22 results about "Response surface methodology" patented technology

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 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.

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 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 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 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 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 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 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.

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.

The invention relates to the technical field of electronic component parameter optimization, in particular to an electronic component parameter optimization method and related equipment, and the method comprises the steps: building a geometric model of a printed board electronic component; determining a design factor and a response target based on the established printed board electronic component geometric model, and performing a thermal simulation test through response surface method design to obtain a plurality of thermal simulation electronic component parameters; fitting parameters of a plurality of thermal simulation electronic components to obtain a multi-target mathematical model; solving and obtaining a Pareto optimal solution set through a non-dominated sorting genetic algorithm based on a multi-target mathematical model; and on the basis of the Pareto optimal solution set, solving the optimal parameters of the electronic component through a superior and inferior solution distance method. According to the method, parameter analysis of the electronic component is carried out in a mode of fusing numerical simulation calculation and theoretical analysis, and the parameters of the electronic component can be analyzed and evaluated more economically, quickly and effectively.

The application provides a process parameter optimization method, device and program product. The method comprises the following steps: constructing a yield prediction model according to a pre-acquired experimental data set; performing an explainability analysis on the yield prediction model to obtain key process parameters; establishing a kinetic model and a computational fluid dynamics model according to kinetic parameters of microbial growth, and coupling the kinetic model to the computational fluid dynamics model; generating a plurality of process parameter combinations according to the key process parameters by using a response surface method; performing numerical simulation on the plurality of process parameter combinations by using the computational fluid dynamics model to obtain a plurality of corresponding methane yields; and determining an optimal process parameter combination according to the plurality of process parameter combinations and the plurality of corresponding methane yields. The scientificity and efficiency of process parameter optimization can be improved, a reliable basis can be provided for industrial scaling of a biological methanation trickle bed, and thus the conversion efficiency of the trickle bed can be improved and the methane yield can be improved.

The invention discloses a radix dipsaci wine processing technology optimized by a response surface method. According to the method, empowerment analysis is carried out on an experimental result in combination with an entropy weight method, key parameters in the teasel root wine processing process are optimized by applying a response surface method, and the optimal process comprises the following steps: weighing teasel root decoction pieces, moistening the teasel root decoction pieces for 10.5 h with 24% semi-dry yellow wine, frying and roasting the teasel root decoction pieces in a pot at 96 DEG C for 6 min, taking out the teasel root decoction pieces, and cooling the teasel root decoction pieces for later use. The wine preparation process is stable and convenient, and the prepared radix dipsaci wine roasted product is high in index component content.

The present application relates to a kind of vertical axis tidal current energy turbine multi-parameter coupling experiment and intelligent model collaborative optimization method, the method includes: based on orthogonal experimental design and response surface method to construct the multi-level interaction working condition of blade key geometric parameters, obtain power and thrust coefficient performance curve, introduce global optimization of genetic algorithm and obtain optimal geometric configuration;Using variable pitch mechanism, determine the optimal variable pitch strategy considering power improvement and load fluctuation suppression;Introduce turbulence intensity correction coefficient, represent the performance degradation law of turbine under complex inflow, construct robust prediction model;Phase-locked PIV flow field measurement is executed under different working conditions, establish the quantitative correlation model of flow field characteristics and instantaneous load fluctuation, and feedback optimal parameter combination back to experimental design.Relative to the prior art, the present application has disclosed the multi-parameter nonlinear coupling mechanism of turbine energy trapping efficiency and operating stability, provides physical basis for its optimization design and the like advantages.

This invention discloses a process for optimizing the extraction of total flavonoids from Houttuynia cordata stems and leaves based on response surface methodology, relating to the field of natural product extraction technology. The method includes the following steps: Step 1, obtaining dried and pulverized Houttuynia cordata stem and leaf powder; Step 2, extracting total flavonoids from the powder using ultrasound, selecting ethanol concentration, extraction temperature, extraction time, and liquid-to-solid ratio as single-factor experiments, and employing response surface methodology with total flavonoid content as the response value to establish a second-order polynomial regression model to predict the optimal extraction conditions; Step 3, determining the optimized extraction parameter combination based on the model; Step 4, performing the extraction operation according to the optimized extraction parameter combination. This invention utilizes response surface methodology to optimize the extraction process of total flavonoids from Houttuynia cordata stems and leaves, determining a process that can effectively extract flavonoids from Houttuynia cordata stems and leaves, providing a theoretical basis for the research and utilization of flavonoids from Houttuynia cordata stems and leaves.

To address the limitations of traditional orthogonal experimental methods, which rely on experience and have limited parameter search capabilities, and response surface methodology, which is heavily reliant on the number of finite element simulation samples and has high computational costs, in optimizing the structural parameters of a six-dimensional force sensor elastomer, this invention proposes a method for optimizing the structural parameters of a six-dimensional force sensor elastomer based on a physical information neural network. The technical approach involves: taking the six-dimensional force sensor elastomer structure as the research object, selecting the length of the floating beam, the length of the strain beam, the width of the floating beam, the width of the strain beam, and the beam thickness as design variables; constructing multiple combinations of structural dimensions through orthogonal experiments, and obtaining the strain response data corresponding to each dimension combination using finite element analysis; establishing an elastomer mechanical model, and introducing the constitutive relations, governing equations, and boundary conditions of the mechanical model as physical constraints into the neural network training process; simultaneously using finite element strain data to supervise and correct the network, thereby constructing a high-precision mapping model between structural parameters and strain response; and further combining this mapping model with a multi-objective genetic algorithm (NSGA-III) to optimize the search for the elastomer structural parameters. This invention reduces the requirement for finite element simulation samples while achieving high-precision prediction of the mechanical response of the elastomer structure, significantly improving the efficiency of structural parameter optimization.