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Articles 1 - 30 of 1035
Full-Text Articles in Aerospace Engineering
Modeling Of Supersonic Wave And Shock Propagation Using The Lattice Boltzmann Method, Timothy P. Schroeder
Modeling Of Supersonic Wave And Shock Propagation Using The Lattice Boltzmann Method, Timothy P. Schroeder
Beyond: Undergraduate Research Journal
The lattice Boltzmann method (LBM) has emerged as a mesoscopic alternative to traditional Navier-Stokes solvers for modeling fluid dynamics offering advantages in computational efficiency, parallelization, and handling of complex boundaries. Despite these strengths, accurately reproducing compressible, shock-driven phenomena remains challenging. This study investigates the performance of LBM in simulating the Sod shock tube problem, a classical benchmark for compressible flow-using both single and double distribution function formulations across one- and two-dimensional lattice stencils. A MATLAB-based solver was developed to model the flow under isothermal conditions and compared to the analytical solution using the L2 norm error. The one-dimensional models achieved …
High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin
High-Level Trajectory Learning For Non-Prehensile Object Manipulation With Hierarchical Reinforcement Learning, Gulsum Tuba Cibuk Girgin
Discovery Day - Daytona Beach
Site exploration requires in-situ resource utilization when the physical properties of resources are unknown. Therefore, a generalizable object manipulation method is crucial for extraterrestrial environments. Existing studies develop reinforcement learning policies that enable interaction with objects, in which quadruped robots learn to reach commanded goals with one foot while balancing with the remaining legs. However, in these studies, goal-oriented task execution relies on high-level trajectories provided by human experts, which limits autonomous robotic operations. In this study, we propose a hierarchical DRL in which a high-level pedipulation policy outputs commands for a low-level reach policy, enabling autonomous, smooth and affordable …
Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez
Vibration And Thermal-Vacuum Feasibility For Micro Carbon Fiber Filled Nylon Filament Lunar Applications, Andrew Murphy, Shannon O'Sullivan, Daniel Lopez
Discovery Day - Daytona Beach
The proposed work seeks to improve the fundamental understanding of the properties concerning 3-D printing filaments that have potential to be used for lunar applications. The associated properties in focus for the proposed study, vibration and thermal-vacuum-resistance, are fundamental aspects of spaceflight and are critical to mission success for objectives associated with the environmental factors in space. The successful outcome of the proposed work will answer questions relating to the feasibility of micro carbon fiber filled nylon 3-D printing filaments such as Markforged’s Onyx® for application for projects in the Space Technologies Laboratory, including for the development of structures relating …
Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy
Advancements In Spacecraft Trajectory Generation Through Matrix Decomposition Techniques, David Stoev, Oshani Jayawardane, Kaitlyn Cavanaugh, Kristiyan Stefanov, Andrew Murphy
Discovery Day - Daytona Beach
The Circular Restricted Three-Body Problem (CR3BP) is renowned for its intricate and chaotic dynamics, leaving it without a closed-form solution. In this poster, we introduce an innovative approach to determine spacecraft trajectories within the CR3BP framework using matrix factorization techniques. We formulate a matrix equation where the right-hand side vector is constructed from the spacecraft's position and velocity data, while the coefficient matrix is derived from the spacecraft's temporal data. Subsequently, we apply several matrix decomposition techniques, including modified Gram-Schmidt, the Householder technique, and Givens Rotation, to analyze the coefficient matrix and derive the spacecraft trajectories. Finally, we evaluate the …
Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter
Lightweight Uav-To-Uav Detection And Tracking For Advanced Air Mobility Applications, Taylor Hostetter
Discovery Day - Daytona Beach
Lightweight UAV-to-UAV Detection and Tracking for Advanced Air Mobility Applications addresses the significant challenge of reliable UAV-to-UAV detection on resource-constrained platforms, particularly within Advanced Air Mobility (AAM) environments where dense, low-altitude airspace requires robust detect-and-avoid capabilities. This work presents the development and experimental evaluation of a lightweight detection and tracking framework for autonomous detect-and-avoid applications. The approach is designed to support real-time onboard operation in multi-vehicle environments characteristic of emerging AAM systems. The proposed framework integrates optical and LiDAR sensing with a low-complexity machine learning decision-support layer that reduces false detections without replacing the underlying control-oriented detection pipeline. This design …
