A novel method of synergistic multi-scale neural operator architecture for accurate aerothermodynamic prediction of thermal protection systems at high speeds

Multistage Enhanced Intelligent Aerodynamic Design Method for Hypersonic Forebody/Inlet Integration

The aerodynamic design of hypersonic forebody/inlet integration systems represents a challenging multiobjective optimization problem characterized by high-dimensionality, strong coupling, and expensive evaluations. To move beyond conventional empirical approaches, this paper introduces a knowledge-driven intelligent de...

Challenges and AI-powered strategies for multi-scale superquadric DEM-CFD modeling of non-spherical particles

Toward a Foundation-Model Paradigm for Aerodynamic Prediction in Three-Dimensional Design

Accurate machine-learning models for aerodynamic prediction are essential for accelerating shape optimization yet remain challenging to develop for complex three-dimensional configurations due to the high cost of generating training data. This work introduces a methodology for efficiently constructing accurate surrogat...

Topology Optimization of Brake Disc Inner Carrier and Development of a Parametric Predictive Model Using Machine Learning

Reducing unsprung mass in high-performance braking systems is critical for vehicle dynamics, but applying topology optimization (TO) to conventional solid discs under combined thermo-mechanical loading often causes “thermal entrapment” and structural failure. This study addresses this limitation by proposing a floating...

Periodic Neural Mapping for Unsteady Rotor-Blade Pressure and Aeroelastic Load Prediction

Accurate prediction of unsteady aerodynamic loads remains a major challenge in turbomachinery design. High-fidelity Computational Fluid Dynamics (CFD) simulations are expensive, while aeroelastic Quantities of Interest (QoI) depend sensitively on the temporal evolution of the pressure field. This work introduces period...

Deposition and Aero-Thermal Synergetic Design of Internal Swirl Cooling for a Turbine Blade Leading Edge: GAN-Based Optimization

The leading edge of turbine blades is subjected to extreme thermal loads, exaggerated by continuously increasing turbine inlet temperatures. This challenge has motivated the development of increasingly sophisticated internal cooling architectures. However, such intricate and confined geometries exacerbate particulate...