2024

ML-based Dimension Reduction Strategies

Deep learning (DL)--based surrogate models have achieved success in various applications in carbon capture and storage (CCS). However, the model training on high-dimensional spaces is computationally expensive and impractical for large-scale and complex geological models, because the models usually contain hundreds of thousands to millions of grid cells, each with a set of parameters. Furthermore, the high cost of generating training data with sufficient variation is another limitation of model training on high-dimensional spaces, which may result in overfitting and reduce the model efficiency and prediction performance. We proposed the workflow incorporating dimension reduction methods and deep learning models, which aim to extract the latent variables of input parameters and output state variables, and then build the mapping function at the latent spaces. The proposed workflow can significantly reduce the computational complexity in solving both forward and inverse problems compared to models trained on high-dimensional spaces. Dimensionality reduction models showed great potential in workflows for fast reservoir simulation, history matching, prior model generation, visualization, and more, ultimately enhancing DL model performance in related SMART Work Packages.

Hosseini, Seyyed↗
NASA NTRS1981

Solar heated office complex--Greenwood, South Carolina

Report contains thorough docuumentation of project meeting 85 percent of building heat requirements. System uses roof mounted recirculating water solar panels and underground hot water energy storage. Aluminum film reflectors increase total solar flux captured by panels.

Source record↗
NASA NTRS1988

A simplified, general-purpose deep-space ranging correlator design

A much-simplified, yet more general-purpose multi-channel deep-space ranging system correlator design that was used in past JPL spacecraft ranging systems is described. The method applies to detection of both single-component and multiple-component ranging codes, in either sequential (mu) or composite (pi) transmitted forms, and using either pseudonoise or square-wave components. Using this design, the Phobos Probe ranging system correlator computational complexity was reduced by over three orders of magnitude in multiply-and-add circuits and 45,000 bits of accumulator storage.

Tausworthe, R. C.↗
DOE OSTI2024

Application Guide for the Cyber-Resilient Design Framework for Hybrid Systems

As the energy landscape evolves, hybrid power plants—integrating multiple renewable energy sources (e.g., solar, wind, and battery storage) with the bulk power electric system—play a crucial role in meeting growing energy demands. However, with a hybrid power plant’s increased number of components, complex network connectivity and digitization of controls, these systems face growing cybersecurity risks. To help mitigate these risks, Idaho National Laboratory (INL) presents this application guide specifically designed for operators and systems engineers to evaluate the cybersecurity resilience of their hybrid power plant’s design.

14 SOLAR ENERGY↗
DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

Close to real life

NASA's Numerical Aerodynamic Simulation (NAS) facility for CFD modeling of highly complex aerodynamic flows employs as its basic hardware two Cray-2s, an ETA-10 Model Q, an Amdahl 5880 mainframe computer that furnishes both support processing and access to 300 Gbytes of disk storage, several minicomputers and superminicomputers, and a Thinking Machines 16,000-device 'connection machine' processor. NAS, which was the first supercomputer facility to standardize operating-system and communication software on all processors, has done important Space Shuttle aerodynamics simulations and will be critical to the configurational refinement of the National Aerospace Plane and its intergrated powerplant, which will involve complex, high temperature reactive gasdynamic computations.

Peterson, Victor L.↗
DOE OSTI2024

Light–Material Interactions Using Laser and Flash Sources for Energy Conversion and Storage Applications

Abstract This review provides a comprehensive overview of the progress in light–material interactions (LMIs), focusing on lasers and flash lights for energy conversion and storage applications. We discuss intricate LMI parameters such as light sources, interaction time, and fluence to elucidate their importance in material processing. In addition, this study covers various light-induced photothermal and photochemical processes ranging from melting, crystallization, and ablation to doping and synthesis, which are essential for developing energy materials and devices. Finally, we present extensive energy conversion and storage applications demonstrated by LMI technologies, including energy harvesters, sensors, capacitors, and batteries. Despite the several challenges associated with LMIs, such as complex mechanisms, and high-degrees of freedom, we believe that substantial contributions and potential for the commercialization of future energy systems can be achieved by advancing optical technologies through comprehensive academic research and multidisciplinary collaborations.

Materials Science↗
DOE OSTI2024

Elucidating the Transition of 3D Morphological Evolution of Binary Alloys in Molten Salts with Metal Ion Additives

Molten salts serve as effective high-temperature heat transfer fluids and thermal storage media used in a wide range of energy generation and storage facilities, including concentrated solar power plants, molten salt reactors and high-temperature batteries. However, at the salt–metal interfaces, a complex interplay of charge-transfer reactions involving various metal ions, generated either as fission products or through corrosion of structural materials, takes place. Simultaneously, there is a mass transport of ions or atoms within the molten salt and the parent alloys. The precise physical and chemical mechanisms leading to the diverse morphological changes in these materials remain unclear. Here, to address this knowledge gap, this work employed a combination of synchrotron X-ray nanotomography and electron microscopy to study the morphological and chemical evolution of Ni-20Cr in molten KCl-MgCl 2 , while considering the influence of metal ions (Ni 2+ , Ce 3+ , and Eu 3+ ) and variations in salt composition. Our research suggests that the interplay between interfacial diffusivity and reactivity determines the morphological evolution. The summary of the associated mass transport and reaction processes presented in this work is a step forward toward achieving a fundamental comprehension of the interactions between molten salts and alloys. Overall, the findings offer valuable insights for predicting the diverse chemical and structural alterations experienced by alloys in molten salt environments, thus aiding in the development of protective strategies for future applications involving molten salts.

36 - MATERIALS SCIENCE↗
NASA NTRS1994

Robotic tape library system level testing at NSA: Present and planned

In the present of declining Defense budgets, increased pressure has been placed on the DOD to utilize Commercial Off the Shelf (COTS) solutions to incrementally solve a wide variety of our computer processing requirements. With the rapid growth in processing power, significant expansion of high performance networking, and the increased complexity of applications data sets, the requirement for high performance, large capacity, reliable and secure, and most of all affordable robotic tape storage libraries has greatly increased. Additionally, the migration to a heterogeneous, distributed computing environment has further complicated the problem. With today's open system compute servers approaching yesterday's supercomputer capabilities, the need for affordable, reliable secure Mass Storage Systems (MSS) has taken on an ever increasing importance to our processing center's ability to satisfy operational mission requirements. To that end, NSA has established an in-house capability to acquire, test, and evaluate COTS products. Its goal is to qualify a set of COTS MSS libraries, thereby achieving a modicum of standardization for robotic tape libraries which can satisfy our low, medium, and high performance file and volume serving requirements. In addition, NSA has established relations with other Government Agencies to complete this in-house effort and to maximize our research, testing, and evaluation work. While the preponderance of the effort is focused at the high end of the storage ladder, considerable effort will be extended this year and next at the server class or mid range storage systems.

Shields, Michael F.↗
NASA NTRS2003

Software for Managing Parametric Studies

The Information Power Grid Virtual Laboratory (ILab) is a Practical Extraction and Reporting Language (PERL) graphical-user-interface computer program that generates shell scripts to facilitate parametric studies performed on the Grid. (The Grid denotes a worldwide network of supercomputers used for scientific and engineering computations involving data sets too large to fit on desktop computers.) Heretofore, parametric studies on the Grid have been impeded by the need to create control language scripts and edit input data files painstaking tasks that are necessary for managing multiple jobs on multiple computers. ILab reflects an object-oriented approach to automation of these tasks: All data and operations are organized into packages in order to accelerate development and debugging. A container or document object in ILab, called an experiment, contains all the information (data and file paths) necessary to define a complex series of repeated, sequenced, and/or branching processes. For convenience and to enable reuse, this object is serialized to and from disk storage. At run time, the current ILab experiment is used to generate required input files and shell scripts, create directories, copy data files, and then both initiate and monitor the execution of all computational processes.

