The discrete element method (DEM) has demonstrated significant advantages in simulating soil-tool interaction and an appropriate contact model notable affected the simulation accuracy. The accuracy of numerical simulation is compromised due to the variations in soil properties when tillage implements are employed in clay-moist soil conditions. This study aims to establish a discrete element model of clay-moist soil based on the Edinburgh Elasto-Plastic Adhesion (EEPA) contact model. Calibration tests using a combination of direct shear tests and cone penetration tests were conducted to identify sensitive parameters that need to be calibrated in the model and analyze the effects of each parameter. The results indicated that contact plasticity ratio and surface energy had significant influence on representing the mechanical properties of clay-moist soil. Then, by utilizing scanning technology to acquire furrow shape data, soil bin test was conducted to validate the reliability of the calibration parameters. Using sensitive parameters as variables, the actual value of clay-moist soil with a moisture content of 33 % as the target value obtained from experimental tests. The optimal combination was: the coefficient of static friction of 0.45, the coefficient of rolling friction of 0.18, and the surface energy of 27.95 J.m-2, the contact plasticity ratio of 0.59. The relative error between the simulated draft force value and the actual measured value was 7.98 %, and the relative errors in the furrow type parameters did not exceed 5 %. The accuracy of the calibration results was verified through comparative analysis of simulation and empirical results. This study provides a scientific approach for employing DEM in modeling clay-moist soil-tool interaction.

Discrete element modeling (DEM) is a useful tool for linking global responses of granular materials to underlying particle-level interactions. A DEM model capable of capturing realistic soil behavior must be calibrated to a reference dataset, typically consisting of laboratory experiments. Calibration of a DEM model often requires numerous simulations as contact parameters need to be iterated upon until the simulation results satisfactorily replicate the experimentally observed behaviors. This paper presents a sensitivity investigation that examines the effects of the contact parameters on the drained triaxial compression response of a poorly-graded sand. It then introduces a calibration procedure capable of providing contact parameters that satisfactorily reproduce the results of laboratory triaxial results in a few simulations. Results show that friction and rolling resistance coefficients jointly influence the mobilized peak and critical state friction angles, secant shear modulus, maximum dilation rate, total volumetric strain, and strain softening magnitude. These parameters also influence the mode of failure at contacts and the evolution of fabric anisotropy. The influence of mu r or mu on the triaxial response and particle-level interactions is coupled, becoming more profound as the other parameter is increased. Contact stiffness is shown to influence the shear modulus and volumetric change behavior independently of mu and mu r. An algorithm that estimates values for mu and mu r needed to reproduce experimental results is developed using triaxial response parameters from experimental datasets. The performance of the proposed calibration method is demonstrated for three natural sands showing that it provides appropriate calibrated parameters for poorly graded sands with different relative densities and confined with varying effective stress magnitudes.

Precise calibration of constitutive models for cyclic liquefaction is essential but often time-consuming and requires significant expertise, limiting broader application in geotechnical practice. This paper introduces an automatic calibration tool designed to streamline the process for advanced constitutive models under both monotonic and cyclic loading. The tool supports various types of monotonic and cyclic laboratory test data, offers multiple choices of suitable comparison planes for error calculation, with a focus to also suit cyclic liquefaction problems, and employs advanced optimization techniques. The calibration follows a two-stage approach: first, optimizing parameters governing monotonic response using monotonic test data; second, refining these and additional parameters with both monotonic and cyclic data. The critical state parameters are fixed throughout, while the elasticity parameters are fixed in the second stage, all within defined bounds. Using this automatic calibration tool and the adapted calibration strategy, extensive element-level test data was used to determine the parameters of the SANISAND-MSf model for a given sand. These calibrated parameters were then used to simulate boundary value problems, including centrifuge tests of liquefiable sand slopes and sheet-pile-supported liquefiable sand deposits, all subjected to base excitations, demonstrating excellent alignment with experimental results. This validation highlights the robustness, reproducibility, and accuracy of the tool to model cyclic liquefaction while significantly reducing the expertise and time required for calibration. This represents a significant advancement toward the broader adoption of advanced constitutive soil models in geotechnical engineering practice.

