Performance of combined offset disc harrow (front active and rear passive set configuration) in soil bin

Ganesh Upadhyay, Hifjur Raheman

Journal of Terramechanics, Volume 78, 2018, Pages 27-37, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.04.002.

Abstract: Soil bin investigations were initiated with combined offset disc harrow (CODH) which unites the benefits of powered discs and combination tillage together through a front active-rear passive set configuration. The proposed configuration may help to achieve timeliness in sowing, better crop residue handling with reduced tillage passes and improved engine power utilization of tractor. The effects of speed ratio (u/v), front gang angle (α), operating depth and cone index (CI) on its draft, torque and power requirement were studied and compared with its traditional passively driven mode at an average soil moisture of 9–10% (db) in sandy-clay loam soil. Optimum system settings were found out before further performance evaluation in the field. The substantially reduced draft requirement with CODH might help to reduce the wheel slippage and improve field productivity while increased power requirement might prevent the under-loading of tractor engine. Tillage quality was assessed considering CI values and found to be far superior compared to traditional mode. Optimum system settings were found at α of 35° and u/v ratio of 3.6 in terms of lowest power expenditure and better work quality with torque power expenditure of 60–70% in total power indicating improved utilization of engine power if operated with tractor power take-off (PTO).

Keywords: Draft; Torque; Passively driven mode; Speed ratio; Front gang angle
 

Probabilistic self-tuning approaches for enhancing performance of autonomous vehicles in changing terrains

Alvaro Javier Prado, Fernando A. Auat Cheein, Saso Blazic, Miguel Torres-Torriti,

Journal of Terramechanics, Volume 78, 2018, Pages 39-51, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.04.001.

Abstract: Motion controllers usually require a tuning stage to ensure an acceptable performance of the vehicle during operation in challenging scenarios. However, such tuning stage is a time consuming process for the programmer and often is based on intuition or heuristic approaches. In addition, once tuned, the vehicle performance varies according to the nature of the terrain. In this work, we study the use of well-known probabilistic techniques for self-tuning trajectory tracking controllers for service units based on the idea of saving both vehicle’s resources and human labour force time. The proposed strategies are based on Monte Carlo and Bayesian approaches to find the best set of gains to tune the controller both off-line and on-line, thus enhancing the controller performance in the presence of changing terrains. The approaches are implemented and validated on a skid-steer mini-loader vehicle usually used for mining purposes. Implementation details and both simulation and empirical results are included in this work, showing that when using our approaches, effort can be saved up to 30% and tracking errors reduced up to 75%.

Keywords: Trajectory tracking control; Auto-tuning; Industrial machinery; Wheel-terrain interaction

State of the knowledge of vegetation impact on soil strength and trafficability

Wendy L. Wieder, Sally A. Shoop

Journal of Terramechanics, Volume 78, 2018, Pages 1-14, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.03.006.

Abstract: Researchers in a variety of fields have studied using vegetation to alter or reinforce soils. However, using vegetation for soil preservation in long-term land management of military training areas used for off-road vehicle maneuvers is more recent. Much of the work reported in the literature deals with trees and larger shrubs, appropriate for slope and bank stabilization. Other research efforts are for agricultural or forestry applications and involve crops, and again, large trees. This review discusses the issue of vegetation and its effect on a variety of soil strength parameters. It also reviews work regarding the effect of vehicle operations on vegetation and conversely the effect of vegetation on vehicle performance, or trafficability. The reviewed test methods and proposed soil strength models, based on a variety of soil properties, provide a basis for continuing work on models to evaluate areas used for off road military vehicle operations.

Keywords: Trafficability; Soil strength; Terrain; Impact; Mobility; Biomass; Vegetation
 

FE-DEM with interchangeable modeling for off-road tire traction analysis

Kenta Nishiyama, Hiroshi Nakashima, Taiki Yoshida, Hiroshi Shimizu, Juro Miyasaka, Katsuaki Ohdoi

Journal of Terramechanics, Volume 78, August 2018, Pages 15-25, ISSN 0022-4898, https://doi.org/10.1016/j.jterra.2018.03.005.

