140 results about "Thermodynamic model" patented technology

The invention provides a cold heading steel wire rod rolling temperature closed-loop control method and system based on PID, and relates to the technical field of cold heading steel wire rod rolling process control, and the cold heading steel wire rod rolling temperature closed-loop control method comprises the following steps: determining temperature control parameters of a rolling area of a rolling mill in different rolling stages of a cold heading steel wire rod according to process requirements of the cold heading steel wire rod; constructing dynamic thermodynamic models of different rolling stages; the real-time state data and the real-time temperature data are preprocessed; the extracted temperature control parameters are compared with the preprocessed real-time temperature data; based on the dynamic thermodynamic model and the real-time temperature deviation, the control quantity is calculated through a PID algorithm, and a control instruction is output to an execution mechanism of the rolling mill; and an execution mechanism of the rolling mill receives the instruction and carries out temperature adjustment action. The method can effectively guarantee that the temperature in each rolling stage is stable, the quality consistency of cold heading steel wire rod products is improved, and the dynamic change requirement in the rolling process is met.

The invention discloses a mass concrete temperature control construction method and system based on phase change energy storage, and the method comprises the steps: S100, building a BIM model for a concrete member pouring region according to a design size, setting a temperature sensor in a concrete member to monitor data in real time, and predicting a temperature field in combination with the BIM model; s200, the space between the conventional cooling water pipe and the concrete protection layer is filled with phase change microcapsules in a gradient density mode, a phase change energy storage buffer layer is formed, and transfer of heat to the interior of the concrete member is delayed; s300, according to the predicted temperature field, the water inlet flow and the water temperature are dynamically adjusted, the temperature peak is controlled, and the cooling rate is controlled; s400, fiber grating sensors are arranged at the four corners and the midspan of the concrete member, and the strain change rate is detected; and S500, establishing a digital twin temperature control platform, integrating temperature, humidity and strain data, constructing a three-dimensional thermodynamic model, predicting the temperature rise trend of the concrete member, and performing adaptive regulation and control on the temperature. Temperature difference inside and outside the concrete is controlled through phase change temperature control.

According to the intelligent plunger pump temperature control method and system based on model predictive control, a thermodynamic model predictive control algorithm is introduced, key parameters such as the oil temperature of a plunger pump body, the water temperature of a water tank and the environment temperature are brought into a unified calculation model, and cooperative closed-loop control over a heating plate, a semiconductor chilling plate and a circulating pump is achieved. By constructing the heat balance equation of the lumped heat capacity system and solving the rolling optimization problem in the limited time domain, the heat load change of the plunger pump can be accurately predicted and adjusted in advance, the oil temperature is always stabilized in the preset target interval, and the temperature control precision is remarkably improved; meanwhile, mutual exclusion constraints of heating and refrigerating power are set, and weights are dynamically adjusted and optimized according to working conditions, so that meaningless consumption of energy is effectively avoided, and the operation cost of equipment is reduced; in addition, according to the control method, preheating, cooling and energy-saving modes can be automatically recognized, so that the plunger pump is rapidly started in the severe cold environment and stably operates in the high-temperature environment.

The invention discloses a heating system feedforward control method integrating building thermal inertia and meteorological prediction, which comprises the following steps of: firstly, dynamically identifying building thermal parameters of each room so as to quantify the thermal inertia; then, inputting the parameters and future meteorological prediction data into a feedforward controller; and the controller predicts a room temperature change trend caused by future meteorological disturbance based on a thermodynamic model, calculates a required feedforward compensation control quantity, and adjusts a heating system in advance so as to counteract the disturbance. Through combination of dynamic identification and predictive control, heating control is changed into active intervention from passive response, the problem of control lag caused by thermal inertia is fundamentally solved, the stability and comfort of indoor temperature are remarkably improved, and meanwhile energy waste is avoided through accurate compensation.

