Time filter

Source Type

Austin, TX, United States

Gallivan V.L.,U.S. Federal Highway Administration | Chang G.K.,Transtec Group Inc. | Horan R.D.,Asphalt Institute
Asphalt Paving Technology: Association of Asphalt Paving Technologists-Proceedings of the Technical Sessions | Year: 2011

Intelligent Compaction (IC) is a major innovation in compaction technology that has been studied extensively in the US over the last five years. IC is defined as a process that uses vibratory rollers equipped with a measurement/documentation system that automatically records various critical compaction parameters in real time during the compaction process. The recorded information is then displayed for the roller operator and project personnel to improve the compaction process. Field studies by the authors and other researchers have shown that IC has many potential benefits that can result in better compaction processes and improved process/quality control/acceptance procedures. These benefits are likely to result in the construction of longer lasting asphalt pavements. Suppliers of IC technology have conducted extensive research and development and are geared up to make IC rollers commercially available. In short, the stage is now set for agencies that would like to implement the use of IC technology in a practical manner. It has been a well known fact for decades that effective compaction is a critical step in the construction of quality Hot Mix Asphalt (HMA) pavement. In recent years, the understanding has grown that pavement materials must be properly compacted in the field to obtain the desired long service lives. With this in mind, there have been many improvements and innovations in compaction equipment, as well as in situ test equipment and specifications related to compaction over the years. Manufacturers have been modifying their compaction equipment, State agencies have been modifying their specifications, and contractors have been modifying their processes over the years all in an attempt to improve the compaction of HMA pavements. This paper discusses the 21st century practical efforts to improve the compaction of HMA pavements by using " intelligent" equipment that provides the contractors and agencies real-time information regarding the effectiveness of their compaction operations. The results of multiple field demonstrations have shown that IC mapping of the underlying materials prior to paving can identify weak or non-uniform areas that affect the quality of the HMA pavement compaction efforts. The contractor can optimize rolling operations using IC with increased knowledge of the HMA surface temperatures and roller locations. Thus, IC is a technology that is increasingly being used nationally and internationally and has been shown to provide for greater control and oversight of the compaction process, resulting in improved and more uniform compaction. Source

Xu Q.,University of Texas at Austin | Chang G.K.,Transtec Group Inc.
Construction and Building Materials | Year: 2014

In the conventional structural analysis and design of highway pavements including the mechanistic-empirical pavement design guide (MEPDG), the layer properties are considered uniform spatially. This research studies the geospatial heterogeneity of asphalt material property and its influence on structural responses with the intelligent compaction (IC) technology on road construction. Instrumented with the satellite navigation system, accelerometer and computer system, the IC roller measured the material stiffness with 100% coverage. A three-dimensional finite element (FE) model was developed to simulate pavement responses with heterogeneous Bomag Evib as elastic moduli of asphalt materials under vehicle loading. This material model considers heterogeneous material properties with geospatial distribution that more closely reflect the actual field conditions on a typical roadway. The statistics and geostatistical semivariogram model were studied to evaluate the heterogeneity of material moduli and structural responses. A coefficient of semivariogram (Cova) index is proposed to quantify the geospatial heterogeneity. Modeling results demonstrated that geospatial heterogeneity of material elastic moduli, rather than commonly used univariate statistics, affects structural responses spatially in a nonlinear fashion. Heterogeneous moduli distribution results in inferior responses than uniform model. Cova has close values and trends with that of the coefficient of variance for the analysis area with small-space, and it could be used to quantify the heterogeneity. Therefore, the geospatial heterogeneity of material property is recommended to be considered in future pavement analysis to account for the in-service conditions. © 2014 Elsevier Ltd. All rights reserved. Source

Rasmussen R.O.,Transtec Group Inc.
SAE International Journal of Passenger Cars - Mechanical Systems | Year: 2013

