Jamnik Julijana_Pavement Management System _PMS_ Implementation on Slovene Motorway Network

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  1 PAVEMENT MANAGEMENT SYSTEM (PMS) IMPLEMENTATION ON SLOVENE MOTORWAY NETWORK Julijana Jamnik, B.Sc. in CE DDC Consulting & Engineering Ltd Kotnikova ulica 40 SI – 1000 Ljubljana e-mail:  Abstract   DDC Consulting & Engineering Ltd is setting up a Pavement Management System application (PMS-DARS) on Slovene motorway network for DARS, the Motorway Company in the Republic of Slovenia. dTIMS_CT (Deighton Total Infrastructure Management System, Concurrent Transformation) software is used for this purpose.  A very significant part of PMS-DARS is an automatic pavement design procedure which calculates thickness of needed overlay according to traffic loading and existent pavement structure, its condition and its age. The Life Cycle Cost Analysis enabled DARS to estimate the needed funds for pavement rehabilitation in the next 15 years and also to see the consequences of insufficient maintenance budgets. Results provide the decision makers with   ̶ condition of the road network as a result of individual (limited) budgets,   ̶ average pavement condition of the network as a result of individual (limited) budgets,   ̶ length of the network in backlog (length of road network in poor and very poor condition),   ̶ treatment cost and length summary (the cost and the length of network maintained with individual treatment) and   ̶ return on investment (the relation between cumulative investment and the resulting average network condition) On the other hand the technical staff gets the detailed short- and long-term maintenance plan based on the administration costs and user benefits, in which defines the type of the treatment, the year of the treatment and the cost of the treatment. Key words:  PMS – Pavement Management System, Life Cycle Analyses, Pavement Design  2 1 OVERVIEW OF PMS-DARS Slovenia started the National Motorway Construction Programme (NPIA) in 1994. Until May 2007 374 kilometres of four or more lane motorways were built. In 2013 Slovenia shall have approximately 660 kilometres of modern motorways in use. Although the building of new motorways has first priority, the increasing length of network demands more and more money for pavement maintenance. DDC Consulting & Engineering Ltd with a help of expert consultant Dr. Alfred Weninger-Vycudil from PMS-Consult Vienna is setting up a Pavement Management System application (PMS-DARS) on Slovene motorway network for DARS, Motorway Company in the Republic of Slovenia. dTIMS_CT (Deighton Total Infrastructure Management System, Concurrent Transformation) software was used for this purpose. The PMS-DARS application consists of two basic parts: database and life-cycle analyses. To be able to set up a pavement management system the detailed information about pavements is essential. Therefore an existing DARS database was searched for needed information about inventory data, road geometry data, pavement structure data (layer material, thickness and age) and traffic data and a set of pavement condition measurements was performed in 2005 to establish the initial condition of pavements on entire motorway network. Visual pavement condition survey was performed by the methodology of Modified Swiss Index (MSI), which includes cracking, patching, revelling and deformation. Longitudinal evenness (expressed with IRI – International Roughness Index), transverse evenness (expressed with the rut depth) and skid resistance were also measured. For determination of short-, medium- and long-term maintenance plans the deterioration models were developed of individual pavement properties. With those models each pavement property can be calculated for any year in the future. A treatment catalogue with different maintenance treatments was established where triggers, resets and unit prices were defined. A model for benefit calculation, which arises from application of maintenance