吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (7): 2067-2077.doi: 10.13229/j.cnki.jdxbgxb.20211010

• 交通运输工程·土木工程 • 上一篇    

基于多元非线性回归的智能压实关键参数最优解

马涛(),马源,黄晓明   

  1. 东南大学 交通学院,南京 211189
  • 收稿日期:2021-10-05 出版日期:2023-07-01 发布日期:2023-07-20
  • 作者简介:马涛(1981-),男,教授,博士.研究方向:功能性路面材料与道路智能化建设.E-mail: matao@seu.edu.cn
  • 基金资助:
    国家重点研发计划项目(2020YFB1600102);国家自然科学基金优秀青年科学基金项目(51922030);山东省交通科技项目(2018B51)

Optimal combination of key parameters of intelligent compaction based on multiple nonlinear regression

Tao MA(),Yuan MA,Xiao-ming HUANG   

  1. School of Transportation,Southeast University,Nanjing 211189,China
  • Received:2021-10-05 Online:2023-07-01 Published:2023-07-20

摘要:

通过对有限元数值仿真软件进行二次开发,实现数值仿真精细化建模并设计所需工况,提供智能压实最优关键参数组合的基础数据,并通过现场试验验证其准确性。在此基础上,通过多元非线性回归的方法,对影响路基压实度参数进行拟合。通过线性搜索的方法,获取能达到最大压实质量对应参数。结果表明:当碾压速度为4 m/s、碾压遍数为2遍时,对应的最终压实度最小,为0.878;当碾压速度为1 m/s、碾压遍数为4遍时,对应的最终压实度最大,为0.955。本文得到如下结论:在常见的压实施工参数范围内,达到最优压实度的施工参数组合如下:碾压速度为1.3 m/s,碾压遍数为4遍。

关键词: 道路工程, 智能压实, 反馈调节机制, 有限元二次开发, 最终压实度, 最优参数组合

Abstract:

In this paper, through the secondary development of the finite element numerical simulation software, the numerical simulation was refined to model and designed the working conditions, which provide the basic data of the optimal combination of key parameters, and verified its accuracy through field tests. On this basis, the parameters affecting compaction quality were fitted by multiple nonlinear regression method. Then, the construction parameters corresponding to the maximum compaction quality can be obtained by linear search method. The results show that the rolling speed of 4 m/s, rolling passes for 2 times, the corresponding minimum final compaction degree, is 0.878, at the same time, the rolling speed of 1 m/s, rolling passes for 4 times, the corresponding final compaction degree is the largest, 0.955. The conclusions are as follows: the combination of construction parameters to achieve the optimal compaction degree is: rolling speed 1.3 m/s, rolling times 4 times.

Key words: road engineering, intelligent compaction, feedback regulation mechanism, finite element redevelopment, final compaction degree, optimal parameter combination

中图分类号: 

  • U416

表1

压实度与黏聚力、内摩擦角试验结果"

实时压实度K黏聚力c/kPa内摩擦角φ/(°)
0.8012.127.0
0.8541.228.8
0.9058.631.2
0.9361.630.5
0.9462.832.4
0.9663.634.3
1.0074.936.9

表2

“场变量”实时压实度K与土体抗剪强度对应表"

压实度K黏聚力c/kPa内摩擦角φ/(°)
0.8026.414.2
0.8126.919.5
0.8227.324.4
0.8327.829.2
0.8428.333.7
0.8528.737.9
0.8629.241.9
0.8729.745.6
0.8830.149.1
0.8930.652.4
0.9031.155.3
0.9131.558.1
0.9232.060.6
0.9332.562.8
0.9432.964.8
0.9533.466.5
0.9633.968.0
0.9734.369.3
0.9834.870.3
0.9935.371.0
1.0035.771.5

图1

路基结构示意图"

表3

路基土初始压实状态参数[20,21]"

层位密度ρ/(kg·m-3弹性模量E/MPa黏聚力c/kPa摩擦角φ/(°)泊松比
上层松铺16341511.88270.33
下层地基18593055.831.150.35

图2

有限元数值仿真网格划分图"

表4

有限元数值仿真工况"

编号碾压速度/(m·s-1碾压遍数编号碾压速度/(m·s-1碾压遍数
No.11.02No.122.54
No.21.03No.133.02
No.31.04No.143.03
No.41.52No.153.04
No.51.53No.163.52
No.61.54No.173.53
No.72.02No.183.54
No.82.03No.194.02
No.92.04No.204.03
No.102.52No.214.04
No.112.53

图3

路基振动压实现场试验示意图"

表5

振动压路机参数"

参数数值参数数值
压路机型号YZ32前/后轮质量/t21/11
频率/Hz28/33速度/(km·h-10~8
名义振幅/mm1.8/1.1额定转速/(rad·min-12200
激振力幅值/kN590/450振动轮宽度/mm2000
总质量/t32振动轮半径/mm600

图4

竖向位移随时间变化曲线和压实度变化趋势"

图5

现场试验压实度变化误差曲线及数值仿真压实度变化对比图"

表6

各参数下对应的最终压实度"

速度/(m·s-1遍数
234
1.00.9330.9480.955
1.50.9310.9410.949
2.00.9390.9480.954
2.50.9220.9340.944
3.00.9040.9240.937
3.50.8870.9020.918
4.00.8780.8960.903

图6

碾压速度与压实度的关系曲线以及碾压遍数与压实度的关系曲线"

图7

最终压实度等高线图"

图8

压实度与碾压速度关系曲线"

1 Vennapusa P K R, White D J, Schram S. Roller-integrated compaction monitoring for hot-mix asphalt overlay construction[J]. Journal of Transportation Engineering, 2013, 139(12): 1164-1173.
2 Xu Q, Chang G K. Evaluation of intelligent compaction for asphalt materials[J]. Automation in Construction, 2013, 30: 104-112.
3 Xu Q, Chang G K, Gallivan V L. Development of a systematic method for intelligent compaction data analysis and management[J]. Construction and Building Materials, 2012, 37: 470-480.
4 Chen T, Ma T, Huang X, et al. Microstructure of synthetic composite interfaces and verification of mixing order in cold-recycled asphalt emulsion mixture[J]. Journal of Cleaner Production, 2020, 263:No.121467.
5 Zhu J, Ma T, Fan J, et al. Experimental study of high modulus asphalt mixture containing reclaimed asphalt pavement[J]. Journal of Cleaner Production, 2020, 263: No.121447.
6 Ding X, Chen L, Ma T, et al. Laboratory investigation of the recycled asphalt concrete with stable crumb rubber asphalt binder[J]. Construction and Building Materials, 2019, 203: 552-557.
7 赵秀璞. 路基智能压实控制技术研究[D].西安: 长安大学机械工程学院, 2016.
Zhao Xiu-pu. Study on intelligent compaction control technology of subgrade[D]. Xi'an: College of Mechanical Engineering, Chang'an University, 2016.
8 陈博. 路基土压实度实时检测系统研究[D]. 西安: 长安大学机械工程学院, 2019.
Chen Bo. Research on real-time detection system of subgrade compaction degree[D]. Xi'an: College of Mechanical Engineering,Chang'an University, 2019.
9 Minchin R E, Thomas H R. Validation of vibration-based onboard asphalt density measuring system[J]. Journal of Construction Engineering and Management-ASCE, 2003, 129(1): 1-7.
10 赵海杰. 路基压实质量评价指标的研究[D]. 西安: 长安大学机械工程学院, 2015.
Zhao Hai-jie. Study on the evaluation index of roadbed compaction quality[D]. Xi'an: College of Mechanical Engineering, Chang'an University, 2015.
11 焦倓, 聂志红, 王翔. 基于连续压实质量检测的压实薄弱区域评价指标研究[J]. 铁道学报, 2015, 37(8): 66-71.
Jiao Tan, Nie Zhi-hong, Wang Xiang. Evaluation of compaction weak areas based on continuous compaction quality detction[J]. Journal of the China Railway Society, 2015, 37(8): 66-71.
12 崔浩. 基于智能压实技术对填筑体路基压实度试验研究[D]. 保定: 河北大学建筑工程学院, 2017.
Cui Hao. Based on intelligent compaction technology of filling roadbed compaction degree test research[D]. Baoding: College of Civil Engineering and Architecture, Hebei University,2017.
13 郝飞. “振动轮⁃土壤”模型的有限元分析[D]. 西安: 长安大学机械工程学院, 2007.
Hao Fei. Finite element analysis of "vibration wheel-soil" model[D]. Xi'an: College of Mechanical Engineering,Chang'an University, 2007.
14 庞国强,苟桂枝. 冲击压路机压实效果的有限元分析法[J]. 机械管理开发, 2003(4): 16-17.
Pang Guo-qiang, Gou Gui-zhi. Finite element analysis method for compaction effect of impact rollers[J]. Mechanical Management and Development, 2003(4): 16-17.
15 Liu D, Lin M, Li S. Real-Time Quality Monitoring and Control of Highway Compaction[J]. Automation in Construction, 2016, 62: 114-123.
16 Zhang Q, Liu T, Zhang Z, et al. Unmanned rolling compaction system for rockfill materials[J]. Automation in Construction, 2019, 100: 103-117.
17 吴泽兵, 张帅, 郭龙龙, 等. ABAQUS二次开发在Pdc单齿破岩仿真中的应用[J]. 西安石油大学学报:自然科学版, 2020, 35(1): 104-109.
Wu Ze-bing, Zhang Shuai, Guo Long-long, et al. Application of ABAQUS secondary development in rock breaking simulation of PDC cutter[J]. Journal of Xi'an Shiyou University(Natural Science Edition), 2020,35(1):104-109.
18 陈飞, 王成雨, 李伟刚, 等. Abaqus二次开发在航空弓形结构件喷丸强化模拟中的应用[J]. 计算机辅助工程, 2020, 29(2): 55-60.
