1241 results about "Wall rock" patented technology

The invention provides a tunnel disaster source multi-attribute joint inversion method and system based on physical property constraint, and relates to the technical field of tunnel engineering and joint inversion, and the method comprises the steps: constructing a tunnel face three-dimensional geologic model, applying controlled disturbance to surrounding rock physical property parameters, analyzing the change characteristics of earthquake and electromagnetic observation response, and obtaining a tunnel face three-dimensional geologic model; establishing a quantitative mapping relation between the surrounding rock physical property parameter disturbance quantity and the multi-field response signal variable quantity; constructing a multi-dimensional sensitivity evaluation index, and generating a joint sensitivity result; the surrounding rock units are identified and divided, differentiated partition rock physical relationship constraints are constructed, and a physical multi-attribute inversion target of joint inversion is determined based on the partition rock physical relationship constraints; and on the basis of a physical multi-attribute inversion target, a multi-source joint inversion target function is constructed in combination with the joint sensitivity result, joint solving and iterative updating are carried out, and a tunnel face advanced inversion result is output. According to the invention, calamity source fine identification and risk quantitative evaluation in front of the tunnel face during the tunnel construction period are realized.

The invention relates to the technical field of construction surrounding rock stability evaluation, discloses a tunnel surrounding rock stability evaluation method and system based on multi-physics field parameter inversion, and aims to solve the problems that an existing method is insufficient in data collaboration, high in parameter inversion multiplicity and poor in surrounding rock stability evaluation accuracy and timeliness. According to the scheme, the method mainly comprises the steps that an acousto-optic electromagnetic vibration drill multi-mode sensing array is arranged, and time-space synchronization is implemented; establishing a mutual interference entropy spectral density model to realize multi-physics field collaborative excitation and acquisition; a unified feature vector is obtained through data correction, feature extraction and weighted fusion; a joint inversion objective function embedded with rock physical constraints is constructed, a three-dimensional physical property parameter field is obtained through inversion, and a dynamic permeability field is calculated in combination with acoustic emission energy; and finally, dynamically updating the model by utilizing ensemble Kalman filtering, and obtaining a final risk probability based on updated parameters and seepage-uncertainty coupling correction. According to the method, the accuracy, the real-time performance and the reliability of the stability evaluation of the surrounding rock of the deep-buried tunnel are improved.

The invention belongs to the technical field of tunnel and underground engineering intelligent construction and geotechnical engineering informatization, and discloses a high-energy geological environment surrounding rock classification and decision-making method based on digital twinning and multi-source feedback. The problems caused by difficulty in realizing surrounding rock state dynamic sensing, multi-source data fusion classification and construction decision closed-loop linkage in the prior art in a high-energy geological environment are solved. The method comprises the following steps: firstly, constructing a tunnel three-dimensional geology-structure digital twinborn body based on initial survey data; in the construction process, multi-source data such as geology, construction disturbance and surrounding rock response are collected in real time through the Internet of Things technology and mapped to the digital twinborn body, and virtual-real synchronous updating is achieved. And then, constructing a deep learning-parameter inversion hybrid model on the basis of the multi-source fusion data, outputting a dynamic surrounding rock classification index DRCI and key mechanical parameters, inputting the DRCI and the key mechanical parameters into a multi-objective optimization module, and giving a self-adaptive drilling and blasting scheme. And finally, reversely correcting the model through a construction feedback result to realize closed-loop self-learning.

The invention discloses a spherical crown dome horizontal circumference drilling and blasting parameter model optimization construction method, and the method comprises the steps: collecting geological, crustal stress, hydrological and structural plane data, building a three-dimensional geological information model, carrying out the working condition partitioning based on a surrounding rock quality evaluation index, and constructing a parameter probability distribution model and an uncertainty boundary of each partition. Therefore, precise space description and parameter variability quantification of the spherical crown dome construction area are realized. The method comprises the following steps: establishing a three-dimensional numerical model of a cavern group, integrating blasting power, seepage and stress multi-physical field effects by adopting a finite element-discrete element coupling method, introducing a surrounding rock deterioration constitutive model considering cumulative damage and unloading aging, calibrating key parameters through an indoor test and field trial explosion, and establishing a three-dimensional model of the cavern group. And the numerical model can truly reflect the mechanical property degradation track of the surrounding rock under repeated blasting disturbance.

