The main purpose of this study is to investigate the relationship between the water turbidity
purification result with raw water turbidity, raw water pH value and PAC dosage,
and find the optimal treatment dosage level. A regression model between the response
and treatment variables has been built with a two-stage procedure. In the first stage,
the regression model treats a given raw water turbidity as the explanatory variable and
the best treatment effect dosage level, among the six experimental dosage levels as the
response. Later the model is used to find the second stage regression model where the
water turbidity purification result is treated as the response, and the other three variables
mentioned above as explanatory variables. According to the results of the second stage
regression model about the best dosage level with a given raw water turbidity, the optimal
PAC dosage is estimated for the optimization in water turbidity purification, which may
be used as a way for future purification of water turbidity.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0728110-161521 |
| Date | 28 July 2010 |
| Creators | Lin, Yi-Heng |
| Contributors | Mei-Hui Guo, Mong-Na Lo, May-Ru Chen, Fu-Chuen Chang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0728110-161521 |
| Rights | withheld, Copyright information available at source archive |
Page generated in 0.0016 seconds