40 results about "Response surface methodology" patented technology

A watershed pollution control measures optimization method employing response surface methodology coupled with a genetic algorithm, the method relating to the cross-disciplinary field of environmental engineering, environmental system simulation and prediction technology, and computer technology. The present invention solves the problem of low optimization efficiency in existing optimization methods. The invention comprises: by using known data, establishing a geographic database for an area; by using the geographic database, calculating a single load of each pollution source, and accordingly calculating the load reduction amount of each pollution source in a single control measure scenario; calculating the total nitrogen pollution load reduction rate and the total phosphorus pollution load reduction rate, and computing the total economic benefit in the single control measure scenario; setting the maximization of the economic benefit, total nitrogen load reduction rate, and total phosphorus load reduction rate as objectives, and establishing a regression function by adopting response surface methodology; and by adopting an NSGA-II genetic algorithm, performing multi-objective optimization on the regression function, and selecting an optimal management measure for a watershed to undergo pollution control. The present invention is suitable for optimizing pollution control measures for a watershed.

The invention relates to the technical field of heat dissipation of electronic devices, in particular to a multi-objective optimization method for a microchannel heat sink turbulent flow structure based on nanofluid. The multi-objective optimization method comprises the steps that integrated computational fluid mechanics simulation, a response surface method and an NSGA-II algorithm are matched; the system solves the problems that in the prior art, research on the synergistic effect of a nanofluid and a turbulent flow structure is insufficient, and multi-objective optimization efficiency is low, firstly, a three-dimensional numerical model is constructed based on ANSYS, and heat transfer and pressure drop characteristics under different parameters are simulated and quantified; secondly, establishing a mathematical model of an input parameter and an output target by adopting a response surface method, and revealing a multi-parameter coupling rule; and finally, performing multi-objective optimization on the synergistic effect by using an NSGA-II algorithm, obtaining a Pareto optimal solution set, and realizing the optimal balance of the heat dissipation performance and the voltage drop. By adopting the technical scheme, through combination of numerical simulation and experimental verification, the optimization efficiency is remarkably improved, and the optimization cost is reduced. And a solution with theoretical preciseness and engineering practicability is provided for thermal management of high-power electronic devices.

The invention discloses a system and a method for predicting reaction conditions of a menthane carboxamide cooling agent, and aims to optimize the reaction conditions, improve the experiment efficiency, reduce the production cost and ensure the stable product quality through an intelligent method. According to the system, the design experiment DoE and the response surface method RSM technology are combined, the relation between reaction conditions and products is systematically analyzed, multi-scale modeling is utilized, a molecular reaction mechanism and a macroscopic reactor model are combined, seamless connection from a laboratory to an industrial scale is achieved, and challenges in the amplification process are solved. By means of real-time data monitoring and feedback adjustment, the system can dynamically optimize the reaction process, controllability and stability of the production process are improved, the scientificity and intelligent level of reaction optimization are improved, and an efficient, controllable and environment-friendly solution is provided for large-scale production of the menthane carboxamide cooling agent.

The invention discloses an aluminum-based material rolling process optimization method based on a response surface method and machine learning, which comprises the following steps: collecting related data of an aluminum-based material rolling process, and establishing a rolling process database; determining key rolling process parameters influencing the performance of the aluminum-based material based on the database; a mathematical model used for describing the key rolling process parameters and the relation between the interaction of the key rolling process parameters and the aluminum-based material performance indexes is established, and prediction results of the aluminum-based material performance indexes under different key rolling process parameter combinations are calculated according to the mathematical model. Aluminum-based materials with performance indexes meeting preset requirements and key rolling process parameter combinations corresponding to the aluminum-based materials are predicted to serve as a preliminary optimization result data set; and constructing a back propagation artificial neural network model optimized by a genetic algorithm to predict aluminum-based material performance indexes corresponding to different key rolling process parameter combinations, and screening out an optimal key rolling process parameter combination and an aluminum-based material performance index corresponding to the optimal key rolling process parameter combination from the aluminum-based material performance indexes. According to the method, the quality of the aluminum-based material is remarkably improved through the proposed collaborative optimization strategy.

The invention relates to the technical field of metal plate stamping forming, and provides a new energy power battery shell deep drawing forming process parameter optimization method which comprises the steps that orthogonal test design is carried out based on a plurality of sets of parameters, and multiple times of shell deep drawing forming tests are carried out under different process parameters; the method comprises the following steps: analyzing a shell drawing forming test by adopting a response surface method, and establishing a maximum forming reduction rate mathematical model and a minimum forming reduction rate mathematical model based on test data; taking the established mathematical model as a target function, solving an optimal solution of the process parameters by adopting a particle swarm optimization algorithm, and adjusting the process parameters in real time by adopting a PID control algorithm; and combining the optimal solution of the process parameters with left and right double-shaft load monitoring to realize deviation verification analysis of multi-objective optimization numerical values of the process parameters. According to the method, dynamic adjustment of shell deep drawing forming process parameters is achieved, the stability and consistency of the machining process are ensured, and the quality of the formed shell is improved.

A method for optimizing the natural frequencies of a paddy field grader structure based on dimensional linkage and response surface methodology is disclosed. The method comprises the following steps: S01: Establishing a simplified 3D model of the paddy field grader structure; S02: Parametrically configuring the model; S03: Linking SolidWorks and Workbench to establish dimensional relationships and a set of dimensional parameters; S04: Performing modal analysis to obtain the total deformation and the first six natural frequencies of the grader structure, setting some output results as output parameters and adding them to the dimensional parameter set; S05: Performing sensitivity analysis on the dimensional parameter set to select input parameters with higher overall sensitivity values; S06: Performing multi-objective response surface optimization to obtain the optimal design parameters; S07: Reconstructing the model based on the optimal parameters and performing modal analysis to confirm the optimization effect. This invention can accurately and efficiently optimize structural parameters using response surface methodology to improve their natural frequencies and reduce resonance risk, belonging to the field of agricultural machinery structure optimization technology.

The invention relates to the technical field of automobile body-in-white thin plate welding process analysis, in particular to a body-in-white thin plate welding, positioning and layout method based on a response surface and a genetic algorithm, which comprises the following steps of: performing three-dimensional assembly modeling on body-in-white thin plates; carrying out rigid assembly deviation modeling by utilizing three-dimensional tolerance simulation analysis software; finite element pretreatment is carried out based on rigid modeling, and grid division is carried out by adopting quadrilateral shell unit grid fragments; a body-in-white thin plate positioning design parameter space and an optimization target are determined through flexible assembly deviation modeling; designing a test by adopting a response surface method, and analyzing and calculating all test results by utilizing a three-dimensional flexible assembly deviation simulation model; analyzing a response surface to confirm the advantages and disadvantages of a fitting effect; and carrying out positioning parameter optimization by using an improved genetic algorithm, and obtaining an optimal parameter combination of positioning coordinates on the basis of the established second-order response surface model by taking the change of the positioning coordinate values as a constraint condition and taking the minimum value of the assembly gap size deviation of the key measurement point as a target.

The invention relates to the technical field of flange laser cladding, in particular to a flange inner wall laser cladding process parameter optimization method which introduces a least square method model containing a time-varying weight coefficient on the basis of a traditional response surface method. A dynamic response model is constructed on the basis, and the process parameters are dynamically adjusted by considering the interaction influence of the parameters in the optimal process parameter combination and the change trend of the interaction influence of the parameters along with time while the optimal process parameter combination can be obtained; compared with a traditional response surface method, the method has the advantages that the interaction weight coefficient of each parameter in the model can be dynamically adjusted along with the time change, and the optimization accuracy of the laser cladding parameters of the flange is improved. And an efficient and reliable remanufacturing solution is provided for flange repairing and strengthening in the deep sea high-pressure and high-corrosion environment, and the method has important engineering application value.

