208 results about "Discrete element method" patented technology

The invention relates to the cross technical field of fluid mechanics and machine learning, and discloses a particle fluid two-phase flow simulation and reverse optimization method based on deep learning. The method comprises the following steps: constructing a two-phase flow coupling simulation framework based on a fusion discrete element method and smoothed particle fluid dynamics; the drag force, buoyancy and capillary force between particles and fluid are introduced, and the calculation efficiency is improved through GPU parallel acceleration; a graph neural network is adopted to establish a particle-level dynamic interaction modeling framework, and coding and prediction of solid particles and fluid particles are independently processed; a differentiable reverse design system is further developed, and layout parameters of a flow control structure are dynamically optimized based on a gradient descent method by combining automatic differential characteristics of GNN and surrounding target functions such as flow collapse degree and centroid offset, so that effective suppression of two-phase flow destructive behaviors and system performance optimization are realized. The method has high-precision simulation and efficient optimization capabilities, and is suitable for complex two-phase flow engineering scenes such as dam burst and debris flow prevention and control.

The invention provides a filling process prediction method and device based on a discrete element method and data driving, and relates to the technical field of bulk material forming, and the method combines the physical modeling advantage of the discrete element method and the powerful prediction capability of a data driving method. The filling process of the granular material under different process parameters is simulated through a discrete element method, key quality indexes are obtained to serve as input of a data driving model, and the process parameters serve as output for training. The model not only can accurately predict the filling quality, but also can adjust the process parameters in real time according to the target quality index, so that the intelligent optimization of the filling process is realized. According to the method, the calculation efficiency is greatly improved, the generalization ability of the model is enhanced, the dependence on empirical data is reduced, a more efficient and accurate solution is provided for the filling process in the industries of building materials, pharmacy, powder metallurgy and the like, the product quality is improved, the production cost is reduced, and the research, development and application of novel materials and equipment are accelerated.

The invention discloses a mine semi-autogenous grinding process analog simulation method and system based on discrete elements, and relates to the field of analog simulation, and the method comprises the steps: according to a crushing characteristic label and a parameter mapping matrix, fusing Internet of Things sensor data, constructing a particle size distribution prediction model and an energy consumption optimization scheduling strategy, and obtaining an energy-saving operation plan; comparing the simulation data set with field production data, adjusting multi-phase coupling particle model parameters, generating a calibration parameter set, researching the influence law of semi-autogenous mill operation parameters by adopting a control variable method based on the calibration parameter set, obtaining a performance index database and an analysis report, and fusing multi-sensor data and laser radar data to obtain a semi-autogenous mill operation parameter analysis result. An ore grinding process sensing mechanism and optimization control logic are constructed, and a visual interface is generated; through multiphase modeling and data driving optimization, the simulation precision and the process suitability are comprehensively improved, and an efficient and economical solution is provided for the mine semi-autogenous grinding process.

The invention provides a mixed material quality prediction method and device based on a discrete element method and data driving, and relates to the technical field of granular material mixing, the method utilizes the discrete element method to construct a physical simulation model in a mixing process, can accurately simulate mixing behaviors of granular materials in different mixing devices, and covers various process parameters. And a data driving technology is introduced, a machine learning algorithm is utilized, and a large amount of high-fidelity data generated by DEM simulation is utilized to train a prediction model, so that a hybrid model fusing a physical mechanism and data intelligence is constructed. According to the model, the mixing effect index can be quickly and accurately predicted according to the input mixing process parameters, the corresponding optimal process parameters can be reversely predicted, and the production efficiency is effectively improved. The method aims at solving the problems that in an existing material mixing process, optimization depends on experience, efficiency is low, cost is high, and the material mixing effect is difficult to accurately predict.

The invention belongs to the technical field of pipe-jacking construction, and relates to a BIM technology-based pipe-jacking construction risk analysis method and system, and the method comprises the steps: integrating geological exploration data through BIM software, constructing a three-dimensional geological model of a pipe-jacking construction region, discretizing a model soil body into a soil body particle set through a discrete element method, inputting pipe-jacking equipment parameters, and carrying out the construction of a pipe-jacking construction risk. The method comprises the following steps: simulating a pipe jacking propulsion process, evaluating each pipe jacking construction risk, including a ground surface settlement risk, a structure damage risk and a central axis deviation risk, through real-time evolution data of soil particle displacement, stress and cluster behaviors, fusing each pipe jacking construction risk evaluation index, and feeding back a pipe jacking construction comprehensive risk state in real time. According to the method, the dynamic response condition of soil particles in the pipe jacking propelling period is accurately described from the microscopic angle, analysis is driven by real-time data of unit time step length, the comprehensive risk condition of pipe jacking construction is helped to be fed back more accurately and more efficiently, and therefore the pipe jacking construction field is promoted to develop towards the intelligent and refined direction.

The invention is suitable for the technical field of solid oxide fuel cells, and provides a gradient solid oxide fuel cell design method and device, and the method comprises the steps: employing a discrete element method DEM and dynamics Monte Carlo KMC combined electrode microstructure evolution numerical simulation method, simulating a microstructure evolution process in a sintering preparation process of the functional gradient electrode to generate a microstructure with a gradient structure; based on the microstructure, utilizing a preset micro-scale multi-field coupling model to evaluate the electrochemical performance and the mechanical performance of the functionally gradient electrode to obtain an evaluation result; inputting the evaluation result into a machine learning prediction model, and outputting electrochemical performance and mechanical performance under a preset gradient design parameter combination; and according to the electrochemical performance and the mechanical performance, a multi-objective optimization algorithm is adopted to optimize the gradient design parameter combination, and a target gradient design parameter combination is determined. And the gradient solid oxide fuel cell can be designed efficiently and accurately.

The invention is suitable for the technical field of plant modeling analysis, and provides a mature-period flexible wheat ear modeling method based on a discrete element method, and the method comprises the following steps: analyzing the geometric morphology and feature size parameters of a plurality of mature-period wheat ears of a variety to be modeled; determining geometric parameters of the wheat ear model and a filling ball arrangement mode; calculating to obtain coordinates of the filling ball; filling the filling balls, and establishing a geometric model of the wheat ears; measuring and calibrating wheat ear contact mechanical parameters and wheat ear bonding mechanical parameters; adding the mechanical parameters to the mechanical model; and inputting the geometric model and the mechanical model into discrete element software to obtain the flexible wheat ear model based on the discrete element method. The invention provides an efficient and accurate wheat ear modeling method, the calculation complexity is reduced while the model precision is ensured, the simulation efficiency is improved, and a more efficient simulation method is provided for research, development and optimization of wheat harvesting machinery.

The invention provides a drinking water pipeline anti-corrosion powder coating multi-component proportioning intelligent batching method and system, and relates to the technical field of intelligent manufacturing, and the method comprises the following steps: obtaining drinking water pipeline anti-corrosion powder coating raw material parameters and formula information; constructing a quantitative characteristic volume element numerical simulation unit, and performing multi-scale bridging calculation in combination with microscopic molecular dynamics and a macroscopic discrete element method; inputting parameters, calculating, correcting a formula, and converting into control parameters; dynamically adjusting parameters through a regression network self-learning feedback compensation algorithm; starting mixing equipment for batching, calculating the uniformity in real time, stopping mixing after the uniformity reaches the standard, detecting a finished product, and generating a report. According to the invention, through a self-learning feedback compensation algorithm based on a regression network, in combination with real-time weight detection and a material blockage identification result, intelligent dynamic adjustment of quantitative feeding control parameters is realized.

The invention provides a multi-scale simulation method for high-fidelity selective laser melting forming and phase field-lattice Boltzmann coupling, and belongs to the technical field of selective laser melting numerical simulation. The method comprises the specific steps that a selective laser melting powder laying process model is constructed based on a discrete element method, and a randomly stacked powder bed model is obtained; a high-fidelity selective laser melting forming thermal fluid dynamic model is established, and macroscopic temperature distribution and flow field distribution of a molten pool are simulated; establishing a phase field model-lattice Boltzmann coupling model; and extracting temperature gradient, solidification velocity and melt flow velocity data of local positions of the boundary of the steady-state molten pool, and simulating solidification structure evolution under flowing of molten metal in the molten pool by taking the data as initial conditions of the phase field-lattice Boltzmann coupling model. According to the method, through high-fidelity multi-scale simulation, the relation between the process parameters and the microstructure is established more comprehensively, and reliable numerical support is provided for selective laser melting process optimization and microstructure prediction.

