682 results about "Finite element computation" patented technology

The invention discloses an urban inland inundation situation deduction method based on fusion of mechanism knowledge and deep learning, and the method comprises the steps: collecting data, such as weather, terrain and historical disaster situations, and constructing a standardized database in combination with an inland inundation production and convergence mechanism; constructing an urban inland inundation numerical twinborn model, and optimizing hyper-parameters to improve prediction precision by adopting finite element calculation and a multi-scale coupling method based on hydrological and hydrodynamic models; constructing a causal association network by using the numerical twinborn data, and identifying a core affected area; designing a situation deduction algorithm of a space-time diagram neural network, capturing rainfall waterlogging dynamic characteristics, and realizing advanced early warning and accurate deduction; based on the waterlogging intensity and the exposure and vulnerability of the disaster-bearing body, a risk assessment system is constructed, the disaster diffusion trend and the disaster risk are analyzed, and support is provided for flood prevention decision and emergency management.

The invention relates to the technical field of data processing, and discloses a comprehensive evaluation method and system for the health degree of a distribution network cable. The method comprises the following steps: collecting cable joint multi-source monitoring signals, normalizing the monitoring signals to obtain a degradation degree feature vector, correcting multi-physics field coupling model parameters, obtaining a recessive degradation index through finite element calculation to obtain an enhanced feature vector, and performing time-frequency domain decomposition to extract multi-scale feature parameters to obtain a comprehensive feature matrix; a double attention mechanism calculates a feature weight and a time sequence correlation degree to obtain a deterioration trend prediction value, and fuzzy integral is fused with a multi-classifier output probability to obtain a health degree evaluation grade and an early warning result. According to the invention, the early defect identification accuracy and the degradation trend prediction precision are improved.

The invention discloses a quantitative relation chart construction method based on fault characteristics and stress disturbance in the technical field of oil-gas exploration and development. The method comprises the following steps: constructing a geological structure model; the geologic structure model is converted into a mechanical model, and stratum three-dimensional heterogeneous geomechanical attribute modeling is completed through single-point test analysis, single-well logging interpretation and plane distribution simulation; importing the established three-dimensional heterogeneous rock mechanical parameter model by using modeling software, endowing rock mechanical parameters, and performing grid division on the imported model to generate a grid mathematical model; taking a three-dimensional heterogeneous rock mechanical parameter model as a parameter model for crustal stress prediction, and setting a boundary load loading mode; through finite element calculation, the current crustal stress distribution characteristics of the research area are obtained. According to the scheme, through the technical means of single-point test analysis, single-well logging interpretation, plane distribution simulation and the like, the mechanical properties of the rock under different conditions can be described more accurately.

The invention belongs to the field of intelligent construction, and discloses a deep foundation pit displacement prediction method combining finite element and data driving, which comprises the following steps: calculating a theoretical elastic modulus according to an investigation report, and constructing a sample space by adopting a Latin hypercube sampling method and an orthogonal experiment design method; a proper constitutive model is selected, and corresponding lateral displacement is calculated through finite elements; dimensionality reduction processing is carried out on the data set based on global sensitivity analysis of variance so as to accelerate convergence during subsequent inversion; training an SKRR-LSBOOST model through an ensemble learning method to replace a traditional model; combining an improved Hemma optimization algorithm with a substitution model, and applying the combined model to parameter inversion; and performing forward analysis based on the finite element model defined by the inversion parameters to predict the deformation of the deep foundation pit in the next excavation stage. According to the method, the advantages of numerical simulation and data driving are fully exerted, the calculation cost is reduced according to the rock and soil parameters, higher prediction precision is achieved, and the accuracy of foundation pit deformation prediction is improved.

