33 results about "Particle dynamics" patented technology

The invention provides an adhesive particle dynamic repose angle prediction method based on a discrete element-machine learning coupling model. The method comprises the steps that a repose angle experimental device is built, the repose angle of the adhesive particles is measured, and a repose angle data set is obtained; constructing a geometric model of the experimental device, performing discrete element numerical simulation on the adhesive particles based on the basic parameters under the characteristic working conditions, obtaining repose angle data corresponding to the characteristic parameters of the adhesive particles, comparing the repose angle data obtained by the experiment and the repose angle data obtained by the simulation one by one, obtaining an optimal parameter combination, and verifying the reasonability of the simulation; the method comprises the following steps: firstly, determining the influence of characteristic parameters on a dynamic repose angle based on the characteristic parameters of a simulation process, then constructing a machine learning prediction model according to repose angle data corresponding to the characteristic parameters under an obtained optimal parameter combination, and carrying out index evaluation and optimization. According to the method, by fusing discrete element numerical simulation and machine learning, the environmental influence is greatly reduced, and the method has excellent accuracy for predicting the dynamic angle of repose under variable working conditions.

The invention discloses a particle accelerator multi-particle dynamics efficient simulation method, system and device and a medium. The method comprises the steps that a small number of macro particles are sampled from an initial macro particle beam to form a new macro particle beam; performing multi-particle beam flow dynamics simulation on the new macro particle beams by adopting a PIC algorithm, and projecting the new macro particle beams to four two-dimensional phase spaces in a distributed manner to generate low-resolution phase diagrams of the four two-dimensional phase spaces; obtaining beam physical parameters based on the new macro particle beam; and inputting the low-resolution phase diagram and the beam physical parameters into a beam halo super-resolution network, and outputting a high-resolution phase diagram of each phase space to realize multi-particle beam flow dynamics simulation. Therefore, by combining a traditional numerical calculation method and an artificial intelligence technology, the problem that an existing artificial intelligence algorithm is weak in generalization ability in the field of beam dynamics simulation is solved, rapid and high-precision simulation of the large-scale multi-particle beam flow dynamics process is achieved, and the method is applied to the field of particle accelerator beam dynamics simulation.

The invention provides a semi-analytic LBM-DEM method for simulating particle-fluid two-phase flow, and the method comprises the steps: constructing a semi-analytic LBM-DEM coupling model, enabling the model to firstly determine the range of an expansion domain of particles, and obtaining the information, such as the average fluid velocity, the vorticity, the pressure gradient and the porosity, near the particles through traversing units in the expansion domain; and then, based on a theoretical formula and a semi-empirical formula, calculating the acting force of the fluid on the particles, and correcting a solid collision operator weight coefficient of a particle covering unit according to the acting force, so that synchronous evolution of particle dynamics and flow field distribution is realized. Compared with a classical analysis LBM-DEM coupling method, the method has the advantages that the calculation cost can be remarkably reduced under the condition that the calculation precision is guaranteed, and the method is particularly suitable for particle two-phase flow simulation in complex flow channels such as porous media and fractures.

The invention relates to a converter valve water-cooling voltage-sharing electrode charged particle distribution simulation method and system. The method comprises the following steps: constructing a three-dimensional geometric model of multiple types of voltage-sharing electrodes; constructing a charged particle multi-physics field coupling model based on the three-dimensional geometric model, wherein the coupling model comprises a flow field control equation, an electric field control equation and a particle dynamics model; simulation boundary conditions and initial conditions are set, the boundary conditions comprise flow field boundary conditions and electric field boundary conditions, and the initial conditions comprise particle release initial conditions; on the basis of the coupling model, the simulation boundary condition and the initial condition, particle tracking and distribution characteristic resolving are executed, a simulation result is obtained, and the simulation result comprises a particle motion trail, a particle capture rate and a capture area. Compared with the prior art, the method has the advantages of breaking through macroscopic monitoring limitation, realizing microcosmic dynamic quantitative analysis, analyzing a multi-field force competition mechanism, revealing a local scaling source, verifying the advantages of a multi-electrode structure, supporting optimal design and the like.

