A Study on Combustion Efficiency of a Paraffin-based Hybrid Rockets

2011 ◽  
Author(s):  
Takafumi Ishiguro ◽  
Keizi Sinohara ◽  
Kazuki Sakio ◽  
Ichiro Nakagawa
Keyword(s):  
Combustion Efficiency ◽  
Hybrid Rockets

Investigation of the Throttling Characteristics of Axial-injection End-burning Hybrid Rockets

2017 ◽  
Vol 65 (4) ◽  
pp. 157-167 ◽  
Author(s):  
Yuji SAITO ◽  
Toshiki YOKOI ◽  
Ayumu TSUJI ◽  
Kazunobu OMURA ◽  
Hiroyuki YASUKOCHI ◽  
...  
Keyword(s):  
Axial Injection ◽  
Hybrid Rockets

Examining Port Geometry/Solid Loading for Additively Manufactured Fuels in Hybrid Rockets

2020 ◽  
pp. 1-9
Author(s):  
Gregory Young ◽  
Terrence L. Connell ◽  
Kyle Fennell ◽  
Steve Possehl ◽  
Michael Baier
Keyword(s):  
Solid Loading ◽  
Hybrid Rockets

Experimental investigations of the combustion efficiency for fire load calculations

2015 ◽  
Vol 57 (10) ◽  
pp. 843-849 ◽  
Author(s):  
Christian Kusche ◽  
Christian Knaust ◽  
Sarah-Katharina Hahn ◽  
Ulrich Krause
Keyword(s):  
Combustion Efficiency ◽  
Experimental Investigations ◽  
Fire Load

Modeling and Experiment on Combustion Characteristics for Biomass Rotary Burner

2020 ◽  
Vol 04 ◽  
Author(s):  
Guohai Jia ◽  
Lijun Li ◽  
Li Dai ◽  
Zicheng Gao ◽  
Jiping Li
Keyword(s):  
Combustion Chamber ◽  
Combustion Temperature ◽  
Combustion Efficiency ◽  
Middle Part ◽  
Combustion Characteristics ◽  
Maximum Temperature ◽  
Excess Air ◽  
Element Simulation ◽  
Excess Air Coefficient ◽  
Secondary Air

Background: A biomass pellet rotary burner was chosen as the research object in order to study the influence of excess air coefficient on the combustion efficiency. The finite element simulation model of biomass rotary burner was established. Methods: The computational fluid dynamics software was applied to simulate the combustion characteristics of biomass rotary burner in steady condition and the effects of excess air ratio on pressure field, velocity field and temperature field was analyzed. Results: The results show that the flow velocity inside the burner gradually increases with the increase of inlet velocity and the maximum combustion temperature is also appeared in the middle part of the combustion chamber. Conclusion: When the excess air coefficient is 1.0 with the secondary air outlet velocity of 4.16 m/s, the maximum temperature of the rotary combustion chamber is 2730K with the secondary air outlet velocity of 6.66 m/s. When the excess air ratio is 1.6, the maximum temperature of the rotary combustion chamber is 2410K. When the air ratio is 2.4, the maximum temperature of the rotary combustion chamber is 2340K with the secondary air outlet velocity of 9.99 m/s. The best excess air coefficient is 1.0. The experimental value of combustion temperature of biomass rotary burner is in good agreement with the simulation results.

scholarly journals Combustion Optimization for Coal Fired Power Plant Boilers Based on Improved Distributed ELM and Distributed PSO

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1036 ◽  
Author(s):  
Xinying Xu ◽  
Qi Chen ◽  
Mifeng Ren ◽  
Lan Cheng ◽  
Jun Xie
Keyword(s):  
Power Plant ◽  
Combustion Process ◽  
Optimization Method ◽  
Combustion Efficiency ◽  
Pollutant Emissions ◽  
Combustion Model ◽  
Nox Emissions ◽  
Coupling Characteristics ◽  
Learning Machine ◽  
Combustion Optimization

Increasing the combustion efficiency of power plant boilers and reducing pollutant emissions are important for energy conservation and environmental protection. The power plant boiler combustion process is a complex multi-input/multi-output system, with a high degree of nonlinearity and strong coupling characteristics. It is necessary to optimize the boiler combustion model by means of artificial intelligence methods. However, the traditional intelligent algorithms cannot deal effectively with the massive and high dimensional power station data. In this paper, a distributed combustion optimization method for boilers is proposed. The MapReduce programming framework is used to parallelize the proposed algorithm model and improve its ability to deal with big data. An improved distributed extreme learning machine is used to establish the combustion system model aiming at boiler combustion efficiency and NOx emission. The distributed particle swarm optimization algorithm based on MapReduce is used to optimize the input parameters of boiler combustion model, and weighted coefficient method is used to solve the multi-objective optimization problem (boiler combustion efficiency and NOx emissions). According to the experimental analysis, the results show that the method can optimize the boiler combustion efficiency and NOx emissions by combining different weight coefficients as needed.

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