48 results about "Entropy production" patented technology

The invention provides an intelligent adjustment method for distributed air treatment equipment, and belongs to the technical field of air treatment equipment, and the method comprises the steps: inputting a personnel distribution image into an airflow field reconstruction model based on a graph neural network, outputting three-dimensional space flow field distribution data, calculating a personnel intensity index, and predicting an average thermal sensation index value; an air supply adjustment double-layer game model is established based on the data, the air supply angle and the air supply speed of an electric side supply nozzle and the air supply quantity of a lower air supply outlet are solved, an actuator is controlled to adjust air supply parameters, and the target air outlet temperature and the refrigerant flow of the heat exchanger are calculated through a thermodynamic entropy production minimization heat exchange optimization algorithm; and feedback correction is performed according to the actually predicted average thermal sensation index deviation to form closed-loop control, so that the technical problem that the distributed air treatment equipment is difficult to adjust the air supply parameters in real time according to the personnel distribution dynamic change so as to ensure the thermal comfort and the energy efficiency at the same time is solved.

The invention provides an optimized design method for an impact type rotating wheel bucket blade structure based on entropy production analysis. The method comprises the following steps: firstly, generating a sample space through parametric modeling and optimal Latin hypercube experimental design of a rotating wheel; then, acquiring internal flow field data through numerical simulation; identifying a key loss area based on entropy yield flow loss; then, a Gaussian process regression agent model is constructed by taking the geometric dimension parameters of the bucket blade as input and hydraulic efficiency and entropy production as output, multi-objective optimization is carried out by adopting an improved NSGA-II algorithm, and the accuracy of the agent model is improved through a dynamic updating strategy; and finally, carrying out numerical simulation verification on the Pareto optimal solution, and screening out a runner design scheme with excellent comprehensive performance. The flow loss can be effectively reduced, the hydraulic efficiency and the operation stability of the impact type runner are improved, and technical support is provided for optimization of the hydraulic performance of the impact type runner.

The invention belongs to the technical field of thermal management and performance regulation and control of a computer hardware system, and particularly discloses a temperature and performance coordinated regulation and control method of an MODT mainboard central processing unit. The entropy production rate of the system is calculated in real time in combination with a thermodynamic entropy production evaluation mechanism, and pre-cooling or advanced frequency reduction pulse type regulation and control are triggered when entropy production exceeds the threshold; meanwhile, a biological rhythm simulation mechanism is introduced, high-frequency and low-frequency alternating periodic oscillation control is carried out on the frequency of the processor in a millisecond-level window, the two mechanisms cooperatively act on the power management unit, and microsecond-level voltage regulation and heat dissipation driving linkage is achieved. According to the technical scheme, on the premise that the hardware cost is not increased, the energy efficiency performance, the transient heat dissipation capacity and the long-term operation reliability of the system under the high dynamic load are improved.

The application provides a multi-stage heat release regulation optimization method and system based on steam extraction energy storage, relates to the technical field of heat regulation, and comprises the following steps: a dynamic thermodynamic model of a heat release process of a steam extraction energy storage system is established, which comprises multiple state variables of heat release power, heat release time, heat release efficiency and temperature change of a heat storage water tank; a multi-objective optimization model is established by taking the minimization of total energy consumption of the system and the minimization of entropy production of a heat exchanger as optimization objectives and combining the constraint conditions corresponding to the optimization variables; a hybrid optimization strategy combining an improved non-dominated sorting genetic algorithm and a multi-objective particle swarm optimization algorithm is used to solve the multi-objective optimization model, so as to determine an optimal regulation strategy set of the multi-stage heat release process of the steam extraction energy storage system; and the valve opening of a steam extraction motor-driven regulating valve and the feed water flow of a steam extraction temperature and pressure reducing device are controlled through a steam extraction energy storage control system, so as to realize the optimal regulation of steam extraction parameters, and the rotation speed of a cold source side water supply and return pump is controlled, so as to realize the optimal matching of water supply and return parameters.

