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Research Opportunities

Mechanical Engineering Research opportunities

If you are interested in one of the opportunities below, please reach out directly to the faculty member listed below each project.

Strength Analysis of Carbon Fiber Composites

  • Undergraduate Research Assistant (hourly rate dependent on experience)
  • 10-15 hrs a week during the semester, full time during the summer
  • Spring/Summer/Fall 2020
  • Contact Prof. Stapleton by email: Scott_Stapleton@uml.edu

The positions are mainly supporting graduate students with their projects.  Unless specified, tasks require normal MECH knowledge and general awesomeness: responsibility, pride in your work, grit, that sort of thing.  This project is perfect for students who would be interested in eventually doing an internship with NASA or the Air Force, or would be interested in eventually applying for fellowships for graduate school.  Positions needed: 1) Experimental: chemical formulations, machining, polishing, running testing equipment, etc. 2) Simulation: run large models on commercial software, including interfacing with a high performance computing cluster (training provided).  3) Software development: requires existing proficiency in programming and the ability to design, implement, test, and maintain engineering software.

Dynamic Modeling, Analysis and Testing of Automotive Transmission Components and Subsystems

  • Research Assistant (fully funded)
  • Spring/Summer/Fall 2020
  • PhD students are preferred, but MS students with outstanding background will be considered. 
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu
The student in this position will develop analytical and computational tools for vibration/noise modeling and suppression from automotive manual and automatic transmissions. The student will develop a probabilistic dynamic model of a subsystem of a passenger car transmission operating under linear/nonlinear/stochastic dynamic excitations. The ideal candidate will have a strong interest in multibody dynamics, mechanical vibrations of discrete and continuous systems, probabilistic approaches, optimization, and Matlab programming. Experience with computer programming and graphical user interface design is preferred. This position requires a high GPA, and satisfactory GRE and TOEFL scores (International students only), work ethics, integrity, motivation and collegiality. 

Machine Learning based Optimal Sensor Placement for Aerospace Applications 

  • Research Assistant (fully funded)
  • Spring/Summer/Fall 2020
  • PhD students are preferred, but MS students with outstanding background will be considered. 
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu
The student in this position is expected to work on developing and testing machine learning algorithms for optimal sensor placement. The algorithms developed will be applied on a variety of applications related to vibrations, acoustics, and other related fields. Matlab/Python will be used to develop supervised and unsupervised machine learning algorithms for damage detection from aerospace structures and related applications using minimum number of optimally-placed sensors. The ideal candidate will have a strong interest in machine learning, probabilistic approaches, optimization, structural health monitoring, algorithm development and coding. Fluency in Matlab (and/or Python), and motivation to learn other modeling and analysis tools is preferred. This position requires a high GPA, and satisfactory GRE and TOEFL scores (International students only), work ethics, integrity, motivation and collegiality. 

Analytical and Computational Aeroacoustics for Structural Health Monitoring of Operational Wind Turbine Blades 

  • Research Assistant (fully funded)
  • Spring/Summer/Fall 2020
  • PhD students are preferred, but MS students with outstanding background will be considered. 
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu
The researcher in this position will develop and use analytical/computational aero-acoustics simulation tools to assess wind turbine blade damage using acoustic measurements/predictions. The computational tools will also be used to optimize the damage detection. Coupled fluid-acoustic and/or high-fidelity predictive tools for aero-acoustics prediction will be considered/developed/used in this research. Analytical and computational modeling will be achieved using tools that will be developed in-house by the student as well as through the use of commercially available tools such as Ansys, Comsol, etc. This student is also expected to help conduct acoustic measurements, analyze and interpret the data collected and help make design decisions related to the acoustic sensing systems. The work is predominantly geared towards wind energy and wind turbine blade structural health monitoring. However, this researcher is expected to continuously learn and help the team with other related work in the near future. The ideal candidate will have a strong interest in scientific computing, aerodynamics and/or aero-acoustics, optimization, structural health monitoring, and wind turbine hardware procurement and testing. Working knowledge of Matlab, and motivation to learn other CFD and acoustic modeling tools, and analytical modeling of acoustic sources and acoustic radiation is preferred. This position requires a high GPA, and satisfactory GRE and TOEFL scores (International students only), work ethics, integrity, motivation and collegiality. 

