14 results about "Thermal optimization" patented technology

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.

This invention relates to an intelligent microchannel heat exchanger and its control method, belonging to the field of heat exchanger technology. It includes a sensor system, a control system, a drive mechanism, adjustable ribs, and heat pipes. The sensor system monitors the temperature and flow rate parameters of the fluid in real time and collects surface temperature data of the heat pipes. The control system receives input signals from the sensor system based on a microprocessor, performs real-time analysis and decision-making through a built-in heat exchange optimization algorithm, and sends corresponding control commands to the drive mechanism. The drive mechanism is linked with multiple adjustable ribs, and by driving their rotation, dynamically adjusts the geometry of the corresponding flow channels, thereby achieving active control of the fluid distribution. The heat pipes directly contact the object to be cooled to maximize the heat transfer area. By adjusting the angle of the ribs, the cross-sectional shape and flow path structure of the microchannels can be changed to adapt to the heat exchange requirements under different operating conditions, achieving efficient and adaptive heat dissipation performance.

The application relates to a lithium ion battery low-temperature preheating charging segmentation optimization method and system based on reinforcement learning, which comprises the following steps: establishing a thermal-electric coupling model of a battery, and establishing state transition expressions of voltage, temperature and SOC; when the battery temperature is lower than a preset switching temperature, starting a high-frequency pulse preheating optimization process based on reinforcement learning; when the battery temperature reaches the preset switching temperature, entering a heating charging process based on reinforcement learning, and adaptively switching among three modes of heating, charging and simultaneous heating and charging, so as to realize safe and rapid charging at low temperature. Through deep reinforcement learning technology, the preheating and charging stages are segmented and optimized, the parameters in the preheating and charging process are accurately controlled, rapid preheating and efficient charging are realized, battery damage is reduced, and the service life of the battery is significantly prolonged.

This invention belongs to the field of aero-engine cooling design and flow heat transfer optimization technology. It provides a method, system, configuration, and blade for constructing turbine blade cooling fringe based on level set topology optimization. The method includes: constructing a fluid-structure interaction (FSI) computational model encompassing the fluid domain of the cooling channel and the solid domain of the blade wall; defining a level set function to implicitly represent the two-phase region; establishing a unified set of governing equations covering the entire computational domain based on this function; introducing a velocity suppression mechanism in the solid domain to perform single-domain coupling solution of fluid flow and solid heat conduction; constructing an optimization model based on the physical field solution, with cooling performance as the objective function and fringe volume fraction as the constraint; calculating the sensitivity of the objective function to the level set function; using this sensitivity to drive the level set function update to evolve the fringe boundary; iterating until convergence to output the final fringe geometry. This invention does not require pre-setting the fringe type and can automatically generate irregular fringe structures with high heat transfer efficiency and low flow resistance.

The application relates to the technical field of intelligent heat supply, and discloses a heat supply optimization method, device, equipment, storage medium and product. The method comprises the following steps: adjusting a weight coefficient of a temperature measuring point according to user behavior data and real-time weather data, obtaining an adjusted weight coefficient, analyzing heat supply evaluation influence factors by using a sensitivity analysis method based on the adjusted weight coefficient, obtaining a most influential factor of heat supply evaluation, constructing a heat supply evaluation model according to the user behavior data based on an optimized long short-term memory network algorithm, inputting the user behavior data, real-time weather data and the most influential factor of heat supply evaluation into the heat supply evaluation model, obtaining an evaluation result, and optimizing heat supply control parameters and operation parameters according to the evaluation result. Since the weight coefficient is adjusted by combining the user behavior data and the real-time weather data, and then the heat supply evaluation model is constructed to optimize the heat supply parameters, the heat supply evaluation model precision is improved, and the heat supply system operation is optimized.

This invention discloses a method and system for optimizing heat dissipation in dense busbar trunking based on copper-aluminum eutectic cooling, relating to the technical field of heat dissipation optimization. The method includes: deploying a multi-physics monitoring network based on the structural attribute information of the target dense busbar trunking; collecting historical data sets of busbar trunking operating temperatures and constructing a digital twin model of the busbar trunking temperature; performing heat dissipation path analysis and deploying a three-dimensional composite heat dissipation unit; monitoring the busbar trunking operating temperature data in real time, and using the busbar trunking temperature digital twin to perform adaptive heat dissipation optimization control of the three-dimensional composite heat dissipation unit. This invention solves the technical problems in existing technologies, such as insufficient perception of the three-dimensional temperature field inside the dense busbar trunking, inability to accurately monitor real-time thermal status, resulting in difficulty in precise heat dissipation control according to dynamic load changes, low heat dissipation efficiency, and lag in response. It achieves precise control of the three-dimensional composite heat dissipation unit, effectively reducing the operating temperature of the busbar trunking and improving operational reliability.

