Hot Mixed Asphalt Pavement Surface Characteristics Related to: Ride, Texture, Friction, Noise and Durability

Transcription

1 Hot Mixed Asphalt Pavement Surface Characteristics Related to: Ride, Texture, Friction, Noise and Durability Second Year Monitoring and Performance Report LRRB INV 868, MPR-6(29) Task 5 (Interim) Report Prepared by Mark Watson Tim Clyne Bernard Izevbekhai Minnesota Department of Transportation Office of Materials and Road Research 14 Gervais Avenue Maplewood, MN February 211

2 Table of Contents Chapter 1. Introduction and Test Cell Description... 1 Minnesota Road Research Project (MnROAD)... 1 Objectives of Report and Research... 2 Study Cells... 3 Chapter 2. Experimental Testing... 8 Introduction... 8 Texture... 8 Sand Patch Test... 8 Circular Track Meter (CTMeter)... 8 Friction Locked Wheel Skid Trailer (LWST) Grip Tester... 2 Dynamic Friction Tester... 2 Ride Ames Light Weight Profiler Sound Sound Absorption (Impedance Tube) Sound Intensity (OBSI) Hydraulic Conductivity Durability Visual Distress Survey (LTPP) Rating with Pavement Management Equipment... 4 Rutting (ALPS) Chapter 3. Conclusions Conclusions References Other References... 6 i

3 List of Figures Figure 1.1. MnROAD Facility... 1 Figure 1.2. Location of Test Cells on MnROAD Mainline (ML)... 1 Figure 1.3. Location of Test Cells on MnROAD Low Volume Road (LVR)... 2 Figure 1.4. Typical Sections of Mainline (ML) Test Cells... 4 Figure 1.5. Typical Sections of Low Volume Road (LVR) Test Cells... 4 Figure 1.6. Ultra Thin Bonded Wearing Coarse [Left], Warm Mix Asphalt [Right]... 7 Figure Taconite [Left] and X-Section of Porous HMA [Right]... 7 Figure 1.8. FA-3 Chip Seal [Front] and FA-2 Chip Seal [Back]... 7 Figure 2.1. Circular Track Meter (CTM)... 9 Figure 2.2. Box and Whisker Plot: Texture (MPD) vs. Cell... 1 Figure 2.3. Macro-Texture vs. and : UTBWC (C 3) & 4.75mm Taconite (C 6) Figure 2.4. Macro-Texture vs. and : 12.5 WMA (C 19) & WMA Control (C 24).. 12 Figure 2.5. Macro-Texture vs. and : Porous HMA (C 86) Figure 2.6. Macro-Texture vs. and : Porous CTRL (C 87) Figure 2.7. Macro-Texture vs. and : Porous HMA (C 88) Figure 2.8. Dynatest Locked Wheel Skid Trailer Figure 2.9. Box and Whisker Plot: Friction (FN4-Ribbed) vs. Cell Figure 2.1. Box and Whisker Plot: Friction (FN4-Smooth) vs. Cell Figure FN(4) vs. : UTBWC (C 2 & 3) & 12.5 SP (C 4) Figure FN(4) vs. : 4.75 Taconite (C 6) & WMA (C 19) Figure FN(4) vs. : FRAP (C 22) & 12.5 SP (C 24) Figure FN(4) vs. : Porous HMA (C 86 & 88) & Porous CTRL (C 87) Figure FN(4) vs. : FA-2.5 CS (C 27-OUT) & FA-2 CS (C 27-IN)... 2 Figure Dynamic Friction Tester (DFT), (1) & test-to-test variation... 2 Figure DFT Measurements vs. & Location: UTBWC (C 3) Figure DFT Measurements vs. & Location: 12.5 SP (C 4) & 4.75 Taconite (C 6) Figure DFT Measurements vs. & Location: 4.75 Taconite (C 6) & WMA (C 19) Figure 2.2. DFT Measurements vs. & Location: 4.75 Taconite (C 6) & FRAP (C 22) Figure DFT Measurements vs. & Location: 4.75 Taconite (C 6) & FRAP (C 22) Figure Lightweight Inertial Surface Analyzer (LISA) ii

4 Figure Box and Whisker Plot: Ride (IRI, in/mi) vs. Cell Figure IRI vs. & Location: UTBWC (C 2-3), 12.5 SP (C 4) & 4.75 Tac (C 6) Figure IRI vs. & Loc.: WMA (C 19), FRAP (C 22), WMA CL (C 24) & CS (C 27) 29 Figure IRI vs. & Location: Porous (86-88) & Porous CTRL (C 87)... 3 Figure Sound Impedance Tube Figure Absorption Ratios at different frequencies for selected HMA Surface Types Figure On Board Sound Intensity (OBSI) Test Setup Figure 2.3. Box and Whisker Plot: A-weighted Sound Intensity vs. Cell Figure A-Wtd. Sound vs. : UTBWC (2-3), 12.5 SP (4), 4.75 Tac. (6) & WMA (19) 35 Figure A-Wtd. Sound vs. : FRAP (22), WMA CTRL (24) & CS (27) Figure Hydraulic Conductivity, k (cm/sec): Porous HMA (86 & 88) Figure Field Permeameter Figure Ride Quality (RQI) & Surface Distresses (PSR) vs. Cell & Figure Automated Laser Profile System (ALPS) Figure Box and Whisker Plot: ALPS Rutting, inches vs. Cell Figure Box and Whisker Plot: ALPS Rutting, inches vs. Cell (Outliers Removed) Figure ALPS Rutting vs. & : UTBWC (2) Figure 2.4. ALPS Rutting vs. & : UTBWC (3) Figure ALPS Rutting vs. & : 12.5 SP (4) Figure ALPS Rutting vs. & : 4.75 Tac (6) Figure ALPS Rutting vs. & : WMA (19)... 5 Figure ALPS Rutting vs. & : FRAP (22) Figure ALPS Rutting vs. & : WMA CTRL (24) Figure ALPS Rutting vs. & : CS (27) Figure ALPS Rutting vs. & : Porous (86) Figure ALPS Rutting vs. & : Porous CTRL (87) Figure ALPS Rutting vs. & : Porous (88) iii

5 List of Tables Table 1.1. Chip Seal Surface Treatment Gradation... 5 Table 1.2. HMA Surface Allocation... 6 Table 2.1. Surface Characteristics Tests: Measurement Type and Frequency... 8 Table 2.2. Descriptive Statistics for Texture Measurements... 9 Table 2.3. Descriptive Statistics for Friction (FN4-Ribbed) Measurements Table 2.4. Descriptive Statistics for Friction (FN4-Smooth) Measurements Table 2.5. Descriptive Statistics for Ride (in/mi) Measurements Table 2.6. Descriptive Statistics for A-Weighted Sound Intensity vs. Cell Table 2.7. LTPP Distress Ratings for Asphalt Concrete Surfaces (13) Table 2.8. Fall 29 LTPP Distress Survey of Mainline Test Cells... 4 Table 2.9. RQI Categories and Ranges (14)... 4 Table 2.1. Descriptive Statistics for Rutting Results (Outliers Removed) iv