Yarrow, Maurice↗
NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Testbed Results with Energy Storage

Electrified aircraft propulsion (EAP) research is a priority of the National Aeronautics and Space Administration (NASA) for its potential to increase propulsion system efficiency, performance, and operability at the subsystem and vehicle levels while decreasing emissions. These EAP systems demand more advanced control algorithms due to increased complexity. NASA has developed a reconfigurable, hardware-in-the-loop rig to verify control algorithm performance using a sub-scale electro-mechanical system. A novel capability of this rig is the ability to test full scale EAP control algorithms on a sub-scale representation of the electro-mechanical system without turbomachinery/rotors. A novel feature is the use of a physical energy storage device within the electro-mechanical system. A dual spool, parallel hybrid-electric turbofan architecture and energy management control system is tested with the goal of verifying the ability to obtain turbomachinery model operability benefits while controlling sub-scale electro-mechanical hardware. Pre-test predictions of the turbofan model, control, and rig performance were obtained through simulation using a software model of the rig. Theoretical results showing the true performance of the turbofan model were obtained through a software simulation using full-scale mechanical shaft models. The paper compares theoretical, predicted, and actual test results from the turbofan model, energy management control and rig perspectives. The results show that the presence of sub-scale electro-mechanical hardware did not inhibit the energy management algorithm from achieving turbomachinery operability benefits.

hybrid↗
NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Testbed Results with Energy Storage

Electrified aircraft propulsion (EAP) research is a priority of the National Aeronautics and Space Administration (NASA) for its potential to increase propulsion system efficiency, performance, and operability at the subsystem and vehicle levels while decreasing emissions. These EAP systems demand more advanced control algorithms due to increased complexity. NASA has developed a reconfigurable, hardware-in-the-loop rig to verify control algorithm performance using a sub-scale electro-mechanical system. A novel capability of this rig is the ability to test full scale EAP control algorithms on a sub-scale representation of the electro-mechanical system without turbomachinery/rotors. A novel feature is the use of a physical energy storage device within the electro-mechanical system. A dual spool, parallel hybrid-electric turbofan architecture and energy management control system is tested with the goal of verifying the ability to obtain turbomachinery model operability benefits while controlling sub-scale electro-mechanical hardware. Pre-test predictions of the turbofan model, control, and rig performance were obtained through simulation using a software model of the rig. Theoretical results showing the true performance of the turbofan model were obtained through a software simulation using full-scale mechanical shaft models. The paper compares theoretical, predicted, and actual test results from the turbofan model, energy management control and rig perspectives. The results show that the presence of sub-scale electro-mechanical hardware did not inhibit the energy management algorithm from achieving turbomachinery operability benefits.

hybrid↗
DOE OSTI2024

Energy Systems Integration Facility (ESIF): World-Class Systems Integration Capabilities and Research

The Energy Systems Integration Facility (ESIF), located at the National Renewable Energy Laboratory (NREL) South Table Mountain campus, is a world-renowned user facility for research and development of modern, advanced, and clean energy technologies. ESIF is distinguished by its continuously evolving, highly integrated systems that span throughout the building, connecting research capabilities across multiple laboratories and test areas. The primary ESIF research systems include: [1] data, cyber, and control networks, [2] research electrical distribution buses (REDB), [3] thermal integration infrastructure, and [4] hydrogen systems. The data, cyber, and control networks provide monitoring, control, communication, automation, visualization, and time series data storage and tagging capabilities for research projects and ESIF systems, including facility safety functions. The REDB system consists of four dedicated AC and DC electrical power networks that can connect devices located across the facility through versatile, automatic circuit configuration to support complex power electronics experiments up to the megawatt-scale. The thermal integration infrastructure consists of three temperature-conditioned water loops that provide heating and cooling interfaces and capabilities for thermal energy research. The hydrogen systems provide megawatt-scale hydrogen production, drying, compression, high-pressure storage, and delivery to laboratory end uses, including hydrogen fuel cell vehicle fueling. The ESIF research systems interconnect and extend throughout the various lab areas of the facility to create elaborate networks composed of diverse technologies for cutting-edge research. The ESIF capabilities are operated and stewarded by the ESIF Research Operations group, who also actively upgrade and advance the systems to ensure they remain ahead of anticipated research - enabling the success of many pioneering energy integration projects. The poster, created by members of the ESIF Research Operations team, highlights and summarizes the four core integrated systems at ESIF. The poster was first presented at the internal NREL Energize Forum on May 13th, 2024, and received the "Best Poster" award.

