Aerospace Engineering Commons^™

Reduced Set-Shifting Processing Speed In Male Rats Following Low Dose (10 Cgy) Proton Exposure, Hui Ho Vanessa Chang, Gyutae Kim, Kyu-Sung Kim, Richard A. Britten

Center for Integrative Neuroscience and Inflammatory Diseases (CINID) Faculty Publications

Space radiation (SR) exposure poses significant biomedical risks, including effects on the central nervous system (CNS). These risks are particularly relevant to cognitive function during long-duration space missions. One critical cognitive skill is decision-making, which requires attentional set-shifting (ATSET)—the ability to quickly assess problems, evaluate options, and select the best actions. Previous studies have shown that exposure to However, the impact of low LET (< 1 keV/μm) protons, which significantly contribute to the total radiation flux astronauts encounter within spacecraft, on ATSET performance is unknown. To address this gap, we evaluated the effects of cranial irradiation with 10 cGy of 100 MeV/n protons (LET = 0.732 keV/μm) on ATSET performance in male Sprague-Dawley rats. We also investigated whether concurrent exposure to variable gravity (hypergravity step-up, step down, purported to have the same effect as exposure to microgravity (another major spaceflight stressor) exacerbated SR-induced cognitive deficits. Our findings indicate that proton exposure alone significantly impaired ATSET performance, as evidenced by decreased processing speed while performing compound discrimination reversal and extra-dimensional shifting. Notably, no additive or synergistic effects were observed when hypergravity was combined with proton exposure. The impact that low-dose proton exposure has on CNS functionality, particularly in reducing processing speed during complex tasks, warrant further investigation. If similar cognitive deficits were to occur in astronauts exposed to galactic cosmic rays, mission success and safety could be significantly compromised.

Neuroinflammatory Signaling And Immune Cell Infiltration Differ In Brains Of Rats Exposed To Space Radiation And Social Isolation, Austin M. Adkins, Zachary N. M. Luyo, Alea F. Boden, Riley S. Heerbrandt, Richard A. Britten, Laurie L. Wellman, Larry D. Sanford

Center for Integrative Neuroscience and Inflammatory Diseases (CINID) Faculty Publications

Astronauts on the proposed Mars missions will be exposed to extended periods of social isolation (SI) and space radiation (SR). SI and SR-induced immune dysregulation can result in persistent neuroinflammation and neuronal damage which could negatively impact an astronaut’s health and ability to maintain adequate levels of performance. The synergistic effects of combined SI and SR on immune system functionality and the brain remain unknown. Determining how single and combined inflight stressors modulate the immune system is crucial for fully understanding pathways impacting astronaut health and performance. We used ground-based analogs of SI and SR in rodent models to investigate …

Versatile Injector Platform: A Modular Design For Supersonic Flow Research, Connor Bell, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Fuel–air mixing remains a critical challenge in the development of high-speed air-breathing propulsion due to the extremely short residence times in supersonic combustors. Experimental studies are essential to investigate the underlying mixing mechanisms, but they require injection systems that can deliver repeatable and controlled flow conditions. In this work, we present the design of a modular strut-type injection platform developed for the Missouri S&T Supersonic Wind Tunnel. In its initial configuration, the platform features a planar trailing-edge slit to generate a two-dimensional jet and includes interchangeable trailing-edge modules to support a wide range of geometries and flow-control strategies. Designed with …

Generative Adversarial Networks For Dimensionality Reduction In Evtol Aircraft Takeoff Trajectory Optimization, Samuel Sisk, Farzaam Khorasani-Gerdehkouhi, Abdulaziz Abutunis, K. Chandrashekhara, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft play a key role in urban air mobility (UAM), which aims to alleviate traffic congestion in urban areas. Despite their value, eVTOL aircraft suffer from battery energy consumption, which affects their range and endurance in real world flight tasks. Especially, the takeoff process has been identified for excessive power demands. Multidisciplinary analysis and optimization manage to discover optimal takeoff trajectories with minimum energy consumption while balancing multidisciplinary trade-offs, such as short distance takeoff and passengers' comfort. However, conventional parametrization methods (such as B-spline curves) leverage an empirically high-dimensional design space to include real …

