IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE IN OTTAWA-CARLETON. Stephen Q. S. Lee, P. Eng. Senior Pavement Engineer

Transcription

1 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE IN OTTAWA-CARLETON Stephen Q. S. Lee, P. Eng. Senior Pavement Engineer Katherine A. Lauter, P. Eng. Pavement Engineer Environment and Transportation Department Regional Municipality of Ottawa-Carleton Ottawa, Ontario CANADA 29 July 1999 (revised 13 August 1999)

2 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER TABLE OF CONTENTS EXECUTIVE SUMMARY 1.0 INTRODUCTION 2.0 PAVEMENT PERFORMANCES 3.0 DATA COLLECTION 3.1 Pavement Roughness 3.2 Pavement Structural Capacity 3.3 Pavement Surface Distress 4.0 RESULTS AND DISCUSSIONS 4.1 Rural and Urban Pavement Performances Rural Pavement Performances Overall Urban Pavement Performances Representative Urban Pavement Performances and Correlations 4.2 Utility Trench Impacts at trench and road network level Pavement Roughness Performance Pavement Structural Adequacy Performance Pavement Surface Distress Performance Overall Pavement Quality Performance 4.3 Costing of Utility Trench Impacts on the road network Utility trench impacts on pavement lifecycle Impact of utility trenching on pavement structural carrying capacity and rehabilitation requirements within the trench area Utility trenching zone of Influence Costs associated with impacts from utility trenching 5.0 CONCLUSIONS 4.4 Comparison of pavement performance for trenches of various shapes and sizes 4.5 Control density trench backfill reinstatement impact on pavement performances 4.6 Impact of resurfacing on reinstated trench areas Page i

3 FIGURES IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Figure 1. Figure 2. Figure 3. Figure 4. Figure 5. Figure 6. Figure 7. Figure 8. Figure 9. Figure 10. Figure 11. Figure 12. Figure 13. Figure 14. Figure 15. Figure 16. Figure 17. Figure 18. Figure 19. Figure 20. Figure 21. Figure 22. Figure 23. Figure 24. Figure 25. Reflective cracking from trench reinstatement Pavement condition deterioration with time Cox profilograph for pavement roughness measurement Paveset profilograph equipment used in pavement roughness measurement Pavement roughness quantification using absolute area under vertical profile Dynaflect deflectometer used for pavement structural adequacy measurement Multi-purpose data collection vehicle Digital video workstation used for pavement distress rating Pavement roughness and transverse cracking relationship for structurally adequate rural roads Relationship for pavement roughness with age since last rehabilitation for structurally adequate rural roads Pavement quality index versus years since last rehabilitation plot for overall rural road network Pavement roughness performance for normalized lifecycle of rural road network Pavement structural adequacy performance for normalized lifecycle of rural road network Pavement surface distress performance for normalized lifecycle of rural road network Pavement quality index performance for normalized lifecycle of rural road network Pavement quality index versus years since last rehabilitation for overall urban road network Pavement roughness performance for normalized lifecycle of overall urban road network Pavement structural adequacy performance over normalized lifecycle of overall urban road network Pavement surface distress performance for normalized lifecycle of overall urban road network Pavement quality index performance for normalized lifecycle of overall urban road network Pavement quality index versus years since last rehabilitation for the selected twelve urban segments Pavement roughness performance for normalized lifecycle of the selected twelve urban segments Pavement structural adequacy performance for normalized lifecycle of the selected twelve urban segments Pavement surface distress performance for normalized lifecycle of the selected twelve urban segments Pavement quality index performance for normalized lifecycle of the selected twelve urban segments including trench impact effect Page ii

4 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Figure 26. Figure 27. Figure 28. Figure 29. Figure 30. Figure 31. Figure 32. Figure 33. Figure 34. Figure 35. Figure 36 Figure 37 Figure 38 Figure 39 Pavement quality index performance for normalized lifecycle of the selected twelve urban segments with trench impact removed Utility trench impact on pavement roughness performance within trench Utility trench impact on pavement roughness performance at road section level Utility trench impact on structural adequacy performance within each trench Utility trench impact on structural adequacy performance at road section level Utility trench impact on surface distress performance within trench area Utility trench impact on surface distress performance at road section level Utility trench impact on overall pavement quality at road section level Utility impact on rehabilitation need year of urban pavement sections Relationship between pavement lifecycle with and without trench impact Typical deflection profile showing utility trenching zone of influence Typical pavement roughness profile showing utility trenching zone of influence Plot of pavement roughness profiles parallel to longitudinal edge of trench at various distances away and within the trench Deflection profiles across utility trenches with granular and control density backfill TABLES Table 1 Utility trenching impact on pavement roughness within trench and road section level Table 2 Relative utility trenching impact on structural adequacy of road sections and segment level Table 3 Relative utility trenching impact on surface distress rating at road section and segment level Table 4 Relative utility trenching impact on overall pavement quality at road section and segment level Table 5 Utility trenching impact on pavement lifecycle Table 6 Utility trenching impact on pavement lifecycle based on equation from Figure 35 Table 7 Areas occupied by the various utilities Table 8 Utility Trenching Impact Costs Table 9 Non-parametric Mann-Whitney statistical analysis of No Difference in the Mean Lifecycles between Urban and Rural Road networks. Table 10 Non-parametric Mann-Whitney statistical analysis of No Difference in the Mean Lifecycles between the Urban Road network and the selected twelve Urban road segments. APPENDICES Appendix A. Roughness determination by weighted absolute area under vertical profile Appendix B. Ottawa-Carleton s Dynaflect seasonal and temperature correction procedures Appendix C. Dynaflect and Benkleman Beam Correlation for Ottawa-Carleton Page iii

5 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER EXECUTIVE SUMMARY Ottawa-Carleton s Regional road system consists of approximately 1300 kilometers of arterial roads and transitway corridor (total of 3,200 lane-kilometers). The urban and semi-urban portion of the Regional road system comprises about 45 % of the system. Pavement lifecycles of 16.0 and 11.7 years were calculated for the rural and urban road networks respectively, using Ottawa-Carleton s pavement management system. The lifecycle difference between urban pavements and rural pavements can be attributed to the presence of buried utilities, the confined work space associated with utility appurtenances, pavement design (geometry) and traffic loading. Analyses based on relationships between the age of the last rehabilitation and pavement performance measures such as the Surface Distress Index (SDI) or its equivalent Pavement Condition Index (PCI) as presented in studies carried out by San Francisco, California, Burlington, Vermont and Cincinnati, Ohio, show consistently low values for the coefficient of determination (R 2 ) for performance curves. R 2 values ranging from 0.18 to 0.34 have been reported in these studies. Most of the previous studies on utility trenching use either the pavement structural carrying capacity or pavement surface distress performance measure or both of these criteria individually to quantify utility trenching impacts. The results from this study indicate that the use of a composite Pavement Quality Index (PQI) performance model, which combines the pavement surface distress, structural adequacy and pavement roughness performance criteria, provides a significantly superior model for correlating field measured data to pavement performance and for forecasting pavement lifecycles. Relationships with R 2 value of 0.80 and 0.83, respectively, were obtained in this study for pavement performances as characterized by the composite PQI and the pavement lifecycle relationship developed for urban pavements with and without the impacts of utility trenching included. The results from this study indicate that overall on a system network basis, utility trenching reduces the lifecycle of Ottawa-Carleton s urban pavements by 7.8 percent. However, a reduction in pavement lifecycle of 32.4 percent is calculated when the trenching impacts are proportioned back to just the trenched areas involved. The cost to Ottawa-Carleton as a road agency associated with the impacts of utility trenching is conservatively estimated to range from $23.45 per square meter of trenched area for pavements that have been resurfaced less than two years to $4.32 per square meter of trenched area for pavements that have been resurfaced for more than 10 years. Page 1

6 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER 1.0 INTRODUCTION The Region of Ottawa-Carleton has a population of about 750,000 people, covering an area of 2,700 square kilometers. The Regional road system consists of approximately 1300 kilometers of arterial roads and the transitway (3,200 lane kilometers). The urban and semi urban portion of the Regional road system comprises about 45 percent of the system. The road and transitway network represents a major area of investment in transportation and consumes between one-third to one-half of the total used funds. To assist the Region in expending the transportation funds to achieve maximum total return on the public s capital expenditure while providing acceptable serviceability, the Region employs a Pavement Management System (PMS). The PMS system uses both the benefit-cost analysis (maximum return on assets) and the cost-effectiveness analysis (biggest benefit for a given dollar of investment) approaches. These approaches aid in selecting the appropriate maintenance and rehabilitation strategies, identifying lifecycle costing alternatives, determining the optimal times for maintenance and rehabilitation needs, and prioritizing road work to be carried out based on given budget constraints. A review of the roads resurfaced in past years in Ottawa-Carleton indicates that the average resurfacing lifecycle is about 9 years for urban road segments and 11 years for rural road segments. These lifecycles are not based on the average life of the total road network. They only represent the average lifecycle of the specific roads being resurfaced at the time of resurfacing. The lifecycle difference between urban pavements and rural pavements can be attributed to the presence of buried utilities, the confined work space associated with installing and servicing utility appurtenances, pavement design (geometry) and traffic loading. Many utility cuts are made and many appurtenances (manholes, valve chambers and other iron works ) are placed in urban and semi urban roads by utility companies. The Regional Regulatory Code and two sets of By- Laws regulate utility trenching on Ottawa-Carleton s Regional road system. The Code and By- Laws prescribe for the issuance of road cut permits to applicants for an administrative fee that is not much more than $100 per cut. In addition, the current Code and By-Laws governing utility trenching in the Region require reinstatement of the cut to match the adjoining pavement structure. Although the intention of these requirements is to reinstate the pavement structure in kind to the pavement structure existing prior to the cut, it is often observed that the reinstated cut areas fail at an accelerated rate. This phenomenon is observed even in instances where roads have been subsequently resurfaced after the original reinstatement by the utility as shown in Figure 1. The purpose of this study was to determine the cost and impact of utility trenches (and appurtenances) on the semi-urban and urban Regional road network in Ottawa-Carleton. Based on a literature review and extensive experience in carrying out pavement management analyses for the Regional road network, it was evident that modifications were needed in the data collection processes and analyses methodologies in order to quantify utility trenching impacts, which are relatively localized in nature. In addition, the data collection and analyses methods employed in this study were designed to ensure that concerns raised in past studies and reviews were addressed. Concerns identified by the Construction Technology Laboratory [1], San Francisco [2] and the National Research Council of Canada [3] were especially considered. Page 2