The invention provides a solid fracture calculation method and device based on smoothed particle dynamics. The method comprises the following steps: establishing a smoothed particle dynamics calculation model, setting conditions, and obtaining a stress state between particles; and when the stress state between any particle pair meets the judgment basis, judging that the particle pair is broken and breaking the link bond. And calculating the midpoint position of the fracture particle pair and setting the midpoint position as a base point, and establishing a failure surface by taking the connecting line direction of the two fracture particles as a normal direction. And on the basis of a preset smooth kernel function, in the fracture particle influence domain, according to the position relationship between the particles and the fracture surfaces, dividing the particles in the domain into a fracture surface same-side set and a fracture surface different-side set, keeping same-side links, and disconnecting different-side links. And repeating the steps until the calculation of the fracture process of the solid structure is completed. According to the method, stable construction of the failure surface is realized, the influence of real-time position disturbance is avoided, and the simulation precision and the applicability of the algorithm are improved by controlling the link keys in the complete influence domain in a regional manner.

The application relates to the technical field of aircrafts, and discloses a calculation method, equipment and medium for the multi-physical effect of ablation particles, the method comprising the following steps: acquiring equivalent inertia items induced by respective multi-physical effects; calculating a multi-physical particle dynamics process according to a particle sliding resistance item and the equivalent inertia items induced by the respective multi-physical effects; performing dimensionless processing on a radiation heat transfer equation of spherical particles in the volume of an arbitrary sampling unit to obtain a dimensionless radiation heat transfer equation; and calculating a thermal radiation particle thermodynamic process by using the dimensionless radiation heat transfer equation. The method can reflect complex physical processes under extreme mechanical environments, ensure that numerical simulation can reproduce the original appearance of ablation physics, has engineering interaction of ablation problems, automatically performs dimensionless processing, avoids numerical rigidity caused by dimensional differences of different physical problems, and fills the gap that the prior art cannot calculate complex processes of multi-physical effects of ablation particles under extreme mechanical conditions.

The application relates to a liquid drop spraying device for an inertial particle dynamics experiment of an online cabinet of a space station, which comprises a fiber coupler, a spray head and a support, the fiber coupler and the spray head are both installed on the support, a light path channel and a liquid path channel are vertically arranged and cross arranged in the support, the spray head is coaxially installed at one end of the liquid path channel and communicates with the liquid path channel, and the other end of the liquid path channel is in an open structure; the fiber coupler is coaxially installed at one end of the light path channel and communicates with the light path channel, the intersection point of the central axis of the light path channel and the central axis of the liquid path channel is a light-liquid intersection point, and the liquid spraying end of the spray head is located above the light-liquid intersection point; the support comprises a support surface and an assembly surface, the spray head is installed on the support surface side of the support through a clamping assembly, the assembly surface of the support is used for assembling with a turbulent flow generating device, and the support surface and the assembly surface are arranged in parallel opposition or at an acute angle.

The application discloses a trajectory optimization method for an electric unmanned aerial vehicle based on fuzzy neural network sequence convex optimization, and belongs to the unmanned aerial vehicle field.The application realizes the method as follows: a residual energy equation is introduced on a particle dynamics equation of the unmanned aerial vehicle, a state equation of a hybrid energy system is constructed, the state equation and an obstacle avoidance constraint are convexed in a trust region range, and a convex optimization model of a hybrid electric unmanned aerial vehicle flight trajectory problem is constructed; in view of a trust region size adjustment problem, a fuzzy neural network is designed according to a constraint violation degree and an objective function increment, the trust region is adaptively adjusted through the fuzzy neural network, the optimality of a sequence convex optimization method is improved, and the convergence speed of the sequence convex optimization method is accelerated; the hybrid electric unmanned aerial vehicle is iteratively solved through the convex optimization method, and a low energy consumption flight trajectory of the hybrid electric unmanned aerial vehicle is obtained. The unmanned aerial vehicle flies according to the obtained trajectory, solar cells can be maximally utilized, energy consumption of the hybrid energy system is reduced, and flight endurance of the unmanned aerial vehicle is increased.

The invention provides a method and a system for inhibiting deposition and splashing of aerosol jet printing by ultrasonic axial deceleration, and relates to the technical field of aerosol jet printing, and the method comprises the following steps: calculating a critical impact speed according to physical property parameters of ink and a preset critical Weber number; and calculating the acoustic radiation force required for reducing the speed of the ink to the critical impact speed when the ink impacts the substrate, calculating the sound intensity, establishing a sound field, and decelerating the ink through the sound field. According to the method, the quantitative relation between the particle dynamics model and the sound field characteristic parameters is established, and the sound field parameters are accurately regulated and controlled, so that quantitative control over the axial deposition speed of the aerosol nano-ink particles is achieved, satellite liquid drops generated by high-speed impact are fundamentally inhibited, and finally the deposition defect of excessive spraying is inhibited; and the marginal definition, the line width consistency and the electrical / mechanical function reliability of a printed pattern are remarkably improved.

According to the model and the simulation method for emitting the microscopic hot electrons to the macroscopic electromagnetic pulse, particle simulation and three-dimensional electromagnetic field simulation are innovatively coupled, and full-chain integrated simulation from microscopic particle dynamics to macroscopic electromagnetic radiation is realized; the technical problem that a micromechanism and macroscopic performance are disjointed in a traditional simulation method is effectively solved; meanwhile, the method has good universality and adaptability, and influences of multiple factors such as laser parameters, target material characteristics and experimental environments can be fully considered. By adjusting simulation parameters, electromagnetic pulse characteristics under different experiment conditions can be accurately predicted, and reliable theoretical guidance is provided for optimizing an experiment design scheme. The method is not only suitable for performance evaluation of an existing laser device, but also can provide technical support for electromagnetic pulse management of a higher-power laser device in the future.

The application provides a ship multi-degree-of-freedom motion fire flame shape evolution simulation method and system based on improved smooth particle dynamics, and belongs to the field of computational fluid dynamics and ship fire safety. The method comprises the following steps: parameter initialization, control equation construction, coupling of rolling inertia force, particle displacement and interface constraint, time advancement loop solving and result output analysis. The application introduces a density dissipation term and a particle displacement technology on the basis of traditional smooth particle dynamics, couples the inertia force generated by the six-degree-of-freedom motion of the ship to the particle momentum equation, and designs anisotropic displacement constraints of the flame interface particles and displacement amplitude limits of the free surface particles, so that the particle aggregation and pressure oscillation caused by dynamic motion are effectively inhibited, the modulation effect of periodic rolling on the flame shape is truly reflected, the clear and stable flame profile in long-time rolling simulation is maintained, and the application is suitable for ship fire design, safety evaluation and emergency decision-making.

The invention discloses a spatial flow field display method and system based on a three-dimensional engine particle system, and belongs to the field of spatial flow field display, and the method comprises the steps: obtaining original flow field data from a turboshaft engine test bed, carrying out the preprocessing and standardization, constructing a database capable of being efficiently read by a three-dimensional engine, and carrying out the three-dimensional scene construction stage, polygonal simplification and topological optimization are carried out on a physical model in a flow field, it is ensured that an engine can keep high-performance operation while the visual effect is ensured, a set of space coordinate-particle trajectory-particle dynamic binding mapping mechanism is established, and the dynamic binding of particles is realized. The abstract flow field data can accurately drive the motion trail of each particle in the particle system, and accurate correspondence between the data and the visual effect is achieved. According to the method, the script is updated through the frame, the particle system can respond to data changes in the database in real time, the motion state is dynamically adjusted, the instantaneous characteristics of the flow field are vividly displayed, and a powerful and convenient interactive tool is provided for flow field analysis.

