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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Novel Real- Time EMT- TS Modeling Architecture for Feeder Blackstart Simulations

This paper presents the development and benchmarking of a novel real-time electromagnetic-transient and transient-stability (EMT-TS) modeling architecture for distribution feeder restoration studies. The work presents for the first time in the literature a real-time EMT-TS testbed in which the grid-forming unit is simulated in EMT domain, operating as the slack bus of the phasor domain while including unbalanced voltage conditions. To evaluate the performance and limitations of the proposed model, an equivalent EMT testbed is developed to serve as a benchmark. First, the co-simulation framework and the domain coupling methodology are introduced. Next, the steady state operation of the EMT-TS and EMT models are matched. Then, tests are conducted to analyze the transient performance of the proposed EMT-TS model when compared to its EMT benchmark. Results reveal that when utilizing a battery energy storage system (BESS) as the grid-forming unit, the EMT-TS testbed can maintain high accuracy for typical load steps.

Paduani, Victor↗
DOE OSTI2022

Non-destructive measurement and real-time monitoring of apple hardness during ultrasonic contact drying via portable NIR spectroscopy and machine learning

Portable near-infrared spectrometer in the spectral range of 900–1700 nm was evaluated for the first time to assess and monitor apple hardness in real-time during ultrasonic drying. Calibration models were developed using PLS and ANN, and their performances were evaluated by internal leave-one-out cross-validation and an external dataset. Several pre-treatments including standard normal variate (SNV), multiplicative scatter correction (MSC), Savitzky–Golay first and second derivatives were employed to examine the effects of spectral variations in hardness prediction. Seven important wavelengths were selected using weighted regression coefficients to develop a simple MLR model to facilitate the model interpretation and circumvent noise. The models using PLS, MLR, and ANN with selected wavelengths predicted the apple hardness with R 2 p of 0.91, 0.91, 0.95, and RMSEP of 14.78, 14.85, and 12.46 N, respectively. Finally, the results indicate that portable NIR spectrometers are quite promising for real-time monitoring of apple hardness during ultrasonic drying.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

An 8.8 ps RMS Resolution Time-To-Digital Converter Implemented in a 60 nm FPGA with Real-Time Temperature Correction

This paper presented a non-uniform multiphase (NUMP) time-to-digital converter (TDC) implemented in a field-programmable gate array (FPGA) with real-time automatic temperature compensation. NUMP-TDC is a novel, low-cost, high-performance TDC that has achieved an excellent performance in Altera Cyclone V FPGA. The root mean square (RMS) for the intrinsic timing resolution was 2.3 ps. However, the propagation delays in the delay chain of some FPGAs (for example, the Altera Cyclone 10 LP) vary significantly as the temperature changes. Thus, the timing performances of NUMP-TDCs implemented in those FPGAs are significantly impacted by temperature fluctuations. In this study, a simple method was developed to monitor variations in propagation delays using two registers deployed at both ends of the delay chain and compensate for changes in propagation delay using a look-up table (LUT). When the variations exceeded a certain threshold, the LUT for the delay correction was updated, and a bin-by-bin correction was launched. Using this correction approach, a resolution of 8.8 ps RMS over a wide temperature range (5 °C to 80 °C) had been achieved in a NUMP-TDC implemented in a Cyclone 10 LP FPGA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Real-time coherent diffraction inversion using deep generative networks

Abstract Phase retrieval, or the process of recovering phase information in reciprocal space to reconstruct images from measured intensity alone, is the underlying basis to a variety of imaging applications including coherent diffraction imaging (CDI). Typical phase retrieval algorithms are iterative in nature, and hence, are time-consuming and computationally expensive, making real-time imaging a challenge. Furthermore, iterative phase retrieval algorithms struggle to converge to the correct solution especially in the presence of strong phase structures. In this work, we demonstrate the training and testing of CDI NN, a pair of deep deconvolutional networks trained to predict structure and phase in real space of a 2D object from its corresponding far-field diffraction intensities alone. Once trained, CDI NN can invert a diffraction pattern to an image within a few milliseconds of compute time on a standard desktop machine, opening the door to real-time imaging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Real‐Time Optical Process Monitoring for Structure and Property Control of Aerosol Jet Printed Functional Materials

Abstract Aerosol jet printing is a popular digital additive manufacturing method for flexible and hybrid electronics, but it lacks sophisticated real‐time process control schemes that would enable more widespread adoption in manufacturing environments. Here, an optical measurement system is introduced to track the aerosol density upstream of the printhead. The measured optical extinction, combined with the aerosol flow rate, is directly related to deposition rate and accurately predicts functional materials properties such as the electrical resistance of printed graphene films. This real‐time system offers a compelling solution for process drift and batch‐to‐batch variability, rendering it a valuable tool for both real‐time control of aerosol jet printing and fundamental studies of the underlying process science.

Tafoya, Rebecca R.↗
NASA NTRS1999

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

Baskaran, Subbiah↗
NASA NTRS2000

A Real-Time Method for Estimating Viscous Forebody Drag Coefficients

This paper develops a real-time method based on the law of the wake for estimating forebody skin-friction coefficients. The incompressible law-of-the-wake equations are numerically integrated across the boundary layer depth to develop an engineering model that relates longitudinally averaged skin-friction coefficients to local boundary layer thickness. Solutions applicable to smooth surfaces with pressure gradients and rough surfaces with negligible pressure gradients are presented. Model accuracy is evaluated by comparing model predictions with previously measured flight data. This integral law procedure is beneficial in that skin-friction coefficients can be indirectly evaluated in real-time using a single boundary layer height measurement. In this concept a reference pitot probe is inserted into the flow, well above the anticipated maximum thickness of the local boundary layer. Another probe is servomechanism-driven and floats within the boundary layer. A controller regulates the position of the floating probe. The measured servomechanism position of this second probe provides an indirect measurement of both local and longitudinally averaged skin friction. Simulation results showing the performance of the control law for a noisy boundary layer are then presented.

Whitmore, Stephen A.↗
DOE OSTI2023

Real-time mixed reality display of dual particle radiation detector data

Radiation source localization and characterization are challenging tasks that currently require complex analyses for interpretation. Mixed reality (MR) technologies are at the verge of wide scale adoption and can assist in the visualization of complex data. Herein, we demonstrate real-time visualization of gamma ray and neutron radiation detector data in MR using the Microsoft HoloLens 2 smart glasses, significantly reducing user interpretation burden. Radiation imaging systems typically use double-scatter events of gamma rays or fast neutrons to reconstruct the incidence directional information, thus enabling source localization. The calculated images and estimated ’hot spots’ are then often displayed in 2D angular space projections on screens. By combining a state-of-the-art dual particle imaging system with HoloLens 2, we propose to display the data directly to the user via the head-mounted MR smart glasses, presenting the directional information as an overlay to the user’s 3D visual experience. We describe an open source implementation using efficient data transfer, image calculation, and 3D engine. We thereby demonstrate for the first time a real-time user experience to display fast neutron or gamma ray images from various radioactive sources set around the detector. We also introduce an alternative source search mode for situations of low event rates using a neural network and simulation based training data to provide a fast estimation of the source’s angular direction. Using MR for radiation detection provides a more intuitive perception of radioactivity and can be applied in routine radiation monitoring, education & training, emergency scenarios, or inspections.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Systems and methods for real-time data processing and for emergency planning

Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.

Yilmaz, Alper↗
DOE OSTI2023

Systems and methods for real-time data processing and for emergency planning

Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Mixed data/goal driven intelligent real-time assessment and control

We describe work in progress to develop model-based systems for real-time assessment and control of complex systems. Intelligent real-time processing must balance accuracy and response-time requirements to maximize expected performance. We use brief (probability) and goal (utility) information to guide construction of an approximate system model on which we then apply approximate inference procedures to yield timely, effective assessments and control decisions.

