EXACT METHODS OF LINEAR PROGRAMMING FOR CHOOSING ROCK FAILURE CONDITIONS.

2013 ◽  
Vol 7 (11) ◽  
pp. 52-57
Author(s):  
Oleg Markovich Terentiev ◽  
◽  
Anton Iosifovich Kleshchov ◽  
Keyword(s):  
Linear Programming ◽  
Rock Failure ◽  
Exact Methods ◽  
Failure Conditions

scholarly journals The Impact Behavior between Coal Gangue Particles and the Tail Beam Based on Rock Failure

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Zhengyuan Xin ◽  
Qingliang Zeng ◽  
Yang Yang
Keyword(s):  
Energy Consumption ◽  
Impact Force ◽  
Rock Failure ◽  
Coal Gangue ◽  
Dynamic Responses ◽  
Particle Model ◽  
Brittle Damage ◽  
Failure Conditions ◽  
Fracture Particle ◽  
The Impact

In top coal caving mining, common impact occurs between coal gangue particles and tail beam. Little attention has been paid to the effects of coal gangue particles failure on impact force and tail beam response theoretically, numerically, and experimentally. This paper aims to reveal the influence of coal gangue particles failure on the impact effect of tail beam. First, this paper incorporates the theory of rock failure and energy consumption to assess the impact process of coal gangue particles on the tail beam. A new model to simulate the actual failure conditions of rock particles was developed: the brittle damage-fracture particle model. By comparing damage phenomena and simulation data, the brittle damage-fracture particle model was proved to be correct. Based on this model, a dynamic simulation of brittle coal gangue particles impacting the tail beam was conducted. Then, the dynamic responses of the particles and tail beam were analyzed. The results show that particle failure significantly affects the impact force and dynamic response of the tail beam. The impact effects of coal and gangue particles on the tail beam and their failure energy consumption also differed significantly. This paper stresses the importance of coal gangue particle failure conditions for research on top coal caving mining. Theoretical support is provided for the research of coal gangue identification technology based on the tail beam vibration signal.

Piecewise Linear Function Fitting via Mixed-Integer Linear Programming

2020 ◽  
Vol 32 (2) ◽  
pp. 507-530 ◽  
Author(s):  
Steffen Rebennack ◽  
Vitaliy Krasko
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Piecewise Linear ◽  
Discrete Data ◽  
Mixed Integer ◽  
Exact Methods ◽  
Function Fitting ◽  
Integer Quadratic Programming ◽  
Univariate Functions

Piecewise linear (PWL) functions are used in a variety of applications. Computing such continuous PWL functions, however, is a challenging task. Software packages and the literature on PWL function fitting are dominated by heuristic methods. This is true for both fitting discrete data points and continuous univariate functions. The only exact methods rely on nonconvex model formulations. Exact methods compute continuous PWL function for a fixed number of breakpoints minimizing some distance function between the original function and the PWL function. An optimal PWL function can only be computed if the breakpoints are allowed to be placed freely and are not fixed to a set of candidate breakpoints. In this paper, we propose the first convex model for optimal continuous univariate PWL function fitting. Dependent on the metrics chosen, the resulting formulations are either mixed-integer linear programming or mixed-integer quadratic programming problems. These models yield optimal continuous PWL functions for a set of discrete data. On the basis of these convex formulations, we further develop an exact algorithm to fit continuous univariate functions. Computational results for benchmark instances from the literature demonstrate the superiority of the proposed convex models compared with state-of-the-art nonconvex models.

Structures in the Universe by Exact Methods

2009 ◽  
Author(s):  
Krzysztof Bolejko ◽  
Andrzej Krasinski ◽  
Charles Hellaby ◽  
Marie-Noelle Celerier
Keyword(s):  
Exact Methods ◽  
The Universe

Elementary Linear Programming (2nd edition)

1997 ◽  
Vol 48 (7) ◽  
pp. 757-758
Author(s):  
B Kolman ◽  
R E Beck ◽  
M J Panik
Keyword(s):  
Linear Programming

Robust state estimation in power systems using sparse linear programming

1985 ◽  
Vol 132 (3) ◽  
pp. 123 ◽  
Author(s):  
B.C. Clewer ◽  
M.R. Irving ◽  
M.J.H. Sterling
Keyword(s):  
Linear Programming ◽  
Power Systems ◽  
State Estimation

Optimal approaches to manage power system decarbonation

2020 ◽  
Vol 64 (1-4) ◽  
pp. 1447-1452
Author(s):  
Vincent Mazauric ◽  
Ariane Millot ◽  
Claude Le Pape-Gardeux ◽  
Nadia Maïzi
Keyword(s):  
Free Energy ◽  
Linear Programming ◽  
Phase Transitions ◽  
Power System ◽  
Energy System ◽  
Energy Sources ◽  
Low Carbon ◽  
Faraday’S Law ◽  
Optimal Description ◽  
Low Carbon Technologies

To overcome the negative environemental impact of the actual power system, an optimal description of quasi-static electromagnetics relying on a reversible interpretation of the Faraday’s law is given. Due to the overabundance of carbon-free energy sources, this description makes it possible to consider an evolution towards an energy system favoring low-carbon technologies. The management for changing is then explored through a simplified linear-programming problem and an analogy with phase transitions in physics is drawn.

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