1. Road Deterioration, Works Effects and Calibration Presenter: William D. Paterson, World Bank HDM-4 Tutorial 9 August 2001, Seattle, WA

2. HDM-44 Road & Pavement Classification

3. Modeling Framework §For each pavement Type there is a generic model which describes how the pavement deteriorates §To take account of the different behaviour of a particular pavement Type constructed with different materials, the coefficients of the generic model depend on the different combinations of the materials §After maintenance treatments the generic pavement type can change

4. Bituminous Pavements Deterioration Modelling

5. Pavement Classification System (Bituminous Pavements)

6. Pavement Classification System Surface Type AM - Asphalt Mix ST - Surface Treatment Surface Material §Asphalt concrete §Hot rolled concrete §Polymer modified asphalt §Rubberised asphalt concrete §Soft Bitumen mix (cold mix) §Porous asphalt §Stone mastic asphalt §Cape seal §Double bituminous surface dressing §Single bituminous surface dressing §Slurry seal §Penetration macadam

8. Pavement Strength §The strength of bituminous pavements is characterised by the adjusted structural number - SNP §The SNP applies a weighting factor, which reduces with increasing depth, to the sub-base and sub-grade contributions so that the pavement strength for deep pavements is not over-predicted. §SNP S = SNBASU S + SNSUBA S + SNSUBG

9. Seasonal and Drainage Effects §The average annual SNP used in the models is derived from SNP d and SNP w, and the lengths of the dry and wet seasons § SNP = f s *SNP d §Drainage effect on pavement strength is modelled through the changes in the drainage factor DF [1 excellent - 5 very poor] § f = f (MMP, DF, ACRA, APOT)

10. Construction Quality §Poor construction quality results in greater variability in material properties and performance §Relative compaction of the base, sub-base and selected subgrade layers - COMP §Construction defects indicator for bituminous surfacings - CDS (based on binder content 0.5 brittle, 1.0 normal, 1.5 soft) §Construction defects indicator for the base - CDB based on gradation of material, aggregate shape, etc. (0 no defects, 1.5 several defects)

11. t 1 t 1 Water ingress Further cracking Patches Shear Uneven surface Spalling Faster deformation ROUGHNESS Potholes Patches Time Uneven Surface Lower strength Area of Cracking Rut depth

12. Cracking §Two types of cracking: §Structural cracking - modelled as ‘All’ and ‘Wide’ cracking §Transverse thermal cracking §(Reflection cracking to be included)

13. All Cracking Initiation l ICA=K cia {CDS 2 *a 0 exp[a 1 SNP+a 2 (YE4/SN 2 )] + CRT} l ICAtime to cracking initiation, in years l CDSconstruction defects indicator for bituminous surfacings l SNPstructural number of pavement l YE4annual number of ESALs, in millions/lane l K cia calibration factor for cracking initiation l CRTcracking retardation time due to maintenance

14. Crack Initiation

15. Crack Progression

16. Rut Depth §Four components of rutting: l Initial densification l Structural deformation l Plastic deformation l Wear from studded tyres §RDM=min[(RDO+RDST+RDPD+RDW), 100]

17. Structural Deformation

18. Plastic Deformation §  RDPD = K rpd CDS 3 a 0 YE4 Sh a1 HS a2 l  RDPD incremental increase in plastic deformation in analysis year, in mm l CDS construction defects indicator for bituminous surfacings l Sh speed of heavy vehicles, in km/h l HS total thickness of bituminous surfacing, mm l K rpd calibration factor

19. Roughness §  RI = K gp [  RI s +  RI c +  RI r +  RI t ] +  RI e §  RI e = K gm m RI a l  RItotal incremental change in roughness during analysis year, in m/km IRI l menvironmental coefficient l K gp calibration factor

20. Concrete Pavements Deterioration Modelling

23. Structural Characteristics §The principal data for predicting the deterioration of concrete pavements: §Properties of materials §Percentage of reinforcement steel §Drainage conditions §Load transfer efficiency (across joints, and between slabs and shoulder) §Widened outside lanes

24. Cracking - JP Pavements §Transverse cracking (% of slabs cracked) is modelled as a function of cumulative fatigue damage in the slabs and: §Cumulative ESALs §Temperature gradient §Material properties §Slab thickness §Joint spacing

25. Faulting §The average transverse joint faulting is predicted as a function of: §Cumulative ESALs §Slab thickness §Joint spacing and opening §Properties of material §Load transfer efficiency §Climate/environment (FI, PRECIP, DAYS90) §Base type §Widened outside lanes

26. Roughness §For JP concrete pavements, roughness is calculated as a function of faulting, spalling and cracking §For JR and CR concrete pavements, roughness is calculated as a function of PSR

