6655 results about "Heat flow" patented technology

The invention relates to the technical field of welding processing, and discloses a dissimilar metal welding joint temperature field optimization control method and system. Real-time temperature field scanning is conducted on the dissimilar metal welded joint, image segmentation processing is conducted on a temperature field image obtained through scanning, temperature data of a weld joint area, a heat affected area and a base metal area are extracted, and whether the temperature gradient exceeds a preset threshold value or not is judged; aiming at an area with non-uniform distribution of heat input quantity, analyzing the performance of the welding joint under the combined action of thermal stress and mechanical stress, obtaining the difference between residual stress distribution and plastic deformation capacity, and analyzing a stress concentration area by combining with the yield strength of the material; and a mapping relation between the welding process parameters and temperature field distribution is established, and a welding process parameter adjustment prediction model is obtained through historical welding process parameters and corresponding temperature field data training in combination with heat flux density distribution. The problems of uneven heat input, stress concentration and the like in dissimilar metal welding are effectively solved, and the welding quality and efficiency are improved.

The invention relates to a lithium battery energy storage system fire-fighting ventilation and explosion venting safety assessment method based on multi-dimensional simulation. The method comprises the following steps: constructing an energy storage system digital twinborn model fusing structure parameters, material attributes and environmental parameters; generating a multi-mode failure scene set covering multiple temperature domains and aging states through mode recognition; simulating and quantifying dynamic interaction of a temperature field, a flow field and a stress field in the thermal runaway evolution process based on thermal-fluid-solid multi-physics field coupling; constructing a space-time associated dynamic safety evaluation matrix, and combining fuzzy comprehensive evaluation and Monte Carlo sampling to generate risk quantitative indexes; and iteratively correcting parameters of the fire-fighting ventilation and explosion venting system through a multi-objective optimization algorithm to form a graded safety assessment conclusion. According to the method, the technical bottlenecks of environmental parameter splitting and single failure scene in a traditional method are broken through, the thermal runaway suppression efficiency is improved, the combustible gas concentration control error is reduced, and collaborative optimization of explosion venting pressure fluctuation suppression and ventilation response is realized through a closed-loop evaluation mechanism.

The invention relates to a heat dissipation control method and device for a high-order computing power automatic driving FPC sensing module, and the method comprises the following steps: carrying out the temperature data collection of a target FPC sensing module through a preset distributed thermosensitive array, and obtaining the data of a three-dimensional temperature field; performing heat flow path calculation on the target FPC sensing module based on the three-dimensional temperature field data to obtain a heat flow density distribution diagram; performing topological optimization calculation on the target FPC sensing module based on the heat flux density distribution diagram to obtain a heat dissipation structure layout scheme; performing dynamic optimization solution on the heat dissipation structure layout scheme through a branch and bound algorithm to obtain a heat dissipation control parameter set; and inputting the heat dissipation control parameter set into a preset execution unit, and performing real-time heat dissipation control on the target FPC sensing module to obtain an ideal heat dissipation state, thereby solving the problems that a traditional method often cannot accurately and effectively cool local hot spots and lacks flexibility to adapt to dynamic thermal changes under different working loads.

The invention relates to the technical field of thermal power plant parameter regulation and control, in particular to an intelligent temperature and pressure regulation method and system for a thermal power plant, and the method comprises the following steps: collecting temperature, pressure and flow data based on heat transfer and flow channels among a boiler, a steam turbine, a condenser and heat exchanger equipment in the thermal power plant; constructing a network structure representing interaction between devices, evaluating heat exchange characteristics of nodes, and constructing heat flow path structure matrix information; according to the method, the complex interaction among the boiler, the steam turbine, the condenser and the heat exchanger equipment is accurately quantified by constructing the heat flow path network structure among the equipment and evaluating the heat exchange characteristics of the nodes. Thermal inertia feedback matrix information is introduced, and transient changes of temperature and pressure are monitored in real time, so that delay and inertia effects in heat transfer and fluid flowing between equipment can be more accurately captured, and the response speed and precision to different loads and working conditions are improved.

The invention relates to the technical field of heat exchange modules, and discloses a multi-cavity cooperative control method and device for a micro-channel heat exchange module and electronic equipment, and the method comprises the steps: carrying out the numerical simulation calculation of a plurality of heat exchange cavities of the micro-channel heat exchange module, and obtaining a training data matrix; coefficient calculation and heat flow coupling relation analysis between cavities are carried out, and a heat flow distribution mathematical model is generated; substituting the heat flow distribution data, the temperature distribution data and the flow distribution data into a non-homogeneous heat conduction equation, and constructing a multi-objective optimization function; executing chaotic mapping processing and multi-target collaborative differential evolution to obtain an optimal control scheme set; carrying out Q-learning state value function solving, and generating a cooperative control instruction; and inputting the cooperative control instruction into an execution unit, and performing real-time adjustment and online updating on inlet temperature parameters and flow parameters of each heat exchange cavity to obtain a target heat flow distribution model. Therefore, information interaction and optimized cooperation among the heat exchange cavities are achieved, and the heat exchange efficiency is remarkably improved.

The invention relates to the technical field of data center heat dissipation, and particularly provides a single-phase and two-phase immersion liquid cooling method and system based on AI intelligent decision, and the method comprises the steps: injecting coupled data into a dynamic feature extraction engine, and outputting a thermodynamic state evolution tensor which comprises the characteristics of a temperature change rate, a load-heat flux density coupling coefficient and the like; the thermodynamic state evolution tensor is input into the deep neural network model, the temperature and pressure matched with the current thermodynamic state evolution tensor are calculated, and a closed-loop control instruction set capable of being executed by equipment is generated; a closed-loop control instruction set is injected into an execution mechanism set, execution mechanisms execute power reconstruction and flow channel switching according to instructions, gaseous fluorinated liquid is liquefied and flows back through an efficient condenser in a two-phase mode, and heat dissipation mode self-adaptive switching and heat cycle reconstruction are achieved. The system comprises a server, an AI algorithm controller, a cooling liquid storage device, a condenser, a circulating pump, an electric valve, a pressure release valve and a temperature sensor. The heat dissipation efficiency and the system reliability are remarkably improved.

The invention discloses a server heat dissipation device and a heat dissipation control method.The surface of a server mainboard is divided into a core heat dissipation area, a transition heat dissipation area and an edge heat dissipation area, and the method comprises the steps that real-time temperature data of all the areas are synchronously collected through a temperature detection module; constructing a three-dimensional temperature field distribution map containing temperature gradient and heat flow direction; then thermodynamic parameter calculation is carried out, temperature time sequence change characteristics of all the partitions are extracted, and a thermal diffusion path in a future set time period is predicted by fusing the temperature time sequence change characteristics and the thermodynamic parameters; a control instruction set is generated according to the predicted thermal diffusion path, the actual heat dissipation response is monitored through an acoustic sensor in the execution process, monitoring data and the predicted thermal diffusion path are dynamically compared, and control parameters of the control instruction set are updated till all the partitions reach the target temperature threshold value; and the sudden temperature change is pre-judged, the hot spot elimination response time is shortened, and the collaborative breakthrough of the heat dissipation efficiency and the energy consumption control of the high-density server cluster is realized.

The invention relates to the technical field of chip heat dissipation, and discloses a photoelectric co-packaging heterogeneous chip heat dissipation integration method, device and equipment, and the method comprises the steps: carrying out the finite element modeling analysis of a photoelectric co-packaging heterogeneous chip, and obtaining a three-dimensional thermal characteristic model; performing signal acquisition and frequency domain characteristic analysis on each functional module of the photoelectric co-packaged heterogeneous chip to generate power consumption prediction data; performing temperature field distribution calculation on the photoelectric co-packaging heterogeneous chip according to the power consumption prediction data and the three-dimensional thermal characteristic model, and constructing a temperature outer ring control model and a heat flow inner ring control model; and performing heat dissipation structure layout optimization calculation based on the temperature outer ring control model and the heat flow inner ring control model, and generating a hybrid heat dissipation layout scheme. Dynamic distribution of heat dissipation power and automatic threshold adjustment are realized, frequent mode switching is avoided, and the thermal characteristic stability of a chip is improved.

