Practical Uses of PODDS Discolouration Modelling Capability in Synergi 4.9

Transcription

1 OIL & GAS Practical Uses of PODDS Discolouration Modelling Capability in Synergi 4.9 Mark Grainger 1 SAFER, SMARTER, GREENER

2 Presentation Objectives To raise awareness of the new PODDS modelling capability available in Synergi 4.9 To show some potential practical examples of how this can be applied to real world problems 2

3 Outline Turbidity/PODDS overview Running a turbidity analysis Practical examples Site Re-Design Study Effectus 2015 Trunk Main Conditioning 3

4 PODDS Theory Discolouration material is held in stable cohesive layers attached to the pipe walls of the systems and that these layers are conditioned by the daily hydraulic regime within the system The cohesive layers have a defined profile of discolouration potential versus layer strength, with an increase in potential corresponding to a decrease in strength The strength of the layers is dictated by the shear stress imposed within each pipe at the time of peak daily flow and hence peak daily flow controls the discolouration potential. 4

5 PODDS Theory The occurrence of disequilibria hydraulic conditions (burst, re-zoning, increased daily flow etc.) is considered to expose the layers to forces in excess of their conditioned cohesive strength and this leads to a mobilisation of the cohesive layers and results in a discolouration event. 5

6 Turbidity Modelling in Synergi Incorporated into the latest versions of Synergi Water Two types of turbidity modelling Standard method Based on PODDS (Prediction Of Discolouration in Distribution Systems) Enhanced method Based on VCDM (Variable Condition Discolouration Model) 6

7 Standard Model (based on PODDS) The Standard method is based on the Prediction of Discoloration in Distribution Systems (PODDS) model developed at the University of Sheffield, and helps you model changes in turbidity due to erosion of material attached to pipe walls. 7

8 Enhanced Method (based on VCDM) The Enhanced method is based on VCDM (Variable Condition Discoloration Model), also developed at the University of Sheffield, and helps you model both erosion and regeneration of material attached to pipe walls, and can give you a better representation of observed turbidity behaviour. 8

9 Process for Running a Turbidity Analysis 9

10 Overview Calibrated Hydraulic Model Layer Condition Calibration Prior-to-event Pressure and Flow data Event Pressure and Flow data Event modelling 10

11 Calibrated Hydraulic Model Will work with any Synergi model Ideally however, requires a more accurate calibration then a purely hydraulic model Calibration usually done using pressures and DMA inlet flow data Accurate turbidity modelling requires accurate calculations of shear stresses Recommended that more flows be included in model calibration to get a more accurate representation of shear stresses and travel times (Boxall, Saul and Skipworth, 2004) 11

12 Layer Condition Calibration Now the model has been calibrated, the initial layer condition needs to be estimated For the standard method, this means estimating/calculating the initial shear strength For the enhanced method, this means estimating/calculating the initial shear band condition versus shear strength profiles For this presentation, I will mostly focus on the standard method 12

13 Layer Condition Calibration Ensure model is running as in normal operating conditions i.e. no special events, bursts etc Nothing that will disturb cohesive layers attached to pipe walls We can now use the peak daily flow from the model to represent initial conditions Involves running the model for an extended period, and retaining the shear strengths as new initial conditions for the model This can now be saved as your PODDS conditioned model, ready for further analysis 13

14 Layer Condition Calibration In the Conditioned Model; Equals Peak Daily Shear 14

15 Event Turbidity Modelling Using the conditioned model, we can now see any increased turbidity responses for an events we model E.g Bursts, re-zones, new-connections, flow reversals etc. Turbidity (measured in NTUs) becomes an attribute that can be viewed on any pipe in the model, at any time during the analysis period 15

16 Practical Usage Site Re-design Study 16

17 Site Re-design Study Site-specific study from early 2015 Due to increased demand over the last few years, low pressures were observed in a tower block DNVGL were asked to investigate the area, and suggest potential improvements to the network 17

18 Recommendations Required pressures could be achieved by changing the metering and valving configuration of the network as shown below Valves opened Meter relocated Valves closed Cross-connection installed and meter relocated 18

19 PODDS Analysis The proposed changes were made and the model re-run to highlight the areas of the network likely to experience an increase in Shear Stress and therefore be potentially subject to discolouration. 19

20 PODDS Analysis The model shear stresses before any changes have been made 20

21 PODDS Analysis After the proposed changes have been modelled Increased shear 21

22 PODDS Analysis Predicted turbidity response 22

23 PODDS Analysis It was recommended that robust flushing or mains conditioning of these sections was incorporated as part of the reconfiguration works. Undertake over a period of several days to ensure the network is conditioned to the increasing flows gradually, in order to keep the turbidity response low 23