The invention relates to the field of powder material manufacturing, and discloses a powder particle model parameter calibration method based on a discrete element method.The method comprises the steps that a static accumulation angle experiment is conducted, and the accumulation angle of micron-sized powder is obtained; performing particle size scaling according to a powder particle size distribution curve; discrete element intrinsic parameters are set according to powder characteristics and mold materials; setting to-be-calibrated parameters and ranges; performing PB design according to the to-be-calibrated parameters and the range; analyzing a test result and screening test parameters which have relatively obvious influence on the simplified and scaled powder accumulation angle; establishing a regression model and seeking an optimal combination by taking a relatively significant test parameter as an independent variable and taking an actually measured static accumulation angle as a target value; and finally determining the mineral particle model parameters based on the discrete element method through the established optimization combination verified by a numerical test. According to the method, the parameter calibration efficiency and the parameter calibration accuracy are improved, and an effective technical means is provided for key parameters of a powder particle numerical simulation experiment.

The invention belongs to the technical field of mining engineering, and particularly relates to a composite roof gob-side entry retaining roof cutting pressure relief deep hole presplitting blasting method which comprises the steps that geological data are obtained, a discrete element method is combined, a composite roof-roadway space three-dimensional mechanical model is constructed, and the roof fracture and collapse process under different blasting parameters is simulated; a whale optimization algorithm and a BP neural network are fused on the basis of roof fracture and collapse processes under different blasting parameters, and a target blasting parameter combination is dynamically output; the method comprises the following steps: monitoring roof microcrack propagation and stress change data in real time, adjusting blast hole arrangement and a charging structure in combination with a target blasting parameter combination, automatically installing a blasting material and an axial air spacer by adopting an intelligent charging robot based on the adjusted blast hole arrangement and charging structure, and accurately controlling blasting through a high-precision electronic detonator. And an ordered pressure relief process is formed according to the detonation time difference. Therefore, the problems that in the prior art, the parameter adjusting range is narrow, blasting stress distribution is uneven, and construction stability is poor are solved.

The invention discloses a direct coal liquefaction pump thermal wear prediction method considering a high temperature effect, and belongs to the technical field of fluid machinery and reliability engineering.The method comprises the steps that the high temperature effect is considered, a liquid phase control equation and a solid particle dynamic model are subjected to coupling iteration, and a solid-liquid two-phase flow numerical model is obtained; the method comprises the following steps: performing full flow field modeling on a fluid domain formed by flow passage components of a pump for direct coal liquefaction, and performing grid division on the fluid domain; constructing a heat-flow-solid multi-field coupling calculation system, and solving the solid-liquid two-phase flow numerical model by adopting a large eddy simulation method based on temperature correction and a discrete element method coupling method to obtain information of flow fields and particle fields at all positions in the pump; operation condition parameters are obtained, the thermal wear rate is obtained through a thermal wear rate calculation formula on the basis of flow field and particle field information of all positions in the pump, and the predicted wear amount of the flow passage component is obtained; and the prediction precision and applicability of the wear model are improved.

The invention discloses a numerical simulation method, device and equipment for ice rock collapse starting and a medium, relates to the technical field of fluid motion simulation, and provides an FDEM-SPH coupling framework. Through a CIE unit in the FDEM method, crack propagation and fracture processes in rock masses are accurately simulated, and after the CIE unit is completely fractured, the FDEM method simultaneously simulates various contact forms between two separated finite units, so that mutual movement and interaction between fractured rock masses can be accurately described; ice and snow melting and movement in the ice-water phase change process are simulated through the smoothed particle flow SPH, and meanwhile, the interaction between ice-water phase change and rock mass fracture movement can be quantified by calculating the contact force between virtual particles in the smoothed particle flow SPH and the surface of a finite element in the finite discrete element method FDEM; the interaction reflects the erosion and impact of the ice-water phase change on the rock mass in the whole process and the actual physical condition in the ice rock collapse starting process, so that the ice rock collapse change more fitting the real condition is described.

