38results about How to "Reduce the number of simulations" patented technology

The invention provides a method and a device for geologic random inversion based on multiple-point geostatistics, and relates to the technical fields of geology and petroleum exploration. The method includes the following steps: determining an initial lithofacies model by a multiple-point geostatistical stochastic simulation algorithm; performing probabilistic disturbance updating to generate a probabilistic disturbance updated lithofacies model; counting the distribution functions of reservoir physical parameters in different lithofacies, and converting the probabilistic disturbance updated lithofacies model into a pseudo-reservoir physical property parameter model; converting the pseudo-reservoir physical property parameter model into an elastic parameter model; carrying out time-depth conversion to obtain a time domain elastic parameter model, determining a reflection coefficient, and synthesizing a seismic record through forward modeling a convolution model; comparing the seismic record with a pre-determined actual seismic record, and determining a lithofacies model result and a pseudo-reservoir physical property parameter model result according to a maximum disturbance numberand a maximum simulation number; and carrying out quantum annealing optimization on the pseudo-reservoir parameter model result to generate a reservoir physical property parameter inversion result.

The invention provides an active distribution network voltage drop simulation and evaluation method. The method comprises the steps that 1, the existing distribution network analysis software is used to build a model, and network flow is calculated; 2, through two-point method sampling, distribution network fault data and distributed power supply capacity data are produced, and a simulation scheme is determined; 3, simulation calculation is carried out, and expectation, variance, a three order central moment, a probability density function f(xi) and an SARFIx index of each node voltage drop are calculated; 4, a Monte Carlo method is used to calculate a probability density function f(xi) MC and an SARFI'x index of each node voltage drop amplitude; 5, the f(xi) and the f(xi) MC are compared, and the SARFIx index and the SARFI'x index are compared; and 6, if a comparing requirement is not met, returning to the step of 2 is carried out. Compared with the existing technology, the active distribution network voltage drop simulation and evaluation method provided by the invention has the advantages that various short circuit faults in a power distribution network are comprehensively considered; the method can adapt to power distribution networks of various wiring modes; and the calculation efficiency is high.

The invention provides a unit load dynamic reactive response based minimum boot order optimization method. The method comprises the steps of determining a weak spot in a heavy load region of a power system; determining an electrical distance index and a dynamic reactive response quantitative index; calculating response effect indexes influencing system voltage of each generator in the power system separately; determining the boot order of the generators according to index values of the response effect indexes; controlling the startup and shutdown of the generators based on the boot order, and detecting the steady state of the weak spot, wherein the actual startup-shutdown order of the generators when the weak spot reaches a critical steady state is the minimum boot order. Compared with the prior art, the invention provides the unit load dynamic reactive response based minimum boot order optimization method; the effect degrees for the system voltage in the shutdown processes of the generators are clearly determined, so that the generator boot order arrangement policy at the minimum machine halt mode is greatly improved, and the method is relatively high in adaptability.

A parameter error accumulation based gear system performance reliability degree calculation method comprises the following steps of 1 determining assembly parameter type; 2 determining sensitivity parameter type; 3 performing sensitivity parameter response surface analysis; 4 calculating gear system performance reliability degree. The parameter error accumulation based gear system performance reliability degree calculation method overcomes the shortcoming that a traditional performance reliability degree calculation method does not give full consideration to assembly accumulation error influence, a coordinate is established for a gear system model and model offset and rotation processing is performed to enable a model assembly mode to approximate to the actual situation, and continuous transformation of model assembly sensitivity parameters within an error range is achieved. Stress simulation of each group of design points is automatically performed after other simulation conditions are controlled by software, consistency of the conditions is ensured, and meanwhile calculation efficiency is also improved. Safety factor distribution of a gear system in different assembly modes is determined through response surface analysis, accordingly performance reliability degree is determined, simulation times are decreased, and efficiency is improved.

The invention discloses a method for optimizing of model selection based on clustering analysis. The method comprises the following steps of 1, establishing a plurality of three-dimensional quantitative geological models, calculating the attribute value of each grid node of each model, standardizing the attribute value, calculating the Euclidean distance between any two models, and obtaining a dissimilarity matrix for representing the difference of each model; 2, reducing the dimension of the dissimilarity matrix, and distinguishing the similarity of the model by vectors in a two-dimensional space; 3, clustering the model by a clustering analysis method, and selecting one or a plurality of models from each type for the research of numerical reservoir simulation; 4, comparing a well point attribute value histogram and a histogram of the selected model, and judging whether the selected model meets the geological concept or not; 5, comparing the reservoir calculated by the selected model and the P10, P50 and P90 reservoirs, and judging the representativeness of the selected model. The method has the characteristics that the simplicity and objectivity are realized, the application range is wide, and the method can be applied to the field of reservoir description.

The invention discloses a method for rapidly optimizing simulation design of an antenna. The optimization method is characterized by comprising the steps of firstly, designing an initial sample through a multidimensional uniform sampling algorithm; then replacing electromagnetic simulation with a Kriging model part for solution; then balancing searching breadth and depth through a population composing and screening method, so that an optimized model of the antenna is obtained. By the adoption of the method, under the same optimization setting, compared with existing algorithms, the number of simulation times required for reaching the optimization target is reduced by 70% or above, and antenna simulation optimization design efficiency is improved.

The invention discloses a circuit yield estimation method based on CAD Monte Carlo analysis. The method comprises steps as follows: a topological structure of an analyzed electronic circuit or integrated circuit, a performance parameter index range of the circuit and statistical distribution laws of a key element parameter and an element parameter are determined; an agent model between a circuit performance parameter and an element parameter nominal value is established for approximating a circuit; a random sampling combination sequence of circuit Monte Carlo analysis is generated according to the circuit element parameter distribution laws; the agent model of the circuit performance parameter is used for predicating the random sampling combination sequence, and circuit performance parameter predicted values and a confidence interval range of each performance parameter predicted value are obtained; the circuit performance parameter predicted values are modified and calculated; and the performance parameter predicted values are substituted into the a performance parameter index standard range for statistical analysis, and the yield of the circuit performance parameter is calculated. According to the method, the time cost is low, the circuit simulation times are few, the analysis efficiency is high, and the accuracy for estimating the yield is high.

The invention discloses a full-working condition performance prediction method for a compressor, and aims at providing a rapid and accurate full-working condition aerodynamic performance prediction method so as to increase the design and optimization efficiency of the compressor. In the method, a formula is established by taking parameters of a design point as the reference to predict the flow, the efficiency and the overall pressure ratio of an off-design working condition; in a flow prediction method, firstly, the flow of the design point is converted according to an empirical formula to flow corresponding to a peak efficiency point at different rotating speeds, and then, blocking flow and surging flow at respective rotating speeds are calculated; in an efficiency prediction method, firstly, the efficiency of the design point is converted according to the empirical formula to peak efficiency at different rotating speeds, and then, the efficiency at different rotating speeds is calculated according to an elliptic piecewise approximation method; and in a prediction method for the overall pressure ratio, work factors at different rotating speeds and different flow are calculated according to the thought of the equivalent width of an impeller exit, and the work factors are combined with current efficiency to obtain the overall pressure ratio. By applying the full-working condition performance prediction method to design and optimization of the compressor, the design cycle can be remarkably shortened, and the design cost is reduced.

The invention discloses a cold rolling method for improving structure properties of ferritic stainless steel plate strips and an analysis method thereof, belongs to the technical field of cold rolling processes, and solves the problem of low structure properties of traditional cold-rolled ferritic stainless steel plate strips. Based on a deformation resistance model of a blank for cold rolling and thermophysical parameters of a material, a finite element analysis model of the plate strip cold rolling process is built according to a actual cold rolling production process; and under the condition of definite total reduction rate, the shear stress and the shear strain distribution in the plate strips under different gate reduction rate distribution systems are analyzed, and a total reduction rate and a reduction rate distribution system for improving the structure properties of the annealed plate strips are determined through calculating the shear strain energy distribution and change rules in the plate strips. The method can accurately analyze the cold rolling process parameters of the ferritic stainless steel annealed plate strips to improve the structure properties of the ferritic stainless steel annealed plate strips so as to obtain the ferritic stainless steel plate strips with excellent formability.

The invention relates to a simulation replay method for a fault record of a high-voltage direct current power transmission system. The method comprises the steps of acquiring the amplitude and the phase of a fault waveform voltage source of a rectifier station and an inverter station before and after a fault of the high-voltage direct current power transmission system through a data reading module respectively, and adjusting the amplitude and the phase of an ideal voltage source of the rectifier station and the inverter station according to the amplitude and the phase respectively to be consistent with the amplitude and the phase of the fault waveform voltage source; and controlling the on-off states of a fault waveform voltage source circuit breaker and an ideal voltage source circuit breaker through a handover control switch, thus realizing stable handover between the ideal voltage source and the fault waveform voltage source based on fault recording data, avoiding manually adjusting simulation parameters for multiple times, reducing the number of simulations, realizing automatic simulation replay of the fault record of the high-voltage direct current power transmission system and improving the fault replay accuracy and the simulation efficiency.

