186 results about "Computational simulation" patented technology

The invention discloses a CFD (computational fluid dynamics) boundary processing acceleration method based on GPU (graphics processing unit) parallelism, and belongs to the technical field of fluid mechanics related calculation. The problem that in the prior art, a traditional CFD boundary processing acceleration method is low in calculation efficiency is solved. The method comprises the following steps: generating a computational grid required for simulating a flow field, and reading grid information and boundary condition information of computational simulation; initializing a flow field according to the calculation parameters, copying flow field data and flow field boundary information from a main memory to a video memory, establishing a boundary pointer array in the video memory, and instantiating a boundary pointed by each pointer; according to the boundary pointer array, the flow field data and the flow field boundary information, time step cycle calculation is carried out by utilizing a GPU, and physical quantity updating of a boundary virtual unit corresponding to the thread is realized; and after time step cycle calculation convergence, video memory flow field data are copied to a main memory, and flow field simulation calculation is completed. The method effectively improves the calculation efficiency, and can be applied to CFD boundary processing.

The invention discloses a laboratory intelligent agent construction method and system based on artificial intelligence, and relates to the technical field of intelligent laboratories. In order to solve the problems of scattered laboratory data information, low scientific and technological resource matching efficiency, lack of a unified AI driving platform and the like in the prior art, a core agent is constructed by introducing machine learning or an artificial intelligence architecture, and digital access and resource pooling are carried out on scientific research total factors such as infrastructures, software and hardware, human property and the like. The intelligent agent is based on semantic alignment and inference rules, dynamic intelligent configuration of resources such as field observation, experimental analysis and computational simulation is achieved, and finally a full-life-cycle intelligent management and scientific research environment integrating equipment perception, intelligent control and business application is formed. According to the method, resource islands are effectively broken, the resource utilization efficiency is improved, a novel scientific research normal form of'big data + AI + model 'is promoted, and systematic support is provided for refined and automatic management of laboratories.

Disclosed is a neural network computing device. The neural network computing device includes a neural network accelerator including an analog MAC, a controller controlling the neural network accelerator in one of a first mode and a second mode, and a calibrator that calibrating a gain and a DC offset of the analog MAC. The calibrator includes a memory storing weight data, calibration weight data, and calibration input data, a gain and offset calculator reading the calibration weight data and the calibration input data from the memory, inputting the calibration weight data and the calibration input data to the analog MAC, receiving calibration output data from the analog MAC, and calculating the gain and the DC offset of the analog MAC, and an on-device quantizer reading the weight data, receiving the gain and the DC offset, generating quantized weight data, based on the gain and the DC offset.

The application relates to the technical field of calculation simulation of ship hull propulsion research, in particular to a simulation model convenient for hydrodynamic calculation of a full-rotation double-propeller ship, which comprises a plurality of groups of water pressure sensors arranged on the circular arc outer wall of a detection column and facing openings, a drainage long groove arranged on the circular arc outer wall of the detection column and located at the openings, a water inlet pipe of an external water pump assembly arranged in the detection column, and a lifting port arranged at one end of the water inlet pipe and capable of sliding along the drainage long groove to adjust the height, wherein the beneficial effects are that the water flow direction and flow rate in the pool model are accurately controlled through water pumping and high-pressure water inflow in the symmetrical direction, the data detection range of the test is improved, the simulation equipment provided with the water pressure sensors and the displacement sensors is arranged, so that the data in the test process can be conveniently collected, the position of the simulation small ship can be accurately collected through the coordinates established by the transparent grid plates, and the test accuracy is greatly improved.

The invention discloses a Fe-Mn-C alloy interstitial atom potential function construction method based on a first principle and machine learning, and belongs to the technical field of material science and computational simulation. The construction method comprises the following steps: firstly, constructing a Fe-Mn-C alloy interstitial element atomic structure model, carrying out structure optimization on the interstitial element atomic structure model by utilizing a first principle, then carrying out first principle molecular dynamics (AIMD) multi-temperature sampling on the model after the structure optimization, and dividing a training set and a verification set; and finally, machine learning is conducted, and the Fe-Mn-C alloy gap potential function is output. According to the construction method, unification of high precision and high efficiency of the potential function is achieved, and the obtained Fe-Mn-C alloy gap potential function can be applied to research of a face-centered cubic (FCC) Fe-Mn-C alloy.

