128 citations · 921 across the 32 of their papers we have counts for
33 papers
Predictive Limitations of Physics-Informed Neural Networks in Vortex Shedding
Pi-Yueh Chuang, Lorena A. Barba
The recent surge of interest in physics-informed neural network (PINN) methods has led to a wave of studies that attest to their potential for solving partial differential equation…
PyExaFMM: an exercise in designing high-performance software with Python and Numba
Srinath Kailasa, Tingyu Wang, Lorena A. Barba +1
Numba is a game-changing compiler for high-performance computing with Python. It produces machine code that runs outside of the single-threaded Python interpreter and that fully ut…
Reproducibility of the First Image of a Black Hole in the Galaxy M87 from the Event Horizon Telescope (EHT) Collaboration
Ria Patel, Brandan Roachell, Silvina Caino-Lores +6
This paper presents an interdisciplinary effort aiming to develop and share sustainable knowledge necessary to analyze, understand, and use published scientific results to advance…
Defining the role of open source software in research reproducibility
Lorena A. Barba
Reproducibility is inseparable from transparency, as sharing data, code and computational environment is a pre-requisite for being able to retrace the steps of producing the resear…
Experience report of physics-informed neural networks in fluid simulations: pitfalls and frustration
Pi-Yueh Chuang, Lorena A. Barba
Though PINNs (physics-informed neural networks) are now deemed as a complement to traditional CFD (computational fluid dynamics) solvers rather than a replacement, their ability to…
[Re] Three-dimensional wake topology and propulsive performance of low-aspect-ratio pitching-rolling plates
Olivier Mesnard, Lorena A. Barba
This article reports on a full replication study in computational fluid dynamics, using an immersed boundary method to obtain the flow around a pitching and rolling elliptical wing…