6 Chapter 1. Introduction and Test Cell Description Minnesota Road Research Project (MnROAD) The Minnesota Road Research Project (MnROAD) was constructed by the Minnesota Department of Transportation (Mn/DOT) in as a full-scale accelerated pavement testing facility, with traffic opening in Located near Albertville, Minnesota (4 miles northwest of St. Paul-Minneapolis), MnROAD is one of the most sophisticated, independently operated pavement test facilities of its type in the world (1). Its design incorporates thousands of electronic in-ground sensors and an extensive data collection system that provide opportunities to study how traffic loadings and environmental conditions affect pavement materials and performance over time. MnROAD consists of two unique road segments located parallel to Interstate 94 as shown in Figure 1.1 as described below: A 3.5-mile Mainline (ML) interstate roadway carrying live traffic averaging 28,5 vehicles per day with 12.7 % trucks. A 2.5-mile closed-loop Low Volume Road (LVR) carrying a MnROAD-operated 18- wheel, 5-axle, 8,-lb tractor-semi-trailer to simulate the conditions of rural roads. Figure 1.1. MnROAD Facility During the summer and fall of 28 MnROAD was undergoing its phase 2 construction project (SP ) to reconstruct or rehabilitate many of its existing cells. Many of these reconstructed cells had unique characteristics and incorporated innovative technologies that were relatively new to Mn/DOT. The close proximity of so many different surface types and mix designs in a real life laboratory setting provided a unique opportunity for an in-depth study of HMA surface characteristics. Figure 1.2 and Figure 1.3 show the relative location of the test cells of interest located on the mainline and low volume road respectively. MnROAD Mainline Figure 1.2. Location of Test Cells on MnROAD Mainline (ML) 1

7 Figure 1.3. Location of Test Cells on MnROAD Low Volume Road (LVR) Objectives of Report and Research This report represents task 5 of Local Road Research Board (LRRB) 868, Minnesota State Planning and Research project number MPR 6-(29) study entitled, HMA Surface Characteristics Related to: Ride, Texture, Friction, Noise and Durability. This report summarizes surface characteristics measurements made during the time period immediately after construction until fall of 21. This report is a follow-up report to task 4 (2-3) that reported on measurements made immediately after construction through fall 29. The surface characteristics tests were designed to characterize: texture, friction, ride, sound, permeability and durability. Generalization of the results will be made, however an in-depth analysis will be reserved for later reports. The overall goal of this research is to provide basic research (monitoring) of key pavement properties that can be used to optimize pavement designs as they relate to durability, safety and environmental stewardship. Pavements have always had the requirement of being safe and durable; however recently, pavements have also been asked to be quiet and environmentally friendly. Pavement safety has traditionally focused on providing adequate skid resistance, which has also requires that rutting be such that hydro-planning does not become an issue. Recently, pavement safety has expanded to include other safety benefits, including reduced splash and spray, which can be provided by gap graded and open graded HMA pavements and skid resistance enhancements provided by lower cost surface treatments. In addition, there is an increased emphasis on environmental stewardship. This includes not only doing a better job of mitigating physical pollution, such as rain water run-off that can be captured and treated by porous pavement systems, but also reducing the demand on environmental materials through the use of recycled materials (recycled asphalt pavement, RAP and Fractionated Recycled Asphalt Pavement, FRAP) and finally it includes addressing noise pollution in urban areas through the use of quiet pavements. An example of one such quiet pavement is cell 6, which is an asphalt surface (quiet) placed over a concrete pavement. However these environmental benefits need to be examined in concert with pavement durability. For example any environmental gains through reduced noise and water pollution and reduced virgin materials usage would be lost if the pavement did not have adequate durability and had to be rehabilitated or repaired sooner than a traditional pavement. As with all engineering problems, there is no simple solution, as oftentimes maximizing one benefit tends to reduce other benefits, for example a surface treatment can provide enhanced friction numbers, but can also increase noise pollution. An HMA overlay over a PCC pavement can reduce noise pollution, but will likely suffer durability (and possibility ride issues) through the onset of reflective cracks. Thus, the problem becomes one of optimization. The goal of this 2

8 research project is to provide performance monitoring and test data that can be used to assist with this optimization process. This includes improving the understanding of the interrelationships among the different surface types and the various surface characteristics, which may involve an analytical model. This research intends to improve the realization of optimized safety, environmental and durability properties of HMA pavements. Another aspect of this optimization, related specifically to noise pollution, involves a global tire-pavement interaction algorithm. This algorithm could incorporate the following pavement surface parameters: ride quality observed in the frequency domain, tire-pavement noise, texture, pavement porosity, effective flow resistivity (EFR) or sound absorption, and friction. These factors are measured and reported on in this report; they influence the tirepavement interaction mechanism. The current Traffic Noise Model (TNM) or MINNOISE (as used in Minnesota) does not account for, or yet provide, for the usage of sound-attenuating and absorbing pavements. This model predicts the noise levels generated by traffic and is useful for designing sound mitigation techniques such as sound walls. If pavement surfaces could be used to mitigate some of the noise, there is the possibility for great cost savings in reduced noise walls. Although textures are officially categorized in terms of wavelength, current research reveals that equal mean texture depth does not imply similar noise and friction response and ride influence. There is a need to characterize the co-dependent pavement surface parameters. The need is especially great in Minnesota because of innovative HMA and surface treatment designs. Study Cells The surface characteristics study includes eleven test cells on both the MnROAD ML and LVR. These test cells have unique surface mixture types that include different gradations (gap graded, one-sized gradation, coarse dense graded and fine dense graded), different binder types, different levels of binder aging (Warm Mix Asphalt and Aging Study) and different amounts and gradations (Fractionated) of recycled asphalt pavement (RAP). Construction details, including mix design worksheets and other pertinent information are available in the task 2 report of this study which documents construction and initial test results (2). Figure 1.4 and Figure 1.5 show the typical sections of the ML and LVR test cells respectively. Note the thickness and type of surface, base (FDR denotes Full Depth Reclamation) and subgrade materials. 3

9 " TBWC 1" TBWC 1" " " " " FDR + EE 6" FDR 26" Class 4 6" FDR + EE 2" FDR 2"Cl 5 33" Class 3 8" FDR + EE 9" FDR + Fly Ash Clay 2" " 6" Cl 1 Stab Agg 6" Class 5 Clay Mesabi 4.75 SuperP 15'x12' 1" dowel 2" " Cl 1 Stab Agg 6" Class 5 Clay Mesabi 4.75 SuperP 15'x12' no dowels 5" WM " Class 5 12" Class 3 7" Select Gran Clay 5" " Class 5 12" Class 3 7" Select Gran Clay Clay 3% Fract RAP Clay Oct 8 Oct 8 Oct 8 Oct 8 Oct 8 Sept 8 Sept 8 Current Current Current Current Current Current Current Figure 1.4. Typical Sections of Mainline (ML) Test Cells " " " " Porous HMA 5" 4" Control 5" Porous HMA 4" Cl6sp Sand 6" Cl-5 4" RR Ballast 4" Mesabi Ballast 4" RR Ballast 1' Fog Seal 28 1' Chip Seals GCBD 7" Clay Borrow Clay 1" CA-15 Type V Geo- Textile Sand 11" CA-15 Type V Geo- Textile Clay Sand 1" CA-15 Type V Geo- Textile Clay Oct 8 Aug 6 Oct 8 Oct 8 Oct 8 Current Current Current Current Current Figure 1.5. Typical Sections of Low Volume Road (LVR) Test Cells 4