The invention belongs to the technical field of geographic information science, and particularly relates to a Markov-FLUS model-based feedback land utilization change simulation method and system, and the method comprises the steps: firstly predicting an initial area target vector based on historical data and a Markov chain, and inputting the initial area target vector into a FLUS model to carry out the first space distribution simulation; by calculating the achievement degree of the simulation result and the area target, the space conflict type which cannot be achieved due to the space constraint is identified, the area target vector is dynamically corrected according to the space conflict type, and the corrected target is fed back to the FLUS model for iterative simulation until the result is converged. According to the method, the technical problem of disjunction of area prediction and spatial layout in a traditional coupling model is effectively solved, and the scientificity and accuracy of land utilization change simulation are remarkably improved.

The invention relates to the technical field of power transmission line verification, and discloses a point cloud-based power transmission line windage yaw double-parabola verification method, system and device and a medium, and the method comprises the steps: obtaining three-dimensional point cloud data of a power transmission line corridor, and extracting key ground feature parameters; according to the input target simulation working condition parameters, applying a wire state equation to iteratively solve the dynamic horizontal tension of the wire under the corresponding working condition, and combining a double-parabola mechanical model to calculate a three-dimensional space curve of the power transmission line under the windage yaw state; inputting a three-dimensional space curve and key ground feature parameters, and calculating a three-dimensional space minimum clearance distance between the power transmission line and a key ground feature in a simulated windage yaw state; and after comparison, a verification result is output. According to the method, the wind deflection and sag forms are accurately reconstructed by applying a double-parabola mechanical model, and dynamic simulation of different working conditions is realized in combination with a wire state equation. By combining high-precision mechanical analysis with an automatic verification process, the stability and safety of power grid operation can be improved.

The invention discloses a modeling method and an analysis method of a geologic body finite element model containing a fault three-dimensional fine structure, and relates to the field of earth science. According to the method, the three-dimensional fault model is properly smoothed, so that the three-dimensional geometrical characteristics of the fault are reserved, and subsequent grid division is facilitated. And meanwhile, during grid division, even if a relatively complex geometric form is adopted, hexahedron units are still adopted, so that more accurate computational simulation is facilitated, and finally, a geologic body finite element model containing a fault three-dimensional fine structure is obtained. According to the invention, flexible adjustment can be carried out according to different geological backgrounds and scientific problems, including but not limited to addition of corresponding material media, friction coefficients, physical equations, fault contact and other parameters, and geologic bodies and faults in a research area can be simulated more accurately and finely. Meanwhile, the geologic body finite element model mesh created by the method can reach million level, and more refined research, simulation and processing work are facilitated.

The invention discloses a method for constructing a two-dimensional layered material machine learning potential function, and belongs to the field of material science and computational simulation, and the method comprises the steps: S1, carrying out the modeling of a two-dimensional layered material through employing a first principle, completing the calculation of the first principle, and taking a result as a data source; s2, extracting structure and force information from the data source, and vectorizing the data to form a data set for training a neural network model; s3, training the processed data set based on a deep learning model DeepMD, and generating a potential function model of machine learning; s4, model detection: calculating an error between a model prediction value and a first principle calculation result; s5, carrying out molecular dynamics simulation; by reasonably designing the modeling process and optimizing the data processing and training steps, the generated potential function model is ensured to have high precision and high efficiency, and the method can be widely applied to the field of material science and molecular dynamics simulation.

The invention discloses an electromagnetic environment-friendly radiation protection assessment method and system, and the method comprises the steps: obtaining electromagnetic field data containing power frequency and high-frequency components through a data collection device, generating a multi-dimensional index data set and a radiation characteristic distribution diagram through the combination of exposure time and a crowd sensitivity index through a computational simulation method, and accurate quantitative analysis of the complex electromagnetic environment is realized. On the basis, a weight analysis method is adopted to fuse effect parameters to calculate a risk quantitative score, when the score exceeds a safety threshold value, radiation limit value data is automatically extracted to generate a visual risk map, and a processing module is linked to output a grading protection instruction. By activating protection configuration in the sensor network, decision unit parameters are dynamically adjusted according to real-time electromagnetic field data, and an optimized protection scheme including a dynamic strategy is formed. According to the invention, the conversion from passive protection to active early warning is realized, and the intelligent level and protection effect of electromagnetic radiation protection are significantly improved.

