Abstract
Grouting is a fundamental technology in engineering construction, and its grouting quality evaluation is a critical scientific problem. Proper and reasonable grouting quality evaluation is vital to ensure engineering safety. Standard research on grouting quality evaluation does not consider the uncertainty in the evaluation process and lacks multi-index comprehensive analysis. Because of the above problems, this paper puts forward a comprehensive evaluation method of grouting quality based on FRES-VFS. Firstly, based on the systematic analysis of relevant factors affecting grouting quality, the comprehensive evaluation of grouting quality is divided into three parts: the groutability before grouting, the rationality of design and construction, and the quality evaluation after grouting. Then, twelve indexes, such as the number of joints in the rock mass, the opening degree of the joint in the rock mass, the water permeability before grouting, the water–cement ratio of grout, the grouting pressure, the design parameters, the hole position, the borehole deviation rate, the construction parameters, the permeability, the compactness, and the durability after grouting, are selected to construct the rating index system. Secondly, the weight of each index in the index system is calculated based on the fuzzy rock engineering system (FRES) method. Furthermore, considering the uncertainty in the comprehensive evaluation of grouting quality, the uncertain mapping between evaluation grade and evaluation index is established using variable fuzzy set (VFS) theory. Finally, the comprehensive evaluation method based on FRES-VFS is applied to the Huanggou Pumped Storage Power Station grouting project in China, which provides a new idea for the comprehensive evaluation of grouting quality.
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Abbreviations
- CT:
-
Computed Tomography
- AHP:
-
Analytic Hierarchy Process
- D-AHP:
-
The D-number Analytic Hierarchy Process method
- ANFIS:
-
Adaptive-Network-Based Fuzzy Inference System
- FFR:
-
Fracture Filling Rate
- RQD:
-
Rock Quality Grade
- FRES:
-
Fuzzy Rock Engineering System
- RES:
-
Rock Engineering System
- TBM:
-
Tunnel Boring Machine
- VFS:
-
Variable Fuzzy Set
- ESQ:
-
Expert Semi-Quantitative
- FIS:
-
Fuzzy Inference System
- AWV:
-
Acoustic Wave Velocity
- C i :
-
The cause value
- I ij :
-
The influence of parameters
- E i :
-
The effect value
- n A, n B, n C, n D, n E :
-
The proportion of the number of experts who interact with each other when making group decisions or voting by experts
- ω i :
-
The weight
- w before, w d&c, w after :
-
The index weight of the three parts
- w j :
-
Total weight of the index
- w * :
-
The index weight of the three parts themselves
- \(w_{s}^{ * }\) :
-
Each index’s weight in the three parts
- h :
-
The multiple standard levels
- i :
-
The multiple indexes
- c :
-
The number of levels
- x i :
-
The index
- y ih, Y :
-
The index standard matrix
- I ab :
-
The standard interval matrix of the index
- I cd :
-
The variable range interval matrix of the index
- M ih :
-
The point-valued matrix with a membership degree of 1
- μ A (x i)h :
-
The relative membership degree of the levels
- U A (u)h :
-
The comprehensive relative membership degree of the evaluation object
- p :
-
The variable parameter
- α :
-
The variable optimization criterion parameter
- H, H t :
-
The level eigenvalue of the object
- U nor :
-
The normalized matrix of comprehensive relative membership degree
- \(\overline{H}\) :
-
The final evaluation result
References
Hao, Z.Y., Li, C.G.: Application of the geophysical survey technology to test grout curtain effectiveness. Jilin Water Resour. 02, 11–15 (2003). (In Chinese)
Xia, J.F., Yue, X.B., Zhang, S.K., Zheng, G.Y.: Quality check for dam curtain grouting by third party and effect evaluation. Yangtze River 06, 89–92 (2013). (In Chinese)
