Mobile Augmented Reality (MAR) integrates computer-generated virtual objects with
physical environments for mobile devices. MAR systems enable users to interact with MAR …

We present an algorithm to learn the relevant latent variables of a large-scale discretized
physical system and predict its time evolution using thermodynamically-consistent deep …

Digital twins can be defined as digital representations of physical entities that employ real‐
time data to enable understanding of the operating conditions of these entities. Here we …

Modular building is becoming a common sight due to government policies promoting greater
automation and productivity. When moving towards modularity, indoor comfort within …

Computational fluid dynamics (CFD) simulations can provide meaningful technical content
in engineering education, broad engineering and business. However, computationally …

Generative AI models have made significant progress in automating the creation of 3D
shapes, which has the potential to transform car design. In engineering design and …

In this paper, a novel self-learning digital twin strategy is developed for fluid sloshing
phenomena. This class of problems is of utmost importance for robotic manipulation of fluids …

We present a method to increase the resolution of measurements of a physical system and
subsequently predict its time evolution using thermodynamics-aware neural networks. Our …

Generative artificial intelligence (AI) models have made significant progress in automating
the creation of 3D shapes, which has the potential to transform car design. In engineering …

We present a real‐time method for computing the mechanical interaction between real and
virtual objects in an augmented reality environment. Using model order reduction methods …