Kevin D Hall

Molecular Dynamics to Understand the Mechanical Behavior of Cement Paste

The tensile strength of cement paste is one of the most important mechanical properties that influence shrinkage cracks in cementitious materials. Cement pastes that exhibit low tensile strength tend to exhibit greater shrinkage crack potential and reduced durability. Increasing the tensile strength in cement paste can minimize the shrinkage cracking potential. It is believed that the strength and cohesion of cement paste are controlled by the formation of calcium silicate hydrate (C-S-H) gel. To enhance macroscopic mechanical properties (tensile strength), it is necessary to understand the structure and behavior of C-S-H gel at the atomic level. Previously, molecular statics was used to determine minimal potential energy and the mechanical properties of crystalline C-S-H structures. From this study, a plausible atomic structure of C-S-H gel is proposed. This research effort builds on the aforementioned work by using molecular dynamics to derive tensile and compressive strengths of C-S-H structures from uniaxial stress–strain data. The results from the molecular dynamics simulations showed that the maximum strengths (i.e., compressive and tensile) for the proposed C-S-H structures are three orders of magnitude higher than the strength at the macrolevel. However, the tensile strength of the proposed C-S-H gel is 23% of the compressive strength. This research also concludes that electrostatic forces and bond forces in the silicate chains are the main contributors to cement strength at the atomic level and that breakage in silicate chains leads to low tensile strength in C-S-H gel.

Development and Influence of Statewide Axle Load Spectra on Flexible Pavement Performance

The Mechanistic–Empirical Pavement Design Guide (MEPDG) developed under NCHRP Project 1-37A requires new inputs for traffic characterization. One important traffic input is axle load distribution factors, or axle load spectra. These spectra represent the percentage of the total axle applications within each load interval for single, tandem, tridem, and quad axles. The Arkansas State Highway and Transportation Department sponsored research to develop statewide axle load spectra and evaluate the significance of the developed inputs in the MEPDG. Of 25 weigh-in-motion sites selected for this study, only 10 stations provided good weight data for development of statewide axle load spectra. On the basis of the available weight data, statewide axle load spectra for single, tandem, and tridem axles were developed. However, the data contained few quad axles; therefore, statewide quad-axle load spectra were not generated. A sensitivity analysis related to the axle load spectra showed a significant difference in predicted pavement performance resulting from the statewide and MEPDG default axle load spectra. Therefore, the state-specific axle load spectra are recommended for implementation of the MEPDG in Arkansas and updated periodically unless no significant changes are observed in the future.

Estimating the Sensitivity of Design Input Variables for Rigid Pavement Analysis with a Mechanistic-Empirical Design Guide

Many highway agencies use AASHTO methods for the design of pavement structures. Current AASHTO methods are based on empirical relationships between traffic loading, materials, and pavement performance developed from the AASHO Road Test (1958-1961). The applicability of these methods to modern-day conditions has been questioned; in addition, the lack of realistic inputs regarding environmental and other factors in pavement design has caused concern. Research sponsored by the NCHRP has resulted in the development of a mechanisticempirical design guide (M-E design guide) for pavement structural analysis. The new M-E design guide requires more than 100 inputs to model traffic, environmental, material, and pavement performance to provide estimates of pavement distress over the design life of the pavement. Many designers may lack specific knowledge of the data required. A study was performed to assess the relative sensitivity of the models used in the M-E design guide to inputs relating to portland cement concr...

Development of Truck Loading Groups for the Mechanistic-Empirical Pavement Design Guide

A key to the use of weigh-in-motion (WIM) traffic data for the Mechanistic-Empirical Pavement Design Guide (MEPDG) is to be able to successfully recognize the differences in loading patterns and to estimate the full axle-load spectrum data occurring under different conditions. However, how to identify these patterns on the basis of the large amount of WIM data remains a challenge. In this paper, WIM data collected in the state of Arkansas are analyzed by using cluster analysis methodologies to identify groups of WIM sites with similar traffic characteristics on the basis of the MEPDG-required traffic attributes. Case studies are presented and the cluster results are discussed. Combining the loading clusters, four long-term transportation planning factors currently adopted in Arkansas, including the modified Arkansas primary highway network (APHN) classification, demography, geography, and region attribute (rural or urban) of a highway under design, are adopted as the influencing criteria to develop the tr...