A living-physics measurement and control system integrates a sensor array, analog front-end, controller module, and feedback actuator network to enable real-time quantification and modulation of energetic organization in open systems. The sensor array comprises thermal, mechanical / vibration, electrical / ionic, and optical sensors, providing multimodal data to the firmware and signal-processing unit. The controller module executes a coherence and entropy feedback control method, which includes system calibration, acquisition of synchronized sensor data, computation of order metrics such as coherence, entropy production, and information flux, and evaluation of energetic organization state. The feedback actuator network, including thermal actuators, mechanical actuators, ionic pumps, and optical emitters, receives actuator command set to dynamically adjust energy flow. The system generates quantitative metrics linking coherence, entropy, and information flow, enabling adaptive feedback to preserve or optimize functional order. The invention addresses the lack of integrated instrumentation and feedback for self-organizing, regenerative stability in open systems.

The application relates to the field of energy management, and discloses an energy consumption management optimization method and system of a comprehensive energy station, which are used for improving the economic optimization ability and the autonomous collaborative operation level of the comprehensive energy station when facing complex uncertainty. The energy consumption management optimization method of the comprehensive energy station comprises the following steps: constructing a device characteristic model representing long memory dynamics of a device based on a fractional calculus theory; establishing a random scene based on an alpha-stable distribution theory, which describes non-Gaussian fluctuations of wind and light loads; constructing an economic cost density field representing energy quality space-time dissipation based on a local entropy production minimization principle; establishing a differential game framework taking the economic cost field as a target and the above model as a constraint; and finally realizing closed-loop optimization through rolling execution and model online correction. The application breaks away from the dependence on a machine learning model, and realizes the economic efficiency optimization and autonomous collaborative operation of the energy station under complex uncertainty from the physical mechanism.

The application discloses a strain-induced supersaturated solid solution analysis method for a non-miscible alloy system based on mixed entropy evolution, and the method comprises the following steps: for a target A-B binary alloy, a mixed entropy-component relationship diagram of the target A-B binary alloy is drawn; the average component and the initial equilibrium phase component point of the target A-B binary alloy are calibrated in the diagram; based on the increase of the mixed degree of the entropy generation driving force, the two-phase components are predicted to evolve in the entropy increase direction during a severe plastic deformation process, until a single-phase supersaturated solid solution is formed. Based on the irreversible thermodynamic principle, the severe plastic deformation process is defined as a continuous external entropy generation source for driving the evolution of the system, through the analysis of the dynamic competition mechanism of element mixing and element demixing dominated by the entropy generation source, the formation mechanism of the supersaturated solid solution is revealed, and the application provides a universal theoretical tool for understanding and predicting the supersaturated solid solution behavior of the non-miscible alloy system under the severe plastic deformation.

The application relates to the field of anomaly detection, and discloses a high-pressure valve flow capacity anomaly detection and strength failure early warning system, which is used for accurately evaluating the thermodynamic and kinetic states of a valve. The system comprises the following steps: obtaining original parameters by synchronously measuring the fluid pressure, temperature, mass flow and valve body vibration acceleration of the inlet and outlet of the valve; calculating an entropy production health index for representing the abnormal degree of energy dissipation in the valve; simultaneously calculating a chaos index for representing the instability degree of the structure kinetic state; nonlinearly fusing the two indexes to generate a composite health index with higher sensitivity and an evolution track of the composite health index; constructing a random dynamic system evolution model based on the track; and projecting to obtain the failure probability of the future state of the valve. The application avoids relying on historical fault data and machine learning models, realizes deep measurement, accurate testing and intuitive indication of the health state of the high-pressure valve through chain processing driven by physical mechanism.

The invention belongs to the technical field of machine learning, and particularly relates to an emulsifier production process temperature control method and system based on machine learning, and the method comprises the steps: obtaining the operation data of an emulsification kettle, and removing the no-load loss to construct a shearing power density sequence; obtaining an embedded vector representing viscosity and heat retardation through the rheological state mapping network; the embedded vector is injected into a gate control circulation unit updating gate, and a temperature prediction sequence is output; calculating a consistency index based on the thermodynamic entropy yield, and combining sensible heat temperature rise power residual error to construct a correction term to rectify the prediction sequence; and inputting the consistency temperature into a model prediction controller to generate a valve instruction. According to the method, deep learning is constrained through a physical mechanism, and the problems of temperature control lag and overshoot of the non-Newtonian fluid caused by shear heat are solved.

The application relates to the field of intelligent control of heat exchangers, and discloses a heat exchanger heat distribution control method based on multi-target optimization, which collects operation data under multiple working conditions and carries out labeling; nonlinear decoupling mapping of heat exchanger multi-working condition thermodynamic parameters and low-dimensional working condition feature extraction; flow distribution multi-target optimization based on double pheromone cooperation and thermodynamic constraint projection; online decision and valve opening degree instruction dynamic smoothing mapping based on variable weight target heart closeness; heat distribution closed-loop control based on variable weight decision and valve dynamic smoothing mapping. The application has the beneficial effect that the sensitivity of entropy production rate to each operation parameter is used as physical guiding information to reweight the original operation state vector in the sense of thermodynamics, so that the subsequent low-dimensional feature extraction and optimization process preferentially pays attention to key variables that truly affect irreversible loss, instead of simply relying on numerical compression.

The application discloses a liquid-cooled battery energy storage cabinet thermal management method and system, relates to the technical field of energy storage cabinet thermal management, and comprises the following steps: collecting basic operation data, calculating the actual heat dissipation amount and real-time heating power of each branch, and calculating the rotating speed adjustment amount according to the total heat dissipation deviation; calculating the local entropy production rate and the global total entropy production rate of each branch, and determining the ideal flow velocity distribution that minimizes the global total entropy production rate; calculating the heat balance deviation, and when the heat balance deviation is within the optimal interval range, it indicates that the heat dissipation is accurate, and an operation state report is output; based on the total heat dissipation deviation, the dynamic supply-demand matching of the total heat dissipation and the total heating is realized, the overcooling or overheating is effectively avoided, and the circulating pump energy consumption is significantly reduced; for the blockage fault, the precise positioning is realized by using the space-time correlation of the temperature field, the fault propagation directed graph is constructed by means of the transfer entropy causal analysis and the active blocking strategy is executed, the hierarchical de-rating instruction is output according to the heat dissipation capacity loss rate, and the reliability and fault tolerance capability of the energy storage cabinet are significantly improved.

The present application relates to the field of fluid machinery, and particularly to a water ring vacuum pump impeller and shell line collaborative design method. The method comprises the following steps: impeller and shell line segmentation and control variable setting, based on impeller parameters and four-section shell control parameters to carry out six-factor collaborative design experiment, and using Latin hypercube sampling to obtain sample library; for each group of impeller and shell line control variable combination, using Bezier curve to generate impeller line, and using DFFD method to obtain shell line; for each group of impeller line and shell line, establishing a calculation domain model, using VOF two-phase flow model to carry out CFD calculation, and loading UDF program to calculate wall effect entropy production after the flow field tends to be stable; based on the sample library, constructing a mixed approximation model of wall effect entropy production; under the condition of keeping the rated working condition, using particle swarm optimization algorithm to optimize the impeller and shell line, so as to reduce the wall effect entropy production.

The invention discloses an electric spindle structure with a directional heat conduction function and a design method of the electric spindle structure. A plurality of heat pipes are embedded in a front bearing area and a rear bearing area of an electric spindle shell to reduce axial heat transfer heat resistance, and a high-heat-conduction material component is arranged on a rotating shaft to enhance conduction of heat to bearings; and a jet cooling local heat sink structure is arranged at the end part of the rotating shaft so as to directly and quickly dissipate heat. The corresponding design method comprises the steps that a key area with limited heat flow transfer in the motorized spindle is identified through entropy production sensitivity analysis, heat conduction path optimization design is conducted on the area on the premise that the original structural form of the motorized spindle is not changed, and the local heat transfer capacity is enhanced by means of a heat pipe, a high-heat-conduction material, jet cooling and the like. Heat generated in the motorized spindle is efficiently guided to heat sink areas such as a machine shell cooling water jacket along a preset path, temperature field distribution in the motorized spindle is improved, the temperature gradient and the hot-spot temperature of the motorized spindle are reduced, thermal deformation is reduced, and the running precision and stability of the motorized spindle are improved.

The invention discloses an air-supplementing enthalpy-increasing heat pump system, and relates to the technical field of heat pump systems. An outlet of a compressor is sequentially connected with a condenser, a first expansion valve and an evaporator. The system is further provided with an air supply branch, the inlet end of the air supply branch is connected with a pipeline between the condenser and the first expansion valve, the outlet end of the air supply branch is connected with a middle air supply port of the compressor, and the second expansion valve is arranged at the inlet end of the air supply branch. The entropy production multi-objective optimization method comprises the following steps: 1, building a test bed, and collecting thermodynamic parameters; 2, establishing and correcting a system entropy production and performance coefficient calculation model; 3, determining a control variable and a security constraint; 4, carrying out data normalization processing, and constructing a comprehensive evaluation function; 5, performing iterative optimization, and outputting a Pareto optimal leading edge; and 6, screening control parameters, and verifying adaptability. According to the method, a comprehensive optimization index combining multi-process entropy production and COP is constructed, so that the system runs in an area with the highest performance coefficient and the lowest total entropy production in the compression process while avoiding liquid impact and overheating risks.

The application relates to the technical field of fault prediction, in particular to an aero-engine key component repair effect and residual life prediction system based on digital twinning, which comprises a repair component digital twinning modeling module, which is used for collecting geometric point cloud data of repaired blades and coatings of an aero-engine, generating a repair area multi-physical field boundary condition, driving finite element grids to perform thermal force coupling iterative calculation according to the repair area multi-physical field boundary condition, and constructing an engine repair component digital twinning body. In the application, the total amount of local cumulative entropy production is compared with a fracture threshold value, and a compatibility evolution trend is combined to double-lock a fault critical point from two dimensions of material body failure and structural interface debonding, so that a prediction result containing a repair effect grade and a residual life cycle is output without a large number of historical sample training, and the reliability of service evaluation of aero-engine remanufactured components is improved.

The invention discloses an air-cooled turbine efficiency correction method considering cold air temperature ratio change, which comprises the following steps: implementing a reference test with the total temperature ratio of 1 to obtain reference efficiency; an actual low-temperature test with the total temperature ratio being equal is implemented, and efficiency is obtained; a non-isothermal heat transfer entropy production calculation model is constructed, and cold air and mainstream mixing entropy production when the total temperature ratio is YES and cold air and mainstream mixing entropy production when the total temperature ratio is YES under the actual working condition are calculated; and calculating to obtain the correction efficiency when the total temperature ratio of the actual working condition is when. The entropy production theory is innovatively introduced to construct the correction model, and the defects that an existing method is weak in theoretical basis and incomplete in loss consideration are thoroughly overcome; extreme low-temperature test conditions are not needed, the equipment cost and the safety risk are greatly reduced, and the engineering feasibility and economical efficiency are improved.

The invention discloses a CW type heat exchanger performance optimization method based on a PINN and a functional variation method, and relates to a CW type heat exchanger performance optimization method. The problem that in existing engineering, heat exchanger design is low in working efficiency is solved. The method comprises the steps that geometric shape parameters of the CW type heat exchanger are determined, flow direction conditions and channels of fuel gas and cooling gas are determined according to the geometric shape parameters, and a flow field grid is drawn; determining a basic equation describing the physical model, constructing a functional equation set corresponding to the basic equation based on a variational method, and determining a weight coefficient of an entropy production item according to an application demand; integrating a temperature inversion equation with a negative diffusion coefficient into the physical information neural network, and solving a conservation equation by using a CFD method; and the CFD solver extracts inverse temperature field information from a neural network calculation result and transmits temperature, pressure and speed physical field information to the PINN solver, so that a coupling calculation method of the CFD solver and the PINN solver is realized. The invention belongs to the technical field of heat exchange device performance optimization.