Acoustics-based Damage Detection from Operational Wind Turbine Blades 

  • Research Assistant (fully funded)
  • Spring/Summer/Fall 2020
  • PhD students are preferred, but MS students with outstanding background will be considered. 
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu

The student in this position will develop and test an acoustic sensor network that is needed for damage detection and identification from operational wind turbine blades. This student is expected to have, or motivated to develop, background in acoustics and vibrations, signal processing and machine learning as well as testing and data analysis. The ideal candidate will have a strong interest in data collection, analysis, and algorithm development. Working knowledge of Matlab/Python, and motivation to learn signal processing, structural health monitoring and machine learning algorithms is preferred. This position requires a high GPA, and satisfactory GRE and TOEFL scores (International students only), work ethics, integrity, motivation and collegiality.

Automotive Powertrain Dynamics

  • Undergraduate Researcher
  • Preferred Start Time: Spring 2020
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu

Structural Dynamics and Acoustic Systems Laboratory (SDASL) is looking for an undergraduate student to work on development of a user interface for the test setup using LabVIEW and helping a grad student with the experimental studies. This project will be on vibration absorber systems for automotive transmissions and requires skills and interest in (a) LabVIEW, (b) Solidworks, (c) Manufacturing and assembly of fixtures, components and subsystems,(d) Mechatronics (controlling motors etc.). 

Error control for Lagrangian-Eulerian spray simulations

  • Directed study or volunteer
  • At least 1 semester, with longer by mutual agreement
  • Graduate student/advanced undergraduate with interest and experience in numerical methods
  • Contact Prof. Noah Van Dam by email: Noah_VanDam@uml.edu

Stochastic Lagrangian-Eulerian method form the backbone of combustion application spray simulations due to their relatively low computational cost. The numerical errors and convergence properties of these mixed methods, however, has never been formally established, and there is evidence that solution errors may be larger than initially thought. This project focuses on establishing robust error convergence criteria for Lagrangian-Eulerian simulations to be used as a basis for robust error control algorithms to be developed later. This position will involve a significant amount of math and programming.

Simulations of alternative fuel sprays in the Engine Combustion Network

  • Directed study or volunteer
  • At least 1 semester, with longer by mutual agreement
  • Undergraduate or graduate looking for spray/multiphase simulation experience
  • Contact Prof. Noah Van Dam by email: Noah_VanDam@uml.edu

The student researcher will be responsible for running simulations of sprays using both standard and alternative fuels at conditions defined as part of the Engine Combustion Network (https://ecn.sandia.gov), and comparing simulation results against available experimental results and calibrating model constants as necessary. This student will focus on diesel-like sprays, collaborating with other students working on gasoline-type sprays. Simulations will be run using the CONVERGE CFD software on the Massachusetts Green High Performance Computing Cluster (MGHPCC). Help will be available get started on MGHPCC and running CONVERGE simulations. Programming experience needed to plot results.

Simulations of Fuel Sprays for Gas Turbines

  • Directed study or volunteer
  • At least 1 semester, with longer by mutual agreement
  • Graduate or undergraduate interested in CFD for aerospace applications
  • Contact Prof. Noah Van Dam by email: Noah_VanDam@uml.edu

This project develops new spray simulations of pressure-swirl atomizers for gas turbine applications. The student researcher will be responsible for setting up and running simulations of a research simplex atomizer, comparing simulation results against experimental data and tuning simulation parameters to improve the match. Simulations will be run using the CONVERGE CFD software on the Massachusetts Green High Performance Computing Cluster (MGHPCC). Help will be available get started on MGHPCC and running CONVERGE simulations. Programming experience needed to plot results.

Characterization of novel thermoresponsive fibers for lightweight smart thermal insulation

  • Full research assistant
  • January 1, 2020 – December 31, 2020
  • Ideal candidate is a master’s level student looking to complete a thesis project
  • Contact Prof. Hongwei Sun by email: Hongwei_Sun@uml.edu

The ultimate goal of the research is to enable the design of fibers with tailored coefficient of thermal expansion (CTEs) for “smart” thermal insulation applications. Fibers with a high CTE are currently being investigated for use in “smart” thermal insulation that adapts to temperature changes. The student is expected to characterize the morphology, structure and CTE of the fibers using techniques such as Differential Scanning Calorimetry, Scanning Electron Microscopy, and ThermoMechanical Analysis and develop apparatus to measure the mechanical and thermal performance of fiber battings for temperature changes ranging from 20 to -50oC. The student will work with researchers from different departments, HEROS and Fiber Discovery Center.

Computational aerodynamics/structure interaction in Bio-Inspired Flight

  • Full research assistant
  • September 1, 2019 - August 30 2020
  • Ideal candidate is a masters level student looking to complete a thesis project
  • Contact Prof. David Willis by email: David_Willis@uml.edu

The student researcher will use computational tools to understand how fluid-structure interaction impacts the generation, evolution and persistence of leading edge vortices in bio-inspired flight. The student will be expected to run existing computer code, as well as develop new computer code. Students may also integrate control into the simulations/models to determine whether wing structural compliance reduces controller complexity. Opportunities exist in this project to collaborate with researchers at other universities.