Dambrosio, Bruce↗
NASA NTRS1979

Low-level processing for real-time image analysis

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Eskenazi, R.↗
DOE OSTI2016

SU-G-JeP4-14: Assessment of Inter- and Intra-Fractional Motion for Extremity Soft Tissue Sarcoma Patients by Using In-House Real-Time Optical Image-Based Monitoring System

Purpose: This study aimed to assess inter- and intra-fractional motion for extremity Soft Tissue Sarcoma (STS) patients, by using in-house real-time optical image-based monitoring system (ROIMS) with infra-red (IR) external markers. Methods: Inter- and intra-fractional motions for five extremity (1 upper, 4 lower) STS patients received postoperative 3D conformal radiotherapy (3D-CRT) were measured by registering the image acquired by ROIMS with the planning CT image (REG-ROIMS). To compare with the X-ray image-based monitoring, pre- and post-treatment cone beam computed tomography (CBCT) scans were performed once per week and registered with planning CT image as well (REG-CBCT). If the CBCT scan is not feasible due to the large couch shift, AP and LR on-board imager (OBI) images were acquired. The comparison was done by calculating mutual information (MI) of those registered images. Results: The standard deviation (SD) of the inter-fractional motion was 2.6 mm LR, 2.8 mm SI, and 2.0 mm AP, and the SD of the intra-fractional motion was 1.4 mm, 2.1 mm, and 1.3 mm in each axis, respectively. The SD of rotational inter-fractional motion was 0.6° pitch, 0.9° yaw, and 0.8° roll and the SD of rotational intra-fractional motion was 0.4° pitch, 0.9° yaw, and 0.7° roll. The derived averaged MI values were 0.83, 0.92 for REG-CBCT without rotation and REG-ROIMS with rotation, respectively. Conclusion: The in-house real-time optical image-based monitoring system was implemented clinically and confirmed the feasibility to assess inter- and intra-fractional motion for extremity STS patients while the daily basis and real-time CBCT scan is not feasible in clinic.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Chemiresistors for the Real‐Time Wireless Detection of Anions

Abstract Reported is an electrical transduction platform for real‐time wireless anion sensing using single‐walled carbon nanotubes (SWCNTs) noncovalently functionalized with squaramide‐based anion binding selectors. Systematically studied are anion‐binding properties and efficiency of the electrical transduction of the functionalized SWCNT composites using the squaramide‐based selectors with two similar electron‐withdrawing groups, 3,5‐bis(trifluoromethyl)benzyl ( 1 ) and 3,5‐bis(trifluoromethyl)phenyl ( 2 ), which induce hydrogen‐bonding interaction with anions and deprotonation of a squaramide N–H proton upon addition of acetate (AcO − ), respectively. Charge transduction occurs with AcO − as a result of charge transfer from the deprotonated selector 2 , whereas less sensitive transduction is observed with selector 1 via hydrogen‐bonding interaction. These results provide guidelines to efficiently transduce the chemical interaction between selectors and anions to create resistive transduction with functionalized SWCNTs. Electron‐withdrawing groups adjacent to the squaramide as well as proximate cationic pyridyl groups, enhance the anion binding affinity and also lower the selector's p K a . The chemiresistive sensor arrays are readily integrated with a wireless sensing module and demonstrated real‐time sensing of multiple anions with a smartphone readout.

Choi, Seon‐Jin↗
DOE OSTI2014

Cherenkov Video Imaging Allows for the First Visualization of Radiation Therapy in Real Time

Purpose: To determine whether Cherenkov light imaging can visualize radiation therapy in real time during breast radiation therapy. Methods and Materials: An intensified charge-coupled device (CCD) camera was synchronized to the 3.25-μs radiation pulses of the clinical linear accelerator with the intensifier set × 100. Cherenkov images were acquired continuously (2.8 frames/s) during fractionated whole breast irradiation with each frame an accumulation of 100 radiation pulses (approximately 5 monitor units). Results: The first patient images ever created are used to illustrate that Cherenkov emission can be visualized as a video during conditions typical for breast radiation therapy, even with complex treatment plans, mixed energies, and modulated treatment fields. Images were generated correlating to the superficial dose received by the patient and potentially the location of the resulting skin reactions. Major blood vessels are visible in the image, providing the potential to use these as biological landmarks for improved geometric accuracy. The potential for this system to detect radiation therapy misadministrations, which can result from hardware malfunction or patient positioning setup errors during individual fractions, is shown. Conclusions: Cherenkoscopy is a unique method for visualizing surface dose resulting in real-time quality control. We propose that this system could detect radiation therapy errors in everyday clinical practice at a time when these errors can be corrected to result in improved safety and quality of radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Hanford Direct Feed Low Activity Waste Real Time Monitoring Program - 18336