The invention discloses a process method for optimizing total flavone and total phenolic acid extraction of gendarussa ventricosa based on a multi-index comprehensive scoring method in combination with a response surface method. A single factor experiment is carried out by taking the material-liquid ratio, the extraction temperature, the extraction time and the ethanol concentration as investigation factors, the total flavone content and the total phenolic acid content are taken as response values, the extraction process is optimized through a response surface design test, and the optimal extraction process of the total flavone of the gendarussa vulgaris is obtained: the material-liquid ratio is 1: 30, the extraction temperature is 60 DEG C, the extraction time is 45 minutes, the ethanol concentration is 70%, and the total flavone content is 2.487 + / -0.1332 mg / g; according to the optimal extraction process of the total phenolic acid, the material-liquid ratio is 1: 20, the extraction temperature is 55 DEG C, the extraction time is 40 min, the ethanol concentration is 70%, and the content of the obtained total phenolic acid is 10.625 + / -0.285 mg / g. The process method provided by the invention is stable, feasible, simple and easy to operate, good in repeatability and relatively high in extraction efficiency.

The invention discloses a preparation method of a carbon dot nano-enzyme based on response surface methodology optimization, the carbon dot nano-enzyme and application of the carbon dot nano-enzyme, and belongs to the technical field of carbon dot nano-enzyme preparation. The preparation method provided by the invention comprises the following steps: stirring and dissolving glucose, ferrous sulfate and concentrated sulfuric acid in water, then carrying out hydrothermal reaction, and after the reaction is finished, purifying to obtain carbon dot nano-enzyme; determining the fluorescence intensity of the carbon dot nano-enzyme; selecting the molar ratio of glucose to ferrous sulfate, the addition amount of concentrated sulfuric acid and the reaction time as influence factors, and taking the fluorescence intensity of the carbon dot nano-enzyme as an inspection value, and performing response surface method optimization to obtain a regression equation; and finally, optimal reaction conditions are obtained through software optimization. The synthesis efficiency is high, and the optimally synthesized carbon dot nano-enzyme has high fluorescence quantum yield and excellent peroxidase-like activity, can be applied to tetracycline detection as a colorimetric probe, and is high in detection sensitivity and accuracy.

The invention provides a chromium-polluted aquifer in-situ layered injection remediation method based on a response curved surface. The method comprises the following steps that a prediction model is constructed based on a response curved surface method, optimal agent parameters are predicted, pilot test verification is conducted based on the predicted optimal agent parameters, and the optimal pilot test agent injection amount is determined; establishing a relational expression between the agent injection concentration and the initial concentration of the underground water Cr (VI) based on the theoretical agent dosage, the adsorption capacity of the water-containing medium to the agent and the model prediction result; the optimal pilot plant test agent injection amount is the total injection amount of all the injection points, and according to the relational expression, the agent injection concentration of all the injection points in the chromium pollution site is determined. The method disclosed by the invention can be used for accurately regulating and controlling medicament parameters in actual engineering application, improving the remediation efficiency, shortening the construction period and saving the capital cost, fully remedying the chromium-polluted aquifer and reducing the risk of'yellowing 'of underground water in the later period, and is suitable for in-situ remediation construction application of the large-scale polluted aquifer.

The method, system, and equipment for screening and optimizing reservoir gas injection parameters based on response surface methodology include: determining the gas injection parameters affecting reservoir gas drive recovery and assigning initial weights; selecting basic spatial sample points using the central composite method; establishing a response surface function; constructing a response surface function model; validating the response surface model and verifying its accuracy; obtaining the gas injection parameter variable set; obtaining the distribution results of the gas injection parameter variable set converted into weight coefficients; and obtaining the quadratic response distribution of the weight coefficients through quadratic response surface analysis to obtain the discrimination criteria for gas drive in fractured-vuggy carbonate reservoirs. The reservoir gas injection parameter screening method provided by this invention uses response surface analysis combined with multiple linear regression to screen reservoir gas injection parameters. It uses graphical technology to display the functional relationships, providing intuitive graphs to clearly identify the optimization region, allowing researchers to observe and select the optimal conditions in experimental design.

The present invention relates to a method for detecting the compaction degree of soil based on the response surface method. First, indoor calibration tests are carried out on the in-situ tested soil to establish a second-order response surface model of the dielectric constant, conductivity, and maximum penetration resistance of the soil varying with the mass moisture content and dry density. Secondly, the correlation between the conductivity and dielectric constant of the soil is studied, a correction model of the soil conductivity is established and the conductivity correction value is calculated. Then, the measured dielectric constant, measured maximum penetration resistance, and conductivity correction value are substituted into the second-order response surface model to establish an objective function with the minimum root mean square error of the measured value and the calculated value. Finally, the particle swarm optimization algorithm is used for inversion to obtain the mass moisture content and dry density of the soil, and the compaction degree of the soil is calculated. The testing method of the present invention can quickly and accurately detect the compaction degree of the soil after field rolling, measure the mass moisture content and dry density of the soil, and is applicable to different engineering filled soils.

The invention discloses a selective laser melting forming optimization method based on a response surface method. The selective laser melting forming optimization method comprises the steps that S1, material parameters are determined through a calibration object printing experiment and simulation combined method; s2, finite element simulation software is utilized, a response surface experiment design method is adopted to establish a simulation experiment with the deformation amount and the equivalent stress as responses and with the laser power, the scanning speed and the powder laying thickness as factors, and a regression model among the laser power, the scanning speed, the powder laying thickness, the deformation amount and the equivalent stress is fitted through the response surface method; s3, obtaining an optimal experiment combination under various factor conditions according to the regression model, and determining optimal process parameters of laser power, scanning speed and powder laying thickness; and S4, performing actual printing by using the optimal process parameters, scanning a printing result, comparing the printing result with the model, and verifying the feasibility of the method. According to the method, the optimal forming process parameters of the material can be screened out more simply and more efficiently, and therefore the precision and quality of a 3D printing forming part are remarkably improved.

The invention belongs to the technical field of offshore converter station construction design, and provides an offshore structural pipe node lightweight design method and system based on a response surface method.The method comprises the steps that a target function is established with the minimum total weight of structural pipe nodes as the target and the condition that the ultimate strength stress ratio is not larger than a preset allowable value as the constraint condition; adopting Latin hypercube sampling to generate a series of test sample points; extracting a structure response value corresponding to each sample point; according to the structure response value, a response surface method is adopted for fitting to obtain a polynomial function; obtaining a lightweight design scheme according to the polynomial function; according to the method, a stress ratio response surface in a high-dimensional design space can be effectively fitted based on a sampled high-precision response surface model, collaborative optimization is carried out on a plurality of key design parameters of a complex pipe node on the premise of meeting safety specifications, constraint conditions of different diagonal bracings are met, structural redundancy can be accurately released, and the design efficiency is improved. And obvious weight reduction is realized on the basis of not sacrificing safety.

The invention relates to the field of traditional Chinese medicines, in particular to a hawthorn processing technology optimization method, which adopts a thermal analysis technology and a high performance liquid chromatography method to systematically analyze the influence of different processing technologies on the contents of main medicinal components of hawthorn. According to the method, an analytic hierarchy process and an evaluation method (AHP-CRITIC) are used for comprehensive weighting, processing parameters are optimized in combination with a response surface method, the quality change in the hawthorn processing process can be effectively analyzed through combination of a thermal analysis technology and an HPLC method, and scientific methodological reference is provided for optimization of the processing technology through combined application of the AHP-CRITIC method and the response surface method.

The present invention provides an acceleration curve prediction method, device, equipment and readable storage medium. The acceleration curve prediction method includes: obtaining a training data set, the training data set includes multiple sets of training data pairs, each set of training data pairs consists of hood structural parameters and acceleration curves corresponding to the hood structural parameters; respectively combining the acceleration value at each moment with the corresponding hood structural parameters; respectively inputting multiple sets of training data pairs at each moment into a machine model for training; respectively inputting new hood structural parameters into the trained machine model at each moment to obtain the predicted acceleration value at each moment; and constructing a predicted acceleration curve. Through the present invention, the prediction of a two-dimensional parameter such as an acceleration curve is realized, which solves the problem that the existing machine learning algorithm can only learn to predict a single value. Compared with the simulation collision test and response surface method in the prior art, the prediction efficiency and the prediction accuracy are improved.

