An artificial neural network for groutability prediction of permeation grouting with microfine cement grouts

Liao, Kuo‐Wei; Fan, Jung-Chuan; Huang, Chien‐Lin

doi:10.1016/j.compgeo.2011.07.008

Cited by 44 publications

(21 citation statements)

References 14 publications

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“…For each data case, the corresponding output is either +1, which means that the grouting is successful, or −1, which indicates unsuccessful grouting. In our research, inherited from the previous research work [11], a grouting process is considered to be successful if the injected grout is at least two times the volume of the void space under the split pressure. Table 2 provides descriptive statistics of influencing factors of the historical data.…”

Section: Historical Datamentioning

confidence: 99%

“…Moreover, the diameter through which 70% of the total grout passes is less than 1 m. Thus, the grout is considered to be a seminanometer material. Recent research works have pointed out that other parameters of the soil and the grout (namely, the fines content of the total soil mass, the water-to-cement ratio of the grout, the void size in soil, the coefficient of uniformity, and the coefficient of gradation of the soil) can be useful for the prediction process [4,[9][10][11]. In this study, seven influencing factors are considered to estimate the outcome of a grouting activity (see Table 1).…”

Section: Historical Datamentioning

confidence: 99%

“…The database used in this research consists of 240 in situ permeation grouting cases [11] for sandy silt soil collected from highway and mass rapid transportation projects. A mixture of microfine cement and microslag in equal proportions was utilized as the injected grout.…”

Section: Historical Datamentioning

confidence: 99%

“…Artificial neural network (ANN) has been applied to deal with groutability prediction as well as with other problems in the construction industry [4,[11][12][13]. Although ANN has been proven to be feasible in the task of groutability estimation, its implementation suffers from several drawbacks.…”

Section: Introductionmentioning

confidence: 99%

“…Liao et al [11] pointed out that information of soil gradation, namely, the coefficient of uniformity ( ), which measures the particle size range, and the coefficient of gradation ( ), which characterizes the particle size curve, can be useful for estimating groutability.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

Tran

Hoang

2014

Journal of Construction Engineering

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Permeation grouting is a commonly used approach for soil improvement in construction engineering. Thus, predicting the results of grouting activities is a crucial task that needs to be carried out in the planning phase of any grouting project. In this research, a novel artificial intelligence approach-autotuning support vector machine-is proposed to forecast the result of grouting activities that employ microfine cement grouts. In the new model, the support vector machine (SVM) algorithm is utilized to classify grouting activities into two classes: success and failure. Meanwhile, the differential evolution (DE) optimization algorithm is employed to identify the optimal tuning parameters of the SVM algorithm, namely, the penalty parameter and the kernel function parameter. The integration of the SVM and DE algorithms allows the newly established method to operate automatically without human prior knowledge or tedious processes for parameter setting. An experiment using a set of in situ data samples demonstrates that the newly established method can produce an outstanding prediction performance.

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Section: Historical Datamentioning

confidence: 99%

Section: Historical Datamentioning

confidence: 99%

Section: Historical Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

Tran

Hoang

2014

Journal of Construction Engineering

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Grouting theories and technologies for the reinforcement of fractured rocks surrounding deep roadways

Kang

Wen-zhou

Gao

et al. 2022

Deep Underground Science and Engineering

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Grouting is an effective method to improve the integrity and stability of fractured rocks that surround deep roadways. After years of research and practice, various theories and a complete set of grouting technologies for deep roadways with fractured rocks have been developed and are widely applied in Chinese coal mining production. This paper systematically summarizes and analyzes the research results concerning the theory, design, materials, processes, and equipment for the grouting and reinforcement of fractured rocks surrounding deep roadways. Specifically, in terms of grouting methods, pregrouting, grouting‐while‐excavation, and postgrouting methods are explored; in terms of grouting theory, backfill grouting, compaction grouting, infiltration grouting, and fracture grouting theories are studied. In addition, this paper also studies grouting borehole arrangement, water‐cement ratio, grouting pressure, grouting volume, grout diffusion radius, and other grouting parameters and their determination methods. On this basis, this paper explores the physical and mechanical properties of organic and organic‐inorganic composite grouting materials, and assess grouting reinforcement quality testing methods and instruments. Taken as the field cases, the application of pregrouting in front of heading faces, grouting‐while‐excavation, and postgrouting in the Kouzidong coal mine are then introduced, and the effects of the grouting reinforcements are evaluated. This paper proposes a development direction for grouting technology based on problems existing in the grouting reinforcement of fractured rocks surrounding deep roadways.

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Predicting groutability of granular soils using adaptive neuro-fuzzy inference system

Tekin

Akbas

2017

Neural Comput & Applic

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An artificial neural network for groutability prediction of permeation grouting with microfine cement grouts

Cited by 44 publications

References 14 publications

An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

An Artificial Intelligence Approach for Groutability Estimation Based on Autotuning Support Vector Machine

Grouting theories and technologies for the reinforcement of fractured rocks surrounding deep roadways

Predicting groutability of granular soils using adaptive neuro-fuzzy inference system

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