The invention relates to the technical field of deformation monitoring, in particular to a mountain tunnel surrounding rock deformation monitoring method and system based on distributed optical fiber sensing. The method comprises the following steps that Brillouin frequency shift original data and center wavelength original data are collected, tunnel construction progress data and surrounding rock geological survey data are obtained at the same time, format standardization and time sequence alignment processing is carried out, and preprocessed optical fiber sensing basic data, construction time sequence data and geological attribute data are generated; surrounding rock deformation characteristic parameters are extracted based on the optical fiber sensing basic data, and surrounding rock deformation multi-dimensional characteristic vectors are constructed; performing deformation mode density clustering and surrounding rock deformation dynamic prediction based on the surrounding rock deformation multi-dimensional feature vector to generate a surrounding rock deformation dynamic prediction value; and carrying out comparison and iterative correction on the dynamic prediction values of the surrounding rock deformation, and carrying out regionalized polymerization to generate a mountain tunnel surrounding rock deformation spatial and temporal distribution visualization result. According to the invention, full-time-space accurate monitoring and early warning of tunnel surrounding rock deformation can be realized.

The invention relates to the technical field of roadway surrounding rock danger identification, and discloses a roadway surrounding rock danger identification model construction method, which comprises the steps of collecting multi-modal data, and generating preprocessed data through synchronous calibration and denoising; extracting a seismic wave frequency domain and image texture features, and generating a multi-modal feature matrix; in combination with a geological prior clustering mining abnormal mode, generating a labeled sample data set; generating a danger identification model based on a transfer learning and feature fusion training network; and the edge deployment model performs real-time reasoning, and generates an early warning result through an adaptive algorithm. According to the method, the frequency domain features of the seismic fluctuation signals and the depth texture features of the surrounding rock images are fused, the multi-modal feature matrix is constructed, abnormal mode mining is carried out in combination with geological prior knowledge, and early weak abnormal signals such as hidden fault slippage or asymmetric microfracture extension which are difficult to find by a single monitoring means can be effectively recognized.

The invention relates to the technical field of tunnel construction safety monitoring, and discloses a tunnel construction safety evaluation method and system based on multi-dimensional data fusion analysis, and the method comprises the steps: constructing a digital twinborn model, and building an initial twinborn body comprising a BIM model and a three-dimensional geologic model; performing mechanical parameter inversion and dynamic updating on the three-dimensional geologic model through real-time multi-dimensional monitoring data to obtain a dynamic twinborn body; performing fusion analysis on the monitoring data by adopting a fusion algorithm, and outputting a safety risk coupling evaluation result; based on an evaluation result, combining with surrounding rock mechanical response of dynamic twinborn simulation, and adopting fuzzy comprehensive evaluation to output a safety level; and performing risk traceability and positioning main risk factors through a Bayesian network based on the security level, generating a customized support decision through case reasoning, and performing visual display and early warning in a digital twinborn model. The system corresponds to the method. According to the invention, dynamic accurate evaluation and intelligent decision support of tunnel construction safety are realized.

The invention relates to an intelligent soft rock tunnel surrounding rock deformation automatic monitoring and early warning system, and belongs to the field of tunnel construction safety monitoring. According to the system, multi-source data of surrounding rocks are synchronously acquired through a micron-sized laser displacement sensor, a fiber grating strain sensor, a pore water pressure sensor and a three-dimensional micro-seismic sensor array which are distributed; the edge calculation node fuses the data in real time and calculates the displacement rate, the strain gradient and the osmotic pressure coupling coefficient, and local early warning is triggered in combination with a dynamic threshold value; the cloud early warning platform predicts a deformation trend based on an LSTM-Transform fusion model, generates a multi-stage early warning signal through a risk grading engine, and is linked with the supporting equipment to regulate and control pressure; and meanwhile, a self-calibration device, an explosion-proof shell and a piezoelectric-thermal energy self-powered system are integrated. According to the method, closed-loop control from millimeter-level deformation sensing to active supporting can be achieved, and tunnel construction safety is remarkably improved.