10 Four cells had surface treatments placed over the HMA surface, these cells include: 2, 3, 24 and 27. Cells 2 and 3 received a ultra thin bonded wearing course (UTBWC), consisting of a high quality, gap graded aggregate and a highly polymer modified asphalt cement (AC). Cell 24 is part of a pooled fund aging study (TPF-5(153)) which requires a different section of the cell to be sealed every year. In 28, the cell received a fog seal of diluted (1:1) CSS-1h emulsion (1 ft section) and in 29 the cell received a fog seal of diluted (1:4) CRS-2p (1 ft section). The cell will receive an additional fog seal every year until 212 (different 1 ft section per year). In September 29, cell 27 received a chip seal surface treatment consisting of a polymer modified CRS-2p emulsion followed by class A aggregate meeting the FA-2 (inside lane) and FA-3 (outside lane) gradations shown in Table 1.1. Table 1.1. Chip Seal Surface Treatment Gradation Table 1.2 shows the details of the hot mixed asphalt (HMA) pavement of the study cells. Note that cells numbered less than 24 (<24) are located on the mainline (ML) and the remaining cells are located on the low volume road (LVR). The HMA surface mixture types are denoted according to Mn/DOT s 28 specifications ( combined.pdf) and can be summarized as follows: All mixtures were SuperPave or Gyratory design (denoted SP) and all had a maximum aggregate size of 19. mm (nominal maximum size of 12.5 mm) denoted by B (except for the UTBWC and 4.75mm Taconite). The mixtures on the LVR were based on 2 year design of 1 to < 3*1 6 ESALS, denoted by 3 where those on the ML were based on 3 to <1*1 6 ESALS denoted by 4. All mixtures had target air voids of 4.% denoted by 4. Finally the last letter indicates the binder Performance Grade (PG): F (64-34), C (58-34), H (7-28) or B (58-28). 5

11 Table 1.2. HMA Surface Allocation Cell (Loc) HMA Surface Mix Type PG Grade, %RAP 2 (ML) 3 (ML) 4 (ML) 6 (ML) 19 (ML) 22 (ML) 24 (LVR) 27 (LVR) 86 (LVR) 87 (LVR) 88 (LVR) UTBWC UTBWC 64-34, % 64-34, % SPWEB44F 64-34, % SPWEB44F Special SPWEB44C Special SPWEB44C Special 64-34, % 58-34, 2% 58-34, 3% SPWEB44C 58-34, 2% SPWEB34A 52 34, % SPWEB44H Special , % SPWEB34B 58-28, 2% SPWEB44H Special , % Description Ultra Thin Bonded Wearing Course (UTBWC) Ultra Thin Bonded Wearing Course (UTBWC) Level mm Dense Graded Superpave (12.5 SP) 4.75 mm Taconite HMA (4.75 Taconite) Warm Mix Asphalt 12.5 mm Dense Graded Superpave (WMA) Fractionated RAP 12.5 mm Dense Graded Superpave (FRAP) Warm Mix Control 12.5 mm Dense Graded Superpave (WMA CTRL) FA-2 (3) Chip Seal FA-2 CS (Inside Lane) FA-3 CS (Outside Lane) Porous HMA on Sand (Porous) Level mm Dense Graded Superpave (Porous CTRL) Porous HMA on Clay (Porous) Figure 1.6 to Figure 1.8 shows the surface of selected study cells, including: ultrathin bonded wearing course (UTBWC), warm mix (WMA), 4.75 taconite, porous and CS, respectively. 6

12 Figure 1.6. Ultra Thin Bonded Wearing Coarse [Left], Warm Mix Asphalt [Right] Figure Taconite [Left] and X-Section of Porous HMA [Right] Figure 1.8. FA-3 Chip Seal [Front] and FA-2 Chip Seal [Back] 7

13 Chapter 2. Experimental Testing Introduction Table 2.1 summarizes the type and frequency of the surface characteristics tests that were conducted during 21 (the second full year of monitoring) that were used in this project to quantify and compare the different HMA surfaces at the MnROAD test facility. All cells were tested unless specified otherwise in the table. The initial results of these tests, as well as a short description of the methodology and results are included in this chapter. Raw data tables are not included; however they can be made available by contacting the Mn/DOT office of Materials and Road Research. The results of the second year tests are oftentimes shown graphically with the initial and first year measurements so that the seasonal and annual changes can be observed. Table 2.1. Surface Characteristics Tests: Measurement Type and Frequency Property Test Employed (Result) Cells Tested 21 Test Frequency Texture 1. Circular Texture Meter (CTM) MPD All Summer/Fall Friction 1. Locked Wheel Skid Trailer FN (4) Ribbed All Fall & Smooth 2. Dynamic Friction Tester (DFT) μ at 7 speeds 3,4,6,19,22 Fall Ride 1. Lightweight Inertial Surface Analyzer (LISA) IRI, inches/mile All Spring/Summer & Fall Sound 1. Impedance Tube Absorption 3,6,19, Spring/Fall 2. On Board Sound Intensity A-Weighted All Spring/Fall (OBSI) Sound Intensity Hydraulic Conductivity 1. Field Permeameter K, cm/sec 86 & 88 Spring/Fall Durability 1. Visual Distress Survey (LTPP) All Spring/Fall 2. Pavement Management Ride (RQI) & All Spring/Fall Distress (PSR) 3. ALPS Rutting, inches All Spring/Summer & Fall Texture Sand Patch Test The sand patch test (ASTM E 965) was only used to characterize the macrotexture on October 28, afterwards the circular track meter (CTMeter) was used. See the task 2 report (2) for sand patch testing results. Circular Track Meter (CTMeter) The circular texture meter (CTMeter), performed in accordance with ASTM E 2157 (4), uses a rotating laser to measure the surface profile of a circle around a circumference (11.2 in.), see 8

14 Figure 2.1. The profile of this circle divided by the circumference yields a spot measurement of the mean profile depth (MPD). According to Abe et al (5) the MPD values are highly correlated with the mean texture depth (MTD) values, equation 2 shows the recommended relationship between MTD and MPD. This relationship was used to convert the sand patch measurements from October 28 to an equivalent MPD value. Figure 2.1. Circular Track Meter (CTM) MTD =.947 MPD +.69 (eq. 3.2) The test reports both the MPD and the root mean square (RMS) values of the macro texture profile (5). Table 2.2 shows the descriptive statistics and Figure 2.2 depicts a box and whisker plot of the MPD measurements. The top and bottom of the box represent the third (75%) and first (25%) quartiles, respectively. The middle of the box represents the median, and the whiskers, or lines extending from the box represent the maximum and minimum values. There do not appear to be any suspected outliers. There appears to be a large difference in the texture behavior among the cells. The cell with the lowest MPD has also the smallest standard deviation, or spread of the data, and the cells with the highest MPD (Porous asphalt and UTBWC) have the highest standard deviations. For example, the standard deviation of the porous cells (86 & 88) is approximately equal to the mean MPD value for the 4.75 (6) cell; the standard deviation of the 4.75 (6) is approximately 1/6 or 1/7 that of the porous cells (86 & 88). Table 2.2. Descriptive Statistics for Texture Measurements MPD/Cell N Mean SD Minimum st Quart rd Quart Maximum Surface texture is important because it is related to: pavements friction and noise. The FHWA has a technical advisory that issues information on, state-of-the-practice for providing surface texture/friction on pavements and issues guidance for selecting techniques that will provide adequate wet pavement friction and low-tire/surface noise characteristics (6). Currently (as of 21) Mn/DOT has no official texture standard for HMA pavement construction. The only texture standard that Mn/DOT employs is for astro-turf or carpet drag texture on new 9

