8233 results about "Heat transfer" patented technology

The invention relates to the technical field of EPP (foamed polypropylene) production and manufacturing, and discloses an EPP foaming process parameter optimization method which comprises the following steps: monitoring temperature field and pressure changes in real time, and judging whether a thermodynamic state deviates from a preset window or not; during deviation, constructing a multi-physics field coupling model to evaluate a bubble growth dynamic unbalance risk, and identifying micro-pore non-uniform distribution characteristics through multi-source sensing data fusion and frequency domain analysis; and judging whether the technological parameters are globally coordinated and regulated based on risks and characteristics, analyzing the heat transfer and heat radiation influence of the temperature control unit, quantifying the parameter regulation sensitivity and determining the regulation priority. The system comprises a thermodynamic monitoring module, a dynamic coupling analysis module and the like. According to the invention, real-time monitoring, accurate analysis and intelligent regulation and control of the EPP foaming process are realized, the process stability and the product quality are improved, and the method is suitable for the field of EPP production and manufacturing.

The invention relates to a proton exchange membrane fuel cell (PEMFC) high current density performance prediction method, system, equipment and medium. The method comprises the following steps: establishing a multi-physical field coupling model which comprehensively considers complex processes such as electrochemical reaction, proton conduction, gas diffusion and heat transfer, and describing the change of each physical quantity by adopting a partial differential equation based on a basic physical law; performing grid division and numerical discretization on the proton exchange membrane fuel cell model; selecting model parameters, and verifying the model through experimental data of different working conditions; inputting actual working condition parameters into a model to predict performance, and analyzing a simulation result; using a convolutional neural network, a recurrent neural network and an auto-encoder to extract features from different types of data and fuse the features to form a comprehensive feature vector; a deep neural network prediction model is constructed, and a cross entropy loss function and an Adam optimizer are adopted for training; dropout, L1 and L2 regularization, k-fold cross validation and transfer learning are utilized to optimize the model, and the generalization ability is improved; the system, the equipment and the medium realize high current density performance prediction of the proton exchange membrane fuel cell (PEMFC) based on the method; the prediction precision is improved, the experiment cost is reduced, the internal mechanism can be deeply understood, and powerful support is provided for design optimization, operation management and fault diagnosis of the fuel cell.

The invention discloses an intelligent self-monitoring temperature management system for a box-type substation, and relates to the technical field of intelligent power grid equipment monitoring. The problems that an existing system is large in temperature measurement deviation, low in reliability, delayed in early warning, inaccurate in hot spot positioning and extensive in heat dissipation control are solved. According to the scheme, multi-source signals are acquired in parallel through a data acquisition module, and a temperature time sequence is extracted; a boundary calibration module is adopted to fuse data to generate a three-dimensional boundary condition; the multi-physical field solving module obtains an internal temperature / stress field; the physical information prediction module is fused with a heat transfer physical constraint training graph neural network to predict a hotspot migration trend; the hierarchical scheduling module is used for solving a fan and oil pump collaborative optimization instruction in real time based on model predictive control; according to the invention, the accuracy of internal temperature monitoring of the box transformer substation, the reliability of hot spot prediction and the accuracy of heat dissipation control are remarkably improved, the insulation life of equipment is effectively prolonged, and the operation safety and reliability of the system are improved.

The invention relates to the technical field of remote control, in particular to a steam boiler operation remote dosing control system which comprises a multi-source acquisition module, a state judgment module, a path switching module, a quality verification module and a health evolution module. According to the method, a monitoring system is constructed by fusing multi-dimensional parameters such as flow, pressure and temperature in real time, a single sensor error is eliminated through Kalman filtering, a heat transfer correlation model is established to quantify the water quality and thermal coupling relation, a pipeline blockage critical point is pre-judged based on grey correlation analysis, and non-inductive switching of a dosing path is achieved by adopting a double-electromagnetic-valve redundancy architecture. The stability of medicament conveying is verified by combining the flow offset of a standby path, closed-loop comparison of a concentration amplification value and a target value is synchronously executed to trigger self-calibration to correct the feeding deviation, a water quality adjustment-path switching-precision verification linkage control chain is formed, the abnormal response period is shortened, the scaling rate of a heat transfer surface is reduced, and the stability of the heat efficiency of the boiler is maintained. The equipment maintenance period is prolonged.

The invention relates to the technical field of electrical cabinet monitoring, in particular to an electrical cabinet active anti-condensation method and system based on a condensation mechanism mathematical model. According to the invention, a mathematical model based on a condensation formation mechanism is constructed, and environmental meteorological parameters, station room environmental parameters, electrical cabinet internal microenvironment parameters and cable trench state parameters are monitored through a four-stage monitoring system; and fusing the multi-source heterogeneous data, inputting a condensation mechanism mathematical model to calculate a condensation risk index, and adopting a hierarchical response mechanism to cooperatively control an execution mechanism according to the obtained condensation risk index value to realize active defense of condensation. According to the method, the condensation phenomenon with the space-time dynamic characteristic is quantitatively described through a mass transfer and heat transfer coupling equation, a grading prevention and control strategy and a cooperative control algorithm are developed by calculating the condensation risk index, setting the threshold condition and judging the condensation formation risk level, the prevention and control intensity is dynamically adjusted according to the risk level, and the control accuracy is improved. And the risk response speed and the resource utilization efficiency under the complex working condition are obviously improved.

A heat exchanger positioned within an annular duct of a gas turbine engine is provided. The heat exchanger extends substantially continuously along the circumferential direction and defining a heat exchanger height equal to at least 10% of a duct height. An effective transmission loss (ETL) for the heat exchanger positioned within the annular duct is between 5 decibels and 1 decibels for an operating condition of the gas turbine engine. The heat exchanger includes a heat transfer section defining an acoustic length (Li), and wherein an Operational Acoustic Reduction Ratio (OARR) is greater than or equal to 0.75 to achieve the ETL at the operating condition.

The invention belongs to the technical field of solid-liquid phase change heat dissipation, and discloses a memory alloy-based phase change expansion buffer structure, which comprises an elastic structure, a supporting structure, a thin wall, a cavity, a flaring, an electronic device, a heat sink, fins, a connecting structure and a phase change material, the thin wall is made of shape memory alloy and separates the internal cavity and the external phase-change material, the internal cavity is communicated with the external environment through the flaring, and in the flying process of the aerospace vehicle, external airflow flows into the flaring to take away heat stored by the phase-change material continuously. Based on the shape memory function of the memory alloy, additional space expansion buffering can be provided for the phase change material when the temperature changes, and stress damage caused by phase change expansion is avoided. The memory alloy thin wall and the elastic supporting structure are combined, the structure is simple, no moving part exists, circulating work in the high-temperature environment and the low-temperature environment can be achieved, local hot spots caused by internal gap movement of the phase change material in the circulating phase change process are reduced, and heat transfer deterioration is avoided.

An aqueous stream cleaning system including a circulation pump to receive a waste fluid and / or a concentrated liquid bottoms stream, and expel a circulation stream. The aqueous stream cleaning system can also include a primary heat exchanger to receive the circulation stream from the circulation pump. The primary heat exchanger can have a plurality of heat exchange plates that define an internal surface area for heat transfer from a distillate stream to the circulation stream to produce a cooled distillate stream and a heated circulation stream. The plurality of heat exchange plates can be spaced to facilitate free flow of solids in the circulation stream between the plurality of heat exchange plates. A mass flow rate and pressure of the circulation stream can be configured to minimize build-up of solids in the primary heat exchanger. The aqueous stream cleaning system can further include an evaporation unit to receive the heated circulation stream from the primary heat exchanger. The distillate stream is formed when steam in the heated circulation stream evaporates in the evaporation unit, and the concentrated liquid bottoms stream is formed from a portion of the heated circulation stream that does not evaporate.

