AN EIGENVALUE METHOD FOR COMPUTING THE BURNING RATES OF RDX AND HMX MONOPROPELLANTS

1997 ◽  
Vol 4 (1-6) ◽  
pp. 1104-1115 ◽  
Author(s):  
Kuldeep Prasad ◽  
Richard A. Yetter ◽  
M. D. Smooke
Keyword(s):  
Eigenvalue Method ◽  
Burning Rates

An eigenvalue method for computing the burning rates of HMX propellants

1998 ◽  
Vol 115 (3) ◽  
pp. 406-416 ◽  
Author(s):  
Kuldeep Prasad ◽  
Richard A. Yetter ◽  
Mitchell D. Smooke
Keyword(s):  
Eigenvalue Method ◽  
Burning Rates

An Eigenvalue Method for Computing the Burning Rates of RDX Propellants

1997 ◽  
Vol 124 (1-6) ◽  
pp. 35-82 ◽  
Author(s):  
KULDEEP PRASAD ◽  
RICHARD A. YETTER ◽  
MITCHELL D. SMOOKE
Keyword(s):  
Eigenvalue Method ◽  
Burning Rates

Correlation of Burning Rates and Energy Transport Mechanisms in Open and Enclosed Liquid Pool Fires

1991 ◽  
Author(s):  
David E. Ramaker ◽  
K. C. Adiga ◽  
H. Zhang ◽  
M. Pivovarov ◽  
S. W. Baek
Keyword(s):  
Energy Transport ◽  
Liquid Pool ◽  
Pool Fires ◽  
Transport Mechanisms ◽  
Burning Rates

Prediction of Advanced Nitramine Propellant Burning Rates with the CYCLOPS Code

2003 ◽  
Author(s):  
Martin S. Miller ◽  
William R. Anderson
Keyword(s):  
Burning Rates

scholarly journals A Numerical Comparison of the Sensitivity of the Geometric Mean Method, Eigenvalue Method, and Best–Worst Method

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 554
Author(s):  
Jiří Mazurek ◽  
Radomír Perzina ◽  
Jaroslav Ramík ◽  
David Bartl
Keyword(s):  
Research Method ◽  
Geometric Mean ◽  
Pairwise Comparisons ◽  
Numerical Comparison ◽  
Priority Vector ◽  
Eigenvalue Method ◽  
Fundamental Scale ◽  
Matrix Vector ◽  
Best Worst Method ◽  
Order Violation

In this paper, we compare three methods for deriving a priority vector in the theoretical framework of pairwise comparisons—the Geometric Mean Method (GMM), Eigenvalue Method (EVM) and Best–Worst Method (BWM)—with respect to two features: sensitivity and order violation. As the research method, we apply One-Factor-At-a-Time (OFAT) sensitivity analysis via Monte Carlo simulations; the number of compared objects ranges from 3 to 8, and the comparison scale coincides with Saaty’s fundamental scale from 1 to 9 with reciprocals. Our findings suggest that the BWM is, on average, significantly more sensitive statistically (and thus less robust) and more susceptible to order violation than the GMM and EVM for every examined matrix (vector) size, even after adjustment for the different numbers of pairwise comparisons required by each method. On the other hand, differences in sensitivity and order violation between the GMM and EMM were found to be mostly statistically insignificant.

scholarly journals Modelling and Stability Analysis of Articulated Vehicles

2021 ◽  
Vol 11 (8) ◽  
pp. 3663
Author(s):  
Tianlong Lei ◽  
Jixin Wang ◽  
Zongwei Yao
Keyword(s):  
Stability Analysis ◽  
Critical Velocity ◽  
Equations Of State ◽  
Steering System ◽  
Analysis Model ◽  
Nonlinear Dynamic Model ◽  
Equilibrium Equations ◽  
Eigenvalue Method ◽  
Articulated Vehicles ◽  
The Stability

This study constructs a nonlinear dynamic model of articulated vehicles and a model of hydraulic steering system. The equations of state required for nonlinear vehicle dynamics models, stability analysis models, and corresponding eigenvalue analysis are obtained by constructing Newtonian mechanical equilibrium equations. The objective and subjective causes of the snake oscillation and relevant indicators for evaluating snake instability are analysed using several vehicle state parameters. The influencing factors of vehicle stability and specific action mechanism of the corresponding factors are analysed by combining the eigenvalue method with multiple vehicle state parameters. The centre of mass position and hydraulic system have a more substantial influence on the stability of vehicles than the other parameters. Vehicles can be in a complex state of snaking and deviating. Different eigenvalues have varying effects on different forms of instability. The critical velocity of the linear stability analysis model obtained through the eigenvalue method is relatively lower than the critical velocity of the nonlinear model.

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