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With the development of civil engineering, the box shaped beam has been widely applied in practical engineering. In general, it is composed of concrete and steel and compared with mechanical analysis, little research has been carried on the back analysis of elastic modulus of box shaped beam. With degraded solid element theory, the shell element is deduced and the displacement function is obtained. The necessary observation revision equation and Kalman regenerative matrix are derived. The stochastic filtering back analysis steps of elastic modulus of the box shaped beam are presented and the analytical procedure is compiled. Through analysis of a classic example, some important conclusions about stochastic filtering back analysis of elastic modulus of box shaped beam are obtained.

In the large-area soft foundation reinforcement project, the loading process is relatively complicated and the preloading load is not consistent with the service load in most cases; thus the conventional settlement curve fitting method cannot nicely predict the post-construction settlement of foundation under the service load. The back analysis method can be used to obtain the calculation parameters, so the settlement and consolidation conditions under various different loads at different time can be calculated and the foundation settlement hereby can be estimated exactly.

Laboratory experiment and back analysis are common methods for selecting shear strength parameters. However, every way has its shortcomings. A way combining two methods is used to determine shear strength parameters for Hutoumao landslide. The result can meet the need of project according to comparison experience value.

The paper deals with the back analysis method in geotechnical engineering, that goal is evaluation the more objective and reliable parameters of the rock mass on the basis of in-situ measurements. Stress, deformational, strength and rheological parameters of the rock mass are usually determined by some inaccuracies and errors arising from the complexity and variability of the rock mass. This higher or lower degree of imprecision is reflected in the reliability of the mathematical modelling results. The paper presents the utilization of direct optimization back analysis method, based on the theory of analytical functions of complex variable and Kolosov-Muschelischvili relations, to the evaluation of initial stress state inside the rock massif.

Through the analysis of ‘gap parameter’ and ground movement pattern in shield tunnel, this paper researched and corrected the model of ‘equivalent circle zone’ proposed by predecessors. The ‘equivalent circle zone’, which is a comprehensive reflection of shield gap, grouting filling and stratum perturbation, is considered to be unequal thickness in this paper. With the measured data of practical shield tunneling, the unknown parameters of corrected ‘equivalent circle model’ can be obtained by back analysis through numbering analysis. The back analysis of Shen Zhen line-5 is carried out to validate the rationality of the method proposed in this paper. Research shows that: the corrected model can reflect the feature and values of ground settlement more factually than the previous model and can offer a reference to predict ground deformation during shield tunneling.

The value of thermal parameter is very crucial in simulating analysis on temperature control for mass concrete. The inverse analysis on some practical project is done by genetic algorithm and finite element method on the basis of observational data of temperature on the site. The temperature control simulation calculation is performed based on parameters obtained from inverse analysis on this project, so that the temperature distribution is consistent basically with the practical one. With improvement of micro-genetic algorithm, the genetic algorithm becomes globally-optimal by changing the optimal reserving and re-starting strategies. The results show this method is very practical in high precision of calculation in mass concrete parametric inversion.

The surrounding rock strain field monitoring have been done during a highway tunnel excavation. The rock rheological parameters was inversed by neural network based the field monitoring data. The predicted value and the field monitoring data have been compared, the result shows that the difference is 12%, the predicted value is credible.

Jixi mine area is one of the early mined areas in China and it's a typical deep mine. Because of large deformation of underground roadway and dynamic disasters occurred frequently in this mine, five measurement points of in-situ stress in this mine was measured and then analyzed with inversion. Based on these in-situ stress measurement data, numerical model of 3D in-situ stress back analysis was established. According to different stress fields, related analytical samples of neural network were given with FLAC program. Through the determination of hidden layers, hidden nodes and the setting of parameters, the network was optimized and trained. Then according to field measurement of in-situ stress, back analysis of initial stress field was conducted. Compared with field measurement, with accuracy requirement satisfied, it shows that the in-situ stress of rock mass obtained is basically reasonable. Meanwhile, it proves that the measurement of in-situ stress can provide deep mines with effective and rapid means, and also provide reliable data to optimization of deep roadway layout and supporting design.