Eliminating Range Constraints For Optical Tracking Of Sub-10 Cm Orbital Debris, James Kirk
Eliminating Range Constraints For Optical Tracking Of Sub-10 Cm Orbital Debris, James Kirk
Discovery Day - Daytona Beach
The growing population of orbital debris, including a significant amount of debris ranging from 1 to 10 cm, has substantially increased the risk to satellites. Due to the sheer number and high velocities, debris ranging from 1 to 10 cm still has the ability to cause mission-ending damage while remaining undetectable by ground-based detection facilities. This study utilizes the NASA Standard Satellite Breakup Model (NASA SSBM), combined with MATLAB, to propagate debris clouds over extended durations, enabling the identification of high-detection zones and debris rings. Using the modeled spacecraft environment, a satellite was positioned below the debris ring altitudes. Lowering …
Low-Complexity Polynomial Ring Learning For Quantum Space Assets, Lola Torres
Low-Complexity Polynomial Ring Learning For Quantum Space Assets, Lola Torres
Discovery Day - Daytona Beach
Secure communication for space-based systems requires cryptographic methods that remain both reliable and efficient under strict computational constraints. This work investigates a low-complexity polynomial ring learning algorithm designed for quantum space assets, including satellite–ground communication systems. The project focuses on post-quantum cryptographic principles, where encryption and decryption rely heavily on repeated polynomial operations; this can be computationally expensive with constrained platforms. This is addressed with reformulating polynomial multiplication as a structured linear transformation on coefficient vectors. By representing these operations as matrices with a cyclic structure, the structure allows the use of the discrete Fourier transform (DFT); this will simplify …
M.O.D.U.S. Modular Optical Design Using Specular Film, Mario Gutierrez, Robert Thibodeau, Emma Show, Desiree Robinson, Lingyuan Meng, Sean Martin, Conner Beeson
M.O.D.U.S. Modular Optical Design Using Specular Film, Mario Gutierrez, Robert Thibodeau, Emma Show, Desiree Robinson, Lingyuan Meng, Sean Martin, Conner Beeson
Discovery Day - Daytona Beach
High-quality parabolic mirrors, which are vital components in reflecting telescopes, are typically bulky, costly, and highly fragile. This experiment explores the feasibility of using specular Class B Mylar as an unconventional, lightweight, and cost-effective alternative. This approach could enable new telescope designs by greatly reducing weight and manufacturing expenses, while also opening options for potential adaptability. This approach involves using Mylar, a flexible, reflective style of plastic. The mylar is formed into a concave mirror by stretching a sheet over a chamber and depressurizing one side to force the sheet into the necessary curved shape. Multiple designs are being created …
String-Of-Pearls Measurements Of Supersonic Plasma Jets Using Magnetospheric Multiscale Satellites, Amelia Koth
String-Of-Pearls Measurements Of Supersonic Plasma Jets Using Magnetospheric Multiscale Satellites, Amelia Koth
Discovery Day - Daytona Beach
High-energy supersonic plasma jets form when the solar wind, which is a flow of charged particles from the Sun, slows down as it encounters Earth’s magnetic shield. Occasionally, the solar wind remains at supersonic speeds as it enters this region. This forms plasma jets that propagate toward Earth; these jets can carry strong magnetic fields, drive magnetic reconnection, and potentially initiate substorms that lead to auroral activity. Previously studied plasma jets occurred when the interplanetary magnetic field (IMF) points southward. In contrast, this study focuses on northward IMF conditions, which are less understood, yet still capable of producing supersonic jets. …
Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk
Helio: Heliophysics Enhanced Learning For Intelligent Orbits, Kylie Nager, James Kirk
Discovery Day - Daytona Beach
