Search results for "Asphalt"

showing 10 items of 151 documents

Rheological properties of asphalt binder modified with waste polyethylene: An interlaboratory research from the RILEM TC WMR

2022

Funding Information: The RILEM Technical Committee on Valorisation of Waste and Secondary Materials for Roads (TC 279-WMR) and the members of Task Group 1 are gratefully acknowledged. The authors would also like to thank Nynas AB and Swiss company Innorecycling for supporting the interlaboratory activity by providing reference neat binder and PE-pellets, PE-shreds additives. The contribution of the Swiss National Science Foundation ( 205121_178991 ) to the Swiss partners is also acknowledged. Funding Information: The RILEM Technical Committee on Valorisation of Waste and Secondary Materials for Roads (TC 279-WMR) and the members of Task Group 1 are gratefully acknowledged. The authors would…

G-R parameterEconomics and EconometricsAsphalt binderWasteAsphalt binder; Dynamic shear rheometer (DSR); G-R parameter; Polyethylene (PE) plastics; Rheological property; WasteSettore ICAR/04 - Strade Ferrovie Ed AeroportiDynamic shear rheometer (DSR)Polyethylene (PE) plasticsRheological propertyAsphalt binder Waste Polyethylene (PE) plastics Dynamic shear rheometer (DSR) Rheological property G -R parameterWaste Management and DisposalResources, Conservation and Recycling
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A machine learning approach to determine airport asphalt concrete layer moduli using heavy weight deflectometer data

2021

An integrated approach based on machine learning and data augmentation techniques has been developed in order to predict the stiffness modulus of the asphalt concrete layer of an airport runway, from data acquired with a heavy weight deflectometer (HWD). The predictive model relies on a shallow neural network (SNN) trained with the results of a backcalculation, by means of a data augmentation method and can produce estimations of the stiffness modulus even at runway points not yet sampled. The Bayesian regularization algorithm was used for training of the feedforward backpropagation SNN, and a k-fold cross-validation procedure was implemented for a fair performance evaluation. The testing p…

Heavy weight deflectometerComputer scienceMaintenanceRunwayGeography Planning and DevelopmentTJ807-830Management Monitoring Policy and LawStiffness modulusTD194-195Machine learningcomputer.software_genreRenewable energy sourcesMachine learningPerformance predictionGE1-350Layer (object-oriented design)Environmental effects of industries and plantsArtificial neural networkRenewable Energy Sustainability and the Environmentbusiness.industryFeed forwardPavement managementBuilding and ConstructionBackpropagationEnvironmental sciencesAsphalt concreteShallow neural networkHeavy weight deflectometer; Machine learning; Maintenance; Runway; Shallow neural network; Stiffness modulusRunwayArtificial intelligencebusinesscomputer
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Image analysis for detecting aggregate gradation in asphalt mixture from planar images

2012

Abstract The mechanical properties of bituminous mixture strongly depend on the gradation of the aggregate that represents the mineral skeleton of the mixture, since for open and gap-graded mixtures, stresses due to vehicles in movement on the pavement are mainly transmitted through their contacts. Internal structure of bituminous mixture is, therefore, of great interest for road and infrastructure engineering and it is appropriate to study it with recently developed image analysis method. The purpose of this study was to finalize an effective analysis of asphalt section image for automatically extracting aggregate gradation without the need of separation of the bitumen from the aggregate. …

Image analysis Segmentation techniques Asphalt mixture Gradation controlMaterials scienceAggregate (composite)business.industryBuilding and ConstructionImage (mathematics)Digital imagePlanarAsphaltSettore ICAR/04 - Strade Ferrovie Ed AeroportiGeneral Materials ScienceSegmentationGradationGeotechnical engineeringProcess engineeringbusinessAnalysis methodCivil and Structural EngineeringConstruction and Building Materials
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Modelling pavement surface characteristics for noise prediction through Bailey-related indicators

2021

The aggregate gradation of bituminous mixtures (hot mix asphalts, HMA) is one of the major factors affecting their surface texture. In turn, this latter is a crucial factor and influences drivers and bystanders’ safety, comfort, and health. Despite this, the design of texture levels still lacks sound bases and dedicated algorithms and this negatively affects the acoustic design of bituminous mixtures. Consequently, the objectives of this study were confined into the derivation of relationships to be used in mix design to predict texture levels. Experimental data were analyzed, in the pursuit of setting up appropriate models and algorithms. Analyses involved the consideration of Bailey-relat…

