Groundwater is one of the key problems that must be faced and solved in underground engineering. Under special conditions, large-scale water damage accidents will be formed. Therefore, it is of great engineering significance to study the stability of surrounding rock of water-inrush roadway. This study focuses on laboratory experiments to study the preparation of similar materials, establish multiple linear regression equations of the ratio and physical parameters, analyze the influence law of roadway depth of roadway, water inrush height and water inrush time on the stability of surrounding rock of water-inrush roadway, and verify and expand it with numerical simulation. The experimental results show that the sensitivity of each factor to roadway stability is as follows: water inrush height > water inrush time > depth of roadway; In the test within 24 hours after water inrush, the sensitivity of each factor to roadway stability is also the height of water inrush > the time of water inrush > the depth of burial. This conclusion can provide an important basis for the rescue work after roadway water inrush and enrich the relevant test simulation after roadway water inrush.
Article
Study on proportion-making and stability of surrounding rock model test of water-inrush roadway
https://doi.org/10.21203/rs.3.rs-2124701/v1
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Similar material
model test
Creep of roadway
Orthogonal test
The safety of underground engineering has always been the focus of attention, in order to realize the safety and sustainability of underground engineering, especially underground coal mining. After the end of mining, the hollow roadway destroys the stress state of the original surrounding rock, leading to the deformation of the surrounding rock of the roadway will be aggravated with the increase of time, and eventually lead to various accidents 1. Among them, the safety hazards caused by underground water inrush remain high, and the water immersion of rock mass promotes the development of internal cracks in surrounding rock, increases the degree of softening, and increases the safety hazards 2,3. however, the current studies mostly focus on the warning before water inrush, while the research achievements during and after water inrush are relatively few. For underground projects with long service life, we should not only pay attention to the safety warning before water inrush, but also study the stability during the water inrush and the stability during the subsequent operation of underground projects after water inrush, so as to guide the rescue work of underground projects and reduce unnecessary casualties and property losses.
Y. Luo. et al. 4 studied the influence of water on tunnel failure. Taking the true rock of tunnel as the research object, they conducted several mechanical property tests, including triaxial compression tests, explored the failure form and failure principle, and concluded that water would weaken the relevant mechanical properties of rock mass. Y. T. et al. 5 took a reservoir as the research object and studied the changes of mechanical properties of slope rock mass in the reservoir under water-saturated condition. Through the field sampling test, it is concluded that the shear strength of the host rock mass is obviously greater than that of the bedding plane, and the quantitative analysis method is used to conclude that the reservoir tunnel can remain stable even in the saturated state. Stability of roadway surrounding rock has been the focus of the scholars focus on objects, especially in the process of secondary recovery, the stability of surrounding rock will be less than a mining, use numerical simulation and in-situ observation, range of destruction of surrounding rock of roadway in actual working condition and stress condition was studied, the damage form is obtained, provide theoretical guidance for the underground roadway support 6,7. Field tests and numerical simulations are mainly used for the stability of roadway surrounding rock, while indoor studies are relatively few. Through theoretical analysis, field experiments, indoor physical model simulation and numerical simulation, the mechanical properties, failure mechanism and prediction forms of roadway are studied. Conclusions such as surrounding rock instability mechanism and support method are obtained, which provide theoretical basis and guidance for related similar roadways. Indoor experiment simulation has irreplaceable advantages, many scholars 8–12 and embarked on the indoor simulation of similar materials selection research, to a variety of mechanical properties of the model test, the research and the relationship between the mechanical properties of ratio, the constitutive model is set up, put forward the model test collection and monitoring methods, etc. With the increase of disaster events in deep tunnels, many scholars 13,14 have conducted research on them and carried out stability research on deep tunnels subjected to high ground stress and strong dynamic disturbance through numerical simulation. It is concluded that the horizontal stress has a greater degree of deformation, displacement monitoring and failure form than the vertical stress of roadway surrounding rock, which gives theoretical guidance to the location selection of deep roadway and