15 concrete pavements (7). The standard specifies that the surface shall have a minimum value of 1. mm. Any lot showing an average of less than 1. mm but equal to or greater than.8 mm will be accepted as substantial compliance but the contractor shall amend their operation to achieve the required 1. mm minimum depth (MTD). If eq. 3.2 is applied to the mean values shown in Table 2.2, every cell, except for Porous (86 & 88) has an MPD standard deviation less than.2 mm. In addition, the UTBWC (3) and the porous (86 & 88) are the only cells that have MPD values greater than the concrete specification. Thus it can be concluded that the variation within a particular cell is relatively small compared to the Mn/DOT standard for Concrete Texture. Furthermore, it appears that acceptable texture values are different for HMA and PCC. Figure 2.2. Box and Whisker Plot: Texture (MPD) vs. Cell Figure 2.3 to Figure 2.7 show the results of the first two years of texture monitoring of the HMA surface test cells, between fall 29 and fall 21. These figures depict variation of the MPD both with time, and location (longitudinal location (station) and transverse location (offset)). Missing values in cells 86 and 88 were interpolated so that they were not counted as zero in the figure. When it was not possible to interpolate missing data, as in the case of WMA CTRL (cell 24), the date for which the missing measurements were made was excluded, interpolation may be appropriate when new data becomes available. When there were repetitive measurements at the same time and location, the average was used. The surface type is denoted according to Table 1.2 with the cell number in parentheses. The transverse locations for the mainline test cells are denoted as either the left or right wheel path of either the driving (right) or passing (left) lane. For the low volume road the lanes are denoted accordingly. The figures confirm the observations drawn from the Box and Whisker Plot and the Descriptive Statistics. The most dramatic changes, both with time and location (station), appear to occur in those cells with the greatest texture: UTBWC (3) and Porous (86 & 88). The texture appears to be influenced more by the location than by the season or year in which the measurement was made. 1

16 Cell 3: DL Right Wheel Path Cell 3: PL Left Wheel Path Mean Profile Depth (mm) Sep 9 Oct Mean Profile Depth (mm) Sep 9 Oct Cell 6: DL Right Wheel Path Cell 6: PL Left Wheel Path Mean Profile Depth (mm) Jun 1 Sep Mean Profile Depth (mm) Jun 1 Sep Figure 2.3. Macro-Texture vs. and : UTBWC (C 3) & 4.75mm Taconite (C 6) 11

17 Cell 19: DL Right Wheel Path Cell 19: PL Left Wheel Path Mean Profile Depth (mm) Jun 1 19 Sep Mean Profile Depth (mm) Jun Cell 24: InLane Right Wheel Path Cell 24: OutLane Left Wheel Path Mean Profile Depth (mm) Jun 1 Sep 9 Nov Mean Profile Depth (mm) Jun Figure 2.4. Macro-Texture vs. and : 12.5 WMA (C 19) & WMA Control (C 24) 12

18 Cell 86: InLane Right Wheel Path Cell 86: InLane Left Wheel Path Mean Profile Depth (mm) Nov 1 3 Jun Mean Profile Depth (mm) Nov 1 Jun Cell 86: OutLane Right Wheel Path Cell 86: OutLane Left Wheel Path Mean Profile Depth (mm) Nov 1 Jun Mean Profile Depth (mm) Nov 1 Jun Figure 2.5. Macro-Texture vs. and : Porous HMA (C 86) 13

19 Cell 87: InLane Right Wheel Path Cell 87: InLane Left Wheel Path Mean Profile Depth (mm) Nov 1 3 Jun 1 16 Oct Mean Profile Depth (mm) Nov 1 Oct 9 Jun Cell 87: OutLane Right Wheel Path Cell 87: OutLane Left Wheel Path Mean Profile Depth (mm) Nov 1 Oct 9 Jun Mean Profile Depth (mm) Nov 1 Oct 9 Jun Figure 2.6. Macro-Texture vs. and : Porous CTRL (C 87) 14

20 Cell 88: InLane Right Wheel Path Cell 88: InLane Left Wheel Path Mean Profile Depth (mm) Nov 1 3 Jun Mean Profile Depth (mm) Nov 1 Jun Cell 88: OutLane Right Wheel Path Cell 88: OutLane Left Wheel Path Mean Profile Depth (mm) Nov 1 Jun Mean Profile Depth (mm) Nov 1 Jun Figure 2.7. Macro-Texture vs. and : Porous HMA (C 88) 15

21 Friction Locked Wheel Skid Trailer (LWST) Locked wheel skid trailer (LWST) tests were performed in accordance with ASTM E 247 (8), with a device similar to Figure 2.8. This test is one of the most common methods employed by state departments of transportation (DOT) to obtain a measure of friction. This test produces a slip speed (speed of the test tire relative to the speed of the vehicle) equal to that of the test vehicle, or a 1% slip condition. The brake is applied to the testing wheel and the resulting constant force is measured for an average of 1 second after the wheel is locked. The two different types of test wheels include a smooth tire (influenced primarily by macro texture) or a ribbed tire (influenced primarily by micro texture). The ASTM Standard (8) requires at least five lockups to be made in a uniform test section, as the test does not give a continuous measurement. The results are reported as a skid number, which is 1 times the friction value. This friction value should be used for comparison and informational purposes only. Figure 2.8. Dynatest Locked Wheel Skid Trailer Friction numbers were measured at a speed of approximately 4 miles per hour with either a ribbed or a smooth tire, and are denoted as either FN4-Ribbed or FN4-Smooth. Table 2.3 and Table 2.4 present the summary statistics of FN4-Ribbed and FN4- Smooth measurements for all cells, respectively. The Ribbed tire is more sensitive to micro texture and the smooth tire is more sensitive to macro texture. Figure 2.9 and Figure 2.1 show a graphical representation of the FN4-Ribbed and FN4-Smooth measurements by cell, respectively. Table 2.3. Descriptive Statistics for Friction (FN4-Ribbed) Measurements FN4Rib N Mean SD Minimum st Quart rd Quart Maximum

22 Table 2.4. Descriptive Statistics for Friction (FN4-Smooth) Measurements FN4Smt N Mean SD Minimum st Quart Median rd Quart Maximum CELL 77 cases Figure 2.9. Box and Whisker Plot: Friction (FN4-Ribbed) vs. Cell CELL 76 cases Figure 2.1. Box and Whisker Plot: Friction (FN4-Smooth) vs. Cell There is no universally accepted default friction value that separates a safe pavement from an unsafe pavement (9). Friction numbers are not sufficient to determine the distance required to stop a vehicle, or the driving speed at which control would be lost (9). Thus the 17

23 measurements presented are for informational and comparison purposes only. They could be incorporated into an analytical model, but that is outside the scope of this task report at this time. Figure 2.11 to Figure 2.15 shows the friction number variation with time, measurements were taken from October 28 to September 21. Aside from the WMA CTRL (cell 24) the 4.75 Taconite (cell 6) appears to have the greatest difference between the smooth tire and ribbed tire results, which is indicative of the influences of macro and micro texture, respectively. The 4.75 Taconite (cell 6) has a relatively high micro texture, but a relatively low macro texture. The 12.5 SP, or WMA Control (cell 24) appears to have both the highest and the lowest ribbed and smooth tire results and the chip seal (cell 27) had the highest smooth and ribbed tire results. One of the major factors influencing the WMA CTRL (cell 24) low friction numbers is that it is part of another study at MnROAD investigating the influence of fog sealing on the mechanical or aging properties of HMA pavements. The low results are due to the fact that the section had a heavy fog seal applied just 7 days prior to being tested. The UTBWC (cells 2 and 3) had consistently relatively high values, and low differences between results, for both the ribbed and smooth tires in both the driving and the passing lanes. The porous (cells 86 and 88) displayed ribbed and smooth tire results lower than the UTBWC (cell 2 and 3), consistent between the inside and outside lanes and a low difference between the smooth and ribbed tire results, except for cell 88, which had a high difference between the smooth and ribbed tire results. It appears that, in general, the fine, dense graded mixtures displayed the greatest variability in the difference between ribbed and smooth tire results and in the difference between lanes, followed by the coarse dense graded mixtures, excluding the 12.5mm WMA (cell 19). 7 FN(4) vs. : Cells 2 & 3 7 FN(4) vs. : Cell DL Rib PL Rib DL Smt PL Smt DL Rib PL Rib DL Smt PL Smt Oct 8 Feb 9 May 9 Aug 9 Nov 9 Mar 1 Jun 1 Sep 1 Oct 8 Feb 9 May 9 Aug 9 Nov 9 Mar 1 Jun 1 Sep 1 Figure FN(4) vs. : UTBWC (C 2 & 3) & 12.5 SP (C 4) 18

24 7 FN(4) vs. : Cell 6 7 FN(4) vs. : Cell DL Rib PL Rib DL Smt PL Smt DL Ribbed PL Ribbed DL Smt PL Smt Oct 8 Feb 9 May 9 Aug 9 Nov 9 Mar 1 Jun 1 Sep 1 Oct 8 Feb 9 May 9 Aug 9 Nov 9 Mar 1 Jun 1 Sep 1 Figure FN(4) vs. : 4.75 Taconite (C 6) & WMA (C 19) 7 FN(4) vs. : Cell 22 7 FN(4) vs. : Cell DL Ribbed PL Ribbed DL Smooth PL Smooth 2 1 IN Ribbed OUT Ribbed IN Smooth OUT Smooth Oct 8 Feb 9 May 9 Aug 9 Nov 9 Mar 1 Jun 1 Sep 1 Oct 8 Feb 9 May 9 Aug 9 Nov 9 Feb 1 May 1 Sep 1 Figure FN(4) vs. : FRAP (C 22) & 12.5 SP (C 24) 7 FN(4) vs. : Cell 86 & 88 7 FN(4) vs. : Cell IN Ribbed OUT Ribbed 2 IN Smooth OUT Smooth 1 Jun 9 Sep 9 Dec 9 Mar 1 Jun 1 Sep 1 3 IN Ribbed 2 OUT Ribbed IN Smooth 1 OUT Smooth Jun 9 Sep 9 Dec 9 Mar 1 Jun 1 Sep 1 Figure FN(4) vs. : Porous HMA (C 86 & 88) & Porous CTRL (C 87) 19

25 7 FN(4) vs. : Cell IN Ribbed OUT Ribbed IN Smooth OUT Smooth 2 1 Chip Seal Applied Oct 8 Feb 9 May 9 Aug 9 Nov 9 Feb 1 May 1 Sep 1 Figure FN(4) vs. : FA-2.5 CS (C 27-OUT) & FA-2 CS (C 27-IN) Grip Tester Unfortunately, the Grip tester was unavailable for testing in fall 21; for April 2, 29 test results; see the task 2 report (2). Dynamic Friction Tester The Dynamic Friction Tester (DFT) consists of three rubber sliders, positioned on a disk of diameter in, that are suspended above the pavement surface (Figure 2.16). When the tangential velocity of the sliders reaches 9 kph water is applied to the surface and the sliders make contact with the pavement. A computer takes friction measurements across a range of speeds as the sliders slow to a stop. The test reports the average of five measurements at a single location (Figure 2.16). Each Location was designated in the following fashion: driving lane (DL) or passing lane (PL) and either between the wheel paths (BWP), outside wheel path (OWP) or left wheel path (LWP). The initial measurements were taken during the fall of 29 followed by second measurements taken during the fall of μ vs. Speed (kph): Cell 3 (DLOWP) Run Figure Dynamic Friction Tester (DFT), (1) & test-to-test variation 2

26 μ vs. Speed, kph: Cell 3 DL, BWP μ vs. Speed, kph: Cell 3 DL, OWP μ vs. Speed, kph: Cell 3 PL, BWP μ vs. Speed, kph: Cell 3 PL, RWP Figure DFT Measurements vs. & Location: UTBWC (C 3) 21

27 μ vs. Speed, kph: Cell 4 DL, BWP 1.9 μ vs. Speed (kph): Cell Loc Driving Lane Outside Wheel Path, 29 Passing Lane Between Wheel Paths, 21 Passing Lane Right Wheel Path, μ vs. Speed, kph: Cell 6 DL, BWP μ vs. Speed, kph: Cell 6 PL, BWP Figure DFT Measurements vs. & Location: 12.5 SP (C 4) & 4.75 Taconite (C 6) 22

28 μ vs. Speed, kph: Cell 6 PL, BWP μ vs. Speed (kph): Cell Loc Passing Lane Right Wheel Path, μ vs. Speed, kph: Cell 19 DL, BWP μ vs. Speed, kph: Cell 19 DL, OWP Figure DFT Measurements vs. & Location: 4.75 Taconite (C 6) & WMA (C 19) 23

29 μ vs. Speed, kph: Cell 19 PL, BWP μ vs. Speed (kph): Cell Loc Passing Lane Right Wheel Path μ vs. Speed, kph: Cell 22 DL, BWP μ vs. Speed, kph: Cell 22 DL, OWP Figure 2.2. DFT Measurements vs. & Location: 4.75 Taconite (C 6) & FRAP (C 22) 24

30 μ vs. Speed, kph: Cell 22 PL, BWP μ vs. Speed, kph: Cell 22 PL, RWP Figure DFT Measurements vs. & Location: 4.75 Taconite (C 6) & FRAP (C 22) 25

31 Ride Ames Light Weight Profiler This international ride standard simulates a standard vehicle traveling down the roadway and is equal to the total anticipated vertical movement of the vehicle accumulated over the length of the section. The IRI is typically reported in units of inches/mile (vertical inches of movement per mile traveled). If a pavement were perfectly smooth, the IRI would be zero (i.e. no vertical movement of the vehicle). In the real world, however, roughness in the form of dips and bumps exist and vertical movement of vehicles occurs. As a result, the IRI is always greater than zero. The higher the IRI is, the rougher the roadway (13). Ride was measured in both the left and right wheel paths of the driving and passing lanes using certified laser profilers: an Ames light weight inertial surface analyzer (LISA, Figure 2.22) and the Mn/DOT pavement management van. The results were separated into cells by cropping the start and end stations of each of the cells. Figure Lightweight Inertial Surface Analyzer (LISA) Table 2.5 shows the descriptive statistics for these ride measurements, divided by cell number. Figure 2.23 shows a box and whisker plot of IRI vs. cell number. Figure 2.24 to Figure 2.26 present graphical representation of the ride values with time and location, organized by cell. Table 2.5. Descriptive Statistics for Ride (in/mi) Measurements IRI (in/mi) N Mean SD Minimum st Quart rd Quart Maximum

32 CELL 658 cases Figure Box and Whisker Plot: Ride (IRI, in/mi) vs. Cell The 4.75 Taconite (cell 6), the 12.5 SP (cell 4), the porous (cells 86 & 88), and the porous control (cell 87) have experienced the greatest fluctuations in IRI. The fluctuations of the 4.75 Taconite (cell 6) and the 12.5 SP (cell 4) appear to be influenced by seasonal factors (i.e. frost heaving and spring/thaw recovery) and transverse location; whereas the porous (cells 86 & 88), and the porous control (cell 87) appear to be influenced primarily by the transverse location in the cell. Recall that cell 4 was a 3 inch thick HMA pavement constructed over an 8 inch thick full depth reclamation, stabilized with engineered emulsion, over 9 inches of clay stabilized with fly ash. This section was observed heaving in the vicinity of core holes during the period of springtime ride measurements. The UTBWC (cells 2 & 3), WMA (cell 19), FRAP (cell 22) and WMA CTRL (cell 24) all appear to have comparatively low IRI. The porous and CTRL (cells 86-88) have substantially higher IRI values than the other study cells. 27