Machine Learning-Based Design and Optimization of Military Helmets

  • Full research assistant
  • September 1, 2019 - August 30, 2020
  • Ideal candidate is a masters level student looking to complete a thesis project
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu

The student in this position is expected to work on optimizing the military helmet designs by applying machine learning approaches. The ideal candidate will have a strong interest in developing software tools using Matlab and/or Python. This position requires a high GPA, work ethics, integrity, motivation and collegiality.

Damage Detection from Operational Wind Turbine Blades

  • Full research assistant
  • September 1, 2019 - August 30, 2020
  • Ideal candidate is a Ph.D. / M.S. level student.
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu

The student in this position will develop and test sensor placement and optimization related signal processing and machine learning algorithms to be used for damage detection and identification from operational full scale wind turbines. This position requires a high GPA, work ethics, integrity, motivation and collegiality.

Testing and Machine learning Code Development for Improved Exoskeleton Controls

  • Undergraduate research assistant
  • September 1, 2019 - May 15, 2020
  • Ideal candidate is a junior/senior level undergraduate student.
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu

The researcher in this position will help collect, analyze and interpret data (acceleration, pressure, and project-related physiological signals) from laboratory tests that the team will collect and leverage in developing Matlab based algorithms that will enable improved exoskeleton controls. The work is predominantly geared towards testing, analysis and interpretation of the results from the tests at the NERVE center, and at the SDASL. However, this researcher is expected to continuously learn and help the team with other related work in the near future. The ideal candidate will have a strong interest in data collection, analysis, and algorithm development. Working knowledge of Matlab, and motivation to learn signal processing, structural health monitoring and machine learning algorithms is preferred. This is an hourly position, and has flexibility to accommodate candidate’s classes, however candidates with flexible working hours are preferred. The candidates can potentially become a graduate student later on, which requires high GPA, work ethics, integrity, motivation and collegiality.

Structural health monitoring of aerospace structures operating under impact and thermal loads

  • Undergraduate research assistant
  • September 1, 2019 - May 15, 2020
  • Ideal candidate is a junior/senior level undergraduate student.
  • Contact Prof. Murat Inalpolat by email: Murat_Inalpolat@uml.edu

The researcher in this position is expected to work on data collection, processing, analysis and interpretation in the laboratory environment. The work is predominantly geared towards structural health monitoring of aerospace structures. However, this researcher is expected to continuously learn and help the team with other related work in the near future. The ideal candidate will have a strong interest in structural health monitoring, algorithm development and hardware procurement and testing. Working knowledge of Matlab, and motivation to learn signal processing, structural health monitoring and machine learning algorithms is required. This is an hourly position, and has flexibility to accommodate candidate’s classes, however candidates with flexible working hours are preferred. The candidates can potentially become a graduate student later on, which requires high CGPA, work ethics, integrity, motivation and collegiality.

Evaluation of the Mechanical Behavior of Fabric Systems for Use with a Tensile Strain Measurement System

  • 1/2 research assistant for one to two years
  • September 1, 2019 – June 30, 2021
  • Ideal candidate is a masters level student looking to complete a thesis project.
  • Contact Prof. Alireza Amirkhizi by email: emptyAlireza_Amirkhizi@uml.edu

The student researcher will use and develop experimental tensile and biaxial test equipment to characterize parachute fabrics at both quasi-static and high-speed impact. The student will be expected to gain expertise in the existing setups and work on the development of a new experimental setup. Students may also integrate simulations/models into the research investigation. This project is funded as prat of an NASA SBIR and student will have opportunities to collaborate with industry researchers.

Development of a calibration system for stereophotogrammetry measurement on large-sized structures

  • Full research assistant
  • September 1, 2019 - August 30, 2020
  • Ideal candidate is a masters level student looking to complete a thesis project.
  • Contact Prof. Alessandro Sabato by email: Alessandro_Sabato@uml.edu

The student researcher will develop a wireless sensor system (embedding a radar and an inertial measurement unit, IMU) to measure the relative position (i.e., distance and tilt/pitch/yaw angles) between a pair of cameras installed on two remotely paired unmanned aerial vehicles (UAVs). The student will be expected to refine an existing sensor board, integrate the radar unit and the IMU on a sensor board, develop computer codes for the sensors controls/operations, as well as run laboratory tests to characterize the accuracy of the developed system. The student may also integrate computer vision and digital image correlation algorithms to combine the position calculated from the sensor system with the pictures taken from the cameras to perform triangulation of the recorded images resulting in quick photogrammetry measurements of large areas, structures, and infrastructure. Opportunities exist in this project to continue as a doctoral candidate after the end of the first year.

