1. Introduction and Overview. 2. Detecting Influential Observations and Outliers. 3. Detecting and Assessing Collinearity. 4. Applications and Remedies. 5. Research Issues and Directions for Extensions. Bibliography. Author Index. Subject Index.

Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

Dynamics of structures

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Random Data Analysis And Measurement Procedures

Emerging artificial intelligence methods in structural engineering

This report presents information on the characterization of cementitiously stabilized layers and the properties that influence pavement performance. It also contains recommended performance-related procedures for characterizing these layers and performance-prediction models for incorporation into the mechanistic–empirical pavement analysis methods. Individual chapters highlight pavement distresses of hot-mix asphalt pavements and concrete pavements, laboratory tests and model development, and model calibration. The material contained in the report will be of immediate interest to state materials, pavement, and construction engineers and others involved in the different aspects of pavement design and construction.

Characterization of Cementitiously Stabilized Layers for Use in Pavement Design and Analysis

In this paper, we propose a novel approach to estimate the damage induced to transported goods by roughness features. The approach proposed herein uses a mechanistic-empirical approach to conduct product fragility assessment using numerical modeling of vehicle and product vibration response. A half-truck model was used to simulate vehicle vibrations. The principle of conservation of momentum (inelastic shocks) was used to estimate damage to goods. The analysis of three case studies for horticultural produce showed that: air suspensions cause less damage to the transported goods than steel suspensions; shorter spacing between faults in jointed concrete pavements will cause less damage to the transported goods in trucks with steel suspension; low speed will cause more damage to transported goods in trucks with steel suspensions than higher speed; and more breaks on the road will cause more damage to the transported goods. The approach reported in this paper could help in better estimating vehicle operating costs at the project and network levels.

Impact of road roughness features on damage to transported goods

State Highway Agencies (SHAs) have long realized the importance of quality assurance (QA) to ensure longer pavement service life. Construction QA programs are intended to ensure that the quality of the materials and construction in highway projects is satisfactory. Failure to conform to either material or construction specifications can result in the premature failure of pavements. The intent of this research project is to assess existing pavement acceptance criteria, conduct a feasibility study to consider the need of using new criteria that relate to pavement performance including the use of non-destructive testing, and develop a process to quantify as-constructed material and structural pavement properties and relate them to pavement service life. This was achieved by reviewing Michigan Department of Transportation (MDOT) construction data, construction and performance data from the national Long-Term Pavement Performance (LTPP) database, reviewing QA programs of other state highway agencies, conducting a literature review of previous research studies on the subject, and finally running simulations using the new Mechanistic-Empirical Pavement Design Guide (MEPDG) software to relate quality characteristics to pavement performance. Finally, Monte-Carlo based simulations were developed to understand how these quality characteristics should be used in the specifications to encourage better quality and reduce the risk of overpayment or underpayment. A plan of action was also developed for MDOT to implement the recommendations in its quality assurance and design process. An important part of this is a feedback process for design.

Assessment of Pavement Acceptance Criteria and Quantifying its As-constructed Material and Structural Properties

The performance of pavement sections subjected to preservation or rehabilitation treatments depends on several factors including: the pavement type, the pavement cross-section, the before-treatment conditions, the rates of deterioration prior to the treatment, the pre-treatment repairs, the type of treatment applied, and the quality of construction. The study of the before- and after-treatment trends in pavement performance with regard to these factors can be a useful tool in the prediction of pavement performance leading to the selection of optimum treatment type, time, and project boundaries. To maximize the benefits of a pavement action the treatment should improve the condition and/or extend the service life of the pavement. The best way to estimate improvements in the pavement performance is to study the results of comparable treatments previously conducted on similar pavements. The historical time-series pavement condition data could be modeled using the appropriate mathematical functions. The modeled pavement performance could then be studied to determine the improvements in pavement conditions, rates of deterioration, and service life. The continuous study of these relationships to calibrate and improve the models used to predict performance will help improve the selection of optimum pavement treatment type, time, and project boundaries. This paper discusses methodology to study the past performance of pavement treatments in a given highway authority’s network. The type and quantity of data required as well as the analyses methods are presented; leading toward a reliable method for estimating treatment performance and selecting the optimum treatment.

Predicting Pavement Treatment Performance from Relationships Between Before- and After-Treatment Trends

The research described here was conducted as a part of NCHRP Project 20-50 (10&16), LTPP (Long-Term Pavement Performance) Data Analysis: Influence of Design and Construction Features on the Response and Performance of New Flexible and Rigid Pavements. The relative effects of various design and site factors on the performance of jointed plain concrete (JPC) pavements are presented. The data used in this study were primarily drawn from Release 17 of DataPave. The Specific Pavement Study (SPS) 2 experiment was designed to investigate the effects of portland cement concrete (PCC) slab thickness, base type, drainage, PCC flexural strength, and slab width on the performance of JPC pavements. On the basis of the statistical analysis of 167 test sections, ranging in age from 5 to 12 years, it was concluded that base type was the most critical design factor affecting performance in terms of cracking and roughness as measured by the international roughness index. Pavement sections with a permeable asphalt-treated b...

Part 1: Rigid Pavements: Network-Level Evaluation of Specific Pavement Study-2 Experiment: Using a Long-Term Pavement Performance Database

Pavement preservation has become a common practice in the management of pavement network across the country. However, the effectiveness of the preservation treatments varies depending on several factors e.g., construction practices, traffic, climate and pavement conditions. The purpose of this paper is to determine the impact of pre-existing pavement conditions in terms of the aforementioned site factors on the effectiveness of pavement preservation treatments. The data from the Long-Term Pavement Performance (LTPP) SPS-3 and SPS-4 experiments were used to quantify pavement benefit in terms of service life extension (SLE) among different flexible and rigid pavement preservation treatments. The SLE was determined based on structural and functional performance measures unique to each pavement type. The SLE is a measure of treatment effectiveness and can be obtained by comparing the performance between treated and untreated control pavement sections. The flexible pavement performance measures considered were structural cracking, thermal cracking, rutting, roughness in terms of the International Roughness Index (IRI), bleeding and raveling. The rigid pavement performance measures considered were structural and thermal cracking, roughness, faulting, and spalling. The impact of various site factors (e.g., traffic, climate, and pavement surface conditions) was determined by performing statistical analyses including analysis of variance (ANOVA) and multiple linear regression (MLR). The efficacy of preservation treatments, in terms of SLE, was associated with varying ranges of pre-existing functional and structural conditions. By characterizing pre-existing conditions, it is possible to associate pre-existing site conditions with expected treatment performance. Such an approach can be used to predict expected service life of a treatment based on thresholds related to the results of a pre-treatment pavement condition survey.

Karim Chatti

Papers

Impact of road roughness features on damage to transported goods

Assessment of Pavement Acceptance Criteria and Quantifying its As-constructed Material and Structural Properties

Predicting Pavement Treatment Performance from Relationships Between Before- and After-Treatment Trends

Part 1: Rigid Pavements: Network-Level Evaluation of Specific Pavement Study-2 Experiment: Using a Long-Term Pavement Performance Database

Impact of Pre-existing Site Conditions on the Effectiveness of Pavement Preservation Treatments