An new intelligent displacement back analysis, named as CACA-SVM, was proposed based on support vector machine (SVM) and Continuous Ant Colony Algorithm (CACA). On the one hand, CACA-SVM used SVM to build the nonlinear mapping relationship between them. On the other hand, CACA-SVM used the global optimization performance of CACA to search the optimal rock mechanics parameters in the global space. The nonlinear mapping relationship built by SVM can fit and forecast the measuring point displacements under different parameters with high accuracy, avoiding the complex numerical calculation. CACA can prevent object function from trapping in local optimum and improve precision of back analysis. Case study shows that the forecasting trend was in good agreement with the measured trend, which indicated that the model was suitable for solving the geotechnical engineering problem of nonlinearity and uncertainty and could well be applied to displacement back analysis.

A new method of displacement back analysis, named SVM-CTS, was proposed based on support vector machine (SVM) and continuous tabu search (CTS). On the one hand, SVM-CTS used SVM to build the nonlinear mapping relationship between the measuring point displacements and rock and soil mechanics parameters of positive analysis based on the study samples. On the other hand, SVM-CTS used the global optimization performance of CTS to catch the optimal rock and soil mechanics parameters in the global space. The nonlinear mapping relationship built by SVM can fit and forecast the measuring point displacements under different parameters with high accuracy. CTS can prevent object function from trapping in local optimum and improve precision of back analysis. Case study shows that SVM-CTS can be well applied to the displacement back analysis in geotechnical engineering.

Tunnel information construction is more and more concerned because of the uncertainty and complexity of geological body. Based on the back analysis principle of tunnel and intelligent science arithmetic, the paper self-developed tunnel information construction analysis visualization system by Visual C# platform and VTK techniques in order to the confliction between tunnel construction expending too much time and the construction period demand. Firstly introduced global optimization method-Difference Evolution (DE) Algorithm and combined it with finite element method (FEM) in order to back analyze the surrounding rock parameters. Then constructed the total software framework and developed the program of the information construction analysis intelligent visualization system. Applied the system to the Dalian Metro tunnel engineering construction and got satisfied results. The soft system developed by the paper has active meaning to promote the intelligence, visualization and automation of the tunnel construction.

The selection of material parameters relates to the excavation stability of the underground caverns. However, back analysis is an efficient method to evaluate mechanical parameters. Given the defects of BP neural network, such as low capability of generalization and long training time, by using GA, which have global optimization ability to optimize the BP neural network weights. The parameter of surrounding rock was designed by uniform and orthogonal method, not only reduced the iterative time also improved the accuracy of the prediction. The proposed method is further illustrated with its application to the underground cavern of Lvchunba railway tunnel. Based on the surrounding rock’s parameters obtained by back analysis, the displacement of the surrounding rock was predicted. The results showed that the error between numerical calculation value and actual monitoring value was 13.2%,-8.3%,-8.9%,9.4% respectively.

Chengdu - Mianyang – Leshan (C-M-L for short) high speed railway in Chengdu section is located in the ground of weathered Mud rock overlying deep Chengdu clay area. Based on Chengdu clay ground of in high-speed railway construction project of CML, this article introduced the Burgers model to establish the objective function to analysis rheological constitutive model. The visco-elastic parameters of Burgers model are determined by back analysis of field monitoring data. By the method of iterative back analysis by layer of visco-elastic parameters, based on measured result, predicted the late settlement, and comparison with the follow-up observations records to verify the Burgers model.

The thermodynamic parameters and boundary conditions is one of the important factors affecting the simulation precision of concrete temperature control, and through the test way obtaining these parameters demands high cost, and often works with practical mismatch. This paper introduces the simulated annealing method, analyse and improve the simulated annealing method . The results show that, the improved of simulated annealing algorithm can be used for the study of concrete temperature field inverse.

