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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Real-Time Inhibitor Recession Measurements in Two Space Shuttle Reusable Solid Rocket Motors

Real-time internal motor insulation char line recession measurements have been evaluated for two full-scale static tests of the Space Shuttle Reusable Solid Rocket Motor (RSRM). These char line recession measurements were recorded on the forward facing propellant grain inhibitors to better understand the thermal performance of these inhibitors. The RSRM propellant grain inhibitors are designed to erode away during motor operation, thus making it difficult to use post-fire observations to determine inhibitor thermal performance. Therefore, this new internal motor instrumentation is invaluable in establishing an accurate understanding of inhibitor recession versus motor operation time. The data for the first test was presented at the 37th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit (AIAA 2001-3280) in July 2001. Since that time, a second full scale static test has delivered additional real-time data on inhibitor thermal performance. The evaluation of this data is presented in this paper. The second static test, in contrast to the first test, used a slightly different arrangement of instrumentation in the inhibitors. This instrumentation has yielded a better understanding of the inhibitor time dependent inboard tip recession. Graphs of inhibitor recession profiles with time are presented. Inhibitor thermal ablation models have been created from theoretical principals. The model predictions compare favorably with data from both tests. This verified modeling effort is important to support new inhibitor designs for a five segment Space Shuttle solid rocket motor. The internal instrumentation project on RSRM static tests is providing unique opportunities for other real-time internal motor measurements that could not otherwise be directly quantified.

McWhorter, B. B.↗
DOE OSTI2022

Safety-assured, real-time neural active fault management for resilient microgrids integration

Federated-learning-based active fault management (AFM) is devised to achieve real-time safety assurance for microgrids and the main grid during faults. AFM was originally formulated as a distributed optimization problem. Here, federated learning is used to train each microgrid's network with training data achieved from distributed optimization. The main contribution of this work is to replace the optimization-based AFM control algorithm with a learning-based AFM control algorithm. The replacement transfers computation from online to offline. With this replacement, the control algorithm can meet real-time requirements for a system with dozens of microgrids. By contrast, distributed-optimization-based fault management can output reference values fast enough for a system with several microgrids. More microgrids, however, lead to more computation time with optimization-based method. Distributed-optimization-based fault management would fail real-time requirements for a system with dozens of microgrids. Controller hardware-in-the-loop real-time simulations demonstrate that learning-based AFM can output reference values within 10 ms irrespective of the number of microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1984

RTMPL: A structured programming and documentation utility for real-time multiprocessor simulations

The NASA Lewis Research Center is developing and evaluating experimental hardware and software systems to help meet future needs for real time simulations of air-breathing propulsion systems. The Real Time Multiprocessor Simulator (RTMPS) project is aimed at developing a prototype simulator system that uses multiple microprocessors to achieve the desired computing speed and accuracy at relatively low cost. Software utilities are being developed to provide engineering-level programming and interactive operation of the simulator. Two major software development efforts were undertaken in the RTMPS project. A real time multiprocessor operating system was developed to provide for interactive operation of the simulator. The second effort was aimed at developing a structured, high-level, engineering-oriented programming language and translator that would facilitate the programming of the simulator. The Real Time Multiprocessor Programming Language (RTMPL) allows the user to describe simulation tasks for each processor in a straight-forward, structured manner. The RTMPL utility acts as an assembly language programmer, translating the high-level simulation description into time-efficient assembly language code for the processors. The utility sets up all of the interfaces between the simulator hardware, firmware, and operating system.

Arpasi, D. J.↗
NASA NTRS1999

An Instrument for Real-Time Measurement of Solid Rocket Motor Insulation Erosion

An instrument (eroding potentionmeter) has been designed to measure real-time case wall and inhibitor insulation char depth within a rocket motor during firing. Thus measurement can be close to the real-time recession of the insulation surface. The eroding potentionmeter consists of two small (3 mils 9in diameter) twisted resistive wires that are polyimide insulated. The wire pair form an electrical circuit and will recede with the erosion of the rocket motor internal insulation. A constant current applied along the wires will detect the resistance change via a voltage drop across the wires as the wire pair recedes with the decomposition fo the insulation. The eroding potentionmeter, as presently designed, can be an effective tool for real time measurement of internal insulation recession of a solid rocket motor. This tool will provide a way to accurately measure inhibitor performance or to measure flight effects of insulation erosion on a flight test. The eroding potentiometer has been verified on a plasma torch test and two static tests of a small solid rocket motor. There are some irregularities in the measured date, but the data remains useful in determining the real-time performance of internal insulation during a motor firing.