The invention provides a deep coal seam roadway surrounding rock stability intelligent early warning method, and relates to the technical field of coal mine dynamic disaster prevention and control. According to the intelligent early warning method for the stability of the surrounding rock of the deep coal seam roadway, a basic sample library is constructed through a dynamic and static combined loading rock test; synchronously collecting field surrounding rock static stress and micro-seismic data and carrying out time sequence polymerization; constructing an equivalent dynamic and static combined stress index based on a dynamic and static load superposition principle, and forming a seismic-force coupling feature vector; establishing an LSTM early warning model, adopting a transfer learning strategy, pre-training by using laboratory data, and then performing fine tuning by using field data; inputting the real-time feature vector into a model and outputting an instability probability; and verifying and correcting the probability based on actual deformation data of the surrounding rock, and applying a missing report sample to online incremental updating of the model. According to the method, the dynamic and static load coupling effect is quantified, the difficulty of small sample training is overcome, and accurate and self-adaptive early warning of the deep roadway surrounding rock instability risk is realized through a physical feedback closed-loop correction mechanism.

The invention provides a tunnel support self-adaptive adjusting method and system based on rock mass-support feedback, and relates to the technical field of tunnel engineering support. The method comprises the following steps: acquiring surrounding rock strain data and stress data through a sensor network arranged in tunnel surrounding rock, and generating original monitoring data; calculating the surrounding rock strain energy density by using a data processing unit; matching the strain energy density with a preset energy stage feature through an adaptive control algorithm to generate an energy stage matching result; determining an energy state stage based on a stage confirmation module and generating an energy stage identifier; a supporting mode switching instruction is generated through a supporting mode mapping querier; and finally, the supporting control unit adjusts the working parameters of the supporting structure, real-time monitoring of the energy state of the surrounding rock and dynamic matching of the supporting parameters are achieved, the adaptability and safety of tunnel supporting are effectively improved, and the hysteresis of manual intervention is reduced.

The invention mainly relates to the technical field of tunnel engineering, and provides a tunnel surrounding rock grading dynamic correction method based on image texture features in order to improve the accuracy and real-time performance of surrounding rock grading under complex geological conditions. An improved deep residual network model integrated with an attention mechanism is input and introduced, the model improves the precision of single-point surrounding rock grade identification based on key textures, an initial prediction value of the surrounding rock grade is obtained, and meanwhile a time sequence prediction model is introduced; the whole excavation process is regarded as a continuous geological sequence based on the multi-source surrounding rock feature vectors of the current excavation cycle and at least one previous historical cycle, a time sequence trend value of the surrounding rock grade is obtained, a self-adaptive weight is set, the surrounding rock grade initial prediction value and the time sequence trend value of the surrounding rock grade are smoothed and corrected, and the surrounding rock grade is obtained. Therefore, the accuracy and the stability of the surrounding rock grading result are improved.

The present disclosure relates to the technical field of stability control of surrounding rock of tunnelling, and provides an excavation compensation method for tunnelling in deep rock engineering, including: acquiring an engineering geological information of the tunnelling in deep rock engineering; determining an engineering hazard type based on the engineering geological information; determining an excavation compensation support strategy for the surrounding rock of the tunnelling in deep rock engineering based on the engineering hazard type; and performing a supplementary support control on the surrounding rock of the tunnelling in deep rock engineering based on the excavation compensation support strategy. Through the supplementary support strategy, the difference value between a radial stress of the surrounding rock of the tunnelling in deep rock engineering and an initial crustal stress can be reduced to within a preset approximate value range, further effectively preventing a stress concentration phenomenon occurred in a tangential stress.

The invention relates to a complex soft rock double-layer primary supporting super-large section tunnel and a construction method. The complex soft rock double-layer primary supporting super-large section tunnel comprises a long pipe shed cover arch supporting system, a deformation control strong supporting structure, an anti-disengaging early-warning lining pouring trolley, a temporary inverted arch deformation control structure and a buffering yielding supporting system. The method has the beneficial effects that the curved surface formwork can be rapidly installed on the upper portion of the guide pipe and the lower portion of the steel arch frame, the installation efficiency is high, stability is good, and the construction period is shortened; a long pipe shed and a small guide pipe penetrate through the deformation control strong supporting structure and are driven into a tunnel, grouting is conducted, the overall stability of the supporting structure is enhanced, and the complex soft rock geology is reinforced; concrete pouring is monitored in real time, and the compactness of vault concrete is guaranteed; section steel is clamped in the inverted arch, reinforcing connecting ribs are welded between the section steel in a penetrating mode, surrounding rock collapse is prevented, and tunnel construction safety is guaranteed. And a buffer yielding support device is arranged between the interface and the double-layer arch frame, so that the pressure at the interface of the layered rock and soil stratum is in smooth transition, and the overall balance is improved.