Infrastructure050210 logistics & transportationhighwaysAggregate (composite)Computer science05 social sciences0211 other engineering and technologiesExperimental data02 engineering and technologySurface finishTexture (music)Industrial engineeringPerformance characteristicsNoiseMechanics of MaterialsAsphaltRoads &amp021105 building & construction0502 economics and businessPavement designSettore ICAR/04 - Strade Ferrovie Ed AeroportiGradationNoiseSet (psychology)Civil and Structural EngineeringInternational Journal of Pavement Research and Technology
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Machine learning techniques to estimate the degree of binder activity of reclaimed asphalt pavement

2022

Part of this research was funded by the project RTI2018-096224-J-I00 that has been cofounded by the Spanish Ministry of Science and Innovation, inside the National Program for Fostering Excellence in Scientific and Technical Research, National Subprogram of Knowledge Generation, 2018 call, in the framework of the Spanish National Plan for Scientific and Technical Research and Innovation 2017-2020, and by the European Union, through the European Regional Development Fund, with the main objective of Promoting technological development, innovation and quality research. Part of this work was financially supported by the Italian Ministry of University and Research with the research Grant PRIN 20…

Intel·ligència artificial - Aplicacions a la medicinaArtificial neural networks:Natural Science Disciplines::Mathematics::Data Analysis [DISCIPLINES AND OCCUPATIONS]:disciplinas de las ciencias naturales::matemáticas::análisis de datos [DISCIPLINAS Y OCUPACIONES]Asphalt pavementsIndirect tensile strengthBuilding and ConstructionHot mix asphaltReclaimed asphalt pavementMechanics of Materials:Mathematical Concepts::Algorithms::Artificial Intelligence::Machine Learning [PHENOMENA AND PROCESSES]Machine learningAprenentatge automàticDegree of binder activity:conceptos matemáticos::algoritmos::inteligencia artificial::aprendizaje automático [FENÓMENOS Y PROCESOS]AsfaltSettore ICAR/04 - Strade Ferrovie Ed AeroportiRecyclingGeneral Materials Science:Enginyeria civil::Infraestructures i modelització dels transports::Transport per carretera [Àrees temàtiques de la UPC]Hot mix asphalt Recycling Reclaimed asphalt pavement Degree of binder activity Machine learning Artificial neural networks Random forest Indirect tensile strengthRandom forestCivil and Structural Engineering
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Bio materials with reclaimed asphalt: from lab mixes properties to non-damaged full scale monitoring and mechanical simulation

2019

Three innovative environmentally friendly pavement materials, designed with 50% of Reclaimed Asphalt and three different biomaterials (2 bio-additivated bitumens and 1 bio-binder), were produced in an industrial plant. These mixes were tested in lab and also at full scale using an Accelerated Pavement Test facility. The asphalt mix viscoelastic properties were measured in lab and their intrinsic viscoelastic response were simulated. These rheological models are used to simulate the pavement mechanical response using both elastic and viscoelastic multilayer codes. Hence, full scale measurement performed during the full scale test at an early stage (without damages) can be compared with these…

JAUGE DE CONTRAINTERECYCLINGRECUPERATION0211 other engineering and technologiesFull scaleBio based02 engineering and technologypavemenViscoelasticity[SPI.MAT]Engineering Sciences [physics]/MaterialsELASTIC SIMULATIONVISCOELASTIC SIMULATIONRESISTANCE (MATER)RheologyBIOMATERIALMATERIAUENROBE BITUMINEUX021105 building & construction0502 economics and businessBIOMATERIAULIANT BITUMINEUXMONITORINGRESISTANCE DES MATERIAUXCivil and Structural Engineering050210 logistics & transportationWaste management05 social sciencesBiomaterialSIMULATION VISCOELASTIQUEEnvironmentally friendlySTRAIN GAUGEDALLAGESIMULATION ELASTIQUEASPHALT MIXPAVEMENTVISCOELASTICITEAsphaltENROBESIMULATIONEnvironmental scienceStructural health monitoringMATERIAU BIOSOURCE
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Uncertainty analysis of life cycle assessment of asphalt surfacings