7 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER The National Research Council [3] presents the most comprehensive summary of the criticisms of the data collected, analyses methodologies used and results obtained with respect to past studies conducted by San Francisco [2], University of California [4], Minnesota [5], Burlington [6], Santa Monica [7], Sacramento [7], Kansas City [7], Los Angeles [8], Cincinnati [9], New York, American Public Works Association [10], Metro Toronto [11], Southern California Gas [13 and 14], Gas Research Institute [15], SEPTA France [16], Central Road Research Institute India [17] and Ministry of Work and Development New Zealand [18]. A modified field data collection approach was used to provide input to new methodologies developed as part of this study and as input to selected sub-modules in the PMS system. The data was analyzed for different trends on a localized point by point basis, paired data points within and outside a trench, and on a trench, road section, road segment and network level basis. Analyses were carried out to define the impacts and costs of utility trenching and associated appurtenances on pavement lifecycle (until the next rehabilitation cycle), pavement performances and rehabilitation strategy requirements. 2.0 PAVEMENT PERFORMANCES The main purpose for which a pavement is constructed is to provide for the efficient transport of persons and goods in a smooth, comfortable and safe manner. Ottawa-Carleton, as a road agency entrusted with the responsibility to manage pavements, strives to achieve these objectives by optimizing cost-benefit or cost-effectiveness for both the road agency and road users. The functional behavior of pavements that provides the best indication of serviceability is road roughness. However, in order to carry out cost-benefit or cost-effectiveness analyses of pavement sections, both the structural and functional evaluation of pavements are required. In addition to the pavement roughness measurements, the pavement characteristics that are required to predict the present and future loss of serviceability are the structural carrying capacity of the road, the pavement surface distress condition, pavement traffic loading, pavement drainage and geometry (design and composition) of the pavement. In Ottawa-Carleton s PMS system, the overall pavement condition of a road section is defined as the Pavement Quality Index (PQI). The PQI is a function of the Pavement Roughness Index (PRI), the Structural Adequacy Index (SAI) and the Surface Distress Index (SDI) which encompass all the parameters having impacts on the present and future performances of the pavement. Each of these three indices are based on a scale with values ranging from 0 to 10 with 10 being perfect and zero being the lowest possible value. The critical value of each of these indices ranges from 5.0 to 6.0 depending on the functional class of the road, traffic volume, truck loading, pavement structural design and speed limit. Based on data collected since 1960, the characteristic of pavement performance deterioration with time is well documented and is illustrated by Figure 2 [Haas, [19]]. The critical PQI indicated in Figure 2 is the point on the pavement deterioration curve where it becomes uneconomical to maintain a pavement using standard maintenance techniques (ie major rehabilitation or reconstruction is required). The critical PQI concept was identified through dynamic programming optimization analyses and lifecycle cost analyses of numerous pavement projects. Page 3

8 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER As indicated above, the impact of utility cuts and associated appurtenances on pavement serviceability can be measured using the PQI performance measure. The determination of road agency costs resulting from utility trenching works on urban roads requires the quantification of any reduction in pavement life, the costs of any additional maintenance and the costs of any rehabilitation and structural strengthening requirements that may result from the utility trenching works. 3.0 DATA COLLECTION In this study, to remove the element of subjectiveness from the data collection and analyses, pavement performance measures such as pavement roughness and pavement structural adequacy, were collected exclusively using objective measuring devices. The subjectivity generally associated with the quantification of pavement distresses via the visual assessment of pavement surface distresses in the field was mitigated by using scaled digital image analysis and the automated collection of profile data. The data collection was carried out at both the detailed road segment and road network level. Pavement performance data were collected for 51 urban roads consisting of 713 road sections and a total centerline distance of 170 kilometers. This data represents the majority of Regional roads within the urban and semi urban road network. Data were also collected on 35 rural roads consisting of 580 sections and a centerline distance of about 600 kilometers. Road inventory and pavement condition data were collected using an automated multi-purpose data collection vehicle equipped with a distance measuring device, a high resolution video camera, an ultrasonic distance rut bar, a three directional gyroscope and accelerometers. Some of the data collected simultaneously were video images of the road and road furniture within the road right-of-way, road profile and pavement roughness. Pavement structural capacity data were collected using non-destructive deflection equipment and road roughness data were collected using profilometric and/or vehicle response type systems. It was determined that twelve road segments would be a statistically significant representation for the 51 urban arterial roads. This statistical determination reduced the number of sites needed for detailed data collection and analyses and recognized the substantial financial, manpower and time resource requirements for the in-depth analyses used in this study to develop the various pavement performance relationships and for quantifying the parameters influencing trench impacts. The 12 urban road segments selected represent roads with different subgrade and pavement structures. These selected roads comprise of 89 individual road sections with a total centreline distance of 17.5 kilometers. All utility companies were requested to locate and mark the position of their plant on the 12 selected road sections. This process was very time consuming but had to be undertaken given that existing utility plans cannot be relied on to determine the exact location and extent of utility plant in the field. The detailed data collected for the development of costs and the quantification of pavement performances would be significantly impacted if the exact field locations of the utility trenches were not determined. Page 4

9 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Pavement roughness, structural adequacy and surface distress data were collected for the 12 road segments as described below. In this study, the quantification of trench impacts includes any effects associated with related utility appurtenances such as any iron works. Hence, the term utility trench when used in this study from here onward means both the utility trench and its associated appurtenances. 3.1 Pavement Roughness Road roughness is the most important indicator for the determination of pavement performance and road user costs. Roughness measurement systems that are currently used can be grouped into three areas: a) profilometric b) vehicle response and c) subjective evaluation. Profilometric methods are the most accurate and best suited for detailed analyses. Vehicle response type roughness measuring systems are considered less accurate than profilometric measurements, but tend to be more widely used for network analysis because of the speed of attaining the data. Subjective evaluation is another method used for network analysis, but has a high variability associated with the individuals doing the rating. In this study, both the vehicle response and the profilometric systems were used to measure road roughness. A Cox single wheel path device and a Paveset dual wheel path profilometric device with a 7.6 m long baseline were used to collect pavement roughness data for the selected 12 urban road segments as shown in Figures 3 and 4, respectively. The vehicle response type roughness equipment consists of a three directional gyroscope and accelerometers mounted on an automated multi-purpose data collection vehicle. This vehicle was used to collect roughness data for all roads in this study. In addition to the vehicle response roughness data, detail profilometric roughness data was collected in each travel lane of the selected 12 urban road segments. As noted earlier, the exact utility trench location had been marked by each utility in the field prior to data collection. The vertical and longitudinal road profiles were collected at 100mm intervals for each wheel path for all the lanes. The chainage at the beginning and end of each utility trench was recorded so that the contribution of the utility trenching to the pavement roughness could be quantified. Typically, roughness measurements are calculated in terms of the International Roughness Index (IRI). The IRI is calculated over equally spaced intervals along the road profile. The IRI computation method employed converts the longitudinal and vertical profile data into a vehicle motion response using the mathematical model developed by the World Bank IRI study [Sayers et al, [20]]. The IRI value is expressed as the average rectified slope of the road or units of displacement over units of length. In the World Bank IRI determination methodology, the condition leading into the area to be measured and the impact of any localized area is averaged over the pavement section under consideration to simulate a standardized vehicle response to the road surface when travelling at 50 or 80 kilometers an hour. This averaging over a pavement section is deemed unsuitable for the quantification of specific roughness contributions by individual utility trenches given the very localized nature of most trenched areas. In this study the pavement roughness attributable to utility trenches was quantified using the absolute area under the vertical profile method developed by Ottawa-Carleton as discussed in Appendix A and as illustrated in Figure 5. The vertical and longitudinal profiles of the pavement sections were plotted at 100 mm intervals with all trenched area being delineated. The absolute area under the vertical profile was calculated for both trenched and non-trenched areas for each Page 5

10 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER road section. The average vertical profile component that contributes to the pavement roughness of the trench and non-trench area was obtained by dividing the absolute areas mentioned above by the respective longitudinal length. This data was used to generate the pavement roughness data for two fundamental scenarios: a) The road section pavement roughness with utility trench impacts included; and b) The road section pavement roughness with utility trench impacts removed. These two scenarios were input to the PMS needs analysis modules separately to determine the change, if any, in pavement lifecycle and rehabilitation strategy due to the presence of the utility trenches. 3.2 Pavement Structural Capacity The reason for evaluating the pavement structural capacity or adequacy is to estimate the load carrying capacity and the service life of pavements under measured traffic conditions. The two main criteria relating to pavement structural adequacy are: a) the maximum vehicle load that the pavement can withstand without causing excessive immediate distress; and b) how many axle load repetitions can the pavement withstand. There are numerous ways the structural adequacy data can be collected but the most effective techniques consist of using non-destructive deflection measurements combined with limited borehole drilling to determine pavement structure and materials. Borehole pavement data were collected at 100 to 500 m spacings for most of the Regional roads in this study. The nondestructive Dynaflect deflectometer shown in Figure 6 was used to collect pavement structural adequacy data at the detailed and network analysis levels. This is a common test apparatus for non-destructive testing (NDT) and was developed in the U.S. in the early 1970 s. The apparatus is trailer mounted and consists of two counter-rotating masses which apply a 4.4 kn peak-to-peak sinusoidal load to the pavement through two polyurethane coated steel wheels spaced 50.8 cm apart at a frequency of 8 Hz. A static weight of 8.9 kn is also applied to the pavement through these rigid steel wheels. The pavement deflection is highest at the application of the load, and propagates outward from the source. The deflection is measured by five geophones which are located at the centre of the two wheels and, starting at the loading point, are spaced at equal distances of 30.5 cm apart. The measured deflections from the Dynaflect represent a deflection bowl similar to what would occur under a wheel load. Analysis of this bowl and the maximum deflection value can provide information about the strength of the pavement and underlying layers. The strength of the pavement structure and subgrade is dependent on climatic and site conditions, hence the deflection value of a pavement section will vary seasonally and annually. In order to correlate readings taken in different years and during different time of the years, Ottawa- Carleton has established eleven field sites for determining seasonal correction factors. In addition, the ambient temperature and temperature within the pavement structure, Page 6

