160 results about "Response surface methodology" patented technology

A method and system for data modeling that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The invention partitions the parameters into a first set of s simple parameters, where observable data are expressible as low order polynomials, and c complex parameters that reflect more complicated variation of the observed data. Variation of the data with the simple parameters is modeled using polynomials; and variation of the data with the complex parameters at each vertex is analyzed using a neural network. Variations with the simple parameters and with the complex parameters are expressed using a first sequence of shape functions and a second sequence of neural network functions. The first and second sequences are multiplicatively combined to form a composite response surface, dependent upon the parameter values, that can be used to identify an accurate model.

A method and system for design optimization that incorporates the advantages of both traditional response surface methodology (RSM) and neural networks is disclosed. The present invention employs a unique strategy called parameter-based partitioning of the given design space. In the design procedure, a sequence of composite response surfaces based on both neural networks and polynomial fits is used to traverse the design space to identify an optimal solution. The composite response surface has both the power of neural networks and the economy of low-order polynomials (in terms of the number of simulations needed and the network training requirements). The present invention handles design problems with many more parameters than would be possible using neural networks alone and permits a designer to rapidly perform a variety of trade-off studies before arriving at the final design.

The invention discloses a three-point support optimization design method of a machine tool bed based on a response surface model. The method comprises the steps that a simplified model of a bed structure is established in CAD (Computer-Aided Design) software; three-point support limiting positions are found; a variable design space and an optimization objective are determined; test sample points for statics analysis are selected from the design space, and subjected to the statics analysis by finite element analysis software; a response value is calculated and extracted; a second-order response surface model, reflecting an input-output relation of structural design, of deformation at guide rails of the bed is established according to the response value; an optimal solution of the response surface model is acquired by a genetic algorithm; based on the established second-order response surface model, three-point support positions when the deformation of the guide rails is minimum are found; a practical model of the bed is subjected to the statics analysis; and the reliability of three-point support optimization design is verified. With the adoption of the method, the deformation of a machine tool is reduced; the machining precision of the machine tool is improved; the three-point support optimization efficiency and the optimization precision are improved; and the problems that the calculation amount is large, the efficiency is low, and an optimal result cannot be ensured easily in the existing optimization technique are solved.

The invention discloses a bridge finite element model modifying method, which comprises the following steps that: 1, an entity finite element model of a whole bridge is built by universal finite element calculation software ANSYS; and 2, the entity finite element model of the whole bridge is subjected to primary modification by a uniform design method. The bridge finite element model modifying method has the following advantages that the uniform design method is used as a test optimization design method with obvious superiority, and the application of the uniform design method to the bridge structure finite element model modification is feasible; on the basis of the uniform design method, a more correct result can be found in a very short time by the uniform design method in the efficiency aspect, and the bridge large-scale finite element model modification efficiency is improved; a response surface method is used as a test design and mathematical statistics combined mathematical analysis method, and the application of the response surface method to the finite element model modification of a large-scale complicated bridge structure is feasible; and higher modification efficiency and higher modification precision can be ensured at the same time.

The invention relates to a bag dust filter air distribution multi-parameter optimization method comprising the following steps: first, determining bag dust filter air distribution main control design parameters and dust filter basic geometric parameters, carrying out multi-parameter working condition optimization design using a response surface methodology, establishing a dust filter geometrical model under each working condition and determining a computation area, and using a grid division tool to divide the computation area into topology grids; then, carrying out discretization equation iterative solution computation based on the principle of computational fluid dynamics, and carrying out multi-parameter optimization design of the solution computation result based on the response surface methodology; and finally, getting an optimal solution set. Through the method, the speed and pressure distribution at any cross section in a dust filter can be obtained, and the multi-parameter optimization design can be carried out on bag dust filter air distribution based on the response surface methodology, namely, a multi-parameter optimization design method. The method is applicable to air distribution optimization design of all types of bag dust filters, and the result is reliable and accurate.