Effective operation of the Low-Activity Waste (LAW) Facility at Hanford will rely on information provided from monitoring and control of chemical process streams to maintain safety and environmental compliance, product quality, and operational efficiency. The LAW Facility has been designed as a contact-maintained facility and it was recognized that establishing a real time, in-line monitoring program could have substantial benefits to the U.S. Department of Energy, Office of River Protection in the long-term, which include significant time savings, increased processing efficiency and effectiveness, reducing worker exposure to radiation and chemical hazards, reducing secondary wastes, and a better understanding of the flowsheet to support direct-feed LAW (DFLAW). The Assistant Manager/Federal Project Director for the Waste Treatment and Immobilization Plant (WTP) Project chartered a multidisciplinary integrated technical team comprised of federal, contractor, and national laboratory staff to develop a phased program to support this initiative. A three-phase approach was adopted: - Phase 1: Requirements and Opportunities Analysis for Sampling Reduction; - Phase 2: Applications and Benefits Determination; - Phase 3: Qualification and Demonstration. The focus of Phase 1 is to identify the drivers behind any requirements for sampling and any opportunities to benefit from a real-time monitoring program. The effort identified 18 sample points and approximately 2,600 potential samples to be collected annually with analytical methods to be performed approximately 18,000 times annually. Based on Savannah River National Laboratory experience and discussions with WTP Analytical Laboratory personnel, these sample analyses will generate approximately 5,000 L of liquid secondary waste and approximately 1,300 m{sup 3} of solid secondary waste each year. Additional solid and liquid secondary wastes will be generated from sample collection. A preliminary evaluation indicates that employing real-time, in-line monitoring, mass balances, and periodic sampling could significantly reduce the number of samples collected, analytical methods performed, and secondary waste generated. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Cross-correlation image analysis for real-time single particle tracking

Accurately measuring the translations of objects between images is essential in many fields, including biology, medicine, chemistry, and physics. One important application is tracking one or more particles by measuring their apparent displacements in a series of images. Popular methods, such as the center of mass, often require idealized scenarios to reach the shot noise limit of particle tracking and, therefore, are not generally applicable to multiple image types. More general methods, such as maximum likelihood estimation, reliably approach the shot noise limit, but are too computationally intense for use in real-time applications. These limitations are significant, as real-time, shot-noise-limited particle tracking is of paramount importance for feedback control systems. To fill this gap, we introduce a new cross-correlation-based algorithm that approaches shot-noise-limited displacement detection and a graphics processing unit-based implementation for real-time image analysis of a single particle.

Instruments & Instrumentation↗
NASA NTRS1987

Computer architecture for efficient algorithmic executions in real-time systems: New technology for avionics systems and advanced space vehicles

Improvements and advances in the development of computer architecture now provide innovative technology for the recasting of traditional sequential solutions into high-performance, low-cost, parallel system to increase system performance. Research conducted in development of specialized computer architecture for the algorithmic execution of an avionics system, guidance and control problem in real time is described. A comprehensive treatment of both the hardware and software structures of a customized computer which performs real-time computation of guidance commands with updated estimates of target motion and time-to-go is presented. An optimal, real-time allocation algorithm was developed which maps the algorithmic tasks onto the processing elements. This allocation is based on the critical path analysis. The final stage is the design and development of the hardware structures suitable for the efficient execution of the allocated task graph. The processing element is designed for rapid execution of the allocated tasks. Fault tolerance is a key feature of the overall architecture. Parallel numerical integration techniques, tasks definitions, and allocation algorithms are discussed. The parallel implementation is analytically verified and the experimental results are presented. The design of the data-driven computer architecture, customized for the execution of the particular algorithm, is discussed.

Carroll, Chester C.↗