20 results about "Diffusion field" patented technology

The invention relates to the technical field of civil engineering and computational mechanics, in particular to a load and environmental corrosion coupled reinforced concrete structure analysis method. The method comprises the following steps: carrying out structural finite element modeling; carrying out mechanical field solving; the diffusion characteristics of the crack-driven corrosive medium are updated; solving a corrosive medium diffusion field; the material performance is corrected; carrying out double-time-domain self-adaptive solution; by means of the mode, the coupling effect of complex loads and multiple environmental factors in the reinforced concrete structure can be comprehensively and accurately simulated within the engineering acceptable calculation cost, and reliable prediction of the full life cycle performance is achieved.

The invention belongs to the technical field of intelligent grouting simulation, and particularly discloses an intelligent grouting simulation method and system based on a large model.The method comprises the steps that grouting pressure and grouting flow data monitored on a grouting site are obtained, and grouting pressure, flow and grout diffusion form data are obtained through a grouting experiment; obtaining multiphase flow field data through numerical simulation; training a teacher model by utilizing the preprocessed numerical simulation data, grouting experiment data and part of field monitoring data; in the computational domain, for a set prediction working condition, a differential knowledge distillation strategy is adopted, non-field data and field data are processed respectively, and generalization knowledge of the teacher model is migrated to the student model; and acquiring parameters under a to-be-measured working condition, and inputting the parameters into the trained student model to obtain prediction results of the slurry diffusion field, the pressure field and the velocity field. According to the method, the requirement of quickly adapting to new working conditions is met, and the efficiency requirement of real-time decision making in grouting engineering is met.

A city traffic ubiquitous perception method of a federal auxiliary large model is provided in the application, and belongs to the technical field of data processing, and specifically comprises the following steps: step 1, constructing a space-time diffusion field based on multi-source heterogeneous traffic data of a target city, and dynamically dividing traffic perception subtasks to obtain a subtask set; step 2, performing situational training according to each traffic perception subtask in the subtask set based on federated learning to obtain a traffic perception submodel corresponding to each traffic perception subtask; and step 3, layering and aggregating and splicing all traffic perception submodels to obtain a layered perception large model, and realizing multi-task parallel perception and dynamic management of the target city traffic. Through the scheme of the present application, the generalization ability and accuracy are improved.

The present application relates to a kind of low odor multilayer composite adhesive tape VOC release prediction method, comprising the following steps: S1: the original data of multilayer composite adhesive tape is obtained and preprocessed, and multimodal input data set is obtained;S2: atomic-bond diagram representation is constructed, and input graph neural network is carried out feature extraction, obtains molecular level characterization vector, molecular level feature is fused with material macroscopic attribute, and unified material characteristic representation vector X1 is obtained;S3: based on material characteristic representation vector and environmental parameter as input, establish the neural network model satisfying diffusion equation constraint, obtain VOC diffusion field data X2 for preliminary prediction;S4: the diffusion field data X2 obtained is converted into time series input, and bidirectional recurrent neural network model is constructed to carry out time series feature extraction, and the feature vector X3 containing time dependence is obtained;S5 based on integrated prediction model, output target prediction value.The present application realizes the high-precision, generalizable prediction of the VOC release behavior of multilayer composite adhesive tape.

The invention provides an ecological environment monitoring system and method, and the method comprises the steps: building a three-dimensional digital twinborn model of a designated city in a target region, and enabling the three-dimensional digital twinborn model to comprise thermal environment dynamic data of different environment nodes; determining spatial structure characteristics of different environment nodes, and constructing a spatial communication relationship through the spatial structure characteristics; determining diffusion intensity indexes of each environment node in different thermal diffusion ranges, and further determining the heat island effect intensity of each environment node by combining all the diffusion intensity indexes with the spatial communication relationship; based on the heat island effect intensity, evaluating the influence of the heat island effect intensity on a pollution diffusion field, and obtaining the heat influence pollution diffusion risk of each environment node in different heat diffusion ranges; and generating a multi-scale thermal pollution report of the target area through all the thermal influence pollution diffusion risks. By adopting the scheme of the invention, multi-scale monitoring can be carried out on urban thermal pollution based on a space-time cooperation mechanism of digital twinning.

This invention relates to the field of water quality monitoring technology, specifically to an AI-driven intelligent detection method for water pollution events. The method includes: acquiring pipeline geometric parameters, numerical water quality indicators, and visual images of the water body using intelligent sensors, and extracting multi-dimensional water quality monitoring indicators to generate a water pollution feature tensor; generating a physical constraint deviation term in the loss function using the hydrodynamic convection-diffusion equation, and performing drift compensation on the measured values ​​of the intelligent sensors based on this physical constraint deviation term to construct a water quality evolution prediction model; inputting the water pollution feature tensor into the water quality evolution prediction model to output a three-dimensional dynamic diffusion field of water pollutants; and performing source tracing using a spatiotemporal field inversion operator to calculate the coordinate probability distribution of potential pollution sources and generate early warning commands. This invention improves the robustness and source tracing confidence of complex pipeline monitoring systems through physical consistency constraints and drift compensation.

The invention discloses a swarm robot deployment method and device in a dynamic diffusion field, a server and a medium, and belongs to the technical field of robot deployment. Comprising the following steps: dividing a dynamic diffusion field into sub-regions, and arranging sensing robots in the sub-regions; constructing a parabolic pollution diffusion field model, and constructing a global field density observer; constructing a projection operator of the diffusion coefficient, and constructing an adaptive updating law of the diffusion coefficient; obtaining an estimated value of a diffusion coefficient, and obtaining an estimated value of global field density; dividing the dynamic diffusion field into a plurality of sub-regions to obtain a Voronoi cell cavity; calculating an estimated centroid; constructing a sliding mode variable and an auxiliary intermediate variable, and constructing a distributed guidance law; and driving each execution robot to move towards the target deployment position to realize deployment. By constructing a global field density observer and a speed-free distributed guidance law, deployment of swarm robots in a dynamic diffusion field under the conditions that a diffusion coefficient is unknown, the speed is unmeasurable and resources are limited is realized.

The invention provides a pollution diffusion prediction method and device based on gamma radioactivity and a wind field, and relates to the technical field of pollutant monitoring, and the method comprises the steps: carrying out the feature peak extraction, nuclide recognition and concentration calculation of a gamma radioactivity energy spectrum data set, and obtaining a nuclide concentration set; constructing a three-dimensional wind field diffusion field through the topographic data and the wind field data set; performing coupling calculation and correlation matching on the nuclide concentration set and the three-dimensional wind field diffusion field through a Gaussian diffusion model, and constructing a correlation matrix of the nuclide concentration and the wind field; obtaining a nuclide half-life period, a gamma-ray emissivity and a terrain, and performing weighted fusion on elements in the incidence matrix through the nuclide half-life period and the gamma-ray emissivity to obtain a fusion coefficient; correcting the fusion coefficient through the terrain to obtain a diffusion trend coefficient set; and constructing a radioactive pollution prediction model, and according to the diffusion trend coefficient set, performing diffusion prediction in a future time period through the radioactive pollution prediction model to obtain a pollution diffusion prediction result.

The invention discloses a vehicle-mounted loudspeaker capable of adjusting a pointing angle and a control method thereof, and relates to the technical field of automotive electronics and electroacoustics, and the vehicle-mounted loudspeaker comprises an in-vehicle microphone array, a main control unit, an electric lifting and rotating loudspeaking unit, an auxiliary loudspeaking unit and a self-adaptive digital signal processing power amplifier. The main control unit collects a voice signal, identifies an instruction intention, and calculates the head center coordinate of a sound production passenger; and planning a physical path according to the instruction and the coordinates, and generating an angle control instruction. Executing acoustic parameter coupling calculation: calculating a delay amount in a high-fidelity mode; a diffusion field equalization parameter is configured in a surrounding mode; and calculating the gain and the phase delay of the auxiliary loudspeaker in the privacy mode. And the main control unit synchronously drives the loudspeaker to perform mechanical action and DSP signal processing. According to the method, deterministic mapping of the mechanical degree of freedom and the acoustic parameters is established, dynamic reconstruction of the acoustic path in the vehicle is achieved, the problem of acoustic image positioning drift is effectively solved, and auditory experience is improved.

The application discloses a kind of dynamic diffusion field under group robot deployment method, device, server and medium, belong to robot deployment technical field.It includes: dynamic diffusion field is divided into sub-region, sensor robot is arranged in sub-region;Parabolic pollution diffusion field model is constructed, global field density observer is constructed;The projection operator of diffusion coefficient is constructed, the adaptive update law of diffusion coefficient is constructed;The estimated value of diffusion coefficient is obtained, the estimated value of global field density is obtained;Dynamic diffusion field is divided into several sub-regions, and Voronoi cell is obtained;Estimated centroid is calculated;Sliding mode variable and auxiliary intermediate variable are constructed, and distributed guidance law is constructed;Drive each execution robot to move to the target deployment position, to realize deployment.By constructing global field density observer and speedless distributed guidance law, the deployment of group robot in dynamic diffusion field is realized under the condition that diffusion coefficient is unknown, speed is not measurable and resource is limited.

The invention discloses a water body micro-plastic magnetic trapping system and method for sewage treatment, and relates to the technical field of sewage treatment.The method comprises the following steps that a density gradient field, a shear-diffusion field and a floating tendency probability field of a water body are obtained; performing interactive mapping on the density gradient field, the shear-diffusion field and the floating tendency probability field to generate an adding amount matrix; and performing short-term prediction on the density gradient field, the shear-diffusion field and the floating tendency probability field in adjacent time windows by taking the dosage matrix as a response variable. According to the method, the time window is divided, the data sequence is constructed, the hybrid predictor is combined to capture the time sequence relevance, and meanwhile, a dynamic fusion mechanism of the vulnerability coefficient and the feeding risk coefficient is introduced, so that the problem that the feeding opportunity is not matched with the micro-plastic concentration peak value due to neglecting of the dynamic change of the water body in the prior art is solved.

The application discloses a kind of escape path planning methods based on flow field global modal characteristics, comprising: the establishment of computational model is carried out to leakage scene, grid division, boundary condition setting, calculation method is determined, non-constant value calculation.The eigenvalue orthogonal decomposition is carried out to the characteristic section of chlorine diffusion field, and the mode is sorted according to the energy proportion, and the first-order mode with the maximum energy proportion is determined as the dominant mode.The escape path node grid file is established, and the dominant mode amplitude is projected onto the grid node.According to the maximum value of mode amplitude and corresponding time coefficient, the risk coefficient partition is determined, and the equivalent path length is calculated using the risk coefficient.According to the equivalent path length, the escape path is planned based on Dijkstra algorithm.The escape path obtained by the application is more universal in the whole leakage process.

The invention discloses a snow crystal morphology prediction method based on structure-dependent dynamics. The method comprises the following steps: step 1, acquiring micro-physical environment parameters of snow crystal growth; step 2, performing simulation initialization of snow crystal growth based on environmental parameters, specifically, configuring a data acquisition and edge calculation module for receiving and processing an original data stream from a sensor in real time, performing data synchronization and screening, and simulating a snow crystal growth initial process; 3, establishing a core attachment dynamics basic model; step 4, constructing a structure dependence correction module; step 5, constructing a growth iteration engine coupled with the diffusion field and dynamics; step 6, coupling in the step 4 and the step 5 automatically triggers and simulates edge sharpening instability; and step 7, form output and database generation. The method is high in prediction precision and physical fidelity, and breaks through the limitation of an empirical map.

The application discloses a water body micro-plastic magnetic trapping system and method for sewage treatment, and relates to the technical field of sewage treatment, and comprises the following steps: obtaining a density gradient field, a shear-diffusion field and a floating tendency probability field of a water body; performing interactive mapping on the density gradient field, the shear-diffusion field and the floating tendency probability field to generate a dosage matrix; and performing short-term prediction on the density gradient field, the shear-diffusion field and the floating tendency probability field in adjacent time windows with the dosage matrix as a response variable. The application solves the problem that the existing technology fails to match the dosage time and the peak value of the micro-plastic concentration due to the neglect of the dynamic changes of the water body by dividing the time window, constructing a data sequence, combining a hybrid predictor to capture the time sequence correlation, and introducing a dynamic fusion mechanism of the vulnerability coefficient and the dosage risk coefficient.

The application belongs to the technical field of intelligent grouting simulation, and specifically discloses a grouting intelligent simulation method and system based on a large model, which comprises the following steps: obtaining grouting pressure and grouting flow data monitored on site, obtaining grouting pressure, flow, and grout diffusion form data through grouting experiments, and obtaining multiphase flow field data through numerical simulation; training a teacher model by using preprocessed numerical simulation data, grouting experiment data, and part of the on-site monitoring data; in the calculation domain, for a set of predicted working conditions, adopting a differentiated knowledge distillation strategy, processing non-field data and field data respectively, and migrating the generalization knowledge of the teacher model to a student model; obtaining parameter input under a to-be-tested working condition and inputting the parameter into the trained student model to obtain the prediction results of the grout diffusion field, the pressure field, and the velocity field. The application realizes the requirement of quickly adapting to new working conditions and meets the efficiency requirement of real-time decision-making in grouting engineering.

The invention provides an oil and gas ground information physical system DoS attack intrusion detection method and system based on cross-domain diffusion field self-adaption, and belongs to the field of oil and gas ground information network security protection. The problems that an oil and gas ground information physical system is prone to being affected by DoS attacks under variable working conditions and cross-scene conditions, and an existing detection method is insufficient in generalization and robustness when domain migration is processed are solved. According to the method, the diffusion model trained on the target domain data is utilized, the source domain data is gradually translated into the target domain data through the reverse denoising process, and the pseudo target domain data is generated; a discriminator-guided gradient regularization mechanism is designed, and a back diffusion trajectory is constrained, so that the authenticity and stability of pseudo target data are improved; a semantic consistency loss function based on a support sample is constructed, semantic information of a source domain is gradually reserved, and the recognition precision of a detector on a pseudo target domain Dos attack is enhanced.

The application provides a cross-domain multi-modal information source perception distribution method and system, and belongs to the technical field of multi-source information management; firstly, the method quantitatively calculates the information demand similarity between different user groups; secondly, the score weight of the similar group is migrated to the target group based on the similarity to generate high-quality initial weight; then, the user group is innovatively modeled as a time-varying probability distribution in a feature space, and an evolutionary dynamics equation fused with the influence of information diffusion field is used to model and predict the dynamic evolution process thereof; finally, a model predictive control framework is adopted, and based on the prediction of the future group state, the score weight is prospectively optimized and adjusted; the application realizes intelligent migration of scoring knowledge among groups, dynamic and accurate prediction of user demand, and rapid response to information environment mutation, and significantly improves the adaptability, accuracy and user experience of the information distribution system.

The invention discloses an escape path planning method based on global modal characteristics of a flow field. The escape path planning method comprises the steps of calculation model establishment, grid division, boundary condition setting, calculation method determination and unsteady numerical calculation for a leakage scene. And carrying out eigenorthogonal decomposition on the chlorine diffusion field of the characteristic cross section, sorting modes according to the energy ratio, and determining the first-order mode with the maximum energy ratio as a dominant mode. And establishing an escape path node grid file, and projecting the dominant modal amplitude to grid nodes. And determining a danger coefficient partition according to the modal amplitude and the maximum value of the corresponding time coefficient, and calculating the equivalent path length by using the danger coefficient. And planning an escape path based on a Dijkstra algorithm according to the equivalent path length. The escape path obtained by the method is more universal in the whole leakage process.

The application provides a semiconductor chip defect detection positioning method and system, relates to the technical field of semiconductor chip detection, and comprises the following steps: acquiring an original image and electrical test data; forming a defect candidate area based on local density analysis; performing variational mode decomposition on the electrical data and marking abnormal points of electrical characteristics; mapping image features to an electrical characteristic space and calculating mutual information values to determine defect points; and calculating diffusion field distribution and paths and determining defect severity. The application realizes accurate positioning and severity evaluation of chip defects, and improves detection efficiency and accuracy.

The application relates to the technical field of digital twinning, and discloses a digital twinning simulation modeling method for interface phenomena of bimetallic composite plates in additive manufacturing. The method constructs an interface multidimensional feature database to store multiscale data and sets a label index system; a cross-scale multi-physical field coupling basic simulation model is established to synchronously solve a macroscopic molten pool thermal flow field, a mesoscopic element diffusion field and a microscopic grain growth field; in response to real-time collection data in additive manufacturing, structured retrieval is performed in the database, interface constitutive parameters and evolution boundary conditions are input into the model, a heterogeneous graph is constructed from simulation output data and measured data, key feature nodes are located by using an attention mechanism, and model correction parameters are calculated; the method eliminates the static deviation between the simulation model and the physical entity, realizes dynamic synchronous mapping of the interface evolution process and efficient reuse of feature data.