The present invention provides a response surface based optimization method for a single reed structure in a novel space deployable hinge. The method comprises: according to an actual operating environment of the single reed structure in the novel space deployable hinge, establishing a simplified mechanical model; performing equivalent processing on constraint and loading modes of the single reed structure; obtaining a first-five-order buckling mode and a buckling load of the structure based on ABAQUS; introducing an initial geometric defect to obtain a load-displacement curve, a critical buckling load and a stress distribution cloud chart of the structure; obtaining an optimization model with the maximum buckling bearing capacity under stress constraint of the structure; realizing explicit expressions of a constraint and an objective function based on a response surface method, checking the precision of fitting and updating the model; and simplifying the optimization model into a standard quadratic programming model, and then solving the model by a sequential quadratic programming method to obtain an optimal result. The present invention provides a reliable stability analysis method for the single reed structure, thereby shortening design cycle of the novel space deployable hinge, improving work efficiency and reducing design costs.

Disclosed is a prediction method for monitoring performance of power plant instruments. The prediction method extracts a principal component of an instrument signal, obtains an optimized constant of a SVR model through a response surface methodology using data for optimization, and trains a model using training data. Therefore, compared to an existing Kernel regression method, accuracy for calculating a prediction value can be improved.

Disclosed is a method for testing a crystal by X-ray diffraction. The crystal comprises a single crystal substrate and at least one layer of lattice mismatch materials growing on the single crystal substrate. The method includes firstly, scanning a reciprocal space mapping of a sample, and calculating a motion speed ratio between a Omega-axial and a 2Theta-axial to be 1:n according to the reciprocal space mapping; and secondly, scanning the sample to be tested at the speed ratio of 1:n of the Omega-axial and the 2Theta-axial in a linking manner, and calculating interplanar spacing of the at least one layer of lattice mismatch materials according to an acquired scanning curve. By the method compared with the RSM (response surface methodology), lattice coefficient of the lattice mismatch materials can be quickly measured, speed can be increased by 20 times and precision in measurement is close to that in the RSM .

A method for reducing the weight of saloon car bodies based on the response surface method includes: a, improving the structure of the spare parts to select the optimum structure, b, carrying out code transformation to the test design variables, c, arranging test points with the isometiric design method to determine a test plan, d, setting up a response surface model based on the test result, e, validating the effectiveness of the response surface model, f, optimizing the spare parts of the body taking the quality of the spare parts as the target function and the energy absorption parameter as the restriction condition.

The invention provides a method for optimizing a PCB microstrip line structure on the basis of a response surface methodology and a genetic algorithm. The method comprises the steps that an electromagnetic simulation model of a PCB microstrip line is built on the basis of HFSS software; return loss and insertion loss of the microstrip line are obtained on the basis of the model; 29 tests are designed for computing simulation by taking the substrate thickness, the microstrip line width, the microstrip line thickness and the dielectric constant as design parameters and taking the return loss as a target value; the relationship, obtained in the tests under the 5-GHZ condition, between the return loss and the influence factors thereof is fit by adopting the response surface methodology; the obtained fit function is optimized by means of the globally optimal solution searching advantage of the genetic algorithm, and combined parameters with the minimal return loss are obtained. In addition, by means of HFSS simulation verification, the accuracy of an optimization result is proved, and the method has a guiding effect on optimization design of other interconnection structures.

An automated headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry for the determination of four N-nitrosoamines in groundwater samples is developed. Response surface methodology technique was employed to investigate the optimized extraction conditions of headspace solid-phase microextraction using CombiPAL autosampler. The method was applied to determine the N-nitrosamine concentrations in groundwater samples.

The invention discloses a high-rockfill-dam transient-rheological-parameter inversion method based on the response surface method.The method includes the steps that a rockfill-dam three-dimensional finite element model is built in combination with dam body material sections and construction grading conditions, the sensitivity of the transient parameters and the rheological parameters of rockfill of the material sections is analyzed, and the transient parameters with the high sensitivity and the rheological parameters with the high sensitivity are selected as to-be-inversed parameters jointly; a material static force model is a Duncan EB model, and a rheological model is a Nanjing-Hydraulic-Research-Institute five-parameter model; the implicit relationship between the finite-element-calculated settling volume and the calculation parameters is represented through a specific-form response surface function, undetermined coefficients of a response surface equation set are solved through several times of finite element calculation, and therefore the nonlinear mapping relationship between the settling volume and the calculation parameters is built.On the bases of the response surface equation, the objective function aims at obtaining the minimum root-mean-square error between the calculated settling volume and the practically-measured settling volume, the transient parameters and the rheological parameters are inversed with the genetic algorithm at the same time, and the obtained set of optimal calculation parameters are the inversion result.

The invention claims a response surface method for identifying the parameters of Burgers model for slope soil, comprising the following steps: determine the model parameters and the level thereof; determine the parameter combination and the test sequence of the numerical test; calculate the response equation; optimally identify the model parameters. Based on the combination of the laboratory test, the numerical simulation and the field monitoring, the response surface analysis method is adopted in the invention to determine the regression equation for the parameters of Burgers model and the slope surface displacement, and meanwhile the regression analysis is adopted to establish the optimal parameter combination.

The invention discloses an optimization method for improving random vibration stress and echo loss of chip package solder joints by unilaterally performing vibration analysis research or unilateral echo loss research. CSP solder joint models are established in ANSYS and HFSS software, the finite element analysis model and three-dimensional electromagnetic simulation analysis of the model are carried out, Response surface method is used to design the horizontal combination of multi-group solder joint morphology parameters and to model for simulation calculation, and the response surface methodis used to calculate the stress value, the relationship between the return loss and the shape parameters of CSP solder joints is fitted, The initial population generation, crossover, mutation and evolutionary inversion were performed on the fitting function respectively, and the two populations were evaluated and updated as a whole. The local catastrophe is performed on the population if the conditions were satisfied, and the random vibration stress value and echo loss value of CSP solder joints were obtained while the parameter level combination is reduced. This method can be used to guide the design of structural parameters which take into account the random vibration stress and return loss of CSP solder joints.

The invention discloses a dynamic property optimization design method for foundation major parts of a machine tool. The method includes the steps that a machine tool assembly is simplified according to the dynamics simulation analysis requirement, and the simplified assembly is imported into ANSYS / Workbench for mesh generation, material setting and boundary condition setting to complete modal analysis of the machine tool assembly; in harmonic response analysis, the maximum amplitude response values of the end of a spindle box of the machine tool assembly under the action of simple harmonic force in the X direction, the Y direction and the Z direction are obtained by simulating the actual working state of a tool; finally, experiment design of quality characteristic parameters of the foundation major parts is carried out with the parametric analysis technology, and a response surface model between the dynamic property response values of the machine tool and the quality characteristics of the foundation major parts is obtained through fitting. By analyzing the response surface model, the weak link of the foundation major parts in the dynamic property of the machine tool can be qualitatively found out, the tendency of influences of changes of the foundation major parts on the dynamic property of the machine tool can be quantitatively predicted, and the precision of machine tool design can be improved.

The invention discloses a method for optimizing BGA (Ball Grid Array) welding spot return loss. The method includes the steps: 1) establishing a BGA welding spot signal integrity analysis model; 2) acquiring return loss of a BGA welding spot; 3) determining an influence factor of the BGA welding spot signal integrity; 4) determining a parameter level value of the influence factor of the BGA welding spot signal integrity; 5) acquiring simulation experiment samples; 6) acquiring a functional relation between the influence factor and the return loss; 7) performing variance analysis; 8) determining the correctness of the functional relation; 9) generating an initial population; 10) acquiring a current evolution generation gen and an optimal fitness value; 11) performing interlace operation onthe population; 12) performing mutation operation on the population; 13) performing evolution reversion on the population; 14) selecting an optimal individual; and 15) performing re-determination after the population is updated. The method uses a response surface method and a genetic algorithm to optimize BGA welding spot return loss, has excellent robust Performance, and is simple in calculationprocess.

The invention provides a method for extracting alfalfa polysaccharide by use of complex enzyme (cellulase, papain and pectinase). The extracting temperature of the alfalfa polysaccharide is reduced, the extracting rate of the alfalfa polysaccharide is improved, and the method is suitable for popularization. The method comprises the following steps: determining the test range of factors influencing the extracting rate of the alfalfa polysaccharide through a single-factor test, determining the optimum proportion of the complex enzyme through an orthogonal test, then obtaining the relation between a response value and an influence factor by combing a central complex test with the response surface methodology (RSM), and computing the level of the influence factor when the maximum response value is obtained so as to determine the optimum extracting condition of extracting the alfalfa polysaccharide by complex enzyme, wherein the cellulase is 2.5%, the papain is 2.0%, pectinase is 3.0%, the extracting temperature is 52.7 DEG C, the extracting pH value is 3.87, the extracting solid-to-liquid ratio is 78.91, and the extracting time is 2.73 hours. The extracting rate of alfalfa polysaccharide is more than 5.0% under the condition provided by the invention.