The invention discloses a construction method applied to underground mine vertical shaft surrounding rock condition improvement. The construction method comprises the steps that a flat working face is cleaned, a temporary water nest is arranged for drainage, the drilling position is projected, and a down-the-hole drill is debugged; rock drilling is conducted according to the designed angle, direction and depth, propelling pressure is adjusted along with the depth, and cleaning and plugging are conducted after hole forming; grouting pipes with holes are used as pipe sheds to be driven into the holes, and are welded into a whole through annular steel bars; single-liquid-slurry and double-liquid-slurry segmented grouting is adopted, and the grouting pressure is controlled; during construction, grout diffusion and stratum deformation are monitored, after surrounding rock consolidation reaches the standard, weak blasting is matched with a small excavator for excavation, and after acceptance inspection is qualified, reinforcing steel bars are bound, formworks are installed, and concrete is poured. Compared with the prior art, the problems of collapse and water gushing of the vertical shaft under the strong weathering and water-rich geology can be solved, and the defects of insufficient supporting strength, grouting uniformity, construction efficiency and long-term stability in the traditional technology are overcome.

The invention discloses an invasion limit surrounding rock excavation method for a large deformation section of soft rock, and relates to the technical field of invasion limit surrounding rock excavation construction for the large deformation section of the soft rock. The invasion limit surrounding rock excavation method for the large deformation section of the soft rock comprises the steps that refined partitioning of an invasion limit body is achieved through dense scanning and loose circle testing; dividing the invasion limiting body into a core pressure-bearing area and a peripheral stress relaxation area; a main stress diversion arch crossing an invasion limit section is constructed through full-ring radial grouting reinforcement and erection of a strong profile steel temporary cover arch, and effective stress transfer is achieved; the mode of subarea gradual type dismantling and chiseling and instant supporting is adopted, a peripheral stress relaxation area is treated firstly, then a core pressure-bearing area is treated, and surrounding rock disturbance is reduced; the circumferential stress equalization is realized by compensating grouting in stages and dynamically adjusting the grouting pressure according to real-time monitoring data. According to the method, the excavation construction safety of the invasion limit surrounding rock of the large deformation section of the soft rock can be improved, surrounding rock disturbance is reduced, stress distribution is optimized, and the treatment efficiency of the invasion limit surrounding rock is improved.

The invention provides a construction tunnel surrounding rock stability evaluation method based on digital twinning and a related device. The method comprises the following steps: constructing a tunnel digital twinning model of a tunnel construction section; geological data and real-time progress position data of a target mileage segment in the construction process are obtained; mapping the geological data to a digital twinborn model, and updating soil body unit parameters; according to the real-time progress position data, synchronously updating activation states of a soil body unit and a supporting structure unit in the model by adopting a state change method; and extracting a surrounding rock stability index based on the updated digital twinborn model, evaluating the stability of the current construction tunnel surrounding rock in combination with a safety threshold to obtain a construction tunnel surrounding rock stability evaluation result, and constructing a tunnel construction process dynamic mapping-oriented digital twinborn model by utilizing the description capability of a finite element method on structural mechanical behaviors. Geological conditions and construction progress information which are obtained in real time on site are used as input, and the construction period structure safety risk of the drilling and blasting method tunnel is evaluated and predicted.

The invention discloses a rock burst ultra-deep hole blasting unloading wave absorption coupling prevention method for a steeply inclined coal seam, and belongs to the technical field of coal mining, and the method comprises the following steps: step 1, determining an unloading target rock stratum where a working face top plate and / or bottom plate stress concentration area is located in the steeply inclined coal seam; 2, determining a wave absorbing target rock stratum between the unloading target rock stratum and a roadway on the corresponding side of the working face of the steeply inclined coal seam; 3, arranging a plurality of unloading blast hole groups in the roadway; step 4, arranging a wave absorbing blast hole group at the position where the unloading blast hole group is arranged in the roadway; 5, all the wave absorbing blast holes are detonated, and all the unloading blast holes are detonated; and 6, after blasting is completed, the near-surface surrounding rock of the roadway on the corresponding side subjected to blasting serves as a supporting bearing layer for combined supporting. According to the invention, a three-level cooperative control mechanism of source unloading, propagation weakening and terminal bearing is realized, and steeply inclined coal seam clamping type roof and floor rock burst disasters are prevented fundamentally.

The invention, which belongs to the technical field of tunnel engineering, discloses a tunnel surrounding rock pressure arch calculation system comprising a multi-source data fusion acquisition module, a surrounding rock grade intelligent identification module, a self-adaptive pressure arch parameter calculation module and a dynamic load prediction and optimization module. The multi-source data fusion acquisition module acquires geological parameters, drilling monitoring data and case data and generates fusion feature vectors; the surrounding rock grade intelligent identification module outputs a surrounding rock classification result based on a deep residual network and an attention mechanism; the self-adaptive pressure arch parameter calculation module calculates pressure arch parameters by adopting an improved Prscherski theory and a stress release time-varying function; the dynamic load prediction and optimization module predicts the load through the space-time collaborative network and feeds the deviation back to the calculation module to form closed-loop optimization, precise dynamic calculation of the surrounding rock pressure arch parameters is achieved, and the calculation precision is improved by 20% or above compared with a traditional method.

The invention relates to the technical field of mining engineering and geotechnical engineering support design, and discloses a roadway anchor rod group support parameter intelligent optimization method based on unbalanced force, and the method comprises the steps: building a surrounding rock finite element model, calculating a plastic stress increment through employing a minimum plastic complementary energy principle, and mapping the plastic stress increment into a node unbalanced force vector; an unbalanced force field reflecting reinforcement requirements is constructed, and an initial scheme is generated according to the unbalanced force field. Then, a virtual anchor rod unit is introduced to establish a nonlinear coupling model, an incremental balance equation is solved, and whether the unbalanced force is smaller than a threshold value or not is judged; if so, outputting an optimal parameter; otherwise, a comprehensive objective function containing safety and economy is constructed, new parameters are obtained through searching and decoding by means of the particle swarm algorithm, and the virtual anchor rod unit is re-entered for calculation to form a closed loop until convergence is achieved. According to the method, intelligent optimization is driven through a physical mechanism, the problem that a traditional design lacks a mechanical basis is solved, and accurate optimization of support parameters is achieved.

The invention discloses a rock mass structural plane parameter calculation method based on a drilling surrounding rock expansion map. The method comprises the steps that a deep learning semantic segmentation network is built to automatically recognize cracks in a drilling surrounding rock hole wall two-dimensional expansion map; processing the segmented fissure image of the pixel level, and eliminating miscellaneous points which interfere with subsequent operation and small fissures which do not influence the integrity of the surrounding rock; extracting a fracture skeleton line, and eliminating burrs on the skeleton line; for fractures with cross structures, adopting a fracture skeleton decoupling algorithm fusing topological connectivity and vector geometry criteria to adaptively separate the fractures; an implicit space mapping method based on a crack pixel sequence is adopted, non-modeling extraction of structural plane space geometric parameters in a borehole expansion diagram is achieved, and the structural plane space geometric parameters comprise the included angle between the structural plane trend and the hole axis and the structural plane dip angle. According to the method, the geometric features of the internal structural surface of the surrounding rock can be quantitatively represented, and the quantitative results are all within the allowable range of actual engineering errors.

The invention provides a surrounding rock stability dynamic analysis method and system in the excavation process of an underground cavern group. The method comprises the steps that original surrounding rock monitoring data of the underground cavern group are collected at the self-adaptive sampling frequency through a distributed optical fiber sensor; performing real-time filtering, abnormal value primary screening and data compression processing on the original surrounding rock monitoring data to obtain target surrounding rock monitoring data; performing feature extraction on the target surrounding rock monitoring data to obtain a feature vector corresponding to the target surrounding rock monitoring data; and inputting the feature vector into a pre-constructed surrounding rock stability evaluation model for evaluation to obtain the stability level of the surrounding rock. Therefore, data redundancy can be prevented, key information omission is avoided, and the reliability of a surrounding rock stability evaluation result is improved.

The invention discloses a tunnel surrounding rock catastrophe precursor feature extraction method and system based on multi-source data fusion, and the method comprises the steps: collecting surrounding rock displacement, stress and pore water pressure data, and carrying out the time-space standardization to form a data set; constructing three types of key feature parameters of time sequence dynamics, field coupling correlation and spatial evolution based on the data set; utilizing quantitative triggering conditions and combining the characteristic parameters to identify co-evolution modes, including a linkage mode and a space-time propagation mode, under the water-soil coupling effect; based on an evolution mode, a dynamic threshold value is generated through a statistical adaptive method, after physical and mode verification, a critical state index and a linkage early warning index are quantitatively extracted, and the threshold value is dynamically updated along with the geology and construction stage; according to the method, a complete technical chain from data to the precursor is constructed, automatic inversion of the catastrophe evolution path and quantitative extraction of the early precursor are realized, and core support is provided for accurate early warning of tunnel disasters.