33 Cell 2 Cell Sep 1 Jun 1 Mar 1 Mar 1 Nov 9 Jun 9 Mar 9 Nov Sep 1 Jun 1 Mar 1 Mar 1 Nov 9 Jun 9 Mar 9 Nov Cell 4 Cell Sep 1 Jun 1 Mar 1 Mar 1 Nov 9 Jun 9 Mar 9 Nov Sep 1 Jun 1 Mar 1 Mar 1 Nov 9 Jun 9 Mar 9 Nov Figure IRI vs. & Location: UTBWC (C 2-3), 12.5 SP (C 4) & 4.75 Tac (C 6) 28

34 Cell 19 Cell Sep 1 Jun 1 Mar 1 Mar 1 Nov 9 Jun 9 Mar 9 Nov Sep 1 Jun 1 Mar 1 Mar 1 Nov 9 Jun 9 Mar 9 Nov Cell 24 Cell Oct 1 Jun 1 Mar 1 Nov 9 Jul Oct 1 Jun 1 Mar 1 Nov 9 Jul Apr 9 Apr Figure IRI vs. & Loc.: WMA (C 19), FRAP (C 22), WMA CL (C 24) & CS (C 27) 29

35 Cell 86 Cell Oct 1 Jun 1 Mar 1 Nov 9 Jul 9 Apr Oct 1 Jun 1 Mar 1 Nov 9 Jul 9 Apr Cell Oct 1 Jun 1 Mar 1 Nov 9 Jul 9 Apr Figure IRI vs. & Location: Porous (86-88) & Porous CTRL (C 87) 3

36 Sound Sound Absorption (Impedance Tube) Figure 2.27 shows the application of the sound impedance tube to measure the sound absorption coefficient. The sound absorption coefficient is defined as the fraction of sound energy absorbed by a material when a sound wave is reflected by its surface and generally depends upon the angle of incidence and the frequency of the sound wave (2). The sound is transmitted to the pavement surface through a projection distance d 1 and is reflected to a set of microphones at a distance d 2 from the source. The reflected noise is received by a set of microphones that are connected to an analyzer that identifies the actual reflection or absorption of each frequency from zero to 2 Hz is detected and recorded. However, the most critical frequency is 1, hz, which is the most dominant in characterizing highway noise generated by traffic. Figure 2.28 shows the absorption ratios at different frequencies of selected HMA surfaces, which were measured during 29 and 21. Not surprisingly, the porous (cell 86 and 88) consistently had significantly higher absorption coefficients than the other surfaces at all frequencies. The UTBWC (cell 3) consistently had a higher absorption ratio than the remaining other surfaces, although this difference was not as great as the porous and varied considerably at different frequencies. However, 21 measurements show that at 16 hz, the UTBWC (cell 3) has absorption values very near the porous (cells 86 & 88). The 4.75mm Taconite (cell 6) appears to have among the lowest absorption coefficients, even less than the 12.5mm level 3 SP (cell 87). The gradation of the HMA mix appears to have a great impact on sound absorption. Note that there were a few instances in 21 in which the sound absorption values were negative at 16 and 63 hz, these negative values are shown as zero on the charts. Figure Sound Impedance Tube 31

37 Absorption Absorption Absorption Median Absorption Values Oct 29 UTBWC (Cell 3) 4.75MM Tac (Cell 6) Porous Ctrl (Cell 87) Porous (Cell 86) Porous (Cell 88) Center Frequency, HZ Median Absorption Values Mar/May 21 UTBWC (Cell 3) 4.75MM Tac (Cell 6) (cell 19) (cell 24) Porous Ctrl (Cell 87) Porous (Cell 86) Porous (Cell 88) Center Frequency, HZ Median Absorption Values Oct 21 UTBWC (Cell 3) 4.75MM Tac (Cell 6) (cell 19) (cell 24) Porous Ctrl (Cell 87) Porous (Cell 86) Porous (Cell 88) Center Frequency, HZ Figure Absorption Ratios at different frequencies for selected HMA Surface Types 32

38 Sound Intensity (OBSI) Sound intensity was measured using the on board sound intensity (OBSI) apparatus shown in Figure 2.29, which is a close proximity method (cpx). OBSI equipment consists of a Chevrolet Impala and eight intensity meters connected via four communication cables to a Bruel and Kjaer front end collector connected to a Dell laptop computer. The intensity meters are mounted on a rig system attached to a standard reference test tire that is installed at the rear right (passenger) side of the vehicle and maintained at a temperature of 3 C. After recording temperature, four intensity meters were plugged in to the B&K front end unit, as well as 12v power supply and Ethernet (computer) cable. With this arrangement, the unit is capable of measuring repeatable tire pavement interaction noise of the tire pavement contact patch at a speed of 6 miles an hour, thus measuring approximately 44 ft within 5 seconds (1-11). Figure On Board Sound Intensity (OBSI) Test Setup The A-weighted frequency is a convenient logarithm scale used to mimic the human hearing spectrum (11). If n similar sources generate a noise level i, then the total noise level is given by equation 3. Consequently, if there are 2 sources with the same sound intensity, the cumulative intensity is thus 3 dba higher than the individual intensity. This implies that a reduction of the sound intensity by 3 dba is equivalent in effect to a traffic reduction to 5 % of original ADT (11). db ( A) 1 /1 db ( A) 2 /1 db ( A) n /1 db ( A) t = 1 log[ ] (eq. 3) Figure 2.31 to Figure 2.32 show the variation of the A-weighted sound intensity of the driving and passing lanes of each individual study cells/surface with time. Figure 2.3 and Table 2.6 compare the A-weighted sound intensity of the study cells using a box and whisker plot and descriptive statistics, respectively. The HMA cells appear to be relatively uniform with mean values ranging from 99.3 (12.5 SP) to 1.7 dba for the FRAP (cell 22). Not surprisingly the loudest and most variable cell is the chip sealed surface (cell 27) which had a mean value of 11.5dBA. The passing lane of the WMA (cell 19), 12.5mm SP-%RAP (cell 4) and the WMA Control (cell 24) had among the lowest. The UTBWC (cells 2 and 3) didn t provide the expected sound abatement advantage, and had among the highest A-weighted sound intensities until September November 29 when it had among the lowest A-weighted sound intensities. The season when the measurements were taken appeared to have a large influence on the results of many of the test cells, with 33

39 observed differences as great as 3 db, and many of the cells appear to show the same general seasonal patterns. Generally, there was not a large variation among test results taken the same day on the same test cell, and little observable difference between measurements taken in the driving and the passing lanes. Table 2.6. Descriptive Statistics for A-Weighted Sound Intensity vs. Cell N Mean SD Minimum st Quart rd Quart Maximum CELL 193 cases 161 missing cases Figure 2.3. Box and Whisker Plot: A-weighted Sound Intensity vs. Cell 34

40 15 OBSI (dba) vs : Cells 2 & 3 15 OBSI (dba) vs : Cell Driving Passing Driving Passing Dec 8 Mar 9 Jun 9 Oct 9 Jan 1 Apr 1 Jul 1 Nov 1 97 Dec 8 Mar 9 Jun 9 Oct 9 Jan 1 Apr 1 Jul 1 Nov OBSI (dba) vs : Cell 6 Driving Passing OBSI (dba) vs : Cell Driving Passing 97 Dec 8 Mar 9 Jun 9 Oct 9 Jan 1 Apr 1 Jul 1 Nov 1 97 Dec 8 Mar 9 Jun 9 Oct 9 Jan 1 Apr 1 Jul 1 Nov 1 Figure A-Wtd. Sound vs. : UTBWC (2-3), 12.5 SP (4), 4.75 Tac. (6) & WMA (19) 35