The invention discloses a multisource monitoring time sequence data-based inversion method for mechanic parameters of a concrete dam. The method comprises the steps of collecting multisource monitoring time sequence data of a physical model of the concrete dam in an experimental process of a seismic station; by adopting a 3D scanning technology, building a three-dimensional finite element dynamic analysis model; by adopting a sensitivity analysis method, determining to-be-inverted parameters; performing evaluation on the to-be-inverted parameters by a Latin hypercube sampling method, generating a to-be-inverted parameter set, and performing dynamic calculation to obtain a comprehensive evaluation index K-RPD; by utilizing a response surface method, establishing an implicit function relationship between the to-be-inverted parameters and the comprehensive evaluation index K-RPD; and by utilizing a Monte-Carlo method, calculating an optimal inverted parameter set Qmax1, namely, an inverted result. By utilizing an advanced full-process full-time-sequence monitoring method, the problem of small monitoring data amount is solved; and by utilizing a mathematic analysis method, the comprehensive index is established, so that various full-process full-time-sequence monitoring data is fully utilized and the problem of single evaluation index is solved.

The invention discloses an optimization design method for an oil casing screwed-joint sealing structure. The optimization design method includes the following steps: 1), creating a parameterized geometric model of the special screwed-joint sealing structure; 2), creating a parameterized finite element model of the special screwed-joint sealing structure; 3), solving the finite element model, determining three optimization design elements, and creating an optimized mathematical model of the sealing structure; 4), performing design of experiments (DOE) on the optimized model, determining optimization solution settings, and solving the optimized model on experiment samples; 5), performing sensitivity analysis on design variables, and fitting a response surface model of sealing performance on experiment sample points; 6) selecting a proper optimization algorithm to perform iteration solution according to the response model; 7), modifying the sealing structure according to a solution result to acquire a structural optimization design result. The optimization design method has the advantages that a structural optimization design philosophy and a finite element analysis method are adopted, and accordingly, optimal design parameter combinations capable of meeting requirements of various working conditions can be achieved.

The invention discloses a method for analyzing the reliability of a construction error of a grid structure based on a buckling mode combination. According to the characteristic that the construction error of nodes influences the stress performance of the grid structure, random distribution of assembly deviations of the nodes is similarly fitted by adopting a random linear combination of a plurality of orders of buckling modes in front of the structure, and the advantages of a response surface methodology and the advantages of a monte carlo method are effectively fused. By adopting the method for analyzing the reliability of the construction error of the grid structure based on the buckling mode combination, a multi-order mode of the structure is acquired by analyzing the buckling of the structure, and the random distribution of the assembly deviations is similarly fitted according to the random linear combination of the buckling modes; a combination result is normalized to an allowance variation interval of the construction error of the nodes, so that the random variable scale of analysis for the reliability is greatly reduced; and the advantages of the response surface methodology and the advantages of the monte carlo method are effectively fused, so that the reliable index of the influence of the construction error on the stress performance of the structure can be efficiently and accurately calculated.

The invention discloses a structural reliability method based on dynamic weight response surface under mixed uncertainty. The invention is applied to the field of reliability technical field, and aimsat structural reliability problems under mixed variables. The method comprises the following steps of determining a fitted sample of a current iterative response surface; fitting and getting the response surface of the current iteration by weighted least squares; getting the reliability design point of the current response surface according to the hybrid variable decoupling method; stopping the iteration, when the value of the random variable part of the reliability design point obtained by two adjacent iterations satisfies the convergence criterion; calculating the failure probability of thestructure by Monte Carlo simulation according to the response surface obtained from the last iteration. The invention constructs the response surface, so that the limit state function in the standardnormal space is explicitly approximated in the form of a quadratic response surface, which facilitates subsequent reliability analysis. And a double weighting mechanism is introduced to effectively improve the accuracy and computational efficiency of the response surface method.

The invention relates to a preparation method of a low-value extraction recombinant minced hairtail product. The preparation method comprises the steps: mixing minced hairtail and a soybean protein isolate with a weight ratio of 1:4 in a chopper mixer, and extruding by adopting a homodromy twin-screw extruder, wherein the water content of a raw material is 30-50 percent, the rotating speed of screws is 80-120rpm, the temperature of the screws is 140-160 DEG C, and the optimal process condition is optimized by using a response surface method. Compared with that of a raw material, the in-vitro digestibility coefficient of the protein is increased by 10.25 percent. According to the preparation method, the low-value minced hairtail is recombined by adopting the homodromy twin-screw extruder, the advantages of high temperature, high pressure and high shearing force of an extrusion system are fully utilized, the degradation of macromolecules in a cylinder is promoted, the ordering transition of a protein array in the material is accelerated, the texturization and the specific retention of the material are improved; meanwhile, through passivating enzyme and damaging antinutritional factors, the in-vitro digestibility coefficient of the protein in the material is increased, and the nutritive value of the material is improved.

The invention relates to a compound enzyme-microwave extraction method for optimizing Nitraria polysaccharide by a response surface methodology. The method comprises the following steps: (1) carrying out sample preparation: preparing Nitraria fruit powder from fresh Nitraria fruits; then, carrying out reaction extraction according to different material / liquid ratios, different soaking times, different microwave powers and different extracting times, so as to obtain dried Nitraria polysaccharide extract powder corresponding to different microwave powers; (2) determining the content of polysaccharides in each extract by using a phenol-sulfuric acid method; (3) carrying out experimental design and statistical analysis: 1) carrying out single-factor test; and 2) carrying out response surface method optimization design: establishing a multivariate quadratic regression equation by selecting four factors, i.e., microwave power, extracting time, soaking time and material / liquid ratio, which have relatively remarkable influence on polysaccharide extracting effect, according to single-factor test results; and (4) analyzing and optimizing experimental results: carrying out drawing analysis according to the multivariate quadratic regression equation by using software Design Expert 8.0, so as to obtain a response surface of the regression equation and a contour map of the response surface. The method is simple in operation and high in extraction ratio.

The invention discloses a prediction method for fatigue reliability of a cable support in a subway tunnel. The method comprises: considering nondeterminacy of model parameters, using a response surface method to generate parameter samples; according to the parameter samples, establishing a finite element model, converting a track irregular spectrum to an irregular spatial waveform, used to adjust node coordinates of steel rail nodes in the model; the steel rail node being provided with a vertical pressed non-pulled unit, used to simulate wheel-rail contact; establishing a train-rail model, a tunnel-soil mass model, and a support-cable model and solving, to obtain stress time-history of the node on the root of the support, amplitude of the node being maximum; using a rain-flow counting method to calculate fatigue life; according to the parameter samples and a fatigue life value to fit the response surface and calculating a reliability index; accordingly, a series of fatigue life target values can be assigned, calculating the corresponding reliability index, so as to draw an invalid exceedance probability curve of the support.

The invention discloses a lightweight design method of a landing gear brake component based on a response surface model and a multi-island genetic algorithm. The lightweight design method comprises the following steps: 1, the ranges of mises stress and fatigue life of the brake component which satisfy the normal function requirements of the landing gear are given; 2, variable range of the brake component design variables is determined; 3, combining the design variables, mises stress and fatigue life, the constraint conditions are given and the objective function is established. 4, an optimal Latin hypercube test design method is adopted to select sample point; 5, comprehensive parameters of the brake component are calculated according to the sample point parameters, including the componentmass, the fatigue life and the maximum mises stress; 6, combining M group of sample points and M group of comprehensive paramete data of brake components, a fourth-order response surface model is established by adopting a complete search mode; 7, based on the established response surface model, multi-island genetic algorithm is used to optimize the lightweight structural design problem, and the optimal solution is selected as the final structural optimization parameters in the convergent solution.

The invention provides a method for optimizing extraction technology of aquilaria sinensis leaf tea polyphenol by utilizing a response surface process. The method comprises the following steps: 1) preparing a test liquid; 2) determining the content of tea polyphenol in the extraction liquid; 3) performing experiment design and statistics analysis: a) performing single-factor experiment; and b) optimizing the design through the response surface process, concretely, taking the single-factor experiment as the basis, selecting extraction time, liquid-material ratio, extraction temperature and ethanol concentration as response variables, taking the aquilaria sinensis leaf tea polyphenol content as the response value, and employing the response surface process to optimize the aquilaria sinensis leaf tea polyphenol extraction conditions; and 4) analyzing and optimizing the experiment results, concretely, performing calculation on the regression equation through a Design-Expert. 8.05 software, so as to obtain the optimum technological conditions for extracting aquilaria sinensis leaf tea polyphenol.

