4 papers
Physics-informed neural networks for phase-resolved data assimilation and prediction of nonlinear ocean waves
Svenja Ehlers, Norbert Hoffmann, Tianning Tang +5
The assimilation and prediction of phase-resolved surface gravity waves are critical challenges in ocean science and engineering. Potential flow theory (PFT) has been widely employ…
The impact of AI on engineering design procedures for dynamical systems
Kristin M. de Payrebrune, Kathrin Flaßkamp, Tom Ströhla +19
Artificial intelligence (AI) is driving transformative changes across numerous fields, revolutionizing conventional processes and creating new opportunities for innovation. The dev…
Evolution beats random chance: Performance-dependent network evolution for enhanced computational capacity
Manish Yadav, Sudeshna Sinha, Merten Stender
The quest to understand structure-function relationships in networks across scientific disciplines has intensified. However, the optimal network architecture remains elusive, parti…
Data assimilation and parameter identification for water waves using the nonlinear Schrödinger equation and physics-informed neural networks
Svenja Ehlers, Niklas A. Wagner, Annamaria Scherzl +3
The measurement of deep water gravity wave elevations using in-situ devices, such as wave gauges, typically yields spatially sparse data. This sparsity arises from the deployment o…