18 results about "Inverse analysis" patented technology

The invention provides a landslide prediction method and system based on big data analysis, and relates to the technical field of big data analysis, and the method comprises the following steps: obtaining multi-source geological data of a target region, constructing a three-dimensional geological model, and dividing slope units; calculating an initial safety coefficient of each slope unit by adopting a limit equilibrium method and Monte Carlo simulation; acquiring real-time monitoring data, establishing an inverse analysis optimization model, and inverting and calibrating physical and mechanical parameters; updating calibration parameters to the model, coupling rainfall infiltration and underground water seepage simulation, dynamically updating a pore water pressure field, and calculating a real-time dynamic safety coefficient; and according to a comparison result of the dynamic safety coefficient and a preset threshold value, determining the stable state of the slope and sending out corresponding early warning. According to the method, through multi-source data fusion, parameter dynamic inversion calibration and real-time hydrological and mechanical coupling simulation, accurate and dynamic evaluation and graded early warning of slope stability are realized, and the accuracy and timeliness of landslide prediction are remarkably improved.

The invention belongs to the technical field of water conservancy and hydropower engineering, and particularly relates to a grotto side wall mechanical parameter displacement back analysis method based on a fungus growth optimization algorithm, which comprises the following steps of: 1, establishing an underground powerhouse FLAC3D numerical model by adopting an elastic-plastic constitutive model conforming to a Hook-Brown failure criterion; 2, converting a parameter back analysis problem into an optimization problem, and determining optimization variables of the mechanical parameters of the side wall of the numerical model; step 3, establishing a displacement error minimum optimization objective function; and 4, solving the target function by adopting an FGO optimization algorithm, and searching global optimal side wall mechanical parameters. According to the method, the rock mass engineering design problem that on-site large-size rock mass mechanical parameter values cannot be accurately obtained based on small-size rock samples due to the remarkable rock mass scale effect is effectively solved.

The invention provides a concrete structure construction period temperature deformation cracking risk prediction method comprising the following steps: S1, temperature monitoring: after concrete structure pouring is completed, continuously monitoring a concrete internal and surface temperature development curve; s2, inverting thermal parameters, namely inverting an equivalent adiabatic temperature rise curve and an equivalent thermal diffusivity of concrete under a field condition and a convective heat transfer coefficient of the concrete under a template in-place condition by combining a monitoring temperature, an environment temperature and a heat preservation condition and utilizing a heat conduction equation inverse analysis method; s3, prediction in the form removal period and the later period: inputting the thermal parameters obtained by inversion into finite element software, performing temperature field prediction, switching a boundary condition to be a heat exchange coefficient after form removal, and simulating subsequent temperature evolution; s4, risk index calculation and grading: calculating a risk index, and quantifying or grading the cracking risk according to a set threshold value; s5, performing construction decision linkage; according to the method, the thermal parameters of the concrete can be quickly inverted by utilizing early field measured temperature data.

To improve estimation accuracy of an underground structure.SOLUTION: In the underground structure estimation method, micromotion of the soil at observation points P1 to P6 is observed by a micromotion array 10, and at least an S-wave speed Vs1 in a base layer 1 and a depth H to an upper surface 1a of the base layer 1 are calculated by inverse analysis using a relationship between a frequency and a phase speed of a wave propagating through the soil G from the observed micromotion, thereby estimating an underground structure at the observation points P1 to P6. In the subsurface structure estimation method, predetermined observation points among the plurality of observation points P1 to P6 are grouped as group observation points Pg, inverse analysis is performed assuming that the S-wave velocities Vs1 in the base layer 1 at all the grouped group observation points Pg are the same, and the S-wave velocities Vs1 in the base layer 1 and the depth H to the upper surface 1a of the base layer 1 at each of the group observation points Pg are calculated.SELECTED DRAWING: Figure 1

The objective is to provide a system that can identify the parameters necessary for development calculations, even when dealing with photosensitive resin compositions that are scattering materials. [Solution] A parameter search device comprising: an acquisition unit that acquires at least one measured value of information relating to the minimum exposure amount or curing rate at which the film thickness does not decrease by development, and information relating to the maximum exposure amount or curing rate at which the film is substantially removed by development, when a resin layer is exposed with stepwise exposure amounts or cured to a predetermined degree by said exposure and then developed under predetermined development conditions; and a search unit that uses the measured value to search for parameters relating to coefficients or constants of a development speed calculation model by inverse analysis.