The invention provides a multi-scale calculation method and system for mechanical properties of a unidirectional fiber reinforced ceramic matrix composite material. According to the method, a sequential multi-scale method is adopted, the surface energy of a matrix material is obtained through molecular dynamics on the nanoscale scale, and the molecular dynamics-discrete element coupled unidirectional fiber reinforced ceramic matrix composite material multi-scale calculation method and system are provided on the basis of the periodic damage characteristic of the material under the microscale. Compared with the prior art, the method has the advantages that the nanoscale damage behavior of the ceramic matrix composite matrix and the aggregation characteristic of the microcracks are fully considered, and the calculation precision of a microscopic result is remarkably improved. The method is suitable for component design, structure optimization and mechanical property prediction of the ceramic-based composite material in the aerospace field.

The invention provides a brittle material cyclic loading and unloading test simulation method based on discrete elements. The method comprises the steps that a cyclic loading and unloading constitutive model used for describing the mechanical state of particles when a brittle material is affected by cyclic loading is constructed; based on a discrete element method and a cyclic loading and unloading constitutive model, inputting parameters and conditions, and if the time step length is not reached, calculating particle stress information; if the time step length is reached, directly outputting a calculation result and drawing a cloud picture; traversing all the particles, calculating the speed and displacement of the particles according to the stress information of the particles, outputting a calculation result, and drawing a cloud picture. According to the invention, reference can be provided for mechanical characteristics of cyclic loading and unloading tests of the fragile material, cyclic loading, fatigue and plastic failure of the fragile material under the cyclic loading condition can be reflected, and production safety in the construction process can be guaranteed; the technical problem that an existing cyclic loading and unloading test simulation method depends on experience judgment of linear regression and cannot meet the scene requirements of a nonlinear relation and plastic failure is solved.

The invention discloses a simulation method for inherent microfractures in rock based on a discrete element method, which comprises the following steps of: constructing a discrete element numerical model sample, performing static equilibrium calculation on the sample by adopting a linear model, applying fixed confining pressure to an initial sample, and performing servo calculation; a Flat-joint contact model is added, and contact bonding mesoscopic parameters are set for static balance calculation; modifying bonding contact into non-bonding contact, adding a contact gap and performing static balance calculation; carrying out a loading test; processing a test result to obtain mechanical parameters of the sample, comparing the mechanical parameters of the numerical model test with the mechanical parameters of the rock sample obtained by the indoor test, if the two mechanical parameters are matched, outputting the result, and terminating the simulation process, otherwise, modifying the contact bonding mesoscopic parameters. And reloading the test until the mechanical parameters of the numerical test are matched with the mechanical parameters of the indoor test. According to the method, the inherent micro-fracture in the rock is simulated, and the defects of a conventional model in a discrete element method are overcome.

The invention provides a CFD-DEM coupling acceleration method, which is applied to the field of computational fluid dynamics and discrete element method coupling simulation and comprises a CFD module, a DEM module, a coupling controller and an optimization module. The DEM module predicts particle distribution based on LSTM to generate a probability distribution diagram; a gradient is calculated in combination with flow field data in a CFD module, and an irregular dynamic coupling region is divided by using a geometric deep learning model; constructing a GNN-based proxy model, and adaptively switching the proxy model and a traditional drag force model based on Reynolds number; the coupling controller monitors a calculation state, and triggers data synchronization of a hierarchical compression strategy when an asynchronous time step threshold value is reached; the optimization module monitors a momentum error after data synchronization, and if the momentum error exceeds a threshold value, a neural network parameter and a threshold value coefficient are fed back and adjusted; according to the method, the problems that a traditional method is low in calculation efficiency, rigid in region division and lack of error control are solved, the calculation efficiency is remarkably improved by 5-10 times, the data synchronization amount is reduced by 58-65%, and it is guaranteed that the precision error is smaller than or equal to 5%.

