1254 results about "Thermal coupling" patented technology

The invention relates to the technical field of power equipment state monitoring, in particular to a lightning arrester state monitoring method, system and equipment based on multi-physics field coupling and a storage medium. Acquiring current-voltage characteristic parameters, temperature distribution data and mechanical stress data of the lightning arrester, performing electro-thermal-mechanical coupling analysis based on multi-physical field monitoring data, identifying overlapping positions of an electric field distortion area, a temperature abnormal area and a stress concentration area, and determining the overlapping positions as a degradation key area; establishing a correlation response relationship between the leakage current and the temperature and a transfer response relationship between the temperature and the mechanical stress for the deteriorated key area; on the basis of the leakage current change trend of the degradation key area and the coupling influence of the superimposed temperature field and stress field, a degradation feature fusion factor is constructed, the evolution law of the degradation feature fusion factor in the time sequence is analyzed, and the degradation threshold value under the multi-field synergistic effect is determined in combination with the electric-thermal coupling acceleration effect and the thermal-mechanical coupling weakening effect.

The invention discloses a CPLD-driven IGBT short-circuit current dynamic monitoring method and system, and relates to the technical field of power electronics, and the method comprises the specific steps of S100 real-time data acquisition, S200 dynamic threshold calculation, S300 short-circuit state judgment, S400 rapid protection execution, and S500 fault data recording and uploading. Accurate and prospective judgment of the short circuit state of the IGBT is achieved, two stress parameters including the direct-current bus voltage and the junction temperature serve as independent variables, when the bus voltage rises, the voltage stress borne by the IGBT in the turn-off period is increased, meanwhile, the current peak at the short circuit moment is more remarkable, early warning is conducted in advance by dynamically lowering the threshold value, and therefore the short circuit state of the IGBT is accurately judged. According to the mechanism, the monitoring system does not simply respond to the occurred overcurrent, but can pre-judge the safety boundary of the device under the current working condition, so that intervention is implemented before the current really reaches a dangerous peak value, and a protection blind area under a severe working condition is effectively avoided.

Disclosed in the present invention is a physics-informed neural network-based thermo-mechanical coupling analysis method for an inertial microsystem, the method comprising: S1, configuring material parameters and boundary conditions of an inertial microsystem, and establishing a thermo-mechanical coupling analysis model; S2, performing electro-thermal coupling analysis to obtain a temperature distribution of the inertial microsystem; S3, performing thermo-mechanical coupling simulation analysis to obtain a thermal stress distribution of the microsystem; S4, predicting temperature fields of the microsystem by means of a physics-informed neural network; S5, using the temperature fields as boundary conditions for mechanical simulation of the microsystem, obtaining mechanical properties such as stress and strain of the microsystem; and S6, performing electromechanical coupling simulation analysis to analyze the impact of structural deformation on various parameters of electrical performance. The present invention improves the solution accuracy of the neural network by means of an improved adaptive weighting strategy, combines a complete polynomial basis function with the neural network, and introduces an expanded basis function to reduce the state dimensionality, thus reducing computational costs and time, achieving accurate prediction of temperature fields of microsystems at multiple moments, and allowing for computation of the performance of microsystems under electro-thermal-mechanical multi-physics coupling.

The invention belongs to the technical field of intelligent home control, and particularly relates to an electric blanket intelligent temperature control system, which analyzes the matching relationship between the heating power and the temperature response in the historical operation cycle of a plurality of independent subareas of an electric blanket, fuses the thermal coupling effect between the subareas, and independently quantifies the dynamic thermal inertia parameter of each subarea. Based on the independent temperature change trend and the real-time temperature deviation of each partition, a control state including a steady state, a transient state or a strong compensation state is decided and maintained for each partition, the dynamic thermal inertia parameter, the real-time temperature deviation and the current control state are integrated, differentiated feed-forward compensation amounts are generated and superposed to the output of a PID controller of the corresponding partition, and the control state of the corresponding partition is calculated. A final power control instruction is generated after amplitude limiting and smooth filtering, temperature response lag caused by thermal inertia is actively predicted and counteracted, precise control is achieved in combination with partition state recognition, and the system response speed and control stability are remarkably improved.

