The Next Generation NATO Reference mobility model development

McCullough, Michael; Jayakumar, Paramsothy; Dasch, Jean Muhlbaier; Gorsich, David

doi:10.1016/j.jterra.2017.06.002

Cited by 60 publications

(17 citation statements)

References 6 publications

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“…Courtesy of [McCullough, et al, 2016] The stochastic approach for mobility predictions over large regions should be integrated into NG-NRMM, where both the terrain profile and vehicle-terrain interaction play a key role. The following recommendations are made in Ref.…”

Section: Figure 1 Ng-nrmm Mobility Map Generation -mentioning

confidence: 99%

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Framework of Reliability-Based Stochastic Mobility Map for Next Generation NATO Reference Mobility Model

Gaul

Jayakumar

Wasfy

et al. 2019

Journal of Computational and Nonlinear Dynamics

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A framework for generation of reliability-based stochastic off-road mobility maps is developed to support the next generation NATO reference mobility model (NG-NRMM) using full stochastic knowledge of terrain properties and modern complex terramechanics modeling and simulation capabilities. The framework is for carrying out uncertainty quantification (UQ) and reliability assessment for Speed Made Good and GO/NOGO decisions for the ground vehicle based on the input variability models of the terrain elevation and soil property parameters. To generate the distribution of the slope at given point, realizations of the elevation raster are generated using the normal distribution. For the soil property parameters, such as cohesion, friction, and bulk density, the min and max values obtained from geotechnical databases for each of the soil types are used to generate the normal distribution with a 99% confidence value range. In the framework, the ranges of terramechanics input parameters that will cover the regions of interest are first identified. Within these ranges of input parameters, a dynamic kriging (DKG) surrogate model is obtained for the maximum speed of the nevada automotive test center (NATC) wheeled vehicle platform complex terramechanics model. Finally, inverse reliability analysis using Monte Carlo simulation is carried out to generate the reliability-based stochastic mobility maps for Speed Made Good and GO/NOGO decisions. It is found that the deterministic map of the region of interest has probability of only 25% to achieve the indicated speed.

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Section: Figure 1 Ng-nrmm Mobility Map Generation -mentioning

confidence: 99%

“…Key variables of off-road conditions include those related to terrain elevation and soil property data and their variabilities as shown in Fig. 1 [1]. The ground vehicle parameters and their variabilities could also be addressed for a full stochastics treatment, but were not considered in this study.…”

Section: Introductionmentioning

confidence: 99%

Framework of Reliability-Based Stochastic Mobility Map for Next Generation NATO Reference Mobility Model

Gaul

Jayakumar

Wasfy

et al. 2019

Journal of Computational and Nonlinear Dynamics

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“…The sensitivities were therefore estimated on the basis of a kriging analysis. Kriging is a semi-parametric Gaussian process regression method that was originally developed in the field of geostatistics (Chilès and Delfiner 1999;McCullough et al 2017). It provides an effective means that may be employed to estimate response quantities, and corresponding derivatives and integrals, over a domain of associated input parameters using only noisy observations or measurements for a limited irregularly spaced set of these parameters.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Difference and Sensitivity Analyses of the LEAP-2017 Experiments

Goswami

Zeghal

Kutter

et al. 2019

Model Tests and Numerical Simulations of Liquefaction and Lateral Spreading

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The experimental results of LEAP (Liquefaction Experiments and Analysis Projects) centrifuge test replicas of a saturated sloping deposit are used to assess the sensitivity of soil accelerations to variability in input motion and soil deposition. A difference metric is used to quantify the dissimilarities between recorded acceleration time histories. This metric is uniquely decomposed in terms of four difference component measures associated with phase, frequency shift, amplitude at 1 Hz, and amplitude of frequency components higher than 2 Hz (2 + Hz). The sensitivity of the deposit response accelerations to differences in input motion amplitude at 1 Hz and 2 + Hz and cone penetration resistance (used as a measure reflecting soil deposition and initial grain packing condition) was obtained using a Gaussian process-based kriging. These accelerations were found to be more sensitive to variations in cone penetration resistance values than to the amplitude of the input motion 1 Hz and 2 + Hz (frequency) components. The sensitivity functions associated with this resistance parameter were found to be substantially nonlinear. 132 N. Goswami et al.

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“…In the beginning they were mainly word comments and thematic maps ( Figure 1) [3,4], at present they are mainly outputs of complex models of terrain passability ( Figure 2) [5][6][7][8][9]. All known models of passability [5,6,[9][10][11][12] assess the impact of the terrain on the movement of vehicles in a comprehensive way. The input layers for modeling are slope, soil, vegetation, hydrology, and more.…”

Section: Introductionmentioning

confidence: 99%

Detection of Microrelief Objects to Impede the Movement of Vehicles in Terrain

Dohnal

Hubáček

Šimková

2019

IJGI

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Relief of terrain as a part of the landscape greatly affects the possibilities of vehicles moving off the road. The main influence on the movement is the slope of terrain and the occurrence of microrelief objects. While the slope limits can be easily modeled in the GIS environment, it is difficult to express the effect of the microrelief on the possibilities of moving vehicles. The aim of this work was to find procedures for identification of impassable microrelief objects using GIS tools and precise digital elevation models. Technical parameters defining the ability of a vehicle to overcome microrelief objects are known and these are mainly defined by the dimensions of the vehicle such as a wheel base, a ground clearance, approach angle, and others. Large-scale digital elevation models have not been able to reliably express the location and shape of microrelief objects until recently. Their accuracy of height in nodes achieved meter or decimeter values. The change occurred with the use of airborne laser scanning technology for digital elevation model creation. The accuracy of models created using this technology achieves centimeter values. These can be used for detection of microrelief objects. One of these models is the DMR5 from the territory of the Czech Republic. Its declared total mean height error is 0.18 meters. This model, together with the GIS tools and the technical parameters of individual vehicles, was used to search for such microrelief objects that act as a barrier to movement. Procedures for detecting impassable microrelief objects were created by ArcGIS tools. Modeling tools and mathematical methods were used to create procedures for detection of microrelief objects. These have been applied to selected locations in the Czech Republic. Raster layers representing individual impassable microrelief objects are the result of modeling. The modeling results were verified in the terrain using military vehicles. Field tests confirmed the high reliability of the proposed procedure. Therefore, the calculation process was optimized and will be introduced in the future as one of the input calculations of the complex model of passability in the Army of the Czech Republic.

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The Next Generation NATO Reference mobility model development

Cited by 60 publications

References 6 publications

Framework of Reliability-Based Stochastic Mobility Map for Next Generation NATO Reference Mobility Model

Framework of Reliability-Based Stochastic Mobility Map for Next Generation NATO Reference Mobility Model

Difference and Sensitivity Analyses of the LEAP-2017 Experiments

Detection of Microrelief Objects to Impede the Movement of Vehicles in Terrain

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