4 results about "Hybrid mesh" patented technology

This invention relates to the field of submersible electric pump (FET) fault diagnosis technology, and particularly to a method and system for FET fault diagnosis based on CFD and deep learning. The method includes constructing a full-channel 3D model, simulating FET faults by modifying key geometric feature parameters, and using a hybrid mesh strategy to divide the mesh; extracting time-domain and frequency-domain features from the simulation data, forming feature vectors from these features, and constructing multi-dimensional labeled simulation data using these feature vectors and multi-dimensional label vectors; constructing a multi-channel deep neural network, training the multi-channel deep neural network using the multi-dimensional labeled simulation data; and deploying the trained multi-channel deep neural network to a well site edge computing gateway to diagnose FET sensor data. This invention utilizes CFD to generate high-quality data to drive deep learning model training, achieving rapid and accurate collaborative diagnosis of multiple faults in FETs.

The application belongs to the field of aerospace and fluid mechanics, and discloses an aircraft internal and external flow field structure grid division method based on a non-matching interface, which comprises the following steps: decomposing the aircraft shape into two topological subdomains of an external flow field, an inlet duct and an internal flow field of a tail nozzle, and connecting each subdomain through a pair of completely coinciding interfaces; wherein the internal flow field of the inlet duct and the tail nozzle adopts an O-type topological structured grid, the external flow field adopts a C-type topological structured grid, and the nodes of the O-type topological structured grid and the C-type topological structured grid can slide on the interface. The problems that the adaptability of the non-structured grid is poor in the near-wall boundary layer region, the calculation amount is large, and the mixed grid is difficult to maintain the overall field conservation and high precision in the current numerical simulation of the internal and external flow coupling of the complex aircraft shape are solved.

This invention relates to the field of geophysical exploration technology and discloses a three-dimensional polarizability inversion method based on cross-gradient constraints. The method includes the following steps: acquiring apparent resistivity observation data d_obsr and equivalent apparent resistivity observation data d_obsη; performing hybrid mesh partitioning on the computational domain to generate a hybrid mesh model containing triangular prism elements, tetrahedral elements, and pyramidal elements; and performing three-dimensional resistivity forward modeling based on the hybrid mesh model to obtain the total field potential. This three-dimensional polarizability inversion method based on cross-gradient constraints, by employing a hybrid mesh (combination of triangular prism, tetrahedral, and pyramidal elements) partitioning technique, can accurately fit undulating surfaces, fundamentally eliminating the terrain influence error caused by mesh simplification. Measured data show that the forward modeling response error at steep terrain measurement points can be reduced from 5.1% to 1.5% using traditional methods, effectively suppressing false anomalies and making the anomaly boundary more clearly delineated.

This invention provides a method for aerodynamic optimization design of wind tunnel profiles, belonging to the field of wind tunnel profile technology. This invention identifies high-gradient feature points by extracting the curvature distribution of profile features, generates a hybrid mesh using a graph-driven adaptive topology reconstruction algorithm, performs flow field calculations based on the hybrid RANS-LES turbulence simulation method, solves the control equations using a high-precision shock capture format coupled with a WENO limiter, and performs adaptive mesh refinement. It adjusts the coordinates of profile control points using a topological potential-based asymptotic optimization algorithm, and determines whether to output the optimization results or return to iterate again by judging whether the aerodynamic performance evaluation parameters meet the convergence criteria. This solves the technical problem of low optimization efficiency and difficulty in converging to the optimal solution caused by the disconnect between mesh generation, flow field calculation, and profile adjustment in the aerodynamic optimization process of wind tunnel profiles.