Application of artificial intelligence for prediction, optimization, and control of thermal energy storage systems
Energy storage is one of the core concepts demonstrated incredibly remarkable
effectiveness in various energy systems. Energy storage systems are vital for maximizing the …
effectiveness in various energy systems. Energy storage systems are vital for maximizing the …
Battery thermal management systems based on nanofluids for electric vehicles
The continuous rapid growth of the world population over the coming decade remains a
crucial issue that requires ambitious innovations such as electric vehicles (EVs) to …
crucial issue that requires ambitious innovations such as electric vehicles (EVs) to …
Recent advances in machine learning research for nanofluid-based heat transfer in renewable energy system
Nanofluids have gained significant popularity in the field of sustainable and renewable
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
energy systems. The heat transfer capacity of the working fluid has a huge impact on the …
Using Bayesian optimization and ensemble boosted regression trees for optimizing thermal performance of solar flat plate collector under thermosyphon condition …
The thermal performance of a flat plate solar collector operating under thermosyphon
conditions using MWCNT+ Fe 3 O 4/Water hybrid nanofluids was investigated in this study …
conditions using MWCNT+ Fe 3 O 4/Water hybrid nanofluids was investigated in this study …
Thermal management systems based on heat pipes for batteries in EVs/HEVs
A thermal management system (TMS) is necessary for lithium-ion batteries (LiBs) used in
electric vehicles/hybrid electric vehicles (EVs/HEVs), which generate excessive heat during …
electric vehicles/hybrid electric vehicles (EVs/HEVs), which generate excessive heat during …
Optimized ANFIS models based on grid partitioning, subtractive clustering, and fuzzy C-means to precise prediction of thermophysical properties of hybrid nanofluids
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 …
Comparative evaluation of AI‐based intelligent GEP and ANFIS models in prediction of thermophysical properties of Fe3O4‐coated MWCNT hybrid nanofluids for …
Hybrid nanofluids are gaining popularity owing to the synergistic effects of nanoparticles,
which provide them with better heat transfer capabilities than base fluids and normal …
which provide them with better heat transfer capabilities than base fluids and normal …
Tribological and rheological properties of novel MoO3-GO-MWCNTs/5W30 ternary hybrid nanolubricant: Experimental measurement, development of practical …
In the present paper, the rheological and tribological measurements of the SAE 5W30 multi-
grade engine oil as a base lubricant and a novel ternary combination of molybdenum …
grade engine oil as a base lubricant and a novel ternary combination of molybdenum …
Recovery of waste heat from proton exchange membrane fuel cells–A review
This work discusses the novel application of proton exchange membrane fuel cells (PEMFC)
in the transport sector as well as portable applications. This kind of fuel cell produces a …
in the transport sector as well as portable applications. This kind of fuel cell produces a …
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 …