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Journal Articles

DARTS-NETGAB: Design Automation and Real-Time Simulation Using Neural Network Ensembles for Turbocompressors on Gas-Bearings

Open Access
Soheyl Massoudi, Joseph Bejjani, Timothy Horvath, Dogukan Üstün, Jürg Schiffmann
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. June 2025, 147(6): 061703.
Paper No: MD-24-1694
https://doi.org/10.1115/1.4068091
Published Online: April 3, 2025
... visibility. Key features like groove depths in the herringbone grooved journal bearings (HGJBs) and spiral groove thrust bearings (SGTBs), as well as impeller blade thickness, are amplified to 0.5mm to circumvent the resolution limits of the 3D printing process and to ensure accurate detail reproduction...
View Articletitled, DARTS-NETGAB: Design Automation and Real-Time Simulation Using Neural Network Ensembles for Turbocompressors on Gas-Bearings
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Topics: Artificial neural networks, Computer-aided design, Design, Gas bearings, Manufacturing, Simulation, Compressors, Visualization, Optimization, Stability
Journal Articles

An Integrated Approach to Designing Robust Gas-Bearing Supported Turbocompressors Through Surrogate Modeling and Constrained All-At-Once Multi-Objective Optimization

Available to Purchase
Soheyl Massoudi, Cyril Picard, Jürg Schiffmann
Journal: Journal of Mechanical Design
Publisher: ASME
Article Type: Research Papers
J. Mech. Des. December 2024, 146(12): 121706.
Paper No: MD-24-1183
https://doi.org/10.1115/1.4065823
Published Online: July 19, 2024
... ,” Astrodynamics , 5 ( 3 ), pp. 185 – 215 . 10.1007/s42064-021-0109-x [18] Massoudi , S. , and Schiffmann , J. , 2023 , “ Robust Design of Herringbone Grooved Journal Bearings Using Multi-objective Optimization With Artificial Neural Networks ,” ASME J. Turbomach. , 145 ( 11 ), p. 111010...
View Articletitled, An Integrated Approach to Designing Robust Gas-Bearing Supported Turbocompressors Through Surrogate Modeling and Constrained All-At-Once Multi-Objective Optimization
Open the PDF for An Integrated Approach to Designing Robust Gas-Bearing Supported Turbocompressors Through Surrogate Modeling and Constrained All-At-Once Multi-Objective Optimization in another window
Topics: Artificial neural networks, Bearings, Blades, Compressors, Design, Gas bearings, Manufacturing, Optimization, Robustness, Rotors