Discrete Element Method Model of Elastic Fiber Uniaxial Compression

A flexible fiber model based on the discrete element method (DEM) is presented and validated for the simulation of uniaxial compression of flexible fibers in a cylindrical container. It is found that the contact force models in the DEM simulations have a significant impact on compressive forces exerted on the fiber bed. Only when the geometry-dependent normal contact force model and the static friction model are employed, the simulation results are in good agreement with experimental results. Systematic simulation studies show that the compressive force initially increases and eventually saturates with an increase in the fiber-fiber friction coefficient, and the fiber-fiber contact forces follow a similar trend. The compressive force and lateral shear-to-normal stress ratio increase linearly with increasing fiber-wall friction coefficient. In uniaxial compression of frictional fibers, more static friction contacts occur than dynamic friction contacts with static friction becoming more predominant as the fiber-fiber friction coefficient increases.Comment: 30 pages, 14 figures, submitted for publicatio

OPTIMIZATION OF THE CLEANING SYSTEM OF GRAPE HARVESTERS USING THE DISCRETE-ELEMENT METHOD

Grape harvesters are mechanized machines designed to remove grapes from vine trees, process them in a cleaning system, and then store them in onboard bins. These bins are later unloaded into a transport wagon and taken to a vinification facility. Cleaning systems can sometimes fail to completely remove the foreign materials (i.e. leaves, petioles, stems, etc.), which may compromise the vinification process. For this reason, the project focused on the cleaning system by minimizing the presence of foreign materials while maintaining an adequate harvesting throughput. The project main objective was to optimize the cleaning system in grape harvesters by using the Discrete-Element Method (DEM). Individual DEM simulations were validated and used to develop a main crop flow simulation for the optimization of the cleaning system. This optimization included reducing the presence of foreign materials (petioles and leaves) while increasing the crop throughput for the specific grape variety of Cabernet Sauvignon. The physical characteristics and properties of the biological materials (grapes, petioles, leaves) were measured during the 2014 grape harvesting season at three different locations (Aigues-Mortes, Saint-Gervais, and Pauillac) in France. Time constraints limited the number of measured properties at the locations. The results from each location were compared using an ANOVA and a Tukey HSD post-hoc test. Given the natural variability of the biological materials, the three populations were found to be significantly different in most cases. The physical characteristics and properties from the Aigues-Mortes and Pauillac locations were used for the validation process. This was done because these locations had the most complete data sets. During the summer of 2015, a second testing phase took place to validate both the DEM leaf deflection and cleaning system models. The additional experiments consisted of testing the leaf samples in controlled deflections and testing the efficiency of the cleaning system. These experiments used Cabernet Sauvignon leaves shipped from the Vineland Research and Innovation Centre (VRIC) in Ontario. The individual simulations included the inclined plane, rebound surface, leaf deflection, and grape trajectory tests on an inclined conveyor. The inclined plane and rebound simulations were adjusted until the results were within 5% of the experimental test results. The leaf deflection simulations used optimized crop material properties until the simulated leaf behavior matched the actual leaf. Some discrepancies in the DEM simulated leaf shape were identified due to the limitations of the particle creation method. The grape trajectory test results coincided with the DEM simulations at greater conveyor speeds. A moderate difference between the simulations and the experimental tests was present at lower conveyor speeds. A possible cause for this difference may have been the effect of gravity and belt friction on the generation and acceleration of the grapes on the conveyor. A main crop flow simulation that included a conveyor and aspirator was developed using the previously validated simulations. Nine conveyor configurations, which included three belt angles from horizontal (10°, 15°, and 20°) and three speeds (350 rev/min (1.4 m/s), 420 rev/min (1.7 m/s), and 500 rev/min (2.0 m/s)), were tested to optimize the cleaning system performance. Based on the DEM simulations, the 420 rev/min-20° configuration was recommended as the optimal crop conveyor setting. This particular configuration minimized product damage and had an increased aspiration success rate of 9.6% compared to the conventional conveyor settings (420 rev/min-15°)

Transdisciplinary top-down review of hemp fibre composites: From an advanced product design to crop variety selection

Given the vast amount of available research in the area of natural fibre composites, a significant step forward in the development of next-generation plant fibre-based products would be to devise a framework for rational design. The authors use a top-down approach, starting with an example final product to define the product specifications for high-performance hemp fibre-reinforced composites. Thereafter, all process steps are critically analysed: from textile preform and reinforcement yarn production, to fibre extraction and the agricultural process chain, to the microbiology of field retting, to cultivation and selection of crop variety. The aim of the analysis is to determine how far the current state of knowledge and process technologies are in order to use hemp fibres in high- performance composites. Based on this critical evaluation of the state-of-the-art, it can be stated that hemp will be found in high-performance composites in the short-to-medium term. There is, however, a need for performance optimisation especially through the selection of crop variety, best practices in retting, and effective fibre extraction methods to obtain more consistent fibre qualities suitable for reinforcement spinning and composite preform manufacturing processes

Discrete Element Modeling of the Grading- and Shape-Dependent Behavior of Granular Materials

