| 引用本文: | 赵倩倩,程培峰,魏玉伟,周兴业.运用MEPDG建立季冻区水泥路面IRI预测修正模型[J].哈尔滨工业大学学报,2018,50(11):171.DOI:10.11918/j.issn.0367-6234.201709056 |
| ZHAO Qianqian,CHENG Peifeng,WEI Yuwei,ZHOU Xingye.IRI predictive revised model for cement pavement in seasonal frozen region using MEPDG[J].Journal of Harbin Institute of Technology,2018,50(11):171.DOI:10.11918/j.issn.0367-6234.201709056 |
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| 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.
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| 关键词: MEPDG IRI 预测修正模型 SPSS 线性相关 |
| DOI：10.11918/j.issn.0367-6234.201709056 |
| 分类号:U418.6 |
| 文献标识码:A |
| 基金项目:黑龙江省交通厅重点科技项目(HLJ2015-10) |
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| IRI predictive revised model for cement pavement in seasonal frozen region using MEPDG |
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ZHAO Qianqian1,2,CHENG Peifeng1,WEI Yuwei1,ZHOU Xingye3
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（1. Civil Engineering College, Northeast Forestry University, Harbin 150040, China; 2. School of Civil and Architectural Engineering, Heilongjiang Institute of Technology, Harbin 150050,China; 3. China Academy of Transportation Sciences, Beijing 100029, China）
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| 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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| Key words: MEPDG IRI prediction revised model SPSS linear correlation |