Current practice to model the occurrence of submarine landslides is based on methods that assess the potential of site-specific failures, all with the objective of providing elements to identify and quantify regional features associated to geohazards, before a project development takes place. Also, survey data to estimate parameters required to model submarine landslides show typically limited availability, mainly because of the cost associated to offshore surveying campaigns. In this paper, a probabilistic calibration approach is introduced using Bayesian statistical inference to maximize the use of available site investigation data, and to best estimate the occurrence of a marine landslide. For this purpose, a landslide model thought for its simplicity is used to illustrate the applicability and potential of the calibration methodology. The aim is to introduce a systematic approach to produce prior probability distributions of the model parameters, based on an actual integrated marine site investigation including geological, geophysical, and geomatics data, to then compare it with a posterior probability distribution of the same model parameters, but estimated after collecting in situ soil samples and testing them in the laboratory to produce the corresponding soil strength properties. This comparison allows to explore (a) the influence of the number of in situ samples, (b) the influence of a landslide factor of safety, and (c) the influence of the soil heterogeneity, into the likelihood of the occurrence of a marine landslide. The model parameters that are considered for calibration include the initial state of the submerged and saturated soil unit weight, the thickness of the soils' unit layers, the pseudo-static seismic coefficient, and the slope angle, while the soil undrained shear strength is considered as the reference parameter to conduct the calibration (i.e., to compare model predictions vs. actual observations). Results show the potential of the proposed methodology to produce landslide geohazard maps, which are needed for the planning and design of marine infrastructure.

In transparent soil model experiments, fused quartz stands out as the most promising substitute for natural sand. However, there is still a lack of a comprehensive evaluation system to assess the similarity of its mechanical properties to natural sand. Therefore, a similarity evaluation method based on constitutive model simulation is proposed. First, due to the high friction angle characteristic of fused quartz in transparent soil model tests, multiple oedometer compression and shear box tests were conducted on various gradations of fused quartz. Subsequently, a hypoplastic sand model, which is abundant in natural sand data, stable, and has a straightforward calibration process, was then selected for parameter calibration of fused quartz. Finally, the substitutability of fused quartz for natural sand was evaluated by comparing constitutive parameters and shear box simulation, considering factors such as initial void ratio and confining pressure. The results indicate that the hypoplastic sand model accurately captures the shear behavior of fused quartz. Particles with grain sizes ranging from 0.5 to 2 mm weaken the strength of well-graded fused quartz. The findings also suggest that well-graded fused quartz maintains consistent shear behavior with various natural sands. By contrast, the applicability of single-sized fused quartz is limited.

The adoption of sustainable farming practices will improve food security around the world. The evidence that food is produced sustainably has become important for maintaining access to global markets and is influencing commodity marketing and pricing. This paper explores the current state of global sustainability reporting and examines whether yield data could improve the sustainability of farming by adding more rigour and transparency to the evidential basis of sustainability. The Australian grains and oilseeds industry is used as a case study with most of the Australian grain and oilseed crop grown for export markets. Sustainability policies in the European Union, United States of America and Australia are contrasted, with a focus on the improved management of nitrogenous fertiliser, which is viewed as the most efficient way to reduce the environmental impact of agriculture. Generally, sustainability reporting is based on a suite of indicators that are easy to measure and interpret, sensitive to change, technically sound and cost-effective. These indicators serve as a mechanism to quantify and document the practices used to produce crops but some of the current measures are relatively coarse and lack transparency. The time and cost incurred to collect these measurements could be reduced by using secondary data to report on sustainability. Yield data are already collected by many grain, and oilseed growers, and provide a transparent, evidence-based way to optimise and report on fertiliser application at fine scale. Yield data can help to maintain soil health and farm profit, reduce environmental damage and generate quantitative data for reporting on agricultural sustainability, but some challenges remain before it could be implemented as a universal reporting measure.

Using the discrete element method (DEM) to simulate the rice machine transplanting operation is important for assessing the plant injury and optimizing the rice transplanter performance, while the DEM flexible model establishment that can accurately reflect the mechanical properties of the rice blanket seedling root blanket is an important foundation. Based on the root blanket's stratification and the root system structure's measurement and statistics, a new method for root blanket flexible modeling was proposed in this study. Firstly, the Hertz-Mindlin with bonding V2 contact model was used to establish substrate I (SI), substrate II (SII), substrate III (SIII), stemroot combination (SRC), and netted layer (NL) flexible models, respectively, and the model parameters were calibrated and determined by angle of repose (AOR), direct shear, and mechanical tests. The calibration results showed that the deviations of AOR simulated values for SI and SII were both less than 1.5 %, and the deviations of shear strength simulated values were both less than 4 %. Secondly, the shear characteristics of SI and SII were determined by direct shear test. The results showed that the physical and simulated shear stress-displacement relationship curves of SI and SII were basically the same; the hair roots mainly relied on the cohesive between them and the substrate to improve the substrate strength; the fitted lines of simulated shear strength and normal stress of SI and SII were in high agreement with these of the measured values; the deviations of the simulated cohesion and internal friction angle were both less than 5 %. After that, the Hertz Mindlin with JKR V2 contact model was used between SRC and substrate. The interfacial surface energy of the root blanket and the bonding parameters of SIII were calibrated by stem, half-SRC, and SRC pulling-out tests layer by layer. The calibration results showed that the deviation of the maximum pulling-out force of SRC was 5.83 %, verifying that the model could accurately simulate the intertwining effect of the crown roots. Finally, the flexible model of the root blanket was verified by cutting, curling, and tensile tests. The simulated test results were consistent with the trends of the physical test results; the deviations of the maximum cutting resistance of front cutting and side cutting were both within 8 %, the error percentage range of the marked points height was 0.35 % to 17.16 %, and the deviation of the maximum tensile force was 9.22 %, indicating the good feasibility of the modeling method and accuracy of the flexible model. The results of this study lay a foundation for the DEM simulation of the rice machine transplanting operation. They can also provide a reference for the numerical simulation of other multiplant root-soil complexes.

