ROSS - Rotordynamic Open Source Software

Timbó, Raphael; Martins, Rodrigo Siqueira; Bachmann, Gabriel; Rangel, Flavio Medeiros; Mota, J. A.; Valério, J. V.; Ritto, T.G.

doi:10.21105/joss.02120

Cited by 18 publications

(9 citation statements)

References 5 publications

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“…The algorithm used was developed in Python, being one of the results of this research, and is available on the GitHub platform, through the software Ross-Rotordynamics [10], in which the authors of this text are co-authored. Currently in this software, the present model and all its functionalities correspond to the part called Fluid Flow, which is responsible for modeling the fluid film in bearings and provides the rest of the program with information necessary for the study of the stability of rotating dynamic systems.…”

Section: Resultsmentioning

confidence: 99%

Lubrication theory stucly with differentiated geometry parameterization and applications in hydrodynamic bearings

Mota¹,

Valério²

2021

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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This article use the lubrication theory to simplify the Navier-Stokes equations for the flow between two cylinders with a small thickness of oil film. An effective parameterization of the geometry, proposed in Mota (2020) [6], is used to analyse traditional hydrodynamic bearings and two other configurations of them: elliptical and worn bearings. The simplifications in the model result in a elliptical partial differential equation, that are solved by the centered finite difference method which solution is the pressure field between the cylinders. The results agreed with the literature and different geometries are analysed. This modeling, as well as all its simulations were developed to integrate Ross-Rotordynamics, a library in Python for rotodynamic analysis, available on the GitHub platform.

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Section: Resultsmentioning

confidence: 99%

Lubrication theory stucly with differentiated geometry parameterization and applications in hydrodynamic bearings

Mota¹,

Valério²

2021

Proceeding Series of the Brazilian Society of Computational and Applied Mathematics

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show abstract

“…The algorithm used was developed in Python, and is available on the GitHub platform, through the software Ross-Rotordynamics 2 [31], an open source library for rotodynamic analysis.…”

Section: Resultsmentioning

confidence: 99%

“…The code used for the simulations presented in this paper is part of ROSS 3 , an open source library written in Python for rotordynamic analysis, by [31].…”

Section: Acknowledgementsmentioning

confidence: 99%

Complete modeling of hydrodynamic bearings with a boundary parameterization approach

Mota¹,

Maldonado²,

Valério³

et al. 2021

Preprint

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The present work aims to revisit the simplifications made in the Navier-Stokes equations for the flow between two cylinders with a small thickness of lubricating oil film. Through a dimensionless analysis, the terms of these equations are mapped and ordered by importance for the hydrodynamic bearing application. An effective parameterization of the geometry is proposed, enabling a more detailed description of the problem and its adaptation to other contexts. At the end, an elliptical partial differential equation is reached and solved by the centered finite difference method, whose solution is the pressure field between the cylinders. To illustrate the effectiveness of the proposed approach, the model is applied to hydrodynamic bearings, where the pressure field and some parameters resulting from it, such as stiffness and damping coefficients, are computed. Based on the facilities offered by the parameterization of the geometry, two different configurations are presented: (1) elliptical and (2) worn bearings. Their responses are evaluated and a comparative analysis is performed. The modeling exposed in this text, as well as all its simulations were developed to integrate Ross-Rotordynamics, an open library in Python, available on the GitHub platform.

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“…The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. They are generated using open-source softwares Kratos [42] and Ross [41].…”

Section: Acknowledgementsmentioning

confidence: 99%

“…Figure 10 compares the predicted bearing stiffness against the actual stiffness. The actual stiffness values are calculated by modelling a fluid bearing with the help of an open source software called ross rotordnamic [41]. It can be observed that the stiffness variation against speed of rotation is captured precisely by the neural network.…”

Section: Fluid Bearing Stiffness Identificationmentioning

confidence: 99%

Finite Element Method-enhanced Neural Network for Forward and Inverse Problems

Meethal

Kodakkal

Khalil

et al. 2022

Preprint

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We introduce a novel hybrid methodology that combines classical finite element methods (FEM) with neural networks to create a well-performing and generalizable surrogate model for forward and inverse problems. The residual from finite element methods and custom loss functions from neural networks are merged to form the algorithm. The Finite Element Method-enhanced Neural Network hybrid model (FEM-NN hybrid) is data-efficient and physics-conforming. The proposed methodology can be used for surrogate models in real-time simulation, uncertainty quantification, and optimization in the case of forward problems. It can be used to update models for inverse problems. The method is demonstrated with examples and the accuracy of the results and performance is compared to the conventional way of network training and the classical finite element method. An application of the forward-solving algorithm is demonstrated for the uncertainty quantification of wind effects on a high-rise buildings. The inverse algorithm is demonstrated in the speed-dependent bearing coefficient identification of fluid bearings. Hybrid methodology of this kind will serve as a paradigm shift in the simulation methods currently used.

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ROSS - Rotordynamic Open Source Software

Cited by 18 publications

References 5 publications

Lubrication theory stucly with differentiated geometry parameterization and applications in hydrodynamic bearings

Lubrication theory stucly with differentiated geometry parameterization and applications in hydrodynamic bearings

Complete modeling of hydrodynamic bearings with a boundary parameterization approach

Finite Element Method-enhanced Neural Network for Forward and Inverse Problems

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