The principle of Particle Swarm Optimization (PSO) and Homotopy Optimization (HO) is introduced. For the purpose of improving the local-searching efficiency of the PSO，HO-PSO is presented by combining the PSO with HO. New space homotopy curve produced by homotopy particle function directs the particle’s local optimization. For comparison，the methods of HO-PSO, PSO and FEM(Finite Element Method) are used to calculate the tunnel parameter inversion of the Shuibuya Project on the basis of the measured displacements. The result shows that HO-PSO takes smaller time compared with PSO and FEM in a same precision level, and the calculated values are in good agreement with the measured values，which also indicate that the HO-PSO can be well applied to the displacement back analysis in tunnel engineering.

The parabolic-apex numerical back-analysis method (PNBM) was proposed to obtain such physical-mechanics parameters as Young's modulus and lateral pressure coefficient of surrounding rock by 3D FEM numerical analysis based on in-situ monitoring data. Taking Xiang-an Subsea Tunnel (located in Xiamen, Fujian Province, China) for example, adopting the PNBM using ABAQUS software, three dimensional elastic-plastic FEM-PNBM of tunnel surrounding rock was validated using in-situ monitoring data. The results show as follows: Using the PNBM, not only may high calculation precision be obtained, better meeting the demand of actual projects, but also more reasonable and reliable physical mechanics indices of surrounding rock such as Young's modulus and lateral confinement pressure coefficient, may be obtained. The applicability and the simplicity of this proposed method also support its usefulness.

The inverse problem of parameter identification is deal with by minimizing an objective function that contains the difference between observed and calculated dam displacements. The optimization problem of minimizing objective function is solved with genetic algorithm. The calculated dam displacements are simulated by using finite element method according to water level change acting on dam upstream. The practical dam displacements are observed on the dam crest. The investigation shows that the forecasted dam displacements agree well with observed ones. The effectiveness of proposed inversion procedure is validated.

The measured data and mechanical parameters were considered unknown but bounded property and interval numbers were used to denote the measured data and mechanical parameters. The interval parameter perturbation method was presented to solve interval FEM and the interval inverse analysis model was established. Based on the interval parameter perturbation method, the mean and deviation of the mechanical parameters were obtained by the back analysis. For the example of the mechanical parameter back analysis of rock mass cave in the large hydro-electric power station, the effect on the measured data precision was studied. From the results it can be found that the method is reasonable and feasible.

A method for modulus back analysis of pavement structure based on particle swarm optimization (PSO) is presented. The principle and implementation process of the method is detailed. Some theoretical and experimental data of pavement deflection are selected to test its performance. The contrastive analysis of the modulus inversion results of the proposed method and some representative pavement modulus back calculation softwares using the same deflection data is also performed. The results show that the presented method has relatively high identification accuracy and notably computational stability, which can effectively reduces the influence of initial tentative value on inversion results of pevement modulus.

Tunnel engineering information construction has been widely used, and the back analysis is its core. As the common useful method, displacement back analysis is of special advantages. This paper introduces the calculative method based on the application in a railway tunnel. The result shows that strain softening model can be used to simulate the large deformation mechanism of surrounding rock.

The self-developed finite element program is used to the simulation of true tunnel with C++ language. Applying to Line 1 of Dalian Metro, inversion parameters and true parameters are close, which indicates the superiority and good prospects of the program, and it can be used for quantitative analysis of actual tunnel.

This article based on the underground workshop region of the Shenzhen pumped storage power station, carrying on back-analysis for the initial geostress field of the region of station with method of this article, and then we can obtained the actual initial ground stress.This article based on the measured ground stress data, a 3D non-linear finite element back analysis numerical model for ground stress is set up and the landforms is simulated. This thesis has used ANSYS to do finite element calculation for rocks and soils, the corresponding sample of neural network have been gained. By setting the parameters, the neural network is optimized, then the network is trained with the optimized result. Finally, the initial ground stress field is back-analyzed with in-situ measured stress values. The result is compared with measured value, which meets the requirement for accuracy, showing the reasonabilily of the rock ground stress field obtained.

In order to obtain the stress distribution in deep level of Datai mine, a nonlinear back analysis method for rock mechanical parameters was proposed by combining genetic algorithm and FLAC3D (GA-FLAC3D). First the hollow inclusion stress gauge (stress relieving method) was used to complete the measurement of local in-situ stress; and then the rock mechanical parameters were obtained by using back analysis; at last the ground stress in deep level was obtained. The results showed, this method is quick in calculation, and has global convergence. The convergence accuracy of normal stress is about 90%.

It is very important to predict ground settlement and provide effective dada for construction on soft soil foundation. There are several prediction methods.However, back analysis method is identified as the most effective method in all these methods. The most primarily used method in back analysis methods is optimization algorithm. In this paper, to realize accurate prediction and calculation of soft soil foundation settlement, an improved immune genetic algorithm is presented by introducing immune mechanism to genetic algorithm. A example was given and illustrated that this algorithm can greatly improve calculation speed and accuracy in predicting soft soil foundation settlement.

Every year, China suffers greatly from economic losses caused by rockfall hazards. The key to effectively control rockfall hazards is to obtain an accurate rockfall trajectory. However, not only is rockfall trajectory complex and unable to be described accurately in mathematical formula, but basic parameters influencing its movement are also unable to be measured directly. Therefore, the back analysis method combining laboratory rockfall simulation test with computer numerical simulation is adopted to study rockfall trajectory and its basic parameters. The results show that the method can not only get basic parameters of rockfall trajectory such as coefficient of restitution and angle of frication, but also precisely deduce true rockfall trajectory, which can provide help in effectively controlling rockfall hazards.

The accuracy of thermal parameters, which are one of the important conditions to study the problem of temperature control and crack prevention of concrete, directly influence the calculation of concrete temperature and stress field. Based on basic genetic algorithm, the FORTRAN procedure was programmed after improving its defects. According to a project, the temperature test was carried out in one of sections of a prototype concrete structure, and the measured temperature dates were obtained. Based on the improved genetic algorithm and the measured temperature dates, the thermal parameters of concrete were obtained after back analysis, and the calculated and measured values were compared. The results show that the improved genetic algorithm provides a effective way for back analysis of concrete temperature field.

The back analysis principle and method for thermal conductivity of RCC is introduced in this paper, and a Jiang Ya RCC dam is cited as a building example , on the basis of prototype temperature data of dam, the mathematic model by Difference principle is founded, the thermal conductivity of RCC is obtained. The result is similar to the data which is received in the laboratory. The back analysis is proved credible. The back analysis for thermal conductivity, on the one hand, actual safety of the completed projects could be evaluated; on the other hand, the design and construction in progress may be optimized. the scientific foundation for optimizing the design and monitoring the running of dam is provided. And it is provided with some scientific value and practical significance.

Aiming at the complexity and uncertainty of rock and soil body, the paper the paper introducing a new global intelligent optimization arithmetic – Difference Evolution (DE) and combined with stress return mapping nonlinear elastic-plastic Finite Element Method(FEM), realizing rapid elastic plastic parameters identification of surrounding rock. The analytical theory and method are introduced in detail, analyzes the tunnel of Dalian Metro by the proposed method, and gets satisfied results.

A great number of large-scale hydropower stations are to be constructed in southwest China. Many of them feature great depth or high in situ stresses. In this paper, a coupled damage and rheology method is adopted for stability analysis of an underground cavern group with time effect to consider the rock deformation. Meanwhile, a new method considering the crackopening displacement is used for back analysis. The stability of the surrounding rock masses is then evaluated.

