90 results about "Reaction model" patented technology

The invention relates to a multi-cell control method for hydrogen production alkaline electrolytic cells based on nonlinear model predictive control, which belongs to the technical field of hydrogen production and comprises the following steps of: performing data acquisition on key positions of a hydrogen production alkaline electrolytic cell system in real time; based on the dynamically determined priority of each electrolytic cell, dynamic load distribution of each electrolytic cell is carried out, and a multi-dimensional cooperative regulation strategy is implemented to obtain a hydrogen yield target value of each electrolytic cell; constructing a nonlinear model comprising an electrolytic reaction model, a heat transfer model and an inter-tank coupling model, and performing parameter identification and verification; and designing a nonlinear model predictive control algorithm, performing discretization processing on the nonlinear model, introducing Kalman filtering to process the uncertainty of the model, taking a corresponding hydrogen yield target value reached by each electrolytic cell on the premise of meeting the constraint as a final control target, constructing an optimized target function, and performing solving to obtain an optimal control scheme. Compared with the prior art, the control precision and the system stability can be effectively improved.

The invention discloses a multi-dimensional multi-physics field coupling analysis platform of a hydrogen fuel cell based on artificial intelligence, and relates to the technical field of hydrogen fuel cells, the platform comprises a user interaction interface module, a multi-physics field model construction module, a data acquisition and preprocessing module, an integration module and an analysis and result output module; an electrochemical reaction model, a temperature field model and a gas and liquid flow model are respectively built through a multi-physical field model building module, the coupling strength among different physical fields is quantified, and the electrochemical reaction model, the temperature field model and the gas and liquid flow model are integrated into a multi-physical field model; physical action parameters such as electrochemical reaction rate, temperature value and the like are associated with time change, spatial distribution and fault conditions, so that the platform can simulate the multi-physical field coupling effect of the hydrogen fuel cell under complex working conditions, and the performance of the fuel cell is analyzed; and a reliable basis is provided for the geometric structure, material selection and operation condition optimization of the fuel cell.

The invention relates to the technical field of chemical production regulation and control, and discloses a system for thickening agent addition and on-line viscosity regulation and control in a post-regulation stage of a polyacrylic acid emulsion. The system comprises an overview construction module, a coefficient generation module, a rate optimization module and an execution control module. The overview construction module creates a production overview based on user settings, wherein the production overview comprises a reaction tank body connection relationship and thickening agent injection node parameters; the coefficient generation module is used for collecting real-time stirring state data and tank reaction data, respectively constructing a stirring state model and a tank reaction model, and outputting a stirring state coefficient and a tank reaction coefficient; the rate optimization module obtains the difference value between the current viscosity measurement value and the target viscosity, constructs a rate optimization model in combination with the tank reaction coefficient, the stirring state coefficient and the viscosity difference value, and outputs the target thickening agent injection rate; and the execution control module drives the thickening agent injection device according to the target thickening agent injection rate. According to the system, the accuracy and the stability of viscosity regulation and control are improved.

The invention discloses a lithium battery thermal runaway internal temperature estimation method based on an electrochemical thermal coupling model, and the method comprises the steps: S1, selecting a to-be-measured lithium battery, and obtaining corresponding electrochemical parameters and physical parameters of the to-be-measured lithium battery; s2, carrying out a basic charging and discharging experiment and an extreme working condition experiment on the battery, and collecting related actual measurement data; s3, establishing a battery electrochemical model; s4, establishing a battery thermal model and a battery side reaction model, and obtaining an electrochemical-thermal coupling model; s5, performing numerical simulation on the electrochemical-thermal coupling model to obtain temperature data of each point in the battery at corresponding moments from the early stage to the last stage of thermal runaway of the lithium battery; and S6, using the data in the step S5 and the actually measured data in the step S2 for training a neural network, establishing a neural network model, and predicting the internal temperature of the lithium battery in real time. According to the invention, the advantages of the mechanism model and the data-driven neural network model are combined, and the speed and precision of temperature prediction are improved.

The invention discloses an explanation method for damage threshold improvement of a fused quartz material in a femtosecond laser processing / welding process. By establishing a fused quartz electron-lattice heat transfer model under femtosecond laser irradiation, a dissociation model of environment molecules and interstitial molecules under the action of femtosecond laser and a defect-containing fused quartz molecule dynamic reaction model based on a ReaxFF reaction force field, atomic structure changes in a system before and after a reaction are analyzed; and finally, obtaining a chemical reaction mechanism of the fused quartz containing the defects under the action of the femtosecond laser, and explaining the phenomenon that the damage threshold of the fused quartz is increased after the fused quartz is irradiated by the low-flux femtosecond laser. According to the method, the research in the current fused quartz femtosecond laser processing / welding process is perfected, and meanwhile, the theoretical blank that the damage threshold lifting mechanism is not clear in the fused quartz glass femtosecond laser processing / welding process is filled up.

An embodiment represents composition of molecules in a feedstock as a combination of individual molecule representations and molecular attribute representations. A representation of chemistry of a chemical reaction of the feedstock in a chemical reactor is then formulated based on the representations. Then, a simulation of the chemical reaction of the feedstock in the reactor is performed using the representations to determine composition of products of the reaction. A first subset of the products are represented as individual molecule represented products, and a second subset of the products are represented as attribute represented products. In turn, the attribute represented products of the second subset are sampled to determine individual molecule representations of the attribute represented products. As a consequence of the sampling, individual molecule representations of the first and second subsets of the products of the chemical reaction of the feedstock in the chemical reactor result.

The invention provides a method and a system for autonomously and intelligently adjusting the pH value of a desulfurization device of a thermal power plant. The method comprises the following steps: collecting inlet flue gas parameters, pH values of multiple points in an absorption tower and slurry physical property parameters in real time; transmitting the data to a control system, and dynamically predicting the optimal pH value range required by the current working condition by using a built-in desulfurization reaction model; comparing the actual pH value with a prediction range, generating a desulfurizing agent adding basic instruction, and performing dynamic correction by combining the liquid level and density of the slurry to obtain a final instruction; a high-precision metering pump and a regulating valve are controlled to execute precise adding; meanwhile, the model is self-optimized according to performance index feedback such as desulfurization efficiency and outlet SO2 concentration. Through combination of multi-parameter perception, model prediction feedforward and physical property parameter dynamic correction, the pH value is converted from passive and lagged adjustment to active and accurate intelligent adjustment, the desulfurization efficiency and the system stability are effectively improved, the operation cost is reduced, and environment-friendly up-to-standard emission is ensured.

The invention discloses a rapid modeling method for a material pyrolysis kinetic model, and solves the problems that prediction of'kinetic three factors' of an existing pyrolysis reaction is suitable for a single-step reaction, calculation errors may be large, or prediction of'kinetic three factors' of the existing pyrolysis reaction is suitable for a complex multi-step reaction, but pre-exponential factors and a reaction mechanism function cannot be directly obtained. According to the method, physical information and an operator neural network are fused, a double-branch network architecture, namely the physical information enabling operator neural network, is constructed, and meanwhile, a physical constraint module containing a kinetic equation is introduced to enhance the interpretability of a neural network model. In practical application, thermogravimetric data measured by experiments and corresponding heating rates can be respectively used as input of a branch network and a backbone network of the neural network model, and then kinetic parameters of the pyrolysis problem multi-step reaction model are predicted. A numerical result shows that the method effectively improves the precision of parameter estimation by fusing physical priori knowledge.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a retrosynthesis tree for a target molecule In one aspect, there is provided a method comprising: selecting a leaf node that is included in one or more retrosynthesis trees in a collection of retrosynthesis trees; processing data defining the respective molecule represented by the selected leaf node, using a reaction modeling neural network, to generate a score distribution over a set of chemical reactions that produce the respective molecule represented by the selected leaf node; selecting one or more chemical reactions from the set of chemical reactions using the score distribution over the set of chemical reactions; and generating one or more new retrosynthesis trees that each extend a respective retrosynthesis tree that includes the selected leaf node based on the one or more chemical reactions selected from the set of chemical reactions.

The invention discloses a construction and performance analysis method for a low-pressure performance prediction model of a fuel cell, which is applied to the technical field of proton exchange membrane hydrogen-air fuel cells, and comprises the following steps: establishing an air pressure and density model changing along with altitude based on an empirical formula; according to a Nernst equation and a fuel cell polarization equation, obtaining a fuel cell monomer voltage; establishing a stack cathode and anode reaction model by using a mass conservation principle and electrochemical characteristics; and an air compressor model based on the MAP and a cathode outlet pipeline model based on the nonlinear nozzle equation are established. A simulation environment is completed by using Simulink based on the model, and simulation result data is obtained and used for predicting the performance of the fuel cell in a low-pressure environment. According to the invention, waste of manpower and material resources caused by blind low-pressure test and irreversible damage possibly caused to the fuel cell system are avoided, theoretical guidance and predictive analysis basis are provided for subsequent test research, and powerful support is provided for low-pressure performance analysis and design of the fuel cell.

The invention discloses a method and system for determining the in-situ limit exploitation depth of oil shale, and the method comprises the steps: measuring the permeability under different depths according to an oil shale sample of an oil shale in-situ region to be evaluated; performing a pyrolysis experiment on the oil shale sample to obtain the composition of each simulated product and the components of each simulated product changing along with the temperature, and fitting a pre-constructed kerogen pyrolysis-based multi-step total reaction model on the basis of the composition and the components, so as to obtain fitted model coefficients and reaction kinetic parameters; predicting a formation temperature field formed on the basis of a heating condition of high-temperature fluid injection in the current formation, and predicting a yield change curve on the basis of the formation temperature field in combination with the permeability at different depths, the model coefficients and the reaction kinetic parameters; and establishing an income prediction model related to the to-be-evaluated oil shale in-situ area, and obtaining the limit mining depth when the income value is zero according to the yield change curve.

This invention discloses a method, system, equipment, and medium for controlling pollutant concentration in wastewater pipe networks, relating to the field of drainage system technology. The method includes: obtaining the mass flushing rate of pollutants under pipe scouring; collecting the amount of components generated by chemical reactions within the pipe; constructing a pollutant reaction model; and, based on convection diffusion, obtaining the concentration changes of sediments following wastewater, constructing a convection diffusion reaction model. The mass flushing rate, pollutant reaction model, and convection diffusion reaction model are coupled to obtain a pollutant concentration prediction coupling model. The pollutant concentration in the wastewater pipe network is predicted based on the pollutant concentration prediction coupling model, and the pollutant concentration is divided into multiple levels. Different flushing methods are selected within different levels to control the pollutant concentration in the wastewater pipe network. This invention can adopt different methods according to different actual scenarios, thereby controlling the pollutant concentration within a reasonable range.

The application discloses a rotary kiln multi-physical phenomenon numerical simulation method based on artificial intelligence reasoning, relates to the technical field of rotary kiln multi-physical phenomenon simulation, and is based on the Euler multiphase flow equation, adds a heat transfer model, a chemical dynamics reaction model, a particle growth model, a chemical reaction model and the like, establishes a three-dimensional numerical model capable of accurately simulating the multi-physical and chemical phenomena such as the gas-solid two-phase flow movement, combustion, NOx generation, clinker calcination and particle growth in the rotary kiln, introduces a long short-term memory neural network to build an AI model, uses the AI model to predict the latter half of the working condition, accelerates the simulation speed, and realizes long-time simulation of the rotary kiln.

A method and medium for simulating a hydrogen absorption / desorption process of a hydrogen storage device relates to the technical field of energy system modeling and simulation, and the method comprises the following steps: obtaining a hydrogen absorption / desorption reaction model of a hydrogen storage material, the hydrogen storage material being a metal hydride for hydrogen storage and desorption in the hydrogen storage device; based on the reaction model, a user-defined function is generated, and the user-defined function is used for representing the hydrogen absorption / desorption process of the hydrogen storage material; determining a user-defined scalar based on the conversion rate of the hydrogen storage material; and based on the user-defined function and the user-defined scalar, simulating the hydrogen absorption / desorption process of the hydrogen storage device by using simulation software so as to realize coupling calculation of hydrogen absorption / desorption reaction and flow, heat transfer and mass transfer.

The present invention provides a method for predicting the production capacity of in-situ steam injection mining of oil shale, which belongs to the technical field of oil and gas field development. The method for predicting the production capacity of in-situ steam injection mining of oil shale uses the steam front evolution theory, combined with the basic characteristics of the pyrolysis reaction of kerogen in oil shale, to divide the entire oil shale reservoir during the steam injection in-situ mining process into different areas, establish a mathematical model for the in-situ steam injection mining of oil shale, and use it to predict its production capacity, while reflecting the different development stages of the oil shale reservoir; the production capacity prediction method belongs to the field of oil and gas field development, and can solve the problems of existing production capacity prediction methods such as numerous calculation parameters and poor calculation ability, which greatly increase the difficulty of solving the model and the model is prone to non-convergence, so that the production capacity settlement result cannot be given; at the same time, it can also solve the problems of existing methods such as difficulty in correcting the reaction model according to actual conditions, involving multiple experimental tests and theoretical calculations, and complex actual operations resulting in poor practicality.

The invention relates to a boiler waste gas blending combustion control method and device, a storage medium and electronic equipment, and the method comprises the steps that the air inlet amount and the waste gas blending combustion amount of a boiler are input into a boiler reaction model obtained through pre-training, and first boiler reaction parameters output by the boiler reaction model are obtained; under the condition that the first boiler reaction parameter does not meet the pollutant emission control condition, the position of an exhaust gas blending combustion inlet in the boiler reaction model is adjusted, and the air inlet amount and the exhaust gas blending combustion amount are adjusted; the adjusted air inlet amount and the adjusted waste gas blending combustion amount are input into the adjusted boiler reaction model, and second boiler reaction parameters output by the boiler reaction model are obtained; and under the condition that the second boiler reaction parameter meets the pollutant emission control condition, the air inlet amount and the waste gas blending combustion amount flowing into the boiler are controlled according to the adjusted waste gas blending combustion inlet position, the air inlet amount and the waste gas blending combustion amount.

The invention discloses a hydrogen-based shaft furnace one-dimensional multi-phase field modeling method based on fuzzy neural network optimization. The method comprises the following steps: firstly, constructing a multi-phase field one-dimensional preliminary model of internal temperature, pressure and concentration of the hydrogen-based shaft furnace by using a fluid mechanics equation; secondly, constructing a reaction model based on an additive reaction time law, endowing each characteristic time item with a coefficient multiplier, and fully exciting the model through random values of the coefficient multipliers to obtain multi-phase field model simulation data; then constructing an agent model and optimizing a coefficient multiplier by utilizing a fuzzy neural network and combining a non-dominated sorting genetic algorithm II (NSGA-II); and finally, inputting the optimized coefficient multiplier and newly collected shaft furnace feeding parameters into the multi-phase field model to obtain an optimized hydrogen-based shaft furnace multi-phase field simulation result. Through cooperative driving of a mechanism and data, precise modeling of a multi-phase field in the hydrogen-based shaft furnace is achieved, and high simulation precision is achieved for different smelting conditions.

This invention discloses a method for constructing a macromolecular model of Hami oil-rich coal and its application. The molecular formula and functional group characteristics of the coal sample are determined through elemental analysis and infrared spectroscopy. A planar structural model is constructed using the Wiser model framework, and a stable configuration is obtained after geometric optimization. Finally, a pyrolysis reaction model containing multiple molecules is constructed through stacking. Targeting the high-oxygen and high-cycloalkane structural characteristics of Hami oil-rich coal, a C1... 128 H 82 NO 16 and C 111 H 88 NO 28 Two precise models were used, and the accuracy of the calculated infrared spectra was verified by comparing them with experimental spectra. ReaxFF molecular dynamics simulations were performed using this model, revealing the influence of different heating rates and pyrolysis temperatures on product distribution. The optimal simulation temperature and critical values ​​for pyrolysis rate control were determined, and the difference in ethylene formation pathways between alkyl-rich coal and ether-rich coal was analyzed. This invention fills the gap in precise models for Hami oil-rich coal, providing key theoretical basis and parameter guidance for optimizing pyrolysis processes, achieving targeted regulation, and improving energy efficiency.

The application discloses a kind of multi-temperature field grouting material reaction model box, including water storage tank, temperature tank and grouting reaction model box;The grouting reaction model box includes box, grouting material unit and reaction unit;The grouting material unit is set on box and is communicated with box, and grouting material is injected into the reaction unit in box;The reaction unit corresponds grouting material unit and is set in box;The water storage tank is communicated with temperature tank, and original water source is input to temperature tank inside and temperature adjustment is carried out to original water source;The temperature tank is communicated with grouting reaction model box, and the water source in temperature tank after heating is injected into grouting reaction model box, and reacts with grouting material on the reaction unit in grouting reaction model box;The scheme can adjust the temperature of grouting material reaction, meet the different temperature under the grouting material anti-seepage plugging performance research proposed in actual engineering, to improve the reliability of grouting material anti-seepage plugging.

This system provides a silica scale generation prediction system that can predict the amount of silica scale generated with greater accuracy. [Solution] The silica scale generation prediction system according to the present invention is based on the temperature T at the predicted site of the target object. s A prediction formula PF for silica concentration C, which depends on the silica concentration, and the time t until the silica-containing fluid reaches the predicted site. s The system includes a silica scale generation prediction unit that predicts the amount of silica scale generated at a predicted site based on at least one of the silica concentration C prediction curve PC which depends on the silica concentration C, wherein the silica concentration C prediction formula PF and the silica concentration C prediction curve PC are obtained based on a reaction model generated using a silica polymerization reaction that includes reversible and irreversible reactions and precipitation equilibrium reactions of silica contained in the fluid, and the silica scale generation prediction unit calculates the amount of silica scale generated at the predicted site using at least one of the initial silica concentration Ci and the fluid flow rate FR.

The present application provides a kind of coal-fired unit boiler abnormal air volume evaluation method and furnace safety evaluation method, steps are: with the combustion region of coal-fired unit boiler as the calculation domain to construct analysis structure model;Based on analysis structure model, reaction model is constructed to obtain air volume analysis model;Input normal induced draft and run air volume analysis model, steady state is obtained using steady-state calculation method;Input to be evaluated induced draft, with steady state as initial condition, run air volume analysis model, transient furnace state is obtained using transient calculation method to judge whether to be evaluated induced draft is abnormal air volume;Transient furnace state includes transient high-temperature flame state of each time step and transient furnace internal pressure of each time step.The evaluation method can greatly reduce the cost of evaluation on whether to be evaluated induced draft is abnormal air volume and furnace safety evaluation through simulation means, without adjusting parameter test in boiler system, and has strong repeatability.

The application provides a coke oven gas dynamic multi-factor coupling prediction method, relates to the coking technology field, and comprises the following steps: S1, data acquisition and preprocessing; S2, dynamic reaction model establishment: simulating the dynamic change of gas precipitation in the coking process, considering the interaction between various factors, and establishing a dynamic mathematical model; S3, model verification and correction; S4, real-time calculation and prediction. The coke oven gas dynamic multi-factor coupling prediction method comprehensively considers various factors such as coal quality characteristics, coke oven heating system and operation parameters, and embeds a multi-factor coupling mechanism, effectively overcomes the problem of large prediction error of the traditional coal quality element balance method for high volatile matter coal, and avoids the problem of poor generalization ability caused by the dependence of the empirical formula method on specific coal data. The method does not depend on the data of specific coal, can accurately predict atypical coal, and significantly improves the prediction accuracy and generalization ability.

The utility model discloses a grouting material reaction model box, which relates to the technical field of grouting materials and comprises a reaction mechanism, the bottom of the reaction mechanism is fixedly connected with a heating mechanism, and the bottom of the reaction mechanism is fixedly connected with an absorption mechanism; and the absorption mechanism comprises a fixing ring, the inner wall of the fixing ring is fixedly connected with a gas collection port, the inner wall of the gas collection port is fixedly connected with a second motor, and the output end of the second motor is fixedly connected with a gas collection fan. Through the cooperation of the gas collecting port, the motor II, the gas collecting fan, the gas collecting pipe, the activated carbon box and the box cover, a worker can load activated carbon into the activated carbon box, the motor II is started to drive the gas collecting fan to rotate, harmful gas generated by the reaction of a grouting material is injected into the activated carbon box through the gas collecting pipe, and harmful substances are adsorbed by the activated carbon; after the reaction of the grouting material is finished, the box cover can be opened to remove and replace the activated carbon in the activated carbon box, so that harmful substances are prevented from being directly discharged into air, and the life health of workers is protected.

The invention discloses a drying process quality monitoring method and equipment based on wafer drying, and a medium, belongs to the technical field of wafer drying process monitoring, and aims to solve the problems that in the existing wafer drying process, the final finished product monitoring is often performed, the process monitoring and defect control of the intermediate link flow are difficult to realize, and the product quality is poor. The overall yield of the wafer is not facilitated, and resource waste is easily caused. The method comprises the following steps: carrying out integrity monitoring treatment under water film coverage on the surface of a wafer which is conveyed and loaded; performing liquid load identification calculation on the wafer surface image after physical spin-drying to obtain a surface water film spot diagram; carrying out volume calculation under related water film pixels on the surface water film spot diagram; carrying out gas concentration reaction model calculation processing on the residual deionized water film volume data and the replaced gas data; carrying out microscopic quality inspection treatment on the wafer surface of the wafer to obtain post-processing quality data; and generating a drying process monitoring report for wafer drying process monitoring.

The application provides a CAR-T cell therapy toxicity management optimization method and system, relates to the technical field of artificial intelligence, and comprises the following steps: acquiring clinical data of a blood tumor patient receiving a CAR-T cell therapy; performing missing value interpolation and standardization processing on baseline characteristic information and process monitoring data to obtain a standardized data set; obtaining a calibrated virtual patient physiological model according to a preset tumor cell kinetics model, an immune cell kinetics model and a toxicity reaction model; taking the calibrated virtual patient physiological model as an interactive environment to obtain a correlation database; constructing a deep Q network intelligent agent with a maximum reward function as a target to obtain an optimized deep Q network intelligent agent; and inputting the process monitoring data into the optimized deep Q network intelligent agent to obtain a target strategy, so that the individualized CAR-T treatment strategy balancing the therapeutic effect and toxicity can be automatically output by inputting the real-time monitoring data of the patient.

The invention discloses a heating well spacing evaluation method and system for in-situ fluid heating of oil shale, and the method comprises the steps: measuring basic parameters of a rock mass according to an oil shale sample of an oil shale in-situ region to be evaluated; performing a pyrolysis experiment on the oil shale sample to obtain the composition of each simulated product and the components of each simulated product changing along with the temperature, and fitting a pre-constructed kerogen pyrolysis-based multi-step total reaction model on the basis of the composition and the components, so as to obtain fitted model coefficients and reaction kinetic parameters; setting well pattern modes based on different well spacing for the mining heating area; predicting a formation temperature field formed on the basis of a heating condition of high-temperature fluid injection in the current in-situ formation, and predicting yield change curves under different well pattern modes on the basis of the formation temperature field in combination with the solved model coefficients and reaction kinetic parameters and the different well pattern modes; and establishing a target index calculation model for evaluating the quality of the well pattern modes, and obtaining corresponding target indexes according to the yield change curves in different well pattern modes, thereby optimizing the optimal well spacing.

The invention provides a numerical simulation method of a circulating type flue gas decarburization system, and belongs to the technical field of chemical energy. Based on gridding modeling and division and setting of multiple reaction areas, a reaction model between gas and solid phases in circulation is established and solved, by setting an absorption area assembly and a regeneration area assembly, the working conditions of a carbon dioxide absorption area and an absorbent regeneration area are adjusted, and then the gas-solid reaction form of the carbon dioxide absorption area and the absorbent regeneration area is adjusted. Therefore, the absorption-removal circulation of carbon dioxide in the system is realized. The device comprises an absorption area assembly and a regeneration area assembly, and further comprises a communicating pipe assembly, one side of the absorption area assembly is provided with an absorbent particle inlet, the other side of the absorption area assembly is provided with a communicating pipe assembly, the other end of the communicating pipe assembly is communicated with a regeneration area assembly, the other side of the regeneration area assembly is provided with a regeneration particle inlet, and the communicating pipe assembly is arranged between the absorption area assembly and the regeneration area assembly.

The invention relates to a method for determining an underground fuel deposition rate, which comprises the following steps of: putting a rock core and high-temperature-resistant cement into a model pipe to prepare a reaction model; the reaction model is placed in the RTO tubular furnace, the reaction model is connected with a gas inlet pipe and a gas outlet pipe, the gas inlet pipe of the reaction model is connected with a first gas cylinder and a second gas cylinder, and the gas outlet pipe of the reaction model is connected with a gas-liquid separation device and a flue gas analyzer; a control valve of the second gas cylinder is opened, a control valve of the first gas cylinder is closed, and gas in the second gas cylinder enters the reaction model; the control valve of the second gas cylinder is closed, the control valve of the first gas cylinder is opened, gas in the first gas cylinder enters the reaction model, the RTO tubular furnace is started, and heating is stopped after the temperature is increased to the preset temperature; calculating fuel consumption according to the volumes of carbon dioxide and carbon monoxide measured by the flue gas analyzer; and measuring the amount of liquid crude oil collected in the gas-liquid separation device after heating is stopped, and calculating the fuel deposition rate based on the amount of the liquid crude oil and the fuel consumption.

The invention relates to the technical field of coal gasification, and designs an automatic optimization intelligent system for a gasification furnace in order to solve the problem of parameter control of an intermittent gasification furnace. The system integrates a plurality of modules of uplink and downlink temperature control, feeding time control and the like, and parameters of blowing time, steam quantity and the like are accurately adjusted by means of self-optimization, fuzzy control, predictive control algorithms and fusion of an in-furnace reaction model and an expert system. During actual operation, the adjustment amount of each parameter is calculated according to real-time data, and automatic intelligent control is achieved. The system is high in commissioning rate, effectively reduces labor intensity and management cost of operators, improves temperature control precision, stabilizes a material layer, reduces blow-over phenomena, guarantees stable, long-term and full-optimal operation of the gasification furnace, remarkably improves production efficiency and economic benefits, and promotes intelligent development of the coal gasification industry.

This invention belongs to the field of lithium-ion battery modeling technology and discloses a multi-physics coupling modeling and simulation method for the puncture process of a pouch lithium battery. The method includes the following steps: establishing an electrochemical reaction model of the lithium-ion battery based on P2D theory; simulating the electrochemical phenomena of the lithium-ion battery discharge process by constructing a 1D battery model; simulating the current distribution in the positive and negative electrode current collectors by constructing a 2D current collector electron transport model; and simulating the heat generation and heat transfer process by constructing a 3D puncture thermal model. These models are then coupled together to form a comprehensive model. This invention employs the aforementioned multi-physics coupling modeling and simulation method for the puncture process of a pouch lithium battery to simulate the SOC, voltage, current, and temperature after puncture. The electrochemical-thermal coupled full 3D modeling method provides simulation support for estimating the internal state of the pouch lithium-ion battery and studying the impact of external abuse on the battery.