The invention relates to the technical field of chip heat dissipation, and provides an immersed heat dissipation system with liquid nitrogen as a cooling medium and an integrated circuit assembly. In an immersed heat dissipation system with liquid nitrogen as a cooling medium, huge heat generated by a high-power-density chip under an extreme working condition can be efficiently absorbed and taken away under the extremely low working temperature and the large phase change heat absorption capacity, the heat transfer limit of a traditional cooling technology is broken through, and deep cooling of the chip is achieved; meanwhile, the liquid nitrogen is non-conductive and stable in chemical property, the electrical short circuit risk and physical and chemical corrosion problems caused by leakage of the cooling working medium are thoroughly eliminated, and the long-term operation reliability and safety of the immersed heat dissipation system with the liquid nitrogen as the cooling medium are remarkably improved. Therefore, stable operation of the chip under high load is guaranteed, physical damage and performance frequency reduction caused by overheating are avoided, and even favorable conditions are created for safe and efficient operation of the chip under higher working frequency.

The invention discloses a ship heat exchanger heat transfer performance simulation method, particularly relates to the field of heat transfer, and comprises the steps of multi-source data acquisition, characteristic parameter calculation, heat transfer stability diagnosis, comprehensive heat transfer degradation evaluation, structure reliability prediction and system efficiency comprehensive evaluation. Multi-dimensional data synchronous acquisition is realized through a multi-source sensor network, a dynamic coupling analysis model is constructed to accurately calculate the heat transfer stability and the comprehensive degradation index, a three-level early warning mechanism is established to improve the state evaluation accuracy, turbulence attenuation characteristics and vibration data are fused to predict the structural reliability, and the reliability of the system is improved. And closed-loop management and control is formed by combining an efficiency index triple evaluation system, so that the spanning from single alarm to preventive maintenance is realized, the health management capability of the system is comprehensively enhanced, and full-life-cycle dynamic optimization support is provided for the ship heat exchanger.

The invention provides a multiphase sewage heat exchanger performance prediction and structure optimization method and system based on an improved particle swarm algorithm, and relates to the technical field of waste heat resource recovery. The method comprises the steps that a performance database with working medium parameters and structure parameters as input and heat exchange and resistance performance as output is constructed based on multi-physics field numerical simulation; training a BP neural network by using the database to construct an initial prediction model, and globally optimizing model parameters by introducing a particle swarm algorithm of a dynamic inertia weight and an adaptive variation mechanism to obtain an optimized prediction model; and further calling the optimization model to carry out multi-objective optimization on the structural parameters by taking a Nusselt number and a Nanning friction factor as a dual-objective function, and outputting an optimal structural combination. According to the method, intelligent prediction and swarm intelligent optimization are fused, and the prediction precision and optimization efficiency of the design of the multiphase heat exchanger are improved.

The invention discloses a blast furnace cooling wall damage probability prediction method, which relates to the field of industrial equipment maintenance, and comprises the following steps: arranging a temperature sensor array, a vibration sensor and an acoustic emission sensor, and collecting temperature gradient data, mechanical vibration frequency and high-frequency stress wave signals in real time; calculating the slag crust thickness of the hot surface of the cooling wall based on an unsteady state heat transfer equation, introducing an in-furnace gas flow parameter correction model, and generating a dynamic slag crust thickness distribution cloud picture; establishing temperature and vibration reference threshold values under different working conditions according to historical operation data of the cooling wall, and detecting temperature over-limit accumulated duration and a vibration energy spectrum abnormal frequency band in real time; taking the temperature gradient range, the slag skin thickness variation coefficient and the vibration dominant frequency offset as input characteristics, training a multi-dimensional coupled damage probability prediction model through a random forest algorithm, and outputting a recent dynamic damage probability value of each section of cooling wall; and dividing risk grades according to the damage probability value, dynamically adjusting a threshold interval in combination with the real-time smelting strength of the blast furnace, and generating a differentiated maintenance suggestion set.

