35 results about "Thermal optimization" patented technology

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 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 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 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 invention provides a distributed heat supply optimization system and method based on the Internet of Things, and belongs to the technical field of heat supply optimization. The system is characterized in that a data acquisition module acquires multi-modal data by using a synchronous acquisition technology and a dynamic acquisition strategy; the feature extraction module performs multi-dimensional feature extraction and constructs a voiceprint feature library capable of being dynamically updated; the acoustic diagnosis module is used for identifying fault types and positioning fault points; the model construction module is used for constructing a thermal inertia digital twinborn model to obtain a thermal dynamic prediction result; the sequence generation module is used for establishing a multi-objective optimization model and generating a self-adaptive pulse control sequence; and the execution and optimization module implements a self-adaptive pulse control sequence through an intelligent actuator, so that autonomous and iterative evolution of the distributed heat supply optimization system is realized. According to the system, heat supply does not meet the requirement in advance, the energy efficiency and the comfort degree are improved, fault diagnosis is intelligent and early, the maintenance efficiency is greatly improved, the system efficiency is maximized, and the system is autonomous and personalized.

The application relates to an intelligent composite energy storage heating system and belongs to the technical field of energy storage heating. The system outputs a high-precision heat supply and demand prediction result through an energy supply and demand prediction module; a storage regulation and decision module generates a comprehensive judgment through a storage state-health degree two-dimensional collaborative evaluation mechanism, and outputs a storage medium dynamic regulation and control strategy, a phase change heat storage component control scheme and a corrected energy start-stop threshold value relying on a hierarchical coupling regulation and control mechanism; a heat exchange optimization module constructs a multi-objective collaborative regulation and control mechanism, dynamically adjusts the contact matching mode, the flow channel adaptation form and the heat medium conveying rhythm of the heat medium and crude oil, and generates optimal heat exchange output; and an energy regulation and control module suppresses energy fluctuation based on a fluctuation grading buffer mechanism, triggers an emergency regulation and control scheme, and simultaneously corrects a subsequent prediction trend judgment benchmark. Through collaborative application of multiple mechanisms, the application effectively guarantees stable operation of the system under working condition fluctuation and mutation scenes, and is suitable for crude oil heating and other energy storage heating scenes.

The invention belongs to the technical field of aero-engine cooling design and flow heat exchange optimization, and provides a turbine blade cooling turbulence rib construction method, system and configuration based on level set topological optimization and a blade. The method comprises the steps that a fluid-solid coupling calculation model containing a cooling channel fluid domain and a blade wall surface solid domain is constructed, defining a level set function to implicitly represent the two-phase region; establishing a unified control equation set covering a full computational domain based on the function, and introducing a flow velocity suppression mechanism into a solid domain to carry out single-domain coupling solution of fluid flow and solid heat conduction; according to the physical field solution, constructing an optimization model taking the cooling performance as a target function and the volume fraction of the turbulent flow rib as a constraint, and calculating the sensitivity of the target function to a level set function; using the sensitivity to drive a level set function update to evolve a spoiler rib boundary; iterating until convergence and outputting the final geometric configuration of the turbulent flow rib. According to the invention, the irregular turbulent flow structure with high heat exchange efficiency and low flow resistance can be automatically generated without presetting a rib type.

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 belongs to the technical field of transformer heat dissipation, and discloses a SiC power electronic converter heat dissipation system multi-objective heat optimization method, which can add temperature uniformity as an optimization target to multi-objective optimization design, and form a three-dimensional multi-objective optimization design method together with pressure drop and thermal resistance. The final optimization result is that the Pin-Fin heat dissipation structure (which is different channel width, depth and spacing when applied to microchannels, and other heat dissipation structures can be analogized in this way) with different diameters, lateral spacings and longitudinal spacings along the heat accumulation direction, and such a structure can make the corresponding chip have different junction flow thermal resistances, so as to compensate for the chip temperature non-uniformity caused by fluid heat accumulation. The working efficiency of the heat dissipation system can be effectively improved, and the temperature non-uniformity of the power electronic converter can be effectively reduced.

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

The application provides a multilevel weight evaluation method for wellhead clean heating optimization scheme, and belongs to the technical field of oilfield wellhead heating. The technical scheme is as follows: a multilevel weight evaluation method for wellhead clean heating optimization scheme comprises the following steps: establishing a wellhead heating test platform, establishing a multilevel evaluation system, the first layer is a criterion layer including technical benefits, economic benefits and social benefits; the technical benefits include primary energy utilization rate, technical maturity and equipment maintainability; the economic benefits include investment, operation cost and investment recovery period; the social benefits include resource availability, policy support and balanced energy structure; the weights of the three criterion layers are determined by experts; the weights of each sublayer index are determined by using independent weights; the comprehensive scores of all schemes are calculated, and the highest score is the optimal scheme. The application is based on the wellhead heating test platform, simulates field conditions, is accurate in data, and can objectively and accurately evaluate the wellhead clean heating optimization scheme.