capabilities↗
NASA NTRSDate not supplied

Initial Development of A Digital Twin Model for an Electrified Aircraft Propulsion Emulation Rig

In support of aviation fuel burn and emission reduction goals, NASA is pursing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP), which relies on the generation, storage, transmission, and use of electrical power for producing thrust and optimizing propulsion system efficiency. Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes advances in propulsion controls, which will be vital for ensuring coordinated efficient operation of the complex integrated subsystems that comprise EAP architectures. To support EAP controls research, the NASA Glenn Research Center has developed the Hybrid Propulsion Emulation Rig (HyPER). The HyPER laboratory hardware includes shaft-mounted electric machines, power converters, power supplies, power distribution cables, and an energy storage device that can be reconfigured to represent a variety of EAP architectures. It also includes an integrated real-time computer system that hosts developed EAP control software and turbomachinery simulations. This enables the electrical system and rotating shafts of EAP designs to be implemented in actual hardware and integrated with turbomachinery simulations and system-level EAP control logic implemented in software. In this form, the HyPER laboratory provides a partially simulated, partially hardware-in-the-loop test environment enabling the initial development and evaluation of EAP control technology. A prerequisite for the development of EAP control designs is the availability of a system model that accurately reflects the operation of the electrical system hardware. To support this need, a digital twin model of the HyPER electrical system hardware is under development. This model is being coded in the MATLAB Simulink environment and uses the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) to construct a digital twin framework. EMTAT contains generic electrical component building blocks that are simulated at turbomachinery timescales. Associated inputs and outputs allow the blocks to be combined to model complete electrical systems. The EMTAT blocks also contain adjustable internal maps and parameters that can be set to reflect the operation of a specific electrical component. For the HyPER digital twin, the settings of these EMTAT block internal maps and parameters is determined through machine learning approaches applied to characterization run data collected from the laboratory. During characterization runs the laboratory electrical system hardware is subjected to a full range of torque, speed, and power settings. Acquired data is then used to estimate EMTAT block parameters using a variety of machine learning techniques. The resulting digital twin model is found to match the operation of actual HyPER hardware with an accuracy suitable for control development purposes. It also holds promise for other applications including modeling the performance of HyPER laboratory reconfigurations and model-based anomaly detection. Planned follow-on work to automate post-processing of acquired laboratory data to update the HyPER digital twin model will also be presented and discussed.

Electrified Aircraft Propulsion↗
DOE OSTI2025

Inverse mapping of properties to composition through generative modeling for designing molten salts

Generative modeling (GM) has been increasingly used for the inverse design and optimization of materials, yet its application to molten salt mixtures remains unexplored despite how a successful approach to the inverse design of molten salts would contribute to efficiently exploiting their customizability and unlocking their advantages in applications, such as energy production and energy storage. This work presents a workflow for the inverse design of molten salts with targeted density values, addressing the challenge of representing these complex mixtures in GM. A dataset of critically evaluated molten salt densities is used to train a variational autoencoder coupled with a predictive deep neural network, which then can be used to generate new molten salt compositions with desired density values. The effectiveness of the approach is demonstrated by designing mixtures with distinct densities and validating the predicted values using ab initio molecular dynamics simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