TY  - JOUR
AU  - Khan, Deepak
AU  - Karim, Sofia
TI  - Genetic Algorithm Optimisation for Gas Turbine Blade Cooling: Performance Evaluation and Optimisation
JO  - Open Access Journal of Engineering Applications
PY  - 2020
VL  - 44
IS  - 2
SP  - 367
EP  - 391
AB  - With metal additive manufacturing becoming more interconnected, the risks associated with poorly characterised gas turbine blade cooling grow accordingly. Field measurements gathered over several months provide the basis for the subsequent genetic algorithm optimisation. The model explained 43% of the variance observed in the field data. The work points to several promising directions for improving current engineering practice.
KW  - gas turbine blade cooling
KW  - genetic algorithm optimisation
KW  - mimo
KW  - machine learning
KW  - particle swarm optimisation
KW  - biomass
SN  - 3105-7004
DO  - 10.55555/oajea.2020.4402.019
UR  - https://journal.bsaps.com/article/9736
ER  -