The invention relates to the technical field of electrical digital data processing, and discloses a train ice melting simulation optimization method of an electromagnetic thermal coupling model fused with a deep learning method, which comprises the following steps of: inputting a geometric representation tensor and a physical working condition parameter vector containing an electromagnetic excitation frequency and a reference environment temperature into a feature mapping neural network; outputting a dual-channel space source item tensor containing basic heat source power density and a heat source to temperature change sensitivity distribution matrix through nonlinear convolution operation; constructing a heat conduction discrete numerical value evolution operator configured with an active item linear correction interface; time stepping operation is executed according to the heat conduction time scale, a basic heat source is corrected in real time through the Hadamard product of a sensitivity distribution matrix and temperature deviation, and an operator is substituted for solution. On the premise that electromagnetic-thermal nonlinear coupling characteristics are reserved, decoupling of the time scale is achieved, and the calculation efficiency in high-frequency physical field simulation is effectively improved.

The invention relates to a boiler flue gas temperature dynamic compensation method based on CFD-reinforcement learning, and belongs to the technical field of boiler operation control. The method comprises the steps that boiler operation parameters and flue gas temperature data are collected in real time, a multi-scale coupling three-dimensional CFD model is constructed, a macroscopic gas-solid two-phase flow-combustion reaction-radiation heat transfer coupling algorithm and a microcosmic pulverized coal particle combustion dynamics algorithm are fused, and hearth and flue temperature distribution is simulated and output; building a CFD-reinforcement learning fusion agent based on a CFD model, taking similar working condition agent parameters as initial values, combining historical and virtual data staged training, and reinforcing the weight of a key temperature measurement point through a focusing regulation and control strategy; an echo state network-predictive control collaborative algorithm is adopted, real-time data are input to obtain an initial adjustment amount, and after security constraint optimization, a compensation execution mechanism is controlled to act. The flue gas temperature is accurately and dynamically compensated, the adaptability to complex working conditions is improved, and equipment safety and operation efficiency are both considered.

The invention relates to a machining path planning system, in particular to the technical field of intelligent manufacturing and numerical control machining, and overcomes the defect that a thermal coupling effect is ignored in traditional geometric planning by constructing an evolution model fused with a physical law. A dynamic decoupling algorithm is utilized to extract a real cutting load from multi-source data and reconstruct a rigidity field changing along with material removal in real time, the problem that a physical boundary is difficult to perceive under a complex working condition is solved, and the system effectively eliminates size out-of-tolerance caused by heat accumulation through transient deformation advanced prediction. According to the method, the non-linear error is actively counteracted in cooperation with a reverse compensation strategy based on sensitivity analysis, the machining precision and surface quality of the thin-wall weak-rigidity part are remarkably improved, the rejection rate and trial cutting cost are reduced, and intelligent closed-loop control over the manufacturing process is achieved.

The invention relates to the technical field of chemical automation control, and discloses an intelligent closed-loop control system for producing p-dichlorobenzene by a biomass method, which comprises a signal acquisition module, a residence time reconstruction module, a thermal coupling analysis module, a parameter self-adaptive scheduling module and an execution control module. The rheological characteristics of raw materials are monitored by collecting the current of a stirring motor, the liquid level is dynamically increased through a retention time reconstruction module to prolong the retention time of the materials, and a liquid level periodic migration strategy is introduced to prevent scaling of a gas-liquid interface; the thermal coupling analysis module and the parameter self-adaptive scheduling module are used for calculating thermal retardation post factors, temperature control parameters are corrected in real time, the upper limit of cooling output is limited, inner wall supercooling crystallization is prevented, and the problems that the conversion rate is reduced, the heat transfer efficiency is reduced and equipment is hung on the wall due to viscosity fluctuation of biomass raw materials are effectively solved. And the self-adaptive stable control of the reaction process is realized.

The present application relates to the technical field of metal plastic forming, and discloses a titanium alloy radial forging reduction rate collaborative optimization method based on material testing, which acquires dynamic characteristic data of a forging process in real time through multi-dimensional material performance parameter collection, constructs a multi-objective collaborative optimization model, and realizes intelligent collaborative configuration of the reduction rate parameter by using an adaptive weight distribution strategy. A thermal coupling factor normalization equation and a phase field free energy functional normalization model are established to solve the technical problems of uneven structure and excessive residual stress caused by the empirical configuration of the reduction rate parameter in the traditional forging process. A lightweight model is deployed through an edge computing node, and millisecond-level dynamic correction of the optimization scheme is realized in combination with a 5G industrial private network, thereby improving the grain size qualification rate and size accuracy of titanium alloy forgings. The present application improves the grain size qualification rate of forgings, ensures stable control of the size accuracy while reducing the residual stress of forgings, and improves the batch stability of high-end titanium alloy components.

The invention discloses a mold partition temperature control system based on an air film adjustable thermal resistance boundary, and belongs to the technical field of mold temperature control and thermal management. The system comprises a mold body, at least two temperature control subareas and gas film adjustable thermal resistance boundary units arranged between the adjacent temperature control subareas. The air film adjustable thermal resistance boundary unit comprises a boundary air cavity, an air injection micropore, an exhaust adjusting structure and an air supply unit. Gas enters the partition boundary area through the gas injection micropores and forms a gas film layer, and the thickness, continuity, stability and coverage range of the gas film layer are changed by adjusting the gas supply pressure, the gas supply flow and the exhaust resistance, so that the thermal coupling strength between the adjacent temperature control partitions is adjusted. The system is suitable for injection molding, pressure casting, hot pressing and composite material forming molds.

The invention provides a tip Raman-based metal oxide nanoparticle in-situ detection method, which comprises: S1, dispersing metal oxide nanoparticles in a nanoparticle dispersion liquid, focusing laser to the tip of a nanometer tip through an objective lens, capturing a single nanoparticle by using an optical tweezers technology, and attaching the single nanoparticle to the nanometer tip; s2, focusing Raman laser on a nano needle tip-particle interface, generating a local high-temperature field through a photo-thermal near-field coupling effect, triggering a thermal chemical reaction of nano particles, and synchronously collecting a Raman spectrum; and S3, carrying out pretreatment and characteristic peak analysis on the collected Raman signal of the Raman spectrum, and determining the reaction critical temperature and the dynamic process in combination with temperature calibration data. According to the invention, capture and accurate heating of the nanoparticles are realized through photo-thermal coupling of the optical tweezers and the needle tip, and thermal chemical reaction monitoring of the nanoparticles is realized.

The invention discloses a synchronous reluctance motor magnetothermal coupling rapid calculation method based on a dynamic thermal network, and belongs to the technical field of motors. Comprising the following steps: calculating motor loss by adopting a finite element electromagnetic field model, and calculating a convective heat transfer coefficient by adopting a finite element fluid field model; constructing a three-dimensional thermal network comprising conduction, contact, convection thermal resistance, thermal capacity and a heat source, and solving to obtain an average temperature and a boundary temperature of component nodes; constructing a sub-domain temperature field calculation model of the heat source component, and calculating temperature distribution in combination with boundary conditions; introducing average temperature compensation thermal resistance and carrying out dynamic correction; carrying out magnetothermal coupling iteration, and updating the loss and the temperature until the precision is met; and introducing maximum temperature compensation thermal resistance into the thermal network, and solving to obtain an average temperature and a maximum temperature transient temperature rise curve of each component. Based on the technical means of combining electromagnetic field and fluid field finite element simulation with thermal network and subdomain temperature field calculation, efficient calculation of magnetothermal coupling of the synchronous reluctance motor is achieved.

The invention belongs to the technical field of welding process optimization, provides a pipeline welding parameter optimization method and system for natural gas conveying system construction, and is used for solving the technical problems of high hydrogen-induced cracking risk, parameter dependence on artificial experience and optimization process isolation lag in shallow hydrogen natural gas conveying pipeline welding. According to the method, a visual image of a molten pool, a joint thermal field, electric arc electrical parameters and environmental data are synchronously collected through a multi-source sensor, a hydrogen diffusion-thermal coupling model is constructed to calculate hydrogen concentration and stress, after reference parameters of a knowledge base are called, current, voltage and speed adjustment amounts are generated through a GBDT algorithm, and then real-time correction is conducted through a closed-loop module. According to the method, hydrogen-induced cracking can be quantitatively prevented and controlled, the weld joint failure probability in the shallow hydrogen environment is reduced, the process robustness and quality consistency are improved, the safe service life of the pipeline is effectively prolonged, and the high-safety energy conveying requirement is met.

The invention discloses a loop heat pipe and water heat storage coupling system and a working method, and belongs to the technical field of heat storage. The system has the modes of light gathering of the light-following trough heat collector, heat conduction of the loop heat pipe, heat storage of the water storage tank and warm water irrigation by using the stored heat water. When sunlight is sufficient in the daytime, the system converts solar energy into sensible heat of water in the heat storage water tank and stores the sensible heat, and the sensible heat is insulated by soil to slow down heat loss; when plants need to be irrigated, warm water in the irrigation water tank is used for irrigation; at night or in the absence of illumination, warm water in the heat storage water tank exchanges heat with air in the greenhouse, so that a lasting and stable heat supply source is provided for the greenhouse. Solar energy collected by the heat collecting groove is efficiently transmitted into the water tank through the loop heat pipe driven by temperature difference to be converted into sensible heat of water to be stored, the sensible heat is used for increasing the greenhouse temperature and irrigating plants when heat is needed at night, and the purposes of efficiently storing heat in the daytime and continuously supplying heat at night are integrally achieved.

The invention discloses an energy storage battery thermal diffusion modeling method based on P2D-solid heat transfer coupling, and relates to the technical field of energy storage battery thermal management. The method comprises the following steps: constructing a pseudo two-dimensional (P2D) electrochemical model and a three-dimensional heat conduction model of a single battery, and calculating lithium ion concentration, potential and corresponding heat source distribution; mapping the obtained heat source as a volume heat source to a thermal model and realizing bidirectional feedback; setting a thermal runaway triggering condition to simulate temperature rise abrupt change; battery SOH state modeling is introduced, and the aging process is dynamically corrected and reflected through material parameters; finally, time domain simulation is carried out, and temperature field evolution and safety behavior prediction in the whole life cycle are obtained. According to the method, the coupling process of the microelectrochemical reaction and the macroscopic temperature change of the battery can be captured at the same time, the thermal diffusion characteristics of different decline stages are accurately described, and visual modeling of thermal runaway behaviors is supported. The method has the remarkable advantages of high precision, high applicability, perfect safety assessment capability and the like.

The invention relates to the field of chip detection, and discloses a high-efficiency chip detection system and method, which are used for realizing long-term performance degradation detection of a chip. Comprising the following steps: synchronously acquiring power pin electric signals and chip surface thermal imaging data to generate an electrothermal coupling characteristic data set in a working state of a to-be-tested chip, and extracting impedance and heat conduction characteristic parameters through impedance spectroscopy analysis and thermal time constant calculation. And analyzing an internal signal transmission path based on impedance characteristic parameters to obtain path characteristic parameters, establishing a mathematical model of dynamic current and working voltage of the chip by combining the two, generating a system identification result, and finally generating a chip detection result and fault positioning information by integrating various parameters. According to the invention, system benchmark testing and environmental interference monitoring and compensation are carried out, and high precision and high robustness of a detection result are realized.

A lithium ion battery thermal management method based on physical perception and entropy cooperation multiple agents comprises the steps that a lithium ion battery electric-thermal coupling model containing data driving compensation is established, and a full-state space system equation describing the dynamic characteristics of a battery is established; constructing a TCN-Transformer hybrid neural network fused with a physical constraint mechanism, and carrying out online identification on parameters in the electric-thermal coupling model by adopting the network to obtain real-time parameters; based on the full-state space system equation and the real-time parameters, constructing a minimum error entropy adaptive extended Kalman filter optimized by an entropy cooperative multi-agent flexible Actor-Critic algorithm, and performing joint estimation on the state of charge of the battery and the temperature of the battery; and based on a joint estimation result, constructing a TD3 deep reinforcement learning control algorithm embedded with a microsecurity layer, and realizing the self-adaptive thermal management direct control of the lithium ion battery under rule guidance through the algorithm. According to the invention, accurate, effective and safe thermal management control of the lithium ion battery is realized.

