1 / 73

Emily M. Zechman Department of Civil Engineering North Carolina State University

Agent-Based Modeling to Simulate Contamination Events and to Analyze Threat Management Strategies in Water Distribution Systems. Emily M. Zechman Department of Civil Engineering North Carolina State University. Contamination Event Management Strategy.

esma
Télécharger la présentation

Emily M. Zechman Department of Civil Engineering North Carolina State University

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Agent-Based Modeling to Simulate Contamination Events and to Analyze Threat Management Strategies in Water Distribution Systems Emily M. Zechman Department of Civil Engineering North Carolina State University

  2. Contamination Event Management Strategy • Management strategy specifies actions and reactions of decision maker • Broadcast no-drink alerts • Flush system • Isolate portion of system • Treat contaminant in-situ

  3. Evaluate a Management Strategy • Maintain public health • Maintain fire fighting flows • Maintain flow to critical care facilities • Avoid inciting panic due to false alarms

  4. Interaction of Actors during a Contamination Event

  5. Agent Based Modeling Framework • Simulate interactions of actors among one another and with water distribution system • Predict effectiveness of alternative management strategies

  6. Agent Based Model • A computer program that simulates an actor • Receives information from other agents and the environment • Has capabilities (set of rules) to decide on an action Agent Based Model Environmental Information Action

  7. Agent Based Modeling Frameworkfor WDS Contamination Event Water Distribution System Model Unusual Water Quality at Sensors Exposure Change Hydraulics Demand Word-of-mouth Decision Maker Agent Public Broadcast Consumer Agents

  8. Illustrative Case Study 35 1 38 34 15 5 8 156 36 111 110 5 22 97 119 45 43 7 43 23 190 34 117 16 Decision Maker Agent 13 14 2 59 8 67 12 89 32 Contaminant Source Industrial Demand Residential Demands (# Consumer Agents per node) 48 21 76 20 34 37 98 19 1 57 54 11 7 Each Consumer Agent represents 10 households 2510 Residential Consumer Agents 53 13 14 58 33 37 45 20 4

  9. Set of Scenarios Consumer Agents modeled only Conservative Decision Maker Agent Adaptive Decision Maker Agent

  10. Drink water once every 4 hrs. • If • consumer agent drinks water • and • contaminant concentration at node > 0 mg/L • then agent is sickened and stops drinking within 2 - 6 hours

  11. 43 Contaminant Source Introduced 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 12:00am 20

  12. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 12:20am 20

  13. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 12:40am 20

  14. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 1:00am 20

  15. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 1:20am 20

  16. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 1:40am 20

  17. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 2:00am 20

  18. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 2:20am 20

  19. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 2:40am 20

  20. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 3:00am 20

  21. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 3:20am 20

  22. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 3:40am 20

  23. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 4:00am 20

  24. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 4:20am 20

  25. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 4:40am 20

  26. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 5:00am 20

  27. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 5:20am 20

  28. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 5:40am 20

  29. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 6:00am 20

  30. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 6:20am 20

  31. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 6:40am 20

  32. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 7:00am 20

  33. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 7:20am 20

  34. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 7:40am 20

  35. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 8:00am 20

  36. 43 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 9:00am 20

  37. 43 859 sick consumer agents 794 consumer agents not drinking 34 13 Percentage of Sick Consumer Agents 2 8 59 67 12 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 32 89 48 76 20 34 21 37 98 1 11 19 57 Sensor Sensor with unusual WQ 54 7 53 13 33 37 45 58 10:00am 20

  38. * * * Average for 5 random trials • If consumer agent stops drinking water, then notify another consumer agent within 10 min - 1 hr • - If agent receives word-of-mouth information, then stop drinking immediately

  39. If consumer agent receives all-broadcast, then stop drinking within 30 min – 6 hrs. • If sensors show unusual water quality, then send no-drink broadcast to all consumer agents after 2 hrs.

  40. If sensors show unusual water quality, then open hydrant at sensor node after 2 hrs.

  41. If consumer agent receives all-broadcast, then stop drinking within 30 min – 6 hrs. • If consumer agent receives targeted broadcast, then stop drinking within 10 min – 1 hr. • If sensors show unusual water quality, then send targeted broadcast after 2 hrs. Reduce reaction time to 1 hr.

  42. If sensors show unusual water quality, then add another sensor in the near vicinity after 2 hrs. Reduce reaction time to 1 hr.

  43. If a sensor shows unusual water quality, then open a hydrant at the sensor node after 2 hrs. Reduce reaction time to 1 hr.

  44. 43 Percentage of Sick Consumer Agents Contaminant Source Introduced 34 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 13 2 8 59 67 12 32 89 48 76 20 34 21 37 Sensor Sensor with unusual WQ Hydrant opened 98 1 11 19 57 54 7 53 13 33 37 45 58 12:00am 20

  45. 43 Percentage of Sick Consumer Agents 34 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 13 2 8 59 67 12 32 89 48 76 20 34 21 37 Sensor Sensor with unusual WQ Hydrant opened 98 1 11 19 57 54 7 53 13 33 37 45 58 12:20am 20

  46. 43 Percentage of Sick Consumer Agents 34 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 13 2 8 59 67 12 32 89 48 76 20 34 21 37 Sensor Sensor with unusual WQ Hydrant opened 98 1 11 19 57 54 7 53 13 33 37 45 58 12:40am 20

  47. 43 Percentage of Sick Consumer Agents 34 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 13 2 8 59 67 12 32 89 48 76 20 34 21 37 Sensor Sensor with unusual WQ Hydrant opened 98 1 11 19 57 54 7 53 13 33 37 45 58 1:00am 20

  48. 43 Percentage of Sick Consumer Agents 34 0 – 20% 20 – 40% 40 – 60% 60 – 80% > 80% 13 2 8 59 67 12 32 89 48 76 20 34 21 37 Sensor Sensor with unusual WQ Hydrant opened 98 1 11 19 57 54 7 53 13 33 37 45 58 1:20am 20

More Related