Department of Ocean and Mechanical Engineering

This thesis investigates geomagnetic survey methodology in support of the development of a geophysical navigation system for an Autonomous Underwater Vehicle (AUV). Traditional AUV navigation methods are susceptible to cumulative errors and often rely on external infrastructure, limiting their effectiveness in complex underwater environments. This research leverages geomagnetic field anomalies as an additional navigational reference to these traditional systems, particularly in the absence of Global Positioning System (GPS) and acoustics navigation systems. Geomagnetic surveys were conducted over known shipwreck sites off the coast of Fort Lauderdale, Florida, to validate the system's ability to detect and map magnetic anomalies. Data from these surveys were processed to develop high-resolution geomagnetic contour maps, which were then analyzed for accuracy, reliability, and modeling in identifying geomagnetic features.

Due to technological advancement, energy consumption and demand have been increasing significantly, primarily satisfied by fossil fuel utilization. The dependence on fossil fuels results in substantial greenhouse gas emissions, with CO₂ being the principal factor in global warming. Carbon capture technologies are employed to mitigate the escalated CO₂ emissions into the atmosphere. Among various carbon capture methods, amine scrubbing is widely utilized because of its high CO2 capture efficiency and ease of adaptability to the existing power plants. This method, however, presents drawbacks, including increased toxicity, corrosiveness, and substantial freshwater use. To overcome these shortcomings and simultaneously develop an environmentally sustainable carbon capture solution, this study aims to evaluate the CO2 capture performance of seawater associated with polyvinylpyrrolidone (PVP) polymer-coated nickel nanoparticles (NiNPs) catalysts. Using high-speed bubble-based microfluidics, we investigated time-dependent size variations of CO2 bubbles in a flow-focusing microchannel, which is directly related to transient CO₂ dissolution into the surrounding solution. We hypothesize that the higher surface-to-volume ratio of polymer-coated NiNPs could provide a higher CO2 capture rate and solubility under the same environmental conditions. To test this hypothesis and to find the maximum performance of carbon capture, we synthesized polymer-coated NiNPs with different sizes of 5 nm, 10 nm, and 20 nm. The results showed that 5 nm polymer-coated NiNPs attained a CO₂ dissolution rate of 77% while it is 71% and 43% at 10 nm and 20 nm NPs, respectively. This indicates that our hypothesis is proven to be valid, suggesting that the smaller NPs catalyze CO2 capture effectively with using the same amount of material, which could be a game changer for future CO2 reduction technologies. This unique strategy promotes the future improvement of NiNPs as catalysts for CO2 capture from saltwater.

Living organisms synthesize and assemble complex bioinorganic composites with enhanced structure and properties to fulfill needs such as structural support and enhanced mechanical function. With the advent of advanced materials characterization techniques, these biomineral systems can be explored with high resolution to glean information on their composition, ultrastructure, assembly, and biomechanics. In this work, the endoskeletal features of two marine organisms are explored.
Acantharia are geographically widespread marine planktonic single-celled organisms. Their star-shaped SrSO4 endoskeleton consists of spicules emanating from a central junction, arranged to satisfy crystallochemical and spatial requirements of their orthorhombic crystal lattice. In this work, synchrotron X-ray nanotomography and deep-learning guided image segmentation methods were used to characterize the endoskeleton of 5 types of Acantharia and to extrapolate their growth mechanism. The results highlight the diverse morphology of the spicules and spicular junctions that Acantharia achieve whilst maintaining overall spatial arrangement. Fine structural features, such as interspicular interstices thought to play a role in the robustness of the overall endoskeleton, were resolved.