41 15 OBSI (dba) vs : Cell OBSI (dba) vs : Cell Driving Passing Inside Outside Dec 8 Mar 9 Jun 9 Oct 9 Jan 1 Apr 1 Jul 1 Nov 1 97 Jun 8 Sep 8 Dec 8 Mar 9 Jun 9 Sep 9 Dec 9 Mar 1 Jun 1 Sep 1 11 OBSI (dba) vs : Cell Inside Outside Chip Seal Applied 96 Jun 8 Sep 8 Dec 8 Mar 9 Jun 9 Sep 9 Dec 9 Mar 1 Jun 1 Sep 1 Figure A-Wtd. Sound vs. : FRAP (22), WMA CTRL (24) & CS (27) 36

42 Inside Lane Outside Lane Sep 8 Dec 8 Mar 9 Jul 9 Oct 9 Jan 1 May 1 Aug 1 Nov 1. Sep 8 Dec 8 Mar 9 Jul 9 Oct 9 Jan 1 May 1 Aug 1 Nov Inside Lane Inside Lane Sep 8 Dec 8 Mar 9 Jul 9 Oct 9 Jan 1 May 1 Aug 1 Nov 1. Sep 8 Dec 8 Mar 9 Jul 9 Oct 9 Jan 1 May 1 Aug 1 Nov 1 Figure Hydraulic Conductivity, k (cm/sec): Porous HMA (86 & 88) 37

43 Hydraulic Conductivity The permeability was also measured for the porous cells using a modified Permeameter as shown in Figure The hydraulic conductivity was found using equation 4. Figure 2.33 shows the hydraulic conductivity measurements of the porous HMA cells which seem to show a general decreasing trend in hydraulic conductivity. This may be an indication that the cells are becoming clogged with debris. T A P X hi + 2 k = ln AX t h f + 2 k = Hydraulic _ Conductivity, cm / sec T A t = h h P i x f = Thickness _ Pavement, cm = Cross _ Sectional _ Area, cm flow _ time,sec = initial _ head, cm = final _ head, cm 2 eq. 4 Figure Field Permeameter Durability Visual Distress Survey (LTPP) The durability of all test cells was evaluated by trained personnel using a rating system based upon the long term pavement performance (LTPP) evaluation method (12). The cells were visually evaluated for a total of 17 different distresses: cracking (9 types), patching/potholes (2 types), surface deformation (2 types), surface defects (3 types) and pumping. Table 2.7 shows the distress name and type, how the distress was measured, and the applicable severity levels. All cells were rated twice annually, once in the spring and once in the fall for a total of 5 evaluations between November 28 and September 21. Rating with Pavement Management Equipment The Mn/DOT pavement management system collects ride and distress information, including rutting, on state highway pavements on an annual basis. Information on MnROAD was collected in April and October of 29 and 21. An overview of the condition rating procedure and indices can be found at ( and details on the distress rating procedures can be found at ( Pavement Performance data on ride and distress has been gathered routinely on the trunk highway (TH) system since Two important measures gathered are the surface rating (SR), which is a rating of visual distresses on a scale of. to 4., with 4. representing a road with no visible distresses, and ride quality index (RQI), which is an indication of pavement roughness on a scale of. to 5. as described in Table 2.9. Figure 2.35 shows the rating results of both of these measurement indices for each cell/lane for the first two years of monitoring Taconite (Cell 6) and porous (86 & 88) have the poorest ride quality and surface ratings as evaluated by pavement management. This is in agreement with earlier discussions. 38

44 Table 2.8 shows the distress name and types that are present in the study cells. There are currently 6 distresses in 5 cells. The cells in the most severe condition are the 4.75 Taconite (cell 6 or 16/26) that has substantial reflective cracking (low severity transverse cracking) and the porous (cells 86 & 88) which have significant raveling. Although some of this raveling may be more appropriately labeled asphalt binder drain down, which occurred during construction, other areas may be wear from snowplow or truck traffic. Note that if the distresses are not shown in the table, then they were not observed in the cell at the time of the evaluation. Table 2.7. LTPP Distress Ratings for Asphalt Concrete Surfaces (12) Distress Unit of Measure Severity (Levels) Cracking 2. Fatigue Area Yes (3) 3. Block Cracking Area Yes (3) 4. Edge Length Yes (3) 5. Longitudinal (Wheel Path) Length Yes (3) 6. Longitudinal (Non-Wheel Path) Length Yes (3) 7. Longitudinal Sealant Det. Length Yes (3) (Wheel Path) 8. Longitudinal Sealant Det. Length Yes (3) (Non-Wheel Path) 9. Transverse Cracking Number & Length Yes (3) 1. Transverse Sealant Det. Number & Length Yes (3) Patching/Potholes 3. Patching Number & Area Yes (3) 4. Pot Holes Number & Area Yes (3) Surface Deformation 2. Rutting Depth No 3. Shoving Number & Area No Surface Defects 3. Bleeding Area No 4. Polished Aggregate Area No 5. Raveling Area Yes (3) Other Distresses 4. Pumping Number & Length No 39

45 Rating with Pavement Management Equipment The Mn/DOT pavement management system collects ride and distress information, including rutting, on state highway pavements on an annual basis. Information on MnROAD was collected in April and October of 29 and 21. An overview of the condition rating procedure and indices can be found at ( and details on the distress rating procedures can be found at ( Pavement Performance data on ride and distress has been gathered routinely on the trunk highway (TH) system since Two important measures gathered are the surface rating (SR), which is a rating of visual distresses on a scale of. to 4., with 4. representing a road with no visible distresses, and ride quality index (RQI), which is an indication of pavement roughness on a scale of. to 5. as described in Table 2.9. Figure 2.35 shows the rating results of both of these measurement indices for each cell/lane for the first two years of monitoring Taconite (Cell 6) and porous (86 & 88) have the poorest ride quality and surface ratings as evaluated by pavement management. This is in agreement with earlier discussions. Table 2.8. Fall 29 LTPP Distress Survey of Mainline Test Cells Distress Assessment Location/Date Cracking 1. Fatigue 2ft 2, Low Severity Cell 27-Out Sum Edge 4ft, Low Severity Cell 27-Out Fall 29 2ft, Med Severity Cell 27-In Fall Longitudinal 19ft, Low Severity Cell 26-DL, Spr 21 (Wheel Path) 4. Transverse Cracking 4 ft, Low Severity Cell 27-Out, Fall 29 2 (24 ft) Low Sev Cell 2-PL, Fall 21 1 (12 ft) Low Sev. Cell 2 DL. Fall (185 ft) Low Sev. Cell 16-DL, Spr 21 2 (18 ft) Low Sev Cell 16-PL, Spr (186 ft) Low Sev 1 (12ft) Med Sev 16 (192 ft) Low Sev. 2 (24 ft) Med Sev Cell 26-DL, Spr 21 Cell 26-PL, Spr 21 Patching/Potholes 5. Patching 1 (48 ft 2 ) Low Sev Cell 26, Spr 21 Surface Defects 6. Ravellinig 94 ft 2 Low Sev Cell 86-In, Fall ft 2 Low Sev Cell 86-Out, Fall ft 2 Low Sev Cell 88-In, Fall ft 2 Low Sev Cell 88-Out, Fall 21 Table 2.9. RQI Categories and Ranges (13) Numerical Rating Verbal Rating Numerical Rating Verbal Rating 4

46 Very Good Fair Good Poor 41

47 RQI: Driving (Inside) Lane vs. Cell RQI: Passing (Outside) Lane vs. Cell Apr 9 Apr Apr 9 Apr 1 4. PSR: Driving (Inside) Lane vs. Cell PSR: Passing (Outside) Lane vs. Cell Oct 1 Oct 9 Apr Oct 1 Oct 9 Apr 9 Figure Ride Quality (RQI) & Surface Distresses (PSR) vs. Cell & 42