HELIO: Heliophysics Enhanced Learning for Intelligent Orbits Satellite constellations operating in near-Earth space are increasingly vulnerable to space weather disturbances, such as solar flares, coronal mass ejections (CMEs), and high-speed solar wind streams, which degrade communications, destabilize attitude control, and accelerate orbital decay. These disturbances directly threaten mission continuity, constellation availability, and space asset survivability. Current protective approaches rely primarily on ground-based alerts and lack integration with broader space domain awareness, which results in programmed reactive protocols that are often initiated too late to prevent performance degradation and asset loss. The HELIO project addresses this gap by turning space-weather forecasts …
Interplanetary Trajectory Optimization With Reinforcement Learning, Shiloh Cuffe
Interplanetary Trajectory Optimization With Reinforcement Learning, Shiloh Cuffe
Discovery Day - Daytona Beach
This project investigates the application of reinforcement learning (RL) to optimize low-thrust interplanetary trajectory design, focusing on the Earth-Venus transfer leg of the BepiColombo mission. Traditional trajectory optimization methods, such as patched conics and genetic algorithms, often require simplifying assumptions or complex optimization schemes. This work formulates the trajectory design problem as an optimal control problem (OCP) within a Markov Decision Process (MDP) framework, enabling an RL agent to learn efficient transfer strategies under realistic spacecraft constraints. The objective is to develop an autonomous guidance approach capable of replicating or improving upon established mission designs. The spacecraft is modeled as …
Generalized Cloud-Based Compressible Aerodynamics Calculator And Simulation Web App, Massimo Mansueto, Liam Griesacker, Andres Torres-Figueroa
Generalized Cloud-Based Compressible Aerodynamics Calculator And Simulation Web App, Massimo Mansueto, Liam Griesacker, Andres Torres-Figueroa
Discovery Day - Daytona Beach
The Generalized Cloud-Based Compressible Aerodynamics Calculator and Simulation Web App focuses on the development of a tool to support the analysis, visualization, and teaching of compressible aerodynamics. In the case of most undergraduate aerospace engineering courses, students rely on static equations, charts, and manual calculations, which can make it difficult to conceptualize complex flow phenomena such as shock waves, expansion fans, and nozzle flow. The purpose of this project is to create an accessible platform that integrates a compressible flow calculator, nozzle sizing tool, and interactive simulations into a single educational resource. The application is implemented using modern web development …
Extending The Essentially Entropic Lattice Boltzmann Method To Three-Dimensional Turbulent Flows, Michael Derderian
Extending The Essentially Entropic Lattice Boltzmann Method To Three-Dimensional Turbulent Flows, Michael Derderian
Discovery Day - Daytona Beach
The Entropic Lattice Boltzmann Method (EELBM) has demonstrated strong numerical stability and accuracy for two-dimensional simulations, particularly at higher resolutions where the entropic formulation introduces only minimal stabilizing turbulent viscosity and eventually converges to the Lattice Bhatnagar–Gross–Krook (LBGK) formulation. This built-in stabilization can be interpreted as an implicit large-eddy simulation (LES) model, allowing EELBM to capture complex turbulent behavior without requiring explicit subgrid-scale closures. While these advantages have been thoroughly validated in 2D, understanding how the entropic constraint regulates dissipation in three dimensions is essential for assessing EELBM’s suitability for practical, turbulence-dominated applications. This work focuses on the development and …
Feasibility Of High-Throughput Onboard Ai For Mars Rovers Under Solar Constraints, Aashman Gupta
Feasibility Of High-Throughput Onboard Ai For Mars Rovers Under Solar Constraints, Aashman Gupta
Discovery Day - Daytona Beach
This project evaluates the feasibility of sustained onboard AI autonomy for a solar-powered Mars rover by directly linking solar energy availability to achievable compute performance. While Mars solar irradiance and edge computing performance have been studied independently, no unified framework currently couples surface power generation to autonomy throughput in an experimentally validated manner. The project will begin with a simulation of solar power generation for a 1 m² rover-mounted array across a Martian sol, accounting for seasonal variation, dust opacity, and array configuration (fixed versus sun-tracking). The resulting power profile will then be coupled to representative compute platforms running autonomy …
An Energy-Aware Meta-Learning Framework For Real-Time Lunar Rover Localization Via Adaptive Algorithm Selection, Jose Demedeiros, Garrett Seyler
An Energy-Aware Meta-Learning Framework For Real-Time Lunar Rover Localization Via Adaptive Algorithm Selection, Jose Demedeiros, Garrett Seyler
Discovery Day - Daytona Beach
