Review of machine learning for hydrodynamics, transport, and reactions in multiphase flows and reactors
Artificial intelligence (AI), machine learning (ML), and data science are leading to a
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
promising transformative paradigm. ML, especially deep learning and physics-informed ML …
Surrogate modelling for an aircraft dynamic landing loads simulation using an LSTM AutoEncoder-based dimensionality reduction approach
M Lazzara, M Chevalier, M Colombo, JG Garcia… - Aerospace Science and …, 2022 - Elsevier
Surrogate modelling can alleviate the computational burden of design activities as they rely
on multiple evaluations of high-fidelity models. However, the learning task can be adversely …
on multiple evaluations of high-fidelity models. However, the learning task can be adversely …
Iterative symbolic regression for learning transport equations
Computational fluid dynamics (CFD) analysis is widely used in chemical engineering.
Although CFD calculations are accurate, the computational cost associated with complex …
Although CFD calculations are accurate, the computational cost associated with complex …
Surrogate model based on hierarchical sparse polynomial interpolation for the phosphate ore dissolution
This paper deals with the development of accurate surrogate models for first-principles
models constructed for the dissolution of phosphate ore in a phosphoric acid solution. The …
models constructed for the dissolution of phosphate ore in a phosphoric acid solution. The …
[PDF][PDF] Development of Mass/Energy Constrained Sparse Bayesian Surrogate Models from Noisy Data
S Adeyemo, D Bhattacharyya - Syst. Control Trans, 2024 - psecommunity.org
This paper presents an algorithm for develo** sparse surrogate models that satisfy
mass/energy conservation even when the training data are noisy and violate the …
mass/energy conservation even when the training data are noisy and violate the …
Towards Machine Learning Applications for Computational Fluid Dynamics Modeling in Chemical Engineering
Abstract Computational Fluid Dynamics (CFD) simulation of multiphase industrial flows is a
significant research concern for studying the performance and efficiency of chemical …
significant research concern for studying the performance and efficiency of chemical …