11 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER especially in the asphalt layers, impacts deflection readings. Deflection values must be corrected to bring the values to the standardized baseline of an equivalent pavement structure at 21 0 C. The temperature and seasonal correction methodologies developed by Ottawa-Carleton are described in Appendix B. In this study, the structural adequacy analysis method used was based on the fatigue analysis of the pavement materials utilizing the maximum tolerable deflection (MTD) versus load repetition relationship as described in Haas et al [22]. Deflection data was collected at a minimum of 100 m intervals spacing for the rural and urban roads at the network level. On the selected 12 urban road segments, multiple lines of deflection testing were carried out at 280 individual utility trenches. At each trench, deflection measurements were taken at paired sample points inside and outside the trench area and on deflection measurement lines through the trench area and extending 1.8 m beyond both sides of the trench area. Typically, measurements outside of the trench area were taken at a distance of 1 m from the edge of the trench. Since it was not known, however, whether or not the trench reinstatement was influencing these deflection readings, in addition to the paired sample data, some deflection measurements were taken at points 0.6m, 1.2m, and 1.8m from the edge of the trench to determine a distance at which the measurements would be representative of the original baseline road condition (ie not influenced by the presence of the trench). Deflection data were also collected at up to four different locations within the trench area to determine if there are differences in performance at the edge, at the centre and at other intermediate points within the trench area. Deflection readings were analyzed on a paired point by point basis at each trench, using the relative difference between corresponding deflection readings taken inside and outside of the trench to develop the relative normalized impact based on respective readings not impacted by utility trenching. On a road section or segment basis the relative impact from each trench is averaged over the road section or segment. This relative difference indicates the change in structural performance of the road attributed to the utility trenching. SAI values were calculated for all the road sections based on the deflection data collected at a minimum of 100 m intervals. Two scenarios were established: a) the SAI for the entire road (trench impacts included); and b) the SAI for the road with the trench influence removed. The calculated SAI value from data collected at a minimum of 100m intervals (normal PMS practice) was the value used for the entire road. This value was multiplied by the average relative difference in structural capacity between measurements taken in and out of the utility trench area to determine a second SAI for the road. These two SAI s were used as separate inputs in the PMS needs analysis to determine the change in needs and strategies due to utility trenches. Page 7

12 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER 3.3 Pavement Surface Distress Road inventory and pavement condition data for this study were collected using the automated multi-purpose data collection vehicle as is illustrated in Figure 7. As noted earlier, this vehicle is equipped with a distance measuring device, a high resolution video camera, an ultrasonic distance measuring bar, a three directional gyroscope and accelerometers. Some of the data collected simultaneously are video images of the road and road furniture within the road right-ofway, pavement cross fall, rutting, road profile and accelerometer based roughness measurements of the pavement surface. Road surface distress data for this study were obtained from the video component of Ottawa-Carleton s PMS data library of Regional roads. The video database consisted of videotapes with front, side and downward views of the Regional road system. Using a pavement rating software, and following the procedures of Ottawa-Carleton s Pavement Management System Visual Condition Rating manual, all roads were rated for pavement distresses, which included edge, alligator, map, longitudinal, and transverse cracking, potholes, raveling, rippling, flushing and patching. Crossfall and rutting data were collected using the cross profile bar in the multi functional data collection vehicle. The distresses were recorded and analyzed for the location of their occurrence (chainage), their severity and the extent of their occurrence, using the video workstation as shown in Figure 8. Distress data for the urban and 12 detailed study roads were collected and analyzed with the PMS to determine the Surface Distress Index (SDI) for the road sections. The methodology on how to obtain the SDI rating from the distress data is described in Haas et al [22]. In this study, all road sections were first rated to determine the sectional SDI with all distresses (including those associated with trenches) included with the chainage, extent and severity of each distress quantified using the video workstation. Then distresses within the utility trenches only were quantified. The distresses attributed only to utility trenches were then removed from the study road sections, and a second SDI was calculated for these sections to determine the impact of the utility trenching on surface distress. The SDI from both scenarios were then input to the PMS needs analysis to determine the changes, if any, in the year when the next rehabilitation is needed and any change in the rehabilitation strategy requirements as a result of the impact from utility trenching. 4.0 RESULTS AND DISCUSSIONS This section presents the results and analyses of the pavement performances in urban and rural settings. 4.1 Rural and Urban Pavement Performances Rural Pavement Performances Pavement performance results from a previous study [Lee et al, [21]] of 38 urban and rural Regional roads indicated that for structurally adequate rural roads, the pavement performance Page 8

13 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER prediction when only thermal cracking is considered was the same as when all distresses were used in the analysis. This indicated that thermal cracking in the form of transverse cracking is the primary distress triggering the rehabilitation needs program for structurally adequate rural roads in Ottawa-Carleton. This study also indicated that rehabilitation strategies such as Cold In-place Recycling (CIR) and the use of SUPERPAVE binder in new construction or in combination with CIR have a significant impact on pavement rehabilitation lifecycles. The results of the pavement performance analysis such as PRI and the transverse cracking frequency as a function of time since the last rehabilitation year for rural structurally adequate roads are shown in Figures 9 and 10. In the current study, 35 rural Regional roads consisting of 580 road sections with a centerline distance of about 600 kilometers were used to characterize overall rural pavement performances. The road sample consists of both structurally adequate and inadequate roads. The pavement performance relationships for these rural Regional roads are shown in Figures 11 to 15. When any two variables are plotted against each other to obtain a relationship through a regression technique such as line of best fit, the R 2 value of the line is known as the coefficient of determination. The coefficient of determination represents a way to measure how much the errors of prediction of the one variable can be reduced using the information from the other variable. The result of plotting the pavement quality index (PQI) for the 35 rural road sections against age (the time since the road section was last rehabilitated) as shown in Figure 11 produces a very low correlation result (R 2 of 0.02) for the line of best fit. This is consistent with the results of utility trench studies conducted in Vermont [Shahin et al, [6]], Cincinnati [Bodocsi et al, [9]] and San Francisco [City and County of San Francisco, [2]] when only the Pavement Condition Index (PCI) (similar to Surface Distress Index (SDI) in this study) is used to determine pavement lifecycles. Regression analyses using linear, second and third degree polynomial, exponential, power and logarithmic lines of best fit were carried out for each pavement performance and lifecycle analysis used in this study to determine the regression that provides the best coefficient of determination. Only the regression analysis with the highest coefficient of determination is reported. The inherent assumption built into expecting a good line of fit or coefficient of determination when plotting the overall pavement performance (PQI) versus age (time since last rehabilitation) is that all the road sections have a similar lifecycle. This is likely true for structurally adequate rural roads where the primary cause of pavement deterioration is thermal/transverse cracking or binder degradation with age as shown by results from the previous study [Lee et al, [21]] noted above. However, in this study, where both structurally adequate and inadequate road segments as well as road segments with more variability are included, the assumption of similar lifecycles does not hold true. To address the effects of the individual road section lifecycles when developing the pavement performance relationships, the performance data for each road section must be plotted against the individually normalized lifecycle of the same road section. The road section lifecycle is Page 9

14 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER normalized by dividing the age (time since the last rehabilitation) by the real lifecycle of the individual road section, which is calculated as the length of time between the year of the last rehabilitation and the year that the PMS predicts that the road section will reach the critical PQI value. A customized PMS sub-module was developed by Ottawa-Carleton that uses historical measured pavement performance data to calibrate individual road section pavement deterioration models. With these modifications, the various pavement performances for each road section are plotted against the real road lifecycle for each road section. As mentioned before, this method overcomes the analytical weaknesses associated with the fact that the data collected from any individual section represents only a specific snap shot in time and that each set of data portrays a road section at a different stage of deterioration and at a different stage of the individual section lifecycle. This method also adequately accommodates the problem with predicting a normalized lifecycle for the road sections and the inherent variations existing among different pavement sections. In additional, any errors in measurement of the performance parameters will also be adequately addressed. The results of the normalized lifecycle pavement performance relationships for the 35 rural roads are shown in Figures 12 to 15. The result of the pavement quality index (PQI) performance measure plotted against the normalized lifecycles indicates a significant improvement in coefficient of determination ( an R 2 of 0.61 compared to the previous R 2 of 0.02 when age instead of normalized lifecycle was used) for a third degree polynomial line of best fit. Among the three primary pavement performance indicators (roughness, structural adequacy and surface distress) the structural adequacy performance (SDI) measure has the highest coefficient of determination (R 2 of 0.42) for the line of best fit. This indicates that for Ottawa-Carleton s rural road system, structural adequacy likely governs the performance of pavement deterioration. The pavement quality index (PQI) performance measure when plotted against the normalized lifecycle of the individual sections showed a much higher coefficient of determination (R 2 of 0.61) than any of the individual pavement performance indicators, thus, confirming the validity of using the combined pavement quality index performance model. Based on this analysis, the average lifecycle (time between rehabilitation) for the 35 rural road sections under review is determined to be 16.0 years Overall Urban Pavement Performances The overall urban pavement performance relationships developed in this study were based on the analysis of 51 urban roads consisting of 713 road sections with a total centerline distance of 170 kilometers. The pavement performance results are shown in Figures 16 to 20. Similar to the overall rural road network results, the overall urban road network illustrated a very low coefficient of determination (R 2 of 0.04) for the line of best fit when the pavement quality index (PQI) performance was plotted against age ( years since the individual road section were last rehabilitated). Page 10

