19 results about "Chemical models" patented technology

The utility model provides a model press-fitting machine convenient to adjust pressure, which belongs to the technical field of press-fitting machines and comprises a press-fitting table, support rods are fixedly connected to four corners of the upper end of the press-fitting table, and a top plate is fixedly connected to the upper ends of the plurality of support rods; the hydraulic cylinder is fixedly connected to the lower end of the top plate; the first pressing plate is fixedly connected to the extension end of the hydraulic cylinder; the second pressing plate is arranged on the lower side of the first pressing plate, and the second pressing plate is slidably connected into the first pressing plate and the hydraulic cylinder; by using the device, under the action of the elastic force of the spring, the model is prevented from being damaged due to overlarge pressure of the hydraulic cylinder during press fitting, and the machining yield of the chemical model is improved.

The present application relates to the technical field of testing or analyzing materials by means of determining chemical or physical properties of materials, in particular to an in-situ characterization method and system for shale reservoir micro-nanopore gas adsorption behavior, the method comprising using non-destructive shale samples, introducing gas in a high-pressure high-temperature reaction kettle simulating formation environment, synchronously collecting Raman spectrum and small-angle / ultra-small-angle X-ray scattering data, and realizing in-situ characterization through multi-scale data fusion analysis.The present application realizes in-situ, non-destructive, high-resolution and multi-component dynamic characterization of shale micro-nanopore gas adsorption behavior under real formation conditions, improves the accuracy of reservoir evaluation, and constructs a more accurate physical and chemical model.

The invention belongs to the technical field of coke two-stage chemical chilling, and discloses a coke two-stage chemical chilling optimization method based on CFD numerical simulation, and the method comprises the following specific steps: 1, building a geometric model: building a three-dimensional geometric model by using SolidWorks according to the actual size of a two-stage dry pulverized coal pressurized gasification furnace, comprise the diameter, length and inclination angle of the downcomer; and the number, diameter and angle of the nozzles. By establishing the numerical simulation physical model and the numerical simulation chemical model and performing transient simulation through CDF software, the flow field, the temperature field and the chemical reaction distribution in the chilling chamber can be accurate, a scientific basis is provided for structure optimization, and meanwhile, according to a set optimization target, the optimization accuracy of the chilling chamber is improved. According to the method, structural parameters, inter-edge conditions, initial conditions and model parameters are dynamically adjusted, multi-parameter coupling optimization is achieved, in addition, through numerical simulation, the number of physical prototype experiments can be reduced, the research and development cycle can be shortened, and optimization cost can be reduced.

The invention relates to atmospheric chemical reaction calculation substitution and acceleration in an atmospheric chemical model, in particular to an atmospheric chemical reaction calculation substitution model and a construction method thereof, the model has a high-precision reappearance chemical reaction process, and in 19-day off-line prediction of 279 predictive variables of a case, the proportion of the predictive variable decision coefficient exceeding 0.99 is 96%; the model can realize continuous stable prediction for at least 10 days; compared with an original GEOS-Chem chemical integrator, the ChemKNet has the advantages that the time consumed by calculation on a single CPU can be saved by about 79%, only about 1% of the original calculation time is needed on a single GPU, and the calculation efficiency of large-scale simulation is greatly improved; the model supports coupling and continuous prediction; the model is provided with a full-chema chemical mechanism covering GEOS-Chem, and is provided with global simulation and a full-chema chemical mechanism covering GEOS-Chem.

This invention discloses a method for calculating the safe density window of hydrate formations considering drilling fluid action. A multi-field coupled thermal-fluid-solid-chemical model is established, taking into account the effects of mud cake seepage at the wellbore and the decomposition of natural gas hydrates. The simulation results present the distribution of pore pressure, temperature, and solute concentration in the drilling fluid around the wellbore after drilling fluid intrusion. Based on the solution results of the multi-field coupled model and combined with the Coulomb-Mohr failure criterion, a method for calculating the safe density window of hydrate formations under drilling fluid action is further established. This method more comprehensively considers the influence of various factors on wellbore stability during hydrate extraction, making the model results more accurately reflect the actual formation conditions and providing a basis for the design of drilling fluid anti-collapse performance during hydrate formation drilling.

The application discloses a radioactive separation laboratory environment radiation field dynamic modeling method and system, and belongs to the field of chemical process modeling. Step 1, the concentration distribution of a non-radioactive process tracer physically associated with a target radionuclide in a process fluid is obtained; step 2, based on the concentration distribution and the macroscopic residence time distribution of the material, the pre-judgment source term of the radionuclide is obtained through time translation and decay scaling; step 3, the radiation field observation waveform collected by a heterogeneous radiation sensitive field sensor network and independent of the pre-judgment source term is obtained; step 4, the theoretical radiation field change waveform calculated based on the pre-judgment source term is obtained; the application can obtain the concentration distribution of the non-radioactive tracer physically associated with the target radionuclide, eliminate the inherent bias of the source term from the source, and accurately depict the time-varying characteristics of the source term caused by the continuous migration of the material without making steady-state or quasi-static simplification assumptions on fluid turbulence, two-phase interface dynamic change and other processes.

The invention discloses a high impact polystyrene test method, electronic equipment and a program product, and relates to the technical field of high impact polystyrene, the method comprises the following steps: building a fully branched polybutadiene model by using butadiene as a monomer; initiating styrene monomer polymerization by taking the first active site in the polybutadiene model as a seed to obtain a cross-linked phase molecular chain of polybutadiene and polystyrene; mixing the cross-linked phase molecular chain with a plurality of pure polystyrene molecular chains to construct a high-impact polystyrene chemical model; a molecular chain space structure of the high-impact polystyrene chemical model is optimized based on a molecular dynamics simulation principle, and a high-impact polystyrene material model meeting preset physical characteristics of the high-impact polystyrene material is obtained; and simulating a mechanical property change rule of the high impact polystyrene material model in a preset extreme test environment to obtain a test result. By adopting the method, the problem that the test result is inaccurate due to the fact that the test environment is easily limited in an extreme test environment can be solved.

The invention discloses a radioactive separation laboratory environment radiation field dynamic modeling method and system, and belongs to the field of chemical process modeling, and the method comprises the steps: 1, obtaining the concentration distribution of a non-radioactive process tracer agent which is in a physical associated relationship with a target radionuclide in a process fluid; step 2, based on the concentration distribution and the macroscopic retention time distribution of the material, obtaining a prejudgment source item of the radionuclide through time translation and scaling according to decay; step 3, acquiring a radiation field observation waveform which is acquired by the heterogeneous radiation sensitive field sensor network and is independent of the pre-judgment source item; 4, changing the waveform of the theoretical radiation field calculated based on the pre-judgment source item; according to the method, the non-radioactive tracer physically associated with the target radionuclide can be adopted to obtain the concentration distribution, steady-state or quasi-static simplified assumption does not need to be made in the processes of fluid turbulence, two-phase interface dynamic change and the like, the inherent deviation of the source item is eliminated from the source, and the time-varying characteristic of the source item caused by continuous migration of the material is accurately described.

The application relates to the technical field of sewage treatment, in particular to a phosphorus removal reagent adding method and system for chemical phosphorus removal in a sewage treatment plant. The method comprises the following steps: collecting operation parameters of the sewage treatment plant in real time; inputting the collected operation parameters into a pre-constructed dynamic physical and chemical model, simulating the dynamic change of a phosphorus removal process, and rollingly predicting a variation trajectory of effluent phosphorus concentration in a future set prediction time domain; the dynamic physical and chemical model comprises a precipitation module, an aging module and an adsorption module; a model predictive control algorithm is adopted to take the minimum phosphorus removal reagent adding amount and the stable and up-to-standard effluent phosphorus concentration in the future set prediction time domain as an optimization target, so as to obtain an optimal phosphorus removal reagent adding amount sequence in the future set prediction time domain. The application can reduce reagent consumption, sludge production and operation cost.

The application discloses a battery simulation model construction method, device, equipment and medium, and belongs to the technical field of new energy storage. The method comprises the following steps: obtaining cell parameters, charging and discharging data and production line statistical data of a battery; the battery comprises a plurality of single cells connected in series and in parallel; a three-dimensional thermal model and a physical and chemical model of a single cell are established according to the cell parameters; the dynamics parameters in the physical and chemical model of each single cell are calibrated according to the charging and discharging data by using a genetic algorithm, and a plurality of single cell pseudo two-dimensional models are obtained; a multi-cell coupling model is established according to the plurality of single cell pseudo two-dimensional models and the series-parallel connection topological structure of the battery; the multi-cell coupling model is corrected according to the production line statistical data by using a Monte Carlo simulation method, and a multi-cell electrochemical model of the battery is obtained; and the multi-cell electrochemical model and the three-dimensional thermal model are coupled to obtain a simulation model of the battery. The application can solve the problem of low precision of existing cell simulation.

The present application relates to the replacement and acceleration of atmospheric chemical reaction calculation in atmospheric chemical model, and particularly relates to a replacement model of atmospheric chemical reaction calculation and a construction method, the model has high precision in reproducing chemical reaction process, in the 19-day offline prediction of 279 prediction variables of the case, the proportion of prediction variable determination coefficient exceeding 0.99 is 96%; the model can realize at least 10-day continuous stable prediction; the model has significant acceleration of chemical calculation: compared with the original GEOS-Chem chemical integrator, the time consumption of ChemKNet calculation on single CPU can be saved by about 79%, and only about 1% of the original calculation time is needed on single GPU, greatly improving the calculation efficiency of large-scale simulation; the model supports coupling and continuous prediction; the model has full-chem chemical mechanism and global simulation covering GEOS-Chem.

The application provides a method for dividing an atmospheric pollution weak diffusion area based on an extended WRF and CMAQ model, which comprises the following steps: collecting data, wherein the data collection comprises collecting local data and satellite remote sensing data of a research area; inverting underlying surface data, wherein the local data of the research area obtained in the data collection stage is used to invert the latest underlying surface condition by using the latest city underlying surface surface cover data, so that the underlying surface data is obtained; constructing an extended WRF-CMAQ chemical model, wherein the extended WRF-CMAQ chemical model comprises a three-dimensional assimilation system, a WRF model and a CMAQ model; optimizing the extended WRF-CMAQ chemical model and performing data simulation; obtaining different index concentration data of air quality; performing normalization processing on the index concentration data to obtain concentration; and determining a weak diffusion area division standard according to the concentration, and dividing the weak diffusion area.

The invention discloses a multi-scale coupling modeling method for an adiabatic axial fixed bed reactor, and relates to the field of chemical process modeling and reaction engineering.The modeling method comprises the following steps that S1, a three-level basic structure unit is constructed; s2, establishing a physical-chemical coupling calculation model; s3, embedding wide modulus parameter dynamic adaptation logic; s4, acquiring micro-scale reaction kinetic parameters, mesoscale transfer characteristic parameters and macro-scale equivalent performance parameters; s5, establishing a diffusion-reaction coupling equation of a single catalyst particle, and obtaining a comprehensive reaction-transfer parameter of the particle size; s6, establishing a macroscopic coupling model, describing a flow process in the reactor, and realizing cross-scale real-time coupling calculation of flow-diffusion-reaction-heat transfer; and S7, based on a cross-scale real-time coupling calculation result, extracting target performance parameters of the whole reactor. According to the method, the prediction precision of the model is improved, reactor hotspot control and safety production are effectively served, and the stability of industrial production is guaranteed.

A method for simulation, in particular for computerized calculation, of at least one physical property of a system of one or more chemical species that includes at least one chemical species dissolved in at least one chemical species, using a quasi-chemical, COSMO-RS, COSMO-SAC, or COSMOSPACE calculation involving composition dependent segment interactions and achieving Gibbs-Duhem consistent chemical potentials and activity coefficients or Gibbs-Duhem consistent chemical potentials or Gibbs-Duhem consistent activity coefficients. According to the invention, either at least one uncorrected segment activity coefficient or at least one segment contacting probability resulting from an initial quasi-chemical, COSMO-RS, COSMO-SAC or COSMOSPACE calculation is used as an input variable as for the calculation, or at least one uncorrected segment activity coefficient and at least one segment contacting probability resulting from the initial quasi-chemical, COSMO-RS, COSMO-SAC or COSMOSPACE calculation are used as input variables as for the calculation.

The invention relates to a method and a system for predicting a viscosity-temperature characteristic curve of coal cinder of a gasification furnace based on a graph network model, and the system collects viscosity-temperature characteristic data and coal ash component data of coal cinder of the gasification furnace, carries out data cleaning and preprocessing, and analyzes the correlation between the coal ash component and a viscosity-temperature characteristic function coefficient by using a Pearson correlation coefficient. And based on a correlation analysis result, constructing a deep learning graph network prediction model, inputting coal ash component data, and outputting a viscosity-temperature characteristic function coefficient. The system adopts a random hyper-parameter optimization method to optimize the model, and the prediction accuracy is improved through model integration. Finally, the system can predict a coal cinder viscosity-temperature characteristic curve in real time, and a scientific basis is provided for optimized operation of the gasification furnace. According to the method, deep learning and chemical process modeling are combined, the prediction precision and the model generalization ability are remarkably improved, and the method has important industrial application value.

The invention discloses an RAG-driven adaptive learning path planning and evaluation method based on a personalized student model. The method comprises the following steps: constructing a dynamic student portrait and updating the dynamic student portrait in real time; weak knowledge points and error types are recognized according to the error question set and the knowledge graph, negative feedback enhanced retrieval is conducted, and accuracy is not poor; a self-adaptive learning task is generated, and intelligent evaluation feedback is carried out; and evaluating a learning effect, and then adjusting a learning path and a stage target. According to the method, a dual vector retrieval mechanism is provided, the user question and the trainee portrait are deeply fused, the retrieval accuracy of an RAG system in an education scene can be effectively improved, and it is ensured that the retrieval content is matched with the question and conforms to the trainee level; besides, a negative feedback enhanced retrieval mechanism is utilized to make full use of a student wrong question set and a knowledge graph, so that accurate difference compensation is realized, and the learning efficiency is remarkably improved; in addition, teaching strategies can be continuously optimized, and real thousand-person and thousand-face personalized teaching is achieved.

The invention relates to an equipment defect sample generation method and device, computer equipment and a storage medium. The method comprises the following steps: constructing an equipment model of target power equipment according to modeling data of the target power equipment; the modeling data is determined by an initial defect detection model and an original data set of the target power equipment, and the modeling data is normal state data; based on the power equipment model, determining multiple defect models of the target power equipment by adopting finite element analysis and a physical field model or a chemical model; performing image rendering and chromaticity fusion processing on various defect models to obtain a preliminary defect sample; and screening the preliminary defect sample based on the confidence threshold of each defect category of the target power equipment to obtain a target defect sample of the target power equipment. By adopting the method, the physical authenticity and scene adaptability of defect sample acquisition can be remarkably improved, the diversity of defect samples is guaranteed, and the generalization ability of a defect detection model is further enhanced.

The invention provides a water-rock reaction rapid simulation method for coupling a neural network and a physical and chemical model, and the method specifically comprises the following steps: building a multi-physics field numerical calculation model of water-rock reaction transportation, defining and initializing key physics field variables in a definition domain, and building a key physics field variable control equation set; acquiring high-fidelity data field data on discrete time nodes in the water-rock reaction corrosion process; constructing a supervision data set for time sequence prediction, and constructing a neural network prediction model; and constructing an adaptive physical solution-data driven prediction dynamic coupling mechanism, remapping a prediction field into a computational grid, inputting the prediction field as a new initial condition into a multi-physical field numerical calculation model, then switching back to a physical solution mode, and continuing numerical calculation from a current time point. According to the technical scheme, the problems that in the prior art, data driving and physical solution cannot be coupled on the pore scale at the same time, and the calculation cost is high are solved.