Mechanical Engineering 2018 SURE and SROP Research Projects

ME Project #1: 3D-Printing of Prosthetic Sockets                                                     
Faculty Mentor: Albert Shih,                                                         
Project Details: This project explores the use of fuse deposition modeling (FDM), one of the additive manufacturing methods, for 3D-printing of carbon fiber composite socket. The project works closely with the University of Michigan Orthotics and Prosthetics Center with the goal to develop design and manufacturing methodologies for a new service system for rapid turn-around and high-quality 3D-printing of custom socket that will have personalized fit and comfort to the residual limb. Contact modeling based on the computed tomography (CT) image of the residual limb will be analyzed to design the geometry of the prosthetic socket. This project will also work closely with Stratasys, a partner and world leader in FDM technology, and Altair, a software company on specialized in cyber design and service.

ME Project #2: Computer Modeling of Novel Materials for Energy Application
Faculty Mentor: Don Siegel,
Project Details: This SURE/SROP project will apply state-of-the-art computational modeling to predict and understand the properties of new materials for various energy-related applications. Specific areas include: (i) high-capacity energy storage materials for applications in transportation (fuel cell and battery electric vehicles) and renewable energy generation (wind and solar); (ii) Materials for CO2 capture; (iii) Lightweight structural alloys. We use state of the art high-performance (parallel) computers and algorithms to model the atomic scale properties that determine the performance of novel energy storage materials. The SURE/SROP student will develop a detailed understanding of a particular energy-related application. They will also gain expertise with the importance & capabilities of computer modeling in modern materials science research.

ME Project #3: Intelligent 3D Printers for Next Generation Manufacturing
Faculty Mentor: Chinedum Okwudire,
Project Details: This project seeks to develop intelligent 3D printers that enable more flexibility and ease in printing of personalized products by unskilled users. Student will study existing 3D printers and come up with ways of re-designing them for versatility, improved performance and ease of use. Student must have very strong design acumen, and experience with micro-controllers and 3D printing.

ME Project #4: Challenges and Opportunities for Desktop 3D Printing in Developing Countries
Faculty Mentor: Chinedum Okwudire,
Project Details: This project seeks to explore various challenges and opportunities in utilizing desktop 3D printing to create meaningful products and employment in developing countries. Student will study existing uses of desktop 3D printers in industrialized and developing countries, and come up with a comprehensive report of challenges and opportunities for developing countries. Student may have the opportunity to visit a developing country as part of this study. Student must have a demonstrated passion for design,manufacturing and sustainable development. Prior experience living in a developing country is a plus.

ME Project #5: Plasma-catalyst for NOx Reduction                                                   
Faculty Mentor: John Hoard,
Project Details: We are working with a major automotive supplier to investigate a nonthermal plasma discharge device along with a catalyst for NOx control in automotive exhaust. The student should have an interest in engines, emissions, and catalysis.

ME Project #6: Engineering Cell Free Expression System for Biomedical Applications
Faculty Mentor: Allen Liu,
Project Details: The overall goal of this project is to develop cell free expression system for producing protein of interests inside lipid bilayer vesicles for biomedical applications. The student will learn and apply capillary droplet microfluidics to assemble lipid bilayer vesicles that encapsulate an in vitro transcription-translation system. We are interested in engineering several membrane channels and reporter proteins to study the input-output relationship. These have potential for creating artificial cells that have biosensing capabilities.

ME Project #7: Model, Measurements, Management of Fuel Cells, Batteries, and Engines
Faculty Mentor: Anna Stefanopoulou,
Project Details: Investigating methods and developing tools for control of a hybrid (switching) power system, for example robots or cars powered from a fuel cell and a battery and the optimization of their switching under a stochastic or partially-known terrain. Students will learn and try modeling, identification, estimation, and optimal control. Software tools such as Matlab and Simulink simulations are our bread & butter. For the fearless we also offer experiments with blasting batteries, generating hydrogen, and supercharging engines. For the folks, that love “paper & pencil” problems we take deep dives in strange, and sometimes esoteric quests in convergence, identifiability, and uncertainty in our models. Important qualifications: 1) Ability to work in interdisciplinary research with a large team of professors, students, industrial collaborators, and scientists. 2) Dexterity in processing data and 3) Strong motivation in experimentally implementing and verifying your dream power system.

