Assessing Pullout Resistance of Earth Reinforced Embankment Model

2014 ◽  
Vol 2 (1) ◽  
pp. 9
Author(s):  
Saad Issa Sarsam ◽  
Aamal A. Al-Saeidy ◽  
Mustafa A. Falih
Keyword(s):  
Pullout Resistance

Predicting Pullout Resistance of Bearing Reinforcement Embedded in Cohesive-Frictional Soils

2020 ◽  
Vol 32 (3) ◽  
pp. 04019379
Author(s):  
Gampanart Sukmak ◽  
Patimapon Sukmak ◽  
Apichet Joongklang ◽  
Artit Udomchai ◽  
Suksun Horpibulsuk ◽  
...  
Keyword(s):  
Pullout Resistance ◽  
Frictional Soils

Pullout Resistance of Vertical Anchors

1975 ◽  
Vol 101 (1) ◽  
pp. 87-91
Author(s):  
Braja M. Das
Keyword(s):  
Pullout Resistance

Comparison of various multivariate models to estimate structural properties by means of non-destructive techniques (NDTs) in Pinus sylvestris L. timber

Holzforschung ◽  
2019 ◽  
Vol 73 (4) ◽  
pp. 331-338
Author(s):  
Antonio Villasante ◽  
Guillermo Íñiguez-González ◽  
Lluis Puigdomenech
Keyword(s):  
Pinus Sylvestris ◽  
Linear Models ◽  
Longitudinal Vibration ◽  
Modulus Of Rupture ◽  
Coefficient Of Determination ◽  
Pullout Resistance ◽  
Density Prediction ◽  
Learning Software ◽  
Artificial Neural Network Ann ◽  
Non Destructive

AbstractThe predictability of modulus of elasticity (MOE), modulus of rupture (MOR) and density of 120 samples of Scots pine (Pinus sylvestrisL.) were investigated using various non-destructive variables (such as time of flight of stress wave, natural frequency of longitudinal vibration, penetration depth, pullout resistance, visual grading and concentrated knot diameter ratio), and based on multivariate algorithms, applying WEKA as machine learning software. The algorithms used were: multivariate linear regression (MLR), Gaussian, Lazy, artificial neural network (ANN), Rules and decision Tree. The models were quantified based on the root-mean-square error (RMSE) and the coefficient of determination (R2). To avoid model overfitting, the modeling was built and the results validated via the so-called 10-fold cross-validation. MLR with the “greedy method” for variable selection based on the Akaike information metric (MLRak) significantly reduced the RMSE of MOR and MOE compared to univariate linear regressions (ULR). However, this reduction was not significant for density prediction. The predictability of MLRak was not improved by any other of the tested algorithms. Specifically, non-linear models, such as multilayer perceptron, did not contribute any significant improvements over linear models. Finally, MLRak models were simplified by discarding the variables that produce the lowest RMSE increment. The resulted models could be even further simplified without significant RMSE increment.

Cooperation Pullout Test of Double Self-Tapping Screws in Wood Structures

2011 ◽  
Vol 374-377 ◽  
pp. 2520-2524 ◽  
Author(s):  
Gang Shi ◽  
Jian Xing Zhang ◽  
Yuan Qing Wang ◽  
Hui Juan Huang ◽  
Zheng Hong Zhang
Keyword(s):  
Experimental Study ◽  
Pullout Test ◽  
The Self ◽  
Connection Strength ◽  
Wood Structure ◽  
Wood Structures ◽  
Pullout Resistance ◽  
Loading Tests ◽  
The Common ◽  
Strength And Stiffness

In this paper, the experimental study on the self-tapping screw’s pullout resistance in the wood structure was conducted. Domestic ordinary screws were used together with imported or domestic wood to fabricate 6 screw connection specimens in wooden walls. Then monotonic loading tests were conducted and it can be concluded that, the common round screw connection strength mainly depends on the failure mode, the lack of cooperation effect significantly influences the strength of screw connections, and the dispersion of screw connection stiffness is high. So, to obtain formulae for the self-tapping screw connection strength and stiffness by further experimental study will be very necessary.

Ultimate pullout resistance of plate anchors buried in sandy seabed

2014 ◽  
pp. 1237-1241
Author(s):  
F Cañizal ◽  
J Cañizal ◽  
J Castro ◽  
A da Costa ◽  
C Sagaseta
Keyword(s):  
Pullout Resistance ◽  
Plate Anchors

scholarly journals SURVIVAL EVALUATION AND SOIL REINFORCEMENT CAPACITY OF FIVE REOPHYTES SPECIES OF THE ATLANTIC RAINFOREST BIOME

FLORESTA ◽  
2019 ◽  
Vol 49 (3) ◽  
pp. 477
Author(s):  
Junior Joel Dewes ◽  
Charles Rodrigo Belmonte Maffra ◽  
Rita Dos Santos Sousa ◽  
Fabrício Jaques Sutili
Keyword(s):  
Survival Rate ◽  
Soil Stabilization ◽  
Land Reclamation ◽  
Survival Rates ◽  
Soil Reinforcement ◽  
Good Survival ◽  
Vegetative Development ◽  
Mechanical Reinforcement ◽  
Pullout Resistance ◽  
Level Of Significance

The aim of this study was to evaluate the survival rate, the vegetative development and vertical pullout resistance of Phyllanthus sellowianus, Salix humboldtiana, Gymnanthes schottiana, Cephallanthus glabratus and Ludwigia elegans propagated by live cuttings. The experiment was conducted at the Federal University of Santa Maria, RS. The experiment was installed in October 2015 and evaluated in June 2016. Experiment was conducted in randomized blocks design with use of 5 plant species and 3 replications. In each block were planted 3 live cuttings of each species, with the total of 45 cuttings for the 3 blocks. The space between plants was of 1 x 1 m. Live cuttings average diameter was 1.7 cm and 60 cm long. Were evaluated the survival rate, morphological variables from shoots, as well as the vertical pullout resistance for each species. The observed survival rates were: P. sellowianus (100%), S. humboldtiana (100%), G. schottiana (83%), %), C. glabratus (67%) e L. elegans (50%), which are statistically different among themselves by Chi-square test (χ ²) at 5% level of significance. The variables, length and diameter of shoots, as well as the vertical pullout resistance are statistically different between species by Tukey’s test at 5% level of significance, and the best results were observed for P. sellowianus and less favorable to L. elegans. The results showed that the evaluated species, excluding L. elegans, had from great to good survival rates. The species P. sellowianus and L. elegans had the major and minor soil mechanical reinforcement capacity, respectively.Keywords: Soil Bioengineering, land reclamation, soil stabilization, vegetative propagation.

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