23 results about "Impact model" patented technology

A method of evaluating impact of a change on nodes of a network, including collecting information of changes to configuration items of the network with a change management module that is executed on a computer of the network and forming a list of changes, receiving a dependency graph that defines dependencies between nodes of the network, receiving an impact model that includes an impact value that provides an indication of a risk value for different types of changes to nodes of the dependencies, executing an impact score generation module configured to receive the dependency graph, the impact model and the list of changes to determine a risk value responsive to a specific change to a node of the network and an impact of the change on other nodes of the network, repairing or predicting problems in the network based on the determined risk value for each change.

The application provides a flood risk prediction method and system considering index and weight uncertainty, and belongs to the technical field of risk analysis, and specifically comprises the following steps: determining the weight coefficients of flood monitoring indexes corresponding to different combinations based on the flood monitoring indexes of historical flood processes in different combinations, determining stable monitoring indexes based on the analysis results of the weight coefficients, determining the construction strategy of the influence model of the flood monitoring indexes based on the variation of the weight coefficients of the flood monitoring indexes between different combinations and based on the stable monitoring index data, and determining a flood risk prediction analysis method according to the influence model and the rainfall data of the rainfall process before the current rainfall process, so that the accuracy of flood risk prediction processing is improved.

Scanner aberration impact modeling in semiconductor manufacturing processes is described. Scanner aberration impact modeling can facilitate co-optimization of multiple scanners. Scanner aberration impact modeling can include executing a calibration model and controlling a scanner based on output from the model. The model is configured to receive patterning system aberration data. The model is calibrated with patterning system aberration calibration data and corresponding patterning process impact calibration data. New patterning process impact data for the received patterning system aberration data can be determined based on the model. The model includes a hyperdimensional function configured to associate the received patterning system aberration data with the new patterning process impact data. The hyperdimensional function is configured to associate the received patterning system aberration data with the new patterning process impact data in an approximate form, rather than full simulation, and without involving computation of aerial images or representations thereof.

Using a failure probability model, a probability of a failure in a first system within a specified time period is predicted. Using an impact model, an impact of the failure on a second system is predicted. Using a resilience model, an impact reduction of the failure is predicted. The probability, the impact, and the impact reduction are mapped into a recommended service level agreement category for the first system, the mapping performed using a classifier model.

This invention relates to the field of wind and sand protection, and discloses a vegetation protection method based on the laws of wind and sand erosion. First, historical wind and sand erosion patterns are collected, recording data on the air impact, soil erosion, and vegetation erosion. Using large-scale modeling technology, an impact model is established, and erosion simulation experiments are conducted to obtain air protection data, soil protection data, and vegetation protection data. Real-time monitoring and evaluation are performed to obtain wind and sand monitoring data. Based on this data, the wind and sand movement patterns are predicted, yielding wind and sand trajectory prediction results. The protection data are then integrated to obtain a first vegetation protection scheme, establishing a vegetation protection trajectory model. The vegetation protection trajectory model is then corrected in real time to obtain a second vegetation protection scheme. This invention solves the problem in existing technologies where vegetation selection for wind and sand protection lacks specificity and cannot be tailored to the wind and sand erosion trajectory.

The application provides a block analysis method for a transient strong impact non-stationary response signal, a storage medium and computer equipment, belongs to the field of non-stationary impact response signal processing, strong impact model test and nonlinear dynamics analysis, and solves the problems that the traditional method cannot objectively identify the stage dynamics evolution of the transient strong impact non-stationary response signal, cannot adaptively extract a local approximate stationary block in the same stage, and finally cannot reveal the system motion evolution law and cannot support subsequent dynamics characteristic extraction analysis. Through signal preprocessing, phase space reconstruction, maximum Lyapunov index stage division, critical time criterion block and stationarity test, the application extracts effective block characteristics, realizes accurate analysis of the transient strong impact non-stationary signal, and has objectivity, adaptivity and universality, and can support subsequent dynamics research.

The invention relates to the field of railway electrified power supply systems, in particular to a railway overhead line system icing form evolution characteristic quasi-steady-state numerical simulation method which comprises the steps of numerical simulation modeling, freezing rain liquid drop impact model setting, freezing rain liquid drop impact simulation, liquid film generation and phase change icing and ice layer appearance updating. According to the method, the whole process of the contact network surface from microscopic droplet impact to macroscopic ice layer formation is fully considered, the whole process comprises droplet impact, breaking, liquid film generation, phase change and ice layer form growth, compared with the prior art, prediction deviation caused by single link simplification is avoided, meanwhile, the grid is dynamically deformed through the RBF interpolation function, and the prediction accuracy is improved. Real-time updating of the ice layer appearance in the simulation process is achieved, and the limitation of a traditional fixed boundary method is overcome; in addition, the method also has the characteristics of real reproduced freezing rain intensity and environmental characteristics and high calculation efficiency.

This invention belongs to the field of unmanned aerial vehicle (UAV) control technology, specifically relating to a method and system for attitude stabilization control of UAVs under special environmental disturbances. The method includes the following steps: S1: Establishing a wind field disturbance model, a dust particle impact model, and an electromagnetic interference model, and dynamically coupling these three models into a total disturbance vector experienced by the UAV; S2: Constructing a six-degree-of-freedom dynamic model incorporating the influence of the total disturbance vector. This model describes the translational and rotational motion of the UAV's center of mass under multi-source disturbances in complex environments; S3: Based on traditional aerodynamic models and incorporating environmental disturbance parameters, constructing a variable structure model with aerodynamic coefficients. This invention effectively improves the UAV's adaptability to multi-source coupled disturbances by constructing a unified multi-layered architecture for environmental identification, disturbance observation, Lyapunov robust control, and actuator compensation, thereby ensuring mission accuracy and safety.

This invention provides a big data-based intelligent matching method for upstream and downstream enterprises in the chemical industry chain, belonging to the technical field of matching upstream and downstream enterprises in the chemical industry chain. The method includes collecting multi-dimensional feature data of the chemical industry chain; analyzing basic enterprise data using an industry chain attribute matching algorithm; analyzing the dynamic changes in supply and demand relationships with market cycles; constructing a quantitative model of supply and demand impact, analyzing the influence weight of dynamic supply and demand data on initial enterprise matching data; and building an intelligent matching model of the industry chain to evaluate the matching process of upstream and downstream enterprises in real time. By integrating multi-dimensional feature data of enterprises and utilizing industry chain attribute matching algorithms, dynamic supply and demand analysis methods, quantitative supply and demand impact models, and intelligent matching models of the industry chain, this invention achieves accurate matching and dynamic optimization of upstream and downstream enterprises in the chemical industry chain, solving problems such as reliance on manual experience in matching, untimely response to dynamic changes in supply and demand, and insufficient risk management capabilities in existing technologies.

The application discloses a method and system for designing parameters of a ground surface concrete cushion layer for protecting a buried pipeline based on rockfall influence, and the method comprises the following steps: constructing a rockfall impact model, a buried pipeline model and a cushion layer model; collecting strain data and velocity of rockfall, variation of earth pressure in an undisturbed soil layer and strain of the buried pipeline model by using a data testing device; analyzing the collected data, and retaining data not exceeding a preset safety range; changing parameters of the cushion layer model by using a control variable method, and keeping other model parameters unchanged until analysis of all parameters of the cushion layer model is completed, and then stopping; further analyzing the retained data to obtain a relationship between strain and the parameters of the cushion layer model, and completing parameter design of the buried pipeline. The application effectively simulates the protection effect of the concrete cushion layer on the buried pipeline under rockfall impact, is closer to an actual engineering, and provides a reference value for the actual engineering.

The invention discloses a method for establishing a multi-particle multi-azimuth impact model for a glass cabinet surface. The method comprises the following steps: establishing a glass substrate model, a plurality of micro-nano super-hydrophobic CNT / SiO2 particle models and an Euler domain model; assembling the glass substrate model, the Euler domain model and the plurality of micro-nano CNT / SiO2 super-hydrophobic particle models; performing grid division on the glass substrate model and the Euler domain model; establishing a temperature-displacement coupling analysis step; setting contact interaction attributes; and setting boundary conditions of all the models, speed parameters of the micro-nano CNT / SiO2 super-hydrophobic particle model and initial temperatures of the micro-nano CNT / SiO2 super-hydrophobic particle model and the glass substrate model, so that the micro-nano CNT / SiO2 super-hydrophobic particle model impacts the glass substrate model in multiple directions at different incident angles. The method lays a foundation for research on particle deformation, equivalent plastic strain, residual stress and the like of cold spraying particle impact.

The invention discloses a method and device for establishing a specific field modeling environment. The method comprises the following steps: constructing a three-layer abstract system for specific field modeling based on a meta-meta model; generating a domain meta-model containing entity class definition, relation class definition and enumeration class definition through an automatic instantiation rule, and configuring attributes, representation forms and constraint relations; packaging the meta-model and the constraint thereof into standardized framework data with a unique identifier; loading the frame data by a runtime analysis module, dynamically generating a visual domain model editor, and enabling a user to complete model construction conforming to constraints; triggering increment verification based on an operation-level event in a model construction process; when the meta-model is updated, executing difference comparison to identify affected model elements and giving repair suggestions; and the runtime expansion of the modeling capability is realized through a plug-in mechanism.

The invention discloses a viewpoint dynamics modeling method introducing external event impact, which comprises the following steps: (S1) constructing a multi-agent opinion dynamics model, and initializing system parameters and agent attributes with activeness; (S2) dynamically constructing a social network structure based on viewpoint homogeneity according to the current opinion difference between the agents; (S3) defining and quantifying an external event, and decoupling the influence of the external event into continuous information content and a dynamic response probability attenuating along with time; (S4) establishing a viewpoint dynamic differential equation by integrating the internal attenuation, the local social influence and the external influence of the intelligent agent; and (S5) updating opinion states of all agents through numerical integration to realize dynamic evolution of viewpoints. According to the method, the dynamic impact model in which the event information and the response intention are decoupled is constructed, so that the technical defect that an existing model simplifies external influence into deterministic impact is overcome, and a computing framework which is closer to reality and higher in interpretation is provided for simulation and prediction of complex social phenomena such as public opinion evolution and crisis response.

This invention discloses a multi-dimensional encryption method for secure data output, comprising: acquiring the data to be encrypted; establishing a quantum-resistant encryption computational model, considering the resource consumption problem that may occur during the encryption process; constructing a side effect impact model; analyzing the resource consumption contribution of the quantum-resistant encryption model; designing a resource consumption contribution mitigation strategy and a model feedback mechanism; optimizing and monitoring the side effect impact model in real time; the optimized model can not only reduce the time and space complexity in the encryption process, but also significantly reduce the computational resource consumption without sacrificing encryption strength, thereby improving encryption efficiency while ensuring data security.

The application provides a lithium battery degradation threshold-impact model construction method and device, equipment and storage medium. It relates to the field of lithium battery life prediction. The method comprises: establishing a lithium battery inherent degradation model using a nonlinear Wiener process to describe the nonlinear characteristics of capacity attenuation; constructing an external impact damage model based on a non-homogeneous Possion process to represent the time-varying characteristics of random impact; coupling the degradation process and the impact damage through a double-threshold failure mechanism to define the capacity attenuation soft failure threshold and the impact cumulative hard failure threshold; dynamically linking the degradation parameters and the impact parameters to correct them using the Bayesian update and optimization algorithm; and realizing the probability distribution prediction of the remaining life based on Monte Carlo simulation. The application can improve the accuracy and engineering applicability of lithium battery remaining life prediction under complex working conditions.

The application provides a kind of impact simulation test construction method based on Digimat / Abaqus, comprising: the setting of the impact finite element model of stab-resistant material, including geometric model, material model, contact definition, load and boundary condition and the output setting of stab-resistant impact simulation result and analysis model, including stab-resistant impact simulation result and stab-resistant impact model verification.The material model containing fabric composite material microstructure information constructed by the application using Digimat can be directly used as the material attribute input of Abaqus / CAE impact finite element model for calculation through Digimat to Abaqus interface technology, realizing the multi-scale analysis of composite material microstructure parameters and macroscopic impact load condition response;And combined with the physical test of stab-resistant impact, the effectiveness of the equivalent impact finite element model of the impact model of the stab-resistant material on the backing is established and verified.

The invention provides a simulation analysis method and device for a negative Poisson's ratio lattice structure, equipment and a medium. The method comprises the following steps: respectively creating a plurality of simulation impact models for various negative Poisson's ratio cell elements; defining a contact relationship, a boundary constraint condition, a simulation impact speed and an output parameter type for the plurality of simulation impact models; grid division and impact simulation are carried out on the multiple simulation impact models, and output parameters corresponding to the output parameter types are obtained; calculating a multi-dimensional evaluation index of each simulation impact model according to the output parameters of each simulation impact model; and according to the multi-dimensional evaluation indexes of the various simulation impact models, carrying out performance comparative analysis on the various negative Poisson's ratio cell elements. According to the method, the performance of the lattice structure of various cell element types can be effectively analyzed.

This invention discloses an intelligent monitoring method for the construction alignment of long-span continuous rigid frames, relating to the field of long-span continuous rigid frame construction technology. The method includes the following steps: S1, data acquisition; S2, data processing; S3, multi-level intelligent early warning; S4, construction control; and S5, output of results. This invention utilizes multi-source devices to collect data synchronously, ensuring data real-time performance and integrity. Deep learning removes anomalies, and neural networks construct environmental impact models to correct data, mitigating the impact of environmental factors on alignment data. Digital twins combined with finite element analysis and neural networks predict deformation trends, improving prediction accuracy, and allowing for early prediction of alignment deviation trends and optimization of construction plans. Multi-level intelligent early warning dynamically adjusts thresholds based on multiple factors, accurately issuing early warning information and enhancing the timeliness of risk response. Construction control automatically generates decision suggestions and provides feedback on evaluation results, optimizing the construction process.

Systems, methods, and other embodiments described herein relate to improving the safety of vehicles by determining lane-level risks of road segments. In one embodiment, a method includes acquiring data about a segment of a roadway. The data indicates at least information about traffic on the segment. The method includes determining a lane-level risk associated with a safety event occurring on the segment using a likelihood model and an impact model. The method includes providing the lane-level risk to cause an approaching vehicle to selectively adapt operation.

The present application relates to the field of bridge health detection, and in particular to a reinforced concrete pier damage evaluation method, device, equipment and storage medium. The method comprises obtaining vehicle impact parameters, simplifying a previously obtained vehicle-pier impact model through the vehicle parameters, obtaining axial displacement, lateral displacement and rotation angle of the nodes at both ends of the fiber beam element; according to the axial displacement, the lateral displacement and the rotation angle, the displacement component of the RC section at any position of the fiber beam element is calculated; based on the displacement component of the RC section of the fiber beam element, the deformation component of the RC section is obtained; according to the RC section deformation component, the first unloading stiffness matrix and the second unloading stiffness matrix at the RC section are obtained; based on the first unloading stiffness matrix and the second unloading stiffness matrix, the third unloading stiffness matrix at the RC section is obtained, and the eigenvalue of the third unloading stiffness matrix is determined; according to the eigenvalue, the pier damage is evaluated.

The invention relates to a form data classification model watermark embedding method for adjusting classification boundaries, and belongs to the technical field of computers. According to the method, firstly, the importance degree of original sample attributes is calculated in combination with Pearson correlation coefficients and mutual information, sample attribute values are adjusted through the importance degree and random numbers, and then samples close to classification boundaries are selected as candidate samples based on model classification results; continuously adding disturbance to the candidate samples until the sample classification result crosses the boundary, weighting the disturbance quantity according to the importance degree of the sample attribute to obtain disturbance scores, and selecting samples from low to high according to the disturbance scores to construct a trigger set; and finally, performing fine adjustment on the model by using a trigger set to realize watermark embedding. In order to solve the problem that the model classification accuracy is greatly influenced due to the fact that samples far away from classification boundaries are easy to select during model fine tuning in an existing method, the fine tuning data set is constructed by selecting samples which have small influence on model performance, and the influence on the accuracy of the watermark model is effectively reduced.

The invention relates to the technical field of geotechnical engineering and foundation treatment, in particular to a self-weight collapsible loess quantification and optimization method based on multiple factors. Comprising the following steps: S1, constructing a settlement model of the self-weight collapsible loess, specifically, constructing a self-weight compression model and a collapsibility potential and environmental influence model, and integrating the self-weight compression model and the collapsibility potential and environmental influence model to obtain the settlement model of the self-weight collapsible loess; s2, carrying out accumulative settlement simulation on the settlement model of the dead-weight collapsible loess constructed in the step S1 to obtain a change chart of the accumulative settlement of the loess along with time, and analyzing the change chart; s3, according to the simulation result of the step S2, optimization measures are put forward, and the optimization measures comprise a dynamic compaction method, a lime-soil compaction pile method and a pre-soaking method; and the settlement of the self-weight collapsible loess is quantified.

This invention proposes an environmental fusion routing method to enhance network resilience. The main function of wireless sensor networks (WSNs) is to collect monitoring data using sensor nodes and transmit the data to a aggregation node. In most cases, WSNs are deployed in unattended monitoring environments, where dynamic changes in the external environment can impact network performance and significantly affect network resilience. This invention first establishes an environmental impact model, mathematically modeling the phenomenon that sensor performance decreases due to changes in environmental factors to derive environmental factors. Secondly, in the data aggregation stage, environmental factors are incorporated into the probability calculation formula for cluster head selection, increasing the probability of nodes with favorable environments being selected as cluster heads. In the data routing stage, path planning is performed using an artificial potential field method, treating the harsh environment as a repulsive field and the distance to the aggregation point and the node's energy as an attractive field, constructing a combined potential field model.