Engineering Commons^™

Numerical Study Of Nutrient Mixing In Trabecular Bone In Microgravity, Disuse And Normogravity, Sagar Gharti

Doctoral Dissertations and Master's Theses

Mechanical loading is known to regulate bone remodeling by driving interstitial fluid flow which stimulates cells and drives nutrient transport within the trabecular network. In microgravity, the absence of mechanical stimulation or loading suppresses convective flow processes, causing diffusion-driven nutrient mixing and renewal, and accelerated bone loss. This thesis investigates how oscillation frequency and trabecular bone density jointly control nutrient mixing and wall shear stress within trabecular cavities.

A computational fluid dynamics (CFD) framework is developed in STAR-CCM+ using a soft-cap oscillation model that mimics cyclic compression. Three idealized trabecular morphologies are simulated across different frequencies to represent microgravity or …

Instrumentation And Control Of A Novel Device To Simulate A Hypersonic Environment, Andrew Marcello

Doctoral Dissertations and Master's Theses

The hypersonic flow regime poses several challenges regarding the design of hypersonic vehicles. Among them is the massive energy and economic expense associated with ground- testing evaluation of material responses within this extreme environment. In order to provide a low-cost, rapid option for preliminary material analysis within hypersonic applications, a novel device is under production to replicate this environment on the surface of these materials. This device has been designed to work in conjunction with Argonne National Laboratory (ANL) Advanced Photo Source (APS) synchrotron, to allow for in-situ characterization of ablation and oxidation on the sample surface.

To achieve this, …

Numerical Investigation Of Rotor-Gust Acoustic Interactions Using The Overflow Cfd Solver, Jordan Mills

Doctoral Dissertations and Master's Theses

The rapid expansion of Urban Air Mobility (UAM) necessitates high-fidelity modeling to predict and mitigate the noise signatures of electric vertical take-off and landing (eVTOL) aircraft within dense urban landscapes. A critical unknown in community-noise certification is the aeroacoustic response of rotors to unsteady inflow conditions. This research addresses this gap by investigating the aerodynamic and acoustic behavior of a representative rotor subjected to time-harmonic inflow disturbances. By establishing a robust numerical framework, this thesis quantifies the relationship between periodic atmospheric gusts and their impact on rotor performance, unsteady blade loading, and subsequent sound radiation. The research consists of a …

Insect Inspired Behavioral Strategies For Improving Multi-Agent System Resilience In The Presence Of Contagious Faults, James E. Hand

Doctoral Dissertations and Master's Theses

As Multi-Agent Systems (MASs) become increasingly involved in every aspect of everyday life the need to maintain reliability and resilience within these systems grows. However, in equal measure bad actors wishing to maliciously control or alter these systems are growing in both scale and capability. Thus, there is a present need for control schemes and agent behaviors that provide security against these threats while also avoiding large degradation in system performance as a tradeoff. Current research has covered a wide breadth of avenues and strategies that provide measurable resilience to faulted agents. However, these strategies often require group consensus, specialized …

Ellie - Exteroceptive Light Locomotion In Eukaryote-Fungi, Brandon Etwarroo

Doctoral Dissertations and Master's Theses

Over the past decade, fungal research and its technological applications have expanded across multiple disciplines, including the emerging field of biohybrid systems. This thesis develops and evaluates a wireless, untethered mobile robot controlled by the action potential-like activity generated by Pleurotus ostreatus sporocarps under red, green, and blue optical stimulation. Light is applied to the sporocarps, the resulting electrical responses are recorded, and these signals are transmitted wirelessly to actuate the mobile robot. Both the action potential-like activity patterns and the robot’s movement trajectories were analyzed. The results demonstrate that wireless robotic control mediated by fungal electrophysiology is feasible. Overall, …

Effect Of Nozzle Pressure Ratio On Thrust And Flow Behavior In A Supersonic De Laval Nozzle, Esha Jain

Doctoral Dissertations and Master's Theses

Supersonic nozzles operate across a range of flow regimes. While an ideally expanded condition yields optimal thrust, practical propulsion systems rarely operate at this design point due to variations in altitude and engine operating conditions. As a result, nozzles frequently operate in off-design conditions. In overexpanded regime, where the exit pressure is lower than the ambient pressure, shock-induced separation may occur within the divergent section of the nozzle, potentially degrading nozzle performance. Understanding the aerodynamic behavior of nozzles operating under off-design conditions is therefore important for improving propulsion system performance and stability. In particular, direct thrust measurements provide a key …

Intelligent Flight Control Systems Using Adaptive Deep Neural Networks And Concurrent Learning-Based Design Methods, Maddox C. Morrison

Doctoral Dissertations and Master's Theses

This thesis investigates deep neural network (DNN)-based adaptive control strategies for unmanned aerial vehicles (UAVs) operating under aerodynamic uncertainty and complex actuator dynamics.

