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“By Trial and Error”. Why do we say that?. FA in Business?. When Toyotas Fail……. Drive it back to root cause!. Sports?. Medicine?. We’re nominating you for the Darwin Award!. A 48” culvert plugs on an abandoned road. Why do we respond?. Did not pay your electric bill?.

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by trial and error

“By Trial and Error”

Why do we say that?

slide13

When Toyotas Fail……

Drive it back to root cause!

why do we respond
Why do we respond?

Did not pay your electric bill?

stream diverts 200 ft down the road
Stream diverts

200 ft down

the road

the cost of no maintenance

The Cost of No Maintenance

This road was built in 2001 for approximately $750,000

the future
The Future?

Level 1 and 2 roads are roughly 60% of our total road miles.

monitoring road watershed performance
Monitoring Road-Watershed Performance

Suggested Initiative for Monitoring:

Combine effort to complete DSRs and INFRA to achieve road performance monitoring

roads are a focus of watershed monitoring
Roads are a focus of watershed monitoring
  • But roads vary greatly in performance
  • Most do not fail
  • Failures tend to cluster in areas of inherent instability
slide45
Why?
  • Failure sites create a useful dataset for defining road performance through time
  • Failures define the limits of practice in various landscape situations
  • When experienced road managers retire, mission-critical knowledge could be conserved
slide46
Why?
  • Little added effort for substantial value returned
    • INFRA in place and working
    • DSRs completed
    • Related monitoring
what you get
What you get
  • Ability to determine thresholds of performance
  • Ability to determine relative risk of failure
  • Quantitative description of risks
use topograpy to define landscape types for chi square analysis
Use Topograpy to Define Landscape Types for Chi-square Analysis

Slope:<=15%, 15-30%, 30-45%, >45%Slope Position:<=20%, 20-55%, 55-85%, 85-100%Distance to Stream:<34m, 34-74m, 74-135m, <=135m

a need for more specific risk information
A Need for More Specific Risk Information

Logistic Regression Modelling:

Combine 509 known failures with 1008 randomly selected locations.

Use slope, slope position, and stream proximity to estimate relative risk of road-related landslides.

relative odds of road related landslides

Slope 7%

Slopos 4%

Distance 27m

Landslide Odds 19X

Reference Segment

95% CL: 7, 51

Slope 23%

Slopos 19%

Distance 27m

Landslide Odds 39X

Reference Segment

95% CL: 15, 100

Reference Segment:

Slope 3%

Slpos 8%

Distance 213m

Relative Odds of Road-Related Landslides
how you get it
How you get it…
  • Add DSR points and attributes to INFRA
  • Some work remaining on attributes to ensure they are optimal
how you get it1
How you get it
  • Modify description block in DSR to include:

 Failure type

 Cause

 Volume (quantity classes)

      • Total
      • To stream
      • To riparian area (within 50 m)
cause attributes questions
Cause Attributes…Questions
  • Perpetrator or innocent bystander
  • Context
  • Impact

Sometimes roads catch and preventsediment delivery

canl systems
CANL Systems
  • Complex
  • Adaptive
  • Non-linear
  • Display emergent behaviors
  • Benefits emerge, destructive tendencies emerge
w w w

W W W

What Went Wrong?

canl systems1
CANL Systems
  • Context develops that controls perceptions and actions.
    • Activities that dampen disorder are encouraged
    • Activities that create disorder are discouraged.
  • Disturbances create disorder and provide opportunity to rebalance the system
our biggest challenge
Our biggest challenge
  • If consequences are hidden, slow, debatable, quiet….
  • CANL systems will tend to avoid detecting failures and therefore errors will chronically recur.

S.M.O.O. (Same Mistakes, Over and Over)

slide69
So…
  • Detect and analyze failures
  • Our own failings are paydirt!
  • Without this:

S.M.O.O.

Don’t let the system suppress your right to learn from your failures and teach others

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