Based on uncertainty measure theory, a stability classification and orderarranging model of surrounding rock was established. Considering the practical engineering geologic condition, 5 factors that influence surrounding rock stability were taken into account and uncertainty measure function was obtained based on the in situ data. In this model, uncertainty influence factors were analyzed quantitatively and qualitatively based on the real situation; the weight of index was given based on information entropy theory; surrounding rock stability level was judged based on credible degree recognition criterion; and surrounding rock was ordered based on orderarranging criterion. Furthermore, this model was employed to evaluate 5 sections surrounding rock in Dongshan tunnel of Huainan. The results show that uncertainty measure method is reasonable and can have significance for surrounding rock stability evaluation in the future.
Entering the new century, with the rapid and sustainable development of national economy and the implementation of the western great development strategy, railway, highway, and hydropower construction gained hitherto unknown development. In particular in recent years, the construction scale and quantity of tunnels were increasing constantly; long tunnels came forth increasingly. According to incomplete statistics, there were more than 1700 highway tunnels built in China [
As the main basis of engineering design and supporting structure calculation, surrounding rock stability evaluation has attracted widespread attention in engineering field. Many scholars had researched this problem and put forward the evaluation methods of all kinds of engineering which could be classified as the single index method and the comprehensive evaluation method [
The uncertainty information and related mathematical theory were first proposed by Professor Wang [
Meeting formula (
In the construction of single index measure evaluation matrix, we should first establish single index measure function. At present, construction methods of single index measure function mainly include linear, exponential, parabola, and sinusoidal. Linear type uncertainty measure function is currently the most widely used and the most simple measure function, so this paper also uses linear type uncertainty measure function. No matter what kind of simulation function is, “nonminus, unitary, additivity” must be satisfied. According to the characteristics of specific indexes, suitable uncertainty measure functions are selected; linear type uncertainty measure function is currently the most widely used and the most simple measure function, so this paper also uses linear type uncertainty measure function.
Matrix
If
In addition to discrimination which evaluation level
In this paper, take tunnel rock mass actual measurement data of Dongshan in Huainan Basin as the research object provided by Liu [
Evaluation factors and grading standard.
Factors  Stability grade  

Stability 
Relative stability 
General stability 
Instability 
Very instability  
(1) Rock quality designation (RQD)/%  >90  75–90  50–75  25–50  <25 
(2) Rock uniaxial compressive strength/MPa  >120  60–120  30–60  15–30  <15 
(3) Rock mass integrity coefficient  >0.75  0.45–0.75  0.3–0.45  0.20.3  <0.2 
(4) Strength coefficient of structural face  >0.8  0.6–0.8  0.4–0.6  0.2–0.4  <0.2 
(5) Groundwater seepage (L/min·10 m)  <5  5–10  10–25  25–125  >125 
Survey statistics table of surrounding rock.
Section  Stability evaluation index  





 

40.0  25.0  0.28  0.35  35.0 

70.5  40.5  0.43  0.55  15.5 

40.5  20.0  0.25  0.30  30.0 

72.0  50.0  0.55  0.55  20.0 

20.0  50.0  0.23  0.51  13.0 
According to the definition of single index measure function above, combined with grading standards in Table
Single index measure function of rock quality designation.
Single index measure function of rock uniaxial compressive strength.
Single index measure function of rock mass integrity coefficient.
Single index measure function of strength coefficient of structural face.
Single index measure function of groundwater seepage.
According to single index measure function above and combined with the actual data in Table
Formula (
Take credible degree
Evaluation results of uncertainty measure model.
Sections  General uncertainty measure  Evaluation results of uncertainty measure model  Evaluation results of artificial neural network model  

I  II  III  IV  V  

0  0  0.27  0.73  0  IV  IV 

0  0.21  0.75  0.04  0  III  III 

0  0  0.15  0.8  0.05  IV  IV 

0  0.29  0.7  0.01  0  III  III 

0  0.1  0.49  0.09  0.32  IV  IV 
According to order formula, because
Evaluation of surrounding rock stability is controlled and affected by many factors. And these factors have obvious diversity, variability, uncertainty, and so forth; considering the characteristics of surrounding rock stability evaluation, uncertainty measure evaluation method is introduced into stability evaluation of surrounding rock, and uncertainty measure evaluation model of surrounding rock stability is built.
According to influence factors of surrounding rock stability and grading standards, uncertainty measure functions of surrounding rock stability evaluation index are built based on uncertainty measure theory, the weight of each index is calculated based on information entropy theory, surrounding rock stability level is evaluated based on credible degree recognition criterion, and finally surrounding rock is ordered based on orderarranging criterion.
The stability analysis of 5 surrounding rock sections in Dongshan tunnel of Huainan shows that uncertainty measure evaluation model is more scientific and reasonable. The surrounding rock stability level and level order could be established in this modeling system. It provides a new mentality for surrounding rock stability evaluation and shows important theoretical and practical significance.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This work was financially supported by the major program of the National Natural Science Foundation of China (41030749), the National Natural Science Foundation of China (41072223), and the Special Fund for Basic Scientific Research of Central Colleges (CHD2011JC111).