ENGINEERING MODELING IN BIO-Safety Monitoring Assessment, Response - - PowerPoint PPT Presentation

engineering modeling in bio safety monitoring assessment
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ENGINEERING MODELING IN BIO-Safety Monitoring Assessment, Response - - PowerPoint PPT Presentation

PAVIA UNIVERSITY Dep. of Civil Engineering and Architecture W-SMART ENGINEERING MODELING IN BIO-Safety Monitoring Assessment, Response Tecnology Luigi Franchioli, PhD Adjunct Professor of Hydraulics University of Pavia SWN Innovation,


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PAVIA UNIVERSITY Dep. of Civil Engineering and Architecture

ENGINEERING MODELING IN BIO-Safety Monitoring Assessment, Response Tecnology

Luigi Franchioli, PhD

Adjunct Professor of Hydraulics University of Pavia SWN Innovation, Challanges & Practice AQUACity Lille, June 15, 2016

W-SMART

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COMPLIANCE WITH THE REQUIREMENTS OF WATER QUALITY

Measured Parameters:

  • pH
  • Turbidity
  • Pressure
  • Conductivity
  • Total Organic Carbon (TOC)

FEEDING/TRANS TREATMENT DISTR NETWORK WATER SUPPLY CHAIN

CONTAMINATION

  • Accidental
  • Deliberate

WATER QUALITY MONITORING IS RELEVANT

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BIO-SMART System Architecture

Phase 1 - Eng. Modeling for acquiring database Phase 2 - AI based on Data Analysis for forecasting Phase 3 - MV analysis reactions for detection Phase 4 - Integration and Decision Support

LACKING DATA (OUTCOME OF PHASE «ZERO»»

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Phase 1: Engineering models to obtain quasi-data

Numerical Experiments

EPANET EPANET-MSX (Multi Spicies

  • Minimize sensor expected detection time
  • Minimize contaminated volume before the alarm
  • Minimize number of sensors
  • Maximize number of events detection

Hydraulic Testing Quality Analysis Contaminants transportation with conservative assumptions Multi-species analysis Chemical models Non-conservative assumpt. (interactions btw wall pipes and substances)

  • Adsorption As+3
  • E.Coli

OBJECTIVES

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Real Network proposed by Alperovits and Shamir (1977), constituted by:

  • 65 nodes
  • 82 pipes
  • 3 tanks

CASE STUDY

HOURLY TIME PATTERN FOR THE NODAL DEMAND (24 coefficients that scale the flow- rate pick value)

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EPANET RESULTS – Non specific injections (1)

  • If the duration increases, the

peak increases until the saturation status

  • The phenomena ends in

approximately one hour

  • Available detected value in

less then 10 min Mass Booster: 0,5 kg/min Injection Duration: 10, 20, 60 min Starting time: 7:00

EPANET DOESN’T CONSIDER THE CHEMICAL OR BIOLOGICAL SPECIES TYPE

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  • Plateau absence due to

insufficient injection duration

  • The phenomena ends in

approximately 20 min

  • Available detected value in less

then 10 min Mass Booster : 0,5 kg/min Injection Duration: 20 min Starting time: variable

EPANET DOESN’T CONSIDER THE CHEMICAL OR BIOLOGICAL SPECIES TYPE

EPANET RESULTS – Non specific injections (2)

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EXAMPLE OF EPANET-MSX INPUT: Adsorption As+3

The sw needs some coefficients regarding the chemical reactions involving species, units and time options, the ineraction among species and pipes, the interaction among species and tanks, starting quality conditions

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EPANET-MSX INPUT: E.Coli

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EPANET-MSX RESULTS (Arsenic, multi-node injection)

  • Small interaction of

monochloramine with arsenic (concentration is more or less constant)

  • The phenomena ends in

approximately 60 min Mass Booster: 10 μg/L Injection Duration: 10 min Starting time: 7:00

ARSENIC, NODE 8, INJ. AT 36-45-50 ARSENIC, NODE 19, INJ. AT 36-45-50 ARSENIC, NODE 45, INJ. AT 36-45- 50

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EPANET-MSX RESULTS (Arsenic, single-node injection)

  • Small interaction of

monochloramine with arsenic (concentration is more or less constant)

  • The phenomena ends in

approximately 60 min Mass Booster: 10 μg/L Injection Duration: 10 min Starting time: 7:00

ARSENIC, NODE 8, INJ. AT 36-45-50 ARSENIC, NODE 19, INJ. AT 36-45-50 ARSENIC, NODE 45, INJ. AT 36-45- 50 ARSENIC, NODE 8, INJ. AT 50 ARSENIC, NODE 19, INJ. AT 50 ARSENIC, NODE 45, INJ. AT 50

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EPANET-MSX RESULTS (E. Coli, multi-node injection)

  • If E. Coli quantity increases, the

level of free chlorine decreases

  • Immediate effect on the network
  • Possibility of bacteria detection

by analyzing the level of free chlorine Mass Booster : 1 CFU/L Injection Duration : 7 hours Starting time : 4:00

  • E. COLI, NODE 8, INJ. AT 36-45-50
  • E. COLI, NODE 19, INJ. AT 36-45-50
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EPANET-MSX RESULTS (E. Coli, single-node injection)

  • If E. Coli quantity increases, the

level of free chlorine decreases

  • Immediate effect on the network
  • Possibility of bacteria detection

by analyzing the level of free chlorine Mass Booster : 1 CFU/L Injection Duration : 7 hours Starting time : 4:00

  • E. COLI, NODE 8, INJ. AT 36-45-50
  • E. COLI, NODE 19, INJ. AT 36-45-50
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CONCLUSIONS

  • Engineering models (Epanet, Epanet MSX) are appropriate to describe

the most common chemical/physical/biological pollutants;

  • In the shown cases the injection duration doesn’t influence the pick

concentration value of the pollutants (saturation at given conditions)

  • E. Coli injection causes a drop of chlorine (bactericide effect).

FREE CHLORINE MONITORING ALLOWS THE E. COLI DETECTION;

  • No interaction between arsenic and monochloramine;
  • The nodal demand influence the diffusion of pollutants (flow-rate

circulation change inside the network)