114 results about "Thermal optimization" patented technology

The invention provides an intelligent temperature field analysis-based heat dissipation optimization method for an IGBT (Insulated Gate Bipolar Translator) power module of an offshore flexible direct current converter valve. According to the method, an IGBT module space temperature data matrix and multi-point temperature sensor data are collected, and filtering processing is carried out through a multi-scale sliding window and a self-adaptive threshold value; establishing a multi-layer thermal network parameter model, and analyzing temperature dynamic change characteristics; layering the feature data according to the thermal response speed, and performing adaptive mapping and weight calculation; establishing a reinforcement learning model based on the heat dissipation efficiency index set to optimize a heat dissipation strategy; and predicting the temperature field distribution by using the graph structure neural network model. Accurate sensing, dynamic characteristic analysis, self-adaptive control and predictive maintenance of the temperature field of the IGBT module are realized, the heat dissipation efficiency and the temperature uniformity are improved, and the service life of equipment is prolonged.

The invention relates to the technical field of data processing, and provides a multi-heat-source networking heat supply optimization operation method and system.The method comprises the steps that environmental parameters, heat source data, market dynamic information, user behavior characteristics and a pipe network topological graph are collected by deploying IoT equipment; acquiring a thermal load time sequence predicted value in a future preset time period; the heat source data and the pipe network topological graph are processed, and a pipe network operation state matrix is obtained; performing feature dimension alignment processing on the pipe network operation state matrix to obtain a pipe network spatial topology feature mapping value; performing weighted fusion on the thermal load time sequence prediction value and the pipe network spatial topological feature mapping value to obtain a final thermal load prediction value; and optimal operation of heat supply is realized according to the final heat load predicted value. According to the method, a real-time response mechanism for environmental parameters, market dynamics and user behavior characteristics can be realized, collaborative optimization of multiple heat sources can be realized, the heat source collaborative efficiency is improved, and energy waste and operation cost are reduced.

The invention discloses an aircraft wheel cooling method and device, and the method comprises the steps: collecting the temperature of a brake disc and the air pressure of a hub in real time through a temperature and pressure sensor, calculating the temperature change rate and the pressure difference through an embedded processing module, and generating a thermodynamic initial parameter set; calculating a thermal stress distribution value of the brake disc based on the initial parameter set, and generating a cooling liquid flow and spraying angle instruction set in combination with a material threshold database; the opening degree of an annular pipeline piezoelectric valve is regulated according to an instruction set, an injection area is regulated according to flow velocity-surface area heat exchange efficiency, and waste heat is synchronously recovered to optimize power consumption; the thermal infrared imager obtains temperature field distribution, the initial parameter tolerance range is compared, the spraying angle and the flow instruction are corrected through a fuzzy PID algorithm, and temperature gradient errors are eliminated; and based on the temperature drop rate, the pressure stability and the waste heat recovery efficiency, an efficiency index is generated by using a neural network scoring model, and algorithm weights and piezoelectric valve response parameters are dynamically adjusted. The cooling efficiency is effectively improved, and the thermal stress risk is reduced.

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 relates to the technical field of motors, and discloses a high-temperature-resistant direct-current coreless gear motor and a test system, and the system comprises a temperature monitoring module, a current regulation and control module, a heat dissipation optimization module, a load response module, a cloud analysis module and a virtual verification module. By arranging the temperature monitoring module, multi-dimensional temperature data during operation of the motor can be acquired in real time, and a temperature distribution diagram can be generated, so that the system can comprehensively sense the internal thermal state of the motor and accurately identify local overheating risk points, thereby improving the operation reliability and safety of the motor under a high-temperature working condition; through cooperative operation and closed-loop control of the current regulation and control module, the heat dissipation optimization module and the load response module, according to real-time temperature and load changes, driving current parameters and heat dissipation resource distribution can be dynamically adjusted, and the heat dissipation efficiency is improved. And the output performance and the torque stability of the motor under high-temperature and high-load conditions are ensured.