The invention relates to the technical field of particle macro-micro mechanics, in particular to a quantitative analysis method, device and equipment for dynamic heterogeneity of an irregular particle material, and the method comprises the following steps: selecting the irregular particle material, carrying out a triaxial test based on X-ray CT, and obtaining CT slice images of the irregular particle material after deformation at different moments; carrying out image segmentation and three-dimensional reconstruction to obtain a result containing particle numbers and geometric features, and obtaining particle dynamic information through cross-strain state particle matching pursuit; active clusters are identified from the information, geometric information of the active clusters is evolved, cluster space distribution in different strain states is compared, and spatio-temporal evolution behaviors of the active clusters are tracked; and calculating the structure, dynamics and comprehensive indexes of the cluster according to the evolution behavior, determining the dynamic heterogeneity quantitative characterization by using at least one index, outputting and carrying out visual analysis on the dynamic heterogeneity quantitative characterization. Therefore, the problem that dynamic heterogeneity spatio-temporal evolution of irregular particle materials is difficult to quantitatively analyze from the micro-scale in the prior art is solved.

A numerical prediction method for heat transfer fire (CHF) based on dry spot-dry spot dynamics and conjugate heat conduction includes the following steps: S1: Establishing a functional relationship model between wall superheat and bubble dynamic parameters through regression analysis of experimental data, i.e., the bubble dynamic parameter model; S2: Establishing a dry spot-dry spot dynamic model based on the bubble dynamic parameter model; S3: Establishing a heat transfer boundary condition model based on the distribution characteristics of dry spots-dry spots on the wall and their corresponding thermal resistance characteristics; S4: Simulating the dry spot-dry spot dynamic model established in step 2 using particle dynamics; S5: Constructing a three-dimensional conjugate heat conduction equation, coupling it with the dynamically updated heat transfer boundary condition model established in S3, obtaining the wall temperature and heat flux distribution through numerical solution, and feeding the results back to the bubble dynamic parameter model established in S3; S6: Visualizing the wall temperature and heat flux distribution in S5. This application improves the physical interpretability and reliability of the simulation results.

The application discloses a large-scale neutral-macroscopic dynamics-microscopic dynamics coupling numerical simulation method based on a plasma statistical physics theory and relates to the technical field of plasma physics research, and comprises the following steps: step 1, obtaining initial physical variables; step 2, performing numerical discrete processing on the initial physical variables to obtain average flow field information on a neutral scale; step 3, performing macroscopic dynamics coupling processing on the average flow field information to obtain an intermediate result after coupling; step 4, performing local refinement processing on the intermediate result after coupling by using a microscopic dynamics numerical discrete method to obtain a refined particle dynamics simulation result; step 5, comprehensively processing the average flow field information, the intermediate result after coupling and the refined particle dynamics simulation result by using a cross-scale coupling algorithm to obtain a cross-time-space coupling numerical simulation result; and step 6, outputting the numerical simulation result and analyzing the evolution law of a solar electromagnetic storm or corresponding plasma dynamic behavior.

The application discloses a rock damage and failure smooth molecular dynamics analysis method. The application combines particle failure with rock numerical damage simulation to construct a new rock damage numerical simulation mode. The particle discrete principle of the material point method is used to discretize the calculation material domain. The calculation domain is discretized into particles by using software such as ANSYS. The particles in the calculation domain are endowed with certain material properties. The Mohr-Coulomb criterion commonly used in rock mechanics is used as the failure criterion. When the material reaches the failure condition, the particles are subjected to failure treatment. The failed particles will be permanently failed. The method is simple and easy to implement. The high efficiency and stability of GIMP itself are utilized. The gradual damage and failure process of the rock is simulated by the failure process of the particles. The whole process of the rock damage and failure can be obtained. The research provides a certain reference for the understanding of the smooth particle dynamics method in rock damage numerical simulation.

