Department of Ocean and Mechanical Engineering

This research presents findings from an in-situ experiment utilizing a hydrophone line array to capture the sound production of the Goliath grouper. Analysis revealed that Goliath grouper calls exhibit multiple frequency components, including one high-amplitude component and 2 to 3 low-amplitude components. The primary high-amplitude component is concentrated in the 30 to 70 Hz band, peaking around 50 Hz, while low-amplitude components span 20 to 30 Hz, 70 to 115 Hz, and 130 to 200 Hz. Comparison between in-situ data and results from a normal modes transmission loss model identified regions where echo level increased with propagation distance. This suggests that the loudness of the call may not necessarily indicate proximity, indicating the Goliath grouper might rely on other cues for localization, such as changes in the frequency profile of its call. Two methods for estimating call distance are presented. The first method vi utilized a transmission loss model and measured transmission loss across a hydrophone line array. This method could also determine the source level of the calls, yielding source level estimates ranging from 124.01 to 144.83 dB re 1 μPa. The second method employed match field filtering, validating the accuracy of the transmission loss model. Both methods produced similar call distance estimations, ranging from 11.5 to 17.1 meters, placing the grouper inside or near its typical habitat.

The feasibility and optimization of small unmanned mobile marine hydrokinetic (MHK) energy platforms for harvesting marine current energy in coastal and tidal waters are examined. A case study of a platform based on the use of a free-surface waterwheel (FSWW) mounted on an autonomous unmanned surface vehicle (USV) was conducted. Such platforms can serve as recharging stations for aerial drones (UAVs), enabling extension of the UAVs’ autonomous operating time. An unmanned MHK platform potentially meets this need with sustainable power harvested from water currents. For the case study, six different waterwheel configurations were field-tested in the Intracoastal Waterway of South Florida in support of determining the configuration that produced the most power. Required technologies for unmanned operations of the MHK platform were developed and tested. The data from the field-testing were analyzed to develop an empirical relation between the wheel’s theoretical hydrokinetic power produced and the mechanical power harnessed by the MHK platform with various waterwheel configurations during field-testing. The field data was also used to determine the electrical power generated by the FSWW configurations during field-testing. The study has led to the development of standardized testing procedures. The empirical relation is used to examine predicted power production through scaling up different physical aspects of the waterwheel.

Aquatic organisms are able to achieve swimming efficiencies that are much higher than any underwater vehicle that has been designed by humans. This is mainly due to the adaptive swimming patterns that they display in response to changes in their environment and their behaviors, i.e., hunting, fleeing, or foraging. In this work, we explore these adaptations from a hydrodynamics standpoint, using numerical simulations to emulate self-propelled artificial swimmers in various flow fields. Apart from still or uniform flow, the most likely flow field encountered by swimmers are those formed by the wakes of solid objects, such as roots of aquatic vegetation, or underwater structures. Therefore, a simplified bio-inspired design of porous structures consisting of nine cylinders was considered to identify arrangements that could produce wakes of varying velocities and enstrophy, which in turn might provide beneficial environments for underwater swimmers. These structures were analyzed using a combination of numerical simulations and experiments, and the underlying flow physics was examined using a variety of data-analysis techniques.
Subsequently, in order to recreate the adaptations of natural swimmers in different flow regimes, artificial swimmers were positioned in each of these different types of flow fields and then trained to optimize their movements to maximize swimming efficiency using deep reinforcement learning. These artificial swimmers utilize a sensory input system that allows them to detect the velocity field and pressure on the surface of their body, which is similar to the lateral line sensing system in biological fish. The results demonstrate that the information gleaned from the simplified lateral line system was sufficient for the swimmer to replicate naturally found behaviors such as K´arm´an gaiting. The phenomenon of schooling in underwater organisms is similarly thought to provide opportunities for swimmers to increase their energy efficiency, along with the other associated benefits. Thus, multiple swimmers were trained using multi-agent reinforcement learning to discover optimal swimming patterns at the group level as well as the individual level.

Malaria is an ancient lethargic disease that remains a global burden. It has been difficult to end the scourge of P. falciparum malaria because of the parasites’ drug resistance so early diagnosis of malaria is crucial. Microscopy remains the gold standard but has limited reliability in detecting malaria parasites. This study proffered a method towards detection of low parasitemia P. falciparum infected RBCs (Pf-RBCs) based on dielectrophoresis (DEP). A microfluidic device was designed for label-free cell sorting of Pf-RBCs from other whole blood in a continuous manner, based on the intrinsic electrical signatures of the cells. The design was validated by a finite element simulation using COMSOL Multiphysics. Simulations show the feasibility of the separation in a 9-mm long microfluidic channel under laminar flow conditions, using a low voltage supply of +/-10 V at 50 kHz.

Modeling, implementation, field testing and control of a power takeoff (PTO) device equipped with a ball-type continuously variable transmission (B-CVT) for a small marine hydrokinetic (MHK) turbine deployed from a floating unmanned autonomous mobile catamaran platform is described. The turbine is a partially submerged multi-blade undershot waterwheel (USWW). A validated numerical torque model for the MHK turbine has been derived and a speed controller has been developed, implemented and tested in the field. The dependance of the power generated as a function of number and submergence level of turbine blades has been investigated and the number of blades that maximizes power production is determined. Bench and field testing in support of characterizing the power conversion capabilities of MHK turbine and PTO are described. Detailed results of the final torque and power coefficient models, the controls architecture, and the MHK turbine performance with varying numbers of blades are provided.

