1729results about "CAD network environment" patented technology

The invention relates to the technical field of logistics transportation, in particular to a logistics transportation route optimization method and system based on digital twinning. The method comprises the following steps: constructing a digital twin logistics base through multi-source heterogeneous data fusion and dynamic logistics network modeling; carrying out regional logistics distribution feature extraction and dynamic time sequence prediction based on a digital twinborn substrate to obtain a predicted regional transportation demand; performing real-time state evaluation on the line, generating a dynamic line performance matrix, and performing vehicle resource allocation in combination with the order task priority; and carrying out multi-objective solution and dynamic adjustment on the transportation scheduling scheme to finally obtain an optimal transportation scheduling scheme. And performing iterative optimization on the digital twin model through real-time deviation analysis and a feedback mechanism, and dynamically adjusting a transportation plan to form a closed-loop optimization process. Through the logistics transportation route optimization technology, the logistics transportation efficiency is remarkably improved, the cost is reduced, and the toughness of the system is enhanced.

A distributed water resource allocation method and which includes: acquiring a sub-basin in a setting region based on data of a digital elevation model, and dividing the sub-basin into a plurality of allocation units by applying a multi-attribute overlaying method; determining a spatial topological relationship between water users and water sources in the various allocation units according to a water supply priority of the water source and a water use priority of the water user; acquiring water demand data in an administrative region, and calculating a water supply amount of each water source as well as a daily amount of water allocation, water consumption, water discharge and pollutant discharge of each water user in the administrative region; constructing objective functions and constraint conditions; and resolving the objective functions based on the constraint conditions and by adopting a genetic algorithm, to obtain water resource allocation data.

The invention relates to the technical field of oil exploration, and discloses a geological digital twinborn model construction method and system in oil exploration. The method comprises the steps of receiving a multi-source heterogeneous geological data flow of a target exploration area, performing multi-scale alignment and feature fusion through a geological feature decoupling model, and generating a three-dimensional geological attribute field distribution map and the like. Constructing an adaptive grid division model to generate a dynamic flow field simulation instruction set; simulating dynamic response under reservoir exploitation disturbance based on a multi-physics field coupling model and optimizing simulation instruction set parameters; and iteratively updating parameters through a quantum computing optimization framework, and outputting a model construction sequence to an exploration decision platform. The system comprises a data receiving module, a feature processing module, a grid instruction generation module, a simulation optimization module and an output module. Multi-source data are integrated, the geological process is accurately simulated, the exploration decision is optimized, and the oil exploration efficiency and exploitation benefits are improved.

The invention relates to the technical field of special equipment intelligent monitoring and maintenance, in particular to a special equipment monitoring and maintenance method and system based on multi-dimensional data fusion, and the method comprises the steps: collecting and processing multi-source heterogeneous sensor data; constructing a dynamic digital twinborn model based on sensor data and a cross-domain term mapping rule; associating the sensor data with the digital twinborn model to establish a lightweight analysis model, performing health state simulation analysis on the edge equipment, and generating an analysis result; the data quality of the edge device is monitored through the analysis model, when the data quality is lower than a threshold value, a co-simulation process is started, a simulation analysis task is transferred to the cloud digital twin platform, and the edge device continues to conduct simulation analysis based on the analysis model; and constructing a simulation design decision rule base, and generating a maintenance suggestion. Through the multi-dimensional data fusion and edge cloud co-simulation architecture, the accuracy, real-time performance and reliability of monitoring and maintenance of the special equipment are improved.

A digital model platform that enables the streamlined creation and management of digital twins and physical twins by leveraging external feedback and artificial intelligence (Al) is disclosed. Methods and systems for a model collaboration platform that facilitate the integration of external feedback, whether from physical, virtual, or human sources, into the streamlined design, validation, verification, certification, assembly, operations, and maintenance processes of complex systems. Updated results are output to those external sources, including physical twins, other digital twins or models and simulations, and / or human users. External feedback includes feedback data from physical prototypes and their environment, virtual prototypes, simulations, and subject-matter experts. Embodiments are directed to integrating external feedback into the assembly and system-level assessment of digital twins, physical twins, digital threads, and the iterative design of constituting digital engineering models, including constructing, maintaining, and improving digital engineering models for the design, validation, verification, certification, operations, and maintenance of complex systems.

