37 results about "Particle trajectory" patented technology

The invention discloses an urban particulate matter migration path identification method based on data fusion of a dynamic diffusion model and multi-source sensing. According to the method, firstly, multi-source pollution related data of a fixed monitoring station, a mobile monitoring device, a meteorological observation node and a traffic sensing system are collected, and standardized input is constructed after time synchronization, coordinate mapping and exception handling. And then establishing a hybrid dynamic diffusion model fusing a two-dimensional Gaussian plume model and a Lagrange particle tracking mechanism, and realizing assimilation of monitoring data and model output in combination with an improved particle filtering algorithm to obtain a correction concentration field. Based on concentration gradient analysis and particle trajectory superposition, a pollution migration path is extracted, then indexes such as a migration intensity index (MII), a path stability factor (PSF) and path average correlation are calculated, and recognition and sorting of a migration direction, a pollution source position and path stability are achieved. Meanwhile, an alpha dynamic weight factor is introduced, adaptive weighting is realized between the Gaussian model and the LPDM model, and the path strength and consistency are considered. Experimental results show that the method is superior to a traditional method in average absolute deviation (MAD) and hot spot overlap ratio (IoU) indexes, diffusion and migration rules of particulate matters under complex urban conditions can be more accurately revealed, and the method has important environmental governance and emergency management application value.

The invention provides an agricultural pest diagnosis and early warning method and system based on an intelligent algorithm. The system comprises a spore collection and detection module, a credibility evaluation module, a wind field inversion and source region identification module, a incubation period modeling module, a risk judgment module, a control decision and scheduling module and an output interface module. The spore collection and detection module obtains a spore living body load value in real time through an air sampling and quantitative PCR detection technology; the credible evaluation module realizes pathogen effective trigger state recognition through multi-dimensional threshold judgment; the wind field inversion and source region identification module determines an upstream source region and a propagation path by using a particle trajectory inversion and clustering algorithm; the incubation period modeling module is used for calculating an incubation period and deducing a potential disease time window based on the environmental parameters and an Arrhenius model; quantitative modeling and intelligent early warning of the whole disease and pest propagation process are achieved, the timeliness and accuracy of prevention and control can be improved, and the prevention and control cost is reduced.

The invention discloses a self-adaptive air pressure regulation and control system of quartz sand unpowered powder selecting equipment, and relates to the technical field of automatic control. According to the method, wind pressure and airflow disturbance signals are collected, a high-resolution map is generated through Hampel filtering and noise reduction, features are extracted through the convolutional neural network, key influence areas are identified, the problem of unstable wind pressure caused by airflow disturbance in a mountainous area is solved, and the particle separation precision is improved; a natural potential energy distribution matrix is constructed based on building floor height difference, velocity field reconstruction and airflow channel optimization are driven, technological parameters are adjusted in combination with a gradient descent algorithm, precise utilization of natural potential energy is achieved, energy consumption is reduced, uneven efficiency is improved, airflow distribution is simulated through a fluid dynamic model, and sedimentation behaviors are analyzed and predicted through particle trajectory. A support vector machine is used for classifying tracks and generating regulation and control instructions, PID control is used for stabilizing air pressure to form a closed loop, the problems that fine powder is mixed with coarse powder, coarse particles are left and the like are avoided, the equipment blockage risk is reduced, and the product purity stability is improved.

The invention relates to the technical field of micro-fluidic chips, and discloses a multi-fluid effect synergistic three-dimensional single-row focusing micro-fluidic chip and a method for single-line focusing of polystyrene microspheres by using the micro-fluidic chip, the micro-fluidic chip comprises a sample liquid inlet, one end of the sample liquid inlet is provided with an inertia focusing link, and the other end of the sample liquid inlet is provided with an inertia focusing link; a tapered flow guide cone structure is arranged between the inertial focusing link and the sample liquid inlet and is used for inhibiting the initial dispersion and diffusion trend of particles at the sample liquid inlet; the bionic gradient height structure is positioned at one end, far away from the tapered flow guide cone structure, of the inertial focusing link and is used for focusing and compressing the particles in the vertical direction; a sheath fluid focusing area is arranged at one end, far away from the inertial focusing link, of the bionic gradient height structure, and a sheath fluid inlet and a chip mixed liquid outlet are sequentially formed in one end, far away from the bionic gradient height structure, of the sheath fluid focusing area. According to the invention, efficient three-dimensional centered arrangement is realized, dynamic convergence of a particle trajectory from a dispersion state to a central single beam is realized, and a digital focusing regulation capability is realized.

