791results about "Chemical data visualisation" patented technology

The invention relates to the technical field of data integration, and particularly discloses a perfluoro / polyfluoroalkyl substance multi-source exposure data integration risk assessment system, which is characterized in that environmental exposure data of perfluoro / polyfluoroalkyl substances is acquired through a multi-source environmental sensor array, and a PFAS multi-mode exposure feature database is established; carrying out pollution source isotope fingerprint analysis, and obtaining source contribution rate distribution maps of three pollution sources of industrial emission, surface runoff and atmospheric settlement through a nonlinear source analysis algorithm; constructing a three-dimensional geographic information dynamic migration model according to the source contribution rate distribution map, and generating a multi-medium dynamic migration flux matrix; a composite risk assessment model is established based on the multi-medium dynamic migration flux matrix, probability risk assessment is executed in combination with an ecological toxicity threshold database, and a space gridding risk grade map is output; the method not only fills the blank of the prior art in the aspects of multi-medium dynamic modeling and nonlinear source analysis, but also provides powerful technical support for environmental pollution control and ecological risk prevention and control.

The invention discloses a drainage basin nitrogen and phosphorus pollution prediction method based on rainfall runoff migration, and relates to the technical field of water quality pollution prediction, and the method comprises the steps: accurately obtaining land utilization and water body distribution through a remote sensing technology, carrying out the space division of a pollution source through combining a nitrogen and phosphorus load coefficient, and constructing a rainfall runoff model. The runoff volume and time and space distribution under different rainfall events are reflected, and the spatial dynamic change of pollutants is captured through a hydrodynamic model, in combination with a convection diffusion equation and by introducing a conversion model of nitrogen and phosphorus in various forms. By integrating remote sensing data, rainfall runoff simulation, hydrodynamic force and nitrogen and phosphorus form transformation, the space-time migration and transformation process of nitrogen and phosphorus pollution in a drainage basin is described, so that the coupling relation between pollution source distribution and runoff power is revealed, the conveying and diffusion rule of pollutants in a river network is dynamically reflected, and the drainage effect is improved. And refining to transformation evolution of different nitrogen and phosphorus forms, and generating intuitive concentration distribution and thermodynamic diagrams through spatial interpolation.

The invention provides a constructional engineering concrete compressive strength detection method and system.The method comprises the steps that multi-modal information of a to-be-detected concrete member for constructional engineering is collected, and the multi-modal information comprises rebound data, ultrasonic data, resistivity data and temperature data; constructing a hybrid prediction model; and outputting compressive strength data according to the mixed prediction model, and visually displaying the compressive strength data. According to the method and the system for detecting the compressive strength of the constructional engineering concrete, disclosed by the invention, multi-modal information such as ultrasonic, rebound, resistivity and temperature of the to-be-detected concrete member is input into the mixed prediction model for compressive strength prediction, and the model can be used for more accurately processing nonlinear and high-dimensional characteristics in data; a transfer learning mechanism is introduced, so that the model adapts to changes of different regions and materials under limited training data, and the generalization ability and accuracy of prediction are improved. And the compressive strength data is visually displayed, so that the analysis efficiency of engineers is improved.

The invention discloses a mixed surfactant system surface tension prediction method and system based on machine learning. Measuring system surface tension data of the mixed surfactant at different temperatures through experiments; secondly, carrying out theoretical correction and data enhancement on the original data by utilizing a Szyszkowski equation; then constructing a multi-dimensional feature space; a nested K-fold cross validation strategy is adopted; the finally established XGB prediction model is excellent in performance on a test set of an enhanced data set, the determination coefficient R2 reaches 0.9994, and the mean square error MSE is 0.0713. The method is particularly suitable for a binary mixed system containing a nonionic polyether surfactant, and not only can accurately predict the surface tension value, but also can determine key parameters such as critical micelle concentration (CMC) and the like. An efficient and reliable technical means is provided for rapid screening and optimization of a surfactant formula, and the method has wide application prospects in the fields of daily chemicals, petroleum, pharmacy and the like.

The invention provides an energy storage battery state simulation and prediction system and method based on digital twinning, and aims to solve the problems that an existing energy storage system is inaccurate in state modeling, insufficient in sensing granularity, unexplained in prediction, lagged in response and the like. According to the method, an equivalent thermal model, an electrochemical model and an aging mechanism model are adopted for modeling a battery, and a self-adaptive gating parameter fusion mechanism and data characteristics are introduced, so that cross-scale state mapping and characteristic reconstruction from a battery cell to a system level are realized; generating a baseline trajectory by using an electric-thermal-aging coupling relationship, realizing multi-time-domain closed-loop prediction by combining a data-driven residual correction mechanism, and identifying potential faults and risks in advance through a multi-time-domain anomaly judgment system; and constructing a three-dimensional topology model to dynamically display the state parameters, generating a graded alarm signal and providing operation suggestions. The system constructed by the invention has high precision, interpretability and prediction and visualization capabilities, and can significantly improve the intelligent operation and maintenance level of the energy storage battery system.

The embodiment of the invention relates to the technical field of sludge treatment, and discloses an AGI-based sludge deep dehydration conditioning method, which comprises the following steps: acquiring time sequence sensor parameters detected by a plurality of sensors at a dehydration conditioning system; acquiring an image, acquired by image acquisition equipment, of sludge at the corresponding capillary water absorption detection system; extracting an image feature vector from the at least one image according to the convolutional neural network, and encoding a corresponding time sequence sensor parameter by adopting a Transform module to generate a time sequence feature vector; fusing the image feature vector and the time sequence feature vector into an input state representation; the input state representation is input into an AGI multi-mode model for recognition processing, and output state information is generated through a multi-task decoder; and transmitting the optimal control parameters to a corresponding programmable logic controller so as to adjust the operation state of the dehydration conditioning system. By means of the method, real-time sensing, intelligent decision making and dynamic optimization of the sludge deep dehydration conditioning process are achieved.

The invention relates to an ecological environment inspection and detection information management method and system based on artificial intelligence, and the method comprises the following steps: carrying out the inspection and detection of water quality, air and soil samples collected by an ecological environment monitoring station, and obtaining environment detection data; performing environmental element association calculation based on the data to obtain element association data, and generating an environmental element distribution diagram through spatial-temporal distribution mapping; tracking a pollutant migration rule by using the distribution map, extracting pollutant migration characteristic data, and carrying out environmental impact assessment according to the pollutant migration characteristic data to form an environmental impact assessment report; according to the method, the monitoring area is subjected to risk distribution division according to the report, area environment risk distribution data is obtained, a targeted ecological environment management scheme is generated based on the data, and the technical problems that in the prior art, an effective correlation analysis means is lacked, and migration and transformation rules of pollutants among different media are difficult to reveal are solved.

The invention discloses a cooperative supervision method and system for a water area ecological environment, and belongs to the technical field of ecological environment supervision, and the method comprises the steps: carrying out the global monitoring of a target water area, obtaining a monitoring image sequence of the target water area, calculating the pollution confidence, recognizing a pollution region, quantifying the area, and generating a diffusion drive signal, obtaining a category label of the target pollutant; obtaining the motion trail of the target pollutant, reversely deducing the local flow velocity and flow direction of the water surface, identifying an abnormal target in the target water area, and generating an abnormal pollution association table in combination with the pollution area; according to the method, local data of a water area are collected in real time, a water area situation base map is generated, a water quality diffusion model is constructed, a multi-time-dimension pollution diffusion simulation result is generated, and plan deduction and risk assessment are performed, so that a supervision decision is upgraded from passive disposal to active prevention and control, and decision requirements of risk pre-judgment and active prevention and control are fully met.

The invention relates to the technical field of soil pollution analysis, and discloses a soil heavy metal intelligent evaluation method, system and terminal, and the method comprises a multi-source heterogeneous data fusion and preprocessing step, a dynamic spatial interpolation modeling step and an intelligent visualization and decision support step. The system corresponds to the method, and the terminal equipment corresponds to the system. According to the method, comprehensive data support for soil heavy metal pollution is realized through multi-source heterogeneous data fusion and preprocessing; through dynamic spatial interpolation modeling and a dynamic parameter adjustment mechanism, high-precision grid surface layer generation is realized, and the fitting precision of pollution spatial distribution is improved; intelligent pollution grading and multi-factor dynamic calculation of pollution indexes are realized through self-adaptive grading and pollution index calculation, and the accuracy of an analysis result is improved; through intelligent visualization and decision support, a dynamic and visual decision basis is provided for multi-department collaborative governance and risk early warning.

The invention discloses a mixed gas absorption spectrum analysis method and system based on variational mode decomposition, specific laser is injected into an optical resonant cavity unit, and a detector unit continuously monitors the light intensity change and records a light intensity attenuation signal; pre-processing the recorded light intensity attenuation signal; carrying out VMD decomposition on the preprocessed ring-down signal to obtain a plurality of IMF components, respectively introducing CO2 and CO gases with known concentrations into the optical resonance unit, and recording spectral data of each single gas component; calculating the similarity and contribution degree of each IMF component, and setting a weight combination to form a joint score; the gas with the highest joint score is selected, the score is compared with an adaptive threshold value, and when the score is higher than the adaptive threshold value, the IMF component is marked as the characteristic component of the corresponding gas; and finally, gathering and outputting the marked IMF components according to gas types to obtain characteristic signals of the gases, thereby realizing multi-component gas separation in the mixed gas absorption spectrum.

The invention discloses a customized generation method of a non-corrosive ionic liquid lubricant, and aims to solve the problem of negative correlation between corrosion and lubricating performance of ionic liquid in application of a metal friction pair. The ionic liquid has the characteristics of low volatility, high thermal stability and the like, but the electrochemical activity of zwitterions of the ionic liquid easily causes metal surface corrosion, and the corrosion and the lubricating property are in a negative correlation relationship. According to the method, through constructing a corrosion-lubrication multi-modal database, combining with the steps of feature engineering, collaborative prediction model training, non-corrosion formula directional generation, molecular dynamics Monte Carlo coupling verification, multi-objective optimization and the like, the whole-process intelligence from molecular structure and performance prediction to formula optimization is realized; and an ionic liquid formula with good lubricating performance and no corrosion is efficiently screened. According to the method, the research and development efficiency of the ionic liquid lubricant is remarkably improved, the research and development cost is reduced, and engineering application of the ionic liquid lubricant in key fields such as spaceflight, military industry and extreme manufacturing is promoted.

The invention discloses a method for depicting and analyzing a heavy non-aqueous phase pollution site based on microbial structure information, which comprises the following steps of: based on a historical geological survey report and a historical leakage event, defining a pollution analysis area, and constructing a site pollution conceptual model by combining high-density resistivity with a stable isotope tracer method; performing sample collection and detection on the target area to obtain area sample detection information; performing microflora analysis according to the regional sample detection information, and judging a potential pollution retention region of the target region to obtain pollution region analysis information; carrying out multi-source data coupling by combining pollution area analysis information and area sample detection information, and carrying out pollution field three-dimensional description on a target area to obtain an area DNAPLs pollution condition diagram; a degradation function gene interaction network is constructed, restoration potential grading is performed on a target area, and area restoration suggestion is performed, so that the limitation of a traditional investigation method is broken through, and accurate analysis and restoration assistance of pollution distribution are realized.

The invention discloses an administration agent in-vivo release and absorption visualization method based on a CFD-PBM coupling model. The method comprises the following steps: constructing a CFD model of a physiological environment of an injection site; establishing a population balance model (PBM) of the drug particles; the PBM is embedded into a CFD model solver, multi-scale coupling simulation is carried out, and a CFD-PBM coupling model is obtained; the three-dimensional visualization engine dynamically displays drug concentration distribution and particle behaviors; reversely adjusting preparation prescription parameters by using a multi-parameter optimization algorithm; and calibrating model parameters, and generating a key data report. According to the method, the prediction precision and the research and development efficiency can be remarkably improved, and the method is suitable for development of long-acting preparations such as microspheres and implants.

The invention discloses a marine fuel leakage assessment method, device and equipment, a medium and a product. The method comprises the following steps: acquiring leakage scene information related to marine fuel leakage, wherein the leakage scene information at least comprises personnel position information, ship environment information, leakage state information and fuel type information; based on the leakage scene information, determining first distribution data of leakage concentration and leakage related positions by calling a preset simulation model realized based on computational fluid dynamics or calling a historical leakage simulation result in a database, and second distribution data of leakage concentration and leakage time at a position indicated by the personnel position information; and according to the first distribution data and the second distribution data, visually displaying a leakage concentration contour map marked with the personnel position information, a leakage concentration time change map and personnel escape suggestion information. According to the scheme, the actual threat degree of leakage to personnel on the ship can be reflected, and suggestions for dealing with leakage are provided.

The invention provides an impact deformation feature extraction method based on high-speed camera shooting and image processing, and the method comprises the steps: collecting the transient deformation data of the edge package of a remote controller housing under impact through high-speed camera shooting, recording the change speed of a strain rate, obtaining the material characteristics, the size of a package structure, and the geometric discontinuous features of an opening and closing part, generating continuous frame sequence images; performing strain field data quantification processing on the third visualization result, extracting strain field characteristic data, and judging influence weights of stress wave reflection on strain fields of different functional areas of the shell in combination with a falling height and an impact angle of the remote controller; and improving edge packaging design parameters according to the deformation buffer effect and discontinuous quantitative indexes at the opening and closing positions, verifying the improvement amplitude of the deformation buffer effect, and obtaining strain field distribution data of the optimized shell.

The invention discloses a plain small watershed nitrogen and phosphorus pollutant collaborative source analysis method, which belongs to the technical field of environmental pollution traceability, and comprises the following steps: 1, collecting multi-source basic data in a target plain small watershed, carrying out unified coordinate system, format and precision preprocessing, and constructing a watershed basic database; and 2, constructing a response relation model of various pollution sources and potential pollution loads on a GIS platform based on a drainage basin basic database, qualitatively identifying main pollution sources through spatial visualization analysis, and delineating key risk areas. According to the method, macroscopic spatial analysis, microchemical tracing and mathematical model calculation are organically fused, high-precision spatial data, hydrochemical and isotope analysis, multi-model quantitative analysis and uncertainty quantification are integrated, and high-precision and high-reliability cooperative source analysis of nitrogen and phosphorus pollutants is achieved.

The invention discloses a combustion chamber nonlinear stability prediction method based on multi-input thermo-acoustic disturbance modeling. The method is used for evaluating thermo-acoustic stability of combustion chambers of aero-engines, gas turbines and the like. According to the method, geometric, operation and analysis parameters are input, and cooling flow distribution is calculated; solving an effective equivalence ratio, a heat release rate and a temperature field, and calculating an acoustic modal frequency; constructing an equivalence ratio and inlet flow double-disturbance MISO transfer function, and generating an FTF curve; and judging oscillation through a limit cycle detection algorithm, calling a Tanh / PowerLaw model to calculate a saturated heat release rate, and finally visually outputting a result. Multi-factor coupling accurate modeling is achieved, intervention can be conducted in the initial stage of design, calculation only needs several minutes, the prediction precision and efficiency are improved, the research and development cost is reduced, and the safety of the combustion chamber is guaranteed.

The invention discloses a dust explosion dynamic blocking method based on multi-modal data fusion. The method comprises the following steps: S1, constructing five core accident trees; s2, collecting multi-source data of dust explosion in real time and preprocessing the multi-source data, and extracting a multi-dimensional feature vector containing temporal and spatial variation features; s3, converting the multi-dimensional feature vector into a real-time state vector of five core accident trees through an event activation rule, and completing multi-source data fusion; s4, according to the real-time state vector, calculating a top event probability of each accident tree by using a Monte Carlo simulation method, and then obtaining an accident tree dynamic coupling risk value through multi-tree coupling analysis; s5, according to the dynamic coupling risk value, using a spatial interpolation method and voxelization processing to obtain a normalized risk value, and generating a dynamic risk thermodynamic diagram; and S6, according to the risk value of each area in the dynamic risk thermodynamic diagram, determining the risk level of dust explosion, then carrying out multi-level interlocking control, and triggering a corresponding blocking strategy to realize dynamic blocking.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for predicting toxicity of a molecule. In one aspect, a method comprises: obtaining data identifying an input molecule; generating data defining a toxicity analysis tree for the input molecule; and processing the toxicity analysis tree to generate a respective toxicity score for each of a plurality of molecule fragments in the input molecule that characterizes an impact of the molecule fragment on a toxicity of the input molecule.

The invention relates to the technical field of microbial fermentation, and discloses a metabolite fingerprint spectrum construction method of a probiotic fermentation type Chinese herbal medicine preparation. The method is realized by sequentially executing a metabolite data acquisition process, a chromatographic data preprocessing process, a metabolite fingerprint spectrum modeling process, a spectrum construction optimization process and a metabolite fingerprint spectrum generation process. In the metabolite data acquisition process, original metabolite data of the probiotic fermented Chinese herbal medicine preparation is acquired; in the chromatographic data preprocessing process, original metabolite data is subjected to signal processing and feature extraction, and preprocessed chromatographic data is obtained; in the metabolite fingerprint modeling process, a preliminary fingerprint is constructed based on the preprocessed chromatographic data; in the atlas construction optimization process, parameter optimization and accuracy improvement are carried out on the initial fingerprint atlas, and the optimized fingerprint atlas is obtained; in the metabolite fingerprint spectrum generation process, the optimized fingerprint spectrum is integrated, and a final metabolite fingerprint spectrum is generated.

The invention provides a radiation dose evaluation method and system based on radiation environment monitoring data, and relates to the technical field of radiation environment monitoring. The method comprises the following steps: recording the release source intensity of each nuclide at a release point, drawing an equally-spaced concentric arc grid, calculating the release height by combining the ground and the release point air pressure, air density and gravitational acceleration, and assigning nuclide hazard factors to the outer edge of the grid; according to the distance between the release point and the outer edge of the grid, diffusion parameters are calculated by using an empirical formula, a Gaussian atmospheric diffusion model is constructed in combination with the release height and hazard factors, and nuclide air activity concentration is output; comparing the total effective dose with a preset threshold value to calibrate a diffusion range, quantifying the radiation dose per unit area, and dividing atmospheric stability coefficient grades; constructing three types of correction factors of release height, material state and weather condition, establishing a comprehensive dose evaluation formula by combining the unit area radiation dose and the correction factors, comparing a preset threshold value, judging a risk level, and performing periodic updating.

The invention discloses a multivariable cross-correlation spatial-temporal feature fusion dissolved oxygen content prediction method and system. The method comprises the following steps: acquiring a water quality sample data set; aiming at the water quality sample data set, screening an influence factor sequence of which the correlation with dissolved oxygen is greater than a preset value by adopting a maximum information coefficient, and screening a dissolved oxygen sequence; standardizing the screened influence factor sequence and the dissolved oxygen sequence to obtain standardized data; the standardized data are adopted to train a dissolved oxygen content prediction model, a trained dissolved oxygen content prediction model is obtained, and the dissolved oxygen content prediction model comprises a spatial feature extraction network, a local feature extraction network, a multi-channel attention network and an encoder-decoder long-short-term memory network combined with an attention mechanism; inputting to-be-detected water quality data into the trained dissolved oxygen content prediction model for prediction, and outputting a dissolved oxygen content prediction result at the next moment. The method can effectively improve the prediction precision of the dissolved oxygen content.

A method performed by at least one processor, includes receiving a query comprising at least one of a product, a reactant, a reagent, and a reaction condition; generating a query embedding vector corresponding to the query by inputting the query into a neural network model; extracting a candidate embedding vector from among a plurality of embedding vectors based on a similarity between the query embedding vector and the plurality of embedding vectors corresponding to reaction records stored in a database; and outputting a synthesis recipe corresponding to the query by retrieving a candidate reaction record corresponding to the candidate embedding vector in the database.

The invention belongs to the technical field of biology, and discloses a non-natural pathway generation method and system based on a continuous biological template, and the method comprises the following steps: obtaining an enzymatic reaction data set, and preprocessing the enzymatic reaction data set; constructing a directed reaction diagram on the basis of the preprocessed enzymatic reaction data set, performing similar compound search on a target compound by utilizing the directed reaction diagram, and obtaining a continuous group conversion template of the similar compound in the natural enzymatic pathway by taking the searched similar compound as a starting point and combining a depth-first search mode; the continuous group conversion template is applied to a target compound in a molecular linear input specification form, and an inverse synthesis process of the target compound is simulated to generate a non-natural synthesis pathway based on the continuous group conversion template. The method not only enhances the biological feasibility and construction success rate of the approach, but also has universality, expandability and engineering potential, and provides a generalizable normal form for the field of synthetic biology.

The invention discloses a process parameter regulation and control method and system for the real-time fermentation state of an agricultural microbial preparation, and the method comprises the steps: S1, building a monitoring and data integration platform, carrying out the coding management of a fermentation container, collecting multi-dimensional data, carrying out the standardization processing, and building a historical database; s2, developing a visual display system, presenting fermentation room layout and color block superposition duration information in a graphical interface, and early warning deviation; s3, constructing an evaluation and prediction model, evaluating the state through a deep neural network and a time sequence algorithm, and predicting the progress; s4, developing an adjustment strategy generation engine, automatically analyzing an abnormal reason and generating a multi-parameter collaborative optimization suggestion; and S5, evaluating the regulation and control effect and continuously optimizing. The system comprises a monitoring and data integration module, a visual display module, an evaluation and prediction module, an adjustment strategy generation module and an effect evaluation optimization module. Intelligent upgrading of the whole production process is achieved, the response speed and decision accuracy are improved, the fermentation regulation lag loss is reduced, and high-quality production is guaranteed.

The invention relates to the technical field of radiation environment monitoring, and discloses a dose calculation method and system based on radiation environment monitoring data. The method comprises the following steps: acquiring radiation source data, calculating initial radiation field distribution based on the data, obtaining an initial dose deposition value of each space point in a monitoring area, analyzing interaction among particles, and determining an energy redistribution coefficient of each space point; adjusting the initial dose deposition value point by point by using the coefficient to obtain corrected three-dimensional dose concentration field data, calculating a gradient vector between spatial points, and generating an optimized gradient distribution diagram; extracting a boundary point set with gradient change exceeding a threshold value, constructing a contour surface grid to form a three-dimensional contour surface structure, obtaining a time sequence radiation source data iteration updating coefficient, and obtaining a concentration field time sequence evolution sequence; the high-concentration area is identified and marked based on the sequence, the high-concentration area and the three-dimensional contour surface structure are fused, a visual distribution model reflecting the dose concentration is generated, and the accuracy of radiation dose calculation is improved.

The invention provides a sparse knowledge graph entity alignment method and system. The method comprises the following steps: acquiring structure data of chemical molecules, and identifying a minimum ring structure based on topological connection and bond energy distribution; clustering molecules with the same ring structure and the bond energy deviation smaller than a threshold value into a molecular group, extracting a shared minimum ring structure as a substructure node, creating a molecular node, and constructing a bidirectional correlation map of the molecules and the substructure node; extracting absorption peak data of the compound sample by utilizing spectral imaging, and generating an energy level spectrum; searching a substructure node combination corresponding to the homonymous molecule based on a map, and obtaining an embedded vector; and segmenting the energy level atlas into energy fragments according to a substructure path, extracting a distribution vector, performing multi-scale fusion on the distribution vector, a path feature and an embedded vector, and generating a composite feature vector to identify an equivalent entity and establish aligned connection. According to the method, high-precision alignment of the functional equivalent entities in the chemical sparse knowledge graph is realized.

The invention discloses a lithium iron phosphate battery thermal runaway gas production and fire explosion risk assessment method, which comprises the following steps: acquiring a battery runaway full-period gas production characteristic by utilizing a thermal runaway gas production experimental device; acquiring a gas production rule according to the full-period gas production characteristic; analyzing a fire explosion risk according to the gas production rule to obtain an analysis result; and performing visualization processing on the analysis result by using a radar map to obtain a research result. Through staged gas production mechanism analysis, multi-parameter coupling evaluation and risk visualization technologies, the purposes of quantifying the thermal runaway fire explosion risk and optimizing the safety prevention and control strategy of the energy storage system are achieved.

The invention discloses a curvature-containing random surface pipeline internal corrosion modeling method and application. The method comprises the steps that the geometric dimension of a pipeline is determined; generating a parameterized curved surface, and establishing a curvature-containing random surface model by setting an N value, a beta value, a random function item and a parameterized curved surface node; and the surface is attached to the inner wall of the pipeline, the generated random surface is attached to the inner wall of the pipeline through operation, pipeline corrosion cutting is conducted, and corrosion parameters are obtained. By introducing the random surface model with curvature and adopting the combination of spatial frequency resolution, spectral index and random function, the corrosion morphology of the inner surface of the pipeline is accurately simulated, the macroscopic pipeline curvature and the microscopic surface fluctuation can be reflected, the model parameters can be flexibly adjusted, the requirements in different corrosion environments can be met, and the method is suitable for large-scale popularization and application. Scientific support can be provided for corrosion evaluation, design optimization and maintenance decision making of pipelines of different shapes and material types, and the method is suitable for pipeline corrosion prediction and analysis in the industries of petroleum, natural gas, chemical engineering and the like.

The invention relates to the field of atmospheric pollution diffusion simulation, and particularly discloses a multi-scale coupled atmospheric pollution diffusion simulation system, which comprises a data source module used for collecting and integrating various data sources including meteorological data, topographic data, pollution source data and atmospheric pollutant concentration data, and providing basic information for simulation; the multi-scale modeling module further comprises a micro-scale model for simulating a detailed diffusion process of pollutants in a local area by calculating a fluid dynamics equation based on a fluid dynamics principle; by integrating various data sources such as meteorological data, topographic data, pollution source data and atmospheric pollutant concentration data, the system can provide more comprehensive and accurate basic information, so that the simulation precision is improved; the combination of microscopic, mesoscopic and macroscopic scale models can respectively capture pollutant diffusion characteristics under different scales, so that the simulation result is more detailed and real.