The invention belongs to the technical field of underground engineering and computer-aided engineering analysis, and particularly relates to an anti-seismic safety collaborative analysis method for multi-modal data of proximity tunnel engineering. By integrating engineering geology, structural design, construction monitoring and multi-level seismic oscillation data, a three-dimensional numerical model fusing geology and structural information is constructed. Firstly, refined simulation of the whole construction process and the operation static load is carried out, and a reference mechanical state is obtained; carrying out multi-task condition earthquake dynamic time history analysis on the basis, dynamically capturing dynamic response of surrounding rock and a structure, carrying out collaborative interpretation on static and dynamic analysis results, emphatically analyzing spatio-temporal evolution and connectivity risks of a tunnel anchor and an adjacent highway tunnel surrounding rock plastic zone, and extracting a plurality of quantitative collaborative indexes; and an interactive analysis report integrating a three-dimensional visual scene, a multi-dimensional comparison chart and a rule base-based safety interpretation conclusion is automatically generated, and systematic decision support is provided for seismic design, construction control and safety evaluation of proximity projects.

The invention relates to surrounding rock stability prediction, and provides a tunnel surrounding rock stability prediction method in order to realize advanced prediction of surrounding rock fracture under a deep burying condition, through coupling of finite elements and discrete elements, overall deformation and microcosmic fracture extension of surrounding rock can be considered at the same time, and the accuracy and calculation efficiency of surrounding rock stability analysis are improved; the two-channel hypergraph neural ODE rupture mode prediction model can give the rupture volume and the instability probability 3-7 days in advance, meanwhile, the physical consistency problem, namely energy and momentum residual real-time convergence, is considered, and the accuracy of the prediction result is guaranteed; real-time monitoring data are obtained through a finite element-discrete element coupling model, stability prediction is carried out based on a dual-channel hypergraph neural ODE rupture mode prediction model, parameters do not need to be manually adjusted, and a system automatically completes data analysis-prediction-early warning closed loop; the stability analysis of the surrounding rock of the deep-buried tunnel is upgraded from static and experience analysis to real-time and dynamic advanced prediction.

The invention relates to the technical field of tunnel engineering, in particular to a tunnel lining long-term safety assessment method based on a PSO-SA hybrid algorithm, and the method comprises the steps: determining a surrounding rock creep constitutive model, and obtaining initial surrounding rock parameters through an inversion algorithm; the influence of a supporting structure on surrounding rock deformation is introduced, and corrected surrounding rock parameters are obtained to improve authenticity; based on the time-varying factors, the surrounding rock parameters and the lining parameters are iteratively updated, and long-term safety dynamic evaluation is achieved; inputting the iteratively updated surrounding rock parameters and lining parameters into numerical analysis software, and obtaining stress deformation characteristics of the lining structure through the numerical analysis software; according to the method, the long-term safety of the tunnel lining structure is evaluated according to the stress deformation characteristics and related specifications, a dynamic evaluation model which truly reflects the time-varying characteristics of the tunnel structure is constructed, qualitative leap in evaluation precision, reliability and foresight is brought, and a powerful technical guarantee is provided for long-term safety of an operation tunnel.

The invention belongs to the technical field of geological energy storage, and particularly provides an underground chamber surrounding rock thermal-mechanical coupling fatigue phase field simulation method and system, and the method comprises the steps: building a phase field evolution equation through a phase field fracture model and a fatigue degradation function; on the basis of the calculation model, according to the air temperature and pressure in the cavern, the Newton heat exchange law is adopted to calculate cavern wall heat exchange, and a cavern wall heat conduction equation is constructed; on the basis of the calculation model, utilizing rock mass displacement and surrounding rock strain to construct a rock mass deformation equation; performing numerical discretization on the phase field evolution equation, the cave wall heat conduction equation and the rock mass deformation equation on a finite element grid unit, and performing thermal-mechanical coupling solution on all discretized equations through an iterative method to obtain evolution results of a temperature field, a stress field, a displacement field and a crack phase field of the underground chamber surrounding rock target area. According to the method, the phase field method is applied to thermal-mechanical coupling simulation of the underground gas storage chamber surrounding rock crack propagation condition, and the authenticity of chamber crack simulation is reflected to the maximum extent.