Compared to cases where weights are not included in the inverse analysis, we obtain an inverse analysis method that can derive parameters with higher accuracy. [Solution] The inverse analysis method by the inverse analysis device 10 is an inverse analysis method that performs inverse analysis using an objective function that obtains the sum of the differences between observed values ​​of predetermined types of physical quantities at multiple locations and calculated values ​​obtained by forward calculation using a mathematical model that approximates the actual field using predetermined parameters corresponding to the observed values, with weights applied to each of the multiple locations, and the parameters and weights are the targets of the inverse analysis.

This invention belongs to the field of 3D image rendering technology, and relates to a method and system for modeling and rendering packaging boxes. The invention generates a basic 3D mesh model by acquiring 2D die-cutting line data of the packaging box, extracts physical parameters of the substrate, binds features to the model, constructs multi-layer material rendering channels for optical interference calculations, and generates a model with anti-counterfeiting visual features. Further, through thermodynamic deformation calculations, a rendering model containing physical indentations is generated. Through interference verification and inverse analysis of 3D spatial features, physical processing control quantities are generated to drive production equipment to achieve automated linkage control of the packaging box. This invention solves the problem of traditional rendering mechanisms lacking accurate representation of physical deformation and complex optical scattering, improves the realism and physical accuracy of the rendered model, breaks down the data barriers from 3D rendering to physical processing, and provides effective support for high-precision packaging box production.

This invention relates to the field of tunnel and underground engineering safety monitoring technology, and discloses a method and system for graded early warning of water-soil coupled disasters in soft strata tunnels based on mechanism inversion. The method includes: using multi-scale coupling technology to parametrically couple a pre-constructed macroscopic continuous medium model and a microscopic constitutive model, and generating a mechanism inversion model based on the parameter coupling results to simulate the water-soil coupled disaster response of the tunnel surrounding rock; inputting pre-processed historical monitoring data into the mechanism inversion model, iteratively adjusting the parameters of the mechanism inversion model through inverse analysis to generate a combination of inversion parameters; and inputting pre-processed real-time monitoring data into the corrected mechanism inversion model. This invention, through local mesh refinement and erosion interface mapping based on level set functions, accurately embeds a microscopic constitutive model capable of describing soil particle migration and pore evolution into high-risk areas of the surrounding rock, achieving coupling of macroscopic and microscopic physical processes at key locations.

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.

This invention relates to the field of tunnel and underground engineering safety monitoring technology, and discloses a method and system for graded early warning of water-soil coupled disasters in soft strata tunnels based on mechanism inversion. The method includes: using multi-scale coupling technology to parametrically couple a pre-constructed macroscopic continuous medium model and a microscopic constitutive model, and generating a mechanism inversion model based on the parameter coupling results to simulate the water-soil coupled disaster response of the tunnel surrounding rock; inputting pre-processed historical monitoring data into the mechanism inversion model, iteratively adjusting the parameters of the mechanism inversion model through inverse analysis to generate a combination of inversion parameters; and inputting pre-processed real-time monitoring data into the corrected mechanism inversion model. This invention, through local mesh refinement and erosion interface mapping based on level set functions, accurately embeds a microscopic constitutive model capable of describing soil particle migration and pore evolution into high-risk areas of the surrounding rock, achieving coupling of macroscopic and microscopic physical processes at key locations.

The invention relates to a method for identifying the mechanical property of each composition phase of a multiphase material, which comprises the following steps: firstly, pretreating the surface of a material to be detected, obtaining grain orientation and grain boundary distribution through EBSD, selecting an indentation position in a target phase single grain, and implementing a nanoindentation experiment to obtain a load-displacement curve; then, scanning the three-dimensional morphology of the indentation through AFM, and extracting the depth of a feature point; establishing a single crystal three-dimensional nanoindentation CPFEM model, endowing crystal orientation measured by EBSD, and simulating to obtain a curve and morphology depth; fitting an experiment curve and a simulation curve by using a parabolic function to obtain a characteristic coefficient, and incorporating the characteristic coefficient and the morphology depth into a back analysis objective function; and finally, carrying out back analysis by adopting a global optimization algorithm to solve crystal plasticity parameters, and outputting a single crystal constitutive parameter set. Compared with the prior art, through curve and morphology double-information constraint and three-dimensional simulation, the deviation of a traditional method is overcome, the parameter identification precision and reliability are improved, and the method is suitable for multi-phase materials such as high-strength steel and titanium alloy.

The invention provides a door and window installation dynamic wind pressure detection method and system based on an intelligent sensor, and relates to the technical field of door and window wind pressure detection, and the method comprises the following steps: collecting the strain data of door and window glass based on a plurality of strain sensors embedded in the door and window glass, and combining the point cloud data of the door and window glass, constructing a three-dimensional deformation model of the door and window glass by using a deformation mapping method; based on the three-dimensional deformation model of the door and window glass, combining material parameters of the door and window glass, and utilizing a finite element inverse analysis method and an inversion compensation method to calculate dynamic wind pressure distribution characteristics of the surface of the door and window glass; and according to the dynamic wind pressure distribution characteristics of the door and window glass surface, evaluating the installation performance of the door and window to obtain a wind pressure performance evaluation detection result. According to the method, installation problems can be found in time, improvement measures can be taken, and the door and window installation quality and safety are improved.

