scholarly journals Determination of Multilayer Soil Strength Parameters Using Genetic Algorithm

2018 ◽  
Vol 4 (10) ◽  
pp. 2383 ◽  
Author(s):  
Seyyed Mohammad Hashemi ◽  
Iraj Rahmani
Keyword(s):  
Genetic Algorithm ◽  
Lateral Displacement ◽  
Error Function ◽  
Back Analysis ◽  
Soil Strength ◽  
Strength Parameters ◽  
Analysis Process ◽  
Project Monitoring ◽  
The Difference ◽  
Python Programming

This paper employs a back analysis method to determine soil strength parameters of the Mohr-Coulomb model from in situ geotechnical measurements. The lateral displacement of a soil nailed wall retaining an excavation in Tehran city used as a criterion for the back analysis. For this purpose, a genetic algorithm is applied as an optimization algorithm to minimize the error function, which can perform the back analysis process. When the accuracy of modeling is verified, the back analysis is performed automatically by creating a link between genetic algorithm in MATLAB and Abaqus software using Python programming language. This paper demonstrated that the genetic algorithm is a particularly suitable tool to determine 9 soil strength parameters simultaneously for 3 soil layers of the project site to decrease the difference of lateral displacement between the results of project monitoring and numerical analysis. The soil strength parameters have increased, with the most changes in Young's modulus of the first to third layers as the most effective parameter, 49.45%, 61.67% and 64.35% respectively. The results can be used in advanced engineering analyses and professional works.

scholarly journals Numerical Comparison of the Performance of Genetic Algorithm and Particle Swarm Optimization in Excavations

2018 ◽  
Vol 4 (9) ◽  
pp. 2186 ◽  
Author(s):  
Seyyed Mohammad Hashemi ◽  
Iraj Rahmani
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Back Analysis ◽  
Friction Angle ◽  
Soil Strength ◽  
Numerical Comparison ◽  
Strength Parameters ◽  
Swarm Optimization ◽  
Python Programming

Today, the back analysis methods are known as reliable and effective approaches for estimating the soil strength parameters in the site of project. The back analysis can be performed by genetic algorithm and particle swarm optimization in the form of an optimization process. In this paper, the back analysis is carried out using genetic algorithm and particle swarm optimization in order to determine the soil strength parameters in an excavation project in Tehran city. The process is automatically accomplished by linking between MATLAB and Abaqus software using Python programming language. To assess the results of numerical method, this method is initially compared with the results of numerical studies by Babu and Singh. After the verification of numerical results, the values of the three parameters of elastic modulus, cohesion and friction angle (parameters of the Mohr–Coulomb model) of the soil are determined and optimized for three soil layers of the project site using genetic algorithm and particle swarm optimization. The results optimized by genetic algorithm and particle swarm optimization show a decrease of 72.1% and 62.4% in displacement differences in the results of project monitoring and numerical analysis, respectively. This research shows the better performance of genetic algorithm than particle swarm optimization in minimization of error and faster success in achieving termination conditions.

Back Analysis of Material Parameters of Concrete Dam Using Genetic Algorithm

2012 ◽  
Vol 562-564 ◽  
pp. 1955-1958
Author(s):  
Jin Bao Liu ◽  
Shou Ju Li ◽  
Wei Zhu
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Optimization Problem ◽  
Back Analysis ◽  
Water Level Change ◽  
Concrete Dam ◽  
Material Parameters ◽  
Level Change ◽  
Inversion Procedure ◽  
The Difference

The inverse problem of parameter identification is deal with by minimizing an objective function that contains the difference between observed and calculated dam displacements. The optimization problem of minimizing objective function is solved with genetic algorithm. The calculated dam displacements are simulated by using finite element method according to water level change acting on dam upstream. The practical dam displacements are observed on the dam crest. The investigation shows that the forecasted dam displacements agree well with observed ones. The effectiveness of proposed inversion procedure is validated.

scholarly journals The Application of Improved Genetic Algorithm to the Back Analysis of Foundation Pit Construction

2021 ◽  
Vol 676 (1) ◽  
pp. 012124
Author(s):  
Kai Peng ◽  
Yuefei Zhou ◽  
Yaolai Liu ◽  
Liangliang Ma ◽  
Yi Xie ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Back Analysis ◽  
Improved Genetic Algorithm ◽  
Foundation Pit

Closed-Form Correlation of Buildings Energy Use With Key Design Parameters Calibrated Using a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Raed I. Bourisli ◽  
Adnan A. AlAnzi
Keyword(s):  
Genetic Algorithm ◽  
Closed Form ◽  
Energy Use ◽  
Building Design ◽  
Office Buildings ◽  
Design Parameters ◽  
Wide Range ◽  
Variable Function ◽  
Real Coded Genetic Algorithm ◽  
The Difference

