437 results about "Simulation modelling" patented technology

The invention discloses a gas pipe network fault positioning method based on a space-time diagram neural network, and the method employs an edge-cloud collaborative architecture, and achieves the precise detection of leakage points through simulation data generation, multi-modal perception, dynamic space-time modeling and hierarchical positioning. Firstly, simulation modeling is conducted on a pipe network, a multi-working-condition leakage data set is generated, and monitoring point layout is optimized through fuzzy clustering; a multi-modal sensing unit and a lightweight anomaly detection module are deployed at an edge end to realize coarse-grained anomaly detection and data hierarchical transmission; the cloud constructs a dynamic space-time diagram neural network, integrates a pipe network topological structure, multi-source time sequence data and physical constraints, and realizes high-precision positioning of leakage points through a hierarchical positioning strategy; and finally, realizing online evolution of the model through elastic weight solidification and hierarchical parameter updating. According to the method, the space-time diagram neural network and the physical characteristics of the pipe network are deeply fused, and the problems that space-time coupling features are difficult to extract and physical constraints are missing in complex pipe network fault positioning are solved.

The invention relates to the technical field of cultural heritage digital protection, in particular to a super-volume historic building three-dimensional simulation modeling method based on multi-source heterogeneous data, and the method comprises the steps: firstly collecting node multi-source heterogeneous data such as laser point cloud, images, structural mechanical parameters and historical repair records, and then carrying out node feature enhancement through a node feature enhancement module; using an improved generative adversarial network to strengthen node edge features, adopting an adaptive threshold segmentation algorithm to extract surface texture features, converting mechanics and size data into a three-dimensional constraint condition parameter matrix, then using a topological relation verification algorithm, using a graph neural network to traverse and verify a component connection relation, and obtaining a three-dimensional confrontation model; and a re-calibration mechanism is triggered when the deviation exceeds the limit, the weight is adjusted based on a Bayesian optimization algorithm, fusion verification is carried out again, finally, hierarchical grid division is adopted to construct high-precision sub-models, and the sub-models are spliced into an integral three-dimensional model, so that the model precision and reliability are improved, and reliable digital support is provided for ancient building protection.

The invention relates to the technical field of data analysis, in particular to a new energy power generation equipment health management platform based on a large model, which comprises a data acquisition and perception layer, an edge computing layer, a cloud processing layer and an application service layer, compared with the prior art that static historical data or single equipment parameters are adopted as a health detection reference, and the influence of environment dynamic change and equipment aging cannot be reflected, the scheme adopts a multi-dimensional simulation modeling technology, equipment parameters, weather parameters and other real-time working condition data are integrated to construct a digital twinborn model, and the digital twinborn model can be used for real-time health detection. Dynamic health reference values including generating capacity, instantaneous current / voltage, equipment temperature and the like are generated by simulating equipment operation states (such as photovoltaic efficiency attenuation at an extreme temperature and aerodynamic load of a fan in a salt mist environment) in different scenes. The method can accurately capture the interaction effect of the environment and the equipment, enables the health detection threshold to be dynamically adjusted along with the working condition, and improves the anomaly recognition accuracy by more than 35% compared with a traditional method.

The invention relates to the technical field of industrial image recognition, in particular to an automatic visual inspection system applied to charging pile production. The method comprises the following steps: the image enhancement module is used for acquiring an omnibearing production monitoring image; carrying out image detail convolution enhancement on the omnibearing production monitoring image, and carrying out topological structure fitting to generate a component topological structure diagram; the twinborn model module is used for performing production process action recognition on the assembly topological structure diagram based on the omnibearing production monitoring image, performing three-dimensional simulation modeling and constructing a dynamic production twinborn model; and the deviation identification module is used for identifying the position deviation of the dynamic production twin model assembly according to a preset production planning log, then carrying out reference positioning deviation calculation, and generating assembly position deviation parameters. According to the invention, efficient and accurate charging pile production diagnosis detection is realized, so that the production process of the charging pile is optimized.

