scholarly journals Determination of the Super-Elliptic Shape of Tire-Soil Contact Area Using Image Processing Method

2015 ◽  
Vol 48 (2) ◽  
pp. 5-14
Author(s):  
R. Farrokhi Teimourlou ◽  
H. Taghavifar

Abstract The present study is aimed at determination of the super-elliptic shape of tire-soil contact area using image processing method. Contact area has a substantial role on determination of soil compaction and tractive parameters of agricultural tractors. A very well-known model in this realm is to describe the contact area with superellipse geometry. A soil bin testing facility equipped with a single-wheel tester was utilized to conduct the needed experiments. The experiments were carried out at three levels of wheel load, three levels of tire inflation pressure with three replicates in a completely randomized block design. Corresponding images were taken for each of the experiments and the images were processed accordingly. The contact length and width were determined using imdistline command in MATLAB commercial software. This experiment was conducted at three levels of wheel load (2, 3, and 4 kN), and three levels of tire inflation pressure (100, 200, and 300 kPa) with three replications. The aforementioned parameters were applied consequently in the superellipse model and the contact area was computed. The obtained results disclosed that increase of wheel load increases the contact area. Contradictory, increment of tire inflation pressure reduces the formed contact area. Additionally, the potential of contact area determination with the proposed model was compared with that of actual values, which denoted coefficient of determination equal to 0.96, which shows the promising ability of the proposed model and the appropriateness of describing contact area with superellipse geometry

2017 ◽  
Vol 132 (3-II) ◽  
pp. 1171-1172
Author(s):  
Ş. Kilinçarslan ◽  
İ.S. Üncü ◽  
İ. Akkurt ◽  
K. Günoğlu ◽  
F. Akarslan ◽  
...  

Author(s):  
Fang Wang ◽  
Yi-Zhao Li ◽  
Li-Ping Li ◽  
De-Ren Kong

After the first initiation, the Fuel Air Explosive (FAE) cloud formed through fuel explosion dispersal and it will generate tremendous damaging power after being detonated the second time. As the damaging power is closely related to the determination of reinitiation time, it is of great significance to study the growth principle of FAE cloud by means of analyzing FAE cloud images. Combining with background subtraction and region growing, an improved region growing image processing method was proposed, in which the seeds of region growing abstracted through background subtraction method and the growing criterion was modified. With this method, the integrate area of cloud can be obtained for extracting geometric parameters. Experiments were carried out on both cloudy and sunny days, and image overlap score was used to quantitatively evaluate the accuracy of images segmentation. The result indicated that this image processing method has advantages of high precision and robustness. In addition, the computation burden is reduced significantly compared with traditional region growing method.


Author(s):  
Longji Du ◽  
Shi Zhang ◽  
Liming Chen ◽  
Jinglong Ye ◽  
Meiting Ma ◽  
...  

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.


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