Long-Term Pavement Performance Indicators for Failed Materials

State Transportation Agencies (STAs) use quality control/quality assurance (QC/QA) specifications to guide the testing and inspection of road pavement construction. Although failed materials of pavement rarely occur in practice, it is critical to have a sound decision framework to assist in making data-driven, informed decisions regarding failed materials because such decisions have profound impacts on the long-term performance of the pavement and the operation and maintenance costs of the responsible highway agencies. A performance-related specification (PRS) is a quality acceptance (QA) specification that specifies the acceptable levels of key acceptance quality characteristics (AQCs) that are directly related to fundamental engineering properties, which in turn, determine the long-term performance of the constructed end products. Two PRS tools, PaveSpec for Portland Cement Concrete Pavement (PCCP) and Quality Related Specification Software (QRSS) for QC/QA Hot Mixed Asphalt (HMA) pavement, were investigated in this study to develop decision frameworks for PCCP and HMA pavement to assist the decision-making regarding failed materials at INDOT. A large number of simulations of various scenarios in the context of INDOT pavement construction were conducted to fully develop and implement the decision framework. For PCCP, the newly developed decision framework based on PaveSpec was validated using data from an INDOT construction project. The framework is readily implementable to assist INDOT in making informed decision regarding failed materials for PCCP. For QC/QA pavement, it was found that QRSS is not an appropriate PRS tool to estimate the long-term performance because of its limitations, the misalignment between QRSS process and INDOT practice, and erroneous simulation results

Nickel Content in Plants and Soil: The Case of Mine Tailing Sites in Bato-Bato Narra Palawan, Philippines

Forests once deforested through mining losses its rich biodiversity. The re-opening of open-pit mining corporation in 2011, in the small village of Bato-Bato, Narra, Palawan had caused deforestation, floods, and low rice harvest. This study determined the nickel content in topsoil and native dominant plants in mine-tailings. Field data collection and laboratory analysis methods were used in this study. Nickel content in topsoil (2 kg replication-1 site-1) was analyzed using X-ray Flourescence (XRF). Inductively Coupled-plasma–Optical Emission Spectrometry (ICP-OES) determine nickel in dominant plants (200 g replication-1 site-1). Normality of data was determined by Pearson coefficient of skewness test. Significant difference on the nickel content in plant tissues was analyzed using Kruskal Wallis test, analysis of variance, and Tukey post hoc test for nickel in soil. Native dominants are National Seed Industry Council Rice cultivar 218, Philippine Seed Board Rice cultivar 18, and carabao grass. The nickel content in native dominant plants is higher in comparison with the average nickel content in plant tissues and the nickel content in topsoil is high in comparison with the average nickel content a topsoil should contain. Prevention of leaching of nickel during flood is recommended

Pavement Acceptance Testing: Risk-Controlled Sampling Strategy

Acceptance testing is a critical aspect of the quality control and quality assurance (QC/QA) program to ensure the reliable long-term performance of pavement. A typical acceptance testing specification includes acceptable quality characteristics (AQCs), testing methods, number of samples, sample locations, and acceptance criteria. In the current practice, Indiana Department of Transportation (INDOT) accepts pavement by sampling and testing materials with a pre-determined, very low frequency at random locations, leading to a significant problem: testing results are not truly “representative” of the project because sampling is neither based on a statistical foundation, nor on the reliability concept. This study developed a systematic guideline that has addressed the aforementioned problem of material acceptance testing in four aspects: identifying key material properties for testing, selecting sample locations, designing acceptance criteria, and determining optimal sample size. Key material properties that are critical to the pavement long-term performance are identified by comparing with sensitive material properties in MEPDG. A random sampling mechanism was devised based on two spatial indices to control the spatial pattern of samples to minimize the influence from spatial autocorrelation. Risk-based acceptance criteria was proposed based on statistical methods to control the agency’s risk at a desired level given a specific sampling and testing strategy, based on which optimal sample size is determined from a risk perspective. Cost analysis approaches were developed to estimate the total cost of acceptance testing by integrating the risk of making incorrect decision and enable the determination of optimal sample size from a cost perspective. Additionally, quality control chart was exploited as a complementary tool to ensure the consistency of the pavement quality of a project. The results of this study were validated using real data from INDOT projects, and a web tool that incorporates the newly created methods in this study was developed to assist the field pavement QA practice

Intelligent Compaction of Soils—Data Interpretation and Role in QC/QA Specifications

This report describes a study of intelligent compaction (IC) technologies, within the context of actual construction projects, for its potential as a component of INDOT’s QC/QA for soils. The output from an IC-equipped roller compaction equipment is a real-time area mapping of the compacted lift stiffness as captured by the IC measure. Data was collected to evaluate the correlation between each of two IC measures—compaction meter value (CMV) and machine drive power (MDP)—and in situ embankment quality test measures, the chief in situ test being the dynamic cone penetrometer (DCP) test which INDOT uses for soil embankment acceptance testing. Researchers sought to understand how well the IC measures might assess embankment quality as currently evaluated by the in situ measures. Window-averaged IC measures were compared with the in situ DCP test points. For CMV, a variable correlation was found between the average CMV and DCP values from 74 in situ locations. Also, a limited head-to-head comparison of CMV and MDP with the in situ measures provided some indication that MDP should be studied further. Lessons were learned regarding the elimination of bias in future correlation studies, critical provisions to facilitate best data quality, and important aspects of data management. IC technology holds promise for monitoring the consistency of the soil compaction effort and flagging weak areas in real time during compaction operations. However, further insight is needed regarding the correlation of the DCP measure with both types of IC measures for various soil characterizations and field moisture conditions