Over the past decade, hydrogen gas generation has been a critical component toward clean energy due to its high specific energy content. Generating hydrogen gas from water is crucial for future applications, including space transportation. Recent studies show promising results using silicon nanoparticles (SiNPs) for spontaneous hydrogen generation, but most methods require external energy like high temperature or pressure. In this work, we investigated hydrogen production from SiNPs without external energy by leveraging high pH water using sodium hydroxide and optimizing the process with a microfluidic approach. When comparing the physical dispersion methods using the 0.1 mg/mL case, ultrasonic bath produced more hydrogen than magnetic stirrer. In this thesis, 0.01% dextran with pure SiNPs at concentrations of 0.1 mg/mL, 0.2 mg/mL, and 0.3 mg/mL was analyzed. The highest concentration with dextran generated at least 40% less hydrogen than silicon alone, thus dextran did not increase hydrogen gas.

The study of non-invasive techniques to analyze the propagation of corrosion in steel reinforced concrete structures proves to be a great alternative to better understanding the corrosive process of rebar and increasing its useful life. The study presented in this document examines the evolution of steel reinforced concrete corrosion over time by applying a small anodic current over four samples, one with a single rebar (16X) and three with three rebars. The rebars were interconnected to apply the anodic current and accelerate their corrosion. Galvanostatic Pulse (GP) was used. This method applies a constant current pulse to the rebar for 150 seconds while monitoring the potential of the rebars. Each rebar's corrosion current was assessed using GP measurements when no anodic current was applied, and the rebars were disconnected. Sample 16X additionally underwent ultrasonic acoustic analysis by collecting the surface and rebar echo response with a transducer and modeling the sound propagation for poroelastic media with an adapted version of the novel Biot-Stoll method.

Due to technological advancement, energy consumption and demand have been increasing significantly, primarily satisfied by fossil fuel consumption. This reliance on fossil fuels results in substantial greenhouse gas emissions, with CO₂ being the most prominent contributor to global warming. To mitigate this issue and prevent CO₂ emissions, Carbon Capture, Utilization, and Storage (CCUS) technologies are employed. Among these, the amine scrubbing method is widely used due to its high CO2 capture efficiency and regenerative ability. However, this method has drawbacks, including high toxicity, corrosion, and substantial freshwater consumption.
To develop an environmentally sustainable carbon capture solution, researchers are exploring alternatives such as the use of seawater and enhanced CO2 capture with catalysts. In this study, we analyze the catalytic performance of nickel nanoparticles (NiNPs) in seawater with carboxymethyl cellulose (CMC) polymers. Using flow-focusing geometry-based microfluidic channels, we investigated CO₂ dissolution at various concentrations of nanoparticles and CMC polymers. The objective is to optimize the concentration of nanoparticles and CMC polymers for effective CO₂ dissolution. We utilized NiNPs with diameters of 100 nm and 300 nm in CMC concentrations of 100 ml/L, 200 ml/L, and 300 ml/L. Additionally, NiNP concentrations ranging from 6 mg/L to 150 mg/L were tested for CO₂ dissolution in seawater. The results indicated that a concentration of 10 mg/L NiNPs in 100 mg/L CMC provided a CO₂ dissolution of 57%, the highest for this specific CMC concentration. At CMC concentrations of 200 ml/L and 300 ml/L, NiNP concentrations of 70 mg/L and 90 mg/L achieved CO₂ dissolution rates of 58.8% and 67.2%, respectively.

The capability to navigate in the proximity of solid surfaces while avoiding collision and maintaining high efficiency is essential for the effective design and operation of underwater vehicles. The underlying capability involves a variety of challenges, and a potential approach to overcome such obstacles is to rely on biomimetic or bio-inspired design. Through evolution, organisms have developed methods of locomotion optimized for their specific environment. One of the common forms of locomotion found in underwater organisms is undulatory swimming. These undulatory swimmers display different swimming behaviors based on the flow conditions in their environment. These behaviors take advantage of changes in the flow field caused by the presence of obstructions and obstacles upstream or adjacent to the swimmer. For example, a free swimmer in near-proximity to a flat plane can experience changes in lift and drag during locomotion. The reduced drag can benefit the swimmer, however, changes in lift may lead to a collision with obstacles. Despite the abundance of qualitative data from observing these undulatory swimmers, there is a lack of quantitative data, creating a disconnect in understanding how these organisms have evolved to exploit the presence of walls and obstacles. By employing a combination of traditional computational fluid dynamics and novel neural network-based techniques it is possible to emulate the evolution of learned behavior in biological organisms. The current work uses deep reinforcement learning coupled with two-dimensional numerical simulations of self-propelled swimmers to better understand behavior observed in nature.