The invention provides a multi-temperature-zone temperature control system optimization method based on a gradient algorithm and segmented control, and the method comprises the steps: building a temperature control prediction model of each temperature zone through the gradient algorithm based on the thermal response characteristics of multiple temperature zones, determining a heat transfer path based on the predicted temperature data determined by the temperature control prediction model, and carrying out the optimization of the multi-temperature-zone temperature control system based on the thermal response characteristics of the multiple temperature zones. A temperature control process is divided into a plurality of stages, a corresponding stage temperature control strategy is established based on temperature control characteristics of each stage, optimal system precision is ensured through optimization and segmented control strategies based on a gradient algorithm, the stage temperature control strategies are optimized based on temperature difference between real-time temperature data and predicted temperature data, and the optimal system precision is ensured. The system can feed back and adjust the control parameters in real time, collect the actual temperature data at the end of each stage of the multiple temperature zones, optimize the heat transfer path based on the actual temperature data, and improve the energy efficiency of the whole temperature control system by optimizing the heat transfer path.

The invention relates to the technical field of industrial automation control, and discloses a water-based paint production and processing equipment control system, which comprises the following steps: acquiring stator current and rotor angular velocity, and reconstructing total load torque by using a sliding mode algorithm; extracting an input power low-frequency component to construct a heat dissipation slow manifold, and calculating a thermal drift disturbance component and an orthogonal residual component through orthogonal projection; on the basis of a two-component generation superposition instruction closed-loop adjustment driving mechanism, a double-time-scale orthogonal projection mechanism is utilized, non-structural thermal drift interference is automatically stripped under the condition that heat transfer parameters of equipment do not need to be predicted, the problem of control divergence caused by model parameter mismatch is solved, and decoupling control over the real rheological state of materials is achieved.

The invention belongs to the related technical field of heat dissipation of electronic equipment, and discloses a liquid cooling device and a preparation method and application thereof, and the method comprises the steps: S1, enabling a control equation of the liquid cooling device to be equivalent to a continuity equation, an N-S equation and a heat transfer equation based on equivalent parameters; s2, taking the minimum average temperature and energy dissipation of the whole design domain of the liquid cooling device as a target function, taking the volume fraction of the fluid domain as a constraint condition, and constructing a topological optimization model based on a continuity equation, an N-S equation and a heat transfer equation; s3, an optimization solver is adopted to carry out iterative solution on the topological optimization model, whether a result meets a convergence condition or not is judged, if yes, a topological structure is output, and the step S4 is executed; otherwise, updating the design variable of the topological optimization model, and turning to the step S1; and S4, the three-dimensional model of the liquid cooling device is corrected based on the obtained topological structure, and then blowing forming is carried out based on the corrected three-dimensional model to obtain the liquid cooling device. According to the invention, the cost is reduced.

The invention relates to the technical field of thermal equipment operation state dynamic test and compensation control, in particular to an AI-based boiler air pre-heater temperature uniformity regulation and control system, which comprises a collaborative closed-loop control network of a data acquisition module, an AI prediction module, a heat storage system control module, a temperature compensation control module and a thermal stress analysis module. The data acquisition module acquires flue gas temperature, coal quality parameters and load instructions in real time, the flue gas temperature, the coal quality parameters and the load instructions are transmitted to the AI prediction module through an industrial bus, XGBoost, LightGBM and a deep neural network model are used for carrying out spatial-temporal feature extraction on the evolution trend of a temperature field, and the heat storage system control module dynamically switches heat storage and release modes according to the load state. The heat distribution proportion among the multiple units is adjusted by combining the three-dimensional stress field distribution data of the thermal stress analysis module; the bottleneck of lack of thermal inertia regulation of an existing system is broken through, dynamic balance of a temperature field under the condition that thermal stress of a heat transfer element is controllable is achieved, and the heat exchange efficiency and operation stability of the air pre-heater are improved.