Aiming at the complexity and uncertainty of rock and soil body, the paper proposed a tunnel surrounding rock parameters identification method combining numerical simulation, particle swarm optimization and artificial neural network. The method acquired data set between rock soil parameters and monitoring displacement and trained artificial neural network. The analytical theory and method are introduced in detail, analyzes the tunnel of Dalian Metro by the proposed method, and gets satisfied results. Which states that the parameters identification method based on PSO-ANN is feasible and has good foreground.

Problem is brought forward by the weak soil layer and the soil near slide surface. The weight back analyzed is presented to solve the problem. For obtaining the weight coefficient, the division of the inclination curve is done. After that, the soil can be divided into several blocks. The displacement of the curve is described by two values: the sliding and the deformation displacement. The method of the weight coefficient calculation is proposed applying the deformation displacement. At last, the sensitivity of the new methods is calculated.

With the rapid development of bridge engineering, the application of supporting and protecting structure that embeds in deep foundation engineering is gradually applied in the design and construction of large-scale suspension bridge. Due to the few amount of stress gauge steel that are pre-installed in the diaphragm wall reinforcement cage in deep foundation engineering and discrete data, it is difficult for the existing frequently-used method to reflect stresses of each part of the wall truly. And for major engineerings, like anchorage foundation, it is necessary to know the stress state of diaphragm wall on time in order to provide basis for decision making for the excavation site. By adopting finite element method, demonstrating the characteristics of its force reversely by using wall deformation and based on the wall deformation data measured in the field, this paper provides strong guarantee for ensuring the safety and reliability of construction.

Initial geostress is one of the most important factors in coal mining. By combination the finite difference software FLAC3D with multivariate linear regression theory, 3-D initial geostress in situ is back analyzed, which also considers the effect of gravimetrical and tectonic stress. The back analysis results of initial geostress in Laohutai coal mine are in a good agreement with the in-situ test results, which provides theoretical support on prediction of geostress and also more convenient geostress data in coal mining.

For the aim of being able to reflect the randomness, fuzziness and the relevance between the two existed in the seepage property of earth rockfill dam, by assumption of normal cloud distribution of the seepage parameter, a new back-analysis method based on cloud neural network(CNN) is presented in this paper, which has being used in the nonlinear system simulation successfully. At last the method was applied to the back analysis of a dam’s seepage property, and the result shows that the application is feasible.

Problem exists in the tradition studies of the stratified soil slope back analysis. The limitation of the tradition method was analyzed on the basis of previous research in this paper. And the definition of the soil layer displacement, which overcomes the size effect of the soil layer, was presented. This displacement was weighted in the objective function, reflecting the sliding characteristics of different soil. Then the calculation method weight of weighted was presented. At last, the strength parameter sensitivity of the objective function was calculated by an example. The result showed the stratified soil slope back analysis can be solved by the new method.

The paper aims to analyse the e ects of topography and building position on themagnitude of pressure exerted by snow avalanches against buildings, through a structural backanalysis and numerical uid-dynamics. Studying a real snow avalanche impact occurred in2008 which destroyed a village in Valsavarenche (Aosta Valley - IT), the attention is focused onthe avalanche ow deviation caused by the destructive interaction with a rst building, whichprotected part of a second building beyond it. By means of photographical and in situ survey,a detailed description of avalanche geometrical, dynamical and physical properties is outlined.A structural investigation, based both on debris arrangement and on measurements on theundamaged parts of buildings is also carried out.Thus, a back analysis is carried out in order to de ne collapse dynamics and to estimate theupper and the lower bound of impact pressure. Afterwards, numerical uid-dynamical analysesare performed to simulate di erent impact scenarios and to understand the e ects of obstacleson avalanche behavior: a qualitative measure of the interactions among buildings, which maymutually protect one another, is obtained.

The in-situ stress is one of important basic data for stability evaluation, engineering design and construction of tunnels. For southwest high mountain region, the in-situ stress in the site test is very difficult. Thus, for satisfying engineering design and construction, it is necessary to back analyze the in-situ stress. The highway tunnel which locates at the 1# road of Lianghekou hydropower station is researched as the object. Based on measured displacements, the inversion model of initial earth stress is built. By comparing the calculated and measured results, the reasonable horizontal pressure parameters and the modulus of elasticity are confirmed.