This work proposes an energy-aware meta-learning framework that selects the single most suitable localization algorithm for a lunar rover, per scene, using only monocular imagery and orbital maps. The goal is to achieve sub-meter accuracy while minimizing onboard compute and energy consumption. We assemble a suite of seven lunar-relevant algorithms spanning relative and absolute localization, including monocular ORB-SLAM3, LuVo homography-based visual odometry, Censible cross-view matching with orbital imagery, crater-based methods (LunarNav and ShadowNav), monocular horizon navigation with a DEM, and DROID-SLAM. Relative methods provide incremental motion updates, while absolute methods deliver global pose fixes; an Extended Kalman Filter fuses these …
Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson
Cars Imass - Comparing Llm Vs Human Operator Effectiveness In Multi-Agent Swarm Coordination, Gatlin Nelson
Discovery Day - Daytona Beach
Title: Dual-Perspective Risk Analysis for Human-LLM Decision Comparison in UAV Swarm Navigation Unmanned aerial vehicle (UAV) swarms operating in low-altitude wireless network environments encounter localized disruptions that degrade positioning and navigation metrics. These disruptions are modeled as geographic failure zones with defined boundaries. A UAV discovers a zone by entering it and observing degraded performance on its onboard systems. This work assumes that affected UAVs can autonomously retreat to safety using onboard sensors and focuses on the subsequent rerouting decision. Once recovered, the system generates candidate repositioning points surrounding the vehicle, each scored using Conditional Value-at-Risk (CVaR). A human operator …
Multi-Dimensional Particle-In-Cell With Monte Carlo Collisions (Pic-Mcc) Simulation For Visualizing Plasma Flow And Secondary Ionization In Constricted-Anode Geometries, Parth Thakar
Discovery Day - Daytona Beach
Constricted-anode plasma sources generate locally intensified electric fields that enhance ionization near the anode, making them valuable in propulsion and laboratory plasma systems. However, the narrow geometry produces complex charge accumulation and secondary ionization effects that remain difficult to measure experimentally. To address this challenge, our research develops and applies a multi-dimensional Particle-in-Cell with Monte Carlo Collisions (PIC-MCC) simulation of a DC discharge in 1-D, 2-D, and 3-D configurations that model a constricted-anode device. PIC-MCC is a first-principles method that tracks electrons and ions individually while computing self-consistent electric fields and incorporating energy-dependent collision processes. This approach enables direct visualization …
Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods
Phaëthon System, Brady Roudabush, Lauren Gallo, Emelia Thompson, Jacob Woods
Discovery Day - Daytona Beach
Phaëthon System is the project name for the Search and Rescue Drone Initiative. This initiative will improve the current search and rescue drone industry by introducing new techniques to get through dense forest canopies and other places where an overhead view is not useful. The Phaëthon System uses a swarm of drones that can penetrate under the tree canopy to map and search with the utmost efficiency and safety for rescuers. A command drone is launched to survey the overall search area, and set up a communications and data link. The next component is then released, which is a swarm …
Effect Of Anode Size On The Properties Of Constricted Hollow Anode Pulsed Plasma Source, Nirav Patel, Garret Seckinger
Effect Of Anode Size On The Properties Of Constricted Hollow Anode Pulsed Plasma Source, Nirav Patel, Garret Seckinger
Discovery Day - Daytona Beach
With the advent of ion thrusters, burns requiring large velocity changes can be performed with a fraction of the propellant required by traditional chemical rocket engines. However, current ion thrusters produce thrust in the order of millinewtons and thus cannot be viable for launching vehicles or burns requiring velocity changes in a small amount of time. Furthermore, current ion thrusters experience grid and component erosion, where the two grids at the termination of the nozzle slowly erode due to particle impact, and the hot electrodes degrade due to high thermal load. This limits the life of ion engines, which require …
Accelerating Search And Rescue Response: A Simulation Study On The Dynamic Efficiency Of Flocking-Enabled Drone Swarms, Sophia Beckwith, Carys Del Prete
Accelerating Search And Rescue Response: A Simulation Study On The Dynamic Efficiency Of Flocking-Enabled Drone Swarms, Sophia Beckwith, Carys Del Prete
Discovery Day - Daytona Beach
