Open Graduate Positions
We are currently seeking qualified and motivated individuals to join our research teams. If you are interested in exploring any of the opportunities with us, please do not hesitate to get in touch with the faculty members.
1) PRELIMINARY TOPIC TITLE: DROPLET IMPACT ONTO A SURFACE FOR CRIME SCENCE ANALYSIS
Description of the project
Pattern of blood droplet spreading and splattering in a crime scene can inform prosecutors a great deal about the weapon used and how; as well as sequence of events and the original location of the event. In this project you will analyze the way the droplets spread on various types of surface, e.g. smooth (glass), porous (e.g. carpet), etc., depending on the impact velocity and its angle. This information is then merged with the droplet flight trajectory to determine the exact location of where the blood droplets have been originated in a crime scene.
Research objective
In this project you need to accomplish the following objectives:
– Gather relevant information from the literature on crime scene blood splatter analysis methods, e.g., Ray-cone back-projection.
– Analyze the spreading pattern of the droplets impacting at different velocities and angles onto a surface by categorizing them according to the splat shape using classification tools.
– Conduct model experiments to understand the droplet spreading on different surfaces for a multi-droplet impact event.
Student profile
– Engineering (mechanical or chemical) and physics background with good computer skills.
– Familiarity with Matlab and especially its tool boxes, e.g. for classification is an asset.
– Good time management skills
– Prior working in a lab environment or experience with research projects is an asset.
– Eager to gain hands-on experience in a multi-disciplinary research environment.
– Having a scholarship or have had applied for one is an asset.
Also, due to school restrictions, the priority is with domestic students.
2) PRELIMINARY TOPIC TITLE: PHYSICS INFORMED MODELING FOR ICING OF AIRCRAFT
Description of the project
Icing is a major hazard in aviation causing flight delays and crashes. Icing also is important for wind turbine industry, as icing of blades can reduce power production by up to 20%. Traditionally, either cumbersome experimentation or complex computational fluid dynamics models have been used to study how ice accumulates on aerodynamic surfaces. In this research, the goal is to apply new methods of physics informed neural networks PINN, to model and understand the icing phenomena as an innovative approach to the icing problem.
Research objective
In this project you need to accomplish the following objectives:
– Gather relevant information from the literature on machine learning methods specifically PINN, related to fluid mechanics and phase change.
– Developing a machine learning framework informed by the fluid mechanics principles that can be used to classify and analyze the images of a freezing liquid film or revolute. For example, by enforce energy conservation and the Stefan condition to reconstruct spatiotemporal temperature, phase fraction, and free-surface shape from sparse IR/contour data or finite-volume simulations in the literature.
– Analyze the spreading pattern of the droplet (or liquid film) freezing on surfaces with a cross wind.
Student profile
– Engineering (mechanical or chemical) and physics background.
– Interest in fluid mechanics related topics, and having good marks in related courses.
– Prior experience with machine learning or good Python skills.
– Familiarity with Matlab and especially its toolboxes, e.g. for machine learning is an asset.
– Good time management skills.
– Eager to gain hands-on experience in a multi-disciplinary research environment.
– Having a scholarship or have had applied for one is an asset.
Also, due to school restrictions, the priority is with domestic students.
Contact: Alidad Amirfazli, alidad.amirfazli@lassonde.yorku.ca
Description of the project
Pattern of blood droplet spreading and splattering in a crime scene can inform prosecutors a great deal about the weapon used and how; as well as sequence of events and the original location of the event. In this project you will analyze the way the droplets spread on various types of surface, e.g. smooth (glass), porous (e.g. carpet), etc., depending on the impact velocity and its angle. This information is then merged with the droplet flight trajectory to determine the exact location of where the blood droplets have been originated in a crime scene.
Research objective
In this project you need to accomplish the following objectives:
– Gather relevant information from the literature on crime scene blood splatter analysis methods, e.g., Ray-cone back-projection.
– Analyze the spreading pattern of the droplets impacting at different velocities and angles onto a surface by categorizing them according to the splat shape using classification tools.
– Conduct model experiments to understand the droplet spreading on different surfaces for a multi-droplet impact event.
Student profile
– Engineering (mechanical or chemical) and physics background with good computer skills.
– Familiarity with Matlab and especially its tool boxes, e.g. for classification is an asset.
– Good time management skills
– Prior working in a lab environment or experience with research projects is an asset.
– Eager to gain hands-on experience in a multi-disciplinary research environment.
– Having a scholarship or have had applied for one is an asset.
Also, due to school restrictions, the priority is with domestic students.
2) PRELIMINARY TOPIC TITLE: PHYSICS INFORMED MODELING FOR ICING OF AIRCRAFT
Description of the project
Icing is a major hazard in aviation causing flight delays and crashes. Icing also is important for wind turbine industry, as icing of blades can reduce power production by up to 20%. Traditionally, either cumbersome experimentation or complex computational fluid dynamics models have been used to study how ice accumulates on aerodynamic surfaces. In this research, the goal is to apply new methods of physics informed neural networks PINN, to model and understand the icing phenomena as an innovative approach to the icing problem.
Research objective
In this project you need to accomplish the following objectives:
– Gather relevant information from the literature on machine learning methods specifically PINN, related to fluid mechanics and phase change.
– Developing a machine learning framework informed by the fluid mechanics principles that can be used to classify and analyze the images of a freezing liquid film or revolute. For example, by enforce energy conservation and the Stefan condition to reconstruct spatiotemporal temperature, phase fraction, and free-surface shape from sparse IR/contour data or finite-volume simulations in the literature.
– Analyze the spreading pattern of the droplet (or liquid film) freezing on surfaces with a cross wind.
Student profile
– Engineering (mechanical or chemical) and physics background.
– Interest in fluid mechanics related topics, and having good marks in related courses.
– Prior experience with machine learning or good Python skills.
– Familiarity with Matlab and especially its toolboxes, e.g. for machine learning is an asset.
– Good time management skills.
– Eager to gain hands-on experience in a multi-disciplinary research environment.
– Having a scholarship or have had applied for one is an asset.
Also, due to school restrictions, the priority is with domestic students.
Contact: Alidad Amirfazli, alidad.amirfazli@lassonde.yorku.ca
Project: Fused Filament Fabrication of Customized Continuous Fiber Physical Activity Enabling Prostheses for Children with Lower Extremity Amputation
Agency: NSF https://www.nsf.gov/awardsearch/showAward?AWD_ID=2508783&HistoricalAwards=false
Positions: Preference will be given to domestic students
Contact: Garrett Melenka, gmelenka@yorku.ca
Agency: NSF https://www.nsf.gov/awardsearch/showAward?AWD_ID=2508783&HistoricalAwards=false
Positions: Preference will be given to domestic students
Contact: Garrett Melenka, gmelenka@yorku.ca