The application discloses a kind of based on CFD simulation and response surface method's microplate fermentation process rapid development method, comprising: S1, establish microplate CFD model, obtain the quantitative relationship of fluid mechanics parameters and operating condition;S2, with fluid mechanics parameters as constraint, construct response surface model and carry out multi-objective optimization, obtain optimal process parameter;S3, adopt 3D printing to manufacture microplate prototype;S4, carry out high-throughput fermentation verification, correct model;S5, scale-up verification.The application is coupled with CFD simulation and response surface method, realizes accurate prediction and control to fluid mechanics condition while maintaining high-throughput advantage, solves the problem of long cycle, low optimization efficiency, scale-up difficulty in traditional process development.The application can shorten process development cycle by more than 50%, product concentration is higher than traditional method by 10-20%, scale-up success rate is increased to more than 80%, and is suitable for process rapid development of a variety of microbial fermentation system.

The invention relates to a method for optimizing the coercive force of a WC-Co hard alloy based on a response surface method. The method comprises the following steps: firstly, determining main factors influencing the coercive force of the WC-Co hard alloy in a sintering process and the value ranges of the factors; designing a response curved surface test scheme by adopting a center composite design method, and testing according to the scheme; establishing a response surface model according to test data, and analyzing a test result to obtain a binary multiple regression equation; performing variance analysis and significance analysis on the regression equation to obtain a variance analysis table and a four-in-one residual image, and judging whether the equation fits test data or not; establishing a contour map and a curved surface map according to the response surface model, and determining an optimal point position by combining the graphs; and establishing a response optimization graph, and determining an optimal sintering process condition. The influence of the highest sintering temperature and the heat preservation time at the temperature on the coercive force of the WC-Co hard alloy is comprehensively considered, the relation between the coercive force of the WC-Co hard alloy and sintering process parameters is obtained, and an optimization scheme is obtained.

The invention discloses an SLM forming part process parameter optimization method based on an evolutionary mixing and melting method, and belongs to the field of metal additive manufacturing. The method comprises the following steps: firstly, selecting key process parameters such as laser power, scanning speed, scanning spacing and powder laying thickness, performing numerical calculation on a deformation problem in an SLM forming process by taking deformation of an SLM forming part as a response index to obtain deformation data, and constructing a mathematical relationship model between the process parameters and the deformation through a response surface method, so as to obtain the deformation data of the SLM forming part; therefore, the deformation can be predicted; then, an evolutionary mixing and melting method is adopted for optimizing technological parameters, the evolutionary mixing and melting method is used for conducting evolutionary operation in predation and migration behaviors of the black wing plinostratums, candidate solutions are generated through two evolutionary strategies, evolution vectors are generated through weighted mixing, and mixed probability factors are introduced to generate test individuals; and whether a new solution is accepted or not is determined by comparing the fitness of the test individual and the fitness of the original solution, so that the technological parameters are optimized, and the deformation of the SLM forming part is reduced. The method can accurately predict and optimize the process parameters, reduce the deformation of the formed part, simplify the parameter adjustment process, reduce the production cost and improve the production efficiency.

The present invention discloses a bridge reliability prediction method based on the response surface methodology, comprising the following steps: determining the statistical characteristics and probability distribution of random variables under the design state of the bridge structure, generating input sample points using the uniform design method; establishing a structural analysis model based on the bridge design data and operational conditions, calculating the target variables corresponding to the input samples, obtaining output samples, and forming a training sample with the input samples; normalizing the sample points, and constructing a response surface model based on an intelligent algorithm; standardizing the random variables, converting the constrained optimization problem into an unconstrained optimization problem using a penalty function, and obtaining the optimal weights of the random variables using an optimization algorithm; and establishing a mathematical model for solving the structural reliability index by constructing the prediction results of the response surface model. The present invention has the following beneficial effects: high calculation accuracy, fast estimation speed, and compatibility with existing finite element analysis software. It is suitable for reliability problems involving high structural analysis costs and highly nonlinear implicit performance functions.

