Search results for "Pavement"

showing 10 items of 115 documents

An extension of the fractional model for construction of asphalt binder master curve

2015

Knowledge and prediction of viscoelastic behaviour of asphalt binder is of great interest in order to design asphalt mixtures for civil construction of road and airports with good performances. The capability of a fractional model – requiring a very limited number of parameters – to describe and predict the linear viscoelastic behaviour of asphalt binder subjected to sinusoidal oscillations is investigated. Experimental data of complex modulus, |G*|, and phase angle, δ, are used to validate the proposed constitutive model. Based on the proposed extension of a fractional model, complex modulus isotherms for a range of frequencies can be created simply starting from isochronals at frequency v…

Engineeringcomplex moduluEnvironmental Engineeringmaster curveConstitutive equation0211 other engineering and technologiesModulusMechanical engineeringValue (computer science)020101 civil engineering02 engineering and technologyViscoelasticity0201 civil engineeringfractional model021105 building & constructionRange (statistics)Applied mathematicsSettore ICAR/04 - Strade Ferrovie Ed AeroportiCivil and Structural Engineeringbusiness.industryasphalt binderPhase angleExtension (predicate logic)Asphaltroad pavementbusinessSettore ICAR/08 - Scienza Delle Costruzioni
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Backcalculation of airport pavement moduli and thickness using the Lévy Ant Colony Optimization Algorithm

2016

Interpretation of NDTdata is crucial in any Airport Pavement Management System (APMS), in order to implement strategies to maintain airport pavementssince they allow to estimate their remaining life and related maintenance needs and activities. In this paper, the AntColony Optimization algorithmwasused for backcalculation of pavement moduli from surface deflection data. The algorithm’s performances are illustrated and improvement in prediction quality is demonstrated both in terms of goodness of fitness and computational effort. Moreover, it is proved that the proposed algorithm is also able to predict layer thicknesses, taking into account their variation too.

Engineeringmoduli backcalculation0211 other engineering and technologies020101 civil engineering02 engineering and technologyheuristic algorithm.0201 civil engineeringModuliDeflection (engineering)Nondestructive testing021105 building & constructionSettore ICAR/04 - Strade Ferrovie Ed AeroportiGeneral Materials ScienceFWD dataCivil and Structural Engineeringbusiness.industryAnt colony optimization algorithmsPavement managementBuilding and ConstructionAbstract interpretationRemaining lifeNon Destructive TestingbusinessSettore ICAR/08 - Scienza Delle CostruzioniAlgorithmairport pavement
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Recommendation of RILEM TC237-SIB: protocol for characterization of recycled asphalt (RA) materials for pavement applications

2018

This recommendation proposes an experimental protocol to characterize Recycled Asphalt (RA) materials. The guidelines presented in this document are based on the results of a Round Robin Test (RRT) organized by the RILEM Technical Committee 237-SIB “Testing and characterization of sustainable innovative bituminous materials and systems” and provide information on the testing procedure, data analysis and indications for the preparation of a test report.

Engineeringrecycled aphalt0211 other engineering and technologies02 engineering and technologyConstruction engineeringTest reportTesting Protocol021105 building & construction0502 economics and businessSettore ICAR/04 - Strade Ferrovie Ed AeroportiGeneral Materials ScienceTechnical committeeCivil and Structural EngineeringProtocol (science)050210 logistics & transportationbusiness.industryroad pavement recycled aphalt testing05 social sciencesBuilding and ConstructionBituminous materialstestingCharacterization (materials science)Mechanics of MaterialsAsphaltroad pavementRound Robin Test (RRT)Round robin testbusinessRecycled Asphalt (RA)
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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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SUP&R DST: SUstainable pavement & railways decision support tool

2018

6th International Symposium on Life-Cycle Civil Engineering, IALCCE 2018; Ghent; Belgium; 28 October 2018 through 31 October 2018, GHENT, BELGIQUE, 28-/10/2018 - 31/10/2018; In order to help the decisions makers to efficiently address eco-design for transport infrastructure technologies, a decision support toll (DST) was developed in the scope of the training-through-research programme Sustainable Pavements & Railways Initial Training Network (www.superitn.eu). It consists of a computational platform that implements a conceptual framework developed to quantify sustainability. It comes with a set of sustainability indicators tailored to both road and railway systems as well as several ob…

INFRASTRUCTURE DE TRANSPORTDECISION SUPPORT TOOLRAIL[SPI] Engineering Sciences [physics]Life cycle analysi[SPI]Engineering Sciences [physics]Multi-criteria decision makingPAVEMENTSustainabilityECO CONCEPTIONTransportation infrastructureAIDE A LA DECISIONdecision sup-port toolSUSTAINABLE INFRASTRUCTURE
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THE DIAGNOSIS OF ROAD SURFACE DISTRESSES THROUGH IMAGE-BASED MODELING TECHNIQUES. EXPERIMENTAL SURVEY ON LABORATORY-RUTTED SAMPLES

2015

In the past few years, there has been a drastic increase in the use of image-based modeling (IBM) techniques to create high quality, reality-based 3D models. The low costs of these techniques, as well as their attractive visual quality, have led many researchers and professionals to invest their energy and resources in several tests. IBM is rarely used in the field of road surface distresses as diagnosis is usually performed using other techniques and devices. Road safety statistics reveal that about a half of the total number of accidents occur mainly due to the deterioration of the pavement. The goal of effective road network management is often incompatible with economic resources design…

Image Based Modeling 3d Acquiry road pavementSettore ICAR/04 - Strade Ferrovie Ed AeroportiSettore ICAR/17 - Disegno
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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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Issues and Perspectives in the Application of Different Pavement Design Methods to Life Cycle Cost Analysis

2016

Life cycle costs analysis (LCCA) is an economic evaluation tool that can provide valuable guidance to transportation officials in management decision process. The application of LCCA to pavement management is vital because it permits the selection of the best alternative, based on the analysis of agency costs and user costs, taking into account (after selecting pavement type) different maintenance and rehabilitation (M&R) strategies within the same pavement type. Additionally, environmental costs can be considered. Issues arise when comparing the expected life of the pavement derived according to different pavement design tools, such as the Mechanistic-Empirical pavement Design Guide (M…

Life-cycle cost analysisTransport engineeringEngineeringbusiness.industryLife cycle cost analysiPay adjustmentPavement designMechanistic-empirical pavement design guideSettore ICAR/04 - Strade Ferrovie Ed AeroportiMaintenance and rehabilitationbusinessDesign methodsConstruction engineeringProceedings of the Eighth International Conference on Maintenance and Rehabilitation of Pavements
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