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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 73 records · Page 4

All sources NASA NTRS DOE OSTI

NASA NTRS2012

Pattern Generator for Bench Test of Digital Boards

All efforts to develop electronic equipment reach a stage where they need a board test station for each board. The SMAP digital system consists of three board types that interact with each other using interfaces with critical timing. Each board needs to be tested individually before combining into the integrated digital electronics system. Each board needs critical timing signals from the others to be able to operate. A bench test system was developed to support test of each board. The test system produces all the outputs of the control and timing unit, and is delivered much earlier than the timing unit. Timing signals are treated as data. A large file is generated containing the state of every timing signal at any instant. This file is streamed out to an IO card, which is wired directly to the device-under-test (DUT) input pins. This provides a flexible test environment that can be adapted to any of the boards required to test in a standalone configuration. The problem of generating the critical timing signals is then transferred from a hardware problem to a software problem where it is more easily dealt with.

Berkun, Andrew C.↗

DOE OSTI2019

Real-Time Signal-to-Noise Ratio Estimation by Universal Grid Analyzer

This paper presents a real-time Signal-to-Noise Ratio (SNR) estimation performed by the distribution level phasor measurement unit, Universal Grid Analyzer (UGA). The hardware and software architectures of the UGA are discussed followed by the introduction of SNR estimation algorithm. To verify the effectiveness of both SNR estimation algorithm and its implementation, a real world test bench is set up in the laboratory. The experimental results validate the implementation of the existing SNR algorithm which has maximum of 5 dB error in real-time measurement.

Bhandari, Apsana↗

DOE OSTI2020

Modeling and Control Using Stochastic Distribution Control Theory for Intersection Traffic Flow

In this work, we investigated stochastic distribution control theory-based traffic signal optimization to achieve a smooth and uniform flow of vehicles through signalized intersections. In this context, the static and linear dynamic stochastic distribution models were developed to express the relationship between the signal timing and the traffic queue length together with its probability density function. Two stochastic distribution control algorithms were designed to control the signal timing at intersections such that the probability density function of the traffic queue of each intersection road segment is made as narrow and as small as possible. Also, a recursive input-output traffic queue estimation model was proposed, which is data-driven and dynamic in nature, to calculate real-time traffic queue length using traffic signal timings and loop-detector data. The control algorithms were evaluated for a one-signal corridor, two-signal corridor, and 2 x 2 network of signalized intersections. MATLAB simulation examples are provided to demonstrate the use of the proposed algorithms and comparison to the existing widely-used semi-actuated control has been made. Desired results were obtained.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Synchronized electric meter having an atomic clock

Smart electric meters configured to perform fast, time-synchronized electrical energy measurements at the consumer-level are disclosed herein. In some embodiments, a smart electric meter includes circuitry configured to measure an electrical value at a location of an end user in a power system. The smart electric meter can further include an atomic clock configured to output a timing signal, and a controller configured to receive (a) the measured electrical value from the circuitry and (b) the timing signal from the atomic clock. The controller can further (a) process the electrical value to generate meter data and (b) generate a time tag based on the timing signal. Then, the controller can associate the time tag with the meter data to generate time-tagged meter data.

Min, Liang↗

NASA NTRS1973

The application of the analog signal to discrete time interval converter to the signal conditioner power supplies

The Analog Signal to Discrete Time Interval Converter microminiaturized module was utilized to control the signal conditioner power supplies. The multi-loop control provides outstanding static and dynamic performance characteristics, exceeding those generally associated with single-loop regulators. Eight converter boards, each containing three independent dc to dc converter, were built, tested, and delivered.

Schoenfeld, A. D.↗

DOE OSTI2023

Uncertainty Aware Deep Learning for Fault Prediction Using Multivariate Time Series Signals

The superconducting radio-frequency cavities are a crucial component of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. When a cavity faults, beam delivery to experimental end users is disrupted. Prediction of cavity faults prior to onset is essential to reduce operation and maintenance costs. In this work, a parallel long short-term memory (LSTM)-convolution neural network (CNN)-based deep learning (DL) model is proposed to predict impending faults using pre-fault signals. Further, we introduce an uncertainty quantification approach using Monte Carlo dropout with the LSTM-CNN model to ascertain confidence in the prediction. The model was tested using multivariate time series signals from stable cavity operations and before faults. Initial results show that on the test dataset, the model can identify impending faults before their onset with an average 10-fold cross validation accuracy of 97.39% and a standard deviation of 0.12% using a 100-ms time window. It is also observed that the model performs better as the prediction time moves closer to the fault onset. For additional context, we compare the performance of the model with three machine-learning-based (ML) fault prediction models. Our proposed parallel LSTM-CNN-based DL method shows better performance than the ML-based methods.

