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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #178927

Title: SOIL FAILURE MODELS FOR VERTICALLY OPERATING AND HORIZONTALLY OPERATING STRENGTH SENSORS

Author
item CHUNG, SUN-OK - NAT INST AG ENG, S KOREA
item Sudduth, Kenneth - Ken

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/5/2006
Publication Date: 6/5/2006
Citation: Chung, S., Sudduth, K.A. 2006. Soil failure models for vertically operating and horizontally operating strength sensors. Transactions of the ASABE. 49(4):851-863.

Interpretive Summary: Precision agriculture aims both to minimize costs and environmental damage caused by agricultural activities and to optimize crop yield and maximize benefits, all based on information collected at within-field locations. One factor that can vary considerably within fields and can also greatly affect crop yields is soil strength, or compaction. Because of this, a quick and inexpensive compaction measurement device is needed by farmers and consultants. This paper reports on a portion of our research to develop such a sensor. We developed mathematical models to describe the interaction of the soil with two types of cutting tools. The first was a vertically operating cone penetrometer, the standard device currently used to quantify soil compaction. The second was a horizontally operating prismatic cutter, the candidate design for our new sensor. We used the prismatic cutter model to select design parameters of the prototype sensor, including overall dimensions, and location, load rating and spacing of sensing elements. Both models were similar mathematically, which is promising for being able to interpret data from the prototype sensor using approaches already developed for cone penetrometer data. These results will benefit other researchers working in the field by providing them with mathematical models to help understand sensor behavior and test data.

Technical Abstract: Soil strength, or mechanical resistance of a soil to failure, has been widely used to estimate the degree of soil compaction. Conventional measurements with cone penetrometers are laborious; therefore, an on-the-go soil strength profile sensor that collects data dense enough to show the spatial within-field variability in soil strength would be a desirable alternative. Because soil failure involves complex interactions among many variables, determining design parameters of a soil strength sensor and interpreting test results could be improved with a theoretical understanding of the soil failure process. Mathematical models to estimate the force required to penetrate (cut and displace) soil with a prismatic cutter traveling horizontally and with a cone penetrometer traveling vertically were developed based on the passive earth pressure theory and the concept of a variable failure boundary. Both models were expressed as additive forms of density, cohesion, and adhesion components of the soil, with each effect multiplied by a corresponding dimensionless number. Charts of dimensionless numbers were developed to investigate the behavior of each strength component at various values of soil internal friction angle, soil-metal friction angle, and tool cutting angle. The models were used in simulation to optimize design parameters of the sensor, including component dimensions, and location and spacing of sensing elements. Based on this optimization, a prismatic sensing tip with a 3.61-cm2 base area and a 60-degree cutting angle was selected, and the corresponding simulated maximum force and strength measurements were 2.2 kN and 6.0 MPa when operating at speeds up to 5 m s-1. Model validation showed that the extension of the failure boundary was significantly correlated with soil properties such as bulk density, water content, and internal friction angle. The variable failure boundary model developed in this study more consistently and accurately represented field data than did three previously developed modeling approaches.