Optimized ANFIS models based on grid partitioning, subtractive clustering, and fuzzy C-means to precise prediction of thermophysical properties of hybrid nanofluids
Z Zhang, M Al-Bahrani, B Ruhani… - Chemical Engineering …, 2023 - Elsevier
Applying machine learning algorithms in the prediction of nanofluids' thermophysical
properties such as density, viscosity, thermal conductivity (TC), and specific heat capacity …
properties such as density, viscosity, thermal conductivity (TC), and specific heat capacity …
Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing …
Suspensions containing microencapsulated phase change materials (MPCMs) play a
crucial role in thermal energy storage (TES) systems and have applications in building …
crucial role in thermal energy storage (TES) systems and have applications in building …
Surfactant free enhancement to thermophysical and tribological performance of bio-degradable lubricant with nano-friction modifier for sustainable end milling of …
An efficient method of lubrication and cooling for green machining is nanofluid minimum
quantity lubrication (NMQL). Compared to other vegetable-based oils, coconut oil has the …
quantity lubrication (NMQL). Compared to other vegetable-based oils, coconut oil has the …
Insights into robust carbon nanotubes in tribology: From nano to macro
FZ Zhang, XB Liu, CM Yang, GD Chen, Y Meng… - Materials Today, 2024 - Elsevier
Over the years, reducing friction and wear-induced deformation, damage and/or removal of
material at various contact interfaces has always aroused significant interests due to the …
material at various contact interfaces has always aroused significant interests due to the …
Using different machine learning algorithms to predict the rheological behavior of oil SAE40-based nano-lubricant in the presence of MWCNT and MgO nanoparticles
In the present study, using 15 machine learning algorithms (MLP, SVM, RBF, ELM, ANFIS, D-
Tree, MLR, MPR, BPNN, BN, LM, GD, BFGS, XGB and GMDH), the rheological behavior of …
Tree, MLR, MPR, BPNN, BN, LM, GD, BFGS, XGB and GMDH), the rheological behavior of …
Experimental study on the dynamic viscosity of hydraulic oil HLP 68-Fe3O4-TiO2-GO ternary hybrid nanofluid and modeling utilizing machine learning technique
Background Considering the importance of hydraulic oils in various tasks, such as
lubrication and cooling, this study evaluated the feasibility of improving the efficiency of …
lubrication and cooling, this study evaluated the feasibility of improving the efficiency of …
Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable …
Optimization of thermophysical properties (TPPs) of MXene-based nanofluids is essential to
increase the performance of hybrid solar photovoltaic and thermal (PV/T) systems. This …
increase the performance of hybrid solar photovoltaic and thermal (PV/T) systems. This …
Artificial neural network hyperparameters optimization for predicting the thermal conductivity of MXene/graphene nanofluids
Background The critical role of thermal conductivity (TC) as a significant thermo-physical
property in MXene/graphene-based nanofluids for photovoltaic/thermal systems has …
property in MXene/graphene-based nanofluids for photovoltaic/thermal systems has …
[HTML][HTML] Enhancing solar energy conversion efficiency: Thermophysical property predicting of MXene/Graphene hybrid nanofluids via bayesian-optimized artificial …
Accurately predicting thermo-physical properties (TPPs) of MXene/graphene-based
nanofluids is crucial for photovoltaic/thermal solar systems, driving focused research on …
nanofluids is crucial for photovoltaic/thermal solar systems, driving focused research on …
Important contributions of carbon materials in tribology: From lubrication abilities to wear mechanisms
R Wang, F Zhang, K Yang, N **ao, J Tang… - Journal of Alloys and …, 2024 - Elsevier
Friction and wear are omnipresent, which have caused many problems such as energy
dissipation and component damage, making all mankind face an energy crisis and huge …
dissipation and component damage, making all mankind face an energy crisis and huge …