Acoustics, Dynamics, and Controls Commons^™

Effect Of Kelvin Seamount On Acoustic Propagation, Lindsey Moss

Open Access Master's Theses

This thesis contains CUI. It cannot be distributed, exported, uploaded, or published until it has gone through the proper public release process.

Characterization And Control Of Rod-Like Soft Robots, Tianrui Li

Mechanical Engineering Research Theses and Dissertations

Micro-scale robotic systems have garnered significant interest for applications in micromanufacturing and biosensing, yet quantitative design rules linking geometry, stiffness distribution, and magnetic actuation to locomotion performance at low Reynolds number remain limited. This thesis investigates magnetically actuated rod-like soft robots composed of hydrogel filaments with embedded micro-magnets and tunable hard:soft length ratios. Four- and eight-magnet swimmers with hard:soft ratios ranging from 1:1 to 2.5:1 and 4:3:1 are fabricated using a simple molding-and-insertion process and tested in water and silicone oil. A triaxial Helmholtz coil system generates rotating magnetic fields from 1 to 10 Hz, and a custom image-processing pipeline …

Stability Analysis Of Thermohaline Convection With A Time-Varying Shear Flow Using The Lyapunov Method, Kalin Kochnev

Honors Scholar Theses

This work applies the Lyapunov method to identify instabilities and compute the growth rate of a linear time-varying system. The linear system studied describes cold fresh water on top of hot salty water with a periodically time-varying background shear flow. A time-dependent weighting matrix is employed to construct a Lyapunov function candidate. The resulting linear matrix inequalities are discretized in time using the forward Euler method. As the number of temporal discretization points increases, the growth rate predicted by the Lyapunov method or Floquet theory, used for comparison, will converge to the same value obtained from numerical simulations. Furthermore, the …

Machine Learning-Enabled Safety-Critical Model Predictive Control For Uncertain Dynamical Systems, Hossein Nejatbakhsh Esfahani

All Dissertations

This dissertation explores the interactions between Model Predictive Control (MPC), Safety-critical Control, and Artificial Intelligence (AI)/Machine Learning (ML) methods, with a particular focus on Reinforcement Learning (RL) and Bayesian Optimization (BO). We then leverage AI/ML to address several challenges in the control design and safe operation of uncertain dynamical systems. In many applications, ranging from autonomous vehicles and robotics to energy systems and industrial processes, ensuring safety is as essential as satisfying control objectives. The use of Control Barrier Functions (CBFs) within the MPC framework recently has emerged as a powerful tool to guarantee safety by enforcing constraints in optimal …

Robust Data-Driven Predictive Control Of Nonlinear Systems Under Modeling Uncertainty, Pegah Ghafghanbari

All Dissertations

Data-driven predictive control enables designing controllers directly from data, making it attractive for complex systems with hard-to-model dynamics. However, practical deployment is challenged by modeling inaccuracies and changing operating conditions. This dissertation develops predictive control frameworks that incorporate robustness and adaptability to address these issues in uncertain nonlinear systems.

The first part employs the Linear Parameter-Varying (LPV) framework, which represents nonlinear dynamics through simple linear form representation. To characterize the plant-model-mismatch often caused by limited data and numerical calculations, Bayesian Neural Networks (BNNs) are used, and their uncertainty estimates are integrated into two robust control approaches. The first is a …

Real Time Markerless 3d Hand Tracking For Intuitive Robotic Arm Control, Dylan G. Featherson

Master's Theses

This thesis presents a real-time, markerless motion-capture system for intuitive control of a multi-degree-of-freedom robotic arm. Using two synchronized RGB cameras and stereo-vision triangulation, the system reconstructs the three-dimensional position of a user’s hand without the need for physical markers or wearable sensors. The reconstructed 3D coordinates are mapped directly to the end-effector position of the Quanser QArm, a four-degree-of-freedom educational manipulator. Developed entirely in Python, the system integrates stereo camera calibration, 3D hand tracking with MediaPipe, coordinate transformation, and inverse kinematics into a unified real-time control pipeline operating at approximately 200 Hz. Calibration is performed through a checkerboard-based stereo …

Origami-Inspired Pneumatic Soft Robotic Gripper, Conor J. Schott

Master's Theses

This thesis presents the design and evaluation of a vacuum-actuated, origami-based soft robotic gripper. A custom Sea Urchin crease pattern forms a lightweight folding skeleton that collapses radially under vacuum. The system emphasizes low cost and accessibility through laser cutting, 3D printing, and silicone molding. The Sea Urchin geometry was selected after digital and physical screening of candidate crease patterns for smooth folding, low strain concentration, and uniform inward motion. The folding skeleton is laser cut from 4 mil drafting film and folded into a compliant core. Four membrane configurations were developed: an origami gripper with a 36-inch balloon (Design …