The invention discloses a multivariable self-adaptive collaborative optimization control system and method for a high-alkali coal boiler, and relates to the technical field of high-alkali coal boiler optimization control, the system is based on real-time operation data acquisition and multi-working-condition state recognition, and dynamic evaluation and collaborative adjustment of combustion heat transfer and physical coupling effects are achieved; by collecting a first data set, a second data set and a third data set, a high-alkali coal quality and load mapping relation is constructed, and a multi-working-condition state label is output; based on the label, the multivariable cooperative adjustment module calculates a combustion heat transfer coupling coefficient and performs efficiency judgment; the physical coupling effect evaluation module evaluates the boiler internal structure risk; and the dynamic control optimization module integrates multiple indexes to realize control response optimization. According to the system, through threshold value judgment and strategy feedback, the combustion efficiency of the high-alkali coal boiler is improved, structural safety guarantee and dynamic regulation and control optimization are achieved, and the operation stability and economical efficiency of the high-alkali coal boiler are remarkably improved.

The invention discloses a method for analyzing the influence of a rock mass multi-scale structure on deep geothermal reservoir circular mining, and relates to the technical field of geothermal resource development and rock mechanics, and the method comprises the following steps: establishing a reservoir rock mass mechanical analysis model and a seepage heat transfer analysis model which simultaneously comprise a microscopic microcrack structure and a macroscopic crack structure; based on the reservoir seepage heat transfer analysis model, reservoir temperature field and seepage field analysis is carried out, and water pressure and temperature distribution results are transmitted to the mechanical analysis model; based on the reservoir mechanical analysis model, reservoir stress and deformation analysis under the heat-water-force coupling effect is carried out, and changes of microcosmic microcrack and macroscopic crack structures in the reservoir rock mass are obtained; the rock mass permeability evolution equation and the porosity evolution equation are adopted to calculate the reservoir rock mass permeability tensor and the porosity, and the reservoir rock mass permeability tensor and the porosity are transmitted to the seepage heat transfer analysis model; and solving the reservoir temperature field, the water pressure field and the mechanical response in the geothermal circulation exploitation process by adopting a seepage heat transfer analysis and mechanical analysis staggered iteration mode. By analyzing the reservoir temperature, the water pressure, the deformation evolution response and the reservoir permeability change in the geothermal exploitation process, geothermal exploitation design and protection can be reasonably carried out, and the application prospect is good.

The invention provides a spacecraft quartz powder heat insulation tile which is prepared by adopting high-purity quartz powder (SiO2) as a main raw material and combining a high-temperature-resistant ceramic fiber reinforcement and a nano aerogel heat insulation layer through a high-temperature sintering process. The heat insulation tile has the following advantages: 1, the heat insulation tile has excellent high temperature resistance, and can tolerate 1600 DEG C high temperature for a long time and tolerate 1800 DEG C instantaneous thermal shock for a short time; 2, repeated use: the structure is stable, and high strength is still kept after multiple thermal cycles; light weight: the density is low (less than or equal to 0.5 g / cm < 3 >), and the load of a spacecraft is reduced; and 4, the thermal conductivity is low (less than or equal to 0.05 W / m.K), and heat transfer is effectively isolated. The method is suitable for thermal protection systems (TPS) of spacecrafts, such as thermal insulation of reentry capsules and rocket engine nozzles.

The invention discloses a deep learning-based middle-deep layer geothermal pipe group multi-field coupling simulation method, which comprises the following steps: carrying out numerical simulation cross mutual verification to obtain a middle-deep layer buried pipe heat pump system model, and carrying out system configuration by adopting a Monte Carlo method to obtain a first parameter environment set; screening the first parameter environment set according to a parameter environment function to obtain a second parameter environment set, performing data augmentation to obtain mid-deep layer geothermal pipe group simulation data, constructing a mid-deep layer geothermal pipe group multi-field coupling deep learning model, and obtaining simulation heat exchange data and prediction coupling heat exchange data; and adaptive grid optimization is carried out to obtain an optimized grid size, and the optimized grid size is adopted to adjust the mid-deep layer buried pipe heat pump system model to output the mid-deep layer buried pipe multi-field coupling model. According to the method, accurate and rapid simulation of the multi-field coupling process of the medium-deep geothermal pipe group can be realized under complex geological conditions, and the method has important practical significance for promoting large-scale development and utilization of medium-deep geothermal resources.