The present invention discloses a method and apparatus for simulating thermal stress of a casting mold during a service process, and a storage medium. The method comprises: importing a pre-built three-dimensional geometric model of the casting mold, processing the geometric model, and then performing grid division to obtain a casting simulation finite element physical model; assigning material parameters, interface parameters, process parameters, and boundary conditions to the finite element physical model to obtain a casting simulation finite element calculation model; performing casting process simulation calculations to obtain casting simulation results such as mold temperature field and stress field, and exporting result data; interpolating a temperature-stress correction factor; multiplying all correction factor data under the same node numbers with mold stress data to obtain final thermal stress distribution data of the mold during the service process.

The invention discloses a three-dimensional finite element simulation method for a complex slope excavation unloading process, which comprises the following steps of: 1) constructing a three-dimensional model of a complex slope, and establishing a finite element grid; 2) inputting boundary conditions of the model and material parameter information of each stratum; 3) calculating and simulating an initial stress field of the slope before excavation; (4) according to the initial stress field, the unloading load of the slope excavation part is calculated; (5) finite element calculation is conducted on stress deformation of the excavated slope; according to the method, the high-precision three-dimensional finite element model is established, various material parameters and actual boundary conditions are combined, the stress change and the unloading effect of the slope in the excavation process are simulated, the stress redistribution in the unloading process is accurately reproduced, the prediction precision of local instability and stress concentration areas is improved, and the prediction accuracy of the slope is improved. Therefore, a scientific basis is provided for safety assessment of slope excavation.

The invention discloses a steel-concrete joint surface defect identification method based on air coupling ultrasonic guided waves, which comprises the following steps: S1, selecting an ultrasonic guided wave mode and a probe frequency, and determining an incident angle theta of an air coupling excitation probe; s2, constructing a detection system according to the parameters in the step S1; s3, constructing a data set, wherein the acquisition mode of the sample of the ultrasonic guided wave signal in the data set comprises the following steps of: performing actual detection by adopting the detection system to obtain the sample of the ultrasonic guided wave signal; by solving the air coupling ultrasonic three-dimensional finite element calculation model, obtaining a sample of an ultrasonic guided wave signal under the condition that interference factors and joint surface defects exist; s4, training the recognition model by using the data set; the input of the recognition model is the time domain feature and the frequency domain feature of the ultrasonic guided wave signal, and the output of the recognition model is a defect probability value of a measuring point corresponding to the ultrasonic guided wave signal; and S5, identifying the ultrasonic guided wave signal of each measuring point by adopting the trained identification model so as to calculate the defect probability of each measuring point.

The invention relates to the technical field of hydraulic engineering and geotechnical engineering, in particular to a parameter updating method and device for a rock-fill dam deformation analysis model.The method comprises the steps that a plurality of Duncan-Zhang E-B model parameter combinations of an indoor triaxial experiment of a target rock-fill dam project are obtained to construct a copula multivariate joint distribution model; sampling a parameter combination sample of the target rock-fill dam project, and inputting the parameter combination sample into the finite element deformation analysis model to generate a finite element calculation sample; training a pre-constructed deep neural network by using the parameter combination sample and the finite element calculation sample to generate a deep learning agent model; and fusing the copula multivariate joint distribution model, the deep learning agent model and an NSGA-III multi-objective optimization algorithm to search for final model parameters for updating the rock-fill dam deformation analysis model generation by generation. Therefore, the problem that an existing dam project parameter updating method neglects complex correlation existing between different parameters is solved.

The present application relates to a BIM-based hanging basket design method, computer device and computer-readable storage medium, wherein the design method comprises following steps: a parameter acquisition step; a hanging basket modularization step: decomposing structures of hanging baskets into a plurality of design modules; a selection step; a calculation step: calculating parameters of the design modules using a structural mechanics calculation method and / or a finite element calculation method; preliminary BIM model building step: building models of the design modules and a preliminary BIM model of the hanging basket; an optimization iteration step: converting the preliminary BIM model of the hanging basket into a finite element model for calculation, and feeding calculation results back to the preliminary BIM model for structural adjustment, repeatedly performing iterative calculations to obtain optimized hanging basket parameter data; final BIM model acquisition step: the BIM model of the hanging basket adjusted according to the optimized hanging basket parameter data is a final BIM model of the hanging basket. The design method enables autonomous calculation and design of the hanging basket with good versatility.

The invention relates to a fiber hybrid composite material anti-explosion structure optimization method and system, and the method comprises the steps: obtaining geometric parameters of fibers through a Latin hypercube sampling method, building a three-dimensional mesoscopic model based on the geometric parameters, and carrying out the grid division of the three-dimensional mesoscopic model, and obtaining a grid file; on the basis of the grid file and pre-configured simulation parameters, finite element calculation is carried out through a finite element analysis method, and an explosion response evaluation index is obtained according to a finite element calculation result; determining the number of neurons of a back-propagation neural network based on the geometric parameters and the number of the explosion response evaluation indexes, taking the geometric parameters and the corresponding explosion response evaluation indexes as training data, and training the back-propagation neural network based on the training data to obtain a proxy model; and searching genetic geometric parameters from a preset fiber geometric parameter range through a genetic algorithm, predicting the fitness of the genetic geometric parameters through the proxy model, and iteratively solving the target geometric parameters based on the fitness.

The invention discloses a method for researching diffusion stress of a lithium ion battery by constructing a high-fidelity microstructure model. The method comprises the following steps: firstly, performing tomography on an electrode material by using a synchrotron radiation X-ray tomography microscope, identifying active particles in the electrode material, calculating geometric parameters such as spatial distribution and volume radius of the particles, and establishing a three-dimensional geometric model of the lithium ion battery; based on mathematical models such as a reaction mechanism, a kinetic equation and a mechanical equilibrium equation of the lithium ion battery, a three-dimensional heterogeneous electrochemical-force coupling model is constructed, initial and boundary conditions are set for the model, grids are divided, and finite element calculation is carried out. According to the invention, the distribution of diffusion stress and the relationship between the distribution of diffusion stress and lithium ion concentration can be analyzed, and meanwhile, the electrode characteristics such as porosity, curvature, anisotropy and uniformity of the electrode can be analyzed. And battery failure phenomena such as particle breakage and particle stripping can be avoided, and theoretical guidance can be provided for preventing battery failure and capacity fading.

The invention discloses a structure monitoring and anomaly identification method and system based on a refined inverse finite element in a wind turbine blade full-size test process, and the method comprises the steps: obtaining a three-dimensional strain field and a displacement field of a wind turbine blade under the action of a torsion load through employing a finite element simulation and load mapping method; pre-classifying each blade part, determining a corresponding monitoring scheme, and performing a full-size test experiment; according to different monitoring schemes, different inverse finite element calculation modules are adopted, monitoring data of the wind turbine blade are processed, and a three-dimensional strain field and a displacement field of the wind turbine blade are obtained through solving; in combination with spatial correlation between a finite element analysis result and an inverse finite element monitoring result, a specific damage position of the wind turbine blade is accurately identified and positioned by using a numerical optimization method; in addition, the torsional rigidity of the wind turbine blade can be directly solved through simulation data obtained through finite element analysis and measured data obtained through inverse finite element monitoring.

The invention belongs to the technical field of bridge engineering, and particularly discloses a proxy model and finite element fusion method and system for bridge safety early warning. Comprising the following steps: simulating a real load of a bridge by adopting a structural multi-scale finite element model to calculate a bridge structural response, constructing a finite element agent model, and training the finite element agent model by adopting a data set to extract a relationship between weight matrix analysis and output items of a neural network; and in the refined grid division part, considering the damage directly observed by the structure, dividing the model parameters extracted from the monitoring point by the model parameters directly corrected by the damage to obtain a final corrected model. According to the method, sensor signal processing, model correction and finite element calculation are closely combined together through neural network analysis, a method basis is provided for dynamic evolution of a digital object fusion model, and technical support is provided for subsequent bridge structure safety evaluation and health early warning.

