Journal of Terramechanics最新文献_第7页

Modelling and simulation fundamentals in design for ground vehicle mobility part I: Eastern approach 地面车辆机动性设计中的建模和仿真基础 I 部分：东方方法

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-10-19 DOI: 10.1016/j.jterra.2024.101020

Vladimir Vantsevich , David Gorsich

For many decades, different approaches, fundamentals, and expressions have been developed in various countries for military vehicle modelling and simulation (M&S) as a core component of ground vehicle design for mobility. The political division of the world into the West and East that existed before the Soviet Union breakdown in 1991 had not facilitated collaboration between researchers and engineers of both sides, and, thus, they created and practiced their own approaches. The war in Ukraine urgently prompted analysis of the origins and essence of the Western and Eastern technical paradigms, which being conceptually different to ground vehicle mobility, had predetermined the development of vehicle M&S methods and techniques in their parts of the world, specifically for studying dynamic interactions of vehicles with severely uncertain terrains, which impact vehicle behavior and performance, and, thus, may either facilitate mission accomplishment or lead to its failure. Furthermore, this analysis of the technical paradigms aims to further advance M&S fundamentals for next generation combat vehicles as described in the U.S. Army’s 2019 Modernization Strategy. Part I of this article considers the Eastern approach and the Western approach is presented in Part II.

几十年来，各国在军用车辆建模与仿真（M&S）方面形成了不同的方法、基本原理和表达方式，这是地面车辆机动性设计的核心组成部分。1991 年苏联解体之前，世界在政治上被划分为西方和东方，这不利于双方研究人员和工程师之间的合作，因此，他们创造并实践了各自的方法。乌克兰战争迫切需要对东西方技术范式的起源和本质进行分析，由于概念上与地面车辆机动性不同，东西方的技术范式预先决定了各自地区车辆 M&S 方法和技术的发展，特别是在研究车辆与严重不确定地形的动态相互作用时，这种相互作用会影响车辆的行为和性能，从而可能促进任务的完成，也可能导致任务失败。此外，对技术范例的分析旨在进一步推进美国陆军 2019 年现代化战略中描述的下一代战车的 M&S 基础知识。本文第一部分介绍了东方方法，第二部分介绍了西方方法。

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引用次数: 0

Towards more efficient tractors: Assessing and refining traction test procedures for agricultural tractors 提高拖拉机的效率：评估和完善农用拖拉机牵引力测试程序

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-10-09 DOI: 10.1016/j.jterra.2024.101018

Leonardo Angelucci , François Pinet , Andrea Vertua , Michele Mattetti

A reliable testing procedure is needed to benchmark different vehicle and tyre parameters. Several testing procedures within two main families – transient and steady states – were adopted to evaluate drawbar performance of tractors. The two procedural families were not hitherto compared using a full vehicle. This article aims to fill this gap. The transient and steady-state procedures were tested using a tractor rated of 230 kW sets in different configurations and equipped with sensors for evaluating the tractive parameters. In the transient procedure, the drawbar load was continuously increased to maintain a fixed ground speed. In the steady-state procedure, the drawbar load was gradually increased by reducing the ground speed. The maximum drawbar force generated by the tractor differed little between procedures, but a difference was observed in power delivery efficiency, mostly for the transmission’s influence during transient conditions leading to variable transmission efficiency. The results of the steady-state procedure for different vehicle configurations were more consistent with findings in the literature than those of the transient procedure. The steady-state procedure is better than the other but it requires more land and therefore it is less convenient when drawbar performances must be quickly evaluated for many vehicle and soil configurations.

需要一种可靠的测试程序来确定不同的车辆和轮胎参数。我们采用了瞬态和稳态两大类测试程序来评估拖拉机的牵引杆性能。迄今为止，尚未使用整车对这两个程序系列进行比较。本文旨在填补这一空白。瞬态和稳态程序使用额定功率为 230 千瓦的拖拉机进行了测试，拖拉机采用不同的配置，并配备了用于评估牵引参数的传感器。在瞬态程序中，牵引杆负载不断增加，以保持固定的地面速度。在稳态程序中，通过降低地面速度逐渐增加牵引力。拖拉机产生的最大牵引力在不同程序中差别不大，但在动力传输效率方面却出现了差异，这主要是由于变速器在瞬态条件下的影响导致了变速器效率的变化。与瞬态程序相比，不同车辆配置的稳态程序结果与文献研究结果更为一致。稳态程序比其他程序更好，但它需要更多的土地，因此在必须快速评估许多车辆和土壤配置的牵引杆性能时，它不太方便。

