Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

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

Methodology for the development of a new Sustainable Infrastructure Rating System for Developing Countries (SIRSDEC)

The improvement of infrastructures in developing countries has become a priority for the most advanced economies, which have founded a broad range of international development organizations to undertake infrastructure projects worldwide. Infrastructure is the key driver that can accelerate the balance among the economic, social and environmental aspects forming the Triple Bottom Line (TBL) in these countries. Given the lack of appropriate tools to ensure the achievement of this goal, this paper describes the methodology conceived for the development of a Sustainable Infrastructure Rating System (SIRSDEC) aimed at promoting the design, construction and operation of sustainable infrastructure projects in these geographical areas. SIRSDEC is structured into a hierarchical decision-making tree consisting of three levels of elements (requirements, criteria and indicators) selected to assess infrastructure systems according to sustainability principles. The methodology on which SIRSDEC is based combines the action of two multi-criteria decision-making methods (MCDM) such as the Analytical Hierarchy Process (AHP) and the Integrated Value Model for Sustainable Assessment (MIVES). AHP is proposed to weight the elements forming the decision-making tree after processing the opinions provided by a group of international experts regarding the importance of requirements, criteria and indicators, whilst MIVES is suggested to value infrastructure projects according to their contribution to the TBL. The article emphasizes the added value provided by the combination of AHP and MIVES in the design of an ad-hoc rating system aimed at fostering the implementation of sustainable infrastructure projects in developing countries

Application of the Sustainable Infrastructure Rating System for Developing Countries (SIRSDEC) to a case study

A large amount of international public and private not-for-profit organizations strives to enhance the conditions of less developed economies under the flagship of sustainability throughout a wide range of infrastructure projects. However, the results are uncertain. Sustainable development in poorer countries requires effective frameworks to ensure the balanced consideration of social, economic and environmental dimensions. This paper discusses the application of the Sustainable Infrastructure Rating System for Developing Countries (SIRSDEC) to a mining infrastructure project located in Peru, in order to validate the methodology developed for this framework. The opinions returned from a questionnaire addressed to international experts according to the pairwise comparison scale of the Analytic Hierarchy Process (AHP) method were processed to obtain the weights of the elements forming the decision-making tree of SIRSDEC. The Integrated Value Model for Sustainable Assessment (MIVES) was introduced to assess infrastructure projects through the definition of value functions for each sustainability indicator, which enables the integration of variables measured in different units into a standardized value index. The weights obtained for SIRSDEC reflected the balance of the three pillars of sustainability, with a slight predominance of the social dimension. The case study highlighted the contribution of the new system to identify key sustainability issues which were omitted in the original project and posed several actions to improve community?s perception and facilitate the development of the project

Machine learning algorithms for monitoring pavement performance

ABSTRACT: This work introduces the need to develop competitive, low-cost and applicable technologies to real roads to detect the asphalt condition by means of Machine Learning (ML) algorithms. Specifically, the most recent studies are described according to the data collection methods: images, ground penetrating radar (GPR), laser and optic fiber. The main models that are presented for such state-of-the-art studies are Support Vector Machine, Random Forest, Naïve Bayes, Artificial neural networks or Convolutional Neural Networks. For these analyses, the methodology, type of problem, data source, computational resources, discussion and future research are highlighted. Open data sources, programming frameworks, model comparisons and data collection technologies are illustrated to allow the research community to initiate future investigation. There is indeed research on ML-based pavement evaluation but there is not a widely used applicability by pavement management entities yet, so it is mandatory to work on the refinement of models and data collection methods

Grapa de fijación de cables

Solicitud: U200301272 (23.05.2003)Nº Pub. de Solicitud: ES1054792U (16.08.2003)Nº de Modelo de Utilidad: ES1054792Y (01.12.2003

Evaluation of existing sustainable infrastructure rating systems for their application in developing countries

Several sustainable building rating systems were created worldwide during the last decades due to economic growth and the significance of environmental impact associated with the building industry. Similar infrastructure rating tools have started to be developed and implemented, being highly necessary to promote its development. Even though the existing sustainable infrastructure rating systems are focused on advanced economies, growing environmental concerns are increasing the need for new systems in the Developing World. This research analyses some of the mainstream infrastructure rating frameworks such as Envision (USA), Civil Engineering Environmental Quality (CEEQUAL) assessment (UK) and Infrastructure Sustainability (IS) Rating Tool (Australia) from the perspective of the Triple Bottom Line (economy, environment and society), in order to determine the effectiveness of their application in the context of the least developed countries. The analysis revealed that the three tools are biased towards the environmental dimension and are mainly oriented to developed countries. Consequently, the foundations on which these systems are based need to be further developed and enhanced to be of real relevance in poorer nations by balancing the weight of sustainable pillars, incorporating effective management guidelines and development goals set by United Nations declarations, and considering impacts beyond the single project framework

Thermal suspectability analysis of the reuse of fly ash from cellulose industry as contribution filler in bituminous mixtures

The increased population has accelerated pavement deterioration of and boosted production of residues, generating a constant environmental problem. One of the main problems of pavements is a failure to develop union between bituminous mastic ligand and aggregate. The following study evaluates the use of ash from cellulose incineration as a contribution filler to improve thermal susceptibility of pavements in different climatic zones. The applied methodology for dosage was based on volumetric criteria and state curves. The obtained results showed that reusing this residue in determined conditions (Cv/Cs???1) offers lower wear loss to 35% of temperatures between ?10 and 60?°C, due to the Cv/Cs?=?0.75 ratio that maximizes the cohesive properties of the mixture. Therefore, we showed that this type of industry residue can be reused without complication in zones of certain climatic criteria and that it provides improved properties to the asphalt mix compared to conventional mixes

Laboratory and Statistical Analysis of the Fatigue Response of Self-Healing Asphalt Mixtures Containing Metal By-Products

ABSTRACT: Fatigue is one of the main forms of deterioration in asphalt mixtures, endangering their service life due to the progressive appearance and expansion of cracks. A sustainable approach to increase the lifetime of asphalt pavement has been found in self-healing technology, especially if boosted with metal by-products due to their economic and environmental interest. Under these circumstances, this research addressed the fatigue behavior of self-healing asphalt mixtures including industrial sand blasting by-products obtained from sieving and aspiration processes. Hence, a uniaxial fatigue test was carried out to determine whether these experimental mixtures can provide a similar response to that of a reference asphalt concrete (AC-16). This analysis was undertaken with the support of descriptive and inferential statistics, whose application proved the absence of significant differences in the fatigue performance of self-healing experimental mixtures with respect to conventional asphalt concrete. These results suggest that designing self-healing mixtures with metal by-products is a sustainable approach to increase the lifetime of asphalt pavements, while contributing to the circular economy through diverse economic and environmental benefits.This research was funded by Spanish Ministry of Economy and Competitiveness with funds from the State General Budget (PGE) and the European Regional Development Fund (ERDF), grant number BIA2016-77372-R

Self-Healing Capacity of Asphalt Mixtures Including By-Products Both as Aggregates and Heating Inductors.

Major advances have been achieved in the field of self-healing by magnetic induction in which the addition of metallic particles into asphalt mixtures enables repairing their own cracks. This technology has already been proven to increase the life expectancy of roads. Nevertheless, its higher costs in comparison with conventional maintenance caused by the price of virgin metallic particles still makes it unattractive for investment. This research aimed at making this process economically accessible as well as environmentally efficient. To this end, an intense search for suitable industrial by-products to substitute both the virgin metal particles and the natural aggregates forming asphalt mixtures was conducted. The set of by-products used included sand blasting wastes, stainless shot wastes, and polished wastes as metallic particles and other inert by-products as aggregates. The results demonstrated that the by-products were adequately heated, which leads to satisfactory healing ratios in comparison with the reference mixture.This paper was financed by the Spanish Ministry of Economy and Competitiveness with funds from the State General Budget (PGE) and the European Regional Development Fund (ERDF) through the research project SIMA+ (Ref. BIA2016-77372-R)