University of Cambridge > Talks.cam > Engineering Department Structures Research Seminars > Bayesian optimisation of nonlinear and imperfect structures

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Bayesian optimisation of nonlinear and imperfect structures

Download to your calendar using vCal

If you have a question about this talk, please contact Dr Maria Marques de Carvalho .

Structural optimisation has many industrial applications in civil, mechanical and aerospace engineering Gradient based method is suitable for most of the practical problems with differentiable objective functions However, there are structural problems where the derivatives of objective functions are expensive to compute or even not available For example, problems with nonlinearities and imperfections are often challenging to use gradient based method Bayesian optimisation is commonly used non gradient method for problems with objective functions that are expensive to evaluate It can reach a reasonably accurate optimal result with limited number of evaluations This project aims to explore the applications of Bayesian optimisation techniques to optimise nonlinear and imperfection sensitive structures

This talk is part of the Engineering Department Structures Research Seminars series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

in person & via zoom in person & via zoom Putlocker Release Date and Popularity

Other talks

Christopher Cowie on the epistemology of assessing biosignature claims LCLU Annual Talk: The Early Aqueous Environment of Mars Inferred From Mission Lifetime Results by the Curiosity Rover at Gale Crater Morning Break Ensemble inequivalence for systems with long-range interactions Title to be confirmed title abstract tba
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity