国家高新技术企业
杭州市西湖区优秀创新人才“325”计划入选单位
杭州市高层次人才项目

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Construction and Building Materials

ISSN: 0950-0618

官网: https://www.sciencedirect.com/journal/construction-and-building-materials

出版商: Elsevier

Title Scholar cited Year Review Cycle Accept Cycle

Kernel machines and firefly algorithm based dynamic modulus prediction model for asphalt mixes considering aggregate morphology

DOI:10.1016/j.conbuildmat.2017.10.133

Received:2017-06-26 ; Revised:2017-09-15 ; Accepted:2017-10-31 ; Online:2017-11-06

- 2018 2.2 4.2
Connections between chemical composition and rheology of aged base asphalt binders during repeated freeze-thaw cycles

DOI:10.1016/j.conbuildmat.2017.10.097

Received:2017-04-25 ; Revised:2017-10-23 ; Accepted:2017-10-23 ; Online:2017-11-06

- 2018 5.6 6

The fungistatic properties and potential application of by-product fly ash from fluidized bed combustion

DOI:10.1016/j.conbuildmat.2017.10.076

Received:2017-04-13 ; Revised:2017-09-13 ; Accepted:2017-10-18 ; Online:2017-11-06

- 2018 4.6 6.3
Correlation between resilient modulus (MR) and constrained modulus (MC) values of granular materials

DOI:10.1016/j.conbuildmat.2017.10.047

Received:2017-07-02 ; Revised:2017-09-15 ; Accepted:2017-10-08 ; Online:2017-11-06

- 2018 2 3.3
Development of sustainable concrete using recycled coarse aggregate and ground granulated blast furnace slag

DOI:10.1016/j.conbuildmat.2017.10.118

Received:2017-02-21 ; Revised:2017-10-21 ; Accepted:2017-10-27 ; Online:2017-11-06

- 2018 7.6 8.3

Algorithm to process the stepped frequency radar signal for a thin road surface application

DOI:10.1016/j.conbuildmat.2017.10.075

Received:2016-11-22 ; Revised:2017-10-11 ; Accepted:2017-10-17 ; Online:2017-11-06

- 2018 10.3 11

Influence of soiling phenomena on air-void microstructure and acoustic performance of porous asphalt pavement

DOI:10.1016/j.conbuildmat.2017.10.069

Received:2017-02-07 ; Revised:2017-10-09 ; Accepted:2017-10-14 ; Online:2017-11-05

- 2018 7.7 8.3

Performance verification of various bulk density measurement methods for open- and gap-graded asphalt mixtures using X-ray computed tomography

DOI:10.1016/j.conbuildmat.2017.10.090

Received:2017-07-29 ; Revised:2017-09-24 ; Accepted:2017-10-19 ; Online:2017-11-05

- 2018 1.4 2.7
Artificial neural networks approach to predicting rut depth of asphalt concrete by using of visco-elastic parameters

DOI:10.1016/j.conbuildmat.2017.10.088

Received:2017-05-10 ; Revised:2017-10-07 ; Accepted:2017-10-19 ; Online:2017-11-05

- 2018 4.5 5.4

Integrating geomatic approaches, Operational Modal Analysis, advanced numerical and updating methods to evaluate the current safety conditions of the historical Bôco Bridge

DOI:10.1016/j.conbuildmat.2017.10.084

Received:2017-06-30 ; Revised:2017-10-12 ; Accepted:2017-10-19 ; Online:2017-11-05

- 2018 3 3.7