Exploring potential energy surfaces using reinforcement machine learning
Reinforcement machine learning is implemented to survey a series of model potential
energy surfaces and ultimately identify the global minima point. Through sophisticated …
energy surfaces and ultimately identify the global minima point. Through sophisticated …
Flowsheet generation through hierarchical reinforcement learning and graph neural networks
Process synthesis experiences a disruptive transformation accelerated by artificial
intelligence. We propose a reinforcement learning algorithm for chemical process design …
intelligence. We propose a reinforcement learning algorithm for chemical process design …
[HTML][HTML] Optimised graded metamaterials for mechanical energy confinement and amplification via reinforcement learning
A reinforcement learning approach to design optimised graded metamaterials for
mechanical energy confinement and amplification is described. Through the proximal policy …
mechanical energy confinement and amplification is described. Through the proximal policy …
Reinforcement learning optimisation for graded metamaterial design using a physical-based constraint on the state representation and action space
The energy harvesting capability of a graded metamaterial is maximised via reinforcement
learning (RL) under realistic excitations at the microscale. The metamaterial consists of a …
learning (RL) under realistic excitations at the microscale. The metamaterial consists of a …
Design synthesis of structural systems as a Markov decision process solved with deep reinforcement learning
ME Ororbia, GP Warn - Journal of Mechanical …, 2023 - asmedigitalcollection.asme.org
Recently, it was demonstrated that the design synthesis of truss structures can be modeled
as a Markov decision process (MDP) and solved using a tabular reinforcement learning …
as a Markov decision process (MDP) and solved using a tabular reinforcement learning …
Teeth mold point cloud completion via data augmentation and hybrid rl-gan
JD Toscano, C Zuniga-Navarrete… - Journal of …, 2023 - asmedigitalcollection.asme.org
Teeth scans are essential for many applications in orthodontics, where the teeth structures
are virtualized to facilitate the design and fabrication of the prosthetic piece. Nevertheless …
are virtualized to facilitate the design and fabrication of the prosthetic piece. Nevertheless …
Reinforcement Learning for Efficient Design Space Exploration With Variable Fidelity Analysis Models
Reinforcement learning algorithms can autonomously learn to search a design space for
high-performance solutions. However, modern engineering often entails the use of …
high-performance solutions. However, modern engineering often entails the use of …
Three-dimensional ship hull encoding and optimization via deep neural networks
Abstract Design and optimization of hull shapes for optimal hydrodynamic performance have
been a major challenge for naval architectures. Deep learning bears the promise of …
been a major challenge for naval architectures. Deep learning bears the promise of …
Flowsheet synthesis through hierarchical reinforcement learning and graph neural networks
Process synthesis experiences a disruptive transformation accelerated by digitization and
artificial intelligence. We propose a reinforcement learning algorithm for chemical process …
artificial intelligence. We propose a reinforcement learning algorithm for chemical process …
Deep Learning in Computational Design Synthesis: A Comprehensive Review
S Kumar Singh, R Rai… - Journal of …, 2024 - asmedigitalcollection.asme.org
A paradigm shift in the computational design synthesis (CDS) domain is being witnessed by
the onset of the innovative usage of machine learning techniques. The rapidly evolving …
the onset of the innovative usage of machine learning techniques. The rapidly evolving …