20 results about "Back analysis" patented technology

The invention discloses a deep tunnel surrounding rock mechanical parameter inversion method based on a three-dimensional brittle failure zone contour and sparrow optimization algorithm-information vector machine (SSA-IVM) combined optimization algorithm. The engineering technical problem that due to the fact that excavation instantaneous displacement is difficult to monitor, deep tunnel surrounding rock mechanical parameters are difficult to reasonably obtain through displacement back analysis is solved. The method comprises the following steps: firstly, constructing a tunnel FLAC3D numerical simulation model with the same ground stress condition at the occurrence position of a three-dimensional brittle failure zone; secondly, taking an absolute error between the total number of computational grid units in the actually measured brittle failure zone and the total number of computational grid units entering a plastic state in the range of the actually measured brittle failure zone after calculation of the FLAC3D numerical model as an optimization objective function; and then, by taking the tunnel surrounding rock mechanical parameters as optimization variables and taking a target function reaching a global minimum value as a target, performing global optimization by combining a tunnel FLAC3D numerical model and adopting an SSA-IVM joint optimization algorithm, thereby obtaining reasonable tunnel surrounding rock mechanical parameters.

The invention provides a debris flow risk assessment method and system based on debris flow parameter probability inversion calibration, and relates to the technical field of geological disaster risk assessment. According to the technical scheme provided by the embodiment of the invention, an effective means is provided for scientifically identifying debris flow parameters, and the method is particularly suitable for setting single gullies which are limited in detailed observation and cannot directly measure the parameters. A traditional method depends on statistical parameters or deterministic back analysis, the former introduces errors due to poor regional adaptability, and the latter has the problem of non-uniqueness of parameters; according to the scheme, the parameter posteriori distribution is updated by combining the Bayesian framework with historical observation data (debris flow influence areas), so that the standard deviation of key parameters is generally reduced. In the embodiment of the invention, the influence area is taken as core observation information, the practical limitation that the flow depth and the flow velocity are difficult to observe in real time in the debris flow event is avoided, the observation information can be obtained through post-event field investigation or satellite images, and the scheme is high in practicability.

The invention relates to the technical field of civil engineering construction monitoring, and discloses a conical shell supporting system construction evaluation system and method based on finite element simulation, and the system comprises a parameter module, a construction simulation analysis module and a safety decision module. The parameter module is used for generating an initial finite element model of a built-in material time-varying constitutive relationship; the construction simulation analysis module dynamically simulates the whole construction process through a unit life-death technology, evaluates a simulation value and field monitoring data, corrects key parameters of the model through back analysis when deviation exceeds a limit, and outputs a corrected finite element model; and the safety decision module performs safety evaluation and advanced simulation based on the corrected model, generates early warning during risk prediction and outputs a construction adjustment decision. Visual, dynamic and intelligent evaluation of the construction process is achieved, and the technical problem that a traditional method cannot accurately predict and control construction safety risks is solved.

The application provides a phanerocrystalline intrusive rock blasting simulation method and device, comprising the following steps: constructing an initial rock crystal sample uniaxial compression model according to the mesoscopic physical parameters of a target phanerocrystalline intrusive rock; generating a cohesive force unit on the contact interface between the grains in the uniaxial compression model to obtain a target rock crystal sample uniaxial compression model; performing a uniaxial compression simulation test on the target rock crystal sample uniaxial compression model, obtaining test simulation data, correcting parameters through a back analysis method, obtaining target material parameters of the target phanerocrystalline rock, and constructing a rock crystal medium blasting construction FDEM model; and performing blasting simulation on the target phanerocrystalline intrusive rock according to the rock crystal medium blasting construction FDEM model and blasting parameters. Therefore, the finite-discrete coupling blasting simulation method can not only reduce the cost and time consumption, but also quantitatively represent the dynamic response law and damage mechanism of the rock mass in the blasting process.

The application discloses a soil-rock dam physical mechanics parameter inversion analysis method based on a hybrid intelligent algorithm, and belongs to the technical field of parameter inversion analysis of geotechnical engineering and hydraulic structure engineering. First, a finite element numerical model of soil-rock dam body-dam foundation integration is constructed, and physical mechanics parameters to be inverted and feasible value ranges are determined. Second, a multi-index weighted comprehensive objective function and a hybrid intelligent algorithm framework are constructed. Third, the hybrid intelligent algorithm is iterated and optimized, and a global optimal parameter set is output. Finally, inversion result precision is verified. The application can solve problems of slow late-stage convergence, easy falling into local optimization, insufficient local search capability and difficulty in giving consideration to global search and local fine optimization when a single intelligent algorithm is applied to soil-rock dam physical mechanics parameter inversion, and realizes efficient, high-precision and high-stability inversion of multi-dimensional soil-rock dam physical mechanics parameters.

The invention provides a geotechnical parameter displacement back analysis error propagation method and related equipment, and the method comprises the steps: building a grid model based on collected working condition data and geological exploration data, and solving to obtain simulated displacement; performing sensitivity analysis on geotechnical parameters in the geological exploration data by using the simulated displacement to obtain geotechnical parameters to be inverted; quantifying error characteristics of each component in the deformation monitoring data to obtain error distribution characteristics so as to generate an observation sample sequence; establishing a prior probability density function and a likelihood function of the geotechnical parameters to be inverted; based on the observation sample sequence, the likelihood function and the prior probability density function, carrying out multiple times of back analysis calculation on the to-be-inverted rock-soil parameters to obtain a posterior rock-soil parameter matrix, and based on the posterior rock-soil parameter matrix, obtaining a back analysis error propagation result of the research area; and the influence of the measurement error on the inversion result, displacement prediction and risk assessment can be accurately calculated and evaluated.

The invention discloses a BIM (Building Information Modeling)-based shield engineering stratum identification and construction parameter optimization method. The method comprises the following steps: establishing a shield construction simulation model for obtaining a shield deformation data analysis process from stratum parameters and construction parameters based on BIM modeling software; a sparrow optimization algorithm is introduced on the basis of a random forest algorithm model, an RF-SSA-based stratum parameter back analysis identification model and an RF-SSA shield construction parameter back analysis model are constructed, and through an optimization method combining the two models, rapid and accurate identification of shield construction stratum parameters is realized, and the method can adapt to a complex and changeable construction environment and is high in practicability. And the dynamic optimization of the shield engineering construction parameters is further realized. The method solves the problem that a traditional method mainly depends on experience and limited geological survey data and is difficult to adapt to complex and changeable construction environments, and consequently high uncertainty and risks exist in the construction process.

The application discloses a kind of complex deep port soft foundation's dynamic compaction-stirring pile synergic reinforcement method and system, belong to geotechnical engineering foundation treatment technical field.The method includes: survey partition, pretreatment and insert drainage board;In test area test construction and monitor soil response;Based on monitoring data and numerical simulation back analysis, dynamic optimization dynamic compaction and stirring pile synergic parameter;According to optimization parameter construction stirring pile, using alkali excitation solid waste base material;Pile top is laid out after coarse aggregate cushion and carries out dynamic compaction, ram pit fills aggregate and forms ram pier, according to the control ramming interval of superpore pressure dissipation rate.System includes construction equipment, monitoring and intelligent decision control module.The application realizes process parameter dynamic synergy and construction intelligent regulation and control, solves parameter disjunction, drainage inefficiency, shallow soft and extensive control problem, significantly improves foundation bearing capacity, overall stability and drainage efficiency, with the advantages of short period, low cost, green environmental protection.

The invention relates to an analysis method for backtracking and analyzing a post according to comments, and the method comprises the following steps: 1, a data collection unit obtains the comment data of the post from a social media platform, and carries out the preprocessing of the post; step 2, a feature extraction unit performs multi-dimensional comprehensive feature extraction on the preprocessed post comment data, and evaluates a comprehensive feature weight; 3, a backtracking analysis unit comprehensively evaluates the post quality based on the high-weight comment set, and establishes a quantitative mapping relation from comment feedback to the post quality; step 4, a negative recognition unit adopts a hierarchical and multi-dimensional detection mechanism to comprehensively recognize and trace negative contents in the comments from three levels of a vocabulary layer, a semantic layer and a context layer; and step 5, a verification unit performs multi-dimensional verification and credibility evaluation on the results of the comment backtracking analysis and the negative identification, and generates corresponding differential output according to the combination of the credibility grade and the quality score.

The application provides a foundation pit excavation deformation analysis method based on finite element model analysis, and relates to the technical field of foundation pit deformation analysis, and comprises the following steps: establishing a foundation pit initial finite element model, dividing a grid and obtaining soil parameters of each unit; defining a plurality of continuous working conditions based on a construction plan, simulating a whole excavation process, calculating horizontal displacement, vertical settlement and support structure stress of activated units under each working condition, and forming a first prediction data set; in an actual excavation process, measured data of each activated unit under a corresponding working condition is obtained, compared with prediction data, and a relative error is calculated; if the error exceeds a threshold value, soil parameters are dynamically corrected through a back analysis algorithm, and a prediction model of the soil parameters changing with excavation depth is established; subsequent working condition parameters are predicted by using the updated parameters, a second prediction data set is obtained by re-performing finite element simulation, deformation characteristic values of each unit are calculated, and finally, dynamic evaluation and hierarchical early warning of foundation pit deformation risk are realized by using a risk level zoning method.