The invention discloses a temperature measurement precision optimization method based on multiple sensors, and belongs to the technical field of temperature measurement, and the method specifically comprises the steps: deploying a temperature monitoring array which comprises a fixed position basic sensor group and a position adjustable auxiliary sensor group; scanning the target area through an infrared thermal imaging device to generate a thermal field temperature gradient distribution map; identifying a high dynamic change region boundary based on the thermal field temperature gradient distribution map, and extracting geometric feature parameters of the boundary; constructing a heat flow propagation prediction model according to the boundary geometric feature parameters, and calculating a key monitoring node space coordinate set on a heat conduction path; generating a sensor deployment instruction according to the key monitoring node space coordinate set, and dynamically scheduling an auxiliary sensor group to move to a target position; fusing the temperature data streams of the basic sensor group and the auxiliary sensor group, and executing space-time calibration calculation to generate an optimized temperature field distribution diagram; according to the invention, the coverage integrity and the result accuracy of temperature measurement in a dynamic scene are improved.

The invention discloses an aircraft surface flow field intelligent reconstruction method and system based on multi-source data fusion, and belongs to the technical field of flow field intelligent prediction. Acquiring multi-source sensor data on the surface of the aircraft, and constructing a multi-source data set; a flow field reconstruction model based on Transform is constructed; a multi-source data set is adopted to train a flow field reconstruction model; and outputting an aircraft surface flow field reconstruction result based on the trained flow field reconstruction model, and visually displaying the aircraft surface flow field reconstruction result. Based on the strong nonlinear mapping capability of the deep learning model, through training of a large amount of sensor data, high-order correlation characteristics among pressure, heat flow and friction resistance stress can be automatically extracted, through fusion of sparse discrete data, a continuous physical field of the whole surface of the aircraft can be effectively reconstructed, and the method is suitable for the aircraft. The limitation of a traditional analytical model in dealing with a strong nonlinear problem is broken through, and the precision and reliability of aircraft flow field prediction are improved.

The invention relates to the technical field of air conditioner cooling load prediction, and discloses an air conditioner cooling load prediction method and system. The method comprises the following steps: acquiring temperature, humidity and CO2 data through an environment sensor network and carrying out standardization processing; establishing a time slice matrix based on the environmental parameters and the personnel density, and obtaining user behavior characteristics; constructing a wall heat storage model by combining the environmental parameters, and calculating instantaneous heat flow; establishing a spatial downscaling model according to the heat flow and meteorological data; time sequence features are extracted based on local weather and heat flow data, and the cooling load is predicted; and a time-phased refrigeration control instruction is generated accordingly. By establishing a data processing and analysis process, factors such as building microclimate characteristics, user behavior modes and wall dynamic thermal characteristics are comprehensively considered, and more accurate prediction of the cooling load of the air conditioner is realized.

The invention relates to a full-automatic injection molding optimization method, device and equipment based on digital twinning, and belongs to the technical field of intelligent manufacturing equipment. Inputting the sensor data into a digital twin model to construct equipment dynamic response simulation, and synchronously comparing the actual mode locking force with the offset of a preset pressure threshold; generating compensation data of mold locking pressure according to the offset, and dynamically correcting an acceleration curve of a servo motor in a glue injection stage on the basis of the displacement of a screw rod; in hot runner control, a thermal interference compensation coefficient is calculated according to a temperature difference value of adjacent temperature zones, and an output power gradient signal of each heating ring is adjusted; the corrected parameter information is transmitted to an equipment PLC through an industrial bus to execute control, and a compensation coefficient threshold value is iteratively updated according to a product weight fluctuation value in the next forming period; closed-loop data interaction of an equipment control system is achieved, and the injection molding process is optimized.

The invention provides a fire early warning method and system based on three-dimensional modeling, and the method comprises the steps: determining the transaction indexes of fire danger at different space units through the spatial structure characteristics of a three-dimensional digital twin model in combination with the state evolution mode of a physical field, and determining a risk cloud picture through all transaction indexes; extracting a risk sub-domain of the fire according to the risk cloud picture, and further generating a heat flux density field matrix among different space units; determining risk fitting degrees of different space units by combining the heat flow diffusion information with the monitoring information of the fire behavior in the target building, and performing time sequence aggregation on the fire risk in the target building according to all the risk fitting degrees and the local temperature field of each space unit to obtain fire danger propagation potential energy; and performing fire diffusion situation monitoring on the target building according to the fire danger propagation potential energy, and outputting a fire diffusion early warning signal. By adopting the scheme of the invention, the diffusion track of the fire heat flow can be accurately identified in the three-dimensional model.

