A5101518637- Thermodynamic and Exergetic Analyses of Power and Cooling Systems
- Advanced Thermodynamic Systems and Engines
- Advanced Thermodynamics and Statistical Mechanics
- Refrigeration and Air Conditioning Technologies
- Heat Transfer and Optimization
- Advanced Combustion Engine Technologies
- Solar Thermal and Photovoltaic Systems
- Phase Change Materials Research
- Adsorption and Cooling Systems
- Advanced Sensor and Control Systems
- Advanced Algorithms and Applications
- Industrial Technology and Control Systems
- Combustion and flame dynamics
- Magnetic and transport properties of perovskites and related materials
- Advanced Condensed Matter Physics
- Geotechnical Engineering and Soil Stabilization
- Solar-Powered Water Purification Methods
- Power Systems and Renewable Energy
- Biochemical Analysis and Sensing Techniques
- Multiferroics and related materials
- Simulation and Modeling Applications
- Real-time simulation and control systems
- melanin and skin pigmentation
- Fluid Dynamics and Mixing
- Metallic Glasses and Amorphous Alloys
Beijing University of Technology
2014-2023
Chang'an University
2023
Soochow University
2023
Anhui University of Technology
2022
Midea Group (China)
2022
Masteel (China)
2020
Hebei University of Engineering
2005-2019
Wuhan University of Technology
2016-2018
Xi'an University of Technology
2015
Harbin Engineering University
2012-2013
A novel free piston expander-linear generator (FPE-LG) integrated unit was proposed to recover waste heat efficiently from vehicle engine. This can be used in a small-scale Organic Rankine Cycle (ORC) system and directly convert the thermodynamic energy of working fluid into electric energy. The conceptual design expander (FPE) introduced discussed. cam plate corresponding valve train were control inlet outlet timing FPE. principle FPE-LG proven feasible using an air test rig. indicated...
As the heat exchange component of organic Rankine cycle (ORC) system, evaporator directly affects overall operation performance system. In this paper, an analytical method for energy level on working fluid side is proposed based and enerty theory. The reliability, validity, correlation are studied by means theoretical analysis, experimental evaluation, Elman neural network (ElmanNN). bilinear interpolation algorithm used to analyze non-linear relationship between system parameters side....
To achieve energy saving and emission reduction for vehicle diesel engines, the organic Rankine cycle (ORC) was employed to recover waste heat from R245fa used as ORC working fluid, resulting engine-ORC combined system presented. The variation law of engine exhaust rate under various operating conditions obtained, running performances screw expander were introduced. Based on thermodynamic models theoretical calculations, performance analyzed condition scenarios. Four evaluation indexes...
The organic Rankine cycle (ORC) is a promising technology for medium-and-low temperature heat utilization. However, the mechanism of how system parameters affect output have been investigated very little in experimental aspect. Experimental investigation on impact each parameter performance requires decoupling these parameters. In this work, series experiments are conducted 10 kW scale ORC experiment setup. Statistical analysis performed to identify key subset based an database. 6...
A dual loop organic Rankine cycle (DORC) system is designed to recover waste heat from a heavy-duty compressed natural gas engine (CNGE), and the performance of DORC–CNGE combined simulated discussed. The DORC includes high-temperature (HT) low-temperature (LT) cycles. HT recovers energy exhaust emitted by engine, whereas LT intake air, coolant, working fluid in preheater. mathematical model established based on first second laws thermodynamics. characteristics CNGE are calculated according...
This paper presents a methodology to predict and optimize performance of an organic Rankine cycle (ORC) using back propagation neural network (BPNN) for diesel engine waste heat recovery. A test bench ORC with is established collect experimental data. The collected data are used train BPNN model prediction optimization. After evaluating different hidden layers, the system determined consideration mean squared error (MSE) correlation coefficient. effects key operating parameters on power...