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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Using an Advanced Distribution Management System Test Bed to Evaluate the Impact of Model Quality on Volt/VAR Optimization: Preprint

In this paper, we present a test bed for evaluating existing and future advanced distribution management system (ADMS) applications in a realistic laboratory setting, including other utility management systems and field equipment. We present an example of using it to evaluate the impact of the ADMS network model quality on a Volt/VAR optimization (VVO) application. The test bed integrates a commercial ADMS with a real-time simulation model of a utility distribution feeder. Representative power and controller hardware are integrated through hardware-in-the-loop (HIL) techniques. The performance of the ADMS VVO application is also evaluated for different levels of measurement density. Initial results indicate that a higher model quality achieves the highest possible energy savings while avoiding voltage violations, whereas a lower model quality results in increased energy savings but at the expense of more voltage violations.

ADMS↗
DOE OSTI2025

A Fast Dynamic Internal Predictive Power Scheduling Approach for Power Management in Microgrids: Preprint

This paper presents a Dynamic Internal Predictive Power Scheduling (DIPPS) approach for optimizing power management in microgrids, particularly focusing on external power exchanges among diverse prosumers. DIPPS utilizes a dynamic objective function with a time-varying binary parameter to control the timing of power transfers to the external grid, facilitated by efficient usage of energy storage for surplus renewable power. The microgrid power scheduling problem is modeled as a mixed-integer nonlinear programming (MINLP-PS) and subsequently transformed into a mixed-integer linear programming (MILPPS) optimization through McCormick's relaxation to reduce computational complexity. A predictive window window with 6 data points is solved at an average of 0.92s, a 97.6% improvement over the 38.27s required for the MINLP-PS formulation, implying the numerical feasibility of the DIPPS approach for real-time implementation. Finally, the approach is validated against a static objective using real-world load data across three case studies with different time-varying parameters, demonstrating the ability of DIPPS to optimize power exchanges and efficiently utilize distributed resources while shifting the external power transfers to specified time durations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

An open-source data storage and visualization platform for collaborative qubit control

Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization ( QubiCSV ), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Design and experimental demonstration of feedback adaptive RMP ELM controller toward complete long pulse ELM suppression on KSTAR

Operation of a fusion power plant requires robust edge localized mode (ELM) suppression simultaneously with high plasma performance. In this study, we describe a novel feedback adaptive resonant magnetic perturbation (RMP) ELM controller designed to address this problem by achieving optimized ELM suppression through the advanced application of 3D RMPs. From real-time $D_α$ data, the controller is achievable robust ELM suppression while simultaneously minimizing the applied RMP in order to enhance plasma performance. In real time, the instantaneous ELM-frequency is analyzed with an adaptive feedback algorithm to determine amplitudes and phases of RMP coil currents that will maximize plasma performance while maintaining ELM suppression. When applied through the KSTAR plasma control system in several experiments using $textiti{n}$ = 1 RMPs, robust ELM suppression is achieved and sustained in feedback while reducing the RMP strength to ~65% of its initial value. Minimization of the RMP strength in this manner not only allows for operation of longer discharges due to a decrease in flux consumption but also allows for a strong recovery of up to ~60% of $β_N$ throughout the ELM-free period.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Cookie-Jar: An Adaptive Re-configurable Framework for Wireless Network Infrastructures

5G advancements like Massive Multiple Input Multiple Output (MIMO) bring high capacity and low latency, but also intensify interference challenges. Static and dynamic coordination techniques address this, often at the cost of increased power draw. We introduce Cookie-Jar (CJ), an interference coordination (IC) framework using reinforcement learning for multi-goal optimization. By dynamically adjusting network, power, and topology parameters based on real-time conditions, CJ improves Signal to Noise and Interference Ratio (SINR) while minimizing power consumption. Simulated 5G experiments showcase CJ's potential, achieving a 15% SINR improvement with near-identical power draw compared to existing methods.

Network↗
DOE OSTI2024

Energy Efficient Streaming Time Series Classification with Attentive Power Iteration

Efficiently processing time series data streams in real-time on resource-constrained devices offers significant advantages in terms of enhanced computational energy efficiency and reduced time-related risks. We introduce an innovative streaming time series classification network that utilizes attentive power iteration, enabling real-time processing on resource-constrained devices. Our model continuously updates a compact representation of the entire time series, enhancing classification accuracy while conserving energy and processing time. Notably, it excels in streaming scenarios without requiring complete time series access, enabling swift decisions. Experimental results show that our approach excels in classification accuracy and energy efficiency, with over 70% less consumption and threefold faster task completion than benchmarks. This work advances real-time responsiveness, energy conservation, and operational effectiveness for constrained devices, contributing to optimizing various applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Grid-Connected Modular Soft-Switching Solid State Transformers (M-S4T)