15 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER The results of the overall pavement performance measures when plotted against the normalized pavement lifecycle, using the methodology developed for the rural road sections, are shown in Figures 17 to 20. The pavement roughness performance has the best coefficient of determination (R 2 of 0.45) for the best fit when compared to the structural adequacy and surface distress pavement performance curves. Similarly, the pavement quality index (PQI) performance curve when plotted against the individual normalized pavement section lifecycle showed a significant improvement in the coefficient of determination (R 2 of 0.75 compared to an R 2 of 0.04 when age only was used ) for the line of best fit. This once again validates that the composite pavement quality index (PQI) performance model is superior to the individual pavement performance indicators in determining pavement lifecycles. The average lifecycle between rehabilitation requirements for Ottawa-Carleton s urban pavements is calculated to be 11.7 years. Results of a Mann-Whitney statistical analysis, as shown in Table 9, indicates that there is a statistically significant difference in the mean lifecycles between the rural and urban road networks analyzed at the 0.05 risk level Representative urban pavement performances and correlations In this study, 12 representative road segments were selected for the detailed data collection and analyses necessary to assess the numerous factors that contribute to the impact of trenching on urban pavement performances, pavement lifecycle and the cost streams associated with the impacts of utility trenching. The 12 selected road segments consist of 89 road sections with a centreline distance of 17.5 kilometers. The pavement performance results for the selected 12 road segments are shown in Figures 21 to 27. Similar to the overall rural and urban road network results, the selected 12 urban road segments showed a very low coefficient of determination (R 2 of 0.08) for the line of best fit when the pavement quality index (PQI) performance is plotted against age (the time since the individual road sections were last rehabilitated). The results of the pavement performance measures when plotted against the normalized pavement lifecycle are shown in Figures 22 to 26. Consistent with the trend found in the overall urban network pavement performance, the pavement roughness performance for the selected 12 segments had the best coefficient of determination (R 2 of 0.73) for the line of best fit when compared to the structural adequacy and surface distress pavement performance curves. The coefficient of determination for the pavement roughness measure for the selected 12 segments is much higher than that determined for the overall urban network. The number of urban pavement sections at or beyond the critical rehabilitation need year that are included in the overall urban pavement roughness analysis (as a result of the underfunding of Ottawa-Carleton s resurfacing programme in recent years) is likely the cause of this difference. This is supported by the observation of data that are below the critical value for the practical end point of pavement lifecycles as shown in Figure 17 when compared to the performance data shown in Figure 22 for the selected 12 urban segments. Page 11

16 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Figures 25 and 26 show the pavement quality index (PQI) performance curves when plotted against the individual normalized pavement section lifecycles for the urban road network analysis with and without utility trenching impacts included. The coefficient of determination values for these performance curves are 0.80 and 0.85, respectively. Most of the previous studies on utility trenching use either the pavement structural adequacy or pavement surface distress performance measures or both of the criteria individually to quantify utility trench impacts. Both the urban and rural pavement performance correlation results above verify that the composite pavement quality index (PQI) performance model used in this study is superior to using the individual pavement performance indicators such as pavement surface distress, structural adequacy and pavement roughness in gauging pavement performance and lifecycle. The average lifecycle (time between rehabilitation requirements) for the selected 12 urban road segments (with the impacts of utility trenching included) is calculated to be 12.3 years. Results of the Mann-Whitney statistical analysis, shown in Table 10, indicates that there is no statistically significant difference between the mean lifecycle value for the urban road network and the mean lifecycle value for the selected 12 road segments. In addition, the plots of pavement performances and lifecycle relationships obtained using data from the selected 12 urban road segments are consistent with the results obtained using the overall urban network data. Hence, it can be concluded that the 12 selected road segments are representative of the overall urban network. This validation is required in order to ensure relationships developed from the in-depth data collected for the 12 road segments are representative of the urban road network as a whole. The data collection and analyses work undertaken for the selected 12 road segments (comprising 89 road sections) was very expensive and time consuming, even given the state-of-the-art automated data collection systems employed in this study. It is estimated that it would take five years to undertake an analysis for the whole urban road network at the detailed level employed in this study. The cost would also be prohibitive. Again this is in recognition of the already considerable capability put into place by Ottawa-Carleton in this area. 4.2 Utility Trench Impacts at trench and road network level Pavement performance measures were quantified at various locations both within and outside of the trench areas to study the impact of utility trenching. Utility trench impacts on the various pavement performance measures were analyzed and quantified in several detailed ways: a) as paired sample data from opposing sides of the trench edges b) as localized groups of data at various distances within and away from the trench; and c) at the trench, road section and road segment level. The impact of utility trenching on the various pavement performance criteria were quantified using the non-trench impacted baseline data at the various levels of analyses to obtain the Page 12

17 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER respective normalized trench impacts. The normalized trench impact values were used to quantify the trench impacts because the actual measured performance data can be different in magnitude for the different localized locations, among trenches and among the different road sections and segments. The differences in the measured data can be attributed to the variation in a number of factors such as pavement composition, workmanship, traffic loading, environmental loading, the nature and presence of utility plant and road maintenance activities. Based on the literature review, the impact of utility trenching on the various pavement performance measures has been shown to extend beyond the limits of the trench area. Data collected at various locations within and outside the trench were used to determine the zone of utility trench influence as describe in Section Utility trench impacts on pavement performance measures at the road section and road segment level were obtained by weighting the combination of individual trench contributing areas and the associated normalized trench impacts at the respective level of analysis. In this study, the pavement surface area for the 89 road sections in the 12 selected urban road segments was measured to be 214,300 square meters and the utility trenches (and their associated appurtenances) were measured to occupy 51,600 square meters of the overall area or 24 percent of the road pavement surface area as shown in Table Pavement Roughness Performance A total of 235,400 profile readings were taken at the selected 12 road segments to assist with the detailed quantification of the utility trench impact. In addition, vehicle response based roughness data were collected at a total of 25,700 sampling points for the urban and rural roads in this study. Results of the pavement roughness analyses are shown on Figures 27 and 28 and Table 1. The presence of the utility trenches were found to increase the pavement vertical profile roughness (within the trench area) by 37 percent on average for the urban road network. The results also showed that the presence of the utility trenches is responsible for an increase in pavement roughness (PRI rating) of two percent when weighted over the total area of all the 89 road sections in the 12 selected urban road segments Pavement Structural Adequacy Performance A total of 2,540 deflection data readings were taken in the selected 12 road segments for a detail quantification of the utility trenching impacts. For the urban and rural road network analyses, a total of 7,700 deflection readings were used. The pavement structural capacity or adequacy of the trench and non-trench impacted areas were analyzed and quantified based on a modified pavement fatigue method developed for this study and the maximum tolerable deflection (MTD) concept as described in Haas et al [22]. Page 13

18 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER All non-destructive structural adequacy data in this study was obtained using the Dynaflect equipment. This was augmented by destructive pavement structure characterizations via a borehole drilling programme. The Benkleman Beam is the predecessor of the Dynaflect. The most widely used and accepted pavement design and evaluation technology remains based on deflection measurements obtained using the Benkleman Beam. A Dynaflect to Benkleman Beam conversion relationship was developed for this study and is discussed in Appendix C. The results showing the average increase in deflection values measured within the trench areas when compared to adjacent non-trench impacted areas are shown in Table 2 and Figure 29. The presence of the utility trenches were found to increase the deflections in the trench areas an average of 52 percent for the urban road network. The results also showed that that utility trenching increased the deflection value measured by 18 percent when weighted over the entire pavement surface on urban road network level. Figures 29 and 30 show the impact of the higher deflections within the trench areas when computed using the Structural Adequacy Index (SAI) concept as discussed in Haas et al [22] Pavement Surface Distress Performance Pavement surface distresses for all of the 770 kilometers of rural and urban roads used in this study were rated for the fifteen distresses ( described earlier in the report) in terms of severity and extent using Ottawa-Carleton s digital video workstation. The extent and severity of each distress is rated using the digital scaled video image of the road. Visual confirmation of distress type is required as part of video image processing for distresses that are not quantified using automated profile data and roughness data collection techniques. The results of the pavement surface distress analyses performed are shown on Figures 31 and 32 and Table 3. In this study, the edges of the initial trench reinstatements were quantified as transverse or longitudinal distresses (only if there was quantifiable cracking present) in addition to any distortion or discontinuity of the pavement surface and alligator cracking observed within the trench areas. Conventional pavement management systems surface distress ratings were modified since those measures developed to quantify distress phenomenon resulting from loading or environmental conditions for the entire pavement surface are not suitable for rating distresses associated with utility trenches and their associated appurtenances. The effects of these latter distresses are very localized. Hence, it was deemed more appropriate to quantify pavement surface distresses related to utility trenching at the road sectional level. The procedure used to determining the pavement surface distress index (SDI) from the rating of the pavement surface distresses is described in Haas et al [22]. The results showed that the presence of the utility trenches reduced the road section surface distress performance measure by an average by 11 percent as shown in Table 3. Page 14