The invention provides a circuit simulation method and device, a storage medium and electronic equipment. The method comprises the steps: obtaining an initial value of a model parameter of a target circuit and a target value of a circuit parameter; setting a first model parameter value and a second model parameter value according to the initial value of the model parameter, the first model parameter value being larger than the initial value, and the second model parameter value being smaller than the initial value; performing simulation according to the initial value, the first model parametervalue and the second model parameter value to obtain a corresponding initial circuit parameter value, a first circuit parameter value and a second circuit parameter value; determining a value interval where a target model parameter value corresponding to the target circuit parameter value is located according to the initial circuit parameter value, the first circuit parameter value and the secondcircuit parameter value; and performing simulation for multiple times in the value interval to obtain the target model parameter value. The efficiency can be improved, and the operand can be reduced.

The invention discloses a probability circuit simulation method based on a steepest descent method and a bisection method. The probability circuit simulation method comprises following steps: (1) determining a corresponding relation between a probability unit and an output signal and determining a "gradient" relation therebetween at the same time; (2) acquiring a probability unit combination matrix with respect to each individual output signal, and meeting required precision requirements by using the bisection method to adjust error probabilities; and (3) carrying out overall optimization so as to obtain a final result, allowing a value of each probability unit to be a maximum value and a minimum value in each row in step 2 to obtain two groups of probability combinations and carry out simulation, finding out an output signal, whose error probabilities are at two sides of a target value and error probability difference value is the biggest in two groups of tests, using the bisection method to optimize the final result again and repeating the above steps until all the output error probability values reach a required precision. The probability circuit simulation method is advantageous in that a probability unit needing to be adjusted can be chosen in a quite precise manner during adjustment of a probability value; an error probability value of the probability unit is adjusted in a quite precise manner; and more energy is acquired and saved.

The invention discloses a network performance increment optimization evaluation method oriented to simulation of a power communication system. The network performance increment optimization evaluationmethod comprises the steps that performance indicator data of the power communication system are preprocessed, and the indicator vector corresponding to each performance indicator datum is obtained;the products of the local densities of all the indicator vectors and the extreme distances are subjected to descending sort, a first preset number of the indicator vectors are selected as central points of all class clusters, and the remaining indicator vectors are divided into the corresponding class clusters to be clustered according to the relative distances; multiple indicator vector representations in each class cluster are determined, and the representative vectors are selected; the representative vectors in each class cluster and the increment simulation performance indicator data are combined to form a new to-be-clustered sample set, and re-clustering is conducted according to the relative distances between the increment simulation performance indicator data and the representativevectors to update the representative vectors; and according to the representative vectors updated after re-clustering, evaluation is conducted through the network performance increment optimization evaluation method of the power communication system.

The invention discloses a yield prediction method and system of a circuit based on a Bayesian filter and resampling. The yield prediction method comprises the following steps: pre-sampling a parameter domain by adopting a Scrambled Sobol sequence to obtain a pre-sampling point; obtaining an initial failure domain and an initial non-failure domain according to the pre-sampling points, constructing initial sampling distribution, and performing iterative operation by taking the initial failure domain as a current failure domain; during iterative operation, a sampling center of a current failure domain is selected according to a corresponding rule to perform resampling, and classifier screening and SPICE simulation are performed to obtain a new failure domain; and if the quality factor of the current failure rate estimation value reaches the convergence standard, stopping iteratively outputting the unbiased estimator of the current failure rate, otherwise, taking the new failure domain as the current failure domain to continue the iterative operation. According to the method, the naive Bayes classifier is constructed by fully utilizing the information obtained by pre-sampling to classify and screen the sampling points, and whether follow-up simulation is carried out or not is determined according to the screening result, so that the SPICE simulation frequency is greatly reduced.

The invention discloses a pintle type solid attitude and orbit control thrust rapid prediction method. A pintle type solid attitude and orbit control thrust physical model, design variables, constraint conditions and a design space after a deposition effect is considered are determined; generating input variables of training sample points in a design space through an experimental design method, and calculating a real output response of the physical model at each training sample point; establishing an augmented radial basis function approximation model of the pintle solid attitude and orbit control thrust by adopting a chaotic polynomial augmented radial basis method; converting a problem of determining a plurality of shape parameters in the approximation model into an anisotropic scaling coefficient optimization problem; and solving the anisotropic scaling coefficient optimization problem by adopting a K-fold cross validation algorithm, selecting the anisotropic scaling coefficient with the minimum cross validation error, and bringing the anisotropic scaling coefficient back to the approximation model to obtain a pintle type solid attitude and orbit control thrust rapid prediction model. And rapid prediction of the pintle type solid attitude and orbit control thrust can be carried out based on the pintle type solid attitude and orbit control thrust rapid prediction model.