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

In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …

Digital twin can be defined as a virtual representation of a physical asset enabled through
data and simulators for real-time prediction, optimization, monitoring, controlling, and …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

At the time of designing structures up to date, the density and magnitude of the load have
increased, and the requirements for regulation have also become more stringent. To ensure …

The evaluation of aerospace designs is synonymous with the use of long running and
computationally intensive simulations. This fuels the desire to harness the efficiency of …

The idea of using a simpler surrogate to represent a complex phenomenon has gained
increasing popularity over past three decades. Due to their ability to exploit the black-box …

Over the past two decades percolation theory has been used to explain and model a wide
variety of phenomena that are of industrial and scientific importance. Examples include …

Abstract We present a Physics-Informed Neural Network (PINN) to simulate the
thermochemical evolution of a composite material on a tool undergoing cure in an …

Deep reinforcement learning (DRL) has been applied to a variety of problems during the
past decade and has provided effective control strategies in high-dimensional and non …