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Full-Text Articles in Engineering

3-D Fabry–Pérot Cavities Sculpted On Fiber Tips Using A Multiphoton Polymerization Process, Jonathan W. Smith, Jeremiah C. Williams, Joseph S. Suelzer, Nicholas G. Usechak, Hengky Chandrahalim Dec 2020

3-D Fabry–Pérot Cavities Sculpted On Fiber Tips Using A Multiphoton Polymerization Process, Jonathan W. Smith, Jeremiah C. Williams, Joseph S. Suelzer, Nicholas G. Usechak, Hengky Chandrahalim

Faculty Publications

This paper presents 3-D Fabry–Pérot (FP) cavities fabricated directly onto cleaved ends of low-loss optical fibers by a two-photon polymerization (2PP) process. This fabrication technique is quick, simple, and inexpensive compared to planar microfabrication processes, which enables rapid prototyping and the ability to adapt to new requirements. These devices also utilize true 3-D design freedom, facilitating the realization of microscale optical elements with challenging geometries. Three different device types were fabricated and evaluated: an unreleased single-cavity device, a released dual-cavity device, and a released hemispherical mirror dual-cavity device. Each iteration improved the quality of the FP cavity's reflection spectrum. The …


End-To-End Direct Digital Synthesis Simulation And Mathematical Model To Minimize Quantization Effects Of Digital Signal Generation, Pranav R. Patel, Richard K. Martin Oct 2020

End-To-End Direct Digital Synthesis Simulation And Mathematical Model To Minimize Quantization Effects Of Digital Signal Generation, Pranav R. Patel, Richard K. Martin

Faculty Publications

Direct digital synthesis (DDS) architectures are becoming more prevalent as modern digital-to-analog converter (DAC) and programmable logic devices evolve to support higher bandwidths. The DDS architecture provides the benefit of digital control but at a cost of generating spurious content in the spectrum. The generated spurious content may cause intermodulation distortion preventing proper demodulation of the received signal. The distortion may also interfere with the neighboring frequency bands. This article presents the various DDS architectures and explores the DDS architecture which provides the most digital reconfigurability with the lowest spurious content. End-to-end analytical equations, numerical and mathematical models are developed …


Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit Sep 2020

Cost Analysis Of Optimized Islanded Energy Systems In A Dispersed Air Base Conflict, Jay F. Pearson, Torrey J. Wagner, Justin D. Delorit

Faculty Publications

The United States Air Force has implemented a dispersed air base strategy to enhance mission effectiveness for near-peer conflicts. Asset dispersal places many smaller bases across a wide geographic area, which increases resupply requirements and logistical complexity. Hybrid energy systems reduce resupply requirements through sustainable, off-grid energy production. This paper presents a novel hybrid energy renewable delivery system (HERDS) model capable of (1) selecting the optimal hybrid energy system design that meets demand at the lowest net present cost and (2) optimizing the delivery of the selected system using existing Air Force cargo aircraft. The novelty of the model’s capabilities …


Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew Terzuoli Aug 2020

Wideband Satcom Model: Evaluation Of Numerical Accuracy And Efficiency, Andrew J. Knisely, Andrew Terzuoli

Faculty Publications

The spectral method is typically applied as a simple and efficient method to solve the parabolic wave equation in phase screen scintillation models. The critical factors that can greatly affect the spectral method accuracy is the uniformity and smoothness of the input function. This paper observes these effects on the accuracy of the finite difference and the spectral methods applied to a wideband SATCOM signal propagation model simulated in the ultra-high frequency (UHF) band. The finite difference method uses local pointwise approximations to calculate a derivative. The spectral method uses global trigonometric interpolants that achieve remarkable accuracy for continuously differentiable …


Nondestructive Electromagnetic Characterization Of Uniaxial Sheet Media Using A Two-Flanged Rectangular Waveguide Probe, Neil G. Rogers, Michael J. Havrilla, Milo W. Hyde Iv, Alexander G. Knisely Jun 2020

Nondestructive Electromagnetic Characterization Of Uniaxial Sheet Media Using A Two-Flanged Rectangular Waveguide Probe, Neil G. Rogers, Michael J. Havrilla, Milo W. Hyde Iv, Alexander G. Knisely

Faculty Publications

Excerpt: Recent advancements in fabrication capabilities have renewed interest in the electromagnetic characterization of complex media, as many metamaterials are anisotropic and/or inhomogeneous. Additionally, for composite materials, anisotropy can be introduced by load, strain, misalignment, or damage through the manufacturing process [1], [2]. Methods for obtaining the constitutive parameters for isotropic materials are well understood and widely employed [3]–[8]. Therefore, it is crucial to develop a practical method for the electromagnetic characterization of anisotropic materials.