The objective of this project is to develop and verify the concept of a flexible and modular soft-switching solid-state transformer (M-S4T) for direct grid-connected applications. The ability to directly connect power electronics converters to the medium voltage grid (4 kV – 13 kV), and to potentially replace the passive and bulky, but ubiquitous 60 hertz service transformer in the 25 kVA to 100 kVA range, with a more flexible and controllable device, has been regarded as the ‘holy grail’ in grid control. However, this has proven to be extremely difficult. This project has developed the solutions to several key challenges of the direct grid-connected power electronics and realized a 7.2 kV M-S4T prototype. First, a protection method to protect the M-S4T from the high voltages (110 kV for the 13 kV system) that occur on the grid due to transients and lightning strikes have been developed and experimentally verified. Second, the realization and the operation of the M-S4T based on high-voltage SiC devices (>3.3 kV) and a medium-frequency medium-voltage low-leakage transformer in a single-stage solid-state transformer with zero-voltage switching, low dv/dt, and low electromagnetic interference has been successfully demonstrated up to 7.5 kV peak. Third, an oil-cooling system and stable communication and distributed control system for converter module voltage sharing have been developed and experimentally verified. The developed M-S4T has realized a modular universal high-performance power conversion system. This conversion system is scalable to different voltage and power levels and adaptable to four-quadrant bidirectional operation. Moreover, the use of passive cooling techniques meets the equipment life requirements, and the lightning protection scheme fulfills the basic insulation level specifications for direct grid connection. Such power conversion system opens up near-term opportunities, including energy storage, solar PV, or electric vehicle charging with significant cost and footprint savings. In the longer term, the possibility of replacing the utility distribution transformer with an M-S4T will be transformative for future distribution grids with a compact footprint and full controllability to enable high renewable energy and storage penetration. In addition to the main project, this report expands on the Plus-Up projected including as part of the main award. This project developed and demonstrated the technology for autonomous collaborative inverters that can be connected in an ad hoc manner to the grid. The aim of the project was to: (1) evaluate the existing techniques for grid-connected inverters and find their limitations; (2) develop detailed requirements for grid-connected inverters in the modern grid with millions of active nodes; (3) design a unified control strategy that brings more autonomy and intelligence to grid-connected inverters, and addresses parts of the issues with the existing techniques. The proposed technique, called UniCon, enables inverters to 1) connect/disconnect to/from the grid in an ad hoc manner; (2) work based on local sensing. Slow communication could be used for a more optimized behavior; (3) work automatically in both grid-forming/grid-following mode; (4) handle large disturbances, e.g., big load step and fault, in an oscillation-free manner; (5) work collaboratively with other inverters in steady-state and during transients. UniCon can be implemented in the middle-level control; hence it is agnostic to the vendor and to the implementation of the inner voltage/current and protection loops. Furthermore, a new synchronization scheme, based on deep learning, was developed that can extract the grid voltage phase and amplitude in a stable manner. The method is cheap to implement can improve the dynamic performance of the grid-connected inverters during fast transients, e.g., fault. The proposed control scheme was validated by (1) MATLAB/Simulink; (2) hardware-in-the-loop results, and; (3) experimental results using three inverters that form a microgrid in a down-scaled feeder. Lastly, both the M-S4T and UniCon have achieved promising tangible paths to markets. In the case of the M-S4T, the underlying technology — the Soft Switching Solid State Transformer (S4T) developed at the Georgia Tech Center for Distributed Energy (GT-CDE) has been licensed by GridBlock from the Georgia Tech Research Corporation, and GridBlock has been working with manufacturing partner Jabil (one of the largest US-based contract manufacturers) and system integrator Power Secure (largest deployer of microgrids in the US with 4.7 GW under management), to meet the strong initial demand. Similarly, GridBlock has an exclusive license to the UniCon technology, developed under this award by GT-CDE. The UniCon provides an intermediate control layer that enables the implementation of the higher-level ‘transactive’ control commands for the system. The architecture of the system - slow communications with the cloud for system optimization and setpoints, and the use of locally measured quantities for real-time control, provide a very robust and secure way of implementing a real-time must-run grid that is also secure and stable. This is a brand-new functionality that is critical for the future grid and key to GridBlock’s business model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)

The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Substation-Level Grid Topology Optimization Using Bus Splitting