The first contribution presents a control strategy employing a concurrent learning (CL)-based DNN training algorithm, which combines online adaptive DNN weight adaptation with offline batch-like training updates using a recorded data stack. The analysis focuses on the closed-loop performance improvements resulting from the use of optimum CL data-selection algorithms, which ensure that the recorded data stack maintains sufficient data diversity to provide a statistically meaningful representation of the operating conditions using a reduced data set. Specifically, this …

Study Of Output And Behavior Of Llms Using Confidence Framing In Prompt Engineering, Micah Parrilla

Doctoral Dissertations and Master's Theses

While prompt engineering is pivotal for shaping Large Language Model (LLM) outputs, the impact of confidence framing on behavioral calibration remains underexplored. This study investigates the ways in which psychological framing, utilizing techniques such as capability praise, role amplification, and doubt induction, affects linguistic tone, objective accuracy, and internal calibration. A 1,080-trial experimental matrix evaluated six diverse models across factual, logical, coding, and cyber security domains. Analysis using the Kruskal-Wallis H-test revealed highly significant behavioral shifts across all measured dimensions, providing conclusive evidence that the applied frames exert a substantial influence on model performance.

The findings identify a distinct cognitive …

Guardrail Height Safety Requirements Given Recent Crash History And Evolution Of Vehicle Design, Delaney Morgan

Doctoral Dissertations and Master's Theses

Roadside barriers such as guardrails are fundamental to roadway safety, providing a critical last line of defense in preventing vehicles from leaving the roadway and impacting potential hazards. As vehicles are ever changing, it is necessary for guardrail design to adapt in response. Many contemporary vehicles such as sport utility vehicles and light trucks have higher centers of gravity than previous years, while electric vehicles have increased weight. Having sufficient guardrail height is essential to ensure proper engagement with vehicles to prevent loss of containment during impact.

The purpose of this study is to evaluate the performance of current Florida …

Safety-Aware Trajectory Generation For Increased Autonomy In Advanced Air Mobility, Edison Alberto Martinez Samaniego

Doctoral Dissertations and Master's Theses

Advanced Air Mobility (AAM) envisions highly automated aircraft that will enable short and medium range transportation. Unlike conventional aviation, these vehicles are expected to operate closer to populated areas and with increased levels of autonomy, making safe operation under abnormal or degraded conditions a critical requirement. Failures or performance degradation can reduce the maneuvering capability of an aircraft, causing trajectories planned under nominal conditions to become dynamically unfeasible.

This thesis presents a trajectory generation and replanning framework designed to maintain safe and feasible flight under reduced flight envelope conditions for a lift+cruise eVTOL aircraft. A unified control architecture based on …

Quantification Of The Depth-Of-Field In A Self-Aligned Focusing Schlieren System, Alexander Ephraim

Doctoral Dissertations and Master's Theses

This thesis investigates self-aligned focusing schlieren (SAFS) as a step toward future volumetric and quantitative measurements of three-dimensional compressible flows. Conventional schlieren imaging provides valuable visualization of density gradients, but it records only a line-of-sight projection and therefore does not directly resolve the spatial distribution of structures through the depth of the flowfield. SAFS addresses part of this limitation by introducing depth sensitivity, but its depth response has not been well characterized quantitatively. To help lay the foundation for future volumetric and quantitative SAFS methods, this work addresses two related problems. First, calibrated quantitative schlieren imaging is applied to an …

Adaptive Methods Of Resident Space Object Identification For Space Situational Awareness, Evan Pavetto-Stewart

Doctoral Dissertations and Master's Theses

One of the fundamental tenets of Space Situational Awareness (SSA) is the detection and sub sequent identification of Resident Space Objects (RSOs) within unresolved optical space imagery. This function is vital to the documentation and tracking of RSOs in their respective operational orbits, knowledge that is necessary for collision avoidance efforts and Space Domain Awareness (SDA) applications. In previous work, development was begun on a MATLAB program called RSOID to fulfill this purpose by accepting a collection (or ’collect’) of unresolved imagery and outputting a sequence of RSO locations (called a ’tracklet’) that can be used to determine the RSO’s …

Developing A Multi-Band Gnss Remote Sensing Station To Measure Precipitable Water Vapor For Flash Flood Nowcasting, Madison Gleydura