Qian, C.Y.: Discussion on quality evaluation of impervious wall and curtain grouting of an earth-rock dam of a reservoir. Eng. Constr. 4, 555–558 (2015)
Bai, H.R., Li, J.J.: Evaluation of grouting effect detection in goaf. Appl. Mech. Mater. 438–439, 1080–1083 (2013)
Huang, X.G., Yang, X.L., Fang, Y.Z.: Study on grouting effect evaluation of f4 weathered slot in Xiamen Xiang’an submarine tunnel. Appl. Mech. Mater. 256, 1217–1220 (2013)
Wu, Y.T., Han, Z.Q., Wang, C.Y., Zhou, J.F., Hu, S.: Grouting effect evaluation of dam foundation rock mass based on fracture filling characteristics. Rock Soil Mech. 38(S2), 311–316 (2017). (In Chinese)
Zhu, Y., Wang, X., Deng, S.: Evaluation of curtain grouting efficiency by cloud model-based fuzzy comprehensive evaluation method. KSCE J. Civ. Eng. 23(3), 2852–2866 (2019)
Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)
Kumar, P.S., Hussain, R.J.: A simple method for solving fully intuitionistic fuzzy real life assignment problem. Int. J. Oper. Res. Inf. Syst. 7(2), 39–61 (2016)
Kumar, P.S.: PSK method for solving type-1 and type-3 fuzzy transportation problems. Int. J. Fuzzy Syst. App. 5, 121–146 (2016)
Kumar, P.S.: A simple method for solving type-2 and type-4 fuzzy transportation problems. Int. J. Fuzzy Logic Intell. Syst. 16(4), 225–237 (2016)
Zeng, D.Z., He, Q.Y., Yu, Z.M., Jia, W.Y., Zhang, S., Liu, Q.P.: Risk assessment of sustained casing pressure in gas wells based on the fuzzy comprehensive evaluation method. J. Nat. Gas Sci. Eng. 46, 756–763 (2017)
Zhang, P., Feng, G.Q.: Application of fuzzy comprehensive evaluation to evaluate the effect of water flooding development. J. Petrol. Exploration Prod. Technol. 8(4), 1455–1463 (2018)
Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1), 87–96 (1986)
Mizumoto, M., Tanaka, K.: Some properties of fuzzy sets of type 2. Inform Control 31, 312–340 (1976)
Kumar, P.S.: A note on a new approach for solving intuitionistic fuzzy transportation problem of type-2. Int. J. Logist. Syst. Manage. 29(1), 102–129 (2018)
Torra, V.: Hesitant fuzzy sets. Int. J. Intell. Syst. 25(6), 529–539 (2010)
Kumar, P.S.: Algorithms for solving the optimization problems using fuzzy and intuitionistic fuzzy set. Int. J. Syst. Assurance Eng. Manage. 11(1), 189–222 (2020)
Kumar, P.S.: Intuitionistic fuzzy solid assignment problems: a software-based approach. Int. J. Syst. Assurance Eng. Manage. 10(4), 661–675 (2019)
Kumar, P.S.: Developing a new approach to solve solid assignment problems under intuitionistic fuzzy environment. Int. J. Fuzzy Syst. Appl. 9(1), 1–34 (2020)
Kumar, P.S.: Computationally simple and efficient method for solving real-life mixed intuitionistic fuzzy 3D assignment problems. Int. J. Softw. Sci. Comput. Intell. (2022).
Ahmed, G.Q., Sarah,S.L., Faisal, A. A fuzzy-based approach for cholera risk assessment and vaccine allocation. Int. J. Fuzzy Syst. (2022).
Peng, B., Zheng, C., Wei, G.: Risk assessment method on haze networks public opinion based on intuitionistic fuzzy choquet integral. Int. J. Fuzzy Syst. 24, 2858–2872 (2022)
Fan, G., Zhong, D., Yan, F., Yu, P.: A hybrid fuzzy evaluation method for curtain grouting efficiency assessment based on an AHP method extended by D numbers. Expert Syst. App. 44(4), 289–303 (2016)
Li, X., Zhong, D., Ren, B., Fan, G., Cui, B.: Prediction of curtain grouting efficiency based on ANFIS. Bull. Eng. Geol. Environ. 78(1), 281–309 (2019)
Yan, F.G.: Theories and applications of unified grouting model and analysis in hydraulic and hydroelectric project. Tianjin University, Tianjing China (2014)
Song, L., Yu, C.W.: A comprehensive evaluation model for curtain grouting efficiency assessment based on prospect theory and interval-valued intuitionistic fuzzy sets extended by improved d numbers. Energies 12, 3674 (2019)
Hudson, J.A.: Rock engineering systems: theory and practice. Ellis Horwood Ltd, Chichester (1992)
Aghababaei, S., Jalalifar, H., Saeedi, G.: Prediction of face advance rate and determination of the operation efficiency in retreat longwall mining panel using rock engineering system. Int. J. Coal Sci. Technol. 6(3), 419–429 (2019)
