37 results about "Physical phenomena" patented technology

Systems and apparatus may carry out analysis of battery physical phenomena, and characterize batteries based on phenomena occurring in particular time and / or frequency domains. These systems may be additionally responsible for charging and / or monitoring a rechargeable battery. Examples of battery physical phenomena include mass transport (e.g., diffusion and / or migration) in battery electrolytes, mass transport in battery electrodes, and reactions on battery electrodes.

The invention discloses a method for predicting shock waves through a multi-region conservation enhanced physical information neural network, and belongs to the field of flow field prediction of shock waves and strong nonlinear physical phenomena in high-speed flow, and the method comprises the steps: S1, carrying out numerical simulation through fluid dynamics software to obtain a reference flow field solution of a to-be-solved N-S control equation, the verification module is used for verifying a model solving result; s2, constructing a neural network comprising an integral layer, a micro-layer and a loss function error layer; s3, constructing a physical information neural network; s4, training is carried out after physical information neural network training parameters are set, and whether a convergence standard is met or not is determined by constructing a joint loss function corresponding to the physical information neural network; and S5, applying the trained neural network model to shock wave prediction of high-speed flow field simulation under different working conditions. Through the multi-region local conservation constraint, the width of the shock wave transition region is effectively compressed, so that the relative error of the physical quantity is obviously reduced compared with the existing method.

Systems and apparatus may carry out analysis of battery physical phenomena, and characterize batteries based on phenomena occurring in particular time and / or frequency domains. These systems may be additionally responsible for charging and / or monitoring a rechargeable battery. Examples of battery physical phenomena include mass transport (e.g., diffusion and / or migration) in battery electrolytes, mass transport in battery electrodes, and reactions on battery electrodes.

The invention provides a compressed air energy storage cavern support stability discrimination method, and relates to the technical field of cavern support, and the method specifically comprises the steps: collecting a cavern support sample and mechanical parameters and influence parameters of a to-be-discriminated support, constructing a current adversarial network, extracting pre-training model parameters in a database through transfer learning, and initializing the pre-training model parameters; simulation parameters are generated through training; building a heat-fluid-solid coupling finite element simulation model based on measured data, and calibrating the model by using simulation parameters; inputting influence parameters of a to-be-discriminated support into the calibrated model, obtaining mechanical parameters, and extracting characteristic parameters such as maximum stress, strain and anchor rod axial force; the safety coefficient is generated through data processing, and the supporting stability is comprehensively evaluated. According to the method, a multi-dimensional data evaluation system is constructed, comprehensive monitoring of complex physical phenomena such as thermal-mechanical coupling and seepage-stress hysteresis in the operation of the cave is achieved, the real stress state of the cave can be accurately evaluated, and potential risks can be pre-judged in advance.

The application provides a compressed air energy storage cavern support stability discrimination method, and relates to the technical field of cavern support, and the specific steps include: collecting the mechanical parameters and influence parameters of the cavern support sample and the support to be discriminated, constructing a current adversarial network, extracting the pre-training model parameters in the database through migration learning and initializing, generating simulation parameters through training; constructing a heat-flow-solid coupling finite element simulation model based on the measured data, calibrating the model by using the simulation parameters; inputting the influence parameters of the support to be discriminated into the calibrated model, obtaining the mechanical parameters and extracting characteristic parameters such as the maximum stress, strain and anchor rod axial force; generating a safety coefficient through data processing, and comprehensively evaluating the support stability. The application constructs a multi-dimensional data evaluation system, realizes comprehensive monitoring of complex physical phenomena such as heat-force coupling, seepage-stress hysteresis and the like in the operation of the cavern, can accurately evaluate the real stress state of the cavern, and can predict potential risks in advance.

This disclosure relates generally to high resolution simulation prediction for Computational Fluid Dynamics (CFD). CFD plays a crucial role in comprehending intricate physical phenomena spanning across scientific and engineering domains, hence it is essential to conduct simulations at high mesh resolutions for the governing equation of fluid flow. The current state-of-the-art super-resolution techniques involve reconstructing high-resolution data from down sampled low-resolution is limited to single scenario and does not accurately reflect real-world scenarios. The disclosed techniques enable prediction of fine-resolution data from low-resolution inputs from a variety of real-world CFD scenarios. Further the disclosed technique also identifies the most relevant network architecture for any CFD scenario and enabling accurate prediction of high-resolution data from low-resolution inputs by training the network architecture. Furthermore, the disclosure ensures also the robustness of the disclosed system through uncertainty analysis, encompassing both aleatoric and epistemic uncertainty analyses.

The application discloses a rotary kiln multi-physical phenomenon numerical simulation method based on artificial intelligence reasoning, relates to the technical field of rotary kiln multi-physical phenomenon simulation, and is based on the Euler multiphase flow equation, adds a heat transfer model, a chemical dynamics reaction model, a particle growth model, a chemical reaction model and the like, establishes a three-dimensional numerical model capable of accurately simulating the multi-physical and chemical phenomena such as the gas-solid two-phase flow movement, combustion, NOx generation, clinker calcination and particle growth in the rotary kiln, introduces a long short-term memory neural network to build an AI model, uses the AI model to predict the latter half of the working condition, accelerates the simulation speed, and realizes long-time simulation of the rotary kiln.

The invention discloses a supersonic cascade flow field reconstruction method fusing a transfer learning theory and adaptive dynamic physical partitioning, and belongs to the technical field of fluid mechanics numerical simulation and machine learning. According to the method, through a physical partitioning strategy, the problem of feature learning fragmentation caused by lack of physical logic in pure data partitioning is avoided; by means of modularized cooperative training of a shared feature extractor and a partition adapter, the defect that a global model is insufficient in local difference learning is overcome, and redundancy of repeated learning of universal features when partition models are independently trained is avoided; in the prediction and iterative optimization link, through automatic verification and backtracking adjustment, the defects of high manual intervention cost, non-physical phenomenon of a prediction result and large local partition error are avoided, and finally efficient, accurate, physical and reasonable prediction of high-precision data is realized.

This invention discloses a scaled-down model simulation system and method for oil-immersed transformers based on similarity theory, comprising: S1 determining the transformer model and structural parameters required for multiphysics analysis, as well as the similarity ratio of the scaled-down model for simulating physical phenomena; S2 determining the eddy current field control equations adapted to the transformer's electromagnetic field using Maxwell's equations, and deriving the eddy current field similarity criterion based on similarity theory; S3 determining the energy conservation similarity criterion based on the energy conservation equation; S4 determining the momentum conservation similarity criterion based on the momentum conservation equation; S5 determining the convective heat transfer similarity criterion based on convective heat transfer boundary conditions; S6 determining the heat flow compensation principle by integrating various similarity criteria, performing temperature-fluid field simulation, and comparing the simulation results with those of the original structural model and prototype experimental results. This invention is computationally simple, highly accurate, and efficient, and can be well applied to engineering practice.

A method can include generating equipment specifications for a facility project at a field site by simulating physical phenomena using one or more computational simulators; using the equipment specifications and a computational facility planner system, generating a work breakdown structure for the facility project, where the work breakdown structure represents activities to be performed to deliver a defined scope of the facility project within a defined time; rendering a graphical user interface to a display that includes graphical controls for dependencies of the activities and equipment characterized by the equipment specifications; responsive to input received via one or more of the graphical controls, automatically updating at least durations of the activities; and, based at least in part on the updating, generating an optimal scenario for the facility project.

This invention discloses a method for determining the non-perfect similarity ratio based on the classification similarity law. The method includes the following steps: S1, extracting a set of parameters describing the physical phenomenon based on experience, previous experimental results, literature, and data; S2, dividing the parameter set into key parameters, basic parameters, and derived parameters; S3, obtaining the similarity ratio of the basic parameters using measurement, material property testing, and other means; S4, deriving the similarity ratio of the derived parameters based on the similarity ratio of the basic parameters; S5, introducing constraint equations based on the physical relationship between the key parameters and the basic and derived parameters to construct a similarity ratio constraint equation; S6, substituting the similarity ratios of the basic and derived parameters into the similarity ratio constraint equation to solve for the similarity ratio of the key parameters. This method, by introducing constraint equations to construct similarity relationships, can effectively reduce scaling errors under non-perfect similarity conditions and is applicable to various scaling test scenarios such as open-loop and closed-loop tests.

Provided herein is a system and method for monitoring, troubleshooting, and providing predictive maintenance to pumps systems. The methods provided herein can utilize and / or interpret physical phenomena of pump systems and components thereof. The physical phenomena may include, but is not limited to, vibration, temperature, sound, or similar characteristics. Further, a cloud-based system can collect data from autonomously operated systems, to provide visualizations of collected data via a user interface, and analyze the collected data with various models to predict maintenance, determine optimizations, and facilitate troubleshooting of the systems.