Abstract: This study examines a new finite element/discrete element method (FE-DEM) with interchangeable modeling between FEM and DEM for tire traction analysis. In the method, named iFE-DEM, the soil in a soil bin is modeled initially by FEM except for the region under or near the tire, which is modeled using DEM. When the FEM tire model starts to travel over DEM soil elements, the updated tire location will activate new conversion of modeling from FEM to DEM so that the zone of influence around the contact interface between tire and soil can be analyzed continuously using DEM. Those mobilized DEM elements rearward of the tire might be converted again to FEM elements by assuming that the effect of the stress state in DEM generated by tire travel might be negligible. The computational time for two-dimensional iFE-DEM analysis of a slip of 40% using the smallest region of initial DEM under the tire could be reduced to 23% of that obtained using DEM only soil modeling.

Keywords: FEM; DEM; Interchangeable modeling; Soil-wheel system; Traction performance

Experimental study of a tracked mobile robot’s mobility performance

Weidong Wang, Zhiyuan Yan, Zhijiang Du

Journal of Terramechanics, Volume 77, 2018, Pages 75-84, ISSN 0022-4898
https://doi.org/10.1016/j.jterra.2018.03.004.

Abstract: This paper proposes an experimental method of predicting the traction performance of a small tracked mobile robot. Firstly, a track-terrain interaction model based on terramechanics is built. Then, an experimental platform of the tracked robot is established, on which the measurement methods of the parameters that influencing the accuracy of the prediction model are introduced and the data post-processing are improved, including drawbar pull, slip ratio, sinkage, track deformation and so on. Based on the experimental data, several key terrain parameters are identified. With the tracked robot platform, the drawbar pull-slip ratio relationship is tested, and the effects on drawbar pull considering different kinds of terrain and the influence of the grousers are analyzed as well. The research results provide a reference for the experimental study on the traction performance of small tracked robots.

Keywords: Tracked mobile robot; Terrain–track interaction; Drawbar pull; Tractive performance; Experimental study

Determination of soil density by cone index data

György Pillinger, Attila Géczy, Zoltán Hudoba, Péter Kiss

Journal of Terramechanics, Volume 77, 2018, Pages 69-74, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.03.003.

Abstract: In this paper a novel soil-density determination method is presented. The classic method (sampling, drying, mass measuring, etc.) can give proper results for the given problem but the standard methodology requires a lot of practical effort. While the soil is generally inhomogeneous, the measured density values of the soil sample applies only for the sample itself. On the entire soil territory this density can be interpreted only with significant errors. For a better mapping of the soil-density distribution expansive measurements are required. The task is complicated by the determination of density distribution in deeper layers of the soil as well. Our work presents a simpler method to determine the soil-density distribution in deeper layers with the use of cone penetration test (CI) results. With this method we can obtain detailed results of the soil-density distribution in deeper layers that may help further calculations for soil deformation analysis such as an exact determination of the soil sinkage below a tire track.

Keywords: Soil density; Deformation; Stubble; Cone penetration; Relative elongation
 

Improving accuracy of vehicle-terrain interface algorithms for wheeled vehicles on fine-grained soils through Bayesian calibration

Ian Dettwiller, Farshid Vahedifard, Masoud Rais-Rohani, George L. Mason, Jody D. Priddy

Journal of Terramechanics, Volume 77, 2018, Pages 59-68, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.03.001.

Abstract: The Vehicle-Terrain Interface (VTI) model for off-road vehicle performance is often used in virtual prototyping to support preliminary vehicle design. Five VTI algorithms for wheeled vehicles on fine-grained soils are calibrated in this study using a Bayesian calibration technique and the Database Records for Off-road Vehicle Environments (DROVE): powered and unpowered sinkage, drawbar pull, motion resistance, and gross traction. These algorithms are improved through a two-stage Bayesian calibration technique utilizing the Metropolis algorithm with three separate calibration strategies. The VTI and proposed algorithms are compared for performance in coefficient of determination and root-mean square error. The results from each algorithm were validated through k-fold cross validation with five folds. The final algorithms from the best performing strategy after accounting for increased complexity for each of the five performance parameters are reported as calibrated algorithms. Validated improvements in coefficient of determination are recorded for all five parameters: 7.8% for powered sinkage, 1.4% for unpowered sinkage, 6.4% for drawbar pull, 0.9% for motion resistance, and 12.5% for gross traction. Improvements are also seen in the normalized root-mean square error performance: 13.4% for powered sinkage, 1.9% for unpowered sinkage, 7.6% for drawbar pull, 17.5% for motion resistance, and 23.2% for gross traction.

