Properties of disordered sphere packings I. Geometric structure: Statistical model, numerical simulations and experimental results

1986 ◽  
Vol 46 (2-3) ◽  
pp. 121-131 ◽  
Author(s):  
L. Oger ◽  
J.P. Troadec ◽  
D. Bideau ◽  
J.A. Dodds ◽  
M.J. Powell
Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 405
Author(s):  
Anam Nawaz Khan ◽  
Naeem Iqbal ◽  
Rashid Ahmad ◽  
Do-Hyeun Kim

With the development of modern power systems (smart grid), energy consumption prediction becomes an essential aspect of resource planning and operations. In the last few decades, industrial and commercial buildings have thoroughly been investigated for consumption patterns. However, due to the unavailability of data, the residential buildings could not get much attention. During the last few years, many solutions have been devised for predicting electric consumption; however, it remains a challenging task due to the dynamic nature of residential consumption patterns. Therefore, a more robust solution is required to improve the model performance and achieve a better prediction accuracy. This paper presents an ensemble approach based on learning to a statistical model to predict the short-term energy consumption of a multifamily residential building. Our proposed approach utilizes Long Short-Term Memory (LSTM) and Kalman Filter (KF) to build an ensemble prediction model to predict short term energy demands of multifamily residential buildings. The proposed approach uses real energy data acquired from the multifamily residential building, South Korea. Different statistical measures are used, such as mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), and R2 score, to evaluate the performance of the proposed approach and compare it with existing models. The experimental results reveal that the proposed approach predicts accurately and outperforms the existing models. Furthermore, a comparative analysis is performed to evaluate and compare the proposed model with conventional machine learning models. The experimental results show the effectiveness and significance of the proposed approach compared to existing energy prediction models. The proposed approach will support energy management to effectively plan and manage the energy supply and demands of multifamily residential buildings.


Author(s):  
Hagen Kohl ◽  
Lisa Schade ◽  
Gabor Matthäus ◽  
Tobias Ullsperger ◽  
Burak Yürekli ◽  
...  

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Jianhua Liu ◽  
Hao Gong ◽  
Xiaoyu Ding

Recently, the wedge self-locking nut, a special anti-loosening product, is receiving more attention because of its excellent reliability in preventing loosening failure under vibration conditions. The key characteristic of a wedge self-locking nut is the special wedge ramp at the root of the thread. In this work, the effect of ramp angle on the anti-loosening ability of wedge self-locking nuts was studied systematically based on numerical simulations and experiments. Wedge self-locking nuts with nine ramp angles (10 deg, 15 deg, 20 deg, 25 deg, 30 deg, 35 deg, 40 deg, 45 deg, and 50 deg) were modeled using a finite element (FE) method, and manufactured using commercial production technology. Their anti-loosening abilities under transversal vibration conditions were analyzed based on numerical and experimental results. It was found that there is a threshold value of the initial preload below which the wedge self-locking nuts would lose their anti-loosening ability. This threshold value of initial preload was then proposed for use as a criterion to evaluate the anti-loosening ability of wedge self-locking nuts quantitatively and to determine the optimal ramp angle. Based on this criterion, it was demonstrated, numerically and experimentally, that a 30 deg wedge ramp resulted in the best anti-loosening ability among nine ramp angles studied. The significance of this study is that it provides an effective method to evaluate the anti-loosening ability of wedge self-locking nuts quantitatively, and determined the optimal ramp angle in terms of anti-loosening ability. The proposed method can also be used to optimize other parameters, such as the material properties and other dimensions, to guarantee the best anti-loosening ability of wedge self-locking nuts.


2016 ◽  
Vol 10 (11) ◽  
pp. 203
Author(s):  
Mohd Zaid Othman ◽  
Qasim H. Shah ◽  
Muhammad Akram Muhammad Khan ◽  
Tan Kean Sheng ◽  
M. A. Yahaya ◽  
...  

A series of numerical simulations utilizing LS-DYNA was performed to determine the mid-point deformations of V-shaped plates due to blast loading. The numerical simulation results were then compared with experimental results from published literature. The V-shaped plate is made of DOMEX 700 and is used underneath an armour personal carrier vehicle as an anti-tank mine to mitigate the effects of explosion from landmines in a battlefield. The performed numerical simulations of blast loading of V-shaped plates consisted of various angles i.e. 60°, 90°, 120°, 150° and 180°; variable mass of explosives located at the central mid-point of the V-shaped vertex with various stand-off distances. It could be seen that the numerical simulations produced good agreement with the experimental results where the average difference was about 26.6%.


2004 ◽  
Vol 127 (3) ◽  
pp. 515-519 ◽  
Author(s):  
Yongjun Lai ◽  
Marek Kujath ◽  
Ted Hubbard

A micro-machined manipulator with three kinematic degrees-of-freedom (DOF): x, y, and φ is presented. The manipulator is driven by three thermal actuators. A six DOF discrete spring-mass model of the compliant mechanism is developed which manifests the dynamic properties of the device. Numerical simulations are compared with experimental results.


2016 ◽  
Vol 713 ◽  
pp. 288-292 ◽  
Author(s):  
Jabid Quiroga ◽  
John Quiroga ◽  
Luis Mujica ◽  
Rodolfo Villamizar ◽  
Magda Ruiz

In this paper, a guided wave temperature robust PCA-based stress monitoring methodology is proposed. It is based on the analysis of the longitudinal guided wave propagating along the path under stress. Slight changes in the wave are detected by means of PCA via statistical T2 and Q indices. Experimental and numerical simulations of the guided wave propagating in material under different temperatures have shown significant variations in the amplitude and the velocity of the wave. This condition can jeopardize the discrimination of the different stress scenarios detected by the PCA indices. Thus, it is proposed a methodology based on an extended knowledge base, composed by a PCA statistical model for different discrete temperatures to produce a robust classification of stress states under variable environmental conditions. Experimental results have shown a good agreement between the predicted scenarios and the real ones


Physics ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 49-66 ◽  
Author(s):  
Vyacheslav I. Yukalov

The article presents the state of the art and reviews the literature on the long-standing problem of the possibility for a sample to be at the same time solid and superfluid. Theoretical models, numerical simulations, and experimental results are discussed.


Author(s):  
Akhil Marayikkottu Vijayan ◽  
Saurabh S. Sawant ◽  
Deborah A. Levin ◽  
Ci Huang ◽  
Mirko Schoenitz ◽  
...  

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