5 results about "Roughness factor" patented technology

The invention provides a method for analyzing the wetting behavior of a liquid drop on a rough solid surface under the action of an electric field, and the method comprises the following steps: S1, building an initial simulation system and a simulation model based on a research and information collection result; s2, configuring operation parameters of the simulation model, and executing simulation calculation; s3, in the molecular dynamics simulation process, applying electric fields with different intensities, and monitoring the state change of the simulation system until the simulation system reaches dynamic balance; and S4, exporting the calculation data in the dynamic balance state, and carrying out visualization processing and data analysis on the calculation data to summarize the internal law of the calculation data. Influences of electric field intensity and roughness factors on complex electrowetting are described through a contact angle and some interface characteristics, and an electrowetting expansion mechanism of micro-nano liquid drops on a rough wall surface is explained from a microscopic perspective.

In order to explore the material removal mechanism of aluminum nitride ceramic in the friction chemical polishing process, molecular dynamics under a reaction force field is used, the roughness of a workpiece and a grinding disc is used as an important consideration factor during simulation, and the aluminum nitride ceramic micro material removal process analysis method considering the roughness effect is provided. The method comprises the following steps: firstly, constructing a molecular dynamics simulation model of an aluminum nitride ceramic matrix and an aluminum oxide ceramic matrix with different rough peak surfaces, and simulating a scratching process between the aluminum oxide ceramic matrix and the aluminum nitride ceramic matrix in a large-scale atom / molecule parallel simulator LAMMPS; then, the simulated track is observed and analyzed in visual software OVITO, and the influence mechanism of different roughness factors on the material removal process of scratching the aluminum nitride ceramic substrate by the aluminum oxide ceramic substrate in the friction chemical polishing process, including the number of bonds generated on the surface of the aluminum nitride ceramic under different roughness factors, the number of the bonds generated on the surface of the aluminum nitride ceramic under different roughness factors and the number of the bonds generated on the surface of the aluminum nitride ceramic under different roughness factors, is determined. The temperature change and the stress change in the scratching process are avoided.

The invention relates to the technical field of automatic control, in particular to a process monitoring method and system for glass plate processing. The method comprises the steps that a grinding disc is divided into a plurality of areas, and temperature, linear speed and pressure data of each area at each moment are collected; constructing a temperature prediction function; acquiring a plurality of groups of initial temperature rise coefficients of each region; based on the roughness factor of each region at each moment and the plurality of groups of initial temperature rise coefficients, constructing a temperature rise coefficient attenuation function, and obtaining each group of temperature rise coefficients of each region at each moment; performing weighted summation on each group of temperature rise coefficients according to the weight of each group of temperature rise coefficients of each region at each moment to obtain a final group of temperature rise coefficients; substituting the final group temperature rise coefficient into a temperature prediction function, and predicting the temperature at the next moment; the linear speed and the pressure of the area are independently adjusted according to the predicted temperature, accurate temperature control is achieved, and accurate temperature control over all the areas is achieved.

The invention provides a roughness factor joint calibration method and device, electronic equipment and a storage medium, and the method comprises the steps: constructing a hydrodynamic model, obtaining a multi-session actual measurement flow sequence of each section, recognizing a critical quantile position of each session in a flow quantile threshold curve from a smooth section to an ascending section, and determining a roughness factor value of each session; determining the optimal low-flow quantile with the highest synchronism at the critical quantile position of each section; constructing a low-flow constraint that the simulated total flow below the optimal low-flow quantile is not lower than the actually measured total flow; determining the comprehensive weight of each section according to the management function importance of each section and the actually measured flow data quality, and constructing a target function in combination with the simulation precision of each section under multiple sessions; and through an optimization algorithm, searching an optimal roughness factor parameter combination enabling the objective function to be minimum on the premise of meeting low flow constraints, and outputting the optimal roughness factor parameter combination as a calibration result. By means of the method, the problems that the simulation precision is low in the low-flow time period, and the key section priority cannot be reflected are solved.

The present application relates to the technical field of automation control, and especially relates to a process monitoring method and system for glass plate processing. The method comprises the following steps: dividing a grinding disc into several regions, collecting temperature, linear velocity and pressure data of each region at each time; constructing a temperature prediction function; obtaining several groups of initial temperature rise coefficients of each region; constructing a temperature rise coefficient decay function based on the roughness factor of each region at each time and the several groups of initial temperature rise coefficients, and obtaining each group of temperature rise coefficients of each region at each time; performing weighted summation on each group of temperature rise coefficients of each region at each time according to the weight of each group of temperature rise coefficients, to obtain a final group of temperature rise coefficients; substituting the final group of temperature rise coefficients into the temperature prediction function to predict the temperature at the next time; and independently adjusting the linear velocity and pressure of the region according to the predicted temperature to realize accurate temperature control. The present application realizes accurate temperature control of each region.