Aerospace Engineering Commons^™

Data Driven Analysis Of Samara Seed Kinematics And Dynamics, Shashwat Sparsh

Master's Theses

Samara Seeds are a class of fruit most famously belonging to the Acer species and are characterized by their single-bladed geometry and their auto-rotation response during descent. This steady-state auto-rotation response is the subject of aerodynamic analysis which aim to quantify the performance. The period prior to the beginning of steady-state auto-rotation is classified as the transition regime and has not been the subject of intense scrutiny.

This thesis employs a data-driven approach to analyzing the kinematic and dynamic response of these seeds during both the transition and auto-rotation stages of flight to quantify the performance with respect to the …

Mae Enewsbrief Jan-Mar 2025, Department Of Mechanical And Aerospace Engineering, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

Mae Enewsbrief Oct-Dec 2024, Department Of Mechanical And Aerospace Engineering, Michigan Technological University

Department of Mechanical and Aerospace Engineering eNewsBrief

No abstract provided.

Leveraging Large Language Models (Llms) For Automated Generation Of Sysml V2 State Machines In Guidance, Navigation, And Control (Gnc) Systems, Andrea Louise Ames

Theses and Dissertations

Modern defense systems continue to grow in complexity, placing increasing pressure on engineering workflows to be faster and more adaptable. While Model-Based Systems Engineering (MBSE) with the emerging SysML v2 standard provides a framework for capturing system behavior, its practical use is often limited by the expertise and time required for manual modeling. This research investigates whether large language models (LLMs) can help overcome that barrier by automatically generating SysML v2 state machines from Guidance, Navigation, and Control (GNC) textual inputs. Three LLM Flowise-based models were developed and evaluated: the Structured Transformation Model (STM), which uses a structured extraction and …

Design And Development Of Hip Implants For Longevity Through Integrating Advanced Groove Structures And Additive Manufacturing, Asarudheen Abdudeen

Dissertations

This doctoral research concerns the design and optimization of hip implants (HIs) to enhance performance, durability, and improve patient outcomes by addressing the key issues of wear, deformation, and stress distribution. Innovative surface groove designs have been introduced to both a solid and a hollow femoral head with the aim of reducing friction and wear. The addition of grooves, with both a hemispherical and rectangular cross-section, onto the femoral head reduced friction, as debris produced by the inner liner was trapped within the grooves, significantly reducing adhesive wear. A numerical simulation study compared the effects of surface modifications both grooves …

Effect Of Thermal History On The Fracture And Fatigue Behaviors Of Semi-Crystalline Polymers Prepared Via Material Extrusion Additive Manufacturing, Ava M. Lea, Khaled Matalgah, Arief Yudhanto, Trevor J. Fleck

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Material extrusion (MEX) additive manufacturing (AM) is transforming the design and production of complex structures, providing reliable on-demand components. However, the effect of thermal history on the resultant microstructure and damage tolerance of MEX-AM materials is not fully understood. This research investigates the critical role of interfacial thermal history, which is dependent on processing conditions, in determining the fracture and fatigue behaviors of semi-crystalline polymers, as exemplified by polyamide-6 (PA-6). Utilizing infrared thermography, the thermal history, and its dependence on nozzle temperature of extruded PA-6, was investigated. Quasi-static and cyclic tests of compact tension specimens were used to evaluate fracture …

Analysis Of The Effects Of Extractor Orientation On The Performance Of An Electrospray System, Hannah Grace Sargent

Masters Theses

In this thesis, a single-emitter porous electrospray thruster was tested at nine different extractor electrode positions. The nine positions were: center, four slightly offset in each cardinal direction, and four significantly offset in each cardinal direction. Slightly offset was defined as ~25% of the distance from the center to the edge of the extractor orifice (~125 ± 2 μm) and significantly offset was defined as ~60% of the distance from the center to the edge of the extractor orifice (~302 ± 2 μm). Three diagnostic measurements were recorded to determine the effect of the extractor electrode position on thruster operation: …

An Inquiry Into The Physics Of Mixing And Floc Filtration, Andrew P. Pennock

Dissertations

Flocculation and clarification are two essential processes to deliver safe water at a reasonable cost to consumers. There are two major thrusts to the research presented in this dissertation. The first is to better characterize the physics and mixing parameters used for the design of hydraulic flocculators in the context of drinking water treatment plants. The second major thrust is to investigate floc filtration as a mechanism for the removal of primary particles during floc blanket clarification.

The intensity of mixing in environmental and chemical engineering applications is often characterized by the Camp and Stein velocity gradient. This parameter has …

Attitude Determination & Control Algorithms, Utah State University Space Dynamics Laboratory

Space Dynamics Laboratory Publications

Purpose

• Quick-look overview of all elements of ADCS (e.g. this control loop)
• Give references and terminology but not the complete "how-to"

Optimizing Concrete Strength: How Nanomaterials And Ai Redefine Mix Design, Dan Huang, Guangshuai Han, Ziyang Tang

Physics and Engineering Science

Nanomaterials and supplementary cementitious materials (SCMs) are typically used together in efforts to enhance the performance of concrete and mitigate the environmental impact of concrete construction. However, the complex interactions between nanomaterials, SCMs, and cement make concrete mix design a challenging, iterative, and labor-intensive process, often relying on trial-and-error experimentation. Machine learning (ML) offers an opportunity to better understand the influence of input parameters and to accelerate the optimization of mix designs through data-driven insights. This study proposes an open-source and easy-to-access framework, Canopy, to support the concrete research community in optimizing mix design. Using a dataset collected from the …

Geometric Calibration Of Near Focus Infrared (Ir) Sensors For Spacecraft Missions, Alex Allgrunn

Space Dynamics Laboratory Publications

SDL Presentation on Geometric Calibration of Near Focus IR Sensors for Spacecraft Missions

Bounding Case Requirements For Power Grid Protection Against High-Altitude Electromagnetic Pulses, Connor A. Lehman, Darrell Robinette, Wayne Weaver, David G. Wilson

Michigan Tech Publications

Securing the power grid is of extreme concern to many nations as power infrastructure has become integral to modern life and society. A high-altitude electromagnetic pulse (HEMP) is generated by a nuclear detonation high in the atmosphere, producing a powerful electromagnetic field that can damage or destroy electronic devices over a wide area. Protecting against HEMP attacks (insults) requires knowledge of the problem’s bounds before the problem can be appropriately solved. This paper presents a collection of analyses to determine the basic requirements for controller placements on a power grid. Two primary analyses are conducted. The first is an inverted …

A Review Of Direct Ink Writing Of Polymer Derived Ceramics, Victoria Bishop, Saket Chand Mathur, Nhu Nguyen, Bhisham Sharma, Mary Drouin, Bin Li, Cheol Park, Wei Wei

Michigan Tech Publications

With the growing demand for materials capable of withstanding extreme temperatures and pressures, ceramic components with exceptional corrosion resistance and reliable mechanical properties have experienced a significant surge in demand. However, traditional ceramic forming methods involve high-temperatures and energy-intensive processes that often struggle to produce complex parts or composites efficiently. Polymer-Derived Ceramics (PDCs) offer a transformative solution by using polymeric precursors that can be converted into a wide variety of silicon-based and non-silicon-based ceramics through heat treatment. The polymeric nature of PDC precursors enables the fabrication of geometrically intricate components using conventional polymer-forming techniques at significantly lower processing temperatures. Furthermore, …

Impact Of Circular And Non-Circular Nozzle Exit Geometries On Jet Flow Propagation And Turbulence Characteristics, Hiba Maazioui

Theses and Dissertations

This thesis aims to investigate the impact of nozzle exit geometry on jet flow propagation and turbulence characteristics. Computational fluid dynamics simulations were performed using ANSYS Fluent, employing the Reynolds-Averaged Navier-Stokes (RANS) approach, to compare circular, elliptic, and rectangular nozzle geometries. The analysis focused on velocity distributions, turbulence characteristics, and cross-flow interactions. Results indicate that circular jets have the longest potential core and slowest velocity decay, reflecting lower mixing rates. In contrast, elliptic and rectangular jets have shorter potential cores, faster velocity decay, and elevated TKE peaks, suggesting enhanced turbulence and mixing. These findings highlight the significant role of nozzle …

Integration Of Machine Learning Techniques With Computational Fluid Dynamics For Enhanced Backward-Facing Step Flow, Yahya Mekkaoui

