Data-Driven Prediction of Impact Sound Insulation of Mass-Timber Floors

Institut

Lehrstuhl für Akustik mobiler Systeme (TUM-ED)

Typ

Bachelorarbeit / Semesterarbeit /

Inhalt

theoretisch /  

Beschreibung

Motivation

While timber construction is gaining popularity, predicting its acoustic performance remains a significant challenge. Wooden floor systems typically consist of multiple layers, whose interactions yield complex sound insulation properties. In particular, impact sound represents a major source of annoyance in residential buildings, motivating the development of accurate and robust prediction methods. At present, reliable assessment often requires costly experimental validation. To address this limitation, a data-driven prediction tool is being developed that employs machine learning techniques to estimate the sound insulation characteristics of wooden floor systems based on laboratory measurement data.

Your Task

A comprehensive set of measurement data has been collected and integrated into a MySQL database. On this basis, feed-forward neural networks and tree-ensemble models have been trained in an initial comparative study to predict airborne sound insulation. In this thesis, you will optimize the existing models and transfer them to predict the impact sound insulation of wooden floor systems. Subsequently, the approaches will be extended to account for uncertainties inherent in the experimental training data, resulting in a robust and interpretable predictive design tool. Your contribution will play a crucial role in refining the existing predictive models and enabling reliable assessment of impact sound insulation in timber floor constructions.

By joining our team, you have the opportunity to apply your theoretical knowledge in a real-world context, gaining valuable insights into the development and deployment of machine learning solutions.

Voraussetzungen

• Knowledge of Python/PyTorch
• High motivation and a structured working style
• Beneficial: Experience in probabilistic modeling and hyperparameter optimization

Application

Please submit your application, including a brief statement of interest, your CV, and a transcript of records via email.

Möglicher Beginn

End of March

Kontakt

Markus Mörwald, M.Sc.
Raum: MW1535
Tel.: 08928955136
markus.moerwaldtum.de

Ausschreibung