A digital documentation system for preparation of engineering documents utilizing one or more artificial intelligence (AI) algorithms is provided. The system includes a user interface for selecting and populating templates with data, and one or more AI algorithms for creating and recommending templates, and preparing documents based on the recommended templates. The system uses natural language processing and semantic analysis algorithms to understand the content of the templates, documents, and associated engineering data, and to generate and recommend relevant templates to the user based on user prompts. The system also uses machine learning and predictive modeling and decision-tree algorithms to assist with the preparation of documents, by generating suggestions for data fields and values based on the user's previous inputs and the overall context of the document and available engineering data, including model data and metadata from digital models accessed in a zero-trust framework.

The invention relates to the technical field of artificial intelligence, and discloses a method and system for assessing the propagation risk of bacteria in a chicken coop, and the method comprises the steps: collecting the multi-modal perception data of the bacteria in the chicken coop in real time through a distributed sensor array, carrying out the spatial-temporal feature extraction of the multi-modal perception data through a dual attention spatial-temporal diagram neural network, and obtaining the spatial-temporal feature of the bacteria in the chicken coop; the method comprises the following steps: generating a bacterial propagation risk prediction map with confidence evaluation, inputting the bacterial propagation risk prediction map into a digital twin platform, simulating a dynamic simulation environment of a chicken house by fusing a BIM model and CFD to obtain a CFD-BIM coupled dynamic simulation model, and constructing a deep reinforcement learning decision model based on the CFD-BIM coupled dynamic simulation model. And after the prevention and control execution instruction is fed back to the digital twin platform for virtual verification, a visual decision report is output. The method can improve the accuracy of risk assessment of bacterial propagation in the henhouse.

The invention relates to the field of shale oil and gas, and discloses a method for identifying a shale oil and gas reservoir dessert, which comprises the following steps: acquiring a core CT image, three-dimensional seismic data and production dynamic data, and carrying out cross-scale preprocessing; constructing a fractional-order non-local seepage field model to represent nano-to-kilometer-level flow characteristics; predicting seepage field parameters through a Lie group symmetry constrained neural network; establishing a cross-scale coupling model of the quantum adsorption effect and the macroscopic seepage law; dynamically updating model parameters based on real-time monitoring data; and executing multi-target collaborative optimization to generate a sweet spot three-dimensional distribution and development scheme. According to the method, a fractal dimension dynamic constraint cross-scale data fusion technology is adopted, the effect of accurate mapping of nanopore and macroscopic fracture network parameters is achieved, and the problem of misalignment of CT scanning and seismic inversion data space registration is solved through pore communication fractal analysis.

The invention relates to the technical field of energy efficiency management, in particular to a water conservancy sensing system based on edge computing. The system comprises the following modules: a riverway edge sensing module, a water conservancy characteristic analysis module, a sediment migration simulation module and a deposition scouring early warning module. Constructing a river channel water conservancy sensing network; performing real-time water conservancy monitoring data acquisition according to the river channel water conservancy sensing network to obtain river channel water conservancy sensing data; performing three-dimensional flow field model processing on the river channel water conservancy sensing data to obtain a three-dimensional sediment flow field network model; carrying out particle flow field simulation on the three-dimensional sediment flow field network model to generate sediment migration space-time distribution data; and according to the sediment migration space-time distribution data, carrying out siltation and scour area identification, and uploading the siltation and scour area data to a cloud platform through an edge computing node to carry out abnormal event alarm so as to obtain river section monitoring data. According to the invention, real-time, accurate and intelligent monitoring and early warning of the sediment deposition and scouring process of the river channel are realized.

The invention discloses a digital twinning-based wastewater and dirty salt treatment process optimization method and system, and relates to the technical field of intelligent wastewater and dirty salt treatment. The method comprises the steps that a digital twinborn model synchronously mapped with a processing system is established, and the digital twinborn model integrates the technological parameter incidence relation of an evaporation section, a crystallization section and a filtering section; collecting component data and flow data of the polluted salt wastewater corresponding to each process section in real time; correcting model characteristic parameters of each process section in the digital twin model based on the component data and the flow data collected in real time; according to the corrected digital twin model and the optimization target, generating a process optimization strategy corresponding to each process section; and monitoring the component data of the treated discharge water, reuse water, industrial salt and solid waste in real time, and if the data does not reach the standard, triggering model parameter correction, optimization strategy iteration or cross-section collaborative logic recalculation. According to the invention, intelligent cooperation of wastewater and dirty salt treatment is realized.

