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Stress-strain behaviour of agricultural soils: towards new approaches (StressSoil) Synopsis: Soil compaction is a serious problem in modern agriculture. State-of-the-art soil compaction models derive from foundation engineering and consider soils as continuous and homogeneous media. However, agricultural soils are structured at different scales. Modelling mechanical strength as a probability-distribution function will account for anisotropy and scale-dependency of soil physical properties. Discrete elements models can integrate this information. This project will evaluate and implement the new approach, and hence contribute to more precise prediction, i.e. prevention of soil compaction. Fig. 1. Soil mechanical properties are, like soil structure, scale dependent and their distribution in the soil profile follows a probability distribution. This can be included in discrete elements models (DEM), in contrast to state-of-the-art compaction models, which consider soil as an elastic or elastoplastic continuous material. The different concepts are illustrated here by the probability, P, of the soil tensile strength τ, as an example. 1. Objectives Prevention of soil compaction requires accurate predictions of stress propagation in the soil profile to be compared to reliable soil failure criteria (i.e. soil strength quantification). Up to date, soil compaction models consider agricultural soils as elastic or elasto-plastic continuous materials when calculating stress propagation, and soil failure is evaluated from measurements of bulk soil compressive strength in the laboratory. However, agricultural soils are aggregated at various scales (Fig. 1). Hence, Soil resistance to deformation is as stochastic and scale-dependent as the structure. Discrete element models (DEM) offer a framework that can be used to understand the effect of stochastic structural features on stress propagation and deformation behaviour of aggregated agricultural soils (Fig. 1). We postulate that soil mechanical properties are scale dependent and that their distribution in the soil profile follows a probability distribution that can be described by discrete elements models (DEM). Our approach centres on the followings hypotheses: H1: Inter-particle bonds are the relevant soil mechanical parameters for the definition of the soil failure criterion (WP1, WP2, WP4, WP6) (“particle” refers to textural particles and structural units). H2: Inter-particle bonds follow a continuous probability distribution (e.g. Weibull distribution) integrating their 1 scale dependency (WP1). H3: The parameters of the probability distribution describing mainly cohesion and friction will enhance the prediction of soil compaction through DEM simulations (WP1, WP3, WP4, WP5, WP6, WP7). Based on these hypotheses, the main project objective is to implement an alternative model for predicting soil compaction ready for use in decision support tools created by the project consortium in other running projects. 2. State-of-the-art Soil compaction is a major threat to a sustained soil quality in modern, mechanized agriculture. A range of important ecological functions are affected when soil is compressed: increase in surface runoff, water erosion, loss of nutrients and pesticides to the groundwater, increase in the production of greenhouse gases, reduction in crop yields (e.g. van Ouwerkerk and Soane, 1995). Soil compaction is defined as a reduction in volume of a soil element subjected to mechanical stresses. On arable soil, these mechanical stresses originate mostly from traffic by agricultural vehicles. At present, the prediction of sustainable traffic on heterogeneous agricultural soils is based on: (i) calculations of stress transmission where soils are considered as perfectly elastic or elasto-plastic materials with isotropic mechanical properties; (ii) methodological approaches for assessment of soil strength that were developed for foundation engineering where large static loads are applied on homogeneous soils. State-of-the-art soil compaction models suffer from drawbacks such as insufficient knowledge about the effects of soil conditions (i.e. soil type, structure, moisture, density, etc.). The continued use of these models is despite even early work identified influences of soil structural heterogeneities on stress propagation (Taylor and Burt, 1987; Dexter et al., 1988). Recent studies further documented that the analytical model based on the elasticity theory could not describe the stress propagation in arable soils when deformations occurred (Lamandé et al., 2007; Keller and Lamandé, 2010; Lamandé and Schjønning, 2011). Even more important is the inadequacy of classical tests for soil compressive strength in predicting soil failure during wheel traffic in agricultural soils (e.g. Trautner, 2003; Arvidsson and Keller, 2004; Keller et al., 2004; Mosaddeghi et al., 2007; Keller et al., 2011). Three main reasons for this inadequacy can be identified: (i) during traffic, stress application is thousands times shorter than during the laboratory test (Keller & Lamandé, 2010), and the longer stresses are applied the larger the final strain (Or and Ghezzehei, 2002); (ii) the direction of major principal stress is not constant during traffic, which means that shear as well as compressive strength should be taken into account (Kirby, 1991; Lamandé et al., 2007); (iii) neither soil structure nor soil strength are isotropic or equally distributed at all scales (Peng and Horn, 2008). Soil 2 mechanical properties, needed to calculate stress-strain behaviour, depend on the soil type, on the scale and are anisotropic. Probability-distribution functions (e.g. Weibull, 1951) have successfully been used to describe particle size distribution (Rosin and Rammler, 1933; Keller and Håkansson, 2010; Keller et al., 2011), aggregate size distribution (Perfect et al., 1993; Keller et al., 2011) or tensile strength (e.g., Munkholm et al., 2002). Soils are structured (voids and compound particles of different size and shape) and fractured (e.g. drying cracks) (e.g. Dexter, 1988), which implies that soil may be better characterized as a granular (where the elements represent the soil structural features) than a continuum material. Discrete element models (DEM; e.g. Cundall & Strack, 1979) offer a framework that can be used to understand particle-particle contact properties, stress propagation (Radjai, 1998) and displacement behaviour of granular media. Recent studies in granular material science focused on the influence of various local properties such as particle size distribution (Voivret et al., 2007), frictional sliding and rolling (Estrada et al., 2008), particle shape (Azema et al, 2009), and cohesion (Delenne et al., 2004) on stress-strain behaviour of geomaterials. To our knowledge, DEM has not been used to simulate soil compaction due to agricultural field traffic, but it may provide a promising method for better understanding soil deformation and stress transmission at different scales (Van Baars, 1996; Delenne et al., 2004; Zhang and Li, 2006; Lamandé et al., 2010). 3. Project organisation The project will be lead by Per Schjønning, who has extensive experience in leading research projects and supervising PhD students. A leader for each of the seven workpackages has been appointed (please see Section 4), reflecting the complementary scientific experience of the research group. A PhD study, funded by the Dept. of Agroecology and Environment (Aarhus University), including both experimental and modelling work, will be conducted in the project and supervised by project participants. It will focus on the definition of scaledependent soil strength expressions and their implementation in DEM (WP1, WP3, WP5). 4. Research plan and methodology The project is composed of three themes. Theme 1 focuses the soil mechanical properties on a discrete element basis. In theme 2 we will perform experiments on the soil as a system. And in theme 3 we put the knowledge together in models. 3 Theme 1. Soil mechanical properties WP 1. Scale-dependent soil strength expressions (Mathieu Lamandé) Objective and approach: To quantify mechanical strength as a probabilitydistribution function. Shear parameters (cohesion and friction) will be measured using the direct shear box method on soil cores sampled systematically on a grid in soil profiles and on samples of different sizes. This sampling will be repeated for several soils presenting contrasted texture and structure, and different soil water suction for each soil type. A probabilitydistribution function (e.g. Weibull, 1951) will be fitted to the experimental data, and the adjusted values for the parameters of this function will be related to intrinsic soil properties. WP 2. Soil failure and soil functions (Per Schjønning) Objective and approach: To quantify soil failure effects on soil pore functioning for different stress fields, i.e. for different combinations of the major and minor principal stress. Soil samples are collected at different coordinates in the profile of a soil subjected to controlled stress application. Air permeability at controlled water suction is used as a structural fingerprint reflecting the effect of compressive and shear strains. Theme 2. System experimentation WP 3. Test for an idealized discrete element soil (Mathieu Lamandé) Objective and approach: To characterise stress-strain behaviour of beads of soil aggregates under loading. Soil aggregates will be sampled in the field. Tensile strength and compressive strength of each aggregate type/size, and cohesion between aggregates will be measured, at controlled water suction, in the laboratory. Soil aggregates will be rearranged in a device equipped with stress sensors in the laboratory. The walls of the device will be transparent to allow the visualisation in 2D of aggregate movement and deformation during loading. WP 4. Tests for real soil (Mathieu Lamandé) Objective and approach: To quantify vertical and horizontal stresses in situ during loading (Lamandé et al., 2006), as well as deformation in 3D using very sensitive micro4 accelerometers (MicroStrain®). Stochastic variations will be covered by the measurements program to be able to relate to the activities in WP 1. Strains will be related to soil pore functions measured in WP2. Theme 3. Discrete Element Modelling WP 5. Stress-strain behaviour simulated with DEM (Jean-Yves Delenne) Objectives and approach: (i) To implement the mechanical strength as a probabilitydistribution function in DEM, and (ii) to simulate traffic on the idealized discrete elements soil. Experiments of WP3 and WP4 will be used to parameterize DEM simulations: compressive and tensile strength of aggregates will be used as input values to the model. Simulations outputs will be evaluated by the stress-strain measurements performed in WP3 and WP4. A sensitivity analysis of the effect of the probability-distribution function parameters on the stress propagation will be conducted. WP 6. Soil failure criteria (Thomas Keller) Objective and approach: To develop new soil failure criteria from the scale-dependent soil strength expressions (WP1) and soil pore functions (WP2). The new failure criteria will combine the probability distribution for soil strength with characteristics of the stress field. WP 7. Synthesis: DEM for decision support (Mathieu Lamandé) Objective and approach: To develop a pedo-transfer function for the parameters of the probability-distribution function. Interpretation of data from WP1 and meta-analysis of a comprehensive data set collected in a previous project (Schjønning, 1991, 1999) will provide the basis for correlations between intrinsic soil properties (e.g. soil texture) and soil water suction on one side and the probability distribution for soil strength on the other side. An alternative model for predicting soil compaction ready for use in the TERRANIMO decision support tool (www.soilcompaction.eu) decision support tool will be implemented. 5. Dissemination The www.soilcompaction.eu web platform will be used by the project group and added with a component describing achievements of the StresSoil project to the public. The project results will be integrated in the TERRANIMO decision support tool available to the public at the same platform. The wheel load carrying capacity maps of Europe produced by the ICT-AGRI project “PredICTor” as a deliverable to the EU Joint Research Centre will similarly be updated with the discrete element approach. The StressSoil project aims at eight peerreviewed publications covering the basic soil mechanical approach as well as the impacts of the results on decision support tools. 5 References Arvidsson, J. & Keller, T. 2004. Soil precompression stress. I. A survey of Swedish arable soils. Soil Tillage Res. 77, 85-95. Azéma, E., Radjai, F., Saussine, G., 2009. Quasistatic rheology, force transmission and fabric properties of a packing of irregular polyhedral particles. Mechanics of Materials 41, 729741. Cundall, P.A., Strack, O.D.L., 1979. A discrete numerical model for granular assemblies. Géotechnique 29, 47-65. 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