The mechanics of hydrothermal systems: II. Fluid mixing and chemical reactions
In the accompanying paper, Part I, hydrothermal mineralising systems are considered as
open chemical reactors that operate far from equilibrium to develop an exothermal alteration …
open chemical reactors that operate far from equilibrium to develop an exothermal alteration …
Unsupervised machine learning based on non-negative tensor factorization for analyzing reactive-mixing
Abstract Analysis of reactive-diffusion simulations representing complex mixing processes
requires a large number of independent model runs. For each high-fidelity model simulation …
requires a large number of independent model runs. For each high-fidelity model simulation …
On enforcing maximum principles and achieving element-wise species balance for advection–diffusion–reaction equations under the finite element method
MK Mudunuru, KB Nakshatrala - Journal of Computational Physics, 2016 - Elsevier
We present a robust computational framework for advective–diffusive–reactive systems that
satisfies maximum principles, the non-negative constraint, and element-wise species …
satisfies maximum principles, the non-negative constraint, and element-wise species …
A numerical framework for diffusion-controlled bimolecular-reactive systems to enforce maximum principles and the non-negative constraint
We present a novel computational framework for diffusive–reactive systems that satisfies the
non-negative constraint and maximum principles on general computational grids. The …
non-negative constraint and maximum principles on general computational grids. The …
Estimating generalized Lyapunov exponents for products of random matrices
J Vanneste - Physical Review E—Statistical, Nonlinear, and Soft …, 2010 - APS
We discuss several techniques for the evaluation of the generalized Lyapunov exponents
which characterize the growth of products of random matrices in the large-deviation regime …
which characterize the growth of products of random matrices in the large-deviation regime …
A comparative study of machine learning models for predicting the state of reactive mixing
Mixing phenomena are important mechanisms controlling flow, species transport, and
reaction processes in fluids and porous media. Accurate predictions of reactive mixing are …
reaction processes in fluids and porous media. Accurate predictions of reactive mixing are …
Reaction enhancement of initially distant scalars by Lagrangian coherent structures
Turbulent fluid flows have long been recognized as a superior means of diluting initial
concentrations of scalars due to rapid stirring. Conversely, experiments have shown that the …
concentrations of scalars due to rapid stirring. Conversely, experiments have shown that the …
Physics-informed machine learning models for predicting the progress of reactive-mixing
MK Mudunuru, S Karra - Computer Methods in Applied Mechanics and …, 2021 - Elsevier
This paper presents a physics-informed machine learning (ML) framework to construct
reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on …
reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on …
A deep learning modeling framework to capture mixing patterns in reactive-transport systems
NV Jagtap, MK Mudunuru, KB Nakshatrala - arXiv preprint arXiv …, 2021 - arxiv.org
Prediction and control of chemical mixing are vital for many scientific areas such as
subsurface reactive transport, climate modeling, combustion, epidemiology, and …
subsurface reactive transport, climate modeling, combustion, epidemiology, and …
Competitive autocatalytic reactions in chaotic flows with diffusion: Prediction using finite-time Lyapunov exponents
We investigate chaotic advection and diffusion in autocatalytic reactions for time-periodic
sine flow computationally using a mapping method with operator splitting. We specifically …
sine flow computationally using a mapping method with operator splitting. We specifically …