The invention discloses a tool and a method for measuring the crimping size of a ground wire hydraulic connecting pipe fitting. The method comprises the following steps: S1, initializing a measurement basis and synchronizing with a data stream; s2, extracting a slice sequence based on curvature topology; s3, defect factor calculation based on dynamics; s4, drifting correction prediction based on thermodynamics; s5, true value inversion reconstruction under multiple physical constraints is carried out; s6, holographic quality portrait generation and dispose.According to the method, random discretization is solved based on curvature locking slicing, the rheological topological structure of the surface of the pipe fitting can be accurately recognized by introducing the Gaussian curvature tensor analysis technology, and a rheological consistency area is adaptively locked for phase locking slicing; the method comprises the following steps: analyzing perspective microscopic hidden defects through a dynamic spectrum, mapping a crimping process into a high-dimensional state track by utilizing a nonlinear dynamic phase-space reconstruction and wavelet stiffness spectrum analysis technology, and sensitively capturing microsecond-level stiffness singular mutation points; and a time-delay drift error is eliminated through an entropy generation inversion truth value.

The invention provides a thermodynamic system regulation and control system and method based on real-time entropy production feedback and electronic equipment. Comprising a multi-source sensing and entropy production calculation terminal, a dynamic regulation and control quantity generation module and an execution module, and the real-time entropy production rate of each target subsystem is determined through multi-dimensional physical field data, collected in real time, of each target subsystem in the thermodynamic system; according to the preset target entropy yield of each target subsystem and the real-time entropy yield of each target subsystem, the entropy production change rate and the accumulated entropy production deviation of each target subsystem are determined through a differential link and an integral link in an adaptive gain PID control method; and obtaining the real-time regulation and control quantity of each target subsystem, dynamically adjusting the actuator parameters of each target subsystem according to the real-time regulation and control quantity of each target subsystem, and driving the real-time entropy yield of each target subsystem to return to the target entropy yield of each target subsystem.

The invention relates to a carbon dioxide energy storage and heat energy storage synergetic efficient heat exchange method and system.The method comprises the steps that the operation working condition of a carbon dioxide energy storage system is determined, and corresponding target heat exchange requirements are obtained and comprise the carbon dioxide side target outlet temperature, the heat energy storage side target outlet temperature and the target heat exchange power; operating data of the carbon dioxide side and the heat energy storage side are collected, and a heat exchange model used for representing heat exchange amount distribution, end temperature difference distribution and pressure drop distribution is established; determining a model boundary condition according to the working condition and a target heat exchange demand, constraining the heat flow direction to point to the heat energy storage unit under the energy charging working condition, and constraining the heat flow direction to point to the carbon dioxide side under the energy releasing working condition; and irreversible loss evaluation indexes such as entropy production, exergy loss and exergy efficiency are calculated based on the heat exchange model, a heat exchange optimization problem which takes minimization of the evaluation indexes as a target and meets preset constraint conditions is constructed, and the optimal control quantity is solved and issued to an execution mechanism to implement heat exchange control.

The invention discloses a control method and system for a multi-configuration gearbox, and relates to the technical field of intelligent control, and the method comprises the steps: calculating the total driving resistance of a vehicle, converting the total driving resistance into traction force, multiplying the traction force with the current vehicle speed, obtaining a power estimation value, calculating the instantaneous change rate of an accelerator pedal opening signal, and converting the instantaneous change rate into driver demand intensity. Constructing a macroscopic feature vector; the required traction force is converted into the required torque of the gearbox input shaft, the thermodynamic entropy yield is obtained, the comprehensive cost is calculated, and a target configuration is screened; and the current gearbox configuration is judged based on the target configuration, and gearbox configuration switching is intelligently controlled. According to the method, the comprehensive performance of the gearbox is improved by utilizing the dynamic calculation of the total driving resistance of the vehicle and the intensity required by a driver, combining the real-time road condition and the driving behavior, optimizing the configuration selection of the gearbox, matching different driving scenes and utilizing the calculation of the thermodynamic entropy yield and the switching transient excitation potential.

