Modelli matematici applicati ai processi di filtrazione a membrana

— Mathematical modelling of MBR systemBiomath, Ghent University, Belgium

06-06-2006

Tao Jiang

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Overview of the presentation

• Modelling the biological performance of MBR

• Modelling of MBR fouling

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Biological difference of MBR and TAS• Complete retention of solids and partial retention of colloidal/macromolecular fraction

• Operational parameters

• Long SRT

• Short HRT

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Colloidal fraction in MBR• Colloidal: 0.001 µm - 1µm

• MBR membrane pore size: 0.03-0.4 µm

• non-settable flocs in TAS: < 5-10 µm

• Additional removal of solids by MBR

• Small flocs (0.45-10 µm)

• Partial retention of colloids (pore size - 0.45µm)

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Colloidal concentration in MBR sludge• TAS Effluent: 30-60 mg/L

• MBR sludge (<0.45µm): 50-200 mg/L

• MBR effluent (<pore size): 5-20 mg/L

• Membrane retention: 70-95%

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Colloidal fraction is S or X?• By size:

• Colloidal fraction < 0.45 µm S

• By retention: • 70-90% retention X

• By biological degradation: • Slow biodegradable X

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Colloidal fraction is X• Colloidal fraction is X, although smaller than 0.45 µm

• No significant error in TSS measurement, if the colloidal fraction is missing (CODCol<<CODTSS)

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Influence of long SRT and short HRT• High MLSS concentration

• MLSS=SRT/HRT*…..

• Increased sensitivity of X (advantage of calibration)

• Inert particulate COD build up in MBR

• XI= SRT/HRT*XI,in

• Careful wastewater characterization

• Low active biomass fraction

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Membrane model• Simple option (BNR study)

• Point settler and include the colloidal fraction into X

• Complete option (membrane fouling study)

• Define new variable S_SMP (X)

• Define retention of S_SMP by membrane

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Modelling of settler vs. membrane• TAS (settler)

• Difficulty in calibrating settling model

• Possible biological processes in settlers

• MBR (Membrane)• Point separation (no volume)

• No biological processes

• Complete retention of X

• Partial retention of colloidal fraction

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Modelling of a lab-scale MBR

Parameter/variable

Reference values

Influent rate 108 L/dayAerobic 17 min

Anoxic mixing 11 minAnoxic

recirculation12 min

SRT 17 daysHRT 6.4 hr

MLSS 7 g/LFiltration flux 31.8 L/(m2h)

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WEST – Configuration

CF_In FC_OutAnaerobic Aerobic

DO_Control

Sludge_Waste

Comb_1 Comb_2

Timer_DO Timer_R

Comb_3

Splitter_2

Internal_R

ASU_Pipe

Loop

Timer_RW

Splitter_RW

Timer_Pump

Timer_Pump2

UFInfluent Effluent

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WEST – Experimentation

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Aerobic_TSSgfedcAerobic_X_HgfedcbAerobic_X_AUTgfedcbAerobic_X_IgfedcbAerobic_X_PAOgfedcbAnaerobic_TSSgfedcAerobic_X_all_CODgfedcAerobic_X_all_TSSgfedc

0.1050.10.0950.090.0850.080.0750.070.0650.060.0550.050.0450.040.0350.030.0250.020.0150.010.005

5,200

5,000

4,800

4,600

4,400

4,200

4,000

3,800

3,600

3,400

3,200

3,000

2,800

2,600

2,400

2,200

2,000

1,800

1,600

1,400

1,200

1,000

800

600

400

Simulation results - Particulate

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Simulation results - effluent

S_NHgfedcbS_NOgfedcbS_POgfedcbS_Ogfedc

0.1050.10.0950.090.0850.080.0750.070.0650.060.0550.050.0450.040.0350.030.0250.020.0150.010.005

9

8

7

6

5

4

3

2

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Simulation results - user defined

AnaerobicMassFractiongfedcSa_Denitrified/Total_InfluentgfedcbEBP/TotalP_removalgfedcbP_Waste_TSS/TSSgfedcPP/PAO_aerobicgfedc

0.1050.10.0950.090.0850.080.0750.070.0650.060.0550.050.0450.040.0350.030.0250.020.0150.010.005

0.65

0.6

0.55

0.5

0.45

0.4

0.35

0.3

0.25

0.2

0.15

0.1

0.05

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Objective of modelling MBR fouling• Prediction of membrane fouling (TMP vs t)

• Facilitate integrated design, upgrading, operation

• Cost reduction

• …

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Influence of biology on fouling• Feed to membrane is activated sludge

• The composition of activated sludge is determined by the influent and operation of biological process

• How biology influence fouling

• What is the main foulant?

• Influence of MLSS, SRT, HRT, DO?

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Foulant in MBRs• The main foulant in MBRs is up to the influent composition, design and operation

• Particulate and colloidal can be the main foulant

• Colloidal fouling is getting more attention (soluble microbial products)

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• Identify the main foulant

• Quantify the amount of foulant and their fouling potential

• Estimate the deposit rate of foulant on/in the membrane

• Predict additional resistance due to the foulant

• Estimate the reversibility of foulant by backwashing and chemical cleaning

Steps in the modelling of fouling

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conclusion

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• Modelling the biolgical performance of MBR is simpler than TAS

• Modelling of MBR fouling, especially fouling prediction is extremely difficult and pre-mature