The invention belongs to the technical field of thermal management, and particularly relates to a dynamic thermal management method and system for a cascade thermal coupling control system. The method comprises the following steps: judging the running state of the current cascade thermal coupling control system; based on the operation state, obtaining operation parameters of the cascade thermal coupling control system in real time; adjusting the heat flow path according to the operation parameters to obtain an actual heat flow value; obtaining a heat flow prediction value by using the heat flow prediction model, and comparing the heat flow prediction value with an actual heat flow value to obtain a heat flow difference value; and adjusting operation parameters of the cascade thermal coupling control system according to the heat flow difference value, and controlling the dynamic heat flow of the cascade thermal coupling control system. According to the invention, the objective function is constructed based on the LSTM neural network, and the state of the phase change material can be adjusted in real time in cooperation with the phase change progress-resistance value mapping model, so that the distribution of the heat flow is realized, and the dynamic management of the cascade thermal coupling control system is completed.

The invention discloses a cutting positioning method and device for laser cutting metal based on big data, and relates to the technical field of laser cutting. The invention discloses a cutting positioning method and device for laser cutting metal based on big data. The cutting positioning method comprises the steps that S1, thermal working condition data, process path spatial feature data and historical working condition data are preprocessed; s2, based on time sequence thermal fluctuation analysis, initial calibration is conducted on multi-point thermal expansion, thermal fluctuation and disturbance coupling space offset before cutting, and a fine compensation process is entered; s3, performing fine adjustment and high-precision track correction on a path node space through thermal coupling compensation theory analysis; and S4, performing real-time monitoring and graded intervention on time sequence response fluctuation and abnormal risks in the compensation process based on time sequence fluctuation and abrupt change criteria. The problems that complex coupling drifting is generated due to multi-source high-temperature instantaneous thermal expansion and deformation of a laser head and a workpiece under the limit cutting working condition, real-time accurate compensation is difficult to achieve through an existing positioning method, and the high-precision cutting stability is seriously affected are solved.

The invention provides a giant magnetostrictive bar multi-physics field coupling dynamic characteristic monitoring system. The giant magnetostrictive bar multi-physics field coupling dynamic characteristic monitoring system comprises a magnetic field loading module, a mechanical loading module, a thermal environment control module, a signal detection module and a signal processing module. The magnetic field loading module generates a broadband superimposed magnetic field through a direct-current bias coil and an alternating-current driving coil; the mechanical loading module applies prestress by adopting a hydraulic device; the thermal environment control module accurately controls the temperature within the range of-50 DEG C to 300 DEG C. The signal detection module is integrated with a B measuring coil, an H measuring coil, a laser displacement sensor, a pressure sensor and an acoustic emission sensor to realize high-speed synchronous acquisition of multi-physical field parameters; and the signal processing module transmits the data to the upper computer in real time based on the data acquisition card for recording and analysis. According to the system, a magnetic-force-thermal coupling excitation environment is constructed, the magnetostriction coefficient, the piezomagnetic coefficient, the magnetic conductivity and the loss angle of the giant magnetostriction bar are obtained, and the system is suitable for comprehensive evaluation of the performance of the bar under different bias magnetic fields, prestressing forces and temperature conditions.

The invention discloses a packaging substrate with a temperature detection function, a power semiconductor module and a manufacturing method thereof, and the packaging substrate with the temperature detection function comprises an integrated ceramic insulating layer which is provided with a first surface and a second surface which are opposite to each other; the temperature sensor comprises a ceramic insulating layer, a sensor mounting groove, an independent temperature sensor chip, an insulating filling body and a three-dimensional interconnection structure, and is configured to lead an electric signal of the temperature sensor chip to an external bonding pad on the second surface or the side surface of the ceramic insulating layer, the packaging substrate has the advantages that high-precision and quick response measurement of junction temperature of a power chip can be achieved, temperature rise decoupling deviation is eliminated, excellent high-voltage electrical isolation reliability is ensured while direct thermal coupling is achieved, the dielectric breakdown risk is avoided, the manufacturing method is flexible, the reliability of a power semiconductor module is improved, and the manufacturing cost is reduced. The comprehensive cost is reduced, and the long-term stability of temperature monitoring can be ensured while the rapid and accurate electrothermal response characteristic of the sensing unit is ensured.

