Mobility algorithm evaluation using a consolidated database developed for wheeled vehicles operating on dry sands

Vahedifard, Farshid; Robinson, Joe D.; Mason, George L.; Howard, Isaac L.; Priddy, Jody D.

doi:10.1016/j.jterra.2015.10.002

Cited by 19 publications

(10 citation statements)

References 10 publications

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“…Because neither of these models accounted for damage accumulation under repeated load cycles, they were not applicable to predicting deformation underneath a matted surface. Vahedifard et al (2016) and Vahedifard et al (2017) assembled a database of thousands of off-road mobility algorithms for sand and clay soils to evaluate numerous parameters such as sinkage. The database is referred to as DROVE (Database Records for Off-Road Vehicle Environments).…”

Section: Soil Classificationmentioning

confidence: 99%

Performance prediction relationships for AM2 airfield matting developed from full-scale accelerated testing and laboratory experimentation

Rushing¹

2018

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The AM2 airfield matting system is used by the U.S. military for temporary, rapidly constructed airfields. Predicting the number of allowable aircraft passes across an AM2 installation is challenging because of the complex design of the joining system and the fatigue behavior of the joints. Prior to this work, the prevailing methods used to predict the performance of AM2 were based on the CBR design procedure for flexible pavements using a small number of full-scale test sections over CBRs ranging from 4 to 10 percent and simulated aircraft that are no longer in service. This report presents results from nine full-scale experiments conducted on sections of AM2 matting installed on unstabilized soil and gravel subgrades with CBRs of 6, 10, 15, 25, and 100 percent, and provides improved relationships for predicting subgrade deformation underneath an AM2 mat installation and the associated fatigue damage when subjected to F-15E and C-17 traffic. Additionally, a laboratory fixture and procedure is described for evaluating an AM2 style joint in fatigue and relating its performance to given field conditions without requiring the expense of full-scale testing. These relationships are suitable for design and evaluation frameworks currently used for airfield pavements and matting systems. DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents.

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Section: Soil Classificationmentioning

confidence: 99%

Performance prediction relationships for AM2 airfield matting developed from full-scale accelerated testing and laboratory experimentation

Rushing¹

2018

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“…As a part of this multi-year effort, DROVE was created and is being further extended using the existing test results performed on coarse-grained and fine-grained soils. Vahedifard et al (2016) presented the first release of DROVE which includes tests conducted on sand. Mason et al (2016) used the sand database to reduce the complexity of previous sinkage algorithms while improving the correlations.…”

Section: Applications and Future Extensionsmentioning

confidence: 99%

Development of a multi-year database to assess off-road mobility algorithms in fine-grained soils

Vahedifard

Williams

Mason

et al. 2017

IJVP

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A gap in off-road mobility is the availability of the test data necessary for the development and validation of tyre, track and soil models. This paper presents the results from a multi-year program to create the database records for off-road vehicle environments (DROVE), a consolidated database of laboratory and field test results. A fine-grained soil component was added to DROVE by compiling 2657 test results. Performance parameters including drawbar pull, motion resistance, torque, sinkage, and slip were included in the database. The database was used to evaluate the accuracy of existing algorithms used in the vehicle-terrain interface (VTI) model. The results indicated that the VTI algorithms can provide reasonable predictions for a few parameters but for others, such as motion resistance, further improvements are warranted. 4 F. Vahedifard et al.The DROVE dataset can be used for several applications including evaluation of existing mobility models, development of improved algorithms, and validation of numerical simulations.

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“…A significant number of test results are required to test and develop prediction equations. A recently created database, DROVE 1.0, 12 provided the historic test data considered in this report. DROVE contains records of over 5000 test results with a variety of parameters and experimental procedures.…”

Section: Database Records For Off-road Vehicle Environments 10mentioning

confidence: 99%

“…11 Despite numerous advances in the development of predictive algorithms, the calibration and simplification of existing equations based on a larger database is required. Vahedifard et al 12 evaluated the predictive accuracy of several algorithms used in the Vehicle Terrain Interface (VTI) model by comparing their predictions against measured values available through Database Records for Off-road Vehicle Environments (DROVE) version 1.0, a recently developed database of historic vehicle tests. The comparison results revealed that the VTI algorithms can be further improved to provide more accurate predictions for off-road vehicle performance.…”

Section: Introductionmentioning

confidence: 99%

New algorithms for predicting longitudinal motion resistance of wheels on dry sand

Williams

Vahedifard

Mason

et al. 2017

Journal of Defense Modeling & Simulation

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Predicting the resisting forces against a vehicle's wheel during movement in loose sand is critical for optimizing tractive capabilities in desert regions, sand dunes, and beaches. We review existing braked, powered, and towed motion resistance equations and present improved algorithms based on field and laboratory measurements when the cone index is used to define soil strength. The algorithm predictions are compared against measured values available through Database Records for Off-road Vehicle Environments (DROVE), a database of tests conducted with wheeled vehicles. The examination of braked, towed, and powered motion resistance algorithms is considered for loads varying from 0.187 to 4.49 kN, tire diameters from 0.377 to 1.05 m, and soil strengths from 50 to 800 kPa. A simplified motion resistance algorithm was developed for each operation type utilizing a bootstrap technique. Simple relationships using wheel slip and the ratio of the contact pressure to the cone index are shown to provide predictions of motion resistance with accuracy comparable to more complex empirical models.

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Mobility algorithm evaluation using a consolidated database developed for wheeled vehicles operating on dry sands

Cited by 19 publications

References 10 publications

Performance prediction relationships for AM2 airfield matting developed from full-scale accelerated testing and laboratory experimentation

Performance prediction relationships for AM2 airfield matting developed from full-scale accelerated testing and laboratory experimentation

Development of a multi-year database to assess off-road mobility algorithms in fine-grained soils

New algorithms for predicting longitudinal motion resistance of wheels on dry sand

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