The invention discloses a double-layer collaborative energy management and control method and system for a cold plate type liquid cooling data center, and belongs to the technical field of data center energy management. The method comprises the steps that upper-layer day-ahead economic dispatching is based on time-of-use electricity price and outdoor environment temperature prediction, and a server load scheme and a cooling system reference flow track are generated with the minimum total operation cost as the target; in lower-layer intraday dynamic regulation and control, model prediction control is adopted to track the trajectory, the load rate of a server and the rotating speed of a secondary pump are adjusted in real time, and it is ensured that the temperature of a chip is within the safety range of 45-70 DEG C; and the lower layer feeds back the actual chip temperature and energy consumption to the upper layer for online correction of dynamic thermodynamic model parameters to form closed-loop optimization. The system comprises a data acquisition module, a dynamic thermodynamic modeling module, an upper and lower layer optimization control module and an information interaction and feedback module. According to the invention, the overall operation cost and the PUE value of the data center are reduced on the premise of ensuring the temperature safety of the chip.

The invention discloses a turbine generator set power oscillation emergency valve switching control method, system, equipment and medium based on a thermodynamic model, and belongs to the technical field of electric power system automation control and thermal energy power engineering, and the method comprises the steps: monitoring the operation state of a set in real time, and collecting the current data of the set; calculating a theoretical balance valve position required for maintaining the current target power in real time by using the corrected inverse thermodynamic model; and the power fluctuation condition is monitored in real time, when it is detected that power oscillation happens to a unit and valve cutting logic is triggered, the system intercepts a conventional feedback instruction for tracking the actual valve position, the theoretical balance valve position is directly used as a target instruction, and a control valve is forcibly driven to act to the valve position through a rate limiter. According to the method, it can be ensured that after closed-loop control of the unit is cut off, the valve rapidly returns to the physical balance opening degree matched with the current load, an oscillation source is effectively eliminated, severe fluctuation of main steam pressure and temperature is stabilized, and the safety and stability of the unit under the abnormal working condition are remarkably improved.

This application provides a method for coating positioning detection and control of sponge substrate, relating to the field of flexible composite material manufacturing, including the following steps: feeding and conveying the sponge substrate, and controlling the tension and lateral position of the sponge substrate; unwinding the coating material, applying adhesive, and preheating; acquiring the full-field deformation field of the sponge substrate surface through a binocular high-speed vision unit, calculating the strain energy density distribution based on nonlinear strain analysis, and generating a deformation risk digital map with energy release rate characteristics; based on the energy release rate characteristics in the deformation risk digital map, calculating control parameters through a dynamic thermodynamic model, and performing local thermal adaptation control of the coating material to match the energy field; aligning and pressing the coating material, which has undergone local thermal adaptation control to match the energy field, with the sponge substrate; and curing and quality verification of the pressed composite material.

The invention provides a Nusselt number experimental calculation method for a special flow channel structure, which comprises the following steps: determining structural parameters and basic input parameters of the special flow channel structure PCHE, and constructing a thermodynamic model of the special flow channel structure PCHE; based on a thermodynamic model, obtaining a total heat transfer coefficient and total heat transfer resistance through a thermal resistance method, and then determining an undetermined coefficient; a heat exchange experiment between the first working media is carried out, nonlinear regression fitting is carried out on the undetermined coefficient through an intelligent algorithm, and a first Nusselt number is obtained; and carrying out a heat exchange experiment between the first working medium and the second working medium, and carrying out nonlinear regression fitting on the undetermined coefficient by using the same intelligent algorithm in combination with the first Nusselt number to obtain a second Nusselt number. According to the method, step-by-step nonlinear regression is carried out on the undetermined coefficient in the thermal resistance model through two groups of heat exchange experiments in combination with an intelligent algorithm, so that the accuracy of measuring the wall temperature is improved, and the fitting precision of the Nusselt number is improved.