The invention discloses a virtual fuel vehicle power assembly mapping method and system. The method comprises the steps that the vehicle speed of an electric vehicle and input signals of an accelerator pedal and a brake pedal are received; performing nonlinear mapping on the accelerator pedal input signal to generate a virtual accelerator opening degree, and performing cooperative control in combination with a brake pedal signal; based on the vehicle speed and the virtual accelerator opening degree, a virtual target gear is determined through a multi-dimensional gear shifting diagram and a self-adaptive gear shifting strategy; the method is characterized in that a dynamic slip frequency factor related to the vehicle speed, the virtual accelerator opening degree and the brake pedal opening degree is introduced in the non-gear-shifting state so as to simulate the slip frequency effect of a torque converter; in the gear shifting state, transient smooth transition of the rotating speed is simulated. According to the method, the nonlinear dynamic behavior of the fuel vehicle can be accurately simulated in real time with low calculation overhead, the authenticity and immersion of simulation are remarkably improved, and powerful support is provided for virtual testing, control system development and man-machine interaction application.

The invention belongs to the technical field of vehicle-mounted display, and relates to a vehicle-mounted display screen touch abnormity recovery method and system, and the method comprises the following steps: dividing a virtual sensing area, and building a mapping table; the method comprises the following steps: periodically collecting original capacitance data of a normal area, synchronously obtaining communication quality and environment state messages, and aligning to form a multi-dimensional data stream; identifying an abnormal region, dynamically adjusting a threshold value in combination with an environment state for rechecking, determining a fault type, and generating an abnormal judgment signal; generating a targeted recovery instruction packet according to the fault type; sending to a controller for execution, updating the mapping table and activating a neighborhood interpolation compensation algorithm; monitoring a touch track in real time, calculating a simulation coordinate by using data interpolation of an adjacent normal area when entering a fault area, and integrating the simulation coordinate with a real coordinate to form a continuous touch coordinate flow; according to the invention, the problems of whole screen interruption caused by inaccurate fault positioning, unnecessary reset caused by environment interference misjudgment and influence on system availability due to long overall reset time in the prior art are solved.

This invention discloses a method for directional experimental verification and performance testing guided by computational simulation in materials chemistry, belonging to the field of materials performance testing technology. The method includes: acquiring the structural parameters of semiconductor devices and initial parameters of interface defects; calculating the characteristic time constant of carrier trapping by interface traps; simulating and generating a theoretical capacitance-voltage hysteresis loop; then performing bidirectional voltage scan tests within a sensitive scan rate range; finally, updating the inversion parameters and resimulating, iteratively adjusting until the characteristic deviation between the theoretical loop and the measured data meets the convergence condition, thus outputting an interface state density distribution map. This invention, through computational simulation-guided directional experiments, achieves accurate capture and non-destructive in-situ characterization of the dynamic response characteristics of interface states, effectively establishing the dynamic structure-property relationship between microscopic interface defects and macroscopic device performance, and significantly improving the accuracy and reliability of interface defect parameter inversion.

The application discloses a blood sample image intelligent recognition and classification system based on computer vision, relates to the technical field of pathological image analysis and computer vision, and comprises the following steps: acquiring an original collected image and performing nonlinear concentration mapping to generate a biochemical layered image containing measured concentration data; locking a cell center and dividing an initial jurisdiction through center response calculation to construct an ideal simulation single-cell layer; calculating a difference image of a simulation superimposed image and a measured image, iteratively correcting the simulation layer in a reverse direction by using concentration difference data until an independent single-cell layer containing recovered texture is obtained; and finally generating an overlapping complexity weight map based on the difference image, constructing a multi-dimensional feature data packet and inputting the multi-dimensional feature data packet into a convolutional neural network to output a classification result; the application effectively solves the recognition problem caused by cell overlapping in high-density samples by combining physical model decoupling with deep learning.

The application relates to the technical field of PLC control, in particular to a conveying line digital twin virtual debugging system and method based on a B / S architecture. The system comprises a three-layer B / S architecture composed of a PLC simulation layer, a business logic layer and a three-dimensional visualization layer. The PLC simulation layer is used for running a PLC program to obtain feedback signals of controlled equipment, simulating the control logic of the PLC on the controlled equipment based on the feedback signals, and sending control signals to the business logic layer. The business logic layer is used for obtaining the control signals and performing business logic operation based on the control signals and the feedback signals to calculate the movement of the simulated controlled equipment and obtain real-time position data. The three-dimensional visualization layer is used for displaying the running state of the controlled equipment based on a pre-constructed virtual model of the controlled equipment and the real-time position data to show the running result of the PLC program, and generating feedback signals based on virtual sensors on the virtual model of the controlled equipment and sending the feedback signals to the business logic layer.