The ctenophore Mnemiopsis leidyi is an opportunistic species that can be extremely abundant and invasive in many parts of the world. It is well known for its bright bioluminescence, but its light emission response to flow stimulation has not been rigorously quantified. The objective of this study is to determine the luminescent response of M. leidyi to several types of mechanical stimuli, an impeller pump with the Underwater Bioluminescence Assessment Tool (UBAT) bathyphotometer and stirring as the stimulus within an integrating sphere. Tests were conducted with three day old cydippid larvae, analyzing flash parameters of rise time, peak intensity, decay slope, decay time, total integrated emission, total mechanically stimulable luminescence (TMSL), integrated flash emission, and flash duration. There were four patterns of bioluminescent responses measured with the UBAT, but they did not have statistically different flash kinetics. For the integrating sphere, the average peak intensity and TMSL were much greater than for the UBAT due to the different forms of stimulation. This study provides a well-defined baseline of cydippid larvae flash responses which may be used for identifying this species at this life stage in situ.

Since 2010, aquaculture practices have produced 70% of global seafood consumption. However, this fast-growing sector of agriculture has yet to see the adoption of advanced technologies to improve farm operations. The Hybrid Aerial Underwater robotiCs System (HAUCS) is an Internet of Things (IoT) framework that aims to bring transformative changes to pond aquaculture.
This project focuses on the latest developments in the HAUCS mobile sensing platform and field deployment. A novel rigid Kirigami-based robotic extension subsystem was created to expand the functionality of the HAUCS platform. The primary objective of this design was to limit the surface area of an extender arm on the drone during flight operations and minimize the in-flight drag. By utilizing a novel combination of shape memory polymer (SMP) and nitinol to extend and retrieve the sensing arm, the structure was able to conserve energy while operating under varying environmental conditions.

Sickle Cell Disease (SCD) is a genetic disease that affects approximately 100,000 people in the USA and millions worldwide. The disease is defined by a mutation in hemoglobin, the red blood cell’s oxygen carrying component. Under hypoxic (low oxygen) conditions, the mutated hemoglobin (known as HbS) polymerizes into rigid fibers that stretch the cell into a sickle shape. These rigid cells can occlude blood vessels and cause an individual immense pain. Currently, no point-of-care devices exist in the market for assisting those with SCD. Using microfluidics with custom designed portable impedance measuring hardware we can achieve label-free in vitro analyses of SCD rheology.
This dissertation presents two impedance-based devices for finger-prick volume blood testing, including a microflow cytometer for SCD diagnostics and a vaso-occlusion tester for monitoring blood flow activities. First, the microflow cytometer is validated by measuring the electrical impedance of individual cells flowing through a narrow microfluidic channel. Cellular impedance is interpreted by changes in subcellular components due to oxygen association-dissociation of hemoglobin, using an equivalent circuit model and Multiphysics simulation. Impedance values of sickle cells exhibit remarkable deviations from normal blood cells. Such deviation is quantified by a conformity score, which allows for measurement of SCD heterogeneity, and potentially disease severity. Findings from this study demonstrate the potential for SCD screening via electrical impedance. Second, a vaso-occlusion tester is validated by measuring the impedance response of blood flow within a microfluidic mimic of capillary bed.

Boiling heat transfer associated with bubble growth is perhaps one of the most efficient cooling methodologies due to its sizeable latent heat during phase change. Despite significant advancement, numerous questions remain regarding the fundamentals of bubble growth mechanisms, a primary source of enhanced heat dissipation. This thesis provides a comprehensive examination of the mechanisms involved in the growth of bubbles during nucleate boiling. By conducting a combination of experiments and numerical analyses, the goal is to enhance our understanding of bubble growth phenomena and their impact on heat transfer. Initially, the experimental work focuses on comparing the heat transfer performance and parameters related to bubble dynamics between regular and modified fin structures. The findings demonstrate that the modified fin structure, which featured artificial nucleation sites, exhibits superior heat transfer characteristics. This improvement is attributed to changes in the bubble departure diameter, bubble departure frequency, and growth time. Subsequently, an artificial neural network is developed to accurately predict the bubble departure diameter based on the wall superheat and subcooling level. This predictive model provides valuable insights into bubble behavior originating from artificial nucleation sites.

In this thesis, we will explore different kinds of metamaterial or architectural structural problems, including structures composed of heterogeneous media with bi periodic sub-structures, discrete structures with sub-elements or continuous structures with discrete attached sub-elements. The thesis is composed of seven parts. After having introduced the specificities of metamaterial mechanics, the second chapter is devoted to the vibration of discrete beam problems called Hencky bar-chain model in a stochastic framework. It is shown that the lattice beam behaves as a nonlocal continuous beam problem, both in the deterministic and the non-deterministic analyses. The third chapter considers the vibration of continuous beams with the introduction of shear effects and attached periodically oscillators. A discussion on beam modelling, for example Timoshenko beam models or truncated Timoshenko beam models is included. It is shown that the bandgap phenomenon observed for metamaterial beams can be accurately captured by a truncated Timoshenko beam model which means the last term in the Timoshenko equation is not that important.