roadway disaster. On the premise of high similarity ratio and low strength mechanical property parameters, Y. B. et al. 15 established the relationship between the ratio of similar materials and mechanical property parameters in model model tests, and fitted multiple linear regression equations. According to the desired mechanical properties, the ratio of similar materials can be backward deduced by this equation, and the error of mechanical properties is within 1.6%. Taking an actual project as the research object, a tunnel model equation is established, the mechanism of tunnel deformation and stress distribution are analyzed, and an improved formula is proposed. The research results provide theoretical guidance for tunnel deformation 16–19. M. Ji. et al. 20 carried out actual measurement and statistics on the roadway of an ancient city, obtained the law of surrounding rock displacement and stress variation, and calculated its plastic region according to Moore-Coulomb criterion, optimized the roadway support parameters. Q.Z. et al. 21 In the face of water inrush problem in underground engineering, physical model simulation and numerical simulation are used to study the influence of dry-wet cycle on the deformation degree of model specimens, and the variation of surrounding rock stress, displacement and pore water pressure of roadway are analyzed. It is concluded that with the increase of dry and wet cycles, the principal stress of roadway surrounding rock increases gradually, and the degree of deformation increases gradually. This is in good agreement with the numerical simulation results.
In most of the existing experimental studies, small cylindrical rock and soil specimens are used for physical and mechanical tests, and then derived from the test results to the actual geotechnical engineering, which cannot simulate the actual engineering stage in a more comprehensive way. In the study of surrounding rock stability of water-related roadway, the problems such as roof water inrush, deformation and failure caused by roadway excavation in water-rich section or roof water seepage are usually studied.22–33 However, there are few studies on surrounding rock stability during and after roadway water inrush. In this paper, the orthogonal analysis method and the physical model simulation method are used to obtain the relationship between the similar material ratio and the main parameters of the physical model, and to predict the change law of the physical model during and after the water inrush, and to verify the rationality of the above conclusion by comparing and analyzing with the numerical simulation. At the same time, the multiple regression equation is the analytical solution rather than the numerical solution, which has high adaptability and generalization ability. On the other hand, the model test is a direct similar simulation of the actual roadway water inrush, instead of extrapolating the conclusion to the actual project, which can provide results closer to the real situation.
Based on the above, this paper innovation points can be divided into two: one is that with similar material proportion model specimens between the physical parameters of multiple regression equation, equations for analytical solutions, has good adaptability, can be either physical model is obtained by similar material proportion of mechanical performance parameters, also want to reverse the physical model parameters of similar material proportion; Second, the model test is the simulation of the actual working condition, namely, the water-inrush roadway, and there are few research results involved. Finally, numerical simulation is used to verify the rationality of the above conclusion.
2.1. Multiple linear regression equations of similar material ratio
|
Materials |
Compressive strength (MPa) |
Modulus of Elasticity (GPa) |
Water absorption (%) |
Softening coefficient |
Coefficient of permeability (10-4cm/s) |
Tensile strength (MPa) |
Density (g/cm-3) |
|---|---|---|---|---|---|---|---|
|
Actual rock mass |
58.8 ~ 98.1 |
5 ~ 80 |
10 ~ 20 |
75 ~ 85 |
1.341 ~ 11.175 |
3.92 ~ 12.7 |
1.8 ~ 2.8 |
|
Similar material |
1.176 ~ 1.962 |
0.1 ~ 1.6 |
10 ~ 20 |
75 ~ 85 |
0.19 ~ 1.58 |
0.0784 ~ 0.254 |
1.8 ~ 2.8 |
Due to the inhomogeneity and discontinuity of the structural plane of real rocks, as well as the randomness and discreteness of sampling, researchers use rock-like materials, namely similar materials, in exploring basic theoretical research. Therefore, before the similar material ratio test in the model experiment, the similar material and the similar ratio should be determined firstly, and the similar ratio and the similar material should be determined according to the geometric size, physical and mechanical characteristics and hydrologic characteristics of the target rock mass as well as the experimental conditions. To ensure that the main performance indicators are similar: compressive strength, elastic modulus, tensile strength, permeability, water absorption, softening coefficient, etc., ignore the secondary performance indicators. Through pre-experiment, the similar materials are finally determined as quartz sand, cement, gypsum and silicone. The cement is composite Portland cement (P.C42.5), the gypsum is glue-free white plaster, and the silicone aqueous solution is HCA 120, as shown in Fig. 1.
The similarity ratio is selected as follows:
The parameter range of actual rock mass was obtained by referring to books related to rock mechanics, and the ideal parameter range of similar materials was determined according to the above similarity ratio, as shown in Table 1.
|
No. |
Quartz sand content(%) |
the ratio of cement to gypsum |
the concentration of silicone |
|---|---|---|---|
|
1 |
60 |
1.5:1 |
10 |
|
2 |
65 |
1:1 |
15 |
|
3 |
75 |
1:1.5 |
20 |
|
4 |
80 |
1:2 |
25 |
After determining similar materials and similarity ratio, the approximate ratio range of similar materials is determined through pre-experiment to ensure that the mechanical property parameters of the physical similarity model formulated are around the range of similar materials. Finally, the quartz sand, the ratio of cement to gypsum and the concentration of silicone were taken as control factors. And four representative levels of each factor were determined (The water consumption of each group of specimens was about 10% of the time mass to ensure sufficient hydration reaction of the binder. Silicone concentration refers to the mass fraction of silicone solution in water). The L16(43) orthogonal test was designed, as shown in Table 2.
In order to explore the relationship between the ratio of similar materials and multiple mechanical property parameters, orthogonal test L16(43) showed a total of 16 different ratios, that is, 16 specimens. These specimens belong to a group, and a total of 6 groups need to be prepared. Physical and mechanical properties and hydrologic properties of each group of specimens were tested respectively. Configuration specimens are shown in Fig. 2.
|
No. |
Quartz sand content (%) |
Cement: gypsum |
Silicone concentration (%) |
Compressive strength (MPa) |
Modulus of Elasticity (GPa) |
Water absorption (%) |
Softening coefficient |
Coefficient of permeability (10-4cm/s) |
Tensile strength (MPa) |
Density (g/cm-3) |
|---|---|---|---|---|---|---|---|---|---|---|
|
1 |
65 |
1.5:1 |
10 |
7.257 |
1.501 |
16.095 |
46.46 |
1.700 |
1.233 |
1.89 |
|
2 |
65 |
1:1 |
15 |
4.714 |
1.324 |
17.048 |
92.86 |
1.889 |
0.523 |
1.85 |
|
3 |
65 |
1:1.5 |
20 |
6.132 |
1.397 |
18.452 |
48.48 |
3.258 |
0.662 |
1.87 |
|
4 |
65 |
1:2 |
25 |
10.861 |
1.179 |
15.826 |
37.33 |
1.947 |
0.415 |
1.91 |
|
5 |
70 |
1.5:1 |
15 |
3.207 |
0.710 |
14.497 |
63.28 |
0.509 |
0.571 |
1.94 |
|
6 |
70 |
1:1 |
10 |
7.523 |
1.306 |
16.634 |
59.64 |
1.802 |
0.548 |
1.87 |
|
7 |
70 |
1:1.5 |
25 |
4.506 |
0.539 |
16.019 |
64.29 |
0.554 |
0.572 |
1.91 |
|
8 |
70 |
1:2 |
20 |
4.217 |
0.895 |
16.933 |
84.80 |
0.328 |
0.457 |
1.85 |
|
9 |
75 |
1.5:1 |
20 |
3.026 |
0.824 |
14.503 |
60.87 |
1.038 |
0.310 |
1.87 |
|
10 |
75 |
1:1 |
25 |
4.639 |
0.772 |
15.444 |
95.42 |
0.665 |
0.388 |
1.85 |
|
11 |
75 |
1:1.5 |
10 |
2.893 |
0.789 |
14.898 |
51.31 |
2.048 |
0.376 |
1.86 |
|
12 |
75 |
1:2 |
15 |
3.833 |
0.895 |
17.749 |
65.22 |
1.590 |
0.305 |
1.84 |
|
13 |
80 |
1.5:1 |
25 |
2.317 |
0.723 |
16.190 |
77.68 |
5.148 |
0.191 |
1.84 |
|
14 |
80 |
1:1 |
20 |
2.695 |
0.543 |
16.243 |
56.26 |
1.261 |
0.080 |
1.76 |
|
15 |
80 |
1:1.5 |
15 |
1.712 |
0.298 |
17.580 |
62.63 |
1.174 |
0.288 |
1.82 |
|
16 |
80 |