This work aims at developing a closed-form correlation between key building design variables and its energy use. The results can be utilized during the initial design stages to assess the different building shapes and designs according to their expected energy use. Prototypical, 20-floor office buildings were used. The relative compactness, footprint area, projection factor, and window-to-wall ratio were changed and the resulting buildings performances were simulated. In total, 729 different office buildings were developed and simulated in order to provide the training cases for optimizing the correlation’s coefficients. Simulations were done using the VisualDOE TM software with a Typical Meteorological Year data file, Kuwait City, Kuwait. A real-coded genetic algorithm (GA) was used to optimize the coefficients of a proposed function that relates the energy use of a building to its four key parameters. The figure of merit was the difference in the ratio of the annual energy use of a building normalized by that of a reference building. The objective was to minimize the difference between the simulated results and the four-variable function trying to predict them. Results show that the real-coded GA was able to come up with a function that estimates the thermal performance of a proposed design with an accuracy of around 96%, based on the number of buildings tested. The goodness of fit, roughly represented by R2, ranged from 0.950 to 0.994. In terms of the effects of the various parameters, the area was found to have the smallest role among the design parameters. It was also found that the accuracy of the function suffers the most when high window-to-wall ratios are combined with low projection factors. In such cases, the energy use develops a potential optimum compactness. The proposed function (and methodology) will be a great tool for designers to inexpensively explore a wide range of alternatives and assess them in terms of their energy use efficiency. It will also be of great use to municipality officials and building codes authors.

AN EVOLUTIONARY APPROACH FOR IMPUTING MISSING DATA IN TIME SERIES

2010 ◽  
Vol 19 (01) ◽  
pp. 107-121 ◽  
Author(s):  
JUAN CARLOS FIGUEROA GARCÍA ◽  
DUSKO KALENATIC ◽  
CESAR AMILCAR LÓPEZ BELLO
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Missing Data ◽  
Genetic Structure ◽  
Evolutionary Algorithm ◽  
Fitness Function ◽  
Error Function ◽  
Missing Observations ◽  
Mean And Variance ◽  
Methodological Aspects

This paper presents a proposal based on an evolutionary algorithm for imputing missing observations in time series. A genetic algorithm based on the minimization of an error function derived from their autocorrelation function, mean, and variance is presented. All methodological aspects of the genetic structure are presented. An extended description of the design of the fitness function is provided. Four application examples are provided and solved by using the proposed method.

Condition Monitoring Technology for Connecting Part and Sliding Part of Reciprocating Compressor

2017 ◽  
Author(s):  
Yoshifumi Mori ◽  
Takashi Saito ◽  
Yu Mizobe
Keyword(s):  
Mathematical Model ◽  
Natural Frequencies ◽  
Error Function ◽  
Connecting Rod ◽  
Value Analysis ◽  
Before And After ◽  
The Difference ◽  
Bending Modes ◽  
Parameter Values ◽  
The Mathematical Model

We focused on vibration characteristics of reciprocating compressors and constructed the mathematical model to calculate the natural frequencies and modes for crank angles and proposed a method to estimate the degree and the suspicious portion of failure by difference of temporal parameter values obtained using measuring data in operation and the mathematical model. In this paper, according to the proposed method, a case study is carried out using the field data, where the data were acquired before and after the failures occurred in the connecting parts of connecting rod, to prospect the difference between each parameter value for two operating states. Inspecting resonant characteristics each in the frequency response data relating to the natural frequencies for bending modes of the piston rod, we determined two resonant frequencies, which could correspond to the 1st and 2nd mode about bending of the piston rod. To equate the calculated each natural frequency from eigen value analysis based on the proposed model with each resonant frequency, we define the error function for the identified problem, namely optimum problem. In the identified results, it is found that some parameter values have much difference and the corresponding failure could occur around the connecting rod. We could show the possibility to detect both the change of the parameter values and the deterioration parts for two different kinds of the operating states by our proposed method.

Side wind and tank speed influence on lateral displacement of the projectile

2021 ◽  
pp. 24-29
Author(s):  
M. Sorokatiy ◽  
M. Voytovych ◽  
L. Velychko ◽  
O. Moskalova
Keyword(s):  
Mathematical Model ◽  
Wind Speed ◽  
Lateral Displacement ◽  
Longitudinal Section ◽  
Projectile Velocity ◽  
Air Density ◽  
Dimensionless Coefficient ◽  
Air Resistance ◽  
The Difference ◽  
Firing Distance

This article indicates the scope of the formula for determining the magnitude of the lateral displacement of the projectile under the action of crosswind, which is used in the compilation of firing tables. This formula is valid under the following conditions: the force of frontal air resistance to the motion of the projectile is proportional to the its velocity squared; wind speed components are much smaller than the horizontal component of projectile velocity; the projectile velocity projections on the Oy and Oz axes are much smaller than the projections on the Ox axis; the dimensionless coefficient of resistance and the magnitude of the crosswind are constant values. However, in reality, the force of frontal air resistance to the motion of the projectile is only sometimes proportional to the its velocity squared; the projectile velocity projections on the Oz axis may be are much smaller than the projections on the Ox axis and may even be greater than it; the coefficient of resistance is depends on the value of the Makh number, so it can be considered constant only when shooting at short distances. The authors propose a mathematical model for determining the magnitude of the lateral displacement of the projectile under the action of crosswinds. It is believed that the force of the crosswind on the projectile depends on the following factors: air density; the maximum area of the longitudinal section of the projectile; the difference between the value of the lateral component of the wind speed and the speed of the lateral displacement of the projectile, which is raised to a certain power. The magnitude of the values of the lateral displacement of the projectile under the action of the crosswind when shooting at short distances, determined based on the proposed mathematical model, slightly differ from the values of the lateral displacement specified in the firing tables. However, with increasing firing distance, the difference between these values is constantly increasing and the value of the lateral displacement of the projectile determined theoretically is much larger than indicated in the firing tables. In addition, in this research the influence of the tank velocity on the value of the projectile lateral displacement taking into account the action of the crosswind is studied.

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