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引用次数: 0

Predicting terrain deformation patterns in off-road vehicle-soil interactions using TRR algorithm 利用 TRR 算法预测越野车与土壤相互作用的地形变形模式

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-10-09 DOI: 10.1016/j.jterra.2024.101021

Behzad Golanbari , Aref Mardani , Adel Hosainpour , Hamid Taghavifar

Soil deformation is one of the parameters affecting the performance of off-road vehicles, including traction, mobility, and steering. This study offers an examination of soil deformation resulting from interactions with pneumatic and track wheels. Experiments were conducted using a soil bin with a single-wheel test rig, equipped with both a standard agricultural tire and a customized track wheel. Three distinct levels of vertical loads (2, 3, and 4kN) and forward velocities (1, 2, and 3 km/h) were applied using the wheel tester. The displacement and deformation of the soil layers, visualized as a vertical cross-section along the motion path, were consistently prepared and photographed for all experiments. Image analysis was undertaken with MATLAB software to scale images and extract graphical data. The highest deformation, with a value of 60.86 mm, is associated with the interaction of a pneumatic wheel with a force of 4 kN, while the lowest deformation occurs when the soil interacts with a track wheel with a force of 2 kN, with a value of 25.05 mm. Furthermore, the fitted surfaces obtained using the optimization algorithm showed good convergence with the experimental data, with R² values of 0.9783 and 0.9516 for the pneumatic tire and tracked tire, respectively. The results demonstrated that the TRR model performs well in accurately predicting soil deformation induced by various types of wheels. A comparison between soil deformations caused by track wheels and pneumatic wheels revealed that track wheels result in less deformation and disturbance, particularly in the upper soil layers. These findings underscore the importance of considering the type of traction device and loading conditions when assessing soil deformation in agricultural environments.

土壤变形是影响越野车牵引力、机动性和转向等性能的参数之一。本研究对与气动轮和履带轮相互作用产生的土壤变形进行了研究。实验使用土壤仓和单轮试验台进行，试验台配备了标准农用轮胎和定制履带轮。使用轮式测试仪施加了三个不同水平的垂直荷载（2、3 和 4kN）和前进速度（1、2 和 3 km/h）。土层的位移和变形沿运动轨迹以垂直横截面的形式呈现，所有实验都进行了统一的准备和拍照。使用 MATLAB 软件进行图像分析，以缩放图像并提取图形数据。变形量最大的是与力为 4 千牛的气动轮相互作用时，变形量为 60.86 毫米；而变形量最小的是与力为 2 千牛的履带轮相互作用时，变形量为 25.05 毫米。此外，利用优化算法获得的拟合曲面与实验数据的收敛性良好，充气轮胎和履带轮胎的 R2 值分别为 0.9783 和 0.9516。结果表明，TRR 模型在准确预测各种车轮引起的土壤变形方面表现良好。对履带车轮和充气车轮引起的土壤变形进行比较后发现，履带车轮引起的变形和扰动较小，尤其是在土壤上层。这些发现强调了在评估农业环境中的土壤变形时考虑牵引装置类型和负载条件的重要性。

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引用次数: 0

Terrain classification and rock abundance analysis at Utopia Planitia using Zhurong image data based on deep learning algorithms 基于深度学习算法，利用祝融影像数据对乌托邦行星进行地形分类和岩石丰度分析

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-10-09 DOI: 10.1016/j.jterra.2024.101022

Yan Shen , Dong Pan , Hongtao Cao , Baofeng Yuan , Yang Jia , Lianbin He , Meng Zou

The complexity of image scene information presents challenges for the trafficability assessment and path planning of Mars rovers. To ensure the operational safety of Mars rovers and extract terrain features from complex image scenes, this paper develops an end-to-end deep learning model, using the deep convolutional neural networks ResNet50 and DeepLabV3 + as the framework, with images from the Zhurong rover’s navigation camera as the training and test datasets. A deep learning model suitable for classification and segmentation of terrain in the Mars Utopia Planitia region has been established and applied to planetary geology research. The classification accuracy of model exceeds 83.90 % and segmentation accuracy exceeds 80 %. Subsequently, an analysis of 1309 raw images from the navigation camera yielded 203,744 individual estimates of rock abundance, the model evaluates the rock abundance in the Utopia Planitia region, where the Zhurong rover is located, at 10.94 %. The terrain classification model proposed in this study provides both engineering and scientific value for future rovers on the Utopia Planitia.

