Identification of parameters for air permeability of shotcrete tunnel lining using a genetic algorithm

1999 ◽  
Vol 25 (1) ◽  
pp. 1-24 ◽  
Author(s):  
A.A Javadi ◽  
R Farmani ◽  
V.V Toropov ◽  
C.P.M Snee
Keyword(s):  
Genetic Algorithm ◽  
Air Permeability ◽  
Tunnel Lining ◽  
Identification Of Parameters

A Genetic Algorithm for Predicting Pore Geometry Based on Air Permeability Measurements

2005 ◽  
Vol 4 (2) ◽  
pp. 389-397 ◽  
Author(s):  
E. Unsal ◽  
J. H. Dane ◽  
G. V. Dozier
Keyword(s):  
Genetic Algorithm ◽  
Air Permeability ◽  
Pore Geometry

PERMEABILITY OF TUNNEL LINING WITH AIR/WATER BUBBLES ON CONCRETE SURFACE

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
Tomoyuki Maeda ◽  
Hiroki Honma ◽  
Masayuki Hirano ◽  
Isamu Yoshitake
Keyword(s):  
Gas Permeability ◽  
Plain Concrete ◽  
Concrete Surface ◽  
Air Permeability ◽  
Tunnel Lining ◽  
Distribution Area ◽  
Concrete Lining ◽  
Bubble Distribution ◽  
Logarithmic Curve ◽  
The Aesthetic

Air and water bubbles are likely to remain on concrete sidewalls in tunnel linings, because the sidewalls are generally constructed with a greater slope than a right angle. The bubbles negatively influence the aesthetic of the concrete lining. In addition, concrete with a lot of large bubbles may decrease durability, such as air permeability. Although most tunnel lining is constructed as plain concrete without reinforcement, the low permeability may affect the maintenance and long-term durability of the tunnel. The study aims to examine the effect of bubble distributions on the permeability of concrete lining. Concrete specimens including various bubble distributions are prepared by using variable angle-forms in a laboratory test. Furthermore, the bubble distribution (area ratio) and the permeability are examined in two actual tunnels. This paper presents a relationship between bubble distribution and air permeability based on these tests. The results show that the relationship is a logarithmic curve of the bubble rate and gas permeability.

A MODEL OF PROCESS STEAM NETWORK IN A STEEL PLANT WITH IDENTIFICATION OF PARAMETERS BY A GENETIC ALGORITHM

2021 ◽  
pp. 1-17
Author(s):  
Gabriel Nazareth Guedes Alcoforado ◽  
Valter Barbosa de Oliveira Junior ◽  
Gustavo Maia de Almeida ◽  
Leandro Colombi Resendo ◽  
Marco Antonio de Souza Leite Cuadros
Keyword(s):  
Genetic Algorithm ◽  
Steel Plant ◽  
Identification Of Parameters

Identification of Parameters and Time Delays of Continuous Systems using the Genetic Algorithm

1994 ◽  
Vol 27 (8) ◽  
pp. 1573-1578 ◽  
Author(s):  
Zi-Jiang Yang ◽  
Tomohiro Hachino ◽  
Teruo Tsuji ◽  
Setsuo Sagara
Keyword(s):  
Genetic Algorithm ◽  
Time Delays ◽  
Continuous Systems ◽  
Identification Of Parameters

A model of process steam network in a steel plant with identification of parameters by a genetic algorithm

2016 ◽  
Author(s):  
Gabriel Nazareth Guedes Alcoforado ◽  
Valter Barbosa de Oliveira ◽  
Gustavo Maia de Almeida ◽  
Marco Antonio de Souza Leite Cuadros
Keyword(s):  
Genetic Algorithm ◽  
Steel Plant ◽  
Identification Of Parameters

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy
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