scholarly journals Three‐dimensional crustal structure in central Taiwan from gravity inversion with a parallel genetic algorithm

Geophysics ◽  
2004 ◽  
Vol 69 (4) ◽  
pp. 917-924 ◽  
Author(s):  
Jian Zhang ◽  
Chi‐Yuen Wang ◽  
Yaolin Shi ◽  
Yongen Cai ◽  
Wu‐Cheng Chi ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Gravity Anomaly ◽  
Seismic Velocity ◽  
Empirical Relation ◽  
Initial Density ◽  
Model Space ◽  
Element Model ◽  
Gravity Inversion ◽  
Central Taiwan

The genetic algorithm method is combined with the finite‐element method for the first time as an alternative method to invert gravity anomaly data for reconstructing the 3D density structure in the subsurface. The method provides a global search in the model space for all acceptable models. The computational efficiency is significantly improved by storing the coefficient matrix and using it in all forward calculations, then by dividing the region of interest into many subregions and applying parallel processing to the subregions. Central Taiwan, a geologically complex region, is used as an example to demonstrate the utility of the method. A crustal block 120 × 150 km2 in area and 34 km in thickness is represented by a finite‐element model of 76 500 cubic elements, each 2 × 2 × 2 km3 in size. An initial density model is reconstructed from the regional 3D tomographic seismic velocity using an empirical relation between velocity and density. The difference between the calculated and the observed gravity anomaly (i.e., the residual anomaly) shows an elongated minimum of large magnitude that extends along the axis of the Taiwan mountain belt. Among the interpretive models tested, the best model shows a crustal root extending to depths of 50 to 60 km beneath the axis of the Western Central and Eastern Central Ranges with a density contrast of 400 or 500 kg/m3 across the Moho. Both predictions appear to be supported by independent seismological and laboratory evidence.

scholarly journals Optimization research on arc height of running surface based on reducing partial wear of straddle-type monorail vehicle running wheel tire

2021 ◽  
Vol 13 (10) ◽  
pp. 168781402110534
Author(s):  
XiaoXia Wen ◽  
ZiXue Du ◽  
Liang Chen
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Finite Element Model ◽  
Simulation Optimization ◽  
Element Model ◽  
Multidisciplinary Optimization ◽  
Improved Genetic Algorithm ◽  
Running Wheel ◽  
Contact State ◽  
Running Wheels

This article proposes an ideal of reducing the partial wear of the running wheels by optimizing the arc height of the running surface to improve the wheel-rail contact state. To realize this idea, two kinds of concave and convex running surfaces were designed, the “running wheel-rail beam” finite element model of three kinds of rail surfaces of concave, convex, and plane were established. Taking the arc height of the running surface as the design variable, the total friction work and the friction work deviation (FWD) value as the dual optimization goal, an optimization model of arc height of running surface was established based on finite element model and multidisciplinary optimization platform Modefrontier. An improved genetic algorithm was used and an co-simulation optimization mode was put forward in the optimization. The optimization results show that when the concave height of the inner running surface is 22.62 mm, the total friction work and the FWD values are reduced by 11% and 11.8% respectively; When the convex height of the outer running surface is 11.81 mm, the objection values are reduced by 4.9% and 32.1% respectively. An ideal running surface was obtained and the life of the running wheel was extended by the research.

Application of a Shell-Spring Model for the Optimization of Radial Tire Contour Using a Genetic Algorithm

2003 ◽  
Vol 31 (1) ◽  
pp. 39-63 ◽  
Author(s):  
G. Unnithan ◽  
R. KrishnaKumar ◽  
A. Prasad
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Optimization Problems ◽  
Optimization Procedure ◽  
Element Model ◽  
Spring Model ◽  
New Approach ◽  
Shell Elements ◽  
Complex Optimization ◽  
Profile Optimization

Abstract Optimization gives a new facet to design and development of tires. A new approach to the tire profile optimization is proposed in this study. The optimization procedure is integrated with a simple shell-spring finite element model for faster evaluation. In the shell-spring model, the shell elements represent the tire carcass, whereas the tread is represented by the spring elements. This is applied for the optimization of the tire contour for better maneuverability. The genetic algorithm, an evolutionary optimization procedure that is robust and efficient in solving complex optimization problems, is chosen. A new tire contour is obtained that improves tire maneuverability by increasing the sidewall belt tension.

Genetic Optimization for the Design of a Machine Tool Slide Table for Reduced Energy Consumption

2021 ◽  
Vol 143 (10) ◽  
Author(s):  
Matthew J. Triebe ◽  
Fu Zhao ◽  
John W. Sutherland
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Energy Consumption ◽  
Machine Tool ◽  
Machine Tools ◽  
Sandwich Panel ◽  
Sustainable Manufacturing ◽  
Element Model ◽  
Genetic Optimization ◽  
Use Phase

Abstract Reducing the energy consumption of machine tools is important from a sustainable manufacturing perspective. Much of a machine tool’s environmental impact comes from the energy it consumes during its use phase. To move elements of a machine tool requires energy, and if the mass of those elements can be reduced, then the required energy would be reduced. Therefore, this paper proposes a genetic algorithm to design lightweight machine tools to reduce their energy consumption. This is specifically applied to optimize the structure of a machine tool slide table, which moves throughout the use of the machine tool, with the goal of reducing its mass without sacrificing its stiffness. The table is envisioned as a sandwich panel, and the proposed genetic algorithm optimizes the core of the sandwich structure while considering both mass and stiffness. A finite element model is used to assess the strength of the proposed designs. Finite element results indicate that the strength of the lightweight tables is comparable with a traditional table design.

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