Redirigiendo al acceso original de articulo en 22 segundos...
ARTÍCULO
TITULO

Experimental Validation of Single- and Two-Phase Smoothed Particle Hydrodynamics on Sloshing in a Prismatic Tank

Andi Trimulyono    
Hirotada Hashimoto and Akihiko Matsuda    

Resumen

This study aimed to validate the single-phase and two-phase smoothed particle hydrodynamics (SPH) on sloshing in a tank. There have been many studies on sloshing in tanks based on meshless particle methods, but few researchers have used a large number of particles because there is a limitation on the total number of particles when using only CPUs. Additionally, few studies have investigated the influence of air phase on tank sloshing based on two-phase SPH. In this study, a dedicated sloshing experiment was conducted at the National Research Institute of Fishing Engineering using a prismatic tank with a four-degrees-of-freedom forced oscillation machine. Three pressure gauges were used to measure local pressure near the corners of the tank. The sloshing experiment was repeated for two different filling ratios, amplitudes, and frequencies of external oscillation. Next, a GPU-accelerated three-dimensional SPH simulation of sloshing was performed using the same conditions as the experiment with a large number of particles. Lastly, two-dimensional sloshing simulations based on single-phase and two-phase SPH were carried out to determine the importance of the air phase in terms of tank sloshing. Based on systematic comparisons of the single-phase SPH, two-phase SPH, and experimental results, this paper presents a detailed discussion of the role of air-phase in terms of sloshing. The currently achievable accuracy when using SPH is demonstrated together with a few sensitivity analyses of SPH parameters.

 Artículos similares

       
 
Shurong Peng, Lijuan Guo, Yuanshu Li, Haoyu Huang, Jiayi Peng and Xiaoxu Liu    
The allocation of biogas between power generation and heat supply in traditional kitchen waste power generation system is unreasonable; for this reason, a biogas prediction method based on feature selection and heterogeneous model integration learning is... ver más
Revista: Applied Sciences

 
Zeyu Xu, Wenbin Yu, Chengjun Zhang and Yadang Chen    
In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic collaboration between quantum and classical computing models has emerged as a promising solution for tackling complex computational challenges. Long short-term memory (LSTM)... ver más
Revista: Information

 
Florin Leon, Marius Gavrilescu, Sabina-Adriana Floria and Alina Adriana Minea    
This paper proposes a classification methodology aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning model. The ap... ver más
Revista: Information

 
Ru Ye, Hongyan Xing and Xing Zhou    
Addressing the limitations of manually extracting features from small maritime target signals, this paper explores Markov transition fields and convolutional neural networks, proposing a detection method for small targets based on an improved Markov tran... ver más

 
Can Li, Hua Sun, Changhong Wang, Sheng Chen, Xi Liu, Yi Zhang, Na Ren and Deyu Tong    
In order to safeguard image copyrights, zero-watermarking technology extracts robust features and generates watermarks without altering the original image. Traditional zero-watermarking methods rely on handcrafted feature descriptors to enhance their per... ver más
Revista: Applied Sciences