24 Practical Usage - Effectus 24

25 Effectus 2014 Systemised outage analysis of every modelled asset including; pipes, pumps, tanks, and sources Identifies areas affected by; Low pressure (DG2) Supply interruption (DG3) Discolouration potential (based on shear stress increases and flow/velocity changes Outputs Include; Pipes affected by DG2/3 and discolouration Number of customers affected in each case List of valves and pipes forming isolated section Valves proximity data & Drain-down time analysis 25

26 Effectus

27 Effectus 2015 Now expanded to include DMA rezoning Open DMA boundary valves Hydrant flushing Simulate hydrant operation Burst main analysis Simulate a burst at each main Every applicable analysis for Effectus 2015 will also include a PODDS turbidity simulation The above analyses have been carried out on a test DMA model 27

28 Effectus Rezoning Simulate DMA inlet failure Trace all DMA boundary valves Sequentially open valve meeting a certain criteria in turn on report on the consequences Report on consequences (pressures, flows, turbidity etc.) Identifies DMAs where the network flexibility exists to allow feasible rezones options Identifies DMAs where no viable rezone exists. Risk of supply interruptions are unmitigated Identifies discolouration risks associated with each viable rezone. Highlights excess shear pipes and the parts of the network likely to experience a turbidity response 28

29 Summary Effectus Analysis Process Effectus 2015 Rezoning Example DMA shear stress values at peak demand time Inlet 29

30 Summary Effectus Analysis Process Effectus 2015 Rezoning Example Predicted turbidity response from conditioned model 30

31 Summary Effectus Analysis Process Effectus 2015 Rezoning Example Shear stresses with inlet closed, and valve opened to re-zone DMA Inlet closed Boundary valve opened 31

32 Summary Effectus Analysis Process Effectus 2015 Rezoning Example Predicted turbidity response from re-zone (maximum over 24 hours) 32

33 Effectus 2015 Hydrant Operation Create a stand pipe element Simulate each hydrant operation running through the stand pipe Report on consequences (pressures, flows, turbidity etc.) Identifies hydrants which do not achieve a predetermined set of flushing criteria Identifies pipes associated with each hydrant operation that experience an increase in shear stress above an agreed threshold 33

34 Summary Effectus Analysis Process Effectus 2015 Hydrant Operation Example Max Shear = Max Shear = Max Shear = Max Shear =

35 Summary Effectus Analysis Process Effectus 2015 Hydrant Operation Example Max Shear = Max Shear = Hydrant Flushed Max Shear = Max Shear =

36 Summary Effectus Analysis Process Effectus 2015 Hydrant Operation Example Max Turbidity Response 36

37 Effectus 2015 Burst Analyse all mains in the network Simulate a burst main Report on consequences (pressures, flows, turbidity etc.) 37

38 Summary Effectus Analysis Process Effectus 2015 Burst Main Example DMA shear stress values at peak demand time Inlet 38

39 Summary Effectus Analysis Process Effectus 2015 Burst Main Example Predicted turbidity response from conditioned model 39

40 Summary Effectus Analysis Process Effectus 2015 Burst Main Example Burst main simulated Burst 40

41 Summary Effectus Analysis Process Effectus 2015 Burst Main Example Predicted turbidity response from conditioned model 41

42 Practical Usage Trunk Main Conditioning 42

43 Effectus Analysis Process Trunk Main Conditioning TM Contingency Planning Sweetening Flow around 1-2 Ml/d Emergency Demand Flows around 50 Ml/d Required to maintain regional supplies during critical asset outage 43

44 Process Trunk Main Conditioning TM Model Conditioned to turnover flow Emergency demand applied and Turbidity response predicted Turbidity at 12 NTU 44

45 Effectus Analysis Process Trunk Main Conditioning Incremental Increases of 1 Ml/d enabled STW to achieve the Emergency flow rate whilst keeping the turbidity response below 2 NTU 45

46 Effectus Analysis Process Trunk Main Conditioning Trunk main conditioned to 50Ml/d Confidence that trunk main is in a state of readiness for any emergency flows 46

47 Summary Turbidity/PODDS now available in Synergi software Version 4.9 onwards Easy to implement Only requires a calibrated model Minimal set up time We plan to use this functionality more going forward in our work 47

48 Mark Grainger SAFER, SMARTER, GREENER 48