ME Project #8: Freezing Sesile Droplets
Faculty Mentor: William Schultz,
Project Details: A freezing water drop sitting on a cold surface creates a cusp at the symmetry axis to resemble a ‘Hershey’s Kiss”. This is caused primarily by the expansion of water upon freezing, but also the tri-phase boundary conditions. This shape is important for many situations including icing on airplane wings. A manuscript is near completion using a boundary integral method. We need to make a simple conversion to the code and run some more cases to finish the manuscript. Collaborators include Grae Worster (U. Cambridge) and Dan Anderson (George Mason U.).

ME Project #9: Oscillatory Contact Lines
Faculty Mentor: William Schultz,
Project Details: The contact line is where a liquid-air interface intersects a solid surface.  When the liquid is relatively inviscid (like water), the motion of this line is often responsible for most of the fluid damping. A nearly finished manuscript measuring and modelling this behavior need some important but straightforward changes. Collaborators include Marc Perlin (TAMU).

ME Project #10: Finite Element Head Modeling for Assessment of Concussion Considering Human Variability
Faculty Mentor: Jingwen Hu,
Project Details: Sport-related concussion is a major public health problem worldwide. Current diagnostic practices typically depend solely on neurological examinations and subjective symptom reporting. Finite element (FE) human models have the potential to better estimate tissue-level brain responses than any other existing biomechanical tools. However, current FE human head models were primarily developed and validated for midsize men, and yet significant morphological and biomechanical variations exist in human skull and brain. The goals of this study are to develop parametric head FE models accounting for the geometric variations in the population, and to conduct a feasibility study using population-based simulations to evaluate the influence of head morphological variation on brain tissue strain. Specifically, in this study, students will use medical image analysis and statistical methods to quantify the geometric variance of the skull and brain among the population; use mesh morphing methods to rapidly morph a baseline head FE model to a large number of head models with a wide range of head size and shape for both males and females; and conduct impact simulations with those models.

The student who will undertake this project is expected to be proficient in Matlab programming, familiar with finite element simulations, and interested in injury biomechanics research. He/she will build a Matlab program to automatically generate diverse head models and conduct population-based FE impact simulations.

ME Project #11: The Biophysics of Embryo Development
Faculty Mentor: Krishna Garikipati,
Project Details: In this project, you will have the opportunity to apply physical principles, such as mechanics and diffusion to study how an embryo develops. Mechanics (elasticity) is relevant to the packing of an increasing number of cells (initially in powers of 2: 1, 2, 4, 8, 16,…) in the embryo, as well as to the compaction of the cells. The latter phenomenon is critical to the differentiation of the embryonic cells into the germ layers that are the scaffolding upon which the organism’s body develops. Diffusion is important to the supply of nutrients to the developing embryo.

Student responsibilities: In your studies of these problems, you will make use of scientific software to model the above physical processes by running large scale computations, analyzing the data. If we make rapid progress in these studies, you also may have the opportunity to further develop the models and the computer code.

ME Project #12: Building Better Batteries: Beyond Li-ion
Faculty Mentor: Jeff Sakamoto,
Project Details: In order to meet the needs of electric vehicles, advanced battery technologies must be developed. This project is focused on developing solid state battery prototypes which would be 2x better compared to current Li-ion batteries. The project is team oriented and fast paced. Students will perform ceramic materials synthesis, processing, chemical modification, materials chemistry characterization, mechanical properties characterization, and battery testing. Work will be performed at the Sakamoto lab in GG Brown and in the Battery Lab at the UMich Energy Institute. The project is ideal for students planned degree path in materials science, mechanical engineering, chemistry, and chemical engineering. Students will work closely with other undergraduate students and post-docs to make and evaluate batteries as a part of a team. The project is hands on and students will see the entire process through: from making powders, to designing experiments, to using equipment like electron microscopes, to fabricating batteries.