The invention relates to the technical field of intelligent welding equipment, and discloses a metal product electric arc welding clamp which comprises a rack, a main workpiece fixing module, an auxiliary workpiece fixing module, a state sensing module and a control module, the main workpiece fixing module comprises a distance adjusting unit and at least two fixing parts, and each fixing part is composed of a lateral clamping unit and a top pressing unit. The main workpiece fixing module, the auxiliary workpiece fixing module, the state sensing module and the control module form an intelligent clamping system, a traditional passive rigid welding clamp is changed, a simplified thermal-mechanical coupling finite element model is constructed and operated in real time, the workpiece deformation trend and the stress state in the welding thermal process are accurately predicted, the force and the position of a clamping mechanism are actively adjusted in advance, and the welding quality is improved. The posture of the main station is continuously and stably maintained; therefore, the welding precision and consistency are improved, and the thermal deformation and residual stress of the workpiece are inhibited.

The invention discloses a rapid design method and system for a turbine blade, electronic equipment and a storage medium, and the rapid design method comprises the steps: firstly, obtaining boundary conditions of a gas side and a cold air side of the turbine blade in an actual working environment based on flow heat exchange test data, and then constructing a heat exchange boundary model based on the boundary conditions; according to the method, temperature field calculation becomes a pure solid heat conduction problem, and only depends on known boundary conditions and material attributes, so that a heat exchange boundary model can be directly applied to a blade three-dimensional model for transient temperature field calculation, and CFD simulation calculation needing iterative solution is replaced; by means of the method, the most time-consuming flow field solving and flow thermal coupling iteration link in the whole analysis process is thoroughly eliminated, the calculation efficiency is remarkably improved while the calculation precision is guaranteed, a thermal-force coupling chain is cut off through decoupling calculation of the transient temperature field and the transient stress field, and the calculation efficiency is further improved.

The invention relates to a rock core seepage heat exchange dynamic coupling simulation system based on outlet temperature feedback. The system comprises a multi-medium precise injection system, a gradient temperature control rock core clamping system, an outlet multi-dimensional information sensing system, a dynamic coupling central control system and a pressure compensation and circulation backflow system. The central control system receives feedback signals of the outlet end and adjusts injection power and an axial gradient temperature control area in real time, and deep dynamic coupling of a seepage field, a temperature field and a stress field is achieved. The problems that a traditional experiment is constant in injection temperature and lacks outlet feedback are solved, real stratum temperature scale distribution can be accurately reconstructed, the physical fidelity and data reliability of a heat exchange coupling experiment are remarkably improved, and an advanced experiment supporting platform is provided for basic mechanism research in the field of energy development.

The invention relates to a heat transfer system (10) with a heat source (14) and a heat sink (50), wherein the heat source (14) has a heat discharge arrangement (34) for heat discharge from the heat source (14) by means of a working fluid (12), wherein within the heat discharge arrangement (34) the working fluid (12) can be thermally coupled or coupled to the heat source (14), and wherein by means of the working fluid (12) the heat source (14) can be thermally coupled or coupled to the heat sink (50).A high and defined heat transfer over a large operating temperature range can be achieved by the heat transfer arrangement (34) comprising at least two stages arranged parallel in terms of flow, a first stage (36) and a second stage (42), for heat transfer from the heat source (14) to the working fluid (12), wherein the stages (36, 42) are designed such that they have a different thermal resistance between the heat source (14) and the working fluid (12).