1:2 |
10 |
1.689 |
0.690 |
19.641 |
61.93 |
2.170 |
0.165 |
1.73 |
Through orthogonal analysis of the experimental results as shown in Table 3, it can be seen that the content of quartz sand has the most significant influence on compressive strength, elastic modulus, permeability coefficient, tensile strength and density, and the proportion of cement and gypsum has a more significant influence on water absorption and softening coefficient. Let quartz sand be \({x}_{1}\), the ratio of cement to gypsum be \({x}_{2}\), and silicone concentration be \({x}_{3}\); Compressive strength index is \({Y}_{1}\), elastic modulus index is \({Y}_{2}\), water absorption index is \({Y}_{3}\), softening coefficient index is \({Y}_{4}\), permeability coefficient index is \({Y}_{5}\), tensile strength index is \({Y}_{6}\), density index is \({Y}_{7}\).
This equation can be used to deduce the ratio of similar materials according to the requirements of physical properties and hydrodynamic properties of similar materials in model tests. Determine the range according to the similarity ratio in the Table 1 above. The compiler uses the least square method to solve the overdetermined equation by Matlab software. The similar material ratio used in the model test is: quartz sand = 81.32%; Cement: gypsum = 1.38:1; Silicone concentration = 31.6%, and its corresponding parameters are shown in the Table 4.
|
Material |
Quartz sand content (%) |
Cement: gypsum |
Silicone concentration (%) |
Compressive strength (MPa) |
Modulus of Elasticity (GPa) |
Water absorption (%) |
Softening coefficient |
Coefficient of permeability (10-4cm/s) |
Tensile strength (MPa) |
Density (g/cm-3) |
|---|---|---|---|---|---|---|---|---|---|---|
|
Model |
81.32% |
1.38:1 |
31.6% |
1.9 |
1.1 |
15 |
80 |
1.5 |
0.2 |
1.8 |
2.2 Creep experiment of water-inrush roadway model
Model test system. The model system is divided into three parts. The first part is the loading system. The loading system uses heavy objects to load and magnifies the loading force according to the two-stage lever principle. The second is the model frame and the water retaining device. The similar materials for the model are prepared by using the ratio shown in Table 4, and then the similar materials are poured into the model frame for layering and compaction. The final molding size is 600*600*180mm. The water weighing device made of acrylic sheet is placed at the front and rear ends of the roadway to form a closed space, with water inlet at the front end, and the water level height inside the roadway is made by the principle of the connector, as shown in Fig. 3.
The experimental monitoring system is divided into two parts. The first is the stress monitoring system. DMTY series strain type earth pressure box and DM-YB1820 dynamic and static strain measurement system are used as the main detection system. The second was a displacement monitoring system, in which S-Eye software was used to control CCD camera SHL-500W to take photos. During creep, four points around the roadway were photographed at ten minute intervals, and then the images were imported to GOM Correlate for displacement monitoring and processing, as shown in Fig. 4.
(b)- Placement of stress monitoring point
Creep test design and process. Aiming at the influence factors of water inrush roadway on surrounding rock stability. Orthogonal test L9 (33) was designed, as shown in Table 6. Three influencing factors were taken as the depth of roadway, height of water inrush and time of water inrush, and three representative levels were selected for each factor, as shown in Table 5, to monitor the stress of 6 measuring points and displacement changes of 4 measuring points in the model test.
|
Factors No. |
Depth of roadway /m |
Height of water inrush /mm |
Time of water inrush/min |
|---|---|---|---|
|
1 |
200 |
1/4 H |
40 |
|
2 |
400 |
1/2 H |
60 |
|
3 |
600 |
3/4 H |
80 |
|
Note: H is the roadway height of 50 mm. |
|||
|
Factors No. |
Depth of roadway /m |
Height of water inrush /mm |
Time of water inrush/min |
|---|---|---|---|
|
1 |
200 |
1/4 H |
40 |
|
2 |
200 |
1/2 H |
60 |
|
3 |
200 |
3/4 H |
80 |
|
4 |
400 |
1/4 H |
60 |
|
5 |
400 |
1/2 H |
80 |
|
6 |
400 |
3/4 H |
40 |
|
7 |
600 |
1/4 H |
80 |
|
8 |
600 |
1/2 H |
40 |
|
9 |
600 |
3/4 H |
60 |
|
Note: H is the roadway height of 50 mm. |
|||
According to the test design in Table 6, similar materials were stirred, filled in the model, layered compaction, embedded pressure sensors, and maintenance for seven days. After seven days, constant water devices were first placed in the front and rear sections of the model roadway, and water injection was performed according to the experimental design requirements. Since similar materials will slowly absorb water, water needs to be continuously added from the injection port of the device in order to keep the water level constant during the whole water inrush experiment. Then, according to the depth of roadway of each group of tests, the converted in-situ stress value is obtained by calculating the in-situ stress formula and the similarity ratio, and the load is increased on the loading system until the pressure display reaches the corresponding converted in-situ stress value. Then the stress and displacement changes of each monitoring point in the model during the water inrush are monitored. After the test during the water inrush of each group of roadway is completed, the constant water device is removed, and the water inside the roadway is drained. The test after the water inrush is continued, and the subsequent stress and displacement changes of the model are monitored within 24 hours.
Taking Test-9 as an example, its depth of roadway is 600m, water inrush height is 3/4 H, and water inrush time is 60min. The experimental results are and analysis as follows:
3.1 During the period of water inrush.
The curves of stress variation with time at six measuring points during water inrush are shown in Fig. 5. The overall trend of vertical stress at point 1 decreased from 0.286 MPa at 0 min to 0.276 MPa at 82 min, with a decreasing rate of 3.50%. The main reason is that due to the influence of roadway water inrush, similar materials around measuring point 1 soften, which leads to a decrease in the overall stress. There are three specific reasons. First, the water inrush time of Test-9 is long. Second, the height of water inrush is high, up to 3/4 H; Third, the measuring point 1 is only 50mm close to the top of the roadway. The overall vertical stress at measuring point 2 increased from 0.308mpa at 0 min to 0.317mpa at 82 min, with an increase rate of 2.92%. There are two main reasons. First, measuring point 2 is 100mm away from the top of the roadway, and it is less affected by water inrush than measuring point 1, which ensures that the softening degree of similar materials around measuring point 2 is weak. Second, the softening of similar materials around the measuring point 1 results in the redistribution of stress around it. At this time, the measuring point 2 replaces the measuring point 1 as the main bearing part, so its stress increases somewhat.
The trend of measuring points 3 and 4 should be similar to that of measuring points 1 and 2. However, the trend of stress change at measuring point 3 was inversely increased compared with that at measuring point 1, from 0.264 MPa at 0 min to 0.278 MPa at 82 min, with an increase rate of 5.30%. The rising trend of stress change at measurement point 4 was much larger than that at measurement point 2, which increased from 0.302 MPa at 0 min to 0.353 MPa at 82 min, with an increase rate of 16.89%. The reason for this abnormal situation is that the similar materials in the model have higher water absorption and larger softening coefficient. In other words, the similar material is relatively easy to absorb water, but relatively difficult to soften. Therefore, the similar materials around measuring points 3 and 4 will soften as they absorb water and gain weight. Specifically, for measuring point 3, on the one hand, as it is close to the bottom of the roadway, it is greatly affected by water inrush similar to measuring point 1, resulting in a relatively high degree of softening. As a result, the stress value of point 3 decreased. However, on the other hand, the weight of similar materials around measuring point 3 increased due to the absorption of more water, so that the stress value of measuring point 3 increased. This "one positive and one negative" effect finally presents the overall trend of slow rise as shown in the figure. Similarly, on the one hand, because the measuring point 4 is far away from the arch bottom, the softening effect of similar materials around it is relatively weak; on the other hand, the mechanical property parameters of the similar materials, such as permeability coefficient and water absorption, are relatively large, so their weight increases more. Therefore, under the joint action of the two main factors, the rising trend of the stress value at measuring point 4 is relatively fast.
During the period of 0 ~ 3 min, the horizontal stress at point 5 showed a slight upward trend, increasing from 0.123 MPa to 0.131 MPa with an increase rate of 6.50%, and then remained at 0.131 MPa. The variation range of measuring point 6 is small and the overall stability is 0.149MPa. It can be seen that during the roadway water inrush, the impact on both sides of the roadway is small. To sum up, during the water inrush, the stress of arch roof and arch bottom is greatly affected, so the deformation is concentrated in the vertical direction, and the horizontal direction is small.
The displacement detection results of four measuring points of Test-9 are shown in Fig. 6. If the convergence value of shrinkage deformation is positive, it means that the measuring point moves into the roadway; otherwise, it is negative. Measuring points 1–2 are vertical convergent deformations, mainly in the forward direction, with a maximum value of 0.180 mm. Measuring points 3–4 are horizontal convergent deformations, mainly positive deformations, with a maximum value of 0.089mm. It can be seen that the vertical deformation is much larger than the horizontal deformation, so during the roadway water inrush, the main convergence deformation is in the vertical direction. The results are consistent with the stress detection results above.
3.2 After the water inrush.
Stress monitoring after water inrush is shown in Fig. 7, which is similar to the analysis during water inrush and will not be repeated. It can be briefly summarized as follows: measuring points 1–4 have obvious changes compared with measuring points 5–6, indicating that the vertical direction has more obvious changes compared with the horizontal direction. The displacement monitoring after water inrush is shown in Fig. 8. The convergence deformation in the vertical direction is mainly positive, and the deformation in the vault direction is inside the roadway, and the maximum convergence deformation value is 0.065mm. In the horizontal direction, the changes are mainly negative. The arch waist deforms outside the roadway, and the maximum convergence deformation value is -0.043mm. It can be seen that the roadway deformation is mainly in the vertical direction after water inrush. It can be seen from stress monitoring and displacement monitoring that the roadway deformation after water inrush is mainly in the vertical direction.
3.3 Orthogonal analysis of creep test
The other eight experimental analysis procedures are similar to the above Test-9 analysis and will not be described here (the detailed data graphs will be placed in the attachment packet). The main deformation is taken as the reference result, as shown in Table 7.
|
Test-1 |
Test-2 |
Test-3 |
Test-4 |
Test-5 |
Test-6 |
Test-7 |
Test-8 |
Test-9 |
|
|---|---|---|---|---|---|---|---|---|---|
|
Convergence deformation value during water inrush/(mm) |
0.069 |
0.049 |
0.126 |
0.057 |
0.056 |
0.068 |
0.074 |
0.041 |
0.065 |
|
Convergence deformation value after water inrush/(mm) |
0.069 |
0.049 |
0.126 |
0.057 |
0.056 |
0.068 |
0.074 |
0.041 |
0.065 |
As shown in Fig. 9, it can be seen that the sensitivity analysis of the stability of roadway surrounding rock during water inrush is water inrush height > water inrush time > depth of roadway. Among the three factors, the water inrush height range of 0.124 is much larger than the other two factors, that is to say, the change of the water inrush height has an obvious influence on the roadway deformation. When the water inrush height exceeds half of the roadway height, the roadway surrounding rock deformation rapidly deforms from 0.08mm to about 0.21mm. Because the high pressure of water will quickly penetrate into the surrounding rock of the roadway and make it soften. The second is the water inrush time. After the water inrush time is 80min, the deformation of roadway surrounding rock increases rapidly from 0.11mm to 0.16mm. Because with the increase of immersion time, the seepage range and softening degree of roadway surrounding rock will increase rapidly. However, the variation of depth of roadway of roadway has little influence on the deformation of surrounding rock.
After water inrush, that is, the water in the roadway is drained, the sensitivity analysis of roadway deformation is as follows: water inrush height > water inrush time > depth of roadway. As shown in Fig. 10, the subsequent deformation of roadway surrounding rock within 24 hours after water inrush is much smaller than that during water inrush, basically keeping within 0.09mm. The influence of water inrush height and water inrush time is similar to that during water inrush. As for the influencing factors of depth of roadway, it can be seen that the deformation of roadway surrounding rock decreases from 0.08mm to 0.06mm when the depth increases from 200m to 400M.
When the depth of roadway continues to increase, the amount of deformation is almost constant. The reason is that with the increase of depth of roadway, the ground stress increases, the horizontal and vertical stress of roadway surrounding rock is greater, so the surrounding rock is closer, and the bearing capacity will be stronger. When affected by water inrush, some surrounding rocks will lose their bearing capacity due to softening, but the redistributed stress is more easily absorbed by the surrounding surrounding rocks, so the deformation of roadway surrounding rocks is small.
To sum up, from the model test, the deformation of surrounding rock of roadway is mainly concentrated in the period of water inrush. When the height of water inrush is high, the deformation of surrounding rock of roadway will be aggravated by a long time of water inrush. Therefore, in the actual project (reflected in the actual project, according to the similarity ratio, the deformation amount and time in the model test conclusion should be multiplied by the corresponding similarity ratio), the rescue work should be carried out in time after the water inrush to reduce casualties and property.
4.1 Model parameters.
Numerical simulation is used as an auxiliary analysis method to simulate and verify the surrounding rock deformation during and after the water inrush. Before that, triaxial compression experiments were carried out on similar materials to obtain the cohesion C and internal friction Angle φ of the model roadway, as shown in Fig. 11. In the numerical simulation software, the model size length × width × height = 30 m×30 m×9 m, and the roadway section shape is 2 m×2.5 m straight wall semicircular arch (this size is the actual rock mass size, corresponding to the similar size of the model test above). And parameter design is shown in the Table 8. Similarly, design the same orthogonal table as the model test above shown in the Table 9. In the numerical analysis, in order to facilitate the expression that the seepage range gradually expanded with time, the records were recorded from 0, and each recording interval was 1/6 of the water inrush time, and each labeled line was called the seepage line, which was recorded for a total of 6 times. Note that in order to visualize and intuitively, The influence degree of each factor on the seepage velocity around the roadway is substituted for the deformation convergence value in the model test, which indirectly indicates the influence degree of each factor on the stability of surrounding rock of the roadway.