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.

A heat exchanger positioned within an annular duct of a gas turbine engine is provided. The heat exchanger extends substantially continuously along the circumferential direction and defining a heat exchanger height equal to at least 10% of a duct height. An effective transmission loss (ETL) for the heat exchanger positioned within the annular duct is between 5 decibels and 1 decibels for an operating condition of the gas turbine engine. The heat exchanger includes a heat transfer section defining an acoustic length (Li), and wherein an Operational Acoustic Reduction Ratio (OARR) is greater than or equal to 0.75 to achieve the ETL at the operating condition.

The invention discloses a multi-mode heat supply energy consumption evaluation method and system, and relates to the technical field of heat supply energy consumption evaluation and dynamic thermal scheduling control, and the method comprises the steps: arranging a multi-source sensor in a high-temperature flue gas path to collect thermal parameters, and building a time sequence mapping model between a unit load and flue gas thermal characteristics; and according to the thermal power data output by the time sequence mapping model and the heat exchange characteristics of all the heat supply modes, a heat energy availability map of the target time period is generated, and heat demand adaptation data is constructed. And selecting a matching path according to energy consumption and switching constraints based on the heat energy availability map and the heat demand adaptive data, and executing mode dynamic switching control. According to the method, a complete technical closed loop from data perception to state evaluation to action execution is formed. In the multi-mode heat supply system, system fusion of three-layer logic of heat load prediction, map expression and dynamic scheduling is realized, and the intelligence, self-adaption and energy efficiency optimization capabilities of the heat supply process are remarkably improved.

The disclosure describes a screen window liquid metal pad disposed between two opposing elements of an electronic device so as to provide a thermal pathway for an efficient heat transfer from one element to the other, comprising: a screen window and a liquid metal, wherein the screen window includes a frame with a window and a thermal conductive mesh; wherein the frame includes a top piece and a bottom piece, a peripheral portion of the thermal conductive mesh is fixed between the top and bottom pieces through an adhesive and the remaining portion forms a window screen covering the window of the frame; and wherein the liquid metal fills in and covers at least part of a middle portion of the window screen.

The invention relates to a thermal simulation numerical simulation method of a multi-physics field architecture with CFD as a core, and belongs to the technical field of cross of computational fluid mechanics and heat transfer science. The method comprises the following steps: constructing a geometry and a conformal / non-conformal grid, presetting a model library, establishing association between a region and a physical field through physical group division, confirming a boundary and initial parameters, and screening a core simulation model; dividing an independent control volume based on a core numerical model, converting an area component and a volume component through integral operation, discretizing a boundary flux to construct a parameter matrix, then solving an equation set, and synchronously optimizing the grid quality; calculating a boundary flux and matching a discrete format, a turbulence model and a corresponding multi-physical field coupling model; original data are screened and processed, and cloud picture results such as temperature and flow field are generated through visualization. Accurate simulation of a multi-physics coupling scene is achieved, the precision and stability of thermal simulation under complex working conditions are improved, and efficient and reliable technical support is provided for engineering design optimization and performance evaluation.

The invention relates to the technical field of distribution boxes, and particularly discloses a distribution box potential fault prediction method and system based on infrared image feature extraction. The multi-time-sequence infrared image set information of the distribution box is obtained, compared with a traditional temperature sensor, monitoring is more comprehensive, the overall temperature field can be reflected, the fault prediction accuracy is improved, a basis is provided for follow-up analysis, after information is obtained, according to space temperature gradient characteristics, multi-stage correlation areas are divided, heat distribution correlation is conducted, and a thermal stress correlation matrix is obtained; analyzing a heat transfer rule; local fluctuation information is obtained according to texture energy distribution characteristics, abnormal point location distribution information is obtained in combination with a thermal stress matrix, and early-stage tiny fault recognition is enhanced; and obtaining associated heat conduction information of adjacent areas according to associated features, associating with abnormal point locations, analyzing a fault influence range, obtaining a comprehensive fault feature value according to a fractal geometric algorithm and the like, comparing the comprehensive fault feature value with a preset value, judging a fault type and performing early warning, comprehensively reflecting a temperature field, and solving the problem that early potential faults are difficult to recognize.