The invention discloses a combustor full life cycle energy efficiency management platform based on digital twinning, and the platform comprises a real-time sensing unit, a digital twinning body construction unit, a monitoring unit, a collaborative optimization unit, and a track writing unit. The real-time sensing unit synchronously collects heat flux density and temperature gradient data in a combustor based on a sensor array. Then calculating a comprehensive entropy production index generated by heat conduction and viscous dissipation in real time; the digital twinborn body construction unit adopts a physical twinborn channel and a data twinborn channel which are parallel to each other to construct a digital twinborn body, and the two channels are bidirectionally coupled through a parameter interaction layer; the monitoring unit continuously collects the pressure difference value of an inlet and an outlet of the combustor through the differential pressure transmitter and constructs a long-term operation database. According to the method, through multi-dimensional entropy production analysis and a self-adaptive digital twinning architecture, deep expansion of complete-cycle energy efficiency evaluation of the combustor is realized, and the early recognition capability of deep-level energy efficiency degradation is remarkably improved.

The application relates to a centrifugal pump cavitation performance optimization method and system based on feature selection, and the method comprises the following steps: taking the cavitation entropy production and the lift of a centrifugal pump as optimization targets, taking the efficiency as a constraint condition, modeling and simulating the centrifugal pump, determining initial optimization variables and an optimization space range; based on the optimization space range, adopting a test design method to extract multiple groups of uniformly distributed variable combination schemes; modeling and simulating the variable combination schemes, obtaining the cavitation entropy production and the lift value, and constructing an initial sample library; training a first approximation model by using the initial sample library, screening out final optimization variables which have a significant influence on the optimization targets, and obtaining a final sample library; training a second approximation model by using the final sample library, optimizing and verifying by using an optimization algorithm, and outputting an optimal parameter combination. The application can better select parameters which have a significant influence on the optimization targets as optimization variables, simultaneously introduces the cavitation entropy production as an optimization target, and further improves the comprehensive optimization effect of cavitation and lift.

The application discloses a centrifugal compressor exhaust waste heat driven organic Rankine cycle power generation system, comprising: an adaptive variable structure waste heat collection module, which adjusts the spiral angle of the fin through a stepping motor, matches the exhaust temperature fluctuation, and realizes dynamic storage and release of waste heat by setting a double medium heat exchange loop; a step expansion power generation module, which adopts a two-stage expander in series and a pressure matcher, and configures a working medium shunt valve to dynamically adjust the working medium proportion; an intelligent coupled power generation and electric energy management module, which integrates a magnetic resistance switching type permanent magnet synchronous generator and a virtual synchronous generator technology, and configures a dynamic reactive power compensation device; and a multi-parameter collaborative control module, which optimizes system parameters based on a model prediction control algorithm, and introduces entropy production analysis to monitor irreversible loss. The application optimizes the heat exchange process through adaptive structure, widens the working condition adaptation range through step expansion, reduces irreversible loss through collaborative control, prolongs the maintenance cycle through self-repair system, and realizes deep utilization and efficient conversion of the centrifugal compressor waste heat.

The invention relates to the field of anomaly detection, and discloses a high-pressure valve flow capacity anomaly detection and strength failure early warning system which is used for accurately evaluating thermodynamic and dynamic states of a valve. Comprising the steps of obtaining original parameters by synchronously measuring fluid pressure, temperature, mass flow and valve body vibration acceleration of an inlet and an outlet of a valve, calculating an entropy production health index representing the abnormal degree of internal energy dissipation of the valve, calculating a chaos index representing the instability degree of a dynamic state of a structure, and carrying out nonlinear fusion on the two indexes to obtain the dynamic state of the valve. And generating a composite health index with higher sensitivity and an evolution trajectory thereof, constructing a random power system evolution model based on the trajectory, and projecting to obtain the failure probability of the future state of the valve. Depending on historical fault data and a machine learning model is avoided, and deep measurement, accurate testing and visual indication of the health state of the high-pressure valve are achieved through physical mechanism driven chain type processing.

