Unfrozen

Table 6 (cont'd). Results of regression analyses--test soils from Mn/ROAD.

B. Unfrozen condtion

Equation (Mr in

Clay subgrade sample 1206 (565)

Mr = 1, 597, 000 f (S)-2.63 f (γ )14.42 f3 (σ)-0.257

Clay subgrade sample 1232 (566)

Mr = 1.518 1030 f (S)-13.85 f3(σ)-0.272

Class 3 "stockpile"

Mr = 283, 300 f (S)-1.003 f2 (σ)0.206

Class 4 (taxiway A subbase)

Mr = 8.946 108 f (S)-3.026 f2 (σ)0.292

Class 5 (dense graded stone)

Mr = 382, 400 f (S)-0.8759 f2 (σ)0.1640

Class 6 "stockpile"

Mr = 1, 391 f (S)-0.507 f (γ )4.04 f1(σ)0.608

Mr = 5, 257 f (S)-0.486 f (γ )4.05 e0.0193 f1(σ)

*Output from equations can be converted to kilopascals through multiplying by 6.895

σd, Deviator Stress

σd, Deviator Stress

a. 1206 Subgrrade

b.1232 Subgrrade

Temperature (C)

Temperature (C)

Figure 5. Effect of stress on frozen resilient modulus.

choice of coefficients for the distribution of unfro-

Figure 6 compares the modulus vs. tempera-

zen water content with temperature.

ture for all the frozen Mn/DOT materials pre-

dicted from the regression equations in Table 6,

with the governing parameters wug/wt and wuv.

Figures 7a through 7f show the resilient modu-

At any given temperature, the subgrade specimens

lus data vs. degree of saturation for the unfrozen

have the lowest moduli. In general, the base and

specimens. For the two subgrade materials, data

subbase moduli increase with decreasing amounts

are from specimens that were never frozen, and

of fines in the material. The curve for the class 5

data from the base/subbase materials are from

special material has a slightly different shape than

specimens that were thawed subsequent to freez-

the rest, which is probably related to the estimated

Western Governors University

Privacy Statement
Press Release
Contact

Integrated Publishing, Inc. - A (SDVOSB) Service Disabled Veteran Owned Small Business