McWhorter, B. B.↗
NASA NTRS1997

Research in Distributed Real-Time Systems

This document summarizes the progress we have made on our study of issues concerning the schedulability of real-time systems. Our study has produced several results in the scalability issues of distributed real-time systems. In particular, we have used our techniques to resolve schedulability issues in distributed systems with end-to-end requirements. During the next year (1997-98), we propose to extend the current work to address the modeling and workload characterization issues in distributed real-time systems. In particular, we propose to investigate the effect of different workload models and component models on the design and the subsequent performance of distributed real-time systems.

Mukkamala, R.↗
DOE OSTI2015

WE-EF-303-05: Development and Commissioning of Real-Time Imaging Function for Respiratory-Gated Spot-Scanning Proton Beam Therapy

Purpose: To realize real-time-image gated proton beam therapy (RGPT) for treating mobile tumors. Methods: The rotating gantry of spot scanning proton beam therapy has been designed to equip two x-ray fluoroscopy devices that enable real-time imaging of the internal fiducial markers during respiration. Three-dimensional position of the fiducial marker located near the tumor can be calculated from the fluoroscopic images obtained from orthogonal directions and therapeutic beam is gated only when the fiducial marker is within the predefined gating window. Image acquisition rate can be selected from discrete value ranging from 0.1 Hz to 30 Hz. In order to confirm the effectiveness of RGPT and apply it clinically, clinical commissioning was conducted. Commissioning tests were categorized to main three parts including geometric accuracy, temporal accuracy and dosimetric evaluation. Results: Developed real-time imaging function has been installed and its basic performances have been confirmed. In the evaluation of geometric accuracy, coincidence of three-dimensional treatment room coordinate system and imaging coordinate system was confirmed to be less than 1 mm. Fiducial markers (gold sphere and coil) were able to be tracked in simulated clinical condition using an anthropomorphic chest phantom. In the evaluation of temporal accuracy, latency from image acquisition to gate on/off signal was about 60 msec in typical case. In dosimetric evaluation, treatment beam characteristics including beam irradiation position and dose output were stable in gated irradiation. Homogeneity indices to the mobile target were 0.99 (static), 0.89 (w/o gating, motion is parallel to direction of scan), 0.75 (w/o gating, perpendicular), 0.98 (w/ gating, parallel) and 0.93 (w/ gating, perpendicular). Dose homogeneity to the mobile target can be maintained in RGPT. Conclusion: Real-time imaging function utilizing x-ray fluoroscopy has been developed and commissioned successfully in order to realize RGPT. Funding Support: This research was partially supported by Japan Society for the Promotion of Science (JSPS) through the FIRST Program. Conflict of Interest: Prof. Shirato has research fund from Hitachi Ltd, Mitsubishi Heavy Industries Ltd and Shimadzu Corporation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A spark‐based big data analysis framework for real‐time sentiment prediction on streaming data