The present application belongs to the field of rock burst risk assessment of deep rock engineering, and particularly relates to a quantitative evaluation method for rock burst tendency of surrounding rock under multiple disturbances, which comprises the following steps: obtaining the distribution depth of excavation damage zone through acoustic testing, and obtaining the average wave velocity of rock mass in the range of original rock zone; obtaining the geological strength index and disturbance factor through the average wave velocity; further obtaining the residual elastic energy of surrounding rock based on the geological strength index and disturbance factor, and evaluating the rock burst tendency of surrounding rock through the residual elastic energy of surrounding rock; the acoustic testing points of surrounding rock are unchanged, and the rock burst tendency of surrounding rock is evaluated after each excavation footage of the working face is completed, until the distribution characteristics of rock burst tendency no longer change obviously, which is taken as the long-term evaluation result of rock burst tendency of surrounding rock. The quantitative evaluation formula of rock burst tendency of surrounding rock considers the rock mass structure effect, which is reflected in the geological strength index, and considers the excavation disturbance effect, which is consistent with the actual situation of engineering construction process, and has strong practicability.

The invention relates to the technical field of ground stress testing, in particular to anchor rod equipment for testing ground stress of an underground chamber, an anchoring body is arranged at the bottom of an anchor hole, and anchoring surfaces are arranged on two opposite sides of the anchoring body so as to directionally extrude surrounding rock outside the chamber through the anchoring surfaces to obtain anchoring stress of the chamber in a set direction; the two ends of the anchor rod are connected with the anchoring body and the load piece through threaded connection structures correspondingly. The loading part is arranged at the hole opening of the anchor hole, the drawing device and the stress meter are arranged between the loading part and the hole opening of the anchor hole, the anchoring faces are arranged on the two sides of the anchoring body, the interaction between the anchor rod and the surrounding rock when the anchor rod is drawn in the rock mass is converted into different drawing forces, and then the ground stress of the surrounding rock of the chamber in a certain direction can be obtained. Therefore, the ground stress direction and size of the surrounding rock of the underground chamber are tested.

The invention discloses a deep learning-based large deformation prediction method for a high ground stress soft rock tunnel, and belongs to the field of tunnel engineering geological disaster prediction. By constructing a double-branch network architecture of'geological mode identification-deep learning prediction ', accurate prediction of large deformation of the tunnel is realized. The method comprises the following steps: firstly, collecting six qualitative indexes such as a rock mass structure, a weathering degree and an underground water condition and three quantitative indexes such as a strength-stress ratio, support rigidity and an equivalent hole diameter, performing encoding and normalization preprocessing, and respectively inputting the indexes into an upper-layer network and a lower-layer network; outputting probability distribution of six types of modes prone to large deformation, such as a weak homogeneous type mode and a block crack structure type mode; and the lower layer predicts the deformation and divides risk levels through a full-connection neural network based on the geological mode identification result and the quantitative index. According to the method, the complex coupling mechanism of large deformation of the high-crustal-stress soft rock tunnel can be fully reflected; adaptability prediction is realized for different geological modes.

The invention relates to the technical field of surrounding rock damage analysis, in particular to a deep-buried tunnel circulating blasting excavation surrounding rock accumulated damage analysis method and a deep-buried tunnel circulating blasting excavation surrounding rock accumulated damage analysis system. Further determining the effect of blasting and ground stress on surrounding rock damage during blasting excavation of the deep tunnel; under the action of blasting and ground stress, the influence of single-cycle blasting excavation and multi-cycle blasting excavation on surrounding rock damage is considered, and the cumulative damage variable of the rock mass is calculated; and evaluating the stable state of the surrounding rock according to the calculated accumulated damage variable, and optimizing a blasting design scheme and a support time sequence. According to the method, on the basis of considering the comprehensive action of blasting and ground stress, accurate calculation of the accumulated damage of the surrounding rock during deep-buried tunnel circulating blasting excavation is realized by analyzing the influence of single-circulation multi-section blast hole delayed blasting and multi-circulation blasting on the damage of the surrounding rock, so that a blasting design scheme and a support time sequence are optimized; and the safety of tunnel engineering is improved.