This research focuses on deformation constraints of honeycomb core cells in a sandwich imposed by bonds to the face sheets. Specifically, the influence of one-sided core constraints on the bending stiffness of a single-face honeycomb core sandwich is examined. To characterize the unconstrained in-plane compressive response of honeycomb core, a range of honeycomb cores was experimentally examined. Cores with a thin cell wall displayed extensive bending deformation of inclined cell walls while cores with thicker walls failed by a shear-type instability of the cells indicated by tilting of vertical cell wall segments. The modulus and compressive strength of the core were compared to the predictions from unit cell models. The results show that geometrical imperfections such as deviation from the intended cell wall angle cause in-plane anisotropy and have strong influence on modulus and strength of the core. Modulus and strength were in reasonable agreement with predictions from unit cell models for cell wall modulus and strength between 5-12 GPa and 72-171 MPa for the set of cores examined.

The Design and Development of a remote attitude-measuring sensor package (RASP) for use onboard an underwater tow fish to analyze its dynamic movement while towing is described. The RASP will be used to determine the orientation, acceleration, and gyroscopic attitude of the tow fish. The collection of this data is important for understanding the trim of the tow fish under different towing conditions behind a manned surface vessel or unmanned underwater vehicle. The trim data acquired will inform the extent to which post-processing of collected three-axis electromagnetic field data would be required. The RASP has been analyzed in the laboratory with a mechanical testing rig that was designed and built to validate the accuracy and performance of the entire sensor package system. The developed package will aid in the assessment of the performance of the tow fish in field operations with the sensor package implemented on the tow fish.

Background Structure Functions (BSFs) are wavefront distortion metrics, functions of Sound Speed Profiles (SSPs) that are functions of depth. Use of these BSFs is a synthesis form of Matched Field Processing (MFP) that detects signals that are otherwise lost to receivers. Underwater Acoustics (UWA) can use these models to forecast communication and imaging performance and to reduce power radiated into the sea. This reduction of Transmission Loss (TL) occurs because the commercial wavefront control has an input format that accepts BSFs. The BSF plots represent the purely statistical distortion for communications and remote sensing. Another source of TL reduction comes from the enclosed BSF-based phase and phase variance forecasting that protects equalizers from losing phase-lock. Protecting the equalizers protects the Signal To Noise (SNR) ratios. This dissertation derives the UWA version of these metrics and applies them to the following locations of our SSPs: The BSFs use measured, corrected, and verified SSP groups for 132 different locations in the Atlantic Ocean and the Gulf of Mexico from a Navy Ocean Atlas, as well as 64 SSPs in two areas in the littorals, Port Everglades, and Saint Andrew Bay, plus tidal variations. Since BSFs digitize the propagation into one or more segments, our purely statistical phase screen model uses only 3 or 4 degrees of freedom (DOFs) per segment compared to many dozen DOFs for conventional structure functions. The BSFs forecast communications and imaging performance, including range, in locations where acoustic measurements are not available, but SSPs are. A separate algorithm forecasts Gouy phase anomalies from background SSPs, which otherwise requires a priori knowledge of anomaly location and use of Catastrophe theory due to ray theory failure at focuses. Avoiding these anomalies and loss of Phase-Locked Loops (PLLs) also helps maintain SNR and lowers transmission power requirements. Combining with phase parameters and performance forecasts improves UWA propagation efficiency using the background (SSPs). In a spatial version of delay equalization, BSF analysis also produces the enclosed Shear Distortion Ratios (SDRs) for the same locations mentioned above, to allow optimum selection of image enhancement algorithms that mitigate image shear distortion.