The invention discloses an assessment method for fuzzy reliability of an automobile passenger restraint system. The method is based on a response surface method, firstly, a probabilistic model is used for describing probabilistic parameters in the automobile passenger restraint system, meanwhile a secondary response surface approximation model of the automobile passenger restraint system is built, and through repeated iteration updates of the response surface model, a fuzzy reliability index of the model can be calculated efficiently and quickly. Compared with the design of an automobile passenger restraint system with deterministic parameters, the probabilistic model is used in the assessment method for describing the indeterminacy of the parameters, and fuzzy reliability analysis is carried out on the automobile passenger restraint system based on key design parameters and failure criterion fuzziness. By means of the method, the protection performance of the automobile passenger restraint system can be well assessed, and guidance and advises are provided for the design of the automobile passenger restraint system to some extent.

The invention relates to an extraction optimization method of Helianthus tuberosus L. straw chlorogenic acid by response surface methodology. The method includes the steps of: (1) preparing a sample solution by washing, drying and crushing Helianthus tuberosus L. straws, and adding them into ethanol solutions with different concentrations to conduct extraction, carrying out centrifugation and precipitation to obtain extracted solutions corresponding to different concentration ethanol solutions; and bringing the extracted solutions corresponding to the different concentration ethanol solutions to a same constant volume; (2) using HPLC (high-performance liquid chromatography) to determine the chlorogenic acid content of each extracted solution; (3) carrying out experimental design and statistic analysis: (i) single factor experiment; and (ii) optimization design by response surface methodology: according to the result of the single factor experiment, selecting the following 4 factors, i.e. extraction solvent ethanol concentration, extraction time, extraction temperature, material-liquid ratio that significantly influence the chlorogenic acid extraction effect to establish a multiple quadratic regression equation 2; and (4) analyzing the experimental result and performing optimization: using the Design Expert 8.0 software to carry out drawing analysis so as to obtain a response surface of the regression equation and its contour map. The method provided in the invention is simple to operate, and is easy to realize industrialization production.

The invention relates to an optimization method of culture conditions of alkaline pectinase gene engineering bacteria, comprising the following steps: (1) adopting a single-factor experiment to optimize the fermentation medium formation of the alkaline pectinase gene engineering bacteria to obtain a preliminarily optimized fermentation medium; (2) optimizing a target strain medium with a response surface methodology to obtain the target strain medium; and (3) optimizing the fermentation culture conditions to the target strain by a post-optimizing medium to obtain the optimization culture conditions. The invention gropes a set of optimal fermentation culture conditions to ensure that enzymatic activity produced by engineering bacteria fermentation reaches 758.7825U / ml which is improved by 50 times compared with the activity of alkaline pectinase produced by original wide strains and is improved by 3 times compared with the enzymatic activity of alkaline pectinase produced by LB fermentation medium fermentation gene engineering bacteria, so that the invention has an important meaning for improving the market competitiveness of industrial enzyme.

The invention discloses a prediction method of a dry gas huff and puff effect of a high-water-content compact condensation gas reservoir, and belongs to the technical field of oil and gas field development. The prediction method comprises the steps that influence factors of the recovery ratio of dry gas huff and puff of the high-water-content compact condensation gas reservoir are obtained, the value ranges of the influence factors are determined, and the influence factors comprise geologic parameters and injection-production parameters; according to the influence factors of the recovery ratioof dry gas huff and puff of the high-water-content compact condensation gas reservoir and the value ranges of the influence factors, a recovery ratio increment prediction model of dry gas huff and puff of the high-water-content compact condensation gas reservoir under interaction of the multiple influence factors is established by utilizing a response surface method; and according to the recoveryratio increment prediction model and the geologic parameters of a to-be-exploited gas reservoir, the recovery ratio increment extreme value, the optimal injection volume and the optimal gas injectiontime within the value ranges of the injection-production parameters are obtained. The prediction method is provided for the dry gas huff and puff effect of the high-water-content compact condensationgas reservoir, the injection-production parameters are accurately and quantificationally optimized, so that injected dry gas is utilized maximally.