The invention discloses a beam column type support rapid design method based on a functional graphic object. The method comprises the following steps that a basic graphic object is established in an interactive drawing system; establishing a longitudinal arrangement object group and a transverse arrangement object group of the beam-column type bracket; modifying a longitudinal arrangement scheme and a transverse arrangement scheme of the steel pipe stand columns; establishing a rod piece finite element calculation model, and calculating the maximum number of required main spandrel girders; carrying out equal-load area segmentation on the reference section of the main beam, and establishing a plane layout diagram including a large cross beam, a small cross beam and a main bearing beam; establishing a plane layout diagram of a steel pipe stand column foot plane and a concrete strip-shaped foundation plane; establishing a plane layout diagram of the section of the steel pipe column and the connector plane; and establishing a two-dimensional / three-dimensional rod finite element calculation model for the designed beam-column type bracket, calculating to obtain a mechanical calculation result of the beam-column type bracket, and establishing an engineering quantity table of a beam-column type bracket design scheme.

The invention relates to the technical field of water conservancy and municipal administration, in particular to a reinforcement calculation method for a non-rod system reinforced concrete structure, which comprises the following steps: replacing long and thin pile and rod structures with one-dimensional units, replacing pier, wall, plate and beam structures with two-dimensional units, and carrying out coupling connection on a whole hydraulic structure model; original three-dimensional entity unit finite element calculation is equivalently converted into one-dimensional line unit, two-dimensional plate unit and three-dimensional entity unit coupling structure finite element calculation; displacement, internal force and stress of all parts of the hydraulic structure are obtained, and structural reinforcement is conducted through the internal force according to a structural mechanics method adopted by the rod system reinforced concrete structure. Compared with the prior art, the method has the advantages that the internal force of each part of the building can be directly obtained, the structure stress can be truly reflected, the structure reinforcement mode and number can be optimized, and the original complicated non-rod-system reinforced concrete structure can be subjected to structure reinforcement according to a structural mechanics method adopted by the rod-system reinforced concrete structure.

The invention provides a model quality evaluation optimization method and device for industrial simulation application and a server, and relates to the technical field of simulation application generalization development, and the method comprises the steps: obtaining a to-be-processed geometric model, and carrying out the format detection processing, format conversion processing and asynchronous processing of the geometric model, and determining a target input model; performing grid division processing and finite element analysis processing on the target input model, determining a finite element calculation result, performing local error estimation analysis processing on the finite element calculation result, locally refining a model grid of the target input model, determining a model key region, performing local encryption processing on the key region, and obtaining a local encryption result of the target input model; determining a model output result; and carrying out optimization processing on the model output result through a model quality evaluation optimization system with a layered architecture, and determining an optimized target model output result. The model quality can be remarkably improved.

The invention discloses a rusty metal wire fatigue life calculation method, device and equipment, and the method comprises the steps: building a finite element calculation model of a real corrosion surface, calculating a stress concentration region of the real corrosion surface, determining the position, size and crack propagation direction of a dangerous corrosion pit, defining a damage evolution criterion and a damage criterion, and calculating the fatigue life of the rusty metal wire. And a criterion program is embedded in finite element software for calculation, and the fatigue crack initiation life and extension life of the rusted metal wire are obtained. And a CM-EIFS extrapolation method is combined with the fatigue crack initiation and propagation model to respectively calculate the fatigue crack initiation life and propagation life of the rusted metal wire, and the fatigue crack initiation life and propagation life are compared with the calculation result of the finite element calculation model to verify the correctness of the fatigue life calculated by the rusted metal wire model. By establishing the finite element calculation model considering the corrosion morphology and the crack initiation life, the calculation result of the fatigue life of the rusted metal wire is closer to the actual situation, the calculation is simple and convenient, and the precision is high.

