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Experimental study on thermal conductivity of water-based Fe3O4 nanofluid: Development of a new correlation and modeled by artificial neural network

International communications in heat and mass transfer, 2016-07, Vol.75, p.262-269

2016

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Measurement of the thermal conductivity of MWCNT-CuO/water hybrid nanofluid using artificial neural networks (ANNs)

Journal of thermal analysis and calorimetry, 2021, Vol.143 (2), p.1097-1105

2021

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Designing an Artificial Neural Network (ANN) to predict the viscosity of Silver/Ethylene glycol nanofluid at different temperatures and volume fraction of nanoparticles

Physica A, 2019-11, Vol.534, p.122142, Article 122142

2019

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Forecasting the thermal conductivity of a nanofluid using artificial neural networks

Journal of thermal analysis and calorimetry, 2021-08, Vol.145 (4), p.2095-2104

2021

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Predict the thermal conductivity of SiO2/water–ethylene glycol (50:50) hybrid nanofluid using artificial neural network

Journal of thermal analysis and calorimetry, 2021, Vol.143 (2), p.1119-1128

2021

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Application of Artificial Neural Networks (ANNs) for Predicting the Viscosity of Tungsten Oxide (WO3)-MWCNTs/Engine Oil Hybrid Nanofluid

International journal of thermophysics, 2020, Vol.41 (12), Article 163

2020

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Statistical modeling and investigation of thermal characteristics of a new nanofluid containing cerium oxide powder

Heliyon, 2022-11, Vol.8 (11), p.e11373-e11373, Article e11373

2022

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Applying Artificial Neural Networks (ANNs) for prediction of the thermal characteristics of engine oil –based nanofluids containing tungsten oxide -MWCNTs

Case studies in thermal engineering, 2021-08, Vol.26, p.101122, Article 101122

2021

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Addition of MWCNT-Al2O3 nanopowders to water- ethylene glycol (EG) base fluid for enhancing the thermal characteristics: Design an optimum feed-forward neural network

Case studies in thermal engineering, 2021-10, Vol.27, p.101293, Article 101293

2021

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Developing dissimilar artificial neural networks (ANNs) to prediction the thermal conductivity of MWCNT-TiO2/Water-ethylene glycol hybrid nanofluid

Powder technology, 2019-10, Vol.355, p.602-610

2019

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Multi-objective optimization of functionally graded materials, thickness and aspect ratio in micro-beams embedded in an elastic medium

Structural and multidisciplinary optimization, 2018-07, Vol.58 (1), p.265-285

2018

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Evaluation of thermal conductivity of MgO-MWCNTs/EG hybrid nanofluids based on experimental data by selecting optimal artificial neural networks

Physica. E, Low-dimensional systems & nanostructures, 2017-01, Vol.85, p.90-96

2017

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Static Pull-in Analysis of Electrostatically Actuated Functionally Graded Micro-Beams Based on the Modified Strain Gradient Theory

International journal of applied mechanics, 2018-04, Vol.10 (3), p.1850031

2018

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Optimization of fatigue life of pearlitic Grade 900A steel based on the combination of genetic algorithm and artificial neural network

International journal of fatigue, 2022-09, Vol.162, p.106975, Article 106975

2022

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Designing an artificial neural network to predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluid

International communications in heat and mass transfer, 2015-11, Vol.68, p.50-57

2015

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Study on thermal conductivity of water-based nanofluids with hybrid suspensions of CNTs/Al2O3 nanoparticles

Journal of thermal analysis and calorimetry, 2016-04, Vol.124 (1), p.455-460

2016

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An experimental study on thermal conductivity of MgO nanoparticles suspended in a binary mixture of water and ethylene glycol

International communications in heat and mass transfer, 2015-10, Vol.67, p.173-175

2015

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Artificial neural network based fatigue life assessment of friction stir welding AA2024-T351 aluminum alloy and multi-objective optimization of welding parameters

International journal of fatigue, 2022-07, Vol.160, p.106840, Article 106840

2022

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Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network

International communications in heat and mass transfer, 2016-08, Vol.76, p.209-214

2016

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Optimization of thermophysical properties of Al2O3/water-EG (80:20) nanofluids by NSGA-II

Physica. E, Low-dimensional systems & nanostructures, 2018-09, Vol.103, p.264-272

2018

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Retraction notice to “An investigation on fatigue behavior of AA2024 aluminum alloy sheets in fuselage lap joints” [Eng. Fail. Anal. 126 (2021) 105457]

Engineering failure analysis, 2024-06, Vol.160, p.108350, Article 108350

2024

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Simulation and Validation of Optimized PID Controller in AGV (Automated Guided Vehicles) Model Using PSO and BAS Algorithms

Computational intelligence and neuroscience, 2022-11, Vol.2022, p.1-22

2022

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Expression of concern “An investigation on fatigue behavior of AA2024 aluminum alloy sheets in fuselage lap joints” [Eng. Fail. Anal. 126 (2021) 105457]

Engineering failure analysis, 2024-04, Vol.158, p.108068, Article 108068

2024

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Prediction of rheological behavior of MWCNTs–SiO2/EG–water non-Newtonian hybrid nanofluid by designing new correlations and optimal artificial neural networks

Journal of thermal analysis and calorimetry, 2018-05, Vol.132 (2), p.1029-1038

2018

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Artificial neural network based fatigue life assessment of riveted joints in AA2024 aluminum alloy plates and optimization of riveted joints parameters

International journal of fatigue, 2024-01, Vol.178, p.107997, Article 107997

2024

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Experimental study on thermal conductivity of water-based Fe3O4 nanofluid: Development of a new correlation and modeled by artificial neural network

Measurement of the thermal conductivity of MWCNT-CuO/water hybrid nanofluid using artificial neural networks (ANNs)

Designing an Artificial Neural Network (ANN) to predict the viscosity of Silver/Ethylene glycol nanofluid at different temperatures and volume fraction of nanoparticles

Forecasting the thermal conductivity of a nanofluid using artificial neural networks

Predict the thermal conductivity of SiO2/water–ethylene glycol (50:50) hybrid nanofluid using artificial neural network

Application of Artificial Neural Networks (ANNs) for Predicting the Viscosity of Tungsten Oxide (WO3)-MWCNTs/Engine Oil Hybrid Nanofluid

Statistical modeling and investigation of thermal characteristics of a new nanofluid containing cerium oxide powder

Applying Artificial Neural Networks (ANNs) for prediction of the thermal characteristics of engine oil –based nanofluids containing tungsten oxide -MWCNTs

Addition of MWCNT-Al2O3 nanopowders to water- ethylene glycol (EG) base fluid for enhancing the thermal characteristics: Design an optimum feed-forward neural network

Developing dissimilar artificial neural networks (ANNs) to prediction the thermal conductivity of MWCNT-TiO2/Water-ethylene glycol hybrid nanofluid

Multi-objective optimization of functionally graded materials, thickness and aspect ratio in micro-beams embedded in an elastic medium

Evaluation of thermal conductivity of MgO-MWCNTs/EG hybrid nanofluids based on experimental data by selecting optimal artificial neural networks

Static Pull-in Analysis of Electrostatically Actuated Functionally Graded Micro-Beams Based on the Modified Strain Gradient Theory

Optimization of fatigue life of pearlitic Grade 900A steel based on the combination of genetic algorithm and artificial neural network

Designing an artificial neural network to predict thermal conductivity and dynamic viscosity of ferromagnetic nanofluid

Study on thermal conductivity of water-based nanofluids with hybrid suspensions of CNTs/Al2O3 nanoparticles

An experimental study on thermal conductivity of MgO nanoparticles suspended in a binary mixture of water and ethylene glycol

Artificial neural network based fatigue life assessment of friction stir welding AA2024-T351 aluminum alloy and multi-objective optimization of welding parameters

Prediction of dynamic viscosity of a hybrid nano-lubricant by an optimal artificial neural network

Optimization of thermophysical properties of Al2O3/water-EG (80:20) nanofluids by NSGA-II

Retraction notice to “An investigation on fatigue behavior of AA2024 aluminum alloy sheets in fuselage lap joints” [Eng. Fail. Anal. 126 (2021) 105457]

Simulation and Validation of Optimized PID Controller in AGV (Automated Guided Vehicles) Model Using PSO and BAS Algorithms

Expression of concern “An investigation on fatigue behavior of AA2024 aluminum alloy sheets in fuselage lap joints” [Eng. Fail. Anal. 126 (2021) 105457]

Prediction of rheological behavior of MWCNTs–SiO2/EG–water non-Newtonian hybrid nanofluid by designing new correlations and optimal artificial neural networks

Artificial neural network based fatigue life assessment of riveted joints in AA2024 aluminum alloy plates and optimization of riveted joints parameters

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