Various embodiments relate to a method and related device and machine-readable storage medium including one or more of the following: receiving, via a first user interface scene, a user specification of a physical structure; committing a data representation of the physical structure to a digital twin; transmitting the digital twin to a remote device; receiving an update to the digital twin from the remote device, producing an updated digital twin; and rendering, via a second user interface scene, a graphical representation of the updated digital twin.

The invention discloses a cooperative monitoring device and method for a large deep foundation pit complex supporting system, and relates to the technical field of foundation pit supporting. The device comprises a multi-dimensional sensor network module, a BIM-GIS digital twin platform module, an intelligent analysis and early warning module, a construction collaborative decision module, a data backup and recovery module and a remote monitoring and management module. The method comprises the following steps: step 1, carrying out multi-source data space-time registration; step 2, dynamically constructing a digital twinborn model; step 3, coupling risk assessment; step 4, construction collaborative optimization; according to the technical scheme, the method comprises the following steps of data processing, data quality control and system performance evaluation, through three innovations of deep coupling of multi-source data, dynamic model correction and intelligent collaborative decision making, a'monitoring-analysis-decision-execution 'full closed loop is constructed, technical breakthroughs are achieved in complex working condition adaptability, early warning real-time performance and construction safety, and the method has remarkable engineering application value.

The invention discloses a digital production plan scheduling method and system, and belongs to the technical field of optimal scheduling, and the method comprises the steps: constructing a distributed storage architecture based on edge computing nodes; a central coordinator is adopted to realize cross-node data synchronization through an improved Raft consensus algorithm, multi-version concurrency control is realized based on a vector clock, and a global consistent data view is established; a visual scheduling platform is built based on a Vue3 framework, and man-machine interaction is realized by adopting a Canvas and WebGL collaborative rendering framework; establishing a dynamic coordinate conversion model based on bilinear interpolation, designing a space mapping function containing distortion compensation, establishing a multi-thread coordinate service based on WebWorker, and realizing submillimeter-level bidirectional mapping of pixel coordinates and physical coordinates; constructing a three-dimensional space-time analysis model fused with the multi-dimensional features; and all the units are subjected to feature fusion through residual connection, and finally a scheduling scheme with a confidence coefficient weight is output. The method and the device have the effect of meeting various scheduling requirements.

The invention relates to the technical field of cloud computing application, and discloses a cloud computing-based shale fracture modeling platform, which comprises a multi-source data acquisition module, a heterogeneous data fusion module, a fracture dynamic modeling module, a parameter optimization module and a cloud verification module. The multi-source data acquisition module acquires various data and uploads the data to the cloud; the heterogeneous data fusion module processes data isomerism to generate a fusion feature matrix; the crack dynamic modeling module constructs a three-dimensional dynamic model; the parameter optimization module optimizes physical property parameters; and the cloud verification module verifies the model in multiple dimensions and manages the version. The platform solves the problems of traditional modeling in the aspects of data acquisition, fusion, modeling algorithm, parameter optimization and model verification by means of the advantages of cloud computing, can efficiently process multi-source data, accurately construct a crack model, improve the precision and reliability of the model, realize comprehensive verification and effective management of the model, and provide powerful support for efficient exploitation of shale gas.

The invention provides a photovoltaic power station design system and method based on ecological collaborative optimization, and relates to the technical field of data processing. The system comprises an initial configuration module which is used for generating an initial layout structure of a photovoltaic module, performing energy-saving and consumption-reducing calculation and economic analysis according to generating capacity data, and obtaining initial energy-saving and consumption-reducing data and initial economic analysis data; the secondary optimization module is used for optimizing the parameters of the photovoltaic module based on the economical efficiency analysis data and determining energy-saving and consumption-reducing data and economical efficiency analysis data through the generating capacity optimization data; the ecological evaluation module is used for determining ecological benefit data of the photovoltaic power station according to the ecological influence parameters; and the collaborative optimization module is used for setting a power generation income weight and an ecological benefit weight so as to optimize the photovoltaic module layout structure and generate a photovoltaic power station design scheme based on ecological collaborative optimization. The method is used for realizing collaborative optimization of power generation benefits and ecological benefits of the photovoltaic power station, so that the power station gives consideration to ecological protection while improving the power generation efficiency.

A prefabricated building design and construction integrated collaborative method based on component parameter library, which belongs to a field of prefabricated building design and construction technology, comprising: constructing a BIM parameter system for a prefabricated building and its prefabricated components, and establishing a component parameter library of the prefabricated components of the prefabricated building based on the BIM parameter system. By forming the component parameter library through the BIM parameter system of the prefabricated building and its prefabricated components, architects are provided with accurate information that meets the subsequent construction requirements and the construction requirements of various disciplines in schematic design and detailed design, and guided to apply BIM and select appropriate prefabricated components for design, so as to increase depth of first design, and improve accuracy for design optimization. Therefore, prefabricated building design and construction integrated collaboration is promoted.

The invention relates to the technical field of model construction, in particular to a method and a system for establishing a parameterized tunnel model based on cloud computing. The method comprises the following steps: acquiring a tunnel section type, and extracting structural semantics to obtain a section feature description set; constructing a parameter dictionary of the tunnel section based on the section feature description set to obtain a dynamic parameter dictionary data set; and modeling a tunnel section geometric structure based on the dynamic parameter dictionary data set to obtain an initial three-dimensional tunnel geometric model. Through dynamic parameter management, a self-correction mechanism and a Latin hypercube sampling technology, efficient automatic modeling and precise simulation optimization of the tunnel section three-dimensional geometric model are achieved, meanwhile, through unified packaging and authority control, safe and efficient management and collaborative sharing of cloud model resources are achieved, and the method is suitable for large-scale popularization and application. And the intelligent level and the engineering efficiency of tunnel model construction and application are comprehensively improved.

The invention relates to the technical field of heat dissipation control, and discloses a heat dissipation fan multi-order filtering control method and device, and the method comprises the steps: collecting the operation parameters of a multi-fan heat dissipation system, and carrying out the construction of a dynamic state space model, and obtaining a system operation state equation and a temperature observation equation; inputting the system operation state equation and the temperature observation equation into an expectation maximization sliding window iteration extended Kalman filter to obtain a system state estimation value and a prediction error covariance matrix; performing three-stage series design on the cut-off frequency of the low-pass filter, the passband range of the band-pass filter and the coefficient of the adaptive filter to obtain a system multi-order filtering control model; based on a system multi-order filtering control model, an airflow coupling influence coefficient matrix among multiple fans is calculated, the total energy consumption, the noise level and the heat dissipation efficiency are subjected to optimization solution, a fan control optimization parameter set is obtained, the heat dissipation efficiency is guaranteed while the energy consumption is reduced, and dynamic balance among all control units is achieved.

The invention provides a hydraulic engineering information management method and system based on big data. The method comprises the following steps: firstly, uploading flood flow velocity dynamic data, terrain elevation data and spectral feature data to a cloud server, then carrying out multi-dimensional superposition on the flood flow velocity dynamic data, associating with a historical inundation path, and generating a superposition association result; constructing a three-dimensional geographic model based on terrain elevation data and spectral feature data, generating a spatial superposition map according to boundary features of a water body and a terrain abrupt change area and a flood routing path, performing position association with a material reserve position, and performing dynamic priority ranking according to a submerging probability gradient, and finally, according to the resource scheduling instruction sequence, correcting the flight path of the unmanned aerial vehicle cluster and the data acquisition area to form a closed-loop feedback mechanism. According to the technical scheme provided by the invention, the accuracy and timeliness of real-time data updating are ensured.

The invention provides an intelligent collaborative management method and system for network security operation and maintenance work, and relates to the technical field of network security, and the method comprises the steps: obtaining operation and maintenance work order information containing a work order priority and a processing time limit, and converting the operation and maintenance work order information into a work order feature vector; inputting the skill score, the historical completion rate and the workload of the operation and maintenance personnel into a multi-objective optimization model, and calculating a work order matching degree score and an emergency degree score; performing state coding on the work order feature vector, the personnel feature and the constraint condition by adopting a multi-layer perceptron, extracting spatial correlation by utilizing a double Q network, and calculating a target Q value; and generating a work order distribution scheme based on a Pareto optimal solution algorithm, monitoring a processing state in real time through a task collaborative scheduling model, and generating a collaborative scheduling strategy. The intelligent level of work order distribution is improved, collaborative management of operation and maintenance tasks is realized, and the operation and maintenance efficiency is improved.

