2results about How to "Meet the parameter requirements" patented technology

The application relates to a modeling method and device for a combined scattering field of a rough surface in a terahertz frequency band. The method comprises the following steps: performing normalization processing on the normal RCS of a single hemisphere, performing fitting characterization on the result, then correcting an approximate formula of the scattering field of the hemisphere by using the normalized RCS, solving the scattering field of a larger radius hemisphere, constructing a phase factor of the scattering field of the hemisphere at different positions by using the relative position relationship of the hemisphere, deducing a scattering field expression of a hemisphere array based on a vector superposition principle, determining the energy ratio of non-coherent scattering field and coherent scattering field according to the ratio of the area of the planar element covered by the hemisphere to the area of the planar element not covered by the hemisphere, performing vector superposition on the scattering field of the hemisphere array and the scattering field of a smooth flat plate based on the superposition idea of non-coherent and coherent scattering, and solving the scattering field of the hemisphere-flat plate combination after the normal RCS of the hemisphere-flat plate combination is corrected. The method can improve the modeling efficiency of the rough surface in the terahertz frequency band.

This application provides a method, apparatus, device, and storage medium for reverse design of material structures, relating to the field of materials design. A three-dimensional feature vector matrix of the sample material is constructed; the three-dimensional feature vectors in the matrix are used to characterize the three-dimensional microstructure features of the sample material. Macroscopic performance parameters of the sample material are extracted and used as model condition information. The three-dimensional feature vectors and model condition information are used to form training data pairs. The conditional diffusion model is iteratively trained using the training data pairs until the training termination condition is met, resulting in the target conditional diffusion model. The target macroscopic performance parameters are input into the target conditional diffusion model to obtain the target three-dimensional microstructure that satisfies the target macroscopic performance parameter conditions. This method enables the reverse design of the three-dimensional microstructure of materials based on required performance, improving material development efficiency and reducing development costs; moreover, the designed structure can more accurately meet the required performance requirements and better fit the actual process.