The Artificial Ground Freezing (AGF) Method play an important role in the geotechnical engineering and the back analysis of thermal conductivity of frozen soil is the main inverse heat conduction problem of temperature field. In this paper the physical modelling test of AGF is carried out with double-row-pipe freezing in the lab. According to the measured temperature, the back analysis of thermal conductivity of frozen soil is solved based on the two-dimensional finite element simulation and the least square principle. It is helpful to investigate the freezing process and determine the frozen wall thickness.

In the numerical calculation of geotechnical project, it’s difficult to confirm the parameters because of the complexity and the uncertainty of them as the time is changing. However, the back-analysis provides us an effective way. Based on the result of the triaxial test on rock-fill of Shui Bu Ya CFRD, the thesis adopts the direct back-analysis method which combines the BP Neural Network and Genetic Algorithm to calculate the Tsinghua non-linear K-G model parameters of the rock-fill. The back-analysis parameters are used to simulate the filling process of Shui Bu Ya CFRD and predict the displacement of the dam. The thesis provides a technical reference for displacement back-analysis of soil parameters for CFRD.

In this paper differential evolution algorithm (DE) which is a new global optimization algorithm is introduced into the displacement back analysis, and the self-developed back analysis program based on DE is used in metro station engineering. The results show that the superiority of DE and the practicability of intelligent displacement back analysis program, more importantly, it is being applied to engineering practice to provide reference and advanced prediction for the construction process.

The rock mass with polycrystalline aggregates is common geomaterial in civil and architectural engineering as well as hydraulic and hydro-power engineering. For this kind of geometerials, the study on the joint deformation parameters Kn and Ks and the calculation method are not enough so far. Focusing on the rock mechanics and engineering problems of columnar jointed rock mass related to Baihetan hydropower project, analytical models and numerical method based on 3DEC are employed to study the mechanical parameters. The joint deformation parameters Kn and Ks are back analysis using GRNN and the field data of load-bearing plate tests. The application shows that the calculation results are in good accordance with in-situ test results.

Shallow multi-arch tunnel under unsymmetrical pressure has complex mechanical behavior to which further study is lacking at present. The existing design methods are thoughtless about the features of shallow and partial pressure. The phenomena of cracks, collapse or other diseases in tunnel lining structure are often seen during the construction or after the completion. Combining one tunnel example, this paper presented scientific feedback design method that suited for Shallow multi-arch tunnel under unsymmetrical pressure: made load back analysis with collected information during construction, then averaged the above load and field monitoring load to make forward analysis and internal force calculation, which was used as reference of reinforcement and sectional design for lining structure.

The large-scale high-speed landslide has a strong destructive power which seriously threatens human lives and belongings. In order to study the dynamic process of large-scale high-speed landslide disasters and find the causes, the back analysis is made to study the Frank slide, a typical large-scale high-speed landslide disaster which happened in Canada, by combining dynamic model equation and method of finite volume discretization. At the same time, the simulation realizes the reappearance of the dynamic process of large-scale high-speed landslide disasters. It is can be seen from the calculation results which are identical to the actual situation that the established theoretical model and the numerical solution are effective. Besides, the low bottom friction parameter obtained from the back analysis shows that the decrease of the friction resistance is one of the most important causes of large-scale high-speed landslide. The further analysis reveals that several factors such as high-speed motion, fluid pressure on the sliding surface and high normal stress can reduce the friction resistance on the sliding surface.

The self-developed finite element program on return mapping algorithm is used to the simulation of the true tunnel with C + + language, while the finite element program is embedded into differential evolution algorithm to achieve the inversion parameter. Applying to Line 1 of Dalian Metro, rock mechanics inversion parameters and true parameters are close, which indicates the superiority and good prospects of return mapping algorithm and different evolution algorithm, and it can be used for quantitative analysis of actual tunnel.

