Solving Transient PDEs in Julia with Gridap.jl | Oriol Colomes | JuliaCon 2022

In this talk we present a new feature of Gridap.jl focusing on the solution of transient Partial Differential Equations (PDEs). We will show a new API that: a) leads to weak forms with very simple syntax, b) supports automatic differentiation, c) enables the solution of multi-field and DAE systems, and d) can be used in parallel computing through GridapDistributed.jl. We will showcase the novel features for a variety of applications in fluid and solid dynamics. For more info on the Julia Programming Language, follow us on Twitter:   / julialanguage   and consider sponsoring us on GitHub: https://github.com/sponsors/JuliaLang 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/JuliaCommunity/You... Interested in improving the auto generated captions? Get involved here: https://github.com/JuliaCommunity/You...