EXAMINATION OF OPERATOR VARIABILITY FOR SELECTED METHODS FOR MEASURING BULK SPECIFIC GRAVITY OF HOT-MIX ASPHALT CONCRETE

The ability of different operators to obtain similar results when performing laboratory tests on the same material is vital for producing accurate testing results. By conducting trials in triplicate for each of three different testing methods, a measurement of the bulk specific gravity (Gmb) of compacted hot-mix asphalt concrete (HMAC) cores was obtained. An analysis of the variability between operators was investigated using a total of almost 1,300 test results, using HMAC sampled from six projects in Arkansas. Three methods were used to determine the bulk specific gravity of compacted HMAC samples, including saturated surface dry (SSD) (as per AASHTO T166), height and diameter (as per AASHTO T269), and vacuum sealing (using the Corelok vacuum sealing device). In almost all cases, Gmb values determined using the height and diameter method were statistically different from those determined using the SSD and Corelok methods; further, statistical differences were noted in paired analyses between the SSD and Corelok methods. The Corelok method exhibited a lower degree of variability than the other two methods used, based on the standard deviation of test results obtained by different operators. In direct comparison with the SSD method, the Corelok exhibited a lower variability (standard deviation) in 81 percent of the cases. Overall, the Corelok method appears to offer a viable alternative for determining the bulk specific gravity of compacted HMAC. However, agencies seeking to use the Corelok must consider the effect of an apparent shift in Gmb values obtained on resulting HMAC volumetric and compaction properties.

Development and Significance of Statewide Volume Adjustment Factors in Mechanistic-Empirical Pavement Design Guide

A new Mechanistic–Empirical Pavement Design Guide (MEPDG) has been developed under NCHRP Project 1-37A. Pavement design procedures recommended for use in MEPDG represent a significant departure from current procedures. The MEPDG requires new traffic inputs for estimating the magnitude, configuration, and frequency of the loads that are applied throughout the pavement design life. The Arkansas State Highway and Transportation Department (AHTD) sponsored research in which one objective was development of statewide truck traffic volume adjustment factors, including class and monthly and hourly distribution factors, and evaluating significance of the developed inputs in the MEPDG. The AHTD provided classification data collected at 55 weigh-in-motion (WIM) sites from 2003 through 2005. Because of missing and inaccurate classification data at several WIM sites, only 23 sites provided classification data suitable for this study. On the basis of selected data, statewide monthly, hourly, and class distribution factors were developed for Arkansas. Analyses using the MEPDG showed the state-specific class distribution factors to have a significant effect on predicted pavement performance, compared with predictions generated by using default distribution values. However, the effect of using state-specific monthly and hourly distribution factors on predicted pavement performance rather than default values was not significant. Therefore, it is recommended that the state-specific class distribution factors be used with the default monthly and hourly distribution factors in the MEPDG. In addition, periodic review and update of statewide class distribution factors, as necessary, are recommended.

