Dynamic stiffness of road pavements: Construction characteristics-based model and influence on tire/road noise

Vázquez, V.F.; Terán, F.; Paje, S.E.

doi:10.1016/j.scitotenv.2020.139597

Cited by 14 publications

(4 citation statements)

References 30 publications

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“…Although using RCA for making RAC is a positive step in the direction of sustainability, it has lower quality in terms of performance than concrete made with natural aggregates [7]. Accordingly, RAC exhibits low flexural, tensile, and compressive strength as well as high porosity, shrinkage, and water absorption [8][9][10].…”

Section: Figure 1 Structural Economic and Environmental Benefits Of R...mentioning

confidence: 99%

Evaluating the Compressive Strength of Recycled Aggregate Concrete Using Novel Artificial Neural Network

et al. 2022

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In this work, the compressive strength of concrete made from recycled aggregate is studied and an intelligent prediction is proposed by using a novel artificial neural network (ANN), which utilizes a sigmoid function and enables the proposal of closed-form equations. An extensive literature search was conducted, which gave rise to 476 data points containing cement, sand, aggregates, recycled aggregates of fine to coarse texture, water, and plasticizer as the constituents of the concrete and the input variables of the intelligent model. The compressive strength (fc) of the recycled aggregate concrete (RAC), which was studied through multiple experiments, was the output variable of the model. The data points of concrete strength collected through literature show a consistent and sustained strength improvement with the increase in the recycled aggregate proportions. However, the outcome of the concrete compressive strength predictive model shows remarkable performance indices as follows; r is 0.99 and 0.99, R2is 0.98 and 0.97, MSE is 28.67% and 44.64%, RMSE is 5.35% and 6.68%, MAE is 4.12% and 5.01%, and MAPE is 12.73% and 13.83% for the model training and testing respectively. These results compared well with previous studies conducted on RAC with less data, different activation functions, and different techniques. Generally, the closed-form equation, which performed at an average accuracy of 97.5% with an internal consistency of 99%, has shown its potential to be applied in RAC design and construction activities for a sustainable performance evaluation of recycled aggregate concrete. Doi: 10.28991/CEJ-2022-08-08-011 Full Text: PDF

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Section: Figure 1 Structural Economic and Environmental Benefits Of R...mentioning

confidence: 99%

Evaluating the Compressive Strength of Recycled Aggregate Concrete Using Novel Artificial Neural Network

et al. 2022

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“…Using the Fourier transform (FFT), the dynamic response in the frequency domain was obtained [20], [21].…”

Section: Determination Of Dynamic Stiffnessmentioning

confidence: 99%

Dynamic stiffness analysis of asphalt mixtures for nondestructive pavement performance assessment

Apaza Apaza,

Vázquez Fernandez,

E. Paje

et al. 2023

Earth Resources and Environmental Remote Sensing/Gis Applications XIV

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Ground-based Non-Destructive Testing (NDT) has been developed as an effective tool for non-invasiveness pavement performance assessment. It is well known that asphalt pavement properties such as density and void content are important parameters that directly affect pavement quality and durability. The dynamic stiffness method is an innovative NDT testing technique which measures dynamic response of the material. In this work, laboratory experimental data about the dynamic stiffness are collected by standardized tests on laboratory Marshall cylindrical bituminous samples. The method performs the analysis of the sinusoidal excitation spectrum (frequency and amplitude) in two random and continuous sweep signals. Both signal are compared for the determination of the bulk density and air void content of the asphalt mixtures. The results show that, by using the dynamic stiffness test, it is possible to generate models with high accuracy in determining the densities and void contents of different bituminous mixtures. Therefore, this method can be potentially considered as an effective non-invasiveness tool for evaluating pavement quality and durability. This research paves the way for the development of a novel procedure introducing several advances implementing a ground-based Non-Destructive Testing (NDT) method based on "dynamic stiffness" for a more effective assets monitoring focused on road pavements.

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“…In recent decades, an extensive literature has 2 of 21 been focused on tire characteristics such as tread shape, carcass, and stiffness patterns and their effects on noise generation [6][7][8]. On the other hand, the impact of the physicomechanical properties of pavements on traffic noise reduction has been investigated, as well as the effects related to surface texture, maximum aggregate size, layer thickness, drainage capacity of the asphalt pavement [9], and other material properties, such as stiffness [10,11] and the shape of the aggregates [12].…”

Section: Introductionmentioning

confidence: 99%

Towards Sustainable Road Pavements: Sound Absorption in Rubber-Modified Asphalt Mixtures

Apaza,

Fernández Vázquez,

Paje

et al. 2024

Infrastructures

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In the last decade, various asphalt paving materials have undergone investigation for sound attenuation purposes. This research aims to delve into the innovative design of sustainable road pavements by examining sound absorption in rubber-modified asphalt mixtures. More specifically, the impact of alternative sustainable materials on the sound absorption of asphalt mixtures across different temperatures, precisely crumb rubber (CR) derived from recycling of end-of-life tires, was investigated. The acoustic coefficient and its Gaussian fit parameters (Peak, BandWidth, and Area Under the Curve) were evaluated. Five different types of asphalt mixtures were studied, encompassing dense, discontinuous, and open mixtures with 0%, 0.75%, and 1.50% CR incorporated through the dry process (DP). The results of sound absorption indicated a slight influence of crumb rubber at temperatures ranging from 10 °C to 60 °C, particularly in mixtures with high void content. On the other hand, as expected, the void content proved to be highly correlated with sound absorption. These findings facilitated the establishment of predictive models that correlate acoustic absorption spectra with the characteristics of asphalt mixtures. As a result, these models will be valuable in the design of the next generation of sound-absorbing pavements.

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Dynamic stiffness of road pavements: Construction characteristics-based model and influence on tire/road noise

Cited by 14 publications

References 30 publications

Evaluating the Compressive Strength of Recycled Aggregate Concrete Using Novel Artificial Neural Network

Evaluating the Compressive Strength of Recycled Aggregate Concrete Using Novel Artificial Neural Network

Dynamic stiffness analysis of asphalt mixtures for nondestructive pavement performance assessment

Towards Sustainable Road Pavements: Sound Absorption in Rubber-Modified Asphalt Mixtures

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