Investigating the Compressibility of Sandy-Clay Soil in the Laboratory Soil Bin Caused by Agricultural Tire Traffic and Analyzed by the Adaptive Neuro–Fuzzy Inference System
Agricultural soil compaction caused by tractors and heavy farm machines has a direct impact on farm productivity. Therefore, the effect of influencing parameters on soil compaction was studied and evaluated using a wheel tester device in the soil bin environment. Experiments were carried out at 3 le...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
|
| Series: | Applied and Environmental Soil Science |
| Online Access: | http://dx.doi.org/10.1155/aess/4471543 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Agricultural soil compaction caused by tractors and heavy farm machines has a direct impact on farm productivity. Therefore, the effect of influencing parameters on soil compaction was studied and evaluated using a wheel tester device in the soil bin environment. Experiments were carried out at 3 levels of vertical load (170, 250, and 320 kg), 3 levels of tire inflation pressure (10, 15, and 20 psi), 3 levels of soil moisture content (2%, 7%, and 13% wet basis), and 2 levels of forward speed (0.386 and 0.879 km/h) in the form of a factorial design and a randomized complete block design in 3 replications. Next, soil compaction was predicted under the influence of investigated parameters using ANFIS. The results showed that the advance of the wheel at low speed and high soil moisture content significantly increases soil compaction. The present findings showed that the soil compaction increases linearly with the relative increase of the vertical load on the tire. Meanwhile, the relative increase of soil compaction in wet soil (7%–13% relative humidity, wb) was relatively 9.93 times higher than the soil compaction in low humidity (2%–7%). The results also show that reducing tire inflation pressure from 20 to 15 psi reduces soil compaction by 12.94%. The correlation coefficient between the measured and predicted data using ANFIS for soil compaction was equal to 1, which showed the high accuracy of ANFIS models in predicting the studied parameters. This approach provides criteria for a more appropriate selection of agricultural tires. |
|---|---|
| ISSN: | 1687-7675 |