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Assessment of ultimate bearing capacity of rock-socketed piles using hybrid approaches

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Abstract

In geotechnical engineering, accurately estimating the ultimate bearing capacity (\({Q}_{u}\)) of rock-socketed piles remains a crucial challenge. This study introduces a methodology that integrates advanced optimization algorithms, specifically Dandelion Optimization (DO) and the Crystal Structure Algorithm (CryStal), with Support Vector Regression (SVR) to enhance predictive capabilities. Three distinct models—SVDO, SVCS, and a hybrid SVR model—are developed through this integration. The core of this predictive framework is SVR, known for its efficacy in capturing intricate non-linear relationships between input variables and the ultimate bearing capacity of rock-socketed piles. To improve predictive accuracy, DO strategically adjusts hyperparameters to emulate the growth and dispersal patterns of dandelion seeds, while CryStal delicately optimizes SVR parameters inspired by crystalline atomic structures. The resulting models offer valuable insights for precisely predicting the ultimate bearing capacity of rock-socketed piles in geotechnical engineering. Among these, SVCS stands out with an exceptional R2 value of 0.997, indicating an outstanding fit to the data, and the lowest Root Mean Squared Error (RMSE) at 930.7, underscoring its unparalleled predictive accuracy. In conclusion, this study presents an innovative approach within geotechnical engineering for the precise estimation of the ultimate bearing capacity of rock-socketed piles. The insights gained contribute significantly to considerations of stability and safety in construction projects, emphasizing a multidisciplinary approach beyond artificial intelligence.

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Authors and Affiliations

  1. School of Information Engineering, Yinchuan University of Science and Technology, Yinchuan, 750011, Ningxia, China

    Rongjun You & Huijun Mao

Authors
  1. Rongjun You
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  2. Huijun Mao
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Contributions

Rongjun You: writing—original draft preparation, conceptualization, supervision, project administration. Huijun Mao: methodology, software, validation, formal analysis.

Corresponding author

Correspondence to Rongjun You.

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Appendix

Appendix

Test Dataset

Lp/D

Ls/Lr

N_SPT

UCS

Hr

Qu

14.77

7.43

157.66

59.86

0.00

17,518.25

5.42

1.71

140.15

62.73

0.00

15,693.43

49.90

1.20

0.00

0.00

1.2

10,360

14.61

5.71

119.71

34.53

0.00

32,481.75

10.96

4.57

140.15

57.55

0.00

32,116.79

31.56

19.43

21.90

29.93

0.00

41,605.84

46.36

8.36

0.00

0.00

8.36

9000

8.47

1.71

132.85

67.34

0.00

13,868.61

9.89

0.86

108.03

49.50

0.00

12,408.76

13.94

3.43

11.68

36.26

0.00

23,722.63

58.00

6.50

0.00

0.00

6.5

10,000

27.3

0.80

0.00

0.00

0.8

8000

55.96

8.08

0.00

0.00

8.08

7600

11.69

4.29

132.85

48.35

0.00

13,868.61

12.99

13.43

2.92

25.90

0.00

34,671.53

72.64

8.98

0.00

0.00

8.08

8073

22.81

0.52

0.00

0.00

0.62

12,006

4.33

0.29

160.58

62.73

0.00

25,547.45

14.03

3.14

124.09

35.11

0.00

24,452.55

20.26

17.14

7.30

28.20

0.00

36,496.35

17.33

3.43

102.19

35.68

0.00

16,058.39

28.29

27.43

10.22

28.20

0.00

34,306.57

13.04

4.86

148.91

28.78

0.00

24,817.52

22.15

2.00

5.84

33.38

0.00

19,708.03

7.51

1.14

128.47

48.92

0.00

25,182.48

11.88

2.00

141.61

59.28

0.00

17,518.25

28.87

22.57

10.22

41.44

0.00

39,781.02

38.14

1.06

0.00

0.00

1.38

13,500

68.08

1.50

0.00

0.00

1.2

6831

9.71

2.29

115.33

49.50

0.00

18,248.18

50.60

2.00

0.00

0.00

1.2

5500

34.77

0.50

0.00

0.00

0.5

8696

9.51

2.57

140.15

62.73

0.00

14,233.58

9.57

2.00

148.91

65.04

0.00

28,467.15

13.71

2.00

119.71

35.68

0.00

13,868.61

74.59

7.14

0.00

0.00

5

7452

29.10

1.67

0.00

0.00

1

1449

75.00

2.13

0.00

0.00

1.7

4761

28.05

24.00

23.36

25.32

0.00

34,671.53

9.87

3.14

90.51

40.86

0.00

19,343.07

12.97

2.57

113.87

42.59

0.00

39,416.06

25.00

1.50

0.00

0.00

1.5

6000

28.06

14.57

46.72

32.23

0.00

18,978.10

48.50

1.91

0.00

0.00

1.53

8400

47.85

1.50

0.00

0.00

1.2

8900

64.66

2.49

0.00

0.00

1.99

7000

49.80

1.25

0.00

0.00

1.5

10,000

7.89

1.14

144.53

64.46

0.00

20,072.99

8.17

2.57

134.31

59.86

0.00

18,613.14

80.32

0.91

0.00

0.00

1

13,041

27.31

1.11

0.00

0.00

1

10,350

47.91

1.09

0.00

0.00

1.2

14,000

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You, R., Mao, H. Assessment of ultimate bearing capacity of rock-socketed piles using hybrid approaches. Multiscale and Multidiscip. Model. Exp. and Des. (2024). https://doi.org/10.1007/s41939-024-00425-3

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