The present disclosure provides a multi-geometry space adaptive visual language modeling system for astronomical simulation. A two-stage training strategy is adopted to receive external images and user queries. First, the external images are input into a multi-geometry space prompt generation module, and the spatial features P E , H , S of three spatial geometry priors of Euclidean, hyperbolic and spherical are output. The spatial features are input into a multi-modal astronomical data input and alignment module together with the user query. After vector splicing, the input is input into a geometry adaptive backbone module, and finally the corresponding numerical value and reply are output through an astronomical task intelligent inference and output module. By integrating the representations of multiple geometry spaces such as Euclidean, spherical and hyperbolic into the visual language model architecture, the defects of existing visual language models that cannot handle complex astronomical physical phenomena due to their limitation to Euclidean space are effectively solved.

The embodiment of the invention discloses a physical multi-dimensional interactive teaching system and method based on molecular simulation and a medium, and the system is characterized in that through a Materials Studio kernel calculation engine, a Visualizer module, a CASTEP module, a DMol3 module and a Forcite module of Materials Studio are integrated, and automatic task scheduling is realized; microscopic physical phenomena are visually and dynamically mapped, and education parameters are simplified; in response to a touch screen gesture, a particle release position is operated, the VR glasses check three-dimensional electric field distribution, and the tablet computer displays a collaborative teaching mode of a simulation data table in real time. Aiming at the characteristics of high school physics courses, through integrating the three-dimensional modeling, quantum mechanics calculation and visualization functions of Materials Studio, a modular teaching scheme conforming to the cognitive law of students is constructed, and dynamic demonstration of abstract physics concepts, autonomous simulation operation of the students and real-time result analysis are realized.

A method can include accessing data for a subsurface region that includes horizons that extend to a fault, where the data includes at least seismic data; selecting a portion of the data that is within a distance range of the fault; creating local horizon models for the horizons using at least the portion of the data; generating on-fault horizon data using the local horizon models and a fault model of the fault; computing two-dimensional stratigraphy for a side of the fault based on at least a portion of the on-fault horizon data; and performing a simulation of one or more physical phenomena for the subsurface region using at least the fault model of the fault and the two-dimensional stratigraphy for the side of the fault.

A system and method for simulating multiple dynamic flows involving movement over time, for example, of water and other fluids, air or wind, fire, or the like, is disclosed. The system and method are a visualization and simulation platform designed to create and execute an approach using deep-learning, computer vision, image processing, and artificial intelligence for predicting all manners of dynamic physical motion over time. The visualization and simulation system is configured to quickly model and predict dynamical physical phenomena including, but not limited to, movement of water or air flow or fire in any topography. The visualization and simulation system predicts flooding behavior patterns in “known” geographical domains (regions and / or areas where the deep-learning system has been explicitly trained on) as well as “unknown” geographical domains (regions and / or areas where the deep-learning system has not been previously exposed or trained on) by providing time-dependent two-dimensional hydrodynamic flooding predictions.

The invention discloses an ultrasonic bonding parameter dynamic regulation and control method based on finite element simulation, and the method comprises the steps: building a multi-physics coupling bonding process simulation model through finite element simulation analysis software in a finite element simulation pre-training stage, considering the key physical phenomena, such as ultrasonic vibration propagation, thermal coupling, etc. Parameterized simulation is carried out by combining orthogonal experimental design and a response surface method, and a quantitative mapping relation and a simulation database of process parameters-quality indexes are constructed. The real-time dynamic regulation and control system constructs a multi-closed-loop cooperative control system of real-time monitoring, simulation prediction and dynamic adjustment, collects data in real time, compares the data with a predicted value of a database, and automatically generates a parameter adjustment scheme when a target is deviated. The method can reduce resource consumption, improve the consistency, stability and reliability of bonding quality, reduce the reject ratio and improve the production efficiency, and can be popularized to other similar connection processes.

