88 results about "Cloud simulation" patented technology

The invention provides an operation management method of an electric power system cloud simulation platform. The electric power system cloud simulation platform comprises a cloud simulation resource management system and a cloud simulation application supporting system. The method comprises the following steps that the cloud simulation resource management system is constructed; the cloud simulation application supporting system is constructed; the safety of the electric power system cloud simulation platform is determined; operation management of the electric power system cloud simulation platform is carried out. Cloud simulation analytical calculation application is achieved, multiple users can carry out currents, transient stability, small interference, short-circuit currents and other simulation calculation functions on one or more sets of data according to the permission in the mode of facing network services, and the limitation that services and data of standalone version software cannot be shared in large-scale interconnected power grid analytical calculation is eliminated.

The invention discloses a system and a method for real-time cloud simulation on an Internet of things sensing device. The system comprises the Internet of things sensing device, an Internet of things gateway device, a cloud device simulation center and an MQTT (Message Queuing Telemetry Transport) server; the Internet of things sensing device is an intelligent sensing device which is accessed to a sensing network; the Internet of things gateway device is used for providing the access for a heterogeneous sensing network; the cloud device simulation center comprises a simulation data processing module and a simulation node module, wherein the simulation data processing module is used for receiving, pushing and processing simulation data, the simulation node module is used for establishing cloud simulation nodes, and the cloud simulation nodes and the Internet of things sensing device are maintained to be synchronized; the MQTT server is an interaction intermediary of the Internet of things sensing device and the cloud simulation node which is corresponding to the Internet of things sensing device. According to the system and the method for the real-time cloud simulation on the Internet of things sensing device, the cloud simulation node which is corresponding to the Internet of things sensing device is established at the position of a cloud according to real-time data sent from the Internet of things sensing device to enable the functions of the cloud simulation node to be as same as the functions of the Internet of things entity sensing device and accordingly the access of the cloud application service to the entity sensing device and the operation of the cloud application service on the entity sensing device are convenient.

The invention relates to a management and control method of a hybrid electric vehicle based on a digital twinning technology. According to the method, a hybrid electric vehicle digital twinning cloudvirtual model matched with a physical entity (hybrid electric vehicle) is built on a cloud simulation platform based on a digital twinning technology, and the simulation working environment of the hybrid electric vehicle digital twinning cloud virtual model is configured to be consistent with the actual working environment of the physical entity; a digital twin cloud storage computing platform dynamically collects physical data generated by operation of the physical entity and virtual data generated by operation of the cloud virtual model in real time and then performs data analysis and fusionprocessing; the data processing result is compared with the current hybrid electric vehicle operation data in real time to update the attribute characteristics of the cloud virtual model in real timeand obtain an optimal control strategy corresponding to the latest model based on the calibration performance and the current state of the physical entity in combination with the cloud online simulation technology, and the optimal control strategy is input into the physical entity to automatically change the operation control of the hybrid electric vehicle, thereby integrally achieving dynamic optimal control.

The invention discloses a distributed cloud simulation method and system based on lightweight virtualization architecture. The distributed cloud simulation comprises: step 1: through the cloud simulation central control platform, the simulation task of the user is received, and the simulation task is decomposed, and a plurality of micro service combined instructions are obtained; step 2: through the cloud simulation central control platform and the server cluster simulation container system for proxy negotiation, the plurality of micro service combination instructions are transmitted to the designated server cluster simulation container system; step 3: through the server cluster simulation container system, the mirrored container of the simulation resource is built in a micro service combination for the user to call. The distributed cloud simulation method and system based on lightweight virtualization architecture realize the fine-grained encapsulation of simulation resources, and the concept of micro services and micro service combination is introduced, which improves the multi center distributed simulation resources sharing and replication efficiency and can rapidly deploy the simulation resources in multiple centers.

