Coastal upwelling is a wind-driven ocean process that brings cooler, saltier, and nutrient-rich deep water upward to the surface. The boundary between the upwelling water and the normally stratified water is called the "upwelling front." Upwelling fronts support enriched phytoplankton and zooplankton populations, thus they have great influences on ocean ecosystems. Traditional ship-based methods for detecting and sampling ocean fronts are often laborious and very difficult, and long-term tracking of such dynamic features is practically impossible. In our prior work, we developed a method of using an autonomous underwater vehicle (AUV) to autonomously detect an upwelling front and track the front's movement on a fixed latitude, and we applied the method in scientific experiments. In this paper, we present an extension of the method. Each time the AUV crosses and detects the front, the vehicle makes a turn at an oblique angle to recross the front, thus zigzagging through the front to map the frontal zone. The AUV's zigzag tracks alternate in northward and southward sweeps, so as to track the front as it moves over time. This way, the AUV maps and tracks the front in four dimensions-vertical, cross-front, along-front, and time.
An open-sourced computational tool for the design and analysis of optimized propellers and turbines is presented. The design tool, called OpenProp, is based on well-proven vortex lattice lifting line methods utilized by the US Navy as well as commercial designers. This paper presents the methodology and numerical implementation of OpenProp, with multiple examples of designs, including actual parts fabricated from the code using 3D printing technology.
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