The invention provides a chip three-dimensional stacking structure, electronic equipment and a thermal optimization method, and belongs to the technical field of semiconductors. The memory module of the chip three-dimensional stacking structure is stacked on the upper surface of the logic chip, and the memory module comprises at least one memory chip which is sequentially stacked in the preset direction; the logic chip comprises a plurality of core groups, each core group comprises at least one performance core and an energy efficiency core, each performance core is used for processing calculation-intensive calculation tasks in the corresponding core group, and the energy efficiency core is used for processing memory-intensive calculation tasks in the corresponding core group; the energy efficiency core of each core group is connected with each performance core in the group, and the energy efficiency core of each core group serves as an agent core of the core group to which the energy efficiency core belongs to communicate with other core groups. According to the logic chip, the heterogeneous design of the performance core and the energy efficiency core is adopted, the power consumption of the logic chip is reduced, heat production of the logic chip is reduced, heat flow distribution is improved, and temperature distribution is more uniform.

The invention belongs to the technical field of optimization of a green electricity heat supply system. The invention provides a green electricity heat supply optimization method fusing load characteristic decomposition and equipment dynamic characteristics, and aims to solve the problems of space-time mismatching, non-quantitative extraction of load characteristics, simplification of the equipment dynamic characteristics and the like caused by renewable energy source intermittency and load volatility in a green electricity heat supply system. Then, through three-layer wavelet decomposition, electric load approximate power and detail power signals are extracted; constructing dynamic models of the electrode boiler and the solid heat storage boiler based on energy balance and dispersing the dynamic models into state space models; further constructing an optimization model with minimum annual total cost and carbon emission as targets; and finally, solving by adopting a multi-target particle swarm algorithm, and realizing energy storage and power grid collaborative energy supply in combination with a power distribution parameter. According to the method, the energy supply stability and the renewable energy consumption rate can be improved, design reference deviation and insufficient equipment output are avoided, economy and environmental protection are both considered, and reliable support is provided for industrial heat energy decarburization.

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 utility model belongs to the technical field of heat dissipation of electronic equipment, and discloses a production device of a GPU (Graphics Processing Unit) immersed heat dissipation system, which comprises splice plates and an oil pump system, each splice plate is a container which is formed by connecting at least two splice plates and is provided with an opening at the upper part, a plurality of server cases are connected in a box body, the outer surface of each splice plate is provided with a groove, and the oil pump system is arranged in the groove. According to the scheme, through the combined design of the aluminum spliced box body and the snakelike coil pipe, triple heat dissipation optimization is achieved, the snakelike cooling flow channel outside the box body greatly increases the heat dissipation area, and oil temperature is rapidly and evenly conducted in cooperation with the high heat conductivity of aluminum materials; the main oil pump and the secondary oil pump cooperatively work to form gradient circulation, the temperature difference in the box body is controlled within + / -1 DEG C, and uniform heat dissipation of each GPU is ensured; for a high-load GPU, heat dissipation of a hot spot area can be independently enhanced through the internal circulation oil pump, the problem of oil temperature layering in immersed heat dissipation is effectively solved, and the method is particularly suitable for long-term stable operation of the high-power GPU of a data center.

The application discloses a kind of based on layered optimization and multi-stage decision-making multi-heat source heating optimization operation method, comprising: constructing upper layer heat source dynamic scheduling model, to system multi-heat source joint scheduling operation benefit maximum, carbon emission minimum as objective function, set system operation constraint condition, optimization object is multi-heat source joint operation scheduling scheme;Upper layer heat source dynamic scheduling model is converted into the Markov process of multi-stage decision-making, in each decision-making stage, the process of cyclically carrying out heating system environmental state observation, making action decision, system state update and feedback reward and punishment information, and the Markov process of multi-stage decision-making is solved by reinforcement learning algorithm and obtains multi-heat source joint operation scheduling scheme;Build lower layer carbon emission evaluation model, obtain carbon emission heat source real-time carbon emission by establishing carbon emission evaluation model, and judge whether carbon emission reaches carbon emission reduction target, and correct multi-heat source joint operation scheduling scheme.

The invention relates to the technical field of high-speed train energy-saving control, and discloses an economic performance evaluation method and system for a ventilation and heat dissipation scheme of a high-speed train equipment compartment. According to the method, the comprehensive economic index with the sum of the train aerodynamic resistance energy consumption amplification and the fan equivalent energy consumption as the core is constructed, the optimal scheme is further determined according to the comprehensive economic index, and quantitative evaluation of the energy-saving performance of the equipment compartment ventilation and heat dissipation optimization system is achieved. According to the method, the coupling relation between aerodynamic resistance and fan energy consumption is established, and traditional separated aerodynamic analysis and electric energy consumption calculation are unified in the same framework, so that the comprehensive influence of different ventilation and heat dissipation optimization schemes on the energy consumption of the whole vehicle can be comprehensively reflected, and the energy-saving effects of the different optimization schemes can be accurately measured.

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 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.

An adaptive charging thermal optimization system for an electrified vehicle includes a set of thermal management components each configured to thermally condition a high voltage battery system of the electrified vehicle and a control system configured to detect whether the electrified vehicle is plugged into electrified vehicle supply equipment (EVSE) and, in response to detecting that the electrified vehicle is plugged into the EVSE, determine a set of charging parameters and limits for the high voltage battery system and the EVSE, determine a type or mode of the EVSE, determine a temperature setpoint for the high voltage battery system based on the charging parameters and limits for the high voltage battery system and the EVSE and the type or mode of the EVSE, and control the set of thermal management components based on the determined temperature setpoint and a measured temperature of the high voltage battery system.

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.