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  • 11th Asia-Pacific Regional Conference of the ISTVS
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  • Papers of the 11th Asia-Pacific Regional Conference of the ISTVS
    • 0303 / Composite Beam Tests with Closed Cell Polyurethane and Aluminum Foam
    • 0356 / Design and Simulation Analysis of Intelligent Suspension for Manned Lunar Rover
    • 0861 / Review of the Reconfigurable Wheel-Tracked System
    • 0963 / A Wheel and Vehicle Mobility Index Based on Traction and Velocity...
    • 1128 / Semi-Active Reinforcement Learning Suspension Control for the Off-Road Vehicles
    • 1491 / Design and Verification of a Creeping Mars Rover
    • 1534 / Foothold Selection Considering Constraint and Slippage Evaluation for Legged Robots
    • 1561 / Prominent Problems and Thoughts of “Paddy Soil-Terrain Machine System”...
    • 1655 / Modeling of Lunar Rover Vehicle Wheel-Soil Interaction Using Fem-Dem Method
    • 2034 / A Comprehensive Lumped Parameter Approach for the Dynamic Simulation...
    • 2149 / Investigation of the Shear Stress Dynamics on Silty Loam Soil and Measurement...
    • 2190 / Tyre Parameterization Tests: Dynamic vs. Static
    • 2539 / Model Predictive Control of a Robot Driven Vehicle for Testing of Advanced Driver...
    • 2632 / Energy Consumption Analysis of Door Opening with a Mobile Manipulator...
    • 2643 / An Improved Simultaneous Localization and Mapping Method Base on LeGO-LOAM and Motion Compens
    • 3351 / Benchmarking of Compression Testing Devices in Snow
    • 4054 / Field Validation of Egress Process for Planetary Rover
    • 4243 / Soil Compaction Monitoring Technique Using Deep Learning
    • 4260 / The Running Gear Construction Impact on Obstacles Overcoming by Light High-Mobility UGV
    • 4409 / Design of Self-Driving Bulldozer System
    • 4744 / Terrain Classification Using Mars Raw Images Based on Deep Learning Algorithms...
    • 4774 / Steadily Learn to Drive with Virtual Memory
    • 4782 / Experimental Study of Track-Soil Interactions of the Steering Performance of Tracked...
    • 4812 / Multi-Fidelity Machine Learning Modeling for Wheeled Locomotion on Soft Soil
    • 4827 / Introducing Polibot: A High Mobility Tracked Robot with Innovative Passive Suspensions
    • 5060 / Bionic Quadruped Robot for Mars Surface Exploration
    • 5408 / Ride Comfort Comparison Between Suspension Modes: Input Towards Designing Difference...
    • 5800 / Interaction Modeling and Dynamic Control Strategy for C-Shaped Leg with Sandy Terrain...
    • 5979 / Research on Drag Reduction Performance of Sliding Plate of Rice Direct Seeding Machine...
    • 6174 / Factors Affecting Bevameter Soil Characterization
    • 6316 / Perceptive Locomotion of Legged Robot Coupling Model Predictive Control and Terrain Mapping
    • 6718 / Research on Vehicle Running Performance on Paved Roads Covered with Falling Volcanic Ash
    • 6796 / Nonparametric Terrain Estimation Based on the Interaction Simulation Between Planetary...
    • 7018 / A Review of Modeling and Validation Techniques for Tire-Deformable Soil Interactions
    • 7092 / A Time Domain Passivity Controller for Teleoperation of Four Wheeled Differential...
    • 7199 / Vehicle Dynamic Factor Characterized by Actual Velocity and Combined Influence...
    • 7233 / Study of Passive Steering Mechanism for Mars Surface Exploration Rovers
    • 7399 / Tire-Soil Tangential Force Reinforcement Learning Modeling
    • 7878 / A Method for Fast Obtaining of Soil Shear Strength Index Based on Dem Free-Fall Cone...
    • 8131 / Parameters Calibration of Red Clay Soil in Hilly Area of Southwest China for Discrete...
    • 8349 / The Effect of Integrating a Bio-Inspired Convex Structure with a Low-Surface Energy...
    • 8654 / Construction of a Soil Clods Recognition Bench-Scale Experiment for Discrete Element...
    • 8658 / Investigation of the Relationship between the Cone Index and the Physical and...
    • 9352 / 3D-DEM Simulation and Post-Process Method of Wheel-Terrain Interaction for Planetary Rovers
    • 9768 / Design and Traction Performance Test of Bionic Paddy Wheel Based on Cattle Hoof
    • 9913 / Acquisition of Flipper Motion in Step-Climbing of Tracked Robot Using Reinforcement Learning
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  1. Papers of the 11th Asia-Pacific Regional Conference of the ISTVS

7878 / A Method for Fast Obtaining of Soil Shear Strength Index Based on Dem Free-Fall Cone...

Paper presented at the 11th Asia-Pacific Regional Conference of the ISTVS

Previous7399 / Tire-Soil Tangential Force Reinforcement Learning ModelingNext8131 / Parameters Calibration of Red Clay Soil in Hilly Area of Southwest China for Discrete...

Last updated 2 years ago

https:/doi.org/10.56884/PFQD4535

Title: A Method for Fast Obtaining of Soil Shear Strength Index Based on Dem Free-Fall Cone Penetration Simulation

Authors: Jincheng Diao, Jingwei Gao, Xiaobo Song, and Baojun Di

Abstract: Soil shear strength is an important index of soil mechanical properties, which is of great significance in fields such as rock and soil stress analysis, agricultural machinery farming, seabed exploration, and vehicle trafficability evaluation. In order to improve the problems existing in the existing methods of obtaining soil shear strength index, such as low accuracy, demanding experimental site conditions and long periodicity, this paper constructed a model of free-fall cone penetration into the soil based on the discrete element method (DEM) simulation, and the corresponding relationship between moisture content and penetration depth was obtained. In addition, the corresponding relationship between the moisture content and the soil shear strength index was obtained from the triaxial compression test. Combining these two relational equations, this paper finally summarized the equation about the relationship between the penetration depth in the simulation and the soil shear strength index in the test. It was verified that the errors of internal friction angle (φ) and internal cohesion (c) obtained by the equation were only 3.45% and 6.68%. It shows that the DEM free-fall cone penetration simulation can replace the triaxial compression test to obtain soil shear strength index with very low error, and it is a quick and accurate new method to acquire the soil mechanical parameters.

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