2 citations · 5 across the 4 of their papers we have counts for
4 papers
Combining Thermodynamics-based Model of the Centrifugal Compressors and Active Machine Learning for Enhanced Industrial Design Optimization
Shadi Ghiasi, Guido Pazzi, Concettina Del Grosso +2
The design process of centrifugal compressors requires applying an optimization process which is computationally expensive due to complex analytical equations underlying the compre…
Learning to Identify Drilling Defects in Turbine Blades with Single Stage Detectors
Andrea Panizza, Szymon Tomasz Stefanek, Stefano Melacci +2
Nondestructive testing (NDT) is widely applied to defect identification of turbine components during manufacturing and operation. Operational efficiency is key for gas turbine OEM…
Deep Surrogate of Modular Multi Pump using Active Learning
Malathi Murugesan, Kanika Goyal, Laure Barriere +3
Due to the high cost and reliability of sensors, the designers of a pump reduce the needed number of sensors for the estimation of the feasible operating point as much as possible.…
DANNTe: a case study of a turbo-machinery sensor virtualization under domain shift
Luca Strazzera, Valentina Gori, Giacomo Veneri
We propose an adversarial learning method to tackle a Domain Adaptation (DA) time series regression task (DANNTe). The regression aims at building a virtual copy of a sensor instal…