The invention relates to the technical field of finite element simulation modeling, in particular to a model construction method, device and equipment for simulating an air effect in a honeycomb aluminum barrier. The method comprises the following steps: building a target honeycomb block simulation model containing a single-degree-of-freedom discrete beam unit; performing a quasi-static working condition test, and performing benchmarking to construct a honeycomb block static extrusion target simulation model based on a result of the quasi-static working condition test and the target honeycomb block simulation model; a dynamic working condition test is carried out, and a honeycomb block finite element model coupled with the air effect is constructed through benchmarking based on the result of the dynamic working condition test and the honeycomb block static extrusion target simulation model; and on the basis of the honeycomb block finite element model of the coupling air effect, according to a preset skin grid and a preset connection relation, a honeycomb aluminum barrier overall model is generated. Therefore, the problems that in the prior art, the simulation result of automobile collision is inaccurate, and automobile body deformation does not conform to reality are solved, the automobile collision simulation accuracy is improved, and the calculation accuracy and efficiency of the obstacle avoidance working condition are optimized.

The invention relates to the technical field of power systems, and discloses an industrial park distributed power utilization network simulation analysis power utilization behavior evaluation method comprising the following steps: S1, data acquisition: power load data, equipment operation state data and environment data of each power utilization unit in an industrial park are acquired in real time, and the environment data comprise temperature and humidity; s2, data preprocessing: preprocessing the collected data to obtain complete data; and S3, simulation modeling: establishing a power load flow model based on the park information and the real-time data, and performing simulation modeling to generate a dynamic model under various power consumption situations. According to the invention, through real-time data acquisition, dynamic load scheduling and a deep reinforcement learning algorithm, flexible optimal distribution of electric power resources is realized, the efficiency and stability of park electric power management are improved, stable operation of equipment is ensured, and energy waste is reduced.

The invention discloses an SWMM simulation model approximation method based on sparse attention and physical embedding, belongs to the technical field of simulation modeling, and aims to effectively process high-dimensional time sequence input through a sparse attention mechanism and embed physical constraints to ensure physical consistency of model approximation and ensure that an output result conforms to the law of flow conservation and pollutant conservation. The SWMM behavior is accurately approached; according to the method, a complex simulation behavior of the SWMM is replaced by an efficient deep learning prediction model, the calculation efficiency is remarkably improved, the credibility of a prediction result is ensured, the method is suitable for a real-time simulation scene of regional drainage optimization, and real-time simulation support is provided for regional hydrological management.

The invention belongs to the technical field of simulation modeling, and provides a high-fidelity three-dimensional reconstruction method fusing attitude prior and geometric constraint, which comprises the following steps: acquiring an original image, and determining an initial camera attitude based on a laser radar inertial odometer; determining error constraint information and relative attitude constraint information, and optimizing the initial camera attitude according to the error constraint information and the relative attitude constraint information to obtain a fine camera attitude; inputting the original image into an image reasoning model obtained by pre-training to obtain a surface normal map output by the image reasoning model; and constructing a three-dimensional Gaussian distribution model, determining geometric constraint information, and performing iterative optimization on the three-dimensional Gaussian distribution model by using the geometric constraint information according to the surface normal map and the fine camera attitude to obtain a three-dimensional scene model. According to the method, the overall reconstruction efficiency is improved through attitude prior and geometric constraints, and the authenticity, accuracy and efficiency of the scene reconstruction process are improved.

The invention belongs to the technical field of deep-sea mining environment assessment, and particularly relates to an autonomous multi-mode mining plume and redeposition thickness monitoring system and method, and the system comprises an autonomous underwater unmanned submersible and detection load equipment connected with the autonomous underwater unmanned submersible. The autonomous underwater unmanned submersible is used for carrying detection load equipment, providing electric energy for the detection load equipment, sending a control instruction to the detection load equipment, preprocessing received data returned by the detection load equipment, and sending an equipment state to the mother ship in real time, so that the mother ship can monitor the autonomous underwater unmanned submersible in real time; the detection load equipment is used for synchronously carrying out deep sea near-bottom mining plume and redeposition thickness monitoring in three detection modes of acoustics, optics and hydrology, carrying out multi-category data comparison and fusion in the same time coordinate system, and sending the collected data to the autonomous underwater unmanned submersible; and data support is provided for later deep-sea mining plume and redeposition simulation modeling.