The invention provides a dynamic fusion system for digital twin energy management BIM modeling and a method thereof, which are used for improving the intelligent level of energy management and optimizing energy scheduling. The system comprises a data sensing node used for collecting heterogeneous operation data of energy facilities; the local twin processor is used for carrying out real-time digital twin mapping on the data and generating a dynamic feature vector; region twinborn nodes perform local optimization based on edge calculation, and realize decentralized collaboration through a block chain or a knowledge graph; the cloud BIM fusion engine constructs a digital twin BIM model, generates a self-optimization energy scheduling scheme and predicts a long-term trend; and the operation control terminal is used for presenting a real-time view and providing a regulation and control instruction. According to the method, technologies such as multi-source data fusion, streaming aggregation optimization and adaptive twin mapping are combined, and the accuracy and dynamic response capability of energy management are improved.

According to the intelligent energy-saving analysis method based on the building information model (BIM), building thermal performance parameters and an intelligent simulation algorithm are integrated, building heat conduction, a heat bridge effect and solar heat gain are accurately simulated, and a scientific basis is provided for design. Meanwhile, an energy-saving optimization strategy is automatically generated, such as wall thickness adjustment and window design, so that energy consumption is reduced. Besides, a multidisciplinary cooperative working platform is established, effective implementation of energy-saving measures is ensured, and energy use and maintenance tracking of the whole life cycle of the building are realized and energy-saving performance is continuously optimized in combination with an energy management system. The innovation of the method lies in the automatic and intelligent analysis process, and a comprehensive solution is provided for the field of building energy conservation.

The invention discloses a comprehensive transportation junction emergency scene simulation deduction system based on digital twinning, which relates to the technical field of digital simulation and comprises a data processing unit, a simulation deduction unit and a visual display unit, the data processing unit is used for acquiring emergency scene basic data of the target digital twin comprehensive transportation hub, performing multi-source integration on the basic data and constructing a model data environment; the simulation deduction unit calls a simulation deduction algorithm to construct a simulation deduction algorithm model according to the emergency scene model data, and carries out emergency situation deduction and scheduling processing based on the simulation deduction algorithm model; and the visual display unit is used for carrying out distribution management on user permissions, carrying out deduction data plotting based on GIS map basic information, and carrying out query and visual display on the deduction data according to a query instruction of a user. According to the method, a digital twinborn platform is built based on a simulation deduction algorithm model and dynamic data, so that the deduction process is more accurate, and visual display is realized in combination with GIS map data.

The invention discloses a transistor high-power electromagnetic heat model optimization system based on deep learning, and relates to the technical field of electromagnetic heat. Comprising an input module, a deep learning module, a global optimization module, an online adaptive module and a real-time simulation module. The input module obtains various key parameters and constructs a high-dimensional input space; the deep learning module constructs a deep learning model by embedding a physical constraint and uncertainty quantization mechanism; the global optimization module is used for carrying out global search on design parameters, rapidly evaluating a target function by utilizing an agent model, and searching a Pareto optimal solution in a design parameter space; the online adaptive module is used for drift detection and updating; the real-time simulation module simulates an electromagnetic field and a thermal field in real time, and data exchange ensures timely synchronization of boundary data through dynamic scheduling and load balancing; all the modules cooperate with one another through data and feedback, and a complete, closed-loop and continuously self-adaptive updating optimization system is achieved.

The invention discloses an indoor environment performance optimization design method and system for a tall and large space building based on CFD and a multi-objective optimization algorithm, and the method comprises the steps: building a parameterized analysis model through combining with a BIM model, carrying out the digital simulation analysis of an indoor light environment and energy consumption through employing Honeybee Radio and Honeybee Entry plug-ins in Rhino and Grasshopper environments, determining optimization parameters and objectives, and carrying out the optimization of the indoor environment and energy consumption. And a BIM model and an IDF file corresponding to the optimal schemes are exported, the uniformity of the indoor airflow organization is evaluated based on FFD software, and parameters of the optimal schemes are determined. Compared with a traditional indoor environment optimization method, the high and large space building indoor environment performance optimization and evaluation method is efficient, accurate and economical, and has higher accuracy, higher adaptability and wider applicability. Natural lighting, building energy consumption and indoor three-dimensional thermal comfort can be considered at the same time, and optimization of the indoor environment performance of the tall and large space building is achieved.

