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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>Investigating long-term performance of flexible pavement using Bayesian multilevel models</title>
      <link>https://trid.trb.org/View/2204446</link>
      <description><![CDATA[Many factors affect the performance of rehabilitative treatments for asphalt concrete pavements. However, which factors have been causing the deterioration of their long-term performance is still unclear. The authors considered the nested and panelled structure of pavement performance data and the unobserved heterogeneity among sites using multilevel Bayesian regression models. The authors incorporated alligator cracking, rutting and roughness represented by the international roughness index (IRI) as performance indicators. To verify the existence of unobserved heterogeneity, the authors adopted an iterative modelling path by adding the per-state or per-climatic region random parameters into the models. The authors then based their inference of the significant factors on the chosen models that are predictive and causally sound. The results show that there existed considerable heterogeneity among different sites and climatic regions. Including per-state or per-region intercepts improved the models’ predictive capacity and accounted for the unobserved heterogeneity.]]></description>
      <pubDate>Mon, 23 Oct 2023 16:52:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2204446</guid>
    </item>
    <item>
      <title>Improving asphalt mix design by predicting alligator cracking and longitudinal cracking based on machine learning and dimensionality reduction techniques</title>
      <link>https://trid.trb.org/View/2028680</link>
      <description><![CDATA[The asphalt mix design based on traditional laboratory fatigue cracking tests of asphalt mixture is not reasonable due to the difficulty of simulating the circumstance where asphalt mixture experiences in the pavement structure and under realistic climate and traffic conditions. The study aims to mitigate the cracking problems during the pavement design life, by improving the asphalt mix design process by introducing machine learning (ML) models, which are used to predict alligator cracking (AC) and longitudinal cracking (LC), and their criteria (required ranges). The data containing AC and LC were extracted from the NCHRP 1-37A report and the long-term pavement performance (LTPP) program. A total of 33 input features about climate condition, traffic, pavement structure, and materials properties of each pavement layer were selected. Support Vector Regression (SVR), Artificial Neural Networks (ANN), Kernel ridge regression (KRR), Gradient boosting (GB), Extra-trees, and eXtreme Gradient Boosting (XGBoost) were used. Meanwhile, three dimensionality reduction approaches, including Auto-Encoder (AE), Principal Component Analysis (PCA), and Recursive feature elimination with Random Forest, were combined with the six ML algorithms (18 hybrid models produced) in order to decrease the computation complexity and search for the optimum model. The 24 models (6 basic ML models plus 18 hybrid models) were trained, and their hyperparameters were tuned using Bayesian optimization. Different evaluation criteria R2, RMSE, MAE, SMAPE, and SI are calculated to evaluate the performance of these models. The results of the study showed that except for ANN and SVR, the basic ML models can get better for predicting AC and LC when they are combined with PCA or AE. Based on the performance indices, the optimum among these developed models proved to be PCA-ANN for predicting AC (R2 = 0.84) and LC (R2 = 0.83). Compared to other pavement layers, the asphalt surface course is the highest contributor to AC and LC. The improved mix design process was implemented to determine the mix proportion for the asphalt surface course of a construction project and Mix-2 with 5.1 % asphalt content was recommended.]]></description>
      <pubDate>Tue, 22 Nov 2022 10:16:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2028680</guid>
    </item>
    <item>
      <title>Investigation of premature failure mechanism in pavement overlay of national highway of Bangladesh</title>
      <link>https://trid.trb.org/View/1900669</link>
      <description><![CDATA[Roadway is the economic lifeline of Bangladesh. Maintenance of this roadway is main challenge of Roads and Highways Department (RHD). Overlay is the most common maintenance practice for National Highways, which design life is five years. However, it’s been reported, the overlay failed prematurely with cracking and rutting within one year even 6 to 9 months in some cases. This study aiming to investigate the premature failure mechanism of national highway pavement. Several field investigations were done on national highway namely N2. A numerical parametric study was also conducted with variable interfacial bond condition, overloading and layers stiffness. To investigate the pavements failures, conventional fatigue and rutting criteria were considered. Laser crack measurement system showed that alligator cracking is dominant failure mode followed by rutting. Alligator crack pattern indicated about slippage failure and overloading induced fatigue failure. Core cutting confirmed that interface de-bonding and cracking are strongly related. Bitumen samples were found highly temperature susceptible which could be correlated slippage failure. Moreover, Base layer stiffness variation was observed from Dynamic Cone Penetration test. Numerical analysis revealed that poor interfacial bonding significantly affects horizontal and vertical strain distributions; subsequently reduce pavement life but only it is not enough to fatigue and rutting failure of N2 within one year. Overloading found more significant than de-bonding especially for rutting. Analysis also suggested that fatigue and rutting failure within one year should be associated by coupling effect of poor bonding and overloading. Variation of base layer stiffness might be exacerbated the coupling effect in N2.]]></description>
      <pubDate>Wed, 26 Jan 2022 14:26:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/1900669</guid>
    </item>
    <item>
      <title>Local Calibration of Mechanistic-Empirical Pavement Design Guide in Tennessee</title>
      <link>https://trid.trb.org/View/1858119</link>
      <description><![CDATA[The Tennessee Department of Transportation (TDOT) has invested effort and resources to transition from the AASHTO 1993 pavement design guide to the up-to-date AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG). To accomplish this goal, several phases of research activities were conducted. In the first phase, a database for soil resilient modulus was established using representative soil samples in Tennessee. In the second phase, a database of concrete coefficients of thermal expansion (CTE) was generated. In another research project, a database was developed for the dynamic modulus of asphalt mixtures. In the current phase, the most important transfer functions in the MEPDG were locally calibrated according to the unique conditions of Tennessee. These models include the alligator cracking (bottom-up cracks), longitudinal cracking or load related wheel-path fatigue cracking, rutting, and smoothness, as indicated by the International Roughness Index (IRI), models.]]></description>
      <pubDate>Mon, 12 Jul 2021 18:57:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1858119</guid>
    </item>
    <item>
      <title>Developing an approach for measuring the intensity of cracking based on geospatial analysis using GIS and automated data collection system</title>
      <link>https://trid.trb.org/View/1844023</link>
      <description><![CDATA[Determination and measurement of the characteristics of surface distresses such as cracking are the important tasks of pavement maintenance authorities. The measurement of main characteristics including the extent, severity, and intensity of cracking, results in a better assessment of pavement condition. The cracking intensity (crack spacing) can be expressed and developed based on the spatial distribution of cracks. Due to the difficulty of measuring the cracking intensity, the importance of this main attribute has been rarely considered. In addition, a practical method has not been provided for measuring and determining the distribution of cracking in the selected pavement section. In this paper, using the locations of pavement surface cracks and geographic information system (GIS), a practical method is proposed for representing and determining the intensity of cracking through identifying the spatial distribution of pavement cracks at the project level. To evaluate the proposed method, longitudinal, transverse, and alligator cracks were investigated in several pavement sections. The cracking assessment was performed by the use of an automated data collection system and the location-based image processing technique in GIS. The results of the study show that through the usage of the proposed method, the intensity of cracking can be determined and considered practically as the main attribute of cracking.]]></description>
      <pubDate>Tue, 27 Apr 2021 11:36:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1844023</guid>
    </item>
    <item>
      <title>Calibration of the M-E Design Guide</title>
      <link>https://trid.trb.org/View/1687983</link>
      <description><![CDATA[Because of potential differences between ‘national’ and ‘local’ conditions, the Mechanistic-Empirical Pavement Design Guide (MEPDG) should be calibrated to a local level. Arkansas has invested heavily in efforts to implement the MEPDG. This report details the initial local calibration of flexible pavement models in the MEPDG for Arkansas. Data from the Long-Term Pavement Performance (LTPP) database and local pavement management system (PMS) were used. The Solver function within Microsoft Excel was used to optimize the coefficients in the alligator cracking. Iterative runs of the MEPDG using discrete calibration coefficients were conducted to optimize rutting models. In general, the alligator cracking and rutting models are improved by calibration. However a question remains regarding the suitability of the calibrated models for routine design. Many default values were used in the MEPDG due to lack of data. It is recommended that additional sites be established and a more robust data collection procedure be implemented for future calibration efforts. The difference in defining transverse cracking between the MEPDG and LTPP may be critical in terms of data collection and identification. Thermal cracking should be specifically identified in a transverse cracking survey to calibrate the transverse cracking model in the MEPDG. The procedure for local calibration of the MEPDG using LTPP and PMS data in Arkansas is established. Additional development of database software for data manipulation, pre-processing, and quality control – currently underway in Arkansas – will significantly streamline the calibration process.]]></description>
      <pubDate>Mon, 23 Mar 2020 16:10:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/1687983</guid>
    </item>
    <item>
      <title>Distress and profile data analysis for condition assessment in pavement management systems</title>
      <link>https://trid.trb.org/View/1657986</link>
      <description><![CDATA[Pavement data collection is the most expensive and time consuming component of Pavement Management System (PMS). Thus, possible methods of minimizing the need of such data might be critical in reducing pavement condition monitoring costs. Also the ability to relate pavement performance prediction models (frequently roughness based) to hot mix asphalt field performance models (distress based) provides valuable conclusions and input in pavement design, performance assessment, maintenance and rehabilitation strategies. Objective of this study was to examine whether specific distresses can influence roadway profile so as to be able to relate the two. The influence of pavement distresses on road profile has been investigated over the years. However, past studies provided conflicting conclusions. Thus, in this study an alternative approach was considered due to the availability of high quality and detailed distress data collected with the Laser Crack Measurement System (LCMS) of the Automatic Road Analyzer, ARAN. As it was expected, specific distresses have higher impact in longitudinal roughness since they are present on the roadway surface at regular intervals (i.e., specific frequencies). For this reason, instead of using summary indexes (i.e., International Roughness Index (IRI), Pavement Condition Index (PCI)), the Power Spectral Density (PSD) of the roadway profile at specific frequency bandwidths was considered along with distresses. The analysis indicated that a specific subset of distresses is affecting roughness at definite wavelength frequencies. Alligator cracking and rutting standard deviation provided the best correlation. IRI was correlated better with distress (e.g. rutting standard deviation) at lower profile frequencies. At high frequency domain (i.e., below 0.8 m wavelengths) better correlation between IRI and high severity cracking was observed through the PSD. Considering multiple frequencies in the regression models between roughness and distresses, the goodness of fit has not necessarily improved. However, the role of different bandwidths was evident. In addition to the specific results, the methodology presented in this study can be used elsewhere to assess potential relations between pavement roughness and distress components.]]></description>
      <pubDate>Tue, 29 Oct 2019 11:29:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1657986</guid>
    </item>
    <item>
      <title>Impact of Heavy Logging Trucks on Flexible Pavement Performance during Spring Thaw</title>
      <link>https://trid.trb.org/View/1638884</link>
      <description><![CDATA[This purpose of this paper is to investigate the impact on flexible pavement performance with truck weights up to 98,000 lbs on six axles that transport loads of raw forest products during spring thaw. Prior to passage of a 2011 state law, Wisconsin Department of Transportation (WisDOT) could suspend overweight permits for the transportation of raw forest products during the spring-thaw suspension period or impose special weight limits on highways. During one spring thaw cycle that allowed the heavier trucks, measurements were taken for load-related pavement distresses including wheel path longitudinal cracking, rutting, and alligator cracking in adjoining lanes of eleven 2-lane, 2-way highway segments known to carry trucks loaded with logs in one direction and no logs on the return trip. The eleven segments were grouped into two paved surface categories: Marshall mix design (4 segments) and Superpave mix design (7 segments). A segment by segment analysis revealed that one Marshall mix segment (age 13 years) exhibited significantly higher rates of progression in alligator and longitudinal cracking in the loaded lane when compared to the adjoining empty truck lane. In general, higher levels of alligator cracking and rutting were associated with the Marshall mix segments compared to the Superpave segments. Levels of longitudinal cracking were, however, not significantly different between the two surface categories.]]></description>
      <pubDate>Tue, 24 Sep 2019 14:52:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1638884</guid>
    </item>
    <item>
      <title>Evaluation of WisDOT Quality Management Program (QMP) Activities and Impacts on Pavement Performance</title>
      <link>https://trid.trb.org/View/1637718</link>