Pavements complying with the ISO 10844 standard are an important component of vehicle and tire noise testing. In 2011, a new version of this standard was published, which includes many important changes compared to the 1994 version. As a result, some tracks that complied with the 1994 standard are now nonconforming with the 2011 version. Many tracks are in the process of being resurfaced, particularly before regulations are adopted that require conformance with the new version of the standard. While repaving is costly, it can also lead to opportunity. Pavement engineering encompasses pavement design, materials selection and proportioning, and the selection of construction techniques. Pavement life is also an important engineering criterion. In the case of test tracks, life is most often defined by functional performance including changes in friction, rolling resistance, ride, and in this instance, noise. Optimized pavement engineering often seeks a balance between initial cost and durability. For example, ISO 10844:2011 now permits polymer-modified asphalt binders. While more costly, higher quality binders can delay the onset of raveling, stripping, and other surface deterioration that affects functional performance including noise. Optimized pavement engineering can target a pavement lifespan, which is related to the evolution of the noise measurements over time. A predictable response can also be sought. For example, the ISO 10844:2011 tests for pavement texture and acoustical absorption. These attributes are affected by paving materials and construction technique. Through optimization, specific measurement targets can be engineered for more predictable and consistent test outcomes. 2013 SAE International. Source

Gharaibeh N.G.,Texas A&M University | Garber S.I.,Transtec Group Inc. | Liu L.,Texas A&M University
Transportation Research Record | Year: 2010

Highway construction and materials acceptance plans use a sample size that is often established on the basis of practical considerations such as personnel and time constraints. Commonly used sample sizes range between three and seven units. While a sample size within this range may be practical, it may not be economically optimal. If this sample size is too small, the probability of making erroneous acceptance or pay adjustment decisions (and thus the expected cost consequences of these decisions) would be too high for state departments of transportation (DOTs). If this sample size is too large, the cost of sampling and testing would be unnecessarily high, especially where destructive testing is used. A computational model for determining the optimum sample size was developed and is presented in this paper. This model is intended to help highway agencies determine how much to sample to minimize their total acceptance cost (cost of sampling and testing plus the cost of erroneously accepting poor-quality materials and construction). Inputs to this model can be obtained from an agency's specifications book, historical data on quality, prevalent unit bid prices, and prevalent sampling and testing prices. The developed model was applied to determine the optimum sample size for the AASHTO acceptance plan for binder content and density of hot-mix asphalt concrete pavements. The model shows that, when historical quality levels are satisfactory, the state DOT may consider reducing sample size as much as practically possible (in most cases, a sample size of three per lot for each acceptance quality characteristic is optimal). Only in the case of large lot size, combined with historically extremely poor quality and high unit bid price, was a larger sample size found to be optimal (n = 7 to 8). Source

Xu Q.,Transtec Group Inc. | Chang G.K.,Transtec Group Inc. | Gallivan V.L.,Office of Pavement Technology
Construction and Building Materials | Year: 2012

Intelligent compaction (IC) on hot-mix-asphalt (HMA) is an emerging, yet still evolving technology for the constructions of highway system, airfield, and parking lots. IC produces massive amounts of geospatial data with 100% coverage of the compacted area in real time, which needs to be effectively analyzed and managed for quality control and acceptance (QC/QA). Accordingly, in this paper a systematic method using both the univariate and geo-statistical modeling techniques was developed for the IC data analysis and management. A data extraction method was proposed to categorize and extract IC data on different layer levels. Consequently, linear regression was performed to correlate IC Measurement Values (ICMVs) with random spot measurements. The semivariogram model was studied to evaluate the compaction uniformity, and the compaction curve was developed to identify the optimum number of roller passes. The systematic method with multiple statistical models was coded for numerical solutions, and demonstrated for eight HMA IC projects. Results indicate that compaction uniformity improves "from the ground, up": subbase, HMA base, and then surface course. The compaction curve can help set the compaction target for QC/QA. ICMV has shown consistent linear correlations with spot measured deflections and material modulus, but it has inconsistent correlations with densities. Multivariate correlations indicate that multiple factors, including the ICMV of underlying layers and temperatures of HMA, affect the ICMV of the HMA layer. © 2012 Elsevier Ltd. All rights reserved. Source

Discover hidden collaborations