The invention discloses a reverse design method of an underwater sound absorption superstructure under a multi-material system in the technical field of vibration and noise control. The reverse design method of the underwater sound absorption superstructure under the multi-material system comprises the following steps: predicting the macroscopic sound absorption performance of the superstructure based on an equivalent medium theory; based on an energy homogenization theory of an SIMP interpolation function, establishing a superstructure topological optimization reverse design method under the multi-material system; and a proper material system is selected, and the multi-material superstructure is precisely designed by taking equivalent elastic parameters of the superstructure as targets. Compared with an existing underwater sound absorption superstructure design method, the method has the advantages that large-scale sound-solid coupling finite element calculation can be avoided, and efficient design of the superstructure and good low-frequency broadband sound absorption performance are achieved; in addition, the design method provided by the invention has universality under different multi-material systems.

The invention relates to the technical field of infrared light machine system thermal deformation prediction, in particular to a multi-material structure thermally induced stress deformation prediction method based on a graph neural network. The method comprises the steps of data set establishment, graph structure establishment, graph neural network model establishment and training and model and parameter optimization. Finite element nodes correspond to graph nodes, finite element edges correspond to graph edges, an encoder-message passing-decoder architecture model is established, and node states are updated through a three-layer physical symmetry message passing mechanism. Physical constraint loss including minimum displacement smoothness constraint and stress continuity constraint is innovatively added into a loss function. Compared with traditional finite element calculation, the method has the advantages that the speed is increased by more than 100 times, high hardware adaptability is achieved, the black box limitation of a data-driven neural network model is broken through, thermally induced stress deformation analysis caused by different material coefficients can be processed, the adaptability to geometric changes is high, and good engineering application value is achieved.

Disclosed in the present invention is a three-dimensional laser point cloud-based cable force measurement method for a stay cable. Stay cable actual measurement line shape fitting is performed by utilizing point cloud data, obtained by means of three-dimensional laser scanning, of the stay cable, and on the basis of a finite element calculation method, a line shape that is calculated by a stay cable finite element model and is the same as the actually measured line shape of the stay cable is found, thereby determining an actual cable force of the stay cable, and achieving the purpose of accurately measuring the cable force of the stay cable. According to the present invention, a three-dimensional laser scanning technology is introduced and applied to cable force measurement of a stay cable, and for the defects of a common cable force measurement method, the characteristics of non-contact measurement, high measurement precision, high measurement efficiency and the like of the three-dimensional laser scanning technology are utilized so as to achieve rapid measurement of the line shape and the section size of the stay cable. On the basis of finite element calculation and analysis, the three-dimensional laser point cloud-based cable force measurement method for the stay cable is provided, thereby achieving rapid and efficient measurement of the cable force of the stay cable.

The invention discloses a simulation optimization method, device and system for tire multi-rubber modulus matching, and belongs to the technical field of tire simulation optimizing.The method comprises the steps that a tire and a pavement finite element model are built, and the tire and pavement finite element model comprises a three-dimensional tire simulation model and a two-dimensional rigid pavement model; matching a modulus attribute of a rubber material to which each finite element grid of the tire simulation model belongs through an orthogonal test design method, carrying out finite element calculation based on the tire and the pavement finite element model, and calculating multiple groups of stress-strain and strain energy data of target belted layer endpoints of the tire under different modulus attributes; and respectively calculating modulus characteristic values of the tire under different modulus attributes on the basis of the multiple groups of stress-strain and strain energy data of the endpoints of the target belted layer, so as to obtain the optimal modulus ratio of multiple rubber materials of the tire. According to the method, the precision and usability of simulation optimization are improved, the service life of the tire is prolonged, the utilization rate of tire design materials is increased, and the design cost is reduced.