The invention discloses a high-efficiency physical simulation method, which comprises the following steps of: introducing a physical simulation engine supporting simulation of various physical phenomena, enabling different physical phenomena to correspond to respective modules through the modular design of the physical simulation engine, and covering various fields of thermodynamics, dynamics and the like; complex tasks such as fluid dynamics, structural mechanics, heat conduction and the like can be quickly processed by utilizing GPU multi-core architecture for parallel computing. By dynamically distributing GPU resources and an intelligent load balancing algorithm, a plurality of simulation tasks can be operated at the same time, resource configuration is optimized, it is ensured that the calculation time of each task is controllable, real-time simulation in a complex scene is achieved, and the time requirements of scenes such as real-time monitoring and dynamic control are met. A simulation result is output in real time and can be compared with actual sensor data for verification, so that the result accuracy is ensured.

The application relates to the technical field of particle simulation, and discloses a particle collision method, device and equipment based on physical simulation and a storage medium, the method comprises the following steps: determining current parameters of each particle in a particle system based on initial parameters and external force parameters of each particle; detecting collision information between each particle and / or collision information between the particle and other objects in the particle system through a collision detection algorithm; and updating target collision parameters of each particle based on a collision model, the current parameters and the collision information. In the foregoing manner, the initial parameters and the external force parameters of the particles are considered to more accurately simulate the motion state of the particles under the action of force, a preset collision detection algorithm is used to detect the collision information between the particles and between the particles and other objects in the system, the simulation effect is more realistic, powerful technical support is provided for simulating complex physical phenomena, and the accuracy of the particle collision effect is improved.

A system, apparatus and product comprising: a quantum sensor that is configured to measure a property of a first physical phenomenon; a quantum computer that is configured to execute a parametric quantum circuit comprising qubits that are set to represent the property of the first physical phenomenon, wherein the parametric quantum circuit comprises: an ansatz parametric circuit configured to approximate a target quantum state of a second physical phenomenon, and to output a manipulated quantum state; and an assessing module configured to assess an expectation value of operators on the manipulated quantum state; wherein said quantum computer is configured to implement a Variational Quantum Eigensolver (VQE) scheme to iteratively adjust values of a set of parameters defining the ansatz parametric circuit until the assessing module provides a desired expectation value; and an output module configured to output the desired expectation value.

The embodiment of the invention discloses an electromagnetic simulation model calibration method and device, a storage medium and a program product. The method comprises the following steps: identifying uncertain parameters in an electromagnetic simulation model and forming an uncertain parameter set; inputting the initial value of each uncertain parameter into the electromagnetic simulation model to obtain an electromagnetic simulation result, and obtaining posterior distribution in combination with the initial prior distribution and the initial value of the uncertain parameter set; solving the posteriori distribution to obtain approximate posteriori distribution and an updated value of each uncertain parameter; obtaining a new electromagnetic simulation result based on the updated value; performing performance evaluation on the electromagnetic simulation model based on the new electromagnetic simulation result; and when the electromagnetic simulation model does not reach the standard, taking the approximate posteriori distribution as the prior distribution of the next iteration, and continuously performing performance evaluation on the electromagnetic simulation model until the electromagnetic simulation model reaches the standard. According to the method, the performance of the electromagnetic simulation model can be gradually improved by adjusting and optimizing the uncertain parameters, so that the electromagnetic simulation model better conforms to the actual physical phenomenon.

A system and method for simulating multiple dynamic flows involving movement over time, for example, of water and other fluids, air or wind, fire, or the like, is disclosed. The system and method are a visualization and simulation platform designed to create and execute an approach using deep-learning, computer vision, image processing, and artificial intelligence for predicting all manners of dynamic physical motion over time. The visualization and simulation system is configured to quickly model and predict dynamical physical phenomena including, but not limited to, movement of water or air flow or fire in any topography. The visualization and simulation system predicts flooding behavior patterns in “known” geographical domains (regions and / or areas where the deep-learning system has been explicitly trained on) as well as “unknown” geographical domains (regions and / or areas where the deep-learning system has not been previously exposed or trained on) by providing time-dependent two-dimensional hydrodynamic flooding predictions.

The utility model provides a Lenz's law demonstration device, and relates to the field of exhibition interaction. Comprising at least three slope slideways and a magnetic trolley, the slope slideways have gradients, so that the magnetic trolley slides along each slope slideway, a variable block is arranged on the surface of each slope slideway, and the variable blocks on the slope slideways are made of different materials. The Lenz's law teaching aid is simple in structure, different physical phenomena caused by different materials in the Lenz's law can be visually observed, audiences can experience manually and observe independently, vividness, intuition and interestingness are achieved, and thinking of the audiences is stimulated in an interactive mode.