The invention discloses a non-inductive cooperative regulation and control method and device for flexible loads in a building and a medium. The method relates to the field of power control, and solves the problem that a high-precision and quick-response flexible load regulation and control scheme is lacked. According to the method, the problem of space-time correlation adaptation of the equipment is solved by collecting the running state, environment and personnel distribution multi-source heterogeneous real-time data of the equipment, constructing the topological dynamic graph of the equipment, outputting nonlinear space-time correlation information and capturing the dynamic thermal-mechanical coupling relation between the equipment in real time. A personalized regulation and control instruction is generated by an independent decision-making unit to replace a fixed threshold value; coupling disturbance is predicted in combination with associated information, initial PID parameters are compensated, it is ensured that the temperature adjusting amplitude is converged to a user perception threshold value, and frequent starting and stopping of equipment are avoided. The independent decision-making unit and PID compensation are both based on local data operation, and the instruction response period is shortened; differentiated control instructions are converted according to equipment sensitivity, a high-sensitivity area is finely regulated and controlled to ensure comfort, and a low-sensitivity area preferentially responds to power grid peak clipping.

A three-dimensional vapor chamber module is configured to be thermally coupled to a heat source. The three-dimensional vapor chamber module includes a first vapor chamber, a second vapor chamber, at least one first heat pipe and a plurality of boiling enhancement structures. The first vapor chamber has a first fluid chamber, and the first vapor chamber is configured to be thermally coupled to the heat source. The second vapor chamber has a second fluid chamber. The first heat pipe has a first fluid channel, and the first fluid channel communicates with the first fluid chamber and the second fluid chamber. The boiling enhancement structures are respectively disposed on the first vapor chamber and the second vapor chamber.

The invention provides a heat supply digital twin modeling method and system based on a U3D engine and a medium. The method comprises the steps that a historical static data set and a historical dynamic data set are obtained for preprocessing, a historical static optimized data set and a historical dynamic optimized data set are obtained, a U3D engine is combined with a preset parameterized component library to conduct heat supply digital twinning model construction, initialization is conducted based on the historical static data set, and a heat supply digital twinning model is obtained. Obtaining an initial heat supply digital twinborn model, generating an LOD model set with different precisions through an LOD rendering method, inputting the historical dynamic optimization data set into the initial heat supply digital twinborn model for processing, obtaining a simulation data set and equipment operation state evaluation data, and evaluating the qualified state of the model through threshold comparison; according to the method, data security fusion is realized through the block chain, the hydraulic and thermal coupling model is constructed by using the U3D engine, and predictive maintenance and multi-objective optimization are realized through an intelligent algorithm, so that intelligent construction of the heat supply word twinborn model is realized.

A heat exchanger with a heat-exchanging portion is electrochemically deposited onto a base (for thermal coupling to a heat source) or directly on the heat source. The heat-exchanging portion comprises extensions that define openings (e.g., channels) for passing heat transfer fluid through the heat exchanger. The geometry of these c and / or openings varies throughout the exchange to achieve different unit-area thermal conductivities for at least two different portions of the heat-receiving surface. For example, the thickness, height, spacing, shape, and / or materials of the heat-exchanging extensions may be selected to achieve the desired heat transfer at each zone. This variability in unit-area thermal conductivities may be used to accommodate for “hot spots”, heating of the heat transfer fluid, fluid dynamics, and other factors associated with the heat exchanger operation. Electrochemical additive manufacturing (ECAM) is used to fabricate at least heat-exchanging extensions thereby enabling precise and zone-specific thermal transfer characteristics.

The invention discloses a differential active temperature control matching method and system based on fluid thermosetting coupling analysis. The method comprises the following steps: determining a multi-physical field action form of a machine tool structure; a fluid-heat-structure multi-physics field coupling simulation model is obtained, specifically, coupling simulation of a cooling fluid field, an endogenous heat field and a machine tool structure field is conducted in sequence, and an effective multi-physics field coupling simulation model is obtained; adopting a response surface design method to generate multiple groups of DOE analysis working conditions; a Kriging algorithm is adopted to construct an agent model and establish a mapping relation: based on the DOE sample points and simulation results thereof, the Kriging agent model is trained, and a mapping relation between machine tool detection parameters and active temperature control parameters is established through an automatic refining process; based on the mapping relation, performing multi-objective optimization on temperature control parameters by taking thermal deformation of the key position as a constraint, and realizing differential control strategy matching of each temperature control loop; the problem of thermal deformation caused by thermal characteristic change of a machine tool structure is solved.