The invention belongs to the technical field of metal material mechanical property research, and discloses a gear shot peening tooth surface residual stress calculation method and system.The method comprises the steps that a shot speed calculation model in the gear shot peening process is built, shot peening process analog simulation is carried out, and dynamic information of collision between shots and a tooth surface is output; the projectile speed is converted from a machine tool coordinate system to a local coordinate system; establishing a sprayed target plate model and a projectile model, dividing grids, and assembling the grid-divided projectile model and the sprayed target plate model to construct a random multi-shot finite element geometric model; and performing finite element simulation calculation on the random multi-shot finite element geometric model, and outputting residual stress distribution of the gear. According to the method, computational fluid mechanics and a discrete element method are coupled, a high-precision calculation model of the shot speed in the gear shot blasting process is constructed, the forming mechanism and distribution characteristics of the tooth surface residual stress in the actual shot blasting process are effectively reflected, and the method is good in economical efficiency, high in simulation precision, high in process executability and closer to engineering practice.

The invention relates to a novel method for constructing a soil constitutive model based on a stress test, which comprises the following steps of: performing the stress test on a soil sample by adopting a discrete element method, and analyzing the strain response of the soil under the action of stress increment in different directions; deriving key composition elements of the constitutive model based on the response envelope obtained by the stress test, including a yield surface, a plastic flow direction, a shear expansion coefficient and a plastic modulus; establishing a state-related constitutive model in combination with a critical state theory; and verifying the prediction capability of the constitutive model through a DEM heuristic test and a triaxial loading test. The method has the beneficial effects that the incremental behaviors of the soil body under different stress paths can be accurately captured through a stress tentative test, and the simulation precision of the model is remarkably improved.

The invention belongs to the field of geologic disaster prevention and control of geotechnical engineering, and provides a multi-scale numerical simulation method for a slope instability mechanism of a ductile shear zone, which comprises the following steps: acquiring physical and mechanical parameters of a rock-soil body material, and establishing a numerical model based on a particle flow discrete element method; a Johnson-Kendall-Robert contact model is adopted as a contact model between particles, the contact force between the particles is calculated, and meanwhile, a pressure interference parameter is defined to control the limit value of normal contact rigidity; performing dynamic modeling of the discrete element particle system based on a particle generator; static modeling of a discrete element particle system is carried out based on a Lagrange body continuous unit component; the acting force of discrete element particles is converted into equivalent grid node force through an equivalent node force conversion method, and surface attributes of all unit sets possibly involved in contact are defined in a solver.

The invention is suitable for the technical field of plant modeling analysis, and provides a discrete element method-based multi-moisture-content corn kernel model construction method, which comprises the following steps of: analyzing the geometrical morphology and characteristic size parameters of mature-period corn kernels with the moisture content of 12-30% of a variety to be modeled, and determining the characteristic size change condition of the corn kernels; analyzing the feature size parameters to obtain geometric parameters of the basic corn kernel model; utilizing a Sigmoid function to be matched with a matrix equation to predict the volume size change of the grains with different water contents; according to an analysis result of the geometric morphology, determining a filling ball arrangement mode of the basic corn kernel model, calculating coordinates of filling balls, and establishing a geometric model; contact parameters of the basic model are determined, the surface adhesion behavior change condition is predicted through a Sigmoid function in cooperation with a matrix equation and a Linear Cohesion model, and a humidity gradient coupling HM-LC model is established. The constructed model accords with the actual moisture content change condition characteristics of the corn kernels, and is suitable for agricultural product processing and production processes.