The invention relates to the technical field of marine environment simulation and risk assessment, in particular to a calculation method for simulating a blockage particle trajectory. The calculation method for simulating the particle trajectory of the blockages comprises the steps that a wave flow coupling model is constructed according to a grid file, and the grid file is constructed through a surface water simulation system; in a particle tracking module of the wave-flow coupling model, adjusting particle parameters of blockage particles according to the dynamic characteristics of the blockage; operating the particle tracking module to obtain simulated trajectory data of the blockage particles after particle parameter adjustment; and according to the simulated trajectory data, counting the number and probability of the blockage particles entering the predetermined range of the nuclear power station water intake so as to predict the blockage risk of the nuclear power station water intake. According to the calculation method, the drifting trajectory of the blockage object can be accurately simulated, the risk that the water intake is blocked is predicted, and a reliable quantitative basis is provided for water intake safety early warning and protection decision making of the nuclear power station.

This application discloses a particle trajectory reconstruction method, apparatus, device, and medium based on flow-sensing implicit neural representation, relating to the field of computer technology. The method includes: constructing a spatiotemporal position embedding network based on Eulerian flow field information of the flow field surrounding an aircraft, utilizing a multilayer perceptron and implicit neural representation model to capture the spatiotemporal distribution and motion patterns of particles in the flow field around the aircraft; constructing a multi-scale residual learning module using Taylor expansion to balance trajectory learning at different time scales; constructing an initial particle trajectory reconstruction model using the spatiotemporal position embedding network and the multi-scale residual learning module; training the initial particle trajectory reconstruction model using target constraints; generating a target motion trajectory using the obtained target particle trajectory reconstruction model and based on the position information and integration time of the target particle in the flow field; where the integration time is the length of the target particle's motion time in the flow field. This improves the efficiency of particle trajectory reconstruction in complex flow fields.

The invention relates to the technical field of industrial dust removal equipment design and fluid simulation, and discloses a macroscopic numerical simulation and verification method for dust deposition uniformity of a metal filter bag deduster, which comprises the following steps: constructing a deduster full-size model loaded with a porous jumping medium boundary; establishing an Euler-Lagrange gas-solid coupling model to calculate a flow field and a particle trajectory; designing a diversion structure orthogonal experiment based on the flow field characteristics, and obtaining operation resistance and deposition mass data under different parameter combinations; establishing an evaluation system comprising a flow distribution coefficient and a deposition uniformity index, and screening an optimal structure; a physical experiment platform is constructed for powder coating and segmented scraping weighing, and the reliability of the method is verified by comparing relative errors of experiments and simulation data. According to the method, through macroscopic equivalent modeling and quantitative evaluation, the deposition behavior in the metal filter bag dust collector is accurately predicted, the problem of uneven load of the filter bag is effectively solved, and a reliable basis is provided for structural optimization.

The invention discloses a method for optimizing a lead-bismuth venturi flow meter with ferroferric oxide particle deposition intervened by a magnetic field. The method comprises the following optimization steps: constructing a parameterized three-dimensional geometric model of the venturi flow meter; performing grid division on the model in computational fluid dynamics (CFD) software, and setting a multiphase flow model and a discrete phase model; compiling UDF for dynamically applying a virtual magnetic field in the flow field area of the tapered fillet section in the CFD solving process; the UDF is loaded, the virtual magnetic field serves as a source item to be coupled to a control equation of the fluid and the particle phase, and the influence of the virtual magnetic field on the particle motion trail is simulated; obtaining and analyzing the motion trail of the particles and the particle deposition amount of the fillet transition structure; based on an analysis result, adjusting the next one or more optimization variables and iteratively executing the steps until the particle deposition amount meets a preset requirement; according to the method, a virtual magnetic field which can be flexibly regulated and controlled is introduced by embedding a user-defined function, and an efficient simulation tool and a theoretical basis are provided for collaborative optimization of a flowmeter structure and a deposition suppression strategy.