2023

The Life Cycle Assessment (LCA) of asphalt pavements are associated with significant uncertainty resulting from variability in the quantity and impact of individual components, the quality of data for each component, and variability of asphalt durability. This study presents a framework to quantify and incorporate the uncertainty of LCA and asphalt durability data into LCA of asphalt surfacings. The suggested framework includes: estimating the uncertainty of asphalt production processes by the pedigree matrix method, conducting a deterministic LCA, applying Monte Carlo Simulation (MCS) to estimate the probability density functions (PDFs) of the considered impacts using the uncertainty data,…

Life cycle assessment asphalt uncertainty durability Monte Carlo simulationCivil and Structural Engineering
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ENVIRONMENTAL IMPACT OF BIO-BASED ASPHALT MIXTURES: LIFE CYCLE INVENTORY, LIFE CYCLE ASSESSMENT AND RECOMMENDATIONS

Life cycle assessment bio-based asphalt mixtures bio-binders
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Characterization of rubberized asphalt for railway sub-ballast. Improvements in the mix-design, performance features and rational methodology of HMA_…

2018

(STR) can be incorporated into asphalt mixtures in two different methods, which are referred to as the wet-dry process. The blending of recycled rubber (CRM) with asphalt has been used for years, and several manufacturing processes have been developed in Europe as well as in the USA. The use of a bituminous sub-ballast layer has been pointed out as an exciting alternative to the granular sub-ballast design traditionally applied in most railroad tracks. Frequently, unbound granular materials are replaced by bituminous sub-ballast that provide additional benefits to the subgrade protection. Much research has been conducted on finding other alternative material to be used as a modifier in asph…

MarshallPlusride-Generic mixtures.CompactionTraffic spectrumElasticityRailway Bituminous sub-ballast Granular sub-ballast Hot mix asphalt Superpave Crumb rubberESALRoadTemperature profileSettore ICAR/04 - Strade Ferrovie Ed AeroportiRUMACTensile strainFatigueSwelling and Rebounding effect
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CHARACTERIZATION OF RUBBERIZED ASPHALT FOR RAILWAY SUB-BALLASTS

Tesi di dottorato sotto la supervisione del professore Gaetano di Mino del Dipartimento di Ingegneria Civile di Palermo), come borsista Marie-Curie all'interno del progetto SUPRITN 2013/2017. Il mio lavoro e la linea della ricerca riguarda i conglomerati bituminosi con granulato di gomma per lo strato di sub-ballast nelle linee ferroviarie. L’attività di ricerca comprende il mix-design dell’asfalto con aggiunta di gomma, la caratterizzazione e le prestazioni per la ferrovia in termini di comportamento meccanico e lo smorzamento delle vibrazioni. In particolare con l’avvento dell’alta velocità, diversi studi hanno evidenziato ottime caratteristiche fisico-meccaniche per ciò che riguarda il c…

MarshallPlusride-Generic mixtures.ElasticitàCompactionSuperpaveMiscele ttoballasto bituminoseRigonfiamentoSub-ballastFerrovia; Approccio sperimentali; Sub-ballast; Miscele ttoballasto bituminose; Fenomeni vibrazionali; Mix-design volumetrico; Traffico ferroviario; Temperatura; Bitume; Superpave; Gomma riclicata; Simulazione Traffico; Profilo di temperatura; ESAL; Spettro di traffico; RUMAC; Marshall; Strade; Miscellazione-Compattazione; Elasticità; Sforzo di trazione; Fatica; Rigonfiamento; Miscele HMA; Plusride_Generic dry.ESALGomma riclicataMiscele HMATemperature profileSimulazione TrafficoSettore ICAR/04 - Strade Ferrovie Ed AeroportiRailway Bituminous sub-ballast Granular sub-ballast Hot mix asphalt Superpave Crumb rubber; Temperature profile; ESAL; Traffic spectrum; RUMAC; Marshall; Roads; Compaction; Elasticity; Tensile strain; Fatigue; Swelling and Rebounding effect; Plusride-Generic mixtures.Traffico ferroviarioMiscellazione-CompattazioneTensile strainFatigueSwelling and Rebounding effectFenomeni vibrazionaliFaticaSforzo di trazionePlusride_Generic dry.Traffic spectrumTemperaturaStradeElasticitySpettro di trafficoRailway Bituminous sub-ballast Granular sub-ballast Hot mix asphalt Superpave Crumb rubberApproccio sperimentaliRoadProfilo di temperaturaMix-design volumetricoRUMACFerroviaBitume
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