This invention belongs to the field of power electronic power module design, specifically relating to a Si / SiC hybrid half-bridge power module and its design method that considers electrothermal synergistic optimization. The upper bridge arm chip is arranged on the left side of the module, and the lower bridge arm chip is arranged on the right side. The DC+ and DC- terminals are located in the middle of the module, and the AC terminal is located at the far right. The emitters of the upper and lower bridge IGBT chips are connected to the corresponding DBC board via eight bonding wires, and the sources of the upper and lower bridge MOSFET chips are connected to the corresponding DBC board via four bonding wires. All drive terminals are independently led out and connected to an external drive circuit. The method includes: constructing a Si / SiC hybrid half-bridge power module, designing transient and steady-state commutation circuits for the hybrid half-bridge power module, and then considering thermal optimization of the module chips. Using the technical solution of this invention, a shorter commutation path is provided for the module, and appropriate chip spacing improves the module's thermal performance.

The present application relates to the field of simulation technology, in particular to a glass polishing auxiliary material cooling correction method based on digital twin thermal field simulation, by constructing a digital twin model, using the spindle load and polishing fluid rheological parameter correction model boundary conditions collected in real time; The workpiece is discretized into a voxel grid, the residence time and friction heat enthalpy of each voxel are calculated by simulating the polishing tool trajectory, and a three-dimensional thermal energy density map is generated; Combined with the rebound characteristics of the polishing pad and the thermal diffusion coefficient of the workpiece, a time sequence constraint matrix based on the maximum cooling time and rebound time is constructed; The path microblock is optimized and encoded by genetic algorithm, and a thermal optimization numerical control program that meets the time sequence constraint is generated; Finally, based on the real-time calculation of the dynamic glazing risk index distribution map, the predictive intervention is carried out by inserting the residence instruction or adjusting the flow. Deep coupling of physical processing and digital twin is realized, and thermal accumulation and surface glazing in the polishing process are effectively inhibited.

The application relates to the technical field of radio frequency coaxial cables, in particular to a radio frequency coaxial cable with a temperature control function, which comprises a cable main body, the cable main body comprises an inner conductor, an insulation layer, an outer conductor, a temperature control layer and a protective layer from inside to outside, the insulation layer comprises a first foaming layer and a second foaming layer; the first foaming layer and the second foaming layer both contain a first filler, and the addition ratio of the first filler is 5-10%; the foaming degree of the first foaming layer is higher than that of the second foaming layer; the temperature control layer contains organic fatty alkane; an outer skin layer is arranged between the temperature control layer and the outer surface of the outer conductor; and the thickness of the temperature control layer is 2-6 mm. Through the gradient design of the insulation layer, the heat conduction optimization of the outer skin layer and the synergistic effect of the active heat absorption of the temperature control layer, the working temperature of the cable is stabilized in a safe range under a high-temperature environment, so that the stability of signal transmission is guaranteed and the service life of the cable is prolonged.

This invention discloses a method for calculating hotspot temperatures of high-frequency transformers based on GOA-MLP and transfer learning. First, the electrical, fixed, and free parameters of the high-frequency transformer heat transfer (HFT) are determined, and a lumped-parameter thermal network model is constructed. This model is then combined with a free parameter scanning method to obtain an analytical sample library of hotspot temperatures. Next, the optimal hyperparameter combination of the MLP model is found using the GOA algorithm, and the model is trained using the analytical sample library to establish a pre-trained hotspot temperature model. Second, two transfer learning strategies are introduced, using a small amount of limited metadata to fine-tune the pre-trained model, selecting the optimal transfer strategy until the new model reaches the required accuracy. Finally, the NSGA-II algorithm is used for multi-objective optimization of the HFT. The aforementioned hotspot temperature calculation model is used to determine whether the HFT hotspot temperature meets the requirements, thereby obtaining the optimal design result. This invention achieves accurate and rapid solution for HFT hotspot temperatures, providing technical support for HFT thermal stability, life assessment, and electromagnetic thermal optimization.

Heat dissipation and electric shielding techniques and apparatuses are disclosed to enable the operation of octal small form factor pluggable (OSFP) modules at higher bandwidths. OSFP compatible techniques are discussed including the use of water cooling, addition of heat pipes, use of intercoolers, air-fins and air-foils, optimization of cooling fins, use of vapor chambers are discussed. In particular the invention relates to an assembly comprising an OSFP module comprising a data connector, a first heatsink having a top surface and an opposed bottom surface facing toward the OSFP module, a first plurality of hollow channels formed between the OSFP module and the bottom surface, a second heatsink having a surface overlying the top surface of the first heatsink and thermally connected with the top surface, and a plurality of fins extending away form the surface of the second heatsink.