The invention discloses a remote regulation and control platform for an LNG industrial chain and a supervision and management method, particularly relates to the technical field of liquefied natural gas receiving station pipe network regulation and control, and is used for solving the problem of storage tank group chain shutdown caused by BOG pipe network disturbance conduction under an existing independent unit control architecture. A pressure gradient change rate is generated by collecting pressure of a storage tank and a pipe network in real time, a disturbance transfer matrix is constructed, and key fragile nodes are calibrated; when the pressure of the target storage tank changes suddenly, a reverse tracing main energy flow path is combined with temperature field data to calculate an entropy generation rate; identifying an energy-entropy increasing resonance strengthening section based on an included angle between an entropy generation rate gradient and a path direction; generating an interlocking false triggering dynamic probability according to the key fragile node position and the resonance strengthening section; and the safety interlocking threshold value of the adjacent storage tanks is dynamically corrected, a directional suppression instruction is generated, accurate pre-judgment of a disturbance conduction path of the BOG pipe network, active recognition of energy abnormal gathering and directional suppression of cascade shutdown are achieved, and the cooperative operation safety of the storage tank group is improved.

This invention relates to the field of heat exchanger optimization design technology, specifically an optimization design method for a spiral tube heat exchanger. The method includes: obtaining the heat exchanger's process operating conditions and structural parameters; establishing a calculation model for heat transfer and flow resistance in the tube and shell sides; using a bisection method to iteratively calculate the outlet temperature of the tube and shell side medium; calculating the corresponding pressure drop; constructing a multi-sub-objective function that characterizes heat transfer performance, flow resistance, entropy production characteristics, and manufacturing cost; and using a differential evolution algorithm framework to optimize the system, conducting multiple iterations with structural parameters as variables. In each generation, modeling, temperature calculation, pressure drop calculation, and objective function evaluation are repeatedly performed for each candidate parameter combination within the population. After convergence, the optimal parameter combination is selected as the design scheme. This invention achieves coupled temperature calculation and full-process iterative optimization, adapting to multi-dimensional design requirements.

The invention provides a high-entropy production region regulation and control system and method, electronic equipment, a storage medium and a program product. Through multi-sensor hard real-time synchronization and edge calculation, entropy production analysis delay is compressed to a millisecond level. Microsecond-level time synchronization precision is realized through laser trigger pulses, so that the time-space correlation between transient eddy current and an entropy increase process can be accurately captured. In-situ real-time measurement and dynamic regulation and control of the local entropy yield of the industrial equipment are realized, and the problems of entropy production calculation error and lag caused by data asynchronism in a traditional method are solved. The system can automatically identify the space overlapping phenomenon of the eddy current region and the high-entropy production region, and rapidly inhibit the energy dissipation source through a closed-loop control mechanism, thereby providing a reliable technical means for the real-time energy efficiency management level.

The invention provides a low-temperature and low-humidity control method and device for a clean workshop, and relates to the technical field of workshop control. An energy-saving intelligent control framework based on a space-time closed loop principle is constructed, and deep linkage of refrigerant circulation energy level and air field flow direction distribution is achieved through energy potential balance vector signals; through a non-inertial thermodynamic hedging mechanism defined by an algorithm, on the basis of maintaining the existing hardware cost, the robustness for the uncertain thermal load is enhanced; the temperature and humidity step fluctuation in the working condition switching transient state can be effectively restrained, it is ensured that the workshop environment is always in the preset steady-state interval in the complex technological process, and the operation energy-saving effect is achieved by optimizing entropy production distribution in the heat exchange process while the humidity control precision of the clean workshop is improved.

The invention provides a method for realizing power simulation loading by controlling a hydraulic system through a PLC (Programmable Logic Controller), and belongs to the technical field of hydraulic motor loading systems.According to the method, a hydraulic motor loading system hardware architecture is established, a power loading instruction is received, time-varying parameter identification is carried out, and an entropy yield monitoring module is started to determine an optimal working point parameter combination; parameters such as target power requirements are input into the multi-working-condition coupling cooperative model to output feed-forward compensation amount and proportional valve reference opening, a self-adaptive notch filter is adopted to filter pressure signals in real time, PID controller parameters are adaptively adjusted through a fuzzy rule base to output valve control signals, whether a distributed cooperative control strategy is started or not is judged, and the control precision is improved. The output torque and the rotating speed of the motor are collected in real time, the power deviation is calculated and iteratively adjusted, and the technical problem that it is difficult for a hydraulic power loading system to simultaneously guarantee rapid dynamic response and high-precision steady-state control under the multi-working-condition variable-load condition is solved.