مهدی جامعی

صفحه نخست /مهدی جامعی
مهدی جامعی
نام و نام خانوادگی مهدی جامعی
شغل عضو یک سازمان آموزشی یا پژوهشی داخلی
تحصیلات 0
وبسایت
پست الکترونیک
 عنوانمجله
1 Experimental study and gradient-based ensemble intelligent computing to investigate effect of ultrasound on rheological behavior of bio-based phase change materials journal of energy storage
2 Assessment of thermal conductivity of polyethylene glycol-carbon dot nanofluid through a combined experimental-data mining investigation Journal of Materials Research and Technology-JMR&T
3 Two-phase mixture numerical and soft computing-based simulation of forced convection of biologically prepared water-silver nanofluid inside a double-pipe heat exchanger with converging sinusoidal wall: Hydrothermal performance and entropy generation analysis ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
4 A parametric assessing and intelligent forecasting of the energy and exergy performances of a dish concentrating photovoltaic/thermal collector considering six different nanofluids and applying two meticulous soft computing paradigms RENEWABLE ENERGY
5 The entropy generation analysis of the influence of using fins with tip clearance on the thermal management of the batteries with phase change material: Application a new gradient-based ensemble machine learning approach ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
6 Experimental exploration of rheological behavior of polyethylene glycol-carbon dot nanofluid: Introducing a robust artificial intelligence paradigm optimized with unscented Kalman filter technique JOURNAL OF MOLECULAR LIQUIDS
7 Investigation on two-phase fluid mixture flow, heat transfer and entropy generation of a non-Newtonian water-CMC/CuO nanofluid inside a twisted tube with variable twist pitch: Numerical and evolutionary machine learning simulation ENGINEERING ANALYSIS WITH BOUNDARY ELEMENTS
8 Experimental evaluation and development of predictive models for rheological behavior of aqueous Fe3O4 ferrofluid in the presence of an external magnetic field by introducing a novel grid optimization based-Kernel ridge regression supported by sensitivity analysis POWDER TECHNOLOGY