|
Material |
Unit type |
Constitutive model |
Modulus of elasticity /GPa |
Poisson's ratio |
Bulk density /kN/m3 |
Cohesion /MPa |
Angle of internal friction /° |
|---|---|---|---|---|---|---|---|
|
Rock mass |
3D/2D entity |
Merle Cullen |
59.8 |
0.3 |
18 |
3 |
59.11 |
|
Factors No. |
Depth of roadway /m |
Height of water inrush /mm |
Time of water inrush/d |
|---|---|---|---|
|
1 |
200 |
1/4 H |
0.2 |
|
2 |
400 |
1/2 H |
0.4 |
|
3 |
600 |
3/4 H |
0.6 |
|
Note: H is the roadway height of 2.5m. |
|||
4.2 Analysis of numerical simulation results.
Taking Test-9 as an example also, the seepage range results of the numerical simulation are consistent with the model during the water inrush, as shown in Fig. 12. With the increase of time, the percolation range increases gradually and the percolation line expands continuously. In terms of seepage expansion velocity, arch bottom > arch waist > vault. At 0.4 days of numerical simulation of actual working conditions, that is, 70 minutes in the model test, the seepage area involves a large range, and the arch bottom reaches 6 ~ 7 times of the hole. The infiltration area on both sides of the arch waist is basically symmetrical, about 4 ~ 5 times the hole. The seepage area of the vault is about 1 ~ 2 times the size of the hole. In the process of seepage, it can be seen that the seepage range of the two is consistent.
Other numerical simulation test results are similar to those of Test-9 and are not described in detail (Test data are placed in the attachment). Range analysis was carried out on the results of numerical simulation of seepage range. The range analysis of the convergence deformation results of the numerical simulation is shown in the Fig. 13 and Fig. 14.
From the analysis of numerical simulation results, it can be seen that the sensitivity of each factor to the combined seepage velocity during the water inrush is: water inrush height > burial depth > water inrush time; The sensitivity of all factors to the combined seepage velocity after water inrush is as follows: water inrush height > water inrush time > buried depth. On the whole, the numerical simulation results are similar to the model test results. Specifically, during and after water inrush, the seepage lines of the numerical simulation are similar to those of the model test, indicating that the influence law of the model test is similar to that of the numerical simulation when the roadway is affected by water inrush, and the two verify each other. Both numerical simulation and model tests show that the height of water inrush is the main influencing factor of surrounding rock deformation, while the depth and time of water inrush are the secondary influencing factors, which have similar effects. In the stage after water inrush, the three influencing factors have a similar range, and all have a weak effect on the deformation of roadway surrounding rock. Therefore, the conclusion of the above numerical simulation of the actual working condition is similar to the conclusion of the model test, which not only verifies the rationality of the model test, but also indicates the reliability of the results.
The relationship between the ratio of similar materials and several mechanical properties parameters was established, and multiple linear regression equations were fitted. And according to the mechanical property parameters of the actual rock mass, according to the similarity ratio, the proportion of similar materials in the roadway model is calculated by MATLAB in reverse. Based on the similar material ratio, a tunnel model is formulated and creep tests are carried out. The influence of three factors on roadway deformation during and after water inrush is analyzed. The deformation of roadway surrounding rock is the most obvious during water inrush, and the height of water inrush is the main influencing factor. After water inrush, roadway surrounding rock deformation is small, suitable for rescue work. Finally, the same creep test of real rock mass is carried out by numerical simulation, and the conclusion is similar to the model test, so as to verify the rationality of the model test and the reliability of the results.
These results prove the validity of mechanical analysis results, increase the study of indoor model test, and improve the understanding of surrounding rock stability of water-inrush roadway.
Data availability
The datasets generated and analyzed during the current study are not publicly available as the datasets are from the team and are only available for this study, but datasets are available from the corresponding author on reasonable request.
Acknowledgements
Thanks for the financial support from the Natural Science Foundation of Shandong (ZR2019MEE082).
Author contributions
Jiwei Li. wrote the main manuscript text. Ziyi Zhou. and Jiwei Li. conducted the experiments. All authors reviewed the manuscript.
Declaration of interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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No competing interests reported.