The Kalman filtering theory was applied for the back analysis of mechanical parameters of mass concrete on the first time. The time-spreading equation and the observation-correcting equation were deduced. After the coupling problem of extending Kalman filtering theory and FEM was solved, the Kalman-FEM formula were deduced and the corresponding back analysis procedures were given. The results indicate that the Kalman filtering method has good characteristics of convergence and stability. The broached method can be used in other research fields such as the back analysis of creeping parameters. Many more conclusions are tested and discussed through a classic example.

On the stability analysis of complex slope, the determination of rock-soil masses shear strength parameters is very important. It’s very necessary to use the back analysis method to verify experiment result of rock-soil masses parameters for the important slope engineering. Because the sensitivity of shear strength parameters to displacement parameters is very poor, so that we couldn’t get the satisfactory shear strength parameters result by traditional back analysis method. Aiming at the problems of traditional back analysis method, this paper puts forward a totally new method of back analysis, which is applicable to the shear strength parameters of rock-soil masses through the integration of complex variable differentiation method, optimization method and elastic-plasticity finite-element method. The method mathematically back calculates shear strength parameters of rock-soil masses on the basis of displacement of measuring point. The sample calculation result indicates that the method possesses high accuracy and searching efficiency, and is a method of back analysis of displacement deserving popularizing.

Composite T-beam in general use is composed of concrete and steel. Compared with mechanical analysis, little research has been carried on deriving the theoretical model for back analysis of composite T-beam. Firstly for composite T-beam, degraded solid element theory is deduced and the displacement function is obtained. Then Markov error function of mechanical parameters of composite T-beam is founded. The back analysis computing formulas are also obtained by adopting optimization method including revised Powell method. Then the steps of back analysis of mechanical parameters of the composite T-beam are given. Through analysis of a classic example, some important conclusions about revised Powell back analysis of mechanical parameters of composite T-beam are obtained.

Due to lots of hypothesis, the theoretical analytical solution of the creep parameters inversion can not reflect the in-situ conditions actually. In order to simulate the process of the compressive creep tests of the in-situ bearing plate, the affection of the stratum distribution and the influence of the geological status in site actually, FLAC3D is used and numerical back analysis method of the creep parameters at dam site is set up. Based on the in-situ compressive creep tests’ data of the diabase rock masses at Dagangshan dam site, creep parameters are got with this method. Results indicate that the numerical calculated displacements of the compressive creep are similar to the in-situ monitoring displacements. It reveals that with this numerical method creep parameters can be backing analyzed logically. This supplies technical assurances to stability estimate and analysis of rock masses in slope projects.

The method of bolt-grouting supporting, grouting into surrounding rock mass by bolts in jointed rock mass roadway, is obtained wide application. However, it is difficult to determine rock mass parameter of bolt-grouting supporting. This paper begins with the displacement, which is measured easily in practice. The method of back analysis is adopted to calculate the equivalent mechanics parameters of bolt-grouting rock mass. In process of back analysis three mechanics models is supposed which are homogeneous elastic model, inhomogeneous elastic model and elastic-plastic model and corresponding algorithm is established. What's more, this paper discusses the stability of inverse algorithm and copes the problem of back analysis parameter probably instable with QR decomposed algorithm and singular value decomposed algorithm, which will be a theoretical base to determine the mechanics parameter of bolt-grouting supporting rock mass and to estimate the surrounding rock stability. In a word, the method is established to estimate mechanics parameters of bolt-grouting jointed surrounding rock mass, and some significant results are obtained, which are of reference for actual project.

Cording to the measured data from the Fenshuiling tunnel of Lingnan freeway, the elastic modulus of tunnel surrounding rock and the horizontal crustal stress are back calculated with the system identification method. The results indicate that it is reasonable and the inversion procedure has stronger adaptive control,good convergent calculation stability,rapid calculation velocity. It shows that the system identification method to back calculate the elastic modulus of tunnel surrounding rock is effective.