19 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Overall Pavement Quality Performance The pavement quality performance index used to quantify the overall pavement performance in this study is a function of the above-noted three individual pavement performance measures as described in Haas et al [22]. The impact of the presence of the utility trenches on the overall pavement quality performance (PQI) is shown in Figure 33 and Table 4. Utility trenching was found to reduce the overall pavement quality performance by 8 percent when weighted over the area of all of the 89 road sections in the 12 selected road segments. 4.3 COSTING OF UTILITY TRENCH IMPACTS ON THE ROAD NETWORK There are three main cost streams that must be considered in quantifying the costs associated with the impact of utility trenching on urban Regional roads. These are: costs associated with any reduction in pavement lifecycle costs associated with any changes in pavement maintenance requirements (ie. from slurry seal to resurfacing) or requirements of additional maintenance (ie. from resurfacing to subgrade repair prior to resurfacing) costs associated with any trenching impacts on pavement areas in the immediate vicinity of the trenches or associated with related utility trench appurtenances ( including costs resulting from their reinstatement or installation) Utility trench impacts on pavement lifecycle The impact of the presence of utility trenches and their associated appurtenance on the lifecycle of urban pavements is shown in Figure 35 and in Tables 5 and 6. Table 5 shows the total pavement lifecycle of the different road sections in the selected 12 road segments. The average pavement lifecycle for the 12 road segments is 13.7 years when the trenching impacts are removed and 12.3 years when the trenching impacts are included. It should be noted that this difference in lifecycle is derived from a dependant relationship. A statistical inference of the differences in the mean lifecycles between the paired road sections is not necessary given that the difference in the results are derived from differences in the dependant variables used to obtain the lifecycles of the same total sample. The significance of the differences in the lifecycles (with and without the impacts of utility trenching) is best gauged by the strength of the correlation obtained using the analyzed field data (ie the R 2 values). Further, these straight averaging calculations for individual section pavement lifecycles should not be used to determine the true loss in pavement life. A regression analysis to determine a pavement lifecycle loss relationship, as shown in Figure 35, is more representative. Figure 35 shows the pavement lifecycle relationship for each road section or segment with and without the utility trenching impacts included. Using the equation developed in Figure 35, Table 6 has been generated to show the impact of utility trenching on pavement sections or segments having different lifecycles. This table also shows the corresponding percentage loss in lifecycle that can be expected due to utility trenching. These results indicate that road sections with longer Page 15

20 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER lifecycles tend to lose a higher percentage of their life when utility trenching occurs. It can also be postulated that utility trenching will still impact on failed roads (these are roads that are beyond the critical PQI point for rehabilitation and which tend to have short lifecycles) but there is a relatively smaller impact, even if these roads are resurfaced (as a holding strategy pending reconstruction) as shown by the results in Figure 35 and Table 6. Further, utility trenching impacts on failed roads cannot be assumed to be non-existent since the trenching contributed to the pavement damage or deterioration all along prior to the point of failure and indeed contributed to the failure itself. It is only after the reconstruction of the entire pavement structure on failed roads that the assumption can be made that any utility trenching that occurred prior to the reconstruction will not likely have any impact on pavement lifecycle. Results from Section indicate that the overall urban road network has an average pavement lifecycle of 11.7 years when trenching impacts are included. Using the regression equation from Figure 35, the corresponding lifecycle of the urban road network with trenching impacts removed is calculated to be 12.7 years. This indicates that at the road network level, utility trenching can be expected to reduce the network lifecycle by about 7.8 percent. Section 4.2 results indicate that utility trenches and associated appurtenances on average occupy only 24 percent of the road network surface area. This means that the impact within the actual trench areas is significantly higher on a square metre basis in order for the weighted net contribution on the whole network area to be 7.8 percent. Accordingly, the reduction in pavement lifecycle due to utility trenching, when proportioned back based on the contributing trenched areas, is calculated to be 32.4 percent. Some factors that influence the results described above are: The lifecycle impacts developed above assume that trenching impacts are confined within the trench areas. This must be modified based on the finding described in Section Based on the trench locations marked by the utility companies, some of the trench locations have no clear visible signs of distress. In these trenches the width of the trench is assumed to be 0.67m wide and trenching is assumed to be the only construction method employed. However, trenching may not have been the only method used in installing the utility plant ie some utility plant may be placed during the initial construction of the roadway or before a road reconstruction operation. These assumptions will tend to produce lower quantified trench impacts since the actual measured trench impacts are distributed over an artificially larger square metre area. The snap shot in time approach used in this study does not pick up the full extent and severity of the trench impacts. Large portions of the trenched areas will have been subsequently resurfaced or rehabilitated (some several times) prior to the data collection. These maintenance works will have significantly mitigated the trenching impacts. Collection of data that would trace the individual road sections separately and result in the development of individual performance curves over entire lifecycles would take up to twenty years. This also would be prohibitively expensive. This again results in this study underestimating the true impacts of utility trenching. Page 16

21 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Another area where the cost and impact of utility trenching is omitted because of the difficulty in quantifying is how much each subsequent rehabilitation cycle and type of rehabilitation activity mitigates the impact of utility trenching. In this study, the utility trenching impact is quantified as if no rehabilitation activities have been carried out over the trench areas and the measured impact is assumed to only affect one pavement rehabilitation cycle. In these assumptions, the actual reduced trench impact will be quantified as if it is the full unmitigated trench impact and would underestimate the true impact of trenching Impacts of utility trenching on pavement structural carrying capacity and rehabilitation requirements within the trench area Based on the detailed surface distress data collected, one percent of the total pavement surface area (four percent of the trench areas) exhibits alligator cracking distresses. This is indicative of a structural carrying capacity deficiency in the trenched areas under traffic loading conditions. Alligator cracking is a load associated distress that require rehabilitation from the subgrade level upward rather than just pavement surface rehabilitation. The weakened areas require road base repair work in addition to the appropriate rehabilitation requirements that are required to address the maintenance requirements of adjacent non-trenched areas. In this study, the differences in pavement carrying capacity of the trench and non-trench areas have been computed using the total equivalent single axle load applications remaining in the pavements calculated based on the Dynaflect deflection readings obtained for the respective areas. The pavement strengthening requirement in this study is obtained by determining the equivalent Total Equivalent Single Axle Load (TESAL) remaining in the pavement for both the trench and non-trench areas with the Maximum Tolerable Deflection (MTD) value used to define the structural adequacy design life for the individual section. Methods for calculating the MTD and TESAL to determine the structural strengthening requirements of the trench areas using the pavement fatigue concept developed for this analysis are discussed in Haas [22]. Based on extensive resilient modulus testing of pavement materials in Ontario, the Granular Base Equivalency (Granular A used as the benchmark) for hot mix asphalt and Granular B is determined to be 2 and 0.67, respectively. The average urban pavement structure is quantified to be equivalent to 197 mm hot mix asphalt, 150 mm Granular A and 210 mm Granular B for a total Granular Base Equivalency (GBE) of 760 mm of Granular A or 380 mm of asphalt hot mix. The average pavement strengthening requirement for the trench areas is calculated to be 8.5 percent of the average urban network pavement structure. Using the GBE mentioned above, the pavement strengthening requirement for the trench area is determined to be 32 mm of hot mix asphalt. In calculating the cost associated with the loss of fatigue strength, the pavement strengthening requirement is reduced proportionally to reflect the diminishing trench impact as a function of the remaining life of the pavement as shown in Table 8. Page 17

22 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Utility trenching zone of influence It has been shown in research and in previous studies mentioned above that utility trenching works do not only affect the areas within the trench reinstatement, but that areas extending beyond the limits of the actual trench are also affected. The additional area affected that extends beyond the trench is termed the zone of influence. In this study, data was collected with the Dynaflect and Profilograph devices to determine the effect of utility trenching on the structural adequacy and road profile within the trench and to define the zone of influence. Surface distress data was not used for this purpose because conventional distress ratings and the distress manifestations in localized trench areas will not capture data that would enable the boundaries of the trench zone of influence to be determined. Dynaflecting was carried out on selected longitudinal, transverse, and square shaped trenches. In all cases, dynaflect measurements were taken within the trench and at various distances from the edge of trench. Results of the structural adequacy deflection testing indicated that the average zone of influence extends 0.63 m from the edge of the trench. A typical deflection profile for a zone of trenching influence is shown in Figure 36. Similarly, the zone of influence was analyzed for a total of 274 trenches using pavement roughness profile measurements. At transverse trenches, the profile data was collected across the trench width. The zone of influence was calculated as the distance from the edge of trench to a point at which the profile distinctly changed. Results of this analysis indicated that the trenching process on average influences pavement roughness to a distance of 0.55 m beyond the trench limits. A typical plot of the profile across a transverse trench is shown in Figure 37. For longitudinal trenches, the profile data was collected along the trench, and at various parallel distances outside of the trench. A typical plot of the profile along the longitudinal trench and outside of the trench is shown in Figure 38. Based on the above, the average zone of influence of utility trenching is quantified to be 0.55m from the edge of the trench or about 60 percent of the average urban road network trench width of 1.9 metres. In this study, both the structural and pavement roughness data quantified the surficial condition adequately but not necessarily the condition beneath the surface. To address this uncertainty, the zone of influence in this study is conservatively assumed to be triangular in nature with no undermining or zero zone of influence at the bottom of the trench and the full zone of disturbance at the surface as determined above. This will reduce the calculated zone of influence from about half of the original profile area to 30 percent of the trench area. Similar to the fatigue strengthening cost calculation in Section 4.3.2, the cost impact resulting from the trenching zone of influence should be reduced proportionally to reflect the existing remaining life of the pavement being trenched. Page 18

23 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER Costs associated with impacts from utility trenching The lifecycle and other costs attributable to the impacts of utility trenching when calculated based on per square meter of trench area using the results from Sections to are tabulated in Table 8 and described below: All trench areas require 35.5 percent of the cost of one lift of 40 mm HL3 asphalt resurfacing to compensate for the reduction in the pavement rehabilitation lifecycle 4 percent of the trench areas require base, subbase and surface asphalt rehabilitation to mitigate base failures manifested in the form of alligator cracking within the trench areas 96 percent of the trenched areas require an additional 32 mm hot mix asphalt layer to restore the reduced pavement fatigue strength in the trenched areas back to the strength of the adjacent pavement areas that have not been impacted by the utility trenching the aggregated costs determined based on the above three factors must be increased by 30 percent to account for the trenching impacts within the zone of influence As indicated by the results from Sections to 4.1.3, the normalized lifecycle of each road section or segment has been shown to provide superior coefficients of determination for determining pavement performance relationships with time. The results in Figure 35 and the corresponding results in Table 6 quantify the reduction in road section pavement life resulting from utility trenching and this is correlated with the individual pavement section lifecycles. The administration of pavement lifecycle reduction cost recoveries via a permit fee using this relationship would require frontline people to have information on each individual pavement lifecycle for every road section in the network. However, the cost allocation for a reduction in pavement lifecycle is not obvious or intuitive. Two roads resurfaced the same length of time ago would have different costs associated with pavement life degradation arising from identical trenching works if the two roads have different lifecycles. For simplicity of administration, a sliding scale table quantifying the costing of trench impacts using the number of years since the last rehabilitation was developed as shown in Table 8. For this table, the urban network average lifecycle of 12.7 years has been used to calculate the baseline costs associated with utility trenching impacts. Hence, some component of costs provided in this table that contribute to the total utility trenching impact cost will deviate from the actual cost as a function of the ratio of the specific pavement lifecycle of the road section being trenched compared to the network average urban road lifecycle of 12.7 years. Another conservative simplification used in generating the costs in Table 8 is that costs associated with the reduction in pavement lifecycle and the pavement strengthening requirements are set to zero when the pavement age is more than 10 years rather than 12.7 years. Table 8 shows the costs attributed to utility trenching on a per square metre of trench area basis for urban pavements that have been resurfaced at different times. The costs attributed to the impacts of utility trenching per square meter of trenched area is determined to range from a high of $23.78 per square meter for pavements that were resurfaced less than 2 years prior to the trenching works to a low of $4.32 per square metre for pavements resurfaced more than 10 years Page 19

24 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER prior to the trenching works. Table 8 presents a sliding scale cost recovery structure for trenching impact on pavements. These figures could be rounded for administrative purposes for cost recovery as follows: Age of Pavement (years) Trenching Fee (per m 2 ) 2 or less $24.00 >2 to 4 $20.00 > 4 to 7 $16.00 >7 to 10 $10.00 More than 10 $ Comparison of pavement performance of trenches with various shapes and sizes A quantification of utility trench impacts reinstated with various shapes, size and depth are still ongoing. Results will be reported in future in conjunction with an assessment of the effects of resurfacing in mitigating trenching impacts. 4.5 Control density trench backfill reinstatement impact on pavement performances Controlled density backfill (CDB) material is a fluid mix of sand, aggregate and a low percentage of Portland cement. CDB is easy to place and has been used in utility cut reinstatements when backfill settlement cannot be tolerated. It is used as an alternative to conventional trench reinstatement material like sand and granular. This study included a detailed assessment of four shallow trenches, and a general assessment of several other trenches. The detail study was carried out on four shallow trenches constructed at the same time and location, in areas with minimal traffic loading, with two different material structures and trench widths. Two trenches were reinstated with asphalt on the surface to match the existing asphalt thickness and CDB was placed in the remainder of the trench. The other two trenches were reinstated with conventional material using asphalt and granular material to match the existing pavement structure. Each group of trenches included one narrow trench (0.7m) and one wide trench (1.3m). Observations of these trenches were carried out five years after construction. Visual observations showed that the CDB trenches exhibited a greater amount of surface distress than conventional reinstated trenches. Specifically, alligator cracking was observed to be prevalent on the CDB trenches indicating subgrade damage. Since traffic loading was minimal, the subgrade damage was likely due to the effects of freeze-thaw cycles and the incompatibility between CDB and the surrounding material. Both reinstatement methods had more distress on the wider trenches. A general assessment of other CDB trenches confirmed these results. The dynaflect and profilograph were also used to assess the condition of these trenches. The profiling was carried out in late spring and showed no significant difference between the two trench types. Dynaflecting was carried out at locations within, and outside of the trench area at each trench. Figure 39 shows the dynaflect profile across each trench. The centre of each trench is at the x-axis zero mark. The figure indicates that the granular trenches are strongest at the Page 20

25 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER centre of the trench and exhibit weakness at the trench edges, and the CDB trenches are weakest at the centre of the trench. Ottawa-Carleton is undertaking further work with respect to trench restoration methods and materials in conjunction with several other agencies including the National Research Council of Canada and the US Army Corps of Engineers. 4.7 Impact of resurfacing on reinstated trench areas Further work is being carried out to assess the impact of pavement resurfacing on trench reinstated areas. Field data on recently trenched areas have been gathered and quantified. Resurfacing over these trench areas is expected to take place in Detailed data will be collected upon the completion of the resurfacing work. The results of this further investigation will be presented in a future report. As noted earlier, this study, in the absence of specific technical information, has assumed that pavement resurfacing has no mitigating effect on the impacts of utility trenches. The future quantification of the actual mitigating resurfacing effects will likely result in an increase in the estimate of utility trenching pavement damage costs on a per square metre basis. 5.0 CONCLUSIONS Pavement lifecycles of 16.0 and 11.7 years were calculated using Ottawa-Carleton s PMS system for the respective rural and urban road networks using a total of 770 kilometers of centerline road data. Analyses based on relationships between the age of the last rehabilitation and pavement performance measures such the Surface Distress Index (SDI) or its equivalent Pavement Condition Index (PCI) as presented in studies carried out by San Francisco, Burlington and Cincinnati, show a consistently low value for the coefficient of determination (R 2 ) for performance curves. R 2 values ranging from 0.18 to 0.34 have been reported in these studies. In this study, pavement performance measures were correlated to the specific unique pavement lifecycle for each road section. To assess the effectiveness of this approach in providing better pavement performance measure assessments, the pavement performance data were plotted both using the method employed in the previous studies and using the normalized pavement section lifecycle method developed in this study. The normalized lifecycle plot of pavement performance measures was found to address the inherent variability introduced into the analyses by pavements with different lifecycles. This method also provides the basis for plotting the pavement performance measures taking into consideration that pavement performance is tied to the stages of the lifecycle timeline rather than a fixed number of years. Most of the previous studies on utility trenching use either the pavement structural adequacy or pavement surface distress performance measure or both of the criteria individually to quantify utility trench impacts. Results from this study indicated that the use of a composite Pavement Quality Index (PQI) performance model, which combines the pavement surface distress, structural adequacy and pavement roughness performances criteria, provides a significantly Page 21

26 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER superior model for correlating field measured data to pavement performance and pavement lifecycle forecasting. The combined effect of plotting pavement performance measures against normalized individual road section lifecycles and the use of a combined pavement quality (PQI) prediction criteria has resulted in the ability to derive numerous very high quality pavement performance and pavement lifecycle relationships with and without the impacts of utility trenching included. This development is instrumental for the production of better pavement performance curves and better estimating the costs associated with utility trenching activities and associated impacts on urban roads. The two most significant pavement performance curves derived for this study are the overall pavement performance as characterized by the PQI plot against normalized pavement lifecycle and the plot of pavement lifecycles with and without the impacts of utility trenching included. These two plots have coefficients of determination (R 2 ) of 0.80 and 0.83 respectively, as shown in Figures 25 and 35. These R 2 values will have corresponding R values of 0.89 and The R value is the coefficient of correlation which measure the strength of the relationship between the plotted variables. These R values indicate the pavement performance (PQI) and lifecycle data used to developed the respective relationships are 89% and 91% attributable to the parameters being plotted, hence, confirming that the relationships developed by the lines of best fit are very significant. Results from this study indicate that utility trenching shortens the lifecycle of Ottawa-Carleton s urban pavements by 7.8 percent when the trenching impacts are spread over the pavement surface area of the entire urban road system. A reduction in pavement lifecycle of 32.4 percent is calculated when the trenching impacts are proportioned back to just the trenched areas involved. Results from pavement lifecycle relationships developed in this study, indicate that road sections with longer pavement lifecycles will experience higher lifecycle losses due from the effects of utility trenching compared to road sections with shorter lifecycles. Utility trenched areas are estimated to occupy about 24.1 percent of the total urban pavement surface. The cost to Ottawa-Carleton as a road agency associated with the impacts of utility trenching is conservatively estimated to range from $23.45 per square meter of trenched area for pavements that have been resurfaced less than two years to $4.32 per square meter of trenched area for pavements that have been resurfaced for more than 10 years. Non-destructive pavement deflection testing results indicate that utility trenching has a significantly negative impact on the fatigue structural carrying capacity of the pavement within the trenched areas. The results of this study, indicate that on average utility trenching reduces the fatigue structural carrying capacity of the pavement in the trench areas by 8.5 percent. This would require pavement strengthening within the trench with about 32 mm of hot mix asphalt to restore the fatigue structural carrying capacity lost as a result of the trenching. The cost to restore the fatigue load carrying capacity of the trenched areas back to the same level as the non-impacted areas is the largest component of the total costs attributed to utility trenching. Page 22

27 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER The impact of the utility trenching was found to extend beyond the edge of the trenches by an average of 0.55 m for the trenches studied (zone of influence, actual zone of influence for a specific trench will depend on the depth of that trench) based on pavement structural carrying capacity and pavement roughness profile analyses. Using the conservative assumption that the zone of influence at the bottom of the trench is zero, a zone of influence extending 30 percent beyond the edge of trench width was calculated. One aspect that was not quantified by this study is the cumulative impact of utility trenching on the loss of pavement life between rehabilitation cycles. It is evident in this study that some of the pavement areas where trench impacts are still manifested have undergone more than one cycle of resurfacing. When the lifecycle lost equation is developed using the snap shot in time condition survey of the pavement condition, the mitigating impacts of all rehabilitation works result in reduced distresses, more structural strength and less pavement roughness in the trench areas than would be otherwise if the resurfacing works were not carried out. As indicated previously, trenches that have experienced subsequent rehabilitation work will have the trenching impacts mitigated and this phenomenon will contribute to the development of a lower assessment of trench impact costs than exists in reality. Alligator cracking that is indicative of subgrade problems and the existence of reflective cracking within trenched areas that have been resurfaced indicates that utility trenching has negative impacts on rehabilitation lifecycles well beyond the initial trench reinstatement cycle. Page 23