Doctoral Dissertations and Master's Theses

Flash flood nowcasting in Central and Southern Appalachia is particularly challenging due to steep terrain, narrow valleys, highly localized rainfall patterns, and limited measurement coverage. Traditional remote sensing methods, such as Doppler radar and microwave radiometry, suffer from reduced resolution at long range and signal blockage by mountains. GNSS-meteorology offers an established alternative for measuring precipitable water vapor and is currently integrated into several numerical weather models. Recent research demonstrates that commercial-grade GNSS receivers can produce tropospheric products comparable to those from geodetic-grade equipment. The gaps in mountain coverage can be addressed by developing a low-cost, self-contained embedded system that …

Evaluating Uav Visual-Inertial Odometry Trajectory Error And Feature-Level Metrics Over Repetitive Floor Patterns, Anass El Mekkoussi

Doctoral Dissertations and Master's Theses

Visual-Inertial Odometry (VIO) is a widely used state estimation technique for Uncrewed Aerial Vehicle (UAV) navigation in environments where Global Navigation Satellite System (GNSS) signals are unavailable. VIO systems that rely on visual feature tracking are susceptible to performance degradation when operating over surfaces containing repetitive visual textures, where visually similar features can produce ambiguous correspondences that introduce errors into the trajectory estimate. Despite the prevalence of repetitive textures in indoor UAV operating environments such as warehouses, manufacturing facilities, and infrastructure corridors, the specific impact of different repetitive pattern geometries on per-surface VIO accuracy has received limited systematic study, and …

Behavioral-Centric Team Evaluation Via Consistent Rewards, Clement Kudakwashe Nyanhongo

Dartmouth College Ph.D Dissertations

Across human domains ranging from sports to business and organizational settings, complex tasks are often solved by teams rather than individuals, leveraging benefits such as interaction, mutual support, complementary skills, cohesion, and task allocation. Evaluating team effectiveness, however, is inherently challenging due to the subjectivity of many existing techniques and the limitations of outcome-driven metrics that primarily focus on performance scores while overlooking the team processes that generated the scores. To address these challenges, this dissertation proposes a behavioral-centric, end-to-end framework for team evaluation grounded in reward functions that model sequential team behavior. Reward functions offer compact and interpretable representations …

Advancement And Characterization Of Next-Generation Solid-State Photon-Counting Image Sensors For Astrophysics Applications, Nicholas R. Shade

Dartmouth College Ph.D Dissertations

Astronomers’ pursuit of detecting light from increasingly faint and distant objects in the expanse of space necessitates continuous improvement in signal-to-noise ratio of camera technology. Recent advancements in solid-state detector technologies have enabled the determination of photon-number, including single photon events, enabling observations at the fundamental limits of physics. These developments are instrumental not only for standard two-dimensional imaging but also for advanced spectroscopy, which increasingly drives future astrophysical applications. This thesis presents an evaluation of three next-generation silicon-based detectors capable of photon-counting with deep-sub-electron input-referred read noise: the electron-multiplying charge-coupled device (EMCCD), the single-photon avalanche diode (SPAD), and the …

An Ultrafine-Resolution Numerical Investigation Of The Influence Of Terrain On Tornado Behavior, Jiamin Dang, Jana Houser, Leigh Orf, Peng Yue, Guirong Yan

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigates the effects of idealized and realistic terrain on tornado characteristics and behavior. It uses a novel simulation approach, nesting a high-fidelity, ultrafine-resolution, tornado-scale, engineering large-eddy simulation (LES) within a Cloud Model 1 (CM1) simulation of a tornadic supercell. We analyze the effects of terrain on the tornado's central pressure, horizontal and vertical velocities, vortex shape, and path. Seven idealized terrain configurations are used including 1) a control run with flat ground, 2) and 3) an idealized hill with steep and gradual slopes having the height of 25.4 m, 4) and 5) an idealized escarpment with steep and …

Tuning And Performance Of Pid Controlled Low Complexity Systems, Timothy Evans

Honors Theses

Proportional integral derivative (PID) controllers are used for precise position and orientation control in systems such as autonomous underwater vehicles (AUVs). This project supports the University of Southern Mississippi’s (USM) Robotics Club’s RoboSub AUV effort by developing, troubleshooting, and manually tuning PID controllers to characterize tracking performance and settling time across systems of increasing complexity. Initially, the project hypothesized that tracking performance would be reduced and settling times would increase as system complexity advanced from one degree-of-freedom (DOF) to two DOF. However, prior research was found that suggests that for small disturbances around an equilibrium state, separate PID-controlled DOFs can …