Computational Fluid Dynamics of Plasma-on-Liquid

  • Doctoral student for three years
  • Spring 2020 start
  • Doctoral (Ph.D.), B.S. or M.S. degree in Engineering, Applied Math, Physics, or related field required.
  • Contact Prof. Juan Pablo Trelles by email: Juan_Trelles@uml.edu

To enable a future based in renewable electricity, electric power has to be efficiently directed to produce the material transformations that fuel society. Plasmas – electrically-conducting gases formed by electrical discharges – are ideal means to produce such reactivity, as amply exploited in varied applications in materials, manufacturing, and energy. An especially important research frontier is the interaction of plasma with liquids, encountered in novel applications in materials and chemical synthesis, environmental remediation, food processing, bioengineering and medicine.

The project consists on the development of a Computational Fluid Dynamics (CFD) model of plasma-on-liquid interactions. The model will be based on the TPORT code developed at UMass Lowell’s Re-Engineering Energy Laboratory (REng|Lab). TPORT is a C++ massively parallel in-house code that is been used in a wide range of fluid flow problems, especially plasma flows.

Solar-plasma system for sustainable fuels and chemicals

  • Doctoral student for three years
  • Spring 2020 start
  • Doctoral (Ph.D.), B.S. or M.S. degree in Engineering, Applied Math, Physics, or related field required.
  • Contact Prof. Juan Pablo Trelles by email: Juan_Trelles@uml.edu

The rapid increase in atmospheric greenhouse gases, especially CO2, represents one of the most pressing existential threats faced by humanity. The conversion of CO2 and other low-value feedstock into high-value compounds has the potential to mitigate environmental emission while fulfilling the global needs for fuels and chemicals. The Re-Engineering Energy Laboratory (REng|Lab) at UMass Lowell has developed novel approaches that combine concentrated solar and electrical energy for the sustainable conversion of CO2 and other chemicals into valuable products.

The project consists on the investigation of solar-enhance plasmachemical conversion of CO2, water, methane, and other gases into fuels and other valuable products.

Simultaneous Kinetics Reduction and Tabulation with Machine Learning (SKRT-ML)

  • Directed Study or volunteer
  • At least 1 semester, with longer by mutual agreement
  • Ideal candidate is an Undergraduate or Graduate with interest in machine learning and/or combustion modeling.
  • Contact Prof. Noah Van Dam by email: Noah_VanDam@uml.edu

The student researcher will run 0D and 1D combustion simulations to generate training data for a neural network-based tabulation method for chemical kinetics calculations. The student will also help train the neural network, and evaluate network performance. This project will require significant programming in Python using the Cantera and TensorFlow libraries for chemical kinetics and machine learning calculations. The student will use the Massachusetts Green High Performance Computing Cluster (MGHPCC) for all calculations.

Computational Analysis of A New Class of Chemical Potential Driven Plug Flow Membrane Reactors for Combined Gas Separation and Direct Natural Gas Conversion

  • Full research assistant for two years
  • September 1, 2019 - August 30, 2021
  • Ideal candidate is a masters level student looking to complete a thesis project.
  • Contact Prof. Xinfang Jin by email: Xinfang_Jin@uml.edu

To guide the engineering design of Potential Driven Plug Flow Membrane Reactors, we will develop a high-fidelity multiphysics model to simulate reactor’s behavior under practical operating conditions and predict PFMRs’ optimal performance. The model will couple transmembrane electrochemical CO2/O2 co-transport with surface catalytic chemical reactions. Opportunities exist in this project to collaborate with researchers at other universities.

A Multifunctional Isostructural Bilayer Oxygen Evolution Electrode for Long-Life Intermediate-Temperature Electrochemical Water Splitting

  • Doctoral Student
  • Start Spring 2020
  • Ideal candidate is a masters-level student in Engineering, Applied Math, or related field
  • Contact Prof. Xinfang Jin by email: Xinfang_Jin@uml.edu

The objective of this project is to develop multiscale Multiphysics models to understand the correlation between the electrochemical performance of the bilayer oxygen evolution electrodes and their degradation mechanisms, identify delamination and fracture failure modes, and plan mechanical failure mitigation strategies. Opportunities exist in this project to collaborate with researchers at other universities.