Slopes

exercise

Which material is cohesive?

Material B is cohesive

How do you know?

Material B is cohesive becuase the linear relationship has a finite intercept, which is the cohesion value. Material A has an intercept of 59.054, which is much less than the value for material B.

What is the cohesion value for the cohesive material?

The cohesion value for material B is 3,947.8 pascals.

Given a normal force of 4000 pascals what will be the shear strengths of the two materials?

Material A

y= 0.696(4,000)+59.054= 2,843.054 pascals

Material B

y= 0.714(4,000)+3,947.8= 6,815.8 pascals

Generalize the relationships that you graphed above using a mathematical formulation.

What do the data define?

The data define a linear relationship between shear strength and normal force.

What is the general formula for this pattern?

Formaula of a line: y=mx+b or S = C + σtanϕ

What is the specific formula for Material A?

y= 0.696x+59.054 or Shear Strength = 0.696x + 59.054

What is the specific formula for Material B?

y= 0.714x+3,947.8 or Shear Strength = 0.7171x + 3947.8

What is the friction angle for Material A and Material B?

Determine under what conditions the 2019 Riverside Avenue slide failed

Dry density (rho) = 1800 kg/m³ Slab thickness (h) = Range of 1 - 10 (m)

Wet density (rho) = 2200 kg/m³ Failure Plane angle (alpha) = Range of 10 - 30 (degrees)

Gravity = 9.8 m s^-2 Cohesion = Range of 2000 - 9800 (pascals)

Phi angle = 30 degrees Saturation depth = Range of 1 - 5 (m)

are the model results consistant with land use changes over time?

The results given by the model are consistent with the land use changes seen over time. Prior to the Halloween night landslide, we know that the slope was unstable from observations of cracks in the parking lot at the top of the slope. This observation is also found looking at the models. We can model with a low level of saturation (before heavy rainfall) and with high saturation (after heavy rainfall). We can see that with low saturation the model predicts "safe" and with high saturation the model predicts "slide". So we can concur that before the Halloween night landslide, the slope was unstable because the model predicts close to 1 but after a heavy rainfall the model predicts under 1, which is a slide; and this is exactly what we saw!

Some of the models more accurately represent land use change, while some are not so accurate to what we have witnessed. We know that a lot of trash dumping has occured over the bank, and this could be best reflected by cohesion in the model. This would result in poor cohesion, which plays a big part in predicting if the slope is safe or will slide. The bottom 3 models show the same data, but with just the cohesion value changing. We can see that as the cohesion decreased, the F value also decreased. Knowing that the soil was very saturated when the slide occured and adding to that a poor cohesion level, it was inevitable that a slide was going to occur.