Aspects of the present disclosure generally relate to systems and methods for flight control of aircrafts driven by electric propulsion systems and in other types of vehicles. In some embodiments, a system of an aircraft is disclosed, configured to determine one or more desired commands for the aircraft, retrieve engine information for at least one electric propulsion unit (EPU) of a plurality of EPUs of the aircraft, wherein the engine information includes at least one time-based metric for temperature associated with the at least one EPU, generates control commands based on the received engine information, and controls effectors according to the generated control commands to meet the desired commands of the aircraft.

The invention belongs to the technical field of overall aerodynamic design of helicopters, and particularly relates to an infrared suppressor fairing of a helicopter and an air heat optimization design method of the infrared suppressor fairing. The fairing comprises a fairing body, a shutter air inlet, a square protective net air inlet, a second-stage exhaust pipe and a first-stage mixed exhaust pipe. The front of the fairing body is regarded as a half ellipse which is laterally cut along a long axis; a shutter air inlet is formed in the front portion of the fairing body, and the plane of a shutter is crescent A square protective net air inlet is formed in front of the top of the fairing body; an oval second-stage exhaust pipe is arranged behind the top of the fairing body so that high-temperature exhaust can be further cooled by means of downwash airflow of the rotor wings. A first-stage mixed exhaust pipe is sleeved in the second-stage exhaust pipe; and the primary mixing exhaust pipe is connected with an outlet of the transmitter. According to the method, the problem that the pneumatic performance and the thermal performance are difficult to consider in a traditional design method is solved, comprehensive optimization of the pneumatic performance and the thermal performance of the fairing is achieved, and a pneumatic design scheme of the infrared suppressor fairing is formed.

Optimal control of multiple heating, ventilation, and air-conditioning units in an open-plan space demands fast and accurate thermodynamic modeling. Prior methods lack scalability required for effective control in large open-plan offices primarily due to air-mixing interactions. The present disclosure describes a physics-informed graph neural network (PI-GNN) to overcome these challenges. Specifically, thermodynamic interactions are modeled as edges between nodes that represent cells. Further, a modeling approach is used that allows explicit modeling of wall and window surface temperatures which are commonly ignored. The method of present disclosure utilizes PI-GNN as a state-estimator that employs a receding-horizon approach for optimal HVAC control. PI-GNNs are adapted for building HVAC control by incorporating a time-resetting strategy to handle time-dependent ambient conditions and therefore set-points. The method of the present disclosure outperforms a regular PINN model and other baseline control strategies on thermal model accuracy, computation time, energy consumption, and user comfort.

The invention relates to a lithium ion battery low-temperature preheating charging segmented optimization method and system based on reinforcement learning, and the method comprises the steps: building a thermoelectric coupling model of a battery, and building a state transition expression of voltage, temperature and SOC; when the battery temperature is lower than the preset switching temperature, starting a high-frequency pulse preheating optimization process based on reinforcement learning; when the temperature of the battery reaches a preset switching temperature, a heating and charging process based on reinforcement learning is entered, and three modes of heating, charging and simultaneous heating and charging are adaptively switched, so that safe and rapid charging at a low temperature is realized. Through the deep reinforcement learning technology, the preheating and charging stages are optimized in a segmented mode, parameters in the preheating and charging processes are accurately controlled, rapid preheating and efficient charging are achieved, meanwhile, battery damage is reduced, and the service life of the battery is remarkably prolonged.

The invention provides a heat dissipation optimization control method and system suitable for a power equipment prefabricated cabin, and relates to the technical field of data processing, and the method comprises the steps: carrying out the arrangement of a temperature sensor for a target power equipment prefabricated cabin according to a preset monitoring point position set; carrying out simultaneous sequence temperature monitoring data acquisition according to a preset monitoring frequency; carrying out double analysis on the temperature monitoring data network sequence; performing risk identification according to a double-item analysis result to obtain a risk monitoring point set and a risk temperature monitoring data set; and taking a preset heat dissipation optimization path as a constraint, and combining the risk monitoring point set and the risk temperature monitoring data set to obtain a heat dissipation optimization control scheme. The technical problems that the temperature in the cabin is still too high and the heat dissipation effect is poor during high-load operation due to the fact that the power equipment prefabricated cabin is difficult to dynamically adjust according to different environmental conditions are solved, and the heat dissipation efficiency of the power equipment prefabricated cabin is improved by introducing two-item analysis and risk identification.

The invention discloses an integrated system and method combining photovoltaic power generation, continuous water taking from air and electrolytic hydrogen production. The system comprises a photovoltaic power generation module, a continuous multi-adsorption-bed module, a thermoelectric temperature control module, a condensation water collection module and an electrolytic hydrogen production module. The photovoltaic power generation module is connected with the thermoelectric temperature control module and the electrolytic hydrogen production module, the thermoelectric temperature control module is connected with the continuous multi-adsorption-bed module and the condensation water collection module, the continuous multi-adsorption-bed module is connected with the condensation water collection module, and the condensation water collection module is connected with the electrolytic hydrogen production module. According to the invention, the continuous device design is adopted, and the adsorption-desorption period of the continuous multi-adsorption-bed module is optimized, so that efficient water extraction from air is realized; the photovoltaic power generation module is arranged, all-weather operation of the photovoltaic power generation module is achieved, and more efficient active heating / cooling is achieved through double-end utilization of the thermoelectric temperature control module and heat transfer optimization of the condensation water collection module; and by arranging the electrolytic hydrogen production module, closed-loop utilization of water resources is achieved, and the system is suitable for desert areas without power grid coverage.

The invention belongs to an optimization adjustment method, and provides a thermal power plant heat supply system heat supply optimization method and a related device for solving the technical problems that a traditional thermal power plant heat supply system monitoring method is incomplete in monitoring and low in real-time performance and accuracy, and temperature data, pressure data and flow data of a thermal power plant heat supply system are monitored and obtained in real time; after correlation analysis and clustering analysis, system health state evaluation and fault type identification are carried out by means of a health state evaluation model and a system fault classification identification model, and a future state prediction result of the system is obtained by means of a system state prediction model; and according to a monitoring result, a future state prediction result, the processed state data and historical data, an optimization algorithm is used for dynamically adjusting a heat supply strategy. The heat supply efficiency can be improved, the energy consumption can be reduced, and personalized and efficient heat supply services can be provided for users.

The invention relates to a heat dissipation analysis and optimization method for an IGBT module, and the method comprises the steps: obtaining the electrical parameters and working conditions of the IGBT module, and calculating the total power loss during the operation of the IGBT module based on the electrical parameters and working conditions. Based on the total power loss and the physical structure of the IGBT module, a thermal resistance network model of a semiconductor junction region and a cooling environment and a Cauer type thermal impedance model based on dynamic characteristics are established. Inputting the total power loss into the thermal resistance network model and the Cauer type thermal impedance model, calling a finite element simulation algorithm to solve a temperature distribution field of the IGBT chip, and determining the total equivalent thermal resistance. And when the junction temperature or the total equivalent thermal resistance of the IGBT chip does not meet the set index, positioning the heat dissipation bottleneck and generating a heat dissipation optimization strategy. And executing a heat dissipation optimization strategy, and updating the thermal resistance network model and the Cauer type thermal impedance model after executing the heat dissipation optimization strategy so as to update the temperature distribution field and the total equivalent thermal resistance.