treatments, was also defined so the maintenance priorities could be established. Those are particularly important when maintenance budgets are insufficient. When all of the above is defined, PMS-DARS each year according to deterioration models changes individual pavement properties and compares achieved pavement condition with triggers from treatment catalogue. If the condition is poor or very poor, an appropriate treatment is triggered (for instance overlay, reinforcement or reconstruction) and all pavement properties are reset to defined values. If all pavement properties are in good or very good condition a treatment is not triggered.  Afterwards a system moves into the next year and deteriorates all pavement properties. This procedure continues until the last analysis year. Each application of maintenance measure causes expense to the manager of the road network and benefit to road users. A ratio benefit/cost is calculated for each section and treatment strategy and a priority is assigned.  An optimisation procedure chooses optimum maintenance strategy for each road section, taking into account different maintenance budgets defined. This way a needed budget can be determined for a certain level of serviceability or a road condition can be determined which can be achieved with certain budget. In the paper two parts of PMS-DARS are presented in detail, namely ã  the transformation of pavement condition properties into dimensionless indices, a combination procedure into sub-indices and finally into Total Condition Index and ã  the automated pavement design procedure. 2 TRANSFORMATION OF PAVEMENT CONDITION PROPERTIES INTO DIMENSIONLESS INDICES, COMBINATION PROCEDURE OF INDICES INTO SUB-INDICES  AND INTO TOTAL CONDITION INDEX In PMS-DARS pavement condition is characterised with: ã  surface defects, expressed with Modified Swiss Index (MSI), taken with visual pavement condition evaluation, ã  longitudinal evenness, expressed with International Roughness Index IRI, ã  skid resistance and ã  transversal evenness. Each pavement condition property is expressed in different unit. Therefore they were transformed into dimensionless indices on a scale from 0 to 5, where class [0-1) represents very good condition, [1-2) good condition, [2-3) fair condition, [3-4) poor condition and [4-5] very poor condition, according to Technical Specifications (Jamnik and Weninger-Vycudil, 2006). Figure 1 presents the example for transformation of rut depth (mm) into Index Rut Depth (I_Rut).  3 Transfromation of Rut depth into Rut Index 610181422 0,00,51,01,52,02,53,03,54,04,55,00510152025 Rut depth [mm]    R  u   t   D  e  p   t   h   I  n   d  e  x   I_   R  u   t .  Very good Good Fair Poor Very poor    Figure 1: Transformation of rut depth into index rut depth I_Rut Figure 2 shows the procedure for obtaining individual condition indices, Comfort and Safety Index, Structural Index and Total Condition Index (Weninger-Vycudil, 2004). For bearing capacity purposes a Structural Index (I_St) was developed which shows the pavement fatigue and depends on age (Structural Index Age – I_St_Age) and pavement condition (Structural Index Condition – I_St_Cond) – Eq. 1. All decrease in bearing capacity is attributed exclusively to the bound layers. ( ) Cond St  I  AgeSt  I 0,7  MAX St  I   _  _ ; _  _  _   ⋅=  (1) Until the first pavement rehabilitation all bituminous layers have the same age. With the first maintenance treatment usually a wearing curse or even a part of bituminous base courses are removed and replaced with new courses. Old layers are already fatigued from climatic, traffic and other influences and do not contribute as much as new layers to bearing capacity of pavement structure. Those changes are described with Structural Index  Age. It depends on the age of wearing course (I_Age_WC) and on the age of underlaying bituminous courses (I_Age_BBC). The age of the unbound layers at the time of the last rehabilitation is not taken into account (Weninger-Vycudil, 2004). Eq. 2 shows the calculation of Structural Index Age for wearing courses and Eq. 3 of Structural Index  Age for underlaying bituminous courses. ( ) ⎟⎟ ⎠ ⎞⎜⎜⎝ ⎛ ⎟ ⎠ ⎞⎜⎝ ⎛ −⋅=  10 _ 135;0;5 _  _   WC  Age MAX  MIN WC  Age I   (2)   ( ) ∑∑  == ⋅⋅= niiinii  BBC  Age I  Deb  Deb BBC  Age I  22  _  _ 1 _  _    (3)   where i  BBC  Age I   _  _   is a Structural Index Age of course i  under wearing course (Eq. 4). 