The invention discloses a tower control simulation training system, and a voice control instruction identification and reading method. The system includes at least one training unit, a teacher seat group, a switch, and a cloud simulation platform; wherein the training unit, the teacher seat group and the cloud simulation platform exchange data through the switch; the training unit includes a simulated captain's chair, a tower flight controller seat, and a tower three-dimensional view system installed in the tower flight controller seat for training simulation; and the teacher seat group includes a teacher's seat, a monitoring seat, and a tower three-dimensional visual system installed in the monitoring seat for simulating the instructor's operation. The cloud simulation platform includes asimulation server, a voice server, a comprehensive application server, and a data storage server for providing various services for tower control training. Based on the system, the corresponding voice control instruction identification and reading method is also given. The system can be used to carry out more realistic and efficient tower controller training.

The invention relates to a cloud simulation platform, which comprises an access interface layer for receiving an operation instruction sent by a user terminal, and sending an operation request of theoperation instruction to a cloud simulation control layer, the cloud simulation control layer for responding to the operation request, sending a resource request to a resource service layer accordingto the operation request, obtaining a resource operation result returned from the resource service layer, and returning the obtained resource operation result to the access interface layer, and the resource service layer for receiving the resource request, allocating resources according to the resource request, obtaining a resource operation result, and returning the obtained resource operation result to the cloud simulation control layer. The scheme of the embodiment provides a simulation supporting environment of a complete simulation process, so that the coordination efficiency of the simulation process can be improved accordingly, and the stability and reliability are high.

The invention discloses a cloud simulation model resource description information storage method and device based on a knowledge graph, a computer device and a readable storage medium, and the methodcomprises the steps of determining the description content of cloud simulation model resources, wherein the description content comprises the static information, the dynamic functions and the interface information, the static information comprises the basic information, the static attributes and the functions, a model relation and the model requirement information, and the dynamic function comprises a conversion relation and a conversion condition between the states of the cloud simulation model resource; determining resource description framework triple information of each cloud simulation model resource in the knowledge graph based on the description content; and importing the resource description framework triple information of each cloud simulation model resource into the knowledge graph to form the knowledge graph for storing the cloud simulation model resource description information. According to the scheme of the embodiment, the expandability of the cloud simulation model resource description is improved, the simplicity and the intuitiveness are achieved, and the cloud simulation model resources are more correlated and higher in efficiency when being searched based on the knowledge graph.

The invention discloses an information security guarantee method of an internet of things sensing device cloud simulation system. The method mainly solves the problem that an existing Internet of things sensing device cloud real-time simulation system is not safe. According to the technical scheme, the method includes the steps that 1, verification is carried out before an Internet of things sending device has access to a cloud real-time simulation system so as to guarantee legality when the Internet of things sending device has access to the cloud real-time simulation system; 2, encryption, transmission in timed and real-time modes, decryption, comprehensive processing of verification are carried out on data in the real-time data transmission process, so that privacy in the data transmission process is guaranteed; 3, when a cloud application service program has access to a cloud simulation node, access control verification is carried out on the cloud application service program so as to guarantee that illegal access of the cloud simulation node is avoided. The method improves safety of the Internet of things sensing device cloud real-time simulation system, and can be used for cloud computation and the internet of things.

The invention provides a cloud computation-based power system simulation data management method. The method comprises the following steps that 1, a foreground receives a task operating command and transmits the task operating command to a cloud simulation platform; 2, a storage server receives and stores the task operating command of a user; and 3, a computation template, which corresponds to the task operating command and is stored in a computation template storage server, is selected when the task operating command is a computation task; a computer group computes to obtain the result of the computation task according to power grid data and the computation template; and the result of the computation task is stored in the storage server, and the user acquires the result of the computation task by accessing the storage server. According to the method provided by the invention, the computation task is computed by the computer group which operates the cloud computation environment, and a large amount of computation resources are managed and cooperated by scheduling and optimizing technologies, so that the whole power grid data are integrated and computed efficiently and quickly.

The invention provides a chaff cloud simulation device. The device comprises a foam cabin. A foam ball is arranged in the foam cabin. The internal portion of the foam ball is used for setting chaff. The two opposite panels of the foam cabin are provided with ventilation holes which are uniformly distributed. A blower air channel or an air-intake air channel used for floating the foam ball in the foam cabin is arranged at one panel which is provided with the ventilation holes. In the technical scheme, the chaff is arranged in chaff balls and the chaff balls are arranged in the foam cabin. Aftera draught fan is started, the chaff balls are blown to be uniformly distributed in the foam cabin. And a real chaff cloud distribution condition can be simulated. A chaff cloud characteristic test ina microwave dark room can be realized, and conditions that the chaff balls can not fly into the dark room through the hole of a cabin bottom or a cabin top and the microwave dark room is polluted areavoided.

The invention discloses a cloud simulation service method comprising the steps of: virtualizing hardware resources in a cloud simulation architecture; virtualizing software resources in the cloud simulation architecture; establishing a unified management platform in the cloud simulation architecture to manage the virtualized hardware resources and the virtualized software resources; and constructing a the professional model and a solver in the cloud simulation architecture. The method has the following advantages of using model sharing service, resource flexible scheduling and solver parallel computing as a core, scheduling tasks and distributing computing resources on demand, providing the professional model and the solver for engineering staff in the form of services by using service middleware, configuring on demand, providing a flexible and reliable computing platform for enterprises; and achieving high data security and high data reliability.

The invention discloses a resource configuration method for a collaborative simulation mode of cloud simulation. The method comprises the steps of determining a plurality of physical machines which can be used for configuring virtual machines and a plurality of to-be-configured virtual machines; adjusting a configuration sequence of the virtual machines according to resource conditions of the virtual machines; and configuring the virtual machines sequentially according to the configuration sequence, wherein each virtual machine is configured on one physical machine. According to the method, the resource configuration mode of the cloud simulation is optimized, and the waste of simulation resources is reduced, so that the utilization rate of the simulation resources is increased, and the quantity of simulation tasks which can be processed in parallel by a cloud simulation system is increased.

The invention discloses a spray simulation method based on cloud simulation of droplets. The spray simulation method includes the steps: adopting a three-dimensional stereo camera to acquire three-dimensional point cloud data of plant bodies, and simulating actual crop plants through a point cloud deleting method and coordinate transformation processing; describing spray droplet particle motion trajectories through Lagrangian trajectory description operators under the conditions of determining nozzle type, nozzle coordinates and spray technology parameters; designing a point cloud intersection algorithm of the spray droplet particle motion trajectories and the plants and judging whether the droplets drop on the plant bodies or not and calculating drop point positions thereof; according to requirements of spray operation speed, constantly changing the space coordinates of a nozzle to complete dynamic simulation till a stop condition is reached, outputting droplet deposition rate, and optimizing spraying height. By the spray simulation method, visual operation indexes of spray operation can be analyzed, and the optimal spraying operation height is achieved by taking the effective deposition rate of the droplets as an objective function, so that certain reference is offered to reduce application amount of pesticides during an actual plant protection process.

The invention discloses a cloud service system based on Internet of Things sensing device cloud simulation nodes. The cloud service system comprises a simulation system layer, an access authentication layer, a cloud service layer and a user layer, wherein the simulation system layer comprises the Internet of Things sensing device cloud simulation nodes and cloud simulation node data access interfaces; the access authentication layer comprises an authentication control module and a device information module; the cloud service layer comprises a real-time data module, a historical data module, a cloud customized service program module and a cloud application service program module; the user layer mainly comprises user system access interfaces and user entities for managing and mapping user information. The cloud service system based on the Internet of Things sensing device cloud simulation nodes solves the problem that the Internet of Things sensing device cloud real-time simulation nodes cannot directly provide cloud services externally, lower-layer differences of Internet of Things sensing devices are packaged and integrated, a distributed storage scheme is designed for storing massive real-time data produced by the Things sensing device cloud simulation nodes, the different requirements of users are met, and the cloud application program service and the cloud customization program service are provided for the users.

