TY  - JOUR
AU  - Karimi, Ahmed
AU  - Wang, Rahul
TI  - Wind Turbine Generators using Life Cycle Assessment
JO  - Open Access Journal of Engineering Applications
PY  - 2018
VL  - 42
IS  - 1
SP  - 548
EP  - 562
AB  - There remains a pressing need for cost-effective methods to assess wind turbine generators in railway engineering. A predictive model based on life cycle assessment is constructed to relate design variables to performance outcomes. Results indicate that wind turbine generators can be improved by up to 8% under the recommended configuration. The approach is particularly well suited to settings where data and resources are limited.
KW  - wind turbine generators
KW  - life cycle assessment
KW  - computational fluid dynamics
SN  - 3105-7004
DO  - 10.55555/oajea.2018.4201.028
UR  - https://journal.bsaps.com/article/9495
ER  -