Data-driven design of CLT buildings – Prediction of vibrations
Description
Increasing the market share of timber buildings is important for reducing the greenhouse gas emissions from the construction industry, and for contributing to a circular economy. New and improved technical solutions for mitigating noise and vibrations are key enablers for increasing the use of timber in construction. In the development of such technical solutions, the availability of computational prediction models is a great advantage that helps explore new ideas and optimize potential solutions.
In the last 10-20 years, research concerning computational models for noise and vibrations in timber buildings has made substantial progress. However, there is a current lack of knowledge regarding suitable computational procedures for handling stochastic parameters in the models. The natural origin of timber causes significant statistical variation in the noise and vibration response among nominally identical building structures. This emphasizes the need to introduce parameters with varying values (i.e. stochastic) in the models.
The goal of the proposed project is to develop computational models which accounts for the effect of variations in material properties of timber on the noise and vibration response. The development will consider a fair trade-off between accuracy, efficiency and ease-of-use of the models. The prediction models are intended for use in the exploration and optimization of conceptual design solutions, thereby facilitating an increased use of timber in construction.
Sensitivity analyses are vital for this purpose. Moreover, other more sophisticated methods could be explored such as techniques that involved probability distributions of material data.
Requirements
• FEM courses (15 credits)
• Structural dynamic computing (7.5 credits) and/or Acoustics (7.5 credits)
Further possibilities
It is not required for the project, but there is a possibility to follow a course in Machine Learning during Jan – March if you join this project. Note that no credits will be given for this course, it should be taken by pure interest.
Our division
We at the Division of Structural Mechanics are driven by understanding engineering problems and conducting research that contributes to solving societal challenges. We offer a good study and work environment, good team spirit with dedicated employees and joint “fika” every day. We have a strong focus on high-quality teaching and research. We are proud to belong to a university that is ranked among the top 100 in the world and we enjoy the international environment in which we operate.
Contact
Peter Persson, Associate Professor, Division of Structural Mechanics, LTH