According to the thermal management method and system of the modular power supply, heating elements are identified, temperature sensors are installed to evaluate thermal resistance and thermal capacity under different load conditions, the thermal coupling effect between modules is evaluated, an isolation layer and a thermal bridge are designed to optimize heat flow, load distribution is dynamically adjusted, an intelligent control mechanism is implemented, temperature stability is ensured, and the reliability of the system is improved. An external environment is monitored, a heat dissipation strategy is automatically adjusted to adapt to different conditions, a temperature prediction model is established by using historical data, measures are taken in advance to prevent overheating, and the whole system comprises a temperature monitoring and data analysis module, a thermal coupling effect evaluation and optimization module, an intelligent load distribution and control module and an external environment monitoring and adaptation module. And the temperature prediction and prevention module ensures that the modular power supply can effectively dissipate heat under various working conditions, so that the reliability and efficiency of the system are improved.

The invention belongs to the technical field of laser welding, and discloses a laser welding macro-micro multi-physics field cross-scale bidirectional coupling modeling method, which adopts a diffusion interface theory, considers macro heat flow information to revise micro phase field and solute field evolution equations, considers micro phase quality information to revise macro temperature field and flow field evolution equations, and considers micro heat flow information to revise micro phase field and solute field evolution equations. A macroscopic heat flow-microcosmic phase and mass multi-physics field bidirectional coupling model is innovatively constructed, and macroscopic and microcosmic bidirectional coupling calculation in the same computational domain is achieved. The model can overcome the limitation that a traditional sharp interface is difficult to couple, and a theoretical model basis is provided for precise prediction of macroscopic forming and microstructure evolution in the laser welding process. According to the method, a macroscopic temperature field / flow field-microscopic phase field / solute field bidirectional coupling mechanism is established, a cross-scale data bidirectional collaborative interaction method is provided, and therefore a laser welding macro-microscopic multi-physical field / cross-scale bidirectional coupling modeling method is provided, and precise simulation of macro-microscopic forming in the laser welding process is achieved.

The invention relates to the technical field of power equipment monitoring, in particular to a 10kV cable joint temperature inversion correction method based on environmental heat exchange conditions, which comprises the following steps: measuring surface temperature data through a sensor array, and analyzing material layering characteristics in combination with X-ray imaging; then, establishing an electromagnetic-thermal-fluid field coupling model, and calculating a dynamic thermal resistance coefficient and a heat flow distortion index; thirdly, optimizing surface temperature distribution and iteratively updating thermal resistance parameters by utilizing a bidirectional feedback correction strategy, and finally generating a high-precision internal temperature field; through adaptive temperature compensation and multi-source data fusion, the accuracy of temperature prediction is improved, long-term monitoring errors are reduced, the method can be widely applied to intelligent operation and maintenance and fault early warning of cable joints, and the safety and stability of a power system are improved.

The invention discloses a temperature control system and method for a hot runner of an injection molding machine mold, and the method comprises the steps that the temperature control system collects the temperature data of each region of the hot runner in real time through a temperature sensor, and carries out the adjustment according to the data feedback; a built-in self-adaptive algorithm automatically adjusts a temperature control strategy according to different injection molding materials and production requirements, such as temperature upper limit, temperature lower limit and heating and cooling opportunities, and the production efficiency is optimized; when the system recognizes temperature fluctuation, a heating mode or a cooling mode is automatically switched, and the cooling system is dynamically adjusted for temperature balance; a plurality of temperature sensors are arranged in a key area of the mold for regional monitoring, and temperature control output is adjusted in real time; meanwhile, an embedded learning algorithm gradually optimizes a temperature control strategy according to historical production data, adjusts control parameters, and improves the production precision and efficiency. According to the temperature control system and the temperature control method for the mold hot runner of the injection molding machine, the problems of low temperature control precision, poor energy efficiency and slow response in the prior art are solved, and efficient and intelligent temperature control capability is provided.