The invention discloses a rigidity determination method, device and equipment of a transmission shell assembly and a medium, and belongs to the technical field of computer-aided engineering.The method comprises the steps that on the basis of a three-dimensional geometric model of the transmission shell assembly, the rigidity of the transmission shell assembly is determined according to the analysis requirement of the transmission shell assembly; establishing a shell assembly finite element model corresponding to the transmission shell assembly; configuring the finite element model of the shell assembly to obtain a finite element calculation file; analyzing the finite element calculation file through a target solver selected by a demand side to obtain a rigidity analysis result of the transmission shell assembly; and determining whether the rigidity of the transmission shell assembly is qualified or not according to a rigidity analysis result. According to the method, physical tests are not needed, the research and development period of the transmission shell assembly is shortened, the material cost in the optimization design process of the transmission shell assembly is reduced, the reliability of the transmission shell assembly is guaranteed, and therefore the overall performance and reliability of a transmission are improved.

The invention relates to the technical field of wharf desilting, and particularly discloses a wharf desilting method and system and electronic device.The wharf desilting method comprises the steps that evaluation of the influence of underwater siltation on a wharf structure is carried out, and a finite element calculation model is constructed; the working states of the high-pile wharf under different deposition depths are simulated based on a finite element model, and a centrifugal model test is carried out; researching the deposition rule of wharf sediment, including collecting hydrological sediment data of water areas near a project for many years and analyzing riverbed evolution; a pneumatic sand flushing device is adopted for treating wharf siltation, and the method comprises the steps of positioning a desilting position, building an indoor water tank to obtain an optimal pneumatic parameter combination and arranging the pneumatic sand flushing device; and an intelligent silt prevention and safety guarantee platform is constructed. According to the wharf desilting method, the stress state of the wharf structure before and after desilting can be accurately evaluated, the reasonable maximum deposition depth and the maximum front-edge desilting elevation are determined, collapse accidents in the desilting process are effectively avoided, and the safety of the wharf structure is guaranteed.

The invention provides a chain ring fatigue damage calculation method and system considering wear conditions, under the conditions of multiple working conditions and multiple wear losses, fatigue load calculation and accumulated damage analysis are carried out on a suspension chain ring, and through time domain simulation, finite element calculation, rain flow counting and S-N curve combination, the fatigue damage of the chain ring is calculated. And a working condition-abrasion loss-fatigue damage database is established. According to the method and the system, accurate evaluation and early warning can be provided for safe service management of the anchor chain or the suspension chain in ship and ocean engineering, and the reliability and the economical efficiency of system operation are greatly improved. All the parts of the device can be independently implemented and can also be modularly combined.

The invention belongs to the field of winding temperature control, and relates to a PCA-FCNN-based converter transformer valve side winding oil flow temperature rise calculation method, which analyzes a thermodynamic conduction process in a valve side winding, determines a characteristic variable having the highest correlation with a temperature field, performs high-correlation characteristic variable parameterization setting by using Latin hypercube sampling, and calculates the oil flow temperature rise of the valve side winding. A valve side winding flow-heat coupling calculation model is established, and finite element calculation software is used for flow-heat coupling calculation; constructing a data set of a calculation model by taking the parameterized characteristic variable as an input characteristic quantity and taking the valve side winding oil flow temperature rise calculated by a finite element as an output characteristic quantity, dividing the data set into a training set and a test set, and generating a valve side winding oil flow temperature rise rapid calculation model with relatively high precision by setting model training parameters; a validation set other than the model data set is set to validate the accuracy of the computational model. According to the method, the required calculation time is shortened by about 300 times compared with the calculation time of a finite element method, and the calculation speed of the oil flow temperature rise of the valve side winding is increased.

The invention discloses an old transformer hot-spot temperature prediction method based on multi-source heterogeneous data processing. The method comprises the following steps: step 1, establishing a transformer digital twinborn analysis model; 2, taking the transformer physical model as an object, obtaining optical fiber temperature measurement data, thermocouple temperature measurement data and an infrared temperature measurement picture, and proposing a heterogeneous data processing technology to carry out data extraction on the infrared temperature measurement picture; 3, finite element calculation is carried out through magnetic-thermal-fluid multi-physics field coupling, and correction is carried out through experimental data obtained in the step 2; 4, temperature data is obtained according to finite element calculation in the step 3 to serve as a data analysis basis, and then a random forest model is established for training and optimization; step 5, obtaining operation temperature data of the transformer; and step 6, performing prediction calculation on the hot spot temperature. The method has the advantages that compared with traditional hot spot temperature calculation in which a temperature field is simplified, the method can effectively avoid the inaccurate situation.

The invention provides an in-situ real-time monitoring method and system for a rock microscopic fracture mechanism and stress evolution. The method comprises the following steps: S1, standardized preparation and pretreatment of a rock sample; s2, in-situ loading and multi-modal data synchronous acquisition are carried out; s3, crack dynamic tracking and stress-strain field joint calculation; s4, constructing a microscopic-macroscopic quantitative correlation and damage model; and S5, performing multi-dimensional dynamic visualization and engineering output. The in-situ scanning electron microscope and the mechanical loading device are integrated, so that cross-scale synchronous monitoring and quantitative analysis of micro crack evolution and macroscopic stress-strain response are realized. A low-disturbance clamping device and a conductive anti-charge sample are treated, and in-situ testing is ensured; combining DIC and deep learning to quantify a crack propagation path, a local strain field and energy characteristics; through DIC strain inversion and finite element calculation, a non-contact stress cloud picture is generated in real time, and finally quantitative correlation between a microscopic fracture mechanism and macromechanical response is established.

The invention provides a pavement structure response monitoring and total distribution calculation method based on a digital twinborn technology. The method comprises the following steps: S1, constructing a road structure and a digital twinborn model thereof; s2, an embedded sensor is arranged in the road structure, and real-time structure response data of the road structure at the feature position under the vehicle load effect are obtained; s3, carrying out an on-site loading test, obtaining structure response actual measurement data under the action of a vehicle moving load, and verifying and correcting the digital twinborn model; s4, using finite element calculation software to perform simulation calculation and output structural response data of the sampling points under the action of different load working conditions based on the digital twinborn model; and S5, training a deep learning model by using the simulation response data. According to the method, a digital twinning technology is utilized, a high-fidelity mapping model of a physical entity in a virtual space is constructed, behaviors of the physical entity in a real environment are accurately simulated, and a data basis can be provided for a machine learning response deduction method at low cost.

The invention discloses a turboshaft engine external pipeline vibration assessment method and system, equipment and a medium, and the method comprises the steps: firstly carrying out finite element calculation analysis on an external pipeline, correcting the connection rigidity through a knock frequency test, considering the influence of the connection rigidity, correcting a finite element calculation model, and carrying out the vibration assessment of the external pipeline; according to the method, the calculation resonance frequency and the knocking resonance frequency are kept consistent, so that accurate pipeline vibration characteristics can be obtained, the accuracy of pipeline risk assessment can be improved, a finite element calculation model is verified and corrected only by performing a simple test comparison frequency result, and a complex modal test does not need to be performed. And then, by adopting a mode of combining finite element calculation and a whole machine maximum unbalance test, the vibration condition of the external pipeline can be simulated more accurately based on an accurate finite element calculation result and combining a whole machine installation condition, and the accuracy of pipeline risk assessment can be further improved.

The invention discloses a containment failure probability curve fitting method and system based on a random forest, and relates to the technical field of nuclear power safety. Comprising the following steps: acquiring key parameters influencing ultimate bearing capacity of a containment, determining a distribution interval of the key parameters, and establishing a key parameter table; performing finite element calculation on the basis of the key parameter table, obtaining ultimate bearing capacity of the containment vessel under different parameter combinations and temperature loads, and establishing a database; performing normalization preprocessing on the database to form a training data set; establishing a random forest model and performing regression model training by using the training data set; inputting actual design parameters of the containment and the temperature required to be evaluated into the trained model to obtain an ultimate bearing capacity predicted value of the containment; and fitting of a failure probability curve is carried out based on the central limit theorem. According to the method, complex probabilistic safety analysis is converted into a standardized calculation task, and the implementation threshold of nuclear power plant design verification and safety review is greatly reduced.