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From page 42... ... 42 CHAPTER 3 FINDINGS AND APPLICATIONS This chapter describes the results of analysis of full-scale pavement data and the use of developed tools to further analyze pavement data to characterize slab-base interaction. Influential factors in pavement performance models are discussed. Read the entire page →
From page 43... ... 43 Table 7. Backcalculated subgrade k-values for LCB and PSAB base type (normalized to AGG base parameters) Read the entire page →
From page 44... ... 44 the full-bond state on a section-by-section basis. For a full-slip interface Λ∗ ൌ 0.0001, and for a fully bonded interface ߉∗ ൌ 100. Read the entire page →
From page 45... ... very high in betwee friction c Figur Figure 19 location a transition A similar these disc bond betw affect the pavemen T was appl conclude for slab-b the hypot behavior reliably d However character interactio can be re H a simplif laborator degrades the PCC due to ch slab-base value in Au n. At the sa oefficients f e 19. Read the entire page →
From page 46... ... 46 Λ௝ାଵ∗ ൌ Λ௝∗ ∙ ݁ି ∑ ൬ ೎்,೘ೌೣି்೎,೘೔೙஼೑ ൰೔ Λଵ∗ ൌ ܮ∗ ܧ௉஼஼݄௉஼஼ܧ௉஼஼݄௉஼஼ ൅ ܧ௕௔௦௘݄௕௔௦௘ 56 where Tc,max and Tc,min are the maximum and minimum constant strain temperatures in the concrete slab for the month, i, respectively, Cf is a friction degradation parameter, index j denotes age in years, and ܮ∗ is the initial non-dimensional friction factor. The simplified friction deterioration model was implemented in the alternative cracking model developed in this study and described below. Read the entire page →
From page 47... ... Figure 2 Although sense, clo for desig extracted profiles a contribut materials irregular slabs clo Figure This anal limited to 0. Effect of the standar se examina n purposes i from the pr re close, the e to varianc , or environ slab profile se to early fo 21. Read the entire page →
From page 48... ... 48  Sensitivity studies of the AASHTO M-E models determined that modifications to T can result in improved model predictions relative to observed performance for the AASHTO M-E calibration projects (Section 2.4) Read the entire page →
From page 49... ... 49 3.2.1 Transverse cracking model To improve consideration of the interaction between the concrete slab and underlying layer in JPCP transverse cracking prediction, an alternative JPCP transverse cracking prediction procedure was proposed. The main steps of the proposed procedure are the same as the AASHTO M-E transverse cracking production and include the following: 1. Read the entire page →
From page 50... ... The mod AASHTO model wa 95% of th Equation assumed A used to d friction a coefficien conducte calibrated cracking resulted i in Figure by base t Figur Figure 22 bias for a types, the 0.9371, r the perfo ified JPCP t M-E calib s assumed f e bottom su 45 is equal to be equal n initial cali etermine the nd friction d ts of 0.211 d using sect by minimi model coeff n values of 22 are the l ype. Read the entire page →
From page 51... ... with asph PSAB se 3.2.1.1 C The mod interactio inch JPC used the have iden the defau file) Read the entire page →
From page 52... ... Figure 2 The crack procedur model re in structu 3.2.1.2 S A factori The simu the factor performa O the initia simulatio initial fri underesti the predi 4. Crackin ing perform e is shown i solves the is ral modelin ensitivity an al of simula lations utili ial focused nce in terms ne subset of l slab-base f ns. Read the entire page →
From page 53... ... Figure 2 Another discussed the streng stresses o develope length is modified 5. Perform subset of the in Section th criteria i nly, corresp d strength cr selected to b strength cri ance of LTP factorial ex 2.2.1.5. Read the entire page →
From page 54... ... Figure Another the modi effects on Figu 26. Perfor length sensitivity a fied built-in the damag re 27. Read the entire page →
From page 55... ... 55 The influence of the calibration parameter A in Figure 27 allows for a more direct modification of built-in curl by the user to adjust A to account for the stiffness of the base material relative to that of the slab. In this way, Equation 57 can then help assess the effects of slab-base interaction on transverse cracking. Read the entire page →
From page 56... ... Each figu 28a show the magn these par Figure calibrat To impro values sh type (SSE relatively should be modified     ܵܵܧ ൌ re identifies s that the C itude of the ameters. Read the entire page →
From page 57... ... Figure Figure 29 near pari granular respectiv This is du calibratio projects w T illustrate F faulting m   As descri alternativ differenc 29. Modifi L shows that ty that is pre bases, this li ely. Read the entire page →
From page 58... ... Figure 3.2.3 P To obtain (Equation calibratio The fatig outs was -3.630 fo A was cond CRCP pu were assu 12, 14, 1 was expr and predi The resul simulatio That is, a M-E cali 30. Compa alternative unchout mo alternative 12) Read the entire page →
From page 59... ... 59 Table 11. Statistics for CTB and PSAB calibration sections from the LTPP GPS-5 experiment f Sum of Squared Error CTB PSAB 0.25 27500 51343 1 20799 36932 2 12431 29036 4 3955 11968 6 2560 7189 8 3486 5579 10 4857 12029 12 4941 12178 14 4942 12178 16 4942 12178 18 4942 12178 20 4942 12179 22 4942 12180 24 4942 12180 The sum of the squared difference between the observed and predicted cracking values was used to assess the recommended value of f by base type for the guidelines for the AASHTO M-E procedures. Read the entire page →
From page 60... ... The effec illustrate compares sections:   Figure 31 t of the mod d using LTP the AASH Section 2 reinforcem Section 2 reinforcem . Predicted ifications to P projects fr TO M-E pun 8-5803, a 7.9 ent and wit 8-5805, a 8. Read the entire page →
From page 61... ... Figure 3 3.3 IM PROCED The impl developm section. 3.3.1 A The trans transvers inputs req prior to tr performs required AASHTO           As the al the AASH 2. Read the entire page →
From page 62... ... 62 neural network files. Information on these files is provided in the AASHTO M-E documentation (ARA, 2004) Read the entire page →
From page 63... ... 3.3.3 C The alter generated perform t and fault faulting a T AASHTO FORTRA software slab-base project. T Step One model, th program "C:\NCH created d input fiel Figur Step Two existing A selected. Read the entire page →
From page 64... ... Number AASHTO directory Figure 3 O navigator shown in Step Thre alternativ input the numbers       1, in red. Up M-E proje of projects 4. Read the entire page →
From page 65... ... Fig Step Fou required project. Read the entire page →
From page 66... ...   These ou generated in the firs month fo complete shown in Figure 3 3.4 A This sect with the 0217, a J is an 8.1AADTT service li F model fo interface fully bon predict su cracking "151_JPC Cracking "151_JPC model. tput files are and used b t line of the r every mon d, the rudim Figure 37. Read the entire page →
From page 68... ... Fig ure 39. LTPP 4-0217 performanc 68 e prediction given user-defined friction data Read the entire page →

From page 42...

... 42 CHAPTER 3 FINDINGS AND APPLICATIONS This chapter describes the results of analysis of full-scale pavement data and the use of developed tools to further analyze pavement data to characterize slab-base interaction. Influential factors in pavement performance models are discussed.