Stress-strain results from high-strain rate consolidated-undrained (CU) triaxial compression tests on partially saturated kaolin clay are presented. The work addresses the scarcity of high-strain rate data for cohesive soils and provides updated strain rate coefficients for kaolin clay. It covers strain rates from quasi-static (0.01%/s) to dynamic (800%/s) regimes. Kaolin clay specimens were prepared wet of optimum using static compaction at a constant water content of 32 +/- 1% and a degree of saturation of 96 +/- 2%. The specimens were then loaded into triaxial cells and consolidated under pressures ranging from 70 to 550 kPa for 24 h prior to testing. Tests were conducted using a modified hydraulic frame, and a methodology for correcting compression data to account for inertial effects observed during high-rate testing was adopted. The data revealed significant strengthening of clays with increased strain rates, especially at low confining pressures. Lightly confined clays (sigma 3 = 70 kPa) experienced a 165% strength increase, while highly confined clays (sigma 3 = 550 kPa) showed a 52% increase. Analysis using secant moduli revealed increased stiffening with loading rate. Posttest examination of specimens revealed a decrease of shear localization with increasing strain rate, indicating that a transition in failure mode contributes to the increased strengthening and stiffening of clays at high rates. The stress-strain data were used to calibrate the semilogarithmic and power law strain hardening models, yielding lambda and beta values that decreased linearly with increasing confining pressure. Equations relating lambda and beta to confining pressure were developed for practical applications, applicable to normally consolidated clays under confining pressures up to approximately 5 atmospheres.

Numerical modeling of permafrost dynamics requires adequate representation of atmospheric and surface processes, a reasonable parameter estimation strategy, and site-specific model development. The three main research objectives of the study are: (i) to propose a novel methodology that determines the required level of surface process complexity of permafrost models by conducting parameter sensitivity and calibration, (ii) to design and compare three numerical models of increasing surface process complexity, and (iii) to calibrate and validate the numerical models at the Yakou catchment on the Qinghai-Tibet Plateau as an exemplary study site. The calibration was carried out by coupling the Advanced Terrestrial Simulator (numerical model) and PEST (calibration tool). Simulation results showed that (i) A simple numerical model that considers only subsurface processes can simulate active layer development with the same accuracy as other more complex models that include surface processes. (ii) Peat and mineral soil layer permeability, Van Genuchten alpha, and porosity are highly sensitive. (iii) Liquid precipitation aids in increasing the rate of permafrost degradation. (iv) Deposition of snow insulated the subsurface during the thaw initiation period. We have developed and released an integrated code that couples the numerical software ATS to the calibration software PEST. The numerical model can be further used to determine the impacts of climate change on permafrost degradation.

The discrete element method (DEM) is proving to be a reliable tool for studying the behavior of granular materials and has been increasingly used in recent years. The accuracy of a DEM model depends heavily on the accuracy of the particle property parameters chosen which is of vital importance for studying the mechanical properties of granular materials. However, the existing DEM parameter calibration methods are limited in terms of applicability, and the trial-and-error method remains the most common way for DEM parameter calibration. This paper presents a novel calibration method for DEM parameters using the multi-objective tree-structured parzen estimator algorithm based on prior physical information (MOTPE-PPI). The MOTPE-PPI does not rely on the training datasets and may optimize with every single test, significantly reducing the computational efforts for DEM simulation. Moreover, MOTPE-PPI is suitable for a variety of contact models and damping parameters in DEM simulation, showing robust applicability and practical feasibility. Taking an example, the DEM parameters of sandy gravel material collected from Dashixia rockfill dam in China are calibrated using MOTPE-PPI in the paper. The prior physical information is obtained through a series of triaxial loading-unloading tests, single-particle crushing tests, and literature research. Seven parameters in the rolling resistance linear contact model and breakage model are considered, and the optimization process takes only 25 iterations. Through quantitative comparison with existing parameter calibration methods, the high efficiency and wide applicability of the DEM parameter calibration method proposed in this study. The calibrated DEM parameters are used to investigate the hysteretic behavior and deformation characteristics of the granular material, revealing that the accumulation of plastic strain and resilient modulus is related to confining pressure, stress level, and the number of cycles.