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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

AC Magnetometry Using Nano-ferrofluid Cladded Multimode Interferometric Fiber Optic Sensors for Power Grid Monitoring Applications

The AC magnetic field response of the superparamagnetic nano-ferrofluid is an interplay between the Neel and Brownian relaxation processes and is generally quantified via the susceptibility measurements at high frequencies. The high frequency limit is dictated by these relaxation times which need to be shorter than the time scale of the time varying magnetic field for the nano-ferrofluid to be considered in an equilibrium state at each time instant. Even though the high frequency response of ferrofluid has been extensively investigated for frequencies up to GHz range by non-optical methods, harnessing dynamic response by optical means for AC magnetic field sensing in fiber-optic-based sensors-field remains unexplored. Instead, the incorporation of nano-ferrofluid as sensing materials has been only limited to DC magnetic field sensing, often citing their long response time as a limiting factor to AC field sensing. This work reports the finding of high frequency (up to 15 kHz) AC magnetic field sensing capability of nanomagnetic fluid as the cladding material of a fiber-optic multimode interferometry (MMI) structure optimized for the fourth self-imaging spectral response. The key parameter enabling high frequency response is the short response time (<1 ms) achieved by optimizing both the sensing structure and nano-ferrofluid solution. Focus has been imparted on 60 Hz line-frequency profiles of various current/magnetic fields to test the efficacy of these sensors in metering and monitoring current and current-induced magnetic fields in the electrical power grid systems. The magnetic field sensitivity of 240 mV/Gauss per dBm of transmitted power was achieved for 60 Hz field applied via Helmholtz coil, whereas the 60 Hz AC current sensitivity of 2.83 mV/A was measured due to magnetic field induced by current in a straight conducting wire.

42 ENGINEERING↗
NASA NTRS1966

Flowgraph techniques for closed systems.

Flowgraph techniques for closed systems, discussing properties, approximation method, topology equation, frequency response, constraints, oscillatory and stochastic processes, etc

HARMONIC OSCILLATOR↗
NASA NTRS2006

Phase Calibration of Microphones by Measurement in the Free-field

Over the past several years, significant effort has been expended at NASA Langley developing new Micro-Electro-Mechanical System (MEMS)-based microphone directional array instrumentation for high-frequency aeroacoustic measurements in wind tunnels. This new type of array construction solves two challenges which have limited the widespread use of large channel-count arrays, namely by providing a lower cost-per-channel and a simpler method for mounting microphones in wind tunnels and in field-deployable arrays. The current generation of array instrumentation is capable of extracting accurate noise source location and directivity on a variety of airframe components using sophisticated data reduction algorithms [1-2]. Commercially-available MEMS microphones are condenser-type devices and have some desirable characteristics when compared with conventional condenser-type microphones. The most important advantages of MEMS microphones are their size, price, and power consumption. However, the commercially-available units suffer from certain important shortcomings. Based on experiments with array prototypes, it was found that both the bandwidth and the sound pressure limit of the microphones should be increased significantly to improve the performance and flexibility of the microphone array [3]. It was also desired to modify the packaging to eliminate unwanted Helmholtz resonance s exhibited by the commercial devices. Thus, new requirements were defined as follows: Frequency response: 100 Hz to 100 KHz (+/-3dB) Upper sound pressure limit: Design 1: 130 dB SPL (THD less than 5%) Design 2: 150-160 dB SPL (THD less than 5%) Packaging: 3.73 x 6.13 x 1.3 mm can with laser-etched lid. In collaboration with Novusonic Acoustic Innovation, NASA modified a Knowles SiSonic MEMS design to meet these new requirements. Coupled with the design of the enhanced MEMS microphones was the development of a new calibration method for simultaneously obtaining the sensitivity and phase response of the devices over their entire broadband frequency range. Traditionally, electrostatic actuators (EA) have been used to characterize air-condenser microphones; however, MEMS microphones are not adaptable to the EA method due to their construction and very small diaphragm size [4]. Hence a substitution based, free-field method was developed to calibrate these microphones at frequencies up to 80 kHz. The technique relied on the use of a random, ultrasonic broadband centrifugal sound source located in a small anechoic chamber. The free-field sensitivity (voltage per unit sound pressure) was obtained using the procedure outlined in reference 4. Phase calibrations of the MEMS microphones were derived from cross spectral phase comparisons between the reference and test substitution microphones and an adjacent and invariant grazing-incidence 1/8-inch standard microphone. The free-field calibration procedure along with representative sensitivity and phase responses for the new high-frequency MEMS microphones are presented here.

