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Summer Undergraduate Research in Engineering (SURE)

SURE offers summer research internships to outstanding current U-M undergraduate students who have completed their sophomore or junior year (preference will be given to those who have completed three years of study) by the time of their internship.  Participants have the opportunity to conduct 10-12 weeks of full-time summer research with some of the country’s leading faculty in a wide range of engineering disciplines. The program provides opportunities for students to assess their interests and potential in pursuing research at the Masters or Ph.D. level in graduate school.  All participants must apply online through the SURE website.  Accepted applicants from the University of Michigan receive guidance by a faculty advisor in a College of Engineering research facility, a stipend of $5,000, attend regular meetings and seminars and contribute to an abstract booklet with highlights of their summer research project and/or experience.

Selection Process: Once the SURE Manager has shared your application with the Department, we will provide the eligible applications to the Faculty Mentors who will review your application materials. It is possible that they will reach out to you directly for further information. You do not need to do anything else, but if you have any specific questions regarding a SURE Project, you are welcome to reach out to the listed Faculty Mentor. Any notification of an offer will be sent from the SURE Manager, Shira Washington.

General Timeline:
January – Application is due
February – Applications are reviewed
March – Offers will begin being sent out
April – Offers may still be issued during this time
May – SURE Projects may begin

Learn more: https://sure.engin.umich.edu/

The SURE Application is now CLOSED for 2022.

Mechanical Engineering 2022 SURE Research Projects

 

ME Project #1: 3D-Printing of Custom Assistive Devices

Faculty Mentor: Albert Shih, shiha@umich.edu
Project description: This project explores the use of 3D-printing (also known as additive manufacturing) for custom assistive devices to improve the quality of care for people with disabilities. The project works closely with the University of Michigan Orthotics and Prosthetics Center (UMOPC) with the goal to develop design and manufacturing methodologies for a new service system for rapid turn-around and high-quality 3D-printing of assistive devices that will have personalized fit and comfort. Such assistive devices include lower and upper limb prosthesis, orthoses for diabetes partial foot amputees, ankle-foot orthoses for stroke patients. Contact modeling based on computed tomography (CT) or 3D scanning images will be developed to design the geometry.
Research Mode: In-Lab

 

ME Project #2: Automatic Fault Detection for 3D Printing

Faculty Mentor: Chinedum Okwudire, okwudire@umich.edu
Project description: The student working on this project will help develop an algorithm for automatic detection of failures and faults in 3D printing using low-cost sensors. The ideal student should be very skilled in CAD software, MATLAB and C++ (or Python), and enjoy coding. Some familiarity with machine learning and 3D printing is a plus. The student will get to implement and test their algorithms on 3D printers.
Research Mode: In-Lab, Hybrid, Remote

 

ME Project #3: Engineering a Synthetic Biology Platform for Reconstitution of Ion Channels

Faculty Mentor: Allen Liu, allenliu@umich.edu
Project description: Building synthetic cells is an exciting area of synthetic biology with opportunities to unravel basic design and organizational principles of cellular life. Besides a cellular reconstitution approach of using purified protein components, the current paradigm in the construction of a bottom-up synthetic cell system involves exploiting cell-free expression systems and synthetic lipid bilayers to create active membranes. To recreate complex cellular events in synthetic cells, the Liu lab and his collaborative team have identified ion channels as highly interesting membrane proteins that are involved in several important cellular processes including action potential generation. In this project, we will study the reconstitution of ion channels in lipid bilayers using a mammalian cell-free expression system and investigate their function by utilizing electrophysiological techniques. As part of the team, the student involved will be offered an opportunity to learn various molecular biology techniques, basics of tissue culture, and electrophysiology. Candidate with interests in biology and hands-on lab work is highly desirable. Basic knowledge in chemistry and molecular biology is a plus.
Research Mode: In-Lab



ME Project #4: Simulation of Off-road Autonomous Vehicles

Faculty Mentor: Bogdan I. Epureanu epureanu@umich.edu Lab: Applied Nonlinear Dynamics of Multi-Scale Systems
Prerequisites/desired background:

  • Programming familiarity with C++ and Python
  • Experience programming in both Windows and Ubuntu environments
  • Experience with Unreal Engine 4 (UE4) is desirable
  • Basic knowledge of Robot Operating System (ROS) and MATLAB
  • Basic knowledge of CarSim or PhysX

Project Description: In this project, students will assist us in our development of a high-fidelity automotive simulation built with Unreal Engine 4. At a high-level, we are building an off-road simulation in which multiple users (human players) can interact with multiple virtual vehicles. Each vehicle will have a sensor suite (camera, LiDAR, IMU, and radar), and will have various control and perception algorithms so they can navigate autonomously in the environment.
Tasks will be defined periodically, and may include:

  • Creating algorithms and programming landscapes in UE 4, which include modeling the terrains, creating materials using multiple textures, and applying these to the landscape. Testing new features in a virtual environment under development
  • Testing VR integration with a virtual environment under development
  • Implementing control/perception/navigation algorithms using UE4 blueprinting, C++, Python
  • Integrating control/perception/navigation algorithms with UE4 using ROS communication
  • Modifying vehicle physics properties using CarSim or PhysX
  • Developing automated data collection capabilities
  • Exploring platooning of vehicles in UE4 by simulating chains of vehicles that follow each other and move on a predetermined path within UE4.

Research Mode: Hybrid or Fully Remote

 

 

ME Project #5: Immersive Environment for Autonomous Vehicles using Unreal Engine Simulations

Faculty Mentor: Bogdan I. Epureanu epureanu@umich.edu Lab: Applied Nonlinear Dynamics of Multi-Scale Systems
Prerequisites/desired background
:

  • Programming familiarity with C++ and Python
  • Experience programming in both Windows and Ubuntu environments
  • Experience with Unreal Engine 4 (UE4)
  • Basic knowledge of Robot Operating System (ROS) and MATLAB
  • Experience with image processing and video systems highly desirable

Project Description: In this project, students will assist us in the development of a high-fidelity automotive simulation built with Unreal Engine 4. At a high-level, we are building an off-road simulation in which multiple users (human players) can interact with multiple virtual vehicles. We are also building a new lab to help us realize this entire simulation and provide an immersive experience for the user. In this new facility, we will be displaying the simulation on a large LED video wall. Students will assist in configuring an existing environment to visualize our simulation on the video wall.
Tasks will be defined periodically, and may include:

  • Adding capabilities in UE4 to our simulation platform to render scenes on a video wall
  • Testing the simulation with the video wall
  • Testing new features in a virtual environment under development
  • Testing VR integration with a virtual environment under development

Research Mode: Hybrid or Fully Remote

 

ME Project #6: AI-Based Interaction of Autonomous Agents and Humans in Synthetic Environments

Faculty Mentor: Bogdan I. Epureanu epureanu@umich.edu Lab: Applied Nonlinear Dynamics of Multi-Scale Systems
Prerequisites/desired background:

  • Programming familiarity with C++ and Python
  • Experience programming in both Windows and Ubuntu environments
  • Experience with Unreal Engine 4 (UE4) is desirable
  • Basic knowledge of Robot Operating System (ROS) and MATLAB

Project Description: In this project, students will assist us in our development of an interface connecting a virtual gaming environment in Unreal Engine to a team of autonomous and human agents/players. In particular, given existing plugins such as high-level task distribution algorithms, path planning algorithms, autonomous agent control algorithms, the desired interface is able to provide visual image, extract essential data (state of the operation, state of the agent, etc.), broadcast information through a communication channel to other players, and exchange information. The developed interface is used for human players to collaborate with autonomous agents in the virtual environment to perform an operation and achieve a defined common mission goal.
Tasks will be defined periodically, and may include:

  • Creating VR, integration with a virtual environment
  • Implementing control algorithms using UE4 blueprinting C++, Python
  • Integrating control algorithms with UE4 using ROS communication
  • Developing automated data collection capabilities

Research Mode: Hybrid or Fully Remote


ME Project #7: Biomechanical Modeling and Experimental Evaluation of Lower Limb Exoskeletons

Faculty Mentor: Robert Gregg, rdgregg@umich.edu
Project Description: This project has 3 main parts. The first part of this project involves biomechanical modelling in  OpenSim (a popular open-source program) and Matlab of the effect of powered lower-limb orthoses on muscle activity, joint loads and metabolic cost. Various exoskeleton assistance strategies can be explored for different activities of daily living. The second part involves performing human subject experiments using our two prototype exoskeletons. This will primarily involve the use of a 3D  motion capture system (Vicon) and electromyography system. Motion capture will require learning the high level operations of the data capture and pre-processing software (Nexus) and customizing of standard biomechanical models to suit the experimental objective. Post processing of the data will be performed in Matlab. The final part will involve CAD design and 3D printing of exoskeleton attachment revisions based on user feedback.
Research Mode: In-Lab

 

ME Project #8: Computational Studies of Bubble Collapse

Faculty Mentor: Eric Johnsen, ejohnsen@umich.edu
Project Description: The goal of this project is to computationally investigate the potential damage produced by collapsing cavitation bubbles. This research is motivated by cavitation erosion observed in naval hydrodynamics (e.g., propellers) as well as deliberate damage produced by ultrasound-induced cavitation to destroy pathogenic tissue. The student will use an in-house code to conduct the numerical simulations. The project may additionally include opportunities to develop reduced-order, data-driven models of collapsing bubbles.
Research Mode: In-Lab or Remote