The invention discloses a method for calibrating finite-discrete element input parameters of a water-containing rock, which comprises the following steps of: respectively carrying out a uniaxial tensile test, a uniaxial compression test and a triaxial compression test on a dry rock sample and rock samples with different water contents; obtaining an evolution equation of the tensile strength along with the moisture content, an evolution equation of the elastic modulus and the uniaxial compressive strength along with the moisture content, and an evolution equation of the cohesive force and the internal friction angle along with the moisture content; carrying out a lateral constraint water absorption swelling test on the dry rock to obtain a vertical expansion evolution curve; on the basis of the obtained results, the fracture energy, the humidity expansion coefficient and the humidity diffusion coefficient in the finite-discrete element method are calibrated; on the basis of the calibration parameters, finite-discrete element uniaxial and triaxial compression numerical simulation of the rock samples with different water contents is carried out, and simulation results are obtained; and when the error between the test result and the simulation result is within a preset threshold value, obtaining a final parameter calibration result. The invention provides a simple, accurate and efficient parameter calibration means for water-rock interaction mechanism research.

The invention belongs to the technical field of barreling finishing machining, particularly relates to a barreling finishing machining method combined with a digital twinborn simulation technology, and solves the problems that an existing barreling finishing machining technology is difficult in real-time state monitoring, debugging of technological parameters needs to consume a large amount of time, existing analog simulation can only obtain the surface stress condition of a machined workpiece, and the machining precision is poor. The method comprises the following steps: establishing a digital twinborn model of a machined workpiece and a digital twinborn model of barreling finishing machining equipment, and carrying out simulation analysis on the barreling finishing machining process of the machined workpiece by utilizing an EDEM discrete element method and an ANSYS finite element method. Constructing a surface roughness cloud picture of the processed workpiece according to the coordinates of the surface roughness points obtained by simulation, and updating a digital twin model of the processed workpiece in real time by utilizing the surface roughness cloud picture; and the Bayesian algorithm is utilized to continuously reduce errors between analog simulation data and actual experimental data, and the surface quality of the workpiece in the machining process is predicted in real time.

The invention relates to a karst area rock sample penetration damage simulation method and system based on discrete elements, and belongs to the field of geotechnical engineering. The invention discloses a karst area rock sample penetration damage simulation method based on discrete elements. The karst area rock sample penetration damage simulation method comprises the following steps: S1, constructing a fracture damage constitutive model reflecting a karst area rock discontinuous surface position; s2, inputting parameters and conditions based on a discrete element method and the fracture damage constitutive model reflecting the position of the rock discontinuous surface in the karst area, and calculating particle stress information; s3, calculating the particle speed and displacement according to the particle stress information to obtain a calculation result; s4, outputting the calculation result; wherein in the step S2, according to the position relation between the particles and the discontinuous surface, the damage coefficient of the discontinuous surface is introduced, the particle stress information is dynamically corrected, and the penetration mechanical response under different discontinuous surface positions is accurately simulated. According to the method, the position and the crushing damage degree of the discontinuous surface of the rock are considered, a new rock sample model is constructed, and more accurate simulation is realized.

The invention relates to the field of remote control, and discloses an intelligent bucket throwing operation method and system for remotely controlling a grab ship unloader, which are used for realizing intelligent bucket throwing operation for remotely controlling the grab ship unloader. The intelligent bucket throwing operation method for remotely controlling the grab ship unloader comprises the steps of generating a full-state expected trajectory containing position, speed and acceleration information, ensuring that the trajectory is smooth and accurate, constructing a nonlinear model prediction controller, integrating a nonlinear disturbance observer, effectively estimating and compensating wind disturbance and unmodeled dynamics, and enhancing the anti-jamming capability of the system. A discrete element method is utilized to simulate interaction of material particles, and in combination with bilge topographic data, spatial distribution after material throwing is accurately predicted, system stability is monitored in real time, and a control instruction is dynamically adjusted. The precision, the stability and the efficiency of bucket throwing operation of the grab ship unloader are remarkably improved, the operation difficulty and the labor cost are reduced, and the grab ship unloader can well adapt to complex working conditions.