Theses and Dissertations

This research presents a novel integrated framework combining computational fluid dynamics (CFD) with machine learning techniques to enhance the analysis of backward-facing step flows. A high-fidelity OpenFOAM CFD simulation was developed and validated against experimental data, accurately predicting the reattachment length (��/�� ≈ 6.18) and velocity profiles throughout the domain. Machine learning models, including Random Forest, Gradient Boosting, and Support Vector Regression, were integrated through a robust data pipeline, with the ensemble approach demonstrating superior performance (RMSE of 1.18 m/s, ��2 of 0.951). Feature importance analysis revealed pressure (32%) and turbulent kinetic energy (28%) as the dominant physical parameters governing …

The Human Element In Space Exploration – Embodying Our Highest Values, Leila Halawi, Mark Miller, Samuel J. Holley

Publications

SpaceX mission and the Polaris Program extended astronaut competencies and skills, suggesting mixing traditional practices with pioneering methods. The current astronaut symbolizes a progression, integrating old skills with evolving competencies. While maintaining core technical and scientific aptitudes, today’s astronauts or space explorers must demonstrate mastery in autonomous operations, cross-cultural collaboration, and navigation between governmental and commercial space protocols. Current training practices echo this change, emphasizing resilience for prolonged isolation, self-governing management proficiencies, and competence throughout distinct spacecraft systems. This chapter explores the fundamental human qualities that drive successful space exploration: resilience, curiosity, collaboration, and hope. We highlight how these vital …

An Adaptation Of Nonlinear Aerodynamic Models For Non-Traditional Control Effectors, Christian R. Bolander, Douglas F. Hunsaker

Engineering Education Faculty Publications

This paper presents the development of a novel aerodynamic model tailored for the Bio-Inspired Rotating Empennage (BIRE), a non-traditional fixed-wing aircraft empennage inspired by avian flight. The BIRE replaces the conventional vertical stabilizer with an extra degree of freedom for the horizontal stabilizer, which is allowed to rotate about the body-fixed x axis. This empennage is similar to the tail of a bird, and allows control of both longitudinal and lateral moments. However, such a design introduces complex nonlinear longitudinal and lateral aerodynamic interactions, not typically accounted for in most fixed-wing aircraft aerodynamic models below stall. This work presents a …

Computational Fluid Dynamics Analysis Of A Turbine Blade, Luis Luna, Fabiha Samiha

Publications and Research

In Aerospace engineering, the use of computer-aided design (CAD) software, such as SolidWorks, is crucial when designing and validating high-performance parts. SolidWorks provides a valuable tool for simulating computational fluid dynamics (CFD), allowing engineers to analyze and visualize how parts behave under real-world aerodynamic conditions.

One such part is a turbine blade, an airfoil-shaped component inside a jet engine that compresses and redirects airflow to generate thrust. This study aims to perform aerodynamic testing of a single turbine blade design while evaluating SolidWorks' ability to simulate external flow conditions. By visualizing velocity profiles, pressure distribution, and vortex formation, the simulation …

Gradient Fibro-Porous Materials For Tailored Sound Absorption, William Johnston, Janith Godakawela, Bhisham Sharma

Michigan Tech Publications

Reducing the pore size of bulk sound absorbers often increases weight and introduces manufacturing challenges, limiting their practical use. To address these issues, a class of materials is introduced that uses 3D printing to seamlessly integrate fibers within porous scaffolds, allowing improved sound absorption performance without a significant weight addition. The reliance on 3D printing enables the creation of gradient fibro-porous structures with customizable acoustic properties. This study explores the effect of through-thickness gradients in the scaffold’s relative density, fiber thickness, and fiber density on the acoustical performance with the goal of identifying the optimal strategy to obtain broader and …

Satellite Reorientation Using Reinforcement Learning Under Unknown Attitude Failure, Matthew Willoughby

Doctoral Dissertations and Master's Theses

This study presents a reinforcement learning (RL) approach for reestablishing communication with deep-space satellites under unknown attitude determination and control system (ADCS) failures. When traditional fault-tolerant control methods cannot restore signal, the proposed RL controller acts as a last-resort measure by autonomously reorienting the satellite’s antenna toward Earth while charging the battery via solar panels. A generic reward function, designed for the RL-based method, enables the controller to adapt to diverse failure scenarios, including severe actuator noise, misalignment, and complete actuator failure. Simulations are conducted in the Basilisk environment and trained with the tonic framework and demonstrate ranging capabilities of …