The invention discloses a clay parameter back analysis method based on an IFC attribute closed loop and an intelligent dual-drive model. The clay parameter back analysis method comprises the steps that a foundation pit three-dimensional BIM model is built, and an IFC attribute set is generated; carrying out orthogonal processing on the soil body core parameters by adopting an orthogonal test design method to obtain a soil body core parameter set, and carrying out finite element simulation analysis through rock-soil finite element calculation software to obtain an analysis result; constructing an RF model, and performing optimization processing through a grey wolf cuckoo optimization algorithm to obtain an optimal RF training model; carrying out classification processing by adopting the optimal RF training model to obtain back analysis soil body core parameters of the target foundation pit; and the back analysis soil body core parameters are updated to soil body core parameters in the IFC attribute set, and the foundation pit three-dimensional BIM model is updated through the IFC attribute set. According to the clay parameter back analysis method based on the IFC attribute closed loop and the intelligent dual-drive model, the actual soil body core parameters of the target foundation pit can be accurately obtained, and then a reliable data basis is provided for safety evaluation and construction optimization of foundation pit engineering.

This invention discloses a method for back-analysis of shear strength parameters of soil in a homogeneous slope under sliding conditions, comprising: collecting crack information of the slope body under sliding conditions and determining the slope safety factor; determining the value range of the shear strength parameters to be inverted; determining the direction and location of cracks and selecting multiple two-dimensional calculation sections of the slope body under sliding conditions; using the geometric coordinate position of the two-dimensional calculation sections at the cracks and the slope safety factor as search constraints, and using the circular arc slip surface search to obtain the potential most dangerous slip surface and the combination of shear strength parameters; and using statistical methods to analyze the combination of shear strength parameters of the potential most dangerous slip surface to obtain the equivalent shear strength parameter combination that satisfies the slope body. This invention can improve the accuracy and reliability of slip surface construction, making the shear strength parameters closer to the actual slope condition, and can also objectively determine the unique or most reasonable equivalent shear strength parameter combination, solving the problem that the solution of shear strength parameters is not unique in the traditional limit equilibrium method back analysis.

The present application provides a kind of geotechnical parameter displacement back analysis error propagation method and related equipment, grid model is established based on the working condition data and geological exploration data collected, and simulation displacement is obtained by solving;The sensitivity of rock-soil parameters in geological exploration data is analyzed using simulated displacement, to obtain the rock-soil parameters to be inverted;The error characteristics of each component in deformation monitoring data are quantified to obtain error distribution characteristics to generate observation sample sequence;Establish the prior probability density function and likelihood function of the rock-soil parameters to be inverted;Based on the observation sample sequence, likelihood function and prior probability density function, multiple back analysis calculations are performed on the rock-soil parameters to be inverted to obtain the posterior rock-soil parameter matrix, and the back analysis error propagation result of the study area is obtained based on the posterior rock-soil parameter matrix;It can accurately calculate and evaluate the influence of measurement error on inversion result and displacement prediction and risk assessment.

The present application relates to the technical field of civil engineering safety monitoring, in particular to a method for foundation pit engineering static and dynamic risk intelligent evaluation system based on multi-source data fusion, which firstly sets personalized initial threshold value based on finite element model back analysis; collects sensor data, field images and texts, and realizes semantic vectorization of unstructured data by using computer vision and natural language processing technology; carries out data cleaning and fault diagnosis by using variational mode decomposition and spatial topology checking logic; applies D-S evidence theory to fuse multi-source data and calculate real-time risk probability; finally establishes a double-control early warning mechanism based on deformation total amount and acceleration, and corrects model parameters through measured data inversion. The present application effectively solves the problems of multi-source heterogeneous data fusion difficulty, low sensor reliability and threshold rigidity, and significantly improves the accuracy and forward-looking of foundation pit risk evaluation.

