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Ohodnicki, Paul

Publications and source records attributed to Ohodnicki, Paul.

7 records
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↗
DOE OSTI2024

Reduced Order Model for Guided Wave Propagation on Gas Pipelines to Enable Real-Time Simulation

Reduced order model for simulation of Guided wave propagation is presented here. The utilization of reduced order models ensures efficient data generation for a variety of parameters where it takes huge computational effort to simulate, crucial for timely monitoring and decision-making. Autoencoder based reduced order models are proposed here, which are trained on simulated data from open-source finite element framework, Firedrake.

Bukka, Sandeep Reddy↗
DOE OSTI2024

Reduced Order Model for Guided Wave Propagation on Gas Pipelines to Enable Real-Time Simulation

Reduced order model for simulation of Guided wave propagation is presented here. The utilization of reduced order models ensures efficient data generation for a variety of parameters where it takes huge computational effort to simulate, crucial for timely monitoring and decision-making. Autoencoder based reduced order models are proposed here, which are trained on simulated data from open-source finite element framework, Firedrake.

Bukka, Sandeep Reddy↗
DOE OSTI2024

Transformer designs for very high isolation with high coupling

Various examples are provided related to transformer designs that offer very high isolation while maintaining high coupling between the windings. In one example, an isolation transformer includes a first excitation coil wound around a first core and a second excitation coil wound about a second core. The second core is electrically separated from the first core by a high resistivity magnetic material or a non-conductive material. The first and second cores can include corresponding core segments arranged in a trident geometry or a quindent geometry. The core segments can align when the first excitation coil is inserted into a void of the second excitation coil. The isolation transformer designs are mechanically separable which can result in safe, energized, plug operations.

Beddingfield, Richard Byron↗
DOE OSTI2024

Achieving precise multiparameter measurements with distributed optical fiber sensor using wavelength diversity and deep neural networks

The development of advanced distributed optical fiber sensing systems that are capable of performing accurate and spatially resolved multiparameter measurements is of great interest to a wide range of scientific and industrial applications. Here, in this paper, we propose and experimentally demonstrate a wavelength diversity based advanced distributed optical fiber sensor system to accomplish multiparameter sensing while greatly enhancing measurement accuracy. A suite of deep neural network (DNN) algorithms are developed and verified for data denoising, rapid Brillouin frequency shift estimation, and vibration data event classification. As a proof-of-concept, we demonstrate the effectiveness of the proposed advanced wavelength diversity distributed fiber sensor system assisted by DNN for simultaneous, independent measurements of static strain, temperature, and acoustic vibrations over a 25 km long sensing fiber at 3 m spatial resolution. These results suggest the potential for an intelligent multiparameter monitoring system with enhanced performance in advanced structural health monitoring applications.

47 OTHER INSTRUMENTATION↗
NASA NTRS2020

Core Losses in Co-Rich Inductors with Tunable Permeability

High frequency, low loss power systems enable electrified aircraft propulsion. Filter inductors that reduce noise in high current systems can account for 50% of the motor drive mass. Efficient inductor cores with tunable permeability reduce system mass by producing less heat, that removes heat sink mass. Requirements for filter inductors vary based on the chosen topology, but all inductor cores must operate below saturation levels. As the saturation flux density is limited (less than ~2 T), high differential current applications require cores with low relative permeabilities. The large induced anisotropies possible in Co-rich metal amorphous nanocomposite materials enables gapless inductors with relative permeabilities down to ~20. These materials have fine grain size ~8nm with a faulted, close packed structure. The impact of different processing methods on core losses are presented along with comparison to other low permeability soft magnetic materials.

Leary, Alex↗