Incorporation of Additives and Fibers in Porous Asphalt Mixtures: A Review

Despite the numerous benefits for preserving the hydrological cycle, permeable pavement systems (PPSs) found their major application in parking spots and for light traffic scenarios due to their limited durability and strength. To make the PPSs suitable for heavy traffic conditions without significant distresses, research is shifting toward the adoption of novel binders and additives for designing multifunctional porous asphalt mixtures which make up the surface course of PPSs. Certain additives are well known for enhancing the durability of dense graded asphalt mixtures and improving fatigue and rutting resistance. However, the studies on the influence of additives on abrasion resistance and binder draindown, which are the common problems in porous asphalt mixtures (PAMs), are still not well established. This paper summarizes best practices performed on PAMs and recommends possible future research directions for its improvement. Particular emphasis is placed on strength and resilience of PAMs by incorporating additives like nanosilica, crumb rubber, warm-mix additives, fibers (such as cellulose, glass, steel, and synthetic fibers), and some eco-friendly materials. It was found that different additives seem to have different effects on the properties of PAMs. Moreover, the combination of additives has synergistic benefits for the performance of PAMs, especially in urban pavements.This project is funded by SAFERUP! from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 765057

CIDMP: Completely Interpretable Detection of Malaria Parasite in Red Blood Cells using Lower-dimensional Feature Space

Predicting if red blood cells (RBC) are infected with the malaria parasite is an important problem in Pathology. Recently, supervised machine learning approaches have been used for this problem, and they have had reasonable success. In particular, state-of-the-art methods such as Convolutional Neural Networks automatically extract increasingly complex feature hierarchies from the image pixels. While such generalized automatic feature extraction methods have significantly reduced the burden of feature engineering in many domains, for niche tasks such as the one we consider in this paper, they result in two major problems. First, they use a very large number of features (that may or may not be relevant) and therefore training such models is computationally expensive. Further, more importantly, the large feature-space makes it very hard to interpret which features are truly important for predictions. Thus, a criticism of such methods is that learning algorithms pose opaque black boxes to its users, in this case, medical experts. The recommendation of such algorithms can be understood easily, but the reason for their recommendation is not clear. This is the problem of non-interpretability of the model, and the best-performing algorithms are usually the least interpretable. To address these issues, in this paper, we propose an approach to extract a very small number of aggregated features that are easy to interpret and compute, and empirically show that we obtain high prediction accuracy even with a significantly reduced feature-space.Comment: Accepted in The 2020 International Joint Conference on Neural Networks (IJCNN 2020) At Glasgow (UK

Laboratory Characterization of Porous Asphalt Mixtures with Aramid Fibers

ABSTRACT: Recent studies have shown that fibers improve the performance of porous asphalt mixtures. In this study, the influence of four different fibers, (a) regular aramid fiber (RegAR), (b) aramid fiber with latex coating (ARLat), (c) aramid fiber with polyurethane coating (ARPoly), (d) aramid fiber of length 12 mm (AR12) was evaluated on abrasion resistance and toughness of the mixtures. The functional performance was estimated using permeability tests and the mechanical performance was evaluated using the Cantabro test and indirect tensile strength tests. The parameters such as fracture energy, post cracking energy, and toughness were obtained through stress-strain plots. Based on the analysis of results, it was concluded that the addition of ARLat fibers enhanced the abrasion resistance of the mixtures. In terms of ITS, ARPoly and RegAR have positively influenced mixtures under dry conditions. However, the mixtures with all aramid fibers were found to have adverse effects on the ITS under wet conditions and energy parameters of porous asphalt mixtures with the traditional percentages of bitumen in the mixture used in Spain (i.e., approximately 4.5%).This work and the APC are funded by SAFERUP! Project, from the European Union’s Horizon 2020 research and innovation program under, the Marie Skłodowska-Curie grant agreement No. 765057

Critical assessment of new polymer-modified bitumen for porous asphalt mixtures

ABSTARCT: New experimental polymer-modified bitumen with a high-vinyl content polymer was fabricated for porous asphalt (PA) mixtures. The bitumen with maximum stability was achieved using storage stability, gelation criteria and physical bitumen tests. A dynamic shear rheometer was used to compare the complex modulus, number of fatigue cycles, yield stress, and non-recoverable creep compliance of the experimental bitumen with a reference virgin bitumen 50/70 and a PMB 45/80-65 binder. PA mixtures were also designed to analyze the abrasion resistance and binder drainage characteristics. It was concluded that the experimental bitumen with 4.5% polymer content showed higher elastic response, better fatigue resistance, and improved rutting behavior than the reference PMB. PA mixtures with the new experimental bitumen exhibited higher abrasion resistance, but underwent higher binder drainage, which was addressed by the incorporation of aramid pulp and glass-hybrid fibers

Multi-Criteria Selection of Additives in Porous Asphalt Mixtures Using Mechanical, Hydraulic, Economic, and Environmental Indicators

Porous asphalt (PA) mixtures are more environmentally friendly but have lower durability than dense-graded mixtures. Additives can be incorporated into PA mixtures to enhance their mechanical strength; however, they may compromise the hydraulic characteristics, increase the total cost of pavement, and negatively affect the environment. In this paper, PA mixtures were produced with 5 different types of additives including 4 fibers and 1 filler. Their performances were compared with the reference mixtures containing virgin bitumen and polymer-modified bitumen. The performance of all mixes was assessed using: mechanical, hydraulic, economic, and environmental indicators. Then, the Delphi method was applied to compute the relative weights for the parameters in multi-criteria decision-making methods. Evaluation based on distance from average solution (EDAS), technique for order of the preference by similarity to ideal solution (TOPSIS), and weighted aggregated sum product assessment (WASPAS) were employed to rank the additives. According to the results obtained, aramid pulp displayed comparable and, for some parameters such as abrasion resistance, even better performance than polymer-modified bitumen, whereas cellulose fiber demonstrated the best performance regarding sustainability, due to economic and environmental benefits.This work and the APC are funded by SAFERUP! Project, from the European Union’s Horizon 2020 research and innovation program under, the Marie Skłodowska-Curie grant agreement No. 765057

Study of the effect of polyolefin-aramid fibers on PA mixture

The present research seeks to investigate the performance of a PA mixture reinforced with polyolefin-aramid fibers. The functional and mechanical performance of the mixture was assessed by different volumetric and mechanical tests including total air voids, interconnected air voids, Cantabro particle loss in dry and wet conditions and binder drainage test.This research is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 769373

Azimuthal anisotropy of charged jet production in root s(NN)=2.76 TeV Pb-Pb collisions

We present measurements of the azimuthal dependence of charged jet production in central and semi-central root s(NN) = 2.76 TeV Pb-Pb collisions with respect to the second harmonic event plane, quantified as nu(ch)(2) (jet). Jet finding is performed employing the anti-k(T) algorithm with a resolution parameter R = 0.2 using charged tracks from the ALICE tracking system. The contribution of the azimuthal anisotropy of the underlying event is taken into account event-by-event. The remaining (statistical) region-to-region fluctuations are removed on an ensemble basis by unfolding the jet spectra for different event plane orientations independently. Significant non-zero nu(ch)(2) (jet) is observed in semi-central collisions (30-50% centrality) for 20 <p(T)(ch) (jet) <90 GeV/c. The azimuthal dependence of the charged jet production is similar to the dependence observed for jets comprising both charged and neutral fragments, and compatible with measurements of the nu(2) of single charged particles at high p(T). Good agreement between the data and predictions from JEWEL, an event generator simulating parton shower evolution in the presence of a dense QCD medium, is found in semi-central collisions. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe