33 results about "Reaction model" patented technology

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.

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.

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 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 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 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 embodiment of the invention provides a control method of a gasification furnace, which comprises the following steps of: firstly, acquiring the current measurement data of the gasification furnace, and solving a data reconciling and optimizing model by using the current measurement data to obtain the input information of the gasification furnace consisting of key elements of coal as fired so as to solve the problem that the elements of the coal as fired are uncertain; then based on input information of the gasification furnace and according to a reaction model of the gasification furnace, field distribution information and coal ash deposition rate distribution information of the gasification furnace are obtained, and temperature distribution of the gasification furnace is calculated according to the information; the obtained temperature distribution of the gasification furnace can well reflect the slag state and temperature information at different positions in the furnace, and the slag blockage or burnthrough risk can be effectively evaluated; and finally, solving a real-time optimization problem based on the target information to obtain an optimized operation variable, so that the aim of guiding and optimizing the subsequent production process of the gasification furnace is fulfilled on the basis of ensuring the production safety, thereby improving the production efficiency of the gasification furnace.

The invention discloses an environment-friendly insulating gas and metal electrode discharge compatibility evaluation and calculation method. The method comprises the following steps: forming a gas-metal molecule reaction model; simulating a discharge condition in the electrical equipment in the gas-metal molecule reaction model; performing geometric structure optimization on the gas-metal molecule reaction model to which the discharge condition is applied to obtain a stable adsorption configuration, and calculating the total energy and related electronic structure properties of the stable adsorption configuration; calculating compatibility key parameters based on the calculated total energy of the stable adsorption configuration and related electronic structure properties; and evaluating the compatibility of the environment-friendly insulating gas and the surface of the metal electrode based on the calculated compatibility key parameters. By simulating the strong electric field and the surface charge effect under the discharge condition, the external electric field and the surface charge effect are systematically introduced into DFT calculation, the key working condition of electrical discharge can be simulated more truly, and the accuracy and the reliability of an evaluation result are improved.

The invention discloses a perforated patch clamp operation method based on particle diffusion control, which belongs to the field of micromanipulation and comprises the following steps: S1, establishing an initial geometric environment statistical model of perforated particles; s2, establishing a perforated particle diffusion model, and obtaining the number of perforated material particles diffused to a cell membrane at any time; s3, establishing a perforation reaction rate model to obtain the number of perforations in the cell membrane at any time; s4, designing a model prediction controller, and realizing perforation membrane rupture based on particle diffusion control by controlling the diffusion velocity of the perforation material; and S5, adjusting the particle diffusion speed according to a modeling result and a transmembrane current peak value in combination with an automatic operation process of the perforation patch clamp, so as to obtain an ideal perforation progress. By establishing the diffusion and reaction model of the perforation solution, the change relation of the perforation number corresponding to the perforation solutions with different concentrations along with the time is obtained, and the perforation process is controlled on the basis of the change relation.

This invention provides a method for constructing a multiphysics-based curing process model for cast PBX explosives, comprising: Step 1, constructing a geometric structure model of the curing process, including a simplified structural model of the curing equipment, a geometric structure model of the curing tooling, and a structural model of the cast PBX explosive charge; Step 2, constructing a multiphysics-based mathematical physics model, including a material model of the cast PBX explosive, an elastoplastic mechanics model, a heat transfer model, and a curing reaction model; Step 3, constructing a numerical calculation model, based on the models in Step 1 and Step 2, performing discretization processing to construct an executable numerical calculation model; the calculation results of the multiphysics-based mathematical physics model numerical calculation model include temperature, pressure, velocity, stress, and chemical reaction progress. This invention describes a method for constructing a curing process model for cast PBX explosives from the perspective of flow, force, heat, and chemistry, thereby improving the simulation design level of cast PBX explosive processes.

Provided are a trained model, a calculation device, a calculation method, a calculation program, and a non-transitory storage medium that enable accurate calculation of culture-related concentrations using a biochemical reaction model. The trained model is trained using culture conditions serving as explanatory variables for when cells are cultured in a culture vessel, and a parameter of a physical model serving as the response variable that is used when a relevant concentration relevant to the culture conditions is calculated. The calculation device is provided with a culture condition input unit, a parameter acquisition unit, and a first concentration calculation unit. The culture condition input unit inputs a first culture condition as an explanatory variable to the trained model. When the first culture conditions are inputted to the trained model, the parameter acquisition unit acquires a first parameter outputted as the response variable from the trained model. The first concentration calculation unit calculates a first relevant concentration relevant to the first culture condition on the basis of the acquired first parameter and the physical model.

An assistance system (100) for assisting in controlling a chemical reaction run in a chemical reactor (10) for producing a plurality of products (20) is presented. The system comprises a) a product demands providing unit (101) configured to provide one or more future demands (40a, 40b, 50) for each of the products, b) a reaction model providing unit (102) configured to provide a reaction model, the reaction model indicating, for each of a plurality of combinations of values of a plurality of reaction control parameters (30a, 30b), a produced amount of each of the products, and c) a reaction parameter determining unit (103) configured to determine future reaction control parameter values based on the one or more future demands and the reaction model. This allows for a more efficient control of chemical reactions run in chemical reactors.

The invention relates to the technical field of electronic digital data processing, and discloses an acrylonitrile polymerization reaction multi-physics field coupling analysis method, which comprises the following steps: establishing a multi-physics field coupling acrylonitrile polymerization reaction model in a reactor, including a stirring kettle flow field model and a concentration field model, and a polymer structure dynamics model and a fluid heat transfer model; setting parameters, including physical parameters, chemical parameters and process parameters, of the acrylonitrile polymerization reaction model; setting a boundary condition and a source item of the acrylonitrile polymerization reaction model, executing time iterative calculation, and solving the multi-physics coupling equation by adopting a generalized minimum residual method until the residual is smaller than a preset threshold value; and outputting the three-dimensional distribution diagram of the multi-physical field, the molecular weight parameters of the polymer, the content of each component and the acrylonitrile conversion rate. The problems of difficult convergence, unstable data and inaccurate simulation in the prior art are solved, and the purposes of accurate simulation, stable calculation and optimal design are achieved.

The invention discloses a flue gas denitration system based on residual fuel utilization, a control method of the flue gas denitration system and an industrial furnace, and relates to the field of flue gas treatment. The SCR system comprises a catalytic reactor with an inlet end and an outlet end, and the catalytic reactor can perform denitration catalysis on flue gas and residual fuel discharged by the industrial furnace; the first monitoring unit can detect the amount of nitric oxide and the amount of residual fuel at the inlet end. The DCS can obtain hearth data of the industrial furnace; the denitration control system can obtain a nitrogen oxide prediction value and a residual fuel prediction value according to hearth data, the nitrogen oxide prediction model and the residual fuel prediction model, and correct the nitrogen oxide prediction value and the residual fuel prediction value according to the nitrogen oxide amount and the residual fuel amount at the inlet end. The denitration demand quantity of the fuel is obtained according to the SCR reaction model and the correction condition, and finally flow regulation and control are conducted on a fuel nozzle of the industrial furnace according to the denitration demand quantity of the fuel. Therefore, the amount of unburnt fuel and the removal rate of nitrogen oxide can be accurately controlled, and the cost is low.

This invention discloses an intelligent simulation and computation method for complex chemical reactions. Combining multimodal data fusion, deep learning models, and physically constrained networks (PINNs), along with reinforcement learning optimization strategies, it achieves efficient and accurate prediction of reaction processes and intelligent control of reactor parameters. The method first constructs a reaction model using graph neural networks (GNNs) and physically constrained neural networks (PINNs), embedding core equations from chemical kinetics, mass transfer, and fluid dynamics to ensure the prediction results conform to physical laws. Then, based on the proximal strategy optimization (PPO) algorithm, it achieves real-time optimization of reaction conditions, dynamically adjusting operating parameters such as temperature, pressure, and flow rate to maximize reaction conversion, selectivity, and energy efficiency. This invention can be widely applied to chemical reaction systems such as catalytic reactions, multiphase reactors, microchannel reactors, and drug synthesis, significantly improving computational efficiency and accuracy, reducing the computation time of traditional methods, and providing intelligent online optimization and control solutions for industrial chemical reaction processes.

Provided in the present application are a method and process for enhanced leaching of lateritic nickel ore. The method comprises: acquiring reaction conditions for a lateritic nickel ore leaching reaction; on the basis of the reaction conditions, determining a reaction model for the lateritic nickel ore leaching reaction, wherein reaction models include a liquid-layer diffusion-controlled model, a product-layer diffusion-controlled model and a reaction-controlled model; on the basis of the reaction model, determining the reaction conversion of the lateritic nickel ore leaching reaction; and on the basis of a reaction temperature, an acid-to-ore ratio and a reaction time, determining applicable reaction models under different reaction conditions, such that accurate control over a lateritic nickel ore leaching process can be achieved. The present application provides a theoretical basis and guidance for enhanced leaching of lateritic nickel ore, and improves the reaction rate of a lateritic nickel ore leaching reaction.

The invention belongs to the field of numerical simulation of combustion discipline, and relates to a novel method for identifying a component coupling relation in a chemical reaction model. The method is based on a data mining theory, takes a reliable simplified reaction model library as a basis, can accurately recognize the coupling relationship between different components, and remarkably reduces the scale of a final simplified reaction model. Meanwhile, based on the method, the influence of pressure and equivalence ratio conditions and simplified targets (the ignition delay period and the component concentration) on the simplified reaction model structure is explored, simplified working conditions and simplified targets are defined, and the calculation cost of large-scale reaction model simplification can be remarkably reduced.

A kind of iron concentration prediction method based on water supply pipeline wall layered structure and automatic calibration, comprising: integrated pipeline hydraulic model, iron concentration release model and microscopic electron microscope layered observation result, construct pipe network iron concentration layered multi-species reaction model, simulate the migration and transformation of iron ions between corrosion base layer, loose porous layer, hard shell layer and surface layer;Multi-objective comprehensive error function is constructed, and the difference between simulation result and observation data is evaluated;Three-stage differential evolution calibration is executed: the model is used as water quality simulation engine, the comprehensive error function is used as optimization target, and the model parameters are optimized by iteration method;First stage global search locates advantage area, second stage local optimization, third stage fine tuning, and after each stage ends, the subsequent parameter search boundary is dynamically contracted based on optimal solution and boundary tightening coefficient;Iron concentration spatiotemporal distribution prediction is output.The method of the application realizes high-precision prediction of complex pipe network iron concentration and efficient automatic calibration of model parameters.

The invention discloses a high-energy explosive post-explosion combustion energy release dynamics numerical simulation method, and belongs to the field of explosive mechanics and computational fluid mechanics. The method solves the problem that a traditional method is difficult to accurately simulate post-combustion energy release and flow field coupling. According to the scheme, the method comprises the following steps: constructing a two-dimensional reaction flow Navier-Stokes control equation; in closed-loop iteration, adaptively determining a time step length, a fifth-order WENO format discrete space item, a primitive reaction model calculation chemical source item and a third-order Runge-Kutta discrete time item; the JASMIN framework is used for realizing parallel computing; and outputting the space-time energy data. The state equation is closed by a JWL equation (detonation product) and a Stiff-gas equation (air). The method is used for simulating energy release characteristics of high-energy explosives and evaluating damage of supporting weapons.

A sample analysis device includes an acquirer that acquires quantitative measurement information (measurement data) of a plurality of substances including a test substance present in a sample, an estimator that retrieves a reaction model stored in a storage device, models the test substance using the reaction model and provides the quantitative measurement information (measurement data) of the plurality of substances to the reaction model of the test substance to estimate a parameter of the reaction model, and a calculator that calculates quantitative estimation information of the test substance in any period of time or information in regard to a period of time until quantitative estimation information of the test substance reaches a predetermined threshold value, based on the parameter estimated by the estimator.

The invention provides a CAR-T cell therapy toxicity management optimization method and system, and relates to the technical field of artificial intelligence. Clinical data of a hematologic tumor patient receiving a CAR-T cell therapy is acquired; missing value interpolation and standardization processing are carried out on the baseline feature information and the process monitoring data, and a standardized data set is obtained; obtaining a calibrated virtual patient physiological model according to a preset tumor cell kinetic model, an immune cell kinetic model and a toxic reaction model; taking the calibrated virtual patient physiological model as an interaction environment to obtain an associated database; constructing a deep Q network agent with a maximized reward function as a target, and obtaining an optimized deep Q network agent; and inputting the process monitoring data into the optimized deep Q network agent to obtain a target strategy, so that the individualized CAR-T treatment strategy for balancing the curative effect and the toxicity can be automatically output by inputting the real-time monitoring data of the patient.

The present invention provides a polishing apparatus and a polishing method that can obtain a desired film thickness profile. The polishing apparatus includes a polishing unit (14a), a film thickness measurer (8) that measures a film thickness profile of a substrate (W), and a control device (30) that controls at least the operation of the polishing unit and the film thickness measurer. The control device stores in advance a reaction model that is created in consideration of changes in polishing amount among a plurality of monitoring regions of the substrate that are caused by changes in pressure within each pressure chamber (7a to 7h). Further, the control device polishes the substrate using the film thickness measurer to obtain a film thickness profile before polishing of the substrate, and polishes the substrate using an optimal polishing plan that is created based on a difference between the film thickness profile of the substrate before polishing and a target film thickness of the substrate, and the reaction model. The next substrate is polished using a new optimal polishing plan that is created based on a target polishing amount of the next substrate and the reaction model that is corrected using the optimal polishing plan and the film thickness profiles of the previous substrate before and after polishing.