2513 _ ;0;5 _  _   ≥⎟⎟ ⎠ ⎞⎜⎜⎝ ⎛ ⎟ ⎠ ⎞⎜⎝ ⎛  −=  i for Plast  Age MAX  MIN  BBC  Age I   ii   (4) where i  number of layer, counted from top to bottom n  number of bituminous layers under wearing course WC  Age  _   age of wearing course (years) i Plast  Age  _   age of individual bituminous layer under wearing course (years) WC   Deb  thickness of wearing course (cm) i  Deb  thickness of bituminous layer i under wearing cou Joint Structural Index Age is calculated according to Eq. 5.   ∑∑ == +⎟ ⎠ ⎞⎜⎝ ⎛ ⋅+⋅= niiWC niiWC   Deb Deb Deb BBC  Age I  DebWC  Age I   AgeSt  I  22  _  _  _  _   _  _    (5) Structural Index Condition is expressed with Equation 6. ⎥⎦⎤⎢⎣⎡⋅⋅=  Rut  I  Rut  IRI  I  IRI  MSI  I  MAX Cond St  I   _ 1600; _ 25,20; _  _  _  22  ( 6) The optimisation (the choice of optimal maintenance strategies) is possible only on one variable and because of that a joint condition index was defined according to Eq. 7. [ ] St  I 0,89CSI  I  MAX Total I   _ ; _  _   ⋅=  (7) 3 AUTOMATIC PAVEMENT DESIGN PROCEDURE  A very significant part of PMS-DARS is an automatic pavement design procedure which calculates thickness of needed overlay according to traffic loading and structural number of existent pavement structure (AASHTO, 1986), which takes into account the condition and age of bituminous layers. Structural number of existent pavement (D exist ) is calculated according to Eq. 8. ( )  [ ] cmr ad  D niiiiexist   ∑ = ⋅⋅= 1  (8)  4 Figure 2: Combining condition indices into sub-indices and into Total Condition Index n  number of bituminous layers d i  thickness of bituminous layer i  (cm) a i material coefficient of bituminous layer i   ri reduction coefficient of bituminous layer i The reduction coefficient of individual bituminous layer depends of age of that layer and of condition of the pavement (Eq. 9 and Eq. 10). ) _  _  _ ; _  _ ( _   Cond St  I r WC  Ager  MIN WC r   =  (9) ) _  _  _ ; _  _ ( _   Cond St  I r  BBC  Ager  MIN  BBC r  ii  =  (10) where r_WC  reduction coefficient for wearing course r_Age_WC  reduction coefficient for wearing course because of the age of the course (Fig. 3) r_BBC i  reduction coefficient for bituminous course i  (under wearing course) r_Age_BBC i reduction coefficient for bituminous course i  (under wearing course) because of the age (Fig. 3) r_I_St_Cond reduction coefficient for pavement structure because of the pavement condition (Fig. 4) Reduction coefficient because of layer age 0,00,10,20,30,40,50,60,70,80,91,00246810121416182022242628303234363840 Age of individual bituminous layer (years)    R  e   d  u  c   t   i  o  n  c  o  e   f   f   i  c   i  e  n   t  r_   A  g  e .  r_Age_WC r_Age_BBCi Figure 3:Reduction coefficient of bituminous courses because of lNeeded structural number of asphalt reinforcement (Dneed) depends on the expected traffic load in project period (expressed with ESAL82kN) and is in PMS-DARS calculated according to Eq. 11. ( )  [ ] cm ESAL D kN need  2178,082 5481,0;8max38,0  ⋅⋅=   (11) where 0,38 average material coefficient of asphalt layers. SR I_CSI Pavement property Technical parameter Condition index Comfort and Safety Index Structural index Total Condition Index Skid resistance Trans. evenness Longitudinal evenness Pavement defects  Age of wearing course  Age of underlaying bituminous courses Rut IRI MSI  Age_WC  Age_BB I_SR I_Rut I_IRI I_MSI I_Age_WC I_Age_BBC I_St_Cond I_St_Age I_St I_Total W MSI max. max. max. W Rut W IRI  W=0,7max. max. max. W=089 max. Weighted with thickness Thick-ness eighted Normalization Weighting, combination
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