A Ground Thermal Vacuum Facility For Simulating Cryogenic Space Environment Conditions, Emmanuel Kofi Asuako Wie-Addo, Lucas Scott, Daoru Han

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This work presents the ongoing progress of a vacuum facility upgrade at the Gas and Plasma Dynamics Laboratory (GPDL) at Missouri University of Science and Technology. A movable shroud has been fabricated and installed to enable the simulation of extreme cold conditions. The cooling rate of the shroud, a dummy test article, and a platform, using liquid nitrogen as the thermal fluid, is analyzed and reported under varying vacuum conditions for cryogenic runs. Preliminary testing revealed substantial thermal exchange between the shroud and the chamber walls, underscoring the necessity for implementing effective thermal isolation measures to mitigate heat transfer.

Arc-Jet And Free-Flight Evaluation Of Laminar And Turbulent Diffusion Models On Ablation, Kyle Worden, Andrew Heider, Serhat Hosder

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper investigates the effect of diffusion models on carbon ablation with a parametric study on a slug-calorimeter geometry in arc-jet flow at two enthalpy conditions using two arc-jet flow modeling approaches, and at corresponding enthalpy-matched free-flight conditions using RANS CFD simulations. Additionally, a sphere-cone geometry is modeled at the arc-jet enthalpy matched free-flight conditions and at a high Reynolds number free-flight condition. The approximate-corrected form of Fick's law and the Stefan-Maxwell diffusion models are investigated for equilibrium and finite-rate carbon ablation in laminar and turbulent flows, which is simulated with the Menter-SST turbulence model. The turbulent cases include the …

Multifidelity Dust Erosion Analysis Of Mars Entry Vehicles, Adam Boland, Dominic Zanti, Serhat Hosder, Andrew Hinkle

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The objective of this paper is to present a multifidelity approach for estimating recession rate and kinetic energy impact rate on the surface of planetary entry vehicles operating in dusty atmospheric environments at hypersonic speeds. The multifidelity model used a co-Kriging approach that combined a low-fidelity correlation with a correction factor from high-fidelity CFD solutions. The developed multifidelity model enables efficient and accurate exploration of a design space to determine at what conditions encountering dust is most dangerous to TPS survivability. Two sample problems are used to demonstrate the effectiveness of the approach: the Mars 2020 lander and a HIAD-type …

An Adaptive Sampling Strategy On Optimal Takeoff Trajectory Prediction Of Electric Drones, Dheeraj Paramkusham, Samuel Sisk, Jiachen Wang, Shuan Tai Yeh, Xiaosong Du, Nathan Roberts

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft transforms future transportation systems by alleviating transportation congestion on the ground. This eVTOL technique possesses unique features, including reduced noise, low pollutant emissions, efficient operating costs, and flexible maneuverability. Meanwhile, battery consumption poses critical challenges to flight task duration. Thus, optimal takeoff trajectory design is essential due to immense power demands during eVTOL takeoffs. Conventional design optimization, however, iteratively evaluates high fidelity simulation models, making the design process computationally intensive. In this work, we implement a machine learning-enabled inverse mapping optimization concept, i .e., directly predicting optimal design based on design requirements (including …

Improving Neural Network Efficiency With Multi-Fidelity And Dimensionality Reduction Techniques, Vignesh Sella, Thomas O'Leary-Roseberry, Xiaosong Du, Mengwu Guo, Joaquim R.R.A. Martins, Omar Ghattas, Karen Willcox, Anirban Chaudhuri

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Design problems in aerospace engineering often require numerous evaluations of expensive to-evaluate high-fidelity models, resulting in prohibitive computational costs. One way to address the computational cost is through building surrogates, such as deep neural networks (DNNs). However, DNNs may only be an effective surrogate when sufficient evaluations of the high-fidelity model are required such that the up-front training cost is amortized, or in situations that require real-time responses (such as interactive visualizations). Typically, the data requirements for adequately accurate training of DNNs are often impractical for engineering applications. To alleviate this issue, the proposed work utilizes output dimensionality reduction along …