Rahman, Md Monibor↗

NASA NTRS2007

Real-time Signal-to-noise Ratio (SNR) Estimation for BPSK and QPSK Modulation Using the Active Communications Channel

Method and apparatus for estimating signal-to-noise ratio (SNR) gamma of a composite input signal e(t) on a phase modulated (e.g., BPSK) communications link. A first demodulator receives the composite input signal and a stable carrier signal and outputs an in-phase output signal; a second demodulator receives the composite input signal and a phase-shifted version of the carrier signal and outputs a quadrature-phase output signal; and phase error theta(sub E)(t) contained within the composite input signal e(t) is calculated from the outputs of the first and second demodulators. A time series of statistically independent phase error measurements theta(sub E)(t(sub 1)), theta (sub E)(t(sub 2)),..., theta (sub E)(t(sub k)) is obtained from the composite input signal subtending a time interval delta t = t(sub k) - t(sub 1) whose value is small enough such that gamma(t) and sigma(t) can be taken to be constant in delta t. A biased estimate gamma(sup *) for the signal-to-noise ratio (SNR) gamma if the composite input signal is calculated using maximum likelihood (ML) estimation techniques, and an unbiased estimate gamma(sup ^) for the signal-to-noise ratio (SNR) gamma of the composite input signal is determined from the biased estimate gamma(sup *), such as by use of a look-up table.

Manning, Robert M.↗

NASA NTRS1979

Satellite time transfer via Tracking and Data Relay Satellite System (TDRSS) and applications

With two geosynchronous relay satellites the tracking and data relay satellite system (TDRSS) can provide nearly worldwide coverage for communication between all near orbiting satellites and the satellite control center at Goddard Space Flight Center. Each future NASA satellite will carry a TDRSS transponder with which the satellite can communicate through a TDRSS to the ground station at White Sands, New Mexico. It is using this system that the ground station master clock time signal can be transmitted to the near Earth orbiting satellite in which a clock may be maintained independently to the accuracy required by the experimenters. The satellite time transfer terminal design concept and the application of the time signal in autonomously operated spacecraft clock are discussed. Some pertinent TDRSS parameters and corrections for the propagation delay measurement as well as the time code used to transfer the time signal are given.

Chi, A. R.↗

DOE OSTI2018

Quantum-authenticated clock signal

The present disclosure is directed to a system and method of distributing time information to enable synchronization in an authenticated manner via a quantum channel. A source device may transmit a timing signal, T on a communication channel from the source device to a receiver device. The timing signal T may be include a time or times stored in memory or calculated using a previously agreed upon formula. The method may include transmitting a quantum system Q from the source device to the receiver device. The quantum system may be prepared in a randomly chosen state and may be measured by the receiver device in a randomly chosen measurement basis.

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

TH-C-17A-01: Imaging Sensor Comparison for Real-Time Cherenkov Signal Detection From Tissue for Treatment Verification

Purpose: To identify the optimum imaging sensor for a clinical system that would provide real-time imaging of the surface beam profile on patients as novel visual information to radiation therapy technologists, and more rapidly collect clinical data for large-scale studies of Cherenkov applications in radiotherapy. Methods: Four camera types, CMOS, CCD, ICCD and EMICCD, were tested to determine proficiency in the detection of Cherenkov signal in the clinical radiotherapy setting, and subsequent maximum supportable frame rate. Where possible, time-gating between the trigger signal from the LINAC and the intensifiers was implemented to detect signal with room lighting conditions comparable to patient treatment scenarios. A solid water phantom was imaged by the EM-ICCD and ICCD to evaluate the minimum number of accumulations-on-chip required for adequate Cherenkov detection, defined as >200% electron counts per pixel over background signal. Additionally, an ICCD and EM-ICCD were used clinically to image patients undergoing whole-breast radiation therapy, to understand the impact of the resolution limitation of the EM-ICCD. Results: The intensifier-coupled cameras performed best at imaging Cherenkov signal, even with room lights on, which is essential for patient comfort. The tested EM-ICCD was able to support single-shot imaging and frame rates of 30 fps, however, the current maximum resolution of 512 × 512 pixels was restricting. The ICCD used in current clinical trials was limited to 4.7 fps at a 1024 × 1024 resolution. An intensifier with higher quantum efficiency at the entrance photocathode in the red wavelengths (30% QE vs current 7%) promises 16 fps at the same resolution at lower cost than the EM-ICCD. Conclusion: The ICCD with the better red wavelength QE intensifier was determined to be the best suited commercial-off-the-shelf camera to detect real-time Cherenkov signal and provide the best potential for real-time display of radiation dose on the skin during treatment. Funding is from grants from the NIH numbers R01CA109558 and R21EB017559.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Integrated Routing and Traffic Signal Control for CAVs via Reinforcement Learning Approach

