Porosity Prediction of Granular Materials through Discrete Element Method and Back Propagation Neural Network Algorithm

Liu, Yu; Li, Miaomiao; Su, Peifeng; Ma, Biao; You, Zhanping

doi:10.3390/app10051693

Cited by 8 publications

(2 citation statements)

References 20 publications

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“…The characteristics of the user's travel target area are mined through the cosine similarity of the user interest vector and the context vector of the interest point. Finally, the user's dynamic interests during the travel process are obtained by weighting the user interest vector and the characteristics of the travel target area (Liu et al, 2020).…”

Section: B the Dynamic Interest Of Usersmentioning

confidence: 99%

Research on the Realization of Travel Recommendations for Different Users Through Deep Learning Under Global Information Management

Song

2022

Journal of Global Information Management

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This article is mainly to study the realization of travel recommendations for different users through deep learning under global information management. The personalized travel route recommendation is realized by establishing personalized travel dynamic interest (PTDR) algorithm and distributed lock manager (DLM) model. It is hoped that this model can provide more complete data information of tourist destinations on the basis of the past, and can also meet the needs of users. The innovation of this article is to compare and analyze with a large number of baseline algorithms, highlighting the superiority of this model in personalized travel recommendation. In addition, the model incorporates the topic factor features, geographic factor features, and user preference features to make the data more in line with user needs and improve the efficiency and applicability of the model. It is hoped that the plan proposed in this article can help users make choices of tourist destinations more conveniently.

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Section: B the Dynamic Interest Of Usersmentioning

confidence: 99%

Research on the Realization of Travel Recommendations for Different Users Through Deep Learning Under Global Information Management

Song

2022

Journal of Global Information Management

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“…Porosity is one of the crucial factors that have a considerable impact on structure and performance. Because of the complex composition, it is hard to observe the porosity without the help of lab experiments [17]. In fine grains, the narrow gap between fine granular produces high resistance of the fluid.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

An experimental study of fluidization post impinging fluid in granular bed for breaking sedimentation

Yudiyanto¹,

Wardana

Hamidi

et al. 2020

EEJET

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The impinging fluid can be used as a prevention of sedimentation in the flow of the pipe and the mixing process. Sedimentation is a problem that often occurs in fluid transportation and fluidization. Granular material behavior due to impinging is a phenomenon that is rarely studied. This condition is difficult to observe due to the position of complex fluid movements in the bed. The study tries to find the behavior of fluidization at various granular sizes. The effect of impinging into the granular bed has been observed with experimental studies. Hele-Shaw cell is used as equipment for the observation process. The glass sand is used as a medium of fluidization. The high-speed fluid is injected into a granular bed in a short time. Granular material moves because of the pressure impinging as fluidization. The motion of the granular material is observed by a camera to determine the behavior of the granular material. The primary outcome of the present study is the identification of two very distinct regimes. There are two types of post-impinging fluidization. The first type is the fluid cavity and fluidization. The condition starts with a fluid cavity expansion and continues with the fluidization process. The fluid cavity occurs because the fluid shock pressure pushes the granular material upward. Granular bonds hold the particles' connection and form a cavity. Fluidization after cavity expansion is a settling motion that is influenced by gravity, buoyancy, drag, and granular bonds. The other type is a local fluidized state. The limit for the occurrence of fluid cavity and fluidization is observed with the Reynolds number of impinging. The Reynolds number of impinging is calculated by the velocity of entry of the shock fluid in the granular and multiplied size of the particles divided by the viscosity. The fluid cavity post-impinging occurs at the Reynolds number of the impinging process less than 4,000 (laminar and transition flow area). The local fluidized state has Re of impinging more than 4,000, and the fluidization follows the flow and disappears immediately. This condition causes the bonding of the granules cannot maintain the agglomeration of the granules

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Study of Particle Avalanches: A Discrete Element Method Approach

Kalokhe

Patil

2023

Lecture Notes in Mechanical Engineering

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Porosity Prediction of Granular Materials through Discrete Element Method and Back Propagation Neural Network Algorithm

Cited by 8 publications

References 20 publications

Research on the Realization of Travel Recommendations for Different Users Through Deep Learning Under Global Information Management

Research on the Realization of Travel Recommendations for Different Users Through Deep Learning Under Global Information Management

An experimental study of fluidization post impinging fluid in granular bed for breaking sedimentation

Study of Particle Avalanches: A Discrete Element Method Approach

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