Securing Photovoltaic (Pv) System Deployments With Data Diodes, Robert D. Larkin, Torrey J. Wagner, Barry E. Mullins Jun 2020

Securing Photovoltaic (Pv) System Deployments With Data Diodes, Robert D. Larkin, Torrey J. Wagner, Barry E. Mullins

Faculty Publications

A survey of a typical photovoltaic (PV) system with and without the cybersecurity protections of a data diode is explored. This survey includes a brief overview of Industrial Control Systems (ICS) and their relationship to the Internet of Things (IoT), Industrial Internet of Things (IIoT), and Industry 4.0 terminology. The cybersecurity features of eight data diodes are compared, and the cyber attack surface, attack scenarios, and mitigations of a typical PV system are discussed. After assessing cybersecurity, the economic considerations to purchase a data diode are considered. At 13.19 cents/kWh, the sale of 227,445 kWh is needed to fund one …


A Multi-Criteria Logistics Analysis Of Photovoltaic Modules For Remote Applications, Nathan Thomsen [*], Dimitri Papazoglou, Torrey J. Wagner, Andrew J. Hoisington, Steven J. Schuldt Jun 2020

A Multi-Criteria Logistics Analysis Of Photovoltaic Modules For Remote Applications, Nathan Thomsen [*], Dimitri Papazoglou, Torrey J. Wagner, Andrew J. Hoisington, Steven J. Schuldt

Faculty Publications

Reliable electrical power grids are frequently unavailable or inaccessible in remote locations, including developing nation communities, humanitarian relief camps, isolated construction sites, and military contingency bases. This often requires sites to rely on costly generators and continuous fuel supply. Renewable energy systems (RES) in the form of photovoltaic (PV) arrays and energy storage present a rapidly improving alternative to power these remote locations. Previous RES literature and PV optimization models focused on economics, reliability, and environmental concerns, neglecting the importance of logistics factors in remote installations. This paper proposes additional optimization variables applicable to remote PV systems and compares PV …


Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan May 2020

Machine Learning Modeling Of Horizontal Photovoltaics Using Weather And Location Data, Christil Pasion, Torrey J. Wagner, Clay Koschnick, Steven J. Schuldt, Jada B. Williams, Kevin Hallinan

Faculty Publications

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined …


Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola Apr 2020

Learning Set Representations For Lwir In-Scene Atmospheric Compensation, Nicholas M. Westing [*], Kevin C. Gross, Brett J. Borghetti, Jacob A. Martin, Joseph Meola

Faculty Publications

Atmospheric compensation of long-wave infrared (LWIR) hyperspectral imagery is investigated in this article using set representations learned by a neural network. This approach relies on synthetic at-sensor radiance data derived from collected radiosondes and a diverse database of measured emissivity spectra sampled at a range of surface temperatures. The network loss function relies on LWIR radiative transfer equations to update model parameters. Atmospheric predictions are made on a set of diverse pixels extracted from the scene, without knowledge of blackbody pixels or pixel temperatures. The network architecture utilizes permutation-invariant layers to predict a set representation, similar to the work performed …


Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides Apr 2020

Single-Pulse, Kerr-Effect Mueller Matrix Lidar Polarimeter, Keyser, Christian K., Richard K. Martin, Helena Lopez-Aviles, Khanh Nguyen, Arielle M. Adams, Demetrios Christodoulides

Faculty Publications

We present a novel light detection and ranging (LiDAR) polarimeter that enables measurement of 12 of 16 sample Mueller matrix elements in a single, 10 ns pulse. The new polarization state generator (PSG) leverages Kerr phase modulation in a birefringent optical fiber, creating a probe pulse characterized by temporally varying polarization. Theoretical expressions for the Polarization State Generator (PSG) Stokes vector are derived for birefringent walk-off and no walk-off and incorporated into a time-dependent polarimeter signal model employing multiple polarization state analyzers (PSA). Polarimeter modeling compares the Kerr effect and electro-optic phase modulator–based PSG using a single Polarization State Analyzer …


Synthesizing General Electromagnetic Partially Coherent Sources From Random, Correlated Complex Screens, Milo W. Hyde Iv Mar 2020

Synthesizing General Electromagnetic Partially Coherent Sources From Random, Correlated Complex Screens, Milo W. Hyde Iv

Faculty Publications

We present a method to generate any genuine electromagnetic partially coherent source (PCS) from correlated, stochastic complex screens. The method described here can be directly implemented on existing spatial-light-modulator-based vector beam generators and can be used in any application which utilizes electromagnetic PCSs. Our method is based on the genuine cross-spectral density matrix criterion. Applying that criterion, we show that stochastic vector field realizations (corresponding to a desired electromagnetic PCS) can be generated by passing correlated Gaussian random numbers through “filters” with space-variant transfer functions. We include step-by-step instructions on how to generate the electromagnetic PCS field realizations. As an …


