Scholarly Works, Biomedical Engineering and Mechanics

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https://hdl.handle.net/10919/24286
Research articles, presentations, and other scholarship

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Browsing Scholarly Works, Biomedical Engineering and Mechanics by Department "Aerospace and Ocean Engineering"

Now showing 1 - 5 of 5
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    Dynamic Analysis and Design Optimization of a Drag-Based Vibratory Swimmer
    Tahmasian, Sevak; Jafaryzad, Arsam; Bulzoni, Nicolas L.; Staples, Anne E. (MDPI, 2020-03-22)
    Many organisms achieve locomotion via reciprocal motions. This paper presents the dynamic analysis and design optimization of a vibratory swimmer with asymmetric drag forces and fluid added mass. The swimmer consists of a floating body with an oscillatory mass inside. One-dimensional oscillations of the mass cause the body to oscillate with the same frequency as the mass. An asymmetric rigid fin attached to the bottom of the body generates asymmetric hydrodynamic forces, which drive the swimmer either backward or forward on average, depending on the orientation of the fin. The equation of motion of the system is a time-periodic, piecewise-smooth differential equation. We use simulations to determine the hydrodynamic forces acting on the fin and averaging techniques to determine the dynamic response of the swimmer. The analytical results are found to be in good agreement with vibratory swimmer prototype experiments. We found that the average unidirectional speed of the swimmer is optimized if the ratio of the forward and backward drag coefficients is minimized. The analysis presented here can aid in the design and optimization of bio-inspired and biomimetic robotic swimmers. A magnetically controlled microscale vibratory swimmer like the one described here could have applications in targeted drug delivery.
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    Intercomparison of Small Unmanned Aircraft System (sUAS) Measurements for Atmospheric Science during the LAPSE-RATE Campaign
    Barbieri, Lindsay; Kral, Stephan T.; Bailey, Sean C. C.; Frazier, Amy E.; Jacob, Jamey D.; Reuder, Joachim; Brus, David; Chilson, Phillip B.; Crick, Christopher; Detweiler, Carrick; Doddi, Abhiram; Elston, Jack; Foroutan, Hosein; González-Rocha, Javier; Greene, Brian R.; Guzman, Marcelo I.; Houston, Adam L.; Islam, Ashraful; Kemppinen, Osku; Lawrence, Dale; Pillar-Little, Elizabeth A.; Ross, Shane D.; Sama, Michael P.; Schmale, David G. III; Schuyler, Travis J.; Shankar, Ajay; Smith, Suzanne W.; Waugh, Sean; Dixon, Cory; Borenstein, Steve; de Boer, Gijs (MDPI, 2019-05-10)
    Small unmanned aircraft systems (sUAS) are rapidly transforming atmospheric research. With the advancement of the development and application of these systems, improving knowledge of best practices for accurate measurement is critical for achieving scientific goals. We present results from an intercomparison of atmospheric measurement data from the Lower Atmospheric Process Studies at Elevation—a Remotely piloted Aircraft Team Experiment (LAPSE-RATE) field campaign. We evaluate a total of 38 individual sUAS with 23 unique sensor and platform configurations using a meteorological tower for reference measurements. We assess precision, bias, and time response of sUAS measurements of temperature, humidity, pressure, wind speed, and wind direction. Most sUAS measurements show broad agreement with the reference, particularly temperature and wind speed, with mean value differences of 1.6 ± 2.6 ∘ C and 0.22 ± 0.59 m/s for all sUAS, respectively. sUAS platform and sensor configurations were found to contribute significantly to measurement accuracy. Sensor configurations, which included proper aspiration and radiation shielding of sensors, were found to provide the most accurate thermodynamic measurements (temperature and relative humidity), whereas sonic anemometers on multirotor platforms provided the most accurate wind measurements (horizontal speed and direction). We contribute both a characterization and assessment of sUAS for measuring atmospheric parameters, and identify important challenges and opportunities for improving scientific measurements with sUAS.
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    Lagrangian Reduced Order Modeling Using Finite Time Lyapunov Exponents
    Xie, Xuping; Nolan, Peter J.; Ross, Shane D.; Mou, Changhong; Iliescu, Traian (MDPI, 2020-10-23)
