PLA Army Engineering University

Physics-Guided Residual Learning for Full-Angular-Domain Scattering Prediction of Coding Metasurfaces

Coding metasurfaces provide an effective approach for manipulating electromagnetic scattering through discrete coding states. However, obtaining angular-domain scattering responses for a large number of coding configurations remains computationally expensive with full-wave electr...

Modeling and Simulation of Steady-State Steering Characteristics for Eight-Tracked Vehicles

Eight-track vehicles feature large grounding areas, low ground contact pressure, and high load-bearing capacity, and are widely adopted for heavy-duty engineering transportation and large special-purpose operation platforms. Accurate characterization of their steady-state steerin...

Simulation Study on Ground Shock Convergence Effect of Multi-Point Explosions in Geomaterials for Underground Engineering

Underground simultaneous multi-point explosions are an efficient attack method against protective structures and critical infrastructure. The superposition and focusing of ground shock waves produce a convergence effect, which significantly increases peak pressure within a specif...

Blast-induced damage and residual performance assessment of steel box arch ribs under out-of-plane close-in explosions

Steel box arch ribs, as critical load-bearing components of arch bridges, may be subjected to explosion threats such as drone attacks during service. To evaluate the blast resistance and post-blast residual bearing capacity of steel box arch ribs under out-of-plane close-in explo...

CCL-CM: cognitive-concept learning and conflict monitoring integration

Explainable models based on concept learning offer relatively intuitive explanations for decisions and hold considerable theoretical appeal. In practice, particularly in classification tasks, they often face challenges related to accuracy and generalization. Drawing inspiration f...

An Intelligent Bearing Fault Diagnosis Model with Physics-Information Fusion: Design and Interpretability Mechanism Research

To address the issue of limited interpretability in current deep learning-based bearing fault diagnosis methods, this study proposes a convolutional neural network model incorporating spectral physical constraints. The model integrates data-driven learning with physical constrain...

Maritime ship target detection based on visible and infrared modal image fusion

Abstract The deep learning based maritime ship target detection is a key technology in fields such as ship navigation, water surface security, and military early warning. In view of the inherent limitations of maritime vessel object detection in single modality, a novel YOLO for...