Data-driven techniques in rheology: Developments, Challenges and Perspective
With the rapid development and adoption of different data-driven techniques in rheology,
this review aims to reflect on the advent and growth of these frameworks, survey the state-of …
this review aims to reflect on the advent and growth of these frameworks, survey the state-of …
Uncertainty covered techno-enviro-economic viability evaluation of a solar still water desalination unit using Monte Carlo approach
Due to much lower initial and operating costs, as well as a great environmental and energy
performance, there has been a growing tendency towards the application of solar still …
performance, there has been a growing tendency towards the application of solar still …
Unbiased construction of constitutive relations for soft materials from experiments via rheology-informed neural networks
M Mahmoudabadbozchelou… - Proceedings of the …, 2024 - National Acad Sciences
The ability to concisely describe the dynamical behavior of soft materials through closed-
form constitutive relations holds the key to accelerated and informed design of materials and …
form constitutive relations holds the key to accelerated and informed design of materials and …
Application of physics encoded neural networks to improve predictability of properties of complex multi-scale systems
MBJ Meinders, J Yang, E Linden - Scientific Reports, 2024 - nature.com
Predicting physical properties of complex multi-scale systems is a common challenge and
demands analysis of various temporal and spatial scales. However, physics alone is often …
demands analysis of various temporal and spatial scales. However, physics alone is often …
Machine learning-based constitutive modelling for material non-linearity: A review
A Hussain, AH Sakhaei, M Shafiee - Mechanics of Advanced …, 2024 - Taylor & Francis
Abstract Machine learning (ML) models are widely used across numerous scientific and
engineering disciplines due to their exceptional performance, flexibility, prediction quality …
engineering disciplines due to their exceptional performance, flexibility, prediction quality …
A deep learning framework for solving the prediction and reconstruction problem of Bingham fluid flow field
Z Gao, R Yin, R Zhai, J Lin, D Yin - Physics of Fluids, 2024 - pubs.aip.org
As a typical non-Newtonian fluid, Bingham fluid is employed in a multitude of fields,
including petroleum, construction, and the chemical industry. However, due to the intricate …
including petroleum, construction, and the chemical industry. However, due to the intricate …
Data-driven constitutive meta-modeling of nonlinear rheology via multifidelity neural networks
Predicting the response of complex fluids to different flow conditions has been the focal point
of rheology and is generally done via constitutive relations. There are, nonetheless …
of rheology and is generally done via constitutive relations. There are, nonetheless …
Stochastic Generalized-Order Constitutive Modeling of Viscoelastic Spectra of Polyurea-Graphene Nanocomposites
A Khoshnevis, DA Tzelepis, VV Ginzburg… - arXiv preprint arXiv …, 2024 - arxiv.org
Polyurea (PUa) elastomers are extensively used in a wide range of applications spanning
from biomedical to defense fields due to their enabling mechanical properties. These …
from biomedical to defense fields due to their enabling mechanical properties. These …
Unifides: Universal fractional integro-differential equation solvers
The development of data-driven approaches for solving differential equations has been
followed by a plethora of applications in science and engineering across a multitude of …
followed by a plethora of applications in science and engineering across a multitude of …