Research Days: Case Study: Creation Of A Student-Driven Radio Talk Show To Answer Cybersecurity Questions And Concerns To Boost Power Skills, Joel Leiva, Anthony Bayate, David Abiandu, Keith Fernandez

Center for Cybersecurity

Power skills are essential in any professional career. Oftentimes, college students don’t feel prepared enough to enter the workforce. Having good power skills in a group can greatly increase production and efficiency. This case study aims to develop these power skills in a group of college students through the creation of a student-driven radio talk show answering cybersecurity questions and concerns. A qualitative approach was used via the creation of the C.Y.B.E.R. radio show. This show enhanced the participants’ power skills such as collaboration, teamwork, and communication skills. The findings from this case study prove the alternate hypothesis of boosting …

Adopting Zero Trust Security In Cloud: A Comparative Study, Landy Jimenez

Center for Cybersecurity

Adopting Zero Trust Security in Cloud: A Comparative StudyLandy Jimenez, Dr. Jiaxin LeiDepartment of Computer Science & Technology, Kean UniversityAbstract:As organizations transition to cloud-native environments, ensuring security across distributed systems has become more difficult. Modern cyberthreats like insider breaches and lateral movement attacks have shown that traditional perimeter-based security strategies, which rely on implicit trust within internal networks, are inadequate. Zero Trust Architecture (ZTA) addresses these challenges by requiring continuous authentication, authorization, and encryption for every access request, regardless of network location. However, cloud native Zero Trust presents concerns about scalability, latency, and resource overhead.This study evaluates Zero Trust at …

The Impact Of Ai Ethics Education On Student Engagement And Ethical Perspectives, Diana Medina

Center for Cybersecurity

Artificial Intelligence (AI) has become a cornerstone of technological innovation. The world has come to see the many advancements AI has to offer and the impact it has on everyday life. The benefits of AI are promising, and institutions are learning how to implement AI to further advance productivity and efficiency. However, AI-based products may produce harmful or unjust consequences, especially when ethical considerations are not deliberated during the developmental stages. This study investigates student engagement and examines the impact in infusing ethical reasoning in AI education. With five participating computer science professors and two historians, ethics modules were introduced …

Stamp-V: Steganographic Traceability For ​ Ai-Generated Images With Multimodal Verification, Xinlei Guan, David Arosema, Tejaswi Dhandu, Meng Xu, Kuan Huang, Tida Umamheswara Rao, Bingya Shen

Center for Cybersecurity

The rapid growth of generative AI has intensified challenges in content moderation and digital forensics, particularly when benign AI-generated images are paired with harmful or misleading text. This contextual misuse undermines traditional moderation systems and complicates attribution, as synthetic images typically lack persistent metadata or device signatures. We introduce STAMP-V, a steganography-enabled provenance framework that embeds cryptographically signed identifiers into images at creation time and verifies provenance through multimodal harmful content detection. Our system evaluates five watermarking methods across spatial, frequency, and wavelet domains, and integrates a CLIP-based fusion model that performs multimodal harmful-content detection as part of the provenance …

Control And Stability Analysis Of Three-Phase Grid-Connected Inverters In Renewable Energy Systems, Yasser Ayeva

Electrical Engineering and Computer Science Faculty Publications and Presentations

The increase in demand for renewable energy sources such as solar and wind systems has led to widespread use and integration of a three-phase grid connected inverters in electric modern electric power systems. The inverters are essential to convert DC power into AC power and to control the delivered power to the grid. However, the use of the inverters in a renewable energy system has some challenges related to stability and control due to the presence of power electronic interfaces and filter dynamics. This paper analyzes the control and stability of three phase grid connected inverter through an LCL filter. …

Competitive Reaction Pathways In The Fully Green Synthesis And Surface Modification Of Silver Nanowires Under L-Ascorbic Acid-Limited Conditions, Finley Neal

Honors Theses

Silver nanowires (AgNWs) are critical building blocks for transparent conductive films (TCFs) in flexible electronics, yet their commercial viability is hindered by environmentally hazardous, energy-intensive synthesis methods and limited intrinsic chemical stability. This study investigated a fully green, room-temperature (25℃) batch synthesis of pristine AgNWs using tannic acid as a biodegradable dual reducing and capping agent under strict kinetic pH control (pH 1.25). To enhance oxidative resistance, a subsequent surface modification protocol was evaluated to deposit a protective palladium (Pd) shell using L-ascorbic acid (LAA) as a secondary reducing agent. The pristine green synthesis yielded one-dimensional Ag nanostructures with a …