48 Rutting (ALPS) Rutting can be defined as a longitudinal surface depression in the wheel path (12). Rutting is an important indicator of performance, as excessive rutting can lead to issues with shedding water and could cause potential vehicle hydroplaning. Mixture rutting is influenced by insufficient compaction (i.e. high air voids), excessively high asphalt content, excessive mineral filler, or insufficient amount of angular particles (14). The Automated Laser Profile System (ALPS), Figure 2.36, was used to characterize the rutting of all study cells. The ALPS collected rutting measurements in both wheel paths of both lanes, every ¼ at 5-foot intervals. For the mainline cells, 29 measurements were made on January, April, July and September and 21 measurements were made on May, July and September. Cell 24 (located on the LVR) was measured five times, during August and September of 29 and during May, July and September of 21. Figure Automated Laser Profile System (ALPS) This data was first examined using a simple box and whisker plot to get an understanding of the distribution of the data. Figure 2.37 clearly shows that the data has a fairly tight distribution, which can be judged by the height of the box and length of the whiskers; the extreme values observed can most likely be described as outliers, and are skewing the data set. Every cell, with the exception of cells 86 and 87 appear to have at least a few of these suspected outliers; however the most extreme values (>3.5 ) occur in cells 3, 19 and 88. Figure Box and Whisker Plot: ALPS Rutting, inches vs. Cell 43

49 The suspected outliers were removed from the data set using the 1.5IQR Rule (15), as shown by equation 2.1. The first criterion produced negative values, so the second criterion (maximum) was used to screen for outliers as the data set did not contain any negative values. Outlier Outlier Where: cell cell < Q 1.5 IQR, or 1 > Q IQR Q 1 is the 25 th percentile measurement for a particular cell Q 3 is the 75 th percentile measurement for a particular cell IQR is the Interquartile Range (Q 3 Q 1 ) for a particular cell equation 2.1 Figure 2.38 shows the distribution of the data after the 58 outliers (~2% of data set) were removed. The scale of the revised plot ranges from to.8, the original plot had a maximum value of 6.. The top of the box represents the 75th percentile, the middle of the box represents the median value of the data set and the bottom of the box represents the 25th percentile. Only rutting values greater than.5 impact the pavement s distress rating, according to Mn/DOT pavement management practice. Table 2.1 shows the descriptive statistics for all study cells. Note that all of the data for all cells, except for the porous asphalt, had rutting values below the.5 inch reporting threshold value. 75% of the rutting data for all of the cells, except for the porous asphalt cells 86 and 88, are below.23 inches. Note that pavements are usually constructed with a small amount of rutting, and the measured values do not subtract out the initial ruts. Figure Box and Whisker Plot: ALPS Rutting, inches vs. Cell (Outliers Removed) 44

50 Table 2.1. Descriptive Statistics for Rutting Results (Outliers Removed) Stat/Cell N Outliers Mean SD Minimum st Quart rd Quart Maximum Figure 2.39 to Figure 2.49 present 3-D graphical summaries of the rutting measurements (vertical axis) with longitudinal station (horizontal axis), and measurement time (z-axis, or into the page ). The figures are labeled as cell: lane-path. Mainline lanes are denoted as either DL for driving lane or PL for passing lane; on the low volume road, lanes are denoted as either IL for inside lane or OL for outside lane. Mainline and low volume road wheel paths are labeled as either inside wheel path, or outside wheel path. Measurements taken in the two lanes and two wheel paths produce a total of four plots for each study cell. Measurements were made on the mainline (ML) cells a total of seven times between construction and fall 21 and five times for the low volume road (LVR) cells. 45

51 Cell 2: DL Inside Wheel Path Sep 9 Jan 9 Sep Sep 9 Jan 9 Sep Cell 2: PL Inside Wheel Path Jan 9 Sep 1 Sep 9 Cell 2: DL Outside Wheel Path Sep 9 Jan 9 Sep Figure ALPS Rutting vs. & : UTBWC (2) Cell 2: PL Outside Wheel Path

52 Cell 3: DL Inside Wheel Path Sep 9 Jan 9 Sep Sep 9 Jan 9 Sep Cell 3: PL Inside Wheel Path Jan 9 Sep 1 Sep 9 Cell 3: DL Outside Wheel Path Sep 9 Jan 9 Sep Figure 2.4. ALPS Rutting vs. & : UTBWC (3) Cell 3: PL Outside Wheel Path

53 Cell 4: DL Inside Wheel Path Sep 9 Jan 9 Sep Sep 9 Jan 9 Sep Cell 4: PL Inside Wheel Path Jan 9 Sep 1 Sep 9 Cell 4: DL Outside Wheel Path Sep 9 Jan 9 Sep Figure ALPS Rutting vs. & : 12.5 SP (4) Cell 4: PL Outside Wheel Path

54 Cell 6: DL Inside Wheel Path Sep 9 Jan 9 Sep Sep 9 Jan 9 Sep Cell 6: PL Inside Wheel Path Jan 9 Sep 1 Sep 9 Cell 6: DL Outside Wheel Path Sep 9 Jan 9 Sep Figure ALPS Rutting vs. & : 4.75 Tac (6) Cell 6: PL Outside Wheel Path

55 Cell 19: DL Inside Wheel Path Sep 9 Jan 9 Sep Sep 9 Jan 9 Sep Cell 19: PL Inside Wheel Path Jan 9 Sep 1 Sep 9 Cell 19: DL Outside Wheel Path Sep 9 Jan 9 Sep Figure ALPS Rutting vs. & : WMA (19) Cell 19: PL Outside Wheel Path

56 Cell 22: DL Inside Wheel Path Sep 9 Jan 9 Sep Sep 9 Jan 9 Sep Cell 22: PL Inside Wheel Path Jan 9 Sep 1 Sep 9 Cell 22: DL Outside Wheel Path Sep 9 Jan 9 Sep Figure ALPS Rutting vs. & : FRAP (22) Cell 22: PL Outside Wheel Path

57 Cell 24: DL Inside Wheel Path Jul 1 Aug Jul 1 Aug Cell 24: PL Inside Wheel Path Jul 1 Aug Cell 24: DL Outside Wheel Path Jul 1 Aug Figure ALPS Rutting vs. & : WMA CTRL (24) Cell 24: PL Outside Wheel Path

58 Cell 27: DL Inside Wheel Path Cell 27: PL Inside Wheel Path Cell 27: DL Outside Wheel Path Figure ALPS Rutting vs. & : CS (27) Cell 27: PL Outside Wheel Path

59 Cell 86: DL Inside Wheel Path Cell 86: DL Outside Wheel Path Jul Jul Aug Aug Cell 86: PL Inside Wheel Path Cell 86: PL Outside Wheel Path Aug 9 Jul Aug Jul Figure ALPS Rutting vs. & : Porous (86) 54

60 Cell 87: DL Inside Wheel Path Cell 87: DL Outside Wheel Path Sep 1 Jul 1 May 1 Sep 9 Aug Sep Jul 1 May Sep 9 Aug Cell 87: PL Inside Wheel Path Cell 87: PL Outside Wheel Path Sep 1 Jul 1 May 1 Sep 9 Aug Aug Jul Figure ALPS Rutting vs. & : Porous CTRL (87) 55

61 Cell 88: DL Inside Wheel Path Cell 88: DL Outside Wheel Path Sep 1 Jul 1 May 1 Sep 9 Aug Sep Jul 1 May Sep 9 Aug Cell 88: PL Inside Wheel Path Cell 88: PL Outside Wheel Path Sep 1 Jul 1 May 1 Sep 9 Aug Aug Sep 1 Jul 1 May 1 Sep Figure ALPS Rutting vs. & : Porous (88) 56