Shams, Qamar A.↗
DOE OSTI2018

Small-Signal Stability Analysis of Large-Scale Power Systems in Response to Variability of Offshore Wind Power Plants

This paper presents a methodology for a small-signal stability analysis of large-scale power systems in response to variability of offshore wind power plants. This study considers the variability of wind power as the source of disturbance introduced to the system. To accomplish this goal, a singular value decomposition-total least squares extended Prony analysis is used to assess the small-signal voltage stability. In addition, a swing-based frequency response metric is used to assess the small-signal frequency stability. The case study here considers the integration of a 1000-MW offshore wind power plant, operating in Lake Erie, into the FirstEnergy/PJM service territory. This study uses a realistic model of the 63 000-bus test system that represents the U.S. Eastern Interconnection. The results verify the utility and practicality of this methodology for the integration studies of offshore wind power plants.

17 WIND ENERGY↗
DOE OSTI2024

Power System Frequency Dynamics Modeling, State Estimation, and Control using Neural Ordinary Differential Equations (NODEs) and Soft Actor-Critic (SAC) Machine Learning Approaches

With the global energy transition of the electric power system, grid control, supervision, and protection is becoming more challenging. With the increasing integration of renewable energy sources (RES), the system dynamics are changing, causing traditional power system dynamic modeling with swing equation-based modeling approaches to fail. Additionally, the converter-dominated power grid is decreasing the system inertia, making the power system more fragile to the frequency swings. This paper first investigates and compares the application of a model-based Kalman filter state estimation approach with (i) a model-free machine learning approach --- neural ordinary differential equations (NODEs) --- and (ii) a data-driven system identification (SysId) approach to model and infer critical state values of the power system frequency dynamics. Then a model predictive control (MPC) framework is compared to a model-free Soft Actor-Critic (SAC) reinforcement learning (RL) control algorithm in providing efficient fast frequency response (FFR) to the power system frequency dynamics. The approaches are compared in terms of their performance goals as well as their per-timestep computational efficiency. Furthermore, the comparative study for state estimation shows that for the model-free requirement, both NODEs and SysId can provide accurate state estimates; however, with increasing model complexity, NODEs can be a better choice for model identification. Similarly, the results from the FFR comparative study show that the SAC RL-based FFR, once trained, outperforms MPC with better control signals and faster computation time, making the SAC RL-based FFR better option for providing FFR to the power system.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1971

Noise analysis of nucleate boiling

The techniques of noise analysis have been utilized to investigate nucleate pool boiling. A simple experimental setup has been developed for obtaining the power spectrum of a nucleate boiling system. These techniques were first used to study single bubbles, and a method of relating the two-dimensional projected size and the local velocity of the bubbles to the auto-correlation functions is presented. This method is much less time consuming than conventional methods of measurement and has no probes to disturb the system. These techniques can be used to determine the contribution of evaporation to total heat flux in nucleate boiling. Also, these techniques can be used to investigate the effect of various parameters upon the frequency response of nucleate boiling. The predominant frequencies of the power spectrum correspond to the frequencies of bubble generation. The effects of heat input, degree of subcooling, and liquid surface tension upon the power spectra of a boiling system are presented. It was found that the degree of subcooling has a more pronounced effect upon bubble size than does heat flux. Also the effect of lowering surface tension can be sufficient to reduce the effect of the degree of subcooling upon the size of the bubbles.