Hybrid Deep Learning Model For Accurate Settlement Forecasting Of Metro Tracks Under Canal Diversion Engineering, Haijie He, Zhenlin Wang, Sifan Shen, Shiyu Sheng, Jing Zhang, Chuang He, Huafeng Shan, Qiongfang Zhang, Li Ai

Civil Engineering Faculty Publications

The structural stability of metro systems is essential for safe and reliable urban rail operation. Large-scale underground construction may influence existing metro lines, making accurate settlement prediction necessary. Traditional empirical and numerical methods often fail to capture long-term settlement behavior. This study predicts track bed settlement of Hangzhou Metro Line 1 using monitoring data collected during the Grand Canal diversion construction. A hybrid model (CEEMDAN-BWO-BiLSTM-ATT model) integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, Beluga Whale Optimization, Bidirectional Long Short-Term Memory, and an attention mechanism is developed. Results from four monitoring points along the up line show good performance, …

Intelligent Cost-Optimized Mix Design Prediction And Engineered Strength System For Geopolymer Concrete: A Machine Learning-Based Recommender System, Yuvaraj Natarajan, K.R. Sri Preethaa, V. Danushkumar, Syed Muhammad Oan Naqvi, M. Shyamala Devi, Karen Lozano, Bubryur Kim, Jinwoo An

Civil Engineering Faculty Publications

Geopolymer concrete is a promising low-carbon alternative to ordinary Portland cement concrete, but its practical use is limited by complex mix-design requirements and limited cost-aware decision-support tools. This study developed the Intelligent Cost-Optimized Mix Design Prediction and Engineered Strength System (iCOMPRESS), a machine learning-based recommender system that integrates 28-day compressive strength prediction, cost optimization, and compositionally diverse mixture recommendation. A database of 443 literature-derived mixtures was used to train a hyperparameter-optimized Random Forest model with domain-informed features related to binder chemistry, alkaline activation, water content, aggregates, and curing conditions. The model achieved a five-fold cross-validation mean absolute error (MAE) of …

A Software-Defined Radio Testbed For Mimo-Ofdm Communications, Chaz G. Maschman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we implement a testbed for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems via GNU Radio. Specifically, we implement a configurable framework for the construction of MIMO-OFDM software-defined radio (SDR) systems as a GNU Radio module. The GNU Radio MIMO-OFDM module consists of multiple algorithmic blocks necessary for implementation of a MIMO-OFDM system. This includes a library for the generation of orthogonal or pseudo-random pilot sequences, amendments to the Schmidl-Cox protocol for MIMO synchronization, and the creation of click-and-drag GNU Radio blocks implementing the conversion of arbitrary data sent via external programs to MIMO-OFDM frames, the initial …

X-Ray Tomography Of Damage Dynamics In Advanced Materials Using A Laser Wakefield Accelerator, Vigneshvar Senthilkumaran, Nicholas F. Beier, Sylvain Fourmaux, Peter Kenesei, Sean Dobson, Joël Maltais, Alvaro R. Arce-Borkent, Tait Richards, Michael G. Lipsett, Le Zhou, John A. Moore, Amina E. Hussein

Mechanical Engineering Faculty Research and Publications

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of …

Cure Sound Project: Study In Silence?, Quezia Abrao, Deeya Bhadresa, Elisa Castro, Fiona Coulbourne, Carlos Flores, Lizzeth Holguin, Lazarus Maldonado, Jeremy Mares, Andrew Martini, Nicole Matthews, Katherine Montero, Mariana Reyes, Jacob Rodriguez, Julieta Ruiz, Eliana Sanchez, Gabriela Varela

Posters - 2026

Difference in sound levels in study areas across campus can affect students’ ability to work and learn efficiently 1.

According to the WHO, safe sound levels are measured to be around 70dB 2. Some study areas on campus experience sound levels exceeding the safe threshold. Unsafe sound levels are considered to be at or above 85dB 3. These unsafe and excessive noise levels negatively affect a student’s ability to concentrate and work efficiently which correlates to a decrease in class performance, attention deficits, and stress 4.

This study aims to get a base-line measurement of dB levels in common study …

Using Ai To Predict Energy Expenditure In Lower Limb Prosthesis Users, Nelly Diaz, Siem Hadish

Posters - 2026

• Computer vision has evolved from simple image classification and object detection to analyzing human motion and biomechanics (1). • CNN’s are usually focused on image classification, but, in this case, we are not asking the model if a person is walking. • Many real-world problems require regression: Predicting a continuous number like energy expenditure of walking is a complex task. • It is essential for Prosthetists to understand energy expenditure of their prosthetic patients (2). • An amputee may use 20-30% more energy to walk. • In this project, we developed an AI model to analyze human motion and …