 

ME Project #9: Shape Memory Alloys for Gripping Middle Ear Prostheses

Faculty Mentor: Karl Grosh
Prerequisites: completed sophomore classes
Project Description:  The middle ear bones are the smallest bones in the human body (1 millimeter in diameter and ~10 millimeters long).  These bones are responsible for transmitting sound from the outer ear to the fluid-filled  cochlea which then sends signals to the brain.  Over 360 million people worldwide and 30 million people in the US suffer from significant hearing loss (loss that affects their daily life), and auditory prostheses (hearing aids and cochlear implants) make a significant difference in people lives.  We have a project to build ultraminiature and lightweight (less than 10 milligrams – lighter than a rice grain) accelerometers that fit on the middle ear bones to enhance the safety, usability, and comfort of auditory prostheses..  Our work in fabricating the acclerometers is progressing with benchtop and human testing underway, but we need a robust way to hold the accelerometer and attach it to the middle ear bones.  In this SURE project, we explore the design and manufacture of tiny grips, related to some already used in middle ear bone (ossicular) replacement surgery, like Grace Medical’s Megerian Nitinol SRP, are contemplated; however our needs are different and a modified approach is indicated.  Interaction with engineering and medical school faculty are planned.
Research Mode: In-lab and online

ME Project #10: Energy Boundary Conditions for CO2 Capture and Utilization

Faculty Mentor: Volker Sick, vsick@umich.edu
Prerequisites: Fundamentals of thermodynamics
Project Description: Outline basic material and energy requirements using stoichiometry and enthalpies for CO2 Capture and Utilization reactions in order to understand the minimum theoretical energy needs for CO2-based products. This study will categorize classes of products and rank them based on their respective energy demands. The analysis objectives are to create a reference document as part of a published paper and/or online database.
Research Mode: Hybrid with preference for in-person



ME Project #11: Investigating motion sickness response of human subjects using an instrumented test vehicle operated on a closed test track (MCity)

Faculty Mentor: Shorya Awtar
Prerequisites: Candidates should meet the following prerequisite criteria: (1) Proficiency in programming and statistical data analysis using Python, MATLAB, (2) Background in Mechatronics covering practical aspects of modeling mechanical and electrical systems, control theory, sensors & actuators, (3) Proficiency in engineering design and analysis tools such as SolidWorks, Simulink, and (4) demonstrated interest and prior activities in applied engineering including hardware design, machining, fabrication, etc.
Project Description: The aim of this project is to support human subject investigations to study the
motion sickness response of subjects when seated in a test vehicle and driven around a closed test track. The research involves studying the motion sickness response when using haptic active passenger stimuli (i.e., vibrating seat) that provides informative stimuli, and using an active seat (i.e., seat that can tip and tilt). The project also includes designing an active restraint system. Students working on this project will have an opportunity to develop and hone mechatronic skills, learn experimental design and data analysis, and participate in closed track testing as drivers or field researchers. Students will receive training on driving the test vehicle to follow a designed path for the experiments. Students will also receive training on how to interact with human subjects during the study. The students working on this project will be responsible for (1) design and analysis of active restraint system, (2) Experimental design and data collection, (3) Experimental data analysis, and (4) All documentation and reports associated with research investigations.
Research Mode: Hybrid work (approx. 60% In-person, 40% remote).



ME Project #12: Radiative Property Measurements for High-Temperature Energy Applications

Faculty Mentor: Rohini Bala Chandran
Project Prerequisites: Candidates should have had an introduction to heat transfer (ME 335) and experience with processing large datasets in MATLAB. Lab courses covering basic measurement techniques and optics will be considered a plus.
Project Description: The performance of renewable energy technologies like particle-based concentrated solar power (CSP) with thermal energy storage (TES) relies on the optical (or radiative) properties of the flowing medium used to absorb, store, and transfer the heat into its application (power cycle, industrial process, etc.). The goal of this project is to quantify the temperature-dependent radiative properties of potential heat transfer media for high-temperature (> 700°C) applications over a wide spectral range. Students will have a hand in (1) sample preparation, (2) developing a setup and procedure for measuring radiative properties for a variety of materials, and (3) data processing and analysis. Candidates with an interest in hands-on and challenging experimental work are preferred.
Research Mode: In Lab

 

ME Project #13: High-performance computing for modeling thermal radiation in solar energy applications

Faculty Mentor: Rohini Bala Chandran
Project Prerequisites: Candidates should have had an introduction to heat transfer (ME 335) and must have prior experience in using C++ and other programming languages such as MATLAB/Python. Prior experience with running computational jobs on clusters, GPU-based computing, data-driven modeling will be considered a plus. Project will be well-suited for both mechanical engineering and computer science undergraduate students 
Project Description: Modeling radiative transport in particulate media such as packed beds, fluidized gas-solid flows, porous foams and granular flows is a complex, multidimensional problem. Radiative exchange in such media will be dictated by its morphology (pore size and porosity), temperature, wavelength, and optical properties. The goal of this project is to leverage existing computational tools (built in C++) in our group to further develop them into high-performance codes. Students will lead the development of (1) parallelized stochastic simulations for radiative transport using MPI packages, (2) run and test these codes on high-performance clusters (Great Lakes at UM), and (3) also explore the use of GPUs to further enhance the computational efficiency of radiation modeling.  Students will have the opportunity to closely work with two senior graduate students in our research group. Candidates for this project should be interested in code development and design.
Research Mode: In-person/Virtual/ Hybrid

ME Project #14: Predicting Bio-Nano Interactions with Molecular Dynamics and Machine Learning

Faculty Mentor: Angela Violi, avioli@umich.edu
Project Prerequisites: Students should be familiar with Python language, have an understanding of machine learning and some of the libraries (e.g. Tensor Flow, Keras, Pytorch) and knowledge of physical science. Experience with molecular simulations would be helpful.
Project Description: One of the challenges of understanding biological interaction is properly being able to predict when these interactions occur. Recently machine learning has emerged as an important technique towards these predictions. Successful prediction depends on both the representation of the biological molecules and the algorithm. This project will involve a computational study of biological systems, such as proteins and membranes, using molecular dynamics simulations and the use of machine learning tools. The student will be part of a team working on prediction algorithms and molecular simulations with the goal of identify nanomaterials for biological applications.
Research Mode: In-person or remote

ME Project #15: Digital Animations to Fight Antimicrobial Resistance

Faculty Mentor: Angela Violi, avioli@umich.edu
Project Prerequisites: Students should have relevant technological expertise in digital animation, which might include programming, gamification, etc.
Project Description: We are interested in developing interactive, digital animations showing how bacteria and biofilms behave and how perturbations, like nanomaterials, alter their function. Students will review content with team experts in biology and work collaboratively to design an online, interactive animation that students can use to better understand the use of nanotechnology to combat antibiotic resistant infections.
Research Mode: In-person or remote

ME Project #16: Synthesis of Nanomaterials in Plasma Conditions

Faculty Mentor: Angela Violi, avioli@umich.edu
Project Prerequisites: Students should be familiar with Python, molecular simulations, have knowledge of physical science. An understanding of machine learning is beneficial.
Project Description: Nonthermal plasma represent a unique and powerful environment to synthesize materials with unique properties. Indeed, the nonequilibrium environment in nonthermal plasmas has a number of attractive attributes: energetic surface reactions selectively heat the nanoparticles to temperatures that can strongly exceed the gas temperature; charging of nanoparticles through plasma electrons reduces or eliminates nanoparticle agglomeration; and the large difference between the chemical potentials of the gaseous growth species and the species bound to the nanoparticle surfaces facilitates nanocrystal doping. The goal of this project is to study the mechanisms of formation of nanomaterials using computational approaches based on molecular simulations and machine learning. The student will be part of a multidisciplinary and multi university team that combines effort in modeling and experiments.
Research Mode: In-person or remote

ME Project #17: Engineering Electrodes and Electrochemical Flow Cells for CO2 Capture

Faculty Mentor: David Kwabi, dkwabi@umich.edu
Prerequisites/desired background: Organic Chemistry, Thermodynamics, Electrochemistry, MATLAB/Python
Project Description: Large-scale CO2 separation and concentration from point sources, seawater and the atmosphere can play key roles in mitigating climate change and promoting the conversion of CO2 into chemical fuels and high-value products. Electrochemical CO2 separation processes have the potential to be more cost-effective than conventional thermal analogues if they use inexpensive active materials and are sufficiently energy-efficient. The aim of this project is to functionalize porous carbon electrodes with organic acid/base groups and deploy them in electrochemical flow cells capable of separating CO2 from seawater or emissions from fossil fuel-burning plants using a pH swing cycle. The experimental work will be coupled with modeling to understand the various thermodynamic and kinetic factors that contribute to the electrical energy consumed per unit of concentrated CO2 (kJ/molCO2), which is a critical figure of merit for practical systems.
Research Mode: In lab/hybrid

ME Project #18: Droplet Motion on Lubricated Surfaces

Faculty Mentor: Solomon Adera, sadera@umich.edu
Project Description: Controlling the motion of water droplets on surfaces has broad technological
implications ranging from microfluidics to thermal management. Past approaches utilized gradients in topography, temperature, chemical composition, surface tension, and/or a combination thereof to actively
control and manipulate droplets on solid surfaces. In this work, we utilize asymmetry of the wetting ridge
that accompanies droplets on lubricated surfaces to trigger and manipulate their motion.
Research Mode: In lab