Incorporating Connected and Automated Vehicles (CAVs) into urban traffic networks presents opportunities and challenges for traffic management systems. This paper aims to develop an integrated routing and traffic signal control system designed explicitly for CAVs, utilizing a Reinforcement Learning (RL) approach. The objective is to enhance traffic flow and improve overall transportation efficiency in the controlled areas. We propose an innovative framework that employs the Deep Reinforcement Learning (DRL) algorithm, especially the Deep Q-network (DQN), to dynamically adjust the number of vehicles in the routes and the duration of traffic signals. Our simulation results demonstrate that a DQN agent successfully optimizes the number of vehicles in the routes and traffic signal timings of traffic signal controllers, eventually reducing total travel time. The study illustrates the potential usage of RL-based systems in managing routing and traffic signals for CAVs, offering a promising opportunity for future urban traffic management strategies.

Park, Jiho [New York University]↗

DOE OSTI2013

Electron-ion relaxation time dependent signal enhancement in ultrafast double-pulse laser-induced breakdown spectroscopy

We investigated the emission properties of collinear double-pulse compared to single-pulse ultrafast laser induced breakdown spectroscopy. Our results showed that the significant signal enhancement noticed in the double pulse scheme is strongly correlated to the characteristic electron-ion relaxation time and hence to the inter-pulse delays. Spectroscopic excitation temperature analysis showed that the improvement in signal enhancement is caused by the delayed pulse efficient reheating of the pre-plume. The signal enhancement is also found to be related to the upper excitation energy of the selected lines, i.e., more enhancement noticed for lines originating from higher excitation energy levels, indicating reheating is the major mechanism behind the signal improvement.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E²)

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2 ) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly considering the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Furthermore, compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Time-dependent signals of new physics at the LHC

The Large Hadron Collider (LHC) is sensitive to signals of beyond the Standard Model physics through a variety of channels including missing energy and resonance searches. In most searches, the new physics and the Standard Model backgrounds are assumed to be invariant in time, up to systematic effects from the experiment. However, new physics with a time variation would provide an additional handle to separate signal from background. Such a time variation may come from ultralight dark matter coupling to an oscillating background field. In this paper, we consider an interaction of dark matter with quarks and an additional heavy particle, and show that the sensitivity of a search that uses timing information at the LHC can be up to a factor of two stronger compared to one that does not use time information.

Fieg, Max H. [Fermilab] (ORCID:0000000270276921)↗

DOE OSTI2019

Ultrafast all-optical modulation of the visible and infrared spectrum with nanorod arrays

Disclosed herein is a method of optical modulation, the method comprising irradiating an optical switch with a control beam at a first control time and irradiating the optical switch with a signal beam at a signal time. The transmitted intensity of the signal beam in a direction depends on the delay time between the first control time and the signal time and the transmitted intensity of the signal beam in the direction is detectably different than a static signal. The optical switch comprises a nanorod array, the nanorod array comprising a plurality of nanorods extending outwardly from a substrate.

Chang, Robert P. H.↗

NASA NTRS1974

The uses and limitations of HF standard broadcasts for time and frequency comparison

The most practical methods of using high-frequency (HF) broadcasts for frequency and time comparison are reviewed. Although standard broadcast and receiving equipment has improved vastly throughout the past fifty years, the HF propagation medium is no more stable today than it was a half century ago. Doppler shift resulting from changes in the effective height of the ionosphere typically limits the usable accuracy of received high frequencies to a few parts in 10 to the 7th power. At locations beyond groundwave range of the transmitter, uncertainties in path delay generally restrict the usable accuracy of HF time signals to the order of a millisecond. Signal-averaging techniques are sometimes employed to extract frequency or time signals from a noisy background.

Stanley, J. T.↗

NASA NTRS1995

Precise Time-Tag Generator For A Local-Area-Network Monitor

Time-tag-generating circuit designed for use in LAN monitor, monitors frames of data transmitted among computers on local-area network (LAN). To each frame of data that LAN monitor receives from LAN, time-tag generator appends ancillary data on time of arrival of frame, precise to within 1 microsecond of centrally generated time signal. Inserts ancillary time data in place of already used frame-check data before frames of data stored in memory of LAN monitor.

Stauffer, David R.↗