28 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER REFERENCES [1] Construction Technology Laboratories Inc., Economic and Environmental Issues in Utility Cuts (Asphalt Pavement Repair Study), 1995, Report to Gas Research Institute. [2] The Blue Ribbon Panel on Pavement Damage, The Impact of Excavation on San Francisco Streets, 1998, The Department of Public Works, City and County of San Francisco. [3] National Research Council, Canada, Utility Cuts Restoration Practices (State of the Art Report), 1999, National Research Council Canada. [4] Davis, H and Finn F, Trench backfill Requirements and practices, 1950, Institute of Transportation and Traffic Engineering, University of California, Berkeley, California. [5] Minnesota Department of Highways and Minnesota Local research Board, Field Evaluation of Trench backfilling procedures, 1968 [6] Shahin M., Crovetti J. and Franco J., The Effects of Utility patching on Pavement Performance and Rehabilitation Costs for City of Burlington, Vermont, 1986, Proceedings of Transport Research Board. [7] American Public Works Association, Managing Utility Cuts, 1997, Special Report. [8] ARE Inc, Comprehensive Study to Evaluate Repair Patches for Asphalt Paved Streets, 1989, Southern California Gas Company, Los Angeles, CA. [9] Bodocsi A., Pant P., Aktans A. and Arudi R., Impact of Utility Cuts on Performance of Street pavements for City of Cincinnati, 1995, City of Cincinnati and American Public Works Association. [10] American Public Work Association, Excavation in the right-of-way: A guide to Coordinate and Regulation, 1996 [11] Metropolitan Toronto Road and traffic Department, Utility Cut Restoration Problems and New Policy, 1985 [12] Dames and Moore, Report Bellhole Compaction Studies, 1984, Southern Gas Company, Northwest Distribution Division. [13] Evans, M and Coulter D., Operations and research A co-operative Effort, 1988, The Southern California Gas Company. [14] Southern California Gas Company, Comparison of Performance of various Standard and T-Section Utility Cut Repair Alternatives on Florence Avenue in Downey, CA. [15] Todres, H. and Saha N., Asphalt Paving repairs Study Theoretical Modeling, 1996, APWA Reporter November [16] Ministere de l Equipment, des Transports et du Tourisme, France, Remblayage des Tranchees et Refection des Chaussees, 1994, Guide Technique. [17] Gokhale Y. and Shukla R., Reinstatement of Trenches Cut for Utility Services on Urban Roads, 1984, Central Research Institute _ India, Road research Paper No [18] Proffitt A., Trench Excavation and Reinstatement in New Zealand, 1987, National Roads Board New Zealand, Road Research Unit Occasional Paper. [19] Haas R., Pavement Design and management Guide,1997, Transport Association of Canada. [20] Sayers M., Gillespie T. and Queiroz C; The International Road Roughness Experiment, 1986, World Bank Technical Paper Number 45. Page 24

29 IMPACT OF UTILITY TRENCHING AND APPURTENANCES ON PAVEMENT PERFORMANCE S.Q.S. LEE AND K.A. LAUTER [21] Lee Q.S, VanBarneveld A. and Corbett M., Low Temperature Cracking Performance of SUPERPAVE and Cold In-place Recycled pavements in Ottawa-Carleton, 1997, 42 nd Canadian Technical asphalt Association Proceedings. [22] [22] Haas R, Hudson R. and Zianiewski J, Modern Pavement Management, 1994, Krieger Publishing Company, Malabar. Page 25

30 FIGURES

31 Figure 1. Reflective cracking from trench reinstatement Figure 2. Pavement condition deterioration with time (Haas [19], 1997)

32 Figure 3. Cox profilograph for pavement roughness measurement Figure 4. Paveset profilograph for pavement roughness measurement

33 Figure 5. Pavement roughness quantification using absolute area under vertical profile Figure 6. Dynaflect Deflectometer for pavement structural adequacy measurement

34 Figure 7. Multi-purpose data collection vehicle Figure 8. Digital video workstation used for pavement distress rating

35 Transverse Cracking Vs PRI (Rural Road- Structurally adequate) y = x x x R 2 = average cracks/km Pavem ent Roughness Index (PRI) Figure 9. Pavement roughness and transverse cracking relationship for structurally adequate rural road (Lee et al [21], 1997) Pavement Rougness Index Vs Pavement Age (Structurally adequate rural road) 10 9 y = x x x R 2 = average PRI 8 7 all Poly. (all) years since last rehabilitation Figure 10. Relationship for pavement roughness with age since last rehabilitation for structurally adequate roads (Lee et al [21], 1997)

36 PQI Vs Year since last rehab (Rural Road) 12 y = x x x R 2 = PQI Value 6 PQ I vs Year since last rehab Poly. (PQ I vs Year since last rehab) Years since last rehabilitation Figure 11. Pavement quality index versus years since last rehabilitation plot for overall rural road network P R I V S N o rm alized L ife C ycle (R u ra l R o ad ) y = x x x R 2 = PRI Value 6 P R I vs N orm alized Life cycle P o ly. (P R I vs N o rm a lized Lifecycle ) Ratio of Normalized Life Cycle Figure 12. Pavement roughness performance for normalized lifecycle of rural road network

37 SAI vs Normalized Life Cycle (Rural Road) 12 y = x x x R 2 = SAI Value 6 SAI vs Normalized Lifecycle Poly. (SAI vs Normalized Lifecycle) Ratio of Normalized Life Cycle Figure 13. Pavement structural adequacy performance for normalized lifecycle of rural road network SDI vs Normalized Life Cycle (Rural Road) y = x x x R 2 = SDI Value 6 SDI vs Normalized Lifecycle Poly. (SDI vs Normalized Lifecycle) Ratio of Normalized Life Cycle Figure 14. Pavement surface distress performance for normalized lifecycle of rural road network

38 P Q I vs N orm alized Life C ycle (R ural R oad) 12 y = x x x R 2 = PQI Value 6 PQI vs Norm alized Lifecycle P oly. (P Q I vs N orm alized Lifecycle) Ratio of Normalized Life Cycle Figure 15. Pavement quality index performance for normalized lifecycle of rural road network PQI VS Years since last rehab (Urban Road) y = x x x R 2 = PQI value 6 ff PQI Poly. (PQI) Years since last rehabilitation Figure 16. Pavement quality index versus years since last rehabilitation for overall urban road network

39 PRI vs Normalized Life cycle (Urban Road) 12 y = x x x R 2 = PRI Value 6 PRI vs Normalized Lifecycle Poly. (PRI vs Normalized Lifecycle) Ratio of Normalized Life Cycle Figure 17. Pavement roughness performance for normalized lifecycle of overall urban road network SAI Vs Norm alized Life Cycle y = x x x R 2 = SAI Value 6 SAI vs Normalized Lifecycle Poly. (SAI vs Normalized Lifecycle) Ratio of Normalized Life Cycle Figure 18. Pavement structural adequacy performance over normalized lifecycle of overall urban road network

40 SDI vs Normalized Life Cycle (Urban Road) 12 y = x x x R 2 = SDI Value 6 SDI vs Normalized Lifecycle Poly. (SDI vs Normalized Lifecycle) Ratio of Normalized Life Cycle Figure 19. Pavement surface distress performance for normalized lifecycle of overall urban road network PQI versus Normalized Life Cycle (Urban Road) y = x x x R 2 = PQI value 6 PQI Vs Normalized Lifecycle Poly. (PQI Vs Normalized Lifecycle) Ratio of Normalized Life Cycle Figure 20. Pavement quality index performance for normalized lifecycle of overall urban road network

41 PQI vs Years since last rehab (Detail study 12 streets) PQI value 6 PQI Values with trench Poly. (PQI Values with trench) 4 y = x x R 2 = Years since last rehabilitation (years) Figure 21. Pavement quality index versus years since last rehabilitation for the selected twelve urban segments PRI vs Normalized Lifecycle (Detail Urban Road) 10 9 y = x x x R 2 = PRI value 5 4 PRI vs Normalized Lifecycle Poly. (PRI vs Normalized Lifecycle) Ratio of Normalized Lifecycle Figure 22. Pavement roughness performance for normalized lifecycle of the selected twelve urban segments

42 SAI vs Normalized lifecycle (Selected 12 urban segments) 12 y = x x x R 2 = SAI Value 6 SAI vs Normalized Life Poly. (SAI vs Normalized Life) Ratio of Normalized Lifecycle Figure 23. Pavement structural adequacy performance for normalized lifecycle of the selected twelve urban segments SDI vs Normalized Lifecycle (Selected 12 Urban Segments) 10 9 y = x x x R 2 = SDI value 5 4 SDI vs Normalized Lifecycle Poly. (SDI vs Normalized Lifecycle) Ratio of Normalized Lifecycle Figure 24. Pavement surface distress performance for normalized lifecycle of the selected twelve urban segments

43 PQI vs Normalized Lifecycle with trench (Detail Urban Road) 12 y = x x x R 2 = PQI value 6 PQI vs Normalized lifecycle Poly. (PQI vs Normalized lifecycle) Ratio of Normalized Lifecycle Figure 25. Pavement quality index performance for normalized lifecycle of the selected twelve urban segments including trench impact effect PQI vs Normalized Lifecycle without trench (Detailed Urban Road) y = x x x R 2 = PQI Value 6 P QI Values without trenches Poly. (PQI Values without trenches) Ratio of Normalized Lifecycle Figure 26. Pavement quality index performance for normalized lifecycle of the selected twelve urban segments with trench impact removed

44 Normalized Pavement Roughness within trench area 3.50 Normalized Roughness Impact within trench area Impact on Rougness within trench area 0.00 section 2820 section 2850 section 2880 section 2910 section 6860 section 6890 section 6920 section 9070 section 9110 section section section section section section section section section section section section Section Number Figure 27. Utility trench impact on pavement roughness performance within trench PRI Values with and without trench effect PRI Values PRI values with trench PRI values without trench Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 26 mo Regional Road 26 mm Montreal Road Montreal Road Montreal Road Richmond Road Richmond Road Scott Street Regional Road 47 Road Sections Catherine Street Catherine Street McArthur McArthur Booth Street Booth Street Kent Street Kent Street Regional Road 89 Regional Road 89 Figure 28. Utility trench impact on pavement roughness performance at road section level

