A unique physics-aided deep learning model for predicting viscosity of nanofluids

Physics-based smart model for prediction of viscosity of nanofluids containing nanoparticles using deep learning

(2021) Satyasaran Changdar et al.   Journal of Computational Design and Engineering

Computationally efficient multiscale modeling for probabilistic analysis of CFRP composites with micro-scale spatial randomness

(2021) Rudraprasad Bhattacharyya et al.   COMPOSITE STRUCTURES

Uncertainty Quantification for Additive Manufacturing Process Improvement: Recent Advances

(2021) Sankaran Mahadevan et al.   ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B-Mechanical Engineering

Prediction of nanofluids viscosity using random forest (RF) approach

(2020) Majid Gholizadeh et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Modeling the viscosity of nanofluids using artificial neural network and Bayesian support vector regression

(2020) Ibrahim Olanrewaju Alade et al.   JOURNAL OF APPLIED PHYSICS

Applicability of connectionist methods to predict dynamic viscosity of silver/water nanofluid by using ANN-MLP, MARS and MPR algorithms

(2019) Mohammad Hossein Ahmadi et al.   Engineering Applications of Computational Fluid Mechanics

Determination of thermal conductivity ratio of CuO/ethylene glycol nanofluid by connectionist approach

(2018) Mohammad-Ali Ahmadi et al.   Journal of the Taiwan Institute of Chemical Engineers

A review on the application of deep learning in system health management

(2018) Samir Khan et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

Developing an ANFIS-based swarm concept model for estimating the relative viscosity of nanofluids

(2018) Alireza Baghban et al.   Engineering Applications of Computational Fluid Mechanics

Sensitivity analysis and application of machine learning methods to predict the heat transfer performance of CNT/water nanofluid flows through coils

(2018) Alireza Baghban et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

(2017) Anuj Karpatne et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Experimental data, thermodynamic and neural network modeling of CO 2 solubility in aqueous sodium salt of l -phenylalanine

(2017) Sahil Garg et al.   Journal of CO2 Utilization

Accurate prediction of nanofluid viscosity using a multilayer perceptron artificial neural network (MLP-ANN)

(2016) Elham Heidari et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Viscosity of nanofluids: A review of recent experimental studies

(2016) Kazem Bashirnezhad et al.   INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER

A novel correlation approach for viscosity prediction of water based nanofluids of Al 2 O 3 , TiO 2 , SiO 2 and CuO

(2016) Mahdi Kalantari Meybodi et al.   Journal of the Taiwan Institute of Chemical Engineers

Review on combined heat and mass transfer characteristics in nanofluids

(2015) Changwei Pang et al.   INTERNATIONAL JOURNAL OF THERMAL SCIENCES

Integration of model verification, validation, and calibration for uncertainty quantification in engineering systems

(2015) Shankar Sankararaman et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Application of Deep Belief Networks for Natural Language Understanding

(2014) Ruhi Sarikaya et al.   IEEE-ACM Transactions on Audio Speech and Language Processing

Viscosity and thermal conductivity measurements of water-based nanofluids containing titanium oxide nanoparticles

(2012) Laura Fedele et al.   INTERNATIONAL JOURNAL OF REFRIGERATION-REVUE INTERNATIONALE DU FROID

Quantitative model validation techniques: New insights

(2012) You Ling et al.   RELIABILITY ENGINEERING & SYSTEM SAFETY

Latest developments on the viscosity of nanofluids

(2011) I.M. Mahbubul et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Experimental Investigation on the Thermal Conductivity and Viscosity of Silver-Deionized Water Nanofluid

(2010) L. Godson et al.   EXPERIMENTAL HEAT TRANSFER

CuO in water nanofluid: Influence of particle size and polydispersity on volumetric behaviour and viscosity

(2010) M.J. Pastoriza-Gallego et al.   FLUID PHASE EQUILIBRIA

On the effective viscosity of suspensions

(2010) B. Abedian et al.   INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE

Effects of Temperature and Particle Size on the Thermal Property Measurements of Al2O3−Water Nanofluids

(2010) D. Kwek et al.   JOURNAL OF CHEMICAL AND ENGINEERING DATA

Measurement of temperature-dependent thermal conductivity and viscosity of TiO2-water nanofluids

(2009) Weerapun Duangthongsuk et al.   EXPERIMENTAL THERMAL AND FLUID SCIENCE

Rheological and flow characteristics of nanofluids: Influence of electroviscous effects and particle agglomeration

(2009) K. B. Anoop et al.   JOURNAL OF APPLIED PHYSICS

A new model for calculating the effective viscosity of nanofluids

(2009) N Masoumi et al.   JOURNAL OF PHYSICS D-APPLIED PHYSICS

Effective viscosities and thermal conductivities of aqueous nanofluids containing low volume concentrations of Al2O3 nanoparticles

(2008) Ji-Hwan Lee et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER