PROPAGATION OF GASEOUS DETONATIONS IN PLANAR CURVED RECTANGULAR CHANNELS

2020 ◽  
Author(s):  
M. L. FOTIA ◽  
◽  
J. HOKE ◽  
A. J. OLSON ◽  
S. A. SCHUMAKER ◽  
...  
Keyword(s):  
Failure Mechanisms ◽  
Engineering Applications ◽  
Gaseous Detonations ◽  
Curved Channels ◽  
Rectangular Channels ◽  
Cellular Detonation ◽  
Practical Engineering ◽  
Rotating Detonation Engines ◽  
Rotating Detonation

The propagation of gaseous detonations through curved channels has a number of practical engineering applications that range from combustion initiation concepts to informing the design of rotating detonation engines. Understanding the failure mechanisms that do not allow a steadily propagating cellular detonation to traverse a curved segment of channel leads directly into these applications.

scholarly journals Design of a new hybrid artificial neural network method based on decision trees for calculating the Froude number in rigid rectangular channels

2016 ◽  
Vol 64 (3) ◽  
pp. 252-260 ◽  
Author(s):  
Isa Ebtehaj ◽  
Hossein Bonakdari ◽  
Amir Hossein Zaji ◽  
Charles Hin Joo Bong ◽  
Aminuddin Ab Ghani
Keyword(s):  
Decision Trees ◽  
Incipient Motion ◽  
Rigid Boundary ◽  
Sediment Bed ◽  
Economical Design ◽  
Rectangular Channels ◽  
Wide Range ◽  
Practical Engineering ◽  
Artificial Neural Network Method ◽  
Bed Thickness

Abstract A vital topic regarding the optimum and economical design of rigid boundary open channels such as sewers and drainage systems is determining the movement of sediment particles. In this study, the incipient motion of sediment is estimated using three datasets from literature, including a wide range of hydraulic parameters. Because existing equations do not consider the effect of sediment bed thickness on incipient motion estimation, this parameter is applied in this study along with the multilayer perceptron (MLP), a hybrid method based on decision trees (DT) (MLP-DT), to estimate incipient motion. According to a comparison with the observed experimental outcome, the proposed method performs well (MARE = 0.048, RMSE = 0.134, SI = 0.06, BIAS = -0.036). The performance of MLP and MLP-DT is compared with that of existing regression-based equations, and significantly higher performance over existing models is observed. Finally, an explicit expression for practical engineering is also provided.

Vortex Visualization for Practical Engineering Applications

2006 ◽  
Vol 12 (5) ◽  
pp. 957-964 ◽  
Author(s):  
Monika Jankun-Kelly ◽  
Ming Jiang ◽  
David Thompson ◽  
Raghu Machiraju
Keyword(s):  
Engineering Applications ◽  
Practical Engineering
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