ME Project #13: Quantitative Analysis of High-Speed Infrared Combustion Imagery
Faculty Mentor: Michael C. Gross,
Project Details: An ongoing research project is investigating the impact of ignition technologies, air/fuel mixture, and other variables on combustion in heavy-duty engines fueled by natural gas. In this project, we record high-speed infrared images of ignition and flame-kernel growth using borescopes inserted into an internal-combustion engine. These images are processed for clarity and then analyzed in order to derive quantitative metrics. The images and image-derived metrics are correlated with metrics derived from in-cylinder pressure measurements and used to understand combustion and improve future engine design. The undergraduate student will support the graduate student on the project by processing and analyzing images that have already been recorded, developing new quantitative metrics, and correlating these metrics with pressure-derived metrics. This work will give the undergraduate student experience conducting research, allow the student to work closely with both graduate students and faculty, and expose the student to new knowledge of both combustion and image processing.
Requirements: The student must be competent with MathWorks MATLAB and Microsoft Excel. Prior experience with image or data processing in MATLAB or another similar computing environment is preferred.

ME Project #14: Engaging People to Define Problems and Develop Design Solutions in Front-end Engineering Design
Faculty Mentor: Shanna Daly,
Prerequisites: Background and interest in design
Project Details: How can designs truly incorporate user’s needs into their design decisions? And, how do designers identify the best design problems to solve in the first place? We are conducting research examining how students and professional engineers explore potential problems to solve and how they interact with people throughout their decision processes and use that information to make design decisions. We are investigating (a) how designers engage with users as they define problems and develop solutions, (b) design strategies novices and experts use in understanding problems, and (c) design tools that can support best design practices in defining the best problems to pursue and incorporating user feedback in developing design solutions. UROP students on our projects will be involved in collecting, organizing, and analyzing data. Researchers will gain hands-on experience in how to do research in engineering design and learn about best practices for front-end design processes.

ME Project #15: Using Bio-logging and Wearable Sensing to Measure Movement in the Real World
Faculty Mentor: Stephen Cain (, Kira Barton (, K. Alex Shorter (
Project Details: The study of human movement and sports performance tends to be limited to controlled experiments conducted in laboratory settings. More recently, advancements in wearable sensors have created the potential to make meaningful measurements of human physiology and movement outside of laboratory settings. Our research team is working to utilize these new technologies by developing the creation of the hardware and analysis algorithms that will enable the study of biomechanics in the real world. For this work we are using a system of body worn sensors that measure movement (accelerometers, magnetometers, gyroscopes) and physiology (heart rate, respiration rate, body temperature) during indoor and outdoor activities. This system will be used to enable the experimental investigation of activity and frailty in at-risk populations and to quantify athletic performance during training and competition. The SURE/SROP student will help run experiments to validate this system with healthy patient subject populations, as well as help analyze the collected data.
Experience with human research, motion data analysis in programs such as Visual 3D, and/or signal processing experience using MATLAB is a plus.

ME Project #16: Connected Testbeds for Connected Automated Vehicles
Faculty Mentor: Tulga Ersal,
Project Description: Connected testbeds, i.e., remotely accessible testbeds integrated over a network in closed loop, will provide an affordable, repeatable, scalable, and high-fidelity solution for early cyber-physical evaluation of connected automated vehicle (CAV) technologies. Engineering testbeds are critical for empirical validation of new concepts and transitioning new theory to practice. However, the high cost of establishing new testbeds or scaling the existing ones up hinders their wide utilization. Enabling high-fidelity cyber-integration of existing but geographically dispersed testbeds can dramatically increase accessibility to engineering experimentation, just as the internet dramatically increased accessibility to information. This project aims to develop a scientific foundation to support this vision and demonstrate its utility for developing CAV technologies.