The invention provides a controllable neural network-type method for predicting reservoir permeability. The method comprises the following steps: SI, acquiring seismic data; adding fault control by taking known drilling data as a longitudinal control point and seismic sequence interpret horizons as horizontal restraint; establishing a geologic framework model; SII, performing seismic inversion under the control of the geologic framework model through a genetic algorithm to obtain N wave impedance data bodies; SIII, performing phase-controlled cloud simulation reservoir permeability prediction by aiming at each wave impedance data body, wherein each wave impedance data body is used for predicting M permeability data bodies; SIV, sedimentary facies comparison on N*M permeability data bodies and mutual linear analysis among the data bodies; SV, performing equal-weighted treatment on the N*M permeability data bodies to obtain final permeability data bodies; SVI, performing engraving aiming at an oil reservoir part on the final permeability data bodies to provide data for a downstream reach.

The invention relates to a cloud simulation device and method for rail transit full-automatic unmanned scene verification. The device comprises a cloud access terminal and a cloud server, wherein thecloud server comprises a central scheduling module, a station control module, a rail-mounted module, an interface logic management layer and an equipment base layer; the cloud access terminal is connected with the central scheduling module, the central scheduling module is respectively connected with the station control module and the rail-mounted module, the station control module, the rail-mounted module and the interface logic management layer are connected in pairs, and the interface logic management layer is connected with the equipment base layer. Compared with the prior art, the methodhas the advantages that the fault injection test can be carried out flexibly, the function test under degradation and emergency operation scenes can be carried out more comprehensively, the large-scale verification work on site is avoided, and the like.

The invention discloses a virtual prototype system building and operation method based on a cloud simulation technique. The method includes the steps: describing building demand information of a virtual prototype system; building the virtual prototype system in a cloud simulation platform environment according to the building demand information; and operating the virtual prototype system based on the cloud simulation technique. The technique scheme can effectively solve the problems existing in a simulation process of the virtual prototype system which is applied to dynamic sharing, high-efficient management and collaboration application of various online cross-region cross-organization scientific research resources; through the advanced information technique means such as innovation model idea, service computing and virtualization of a cloud, on-demand sharing and high-efficient collaboration abilities of information engineering resources can be effectively improved, and then distribution, heterogeneity, cross-section collaborative design research and development and simulated test during a research process of virtual prototype products can be effectively supported.

The invention discloses a cloud simulation platform model security guarantee system. The system comprises a cloud simulation server used for receiving a simulation request and basic task data transmitted by terminals, wherein the simulation request comprises configuration and organization information of a simulation module, and calling a basic simulation module required to execute a simulation task in a plurality of simulation modules to simulate and calculate the basic task data according to the configuration and organization information of the simulation module, so as to obtain basic resultdata and return the basic result data to the terminals; and a plurality of terminals used for simulating and calculating a key task in the simulation task to obtain key result data, and synthesizing the key result data and the basic result data transmitted by the cloud simulation server to complete the simulation task. The invention further discloses a cloud simulation server, a terminal and a cloud simulation platform model security guarantee method, wherein the model, data and simulation in the cloud simulation process are stripped, so that the model security in a cloud simulation platform is guaranteed.

The invention discloses a reinforcement learning-based mobile terminal application test method, a device, equipment and a medium. The method comprises the steps of creating a mobile terminal application simulation environment of a cloud data center; collecting user behavior data, extracting features of the user behavior data, generating a sample of a user operation behavior, and generating an intelligent agent for simulating the user operation behavior in combination with the designed test case; interacting the intelligent agent with the created simulation environment, and obtaining a trainedstrategy model and evaluation model through reinforcement learning training; and carrying out DevOps automatic test on the mobile terminal application to be tested through the trained model. In this way, in a cloud simulation environment; by utilizing the collected user behavior data and the designed test case, a user behavior model for cloud simulation test is formed through reinforcement learning training, the test coverage rate is ensured, the behavior of an actual user can be better simulated, a user operation scene is reproduced, accurate test evaluation is formed, and the test efficiencyis improved.