      <description><![CDATA[This project aims to evaluate the effectiveness of the quality measures employed by the Wisconsin Department of Transportation to influence the in-service performance of flexible pavements. The study involved creating a relational geo-referenced database connecting production, placement, and routine in-service performance data collected over the years for Wisconsin Projects. The database relied on geo-referencing all the data such that each individual data point is assigned a location. This approach allows for tracking the quality of the material and construction of specific segments of the roadway to the in-service performance. A subset of the projects was also included in an in-depth study using on-site distress survey and non-destructive testing using Falling Weight Deflectometer (FWD). In general, the thirty highway projects studied in this project show that transverse and longitudinal cracking are the most common distresses. Construction joint longitudinal cracking appears to be highly common in all the on-site visits. Rutting is localized but not common. Alligator cracking takes place in multiple locations. This distress appears to relate to either soft foundation or some of the quality measures. Deviations from the quality indicators’ targets show correlations with the distresses. Mix production air voids (Va), mix voids in mineral aggregate (VMA), and placement density (%Gmm) are correlated with in-service performance. Deviation from target Va by reduction of 0.25% or more, correlates with a reduction in performance. Accomplishing VMA higher than the target is associated with lower levels of distresses. For %Gmm, about 2% increase in the compacted density shows improved performance for thicker than 2” lifts. Thin lifts are more sensitive to increase in compaction effort than thicker pavements.]]></description>
      <pubDate>Mon, 22 Jul 2019 15:30:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/1637718</guid>
    </item>
    <item>
      <title>Revised Condition Rating Survey Models to Reflect All Distresses: Volume 1</title>
      <link>https://trid.trb.org/View/1508223</link>
      <description><![CDATA[Pavement condition assessment plays a key role in infrastructure programming and planning processes. Similar to other state agencies, the Illinois Department of Transportation (IDOT) has been using a system to evaluate the condition of pavements since 1974. Since 1994–1995, IDOT has been using a system to project future pavement performance as well. The condition rating survey (CRS) value is the index between 1 (failed) and 9 (new), representing the overall condition of pavement. The purpose of this study was to update and revise the existing CRS calculation and prediction models using new data. To accomplish the goals of the study, the CRS data was received for the years 2000–2014. The data was initially processed and cleaned in preparation for modeling. CRS prediction models were prepared for Interstate and Non-Interstate pavement types. The two-slope model was used for all asphalt-surfaced pavements, whereas a new model was proposed for concrete-surfaced pavements. The proposed model for concrete-surfaced pavements is a nonlinear survival type designed to capture the distinct deterioration patterns of concrete pavements with little to no reduction in CRS—followed by a rapid and linear deterioration and a flatter region at the end, once the pavement is saturated with damage. The CRS calculation models were updated to incorporate new distresses. Based on the literature review and the analysis of distress composition, it was found that IDOT’s distress ratings are generally in agreement with the ASTM standard—with the exception of alligator cracking. A database containing recorded distresses, used by experts, was referenced to add missing distresses, such as alligator cracking, for each Interstate model.]]></description>
      <pubDate>Tue, 29 May 2018 16:03:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/1508223</guid>
    </item>
    <item>
      <title>Evaluation of Impacts of Allowing Heavier Log Loads in Northern Wisconsin During Spring Thaw</title>
      <link>https://trid.trb.org/View/1512267</link>
      <description><![CDATA[This study investigated the impact of a January 1, 2011 Wisconsin statutory change (RS permit law) that allows vehicle combinations up to 98,000 pounds on six axles to transport loads of raw forest products during the spring-thaw suspension period. Prior to the statutory change, Wisconsin Department of Transportation (WisDOT) could suspend overweight permits for the transportation of raw forest products during the spring thaw, or impose special weight limits on highways. The specific goals of the investigation were to: (1) determine if there is an impact with this statutory change; (2) identify whether certain vehicle classes or categories are more damaging than others, and the possibility of lessening the impact of these heavy loads; and (3) determine if certain pavements are impacted with increased loads due to the policy change. A total of eleven pavement segments were analyzed in the study and fell into two paved surface categories: older Marshall mix design (4 segments) and newer Superpave mix design (7 segments). The analyses showed that the Superpave mix design segments generally produced better performance than the Marshall mix design segments. Higher levels of alligator cracking and rutting were associated with the Marshall mix segments compared to the Superpave segments. Levels of longitudinal cracking were, however, not significantly different between the two mix types. A segment by segment analysis revealed that one Marshall mix segment (age 13 years) exhibited significantly higher rates of progression in alligator and longitudinal cracking in the loaded lane when compared to the adjoining empty lane. Hence, the rehabilitation or replacement of older Marshall segments within the logging route network is needed to allow up to 98,000 pounds of raw forest products to be transported on six-axle vehicles, while inflicting lesser damage to the pavement network. In addition, this study was initiated just one year after the implementation of the RS Permit law and focused on only a few segments. A longer time frame and many more segments may be needed to help evaluate the overall long-term impacts from log loaded trucks, or a field test consisting of a special test section could be constructed and subject to the RS permit law trucks to capture their overall impact during the spring-thaw season. Federal Highway Administration (FHWA) vehicle classes 9 and 10 were the main carriers of logs throughout the studied network. The relative-log carrying efficiency (with reference to the pavement damage caused) of class 10 trucks averaged approximately 22,000 lb/ESAL (equivalent single axle load) compared to 15,400 lb/ESAL for class 9 trucks. A considerable proportion of trucks was found overloaded at two platform scales, averaging 31% and 24% in the winter, and 25% and 33% during the spring. The magnitude of the truck overload, however, averaged less than 5% of the 98,000-lb limit permitted under the law for gross vehicle weight.]]></description>
      <pubDate>Mon, 28 May 2018 09:48:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/1512267</guid>
    </item>
    <item>
      <title>Use of Crack Characteristics in Crack Sealing Performance Modeling and Network-Level Project Selection</title>
      <link>https://trid.trb.org/View/1440411</link>
      <description><![CDATA[Crack sealing (CS) and crack filling (CF) are commonly used crack treatment methods. However, the study of their performance is still very limited, making it difficult for highway agencies to systematically and optimally select network-level CS-CF projects within available budgets. To address this issue, a generalized performance model for CS-CF–treated pavements is proposed. Detailed crack characteristics—including crack type, density, and width—are employed in the model. In the proposed performance model, crack density related to three types of cracks (transverse cracks, nonwheelpath longitudinal cracks, and wheelpath longitudinal cracks) is used to determine performance gain. Two discount functions are incorporated to consider the negative impact caused by alligator cracks and cracks that are very tight or very wide. The proposed model is instantiated and estimated using the practices of the Georgia Department of Transportation on CS and CF and the department’s pavement distress survey protocol. The case study—which uses three-dimensional laser data collected from a 1-mi pavement section on State Route 26 (US-80) near Savannah, Georgia, from 2011 to 2016—validates the feasibility and reasonableness of the model. An integer programming method is formulated for network-level CS-CF project selection. The testing results of 53 pavement segments show that the model and programming method can be used to select CS-CF projects within budget constraints while maximizing the length-weighted average performance gain. The proposed performance model and integer programming method show promise for use in incorporating CS and CF into a highway agency’s pavement management system. Conclusions and recommendations are offered.]]></description>
      <pubDate>Thu, 29 Dec 2016 15:53:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/1440411</guid>
    </item>
    <item>
      <title>Sensitivity Analysis of Flexible Pavement Sections Using Mechanistic-Empirical Pavement Design Guide</title>
      <link>https://trid.trb.org/View/1391916</link>
      <description><![CDATA[In damage analysis of flexible pavement sections, the AASHTO 2002 design guide, also known as the MEPDG (Mechanistic-Empirical Pavement Design Guide), adopted a mechanistic-empirical approach. In the MEPDG, the pavement performance is computed using different input parameters that characterize pavement materials, design features and condition. However, these input parameter values are expected to differ to varying degrees and, therefore, the predicted performance may also vary to some degree depending on the input parameter values. The current study evaluated the influence of four input parameters, namely, reliability level, climate, traffic characteristics and modulus values on the performance of selected pavement sections using MEPDG software. Knowledge gained from the sensitivity analysis of different pavement sections using MEPDG is expected to be useful to pavement designers and others using MEPDG for future pavement design. Specifically, this paper focuses on the sensitivity study of flexible pavement sections at four different locations namely, Chicago in Illinois, Grand Forks in North Dakota, Oklahoma City in Oklahoma, and Houston in Texas, for addressing sensitivity towards climatic conditions. For addressing effect of reliability and traffic three levels of reliability (80%, 90%, 95%) and traffic (low, medium, high) were used, respectively, for designing flexible pavement sections. Additionally, sensitivity towards modulus of subgrade soil was evaluated by designing pavement sections containing 6% lime, 15% class C fly ash (CFA), and 15% cement kiln dust (CKD). The performance of each pavement section was monitored for 240 months (20 years) using MEPDG software by generating plots for rutting, alligator cracking, and International Roughness Index (IRI). It was found that rut predicted by MEPDG is sensitive towards climate, modulus values of chemically stabilized layer and reliability level. IRI values showed sensitiveness toward only reliability and traffic level. Alligator cracking showed sensitiveness toward climate with unexpected trend, modulus of chemically stabilized layer, reliability and traffic level.]]></description>