Automating the Generation of Construction Checklists

Construction inspection is a critical component of INDOT’s quality assurance (QA) program. Upon receiving an inspection notice/assignment, INDOT inspectors review the plans and specifications to identify the construction quality requirements and conduct their inspections accordingly. This manual approach to gathering inspection requirements from textual documents is time-consuming, subjective, and error-prone. This project addresses this critical issue by developing an inspection requirements database along with a set of tools to automatically gather the inspection requirements and provide field crews with customized construction checklists during the inspection with the specifics of what to check, when to check, and how to check, as well as the risks and the actions to take when noncompliance is encountered. This newly developed toolset eliminates the manual effort required to acquire construction requirements, which will enhance the efficiency of the construction inspection process at INDOT. It also enables the incorporation of field-collected data to automate future compliance checking and facilitate construction documentation

Lurasidone hydro­chloride

In the crystal structure of the title compound, C28H37N4O2S+·Cl− [systematic name: 4-(1,2-benzothia­zol-3-yl)-1-({2-[(3,5-dioxo-4-aza­tricyclo­[5.2.1.02,6]decan-4-yl)meth­yl]cyclo­hex­yl}meth­yl)piperazin-1-ium chloride], the anions and cations are linked by N—H⋯Cl hydrogen bonds. The crystal structure is further stabilized by C—H⋯π and C—H⋯O inter­actions

A Quantitative Evaluation of the Nighttime Visual Sign Inspection Method

A research project to determine the appropriate sign inspection and replacement procedure was conducted at North Carolina State University and sponsored by the North Carolina DOT. The purpose was to determine the optimum strategy for sign inspection and replacement under different conditions to respond to the pending retroreflectivity requirements. This paper reports on a spreadsheet tool developed to quantitatively evaluate the effectiveness of different sign inspection and replacement scenarios. The spreadsheet was designed for yellow and red engineer-grade sign sheetings, and takes into account sign vandalism and knock-downs as well as normal sign aging. The spreadsheet provides estimates of the number of signs in place that would not meet the minimum retroreflectivity standard and the cost of the sign inspection and replacement program. The results from a number of trials of the spreadsheet show that agencies that generally conform to the key assumptions made to build the spreadsheet should consider replacing all signs every seven years, as that insures that no aged signs are in place at a relatively low cost. If total replacement is not possible, an inspection program using retroreflectometers every three years appears very competitive in its effectiveness with a program using typical visual inspection rates each year. The retroreflectometers appear to allow fewer deficient signs, while the typical visual inspection program costs are lower for a given vandalism rate. More conservative visual sign replacement rates do not appear to offer distinct advantages, because typical replacement rates with visual inspections every two or three years allow relatively high numbers of deficient signs to remain on the roads

A Synthesis Study on Collecting, Managing, and Sharing Road Construction Asset Data

Accurate and complete construction records and as-built data are the key prerequisites to the effective management of transportation infrastructure assets throughout their life cycle. The construction phase is the best time to collect such data. Assets such as underground drainage and culverts are visible and physically accessible only during construction. For assets such as guardrails, signals, and pavement, it is safer and more efficient to collect data during construction than after construction when the road segment is open to traffic. The purpose of this project was to conduct a synthesis study to 1) assess the current status at INDOT regarding the collection of asset data during the construction phase and the use of such data in the operation and maintenance (O&M) phase, and 2) develop a framework for INDOT to leverage the construction inspection and documentation process to collect data for assets. Data needs during O&M were identified through rounds of meetings with relevant INDOT business units. The current practice in construction documentation was investigated in detail. A survey of state highway agencies (SHAs) was conducted to assess the state-of-the-practice. A practical framework was developed to leverage the construction inspection and documentation practice to collect asset data that are needed in O&M. The framework uses specific pay items—construction activities that result in physical structures—as the bridge to connect plan assets (i.e. physical structures specified in the design documents) to their corresponding counterparts in the asset management systems. The framework is composed of 1) a data needs component for determining the information requirements from the O&M perspective, 2) a construction documentation module, and 3) a mapping mechanism to link data items to be collected during the construction documentation to data items in the asset management systems. The mapping mechanism was tested and validated using four priority asset classes—underdrains, guardrails, attenuators, and small culverts—from an INDOT construction project. The testing results show that the newly developed framework is viable and solid to collect asset data during the construction phase for O&M use in the future, without adding extra workload to construction crews. The framework can reduce/eliminate the duplicate data collection efforts at INDOT, leading to savings and efficiency gains in the long term