The present disclosure provides a particle special effect rendering method for simulating extreme working conditions in a virtual engine, comprising: obtaining fire scene parameters, and constructing a decoupled particle system architecture in the virtual engine according to the fire scene parameters to generate a particle initialization result. Determine the fire source area particle quota through the particle initialization result, and generate fire particles based on the fire source area particle quota to construct different types of initial particle states. Based on the different types of initial particle states, the dynamics trajectory of the fire particles is calculated, and the first particle state after updating the particle trajectory is determined according to the dynamics trajectory. Determine the interaction behavior between the fire particles and the scene material through the first particle state, and generate the second particle state after updating the particle behavior according to the interaction behavior. According to the second particle state, the particle rendering is carried out to generate a dynamic light and shadow fusion result, and a fire particle special effect frame is drawn according to the dynamic light and shadow fusion result, realizing the real-time rendering of the particle reality.

The invention provides a micro-plastic adsorption performance medical mask quality detection system based on artificial intelligence, relates to the field of quality detection, and improves the accuracy and efficiency of medical mask micro-plastic adsorption performance detection. The method comprises the following steps: firstly, extracting fiber pore distribution features, fiber directional arrangement features and fiber surface roughness features from a mask microscopic image by adopting a trained deep neural network; thirdly, constructing a virtual filter material structure model based on the extracted morphological characteristics, injecting simulated micro-plastic particles with different particle sizes, calculating the capture rate and the passing rate of the particles by adopting a particle trajectory tracking algorithm, and predicting the comprehensive micro-plastic adsorption efficiency; and finally, setting a dynamic efficiency threshold value according to an application scene to carry out quality judgment, and automatically identifying a morphological defect type when detecting that the performance is unqualified. Through combination of deep learning and a virtual simulation technology, the intelligent level and the defect diagnosis capability of medical mask micro-plastic adsorption performance detection are remarkably improved.

The invention discloses a Kerr black hole equatorial plane particle trajectory rapid prediction method and system. The method comprises the steps of S1, data construction and screening; s2, carrying out sequence standardization and pretreatment; s3, constructing a trajectory prediction model; s4, training a mixed physical constraint loss function; and S5, performing rapid reasoning and trajectory reconstruction. According to the method, complex Kerr space-time three-dimensional motion is simplified into two-dimensional motion of the equatorial plane, end-to-end mapping from an initial condition to a complete trajectory is realized by using deep learning, a time-consuming process of solving a geodesic equation is replaced by single forward propagation of a neural network, and the calculation efficiency is far higher than that of a traditional numerical integration method. According to the method, the robustness of the geometrical morphology of the track is ensured through the chamfering distance loss, and geometrical characteristics such as recent point precession angles can be accurately predicted; the common noise jitter of the neural network is eliminated by the smoothness loss, and the physical rationality of the trajectory is ensured.

The invention provides a particle effect rendering method for simulating an extreme working condition in a virtual engine, and the method comprises the steps: obtaining a fire scene parameter, and constructing a decoupling type particle system architecture in the virtual engine according to the fire scene parameter, so as to generate a particle initialization result. And determining the particle quota of the fire source region through the particle initialization result, and generating fire particles based on the particle quota of the fire source region to construct different types of initial particle states. And based on the different types of initial particle states, calculating a dynamic trajectory of the fire particles, and determining a first particle state after the particle trajectory is updated according to the dynamic trajectory. And determining an interaction behavior between the fire particles and the scene material through the first particle state, and generating a second particle state after the particle behavior is updated according to the interaction behavior. And performing particle rendering according to the second particle state to generate a dynamic light and shadow fusion result, and drawing a fire particle special effect frame according to the dynamic light and shadow fusion result to realize particle authenticity and real-time rendering.

