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008			260216t20252025my a|||fr|||| 000 0 eng d
020			_aTHE0010341 (Local) _qHardback
040			_aUMPSA _beng _cUMPSA _erda
090			_aFTKMA .S95 2025 r Thesis
100	1		_aGanesan A/l Kadirgama, _eauthor.
245	1	0	_aCharacterization of hybrid alumina-copper oxide based therminol 55 heat transfer fluid and its performance evaluation by machine learning approach / _cGanesan A/l Kadirgama
264		1	_aKuantan Pahang : _bUMPSA, _c2025
264		4	_c© 2025
300			_axv, 138 pages : _billustration ; _c30 cm.+ _e1 CD-ROM
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
347			_2rda _atext file _bPDF
500			_aFaculty of Chemical and Process Engineering Technology
502			_aThesis (Doctor of Philosophy) -- Universiti Malaysia Pahang Al Sultan Abdullah - 2025
504			_aInclude bibliographical reference
520	3		_aEfficient thermal management plays a critical role in various industrial applications, particularly in systems utilizing Therminol 55, where the selection of appropriate heat transfer fluids can significantly influence system performance. This study investigates the thermophysical properties of hybrid alumina-copper oxide (Al2O3-CuO) nanoparticles dispersed in Therminol 55, focusing on enhancing both thermal conductivity and viscosity. The research aims to develop a superior heat transfer fluid for medium-temperature applications by optimizing the nanoparticle concentration and hybrid ratio. A one-step ultrasonication method was employed to achieve homogeneous dispersion of the nanoparticles, ensuring optimal stability. Concentrations of the hybrid nanoparticles were varied from 0.1 wt% to 1.0 wt%, with three hybrid ratios of Al2O3 to CuO (10:90, 20:80, and 30:70) tested.The experimental results demonstrated that the hybrid nanofluids exhibited notable improvements in thermal properties. Specifically, the formulation with a 0.5 wt% concentration and a 30:70 ratio of Al2O3 to CuO achieved the highest thermal conductivity, recording a 27% increase compared to pure Therminol 55. This enhanced thermal conductivity was attributed to the synergistic effects of combining Al2O3, known for its thermal stability, with CuO, which offers high thermal conductivity. In contrast, the viscosity of the optimized nanofluid increased by 45%, presenting a challenge in balancing improved heat transfer and fluid flow. The study also observed that viscosity decreased with increasing temperature, highlighting the potential for practical applications at elevated operating conditions.To further analyze the complex interactions influencing the thermal behavior of the hybrid nanofluids, a machine learning model was developed using the Adaptive Neuro-Fuzzy Inference System (ANFIS). The model was designed to predict both thermal conductivity and viscosity under varying conditions of temperature, concentration, and nanoparticle ratio. The ANFIS model achieved high accuracy, with a mean absolute error (MAE) of 0.015 W/m.K for thermal conductivity and 0.009 mPa.s for viscosity predictions. This demonstrated the model’s capability to capture nonlinear dependencies between input parameters. The findings from this study indicate that hybrid alumina-copper oxide nanofluids in Therminol 55 hold significant promise for enhancing the efficiency of medium-temperature heat transfer systems. In addition to offering improved thermal performance over conventional nanofluids containing either Al2O3 or CuO alone, the hybrid formulation also demonstrated long-term stability and resistance to sedimentation, making it suitable for real-world industrial applications. The study’s contributions are aligned with global sustainability goals, particularly SDG 7 (Affordable and Clean Energy) and SDG 9 (Industry, Innovation, and Infrastructure) with 10-10 MySTIE Framework in Energy and Advanced Materials the research offers practical insights into sustainable energy.
610	2	0	_aFaculty of Chemical and Process Engineering Technology _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses _xDissertations
942			_2lcc _cTHESIS
999			_c104195 _d104201