Presentation on theme: "Lec 29, Ch.20, pp.990-1007: AASTHO flexible pavement design method (objectives) Know the factors considered in the AASHTO design method Become familiar."— Presentation transcript:
Lec 29, Ch.20, pp.990-1007: AASTHO flexible pavement design method (objectives) Know the factors considered in the AASHTO design method Become familiar with use of Tables 20.13a and b through 20.18 and Figures 20.15 through 20.20 Know how the structural numbers are used in thickness determination Become thoroughly familiar with the structural design process of the AASHTO flexible pavement design method
What we discuss in class today… Design considerations Use of tables and figures related to the factors considered Structural design procedure
Design considerations for the AASHTO Flexible Pavement Design Pavement performance Traffic Roadbed soils (subgrade material) Materials of construction Environment Drainage Reliability The following factors are considered in the pavement thickness design.
Pavement performance Structural Cracking, faulting, raveling, etc. Functional Riding comfort (measured in terms of roughness of pavement.) Serviceability Performance: Measured by PSI Present Serviceability Index with scale 0 to 5. 0 “Road closed” 5 “Just constructed” 4.2 Initial PSI (p i ) Terminal PSI (p t ) 2.5 to 3.0 for major highways 2.0 for lower class highways 1.5 for very special cases PSI
Traffic In the AASHTO flexible pavement design, traffic is considered in terms of ESAL for the terminal PSI (Table 20.13 for p t = 2.5.) You must assume the structural number of the pavement. So, you must check if the final SN 3 is similar to the assumed SN. Higher SN means stronger pavement, thus the impact of traffic on pavement deteriorations is less.
Roadbed soils (Subgrade material) CBR (California Bearing Ratio), R-value (Resistance), and M r (Resilient modulus) are used to describe the property of the subgrade material. During the structural design, only M r values are used. The following conversion formulas are used if either CBR or R- values are given. M r (lb/in 2 ) = 1500 x CBR for fine-grain soils with soaked CBR of 10 or less. M r (lb/in 2 ) = 1000 + 555 x (R-value) for R <= 20
Materials of construction (Subbase), a 3 Charts are available to convert the properties of pavement construction materials to structural numbers: a 3, a 2, and a 1 Structural number of the subbase, a 3 Use CBR, R-value, or M r to find a 3 values
Materials of construction (Base course), a 2 Base! Structural number of the base course, a 2 Use CBR, R-value, or M r to find a 2 values
Materials of construction (AC surface), a 1 = Resilient modulus, M r Structural number of the AC surface, a 1 0.44
Environment Temperature and rainfall affect the level of strength of the subgrade, reflected on the value of resilient modulus. AASHTO developed a chart that helps you to estimate the effective roadbed soil resilient modulus using the serviceability criteria (in terms of “relative damage, u f.”) Determine the average u f. value and obtain M r from the chart or the equation of u f.. The bar on the right is used twice: Once to read u f value for each month’s sample M r, then to read annual average M r using the average u f value. Step 1 Step 3 Step 2
Drainage The effect of drainage on the performance of flexible pavements is considered with respect to the effect water has on the strength of the base material and roadbed soil. This effect is expressed by the drainage coefficient, m i. This value is dependent on the drainage quality and the percent of time pavement structure is exposed to moisture levels approaching saturation.
Definition of drainage quality and finding recommended m i values Time required to drain the base/subbase layer to 50% saturation. If “Fair” and 30% exposure, then m i is 0.80. Step 1 Step 2
Reliability The reliability factor (F R ) is computed using: The Reliability design level (R%), which determine assurance levels that the pavement section designed using the procedure will survive for its design period (it is a z-score from the standard normal distribution the standard deviation (S o ) that accounts for the chance variation in the traffic forecast and the chance variation in actual pavement performance for a given design period traffic, W 18. SD, S o Flexible pavements 0.40-0.5 Rigid pavements 0.30-0.40 Why do we have a negative sign here? Are Z R values negative? Why not Z R S o ! Well the clue is in Eq. 20-13 and the bell curve shown below. One-sided Z- score is used here. Survive Fail
Structural design The object of the design using the AASHTO method is to determine a flexible pavement SN adequate to carry the projected design ESAL. The method discussed in the text (Example 20-8) applies to ESALs greater than 50,000 for the performance period. The design for ESALs less than this is usually considered under low-volume roads. Simplify this as f(W 18 ) = f(Z R S o ) + f(SN) We will keep the ESAL value constant and try to prove whether Z R must be negative or not. Note that S o and SN are always positive. Standard deviation is always positive because it is a physical difference from the mean value, and SN is also positive because it means pavement thickness. Where,
Solving the riddle of the negative values of Z R f(W 18 ) = f(Z R S o ) + f(SN) ESAL is an estimated value. It may actually more or less. In the design formula, however, the ESAL value is set to a constant. Then to make sure the pavement survive, you have to have a thicker one than the thickness that the estimated ESAL requires. To make that happen in the design formula, we need to subtract a value from the RHS. Hence, the reliability factor must be negative. The only way to make Z R S o smaller is to have a negative value of Z R because S o is always positive.
How to use Fig. 20.20 to get structural numbers based on Eq. 20.13 This line has nothing to do with Example 20-8. This line is for the subgrade in Example 20-8. M r =1500*6=9000 SN 3 = 4.4 For subbase, M r =13,500 For base course, M r =31,000 SN 2 = 3.8 SN 1 = 2.6
Once SN value is set, thickness design begins… Proceed in this direction Use Fig.20.15 for a3, Fig.20.16 for a2, Fig.20.17 for a3, and Tab. 20.14 and 20.15 m2 and m3. Find the depth that results in a SN value close to the SN value obtained from Fig. 20.20.
Example 20-8 Given: ESAL = 2 x 10 6 One week for water to be drained Saturation level moisture exposure = 30% of the time AC’s M r at 68F o = 450,000 lb/in 2 CBR of base course =100, M r = 31,000 lb/in 2 CBR of subbase =22, M r = 13,500 lb/in 2 CBR of subgrade = 6, M r = 1500CBR= 6*1500 = 9000 lb/in 2 Rural interstate Parameter values: Reliability level (R ) = 99% from Tab. 20.16 Standard Deviation (S o ) = 0.49, Table 20.16, p.973 Initial serviceability, p i = 4.5 Terminal serviceability, p t = 2.5 Drainage mi values = 0.8 for “Fair” category in Tab. 20.14 and “Greater than 25%” category in Tab. 20.15