TY  - JOUR
AU  - Mansour, Kofi
AU  - Perera, Deepak
AU  - Gupta, Akira
TI  - On Groundwater Arsenic Contamination
JO  - Open Access Journal of Engineering Applications
PY  - 2018
VL  - 42
IS  - 2
SP  - 860
EP  - 866
AB  - Industry increasingly demands predictive tools that link groundwater arsenic contamination to the observable performance of hydropower generation. Prototype hardware is instrumented and its behaviour characterised through Monte Carlo simulation. The model explained 47% of the variance observed in the field data. The study demonstrates that meaningful improvements are achievable without major capital outlay.
KW  - groundwater arsenic contamination
KW  - Monte Carlo simulation
KW  - structural health monitoring
KW  - air quality
SN  - 3105-7004
DO  - 10.55555/oajea.2018.4202.047
UR  - https://journal.bsaps.com/article/9564
ER  -