Operations of substation circuit breakers are important for maintenance needs and topology reconfiguration in power systems. Bus splitting is one type of topology change where the two bus bars at a substation can become electrically disconnected under certain actions of circuit breakers. Because these events involve detailed substation modeling, they are typically not considered in routine power system operation and control. In this paper, an improved substation-level topology optimization framework is developed by expanding traditional line switching decisions by breaker-level bus splitting, which can further reduce grid congestion and generation costs. A tight McCormick relaxation is proposed to reformulate the bilinear terms in the resultant optimization problem to linear inequality constraints. Thus, a tractable mixed-integer linear program reformulation is attained that allows for efficient solutions in real-time operations. Numerical studies on the IEEE 14-bus and 118-bus systems demonstrate the computational performance and economic benefits of the proposed topology optimization approach.

bus split↗
NASA NTRS1981

Wakeflow analysis by cost

COST (Computerized Optical Scanning Tomography) is proposed for visualizing wakeflows of aircraft and wind-tunnel models. Operating very close to real time, COST hardware could be installed at airports to monitor turbulent flow trailing large aircraft, so that smaller aircraft could be directed to avoid turbulence. Real-time analysis of jet-engine exhaust plumes, to reduce pollution and optimize performance, is also possible.

Anselmo, V. J.↗
NASA NTRS1986

Stanford Hardware Development Program

Architectures for high performance, digital signal processing, particularly for high resolution, wide band spectrum analysis were developed. These developments are intended to provide instrumentation for NASA's Search for Extraterrestrial Intelligence (SETI) program. The real time signal processing is both formal and experimental. The efficient organization and optimal scheduling of signal processing algorithms were investigated. The work is complemented by efforts in processor architecture design and implementation. A high resolution, multichannel spectrometer that incorporates special purpose microcoded signal processors is being tested. A general purpose signal processor for the data from the multichannel spectrometer was designed to function as the processing element in a highly concurrent machine. The processor performance required for the spectrometer is in the range of 1000 to 10,000 million instructions per second (MIPS). Multiple node processor configurations, where each node performs at 100 MIPS, are sought. The nodes are microprogrammable and are interconnected through a network with high bandwidth for neighboring nodes, and medium bandwidth for nodes at larger distance. The implementation of both the current mutlichannel spectrometer and the signal processor as Very Large Scale Integration CMOS chip sets was commenced.

Peterson, A.↗
NASA NTRS1989

Real time processor for array speckle interferometry

The authors are constructing a real-time processor to acquire image frames, perform array flat-fielding, execute a 64 x 64 element two-dimensional complex FFT (fast Fourier transform) and average the power spectrum, all within the 25 ms coherence time for speckles at near-IR (infrared) wavelength. The processor will be a compact unit controlled by a PC with real-time display and data storage capability. This will provide the ability to optimize observations and obtain results on the telescope rather than waiting several weeks before the data can be analyzed and viewed with offline methods. The image acquisition and processing, design criteria, and processor architecture are described.

Chin, Gordon↗
NASA NTRS1990

Optimization and guidance of trajectories for coplanar, aeroassisted orbital transfer

Guidance trajectories for coplanar aeroassisted orbital transfer (AOT) from high earth orbit to LEO are presently optimized under the assumption of trajectory control during its endoatmospheric phase by alpha-dependent lift coefficient. Optimal trajectories are first computed by minimizing the total velocity impulse required for AOT; attention is then given to guidance trajectories capable of approximating such key properties of the optimal trajectories as minimum altitude, exit velocity, and exit path inclination, in real time. A switch is made from target-altitude guidance to target path inclination-guidance according to the velocity depletion required for optimum flight.

Miele, A.↗
NASA NTRS1991

A parallel trajectory optimization tool for aerospace plane guidance

A parallel trajectory optimization algorithm is being developed. One possible mission is to provide real-time, on-line guidance for the National Aerospace Plane. The algorithm solves a discrete-time problem via the augmented Lagrangian nonlinear programming algorithm. The algorithm exploits the dynamic programming structure of the problem to achieve parallelism in calculating cost functions, gradients, constraints, Jacobians, Hessian approximations, search directions, and merit functions. Special additions to the augmented Lagrangian algorithm achieve robust convergence, achieve (almost) superlinear local convergence, and deal with constraint curvature efficiency. The algorithm can handle control and state inequality constraints such as angle-of-attack and dynamic pressure constraints. Portions of the algorithm have been tested. The nonlinear programming core algorithm performs well on a variety of static test problems and on an orbit transfer problem. The parallel search direction algorithm can reduce wall clock time by a factor of 10 for this part of the computation task.