The invention belongs to the technical field of slope engineering numerical simulation research, and discloses an engineering scale earth-rock mixed slope numerical modeling and critical dimension determination method and system, a terminal and a storage medium, and the method comprises the steps: generating geometric parameters of stones through employing a discrete element method, and building an earth-rock mixed slope finite element model according to the geometric parameters; the safety coefficient of the earth-rock mixed slope finite element model is calculated, the critical dimension of the earth-rock mixed slope is determined based on a hypothesis testing method, and a numerical result needed for calibrating the earth-rock mixed slope critical dimension calculation model is obtained; calibrating model parameters of the critical dimension calculation model based on the preset number of numerical simulation results; stone information of the soil-rock mixed slope in the engineering scale test is obtained; and substituting the obtained stone information into the soil-rock mixed slope critical dimension calculation model, and solving and outputting the engineering scale soil-rock mixed slope critical dimension. According to the method, the size of the representative unit of the soil-rock mixed slope under the engineering scale can be quickly and accurately determined.

This invention discloses a method and apparatus for simulating the motion of a projectile landslide. The method includes: acquiring rock mass parameters of the projectile rock mass; calculating the initial state parameters of the projectile rock mass during the landslide; analyzing the flight process of the projectile rock mass in the air using an aerodynamic analysis model based on the rock mass parameters and the initial state parameters to determine the state parameters of the projectile rock mass before impact with the ground; and analyzing the motion process of the projectile rock mass after impact and after impact using a discrete element method (DEM) model based on the state parameters before impact with the ground to obtain the final shape of the projectile rock mass. This embodiment, by simultaneously utilizing both an aerodynamic analysis model and a DEM model, can more realistically simulate the motion process of a projectile landslide.

The invention relates to the technical field of particle blocking research, in particular to a blocking behavior analysis research method and system based on particle shape influence, and the method comprises the following steps: obtaining ellipsoidal particles with different particle shapes, and constructing a first blocking behavior coupling simulation model of the ellipsoidal particles; configuring and verifying the first blockage behavior coupling simulation model to obtain a second blockage behavior coupling simulation model; performing dynamic simulation on the ellipsoidal particles according to the second blockage behavior coupling simulation model to obtain a blockage behavior fitting result; and performing comprehensive analysis on the blockage behavior based on the blockage behavior fitting result, thereby realizing analysis research on the blockage behavior. According to the method, a full-analytic calculation fluid dynamics coupling discrete element method is adopted, and the particle blockage condition in the geometric shapes of the simplified pores of the ellipsoidal particles with different transverse-longitudinal ratios under the fluid flowing condition is simulated. The influence of different particle shapes on the pore blockage characteristics is evaluated through parameter analysis.

The invention discloses a dynamic adding control method of calcium oxide in flue gas desulfurization, which relates to the technical field of environmental engineering, and comprises the following steps: constructing a computational fluid mechanics and discrete element method coupling simulation model, and introducing a humidity parameter field, a particle size parameter field and an agglomeration degree parameter field into the model, and generating a spatial distribution map and a blockage probability map of the calcium oxide particles in the conveying path, and generating a conveying path control priori according to the spatial distribution map and the blockage probability map. Through coupling simulation and multi-array sensing, accurate recognition of particle aggregation and targeted disturbance control are achieved, the effective adding efficiency of calcium oxide is improved, model parameters are optimized in combination with by-product quality feedback, dynamic closed loop and predictive control are achieved, the desulfurization efficiency is remarkably improved, resource waste is reduced, the by-product quality is stabilized, and the method is suitable for industrial production. And the intelligent level of the system is enhanced.

The invention provides a material dryness and humidity prediction method and device based on a discrete element method and data driving, and relates to the technical field of material detection.According to the method, the change of interaction force between particles generated due to the change of the moisture content in the stirring process of materials is analyzed and converted into measurable engineering parameters, and the material dryness and humidity prediction result is obtained. And a quantitative mapping relation is established. According to the method, a particle system model is constructed by using a discrete element method, stirring mechanical behaviors under different water content conditions are simulated, and the accuracy of the model is verified by combining experimental data. On the basis, simulation and experimental data are trained by utilizing a machine learning algorithm, so that an intelligent model capable of predicting the water content of the material in real time is formed. The invention aims to realize efficient and accurate monitoring of the moisture content of the material.