Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …

The application of artificial intelligence in everyday life is becoming all-pervasive and
unavoidable. Within that vast field, a special place belongs to biomimetic/bio-inspired …

For complex systems involving multiple operating conditions and multiple failure modes, its
reliability analysis usually presents the cascade failure correlation between multiple levels …

The biopharmaceutical industry is rapidly advancing, driven by the need for cutting‐edge
technologies to meet the growing demand for life‐saving treatments. In this context, Model …

Due to the limited computational power of edge devices in distributed manufacturing
systems, the challenge of meeting real-time computing requirements for industrial big data …

A multi-objective optimization method utilizing genetic algorithms is developed to optimize
wind farm layout design with the dual objectives of enhancing the production of wind power …

The optimization of aircraft is a typical multidisciplinary and multi-objective problem. To solve
this problem, the difficulty lies not only in the high cost of discipline performance evaluation …

In the context of traditional aerodynamic shape optimization design methods, the necessity
to re-execute the complete optimization process when the initial shape changes poses …

A method using deep reinforcement learning (DRL) to non-iteratively generate an optimal
mesh for an arbitrary blade passage is developed. Despite automation in mesh generation …

Optimizing conductor casing jetting installation in offshore oil and gas exploration is
essential for underwater wellhead reliability. Traditional models often struggle with the …