High-Order Dynamic Mode Decomposition For Multidimensional Harmonic Retrieval, Yanming Zhang, Steven Gao, Lijun Jiang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Estimating channel parameters such as azimuth, elevation, Doppler shift, and delay is a key challenge in wireless communication, often formulated as a multidimensional harmonic retrieval (MHR) problem. To address this, we propose a high-order dynamic mode decomposition (HODMD) framework for robust frequency estimation from high-dimensional signals in noisy environments. The HODMD approach combines high-order singular value decomposition (HOSVD) to decompose tensor data into a core tensor and mode matrices, with dynamic mode decomposition (DMD) to extract frequencies from the imaginary parts of the DMD eigenvalues. Simulation examples validate the effectiveness of the proposed method, demonstrating its efficiency in solving MHR …

Characterizing Intralaminar Distal Crack And Delamination In Multidirectional Laminates Under Low Velocity Impact: Modeling Approach With Ultrasound Testing Validation, Niildiip Chandraa, Rachel Van Lear, Arief Yudhanto, Yuqing Zhao, David A. Jack, Douglas E. Smith

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Multidirectional laminated composites are essential for load-bearing structures, especially under frequent impact loading. While existing modeling techniques simulate various impact damage modes, our understanding of the underlying mechanisms, specifically the initiation and progression of intralaminar distal cracks and interlaminar delamination, needs improvement. Validating these mechanisms is crucial for enhancing modeling accuracy and expediting the design process. In this work, we propose a three-dimensional finite element modeling (3D FEM) approach aimed at elucidating the impact damage mechanisms in multidirectional carbon fiber reinforced polymer (CFRP). Our model incorporates cohesive zone models (CZM) to simulate the behavior of intralaminar cracks at distal points …

Anisotropic And Temperature-Tunable Second-Harmonic Vortex Generation In Ferroelectric Nbocl2 Holograms, Jayanta Deka, Xiaodong Yang, Jie Gao

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Optical vortex beams with helical phase fronts have immense potential to enhance data capacity due to the unbounded values of orbital angular momentum. Chip-scale platforms for producing vortex beams are of paramount importance for a variety of applications. On the other hand, 2D materials with unique optical properties are essential for developing multifunctional ultrathin photonic devices. Here, anisotropic and temperature-tunable second-harmonic vortex beam generation is demonstrated with ultrathin ferroelectric niobium oxide dichloride (NbOCl₂) fork holograms. The polarization-resolved Raman measurements are performed on the NbOCl₂ crystal to understand the anisotropic behavior of the Raman modes. It is demonstrated …

Performance Evaluation And Multiphysics Process Modeling Of Carbon Fiber Reinforced Thermoset Composites Using Microwave And Autoclave, Nayan Pundhir, Patrick Schwartzkopf, K. Chandrashekhara, Logan Wilcox, Kristen M. Donnell, Jim Lua, Rui Li

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this study, IM7/Cycom 5320-1 unidirectional prepreg has been utilized to manufacture 16-layer laminated composites: a symmetric cross-ply ([0°/90°]4s) and a quasi-isotropic ([45°/90°/−45°/0°]2s) configuration. Microwave and autoclave curing processes have been employed to manufacture the laminated composites. The manufactured composite cure was assessed using differential scanning calorimetry (DSC). The quality and porosity of the microwave-cured parts were juxtaposed to those of autoclave-cured parts through optical microscopy and micro-computed tomography (micro-CT) scanning. Mechanical characterization of the microwave-cured panels was conducted using uniaxial tensile and flexural tests, with results juxtaposed to autoclave-cured samples. Experimental characterization revealed that the microwave-cured parts exhibited nearly …

Design And Testing Of An Intrusive Arm For Supersonic Flow Sampling, Caleb Roberts, Davide Viganò

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Intrusive probes are critical tools in supersonic wind tunnel testing, enabling direct measurement of flow properties such as pressure and heat flux. To support these measurements, a single-axis intrusive arm was designed and implemented in the Missouri S&T Supersonic Wind Tunnel. The system is designed to maintains precise probe positioning, while withstanding the aerodynamic loads, and preserving a dynamic seal between the test section and ambient environment. Its modular design accommodates a range of probe types for various research applications. This paper presents the design methodology, including structural, mechanical, and aerodynamic considerations, and details the integration process. System performance was …

Physics-Constrained Generative Artificial Intelligence For Rapid Takeoff Trajectory Design, Samuel Sisk, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The urban air mobility (UAM) industry is rapidly growing to alleviate regional transportation congestion. Electric vertical takeoff and landing (eVTOL) aircraft plays a critical role in this growth due to their efficiency and reduced operating cost. However, excessive energy demands by the takeoff phase impact the practicality of the aircraft. Conventional multidisciplinary analysis and optimization (MDAO) identifies a minimum energy trajectory but can be computationally intensive due to iteratively evaluating high-fidelity simulation models. In addition, complex constraints in practical MDAO pose crucial challenges to the already demanding process. Surrogate models enable efficient design optimization, but complex constraints could prohibit surrogate-based …

Deep Reinforcement Learning-Based Optimal Takeoff Trajectory Design Of An Evtol Drone, Nathan M. Roberts, Bingling Huang, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The continuing development of electric vertical take-off and landing (eVTOL) aircraft presents promising opportunities to alleviate transportation congestion. However, designing and executing takeoff trajectories that optimally balance energy usage, passenger comfort, and aircraft constraints remains challenging. Conventional design optimization provides a solution for pre-defined flight conditions and environments but is not ideal in real-world applications. In contrast, deep reinforcement learning (DRL) implements optimal policy making real-time decisions with no assumption of mathematical models. Seeing the lack of literature on DRL-based takeoff trajectory design of eVTOL aircraft, we implement and conduct DRL-based optimal takeoff trajectory designs for the Airbus³ Vahana …

Optimizing Uav Swarm Deployment For Efficient Communication Signal Strength Alignment In Disaster Scenarios, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In disaster scenarios, establishing reliable communication infrastructure is critical, and unmanned aerial vehicle (UAV) swarms offer a promising solution as temporary base stations. This study models communication demand in disaster-affected areas by applying Gaussian kernels to building data, forming a spatial demand distribution. Signal strength is estimated using the normalized inverse Free Space Path Loss (FSPL) to account for realistic attenuation. To guide UAV placement, we extract high-demand regions from the demand distribution using a gradient-based thresholding method. Based on this information, we develop a greedy algorithm to iteratively position UAVs for optimal coverage in areas with the greatest communication …

Few-Shot Learning-Enhanced Tiered Path Planning For Mars Rover Navigation, Ziyi Wang, Di Yu, Mina Khalilzadeh Fathi, Chaoying Pei

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Path planning for Mars rovers presents significant challenges due to the diverse terrain, ranging from easily navigable areas to hazardous zones. Traditional methods typically classify terrain simply as passable or impassable, failing to account for the nuances of more moderately challenging areas. In this paper, we introduce a tiered terrain-aware path planning strategy, employing few-shot learning to classify and segment Martian terrain into levels of difficulty. The few-shot learning model, trained on Earth, is sent to the rover, enabling real-time processing of images from satellites or helicopters. The flexibility of few-shot learning, which requires minimal data and training time, enables …

Ground Testing Of A Magnetic-Electrostatic Separation System For Lunar Regolith Beneficiation, Peter Bachle, Charles Wood, Jeffrey Smith, Fateme Rezaei, David Bayless, William Schonberg, Daoru Han

Materials Science and Engineering Faculty Research & Creative Works

The separation of lunar regolith by mineral composition and size category is useful forin-situ resource utilization (ISRU). The research presented herein discusses the designing and development of equipment that has the potential to separate lunar regolith into aluminum, iron-titanium, and magnesium-iron ores. Along with the metal ore separation, this equipment shows the potential to separate regolith by size categories. The combined effect of these separation methods generates output that is valuable to subsequent use in metal and oxygen extraction, additive manufacturing, and regolith sintering processes. The designed equipment uses a dual-strength magnet system with N42 and N52 neodymium magnets for …

Security Enhancement In Uav Swarms: A Case Study Using Federated Learning And Shap Analysis, Sushmitha Halli Sudhakara, Lida Haghnegahdar