The invention discloses an ultrasonic bonding parameter dynamic regulation and control method based on finite element simulation, and the method comprises the steps: building a multi-physics coupling bonding process simulation model through finite element simulation analysis software in a finite element simulation pre-training stage, considering the key physical phenomena, such as ultrasonic vibration propagation, thermal coupling, etc. Parameterized simulation is carried out by combining orthogonal experimental design and a response surface method, and a quantitative mapping relation and a simulation database of process parameters-quality indexes are constructed. The real-time dynamic regulation and control system constructs a multi-closed-loop cooperative control system of real-time monitoring, simulation prediction and dynamic adjustment, collects data in real time, compares the data with a predicted value of a database, and automatically generates a parameter adjustment scheme when a target is deviated. The method can reduce resource consumption, improve the consistency, stability and reliability of bonding quality, reduce the reject ratio and improve the production efficiency, and can be popularized to other similar connection processes.

The invention relates to the technical field of computational modeling and numerical optimization, and particularly discloses a multi-parameter objective function comprehensive optimization method based on a response surface and multiple rounds of orthogonal tests, which comprises the following steps of: firstly, establishing a response surface relationship between parameters and an objective function by using a response surface method, solving constants in the response surface function through a sample library obtained by the orthogonal tests, and calculating a response surface relationship between the parameters and the objective function; solving a response surface function to obtain a preliminary optimal parameter combination; and then, performing round-by-round reduction and iterative optimization on a parameter value range by combining a multi-round orthogonal test method, and finally outputting an optimal parameter combination of an objective function by calculating an objective function value of each orthogonal scheme and performing comparison and screening. The method has the advantages of being high in optimization precision, high in calculation efficiency, wide in application range and high in expandability, the system or model performance can be remarkably improved, the test frequency and calculation cost are reduced, the optimization period is shortened, and the method is suitable for multi-parameter and multi-target optimization of physical models, engineering optimization and other scenes.

The present invention discloses a safety assessment method for a high-pile wharf based on the response surface methodology, comprising the following steps: S1. establishing a finite element model; S2. determining response surface parameters; S3. selecting the polynomial order; S4. designing a sample experiment; S5. selecting significant parameters; S6. performing regression fitting of the response surface; S7. optimizing parameters; and S8. performing calculations based on a revised three-dimensional finite element model as an assessment benchmark, and then comparing the calculated values ​​of the three-dimensional finite element model with a safety threshold to determine whether the high-pile wharf structure is safe. The present invention can more efficiently and accurately assess the structural safety of a high-pile wharf.

The invention aims to solve the problems of poor utilization rate of water resources and great influence of equipment parameters and operation conditions in the operation of the sprinkling machine. According to the research, spray irrigation intensity and uniformity are taken as key evaluation indexes, the spray irrigation intensity determines soil infiltration and runoff risks, the uniformity affects space-time consistency of crop moisture acquisition, and four influence factors including spray nozzle spacing, spray nozzle height, spray nozzle pressure and running speed are selected; the optimal hydraulic performance interval range is selected on the basis of a single-factor test result, a mathematical model under the multi-factor coupling effect is established through a response surface method, the influence rule of the mathematical model on the hydraulic performance is explored, multi-target optimization analysis is carried out, the optimal parameter combination of structural parameters of the sprinkling machine is obtained, and the hydraulic performance of the sprinkling machine is improved to the maximum extent. Researches prove that the response surface method can effectively analyze a multi-parameter coupling mechanism, an optimal sprinkler structure combination parameter is obtained, a theoretical basis is provided for sprinkler design and field operation, and the method has engineering popularization value.

This invention discloses a method and system for optimizing the proportion of tailings cementitious materials based on response surface methodology, relating to the field of tailings recycling technology. The method includes: using lead-zinc tailings content, fly ash content, sand-cement ratio, and water-cement ratio as process parameters, determining multiple cementitious material formulations based on response surface methodology; preparing physical cementitious material test blocks according to these formulations; conducting compressive strength tests to obtain the compressive strength results; establishing a compressive strength prediction model based on the results using regression analysis; and determining a target combination of process parameters based on the compressive strength prediction model, with a target compressive strength or target cost-effectiveness ratio as the objective. The target combination of process parameters is the proportion of lead-zinc tailings content, fly ash content, sand-cement ratio, and water-cement ratio. The cementitious material is then produced using this target combination of process parameters. This invention systematically optimizes the proportion of tailings cementitious materials through response surface methodology, establishing a compressive strength prediction model to achieve controllable performance prediction, providing a scientific solution for tailings resource utilization.

