Bulletin of the American Physical Society
2018 Annual Meeting of the APS Four Corners Section
Volume 63, Number 16
Friday–Saturday, October 12–13, 2018; University of Utah, Salt Lake City, Utah
Session C02: Acoustics and Vibrations 1 |
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Chair: Meenakshi Singh, Colorado School of Mines Room: JFB 102 |
Friday, October 12, 2018 10:45AM - 11:09AM |
C02.00001: Learning how to listen to the ocean Invited Speaker: Tracianne B Neilsen Shallow ocean environments are diverse. Variations in water depth,sound speed, and the ocean floor affect how sound propagates making it difficult to identify where sound originates. Models for sound propagation are based on ray tracing, normal modes, and parabolic equations. These models predict the frequency-dependent sound field for a set of environmental parameters when the location of the sound source is known. The inverse problem is actually of more interest: finding the location of a sound source when you don’t know the exact ocean environment. Optimization algorithms have tackled this problem for many years. The future, however, lies with machine learning and deep learning. Machine learning will likely be sufficient for source classification when a fairly good estimate of the environment is known, but deep learning will be needed to address complexities associated with uncertain ocean properties. |
Friday, October 12, 2018 11:09AM - 11:21AM |
C02.00002: Efficient Computation of Vibrational Properties of Bulk and Surface BCC, FCC, HCP and 9R Lattice Structures Jake D Christensen, D.M. Riffe Models of the potential energy of metallic crystalline structures are commonly used to compute interesting and useful properties of those metals. Dispersion curves and densities of state can be calculated by finding the eigenvalues of the dynamical matrix. Although simple expressions for the dynamical matrix exist for certain crystalline structures, such as body-centered cubic (BCC) and face-centered cubic (FCC), calculating the dynamical matrix for an arbitrary crystal structure is computationally non-trivial. Here, we develop a user-friendly program to efficiently compute thermal properties of both bulk and surface BCC, FCC, hexagonal close packed (HCP), and 9R materials. Results derived from a previously developed EAM model are discussed |
Friday, October 12, 2018 11:21AM - 11:33AM |
C02.00003: Vibrational spectroscopy of 2:1 family of Prussian Blue Analogues Md Minuddin, Luke Daemen, Antonio Dos Santos, Heinz Nakotte Prussian Blue Analogues (PBAs) have important technological applications in negative thermal expansion, hydrogen storage and magneto optical devices. It provides large tolerances for atomic substitutions, which opens up the prospect that one can tune their functional properties to specialized applications. In the PBAs framework structure there are coordinated water molecules and interstitial water molecules that affect the properties. We synthesized 5 different compounds with compositions M^{II}_{2}[Fe^{II}(CN)_{6}]._{ }xH_{2}O, where M = Mn, Co, Ni, Cu, and Zn and x is number of water molecules. Thermogravimetric Analysis was used to find the number of water molecule in each compound. The positions of water molecules were determined using Rietveld refinement of X-ray diffraction data. The neutron vibrational spectrum for all those compounds were studied in detail. It shows well-defined, well-separated bands corresponding to stretching and deformation modes of the Fe and M^{II} octahedra. |
Friday, October 12, 2018 11:33AM - 11:45AM |
C02.00004: Characterizing Vibrationally Induced Damage of Carbon Nanotube Forests Jordan Lee, Brian Wood, Ashlan Keeler, JR Dennison, T.-C. Shen Carbon nanotubes (CNT) have been a topic of scientific interest due to their high tensile strength, high aspect ratio geometry, and unique electromagnetic characteristics. Carbon nanotube forests, vertically aligned CNT arrays grown on substrates, have specifically been considered to assist with space-faring sensor applications due to their extremely low photon and electron reflectivity. Three multi-walled CNT forests of varying height and density were submitted to intense off-axis shaking with g-forces similar to those experienced during rocket liftoff. Scanning electron imagery, optical UV/Vis/NIR reflectivity, and electron yield were measured before and after the samples had been shaken to characterize changes. A drastic morphological change was apparent on the edges of the samples, yet optical reflectivity and electron yield produced no substantial variance. This provides evidence that CNT forests are robust enough to in survive the transit into space for integral sensor applications. |
Friday, October 12, 2018 11:45AM - 11:57AM |
C02.00005: Directionality of Scale-model Volcano Acoustics Sarah A Shaw, Julio A. Escobedo, Carla Butts, Tracianne B Neilsen Volcanic eruptions, and the ash they produce, have the potential to cause problems to air travel as well as to the environment in general. The purpose of this study is to discover the directionality of the infrasound of volcanoes in order to estimate the power of a volcano and the quantity and ash content of the debri. We used scale-model explosions to measure acoustic levels, sound power and directivity. Our goal is to estimate the directionality of these explosions when measurements were not concentric with the origin of the explosion. Balloons filled with a stoichiometric mixture of oxy acetylene when exploded produced acoustic shock waves. We used a high-fidelity data acquisition system and research-grade microphone arrays. We used four circular microphone arrays centered on the four blast locations. Then we took measurements using a single semi-circle setup for the four blasts locations. The goal is to connect the two measurements and determine how to interpret the directivity from data collected from the semicircle setup. This study of acoustic scale-model explosions will help us interpret volcano infrasound. |
Friday, October 12, 2018 11:57AM - 12:09PM |
C02.00006: Estimation of the Maximal Lyapunov Exponent in Thermoacoustic Engines Kyle S.H. Hutchings, Don McLaughlin, Bonnie J. Andersen Nonlinear dynamics and chaos theory have given insights into the behavior of a wide variety of systems. Nonlinearities in acoustic systems can result in intriguing behavior, such as period doubling and structured chaos. Historically, mathematical modeling for thermoacoustic engines has been in the analytic realm. In this work we visit an alternative visual realm to study their behavior. The possible presence of chaos was tested by looking for a key element of chaos: a positive Lyapunov exponent. Twenty-one data sets of discrete pressure data gathered from thermoacoustic prime movers were analyzed with two programs. One estimated the maximal Lyapunov exponent, and another displayed phase-space plots. For each data set, a positive Lyapunov exponent was found and corresponding phase-space plots qualitatively confirmed orbital divergence. These results strongly suggest that chaotic behavior is obtainable in thermoacoustic systems. A careful study of the experimental time series data suggests an intuitive quantitative model consisting of discrete sigmoid modulated growth. We chose two simple component functions, sine modulations and Verhulst logistic growth. Using this method, experimental data can be faithfully projected to an event horizon at about 15 iterations. |
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