Cyber-Physical Security With Rf Fingerprint Classification Through Distance Measure Extensions Of Generalized Relevance Learning Vector Quantization, Trevor J. Bihl, Todd J. Paciencia, Kenneth W. Bauer Jr., Michael A. Temple Feb 2020

Cyber-Physical Security With Rf Fingerprint Classification Through Distance Measure Extensions Of Generalized Relevance Learning Vector Quantization, Trevor J. Bihl, Todd J. Paciencia, Kenneth W. Bauer Jr., Michael A. Temple

Faculty Publications

Radio frequency (RF) fingerprinting extracts fingerprint features from RF signals to protect against masquerade attacks by enabling reliable authentication of communication devices at the “serial number” level. Facilitating the reliable authentication of communication devices are machine learning (ML) algorithms which find meaningful statistical differences between measured data. The Generalized Relevance Learning Vector Quantization-Improved (GRLVQI) classifier is one ML algorithm which has shown efficacy for RF fingerprinting device discrimination. GRLVQI extends the Learning Vector Quantization (LVQ) family of “winner take all” classifiers that develop prototype vectors (PVs) which represent data. In LVQ algorithms, distances are computed between exemplars and PVs, and …


Generating Electromagnetic Dark And Antidark Partially Coherent Sources, Milo W. Hyde Iv Jan 2020

Generating Electromagnetic Dark And Antidark Partially Coherent Sources, Milo W. Hyde Iv

Faculty Publications

We present two methods to generate an electromagnetic dark and antidark partially coherent source. The first generalizes a recently published scalar approach by representing the stochastic electric field vector components as sums of randomly weighted, randomly tilted plane waves. The second method expands the field’s vector components in series of randomly weighted dark and antidark coherent modes. The statistical moments of the random weights—plane waves in the former method, coherent modes in the latter—are found by comparing the resulting means and covariances to those of the desired electromagnetic dark and antidark source. We validate both methods by simulating the generation …


Object Identification In Radar Imaging Via The Reciprocity Gap Method, Matthew Charnley, Aihua W. Wood Jan 2020

Object Identification In Radar Imaging Via The Reciprocity Gap Method, Matthew Charnley, Aihua W. Wood

Faculty Publications

In this paper, we present an experimental method for locating and identifying objects in radar imaging, specifically problems that could arise in physical situations. The data for the forward problem are generated using a discretization of the Lippmann‐Schwinger equation, and the inverse problem of object location is solved using the reciprocity gap approach to the linear sampling method. The main new development in this paper is an exploration of determining the permittivity of the object from the back‐scattered data, utilizing another discretization of the Lippmann‐Schwinger equation.
Abstract © AGU.


Magslam: Aerial Simultaneous Localization And Mapping Using Earth's Magnetic Anomaly Field, Taylor N. Lee, Aaron J. Canciani Jan 2020

Magslam: Aerial Simultaneous Localization And Mapping Using Earth's Magnetic Anomaly Field, Taylor N. Lee, Aaron J. Canciani

Faculty Publications

Instances of spoofing and jamming of global navigation satellite systems (GNSSs) have emphasized the need for alternative navigation methods. Aerial navigation by magnetic map matching has been demonstrated as a viable GNSS‐alternative navigation technique. Flight test demonstrations have achieved accuracies of tens of meters over hour‐long flights, but these flights required accurate magnetic maps which are not always available. Magnetic map availability and resolution vary widely around the globe. Removing the dependency on prior survey maps extends the benefits of aerial magnetic navigation methods to small unmanned aerial systems (sUAS) at lower altitudes where magnetic maps are especially undersampled or …


Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael Pak, Dmitri S. Golubev, Alexey Bezryadin Jan 2020

Superconducting Phase Transition In Inhomogeneous Chains Of Superconducting Islands, Eduard Ilin, Irina Burkova, Xiangyu Song, Michael Pak, Dmitri S. Golubev, Alexey Bezryadin

Faculty Publications

We study one-dimensional chains of superconducting islands with a particular emphasis on the regime in which every second island is switched into its normal state, thus forming a superconductor-insulator-normal metal (S-I-N) repetition pattern. As is known since Giaever tunneling experiments, tunneling charge transport between a superconductor and a normal metal becomes exponentially suppressed, and zero-bias resistance diverges, as the temperature is reduced and the energy gap of the superconductor grows larger than the thermal energy. Here we demonstrate that this physical phenomenon strongly impacts transport properties of inhomogeneous superconductors made of weakly coupled islands with fluctuating values of the critical …