Multi-objective optimization of asymmetric v-shaped ribs in a cooling channel using CFD, artificial neural networks and genetic algorithms

Damavandi, Mohammad Darvish; Safikhani, Hamed; Yahyaabadi, Mojtaba

doi:10.1007/s40430-016-0698-0

Cited by 16 publications

(2 citation statements)

References 25 publications

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“…Convolutional neural networks were first applied to image data, and later researchers found that they can also achieve good results on text data. Especially in the case of large datasets, text features can be extracted more fully and the feature dimension can be reduced [ 15 , 16 ]. The convolutional neural network consists of a convolutional layer, pooling layers, and a fully connected layer, as shown in Figure 7 .…”

Section: Deep Learning Methods Based On the Passing Methodsmentioning

confidence: 99%

Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning

Wang

Xia

2022

Computational Intelligence and Neuroscience

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Deep learning is a new direction in the field of machine learning, which learns the inherent laws and levels of data sample representation. The information gained during learning plays an important role in interpreting data such as text, images, and speech. This paper aims to study how to analyze and study the physical energy consumption of passers and receivers in different passing methods in football based on deep learning. This paper proposes the problem of physical energy consumption, which is based on deep learning, then elaborates on the concept of deep learning and related algorithms, and designs and analyzes the case of physical energy consumption of athletes. The experimental results showed that the average heart rhythm (184.35) of the subjects in the first and third experiments was more than twenty points higher than the average heart rhythm (159.85) of the kickers in the second and fourth experiments. Different passing styles have significantly different effects on the physical energy expenditure of players and defensive receivers.

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Section: Deep Learning Methods Based On the Passing Methodsmentioning

confidence: 99%

Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning

Wang

Xia

2022

Computational Intelligence and Neuroscience

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“…They are now widely used in the structural design process. [36][37][38][39][40][41] It is a robust global optimization algorithm that does not require gradient information and does not easily fall into a local optimum. In addition, it is not constrained by the continuity of design variables and does not require a starting point at the beginning of the optimization process.…”

Section: Multi-island Genetic Optimization Algorithmmentioning

confidence: 99%

Optimization design of curved outrigger structure based on buckling analysis and multi-island genetic algorithm

et al. 2021

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In the present work, the working state of the crane leg is analyzed and discussed, and its structure is optimized. SolidWorks software is used for modeling; ANSYS software is used for finite element analysis. First of all, the constrained finite element method (CFEM) is used to analyze the linear eigenvalue buckling and geometric nonlinear buckling of outriggers with different cross-section shapes. Prove that the curved leg has certain advantages in buckling. At the same time, analyzing the leg along a different path of buckling condition and stress changes provide the basis for the design of the subsequent reinforcement. After selecting the best cross-section shape of the outrigger, the agent-based multi-island genetic algorithm is used to optimize the structural parameters of the outrigger under the transverse stiffened plate reinforced structure and the longitudinally stiffened plate reinforced structure respectively. It is proved that the outrigger with the transverse stiffened plate has a significant effect in improving the bearing capacity and in the lightweight of the structure. Finally, the gap between the movable leg and the fixed leg was changed, the stress of different gaps was analyzed by using the finite element method, and the appropriate gap value was selected according to the high-order fitting curve.

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Numerical investigation on location of protrusions and dimples during slot jet impingement on a concave surface using hybrid ANN–GA

Singh

2020

Heat Trans

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Numerical simulations using ANSYS Fluent 17.2 are explored for a detailed discussion on jet impingement over a compound dimpled and protrusioned concave surface. Previous researchers have proved that both dimples and protrusions help in heat transfer augmentation. However, the combined effect of dimple and protrusion over a concave surface is still not studied, which may show a significant improvement in heat transfer. Therefore, the present study is devoted to the alternate location of dimple and protrusion over a concave surface for enhancement in impingement heat transfer. Simulations are performed for several arrangements of dimples and protrusions over a concave surface. It is noticed that a particular arrangement of dimples and protrusions leads to an increase in heat transfer compared with a fully protruded or fully dimpled concave surface. Furthermore, it is also noticed that protrusions/dimples at the stagnation region degrade overall impingement heat transfer. The wall shear stress profile is found to be similar to its corresponding local Nusselt number profile. Lastly, the optimal location of dimples and protrusions is predicted using an artificial neural network and a specially formulated discrete version of genetic algorithm.

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Multi-objective optimization of asymmetric v-shaped ribs in a cooling channel using CFD, artificial neural networks and genetic algorithms

Cited by 16 publications

References 25 publications

Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning

Influence of Different Passing Methods of Physical Fitness in Football Using Deep Learning

Optimization design of curved outrigger structure based on buckling analysis and multi-island genetic algorithm

Numerical investigation on location of protrusions and dimples during slot jet impingement on a concave surface using hybrid ANN–GA

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