Granular materials, such as sand, biomass particles, and pharmaceutical pills, are widespread in nature, industrial systems, and our daily life. Fundamentally, the bulk mechanical behavior of such materials is governed by the physical and morphological features of and the interactions among constituent particles at the microscopic scale. From a modeling standpoint, the particle-based discrete element method (DEM) has emerged as the most prevalent numerical tool to model and study the behavior of granular materials and the systems they form. A critical step towards an accurate and predictive DEM model is to incorporate those physical and morphological features (e.g., particle size, shape, and deformability) pertaining to the constituent particles. The main objective of this dissertation is to approach an accurate characterization and modeling of the grading- and shape-dependent behavior of granular materials by developing DEM models that incorporate realistic physical and morphological features of granular particles. Revolving around this objective, three studies are presented: image-based particle reconstruction and morphology characterization, grading and shape-dependent shearing behavior of rigid-particle systems, and granular flow of deformable irregular particles. The first study presents a machine learning and level-set based framework to re- construct granular particles and to characterize particle morphology from X-ray computed tomography (X-ray CT) imaging of realistic granular materials. Images containing detailed microstructure information of a granular material are obtained using the X-ray CT tech- nique. Approaches such as the watershed method in two dimensions (2D) and the combined machine learning and level set method in three dimensions (3D) are then utilized and implemented to segment X-ray CT images and to numerically reconstruct individual particles in the granular material. Based on the realistic particle shapes, particle morphology is characterized by descriptors including aspect ratio, roundness, circularity (2D) or sphericity (3D). The particle shapes or morphology provide important constraints to develop DEM models with particle physical and morphological features conforming to the specific granular material of interest. In the second study, DEM models incorporated with realistic particle sizes and shapes are developed and applied to study the shearing behavior of sandy soils. The particle sizes and shapes are obtained from realistic samples of JSC-1A Martian regolith simulant. Irregular-shape particles are represented by rigid clumps based on the domain overlapping filling method. The effects of particle shape irregularity on the shearing behavior of granular materials are investigated through direct shear tests, along with the comparisons from spherical particles with or without rolling resistance. The micro-mechanisms of shape irregularity contributing to the shear resistance are identified. The last study investigates the effects of particle deformability (e.g., compression, deflection or torsion), together with particle sizes and shapes, on the granular flow of flexible granular materials. A bonded-sphere DEM model is implemented with the capability of embodying various particle sizes and irregular shapes, as well as capturing particle deformability. This approach is then applied to simulate and study the behavior of flexible granular materials in cyclic compression and hopper flow tests. The effects of particle size, shape and deformability on the bulk mechanical behavior are investigated on the basis of the DEM simulation results. The importance of particle deformability to the DEM simulations of flexible granular materials is demonstrated

Agricultural Structures and Mechanization

In our globalized world, the need to produce quality and safe food has increased exponentially in recent decades to meet the growing demands of the world population. This expectation is being met by acting at multiple levels, but mainly through the introduction of new technologies in the agricultural and agri-food sectors. In this context, agricultural, livestock, agro-industrial buildings, and agrarian infrastructure are being built on the basis of a sophisticated design that integrates environmental, landscape, and occupational safety, new construction materials, new facilities, and mechanization with state-of-the-art automatic systems, using calculation models and computer programs. It is necessary to promote research and dissemination of results in the field of mechanization and agricultural structures, specifically with regard to farm building and rural landscape, land and water use and environment, power and machinery, information systems and precision farming, processing and post-harvest technology and logistics, energy and non-food production technology, systems engineering and management, and fruit and vegetable cultivation systems. This Special Issue focuses on the role that mechanization and agricultural structures play in the production of high-quality food and continuously over time. For this reason, it publishes highly interdisciplinary quality studies from disparate research fields including agriculture, engineering design, calculation and modeling, landscaping, environmentalism, and even ergonomics and occupational risk prevention

Discrete Element Modeling of the Shape- and History-Dependent Behavior of Granular Materials

Granular materials, such as biomass feedstocks, agricultural grains, pharmaceutical pills, and geomaterials, are widespread in nature, industrial systems, and everyday life. Fundamentally, the bulk mechanical behavior of granular materials is governed by particle-level attributes such as particle morphology, surface roughness, and contact behavior. Among various numerical methods developed for modeling granular materials, the particle-based discrete element method (DEM) is particularly suited and effective in modeling the mechanical, flow, and failure behavior of granular materials. Focusing on one specific type of granular material (i.e., biomass feedstocks), the main objective of this dissertation is to develop and validate novel DEM models that can effectively capture complex particle shapes and the history-dependent contact behavior of biomass particles. Revolving around the main objective, four studies have been conducted: In the first study, the computed tomography-informed DEM models are proposed for modeling complex-shaped biomass particles, in which particle surface geometries are approximated by a polyhedral model and a sphero-polyhedral model. These models are applied to simulate compressibility tests of biomass particles, where the polyhedral model demonstrates convincingly better suitability than the sphero-polyhedron model. The polyhedral model is then applied in the simulation of the friction test. Remarkably, the polyhedral model is capable of predicting both the compressive and frictional behavior of the pine particles when evaluated against experimental data. In the second study, a set of hysteretic nonlinear DEM contact models are developed and calibrated to capture the history-dependent and the strain-hardening behavior of granular biomass feedstocks. The developed models are applied to simulate axial compression tests of biomass pine particles. Results show that the proposed models can reproduce the bulk stress-strain profiles of the physical samples and that the predicted bulk compressibility and constrained modulus under repeated compression agree reasonably with the experimental data. In the third study, the exponential form of the proposed hysteretic models is applied to granular hopper flow simulations. Numerical studies are conducted to predict the potential processing upsets and their relationships to hopper design parameters. A detailed analysis of the granular hopper flow has been provided in cross-validation of the experimental flow tests over wide ranges of the processing parameters of the hopper and material attributes of pine particles. In the fourth study, the exponential form of the proposed hysteretic models is applied to simulate the quasi-static and dense flow along an inclined plane. The effect of irregular shapes is approximated by a motion (rolling) resistance model, and the impact of particle shapes on bulk flowability is then investigated. DEM studies have verified the strong influence of inter-particle motion resistance (equivalent to particle interlocking) as critical material attributes on determining the flowability in the dense flow regime