Multiphysics Model of an Inductive Conductivity Sensor - ON-236

Preferred Disciplines: Physics, Applied Mathematics, Engineering Physics (Masters level)
Company: RBR Ltd.
Project Length: 12-18 months
Desired start date: September 2019
Location: Ottawa, ON
No. of Positions: 1
Preferences: University of Ottawa or Carleton University

About the Company: 

Since 1973, RBR has been designing and manufacturing oceanographic instruments to measure the blue planet. From the ocean abyss to the polar ice cap, our sensors track water parameters such as temperature, depth, salinity, dissolved gases, and many others. RBR equipment enables researchers to develop innovative measurement solutions that are deployed in the surf zone, mounted on underwater drones, dropped out of planes, towed behind boats, and sent to the bottom of the deep, dark ocean.

Project Description:

RBR designs and manufactures inductive conductivity sensors for measuring the salinity of natural waters.  The scientific community requires very high accuracy salinity measurements in all conditions of salinity, temperature, pressure, flow velocity, and proximity to other objects, encountered in the oceans.  The theoretical operating principles of the sensor are insufficient to predict sensor response at high precision and accuracy over the full range of independent variables, and therefore sensor calibration requires numerous reference points across several dimensions to develop multivariate fitting formulas. 

The goal is to develop a multiphysics model of the inductive conductivity sensor that predicts the effects of environmental conditions on the sensor response, to improve the efficiency of production calibration and of development of design improvements.

Research Objectives:

  • Develop a multiphysics model of the inductive conductivity sensor that predicts the effects of environmental conditions on sensor response.
  • Validate the model to predict effects of a mechanical design change, such as a change in the sensor body material.
  • Validate the model to predict a class based pressure compensation formula.
  • Validate the model to predict the effect of a body in proximity to the sensor, such as a change in the shape of an autonomous vehicle on which the sensor is mounted.

Methodology:

  • Using Comsol, develop a multiphysics model of the inductive conductivity sensor including the electromagnetic, mechanical, thermal, and kinematic properties of the sensor, sensor platform, and medium.
  • Collect experimental data from tests with a sensor prototype to validate the model:
    • to predict effects of mechanical design changes;
    • to predict pressure dependence;
    • to predict the effect of a body in proximity to the sensor.

Expertise and Skills Needed:

  • Electromagnetic theory, classical mechanics, thermodynamics, strength of materials, stress analysis, calculus (differential and partial differential equations), numerical analysis, statistics.
  • Programming and data analysis using Matlab.
  • Modeling and simulation using Comsol.
  • Written communications.

For more info or to apply to this applied research position, please

  1. Check your eligibility and find more information about open projects
  2. Interested students need to get the approval from their supervisor and send their CV along with a link to their supervisor’s university webpage by applying through the webform or directly to Mel Chaar
Program: