Journal of Jilin University(Engineering and Technology Edition) ›› 2024, Vol. 54 ›› Issue (10): 2859-2869.doi: 10.13229/j.cnki.jdxbgxb.20221520

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Geostatistical analysis and evaluation of subgrade spatial uniformity based on intelligent compaction technology

Jin-song QIAN1,2(),Yi-cheng YANG1,2,Jian-ming LING1,2   

  1. 1.Key Laboratoty of Road and Traffic Engineering of the Ministry of Education，Tongji University，Shanghai 201804，China
    2.Key Laboratoty of Infrastructure Durability and Operation Safety in Airfield of CAAC，Tongji University，Shanghai 201804，China
  • Received:2022-11-28 Online:2024-10-01 Published:2024-11-22

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Abstract:

The standard subgrade uniformity evaluation method， which relies on data variability， struggles to quantify the spatial distribution properties of the compaction data and is unable to identify regional compaction surface non-uniformity. To solve this issue， test fields constructed under the Songtong Expressway's subgrade were used to obtain spatial data of compaction. Based on geostatistical approaches， a half-variance function model with intelligent compaction parameters were established， to reveal the probability distribution and spatial autocorrelation of the subgrade， and then evaluate the regional uniformity of the subgrade. The results reveal that， the vibration modulus followed the normal distribution； The spatial autocorrelation distance was approximately 5~8 meters and the maximum autocorrelation coefficient was about 0.6~0.8； The nugget and geographic heterogeneity were positively correlated， while the range and patchiness were negatively correlated. The nearest neighbor index revealed the level of weak point concentration， and if it is larger than 1， it signifies that the weak points are separated and the spatial uniformity is good.

Key words: subgrade engineering, intelligent compaction technology, geostatistical analysis, spatial characteristics, evaluation of uniformity

CLC Number: 

  • U416.1

Fig.1

Construction site and intelligent compaction equipment"

Fig.2

Intelligent compaction collection and analysis system"

Table 1

Operating parameters of rolling equipment"

技术参数数 值
工作质量/kg13 000
激振力/kN290
频率/Hz32
振幅/m0.95
轮宽/m2.15

Fig.3

Overview of test field"

Fig.4

Relationship between vibration modulus anddegree of compaction"

Fig.5

Model of half-variance function"

Fig.6

Nearest neighbor index in different types of spatial distribution"

Fig.7

Probability distribution of rolling parameters"

Table 2

Normal distribution test of rolling parameters"

试验编号样本个数Wp检验结果
A-2660.9760.251不能拒绝
A-4660.9770.293不能拒绝
A-6660.9750.226不能拒绝
A-8660.9750.224不能拒绝
B-2660.9410.003可以拒绝
B-4660.9680.086不能拒绝
B-6660.9710.126不能拒绝
B-8660.9750.212不能拒绝

Fig.8

Autocorrelation coefficient of the rolling test field"

Table 3

Mathematical statistics of rolling parameters"

试验编号

均值

/MPa

标准差

/MPa

变异系数

/%

A-255.380.631.14
A-456.240.611.08
A-656.420.651.16
A-856.530.540.96
B-255.500.681.23
B-456.210.761.36
B-656.720.611.07
B-856.710.591.04

Fig.9

Trend of rolling parameters"

Fig.10

Centralized and decentralized week area"

Fig.11

Test fields with different levels of concentration"

Table 4

Mathematical and geostatistical statistics offield C"

试验编号均值标准差块金基台变程/m
C-150.40.570.201.1320.9
C-250.40.570.220.9916.2
C-350.40.570.120.9210.3
C-450.40.5701.026.7
C-550.40.5700.984.7

Fig.12

Half-variance functions and interpolation plots with different levels of concentration"

Fig.13

Spatial distribution of week areas and nearest neighbor index"

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