Post on 14-Jan-2016
description
Technologies for Hazard Detection and Monitoring of
DamsTissa Illangasekare
Center for Experimental Study of Subsurface Environmental Processes, Colorado School of Mines
Anura Jayasumana
Department of Electrical and Computer Engineering
Colorado State University
Teton Dam, a 305-foot high earth fill dam across the Teton River in Madison County, southeast Idaho, failed completely and released the contents of its reservoir at 11:57 AM on June 5, 1976. Failure was initiated by a large leak near the right (northwest) abutment of the dam, about 130 feet below the crest. The dam, designed by the U.S. Bureau of Reclamation, failed just as it was being completed and filled for the first time.
Teton Dam Failure
On June 3, two small springs developed on the right abutment (clear water at 40-60 gpm) On June 4, another small spring found 150 ft from toe (20 gpm) June 5- (7:30 -8:00 am) ain leak flowing 20-30 cfs from a rock on right abutment near the toe
11:00 am- a whirlpool observed11:30 am- embankments eroding11:55 am the embankment fell into water and dam breached at 11:57 am 2-2.5 hours after the first seepage was observed, the dam failed releasing
251,000 act ftin 5 hours
What need to be monitored and how?
Need adequate time for warning
Observe parameters that are good indicators to detect failure
Warning needed for:
Possible failure of the dam
Flood risk and damage (evacuation)
Seepage
MovementPore-pressure
1. Embankment dams
2. Gravity dams
Tiltmeter
H
Displacement
3. Arch Dams
Multiple tiltmeters
d1
d1 d2 d3
d1 d2
d1 d2 d3 d4
SensorNetwork
SensorNetwork
Distributed Multi-sensor Network Monitoring
Monitoring
Decision Making
Utilize Networking and Processing Technologies to:
Achieve continuous real-time monitoring Overcome geographic limitations
Sensor Network for 3-D Transient Plume Monitoring (CSU/COSM/Sandia)
Spill
3-D Plume
SensorInstallationwells
Water table
Land surface
S-nodes
W-nodes
Example 1
Test-bed
Sensor Networks – Bridging Physical and Digital Worlds
Motes …………………..Cameras…...…….Radars, Observatories
Low data rates High data ratesPower limited Not power limitedProcessing limited Not processing limitedStorage limited Not storage limited
Example: CASA - Collaborative and Adaptive Sensing of the Atmosphere
assimilation/synthesis of
data
numericalweather
prediction
resource databasesensing,meteorological
utility functions
Control:what/when to sense,compute
policy
“external” users
signalprocessing
radars
Mote-based Sensor Networks
WirelessLow data ratesPower limitedProcessing limitedStorage limited
CPU 8-bit, 4MHZ
Storage 8kB Flash (Instructions)
512B RAM, 512B EEPROM
Communication 10kBps over 916 MHz radio
Operating System Tiny OS (3500B)
Available code space
4500 B
Ex. Seismology
1 km
• 38 strong-motion seismometers in 17-story steel-frame Factor Building.• 100 free-field seismometers in UCLA campus ground at 100-m spacing
http://nesl.ee.ucla.edu/tutorials/mobicom02/Deborah Estrin
Source: Technology Review, July/Aug 2003
Ex. Monitoring Water Quality
Distributed Multi-sensor Network Monitoring
Local Monitor
Choice of Technologies-Wired/Wireless/Hybrid-Manual/Automated……
SensorNetwork
SensorNetwork
Choice of Technologies-Simple communication relay-Personal Computer-Workstation- Engineer/Technician…..
Choice of Technologies-Modem dial-up-Dedicated phone/data line-Satellite-….
Monitor
Archive
ArchiveSensors Choice of Technologies-Server-Man in the loop (Engineer/Technician)-Control/Monitoring room…..
Choice of Technologies-Pressure-Tiltometers-Time-lapse photography-Real-time/Manual…..
Distributed Multi-sensor Network Monitoring
Local Monitor
SensorNetwork
SensorNetwork
Monitor
ArchiveArchive
SensorsOperational Modes:-Autonomous (Computer Based)
-Monitor-Change Monitoring -Send Alert
-Remotely Controlled /Manual-All information made available to remote location
-Hybrid of the two