The application provides a two-phase flow simulation method and device for an aluminum-containing solid-liquid rocket engine, and relates to the technical field of rocket simulation, and comprises the following steps: in a current simulation time period, attribute parameters of aluminum-containing fuel in the aluminum-containing solid-liquid rocket engine and historical simulation results of a previous simulation time period are obtained; based on the attribute parameters and the historical simulation results, a combustion process of aluminum particles in the aluminum-containing fuel and a particle size evolution process of aluminum oxide smoke generated by the combustion of the aluminum particles are simulated respectively, so that particle dynamics parameters and smoke dynamics parameters are obtained; the particle dynamics parameters and the smoke dynamics parameters are processed, so that interphase exchange characteristics of the aluminum-containing solid-liquid rocket engine are obtained; and the particle dynamics parameters, the smoke dynamics parameters and the interphase exchange characteristics are determined as simulation results of the current simulation time period. The application can continuously and recursively simulate the two-phase flow and phase change process in the combustion chamber of the aluminum-containing solid-liquid rocket engine.

The invention discloses an electromagnetic sensor signal analysis method and system based on real abrasive particle dynamic trajectory and time-harmonic field intensity coupling, and belongs to the field of mechanical equipment state monitoring and sensor simulation. The method comprises the following steps: firstly, based on a CFD-DEM coupling theory, combining abrasive particle multi-physical field stress, and accurately reconstructing a real three-dimensional dynamic track in a complex flow field of a lubricating oil pipeline; and establishing a three-dimensional time-harmonic magnetic field analysis model based on magnetic vector potential and a modified Bessel function, constructing a dynamic mapping relation between the transient position of the abrasive particles and a non-uniform magnetic field, quantifying the disturbance characteristic of the abrasive particle eddy current to the magnetic field, and solving the transient response of the sensor induced electromotive force. Abrasive particle size, material conductivity and magnetic conductivity parameter correction are fused, simulation distortion caused by a simplified motion model and neglect of radial magnetic field difference in a traditional theory is overcome, and high-precision prediction of dynamic signals of the whole process that the abrasive particles pass through the sensor is achieved. The method is suitable for health monitoring of aero-engines and industrial gearboxes.

The invention relates to the technical field of image data processing, and provides a progress display method and system based on data-driven particle dynamic reconstruction identification. The method comprises the steps of segmenting a data packet into data blocks and generating a meta-information file to establish a mapping relation between a data block index and an anchor point by presetting an anchor point coordinate set and a particle coordinate range of a target identifier, determining an initial position of a particle based on meta-information, and driving the particle to dynamically converge to the anchor point according to a transmission progress until the target identifier is aggregated. According to the method, deep binding of data and vision, multi-dimension of progress perception, self-adaptive compatibility and fusion of visual information spreading value and user experience are realized, and the technical bottleneck that a traditional progress display mode is boring and lacks interactivity and brand relevance is effectively solved.

The application discloses a high-speed train dynamic system fault detection method based on an interval observer, and belongs to the high-speed train fault detection field. First, a high-speed train multi-particle longitudinal unknown bounded dynamic model is constructed, and the tractive force output by each car compartment in a balanced state is obtained; a multi-particle speed tracking state space model and a system state equation when an actuator fault occurs are established according to the constructed dynamic model; a fault detection interval observer is constructed, and an observer gain matrix is obtained by solving a linear matrix inequality constraint optimization problem; the upper bound and the lower bound of the system state error are defined, a state error dynamic model of the interval observer is constructed to obtain the estimated values of the upper bound and the lower bound of the state error of the designed interval observer, and whether the high-speed train dynamic system has a fault is judged according to the estimated values. The method can realize fault detection on the multi-particle dynamic characteristics of the high-speed train without needing to obtain accurate model parameters and car forces of the high-speed train in advance.

