Investigation of complex modulus of base and EVA modified bitumen with Adaptive-Network-Based Fuzzy Inference System

This study aims to model the complex modulus of base and ethylene-vinyl-acetate (EVA) modified bitumen by using Adaptive-Network-Based Fuzzy Inference System (ANFIS). The complex modulus of base and EVA polymer modified bitumen (PMB) samples were determined using dynamic shear rheometer (DSR). PMB samples have been produced by mixing a 50/70 penetration grade base bitumen with EVA copolymer at five different polymer contents. In ANFIS modeling, the bitumen temperature, frequency and EVA content are the parameters for the input layer and the complex modulus is the parameter for the output layer. The hybrid learning algorithm related to the ANFIS has been used in this study. The variants of the algorithm used in the study are two input membership functions and three input membership functions for each of the all inputs. The input membership functions are triangular, gbell, gauss2, and gauss. The results showed that EVA polymer modified bitumens display reduced temperature susceptibility than base bitumens. In the light of analysis the Adaptive-Network-Based Fuzzy Inference System and statistical methods can be used for modeling the complex modulus of bitumen under varying temperature and frequency. The analysis indicated that the training accuracy is improved by decreasing the number of input membership functions and the utilization of the two gauss input membership functions appeared to be most optimal topology. Besides, it is realized that the predicted complex modulus is closely related with the measured (actual) complex modulus

Prediction of permanent deformation in asphalt mixtures

An asphalt mixture is combined of different sizes of aggregate, filler, and bitumen for application on the most common road construction materials. In asphalt pavement material there are different types of distress such as permanent deformation (rutting), fatigue cracking, ravelling, potholes, stripping, etc. There are many reasons for these types of distress, some of them related to the pavement structure, e.g. whether the underlying layers are weak, others related to the mixture properties. Other causes could be related to external conditions such as high temperature, high axle load, long duration of load application, etc. This research has focused on the permanent deformation (rutting) as a function of aggregate gradation. The aggregate gradations of more than twenty asphalt mixtures, manufactured with different gradations, were analysed by using the Bailey method of gradation analysis. The analysis was performed in relation to Repeated Load Axial Test (RLAT) testing results to study the performance of each mixture. The results showed that the Bailey method is not capable on its own to define the differences between the gradations of each mixture. Therefore, three more packing ratios were introduced to adequately describe the aggregate gradation. The aggregate particle packing was extensively studied through these packing ratios and it was shown how the different particle sizes interact with each other. Images were taken for two mixtures to validate the theory behind the ratios. The five packing ratios (two of Bailey and three new ratios) were used in Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques for all the mixtures as input data to predict the mixture performance (RLAT permanent deformation and Indirect Tensile Stiffness Modulus ITSM stiffness modulus) and they showed good prediction capability. After establishing the impact of aggregate packing on the performance, six mixtures were re-manufactured and re-tested with different variables; the selection of the mixtures was made to cover a range of different gradations (ratios). The aim of this step was to understand the effect of these variables on the asphalt mixture in the light of the packing ratios. The variables that were used were binder content, testing temperature and compaction effort. The binder content results showed an interesting effect on the permanent deformation and stiffness of the asphalt mixture. The packing of aggregate was very helpful in understanding the different mixture behaviour with different binder content. The effect of aggregate packing was not shown at relatively low testing temperature, but as the temperature rises the aggregate packing effect starts to appear. The effect of compaction which was represented by the number of gyrations in gyratory compactor was inconsistent; results show over-compaction can lead to poor performance. Finally, a linear viscous method was introduced aiming to predict the rutting in an asphalt mixture. The method was based on using a multilayer linear programme (BISAR) and using viscous parameters of the mixture as input. The non-linear properties of the material were incorporated by using the RLAT test. For this purpose, six mixtures were used and tested in a wheel tracking machine. The predicted results were compared with the wheel tracking rut depth in the laboratory and showed good agreement at different temperatures. However, at high temperature (50 °C) the material properties in the RLAT test did not behave as linear viscous, which resulted in a much poorer prediction. Trials were made to predict field rut but it was found that special requirements were needed for the approach which were not available at the time of the research. However, for the available field data, the method was found to be a good predictor

Prediction of permanent deformation in asphalt mixtures

An asphalt mixture is combined of different sizes of aggregate, filler, and bitumen for application on the most common road construction materials. In asphalt pavement material there are different types of distress such as permanent deformation (rutting), fatigue cracking, ravelling, potholes, stripping, etc. There are many reasons for these types of distress, some of them related to the pavement structure, e.g. whether the underlying layers are weak, others related to the mixture properties. Other causes could be related to external conditions such as high temperature, high axle load, long duration of load application, etc. This research has focused on the permanent deformation (rutting) as a function of aggregate gradation. The aggregate gradations of more than twenty asphalt mixtures, manufactured with different gradations, were analysed by using the Bailey method of gradation analysis. The analysis was performed in relation to Repeated Load Axial Test (RLAT) testing results to study the performance of each mixture. The results showed that the Bailey method is not capable on its own to define the differences between the gradations of each mixture. Therefore, three more packing ratios were introduced to adequately describe the aggregate gradation. The aggregate particle packing was extensively studied through these packing ratios and it was shown how the different particle sizes interact with each other. Images were taken for two mixtures to validate the theory behind the ratios. The five packing ratios (two of Bailey and three new ratios) were used in Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques for all the mixtures as input data to predict the mixture performance (RLAT permanent deformation and Indirect Tensile Stiffness Modulus ITSM stiffness modulus) and they showed good prediction capability. After establishing the impact of aggregate packing on the performance, six mixtures were re-manufactured and re-tested with different variables; the selection of the mixtures was made to cover a range of different gradations (ratios). The aim of this step was to understand the effect of these variables on the asphalt mixture in the light of the packing ratios. The variables that were used were binder content, testing temperature and compaction effort. The binder content results showed an interesting effect on the permanent deformation and stiffness of the asphalt mixture. The packing of aggregate was very helpful in understanding the different mixture behaviour with different binder content. The effect of aggregate packing was not shown at relatively low testing temperature, but as the temperature rises the aggregate packing effect starts to appear. The effect of compaction which was represented by the number of gyrations in gyratory compactor was inconsistent; results show over-compaction can lead to poor performance. Finally, a linear viscous method was introduced aiming to predict the rutting in an asphalt mixture. The method was based on using a multilayer linear programme (BISAR) and using viscous parameters of the mixture as input. The non-linear properties of the material were incorporated by using the RLAT test. For this purpose, six mixtures were used and tested in a wheel tracking machine. The predicted results were compared with the wheel tracking rut depth in the laboratory and showed good agreement at different temperatures. However, at high temperature (50 °C) the material properties in the RLAT test did not behave as linear viscous, which resulted in a much poorer prediction. Trials were made to predict field rut but it was found that special requirements were needed for the approach which were not available at the time of the research. However, for the available field data, the method was found to be a good predictor

Review of advanced road materials, structures, equipment, and detection technologies

As a vital and integral component of transportation infrastructure, pavement has a direct and tangible impact on socio-economic sustainability. In recent years, an influx of groundbreaking and state-of-the-art materials, structures, equipment, and detection technologies related to road engineering have continually and progressively emerged, reshaping the landscape of pavement systems. There is a pressing and growing need for a timely summarization of the current research status and a clear identification of future research directions in these advanced and evolving technologies. Therefore, Journal of Road Engineering has undertaken the significant initiative of introducing a comprehensive review paper with the overarching theme of “advanced road materials, structures, equipment, and detection technologies”. This extensive and insightful review meticulously gathers and synthesizes research findings from 39 distinguished scholars, all of whom are affiliated with 19 renowned universities or research institutions specializing in the diverse and multidimensional field of highway engineering. It covers the current state and anticipates future development directions in the four major and interconnected domains of road engineering: advanced road materials, advanced road structures and performance evaluation, advanced road construction equipment and technology, and advanced road detection and assessment technologies

Mechanical Properties for Buton Asphalt - Aggregates Mixes

The objectives of this research are to study the effect on the resistant to permanent deformation and fatigue cracking of asphalt mixtures using granular Buton Rock Asphalt (BRA) modifier binder. The BRA modified binder was formed by replacing 10, 20 and 30% of the base binder C-170 with BRA natural binder. The results of this study show that BRA modified asphalt mixtures performed better than unmodified asphalt mixtures with regard to permanent deformation and fatigue cracking

Balancing fracture and fatigue performance in asphalt pavements: A hybrid mechanistic and statistical modelling approach

The asphalt mix design and evaluation approaches are divided into two main categories as empirical and mechanistic-empirical (M-E) methods. The empirical methods are based on empirical observations of in-service pavement performance, and they do not take into account engineering properties or failure criteria. The M-E methods were introduced as a new generation for design and evaluation approaches that consider fundamental mixture properties such as material stiffness to determine the pavement\u27s structural response. However, the need for expensive and time-consuming performance-based laboratory tests and local calibration makes the M-E methods unsuitable for routing design. In addition, during the last few years, the asphalt paving industry has been consistently tried to improve pavement performance by introducing new types of materials in asphalt mixtures. Regardless of all the positive effects of innovative materials on mix performance, the M-E design and evaluation methods might not be able to fully capture the benefits that may be achieved through using these materials. It likely stems from the fact that the M-E methods only utilize mix stiffness to evaluate the performance with respect to different distresses. Therefore, a methodology needs to be developed within the framework of current design and evaluation approaches to consider the mixture performance and the impact of innovative materials on pavement performance.This dissertation research aimed to assess the mixture properties indices that can be implemented in performance-based design methods. The proposed endeavor will yield a more precise evaluation of the innovative materials impact on asphalt mixture performance through consideration of the viscoelastic nature of asphalt mixtures to determine mechanistic damage effect. Furthermore, several prediction models for a simplified viscoelastic continuum damage-based fatigue index (as crack initiation phase) and mixture fracture energy (as crack propagation phase) were developed to investigate asphalt mixture performance with respect to cracking. The models include the simultaneous impact of various mix variables that are available during the mix design process. Thus, they can be used as a predesign tool to investigate mixtures\u27 cracking properties without the need for any performance laboratory test data. Finally, a cracking balance design diagram (CBDD) was generated with a combination of prediction models for crack initiation and propagation. The CBDD helps toward better identification of cracking performance considering the simultaneous effects of both cracking phases in a single diagram

World Multidisciplinary Civil Engineering- Architecture- Urban Planning symposium

We would like to express our sincere gratitude to all 900+ submissions by 600+ participants of WMCAUS 2018 from 60+ different countries all over the world for their interests and contributions in WMCAUS 2018. We wish you enjoy the World Multidisciplinary Civil Engineering-Architecture-Urban Planning Symposium – WMCAUS 2018 and have a pleasant stay in the city of romance Prague. We hope to see you again during next event WMCAUS 2019 which will be held in Prague (Czech Republic) approximately in the similar period

Articles indexats publicats per investigadors del Campus de Terrassa: 2018

Aquest informe recull els 290 treballs publicats per 267 investigadors/es del Campus de Terrassa en revistes indexades al Journal Citation Report durant el 2018Postprint (published version