Summary There are many data sources that produce large volumes of data. The Big Data nature requires new distributed processing approaches to extract the valuable information. Real‐time sentiment analysis is one of the most demanding research areas that requires powerful Big Data analytics tools such as Spark. Prior literature survey work has shown that, though there are many conventional sentiment analysis researches, there are only few works realizing sentiment analysis in real time. One major point that affects the quality of real‐time sentiment analysis is the confidence of the generated data. In more clear terms, it is a valuable research question to determine whether the owner that generates sentiment is genuine or not. Since data generated by fake personalities may decrease accuracy of the outcome, a smart/intelligent service that can identify the source of data is one of the key points in the analysis. In this context, we include a fake account detection service to the proposed framework. Both sentiment analysis and fake account detection systems are trained and tested using Naïve Bayes model from Apache Spark's machine learning library. The developed system consists of four integrated software components, ie, (i) machine learning and streaming service for sentiment prediction, (ii) a Twitter streaming service to retrieve tweets, (iii) a Twitter fake account detection service to assess the owner of the retrieved tweet, and (iv) a real‐time reporting and dashboard component to visualize the results of sentiment analysis. The sentiment classification performances of the system for offline and real‐time modes are 86.77% and 80.93%, respectively.

Kılınç, Deniz↗
DOE OSTI2021

DERMS-RT (Distributed Energy Resource Management Solution using Real-Time Optimization) [SWR-20-46]

DERMS-RT provides a distributed energy resource management solution using real-time optimization to control different types of distributed energy resources (DERs) — such as rooftop PVs, battery energy storage systems, HVAC loads, electric water heater loads, and EV charging loads, and use these DERs to provide distribution voltage regulation and peak demand management services. The control approach implemented by DERM-RT is developed based on the real-time optimal power flow and distributed control previously developed by NREL researchers. The software codes are designed to provide modular DER management solution that can be easily applied to control heterogeneous DERs in distribution grids in coordination with centralized utility management systems. Also, DERMS-RT provides application programming interface (API) to extract useful grid model information from an open-source power system simulation software, use the information to solve the optimization problem, and apply the optimal set-points to the controlled DERs. In this way, DERMS-RT provides a plug-and-play function for implementing the real-time DER control on different utility system models, and it can be used as a simulation testbed to demonstrate the impact of real-time DER optimization on improving grid operations.

Ding, Fei↗
DOE OSTI2022

Nonlinear multiobjective and dynamic real-time predictive optimization for optimal operation of baseload power plants under variable renewable energy

Considering the increase of disruptive variable renewable energy penetration into the power grid, this article focuses on the investigation of a multiobjective and dynamic real-time optimization framework to address the cycling of large-scale power plants under renewable penetration. In this framework, a parallelized particle swarm optimization step is first performed to generate feasible initial points. Then, a multiobjective and dynamic real-time optimization formulation generates optimal trajectories. Further, the benefit of predictive capability is investigated for the dynamic component, which introduces the novel nonlinear multiobjective and dynamic real-time predictive optimization approach. Two multiobjective formulations to obtain Pareto front optimal in real time are explored: the modified Tchebycheff-based weighted metric and ϵ-constraint methods. Economic and environmental objectives are considered in this study. A novel topical discussion on the intersection of dynamic real-time optimization with model predictive control is also presented. The developed framework is successfully applied to a baseload coal-fired power plant with postcombustion CO 2 capture. Results indicate that the approach can be deployed for a large-scale system if automatic differentiation, model reduction, and parallelization are adopted to improve computational tractability, with computational improvement up to 120-folds after performing these steps. Finally, market and carbon policies showed an impact on the optimal compromise between the objectives with an additional 63 ton of CO 2 captured under favorable market conditions.

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NASA NTRSDate not supplied

Keeping Up With the Time(s): Advancing NASA’s Worldview to Facilitate Quick Access to Global Near Real-Time Imagery

Striving to keep up with the constantly changing environment, whether physical or computing, NASA Worldview’s interactive web mapping application continues to make improvements to ensure that avenues to near-real time imagery are quick, easy and accessible. This poster will explore recent additions to NASA Worldview and the Global Imagery Browse Services (GIBS) of near real-time imagery and imagery visualizations - from geostationary to flood mapping visualizations; improvements to access to imagery - from granule swath visualizations to vector interactions with fires and other types of vectors; and improvements to imagery discovery - from enhancements to the timeline to providing more ways to locate relevant imagery in the layer picker.

Min Minnie Wong↗
NASA NTRS1990

PRAIS: Distributed, real-time knowledge-based systems made easy

This paper discusses an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS). PRAIS strives for transparently parallelizing production (rule-based) systems, even when under real-time constraints. PRAIS accomplishes these goals by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors.