The invention discloses a method for predicting a new crystal structure based on an adversarial generative model, which combines a group theory, Wyckoff site analysis, a machine learning coding technology and an energy prediction agent model, and aims at reducing the experiment trial and error cost and realizing efficient structure prediction and screening. According to the method, by calculating, simulating and predicting the crystal structure, dependence on experimental conditions and trial and error times are reduced, and efficient prediction and rapid screening of the crystal structure are achieved by combining the adversarial generative model and the proxy model. A user can specify or not specify conditions such as components, space groups and the total number of atoms in unit cells according to needs, and the crystal structure is generated in a customized mode.

The application discloses a kind of full-diameter core radial permeability test error calculation methods, belong to oil and gas exploration technical field, it is characterized in that, include the following steps: a, preparation core;B, the true value k of permeability when the texture of core and the end surface of core are parallel is calculated / / ; the true value of permeability when the texture of core and the end surface of core are vertical is calculated to simulate the permeability value c that passes through the left and right sides of cuboid;D, the radial permeability test error value ε of core is calculated by formula 5.The application can carry out error analysis to core radial permeability test, effectively estimate the accuracy of core radial permeability test, carry out reliability evaluation to core radial permeability test.

A metal modified graphene structure model is applied to predict hydrogen storage materials, comprising a structure simulation unit, a simulation data unit, a preparation measurement unit, a data processing unit and a parameter feedback unit; the structure simulation unit includes a graphene base structure composed of carbon atoms and a plurality of modified structure models pre-prepared for metal modification of the graphene base, combined into hydrogen storage materials; the simulation data unit calculates the structure of H2 molecules adsorbed on the hydrogen storage materials and calculates the simulation hydrogen storage data; the preparation measurement unit actually prepares the hydrogen storage materials and measures the actual hydrogen storage data; when the actual hydrogen storage rate data is greater than or equal to the first threshold value, the data processing unit calculates the difference percentage of the actual hydrogen storage data and the simulation hydrogen storage data, and outputs the data difference degree; otherwise, an abnormal warning signal is output; when the data difference degree is less than or equal to the second threshold value, the parameter feedback unit outputs that the hydrogen storage data of the preparation measurement unit is qualified, otherwise, an abnormal warning signal is output and feedback is performed, and data optimization is performed.

The invention discloses a quantum circuit optimization method and device and a medium, and the method comprises the steps: firstly determining a quantum logic gate in a to-be-optimized quantum circuit, and then converting the quantum logic gate into a target quantum logic gate which can be executed by an ion trap quantum chip, according to the method, a target quantum circuit which is equivalent to a to-be-optimized quantum circuit and comprises a target quantum logic gate is generated, the target quantum logic gate comprises an MS gate and an RPhi gate, a to-be-optimized common quantum circuit is compiled into the target quantum circuit which can be directly executed by an ion trap quantum chip by utilizing a quantum logic gate conversion and combination rule, and the target quantum logic gate is converted into the target quantum circuit which can be directly executed by the ion trap quantum chip. The number of quantum logic gates in the target quantum circuit is reduced, the depth of the optimized target quantum circuit is smaller, and a basis is provided for calculation simulation of a common quantum circuit on an ion trap quantum chip.

The invention belongs to the field of oil and gas field exploration and development, and discloses a numerical reservoir model optimization and history fitting method and related device.The method comprises the steps that firstly, geological exploration data are utilized, a spatial clustering algorithm is adopted to automatically determine the local updating range of a structural model, and structural layers and stratums are optimized through spatial interpolation; outputting an optimized construction model and uncertainty measurement; based on the model and logging lithofacies attribute data, adaptively identifying a lithofacies updating key area and variation function parameters by applying a machine learning algorithm, and performing lithofacies simulation to output an optimized lithofacies model; combining the porosity, permeability and saturation attribute data, adaptively determining an attribute optimization range and variation function parameters by adopting a probabilistic neural network, and outputting an optimized attribute model through phase control attribute modeling; a three-dimensional oil-water two-phase black oil seepage model is constructed, a global optimization algorithm is adopted to automatically adjust parameters based on a target function, simulation data is calculated until convergence, optimal parameters are output to complete historical fitting, and efficient and reliable intelligent support is provided for complex oil reservoir development.