Investigation Of Laser Based Flow Diagnostics With Metastable Argon, Sterling S. Gordon

Physics Theses & Dissertations

The overarching motivation of this work is the development of seedless, non-intrusive, laser-based diagnostics for supersonic airflow in wind tunnels. To advance this goal, this dissertation fo-cuses on three-photon excitation in a research-grade argon beam within a tabletop vacuum system, which offers a controlled environment for testing and refining the approach. The chosen excitation scheme drives argon atoms to the 3d[5/2]₃ state using a pulsed Ti:Sapphire laser system, enabling time-of-flight (ToF) measurements on atoms that subsequently undergo a multi-step decay to the metastable 4s[3/2]₂ state. Although full realization of this excitation scheme was hindered by technical …

A Polar Turbulence Invariant Map With Applicability To Realisable Machine Learning Turbulence Models, James G. Wnek, Christopher Schrock, Eric M. Wolf, Mitch Wolff

Mechanical and Materials Engineering Faculty Publications

Invariant maps are a useful tool for turbulence modelling, and the rapid growth of machine learning-based turbulence modelling research has led to renewed interest in them. They allow different turbulent states to be visualised in an interpretable manner and provide a mathematical framework to analyse or enforce realisability. Current invariant maps, however, are limited in machine learning models by the need for costly coordinate transformations and eigendecomposition at each point in the flow field. This paper introduces a new polar invariant map based on an angle that parametrises the relationship of the principal anisotropic stresses, and a scalar that describes …

Decision Field Theory For Human-Multi-Robot Collaboration: Human-Centric Decision-Making For Multi-Robot Systems, Ryan Mbagna Nanko

All Theses

At first glance, choosing between an apple and an orange appears to be a straightforward matter of personal taste; however, this seemingly simple preference opens a window into the multifaceted world of decision-making, revealing the complex interplay of cognitive processes, psychological, and behavioral-economic principles that guide our choices \cite{bandyopadhyayRoleAffectDecision2013}. By unpacking these nuanced perspectives, we uncover insights that can drive more effective human-robot interaction and collaboration.

Modeling human cognition requires understanding the evolution of choice utility and the influence of emotions. Decision Field Theory (DFT) stands out by capturing the fluctuating nature in human preferences over time, explaining why choices …

Networked Systems: Synchronization, Decomposition And Transient Dynamics, Amirhossein Nazerian

Mechanical Engineering ETDs

This dissertation investigates synchronization, transient dynamics, control, and signal amplification in networked dynamical systems. First, it examines complete and cluster synchronization, including cases with large parametric mismatches, in both natural (e.g., brain networks, fireflies) and technological systems (e.g., power grids, robotics). Second, it studies transient dynamics in consensus processes, designing synchronization strategies that link reactivity, contraction theory, and Lyapunov exponents. Third, it addresses the computational limits of Model Predictive Control (MPC) for large networks by introducing an algebraic decomposition method that enables parallel online computation of smaller subproblems, enhancing MPC performance under hardware constraints. Finally, it analyzes the structural role …

The Design And Effect Of Continuum Robot Compliance On Locomotion, Parsa Molaei

LSU Doctoral Dissertations

Continuum robots, due to their compliant structures and ability to navigate through constrained environments, offer significant advantages in applications requiring safe physical interaction and dexterous motion. However, challenges related to limited structural stiffness, payload capacity, and precise control remain open problems in the field. This dissertation presents novel contributions aimed at addressing these limitations through two main actuation units of continuum robots: tendon-driven continuum robots (TDCRs) and concentric tube robots (CTRs). In the first part, we focus on methods to improve the stability and modify the stiffness of the TDCR. A tendon decoupling strategy is introduced for planar TDCRs. The …

Data-Driven Constrained Control, Ali Kashani

Mechanical Engineering ETDs

Ensuring safety is a fundamental challenge. Traditional methods often rely on precise mathematical models, which are difficult, impractical, or costly to obtain for real-world systems with complex, nonlinear dynamics. This dissertation develops direct data-driven control approaches that enable safe and efficient operation of nonlinear systems without requiring explicit models or performing system identification. This effort leverages machine learning, optimization, and control theory to bridge theoretical rigor and practical applicability. Deterministic guarantees are provided based on the Lipschitz continuity of the system, and probabilistic guarantees through scenario optimization. The computation of safe sets is performed using one-shot approaches with broad neural …

An Engineering Solution For Fan Aeroacoustics Measurements Correction In A Non-Anechoic Testing Environment, Saad-Eldin Taha, Mohamed Y.Zakaria, Mohamed Abdelgaied, M.M. Bassuoni Prof. Dr.