The invention belongs to the technical field of locomotive dynamic characteristic modeling, and particularly provides a locomotive dynamic braking characteristic self-learning modeling system and method, and the system comprises a dynamic characteristic model building module which is used for building a locomotive simple substance point dynamic characteristic model; the braking characteristic model construction module is used for constructing a locomotive dynamic braking characteristic model based on OBSCNs by adopting an optimal block increment random configuration neural network OBSCNs; the self-learning modeling module is used for obtaining a locomotive dynamic braking characteristic self-learning model; and the locomotive braking control module is used for obtaining the locomotive dynamic braking characteristics based on the locomotive dynamic braking characteristic self-learning model and completing control over the locomotive parking braking process. According to the technical scheme, the hybrid braking dynamic characteristics of the locomotive under the complex environment change can be accurately and effectively described, a characterization tool is provided for safe, stable, comfortable and accurate control of the parking braking process of the locomotive, and safe, efficient, energy-saving, comfortable and tight tracking operation of the locomotive is achieved.

The invention discloses a soot particle size distribution calculation method based on a detailed transport model and a zoning method, and belongs to the technical field of soot numerical simulation in a carbon-containing fuel combustion process. According to the method, on the basis of a detailed transport model of a standard gas kinetic theory, a partitioning method is coupled with a limited rate chemical reaction model, and a detailed chemical reaction mechanism and a difference diffusion effect are combined, so that the problem that components, temperature, soot particle size distribution and component-soot interaction cannot be accurately described by a traditional numerical method is solved. The method comprises the following specific steps: calculating component transport characteristics through a detailed transport model, coupling a partition method and a particle dynamics process, establishing a control equation, discretizing and solving numerical values, and realizing parallel simulation acceleration in combination with a reference mapping model and a dynamic load balancing method. According to the method, key parameters such as components, temperature, soot volume fraction and particle size distribution can be predicted with high precision by solving the components and soot transportation in real time, and theoretical support is provided for low-carbon emission design of a new energy burner.

The application discloses a train speed prediction method, device, equipment, medium and product, relates to the field of train speed prediction, and the method comprises the following steps: constructing a train speed prediction model; the train speed prediction model comprises a nonlinear autoregressive module, a block feature extraction module, a dynamic feature extractor and an FNN module; the nonlinear autoregressive module is constructed based on high-speed train single-particle dynamics; the dynamic feature extractor is constructed based on high-speed train multi-particle coupled dynamics; the average speed of the high-speed train at the current time and each historical time and the unit features of each dynamic unit are input into the train speed prediction model to obtain the predicted average speed of the train at the next time, and the application provides a train dynamics model which simultaneously meets the explainability, lightness and multi-particle global modeling, thereby improving the speed prediction efficiency.

The application discloses a kind of numerical simulation systems of stent intervention smooth particle dynamics based on intravascular image;Including: vascular attribute collection module, stent establishment module, particle and assembly module, stent release setting module and release stent mechanics simulation module, particle and assembly module reads the three-dimensional vascular model of vascular attribute collection module, the three-dimensional stent model of stent establishment module and the specified lesion position of input, and constitutes the complete model to be particle;Particle is generated after particle by the particleization of stent model through the pre-processing of smooth particle method, and the complete model after particle;Stent release setting module sets given geometric constraint to stent;Release stent mechanics simulation module simulates using smooth particle method according to the boundary condition of force.The present application combines patient image data, realizes the stress distribution when stent expansion is predicted before operation, improves compliance and support force balance;Evaluate the risk of plaque rupture, avoid vascular injury.

