Master Thesis - MATLAB/Python toolbox for Air-borne transfer function

Background:

The Air-borne Transfer Function (ATF), also referred to as the cab filter, is the cabin interior noise response to external airborne excitation. Mathematically, it is defined as the ratio between the interior cabin sound pressure level and the external acoustic excitation. The external excitation can be characterized in terms of sound pressure, sound power, or volume velocity. At Scania, these measurements have been performed, and the results are stored as MATLAB files. Such data can be utilized to define component targets or to estimate the interior sound pressure level when the source strength is known. However, to ensure accessibility across different teams, a dedicated toolbox and graphical user interface (GUI) are required to facilitate efficient use of this data within Scania.

Goal:

The goal of this project to develop a MATLAB/Python tool box and a GUI for ATF.

Assignment:

Acoustic sources on Scania trucks are distributed across various locations, and several evaluation points exist inside the cab. This results into multiple airborne transfer functions. Moreover, the transfer function can be expressed in different forms, such as sound pressure-to-sound pressure, sound power-to-sound pressure, and volume velocity-to-sound pressure. In addition, Scania has cabs and engines of different sizes, which further increases the number of possible combinations. Accordingly, the present task can be divided into the following parts:

• Design a GUI architecture that accommodates all possible combinations.
• Review and understand the available ATF data (no new measurements are required).
• Develop the underlying software code and integrate the ATF into the toolbox.
• Prepare a final presentation and report.

Education:

Masters student with focus on Engineering mechanics, Acoustics or Computer science.

Strong background in MATLAB or similar tools would be considered a plus.

Number of students: 1

Start date: Jan/Feb 2027

Estimated time needed: 20-25 weeks

Contact persons and supervisors: Mohammad Afzal, +46 8553 819 29, [email protected]

Application: Your application should contain a covering letter, CV and transcripts.