School of Cybersecurity Faculty Publications

As cyber-physical systems (CPSs) increasingly integrate physical and digital realms, securing critical infrastructure, such as the Port of Virginia, becomes paramount. Among CPSs, Unmanned Aerial Vehicles (UAVs) are vital for monitoring, communication, and supporting the command and control through remote reconnaissance and surveillance missions. These UAV applications often require coordination, planning, and runtime reconfiguration, traditionally managed by human decision-makers. However, this approach has limitations, as extensively documented in the literature. Artificial Intelligence (AI) has emerged as a pivotal tool to address these limitations, enhancing risk mitigation and informed decision-making. This research proposes a machine learning (ML) based security mechanism, leveraging …

Security Enhancement In Aav Swarms: A Case Study Using Federated Learning And Shap Analysis, Sushmitha Halli Sudhakara, Lida Haghnegahdar

School of Cybersecurity Faculty Publications

As cyber-physical systems (CPSs) increasingly integrate physical and digital realms, securing critical infrastructure, such as the Port of Virginia, becomes paramount. Among CPSs, Autonomous Aerial Vehicles (AAVs) are vital for monitoring, communication, and supporting the command and control through remote reconnaissance and surveillance missions. These AAV applications often require coordination, planning, and runtime reconfiguration, traditionally managed by human decision-makers. However, this approach has limitations, as extensively documented in the literature. Artificial Intelligence (AI) has emerged as a pivotal tool to address these limitations, enhancing risk mitigation and informed decision-making. This research proposes a machine learning (ML) based security mechanism, leveraging …

Hybrid Rans-Les Analysis Of Turbulent Flame Under Near Blow-Off Condition In A Multi-Stage Swirl Combustor, Brandon O'Brien

College of Graduate Studies: Theses & Dissertations

Advances in computational resources are making computational fluid dynamics (CFD) increasingly accessible for a variety of engineering applications. However, certain complex problems, such as simulating detailed flame kinetics, remain computationally prohibitive for many users. Developing cost-effective methods to simulate these challenges would greatly benefit applications involving flame dynamics, such as turbine engines or industrial burners. This study investigates the effect of main stage swirler intensity on near lean blow-off characteristics in a multi-staged swirl combustor using Ansys Fluent. The hybrid RANS-LES turbulence model, Stress Blended Eddy Simulation (SBES) coupled with Flamelet Generated Manifold (FGM) combustion model was selected to model …

Reactive Model-Free Control For Underactuated Vehicles Operating In Resource-Constrained Environments, Austin Lane Sponaugle

Graduate Theses, Dissertations, and Problem Reports (ETD)

Buoyancy-driven, underactuated vehicles offer a compelling solution for long-duration autonomous operations in constrained environments. By leveraging buoyancy to generate lift, these vehicles can remain aloft for extended periods with minimal power requirements, making them well-suited for applications in atmospheric monitoring, planetary exploration, and communications. However, their limited actuation authority, strong coupling with environmental forces, and operating domains introduce significant control challenges, including nonlinearity, sensitivity to external disturbances, and limited observability.

This work investigates the design and implementation of lightweight, reactive model-free control strategies that enable robust autonomy in such constrained settings. A digital Extremum Seeking Controller (ESC) is first implemented …

Evaluation Of Small Unmanned Tailsitter Hybrid Air Vehicles Via Full Flight Simulation, Andrew Spencer Winters

Graduate Theses, Dissertations, and Problem Reports (ETD)

Small Unmanned Aerial Vehicles have exploded in popularity in the past 15 years among researchers and for industrial uses such as agriculture, search and rescue, and infrastructure inspection. Fixed wing and multirotor designs present two major paths that can be taken with these technologies. Fixed wing platforms have superior aerodynamic efficiency but require large areas for takeoff/landing and cannot hold a constant position in space, limiting their use. Multirotor configurations offer a more versatile platform that can maneuver in 3 dimensions independently but lack the endurance of fixed wing vehicles. This thesis analyses a quadrotor biplane and a variable wingspan …

Novel Design And Fabrication Of A High-Speed Transient Heat Flux Sensor For Application To Rotating Detonation Engines, Zachary Todd Tallman

