Theory & Simulation (TS) Projects

Solar Analysis

Manager: Emma Peavler – In-House & Partnership with the REA Solar Team 

Learning ObjectivesSimulation Programming (Python, Matlab, and/or Mathematica), Report Writing

Applications closed

As the effects of non-renewable energy resources (i.e. coal, oil etc) are compounding the issue of global warming, the creation of practical and manufacturable renewable energy sources is necessary for the future of humanity. This experiment group will be designing, simulating and creating solar energy storage devices using lithium ion battery cells (18650) and various solar panels. In this experiment team members will learn and use basic programming knowledge to simulate the efficiency of various solar panels and optimize a design that allows for the maximum return on investment for each solar pack. Members will also be able to engineer and build the energy storage packs for optimized use.

LabVIEW Interfacing

Manager: TBA – In-House

Learning ObjectivesLabVIEW, Measurement System Design, Sensor Control

LabVIEW programming is used to control various measurement devices such as thermocouples, photosensors, strain gauges, and potentiometers to take measurements of properties of physical systems. Team members will set up these measurement device systems and program them to take such measurements. They will then test these systems to measure temperature, light, pressure, displacement, and other properties of interest.

Cyclotron Motion Simulation

Manager: Jared Rivera – In-House

Learning Objectives: Programming (Python)

Applications Open

Cyclotron motion is the motion that charged particles undergo in a magnetic field such that they move outward in a spiral path. Team members use Python to simulate the motion of charged particles undergoing cyclotron motion. They will then apply this simulation to physical systems to predict outcomes of potential experiments, one example of which includes determining plasma wave behavior in the atmosphere using cyclotron accelerators, and another example being determining particle trajectories in a particle collider.

Particle Collider Simulation with Mathematica

Manager: TBA – In-House

Learning Objectives: Programming (Python, Matlab, and/or Mathematica), Data Analysis

Particle colliders are used to smash together particles to produce conditions similar to that of the Big Bang. Team members will use a programming language (Python, Matlab, and/or Mathematica) to simulate particle collisions that produce phenomena such as such as quark-gluon plasmas, and analyze real data from CERN. They will test this program using a particle accelerator to determine the success of the simulation.

Efficient Electricity Generation via Novel Methods

Manager: Wynne Turner – In-House

Learning Objectives: Programing (Python)

Applications Open

To meet increasing energy demands, scientists are researching electricity generation using novel methods such as thermoelectrics, photovoltaics, wave power, and other methods. Thermoelectric materials generate electricity from temperature differences between their layers, photovoltaics generate electricity using light, and wave power is a way to utilize wind waves to generate power. Team members will create simulations of these methods using Python, optimizing for maximized efficiency. These simulations can be used as a basis for actual power generators in the future.

Data Analysis

Managers: Mihai Bibireata – In-House

Learning Objectives: Solid Programming Practices, Data Visualization, Statistical Modelling

Applications Open

Project will involve analyzing and visualizing collision data from the Large Hadron Collider in the Python language. Members can expect to put one or more coding proficiencies on their resumes after completing this project. Members with substantial coding experience can furthermore expect to contribute to the machine learning aspects of the project.