The invention discloses an automatic interface method for vibration cloud simulation of an avionics product based on ANSYS scripting language. The method comprises the following steps: inputting a 3Dgeometric model local address, material parameters, fixed restraint position, a load PSD spectrum value, a direction and an analysis type in a local visual interface, ; uploading data to the cloud end, importing ANSYS work simulation software at the cloud end into the 3D geometric model; giving material parameters to a 3D geometric model, updating and meshing the 3D geometric model, then applyingmodal boundary conditions, then performing post-processing of modal analysis, selecting one of random vibration analysis, harmonic response analysis and transient analysis according to a user, then applying different loads, and correspondingly performing post-processing. The cloud platform is used for simulation, the simulation efficiency is improved, and aviation electronic product fault behaviorsimulation and reliability prediction are rapidly and accurately conducted.

The invention discloses a cloud simulation task scheduling method based on a hybrid queuing network. The method includes calculating a resource quantity required by each of the plurality of cloud simulation tasks; Prioritizing the plurality of cloud simulation tasks according to the resource amount of each cloud simulation task; constructing A plurality of sub-queues, and allocating a plurality ofcloud simulation tasks to the plurality of sub-queues according to the request entry time of the plurality of cloud simulation tasks and the number of cloud simulation tasks that each sub-queue can bear, so as to provide an optimized cloud simulation task scheduling method and improve the processing efficiency of the cloud simulation tasks.

The invention discloses a cloud simulation method and system integrated with various simulation software. The cloud simulation method comprises the following steps: providing an interactive interfacecapable of designing a simulation model and simulation parameters for a user; describing the simulation model and the simulation parameters through simulation elements, forming a description file, andsending the description file to a server integrated with various simulation software; analyzing the description file through the server, extracting a simulation element, calling corresponding simulation software for simulation according to the type of the simulation element, and feeding back a simulation result to a user.

The invention discloses a container cloud-based modular simulation model operation control system and method and a medium, particularly relates to a container cloud and modular distributed system simulation model operation-based construction method, and belongs to the technical field of computer simulation. According to the invention, a unified model operation management and control mechanism of the simulation micro-service is established; on one hand, the problems of high complexity and high difficulty in the assembly process of an equipment simulator-level complex model in container cloud simulation are solved, and on the other hand, a state management function for multi-level modular simulation model service is realized, the complexity of state information management is reduced, and thereusability requirement of a micro-service instance is met.

The invention discloses a water conservancy model simulating computation system and computation method based on cloud serving. The system comprises a terminal, a cloud simulation platform, a computation cluster and a simulation result processing server, wherein the cloud simulation platform is independently connected with the terminal, the computation cluster and the simulation result processing server; a water conservancy model program file is obtained from a file server through the cloud simulation platform according to requirements; a simulating computation task is dynamically constructed and is then distributed to the computation cluster for carrying out simulating computation; generated result data or a chart is stored to a chart server; a computation process result is stored to a database server; and finally, the computation process result is returned to the terminal through an application server to show a simulation result. Resources or capabilities for obtaining the simulation service of various professional water conservancy models through the internet can be provided for users so as to truly break through a wide gap between a water conservancy model owner and the users, and urgent demands including quick modeling, efficient computation, model reuse and the like with which water conservancy model simulating computation is confronted at present can be effectively met.

The invention provides a complex product collaborative simulation environment construction method. The method comprises the steps that: edge end simulation resources are sensed and imported; the edgeend simulation resources tare virtualized and made to be service-oriented, so that cloud simulation resources and services are formed; collaborative simulation running middleware is deployed; and collaborative simulation tasks are distributed, and a collaborative simulation environment is constructed. According to the complex product collaborative simulation environment construction method provided by the invention, physical interconnection between an edge end and a cloud end is realized through the import and sensing of the edge end simulation resources; through the virtualization and servitization of the edge end simulation resources, the abstraction and management of the edge end are realized; with the simulation middleware deployed, the construction of a simulation operation basic environment is realized; the collaborative simulation tasks are by distributed, the collaborative simulation environment is constructed, and therefore, the interactive modeling and resolving of a multi-professional model are achieved at the edge end; and collaborative data such as resolving results are obtained at the cloud end on the basis of a cloud simulation environment / engine, so that a complex product full-system virtual prototype collaborative simulation environment is constructed.

