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| Content Provider | Springer Nature Link |
|---|---|
| Author | Ilamathi, P. Selladurai, V. Balamurugan, K. Sathyanathan, V. T. |
| Copyright Year | 2012 |
| Abstract | An artificial neural network (ANN) and genetic algorithm (GA) approach to predict NOx emission of a 210 MW capacity pulverized coal-fired boiler and combustion parameter optimization to reduce NOx emission in flue gas, is proposed. The effects of oxygen concentration in flue gas, coal properties, coal flow, boiler load, air distribution scheme, flue gas outlet temperature, and nozzle tilt were studied. The data collected from parametric field experiments was used to build a feed-forward back-propagation neural net. The coal combustion parameters were used as inputs and NOx emission as outputs of the model. The ANN model was developed for full load conditions and its predicted values were verified with the actual values. The algebraic equation containing weights and biases of the trained net was used as fitness function in GA. The genetic search was used to find the optimum level of input operating conditions corresponding to low NOx emission. The results proved that the proposed approach could be used for generating feasible operating conditions. |
| Starting Page | 125 |
| Ending Page | 131 |
| Page Count | 7 |
| File Format | |
| ISSN | 1618954X |
| Journal | Clean Technologies and Environmental Policy |
| Volume Number | 15 |
| Issue Number | 1 |
| e-ISSN | 16189558 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2012-05-23 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Coal combustion process NOx emission ANN GA Predictive modeling Optimization Sustainable Development Industrial Chemistry/Chemical Engineering Industrial and Production Engineering Environmental Engineering/Biotechnology Environmental Economics |
| Content Type | Text |
| Resource Type | Article |
| Subject | Environmental Chemistry Environmental Engineering Economics and Econometrics Business, Management and Accounting Management, Monitoring, Policy and Law |
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