Keywords: Off-road mobility; Vehicle Terrain Interface (VTI) model; Bayesian calibration; Metropolis algorithm; Fine-grained soils; Sinkage; Drawbar pull; Traction; Motion resistance; Database Records for Off-road Vehicle Environments (DROVE)

Prediction effect of farmyard manure, multiple passes and moisture content on clay soil compaction using adaptive neuro-fuzzy inference system

Kamel Ghadernejad, Gholamhossein Shahgholi, Aref Mardani, Hafez Ghafouri Chiyaneh

Journal of Terramechanics, Volume 77, 2018, Pages 49-57, ISSN 0022-4898,
https://doi.org/10.1016/j.jterra.2018.03.002.

Abstract: Soil compaction by machine traffic is a complex process with many interacting factors. The strength of adaptive neuro-fuzzy inference system (ANFIS) is the ability to handle linguistic concepts and find nonlinear relationships between inputs and outputs parameters. In this research, the effect of farmyard manure, the number of tire passes, soil moisture contents and three average depths on clay soil compaction is predicted using ANFIS and Regression. For the prediction of soil compaction, an agricultural tractor tire was used and the experiments were carried out in the controlled condition of soil bin facility utilizing a well-equipped single-wheel tester. To measure soil compaction, cylindrical cores in groups of three were inserted into the three different depths. Various member function ANFIS were tested to discover the supervised ANFIS-based models for the soil compaction. On the basis of statistical performance criteria of MAPE and R2, Gaussian curve built-in membership function (gaussmf) was found as a proper model. In addition, the ANFIS model with ‘Gaussian mf’ is recommended considering the higher prediction performance values of MAPE = 0.2957%. The regression analyses of ANFI and Multiple Linear Regression (MLR) revealed a high correlation with farmyard manure, the number of tire passes, soil moisture, and depth. Also, it showed a higher performance compared to the regression model for predicting soil compaction. Thus, it can be concluded that ANFIS-based methodology is a soft computing approach that provides excellent nonlinear systems such as soil compaction.

Keywords: Farmyard manure; Multiple passes; Soil compaction; ANFIS; Multiple linear regression

Comparison of soil strength measurements of agricultural soils in Nebraska

Wendy Wieder, Sally Shoop, Lynette Barna, Trenton Franz, Catherine Finkenbiner

Journal of Terramechanics, Volume 77, 2018, Pages 31-48, ISSN 0022-4898, https://doi.org/10.1016/j.jterra.2018.02.003.

Abstract: In 2014 the University of Nebraska, Lincoln (UNL) was engaged in field testing program to investigate a soil moisture mapping system as a crop management tool. In conjunction with this work, the US Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory (ERDC-CRREL) deployed a team to perform soil characterization and strength measurements at three agricultural test sites. The primary objective was an investigation of the Lightweight Deflectometer (LWD) as a soil surface strength tool for the purposes of assessing bearing capacity of soft soils. The LWD measurements were performed with those from more “standard” tests, i.e. the Dynamic Cone Penetrometer, Cone Penetrometer, and Clegg Impact Hammer to determine if the LWD produced results that compared with these methods. The strength test data were also used to calculate California Bearing Ratio (CBR) values using existing equations in order to see if the different test methods produced similar CBR values that could in turn be used to predict the bearing capacity of the sites. The secondary objective was to compare the strength data with the corresponding soil water content data taken by UNL to determine if soil moisture was an indicator of soil strength.

Keywords: Agricultural soils; Soil strength; Bearing capacity; DCP; CI; CIH; LWD; Soil water content