A Review on Acoustic and Skid Resistance Solutions for Road Pavements

Callai, Sergio Copetti; Sangiorgi, Cesare

doi:10.3390/infrastructures6030041

Cited by 22 publications

(5 citation statements)

References 57 publications

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“…The artificial aggregate was produced using 3D-printed molds that guarantee a specific shape and size that, according to [31,44], could have an interesting behavior in friction and acoustic prospects. The mixtures were prepared as described in Figure 3.…”

Section: Artificial Aggregate Productionmentioning

confidence: 99%

A Preliminary Laboratory Evaluation of Artificial Aggregates from Alkali-Activated Basalt Powder

et al. 2022

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The widespread use of natural aggregates is one of the main causes of the depletion of natural resources, as aggregates are constituents of several construction materials. Alternatively, it is, today, proven to be feasible to use mining tailings, either natural or recycled materials, to produce artificial aggregates through specific processes. A possible way to produce artificial aggregate is through the alkali activation of the powdered material in a process called geopolymerization. This study proposes to use a basalt powder and two different metakaolins as precursors for the production of an alkali-activated artificial aggregate, with a specific shape and size achieved by using 3D-printed molds. The experimental aggregates were evaluated using traditional tests for natural aggregates, such as resistance to compression, specific density and resistance to abrasion and fragmentation. Furthermore, the material was chemically analyzed in order to evaluate the geopolymerization process promoted by the two adopted metakaolins. The physical tests showed that artificial aggregates do not perform well in terms of resistance to wear and fragmentation, which can be improved. However, they revealed promising results in terms of skid, polishing and micro-texture.

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Section: Artificial Aggregate Productionmentioning

confidence: 99%

A Preliminary Laboratory Evaluation of Artificial Aggregates from Alkali-Activated Basalt Powder

et al. 2022

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“…They are a usual solution for pavement maintenance, acting as a protective surface course that can address issues related to skid resistance, raveling, or oxidation on structurally sound pavements, improving the road surface characteristics [5,11,12]. Microsurfacing is also employed to correct the shape or profile rutted wheel paths and obtain a faster traffic opening [13], with a 40% reduction in the number of original rutting and substantial increases in the friction characteristics of the pavement being reported in previous works [14].…”

Section: Introductionmentioning

confidence: 99%

Development and Application of a Microsurfacing Mix Design Method to Assess the Influence of the Emulsion Type

et al. 2023

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Microsurfacing asphalt mixtures are a preventive maintenance technology comprising the application of a slurry (produced with a modified asphalt emulsion), aggregate, filler, and water on top of an existing pavement at ambient temperature. Although it is a widely used technology, further studies on the mix design procedures are necessary to ensure an adequate composition. Thus, this study contributes to developing an improved mix design procedure for microsurfacing asphalt mixtures. Different mixtures were prepared, and the influence of the type and amount of asphalt emulsion and the amount of added water and filler (cement) on the characteristics of the mixture were evaluated. Two preliminary tests, referred to as the “pizza test” and the “ball test”, were proposed to determine the initial proportions of added water and cement in the mixture, respectively. Then, consistency, cohesion, and shaking abrasion tests were performed to determine the optimum content of each component and evaluate their influence on the mixture characteristics. The results showed that these tests are essential to optimize the mix composition, even though it was found that the mix design of microsurfacings is a complex task because the mixture is a system with chemical interactions strongly influenced by its composition.

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“…The need for effective and automatic sound classification systems is on the rise, as its relevance cannot be underestimated in our everyday life. Automatic sound classification technologies are widely applied in surveillance systems [6], voice assistants [7], chatbots [8], smart safety devices [9], and in different real-world environments, such as engineering [10], industrial [11], domestic [12], urban [13], road [14], and natural [15].…”

Section: Introductionmentioning

confidence: 99%

Data Augmentation and Deep Learning Methods in Sound Classification: A Systematic Review

et al. 2022

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The aim of this systematic literature review (SLR) is to identify and critically evaluate current research advancements with respect to small data and the use of data augmentation methods to increase the amount of data available for deep learning classifiers for sound (including voice, speech, and related audio signals) classification. Methodology: This SLR was carried out based on the standard SLR guidelines based on PRISMA, and three bibliographic databases were examined, namely, Web of Science, SCOPUS, and IEEE Xplore. Findings. The initial search findings using the variety of keyword combinations in the last five years (2017–2021) resulted in a total of 131 papers. To select relevant articles that are within the scope of this study, we adopted some screening exclusion criteria and snowballing (forward and backward snowballing) which resulted in 56 selected articles. Originality: Shortcomings of previous research studies include the lack of sufficient data, weakly labelled data, unbalanced datasets, noisy datasets, poor representations of sound features, and the lack of effective augmentation approach affecting the overall performance of classifiers, which we discuss in this article. Following the analysis of identified articles, we overview the sound datasets, feature extraction methods, data augmentation techniques, and its applications in different areas in the sound classification research problem. Finally, we conclude with the summary of SLR, answers to research questions, and recommendations for the sound classification task.

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A Review on Acoustic and Skid Resistance Solutions for Road Pavements

Cited by 22 publications

References 57 publications

A Preliminary Laboratory Evaluation of Artificial Aggregates from Alkali-Activated Basalt Powder

A Preliminary Laboratory Evaluation of Artificial Aggregates from Alkali-Activated Basalt Powder

Development and Application of a Microsurfacing Mix Design Method to Assess the Influence of the Emulsion Type

Data Augmentation and Deep Learning Methods in Sound Classification: A Systematic Review

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