The invention relates to the technical field of industrial data prediction and simulation modeling, in particular to a life loss prediction method and system for a petroleum transportation and transfer hose, and the method comprises the steps: generating loss distribution data of a hose material based on a multi-modal data fusion and multi-field collaborative simulation technology; according to the method, inter-regional resource allocation and model parameter optimization are realized through a quantum game optimization algorithm and a genetic algorithm, a high-precision regional loss prediction model is constructed, prediction model parameters are dynamically corrected through a difference analysis module of a digital twin system, simulation environment input parameters are iteratively adjusted in combination with a closed-loop feedback optimization process, and a prediction result is obtained. Generating high-precision life prediction data reflecting a real-time operation state; according to the method, the accuracy and adaptability of life prediction are effectively improved, the problem of insufficient response capability to complex working conditions in the prior art is solved, and reliable technical support is provided for operation maintenance and full-life-cycle management of the hose.

The invention relates to the technical field of diodes, and particularly discloses a high-temperature superconducting diode structure model which is used for solving the problems that an integrated circuit is high in power consumption and low in speed, and a traditional semiconductor technology is difficult to meet requirements. The semiconductor diode has the problems of power consumption and time delay, the research of the existing superconducting diode mostly focuses on low-temperature superconducting, low working temperature hinders the application and contradicts with the original intention of low power consumption, and the high-temperature superconducting diode which can work in a liquid nitrogen environment is urgently needed, including geometric, material and physical models. The geometric model is provided with a substrate with a superconductive microbridge strip with an asymmetric structure and metal films at two ends, the physical model contains an external magnetic field and current, and electromagnetic transport characteristics are analyzed through simulation modeling; through geometric structure and material selection and physical model setting, electromagnetic transport characteristics are analyzed by using the corrected RCSJ model, the geometric structure of the superconducting micro-bridge strip is optimized, and the problems of power consumption and speed of an integrated circuit are solved.

The invention provides an exhibition hall dynamic layout planning method and system based on three-dimensional modeling, and relates to the technical field of simulation modeling, and the method comprises the steps: building a layout simulation model of exhibition hall layout planning; performing association behavior response constraint on a layout evolution topological structure in the layout simulation model according to a cross correlation coefficient of display response characteristics among different display units to obtain a layout constraint condition among the display units; determining the spatial adaptability loss of each display unit under the condition of displaying different contents according to the change characteristics of the space utilization rate of each display unit under the condition of displaying different contents and the behavior feedback characteristics of the audience when each display unit displays different contents; and target optimization is carried out on the spatial streamline of each display unit in the target exhibition hall based on the layout constraint condition and all the spatial adaptability losses, and an optimal structure path for dynamic layout planning of the exhibition hall is obtained. According to the method, cost optimization of the exhibition hall layout structure can be realized based on the simulation model, so that the robustness of dynamic layout planning of the exhibition hall is improved.

The invention discloses a full-life-cycle-oriented product management system and management method, and relates to the technical field of product management, and the method comprises the steps: dividing a product life cycle, and determining the product data management content of each stage; performing preliminary analysis on the product data in the cache by using an AI technology; according to a root node number and a version number of a product, combining with the preliminary analysis report, recursively obtaining product data of each sub-node, constructing a virtual simulation model by utilizing a digital twin technology and combining with a classification result, carrying out full life cycle tracking through a block chain technology, and carrying out detection and warning by utilizing an AI technology; when the life cycle of the product is finished, product data updating is stopped; according to the method, the product life cycle is divided, the data management content of each stage is clarified, and the AI technology and the digital twinning technology are introduced, so that automatic acquisition, anomaly detection and simulation modeling of the product data are realized, and the overall efficiency and accuracy of product data management are remarkably improved.