Goldstein, David G.↗
DOE OSTI2019

Toward the implementation of self-powered, wireless, real-time reactor power sensing

The successful development of real-time, self-powered, wireless reactor power sensing technology would enable key operating parameters of every fuel assembly in a commercial reactor core to be continuously monitored, and potentially be utilized for applications such as closed-loop reactor control. This paper discusses the expansion of successful work on the application of Self Powered Neutron Detectors (SPND) for reactor power monitoring and the wireless transmission of these detector signals using advanced vacuum micro-electronic (VME) transmitter technology developed by Westinghouse in collaboration with the Penn State University Radiation Science and Engineering Center. Results demonstrate that this technology may be successfully applied via long-term testing in the Penn State TRIGA reactor. SPND are inherently slower than, for example, ion chambers due to their dependence on radioactive decay to generate a signal. Additional research developed delay compensation algorithms to accelerate the response of these detectors for use in near-real-time closed-loop reactor control. Initial results indicate that practical signal acceleration can be obtained digitally or with an equivalent analog circuit. Future research will apply an inverse model of the sensor’s balance differential equations to more-effectively accelerate the SPND signal. Use of inverse models will also prove to be adaptive in the sense that time-dependent burn-up of these detectors, due to neutron activation of the detector material, can be modeled and applied in the acceleration algorithm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Stochastic Resolution of Identity for Real-Time Second-Order Green’s Function: Ionization Potential and Quasi-Particle Spectrum

Here, we develop a stochastic resolution of identity approach to the real-time second-order Green's function (real-time sRI-GF2) theory, extending our recent work for imaginary-time Matsubara Green's function [ Takeshita et al. J. Chem. Phys. 2019 , 151 , 044114 ]. The approach provides a framework to obtain the quasi-particle spectra across a wide range of frequencies and predicts ionization potentials and electron affinities. To assess the accuracy of the real-time sRI-GF2, we study a series of molecules and compare our results to experiments as well as to a many-body perturbation approach based on the GW approximation, where we find that the real-time sRI-GF2 is as accurate as self-consistent GW. The stochastic formulation reduces the formal computatinal scaling from O(N e 5 ) down to O(N e 3 ) where N e is the number of electrons. Finally, this is illustrated for a chain of hydrogen dimers, where we observe a slightly lower than cubic scaling for systems containing up to N e ≈ 1000 electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Prior data assisted compressed sensing: A novel MR imaging strategy for real time tracking of lung tumors

Purpose: Hybrid radiotherapy-MRI devices promise real time tracking of moving tumors to focus the radiation portals to the tumor during irradiation. This approach will benefit from the increased temporal resolution of MRI's data acquisition and reconstruction. In this work, the authors propose a novel spatial-temporal compressed sensing (CS) imaging strategy for the real time MRI–-prior data assisted compressed sensing (PDACS), which aims to improve the image quality of the conventional CS without significantly increasing reconstruction times. Methods: Conventional 2D CS requires a random sampling of partial k-space data, as well as an iterative reconstruction that simultaneously enforces the image's sparsity in a transform domain as well as maintains the fidelity to the acquired k-space. PDACS method requires the additional acquisition of the prior data, and for reconstruction, it additionally enforces fidelity to the prior k-space domain similar to viewsharing. In this work, the authors evaluated the proposed PDACS method by comparing its results to those obtained from the 2D CS and viewsharing methods when performed individually. All three methods are used to reconstruct images from lung cancer patients whose tumors move and who are likely to benefit from lung tumor tracking. The patients are scanned, using a 3T MRI, under free breathing using the fully sampled k-space with 2D dynamic bSSFP sequence in a sagittal plane containing lung tumor. These images form a reference set for the evaluation of the partial k-space methods. To create partial k-space, the fully sampled k-space is retrospectively undersampled to obtain a range of acquisition acceleration factors, and reconstructed with 2D-CS, PDACS, and viewshare methods. For evaluation, metrics assessing global image artifacts as well as tumor contour shape fidelity are determined from the reconstructed images. These analyses are performed both for the original 3T images and those at a simulated 0.5T equivalent noise level. Results: In the 3.0T images, the PDACS strategy is shown to give superior results compared to viewshare and conventional 2D CS using all metrics. The 2D-CS tends to perform better than viewshare at the low acceleration factors, while the opposite is true at the high acceleration factors. At simulated 0.5T images, PDACS method performs only marginally better than the viewsharing method, both of which are superior compared to 2D CS. The PDACS image reconstruction time (0.3 s/image) is similar to that of the conventional 2D CS. Conclusions: The PDACS method can potentially improve the real time tracking of moving tumors by significantly increasing MRI's data acquisition speeds. In 3T images, the PDACS method does provide a benefit over the other two methods in terms of both the overall image quality and the ability to accurately and automatically contour the tumor shape. MRI's data acquisition may be accelerated using the simpler viewsharing strategy at the lower, 0.5T magnetic field, as the marginal benefit of the PDACS method may not justify its additional reconstruction times.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Streaming Data from Experimental Facilities to Supercomputers for Real-Time Data Processing