Chen Fei, Wang Cheng-yu, Li Wei-gang, et al. Application of Abaqus secondary development in shot peening strengthening of aerospace arc-shaped frame[J]. Computer Aided Engineering,2020,29(2):55-60.
19 Hu W, Jia X, Zhu X, et al. Influence of moisture content on intelligent soil compaction[J]. Automation in Construction, 2020, 113: No.103141.
20 Ma Y, Luan Y, Zhang W, et al. Numerical simulation of intelligent compaction for subgrade construction[J]. Journal of Central South University, 2020, 27(Sup.1): 2173-2184.
21 马源, 方周, 韩涛, 等. 路基智能压实关键控制参数动态仿真及演变规律[J]. 中南大学学报:自然科学版, 2021, 52(7): 2246-2257.
Ma Yuan, Fang Zhou, Han Tao, et al. Dynamic simulation and evolution of key control parameters for intelligent compaction of subgrade[J]. Journal of Central South University(Science and Technology), 2021, 52(7): 2246-2257.
22 闫星宇. 函数型线性回归的若干研究[D]. 上海: 华东师范大学统计学院, 2020.
Yan Xing-yu. Some studies on functional linear regression[D]. Shanghai: School of Statistics, East China Normal University, 2020.
23 陈育民,徐鼎平. FLAC/FLAC3D基础与工程实例[M]. 北京:中国水利水电出版社, 2009:220-222.
24 滕显飞. 黄泛区粉土路基强夯加固数值分析与质量控制技术研究[D]. 济南: 山东大学土建与水利学院,2017.
Teng Xian-fei. Numerical analysis and quality control of dynamic consolidation of silty soil subgrade in Yellow River alluvial plain[D]. Jinan: School of Civil Engineering, Shandong University,2017.
25 徐群. 非线性回归分析的方法研究[D]. 安徽:合肥工业大学数学学院, 2009.
Xu Qun. The research on non-linear regression analysis methods[D]. Anhui: School of Mathematics, Hefei University of Technology,2009.
26 周大力. 基于Laplace机制的差分隐私回归分析相关优化研究[D]. 哈尔滨: 黑龙江大学数据科学与技术学院, 2018.
Zhou Da-li. Research on correlation optimization of differential privacy regression analysis based on Laplace mechanism[D]. Harbin: School of Data Science and Technology, Heilongjiang University, 2018.
27 White D J, Vennapusa P K R, Gieselman H H. Field assessment and specification review for roller-integrated compaction monitoring technologies[J]. Advances in Civil Engineering, 2011(1): No.783836.
[1] 杨柳,王创业,王梦言,程阳. 设置自动驾驶小客车专用车道的六车道高速公路交通流特性[J]. 吉林大学学报(工学版), 2023, 53(7): 2043-2052.
[2] 郑睢宁,何锐,路天宇,徐紫祎,陈华鑫. RET/胶粉复合改性沥青制备及其混合料性能评价[J]. 吉林大学学报(工学版), 2023, 53(5): 1381-1389.
[3] 魏海斌,韩栓业,毕海鹏,刘琼辉,马子鹏. 智能感知道路主动除冰雪系统及实验技术[J]. 吉林大学学报(工学版), 2023, 53(5): 1411-1417.
[4] 杨帆,李琛琛,李盛,刘海伦. 温缩作用下双层连续配筋混凝土路面配筋率设计参数对比分析[J]. 吉林大学学报(工学版), 2023, 53(4): 1122-1132.
[5] 关博文,邸文锦,王发平,吴佳育,张硕文,贾治勋. 干湿循环与交变荷载作用下混凝土硫酸盐侵蚀损伤[J]. 吉林大学学报(工学版), 2023, 53(4): 1112-1121.
[6] 刘状壮,张有为,季鹏宇,Abshir Ismail Yusuf,李林,郝亚真. 电热型融雪沥青路面传热特性研究[J]. 吉林大学学报(工学版), 2023, 53(2): 523-530.
[7] 魏海斌,马子鹏,毕海鹏,刘汉涛,韩栓业. 基于力学响应分析方法的导电橡胶复合路面铺装技术[J]. 吉林大学学报(工学版), 2023, 53(2): 531-537.
[8] 时成林,王勇,吴春利,宋文祝. 路堤挡土墙主动土压力计算方法修正[J]. 吉林大学学报(工学版), 2022, 52(6): 1394-1403.
[9] 郭庆林,刘强,吴春利,李黎丽,李懿明,刘富春. 导电沥青及混合料裂缝局部温度场及愈合效果[J]. 吉林大学学报(工学版), 2022, 52(6): 1386-1393.
[10] 姚玉权,仰建岗,高杰,宋亮. 基于性能-费用模型的厂拌再生沥青混合料优化设计[J]. 吉林大学学报(工学版), 2022, 52(3): 585-595.
[11] 夏全平,高江平,罗浩原,张其功,李志杰,杨飞. 用于高模量沥青砼的复合改性硬质沥青低温性能[J]. 吉林大学学报(工学版), 2022, 52(3): 541-549.
[12] 叶奋,胡诗园. 考虑旧水泥路面接缝传荷能力的超薄罩面力学特性[J]. 吉林大学学报(工学版), 2022, 52(11): 2636-2643.
[13] 于晓贺,罗蓉,柳子尧,黄婷婷,束裕. 沥青路面典型裂缝湿度场数值模拟[J]. 吉林大学学报(工学版), 2022, 52(10): 2343-2351.
[14] 杨彦海,崔宏,杨野,张怀志,刘赫. 冻融循环作用对非饱和乳化沥青冷再生混合料性能的影响[J]. 吉林大学学报(工学版), 2022, 52(10): 2352-2359.
[15] 冉武平,陈慧敏,李玲,冯立群. 干湿循环下粗粒土回弹模量演变规律及模型预估和修正[J]. 吉林大学学报(工学版), 2021, 51(6): 2079-2086.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!