This project explores how imitations observed in animal group behavior, specifically flocking in birds, can be applied to the functionality of autonomous drone systems to aid in search and rescue efforts. The goal is to demonstrate how incorporating code based on the Boids, Vicsck and predictive control linear algebraic mathematical models for drone flight controls and the collective behaviors of flocks will increase the efficiency of drone maneuvers, allowing them to reorganize and fill gaps when one is removed. A MATLAB-based simulation was developed to model the behaviors using research conducted on the symmetric and synchronized behaviors observed from flocks …
Optimization Of Engine, Jordan Reed, Dev Shah
Optimization Of Engine, Jordan Reed, Dev Shah
Discovery Day - Daytona Beach
A matrix-based framework for modeling and optimizing fluid and gas in feed systems to pressurize for propulsion applications using advanced linear algebra techniques will be used in this project. The governing equations are derived from conservation of mass, momentum, and energy and are formulated in state space form. This enables the system to be expressed as a set of coupled linear differential equations. These equations are assembled into structured system matrices that show the interactions between pressure, flow rate, and component dynamics. This representation allows for numerical implementation and scalability to complex systems with multiple components. System behavior is analyzed …
Modeling Seiche Oscillations Using Damped Vibration Differential Equations, Sharjeel Malik, Justin Della
Modeling Seiche Oscillations Using Damped Vibration Differential Equations, Sharjeel Malik, Justin Della
Discovery Day - Daytona Beach
Combustion instability in liquid rocket engines is driven by coupling acoustic pressure oscillations and unsteady heat release. To achieve specific desired outcomes, small perturbations can be made to either decay or grow, depending on system dynamics and artificial parameters. Using a linearized eigenvalue framework, where eigenvalues determine growth/decay rates and frequencies, and eigenvectors describe spatial mode shapes and couplings between pressure, velocity, and heat release, a mathematical model can be derived to describe said behavior for a cross-section of the rocket engine. The Rayleigh criterion is used to identify conditions under which energy is added to oscillations, while flame transfer …
Navier Stokes Pressure Drop Derivation, Brayden Benedetti, Gedaliah Dimbert, Jaden Turobiner
Navier Stokes Pressure Drop Derivation, Brayden Benedetti, Gedaliah Dimbert, Jaden Turobiner
Discovery Day - Daytona Beach
Accurate prediction of pressure losses in propellant and fluid feed systems is essential for reliable design and operation of aerospace and industrial flow networks. This project presents a systematic derivation of a practical pressure drop calculator for a feed system using isopropyl alcohol, beginning from the fundamental conservation laws and culminating in an engineering-level computational model. Starting with the differential form of the Navier–Stokes equations for incompressible flow, the governing equations are simplified through a series of physically justified assumptions, including steady-state flow, negligible body forces, and fully developed internal flow within circular piping. The resulting momentum balance is reduced …
Application Of Navier Stokes In Cfd, Hayden Kerkhoff, Gavin Palmer, Garret Seckinger
Application Of Navier Stokes In Cfd, Hayden Kerkhoff, Gavin Palmer, Garret Seckinger
Discovery Day - Daytona Beach
This project investigates the use of 2-Dimensional Computational Fluid Dynamics (CFD) to analyze aerodynamic behavior, then compare data with the numerical solution of the Navier–Stokes equations run by MATLAB. By leveraging open‑source and possible industry CFD platforms—including OpenFOAM and commercial solvers such as ANSYS Fluent and Inventor Professional—the study evaluates how computational methods simulate, optimize, and predict key aerodynamic quantities such as lift, drag, stall angle, and Reynolds number. The project focuses on modeling an airflow over specific parameters, such as different angles of attacks and ISA Atmospheric Conditions. Parametric variations in density, angle of attack, chord length, and temperature …
Numerical Modeling Of Badminton Shuttlecock Trajectories, Lola G. Torres, Cassandra Pumphrey, Jadyn Peterson, Domenic Barsotti
Numerical Modeling Of Badminton Shuttlecock Trajectories, Lola G. Torres, Cassandra Pumphrey, Jadyn Peterson, Domenic Barsotti
Discovery Day - Daytona Beach
The Trajectory of a badminton Shuttlecock can vary significantly when compared to a classic projectile motion, primarily due to aerodynamic drag. This project aims to model the flight of the shuttlecock using Newton's second law for gravitational and drag related forces, resulting in a nonlinear system of a first order differential equation. The given parameters include the shuttlecock mass, cross-sectional area, air density, as well as the drag coefficient, determining the overall magnitude of the drag force. The resulting initial value problem is solved numerically using a multitude of Runge_Kutta methods to compare the accuracy and stability across different computational …
Motion With Air Resistance, Gauge Mccain, Jacob Bealefeld, Francesca Wise
Motion With Air Resistance, Gauge Mccain, Jacob Bealefeld, Francesca Wise
Discovery Day - Daytona Beach
The motion of objects moving through air is influenced not only by gravity but also by air resistance, which affects the speed and acceleration of the object over time. This project examines the motion of a falling object by modeling it with an ordinary differential equation that accounts for both gravitational force and a resistive drag force proportional to velocity. Using Newton’s Second Law, a first-order differential equation is derived to describe how the velocity of the object changes as it falls. The solution of this equation demonstrates how the velocity increases initially and gradually approaches a constant value known …
Engineering Path Trajectories With Gravitational Fields, Eliane Dean, Aidan Hart, Isabel Noot, Nathan Browning, Valeria Villazon Fito
Engineering Path Trajectories With Gravitational Fields, Eliane Dean, Aidan Hart, Isabel Noot, Nathan Browning, Valeria Villazon Fito
Discovery Day - Daytona Beach
This project explores how vector calculus concepts play a role in aerospace engineering though spacecraft trajectory design. In particular, the notion of vector fields is used to model the gravitational force, whose work done is expressed through line integrals. By taking the curl of the gravitational field and showing it is zero, the field is recognised as conservative, implying that the work done by gravity is path independent. This property is conceptually linked to gravitational potential energy and the principle of energy conservation. The results are then applied to spacecraft motion, where engineers use energy-base methods to determine efficient trajectories …
Modelling Quadcopter Thrust And Torque Using Lu-Decomposition, Diya Patil
Modelling Quadcopter Thrust And Torque Using Lu-Decomposition, Diya Patil
Discovery Day - Daytona Beach
3 & 4 motor systems have been in the world of aviation in many different forms as the field grows and evolves. To understand the complexities of an Unmanned Aerial Vehicle (UAV) and its stability, assessing the amount of thrust put into each motor can help generate the torque produced despite factors such as multidirectional movement. While a UAV does this multiple times a second, producing a simplified version of this calculation can aid in simpler models simulating UAV movement. Due to the popularity of the quadcopter drone, a simple algorithm depicting thrust through each spinning motor can aid in …
Simulations Of Phugoid Motion Of Jal 123, Dereth J J. Drake Scheuermann
Simulations Of Phugoid Motion Of Jal 123, Dereth J J. Drake Scheuermann
Georgia Journal of Science
Airplanes rely on a balance between the four forces of flight: lift, weight, thrust, and drag. If these forces are balanced, the airplane will remain stable. However, if structurally or systematically compromised, the motion can rapidly become unstable. In the aviation industry, mistakes in repairs and aircraft design can lead to accidents causing the loss of life in some cases. In this article, we will be analyzing what happened 70 Japan Airlines flight 123 and how the flight’s motion deteriorated due to a defective repair. More specifically, we will discuss the aerodynamic effects of phugoid motion and how it developed …
Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury
Machine Learning For Predictive Energy And Emissions Modeling Of Vehicles And Power Grids In The United States, S M Tanvir Faysal Alam Chowdhoury
Dissertations
The environmental benefits of electric vehicle (EV) adoption depend on more than replacing internal combustion engine vehicles with electric powertrains. EV adoption reshapes electricity demand, interacts with regional generation mixes, and influences travel behavior and congestion, creating a coupled transportation-energy system in which vehicle and power-plant emissions must be evaluated together. This dissertation develops machine-learning frameworks for predicting energy consumption and emissions from vehicles and power grids under rising EV adoption. The first component forecasts grid emissions from EV charging. Using simulation data from NREL's Cambium database, a Prophet-based time-series framework predicts carbon dioxide, nitrous oxide, and methane emission rates …