In this paper we demonstrate direct data streaming from instruments and detectors at a large-scale experimental facility to a supercomputer for real-time data processing and feedback. Streaming data to supercomputers introduces the potential for novel scientific applications and workflow models, including the ability to provide real-time feedback from very large datasets during an experiment and the integration of real-time ML training and inference at scale. We discuss a successful demonstration for real-time processing of data from the Advanced Photon Source (APS) on the Polaris supercomputer using an EPICS-based streaming framework. We describe the capabilities of the streaming framework itself, and outline the architecture that allows us to process experimentally derived data on a supercomputer without file-based data transfers. We present throughput measurements that are indicative of system performance capable of sustaining the expected data production rates of the facility, as well as discuss some outstanding challenges and our future directions.

real-time processing↗
DOE OSTI2024

Development of Real-Time High-Density Pulsar Data Transmission and Processing for Grid Synchronization

Taking advantage of the extreme stability of the pulsar period, it can serve as the timing source for grid synchronization to compensate for the timing drift instigated by the loss of GPS signal. Nevertheless, the real-time transmission and processing of the pulsar data suffer from its high-frequency data rate, varying from megahertz to gigahertz, resulting in reduced computing speed and increased time delay. To mitigate this issue, the hardware and software frameworks are implemented for the high-density pulsar data transmission and processing for grid synchronization in this research. Initially, the high-density pulsar data is transferred using open-source software. The complementary duty cycle timing module is designed to coordinate the operation of the dual-channel high-speed interface and software. Subsequently, the multiple-threading is applied to the receiving, parsing, and splicing pulsar data. Next, the pulsar signal extraction method is implemented based on the polyphase filterbank and time of arrival estimation. Ultimately, real-time performance verification experiments are carried out for different components under two hardware platforms. Finally, the results demonstrate that only 0.482 s is required for processing 4 Gigabyte data through multiple-threading, which is 3.8 times faster than the single thread. The pulsar signal extraction can also be executed within 707 ms for 4.8 seconds of data, thereby indicating that real-time requirements can be met.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1991

An SSME High Pressure Oxidizer Turbopump diagnostic system using G2 real-time expert system

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2 real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for the SSME. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach has been adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

Guo, Ten-Huei↗
NASA NTRS1982

A comparative study of real-time spaceborne synthetic aperture radar processing techniques

A review of various spaceborne synthetic aperture radar (SAR) processing algorithms and their associated real-time SAR processor architectures is given in this paper. The processing complexity for each real-time SAR processor is presented next. A complexity comparison is then given based on the Seasat SAR parameters. It is shown that the frequency/time domain hybrid fast correlation and the two-stage fast Fourier transform (FET) approaches are the two most cost-effective choices for real-time spaceborne SAR processing. Finally, a discussion on future development trends in real-time spaceborne SAR processing is given.

Liu, K. Y.↗