Search Results for author: Daniel J Pitchforth

Found 3 papers, 0 papers with code

A spectrum of physics-informed Gaussian processes for regression in engineering

no code implementations19 Sep 2023 Elizabeth J Cross, Timothy J Rogers, Daniel J Pitchforth, Samuel J Gibson, Matthew R Jones

Despite the growing availability of sensing and data in general, we remain unable to fully characterise many in-service engineering systems and structures from a purely data-driven approach.

Gaussian Processes regression

Physics-informed machine learning for Structural Health Monitoring

no code implementations30 Jun 2022 Elizabeth J Cross, Samuel J Gibson, Matthew R Jones, Daniel J Pitchforth, Sikai Zhang, Timothy J Rogers

The chapter will demonstrate how grey-box models, that combine simple physics-based models with data-driven ones, can improve predictive capability in an SHM setting.

BIG-bench Machine Learning Physics-informed machine learning +1

Grey-box models for wave loading prediction

no code implementations10 May 2021 Daniel J Pitchforth, Timothy J Rogers, Ulf T Tygesen, Elizabeth J Cross

The quantification of wave loading on offshore structures and components is a crucial element in the assessment of their useful remaining life.

Physics-informed machine learning

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