The invention provides an intelligent electric energy distribution cabinet heat flow field prediction method and system, and relates to the technical field of cabinet heat flow field prediction, and the method comprises the steps: carrying out the clustering analysis of the obtained operation data and material attributes of each region in an intelligent electric energy distribution cabinet, and the element layout information of equipment in the cabinet; respectively establishing a thermal-mechanical coupling model, a fluid dynamic model and an electromagnetic model; and according to the final refined grid model, simulating fluid dynamics by using a motion constraint smoothing particle fluid dynamics method so as to obtain an optimal layout scheme of the internal structure of the intelligent electric energy distribution cabinet. And calculating the optimal layout scheme by using an analog simulation technology to obtain an optimization scheme of air flow and heat transfer in the intelligent electric energy distribution cabinet, and realizing prediction of the heat flow field of the intelligent electric energy distribution cabinet. Accurate prediction and optimization of the heat flow field of the power distribution cabinet are realized, the reliability and safety of a power system are improved, and the accident risk and loss are reduced.

The invention relates to the technical field of server heat dissipation optimization, in particular to an intelligent heat dissipation control optimization method and system for a server, and the method comprises the steps: obtaining the temperature information of each region of the server and the working load data of the server; based on the temperature information, constructing multi-dimensional thermal field topological mapping; executing group theory base heat flow dynamic analysis according to the multi-dimensional thermal field topological mapping; performing spectral decomposition heat dissipation efficiency evaluation based on a group theory basis heat flow dynamic analysis result; according to the spectral decomposition heat dissipation efficiency evaluation result and the workload data, nonlinear heat transfer optimization is executed; a self-adaptive feedback control strategy is generated and used for adjusting a heat dissipation system of the server, accurate description of internal temperature distribution of the server is provided by a multi-dimensional thermal field topology mapping technology, and a foundation is laid for subsequent optimization; the group theory-based heat flow dynamic analysis method deeply reveals the essential law of heat transfer; the spectrum decomposition heat dissipation efficiency evaluation provides a brand new performance quantitative index, and the heat dissipation efficiency of the system is improved by more than 20%.

The invention provides an indoor environment monitoring method and system integrating temperature and humidity, and is applied to the field of sensing data processing. According to the method, the reading difference of the temperature sensor is collected, whether local deviation exists or not is judged, the arrangement type of the sensor is combined, a low temperature value generated by the wall-leaning sensor due to the cold bridge effect is dynamically compensated, misjudgment of an environment system is avoided, and the human body temperature is introduced as a sensing reference by constructing a temperature difference deviation function. According to the method, comprehensive temperature indexes closer to real experience can be generated, when abnormal fluctuation is detected, the space structure and heat source information are further combined, boundary conditions are constructed, dynamic heat flow and temperature and humidity distribution diagrams are simulated, temperature sensing deviation is effectively and reversely corrected, the precision, stability and energy-saving performance of an environment adjusting system are remarkably improved, and the comfort degree of a human body is improved.

The dynamic hot runner temperature control method suitable for the mold comprises the steps that S1, a temperature sensor is installed in a mold hot runner to collect flow characteristics, heat distribution and temperature original data in the material solidification process, and the temperature original data are transmitted to a temperature control system; s2, the required power adjustment amount Pc is calculated through a PID controller in the temperature control system according to the deviation value delta T between the actual temperature Ta and the set target temperature Ts, and the power adjustment amount Pc is sent to a heater for adjustment; s3, constructing a temperature prediction model M, and predicting the temperature change trend of each section of the mold hot runner through the temperature prediction model M; and S4, a multi-objective optimization function Ft is created, an optimal combination solution St is searched through a particle swarm optimization algorithm PSO, and the optimal set value combination of the hot runner temperature is maintained according to an optimization objective. According to the invention, the energy consumption is reduced while uniform temperature distribution is ensured, the temperature control precision and the response speed are obviously improved, and the requirement of human intervention is reduced.

