On-Line Analysis of Gas-Phase Composition in the Combustion Chamber and Particle Emission Characteristics during Combustion of Wood and Waste in a Small Batch Reactor

2005 ◽  
Vol 39 (6) ◽  
pp. 1393-1402 ◽  
Author(s):  
T. Ferge ◽  
J. Maguhn ◽  
K. Hafner ◽  
F. Mühlberger ◽  
M. Davidovic ◽  
...  
Keyword(s):  
Phase Composition ◽  
Combustion Chamber ◽  
Gas Phase ◽  
Batch Reactor ◽  
Particle Emission ◽  
Emission Characteristics ◽  
On Line ◽  
Line Analysis

CORRELATION OF GAS-PHASE COMPOSITION AND PARTICLE EMISSION DURING COMBUSTION OF WOOD AND MODEL WASTE IN A SMALL BATCH REACTOR

2004 ◽  
Vol 35 ◽  
pp. S1087-S1088
Author(s):  
T. FERGE ◽  
J. MAGUHN ◽  
K. HAFNER ◽  
F. MÜHLBERGER ◽  
M. DAVIDOVIC ◽  
...  
Keyword(s):  
Phase Composition ◽  
Gas Phase ◽  
Batch Reactor ◽  
Particle Emission

scholarly journals On-line chemical oxygen demand estimation models for the photoelectrocatalytic oxidation advanced treatment of papermaking wastewater

2018 ◽  
Vol 78 (2) ◽  
pp. 310-319 ◽  
Author(s):  
Wenhao Shen ◽  
Feini Huang ◽  
Xuewen Zhang ◽  
Yuefei Zhu ◽  
Xiaoquan Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Chemical Oxygen Demand ◽  
Batch Reactor ◽  
Estimation Method ◽  
Oxygen Demand ◽  
Paper Mill ◽  
Advanced Treatment ◽  
On Line ◽  
Line Analysis ◽  
Papermaking Wastewater

Abstract Chemical oxygen demand (COD), an important indicative measure of the amount of oxidizable pollutants in wastewater, is often analyzed off-line due to the expensive sensor required for on-line analysis. However, its off-line analysis is time-consuming. An on-line COD estimation method was developed with photoelectrocatalytic (PEC) technology. Based on the on-line data of the oxidation–reduction potential (ORP), dissolved oxygen (DO) and pH of wastewater, four different artificial neural network methods were applied to develop working models for COD estimation. Six different batches of sequence batch reactor (SBR) effluent from a paper mill were treated with PEC oxidation for 90 minutes, and 546 data points were collected from the on-line measurements of ORP, DO and pH, and the off-line COD analysis. After having training and validation with 75% and 25% of data, and evaluation with four statistical criteria (R2, RMSE, MAE and MAPE), the estimation results indicated that the developed radial basis neural network (RBNN) model demonstrated the highest precision. Subsequently, the application of the RBNN model to a new batch of SBR effluent from the paper mill revealed that the RBNN model was acceptable for COD estimation during the PEC advanced treatment process of papermaking wastewater, which implied its possible application in the future.

On-line measurements of settling characteristics in activated sludge

1997 ◽  
Vol 36 (4) ◽  
pp. 307-312
Author(s):  
Michael R. Rasmussen ◽  
Torben Larsen
Keyword(s):  
Activated Sludge ◽  
Settling Velocity ◽  
Continuous Measurement ◽  
Batch Reactor ◽  
Volume Index ◽  
Sludge Volume Index ◽  
Dynamic Variations ◽  
On Line ◽  
Settling Column ◽  
Settling Characteristics

An on-line settling column for measuring the dynamic variations of settling velocity of activated sludge has been developed. The settling column is automatic and self-cleansing insuring continuous and reliable measurements. The settling column was tested on sludge from a batch reactor where sucrose was added as an impulse to activated sludge. The continuous measurement of settling velocity revealed a highly dynamic response after the sucrose was added. The results were verified with simultaneous measurement of the initial settling rate. A 200 hour experiment showed variations in settling velocity, which was not apparent in the DSVI (Diluted Sludge Volume Index).

First on-line analysis of petroleum from single inclusion using ultrafast laser ablation

2010 ◽  
Vol 41 (2) ◽  
pp. 74-77 ◽  
Author(s):  
Herbert Volk ◽  
David Fuentes ◽  
Alexander Fuerbach ◽  
Christopher Miese ◽  
Wolfgang Koehler ◽  
...  
Keyword(s):  
Laser Ablation ◽  
Ultrafast Laser ◽  
Single Inclusion ◽  
On Line ◽  
Line Analysis ◽  
Ultrafast Laser Ablation
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