Psiaki, Mark L.↗
NASA NTRS1992

Evaluation of an optimal guidance algorithm for aero-assisted orbit transfer

A detailed evaluation is performed of a guidance algorithm for aeroassisted orbit transfer that was developed earlier based on the method of matched asymptotic expansions. It is shown that, by exploiting the structure of the matched asymptotic expansion solution procedure, the original problem which requires the solution of a set of 20 implicit algebraic equations can be reduced to a problem of six implicit equations in six unknowns. The main contribution here is that it was possible to obtain a solution that is near optimal, requires a minimum of computation, and thus can be implemented in real time and on-board the vehicle. Guidance law implementation entails treating the current state as a new initial state and repetitively solving the matched asymptotic expansion problem to obtain the feedback controls.

Melamed, N.↗
NASA NTRS1993

Guidance law development for aeroassisted transfer vehicles using matched asymptotic expansions

This report addresses and clarifies a number of issues related to the Matched Asymptotic Expansion (MAE) analysis of skip trajectories, or any class of problems that give rise to inner layers that are not associated directly with satisfying boundary conditions. The procedure for matching inner and outer solutions, and using the composite solution to satisfy boundary conditions is developed and rigorously followed to obtain a set of algebraic equations for the problem of inclination change with minimum energy loss. A detailed evaluation of the zeroth order guidance algorithm for aeroassisted orbit transfer is performed. It is shown that by exploiting the structure of the MAE solution procedure, the original problem, which requires the solution of a set of 20 implicit algebraic equations, can be reduced to a problem of 6 implicit equations in 6 unknowns. A solution that is near optimal, requires a minimum of computation, and thus can be implemented in real time and on-board the vehicle, has been obtained. Guidance law implementation entails treating the current state as a new initial state and repetitively solving the zeroth order MAE problem to obtain the feedback controls. Finally, a general procedure is developed for constructing a MAE solution up to first order, of the Hamilton-Jacobi-Bellman equation based on the method of characteristics. The development is valid for a class of perturbation problems whose solution exhibits two-time-scale behavior. A regular expansion for problems of this type is shown to be inappropriate since it is not valid over a narrow range of the independent variable. That is, it is not uniformly valid. Of particular interest here is the manner in which matching and boundary conditions are enforced when the expansion is carried out to first order. Two cases are distinguished-one where the left boundary condition coincides with, or lies to the right of, the singular region, and another one where the left boundary condition lies to the left of the singular region. A simple example is used to illustrate the procedure where the obtained solution is uniformly valid to O(Epsilon(exp 2)). The potential application of this procedure to aeroassisted plane change is also described and partially evaluated.

Calise, Anthony J.↗
NASA NTRS2004

Structural Health Management for Future Aerospace Vehicles

Structural Health Management (SHM) will be of critical importance to provide the safety, reliability and affordability necessary for the future long duration space missions described in America's Vision for Space Exploration. Long duration missions to the Moon, Mars and beyond cannot be accomplished with the current paradigm of periodic, ground based structural integrity inspections. As evidenced by the Columbia tragedy, this approach is also inadequate for the current Shuttle fleet, thus leading to its initial implementation of on-board SHM sensing for impact detection as part of the return to flight effort. However, future space systems, to include both vehicles as well as structures such as habitation modules, will require an integrated array of onboard in-situ sensing systems. In addition, advanced data systems architectures will be necessary to communicate, store and process massive amounts of SHM data from large numbers of diverse sensors. Further, improved structural analysis and design algorithms will be necessary to incorporate SHM sensing into the design and construction of aerospace structures, as well as to fully utilize these sensing systems to provide both diagnosis and prognosis of structural integrity. Ultimately, structural integrity information will feed into an Integrated Vehicle Health Management (IVHM) system that will provide real-time knowledge of structural, propulsion, thermal protection and other critical systems for optimal vehicle management and mission control. This paper will provide an overview of NASA research and development in the area of SHM as well as to highlight areas of technology improvement necessary to meet these future mission requirements.

Prosser, W. H.↗
NASA NTRS2014

Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-14

Ms. Crawford completed the final report for the dual-Doppler wind field task. Dr. Bauman completed transitioning the 915-MHz and 50-MHz Doppler Radar Wind Profiler (DRWP) splicing algorithm developed at Marshall Space Flight Center (MSFC) into the AMU Upper Winds Tool. Dr. Watson completed work to assimilate data into model configurations for Wallops Flight Facility (WFF) and Kennedy Space Center/Cape Canaveral Air Force Station (KSC/CCAFS). Ms. Shafer began evaluating the a local high-resolution model she had set up previously for its ability to forecast weather elements that affect launches at KSC/CCAFS. Dr. Watson began a task to optimize the data-assimilated model she just developed to run in real time.

Applied Meteorology Unit↗