Slope Stability Analysis Using Genetic Simulated Annealing Algorithm in Conjunction with Finite Element Method

Cen, Weijun; Luo, Jiarui; Yu, Jishun

doi:10.1007/s12205-020-2051-5

Cited by 14 publications

(6 citation statements)

References 15 publications

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“…It can accept inferior solutions to a limited extent to not fall into the local optimum. e rule of thumb requires the algorithm to search for the most significant possible solution space in a reasonable time, with only a sufficiently large time [27,28]. is may lead to too long execution time, making the simulated annealing algorithm infeasible.…”

Section: Water-saving Control Based On Simulatedmentioning

confidence: 99%

Water Saving Control of Turfgrass Irrigation Robot Using Genetic Simulated Annealing Algorithm

Han

2021

Mobile Information Systems

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Artificial intelligence through the robotic system offers a solution to the quest for an autonomous system with high cutting efficiency for lawn mowing. Because of the current trimming and maintenance operations on grasslands and gardens, it is essential to develop autonomous and efficient lawn pruning electromechanical equipment. This paper describes the design and construction of a high-performance automated grass trimming and irrigating robot. This device cuts and irrigates grass automatically with little human intervention. A genetic simulated annealing algorithm was employed to optimize motor parameters, specifically design a set of mowing mechanisms and mowing height adjustment system. The prototype was tested, which mainly includes the running status evaluation of the walking module, the mowing module, the cutter head lifting module, and the collision detection module. This robot can save water while watering the lawns, reduce labor costs, and improve mowing efficiency. We note that the proposed system can be implemented on a large scale under natural conditions in the future, which will be helpful in robotics applications and cutting grass on lawns and playing grounds.

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Section: Water-saving Control Based On Simulatedmentioning

confidence: 99%

Water Saving Control of Turfgrass Irrigation Robot Using Genetic Simulated Annealing Algorithm

Han

2021

Mobile Information Systems

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“…They believe that compared with the golden section method based on the finite element calculation of the same stress field, the genetic simulated annealing algorithm is more accurate and efficient in searching for the critical slip surface of the slope of the earth-rock dam. The measurement is not in place [2]. Reddy et al adopt a new method based on the hybrid technology of genetic algorithm and simulated annealing.…”

Section: Introductionmentioning

confidence: 99%

The Implementation of Multiobjective Flexible Workshop Scheduling Based on Genetic Simulated Annealing-Inspired Clustering Algorithm

Huang

Wang

2022

Wireless Communications and Mobile Computing

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Multiobjective flexible workshop scheduling is an important subject to improve resource utilization and production efficiency and enhance the competitiveness of enterprises. As the situation of resource constraints becomes more and more severe, the problem of companies rationally allocating limited resources in production is becoming more and more serious. Today, the manufacturing industry widely adopts advanced manufacturing modes such as computer-integrated manufacturing and intelligent manufacturing, but in these semi-intelligent manufacturing modes with a high degree of uncertainty and a high degree of personnel dependence, it is difficult to adapt to the work of large-scale production. Therefore, suitable clustering algorithms are urgently needed to help solve these problems, and this paper selects a clustering algorithm based on the genetic simulation annealing algorithm. This article is aimed at studying the problem of efficiency improvement in the production process of large-scale manufacturing and at finding a stronger and more effective production mode for the manufacturing industry. Firstly, this paper introduces the basic principles of simulated annealing genetic algorithm and regularized clustering algorithm. These algorithms have excellent performance in searching for global optimal solutions. They can be constantly tested and computed to keep the calculation results close to the global optimal solution. In this paper, the K -means clustering algorithm is used to select the shortest completion time to represent the clustering target. According to the minimum distance principle, the machine, workpiece, and other objects are input into the clustering of the algorithm, and the K -means algorithm will send out the sorting plan. Therefore, a multiobjective flexible job shop scheduling model based on genetic simulated annealing algorithm and clustering algorithm is established. Then, by using hypothetical production data to simulate the operation of the workshop, the scheduling model was applied to conduct a deduction and empirical comparative study. The experimental results showed that the model shortened the completion time of the workpiece by 4.4% and increased the average load rate of the machine by 10%.

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“…However, due to the limitation of the technical level during the construction period or the comprehensive impact of the later transportation and maintenance, there are still hidden dangers in the seepage stability of a large number of reservoir dams. e three-dimensional nite element stress-seepage coupled calculation method is a preferred method to study the dam instability caused by seepage, and the method has been widely used in the analysis of the deformation and stability of Earth rock dams [12][13][14][15]. However, only are the Earth rock dams in the design stage or in safe operation mentioned in previous studies, but the Earth rock dam with leakage has not been studied yet.…”

Section: Introductionmentioning

confidence: 99%

Deformation and Stability Analysis of a Core Rockfill Dam with Leakage

Chen¹,

Lin²,

2022

Shock and Vibration

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The No. 4 clay core rockfill dam of the Gongming Reservoir experienced leakages when the reservoir water level was low. To analyze the leakage causes, a series of seepage tests were conducted on the dam materials in this paper. And a three-dimensional finite element stress-seepage coupled calculation model of the dam was established to study the deformation and stresses of the dam under the condition of normal storage water level and the sharp drop in the storage level. The test results show that the permeability coefficient of the clay core material is close to that of the dam shell material, resulting in the leakage of the dam under the condition of the low-water level. The simulation results show that the dam deforms a little under the condition of normal storage water level and the sharp drop in the storage level, and the stress distribution under the condition of the sharp drop in the storage level is basically consistent with that under the condition of normal storage water level. The safety factors of the dam under the two conditions meet the requirements of the specification, but the margin of the safety factor is small.

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Slope Stability Analysis Using Genetic Simulated Annealing Algorithm in Conjunction with Finite Element Method

Cited by 14 publications

References 15 publications

Water Saving Control of Turfgrass Irrigation Robot Using Genetic Simulated Annealing Algorithm

Water Saving Control of Turfgrass Irrigation Robot Using Genetic Simulated Annealing Algorithm

The Implementation of Multiobjective Flexible Workshop Scheduling Based on Genetic Simulated Annealing-Inspired Clustering Algorithm

Deformation and Stability Analysis of a Core Rockfill Dam with Leakage

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