The invention relates to a clean room airflow simulation modeling method and system fused with process layout optimization, belongs to the technical field of simulation modeling, and solves the problem that process layout and airflow cannot be optimized at the same time in existing simulation modeling. Comprising the steps of obtaining a process layout model, and constructing a label database according to a design general drawing, an architectural drawing and the process layout model; designing the purification air-conditioning system according to the process layout model and the label database, and determining design parameters; importing the process layout model and the design parameters into CFD pretreatment software to generate an initial model of the clean room, and arranging an air return passageway, a fan filter unit, a dry coil and a raised floor in the initial model according to the label database and the design parameters to obtain a fusion model; and grid division is performed on the fusion model to obtain a clean room airflow simulation model, then the clean room airflow simulation model is imported into CFD software for fluid simulation, and a process layout model of the clean room is optimized according to a fluid simulation result. And iterative optimization of the process and the airflow is realized.

The invention discloses an MBSE-based aircraft undercarriage system model integration method, and belongs to the technical field of system engineering. The method comprises the following steps: constructing an aircraft undercarriage system architecture, a classification mapping of simulation design information and a GOPPRR-E element model, and a meta-model library; constructing an architecture model according to a demand-function-logic-physical process, and generating a Simulink simulation model according to the architecture; a simulation model semantic mapping rule is constructed according to an OSLC specification, and design information is analyzed to establish an integrated data model; and a Simulink simulation tool integration adapter is constructed, and a tool interoperation service based on Web is provided. According to the method, a multidisciplinary model can be accurately constructed, uniform expression of architecture and simulation models and semantic consistency of heterogeneous models are realized, two-way transmission of cross-domain information and interoperation between tools are supported, the problem of interoperation between architecture modeling and simulation modeling tools in aircraft undercarriage system design is effectively solved, and the design efficiency is improved.

The invention provides a universal 3D intelligent modeling method for multi-view coupling constraint, belongs to the technical field of three-dimensional simulation modeling, and solves the problems that an existing intelligent three-dimensional modeling generation method is poor in generalization ability, a generation result is easy to over-fit, and multi-view geometric inconsistency is easy to occur. Comprising the following steps: optimizing learnable three-dimensional representation through a pre-trained text generation image diffusion model and a fine-adjusted multi-view generation diffusion model, and generating initial three-dimensional representation which is completely consistent with text semantics; according to the transparency prediction information of each point in the preliminary three-dimensional representation and the multi-view rendering graph of the preliminary three-dimensional representation, extracting and converting into a rough three-dimensional grid representation containing geometric structure and texture information; a geometry and texture decoupling optimization method is adopted, multi-view coupling constraints are combined, the geometrical shape and the surface texture of the triangular mesh are finely adjusted and optimized respectively, and a three-dimensional triangular mesh model with high-quality geometrical morphology and realistic texture is generated.

The invention provides a method and a system for predicting residual compression strength of a carbon fiber composite material after lightning stroke, and belongs to the technical field of electric digital data processing. According to the method, by considering the pyrolysis degree of the lightning stroke CFRP composite material, the non-linear mechanical property parameters related to the pyrolysis degree actually measured based on the test and the thermal and mechanical damage results predicted based on the electric-thermal-mechanical multi-physics field coupling model are calculated; an actually measured nonlinear mechanical property thermal damage factor and a mechanical damage factor caused by impact damage are introduced into a constitutive relation of the CFRP composite material, and a finite element simulation method capable of quantitatively predicting the residual compression strength after lightning stroke is established by virtue of finite element software ABAQUS; the problems that in the prior art, the influence mechanism of lightning stroke damage on the mechanical property of the CFRP composite material is not clear, and a simulation modeling method capable of being directly used for calculating and predicting the residual compression strength after lightning stroke is lacked are solved.