Journal of Engineering Research

Abstract- Nowadays, acoustic signatures of daily used applications are to be minimized. The study of noise generated through aerodynamic interaction with moving bodies has passed through different phases since the early 50s, and this leads to the evolvement of many analytical, empirical and computational techniques in order to be able to estimate the emitted noise. Concerning fan blades, until now the researches are still going for a reliable method for noise estimation during the early phases of design which help in the development of blades with a lower aeroacoustic signature, the Brooks, Pope and Marcolini (BPM) model was chosen to …

In-Situ Defect Detection In Selective Laser Melting Using Convolutional Neural Networks, Ethan Gaigalas

Master's Theses

This thesis develops and trains a convolutional neural network (CNN) to classify defects in metal parts produced by selective laser melting (SLM) using acoustic emission (AE) data. The model successfully identified porosity and standard build layers with high accuracy but consistently struggled to classify lack of fusion (LOF) defects, regardless of input type, normalization, or class count. These results suggest that while AE signals contain distinguishable features for certain defect types, LOF signals may be too subtle or inconsistent for reliable detection. The study addresses the ongoing challenge of in-situ quality monitoring in metal additive manufacturing, where defects like cracks, …

Torsional Vibration Kit Simulator (Tks), Joseph Thachet, Luca Lawson, Ryan Ota, Otis Mcloughlin

Mechanical Engineering

The goal of this project was to create torsional vibration on a shaft while limiting axial and radial vibration. To do this an eddy current brake was used to slow down a rotating shaft. The electromagnets used to create the eddy currents are able to be turned on and off at a frequency produced by a function generator. This power cycling of the electromagnets creates an alternating braking force thereby inducing torsional vibration while limiting the other two vibration types

Brush Seal Cycling Test Rig, Angelo J. Reis, Neil M. Bedagkar, Max A. Soury, Eoin K. Lenham

Mechanical Engineering

To prevent backflow from the high pressure compressor stages of their gas turbines to lower pressure regions, Solar Turbines utilizes brush seals along their driveshafts. Due to manufacturing limitations, no shaft is perfectly symmetric about its rotating axis, leading to orbiting that creates asymmetric friction on the shaft through rubbing. With this biased application of friction comes a hotspot on one side of the shaft, causing bowing of the shaft and cascading into an amplified vibrational response. Our goal is to gather data on this phenomenon and offer a potential solution.

Hydropower Collegiate Competition, Aiden D. Foster, Devon Bountry, Joanna Vo, Timothy Rinker, Amanda Rodriguez, Minh Nguyen, Eli Haushalter, Sophie Watkinson, Maiya Holton, Breanne Evans

Mechanical Engineering

The Cal Poly SLO HCC team presents a feasibility study and engineering design review package for retrofitting the non-powered Ritschard Dam in Colorado into a hydroelectric facility as part of the 2025 Hydropower Collegiate Competition. Through a rigorous and multi-staged assessment of plausible dam sites in the western US, the team has chosen the Ritschard Dam in Colorado to implement an electromechanical component designed to accommodate a large range of flowrates stemming from a large variance in upper reservoir capacity due to geographical and climate effects. The team evaluated non-powered dams based on technical feasibility, electric grid proximity, power generation …

Conversational Social Robot, Julianna M. Christopoulos, Mackenzie Goldman, Cece E. Hujanen, Jared Hunter

Mechanical Engineering

Background: Social robots are used in various settings to reduce burden on human workers and expand opportunities for people in need of assistance.

Challenge: Design a humanoid robot head and torso capable of holding conversations and interacting with a user using a LLM and motion. Conversations are limited to discussing Cal Poly resources and opportunities with visitors to the Bently Research Center on campus.

Pendulum Wave Generator, Abigail Jocelyn Romero, Paul Staley, Wendy Dong, Kyle Schumacher

Mechanical Engineering

The Cal Poly Mechanical Vibrations Laboratory (Vibes Lab) serves to educate and excite students about mechanical vibrations through hands-on experiments. While the lab contains several relatively complicated technical experiments, it lacks simple demonstrations with immediate visual interest to appeal to audiences with less technical backgrounds. Because of this, faculty desired a fun and interactive demonstration project that could be operated with no prior training. The project chosen for this is a Pendulum Wave Generator which is a set of multiple pendulums with differing lengths that combine to create complex and observable patterns over time. This project was completed by a …