      <pubDate>Mon, 18 Jan 2016 16:36:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/1391916</guid>
    </item>
    <item>
      <title>Developing Temperature-Induced Fatigue Model of Asphalt Concrete for Better Prediction of Alligator Cracking</title>
      <link>https://trid.trb.org/View/1376195</link>
      <description><![CDATA[Currently, the fatigue performance of asphalt concrete (AC) is predicted according to repeated traffic-induced tensile strain at the bottom of AC layer. Cyclic thermal strain caused by day-night temperature fluctuation is not considered because of the fact that there is no closed-form solution or model available for calculating thermal fatigue damage. This study, for the first time, develops a closed-form equation for calculating the temperature-induced fatigue damage of AC. To generate data, beam fatigue testing was conducted on three Superpave mixtures in the laboratory. The mechanical beam fatigue test data were correlated with the actual cyclic temperature loading test data. The developed model was then calibrated for field condition. Finally, the model was used to evaluate fatigue damages of randomly chosen 34 long-term pavement performance (LTPP) test sections from 19 states in the United States. Fatigue damage determined by the traditional pavement design software (which considers traffic-induced fatigue damage only) is compared with that by the combined traffic- and temperature-induced fatigue. The results show that the error may decrease by 14% through the incorporation of temperature-induced fatigue damage in the current design approach. Therefore, it is suggested to include the temperature-induced fatigue damage in the pavement design software.]]></description>
      <pubDate>Wed, 23 Dec 2015 08:09:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1376195</guid>
    </item>
    <item>
      <title>Pavement Research at the Washington State University Test Track. Volume 4, Experimental Ring No. 4: A Study of Untreated, Sand Asphalt, and Asphalt Concrete Bases</title>
      <link>https://trid.trb.org/View/1372774</link>
      <description><![CDATA[Three different kinds of base material of varying base thicknesses were tested at the Washington State University Test Track on Ring #4 during the fall of 1968 and the spring of 1969. Twelve 18-ft test sections consisting of 4.5, 7.0, 9.5, and 12 in. of untreated crushed rock surfacing top course base; 2.0, 4.0, 6.0 and 8.0 in. of sand-asphalt base; and 0.0, 2.0, 3.5 and 5.0 in. of Class "F" asphalt concrete base, covered by a uniform 3.0-in. thick Class "B" asphalt concrete wearing course were tested during this period. The pavement structure was built on a clay-silt subgrade soil. Instrumentation consisted of moisture tensiometers, strain gages, pressure cells, Linear Variable Differential Transformer (LVDT) gages and thermocouples for measuring moisture, strain, stress, dynamic deflections and temperatures. Benkelman beam readings were taken. The testing revealed that the fall failure modes were different from the spring failures. The fall failure pattern started from transverse cracks in the thin sections which developed into alligator cracking patterns. These cracks appeared after a period of cold weather and heavy rains followed by a warming trend. Thermal and mechanical loads in conjunction with adverse environmental conditions during construction and prior to and during the fall testing period were believed to be responsible for the early fall failures on the thin sections. The spring failures were very rapid and sudden and were due to environmental factors which led to highly saturated subgrade, thus resulting in poor bearing capacity. Punching shear was the failure mode. The thickest sections survived without cracks but developed severe rutting. Comparison of the results with those obtained from Rings #3 and #4 show that they were similar in many respects. This indicates that the test track is capable of replicating results and is a reliable research instrument. Equivalencies were developed for the different materials. On this basis the Class "F" asphalt concrete base was superior to the sand-asphalt and untreated crushed rock bases i that order. Maximum values for static and dynamic deflections, strains and stresses for different times and temperatures were developed. The lateral position of the dual tires with respect to the gage severely affected the strain, stress and deflection values. Temperature also caused variations in the measurements. Spring instrument readings for static and dynamic deflections, strain ad stress show values as much as 2 to 4 times those obtained in the fall. Spring subgrade conditions probably were responsible for these differences. Ring #4 series operational time was half that of Ring #3 and about the same as Ring #2. Ring #4 sustained about a quarter of the wheel load applications of Ring #3. Construction and testing environmental conditions were inferior to those for Ring #3, although they were similar for Ring #2 and hence contributed to the lower test period. This points out that environmental factors are very important in pavement life.]]></description>
      <pubDate>Mon, 02 Nov 2015 15:17:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/1372774</guid>
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