The invention relates to the field of heat dissipation of electric aircrafts, and discloses an electric aircraft heat dissipation optimization method and system based on a numerical simulation model. Respectively analyzing the heat dissipation performance and the heat dissipation efficiency of the model simulation electric aircraft in the wind tunnel test and the numerical simulation so as to evaluate the heat dissipation capability change of the electric aircraft in the wind tunnel test and the numerical simulation, and performing comparative analysis based on the heat dissipation performance and the heat dissipation efficiency to obtain a heat dissipation difference coefficient; the heat dissipation difference coefficient in a period of time is analyzed, the heat dissipation control coefficient is calculated, the heat dissipation control threshold value is set, and the heat dissipation control coefficient is compared with the heat dissipation control threshold value, so that the heat dissipation state is continuously kept within the optimal heat dissipation range, comprehensive evaluation of the heat dissipation performance of the electric aircraft is achieved, and the heat dissipation performance of the electric aircraft is improved. The method is beneficial for realizing fine control of the heat dissipation process, and improves the accuracy of heat dissipation optimization control.

The invention discloses a heat supply unit deep peak regulation and heat supply optimization operation method based on multi-mode collaboration, and particularly relates to the technical field of thermal power generation and heat supply, and the method comprises the steps of S1, system modeling and parameter identification, S2, thermoelectric load prediction, S3, multi-objective optimization solution, S4, operation decision and feedback, and S5, data agent mapping acceleration. According to the method, the thermoelectric load is accurately predicted through mechanism and data dual-drive modeling, and based on the target of maximizing the economic benefits of the whole plant, the optimal cooperation scheme of multiple operation modes such as heat supply, power supply and deep peak regulation is dynamically solved by utilizing the multi-target optimization algorithm on the premise of ensuring the safety of the unit, so that the power supply efficiency is improved. Finally, production is guided through an online decision-making and closed-loop feedback system, and safe, economical and flexible operation of the unit under the working condition of deep peak regulation is achieved.

The invention provides a centralized heating optimal scheduling method and system based on multi-heat-source dynamic matching, and the method comprises the steps: constructing a thermal load prediction model, and fusing various types of data to generate a thermal load demand dynamic curve in the next 24 hours; establishing a dynamic priority ranking model, and generating a heat source priority sequence; generating a multi-heat-source cooperative operation strategy; constructing a multi-heat-source dynamic matching optimization model to obtain an optimal scheduling strategy; heat sources are adjusted in real time through the central control system, and dynamic correction is conducted by combining pipe network feedback data; and periodically updating the thermal load prediction and dynamic priority ranking model. According to the method, a bidirectional LSTM neural network is fused with data to construct a high-precision thermal load prediction model, and a curve is generated in combination with a feature pyramid network; meanwhile, related data are periodically combined, the weight of the LSTM neural network is updated through an incremental learning algorithm, the weight of the priority ranking model is adjusted through a gradient descent method, the adaptability of the prediction model is continuously optimized, and the prediction precision is improved.

The invention relates to the technical field of power device heat dissipation, and discloses a power device packaging heat dissipation optimization method based on three-dimensional thermal field regulation and control. A power device packaging structure is divided into a heat source area, a heat dissipation substrate area and an interface material area, corresponding models are established after parameters of all the areas are determined, and a nonlinear thermodynamic simulation model is constructed. Thermal field data are obtained through transient thermal field simulation, an optimization objective function with a thermal field uniformity index, maximum temperature rise and thermal resistance as indexes is defined, and heat dissipation substrate parameters and interface material heat conductivity coefficient distribution are optimized through an improved particle swarm optimization algorithm. And performing sensitivity analysis by using an adjoint variable method, and dynamically adjusting model parameters according to whether the uniformity index of the thermal field reaches the standard or not. The method can accurately simulate the thermal field, optimize the heat dissipation performance in a multi-index manner, improve the optimization efficiency, effectively solve the packaging heat dissipation problem of the power device, and improve the performance and reliability of the power device.

The invention discloses a multi-source collaborative energy storage peak regulation heat supply optimization method and a related device. The method comprises the following steps: acquiring meteorological data, historical load data, an electricity price signal and an equipment state in real time; according to the meteorological data, the historical load data, the electricity price signal and the equipment state, utilizing an LSTM neural network to predict the load and the electricity price in the future 72 hours; according to the predicted load and electricity price in the future 72 hours, an optimal scheduling scheme is generated through a reinforcement learning-fuzzy control hybrid algorithm; a scheduling instruction is generated according to the optimal scheduling scheme, the scheduling instruction is executed through the Internet of Things equipment, and the method and the related device can improve the stability of energy supply.

The invention relates to the technical field of heat dissipation of electronic equipment, in particular to a chip heat dissipation optimization system based on a multi-layer stacking structure. A heat conduction module; a heat dissipation module; a heat recovery module; the temperature monitoring and control module monitors the temperature of each layer of chip and the temperature difference of an inlet and an outlet of cooling liquid in real time, judges the working state of the whole system and controls the whole system; by arranging the heat conduction and heat dissipation modules, adopting heat conduction pores in gradient distribution and a mixed phase change material, and combining a nano-porous graphene substrate, cooperation of hot spot rapid heat conduction and non-hot spot buffer energy storage is achieved, the defect that a traditional phase change material is single is overcome, the dual-mode cooling pore channel design is achieved, seamless switching between a conventional system and an emergency system is achieved, and the energy storage efficiency is improved. The heat dissipation capacity is greatly improved, 0.1 mm resolution ratio temperature field reconstruction is achieved through the temperature monitoring and control module, hot spots are predicted 300 ms ahead of time, and temperature control is more accurate.

A semiconductor device is made by calculating a thermal resistance matrix for the semiconductor device. A plurality of maximum junction temperatures for the plurality of die of the semiconductor device is selected. A plurality of power envelope surfaces are calculated for the semiconductor device based on the thermal resistance matrix and the maximum junction temperatures. A plurality of powers is selected for the plurality of die. The plurality of powers are compared against the plurality of power envelope surfaces to determine a plurality of risk values.

The invention belongs to the field of numerical control machine tool temperature monitoring, and provides a method for monitoring a machine tool lead screw temperature field in real time by using numerical control motion data, which comprises the following steps: when a machine tool feed shaft structure is blocked, in the irregular rotation motion process of a lead screw, under the condition that the lead screw temperature data cannot be directly measured by a measuring instrument, determining the temperature field of the lead screw; and real-time monitoring of the temperature field of the lead screw is realized. Firstly, the feeding speed, the mechanical coordinates and the feeding load of a machine tool are collected from a numerical control system, then the friction heat and the temperature of a ball bearing pair are deduced, then the friction heat of a rolling bearing and a ball screw pair is calculated, and finally the temperature field of a ball screw is calculated. According to the invention, the temperature field of the ball screw in a complex motion state is calculated in real time by fully utilizing data which is easy to measure and can be collected in the motion process of the ball screw and combining a heat source heat generation mechanism and a structure heat transfer mechanism, so that online monitoring of the temperature field of the ball screw is realized. Technical support can be provided for machine tool thermal optimization design, thermal error compensation, machine tool digital twinborn body construction and the like.

The present invention discloses an aircraft wheel cooling method and device. The method includes: a temperature and pressure sensor collects the brake disc temperature and wheel hub air pressure in real time, and an embedded processing module calculates the temperature change rate and pressure difference to generate a set of initial thermodynamic parameters; based on the set of initial parameters, the thermal stress distribution value of the brake disc is solved, and a coolant flow rate and injection angle instruction set is generated in combination with a material threshold database; according to the instruction set, the opening degree of the piezoelectric valve of the annular pipeline is regulated, and the injection area is adjusted according to the flow velocity-surface area heat exchange efficiency, and the waste heat is recovered synchronously to optimize the power consumption; an infrared thermal imager obtains the temperature field distribution, compares it with the initial parameter tolerance range, and corrects the injection angle and flow rate instructions through a fuzzy PID algorithm to eliminate the temperature gradient error; based on the temperature drop rate, pressure stability and waste heat recovery efficiency, a neural network scoring model is used to generate an efficiency index, and the algorithm weight and piezoelectric valve response parameters are dynamically adjusted. The present invention effectively improves the cooling efficiency and reduces the risk of thermal stress.

The invention belongs to the field of chip packaging, and discloses an HBM chip with an optimized heat dissipation structure. The HBM chip sequentially comprises a substrate, a micro-bulge layer, a logic chip layer, a storage layer, a heat conduction layer and a heat dissipation layer from bottom to top, the storage layer is formed by stacking a plurality of storage chips from bottom to top; a heat optimization area is also arranged between the logic chip layer and the heat dissipation layer; the heat optimization area is made of a heat conduction material, the upper end of the heat optimization area is directly bonded with the heat dissipation layer, and the lower end of the heat optimization area is directly bonded with the logic chip layer and is in contact with the storage layer and the heat conduction layer. The heat optimization area directly connected with the logic chip layer and the heat dissipation layer is arranged between the logic chip layer and the heat dissipation layer, heat of the logic chip can be directly transmitted into the heat dissipation layer through the heat optimization heat dissipation area, heat dissipation in a more efficient mode is achieved, the storage performance is higher, and chip warping is reduced.

The invention discloses a supercritical gas-fired boiler based on tower type arrangement and a thermal optimization control method, and relates to the field of supercritical gas-fired boilers, the supercritical gas-fired boiler comprises a hearth, a burner, a water cooling wall, a heating surface in the boiler, a header outside the boiler, an economizer and a tubular air preheater. The periphery of the hearth is wrapped by an ash bucket water-cooled wall, a spiral tube coil water-cooled wall and a vertical tube coil water-cooled wall, in-furnace heating surfaces are sequentially arranged in the smoke flowing direction and are suspended through in-furnace suspension tubes, and an out-furnace collecting box is suspended through out-furnace suspension tubes; the economizer is divided into an upper stage and a lower stage, is arranged by adopting sequential tube bundles and is provided with a bypass, and a denitration reactor is arranged between the upper stage and the lower stage; the suspension pipe is made of high-strength alloy steel, a working medium flows in the suspension pipe, and a heating surface and related parts are made of alloy materials with adaptive performance. The invention has the technical effects of high safety of the wall temperature of the heated surface, small deviation, small occupied area, low smoke, wind, steam and water resistance, smooth expansion system, adaption to the rapid variable load requirement, excellent environmental protection property, reliable operation and the like.

The invention relates to the technical field of server heat dissipation optimization control, and discloses a server heat dissipation optimization control method and system based on environmental parameters, and the method comprises the steps: obtaining a heat distribution data set, screening out an abnormal region set, selecting temperature change information and temperature values as region temperature features, and carrying out the K-means clustering to obtain a second region set, screening high-risk areas with the ventilation flow speed lower than a threshold value and the humidity higher than the threshold value, determining a heat transfer path in combination with a real-time airflow direction, screening out a high-risk path, constructing an evaluation system to calculate an overheat risk evaluation value, and if the overheat risk evaluation value exceeds the pre-estimated threshold value, selecting an adjustment operation from a preset control strategy library as a preliminary scheme; and adjusting the scheme according to the applicability of the scheme. And extracting an instruction issuing device from the adjustment scheme, performing parameter deviation correction according to execution, and determining a final scheme if an execution effect meets a preset heat dissipation target. The method solves the defect that in the prior art, spatial relevance and dynamic heat conduction cannot be fused to form a precise heat dissipation strategy.

This invention discloses a method and device for optimizing and controlling the hydrothermal environment of green roofs based on modified matrix synergy, belonging to the field of green building technology. The method involves acquiring meteorological parameters and roof structure requirements of the target area to determine the hydrothermal control objectives, and customizing a modified matrix formula composed of garden soil, gravel, and wood chip biochar, pretreated for porosity optimization. A layered structure is constructed, and sensors collect data such as matrix moisture content, roof temperature, and rainfall intensity in real time. Based on a coupling algorithm, the porosity and height of the water storage and drainage layer are dynamically adjusted to achieve hydrothermal control through the synergistic effect of the modified matrix's water retention and thermal insulation properties and vegetation evapotranspiration. The control effect is periodically evaluated, and the matrix ratio and water storage and drainage layer parameters are iteratively updated. The device employs an intelligent modular adjustable ventilated water storage and drainage layer, with built-in sensors and a drive motor, and a distributed data acquisition and control module to achieve intelligent control. This invention solves the problems of poor adaptability and weak hydrothermal control capabilities of traditional green roofs.

The present application relates to the technical field of sports building light heat optimization, and more particularly to a method for balancing and optimizing the light heat environment of a retractable roof sports building based on a generative adversarial network and a genetic algorithm. The method comprises the following steps: obtaining retractable roof shape data; parameterizing the retractable roof shape data to generate a two-dimensional grayscale image of the retractable roof; performing fluid dynamics and light heat environment numerical simulation on the retractable roof shape data to obtain environment simulation data of the retractable roof; pairing the two-dimensional grayscale image of the retractable roof with the environment simulation data of the lower space of the retractable roof to obtain an input-output image pair; and using the generative adversarial network to predict the wind speed distribution of the input-output image pair to generate a wind speed distribution prediction value of the retractable roof. The present application realizes intelligent optimization of the light heat balance of a retractable roof sports building by combining a generative adversarial network and a genetic algorithm, and solves the deficiencies of traditional methods in flexibility, optimization accuracy and computational efficiency.

The invention discloses a three-dimensional chip thermal perception optimization method based on tensor data flow, and relates to the field of integrated circuits, and the method comprises the steps: firstly, starting from the angle of tensor data flow, providing a collaborative thermal optimization process combining a network, an architecture, physics and packaging; then, based on a quantitative modeling tensor data flow energy optimization method, automatically identifying the most energy-saving tensor data flow under given three-dimensional chip constraints by using a heuristic optimization method; and finally, providing a thermal sensing three-dimensional architecture spatial layout method, simplifying the spatial layout problem of the SRAM macro block into an affine mapping optimization problem, and optimizing an affine mapping relationship through a heuristic optimization method to obtain the spatial layout with optimal thermal performance. According to the method, the tensor calculation characteristics are optimized in a targeted manner, so that the three-dimensional stacked SRAM chip meets the thermal reliability requirement in a high-density integration scene.

The invention discloses a heat exchange optimization structure of a power plant cooling tower, which comprises a cooling tower main body, a water inlet pipe mounted at the top of the cooling tower main body, a water outlet pipe mounted at the bottom of the cooling tower main body, a flow guide fan mounted at the upper part in the cooling tower main body, a filler groove mounted at the lower part in the cooling tower main body, and an air inlet groove formed in the inner wall of the cooling tower main body, an air inlet pipe communicated with the air inlet groove is arranged in the side wall of the cooling tower main body; the flow guide fan comprises a bottom plate, a plurality of arc-shaped vertical plates are annularly fixed to the edge of the bottom plate, flow guide plates are installed on the inner sides of the arc-shaped vertical plates, a first through hole is formed in the center of the bottom plate, and a plurality of fan blades are evenly arranged between the first through hole and the edge of the bottom plate. A plurality of layers of conical screen plates are arranged in the packing groove, the adjacent conical screen plates face opposite directions, and the height of the conical screen plate on the top layer is gradually reduced from the middle to the edge. The defects in the prior art can be overcome, and the cooling efficiency of the cooling tower under all working conditions is effectively improved.

The invention relates to the technical field of aircrafts, in particular to an equipment aerodynamic heat optimization method and device, equipment and a computer readable storage medium. The equipment aerodynamic heat optimization method comprises the following steps: determining an initial shape of to-be-optimized equipment and a structural grid of a structural field; determining adjoint variables corresponding to a plurality of moments; wherein the multiple moments are moments corresponding to each changed flow field in a temperature rise period of the equipment under the action of the changed flow fields; determining an objective function gradient according to the adjoint variables corresponding to the multiple moments; and optimizing the coordinates of the structure grid of the structure field based on the target function gradient so as to obtain the shape of the optimized equipment.