Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.
The effect of adding sand on clayey soil shear strength is investigated in this study. Five different percentage of clay-sand mixtures are used; 100% clay with 0% sand termed 100C, 60% clay with 40% sand termed 60C-40S, 30% clay with 70% sand termed 30C-70S, 15% clay with 85% sand termed 15C-85S, and as well as 100% sand termed 100S. The used clay was obtained from Baghdad city in Iraq and classified as CH soil, while the used sand was taken from Al-Khider area from Iraq and classified as SW soil. The initial dry unit weight for all mixtures is 16 kN/m3. The results show that the variations of the soil shear strength properties with soil components content changes
Found through the study of tissues Alnbarh and domestic focus where a direct impact on the development of the larvae mature into pupae and then to adults appeared to clay soils have a negative impact more than sandy soil at different concentrations salt where as it turns out that the percentage of evolution fly larvae worm Lhalzonnih of the ancient worldadult to have reached more than 80%
Gypseous soils represented one of the most complex salty soils that faced the geotechnical engineers. Structures that built on gypsum soil will undergo unexpected distortions that will eventually contribute to catastrophic failure. The purpose of this article is to understand the durability of gypsum soil against wetting drying cycles after improvement with polyurethane polymer especially investigate the effect of the wetting-drying cycle on collapsibility. The soil was brought from Sawa lake in AL-Muthanna Governorate in Iraq, with gypsum content 65.5%, A set of Odometer tests were performed to determine the collapsibility potential (CP) for treated and untreated gypsum soil. The result shows that adding a different per
... Show MoreThe study is devoted to both static and earthquake response analysis of retaining structures acted upon by lateral earth pressure. Two main approaches were implemented in the analysis, namely, the Mononobe-Okabe analytical method and the numerical Finite element procedure as provided in the ready software ABAQUS with explicit dynamic method. A basic case study considered in the present work is the bridge approach retaining walls as a part of AL-Jadiriya bridge intersection to obtain the effects of the backfill and the ground water on the retaining wall response including displacement of the retaining structure in addition to the behavior of the fill material. Parametric studies were carried out to evaluate the effects of several factors
... Show MoreThis paper presents the results of experimental investigations to predict the bearing capacity of square footing on geogrid-reinforced loose sand by performing model tests. The effects of several parameters were studied in order to study the general behavior of improving the soil by using the geogrid. These parameters include the eccentricity value, depth of first layer of reinforcement, and vertical spacing of reinforcement layers. The results of the experimental work indicated that there was an optimum reinforcement embedment depth at which the bearing capacity was the highest when single-layer reinforcement was used. The increase of (z/B) (vertical spacing of reinforcement layer/width of footing) above 1.5 has no effect on the re
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