The application provides a kind of agricultural disease and insect pest diagnosis early warning method and system based on intelligent algorithm, system includes: spore collection and detection module, credible evaluation module, wind field inversion and source area identification module, incubation period modeling module, risk determination module, prevention and control decision and scheduling module and output interface module.Said spore collection and detection module obtains spore living body load value in real time by air sampling and quantitative PCR detection technology;The credible evaluation module realizes the effective triggering state identification of pathogen by multidimensional threshold determination;Wind field inversion and source area identification module determines upstream source area and propagation path using particle trajectory inversion and clustering algorithm;Incubation period modeling module calculates incubation period based on environmental parameters and Arrhenius type model and deduces potential disease time window;The application realizes the quantitative modeling and intelligent early warning of the whole process of disease and insect pest transmission, can improve the timeliness and accuracy of prevention and control, and reduce the prevention and control cost.

The application discloses a kind of water pump flow field measurement method and velocity measuring particle based on inertial guidance, it is related to water pump flow field measurement technical field.The method comprises: assembling and calibrating the velocity measuring particle of built-in IMU, releasing at water pump entrance, so that it enters water pump interior and records acceleration data itself, recycles particle at water pump in outlet, reads IMU data in particle, reconstructs particle motion track by zero offset calibration, attitude solution, gravity elimination, integral positioning, zero speed correction and other steps, reconstructs global velocity field using the trajectory of multiple particles by RBF interpolation, and then calculates flow, traces streamline and generates velocity nephogram.The application does not need to reconstruct the structure of water pump, is not limited by flow pattern and pipeline transparency, can simultaneously output high-precision flow and full flow field visualization result, provides a kind of new technical means for water pump operation monitoring and optimization design.

The application provides a trajectory tracking model training method and a hydrous particle trajectory tracking method. The method comprises: obtaining training data, the training data comprising simulation information of at least one hydrous particle in at least one preset time period, the simulation information comprising at least three-dimensional environmental wind information of an environment in which the at least one hydrous particle is located in the at least one preset time period and a terminal falling speed of the at least one hydrous particle in the at least one preset time period; and training an initial trajectory tracking model based on the training data to obtain the trajectory tracking model, the trajectory tracking model being used to calculate motion trajectory information of the hydrous particle according to the simulation information of the hydrous particle. The method of the application can solve the problem of how to track the trajectory of a hydrous particle group, thereby improving the comprehensiveness and accuracy of gas phase observation.

A super-resolution ultrasonic blood flow imaging method fusing particle trajectory prediction and motion compensation comprises the following steps: injecting a microbubble contrast agent into a living body to obtain a microbubble distribution image; arranging all the microbubble distribution images according to a time sequence, and obtaining a blood flow distribution diagram through a particle trajectory prediction method; further eliminating a wrong track through speed difference constraint; and eliminating the influence of the micro motion of the background organization on the track result through a dynamic compensation method. The method has the advantages that the imaging resolution is obviously improved, and the movement interference of tissues and organs can be effectively reduced. According to the method, historical data and velocity vector information of the microbubbles are combined, the future positions of the microbubbles are predicted by using a Kalman filter, and matched microbubbles are searched nearby the future positions, so that the trajectory matching accuracy is improved, and the imaging resolution is improved. Meanwhile, cross-correlation search based on dynamic programming is adopted, wrong trajectories caused by tissue movement are extracted and eliminated, the definition of the microvascular morphology is further optimized, the signal-to-noise ratio of the image is remarkably improved, and the method is suitable for imaging of moving organs.

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.