Mcknight, R. D.↗
NASA NTRS2000

Characterization of Advanced Avalanche Photodiodes for Water Vapor Lidar Receivers

Development of advanced differential absorption lidar (DIAL) receivers is very important to increase the accuracy of atmospheric water vapor measurements. A major component of such receivers is the optical detector. In the near-infrared wavelength range avalanche photodiodes (APD's) are the best choice for higher signal-to-noise ratio, where there are many water vapor absorption lines. In this study, characterization experiments were performed to evaluate a group of silicon-based APD's. The APD's have different structures representative of different manufacturers. The experiments include setups to calibrate these devices, as well as characterization of the effects of voltage bias and temperature on the responsivity, surface scans, noise measurements, and frequency response measurements. For each experiment, the setup, procedure, data analysis, and results are given and discussed. This research was done to choose a suitable APD detector for the development of an advanced atmospheric water vapor differential absorption lidar detection system operating either at 720, 820, or 940 nm. The results point out the benefits of using the super low ionization ratio (SLIK) structure APD for its lower noise-equivalent power, which was found to be on the order of 2 to 4 fW/Hz(sup (1/2)), with an appropriate optical system and electronics. The water vapor detection systems signal-to-noise ratio will increase by a factor of 10.

Refaat, Tamer F.↗
NASA NTRS2005

Real-Time Stability Margin Measurements for X-38 Robustness Analysis

A method has been developed for real-time stability margin measurement calculations. The method relies on a tailored-forced excitation targeted to a specific frequency range. Computation of the frequency response is matched to the specific frequencies contained in the excitation. A recursive Fourier transformation is used to make the method compatible with real-time calculation. The method was incorporated into the X-38 nonlinear simulation and applied to an X-38 robustness test. X-38 stability margins were calculated for different variations in aerodynamic and mass properties over the vehicle flight trajectory. The new method showed results comparable to more traditional stability analysis techniques, and at the same time, this new method provided coverage that is more complete and increased efficiency.

Bosworth, John T.↗
NASA NTRS2014

Wireless Temperature Sensor Having No Electrical Connections and Sensing Method for Use Therewith

A wireless temperature sensor includes an electrical conductor and a dielectric material on the conductor. The conductor is electrically unconnected and is shaped for storage of an electric field and a magnetic field. In the presence of a time-varying magnetic field, the conductor resonates to generate harmonic electric and magnetic field responses, each of which has a frequency associated therewith. The material is selected such that it experiences changes in either dielectric or magnetic permeability attributes in the presence of a temperature change. Shifts from the sensor's baseline frequency response indicate that the material has experienced a temperature change.

Woodard, Marie↗
NASA NTRS2018

Wireless Temperature Sensing Method Using no Electrical Connections

A wireless temperature sensor includes an electrical conductor and a material spaced apart from the conductor and located within one or more of the responding electric field and responding magnetic field of the conductor. The conductor is electrically unconnected and is shaped for storage of an electric field and a magnetic field. In the presence of a time-varying magnetic field, the conductor resonates to generate harmonic electric and magnetic field responses, each of which has a frequency associated therewith. The material is selected such that it experiences changes in one of dielectric properties and magnetic permeability properties in the presence of a temperature change. Shifts from the sensor's baseline frequency response indicate that the material has experienced a temperature change.

Woodard, Stanley E.↗
NASA NTRS2018

Practical Aspects of the Frequency Domain Approach for Aircraft System Identification

Practical aspects of the frequency-domain approach for aircraft system identification are explained and demonstrated. Topics related to experiment design, flight data analysis, and dynamic modeling are included. For demonstration purposes, simulated time series data and simulated flight data from an F-16 nonlinear simulation with realistic noise are used. This approach enables detailed evaluations of the techniques and results, because the true characteristics of the data and aircraft dynamics are known for the simulated data. Analytical techniques and practical considerations are examined for the finite Fourier transform, nonparametric frequency response estimation, parametric modeling in the frequency domain, experiment design for frequency-domain modeling, data analysis and modeling in the frequency domain, and real-time calculations. Flight data from a subscale jet transport aircraft are used to demonstrate some of the techniques and technical issues.

Morelli, Eugene A.↗