Faculty Mentor:  Dr. Mostafa Hassanalian, Associate Professor of Mechanical Engineering

Across millions of years of evolution, nature has developed processes, objects, materials, and functions to increase efficiency. Through biomimicry and inspiration, engineers and biologists leverage evolutionary insights to produce solutions for complex tasks in aerospace industries, such as drag reduction, locomotion, navigation, control, sensing, and drone/robot design. This research project will investigate bioinspired solutions for the development and optimization of autonomous systems for planetary exploration. The REU student will study the characteristics of natural species, such as animals, birds, or insects’ locomotion, dynamics, structure, behavior, etc., and will apply the bioinspired lessons to the design of efficient drones and robots for planetary exploration. Students will perform laboratory analyses on natural species to explore wing geometries and body structures then apply the concepts to design and prototype aerial, aquatic, or terrestrial robots including the aerodynamic structures, control systems, and operational machinery. The student will learn aerodynamics, design principles, SolidWorks software for design and 3D printing, programming for Arduino controls, and electrical circuit wiring through development of the bioinspired drones/robots. Research outcomes will include enhanced understanding of flight aerodynamics, development of novel control algorithms for the designed motive platform, and the integration of bioinspired designs to planetary exploration challenges. 

Faculty Mentor: Dr. Jamie Kimberley, Associate Professor of Mechanical Engineering 

As additive manufacturing has become more prevalent in engineering design, researchers have sought to leverage the unique capability to create complex structures not achievable by traditional manufacturing techniques.  Of particular interest are lattice structures which are capable of absorbing large quantities of energy under dynamic loading (e.g. impact) conditions. Many recent studies have focused on demonstration of the response of various lattice topologies, while very few studies have investigated the high-rate response of the constituent materials themselves. These material response data are critical for design, simulation, and optimization of novel AM structures for dynamic energy absorption.  This research project will engage the INTENSE REU participant to address this knowledge gap by conducting dynamic compression experiments on AM polymer specimens. The participant will design cylindrical specimens to be loaded at three orientations (0, 45, 90 degrees) with respect to the AM build direction. These specimens will be printed using a variety of feedstocks (e.g. PLA, PVB, ABS). Dynamic compression experiments will be conducted on the Kolsky bars in Dr. Kimberley’s research laboratory. As part of this research the REU participant will develop skills in computer modelling, 3D printing, high-speed imaging, digital image correlation, and data processing in MATLAB. Research outcomes include an improved understanding of the rate-dependent mechanical response of common AM polymer feedstocks and stress–strain data sets associated with these materials as a function of orientation relative to the build direction.

Faculty Mentor:  Dr. Michaelann Tartis, Professor of Chemical Engineering 

This research study will utilize previously developed hydrogel formulations that match the mechanical properties (stiffness) of human cranial tissues to study the role of cavitation and shear deformation in simulated traumatic brain injuries (TBI). Hydrogel formulations will be optimized to include tissue mimics for both anisotropic white matter properties and isotropic grey matter properties, for both optical and acoustic imaging during an impact of a cranial phantom in a drop tower apparatus.  Optimization for simultaneous imaging requires these materials to be transparent, contain tissue-like sound scatter, and tissue-matched attenuation. The REU student will acquire images of high-rate loading experiments using high-speed digital cameras and high-frame rate ultrasound.  To understand which impact circumstances may result in cavitation induced injuries in mild to severe traumatic brain injuries, several parameters will be varied: impact energy, head orientation, location of ultrasound transducer, soft tissue models, and 3D printed skull geometries. The student will use MATLAB and ImageJ softwares to extract cavitation event number, location, persistence, and frequency over a given time period. The student will gain experience in acquiring and quantifying image datasets using image processing.  Research outcomes will include new understanding of impact-induced traumatic brain injury conditions and insights toward mitigation methods.

Faculty Mentor:  Dr. Chelsey Hargather, Associate Professor of Materials Engineering

Additive manufacturing (AM or 3-D printing) is the process of fabricating objects by depositing layers of material.  This project focuses on adding thermite to standard 3-D printer filament to create an energetic ink. The ink could be 3-D printed onto an energetic material substrate, allowing for multi-point initiation, user-imposed control of the burn rate, and/or burn profile modification in the energetic substrate.  Current research has demonstrated printing of an ABS filament with 20% Ba(NO₃)₂ (barium nitrate) + Al thermite into combustible geometries as shown in Figure 4.  The INTENSE REU participant will engage on this project by creating custom 3-D printer filament using a Filabot EX2 filament extruder, exploring variables to enhance and tailor the energy release. A test matrix with variables including base filament material, thermite system, mass loading, and burn rate enhancer addition will be explored. Upon extrusion, the consistency of the material, in terms of filament diameter, will be evaluated for each material system.  The best performing materials will be printed using a standard commercial 3-D printer (e.g. Prusa or Artillery) for characterization of burn rate and mechanical properties (e.g. tensile strength) of the 3-D printed samples.  The REU participant will test the effectiveness of these energetic inks at initiating an energetic substrate through supervised combustion testing. The REU participant will learn materials selection and design techniques through the generation and testing of the systems in the materials matrix.  Skills in planning and safely executing combustion testing, as well as materials characterization will be developed by the REU student. Research outcomes include development of printability maps for thermite mixtures and insights for a priori materials property estimation for compositions based on material composition. 

 Faculty Mentor:  Dr. Curtis O'Malley, Assistant Professor of Mechanical Engineering

Faculty Mentor:  Dr. Andrei Zagrai, Professor of Mechanical Engineering

The dramatic increase in the number, nature, and operators of space missions in recent years reinforces the need for techniques and methods to assess and qualify the structural integrity of a vehicle or payload through all stages of spaceflight from launch to orbit to re-entry.  NMT has developed structural health monitoring techniques using electro-mechanical impedance of active piezoelectric sensors through undergraduate design teams and graduate research projects.  The developed systems and experiments have been tested on high altitude balloon and suborbital rocket flights.  The student performing research on this project will perform ground-testing of structural health monitoring systems investigating the integrity of structural joints.  The goal of the project is to determine characteristic electro-mechanical impedance signatures of bolted and welded joints in pristine and “damaged” conditions to train intelligent algorithms to detect damage anomalies.  The project will utilize previously developed hardware, as shown in Figure 5, and the student will construct their own test setups for the joint testing.  The student will be exposed to the science of vibrations and signal processing as well as the technology of piezoelectric and acoustic sensors.  Research outcomes include an understanding of system vibrational response change as a function of various damage states including weld failures or loose bolts