This invention discloses a rapid prediction method for insulator surface flashover voltage considering microscopic surface collisions, achieving a balance between computational efficiency and microscopic physical accuracy. The method innovatively maps the macroscopic roughness of the insulator to the collision restitution coefficient (characterizing kinetic energy dissipation), local electric field enhancement factor (characterizing microscopic distortion), and diffuse reflection distribution model of microscopic particles. Under electric field driving, particle trajectories are iteratively calculated, and velocity reduction and local field strength correction are performed based on the aforementioned dual competition mechanism when particles collide with the interface. Finally, the effective ionization coefficient is integrated in the time domain with velocity weight along the microscopic trajectory, and the flashover voltage is iteratively output by comparing it with the streamer critical criterion. This method, by introducing a particle tracking mechanism, maps macroscopic surface roughness to microscopic collision restitution coefficients and diffuse reflection distribution, and proposes a time-domain integration model, achieving efficient and accurate prediction of flashover voltage.

The invention discloses a tracer particle adaptive clustering algorithm based on an event camera and a velocity measurement system, and belongs to the field of experimental fluid mechanics flow field velocity measurement. According to the algorithm, continuous laser is used for irradiating flow field tracer particles, and an event camera is used for collecting asynchronous event flows generated by particle movement to obtain event point clouds; particle trajectory reconstruction and velocity field estimation are realized through the steps of statistical filtering, preliminary clustering and velocity fitting, displacement correction, secondary clustering, iterative convergence, velocity field fitting and the like. Microsecond-level time resolution of the event camera is fully utilized, high-frequency laser is replaced by continuous laser, cost is reduced, boundary layer measurement interference is avoided, the problems of time resolution waste and high cost in the prior art are solved, and the method is suitable for experimental fluid mechanics flow field particle tracking speed measurement scenes.

The application relates to a kind of charged particle CT imaging detection method and system. Including: obtaining the beam parameter of charged particle beam, and calculating the relative position of the charged particle beam out of the beam parameter and the adjustment position of each detector, the detector includes the upstream detector before the charged particle beam passes through the object to be measured and the digital detector after passing through the object to be measured;The position of the upstream detector and the digital detector is controlled to the corresponding adjustment position;Receive the charged particle beam, sequentially through the upstream detector, the object to be measured and the digital detector, and read the detection information of the upstream detector and the digital detector in the form of digital signal;According to the detection information, generate Sinogram image, and carry out preliminary image processing;According to the Sinogram image of preliminary image processing, generate tomographic image based on image reconstruction algorithm.The application can improve data processing efficiency and accurately measure particle trajectory.

The application relates to a water vapor tracing and quantitative contribution evaluation method for a strong rain and snow process, and comprises the following steps: for a strong rain and snow process, a cumulative precipitation falling area graph and an hourly precipitation distribution graph are established, a strong precipitation falling area and a strong precipitation period are determined, a water vapor tracking scheme is established, and a tracking area and a tracking time are determined; the HYSPLIT tracking mode is used to determine the trajectory source of air particles leading to the strong rain and snow process; all air particle trajectory results obtained through tracking are screened to obtain contributing air particles; the screened air particle trajectories are classified to obtain the contributing air particle trajectories; the water vapor source of the strong rain and snow process is identified according to the sign of dq in the air particle trajectory; the average specific humidity evolution of the screened air particles and the final relative water vapor contribution of each water vapor source to the strong rain and snow process are quantitatively confirmed. The application can provide reliable decision-making basis for the transportation, power, agriculture and other departments of the target region.

The invention discloses a three-dimensional flow field dynamic adaptive visual sampling method based on deep reinforcement learning, and belongs to the technical field of scientific visualization and computer graphics. According to the method, an interaction environment fusing multi-dimensional physical characteristics and real-time particle density is constructed; the method comprises the following steps: designing an intelligent agent based on an Actor-Critic architecture, and capturing space-time correlation characteristics of a flow field structure and particle distribution by adopting a three-dimensional U-Net combined with a ConvGRU as a strategy network; dynamically outputting newly added particle quantity budget and spatial probability density distribution through a double-head action decision mechanism; and finally, in a GPU-based parallel simulation environment, a particle trajectory is updated by using high-order numerical integration and adaptive life cycle management, and animation rendering is carried out. According to the method, a threshold value does not need to be set manually, the sampling strategy can be automatically adjusted according to the flow field features and the current visual density, the contradiction between visual occlusion and feature loss is effectively solved, and clear and dynamic visualization of a large-scale complex flow field is achieved.