The invention relates to the technical field of material testing, and discloses a coating performance simulation method based on high and low temperature circulation and prestress loading. The method comprises the following steps: constructing a coating matrix composite geometric model containing a microporous structure by acquiring actually measured working condition data of a pipeline or a part, and quantifying surface roughness and interface curvature characteristics in combination with reverse engineering; a dynamic temperature-pressure coupling equation is generated based on the thermal expansion effect of a high-pressure medium, a micropore optical load is converted into equivalent heat flux density through a ray tracing algorithm, transient boundary conditions of a temperature field and a stress field are associated, a crack initiation path is simulated through an extended finite element method, and a life attenuation curve is predicted in combination with a Paris formula. And material parameters are dynamically corrected based on experimental data, and a multi-parameter collaborative optimization model is generated. According to the method, the problems of interface stress evaluation distortion and life prediction deviation under the combined load are solved, and multi-physics field co-simulation support is provided for coating compression resistance optimization.

The invention relates to the technical field of environment intelligent regulation and control, in particular to a vegetable greenhouse environment intelligent regulation and control method and system. The method comprises the following steps: acquiring all-weather illumination data and internal environment data of the vegetable greenhouse through a sensor; performing air heat flow exchange path identification based on the internal environment data of the vegetable greenhouse to obtain internal air heat flow exchange path data; according to the all-weather illumination data of the vegetable greenhouse, carrying out heat flux period temperature and pressure deposition simulation on the internal air heat flow exchange path data, and carrying out gas exchange barrier effect analysis to obtain gas exchange barrier effect data; performing regional environment staged regulation and control on the gas exchange barrier effect data to obtain regional environment staged regulation and control data; and carrying out environment regulation and control model construction on the regional environment stage regulation and control data to obtain an environment regulation and control logic model. According to the invention, the intelligent environment regulation and control technology is optimized, so that the intelligent environment regulation and control technology is more accurate.

The invention discloses a circuit board heat management optimization method combined with quantum computing, which comprises the following steps of: predicting heat flow distribution of each heat source on a circuit board through a quantum optimization algorithm, identifying a potential overheat area, allocating cooling resources in advance, and determining whether the circuit board is abnormal or not according to a local temperature abnormal condition. A quantum gate control algorithm is adopted to adjust the conduction path and rate of heat, redundant heat is guided to a low-temperature area so as to avoid heat accumulation, the system monitors the temperature change and power consumption fluctuation of a circuit board in real time, parameters of cooling equipment are dynamically adjusted according to a feedback result, the redundant heat is converted into electric energy through a heat energy recovery device and stored, and the cooling efficiency is improved. When the power consumption is low, the heat flow is released to balance the overall heat flow of the circuit board and prolong the service life of equipment. The invention aims to realize more efficient heat dissipation management through a quantum algorithm.

The invention relates to an inverter IGBT junction temperature prediction method and related equipment, and the method comprises the following steps: generating a loss characteristic spectrum through collecting IGBT electrical parameters and analyzing switching loss; calculating surface heat flux density, and constructing a heat flux distribution matrix. And performing thermal-electric coupling analysis by combining the two to obtain a junction temperature dynamic response sequence. Fourier transform is utilized to extract temperature fluctuation harmonic features, and a feature set is constructed; and extrapolating and predicting a junction temperature change trend based on the feature set, and outputting an IGBT junction temperature early warning signal through threshold judgment. The technical problem that the service life of a device is affected due to the fact that a large amount of loss is generated due to frequent switching actions in the working process of the inverter, the junction temperature of a chip rises and even temperature fluctuation occurs is solved.

The invention relates to the field of industrial automation and intelligent control, and discloses an intelligent temperature automatic control system for a digital glass mold. The method comprises the following steps: acquiring mold surface temperature and heat flow data through a thermocouple array and a thermal infrared imager, and constructing heat flux and a disturbance coefficient; forming state vectors are established in combination with the forming process parameters and the heat flow distribution, and forming stability levels are generated through support vector regression; building a heat balance deviation model based on the thermophysical parameters and the environment variables, and predicting a temperature trend; a temperature control instruction is generated through the fuzzy neural controller, and temperature dynamic closed-loop control is achieved. The system improves the temperature control precision and thermal field balance of the glass mold, and is suitable for intelligent temperature control management in the glass container forming process.

The present disclosure relates to a system for utilizing waste heat of a data center. The system comprises a first heat exchange module, a second heat exchange module, a heat storage and extraction flow path, a heat supply flow path and a buried pipe, wherein the first heat exchange module is used for connecting to a data-center heat dissipation system for dissipating heat of a data center, and both the heat storage and extraction flow path and the heat supply flow path are connected to the first heat exchange module, so that the first heat exchange module can transfer, to the heat supply flow path and / or the heat storage and extraction flow path, heat which is generated by the data center and absorbed by the data-center heat dissipation system; the second heat exchange module is connected in the heat storage and extraction flow path and the heat supply flow path, so that heat exchange can be performed between the heat storage and extraction flow path and the heat supply flow path; and the heat storage and extraction flow path is provided with the buried pipe, which is configured to be buried below the ground surface, and is used for storing, in soil below the ground surface, the heat which is transferred from the data-center heat dissipation system to the heat storage and extraction flow path, or for transferring, to the heat supply flow path via the second heat exchange module, the heat which is stored in the soil below the ground surface.

The invention relates to the technical field of lithium battery thermal management, and discloses a lithium battery thermal management regulation and control method, device and equipment and a computer program product, and the method comprises the steps: collecting the temperature data of a lithium battery cell in real time through a plurality of embedded temperature sensors, and forming a temperature matrix; calculating heat flux density between the battery cells based on a Fourier heat conduction equation to generate a heat flux matrix; forming a cooling demand parameter matrix; and dynamically adjusting the flow velocity of the cooling liquid based on a particle swarm optimization algorithm, and automatically adjusting the flow velocity of the cooling liquid through a closed-loop feedback mechanism. Compared with the prior art that performance reduction or service life shortening of a lithium battery system is easily caused by overheating under high-power use or extreme environment conditions, and particularly, effective and uniform heat dissipation cannot be realized when the temperature difference of battery cells is relatively large, accurate heat management is realized by combining temperature real-time monitoring and adjustment of the flow rate of cooling liquid, and the service life of the lithium battery system is prolonged. Therefore, the problem of overheating or non-uniform local cooling is avoided, and the stability and safety of the battery system are improved.

The invention relates to the technical field of fire extinguishing control, in particular to an unmanned aerial vehicle fire extinguishing control method and system. The method comprises the following steps: carrying out hot-flow wind field real-time data acquisition on a high-rise building fire scene through a sensor carried on an unmanned aerial vehicle, carrying out approaching hot-flow wind field intensity difference analysis, and then carrying out unmanned aerial vehicle flight attitude instability numerical value quantification to obtain flight attitude instability numerical value quantification data; time-varying attitude spraying strategy adjustment is carried out according to the flight attitude instability numerical value quantization data, and a time-varying attitude spraying adjustment strategy is obtained; building a fire extinguishing spraying control model for the time-varying attitude spraying adjustment strategy based on a strategy gradient algorithm to obtain a fire extinguishing spraying control model; and sending the fire extinguishing spraying control model to the terminal. The fire extinguishing control technology is optimized, so that the fire extinguishing control technology is more perfect.

The invention provides a performance optimization and regulation method for a high-temperature sintering furnace, and belongs to the technical field of intelligent regulation, and the performance optimization and regulation method comprises the following steps: arranging sensors in each heating area of the high-temperature sintering furnace, and monitoring the heating areas in real time; constructing a heating area operation state database, comparing the collected real-time data with a preset sintering process parameter range, and analyzing to obtain a performance analysis set of each heating area; establishing a three-dimensional heat conduction model, simulating heat flow distribution of each heating area under different heating powers and temperature settings, determining a thermal coupling effect of each heating area in different stages, and determining a heat transfer coefficient between adjacent heating areas; and an initial strategy of the high-temperature sintering furnace is determined, the initial strategy is optimized based on the auxiliary parameters of all the heating areas, and all the heating areas of the high-temperature sintering furnace are regulated and controlled according to the optimization strategy. The problems of inaccurate temperature control, single parameter analysis, insufficient thermal coupling effect processing and the like in the traditional regulation and control technology are effectively solved.