An apparatus for determining simulation input data for simulating a physical phenomenon with a simulation software includes a user interface for receiving user input data relating to the physical phenomenon to be simulated and a computer interface for extracting initialization data from a predefined definition file. The computer interface is configured to provide the initialization data and user input data to a large language model processor and to receive feedback data and / or simulation input data from the large language model processor. The apparatus further includes a processing unit for determining whether the feedback data indicates that further user input data is required and for controlling the user interface to correspondingly prompt the user and controlling the computer interface to provide the further user input data to the large language model processor in this case, and (b) whether the simulation input data is valid based on the predefined definition file.

The utility model discloses an educational toy for displaying the physical phenomenon of immiscible liquid, which comprises a shell consisting of a back plate and a shell, a circular flow device is arranged in the shell, a visible window is arranged on the front side of the shell corresponding to the circular flow device, a closed cavity for containing the immiscible liquid is arranged in the circular flow device, and the visible window is arranged in the closed cavity. A circulating water pump is installed on the rear side of the circulating flow device, an inlet of the circulating water pump is connected with a pipeline of the confluence part, and an outlet pipeline of the circulating water pump is connected to the position, located on the upper side of the flow dividing part, of the closed cavity; the immiscible liquid is pumped into the closed cavity through the circulating water pump and then naturally falls down, the abstract scientific concept is converted into visual and interesting display, children can experience and observe the characteristics of the immiscible liquid personally, the curiosity of the children is further met, and the enthusiasm of scientific exploration is stimulated.

This invention discloses a physical phenomenon experience learning system based on immersive virtual reality technology, comprising at least a hardware perception layer, a software platform layer, a core logic layer, and a functional module layer. In corresponding scenarios, dynamic commands are implemented through the hardware perception layer, and material attribute parameters in the physics dynamics engine are adjusted through the core logic layer to achieve interaction within the scene. This system deeply integrates experiential education concepts with virtual reality technology. By constructing a high-precision physics engine-driven, high-fidelity scene, it reconstructs ideal observation conditions such as resistance-free and customizable gravitational fields in virtual space. This facilitates a more intuitive, vivid, and cost-effective way for primary and secondary school students and the general public to overcome the limitations of real-world time and space, personally conduct classic and surreal physics experiments, effectively enhance their sense of spatial presence, and deepen their understanding of abstract physics knowledge.

The present specification discloses an entertainment / educational system having one or more interactive stations having associated systems comprising apparatus and activities that demonstrate various physical phenomenon. Each interactive station comprises a different system featuring differing apparatus that provides users the ability to form various types and numbers of bubbles that the users can experience and interact with. User progression and interaction with a particular set of / order of interactive stations is correlated with lessons about physical phenomena exemplified by the bubbles made at a particular station of the total stations visited. The lessons may be further enhanced by information provided to users via a poster, handout, booklet or other informative media or information provided by a guide / attendant escorting user(s) through the set of stations.

Systems and apparatus may carry out analysis of battery physical phenomena, and characterize batteries based on phenomena occurring in particular time and / or frequency domains. These systems may be additionally responsible for charging and / or monitoring a rechargeable battery. Examples of battery physical phenomena include mass transport (e.g., diffusion and / or migration) in battery electrolytes, mass transport in battery electrodes, and reactions on battery electrodes.

An attack detection method according to the present invention involves acquiring change-over-time information that indicates the change over time in physical phenomena that occur in a prescribed space, acquiring sensor data obtained by the sensing of physical phenomena by two or more sensors that are fixed in the prescribed space (S2100), acquiring placement information about the placement of the two or more sensors (S2500), and detecting attacks on the two or more sensors on the basis of the change-over-time information, time series data for the sensor data from each of the two or more sensors, and the placement information (S2500).

A plurality of beds each have, one or more sensors configured to: sense physical phenomena of a user of the bed; and send, to a computer system, sensor readings, wherein the sensor readings include objective data representing measurements of the physical phenomena. A computer system is configured to: receive the sensor readings; receive a plurality of text objects; embed the sensor readings into first vectors of a fixed size; embedding each of the text objects into second vectors of the fixed size; generating, for each user, an aggregated matrix that represents objective data and plurality of text objects; generating a clustering of the users based on the objective data and the plurality of text objects such that users with similar data are placed into the same cluster; and generating a visual representation describing the clustering of the user users.