The need for more and more complex and performant systems calls for the development of new design methodologies that leverage the power of computers and exploit expanding AI-based tools. Besides developing automated design methodologies, we are also interested in understanding the impact of these AI-based tools on the education of future engineers.

Recent Journal Publications

Data-Driven Predesign Tool for Small-Scale Centrifugal Compressor in Refrigeration

V. Mounier; C. Picard; J. A. Schiffmann 

Journal of Engineering for Gas Turbines and Power. 2018-10-24. Vol. 140, p. 1-8, 121011. DOI : 10.1115/1.4040845.

Towards a real-time capable hybrid-twin for gas-bearing supported high-speed turbocompressors

L. E. Olmedo; J. Schiffmann 

Energy. 2023-07-15. Vol. 275, p. 127385. DOI : 10.1016/

Thermal management for gas lubricated, high-speed turbomachinery

L. Olmedo; W. Liu; K. Gjika; J. Schiffmann 

Applied Thermal Engineering. 2023-01-05. Vol. 218, p. 119229. DOI : 10.1016/j.applthermaleng.2022.119229.

High-speed turbocompressors for natural fluid heat-pumps: from integrated design to digital-twin

L. E. Olmedo Ocampo / J. A. Schiffmann (Dir.)  

Lausanne, EPFL, 2023. 

Dimensionless correlations and performance maps of scroll expanders for micro-scale Organic Rankine Cycles

L. E. Olmedo Ocampo; V. Mounier; L. C. Mendoza Toledo; J. A. Schiffmann 

Energy. 2018-05-06. Vol. 156, p. 520-533. DOI : 10.1016/

Small scale radial inflow turbine performance and pre-design maps for Organic Rankine Cycles

V. Mounier; L. E. Olmedo; J. Schiffmann 

Energy. 2018. Vol. 143, p. 1072-1084. DOI : 10.1016/

See more LAMD’s publications