Heat transfer enhancement, intensification and optimisation in heat exchanger network retrofit and operation

JJ Klemeš, QW Wang, PS Varbanov, M Zeng… - … and Sustainable Energy …, 2020 - Elsevier
The improvement of heat recovery in the industry has traditionally been approached from
two different viewpoints–Process Intensification and Process Integration. Many of the …

Application of porous metal foam heat exchangers and the implications of particulate fouling for energy-intensive industries

STW Kuruneru, K Vafai, E Sauret, YT Gu - Chemical Engineering Science, 2020 - Elsevier
Curtailing the ever-increasing global energy demand remains an arduous challenge. The
US Energy Information Administration emphasized that the deployment of new heat …

Modeling of CO2 capture ability of [Bmim][BF4] ionic liquid using connectionist smart paradigms

B Daryayehsalameh, M Nabavi, B Vaferi - Environmental Technology & …, 2021 - Elsevier
The burning of fossil fuels produces large amounts of exhaust gases containing carbon
dioxide (CO 2). The emission of CO 2 into the atmosphere is widely known as the leading …

Prediction of viscosity of biodiesel blends using various artificial model and comparison with empirical correlations

Y Zheng, MS Shadloo, H Nasiri, A Maleki… - Renewable Energy, 2020 - Elsevier
From the perspective of renewability and environmental pollution, biodiesels are appropriate
alternatives to conventional diesel fuels due to their proper combustion behavior and …

Multi-objective optimization of a tubular heat exchanger enhanced with delta winglet vortex generator and nanofluid using a hybrid CFD-SVR method

SM Ekrani, S Ganjehzadeh, JA Esfahani - International Journal of Thermal …, 2023 - Elsevier
The present study improves the thermal-hydraulic performance of a circular tube equipped
with a delta winglet vortex generator by providing a numerical model, investigating the effect …

Application of hybrid artificial neural networks for predicting rate of penetration (ROP): A case study from Marun oil field

SB Ashrafi, M Anemangely, M Sabah… - Journal of petroleum …, 2019 - Elsevier
Rate of Penetration (ROP) can be considered as a crucial factor in optimization and cost
minimization of drilling operations. In order to predict ROP with satisfactory precision, some …

Hydrogen solubility in aromatic/cyclic compounds: Prediction by different machine learning techniques

Y Jiang, G Zhang, J Wang, B Vaferi - International Journal of Hydrogen …, 2021 - Elsevier
A systematic procedure based on adaptive neuro-fuzzy inference systems (ANFIS), artificial
neural networks, and least-squares support vector machines develop to estimate hydrogen …

Monitoring the effect of surface functionalization on the CO2 capture by graphene oxide/methyl diethanolamine nanofluids

Z Zhou, E Davoudi, B Vaferi - Journal of Environmental Chemical …, 2021 - Elsevier
Different processes exist to capture carbon dioxide (CO 2) and reduce its undesirable effects
on the atmosphere. Stable suspensions of graphene oxide (GO) nanosheets in aqueous …

A machine learning approach to predict drilling rate using petrophysical and mud logging data

M Sabah, M Talebkeikhah, DA Wood… - Earth Science …, 2019 - Springer
Predicting the drilling rate of penetration (ROP) is one approach to optimizing drilling
performance. However, as ROP behavior is unique to specific geological conditions its …

Effects of variable magnetic field on particle fouling properties of magnetic nanofluids in a novel thermal exchanger system

F Fan, C Qi, J Tu, Z Ding - International Journal of Thermal Sciences, 2022 - Elsevier
Magnetic nanofluids, as a new type of heat transfer media, propose a possible way to
achieve low energy consumption and carbon neutrality, which has attracted a lot of attention …