Work

High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks

Year: 2023

Type: article

Source: Journal of Turbomachinery

DOI: 10.1115/1.4063391

Authors: Zhihui Li, Francesco Montomoli, Nicola Casari, Michele Pinelli

Institutions: Imperial College London, University of Ferrara

Language: English

Topic: Probabilistic and Robust Engineering Design

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

Open Access status: closed

Funder: European Commission

Award: A Novel and Affordable Multi-Fidelity Deep Neural Network Uncertainty Quantification/Robust Optimization Design Framework for Industrial Turbomachinery

OpenAlex ID: W4386616384

FWCI: 3.372

Cites: 35

Cited by: 18

Related to: 10