37results about How to "Reliable optimization results" patented technology

The invention discloses a hydrofracture design parameter optimization method based on fine classification of a reservoir. The hydrofracture design parameter optimization method based on fine classification of the reservoir comprises the following steps of (A) calculating current stratum coefficients Kh corresponding to all oil wells on the reservoir; (B) dividing the reservoir into four small categories; (C) calculating a net present value after hydrofracture for 3 years under the conditions that the fracture length ratio of a hydrofracture crack is 0.18-0.43 and the flow guiding capability of the hydrofracture crack is 10D.cm, 20D.cm, 30D.cm, 40D.cm and 50D.cm, and drawing a curve graph by using the fracture length ratio of the crack as an abscissa and the net present value after hydrofracture for 3 years as an ordinate; (D) using the crack fracture length ratio and the crack flow guiding capability which correspond to an inflection point with the maximum net present value as the optimal hydrofracture design parameters of the small categories of the reservoir; and (E) designing hydrofracture schemes on the different small categories of the reservoir by using the different optimal hydrofracture parameters. The principle of the hydrofracture design parameter optimization method is reliable; and the hydrofracture design parameter optimization method is easy and convenient to implement and can provide a refined guidance for parameter optimization in the hydrofracture scheme design.

A method for designing the impeller of an axial flow pump under full working conditions, comprising the following steps: (1) Parametric modeling of the impeller of the axial flow pump: selecting k airfoil sections of the axial flow pump impeller, the cascade density and the total value of the airfoil placement angle 2k design parameters; (2) Optimal design for all working conditions: First, determine the conventional design parameters of the impeller; then perform numerical calculations on the design working conditions of the axial flow pump impeller, comprehensively analyze various losses in the pump, and minimize the total loss Preliminary design of a pair of axial flow pump impellers with better hydraulic performance under the design working conditions; second, design guide vanes, water guide cones and water inlet and outlet channels for the impeller; The optimal weighted average efficiency is the goal, and the head is the constraint condition. The sequential quadratic programming method of the gradient optimization algorithm is used to continuously change the design parameters of the axial flow pump impeller, and iterative numerical calculations are performed on the pump device. The invention adopts CFD numerical calculation, has high design precision and reliable optimization result.

The invention discloses an optimization method of a degeneration acceleration test scheme of an electric connector. The sample size used in a stress-constant degeneration acceleration test and the distribution ratio of samples in different tests influence a test result. The method comprises the concrete steps that 1) the working life tg, the storage environment temperature T0, the lowest test temperature Tz, the highest test temperature Tm and the cutoff time tau of the electric connector are determined; 2) a random process degeneration model of median life of the electric connector is established; 3) m electric connectors to be detected are taken for primary test to obtain parameters a, b, gamma0 and gamma 1 to be evaluated; 4) an optimized target function is determined; and 5) the test temperature and sample distribution ratio of each test are determined. According to the optimization method, the sample distribution ratio of each test is optimized, and the storage life is estimated in higher precision compared with a traditional test scheme in which samples are distributed equivalently under the same total sample size, the same cutoff time, and the same test interval.

The invention relates to a distribution network reactive power optimization control sequence determining method based on big data. The method comprises the following steps: taking the existing historical load data and historical optimization data of a power system as a data source; constructing a distribution network reactive power optimization random matrix; calculating the average spectral radius of the load random matrix based on the ring law; calculating the correlation coefficient of historical load and current load; obtaining a load day with larger correlation by comparing the values of correlation coefficient, and taking the reactive power optimization control sequence of the day as the current optimization sequence. Through the technical scheme of the invention, the problem concerning distribution network reactive power operation optimization is solved.

The invention provides a bogie suspension parameter optimization matching method, which relates to the technical field of suspension parameter optimization design of rolling stock. Establish vehicle dynamics simulation model; carry out suspension parameter matching optimization analysis, determine the input variables and their value ranges required by the model, output evaluation indicators and their threshold settings, and establish a joint simulation module between vehicle dynamics model simulation and MATLAB, According to the optimization goal, the eigenvalue simulation calculation of the vehicle dynamics model is carried out, and the optimization goal value obtained by the simulation is extracted through the co-simulation interface; the required suspension parameter group is obtained from a large number of random parameters by layer-by-layer screening, Finally, the method of discrete statistics is used to process the optimization result data, combining the three-dimensional histogram to mine the matching relationship between the suspension parameters, and according to the actual needs, select the specific value of the matching combination of suspension parameters that meet the requirements and the corresponding optimization target value .

A DOE-based optimization method for the anti-collision performance of the front bumper of the automobile belongs to the technical field of the structural design of the front bumper of the automobile. The peak value of the contact force of the roll-pressed front bumper is taken as the target, and the aluminum alloy front bumper with the largest weight reduction ratio is brought into the vehicle working condition for verification, the variable range and response are set and the optimization calculation is carried out. The optimal solution is obtained from the verification of the working conditions of the whole vehicle. The beneficial effect of the present invention is that the optimization method compares the simulation model with the test model, optimizes the simulation model, performs optimization calculations on multiple groups of variables and responses, and obtains the solution After repeated verification, the optimal solution is finally obtained. The efficiency of model establishment and optimization calculation is high, and the optimization result of the front beam is more reliable, which provides strong data support for the production design of the front beam and saves the company's product development. cost.

The invention discloses a hydrofracture design parameter optimization method based on fine classification of a reservoir. The hydrofracture design parameter optimization method based on fine classification of the reservoir comprises the following steps of (A) calculating current stratum coefficients Kh corresponding to all oil wells on the reservoir; (B) dividing the reservoir into four small categories; (C) calculating a net present value after hydrofracture for 3 years under the conditions that the fracture length ratio of a hydrofracture crack is 0.18-0.43 and the flow guiding capability of the hydrofracture crack is 10D.cm, 20D.cm, 30D.cm, 40D.cm and 50D.cm, and drawing a curve graph by using the fracture length ratio of the crack as an abscissa and the net present value after hydrofracture for 3 years as an ordinate; (D) using the crack fracture length ratio and the crack flow guiding capability which correspond to an inflection point with the maximum net present value as the optimal hydrofracture design parameters of the small categories of the reservoir; and (E) designing hydrofracture schemes on the different small categories of the reservoir by using the different optimal hydrofracture parameters. The principle of the hydrofracture design parameter optimization method is reliable; and the hydrofracture design parameter optimization method is easy and convenient to implement and can provide a refined guidance for parameter optimization in the hydrofracture scheme design.

An aviation command guaranty optimization method based on a discrete event system comprises the following steps: firstly, obtaining an aviation command guaranty simulation task and dividing an aviation command guaranty process into a shipboard sub-process, a takeoff sub-process and a landing sub-process; obtaining all discrete events of each sub-process and establishing a discrete event model of the aviation command guaranty process; finishing the aviation command guaranty simulation task to obtain the discrete event system corresponding to the aviation command guaranty simulation task; establishing a discrete event system corresponding to a simulated aviation command guaranty simulation task in process simulation software; finally, obtaining an operation time threshold value range of each discrete event and comparing to obtain an abnormal discrete event which is used as a discrete event needing to be adjusted, and outputting the abnormal discrete event. By adopting the aviation command guaranty optimization method, analysis of the aviation command guaranty process and simulation of a landing success probability are realized, and the abnormal discrete event of an aviation command guaranty system can be found and are pointedly optimized, so that the aviation command guaranty optimization method has better applicable value.