This application discloses a particle trajectory reconstruction method, apparatus, device, and medium based on flow-sensing implicit neural representation, relating to the field of computer technology. The method includes: constructing a spatiotemporal position embedding network based on Eulerian flow field information of the flow field surrounding an aircraft, utilizing a multilayer perceptron and implicit neural representation model to capture the spatiotemporal distribution and motion patterns of particles in the flow field around the aircraft; constructing a multi-scale residual learning module using Taylor expansion to balance trajectory learning at different time scales; constructing an initial particle trajectory reconstruction model using the spatiotemporal position embedding network and the multi-scale residual learning module; training the initial particle trajectory reconstruction model using target constraints; generating a target motion trajectory using the obtained target particle trajectory reconstruction model and based on the position information and integration time of the target particle in the flow field; where the integration time is the length of the target particle's motion time in the flow field. This improves the efficiency of particle trajectory reconstruction in complex flow fields.

This invention discloses a method and system for rapid prediction of particle trajectories on the equatorial plane of a Kerr black hole, including steps S1, data construction and screening; step S2, sequence standardization and preprocessing; step S3, trajectory prediction model construction; step S4, training of a hybrid physical constraint loss function; and step S5, rapid inference and trajectory reconstruction. This invention simplifies the complex three-dimensional motion of Kerr spacetime to two-dimensional motion on the equatorial plane, utilizing deep learning to achieve an end-to-end mapping from initial conditions to the complete trajectory. It replaces the time-consuming process of solving geodesic equations with a single forward propagation of the neural network, achieving computational efficiency far exceeding traditional numerical integration methods. This invention ensures the robustness of trajectory geometry through chamfer distance loss, accurately predicting geometric features such as the perihelion precession angle; smoothness loss eliminates common noise jitter in neural networks, ensuring the physical rationality of the trajectory.

The application discloses a self-adaptive air pressure regulation system of a quartz sand non-powered powder separation device, and relates to the technical field of automatic control.The application collects air pressure and airflow disturbance signals, generates high-resolution graphs through Hampel filtering noise reduction, extracts features and identifies key influence areas through a convolutional neural network, solves the problem of unstable air pressure caused by airflow disturbance in mountainous areas, and improves particle separation precision; a natural potential energy distribution matrix is constructed based on building height differences, driving speed field reconstruction and airflow channel optimization, combined with a gradient descent algorithm to adjust process parameters, realizing accurate use of natural potential energy, reducing energy consumption, improving uneven efficiency, simulating airflow distribution and particle trajectory through a fluid dynamics model to analyze and predict sedimentation behavior, classifying trajectories through a support vector machine and generating regulation instructions, forming a closed loop through PID control to stabilize air pressure, avoiding problems such as mixing fine powder with coarse powder and coarse particle residues, reducing the risk of device blockage, and improving product purity stability.

The invention discloses an ultra-compact superconducting cyclotron high-frequency device capable of accelerating two kinds of particles. The device comprises a high-frequency upper D plate, a high-frequency lower D plate and a tail connecting plate between the high-frequency upper D plate and the high-frequency lower D plate. The accelerated two kinds of particles are alpha particles and H2 < + > particles; the tail curves of the high-frequency upper D plate and the high-frequency lower D plate of the high-frequency cavity capable of accelerating the two kinds of particles are arc lines instead of chamfers and straight lines; the tail connecting plate is not in through connection with all tail arcs of the high-frequency upper D plate and the high-frequency lower D plate, but is in a cut-off state at one end, tangent to the tails of the high-frequency upper D plate and the high-frequency lower D plate, of an alpha particle track; the tail curve shapes of the high-frequency upper D plate and the high-frequency lower D plate are improved, the originally designed'chamfer and straight line 'is changed into an optimized arc line, and the tail connecting plate is cut off, so that the physical interference between the alpha particle track and the tail of the high-frequency cavity is successfully avoided, and the smooth acceleration and extraction of the alpha particles are ensured.

The application belongs to the technical field of general control or regulation system, and particularly relates to a building engineering construction quality whole-process digital control method and system, which comprises the following steps: obtaining an environmental wind speed reference sequence, a radiation intensity reference sequence, and an internal temperature reference sequence and a surface temperature reference sequence of concrete of a current control period; determining a surface temperature fluctuation degree; determining an environmental coupling degree, an environmental activity index, and a particle trajectory trust weight; obtaining an optimized particle velocity update expression; determining a global optimal particle, outputting a control instruction to adjust a cooling water flow, and realizing internal temperature control of the concrete. By introducing the particle trajectory trust weight based on multi-dimensional data feature analysis and optimizing the particle velocity update expression, the application overcomes the limitation of the fixed weight distribution strategy of the traditional PSO algorithm in updating the particle velocity, and improves the accuracy of the internal temperature control of the concrete and the durability of the engineering entity.

The application belongs to the technical field of offshore target drift tracking, and specifically discloses a multi-core parallel particle tracking acceleration method for large-range marine drifting targets. First, an offshore target drift prediction model is constructed; a forecast area satellite remote sensing image is acquired to obtain an initial distribution position of the offshore target; model calculation area, particle number and prediction time length model parameters are set; model driving fields such as wind field and flow field are acquired; parallel setting is performed on a multi-core processor, including the number of calculation CPUs and the number of physical cores, the number of running threads, task division, one-time thread pool creation and scheduling strategy setting; particle state is initialized, a time advancement and drift numerical simulation process is performed, large-scale drift particles are tracked and calculated in parallel, and finally a particle trajectory set is predicted. The method realizes high-fidelity and fine drift prediction within a minute-level time limit.

The present application relates to a kind of coastal nuclear power plant water intake suction risk space-time spectrum calculation method, comprising, establish large-scale sea area two-dimensional hydrodynamic mathematical model;Hydrodynamic model verification;Two-dimensional hydrodynamic tidal flow reverse processing;Identify suction influence area;In the influence area, source point is laid out in the area of sustained particle release;In the forward flow field, simulate particle transport trajectory with tide;Determine all the release period and release point of particle into water intake facility;Calculate the probability of water intake suction risk space-time spectrum;According to the monitoring data of outer sea, quickly determine the suction process curve.The present application takes the maximum envelope line of particle trajectory in prediction period as the maximum influence area of suction;Particle source is laid out in the area, simulate particle trajectory of each source point, build the suction risk space-time spectrum of release point-release period-suction period one-to-one according to time interval;For any outer sea potential disaster material group, can check spectrum real-time prediction its influence on water intake, provide basis for coastal nuclear power plant water intake safety protection and operation.

This application discloses a spatial flow field display method and system based on a 3D engine particle system, belonging to the field of spatial flow field display. The method includes: acquiring raw flow field data from a turboshaft engine test stand, preprocessing and standardizing it to construct a database that can be efficiently read by a 3D engine; in the 3D scene construction stage, performing polygon simplification and topology optimization on the physical model in the flow field to ensure that the engine can maintain high-performance operation while maintaining visual effects; and establishing a mapping mechanism of spatial coordinates-particle trajectory-particle dynamic binding, enabling abstract flow field data to accurately drive the motion trajectory of each particle in the particle system, achieving a precise correspondence between data and visual effects. Through frame update scripts, this application allows the particle system to respond in real time to data changes in the database, dynamically adjusting its motion state and vividly displaying the instantaneous characteristics of the flow field, providing a powerful and convenient interactive tool for flow field analysis.