The application discloses a heating furnace control method, device, equipment and storage medium for delayed coking, and the method comprises the following steps: generating a three-dimensional thermodynamic model of the heating furnace and performing gridding according to heating furnace modeling; obtaining simulation results of the three-dimensional thermodynamic model according to preset input parameters; judging whether the outlet cross-section position of the heating furnace includes a grid exceeding a preset target temperature range, if yes, updating the heat source power and returning to the simulation result calculation step; if no and the current judgment is the first judgment, updating the feeding rate and returning to the simulation result calculation step; if no and the current judgment is not the first judgment, going to the next step; judging whether the heating furnace includes a grid exceeding the preset upper limit of free state coke content, if yes, updating the heat source power and the feeding rate and returning to the simulation result calculation step; if no, generating a control instruction according to the current heat source power and the feeding rate. The application can fully exert the production efficiency of the heating furnace.

The invention provides a ship energy consumption prediction method, device and equipment based on digital twinning and a medium, and belongs to the field of ship intelligent energy consumption management.The method comprises the steps that on the basis of a preprocessed real ship data set, a corresponding multi-physics field coupling digital twinning body is driven to operate, and real-time physics field distribution data is obtained; determining a real-time total energy consumption initial value through a thermodynamic model; calculating a deviation field between the real-time physical field and the reference physical field to generate energy consumption deviation data, positioning abnormal key parts of the ship power system, and analyzing energy consumption contribution degree factors of the abnormal key parts; and combining the real-time total energy consumption initial value with the component energy consumption influence quantity to generate an energy consumption prediction result. The method can accurately predict the ship energy consumption and trace the source of energy consumption abnormity, improves the energy consumption management precision, and effectively supports the predictive maintenance of the ship.

The application relates to the technical field of air purification, and discloses a negative ion purifier ion yield drift self-calibration control method and system, which comprises the following steps: obtaining the cumulative running time of an air pump to determine a mechanical fatigue reference drift amount; constructing a theoretical evaporation model to solve a theoretical water evaporation rate and a theoretical conductivity reference slope; comparing the actual conductivity change slope to obtain a deviation index, on the basis of which water quality state binary determination is performed, and a water quality damping drift amount is generated; superimposing the mechanical fatigue reference drift amount and the water quality damping drift amount to obtain a total performance drift amount, generating a target driving instruction, and performing clamping output in combination with a running envelope; the application effectively eliminates the conductivity false high interference caused by natural evaporation through a thermodynamic model, realizes layered and accurate compensation of hardware aging and water pollution, maintains the constant ion yield, and avoids the overcompensation and air pump dry burning risk caused by misjudgment.

The invention discloses an energy room environment intelligent control method and system based on renewable energy fluctuation, and relates to the technical field of building energy intelligent management, and the method comprises the steps: collecting the real-time operation data of an energy room, initializing the environment memory and the energy memory, and storing the environment memory and the energy memory; combining external weather prediction and a thermodynamic model to generate an energy demand prediction quantity under a comfortable condition; comparing the energy demand predicted quantity with the real-time power, and calculating to obtain a cheap energy index representing the renewable energy remaining degree; a virtual price curve is constructed by combining environment memory and energy memory, and channel weight distribution of an execution layer is generated; under the constraint of the virtual price curve and the channel weight, a joint optimization problem is established in combination with a thermodynamic model, a control instruction is solved and obtained, execution feedback is written back to environment memory and energy memory, and a self-adaptive closed loop is formed; the indoor comfort and the energy economy can be kept under the fluctuation condition, and the utilization rate of renewable energy sources and the stability of system operation are improved.

The invention provides an unmanned aerial vehicle routing inspection power equipment path planning method, and belongs to the technical field of industrial visual intelligence, and the method comprises the following steps: selecting at least one power equipment part as a routing inspection target, and obtaining basic potential field map data including at least one routing inspection target gravitational field and at least one obstacle repulsion field; acquiring infrared thermal image data of the power equipment component, and calculating to obtain temperature deviation data representing the current thermodynamic state of the power equipment component in combination with the theoretical thermodynamic model; performing time sequence analysis on the current temperature deviation data and the temperature deviation historical storage data to generate a thermodynamic degradation rate index; dynamically correcting the basic potential field map data based on the temperature deviation data and the thermodynamic degradation rate index, and generating a prognosis potential field indication signal according to the corrected basic potential field map data; and calculating and controlling the flight path of the unmanned aerial vehicle in real time according to the prognosis potential field indication signal, and executing an inspection task by the unmanned aerial vehicle according to the flight path of the unmanned aerial vehicle.

The invention relates to the technical field of energy efficiency data acquisition and analysis oriented to factory management, in particular to an intelligent factory standardized production line energy efficiency data acquisition and analysis method and system, and the method comprises the following steps: a multi-source data perception interaction module captures a component pose and thermal parameters to construct a data set; the thermal energy efficiency dynamic analysis module calculates thermal demand and energy supply deviation based on a process stage; the logistics transmission power consumption evaluation module constructs a damping loss model and distinguishes effective work and abnormal loss, and the global energy efficiency optimization decision-making module executes an adaptive weighted fusion algorithm, solves an optimal working point and generates a closed-loop feedback energy-saving regulation and control strategy. The energy flow relation of production nodes is analyzed in real time through a high-frequency sensor and a dynamic thermodynamic model, hidden energy waste points are accurately positioned, process-level standardized energy efficiency indexes are formed, and energy consumption optimization, abnormity tracing and production line energy utilization rate improvement are achieved.

The application discloses a kind of automobile high-low pressure EGR control method, system, vehicle and storage medium, the method includes, establishing and according to the engine thermodynamic model selects engine simulation operating condition;Formulate high-low pressure EGR control strategy of external characteristic and formulate partial load high-low pressure EGR control strategy, and the external characteristic high-low pressure EGR control strategy and formulate partial load high-low pressure EGR control strategy are input into the engine thermodynamic model to obtain a plurality of first simulation parameters and second simulation parameters, to evaluate whether the external characteristic high-low pressure EGR control strategy and formulate partial load high-low pressure EGR control strategy are qualified according to the plurality of first simulation parameters and plurality of second simulation parameters;By selecting multiple target operating conditions, the entire engine universal characteristic region is covered, so that the reliability and accuracy of the external characteristic high-low pressure EGR control strategy and formulate partial load high-low pressure EGR control strategy increase.

This invention discloses a smart building energy consumption optimization and comfort control system based on BIM-IoT integration, comprising: a BIM-IoT integrated digital twin module; a load prediction module based on a thermodynamic model; a multi-system collaborative optimization control module; and an equipment fault diagnosis module. By constructing a building digital twin model and integrating BIM static parameters and IoT dynamic data, this invention achieves accurate prediction of building heat load, multi-system collaborative optimization control, and intelligent balance between energy consumption and comfort, thereby significantly reducing building operating energy consumption and improving user experience.

The present application belongs to the field of chemical thermodynamics, and particularly relates to a thermodynamic model for predicting the thermodynamic properties of a salt-solvent system. The model first obtains the coordination number n of cations and anions in the salt-solvent system through molecular dynamics simulation, then obtains the initial configuration of the cation-n solvent molecule-anion through configuration optimization, and obtains the most stable structure through quantum chemistry calculation program optimization, and finally obtains the VLE (vapor-liquid equilibrium) data prediction value of the salt-solvent system based on the COSMO-RS theory. The model can obtain the prediction value with high accuracy without experiment, thereby saving a large amount of manpower, material resources and financial resources. Meanwhile, the present application also discloses the phenomenon that the salt in the salt-solvent system is volatile.

This invention discloses a method, apparatus, equipment, and medium for predicting the dew point pressure of condensate gas. The method includes: inputting basic data of a condensate gas sample and initializing the dew point pressure value; using the 4CM splitting method to split and characterize the C7+ component in the condensate gas; estimating the gas-liquid phase equilibrium constant and the mole fraction of each component in the liquid phase based on the mole fraction of each component after splitting; calculating the gas-liquid phase compressibility factor using the improved equation of state (MPR) based on the gas-liquid phase equilibrium constant, the mole fraction of each component in the liquid phase, and the relevant data after characterization; determining whether the absolute value of the difference between the gas and liquid phase fugacity satisfies the equilibrium condition and whether the sum of the mole fractions of each component in the liquid phase satisfies the preset convergence condition; and finally outputting the calculated dew point pressure. This invention utilizes an integrated and innovative method for thermodynamic model construction, resulting in high accuracy and low calculation error in predicting the dew point pressure of condensate gas.

A method and related apparatus for determining the oil column height in carbonate fault-controlled reservoirs include: collecting temperature and geological data from wells in the carbonate fault-controlled reservoir to obtain static temperature test data at the initial production stage and flow temperature test data for the scheduled production date; establishing a coupled thermodynamic physical model of the wellbore and reservoir in the fault-controlled reservoir; establishing a wellbore temperature distribution model using energy conservation, and calculating the bottom hole temperature from the wellhead temperature; then establishing a one-dimensional vertical thermodynamic model of the reservoir, and iteratively calculating the height from the bottom of the well to the bottom of the reservoir; adding the calculated height to the height of the drilling and development formations to obtain the oil column height in the carbonate fault-controlled reservoir. This invention, based on a coupled thermodynamic model of the wellbore and reservoir, determines a method suitable for calculating the oil column height in carbonate fault-controlled reservoirs. It can directly calculate the oil column height of fault-controlled reservoirs using wellhead temperature data, solving the problem of large calculation errors in conventional static description methods.

The invention discloses a building environment self-adaptive regulation and control method and system based on a space-time attention mechanism, and the method comprises the steps: collecting environment data, such as temperature, flow density, humidity and air pressure, and constructing a three-dimensional thermodynamic model through a dynamic weighted Bayesian collaborative fusion algorithm; the method comprises the following steps: processing environment data by virtue of a space-time cross attention network, and generating a regulation and control priority map with a dynamic space-time weight through operations of dynamic multi-feature embedding, parallel space-time self-attention, cross attention fusion and the like; and the fuzzy-PMV decision engine fuzzifies the atlas and PMV comfort indexes, outputs an equipment regulation and control instruction set through expert rule matching and defuzzification, and realizes closed-loop control from environmental data to equipment actions. Compared with the prior art, the method can accurately analyze the space-time correlation of building environment parameters, adaptively regulate and control equipment, improve the environment comfort and regulation and control efficiency, has the advantages of energy conservation and intelligence, and is suitable for the field of intelligent building environment control.

This application provides a flushing and cooling method, system, and device with automatic route identification. The method includes: constructing a device model through three-dimensional laser scanning and obtaining the surface thermal conductivity using material identification technology; generating a temperature gradient and heat load distribution map using multi-sensor data fusion; analyzing heat dissipation requirements and determining flushing priorities based on a thermodynamic model; optimizing the flushing path and sequence using a dynamic programming algorithm; and adaptively adjusting the pressure, flow rate, and time parameters at each flushing point according to the heat load distribution to form a personalized flushing plan. During execution, temperature changes are monitored in real time, and parameters are dynamically adjusted to ensure cooling efficiency. This method achieves intelligent identification of the thermal state of the equipment surface, automatic planning of the flushing path, and precise control of flushing parameters, significantly improving the accuracy and efficiency of flushing and cooling, and is suitable for efficient heat dissipation maintenance of industrial equipment.

The invention discloses an AI-based information security risk early warning system, and relates to the technical field of network security. The system extracts transmission layer features for the encrypted traffic through an entropy feature quantization unit and generates an entropy turbulence index; calculating, by a state scheduling unit, a resident energy value of the network connection based on a nonlinear thermodynamic model; executing serialized replacement and wake-up operation between the dynamic random access memory and the nonvolatile solid state disk through the hierarchical storage management unit, and executing space-time folding to eliminate a physical time interval; and finally, performing Granger causal verification on the spliced discontinuous historical state sequence through a discontinuous causal verification unit. The technical problem that continuous state tracking cannot be carried out on hidden attack behaviors crossing a long period under the hardware condition that gateway equipment memory resources are limited is solved, high-speed small-capacity memory resources are replaced with a low-speed large-capacity storage medium, and risk early warning is achieved on the premise that context logic integrity is guaranteed.

The invention relates to a user-side load-oriented optimal scheduling method, which belongs to the technical field of energy scheduling and intelligent power grids, and comprises the following steps of: constructing a household micro-grid model containing electric equipment and HVAC, establishing an HVAC thermodynamic model based on building heat balance, describing room temperature change in combination with meteorological and building parameters, and establishing an HVAC thermodynamic model based on the HVAC thermodynamic model. Classification modeling of the rigid load and the flexible load is completed; a multi-objective optimization framework with thermal comfort, power consumption behavior deviation and economy as objectives is constructed, human body thermal perception is quantified by adopting a PMV index based on a Fanger model, and dynamic coupling of scheduling and comfort is realized; hVAC scheduling is modeled as MDP, and double TD3 is introduced to realize continuous power and mode control; an integer programming model is constructed for a flexible uninterrupted load, and a starting time slot is optimized through a rolling time domain strategy, so that overall load coordinated scheduling is realized. According to the invention, the resource utilization efficiency and the load scheduling flexibility of the household micro-grid are obviously improved.

The invention discloses a fuel gas component correction method and system, a storage medium and electronic equipment, and relates to the technical field of gas turbine measurement and control. The method specifically comprises the steps that two fuel flows of a thermodynamic model and a physical model are calculated in parallel, and the difference value is obtained; reversely deducing fuel calorific value and component change according to the difference value signal to finish online calibration of a fuel relative component model; switching the industrial gas chromatograph to an on-demand standby mode based on the calibration result; the flow difference is converged to zero through iterative calculation, and model self-calibration is achieved; and finally, carrying out performance calculation and self-adaptive regulation and control based on a convergence result. According to the scheme, the problems of high cost and response lag caused by dependence on continuous chromatographic analysis in the prior art are solved, online real-time correction is realized, the operation cost is remarkably reduced, and the self-adaptive capacity and the operation economy of the system to fuel change are improved.

The invention relates to a method for optimizing a procedure for triggering an offline washing of a compressor in a turbine-compressor assembly, the method comprising: - measuring (110) the compressor inlet temperature and the compressor inlet pressure; - receiving (120) a first measured value corresponding to the compressor inlet temperature, and a second measured value corresponding to the compressor inlet pressure; - calculating (121) the compressor isentropic efficiency from the first and second measured values, using a predefined thermodynamic model; - predicting (122) the compressor isentropic efficiency from the first and second measured values, using a predefined mathematical model; - calculating (124) the real time difference between the calculated compressor isentropic efficiency and the predicted compressor isentropic efficiency; - based on the calculated real time difference, providing (128, 130, 132A, 134, 136, 138A, 140, 142A, 142B) at least one decision indicator as to whether or not a compressor offline washing is necessary.

The application discloses an online detection method and system for atmospheric aerosol acidity, and belongs to the field of atmospheric pollutant detection, and comprises the following steps: acquiring aerosol data and meteorological data of an atmospheric observation station, and pre-processing the acquired data; adopting a Metastable-Forward mode thermodynamic model ISORROPIA II to calculate the pre-processed data, so as to obtain a theoretical value pH of aerosol acidity; taking preset measurement parameters as characteristic variables and taking the theoretical value pH of aerosol acidity as a target variable, a plurality of machine learning models are constructed, cross validation is carried out, and the machine learning model with the optimal performance is selected; adopting mass spectrum analysis to acquire real-time aerosol component data and current meteorological data, and utilizing the optimal machine learning model, real-time atmospheric aerosol acidity is calculated. In view of the poor real-time performance of the atmospheric aerosol acidity detection by physical sampling, the application combines a thermodynamic model and machine learning, and does not need to replace detection consumables, so that the real-time performance is improved.

The invention relates to the technical field of thermodynamic system design, in particular to a multi-configuration thermodynamic system comprehensive design method and device and a storage medium, and the method comprises the steps: setting boundary parameters of a thermodynamic system, and setting structural parameters of the thermodynamic system and variable initial values of the thermodynamic parameters; establishing a thermodynamic model through a thermodynamic static simulation tool, and performing static simulation on the thermodynamic system; collecting feasible result data meeting a thermodynamic system operation mechanism as a debugging data set; carrying out equipment structure design through an equipment structure design tool; carrying out dynamic simulation on the thermodynamic system through a thermodynamic dynamic simulation tool and calculating a flexibility index of the thermodynamic system; calculating an economic index of the thermodynamic system through a cost estimation tool; and performing single-objective optimization or multi-objective optimization on the thermodynamic system through a data analysis processing tool, and updating the structural parameters and thermodynamic parameters of the thermodynamic system until various index requirements are met. According to the method, flexible, comprehensive and easy-to-use thermodynamic system comprehensive design can be realized.

The invention relates to the technical field of air purification, and discloses a negative ion purifier ion yield drift self-calibration control method and system, and the method comprises the steps: obtaining the accumulated operation time of an air pump to determine a mechanical fatigue reference drift amount; constructing a theoretical evaporation model to solve a theoretical moisture evaporation rate and a theoretical conductivity reference slope, comparing the theoretical moisture evaporation rate and the theoretical conductivity reference slope with an actual conductivity change slope to obtain a deviation index, executing water quality state binary judgment according to the deviation index, and generating a water quality damping drift amount; superposing the mechanical fatigue reference drift distance and the water quality damping drift distance to obtain a total performance drift distance, generating a target driving instruction, and combining the target driving instruction with the operation envelope to execute clamping output; according to the method, conductivity virtual high interference caused by natural evaporation is effectively eliminated through the thermodynamic model, layered accurate compensation of hardware aging and water quality pollution is achieved, and the risk of excessive compensation and air pump dry burning caused by misjudgment is avoided while the constant ion yield is maintained.

The invention relates to the technical field of mineral resource development, and discloses a deep solid resource fluidization mining-based dynamic simulation method and system, and the method comprises the following steps: S1, constructing a deep geology and resource occurrence digital model, integrating the geological information and resource characteristic information of a target mining region, and constructing a deep geology and resource occurrence digital model; establishing a three-dimensional geology-resource occurrence digital twinborn model; and S2, defining a fluidized conversion reaction model, determining an in-situ conversion path for a target solid resource based on the digital twinborn model, and establishing a corresponding chemical reaction kinetic model, a thermodynamic model and a phase change model. According to the fluidized mining dynamic simulation method based on the deep solid resources, a dynamic simulation method and system specially aiming at a brand new mode of in-situ fluidized mining of the deep solid resources are provided and constructed, and the blank of digital simulation tools in the field is filled; and meanwhile, full-chain and multi-physical field coupling simulation from microscopic chemical reaction to macroscopic system integration is realized.

The invention relates to the technical field of mine tunneling, in particular to a function decoupling regulation and control system and method for the hot and humid environment of a deep mine TBM tunneling face. According to the method, multi-source environment parameters are obtained, the hot and humid state and air quality data are generated through fusion processing, and the current hot and humid grade and the oxygen demand are recognized; outputting an environment grade result and an oxygen supply demand signal; and constructing an oxygen supply-cooling-environment coupling thermodynamic model, and estimating the functional coupling degree of the two systems in a future time period in combination with a dynamic prediction method. The self-adaptive decoupling controller is used for dynamically optimizing energy consumption distribution of the oxygen supply and cooling system according to a prediction result, regulation and control parameters are generated, control signals of oxygen supply equipment and cooling equipment are output according to the regulation and control parameters, and dynamic decoupling of the oxygen supply and cooling functions is achieved. The problems of response lag, too high energy consumption and control conflict caused by system coupling in traditional control are solved, and the accuracy, energy efficiency and stability of tunneling face environment regulation and control in the deep high-temperature and high-humidity environment are improved.