IRI predictive revised model for cement pavement in seasonal frozen region using MEPDG

ZHAO Qianqian; CHENG Peifeng; WEI Yuwei; ZHOU Xingye

doi:10.11918/j.issn.0367-6234.201709056

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IRI predictive revised model for cement pavement in seasonal frozen region using MEPDG

更新时间：2026-10-19

- IRI predictive revised model for cement pavement in seasonal frozen region using MEPDG
- Vol. 50, Issue 11, Pages: 171-177(2018)
- 作者机构：
  
  1. 东北林业大学土木工程学院,哈尔滨,150040
  2. Civil Engineering College, Northeast Forestry University,Harbin,China,150040
  3. 黑龙江工程学院土木与建筑工程学院,哈尔滨,150050
  4. School of Civil and Architectural Engineering, Heilongjiang Institute of Technology,Harbin,China,150050
  5. 交通运输部公路科学研究院,北京,100029
- 作者简介：
- 基金信息：
- DOI：10.11918/j.issn.0367-6234.201709056
  CLC： U418.6
- Published：2018
- 稿件说明：
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ZHAO Qianqian, CHENG Peifeng, WEI Yuwei, et al. IRI predictive revised model for cement pavement in seasonal frozen region using MEPDG[J]. 2018, 50(11): 171-177.
DOI：

ZHAO Qianqian, CHENG Peifeng, WEI Yuwei, et al. IRI predictive revised model for cement pavement in seasonal frozen region using MEPDG[J]. 2018, 50(11): 171-177. DOI： 10.11918/j.issn.0367-6234.201709056.

摘要

为解决季冻区水泥路面平整度预测问题，基于MEPDG构建了季冻区水泥路面国际平整度指数(IRI)预测修正模型.该模型充分考虑了交通状况、气候条件和道路各层材料的特性，在原有预测模型基础上对CRK、TFAULT、SPALL和SF 4个指标变化趋势进行分析并与IRI相关性进行了验证，利用SPSS分析软件提出适用于季冻区特点的水泥路面平整度指数预测修正模型，结合黑龙江省水泥路面调查数据进行验证.结果表明：气候、交通、材料参数均对构成预测国际平整度指数的4个指标CRK、TFAULT、SPALL和SF有显著影响；且4个指标和国际平整度指数线性拟合可靠度高；利用交通量、降水、降雨、潮湿天数、冻融循环次数，路面材料性能等参数可对季冻区水泥路面国际平整度指数进行预测.提出的预测修正模型预测的精确度高，具有良好的实用性和较高的预测性能.

Abstract

To solve the problem of flatness prediction of cement pavement in seasonal frozen region

the international roughness index (IRI) prediction revised model of cement pavement in frozen season was constructed using MEPDG. The model takes into account the traffic conditions

climatic conditions

and the characteristics of the materials of the pavement layers. The trends of CRK

TFAULT

SPALL

and SF were analyzed and verified with IRI correlation on the basis of the original prediction model. SPSS analysis software was used to obtain the prediction revised model of cement pavement roughness index in seasonal frozen region. The cement pavement survey data of Heilongjiang Province was used to verify this model. The results show that climate

traffic

and material parameters had significant influence on the four indexes CRK

TFAULT

SPALL

and SF. These indicators and international flatness index were linearly fitted with high reliability. The number of traffic

precipitation

rainfall

wet days

the number of freeze-thaw cycles

and the performance of pavement materials can be used to predict the international flatness index of cement pavement in seasonal frozen region. The accuracy of the model was high

with good practicability and high predictive performance.

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