The invention discloses a TSV-based multi-layer microsystem interconnection module total dose effect simulation modeling method, and relates to the technical field of three-dimensional integrated microsystems, and the method comprises the steps: obtaining geometric parameters and material parameters of a multi-layer three-dimensional microsystem interconnection module, building a finite element model of a microsystem module based on the geometric parameters and the material parameters, and carrying out the simulation modeling of the TSV-based multi-layer microsystem interconnection module total dose effect. Setting boundary conditions and port excitation; scattering parameters under different material conditions in the finite element model are extracted, frequency points are fixed, and a relational expression of the scattering parameters and material parameters is established; an RLC equivalent circuit model is constructed, and an equivalent circuit extraction method is obtained; according to an equivalent circuit extraction method, in combination with a relational expression of scattering parameters and material parameters, establishing a relationship between return loss parameters and equivalent circuit parameters; and establishing a relation model between the radiation dose and the resistance, inductance and capacitance in the equivalent circuit according to the relation between the return loss parameter and the equivalent circuit parameter. According to the invention, a scientific basis is provided for the reliability design of the three-dimensional microsystem in the radiation environment.

The invention relates to a cross-vehicle-type collision waveform prediction method and device, a vehicle and a storage medium, and the method comprises the steps: obtaining a plurality of sample vehicle types, and a real vehicle collision waveform and a simulated collision waveform under a collision working condition corresponding to each sample vehicle type, a sample data set is constructed based on various sample vehicle models, collision working conditions, real vehicle collision waveforms and simulated collision waveforms; initializing a pre-constructed collision waveform prediction model to obtain an initial collision waveform prediction model; and calculating covariance of each sample vehicle model under different collision working conditions based on the sample data set and the initial collision waveform prediction model, training the initial collision waveform prediction model by using the covariance and the sample data set to obtain a final collision waveform prediction model, and performing collision prediction of the target vehicle model by using the final collision waveform prediction model. Therefore, the technical problems that real vehicle testing cost is too high, time cost and generalization performance are difficult to balance through simulation modeling, and high-precision collision waveforms are difficult to obtain efficiently in the prior art are solved.

The present invention discloses a simulation modeling method based on graphic matching recognition, comprising: obtaining configuration information of drawings in a source file of a first format, the configuration information including line segment information and text information; generating a redrawn picture and a mapping table according to the obtained configuration information, wherein the redrawn picture includes a library composed of line segments and connecting line segments between the libraries, and the mapping table includes a mapping relationship between text content and line segments and their position coordinates; identifying the library category, the attributes of the connecting line segments, and the parameter attributes in the mapping table in the redrawn picture according to a preset feature information library; converting the identified library category, the attributes of the connecting line segments, and the parameter attributes into a simulation model file; importing the simulation model file into a simulation modeling software to generate an executable simulation model. Correspondingly, a simulation modeling device based on graphic matching recognition is also provided. The simulation modeling method can improve modeling efficiency and modeling accuracy.

The invention relates to a three-level SVG multistage WARD equivalent modeling method based on an L / C constant admittance model. An ANPC type three-level converter model is an important part of various types of power electronic equipment, and is applied to scenes such as a three-level static var generator (SVG) and the like. In small-step offline simulation, an existing simulation modeling technology cannot consider precision and efficiency at the same time. Aiming at the problem that the simulation speed is extremely low in an offline simulation platform, a three-level SVG electromagnetic transient simulation acceleration model equivalent to a multi-stage nested fast simultaneous solution algorithm is provided based on a device Norton equivalent circuit. Firstly, an L / C equivalent constant admittance model is used for carrying out equivalent processing on a switching device, first-time WARD equivalence is carried out, then an equivalent circuit is connected with other transformer and filter inductance circuit parts, WARD equivalence is carried out again, and finally a Norton form equivalent circuit is formed.

