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60 third highest EI at 68.04; the second largest effectiveness Oxidation--viscosity and penetration of asphalt from (87.43) is with an application age of 4 years. The results of this recovered cores (available for a very limited number of analysis session, shown in Figure 33, illustrate EI, extension of sections) life, and EUAC versus treatment application age relationships. For rigid pavements, 43 SPS-4 sections were found to have data for crack and joint sealing treatments. However, Case Study 5--LTPP Data these maintenance activities were combined in these sec- This example involves the use of data from the LTPP tions, making it difficult to isolate the separate effect of each SPS-3 and SPS-4 experiments. In these experiments, main- treatment. For these sections, the following types of condi- tenance treatments were applied to both HMA and PCC tion indicator data are available: pavements and performance of these pavements and nearby control sections was monitored over time. Using the LTPP Cracking DataPave 3.0 software program, LTPP data were examined Joint spalling to identify maintenance effectiveness test sections meeting Faulting the following requirements: IRI Friction Have "adequate" time series data--in order to establish accurate condition indicator trends over time, only sec- An initial review of the collected data was conducted to tions with three or more time series data points were determine their usefulness in evaluating the optimal timing included. methodology. Specifically, it was considered essential to Be applied on pavements in "Good" condition--since have data available on the performance of the pavement after preventive maintenance treatments are applied to pave- application of a specific preventive maintenance treatment to ment in "Good" condition, only sections with treatment compare with the performance of a control section that did applied to a pavement in "good" condition were not receive the treatment (i.e., the do-nothing trends). This included. review concluded that the LTPP data could not be used to con- Have condition data before first preventive mainte- duct a meaningful analysis for several reasons. The perfor- nance treatment application--in order to determine the mance trends for a large number of sections revealed counter- initial impact of a preventive maintenance treatment on intuitive trends (e.g., untreated control sections performing condition, sections that had condition information in better than adjacent sections that received a preventive main- the year immediately prior to the preventive mainte- tenance treatment [see Figure 34]). Because these sections nance treatment applications were included. did not show an improvement in performance as a result of Use of control section--in order to assess the impact of treatment application, they were not studied further. Also, preventive maintenance on pavement performance its sections that were not in good condition when treatment was expected service life, all sections suitable for this eval- applied were excluded because they do not meet the defini- uation must have data associated with a "control" sec- tion of preventive maintenance. With this, there were not tion to define the do-nothing performance trend. enough remaining sections with treatments applied at differ- ent ages that exhibited the expected trends to support a mean- For flexible pavements, the initial search of the database ingful analysis. identified the following SPS-3 sections as meeting these criteria: SUMMARY 80 sections with chip seal coats A product of this research was the development of a 80 sections with slurry seal coats methodology that can be used to determine the optimal time to 69 sections with crack sealing apply preventive maintenance treatments. The methodology is 79 sections with (thin) overlays based on an understanding of how pavements perform over time and how preventive maintenance affects its performance. The following types of condition indicator data are available By analyzing appropriate performance data from pavements for each of these sections: treated at a variety of times, it is possible to identify the "right" time to apply preventive maintenance. That "right" time, iden- Nonload-related and load-related cracking tified through the optimal timing methodology, is defined as Average rut depth the time when the treatment's application provides the great- IRI est ratio of improvement in condition (benefit) to cost (i.e., that Friction time with the largest associated B/C ratio).

OCR for page 60
61 1.6 1.4 1.2 1 IRI (m/km) 0.8 0.6 0.4 48 1310 (w/Thin Overlay) 48 1340 (Control) 0.2 0 12/23/1988 5/7/1990 9/19/1991 1/31/1993 6/15/1994 10/28/1995 3/11/1997 7/24/1998 12/6/1999 Survey Date Figure 34. Example of LTPP data exhibiting a counterintuitive trend for a thin overlay application. To assist in the implementation of the methodology, strate the use of the OPTime tool. These data were analyzed OPTime, a Microsoft Excel-based analysis tool capable of using OPTime although the results of the analyses did not analyzing actual preventive maintenance-related performance always match expectations. Data from the LTPP experi- data, was developed. The analysis tool greatly facilitates the ments were not analyzed because the data did not support application of the methodology through a logical, step-by- the premise that the maintenance treatments improved per- step, input sequence. Further explanation of the optimal tim- formance compared with the do-nothing case. A holistic ing approach and a detailed user's guide is provided in Appen- approach to identifying the optimal time of preventive main- dix C, which is available to users by accessing the NCHRP tenance application is needed. Such an approach should website ( address project selection, treatment selection, pavement per- Data were collected from four SHAs and from the LTPP formance monitoring, and data analysis and reporting. These SPS-3 and SPS-4 experiments for possible use in an analy- observations are further described in Chapter 4 as part of sis to validate the optimal timing approach and to demon- Suggested Research.