The invention relates to the field of building construction, and discloses a deep and shallow foundation pit group construction deformation prediction control method, which comprises the following steps: acquiring engineering geological parameters of a construction site and foundation pit parameters of a plurality of foundation pits to be constructed; determining a plurality of calculation simulation working conditions; establishing a three-dimensional numerical model by adopting finite element software; simulating the states of the retaining structures of the first foundation pit, the second foundation pit and the third foundation pit in the construction process under different calculation simulation working conditions in the three-dimensional numerical model; deformation data of the adjacent foundation pit limited width soil strip enclosure structure and soil pressure data of the two sides of the adjacent foundation pit limited width soil strip are tested and fed back, and the construction requirement is adjusted according to the data fed back through detection; the three-dimensional numerical model is used for simulating the deformation condition of each enclosure structure of the deep and shallow foundation pit group under different construction sequences, different foundation pit distances and different loads among foundation pits, so that the actual construction requirements are adjusted, and the deformation trend of the enclosure structures in the actual construction process is controlled.

The present application belongs to the technical field of nuclear fuel simulation design, and aims at the problem that the interface reaction between U3Si2 fuel particles and Al matrix of the existing U3Si2-Al fuel is prone to occur at high temperature, and provides a U3Si2-Cu dispersion type nuclear fuel with interface stability at high temperature and a simulation construction method, a U-Si-Xe-M quaternary potential function is developed by a gradient optimization algorithm of multi-objective simulated annealing combined with a MEAM model, wherein M is any one of Al, Cu, Mg and W, and atomic scale information of irradiation defects and fission gas at the interface in the U3Si2-M fuel is obtained by means of calculation simulation, and finally the U3Si2-Cu dispersion type nuclear fuel is obtained. The U3Si2-Cu dispersion type nuclear fuel provided by the present application has high interface stability at high temperature.

The invention discloses a radar communication simulation method and system for a self-adaptive deception strategy, and the method comprises the steps: receiving a simulation scene selected by a user, simulation equipment and an input frequency set, carrying out the scene configuration according to the input frequency set, and according to the corresponding behavior and signal characteristics of the scene configuration, carrying out the deception strategy simulation. Calculating a signal time sequence needing to be generated by the simulation equipment and generating a global time sequence; performing time sequence conflict detection and adjustment on the global time sequence to obtain a task time sequence after time sequence conflict calibration; and sequentially issuing the time sequence instruction of each simulation device to each simulation device according to the task time sequence for scene signal output. By automatically carrying out conflict detection and adjustment on the signal time sequence of each piece of simulation equipment in the simulation scene selected by the user, the working state of each piece of equipment in the real scene can be really simulated, and the purpose of deception investigation equipment is achieved.

A method for training an operator of a spray drying plant is disclosed, the spray drying plant comprising a plurality of plant elements, the plurality of plant elements comprising a pre-treatment element, a spray drying element, a post-treatment element, a powder recovery element and a programmable logic controller (PLC). The method comprises the steps of: obtaining a transient mode of the spray drying plant, wherein the transient mode comprises a transient sub-mode of the plurality of plant elements; repeatedly calculating simulated sensor data using a processing unit based on the obtained transient mode; displaying a training human-machine interface (tHMI) on a display, the training human-machine interface being configured to communicate with the transient mode of the spray drying plant and display simulated sensor data and control data of the transient mode; and updating the transient mode based on operator input on the tHMI for controlling the transient mode of the spray drying plant.

The invention discloses a self-adaptive pre-stressed plate girder mechanical state forecasting method based on digital twinning, and the method comprises the steps: obtaining state parameters of a current plate girder through a pre-erected multi-source sensor network; noise reduction, abnormal value elimination, data completion and standardization processing are sequentially carried out on the state parameters, the processed state parameters of the current plate girder are sent into a digital twinborn model, and actually measured prestress is obtained through calculation; acquiring a simulated prestress in the digital twin model, and calculating an error between the simulated prestress and the actually measured prestress; updating the digital twin model according to the error; and based on the updated digital twin model, predicting the structural state of the plate girder by using a prediction algorithm. According to the method, the digital twin model of the plate girder is continuously updated according to the actually detected data, the prestress is output in real time through the digital twin model, and the structural state of the plate girder is predicted through a prediction algorithm.