This invention discloses a reliability modeling and evaluation method for spacecraft separation control systems under radiation environments. The method constructs a system state transition model considering fault propagation, integrates the space radiation environment and the single-event sensitivity characteristics of the hardware, generates a particle incident time series conforming to a Poisson distribution, and performs fault injection simulation of the system based on the Monte Carlo method. On this basis, it extracts multi-dimensional evaluation indicators such as system reliability, fault shielding rate, fault shielding capability, and fault distribution uniformity to form a weighted comprehensive reliability score index. Furthermore, it utilizes Bayesian networks to conduct inverse analysis to identify critical fault paths and sensitive components. This invention can effectively characterize the fault propagation mechanism of single-event upset effects in spacecraft separation control systems, achieving high-reliability evaluation of critical space control systems, and providing theoretical and methodological support for system design optimization and safety verification.

The application provides a door and window installation dynamic wind pressure detection method and system based on an intelligent sensor, relates to the technical field of door and window wind pressure detection, and comprises the following steps: based on a plurality of strain sensors embedded in door and window glass, collecting strain data of the door and window glass, combining point cloud data of the door and window glass, and constructing a three-dimensional deformation model of the door and window glass by using a deformation mapping method; based on the three-dimensional deformation model of the door and window glass, combining material parameters of the door and window glass, and calculating dynamic wind pressure distribution characteristics of a surface of the door and window glass by using a finite element inverse analysis method and an inversion compensation method; and according to the dynamic wind pressure distribution characteristics of the surface of the door and window glass, evaluating installation performance of the door and window to obtain a wind pressure performance evaluation detection result. The application is helpful for discovering installation problems in time and taking improvement measures, and improves installation quality and safety of the door and window.

The invention discloses a method for determining thermodynamic parameters of concrete by using an improved sea elephant optimization algorithm. The method comprises the following steps: carrying out inversion analysis on the thermodynamic parameters of the concrete by using a sea elephant algorithm MWaOA optimized by a chaos reverse learning initialization strategy; a Friedman test and a Wilcoxon rank sum test are adopted to carry out statistical significance analysis on a calculation result; constructing a to-be-poured bin temperature field model, and comparing the to-be-poured bin temperature field model with field measured data for verification; establishing an unstressometer statistical model according to the actually measured strain data; constructing a statistical model of strain gauge monitoring data, and inverting a creep degree mathematical expression containing eight parameters; temperature-stress field joint inversion is realized in combination with an MWaOA algorithm; repeating mechanical parameter inversion calculation and outputting optimal thermodynamic parameters; according to the method, joint inversion calculation is carried out on the concrete thermodynamic parameters by utilizing the improved sea elephant optimization algorithm, so that the simulation precision of the temperature stress field is effectively improved, and a reliable basis is provided for real-time temperature control and structural safety evaluation of the dam.

This invention improves the search technology for phenolic compounds. A method for searching phenolic resins of the varnish type, executed by an information processing device, includes the following steps: using empirical data related to phenolic resins of the varnish type to generate multiple prediction models corresponding to multiple target variables; and searching for phenolic resins of the varnish type with a desired physical property balance by using inverse analysis of the multiple prediction models, wherein the empirical data includes the polymer composition, structural formula, reaction solvent, and reaction parameters related to the phenolic resins of the varnish type, and the target variables include developability, heat resistance, and molecular weight.

The present application relates to a kind of riprap area perfusion pile-rotary jet anchor composite support deformation prediction method, specifically relates to the field of finite element numerical simulation and data processing in computer-aided engineering design, by reconstructing riprap area three-dimensional random block stone distribution field, the systematic prediction deviation caused by ignoring the block stone dispersion of homogeneous model is overcome;With batch finite element analysis and proxy model, the displacement prediction efficiency of support structure is improved to millisecond level, while maintaining high precision under the constraint of physical mechanism;Using real-time sensing data driven bayesian inverse analysis in the process of excavation, the posterior distribution of block stone random variable is dynamically updated and substituted into the proxy model, the adaptive correction of support structure displacement prediction and early warning threshold is realized, the false alarm or miss alarm risk caused by insufficient prior information is significantly reduced, and a reliable and real-time deformation control basis is provided for riprap area deep foundation pit construction.

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).