The vehicle material parameter calibration method, device and electronic equipment provided by the embodiment of the application generate a plurality of selectable material characteristic curves randomly based on the actual stress-strain curve of the vehicle material to be calibrated, input the selectable material characteristic curves into a pre-constructed deep operator network model to output a plurality of predicted stress-strain curves, in response to the curve error between the predicted stress-strain curve and the actual stress-strain curve not meeting a predetermined standard, screen and update the selectable material characteristic curves, and in response to the curve error meeting the predetermined standard, determine the current selectable material characteristic curve as the target material characteristic curve of the vehicle material to be calibrated. The deep operator network model and the approximate Bayesian back analysis framework are used to iteratively screen and update the candidate material characteristic curves, efficient, continuous and multi-working-condition joint calibration of the vehicle material GISSMO parameters is achieved, the calculation cost and the calibration period are significantly reduced, and the parameter precision and the cross-material generality are improved.

The invention discloses a long-span bridge construction monitoring method which is applied to the technical field of construction control. Comprising the steps of obtaining sensor monitoring data of each bridge section in a current construction stage; preprocessing the monitoring data of the sensor; calculating the structural displacement and stress state of each bridge section under the action of self weight, prestress, concrete shrinkage and creep and temperature change according to the preprocessed data to obtain the structural displacement and stress state of each construction stage; according to the calculated structural displacement and stress state of each construction stage, determining the formwork erection elevation of the bridge structure of each construction stage through backward analysis; and correcting the difference value between the formwork erecting elevation and the predicted value, so as to monitor the construction of each bridge section. According to the construction monitoring method, internal force and displacement of each stage can be prevented from deviating from the design value along with the change of the concrete pouring process, the safety of the structure in the construction process is improved, the construction safety and quality are guaranteed, and the construction finished bridge state meets the design requirement.

The application provides a method, device and equipment for determining a parameter reference interval of a tungsten alloy, and relates to the technical field of refractory metal material design and intelligent prediction. The method comprises the following steps: obtaining tungsten alloy data; the tungsten alloy data comprises chemical composition information, sintering process parameters and second phase attribute information. Physical mechanism features of the tungsten alloy data are extracted; based on the physical mechanism features, dispersion strengthening channel codes and solid solution strengthening channel codes are constructed. The tungsten alloy data, the physical mechanism features, the dispersion strengthening channel codes and the solid solution strengthening channel codes are all input into a preset back propagation neural network model for performance prediction, and predicted mechanical property data is output. Based on the predicted mechanical property data, back analysis is performed to generate a tungsten alloy parameter reference interval. The problems of insufficient mechanism expression, weak model interpretability and difficulty in simultaneously describing the coupling effect of dispersion strengthening and solid solution strengthening in the prior art are solved.

This invention relates to the field of geotechnical engineering technology and discloses a method and system for inclined borehole pressure water testing based on data traceability. The method includes: context binding of the pressure water test data based on the collected metadata of the inclined borehole test section to obtain data lineage flow records and data lineage pressure records; then performing hash feature mapping on the records to obtain integrity verification values; performing trusted data aggregation on the records based on the verification values ​​to obtain traceability data packets; performing tamper-proof chain derivation on the data packets to obtain a traceability data chain and storing it in a distributed storage node; finally reconstructing and fitting the traceability data chain to obtain a flow-pressure relationship curve, and obtaining a pressure water test report of the inclined borehole test section through seepage field back analysis. This invention can improve the efficiency of inclined borehole pressure water testing based on data traceability.

This invention provides a probabilistic inverse analysis method and system for shear strength parameters of soil and rock masses based on multi-source information fusion, relating to the field of geological hazard risk assessment technology. This invention integrates indoor experimental information, historical prior information, and vegetation age observation information for shear strength parameters. Through Bayesian updating and probabilistic inverse analysis methods, it obtains the final shear strength parameters, significantly reducing the uncertainty of these parameters. The accurate shear strength parameters of various soil and rock masses in deformable slopes output by this invention can be directly used for precise evaluation of slope stability, providing a reliable scientific basis for identifying potential instability and sliding locations and optimizing the design of support structures (such as anti-slide piles and anchors).

A method of evaluating a springback amount of a press formed part includes: obtaining a springback amount of an actual press formed part by giving a predetermined constraint condition to a press formed part workpiece shape model acquired by elastic mechanical analysis including a process of sandwiching the actual press formed part obtained by performing actual press forming and springback up to the forming bottom dead center and performing spring-back analysis; calculating a springback amount by giving the same constraint condition to a press formed part analysis model acquired by elasto-plastic mechanical analysis including a process of press forming the actual press formed part and performing the spring-back analysis; and comparing and evaluating these springback amounts.