The invention discloses an intelligent networked vehicle intelligent driving function cloud simulation test system and method based on DevOps. The system comprises a WEB front end subsystem, a WEB rear end subsystem, an application service subsystem, a third-party service subsystem, a basic service subsystem, a data storage subsystem and a container arrangement engine subsystem. The WEB front end is used for providing an interactive interface for a user; the WEB back end responds to the front-end user operation; the third party service comprises a Jenkins service, a Gitlab service and an ALM service; and the container arrangement engine comprises a mirror image warehouse and a simulation execution node, and the mirror image warehouse is used for storing container mirror images developed based on the application of the container and mirror images prepared for various users in advance in the simulation execution node. According to the test system, a developer submits software to the project management platform, issues and automatically constructs platform integration and releases the platform integration to the mirror image management platform, issues the platform integration to the mirror image management platform, tests and issues a test report, a tester analyzes problems and submits a problem list to the defect management platform in a closed loop mode to the developer, and automation of the whole process is achieved.

The invention provides an online prewarning analyzing system based on a cloud simulation platform. The system comprises the cloud simulation platform, a report server, a disk array, a database server, an application server and a man-machine interface display module. The cloud simulation platform distributes dynamic data to a parallel computer platform for power grid online prewarning analyzing calculation, an abstract result and a historical result are stored in the report server and the disk array respectively, a calculation result is stored in the data server, and a user can display the calculation result on the man-machine display module through the application server. Due to full use of the resource of the cloud simulation platform, online prewarning analyzing efficiency is improved, and a platform foundation and target analysis are provided for power grid prewarning.

The invention provides a two-stage scheduling method of an electronic product stress cloud simulation platform, which comprises the following steps: S1, packaging each test sample data into a job of asimulation system and enters a job sorting queue; S2, standardizing the job priority, job length and job waiting time; S3, calculating a maximum weight priority strategy index matrix; S4, selecting the number of jobs exceeding the number of servers and entering the job distribution queue; S5 Input population size, catastrophe probability, crossover probability and iteration times; S6 initializinggenetic population; S7 calculating individual fitness evaluation; S8 selection; S9 crossing; S10 mutation; S11 a loop performs step S7-S10 reaches the iteration times and outputs the chromosome withthe largest individual fitness value in the population. The system assigns jobs to different servers according to the chromosomes. This method not only considers the job priority, job length and jobwaiting time, but also ensures the fastest use of limited servers for calculation.

The invention discloses a cloud simulation service correlation and resource scheduling system. The system comprises an external service interface, a hardware layer, a software layer, an expansion interface and a control layer. The external service interface is used for receiving an externally input cloud simulation demand and feeding back a cloud simulation result, wherein the cloud simulation demand comprises selection information of a cloud simulation model and a calculation example. The hardware layer is used for providing hardware resources. The software layer is used for providing the cloud simulation model and a solver, wherein the cloud simulation model is used for providing a simulation model required for cloud simulation, and the solver is used for solving the simulation model. The expansion interface is used for accessing new hardware equipment or new software equipment. The control layer is used for selecting the corresponding cloud simulation model according to the selection information of the cloud simulation model and determining the required hardware resources according to the calculation example. The control layer is further used for feeding back the cloud simulation result through the external service interface. The system has the following advantages: software resources and the hardware resources can be expanded to improve the calculation capability of the system and increase the types and quantity of simulation models.

The invention provides a volume cloud simulation method and a volume cloud simulation device, and relates to the technical field of scene simulation. The volume cloud simulation method comprises the following steps: constructing a volume cloud model, wherein the volume cloud model comprises two sub-models arranged oppositely; and for each sub-model, carrying out rendering on the sub-model according to preset rules to finish simulation of the volume cloud. Through the method above, the problem of complex simulation calculation in the existing volume cloud simulation technology can be improved.