Development of Empirical-Mechanistic Pavement Performance Models using Data from the Washington State PMS Database

A Pavement Management System (PMS) is a decision-support tool that aids public agencies in planning maintenance activities of their facilities. A complete PMS involves the following tasks: inspecting facilities and collecting data, predicting the deterioration of facilities through performance models, and optimizing the Maintenance, Rehabilitation, and Reconstruction (MR&R) policies over the planning horizon. Performance models are a core component of PMS. These models are also used to calibrate facility design procedures.The main objective of this project was to develop Empirical-Mechanistic (E-M) performance models using data from Washington State’s PMS databases. Four models were developed from that data:* A model for predicting the initiation of overlay cracking in asphalt concrete (AC) pavements * A model for predicting the progression of roughness for AC pavements * A model for predicting the initiation of cracking in portland cement concrete (PCC) pavements * A model for predicting the progression of roughness for portland cement concrete pavementsAt the start of the project, models using pavement maintenance data from the Washington State Department of Transportation (WSDOT) and the Arizona Department of Transportation (ADOT) were attempted. The initial reasoning for using PMS data from those states is that they have very measured pavement conditions consistently over a long period of time, and they have topographic and climate regions similar to parts of California. Therefore, Caltrans could use models developed using data from those states to manage a subset of California’s pavement infrastructure until the department develops the database needed to support model development. However, the research team found that the ADOT data were inappropriate for developing the type of performance models needed in this project, so only WSDOT pavement data were used

Development of an Empirical-Mechanistic Model of Overlay Crack Progression using Data from the Washington State PMS Database

This is the second of two reports that present fatigue cracking performance models for asphalt concrete overlays placed on existing asphalt concrete pavement. The models were developed from the pavement management system (PMS) database of the Washington State Department of Transportation (WSDOT). The database included existing pavement structure, overlay thickness and type, truck traffic, and observed percent of the wheelpath cracked from annual condition surveys. Climate data was developed by the UCPRC to augment the WSDOT data. This report presents a model for crack propagation, starting from crack initiation, which was defined as 5 percent of the wheelpath with longitudinal cracking. The combined initiation and propagation models were included in a spreadsheet calculator which was used to perform an analysis of the sensitivity of crack initiation and propagation to the input variables. The models are extremely useful for predicting pavement performance. For use in California they will need recalibration of the coefficients to reflect differences in WSDOT and California practice, primarily the use of thicker overlays in California, placement of overlays at much more advanced states of cracking in the existing pavement, and possible differences in routine maintenance activities

Development of Empirical-Mechanistic Pavement Performance Models using Data from the Washington State PMS Database

A Pavement Management System (PMS) is a decision-support tool that aids public agencies in planning maintenance activities of their facilities. A complete PMS involves the following tasks: inspecting facilities and collecting data, predicting the deterioration of facilities through performance models, and optimizing the Maintenance, Rehabilitation, and Reconstruction (MR&R) policies over the planning horizon. Performance models are a core component of PMS. These models are also used to calibrate facility design procedures.The main objective of this project was to develop Empirical-Mechanistic (E-M) performance models using data from Washington State’s PMS databases. Four models were developed from that data:* A model for predicting the initiation of overlay cracking in asphalt concrete (AC) pavements * A model for predicting the progression of roughness for AC pavements * A model for predicting the initiation of cracking in portland cement concrete (PCC) pavements * A model for predicting the progression of roughness for portland cement concrete pavementsAt the start of the project, models using pavement maintenance data from the Washington State Department of Transportation (WSDOT) and the Arizona Department of Transportation (ADOT) were attempted. The initial reasoning for using PMS data from those states is that they have very measured pavement conditions consistently over a long period of time, and they have topographic and climate regions similar to parts of California. Therefore, Caltrans could use models developed using data from those states to manage a subset of California’s pavement infrastructure until the department develops the database needed to support model development. However, the research team found that the ADOT data were inappropriate for developing the type of performance models needed in this project, so only WSDOT pavement data were used

Development of an Empirical-Mechanistic Model of Overlay Crack Progression using Data from the Washington State PMS Database

This is the second of two reports that present fatigue cracking performance models for asphalt concrete overlays placed on existing asphalt concrete pavement. The models were developed from the pavement management system (PMS) database of the Washington State Department of Transportation (WSDOT). The database included existing pavement structure, overlay thickness and type, truck traffic, and observed percent of the wheelpath cracked from annual condition surveys. Climate data was developed by the UCPRC to augment the WSDOT data. This report presents a model for crack propagation, starting from crack initiation, which was defined as 5 percent of the wheelpath with longitudinal cracking. The combined initiation and propagation models were included in a spreadsheet calculator which was used to perform an analysis of the sensitivity of crack initiation and propagation to the input variables. The models are extremely useful for predicting pavement performance. For use in California they will need recalibration of the coefficients to reflect differences in WSDOT and California practice, primarily the use of thicker overlays in California, placement of overlays at much more advanced states of cracking in the existing pavement, and possible differences in routine maintenance activities

Absolute real-time non-destructive ethylene detection with SRI-MS and PTRMS: the example of fruits, leaves and bacteria

The goal of this work is to demonstrate that it is possible to perform quantitative ethylene (C2H4) measurements using PTR-MS. In order to demonstrate that this is possible, we need to investigate the reactions that take place in the PTR-MS with ethylene. New PTR-MS instruments allow to choose between the three primary ions H3O+, O2 + and NO+ [1], hence the name Selective Reagent Ion - Mass Spectrometry (SRI-MS). Moreover, O2 + and NO+ are the ions typically encountered in H3O+ mode and can act as parasitic, precursor ions [2,3].We performed extensive calibrations using ethylene external standards at different instrumental conditions and showed that it is possible to accurately predict ethylene concentrations by considering ethylene reaction with O2 + ions, which are found to proceed at about collision rate. We also showed that NO+ ions do not react with ethylene while for H3O+ ions the reation proceeds much below collision rate.We tested our methodology on real samples (fruits, leaves and bacteria) and compared the results with an optical ethylene sensor. A very good agreement was found. Moreover, we demostrated that SRI-MS has a broader dynamic range and a better linearity than the optical senso