Mechanistic-empirical pavement design guide (MEPDG): a bird's-eye view

Past editions of the American Association of State Highway and Transportation Officials (AASHTO) Guide for Design of Pavement Structures have served well for several decades; nevertheless, many serious limitations exist for their continued use as the nation’s primary pavement design procedures. Researchers are now incorporating the latest advances in pavement design into the new Mechanistic-Empirical Pavement Design Guide (MEPDG), developed under the National Cooperative Highway Research Program (NCHRP) 1-37A project and adopted and published by AASHTO. The MEPDG procedure offers several dramatic improvements over the current pavement design guide and presents a new paradigm in the way pavement design is performed. However, MEPDG is substantially more complex than the AASHTO Design Guide by considering the input parameters that influence pavement performance, including traffic, climate, pavement structure and material properties, and applying the principles of engineering mechanics to predict critical pavement responses. It requires significantly more input from the designer. Some of the required data are either not tracked previously or are stored in locations not familiar to designers, and many data sets need to be preprocessed for use in the MEPDG. As a result, tremendous research work has been conducted and still more challenges need to be tackled both in federal and state levels for the full implementation of MEPDG. This paper, for the first time, provides a comprehensive bird’s eye view for the MEPDG procedure, including the evolvement of the design methodology, an overview of the design philosophy and its components, the research conducted during the development, improvement, and implementation phases, and the challenges remained and future developments directions. It is anticipated that the efforts in this paper aid in enhancing the mechanistic-empirical based pavement design for future continuous improvement to keep up with changes in trucking, materials, construction, design concepts, computers, and so on.

Evaluation of Testing Protocols for Dynamic Modulus of Hot-Mix Asphalt

The dynamic modulus (|E*|) of hot-mix asphalt (HMA) is one of the fundamental inputs in the mechanistic-empirical (M-E) pavement design guide developed in NCHRP Project 1-37A. The M-E design guide provides three levels for |E*| input, which are related nominally to the reliability of pavement performance estimates generated by the guide. Level 1 |E*| inputs require laboratory-measured |E*| -values, and Level 2 and 3 |E*| inputs are estimated by using a predictive equation. To provide the laboratory-measured |E*| inputs for implementation of the M-E design guide, a comprehensive research effort was completed in Arkansas. The research included a study evaluating different |E*| testing protocols, derived by varying combinations of the number of test replicates and the number of measurement instruments affixed on each test specimen recommended in AASHTO TP 62-03. The testing protocols were evaluated in terms of the variability of the resulting |E*| test results. The total research effort included three replic...

Calibration of the Mechanistic-Empirical Pavement Design Guide for Flexible Pavement Design in Arkansas

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 paper summarizes 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 in Microsoft Excel was used to optimize the coefficients for alligator cracking. Iterative runs of the MEPDG by means of 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 about the suitability of the calibrated models for routine design. Many default values were used in the MEPDG because of a 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 the definitions of transverse cracking between the MEPDG and the LTPP may be critical to data collection and identification. Thermal cracking should be specifically identified in a transverse cracking survey to calibrate the transverse cracking model in MEPDG. The procedure using LTPP and PMS data for local calibration of the MEPDG in Arkansas is established. Additional development of database software for data manipulation, preprocessing, and quality control—under way in Arkansas—will significantly streamline the calibration process.

Coefficient of Thermal Expansion of Concrete Materials: Characterization to Support Implementation of the Mechanistic–Empirical Pavement Design Guide

The new Mechanistic-Empirical Pavement Design Guide (MEPDG) requires the coefficient of thermal expansion (CTE) of concrete materials as a direct input to determine critical pavement distresses. The CTE can be determined using AASHTO TP 60. For this study, a CTE measuring device in compliance with AASHTO TP 60 was acquired. Three replicate specimens were prepared for each of 24 concrete and cement paste mixtures and tested at 7 and 28 days. The range of CTE determined in this study was in agreement with the range of values reported by other studies, and the variability of test results was favorably comparable. Analysis of variance and sensitivity analyses were performed to evaluate the influence of mixture properties on the CTE and the effect on pavement performance predictions of using Level 1- and 3-CTE inputs. It was concluded that the type of coarse aggregate used in portland cement concrete (PCC) mixtures significantly influenced the CTE and pavement performance predictions. The proportion of coarse aggregates in the PCC mixture could significantly affect the CTE depending on the types of aggregates used in the mixture. In addition, recommendations for Level-3 CTE input can be used for PCC mixtures with limestones and sandstones. However, CTE recommendations for PCC mixtures with gravels were not available for comparisons. It is recommended that a future CTE testing program for supporting implementation of the MEPDG include primary local aggregate types and that CTE recommendations for Level-3 CTE input in the design software be updated to include more aggregate types, especially gravels.