45 Im pact on S AI w ithin trench area 2.5 Normalized SAI Impact within trench area Im pact on SAI within trench area Section Number Figure 29. Utility trench impact on structural adequacy performance within each trench SAI Values with and without trenches SAI Values SAI Values with trench SAI Values without trench Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 26 mo Regional Road 26 mm Road Sections Montreal Road Montreal Road Montreal Road Richmond Road Richmond Road Scott Street Regional Road 47 Catherine Street Catherine Street McArthur McArthur Booth Street Booth Street Kent Street Kent Street Regional Road 89 Regional Road 89 Figure 30. Utility trench impact on structural adequacy performance at road section level

46 Normalized Surface Distress Index Values for road sections Normalized SDI Impact within trench area Section Number Figure 31. Utility trench impact on surface distress performance within trench area SDI Values with and without trenches Impact on SDI within trench area SDI values 6 SDI Values with trench SDI Values without trench Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 26 mo Regional Road 26 mm Road Sections Montreal Road Montreal Road Montreal Road Richmond Road Richmond Road Scott Street Regional Road 47 Catherine Street Catherine Street McArthur McArthur Booth Street Booth Street Kent Street Kent Street Regional Road 89 Regional Road 89 Figure 32. Utility trench impact on surface distress performance at road section level

47 PQI Values with and without trenches PQI Values PQI Values with trench PQI Values without trenches Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 26 mo Regional Road 26 mm Montreal Road Montreal Road Montreal Road Richmond Road Richmond Road Scott Street Regional Road 47 Catherine Street Catherine Street McArthur McArthur Booth Street Booth Street Kent Street Kent Street Regional Road 89 Regional Road 89 Road Sections Figure 33. Utility trench impact on overall pavement quality at road section level Impact of Utility trenching on remaining life of road Year of Road Need (Date in Year) Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 10 Regional Road 26 mo Regional Road 26 mm Montreal Road Montreal Road Montreal Road Richmond Road Richmond Road Scott Street Regional Road 47 Catherine Street Catherine Street McArthur McArthur Booth Street Booth Street Kent Street Kent Street Regional Road 89 Regional Road 89 Road Sections Figure 34. Utility impact on rehabilitation need year of urban pavement sections Need Yr with trench Need Yr without trench

48 Pavement Lifecycle Plot with and without Trench Impact 35 Pavement lifecycle with trench impact removed Lifecycle plot with and without trench im pact Power (Lifecycle plot with and without trench impact) y = x R 2 = Pavement Lifecycle with trench impact Figure 35. Relationship between pavement lifecycle with and without trench impact Typical deflection profile across transverse trench Deflection Value (micro inches) Edge of trench Edge of trench Line 1 Line 2 Line Horizontal Distance (m) Figure 36. Typical deflection profile showing utility trenching zone of influence

49 Typical road profile across utility trench Vertical Road Profile (mm) (LWP) 3 (RWP) Edge of Trench Edge of Trench Horizontal Distance (m) Figure 37. Typical pavement roughness profile showing utility trenching zone of influence Typical Longitudinal Roughness Profile at various Distance from Edge of Trench Vertical Profile at various distance from the Trench Edge (mm) m in 0.15m in 1.85m out 0.15m out -40 Horizontal Distance parallel to Trench Edge (m ) Figure 38. Plot of pavement roughness profiles parallel to longitudinal edge of trench at various distances away and within the trench

50 Deflection versus location to trench, average maximums for four trenches CDB -1 Granular -2 Granular -3 CDB indicates centreline of trench Figure 39. Deflection profiles across utility trenches with granular and control density backfill

51 TABLES

52

53

54

55

56

57 TABLE 6 Utility Trenching Impact on Pavement Lifecycle based on Equation from Figure 35 Equation from Figure 35: Lifecycle without trench Impact = *(Lifecycle with trench Impact)^ Pavement Lifecycle with trench Impact (Years) Pavement Lifecycle without trench impact (years) Difference in Lifecycle (years) Percent Difference in Lifecycle

58 TABLE 7 Area occupied by the Various Utilities Area of Utility Trench Utility Type as % of Total Utility Type (square metres) Utility Area Sewer 15, Water 11, Gas 7, Bell 6, Hydro 1, Traffic Cable Catch Basin Fire alarm Multiple utilities within trench area 7, Sum 51,

59 Table 8 Utility Trenching Impact Costs Years since last Resurfaced Percent Reduction Corresponding Percent Reduction In Per sq. m Cost used to quantify trench impact Total Cost of In Pavement Lifecycle Lifecycle proportion back to trench area Item A Item B Item C Item D Utility Trench Impact 0 to 2 years $4.42 $3.32 $10.30 $5.41 $23.45 > 2 to 4 years $3.83 $3.32 $8.92 $4.82 $20.88 >4 to 7 years $2.87 $3.32 $6.68 $3.86 $16.73 >7 to 10 years $1.09 $3.32 $2.54 $2.09 $9.04 > 10 years $0.00 $3.32 $0.00 $1.00 $4.32 Note: Item A - Cost associated with reduced pavement lifecycle equivalent to 35.5 percent of 40 mm asphalt hot mix Item B - Cost associated with additional base repair Item C - Cost associated with additional 32 mm asphalt strengthening requirement within the trench area Item D - Cost associated with area impacted beyond the trench area - zone of influence

60 TABLE 9 Non parametric Mann-Whitney Statistical Analysis of No Difference in the Mean Lifecycles (δ=0 ) between the Urban and Rural Road networks. Mean Variance Sum of Ranking, S Sample Size Hypothesized Mean Difference, δ α =0.05, S Upper limit α =0.05, S Lower limit Reject Ho:δ=0 at α =0.05, two tail Overall Urban Road Sections , , ,251 Yes Rural Road Sections , , ,882 Yes CONCLUSION: Result indicates that the mean lifecycle for the Urban and Rural road network are different from each other. TABLE 10 Non parametric Mann-Whitney Statistical Analysis of No Difference in the Mean Lifecycles (δ=0 ) between the Urban Road Network and the Selected twelve Urban Road segments. Mean Variance Sum of Ranking, S Sample Size Hypothesized Mean Difference, δ α =0.05, S Upper limit α =0.05, S Lower limit Reject Ho:δ=0 at α =0.05, two tail Overall Urban Road Sections , ,894 30,020 No Twelve Urban Road Segments , , ,906 No CONCLUSION: Result indicates that there is no difference in the mean lifecycle for the overall urban road network and the selected twelve urban road segments.

61 APPENDICES

62 APPENDIX A Roughness determination by weighted absolute area under vertical profile For pavement sections longer than 30m, the pavement roughness rating system used by the Region s PMS system is based on profilometric data using the IRI method developed by the World Bank. However, it this study the area impacted by utility trenching is generally localized in nature. Hence, an alternate method to quantify the area under consideration to the pavement roughness is required. The method proposed uses the existing detailed profile measurement along the pavement with the trench area identified. The proposed sampling for the profile measurement is every 100 mm. The absolute area under the vertical profile was calculated for both trenched and non-trenched areas for each road section as shown by the shaded areas in Figure 5. The normalized average vertical profile component that contributes to the pavement roughness of the trench and nontrench area was obtained by dividing the absolute areas mentioned above by the respective longitudinal length. The normalized average vertical profile value within trench and non-trench area are used to determine the relative impact of trenching when compared to the non-trenched impacted area. The value of the pavement roughness is still initially computed using the IRI concept for the pavement section. Then, using the relative impact on roughness, it was computed using the weighted absolute area under the vertical profile.

63 APPENDIX B Dynaflect Seasonal Correction The dynaflect determines the surface strength of the pavement. This surface strength is a measure of the strength of the subgrade at the time that the load was applied to the pavement. It also provides the load distribution characteristics of the material layers in the flexible pavement structure. The strength of the subgrade is dependent on the climate conditions, and thus dynaflect deflection values of a pavement section will vary seasonally and annually. The dynaflect values are sensitive to changes in surface temperature and thus temperature correction values are applied to all measurements. This temperature correction is based on the temperature gradient of the asphalt and thus is determined using the temperature of the asphalt at the time of measurement and the thickness of the pavement. The deflection values of flexible pavements that are subjected to frost action will increase during the spring season. The pavement structure will be at its weakest in this season, indicating the critical performance period of the pavement. Pavement design, therefore, must be for this critical strength period. Dynaflect measurements, however, can be taken at different times during the year. In order to compare readings taken at different times, all values must be corrected to a common baseline by applying a seasonal correction to the measurements. The Region has eleven correlation sites, as shown in Figure B1, that are used to determine the seasonal correction values. These locations were selected such that they would be distributed evenly throughout the Region, and they would represent the different subgrade types found within the Region. Dynaflect data are collected at each site several times in a year. A significant number of visits are made in the spring to capture the rapid change in subgrade strength. The average deflection for all of the sites is calculated from the individual average maximum deflection for each site, and is plotted with time. This will generate a curve similar to Figure B2. Using this curve, data collected at any point in time on this curve is corrected so that it represents the deflection during the critical period. Dynaflect Temperature Correction In the Region s PMS deflection analysis, the temperature correction procedure used for asphalt pavement greater than 50 mm follows the Asphalt Institute method to determine the mean temperature at the time of the deflection measurements are taken. However for pavements with asphalt depths less than 50 mm, the temperature correction procedure used is based on the method developed by Southgate. This method is more dependent on the amount of heat absorption and degree Celsius days than on the maximum and minimum air temperatures for the five days prior to the deflection data collection, as per the Asphalt Institute method. 2

64 Figure B1: Dynaflect Correlation Sites in the Region of Ottawa-Carleton 2