The application belongs to the field of material calculation simulation, and relates to a prediction method for magnetic coupling evolution characteristics of two-dimensional Janus materials based on first principles. The technical problem to be solved is that the existing technology fails to uniformly analyze the magnetic freedom and structural evolution behavior, resulting in interlayer abnormal shrinkage, spontaneous bond collapse and lack of judgment basis for the coupling relationship between magnetism and interlayer structure. The technical scheme comprises the following steps: establishing a crystal structure model taking MA2Z4 material as a mother body; cutting and constructing an asymmetric Janus single layer; constructing a double-layer AA stacking initial model; performing geometric structure optimization and static self-consistent calculation under non-spin polarization and spin polarization conditions respectively; comparing the interlayer spacing, magnetic moment distribution and electronic state characteristics under the two conditions; analyzing the inhibitory effect of interface magnetism on interlayer bonding tendency by combining the electron localization function and the crystal orbital Hamiltonian population; and finally establishing the cooperative evolution relationship among magnetism, interlayer coupling and electronic structure, thereby providing a theoretical basis for identifying stable double-layer van der Waals configuration.

The invention relates to the technical field of tailing pond safety and geotechnical engineering, and discloses a tailing pond dam slope anti-sliding stability analysis method based on a Sweden segmentation method. The method comprises the steps of fusing dam slope form point cloud, a stratum lithology profile and a multi-stage pore water pressure monitoring sequence through a field domain conversion technology, and constructing a unified three-dimensional space-time analysis model. And intelligently generating a candidate slip trend surface based on the high-precision point cloud data, and carrying out strip division. Rock and soil parameters and pore water pressure which change along with time and space are given to each strip block, and a dynamic strip state set is formed. And carrying out loop iterative calculation by utilizing a Sweden slice method principle, simulating stability evolution under different working conditions, and outputting a stability result of each sliding surface. Finally, the dominant slip plane and the most unfavorable working condition are identified, and an accurate basis is provided for reinforcement decision. According to the method, deep fusion of multi-source data and dynamic simulation of a stability state are realized, and the accuracy of an analysis result and engineering applicability are improved.

The invention discloses an anti-interference alternating current and direct current non-contact measurement method, system and device and a medium, and the method comprises the steps: calculating and simulating differential magnetic field data through simulating magnetic field distribution under different cable models and current conditions, and storing the current conditions and characteristics as a magnetic field database; establishing a mapping relation between the simulated diagram structured input and the conductor current through a diagram neural network model; actual magnetic field signals are collected, and magnetic field data are obtained through a plurality of magnetic field sensors arranged outside the tested cable; performing feature extraction on the actual differential magnetic field data; and sending the actual graph structured input into the graph neural network model for reasoning, and processing the actual graph structured input through the graph neural network model. According to the method, common-mode rejection is achieved on a hardware level through a diameter difference array arrangement structure, time domain and frequency domain joint feature extraction is combined, and the multi-dimensional characteristics of alternating current and direct current mixed current are fully represented.

The invention discloses a bioreactor flow field intelligent prediction method and system. The prediction method comprises the following steps: constructing a CFD model of a series of bioreactors; engineering parameters of the series of bioreactors under the simulated working condition are obtained through the CFD model; based on the bioreactor, a corresponding cold model experiment is built, and experiment data of the cold model experiment under the simulated working condition are obtained; calculating the deviation between the engineering parameters and the experimental data under the simulated working condition, and correcting the CFD model; carrying out an orthogonal experiment by utilizing the corrected CFD model so as to at least fit flow field data of each bioreactor under different working conditions and establish a database; calculating and calling flow field data of the specified bioreactor under the specified working condition according to the database, and determining engineering parameters of the specified bioreactor under the specified working condition, so as to predict the working condition of the first-scale bioreactor close to the flow field of the specified bioreactor, and real-time prediction and intelligent amplification of flow field data in different stages of a biological culture process are realized.

The invention discloses a micro-topography dynamic stagnation process simulation method based on basic micro-topography units, which comprises the following steps: for a micro-topography area, taking the basic micro-topography units as basic units for filling pits, and performing iterative calculation by adopting a dynamic pit filling method according to a filling and discharging relation of the basic micro-topography units, so as to obtain a micro-topography dynamic stagnation process; and simulating a depression filling process of a depression system in the micro-topographic region in a rainfall process to obtain a dynamic retention process of the whole micro-topographic region. According to the method, ordered expression of an unordered microtopography structure is achieved, the number of units participating in dynamic depression filling calculation is greatly reduced, the dynamic depression filling calculation efficiency of the microtopography can be remarkably improved, the method can be widely applied to simulation analysis of the dynamic stagnation process of the microtopography area, and the dynamic depression filling calculation efficiency of the microtopography area is improved. And an efficient and extensible new method is provided for quantitatively depicting the dynamic retention effect of the microtopography on the surface runoff.