The invention discloses a dynamic simulation modeling method for a compressed air energy storage system based on AMESIM and application, and belongs to the technical field of compressed air energy storage.The method comprises the steps that firstly, system indexes are determined, based on the system indexes, a system technological process diagram is designed, main equipment and auxiliary equipment are selected, and design point parameters of the main equipment and the auxiliary equipment in the energy storage and release stage are determined; then, according to the equipment model selection result, sub-models of all elements in the air circulation loop and the heat storage and exchange loop are selected in the AMESIM; thirdly, calibrating and verifying each main equipment sub-model by utilizing main equipment characteristics and model selection parameters, and building a steady-state simulation model of the compressed air energy storage system; and then, constructing a dynamic simulation model based on the steady-state model, and carrying out dynamic simulation verification and evaluation. According to the method, the co-simulation model integrating thermodynamics, fluid mechanics, control theory and mechanical dynamics can be quickly built, and the method has the advantages of being high in model modeling precision, high in multidisciplinary coupling calculation capacity, high in simulation efficiency and the like.

The invention relates to the technical field of mechanical equipment fault diagnosis, and particularly discloses an attention mechanism CNN-based electric actuator fault feature extraction method and system. The method comprises the following steps: through a mode of combining simulation modeling and field acquisition, obtaining a fault feature of an electric actuator; obtaining multi-source data of the electric actuator in a normal state, a known fault state and an unknown fault state, and preprocessing and enhancing the multi-source data; and constructing a lightweight convolutional neural network model containing a cross-modal attention mechanism. According to the method, multi-source signals such as current, voltage and displacement can be effectively fused, weights of different modes and characteristics are automatically distributed, and the extraction capability of key fault characteristics is enhanced; accurate distinguishing between known faults and unknown faults is realized through multi-scale feature complexity measurement and a dynamic discrimination mechanism; in combination with domain self-adaption and an incremental learning mechanism, the model can migrate between simulation and real working conditions, and has self-expansion capability for a novel fault mode.

The invention provides an electric field analysis method. Firstly, a target model is generated through simulation modeling, continuous electric field distribution data is obtained, a first data set and a second data set are established, rasterized image feature extraction is performed on the first data set and the second data set through a graph neural network, corresponding first graph features and second graph features are obtained, and a cascade grid processing network is used to process the electric field distribution data. Firstly, a target power line is predicted according to the first graph feature, then the target power line is converted into a target electric field mode according to the second graph feature, and finally an electric field prediction result is generated and a preset analysis process is executed. According to the method, through the combination of the graph neural network and the cascade grid processing network, the continuity characteristic of electric field distribution is effectively reserved, and meanwhile, the noise problem caused by discretization is avoided. And through rasterized feature data processing, the data demand and the calculation complexity are greatly reduced, and the efficiency and the accuracy of modeling analysis are improved.

The invention discloses a simulation data enhanced controllable-pitch propeller small sample fault diagnosis meta-learning method, and relates to the field of fault diagnosis, and the method comprises the steps: carrying out the simulation modeling and fault injection based on the working mechanism of a controllable-pitch propeller, and building a system fault model; constructing a fault simulation enhancement data set; constructing a variable-length time series data classification network model, wherein the model is connected with a multimode encoder and a triple loss function in combination with a residual error; training the variable-length time series data classification network model by utilizing a three-stage meta-learning training process, wherein the three-stage meta-learning training process comprises a meta-learning training process by utilizing an open source data set and a fault simulation enhancement stage by utilizing a fault simulation enhancement data set; and applying the trained variable-length time series data classification network model to an actually collected fault small sample data set for small sample task training. According to the method, the model is pre-trained by using the historical related data set, so that the current task data is reduced, training samples are reduced, and higher diagnosis precision is achieved.

The invention discloses a construction method of a concrete inner formwork supporting system for an ultra-large wind tunnel diffusion section. The construction method comprises the steps that S1, full-simulation modeling is conducted on a runner structure and a steel formwork according to a construction drawing by means of the BIM technology; s2, after processing by a factory, re-checking and splicing the steel templates by using BIM data, and pasting two-dimensional codes, and S3, carrying out on-site positioning and paying-off on each section of the inner steel template; s4, before the inner template supporting system is installed, the worker installs the inner template supporting system according to the sequence of animation demonstration of the BIM model; s4, before the inner template supporting system is installed, a BIM engineer makes and installs animation demonstration through the inner steel cylinder template BIM model, visual disclosure is conducted on field management personnel and workers, and the workers install the inner template supporting system according to the sequence of animation demonstration; effective combination of the bottom plate and the steel formwork can be effectively guaranteed, displacement of the steel formwork in the mounting process is prevented, defects existing in construction are reduced, and working efficiency is improved.

The invention relates to a simulation modeling method and system based on a natural language and computer equipment. Comprising the steps that natural language modeling simulation is achieved according to the technology of a large model, an intelligent entity and a protocol module, and the intelligent entity serves as a communication bridge between the protocol module and the large model. After a user question based on a natural language is obtained through an intelligent entity, a response of a large model to the natural language and communication interaction between the large model and a protocol module are triggered; the related target tool interface provided by the protocol module is called by the intelligent entity, so that the tool calling specification is ensured to be accurate, and the protocol module is enabled to determine and execute the target tool after the request is responded for multiple times. Therefore, through interactive use of the natural language of the large model, the use threshold of the user is reduced, the accessibility of the model is improved, codes do not need to be written or complex graphs do not need to be drawn, and the simulation modeling efficiency is greatly improved.

The present invention relates to the field of simulation modeling technology, specifically to an intelligent water conservancy design simulation system and method, the system comprising: a basin feature dynamic zoning module, a zoning adaptive modeling module, a multi-region coupling dynamic interaction module, a dynamic adjustment mechanism module, and a model verification and optimization module. In the present invention, by combining the water flow rate, flow volume and boundary condition adjustment, a dynamic water flow relationship model is constructed to improve the accuracy of fluid behavior modeling and the flexibility of flow simulation, and the dynamic coupling of the flow rate and pressure gradient interaction between regions is utilized to optimize the transfer of boundary parameters, enhance cross-regional data consistency and model continuity, dynamically adjust the permeability coefficient and water flow rate changes, correct boundary conditions, and enhance the model's ability to respond to real-time changes. Based on the error correction factor, the dynamic error of the zoning is reduced, and the precise control of water conservancy design parameters and the overall simulation reliability are improved.

The invention relates to the technical field of blasting, in particular to a method and system for eliminating rockburst through excavation blasting energy, and a finite element numerical calculation model of a tunnel is constructed through simulation modeling. And then determining the influence of the blasting energy to control the aperture of the gun barrel on the blasting process in the model, and further adjusting the aperture ratio in different directions, thereby realizing the accurate control of the blasting energy, further presplitting the deep surrounding rock, and achieving the purpose of eliminating the risk of rock burst. The blasting energy control gun barrel is designed around the explosive, the hole diameter of one side of the tunnel surrounding rock and the hole diameter of one side of the volley face in the tunnel are adjusted, the spreading direction and strength of the blasting energy are accurately controlled, and therefore the purposes of increasing surrounding rock cracks and reducing the rock burst risk are achieved. According to the method, the rockburst risk can be effectively eliminated, the blasting efficiency can be improved, the construction cost is reduced, and remarkable technical advantages and economic benefits are achieved.

The invention provides a thermal power generating unit deep peak regulation and efficient heat supply cooperative regulation and control method. The method comprises the steps of 1, thermodynamic modeling and performance analysis; 2, multi-section steam extraction optimal configuration; 3, designing a heat exchange and storage device; 4, dynamic regulation and control strategy development; and 5, verifying the system performance. According to the method, thermal performance and heat supply capacity of the unit under different load conditions are analyzed by constructing a thermal power unit thermodynamic simulation model, collecting operation parameters and performing thermotechnical calculation, steam distribution is optimized by adjusting the steam extraction proportion of a high-medium pressure cylinder and a low pressure cylinder, and meanwhile a heat exchange device and a heat storage device are designed and integrated. The method is used for balancing the heat supply capacity under the low-load and high-load working conditions. The dynamic regulation and control strategy further realizes real-time optimization and adjustment of combustion and heat supply, and ensures that the system stably operates under the deep peak regulation condition. Through simulation modeling and a dynamic regulation and control strategy, the heat energy utilization efficiency and the unit stability are effectively improved, meanwhile, coal consumption is reduced, and the deep peak regulation requirement is met.