    There are two main strategies for improving the projection-based reduced order model (ROM) accuracy—(i) improving the ROM, that is, adding new terms to the standard ROM; and (ii) improving the ROM basis, that is, constructing ROM bases that yield more accurate ROMs. In this paper, we use the latter. We propose two new Lagrangian inner products that we use together with Eulerian and Lagrangian data to construct two new Lagrangian ROMs, which we denote α-ROM and λ-ROM. We show that both Lagrangian ROMs are more accurate than the standard Eulerian ROMs, that is, ROMs that use standard Eulerian inner product and data to construct the ROM basis. Specifically, for the quasi-geostrophic equations, we show that the new Lagrangian ROMs are more accurate than the standard Eulerian ROMs in approximating not only Lagrangian fields (e.g., the finite time Lyapunov exponent (FTLE)), but also Eulerian fields (e.g., the streamfunction). In particular, the α-ROM can be orders of magnitude more accurate than the standard Eulerian ROMs. We emphasize that the new Lagrangian ROMs do not employ any closure modeling to model the effect of discarded modes (which is standard procedure for low-dimensional ROMs of complex nonlinear systems). Thus, the dramatic increase in the new Lagrangian ROMs’ accuracy is entirely due to the novel Lagrangian inner products used to build the Lagrangian ROM basis.
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    Pollution Transport Patterns Obtained Through Generalized Lagrangian Coherent Structures
    Nolan, Peter J.; Foroutan, Hosein; Ross, Shane D. (MDPI, 2020-02-06)
    Identifying atmospheric transport pathways is important to understand the effects of pollutants on weather, climate, and human health. The atmospheric wind field is variable in space and time and contains complex patterns due to turbulent mixing. In such a highly unsteady flow field, it can be challenging to predict material transport over a finite-time interval. Particle trajectories are often used to study how pollutants evolve in the atmosphere. Nevertheless, individual trajectories are sensitive to their initial conditions. Lagrangian Coherent Structures (LCSs) have been shown to form the template of fluid parcel motion in a fluid flow. LCSs can be characterized by special material surfaces that organize the parcel motion into ordered patterns. These key material surfaces form the core of fluid deformation patterns, such as saddle points, tangles, filaments, barriers, and pathways. Traditionally, the study of LCSs has looked at coherent structures derived from integrating the wind velocity field. It has been assumed that particles in the atmosphere will generally evolve with the wind. Recent work has begun to look at the motion of chemical species, such as water vapor, within atmospheric flows. By calculating the flux associated with each species, a new effective flux-based velocity field can be obtained for each species. This work analyzes generalized species-weighted coherent structures associated with various chemical species to find their patterns and pathways in the atmosphere, providing a new tool and language for the assessment of pollutant transport and patterns.
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    Wind Dispersal of Natural and Biomimetic Maple Samaras
    Nave, Gary K.; Hall, Nathaniel; Somers, Katrina; Davis, Brock; Gruszewski, Hope A.; Powers, Craig W.; Collver, Michael; Schmale, David G. III; Ross, Shane D. (MDPI, 2021-03-29)
    Maple trees (genus Acer) accomplish the task of distributing objects to a wide area by producing seeds, known as samaras, which are carried by the wind as they autorotate and slowly descend to the ground. With the goal of supporting engineering applications, such as gathering environmental data over a broad area, we developed 3D-printed artificial samaras. Here, we compare the behavior of both natural and artificial samaras in both still-air laboratory experiments and wind dispersal experiments in the field. We show that the artificial samaras are able to replicate (within one standard deviation) the behavior of natural samaras in a lab setting. We further use the notion of windage to compare dispersal behavior, and show that the natural samara has the highest mean windage, corresponding to the longest flights during both high wind and low wind experimental trials. This study demonstrated a bioinspired design for the dispersed deployment of sensors and provides a better understanding of wind-dispersal of both natural and artificial samaras.