The invention discloses a lithosphere thermal structure analysis method, device and equipment and a storage medium, and relates to the technical field of geothermal energy analys.The method comprises the steps that rock information of a current area is obtained, a current lithosphere model is constructed, and the current lithosphere model is composed of a plurality of layers of lithologic units; according to the rock information and a preset temperature change rule, determining a surface earth heat flow value and a lithosphere bottom boundary position corresponding to the current lithosphere model; according to the rock information, determining a hierarchical heat flow value corresponding to each lithologic unit located above the bottom boundary position of the lithosphere, and obtaining a lithosphere heat flow value according to each hierarchical heat flow value; and determining a heat flow ratio parameter as a lithosphere thermal structure analysis result of the current area by combining the earth surface heat flow value and the lithosphere heat flow value. According to the method, the heat flow ratio parameter is obtained by performing layered modeling on the lithosphere, so that accurate quantification of the lithosphere thermal structure is realized from the aspects of heat source properties and a heat transfer mechanism, and the reliability of an analysis result is improved.

The invention discloses a rapid heat transfer simulation method and device based on a neural network, and relates to the technical field of physical simulation. The method comprises the steps that a hybrid neural network model is trained, the model learns operator mapping from an input function to a temperature or heat flow field, and meanwhile physical constraints such as a heat conduction partial differential equation are coded into a loss function; for a new simulation task, single forward inference is carried out by using the operator mapping, and an initial prediction result is rapidly generated; then, according to physical constraints of coding, calculating a physical residual error of initial prediction, and when the residual error exceeds a preset threshold value, executing a small amount of optimization iteration by taking the prediction as an initial value to carry out rapid local correction; the problems that a traditional numerical method is long in calculation time and an existing neural network method is insufficient in physical fidelity are solved, and high efficiency and high precision of heat transfer simulation are achieved.

The invention relates to the field of intelligent detection, and provides a phase change energy storage heat reservoir anomaly detection system and method based on deep learning, and the method comprises the steps: carrying out the independent time sequence coding of the PCM temperature, the inlet and outlet temperature, and the environment temperature, so as to extract the time correlation characteristics of all parameters; performing bitwise difference operation on the environment temperature time sequence correlation implicit features and inlet and outlet temperature time sequence correlation implicit features to strip noise interference of environment temperature fluctuation on a heat transfer link from a feature space, and constructing a thermodynamic response model between the inlet-outlet temperature and the PCM temperature by using chain reasoning coding; pCM temperature simulation features based on normal working conditions are generated, and finally, thermodynamic constitutive relation deviation degree detection after environmental noise decoupling is achieved by comparing difference vectors of the simulation features and actual features. Therefore, the detection sensitivity of the abnormity of the phase change energy storage heat reservoir can be obviously improved.

The invention discloses an efficient gradient utilization medium and low temperature flue gas waste heat recovery system and method, and relates to the technical field of waste heat recovery. When the contact time between the medium and low temperature flue gas and a heat medium is short and the heat conduction contact area is small, the heat transferred to the heat medium by the medium and low temperature flue gas is small, the waste heat recovery amount is small, and the recovery effect is affected. The arc-shaped recess in the center of the inner side of the heat medium bin is matched with the smoke exhaust mechanism, the contact area between the inner side of the heat medium bin and smoke is increased through the recess, the smoke exhaust mechanism limits smoke exhaust, the contact area between the smoke and the heat medium bin is increased, and meanwhile the contact time between the smoke and the heat medium bin is prolonged; the heat of medium and low temperature flue gas is more effectively transferred to the heat medium in the heat medium bin, and the situation that the flue gas and the heat medium bin are small in contact area and short in retention time, heat is not completely transferred and discharged, and the waste heat recycling rate is low is avoided.