The invention discloses a method for optimizing infrared spectrum detection parameters of ginseng leaves based on a response surface method. A multi-level system with a signal-to-noise ratio, a peak height, a half-peak width and a peak area as evaluation indexes is constructed by taking scanning times, resolution and a ratio of a sample to KBr as variables. According to the method, a multi-index weight system is constructed through an analytic hierarchy process (AHP) for the first time, the weight values are as follows: the signal-to-noise ratio is 24.735%, the peak height is 14.022%, the half-peak width is 8.214% and the peak area is 53.029%, multi-factor collaborative optimization is converted into a mathematical problem based on quantitative scoring, and detection parameters are iteratively optimized by taking comprehensive scoring as an optimization target and combining a response surface method, so that the comprehensive performance of the detection parameters is improved. The optimal parameters of infrared spectrum detection of the ginseng leaves are determined as follows: the resolution is 4cm <-1 >, the scanning times are 32, and the mass ratio of the sample to KBr (mg) is 1: 100. According to the method, the problem of multi-factor collaborative optimization is solved by quantifying the index weight, the accuracy and sensitivity of spectrum detection are remarkably improved, and an efficient and accurate parameter optimization scheme is provided for infrared detection of traditional Chinese medicinal materials.

This invention belongs to the field of oil and gas reservoir development technology, and relates to a numerical simulation and parameter optimization method for composite gas-driven reservoirs based on response surface methodology, electronic equipment, and storage medium. The numerical simulation and parameter optimization method for composite gas-driven reservoirs includes the following steps: Step S1: Selecting gas injection parameters; Step S2: Determining the range and experimental point values ​​of the gas injection parameters; Step S3: Establishing a predictive model of the relationship between the gas injection parameters and the cumulative oil increase as the dependent variable; Step S4: Fitting and analyzing variance of the data obtained from the predictive model to determine the response surface model and the optimal parameter combination; Step S5: Response surface analysis. This invention establishes an accurate response surface model within a limited number of experiments, enabling the analysis and optimization of the impact of various operating parameters on reservoir recovery.

The application discloses a lead styphnate compound process optimization method based on a response surface method and an artificial neural network, belongs to the field of primers and pyrotechnics, and solves the problem that in the existing lead styphnate production line, compound process parameters are adjusted depending on artificial experience, leading to great product purity fluctuation, wide particle size distribution, poor flowability and insufficient batch consistency. The method comprises the following steps: determining key compound process parameters influencing the performance of lead styphnate based on collected lead styphnate compound process related data; and establishing a mathematical model for describing the relationship between the key compound process parameters, the interaction thereof and the performance index of lead styphnate. The method forms a stable and reliable performance influence rule by optimizing the lead styphnate compound process parameters, improves production efficiency, and solves the problem that the performance control mainly relies on artificial experience setting in the past.

This application discloses a method for calculating and optimizing the magnetic field of high-current lead wires based on the response surface methodology, comprising: constructing a parameterized three-dimensional nonlinear electromagnetic-thermal bidirectional coupled finite element model; selecting representative sample points in the design space using the optimal Latin hypercube sampling method, training a surrogate model based on the sample points and dynamically adding points, and outputting a set of representative sample points; performing finite element calculations on each output representative sample point, extracting the performance indicators corresponding to each sample point, and then constructing a Kriging gradient-enhanced hybrid response surface model; establishing an optimization objective function to guide the optimization direction, and then using a multi-objective optimization algorithm to quickly optimize the high-precision hybrid response surface model, generating a Pareto optimal solution set; selecting the optimal design scheme from the Pareto optimal solution set based on the entropy weight-TOPSIS dynamic decision method and performing double verification, and outputting optimization parameters and a performance report after successful verification. This application achieves synergistic optimization of performance, cost, and reliability.