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rotating detonation engine (RDE) combustion systems have been a topic of interest in the pressure gain combustion community for their benefits over traditional gas turbine engine combustors. However, cooling requirements for these engines are significantly higher and less predictable than those of non-detonating engines. To understand and quantify the high-speed heat transfer dynamics within an RDE, a novel high-frequency heat flux sensor is presented. This study aims to design a robust, single-sided sensor that can withstand the high temperature and harsh environment of an RDE for extended durations. Screen printing is used to deposit a layered, platinum-yttria-stabilized zirconia (YSZ) film …

Potential Of Lidar And Hyperspectral Sensing For Overcoming Challenges In Current Maritime Ballast Tank Corrosion Inspection, Sergio Pallas Enguita, Jiajun Jiang, Chung-Hao Chen, Samuel Kovacic, Richard Lebel

Electrical & Computer Engineering Faculty Publications

Corrosion in maritime ballast tanks is a major driver of maintenance costs and operational risks for maritime assets. Inspections are hampered by complex geometries, hazardous conditions, and the limitations of conventional methods, particularly visual assessment, which struggles with subjectivity, accessibility, and early detection, especially under coatings. This paper critically examines these challenges and explores the potential of Light Detection and Ranging (LiDAR) and Hyperspectral Imaging (HSI) to form the basis of improved inspection approaches. We discuss LiDAR’s utility for accurate 3D mapping and providing a spatial framework and HSI’s potential for objective material identification and surface characterization based on spectral …

A Proximal Policy Optimization-Based Controller For Enhanced Power Sharing In Microgrids, Seyedmohammad Hasheminasab, Armin Lotfy, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

This paper introduces a Proximal Policy Optimization (PPO)-based virtual impedance (VI) controller to enhance both power sharing and system response under disturbances in inverter-interfaced microgrids. Traditional droop control methods often face challenges due to variations in feeder impedance, which degrade performance. The proposed controller continuously updates its policy based on changes in the operating environment. The control problem is modeled as a Markov Decision Process (MDP), in which the state and action spaces are explicitly defined, and a carefully designed reward function, satisfying system criteria and constraints, guides the learning process toward achieving the desired transient and steady-state performance. By …

Mars Sample Return Earth Entry System Uncertainty Analysis, Michael D. Squire, Victor Cabrera, Eric Christiansen, Alan Jenkin, Kevin Hoffman, Quincy Mckown, Peter Parker, Glenn Peterson, Bruno Victorino Sarli, William P. Schonberg, Katie Steward, Brian Tulaba, Joel Williamsen

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Spacecraft designers and operators use micrometeoroid and orbital debris (MMOD) risk assessments to predict the probability that an MMOD particle impact will cause a critical failure to their systems. An important aspect of MMOD risk and associated requirements is the treatment of uncertainty, often difficult to quantify, or even estimate, for many elements of MMOD risk. This paper describes recent efforts to estimate uncertainties in inputs to the MMOD risk assessment process for a portion of the planned Mars Sample Return (MSR) campaign. The uncertainty bounds developed were used to examine their effect on overall mission MMOD risk.

Lunar Payload Logistics: Advancing Autonomous Control For Lunar Surface Transporter Vehicles, Liam Murray

Electronic Theses and Dissertations

No abstract provided.

Investigation Of A Busemann Intake At Negative Angle Of Attack, Mark E. Noftz, Andrew N. Bustard, Nicholas J. Bisek, Thomas J. Juliano, Joseph S. Jewell

Publications

A high-speed, shape-transitioned, inward-turning intake was tested in Purdue’s Boeing/AFOSR Mach 6 Quiet Tunnel. The inlet model, called the Indiana Inlet (INlet), had a total contraction ratio of 4.68:1 and a design point of Mach 6 at 0° angle of attack. The model was outfitted with a suite of high-frequency pressure transducers, and the external flowfield was imaged with high-speed schlieren photography. The INlet was tested under low freestream disturbance levels for a variety of freestream unit Reynolds numbers and at-4° angle of attack. An unsteady shockwave near the leading edge of the inlet forebody, indicative of boundary layer separation, …