Faramarzi, F., Mansouri, H., Farsangi, M.A.: A rock engineering systems based model to predict rock fragmentation by blasting. Int. J. Rock Mech. Min. Sci. 60, 82–94 (2013)
Frough, O., Torabi, S.R.: An application of rock engineering systems for estimating TBM downtimes. Eng. Geol. 157, 112–123 (2013)
Hasanipanah, M., Armaghani, D.J., Monjezi, M.: Risk assessment and prediction of rock fragmentation produced by blasting operation: a rock engineering system. Environ. Earth Sci. 75(9), 808 (2016)
Naghadehi, M.Z., Jimenez, R., KhaloKakaie, R., Jalali, S.M.: A new open-pit mine slope instability index defined using the improved rock engineering systems approach. Int. J. Rock Mech. Min. Sci. 61, 1–14 (2013)
Rafiee, R., Khalookakaie, R., Ataei, M., Jalali, S.M., Sereshki, F., Azarfar, A.: Improvement of rock engineering system coding using fuzzy numbers. J Intell. Fuzzy Syst. 30(2), 705–715 (2016)
Rafiee, R., Mohammadi, S., Ataei, M., Khalookakaie, R.: Application of fuzzy RES and fuzzy DEMATEL in the rock behavioral systems under uncertainty. Geosyst. Eng. 22(1), 18–29 (2019)
Rafiee, R., Ataei, M., Khalookakaie, R.: A new cavability index in block caving mines using fuzzy rock engineering system. Int. J. Rock Mech. Min. Sci. 77, 68–76 (2015)
Chen, S.Y., Guo, Y.: Variable fuzzy sets and their application to comprehensive risk evaluation for flood control engineering system. Adv. Sci. Technol. Water Resour. 5, 153–162 (2005)
Chen, S.Y., Li, M.: Assessment model of water resources reproducible ability based on variable fuzzy set theory. J. Hydraul. Eng. 37, 431–435 (2006). (In Chinese)
He, G., Chai, J., Qin, Y., Xu, Z.G., Li, S.Y.: Coupled model of variable fuzzy sets and the analytic hierarchy process and its application to the social and environmental impact evaluation of dam breaks. Water Resour. Manage 34(9), 2677–2697 (2020)
Fang, Y., Zheng, X., Hui, P.: A new method of the relative membership degree calculation in variable fuzzy sets for water quality assessment. Ecol. Indicat. 98, 515–522 (2019)
Yan, F., Liu, L., Zhang, Y., Chen, M.S., Chen, N.: The research of dynamic variable fuzzy set assessment model in water quality evaluation. Water Resour. Manage 30, 63–78 (2016)
Gong, W., Chen, K., Huggins, T.J.: Risk evaluation based on variable fuzzy sets and information diffusion method. J. Appl. Math. Phys. 8(5), 821–830 (2020)
Li, X., Zhang, W., Wang, X., Wang, Z., Pang, C.: Evaluation on the risk of water inrush due to roof bed separation based on improved set pair analysis-variable fuzzy sets. ACS Omega 7(11), 9430–9442 (2022)
Wang, Y., Xie, Y., Qi, L., He, Y., Bo, H.: Synergies evaluation and influencing factors analysis of the water- energy-food nexus from symbiosis perspective: a case study in the beijing-tianjin-hebei region. Sci. Total Environ. 818, 151731–151746 (2022)
Jia, Wu., Yun, C., Jingyi, L.: One-at-a-time based weight sensitivity analysis in spatial multi-criteria decision making [J]. Resour. Sci. 36(9), 1870–1879 (2014). (In Chinese)
Funding
This research was supported by the project Funded by the Key projects of natural science basic research program of Shaanxi province (Grant Num. 2018JZ5010). The joint fund project of Natural science basic research program of Shaanxi province and Hanjiang to Weihe River Water Diversion Project Construction Co.Ltd. Shaanxi Province (Grant Num. 2019JLM-55) and the water science plan project of Shaanxi Province (Grant Num. 2018SLKJ-5).
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Tong, F., Yang, J., Zheng, C. et al. Research on the Comprehensive Evaluation of Grouting Quality Based on Fuzzy Rock Engineering System and Variable Fuzzy Set Theory. Int. J. Fuzzy Syst. 25, 1191–1212 (2023). https://doi.org/10.1007/s40815-022-01433-6
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DOI: https://doi.org/10.1007/s40815-022-01433-6