Scheda di dettaglio – i prodotti della ricerca
| Dato | Valore |
|---|---|
| Title | Gross parameters prediction of a granular attached biomass reactor through evolutionary polynomial regression |
| Abstract | Heavy fluctuations in wastewater composition, such as those typical of tourist areas, can lead to a deteri- orationintreatmentplantperformanceifnoactionistakeninadvance.Mathematicalmodelling,applied to treatment plant performance prediction, can provide valuable information to address the stress issue. The present study shows that the evolutionary polynomial regression methodology (EPR) is able to pre- dicttheperformancesofanattachedgranularbiomasssystemsothatitispossibletomakethenecessary operatingchangesinadvance,avoidingdeteriorationinthequalityoftheeffluentdischarged.Thepresent papershowstheresultsofEPRapplicationtogrossparametersofagranularattachedbiomassreactor.For each parameter, a model capable of predicting the effluent value was assessed, based on the knowledge oftheinfluentcharacteristics.Coefficientsofdeterminationvalues(CoD)obtainedduringthemodelsval- idation phase, can be said to be more than satisfactory, varying between 84.2% and 94.6%. Moreover, the applied tests showed typical behaviours commonly found when observed and predicted values are quite similar. This paper reports the first application attempt for modelling this kind of emerging treatment system and gross parameters. |
| Source | Biochemical engineering journal 94, pp. 74–84 |
| Keywords | Aerobic processesEvolutionary polynomial regressionFixed-bed bioreactorsOptimizationPredictive modelsWaste-water treatment |
| Journal | Biochemical engineering journal |
| Editor | Elsevier,, New York, NY, Paesi Bassi |
| Year | 2014 |
| Type | Articolo in rivista |
| DOI | 10.1016/j.bej.2014.11.016 |
| Authors | Barca E., Del Moro G., Mascolo G.,Di Iaconi C. |
| Text | 298578 2014 10.1016/j.bej.2014.11.016 Aerobic processes Evolutionary polynomial regression Fixed bed bioreactors Optimization Predictive models Waste water treatment Gross parameters prediction of a granular attached biomass reactor through evolutionary polynomial regression Barca E., Del Moro G., Mascolo G.,Di Iaconi C. IRSA U.O.S. Bari Heavy fluctuations in wastewater composition, such as those typical of tourist areas, can lead to a deteri orationintreatmentplantperformanceifnoactionistakeninadvance.Mathematicalmodelling,applied to treatment plant performance prediction, can provide valuable information to address the stress issue. The present study shows that the evolutionary polynomial regression methodology EPR is able to pre dicttheperformancesofanattachedgranularbiomasssystemsothatitispossibletomakethenecessary operatingchangesinadvance,avoidingdeteriorationinthequalityoftheeffluentdischarged.Thepresent papershowstheresultsofEPRapplicationtogrossparametersofagranularattachedbiomassreactor.For each parameter, a model capable of predicting the effluent value was assessed, based on the knowledge oftheinfluentcharacteristics.Coefficientsofdeterminationvalues CoD obtainedduringthemodelsval idation phase, can be said to be more than satisfactory, varying between 84.2% and 94.6%. Moreover, the applied tests showed typical behaviours commonly found when observed and predicted values are quite similar. This paper reports the first application attempt for modelling this kind of emerging treatment system and gross parameters. 94 Published version Gross parameterspredictionofagranularattachedbiomassreactor through evolutionarypolynomialregression paper.pdf Articolo in rivista Elsevier, 1369 703X Biochemical engineering journal Biochemical engineering journal Biochem. eng. j. Biochemical engineering journal. BEJ claudio.diiaconi DI IACONI CLAUDIO emanuele.barca BARCA EMANUELE giuseppe.mascolo MASCOLO GIUSEPPE TA.P04.005.008 Integrazione di metodologie per il monitoraggio e la modellizzazione per la gestione delle risorse idriche |