图像场景信息的复杂性给火星车的交通性评估和路径规划带来了挑战。为了确保火星车的运行安全，并从复杂的图像场景中提取地形特征，本文以深度卷积神经网络ResNet50和DeepLabV3 +为框架，以 "祝融号 "火星车导航相机的图像为训练和测试数据集，建立了端到端的深度学习模型。建立了适用于火星乌托邦地区地形分类和分割的深度学习模型，并将其应用于行星地质研究。模型的分类准确率超过 83.90%，分割准确率超过 80%。随后，对导航相机拍摄的 1309 幅原始图像进行了分析，得出了 203744 个岩石丰度估算值，该模型评估出 "祝融 "号探测器所在的乌托邦星区的岩石丰度为 10.94%。本研究提出的地形分类模型为未来在桃花星上的漫游车提供了工程和科学价值。

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引用次数: 0

Tire sinkage measurement and entry angle calculation using stereo cameras 使用立体相机测量轮胎下沉量并计算进入角

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-10-07 DOI: 10.1016/j.jterra.2024.101019

Hannah White , Corina Sandu , Jyotirmoy Mukherjee , Andrea L’Afflitto , David Gorsich , Michael Cole

In the modern world the use of autonomous vehicles is growing more and more common. There are many applications for autonomous vehicles on deformable terrain, such as in military, farming, and mining but the problem with most established autonomous vehicle models is that they do not take into account the effect the terrain has on vehicle performance. To be able to accurately include these values in the vehicle model, they need to be directly sensed or estimated. One of the most valuable of these values is the tire sinkage. Tire sinkage is very important when it comes to terrain-vehicle interaction. The slip-sinkage relationship is an important factor in tractive performance. This paper is part of a larger project that is working on autonomy in conditions with deformable terrain and this paper presents on the methods employed to measure and find important values for the terramechanics of the model. This study specifically focuses on measuring the rut depth left behind after a tire travels over the terrain using a set of two stereo cameras. The sinkage is then used to be able to find the entry angle of the tire in the terrain.

在现代社会，自动驾驶汽车的使用越来越普遍。自动驾驶车辆在可变形地形上有很多应用，如军事、农业和采矿，但大多数已建立的自动驾驶车辆模型的问题在于，它们没有考虑到地形对车辆性能的影响。为了能够在车辆模型中准确地包含这些值，需要直接感知或估算这些值。其中最有价值的数值之一是轮胎下沉量。在地形与车辆相互作用方面，轮胎下沉量非常重要。滑移-下沉关系是影响牵引性能的重要因素。本文是一个大型项目的一部分，该项目致力于在可变形地形条件下实现自动驾驶，本文介绍了测量和查找模型地形力学重要值的方法。这项研究的重点是使用两台立体摄像机测量轮胎碾过地形后留下的车辙深度。然后，利用下沉量可以找到轮胎在地形中的进入角。

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引用次数: 0

Natural recovery of different soil types after passes by wheeled military truck: Implications for soil as a ground for follow-on mobility operations 轮式军用卡车通过后不同土壤类型的自然恢复：土壤作为后续机动作战地面的意义

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-09-27 DOI: 10.1016/j.jterra.2024.101017

Kersti Vennik

The trafficking of off-road military vehicles generates disturbed soil conditions. Thus, former active combat areas can have a serious effect on subsequent operations. More precisely, an uneven soil surface will remarkably increase the vibration of travelling vehicles, and over-compacted as well as displaced soil layers affect soil water dynamics that, in turn, have a long-lasting effect on soil strength. In addition, soil as a habitat for plants must provide air, water, and nutrients for the plants to grow. Luckily, soil can naturally recover from being disturbed thanks to freezing-thawing cycles, wetting–drying cycles, and biological activity. However, the rate of recovery depends on the physical parameters of soil. The objective of this study was to monitor and summarize the natural recovery rate of soils. As an experiment, single pass and repeated passes with military trucks (total weight 70 kN) were carried out. The ruts that formed were monitored and soil samples were collected up to 2 years after wheeling. The rut depth, cone index values, bulk density, soil moisture content as well as field-saturated hydraulic conductivity were measured and soil pore size distribution was determined in a laboratory during the entire studied recovery period. The results about the natural recovery on different soils are presented herein.

