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Back analysis of geomechanical parameters in underground engineering using artificial bee colony.

Zhu C, Zhao H, Zhao M - ScientificWorldJournal (2014)

Bottom Line: To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis.The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution.The results show the proposed method is feasible.

View Article: PubMed Central - PubMed

Affiliation: School of Civil Engineering, Henan Polytechnic University, Jiaozuo 454003, China.

ABSTRACT
Accurate geomechanical parameters are critical in tunneling excavation, design, and supporting. In this paper, a displacements back analysis based on artificial bee colony (ABC) algorithm is proposed to identify geomechanical parameters from monitored displacements. ABC was used as global optimal algorithm to search the unknown geomechanical parameters for the problem with analytical solution. To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis. The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution. The results show the proposed method is feasible.

Show MeSH
Comparison between monitored displacement and predicted displacement using identified parameters.
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Related In: Results  -  Collection


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fig11: Comparison between monitored displacement and predicted displacement using identified parameters.

Mentions: To verify the model, we suppose there is a tunnel (see Figure 10). The size of tunnel, geomechanical parameters, and in situ stress are listed in Figure 10. The value in Figure 10 is theoretical values. Displacement values for some key points, indicated by nodes, are calculated by elastic finite element method. The suggested algorithm above is used to identify initial geostress components P1 and P2, and angle between P1 and P2. We used orthogonal experiment design to create 25 sets of tentative geostresses P1 and P2 and angle between P1 and P2. The training samples will be obtained through computing the displacement of each set of tentative geostresses. Then the LSSVM model was build based on (13). The training samples and model parameters of LSSVM are listed in Table 5. In situ stresses, P1 and P2, and angle at different stages can be identified according to the procedure of Section 4.3. Identified in situ stress, P1 and P2, and angle at different stages are listed in Table 4. The comparison between displacement of the key points using the theoretical parameters and displacements identified by back analysis based on ABC and LSSVM is shown in Figure 11. Stresses of surrounding rock are shown in Figure 12 after stage 3. Results show the proposed method can effectively identify the in situ stress.


Back analysis of geomechanical parameters in underground engineering using artificial bee colony.

Zhu C, Zhao H, Zhao M - ScientificWorldJournal (2014)

Comparison between monitored displacement and predicted displacement using identified parameters.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4127281&req=5

fig11: Comparison between monitored displacement and predicted displacement using identified parameters.
Mentions: To verify the model, we suppose there is a tunnel (see Figure 10). The size of tunnel, geomechanical parameters, and in situ stress are listed in Figure 10. The value in Figure 10 is theoretical values. Displacement values for some key points, indicated by nodes, are calculated by elastic finite element method. The suggested algorithm above is used to identify initial geostress components P1 and P2, and angle between P1 and P2. We used orthogonal experiment design to create 25 sets of tentative geostresses P1 and P2 and angle between P1 and P2. The training samples will be obtained through computing the displacement of each set of tentative geostresses. Then the LSSVM model was build based on (13). The training samples and model parameters of LSSVM are listed in Table 5. In situ stresses, P1 and P2, and angle at different stages can be identified according to the procedure of Section 4.3. Identified in situ stress, P1 and P2, and angle at different stages are listed in Table 4. The comparison between displacement of the key points using the theoretical parameters and displacements identified by back analysis based on ABC and LSSVM is shown in Figure 11. Stresses of surrounding rock are shown in Figure 12 after stage 3. Results show the proposed method can effectively identify the in situ stress.

Bottom Line: To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis.The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution.The results show the proposed method is feasible.

View Article: PubMed Central - PubMed

Affiliation: School of Civil Engineering, Henan Polytechnic University, Jiaozuo 454003, China.

ABSTRACT
Accurate geomechanical parameters are critical in tunneling excavation, design, and supporting. In this paper, a displacements back analysis based on artificial bee colony (ABC) algorithm is proposed to identify geomechanical parameters from monitored displacements. ABC was used as global optimal algorithm to search the unknown geomechanical parameters for the problem with analytical solution. To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis. The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution. The results show the proposed method is feasible.

Show MeSH