Application of artificial intelligence to revive numerical studies of fluid motion in a curved pipe

This paper presents an artificial intelligence (AI) assisted revival of FORTRAN 66 code which calculates laminar flow through curved pipes. Dean numbers D for the entire laminar range are covered: $$10 \le D \le 5000$$ . Results from the code were originally presented in Greenspan (Secondary flow in a curved tube. J Fluid Mech 57: 167–176, 1973). The coupled non-linear system of partial differential equations was solved numerically using a finite difference method. We demonstrate a step-by-step AI-assisted code revival process and compare original (coarse grid resolution) results to updated (fine grid resolution) solutions. Both the structure of streamwise (primary) and secondary flows are covered. The purpose of our paper is both to demonstrate the revival of legacy scientific code and to make the code available as modern Fortran for the scientific community. The code runs quickly on modern hardware architectures and enables fast understanding of the physical effects included.

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Publication Details

Journal
Discover Mechanical Engineering
Published
2026-02-17
DOI
https://doi.org/10.1007/s44245-026-00188-w
Primary Topic
Lattice Boltzmann Simulation Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Application of artificial intelligence to revive numerical studies of fluid motion in a curved pipe

N. Basse
Discover Mechanical Engineering
Lattice Boltzmann Simulation Studies
article

Application of artificial intelligence to revive numerical studies of fluid motion in a curved pipe

N. Basse
article en

Abstract

This paper presents an artificial intelligence (AI) assisted revival of FORTRAN 66 code which calculates laminar flow through curved pipes. Dean numbers D for the entire laminar range are covered: $$10 \le D \le 5000$$ . Results from the code were originally presented in Greenspan (Secondary flow in a curved tube. J Fluid Mech 57: 167–176, 1973). The coupled non-linear system of partial differential equations was solved numerically using a finite difference method. We demonstrate a step-by-step AI-assisted code revival process and compare original (coarse grid resolution) results to updated (fine grid resolution) solutions. Both the structure of streamwise (primary) and secondary flows are covered. The purpose of our paper is both to demonstrate the revival of legacy scientific code and to make the code available as modern Fortran for the scientific community. The code runs quickly on modern hardware architectures and enables fast understanding of the physical effects included.

Discover Mechanical EngineeringVol. 5(1)
RISE Research Institutes of Sweden (SE)
Openalex Percentile: Top 49%
Lattice Boltzmann Simulation Studies
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