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RISS 인기검색어
- 검색키워드
- 저자 : Zhanping You (검색결과 3 건)
- 무료
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Viscoelastic Fatigue Damage Properties of Asphalt Mixture with Different Aging Degrees
Songtao Lv,Chaochao Liu,Jianlong Zheng,Zhanping You,Lingyun You 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.6
In order to reveal the effects of aging on fatigue damage evolution pattern of asphalt mixture, and to reveal the fatigue damagepatterns of asphalt pavement during its service life more accurately, the viscoelastic fatigue damage model for the aged asphaltmixtures was proposed based on the Burgers viscoelastic model. The dissipation energy was taken as the damage variable, and thedirect tension fatigue tests for asphalt mixture in five different aging degrees were conducted. The viscoelastic parameters of the agedasphalt mixtures were obtained.The calculationmethod of the cumulative fatigue damage was proposed, which considers the agingeffects. Moreover, the critical fatigue damage degree and fatigue life calculation equations were derived by employing the fatiguedamage model, which were calculated and compared. The calculation errors range from 3% to 18%, which was within an acceptableerror range of 30%. The research results show that the aging has a prominent impact on fatigue properties of asphalt mixtures, whichcould be illustrated by the change of the parameters of the viscoelastic fatigue damage model for the aged asphalt mixtures. Theprediction precision of fatigue life is acceptable for using the proposed viscoelastic fatigue damage model.
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A Combinational Prediction Model for Transverse Crack of Asphalt Pavement
Chen Zhang,Hainian Wang,Xu Yang,Zhanping You 대한토목학회 2018 KSCE Journal of Civil Engineering Vol.22 No.6
Reliable transverse crack prediction can benefit the design and maintenance and improve the reliability of field investigation forasphalt pavement in permafrost regions of Qinghai-Tibet plateau. This study adopted the crack prediction model in the newlydeveloped pavement design method named Pavement ME Design (PMED) and the modified grey predictive model (GM (1, 1)) topredict the transverse crack of asphalt pavement in permafrost regions. The complementary advantages for the two models based onthe weight distribution theory were discussed, and a combined prediction model (PME-DGM combination model) taking accountinto region characteristics was developed. Finally, the applicability of combined prediction model was analyzed. The result showedthat, the predictive accuracy of PME-DGM combination model established by the error sum of squares reciprocal method was thehighest, the best weight allocations for each sub-model were LNCH = 0.601 and LDGM = 0.399, and the combination model can beapplied in the permafrost region involved in this paper; The combination model is more appropriate in predicting the developmenttrend of transverse crack of project-level asphalt pavement in permafrost regions; For PMED predictive model, this study raised amodified method base on a third-party model (DGM (1,1), and the result showed that the method worked well in the permafrostregion of Qinghai-Tibet plateau.
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Effect of Water Absorption and Loss Characteristics of Fine Aggregates on Aggregate-Asphalt Adhesion
Jie Ji,Yang Dong,Ran Zhang,Zhi Suo,Chenwei Guo,Xu Yang,Zhanping You 대한토목학회 2021 KSCE Journal of Civil Engineering Vol.25 No.6
This study aims to investigate the effect of aggregate water absorption and loss characteristics on aggregate-asphalt adhesion. Lab tests were designed to analyze the water absorption and loss characteristics of limestone, basalt. and steel slag fine aggregates with different particle sizes under various temperatures and humidity conditions. Meanwhile, the low temperature nitrogen adsorption test, combined with the Brunauer, Emmett and Teller (BET) theory and Barret, Joyner and Halend (BJH) model, were used to calculate the specific surface area and pore size distribution of aggregate. Moreover, the asphalt-aggregate adhesion was evaluated by the net adsorption test. The results indicated that the change trends of water absorption and loss for the aggregates exhibited two stages. In the first stage, the amounts of water absorption and loss of aggregates were large and their change rates were high, while in the second stage, an opposite trend was observed. Humidity had the greatest influence on the water absorption and loss of aggregates, followed by aggregate particle size, contact time, temperature, and aggregate type. The smaller-sized aggregates had greater specific surface area, which led to a higher sensitivity to temperature and humidity changes. In comparison, the 0.3 mm-sized aggregate had a large capillary energy inside the pores, and it was the most sensitive to moisture. The steel slag aggregate had the strongest adhesion with asphalt, followed by the limestone aggregate, and the worst was basalt aggregate.
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