The invention relates to the technical field of building information modeling, and discloses a parameterized BIM modeling method, which comprises the following steps: step 1, acquiring specific design parameters of a modeling object in a project design requirement, marking key geometric parameters of the object, including length, width, height, volume and material characteristics, and defining units, physical meanings and application ranges of the parameters in a marking process, a basis is provided for subsequent entity model construction; and 2, based on the geometric parameters marked in the step 1, a solid model is constructed through a BIM modeling tool, and the solid model is a visual model with the shape, the size and the position determined through the geometric parameters in a three-dimensional space. The three-dimensional BIM model is dynamically generated and modified by modifying geometric parameters, model construction is more flexible and efficient due to introduction of parameterization logic, automatic adjustment and rapid iteration of the model are achieved, and the reusability of BIM modeling and the design efficiency of the building model are remarkably improved.

A computer-implemented method includes editing, at a local client device, an engineering design (e.g., computer aided design (CAD) model), hosted on a remote server. The local client device and the remote server communicate over a communications network and are remote from each other. The remote server configures an operation within a CAD model based on user input during an edit of the CAD model involving a drag. This results in a subset of the CAD model and the solving instructions required to perform the user update being generated and sent as a data package including the subset of the CAD model and the solving instructions to the local client device. The CAD model and any associated algorithms stored on the remote server are not communicated to the local client device.

The invention discloses a push strategy adaptive optimization method and system oriented to personalized demands, and relates to the technical field of data processing, and the method comprises the steps: firstly obtaining and processing the information of a push target, and then extracting and recognizing the commodity information through a natural language processing technology and a double-layer attention analysis model. And establishing a personalized label set, and extracting information from the historical push interaction record. And fusing the subjective demand and the objective label set through a collaborative attention fusion network to generate standard personalized demand information. Mapping the plans in the pushing strategy library into vectors, and retrieving candidate plans by adopting a multi-dimensional weighted cosine-divergence combined similarity function; and finally, strategy evolution is carried out through a dynamic multi-target optimization space, an improved NSGA-III algorithm is adopted to generate a Pareto frontier solution set, and an optimal solution is selected as a target pushing strategy. According to the method, the accuracy and efficiency of the push strategy can be improved, and the user satisfaction is improved.

The embodiment of the invention provides a simulation evaluation method and device for a multi-satellite cooperative task, and the method comprises the steps: building a unified time-space reference based on a standard time signal, and building a complete environment disturbance model comprising sunlight pressure, atmospheric resistance and geomagnetic field interference. A fault injection mechanism of load, attitude and orbit control is innovatively designed, and real simulation of multi-satellite cooperative motion is realized. According to the system, a system-level, subsystem-level and component-level multi-level evaluation index system is established, a dynamic weight calculation method based on a task execution state is adopted, and matching analysis of a three-dimensional error curve and a key event time sequence is combined, so that accurate evaluation of multi-satellite cooperative task performance is realized; and a reliable decision basis is provided for space task planning and system optimization.

The invention relates to an aircraft concept scheme design method and system based on generative artificial intelligence. The method comprises the following steps: selecting a large language model as a system basic model; constructing an aircraft collaborative design cloud platform; driving the large language model to generate a design scheme in a local calling mode, wherein the design scheme comprises model type selection and cue word selection; weight, pneumatic, performance and modeling professional analysis tools are packaged into a capability unit of a design system, and related modeling, evaluation and verification links comprise appearance, power, pneumatic, weight, RCS and flight performance parts and are deployed and operated in a distributed mode. On the basis of a design project in a collaborative design cloud platform, an aircraft CATIA model, overall parameters, aerodynamic parameters, weight parameters and performance data formed by a design scheme are extracted, and elements therein are displayed. According to the system, the aircraft design efficiency is remarkably improved, and the design cost is reduced.