This invention discloses a rock failure simulation method based on three-dimensional particle dynamics analysis (DDA), relating to the field of rock mechanics. The study domain is discretized into a set of multiple rigid spherical particles, and their initial positions, radii, material properties, and control parameters are recorded. A contact determination scheme is used to determine the spatial positions of contact points between particles, and a distance threshold is used to control the contact activation conditions. Based on the principle of minimum potential energy, stiffness sub-matrices corresponding to four types of springs (normal, shear, torsional, and rolling) and friction force sub-matrices corresponding to frictional forces are generated. These matrices are assembled into a system of simultaneous equations, and the correct contact state is determined using open-closed iteration. During this process, a set of contact states is first predicted, the simultaneous equations are solved, and the solved contact states are updated. If the solved contact states are consistent with the predicted contact states, the iteration converges; otherwise, the updated contact states are used to update the predicted contact states, and this process is repeated until convergence. This solves the problem of maintaining consistent macroscopic mechanical responses at different particle scales.

The application discloses a kind of based on deep learning's oil liquid abrasive particle dynamic monitoring method and system, belong to oil liquid abrasive particle dynamic monitoring technical field.S1.Through multiple sensors in the equipment lubrication system Real-time acquisition oil sample set;S2.Extract abrasive particle image in oil sample set;S3.Construct double-layer generative adversarial network model;S4.The trained double-layer generative adversarial network model is deployed in monitoring system, real-time acquisition and input abrasive particle image, and generate wear characteristic data;S5.Based on the wear characteristic data of identification, calculate the wear state index of equipment, judge whether equipment is in abnormal state;S6.If wear state index is detected to exceed set threshold, system automatically triggers early warning mechanism, and generates early warning information and informs relevant personnel to take maintenance measures;S7.Monitoring result is stored in database.The present application realizes accurate analysis and classification to oil liquid abrasive particle data, greatly improves the real-time monitoring and early warning capability of system.

The invention provides a solid-liquid two-phase flow wear prediction method and prediction system based on artificial intelligence and fractal dimensions, and belongs to the technical field of equipment state monitoring. According to the method, particle dynamic signals in equipment are collected through vibration, ultrasonic and other multi-mode non-intrusive sensors; performing fusion processing on the multi-source signal to generate a feature vector; predicting fractal dimensions representing the complexity of the particle aggregation structure by using a pre-trained model; determining an optimal wear correlation model through a three-layer progressive screening strategy, and converting the optimal wear correlation model into a real-time wear rate; and according to the interval and the duration of the wear rate, triggering graded early warning and controlling the equipment in a linkage manner. According to the method, real-time, online and quantitative evaluation and intelligent operation and maintenance of the internal wear state of the all-metal structure equipment are realized, the dependence of traditional optical monitoring on a transparent window is broken through, and the method has the advantages of high anti-interference performance, wide applicability and high prediction precision.

This invention belongs to the field of blast furnace ironmaking technology, specifically disclosing a method for constructing a three-dimensional numerical model of the gas-solid reaction flow in the vortex zone of a hydrogen-rich carbon-circulating oxygen blast furnace. The method involves geometric modeling and mesh refinement, definition of an Eulerian multiphase flow system, and establishment of the gas-solid two-phase mass-momentum-energy conservation equations. The standard turbulence model, particle dynamics theory, and Gidaspow drag model are used to close the equations, which are then solved using the finite volume method. The accuracy of the model is verified by combining actual production data. This solves the problem that traditional models cannot be adapted to high-precision simulation of hydrogen-rich carbon-circulating oxygen blast furnaces. Results show that the simulation error in the depth of the vortex zone is low, meeting the accuracy requirements, and achieving refined simulation of the vortex zone morphology, temperature field, and composition field.

The invention discloses a train speed prediction method and device, equipment, a medium and a product, and relates to the field of train speed prediction.The method comprises the steps that a train speed prediction model is constructed; the train speed prediction model comprises a nonlinear autoregression module, a block feature extraction module, a dynamic feature extractor and an FNN module; the nonlinear autoregression module is constructed based on high-speed train simple substance point dynamics; a dynamic feature extractor is constructed based on high-speed train multi-mass-point coupling dynamics; and inputting the average speed of the high-speed train at the current moment and each historical moment and the unit characteristics of each power unit into the train speed prediction model to obtain the predicted average speed of the train at the next moment. And the prediction speed and efficiency are improved.