27. Calibration of Pavement Relationships §Level 1 – Desk-based study & minor field work §Level 2 – Based on field survey data of sample of pavement sections §Level 3 – Based on long-term pavement performance data to reconfigure predictive relationships

28. Pavement - Sensitivity Ranking

29. Pavement Models - Level 1 Calibration l Estimate unmeasured parameters from table, e.g. environmental ‘m’ l Estimate calibration factors through secondary information (tables, etc.) l Verify that average predicted condition is similar to current condition

30. 16 Pavement Models - Level 1 Verification § Simulation of Past l take sample of roads with historical data (traffic, design, etc.) l predict deterioration from construction to current age (using HDM or s/sheet) l compare results § Average predicted condition should be similar to current condition

31. Pavement Models - Level 2 Calibration § Age-environment: l sample 5 sections x 2-4 climatic zones l compute m from IRI, NE, SNC, AGE § Crack Initiation: l 15 sections per surface-climate group (prefer “low” distress) l Kci = mean Obs’d / mean Predicted § Crack progression: similarly

32. Level 2 Calibration of Environment coefficient ‘m’ for Roughness Progression Prediction m = {ln [RI t ] - ln [RI 0 + 263 NE (1+SNC)^-5]}/ AGER

33. Adaptation of IQL-3 to IQL-2 input

34. Pavement Models - Level 2 Calibration (cont) § Rut depth progression (low) l 20 x 200m sections (30 for thin & thick AP), 50% with mean RD> 6mm l use prediction equation & calculate geometric means of Obs & Pred § Ravelling initiation (low) § Potholing Initiation (low)

35. Pavement Models - Level 2 Calibration (cont) § General Roughness Progression (low) l 4-yr series of reliable roughness data, 20+ sections (>10 / pavement type) l determine incremental data l calculate Predicted using algorithm l compare Obs & Pred, check residuals

36. 17 Pavement Models - Level 3 § Controlled Long-term Studies l collects detailed data over time on traffic, roughness, deflections, condition, rut depths l sections must be continually monitored l long-term (5 yr) commitment to quality data collection § Advanced statistical analysis & modelling

37. Works Effects

38. HDM-44 Road Works Classification

39. Works Standards

40. HDM-45 Defining Road Works §Intervention Criteria l scheduled at a fixed time or intervals, multiple points in time l responsive, condition, strength, speeds, flows, accidents l Limits: time, roughness, traffic §Design l pavement structure, road geometry, road type and class §Effects l pavement strength, condition, history, road use §Duration and Costs

41. Works Effects and Costs C b1 C b4 C b2 = C a3 Years15432 Percent total costs 100 C a2 C ao Road variable 15432Years C bo = C a1 Scheduled intervention Responsive intervention Note: C ay = Variable at the beginning of year y C by = Variable at the end of year y

42. Bituminous Pavements Works Effects

44. Drainage Works §Drainage maintenance is modelled through its effect on pavement strength, SNP §f =  (MMP, DF, ACRA, APOT) §After drainage works DF is reset based on DF bw and DMCF (drainage maintenance cost factor) §DMCF is defined as the ratio of the annual cost of drainage works performed to the annual cost required to maintain the drainage system in excellent condition

45. Resealing §Resealing without shape correction can repair surface distress but cause little change to roughness or structural strength §Resealing with shape correction can achieve some reduction in roughness through the filling of depressions and repair of damaged areas §Not performed if AGE2 < user-specified minimum §Preparatory works applied and quantities calculated separately, roughness reset to RI ap

46. Overlay §Adds structural strength, SNP §Not performed if AGE3 is less than the user-specified minimum, or if AGE2 < 4 or if AGE1 < 2 §Preparatory works (patching and edge repair) are applied §Resets surface distresses to zero, rutting to 0.15*RDM bw (by default) §Resets roughness as a function of roughness before works and the overlay thickness §Resets pavement age, previous cracking, TD, SFC, etc.

47. Widening §This includes lane addition and partial widening, and it is assumed that these operations will not alter the road alignment §Specified by the new road type (speed-flow), road class, increase in width or number of lanes, pavement type for the entire section, pavement details of the widened part of the carriageway, etc. §Additional works include re-surfacing the existing carriageway, patching, crack sealing §The modelling parameters are the weighted average of the original pavement and the pavement widening

48. Upgrading §Involves pavement upgrading and geometric improvements §Changes the existing surface class to another surface class of a higher performance grade §Specify new length, width, road geometry, pavement details, road type, road use, RD factors, etc. §Downgrading??

49. Concrete Pavements Works Effects

55. 23 Can We Believe HDM-4 Output? § Yes, when calibrated § HDM has proved suitable in a range of different countries and conditions § As with any model, need to carefully scrutinise output against judgement § If predictions are unexpected, review (a) data, (b) calibration, (c) your judgement!