TY  - JOUR
AU  - Park, Kwame
TI  - Support Vector Machines for Turbulent Flow in Pipes
JO  - Open Access Journal of Engineering Applications
PY  - 2018
VL  - 42
IS  - 2
SP  - 761
EP  - 773
AB  - Practitioners have long relied on empirical rules to design building energy efficiency, yet these often neglect the complexity of turbulent flow in pipes. Model parameters are calibrated against field data and independently validated using support vector machines. Results indicate that turbulent flow in pipes can be improved by up to 36% under the recommended configuration. Further validation across a broader range of conditions is recommended before large-scale deployment.
KW  - turbulent flow in pipes
KW  - support vector machines
KW  - fatigue
KW  - heavy metal removal
SN  - 3105-7004
DO  - 10.55555/oajea.2018.4202.038
UR  - https://journal.bsaps.com/article/9555
ER  -