Fast prediction tools for turbine cooling performance have been demanded by industry for
decades to support the iterative design process and the comprehensive response analysis …

This paper develops a machine learning-based method to predict gas turbine performance
for power generation. Two surrogate models based on high dimensional model …

Dry-Low Emission (DLE) technology significantly reduces the emissions from the gas turbine
process by implementing the principle of lean pre-mixed combustion. The pre-mix ensures …

This study examines the predictive capability of deep learning method for adiabatic film
cooling effectiveness distribution with variable operating conditions and geometric layouts. A …

The current study is based on multiple machine learning algorithms to predict the normal
behavior of operational parameters including power generated and blade path temperature …

Gas turbines are used to generate electricity in thermal power plants and are also used as a
backup for renewable energy. Recently, following various environmental regulations …

Film cooling is one of the effective cooling methods to ensure the longevity of high thermal
load turbines. Due to multiple corresponding design parameters, it is difficult to seek rapid …

The direct prediction model for adiabatic film cooling effectiveness distribution and inverse
prediction model for design parameters are studied in this article. Convolutional neural …

Cooling design optimization with complex nonuniform heat loads is a typical challenge in
the development of new generation gas turbines. Combined inlet hot streaks and swirls …

In recent years, artificial intelligence (AI) technologies have been widely applied in many
different fields including in the design, maintenance, and control of aero-engines. The air …