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Jessica Noe

Mechanical Engineer III

Email

jnoe@apl.washington.edu

Phone

206-221-8015

Department Affiliation

Ocean Engineering

Education

Master of Science Mechanical Engineer, University of Washington, 2020

B.S Mechanical Engineering, University of Washington, 2017

Publications

2000-present and while at APL-UW

Adaptable and distributed sensing in coastal waters: Design and performance of the μFloat system

Harrison, T.W., C. Crisp, J. Noe, J.B. Joslin, C. Riel, M. Dunbabin, J. Neasham, T.R. Mundon, and B. Polagye, "Adaptable and distributed sensing in coastal waters: Design and performance of the μFloat system," Field Rob., 3, 516-543, doi:10.55417/fr.2023016, 2023.

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1 Mar 2023

Buoyancy-controlled underwater floats have produced a wealth of in situ observational data from the open ocean. When deployed in large numbers, or "distributed arrays," floats offer a unique capacity to concurrently map 3D fields of critical environmental variables, such as currents, temperatures, and dissolved oxygen. This sensing paradigm is equally relevant in coastal waters, yet it remains underutilized due to economic and technical limitations of existing platforms. To address this gap, we developed an array of 25 μFloats that can actuate vertically in the water column by controlling their buoyancy, but are otherwise Lagrangian. Underwater positioning is achieved by acoustic localization using low-bandwidth communication with GPS-equipped surface buoys. The ĀµFloat features a high-volume buoyancy engine that provides a 9% density change, enabling automatic ballasting and vertical control from fresh to salt water (~3% density change) with reserve capacity for external sensors.

In this paper, we present design specifications and field benchmarks for buoyancy control and acoustic localization accuracy. Results demonstrate depth-holding accuracy within ±0.2 m of target depth in quiescent flow and ±0.5 m in energetic flows. Underwater localization is accurate to within ±5 m during periods with sufficient connectivity, with degradation in performance resulting from adverse sound speed gradients and unfavorable spatial distributions of surface buoys. Support for auxiliary sensors (<10% float volume) without
additional control tuning is also demonstrated. Overall performance is discussed in the context of potential use cases and demonstrated in a first-ever array-based three-dimensional survey of tidal currents.

Evaluation of two depth-holding algorithms for a buoyancy-controlled coastal float

Harrison, T., A. Ziemann, J. Noe, B. Shappell, and K. Morgansen, "Evaluation of two depth-holding algorithms for a buoyancy-controlled coastal float," Proc., IEEE OCEANS, 17-20 October, Hampton Roads, VA, doi:10.1109/OCEANS47191.2022.9977033 (IEEE, 2022).

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19 Dec 2022

For coastal floats, buoyancy control algorithms must provide high-accuracy depth control in shallow waters with fast currents and strong density gradients. Here, we compare two depth-holding algorithms through tank and field testing with the μFloat, a coastal float designed for distributed array surveys of tidal currents and other water properties. A linear-quadratic-regulator (LQR) controller was designed and implemented on the μFloat. The LQR controller was evaluated against a two-stage proportional-differential (2S-PD) previously used on the μFloat. Relative to the original 2S-PD controller, the LQR controller reduced overshoot, motor actuation, and power consumption. Implementing a wide (±0.5 m) dead-band on the LQR controller proved particularly successful, reducing motor actuation by 80% and reducing power consumption by 40–60%. The original 2S-PD controlled remained superior in minimizing time to target depth and depth-holding accuracy. Future improvements on the LQR controller are discussed.

Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center
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