越野军用车辆的贩运会造成土壤条件紊乱。因此，前作战地区会对后续行动产生严重影响。更确切地说，不平整的土壤表面会显著增加行驶车辆的振动，过度压实和移位的土层会影响土壤水分动态，进而对土壤强度产生长期影响。此外，土壤作为植物的栖息地，必须为植物生长提供空气、水和养分。幸运的是，由于冰冻-解冻周期、湿润-干燥周期和生物活动的作用，土壤受到扰动后可以自然恢复。不过，恢复速度取决于土壤的物理参数。本研究的目的是监测和总结土壤的自然恢复率。作为一项实验，使用军用卡车（总重量 70 千牛）进行了单次通行和多次通行。对形成的车辙进行了监测，并收集了车轮碾压两年后的土壤样本。在整个研究恢复期间，在实验室测量了车辙深度、锥体指数值、容重、土壤含水量以及实地饱和导水率，并测定了土壤孔径分布。本文介绍了不同土壤的自然恢复结果。

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引用次数: 0

Tractive performance of rigid wheel in granular media using coarse-scale DEM models 利用粗尺度 DEM 模型实现刚性车轮在颗粒介质中的牵引性能

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-09-26 DOI: 10.1016/j.jterra.2024.101016

Bohumir Jelinek , Angela Card , George L. Mason , Karl Grebner , Aidan Dickerson , Thomas Skorupa , Michael Cole , Jody D. Priddy

Understanding interactions between wheel and granular media in variable loading conditions is critical for prediction of mobility of wheeled vehicles in off-road environments. The discrete element method (DEM) is routinely used for modeling vehicle off-road performance, but the method’s accuracy is often not fully established.

In this work, the DEM modeling accuracy is assessed by the comparison of ten DEM soil models with laboratory soil-bin measurements of net traction, gross traction, and sinkage of a wheel operating in sand. Laboratory soil-bin measurements, serving as reference for DEM simulations, were taken from physical experiments by Shinone et al. (2010), examining a 165/60R13 wheel with circumferential velocity of 97.6 mm/s and vertical contact load of 980 N in varying slip conditions.

The set of ten DEM models was selected from the Generic EDEM Material Model database from Altair®’s EDEM™ software package, choosing the materials matching the bulk density and angle of repose for dry sand.

Given the large particle size and no additional calibration of the DEM models, finding overall reasonable match with the gross traction from lab measurements and identifying a material predicting the net traction with a satisfiable accuracy encourages further use, refinement, and calibration of the DEM-based soil models.

了解车轮和颗粒介质在不同载荷条件下的相互作用对于预测轮式车辆在越野环境中的机动性至关重要。离散元法（DEM）通常用于车辆越野性能建模，但该方法的准确性往往尚未完全确定。在这项工作中，通过比较十个 DEM 土壤模型和沙地车轮净牵引力、总牵引力和下沉量的实验室土壤箱测量结果，评估了 DEM 建模的准确性。作为 DEM 模拟参考的实验室土仓测量数据来自 Shinone 等人（2010 年）的物理实验，在不同滑移条件下对圆周速度为 97.6 mm/s、垂直接触载荷为 980 N 的 165/60R13 车轮进行了测试。由于 DEM 模型的粒度较大，且无需额外校准，因此从实验室测量结果中找到了与总牵引力总体上合理匹配的材料，并确定了一种可预测净牵引力且精度令人满意的材料，从而鼓励了对基于 DEM 的土壤模型的进一步使用、改进和校准。

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引用次数: 0

Predicting the impact of wheel passage on terrain unevenness 预测车轮通过对地形不平的影响

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-09-24 DOI: 10.1016/j.jterra.2024.101015

Antonio Leanza, Angelo Ugenti, Rocco Galati, Giulio Reina

This article presents a novel approach to accurately predict how terrain unevenness is modified by the passage of a wheel under varying operating conditions. The proposed method uses a moving average filter to model the deformation of the soft soil caused by the rolling wheel. The window length of the filter is determined by key terrain parameters as well as the geometry of the wheel. The method’s accuracy and robustness are validated through a series of comparisons with a high-fidelity model developed in the multibody simulation environment MSC Adams, along with an experiment conducted in a real agricultural scenario. This model incorporates classical terramechanics theory to simulate the complex interactions between the wheel and the terrain. Key findings indicate that the moving average filter approach not only simplifies the computational process but also maintains a high degree of accuracy in predicting terrain deformation across a range of operating conditions. This method offers significant potential for improving the design and optimization of off-road vehicles, agricultural machinery, and planetary rovers by providing a more efficient tool to assess terrain interaction dynamics. In general, this study lays the foundations for advances in understanding and predicting terrain behavior under the influence of rolling wheels, contributing to the broader field of vehicle-terrain interaction research.

本文提出了一种新方法，用于准确预测车轮在不同运行条件下通过时如何改变地形的不平整度。所提出的方法使用移动平均滤波器对车轮滚动造成的软土变形进行建模。滤波器的窗口长度由主要地形参数和车轮的几何形状决定。通过与在多体仿真环境 MSC Adams 中开发的高保真模型以及在真实农业场景中进行的实验进行一系列比较，验证了该方法的准确性和稳健性。该模型结合了经典的地形力学理论，模拟了车轮与地形之间复杂的相互作用。主要研究结果表明，移动平均滤波器方法不仅简化了计算过程，而且在预测各种运行条件下的地形变形时保持了很高的准确性。这种方法为评估地形相互作用动力学提供了更有效的工具，从而为改进越野车、农业机械和行星漫游车的设计和优化提供了巨大的潜力。总之，这项研究为进一步了解和预测滚动车轮影响下的地形行为奠定了基础，为更广泛的车辆-地形相互作用研究领域做出了贡献。

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引用次数: 0

Design and development of jamming-based stiffness-adjustable wheel on soft terrain 设计和开发基于干扰的软地形刚度可调车轮

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-09-19 DOI: 10.1016/j.jterra.2024.101014

Tachadol Suthisomboon, Stephane Bonardi, Genya Ishigami

Traversing soft terrain poses a major challenge for planetary wheeled rovers, and various studies have demonstrated ways to enhance rover mobility by transforming the wheel structure or adjusting the wheel’s stiffness, which results in a change in wheel contact area on the terrain. This paper presents a novel idea using the jamming mechanism for modulating the wheel’s stiffness. The developed wheel consists of the core body, wheel outer rim, inner flexure, and cable tension mechanism. The jamming mechanism is realized by adjusting the cable tension inserted between the outer rim of the wheel. The wheel stiffness measuement test confirms that the wheel with low stiffness can reduce its stiffness for 75% of the high stiffness configuration. The wheel’s traversability on soft terrain are also evaluated based on slip ratio and current consumption. The results demonstrate that the lower-stiffness configuration outperforms the higher-stiffness wheel under various conditions. These findings, being consistent with previous works on flexible wheels, highlight the potential benefits of the jamming-based stiffness-adjustable wheel for rough terrain traverse with various payload conditions.

穿越松软地形对行星轮式漫游车来说是一项重大挑战，各种研究已经证明了通过改变车轮结构或调整车轮刚度来增强漫游车机动性的方法，从而改变车轮与地形的接触面积。本文提出了一种利用干扰机制来调节车轮刚度的新思路。所开发的车轮由核心主体、车轮外圈、内挠和拉索张紧机构组成。干扰机构是通过调整插入轮毂外缘之间的拉索张力来实现的。车轮刚度测量试验证实，低刚度车轮的刚度可降低到高刚度配置的 75%。此外，还根据滑移率和电流消耗评估了车轮在松软地形上的可穿越性。结果表明，在各种条件下，低刚度配置的车轮都优于高刚度车轮。这些研究结果与之前关于柔性车轮的研究结果一致，凸显了基于干扰的刚度可调车轮在各种有效载荷条件下穿越崎岖地形的潜在优势。

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引用次数: 0

Shortwave infrared fusion for snow surface traversability mapping 融合短波红外线绘制雪面可穿越性地图

IF 2.4 3区工程技术 Q3 ENGINEERING, ENVIRONMENTAL

Journal of Terramechanics

Pub Date : 2024-09-17 DOI: 10.1016/j.jterra.2024.101010

Anthony T. Fragoso, Sarah M. Piedmont

Estimating the mechanical properties of snow from imagery is an essential part of over-snow vehicle autonomy. However, snow surfaces that differ widely in strength, traction, and motion resistance tend to appear a uniform bright white in visible or broadband infrared imagery, and it is difficult to determine where an oversnow vehicle should operate from imagery alone. In this work we determine the optimal fusion of filtered broadband shortwave infrared (SWIR) imagery to separate snow types with different mechanical properties by appearance. We demonstrate vastly increased discrimination skill in distinguishing snow types using a small number of SWIR cameras in both field and laboratory settings, and also identify sources of environmental context that can improve lookahead sensing for oversnow vehicles. Overall, we show that a small set of inexpensive SWIR filters is a powerful tool for over-snow autonomy and motion planning.

从图像中估计雪的机械特性是雪地车自动驾驶的重要组成部分。然而，在可见光或宽带红外图像中，强度、牵引力和运动阻力差异很大的雪面往往呈现出统一的亮白色，因此很难仅凭图像确定雪地车的运行位置。在这项工作中，我们确定了滤波宽带短波红外（SWIR）图像的最佳融合方式，以通过外观区分具有不同机械特性的雪类型。我们证明了在野外和实验室环境中使用少量 SWIR 摄像机区分雪类型的辨别能力大大提高，同时还确定了可改善雪地车前瞻性传感的环境背景来源。总之，我们证明了一小套廉价的 SWIR 滤波器是实现雪上自动驾驶和运动规划的强大工具。

引用次数: 0