Real Grain Research Articles

Optimisation of calibration parameters for a discrete element method (DEM) model of plant-origin grains with a low elasticity modulus

This paper presents the application of the Discrete Element Method (DEM) to describe the physical properties of plant-origin grains with a low elasticity modulus for the needs of numerical simulation of processing processes. The study proposes the modelling of maize grains based on 3D scanning of real grains and further use of the multi-sphere method to fill the numerical model with a conglomerate of elementary spheres. The main aim of the paper is to develop a calibration method based on exploring parameter spaces at points selected using Sobol's grids. As criteria and functional limitations for the calibration, the following were proposed: the slope angle of repose (AoR), the radius of the heaped cone's vertex (Rad), the number of grains, and the slope height. The study results show that for the calibration of the DEM model describing maize grains, test points with a set of the following nine parameters should be used: Poisson's Ratio for grain, Density of grain, Shear Modulus, Coefficient of Restitution for grain-grain, Coefficient of Restitution for grain-material, Coefficient of static friction for grain- grain, Coefficient of static friction for grain-material, Coefficient of rolling friction for grain-grain, and Coefficient of rolling friction for grain-material.

The Innate Rates of Increase in Two Common Stored Grain Insects under Different Grain Storage Conditions and Times.

The determination of innate rate of increase (r) values under different grain storage conditions is critical for insect population predictions. The r values for Cryptolestes ferrugineus (Stephens) and Tribolium castaneum (Herbst) were calculated by using a new suggested method (continuous time analysis) and data from the literature, and these calculated r values were compared to identify the r values and carrying capacities under real grain storage conditions and times. The insects were reared in small glass vials (0.3 kg wheat), small PVC columns (2 kg wheat), large PVC columns (14 kg wheat), and shallow containers (14 kg wheat or wheat + cracked wheat). The wheat or cracked wheat had 13.8 to 14.5% moisture contents at different constant temperatures (17.5 to 42.5 °C) and fluctuating temperatures. The r values at the beginning of the population were the highest. Before r became negative, it gradually decreased with increasing time. After the r value became negative, it sometimes increased to positive; however, the rebounded r was much less than the initial r and gradually tended to stabilize within an up-and-down range. This up-and-down r was related to the carrying capacity. The larger the grain bulk, the higher the innate rate was for both species. The r values associated with 14 kg of wheat could be used to predict the insect population dynamics in stored grain bins.

Discrete model for discontinuous dynamic recrystallisation applied to grain structure evolution inside adiabatic shear bands

Discontinuous dynamic recrystallisation (DDRX) is a well-known phenomenon playing a significant role in the high-temperature processing of metals, including industrial forming and severe plastic deformations. The ongoing discussion on the Zener–Hollomon (Z–H) parameter as a descriptor of materials’ propensity to DDRX and a measure of microstructure homogeneity leaves more questions than answers and prevents its practical application. Most of the existing DDRX models are continuous, and so the geometry and topology of real grain microstructures cannot be considered. The present study uses a fully discrete representation of polycrystalline aluminium alloys as 2D/3D Voronoi space tessellations corresponding to EBSD maps. Such tessellations are geometric realisations of combinatorial structures referred to as polytopal cell complexes. Combining discrete models with FEM LS-Dyna simulations of shock-wave propagation in AA1050 and AW5083 aluminium alloys makes it possible to estimate for the first time the contribution of DDRX to the final material microstructure inside adiabatic shear bands. It is shown that the increase of the initial fraction of high-angle grain boundaries, caused by preliminary deformation, significantly increases the spatial homogeneity and decreases the clustering of DDRX grains. The obtained results contradict the conventional assumption that the microstructures obtained by severe plastic deformation under quasi-static and dynamic deformation conditions are similar due to the similar value of the Z–H parameter: competition between the two recrystallisation mechanisms leads to almost unpredictable final grain structures inside share bands that require further comprehensive experimental studies. This agrees with experimental evidence for high material sensitivity to the Z–H parameter.

A Phase-Field Discrete Element Method to study chemo-mechanical coupling in granular materials

This paper presents an extension of the discrete element method using a phase-field formulation to incorporate grain shape and its evolution. The introduction of a phase variable enables an effective representation of grain geometry and facilitates the application of physical laws, such as chemo-mechanical couplings, for modeling shape changes. These physical laws are solved numerically using the finite element method coupled in a staggered scheme to the discrete element model. The efficacy of the proposed Phase-Field Discrete Element Model (PFDEM) is demonstrated through its ability to accurately capture the real grain shape in a material subjected to dissolution only and compute the stress evolution. It is then applied to model the phenomenon of pressure solution involving dissolution and precipitation in granular materials at the microscale and enables to reproduce the creep response observed experimentally. This framework contributes to the enhanced understanding and simulation of complex behaviors in granular materials and sedimentary rocks for many geological processes like diagenesis or earthquake nucleation.

Accurate modeling and controlling of weak stiffness grinding system dynamics with microstructured tools

The weak stiffness grinding system often produces uncontrollable vibration, which directly reduces the machining quality. In order to accurately predict and control the weak stiffness grinding system dynamics, an accurate dynamics modeling and the controlling method with microstructured tools are presented innovatively. Based on the real random abrasive grain model, an instantaneous undeformed chip thickness model considering the phase deviation, time accuracy and grinding wheel-workpiece separation caused by vibration is established. On this basis, the controlling principle of microstructured grinding wheel on chip formation mechanism and grinding forces is studied. Then, combined with the element division principle and dynamics parameters of grinding system, the dynamics model of weak stiffness grinding system is established. According to the grinding experimental results based on vibration monitoring, the error rate of the established dynamics model is less than 9.8 %. Compared with the non-structured grinding wheel, the microstructured grinding wheel can control the vibration amplitude, the vibration frequencies and the wheel deflection. Based on the workpiece surface machining results, the addition of microstructures suppresses the phenomena of overcutting and the wheel bounce, and the profile protrusion height caused by grinding vibration is decreased by 77 %. The established dynamics model is of great significance for understanding and control the dynamic behavior of weak stiffness grinding systems.

Effect of Tillage Depths and Addition of Organic Acids on some Physical Properties and Yield of Wheat (Triticum eastvum L.)

The experiment was carried out in the field at the first research station (Al Bandar) affiliated to the College of Agriculture - University of Al-Muthanna, 5 km from the center of the city of Samawah during the agricultural season 2021-2022 in order to study the effect of plowing depth and the addition of organic acid based on the physical properties in soil and wheat yield (Triticum eastvum L.) The experiment was designed as a factorial on the basis of a split plot design and in (R.C.B.D) design. The experiment included two factors. The first factor was the plowing depths that included three levels of plowing depths (8, 16 and 24) cm and symbolized by (D1, D2, and D3) respectively. The second was the addition of humic and fulvic organic acids, which included five levels (0, 10, 20, 30, 40) liters H-1 and symbolized by H0, H1, H2, H3, and H4 in sequence, subsequently the land was divided into experimental units, and 45 experimental units contained three Sectors, which included the area of one experimental unit (2×2) m2. 8 lines, each 2 m in length, were spaced 20 cm apart to make up the experimental unit, the distance between 75 cm was left between one repeater and another. Then the harvest stage was on 22/4/2022, and the yield was measured The moisture content, apparent and real density, porosity, and grain yield, and the results showed the following: the addition of organic acids at a level of 40 liters of H-1 (H4) affected the reduction of the bulk density (1.277) g.cm-3 and increased the soil moisture (40.56%) and the porosity (51.25%) while it exceeded the level of 30 liters H-1 (H3). ) in the grain yield amounted to (5,489) mcg ha-1. The depth of plowing affected, as the depth D1 exceeded (8) cm in reducing the bulk density (1.276) and the porosity increased (51.21)%, while the depth D3 (24) cm exceeded in the moisture content (36.87), while the depth of (16) cm exceeded D2 in The grain yield reached (5.571) mcg ha-1 The interactions between the added organic fertilizers H3 and the depth of tillage D2 significantly affected the increase in grain yield, which amounted to 5.519 mcg ha-1.

Energy Crisis—Alternative Use of Winter Bread Wheat Grain Depending on Protein Content

Our economic analysis aimed to evaluate the profitability of winter bread wheat production based on two fundamental aspects. The first was the grainprotein content as a criterion for determining grain prices. The other was a comparative simulation of production profitability relying on grain production costs in 2015 and 2022. We used the results of a field experiment conducted in 2014 and 2015 involving winter bread wheat fertilised with nitrogen applied at progressive increments of 40 kg N ha−1 within arange from 0 to 240 N ha−1 with or without fungicide protection. We assumed that experimental factors significantly affected both the yield and the market value of grain, and hence the profitability conditioned by wheat prices on global markets. The working hypothesis of this paper is: wheat production profitability has not changed in the face of a global energy crisis. Our analysis shows that growing bread wheat generates profit when inputs are high: these inputs include high nitrogen rates and full crop protection. The real grain selling price guarantees production profitability. We should consider that, in the circumstances of a global energy crisis, the world should possibly switch to baking products from low-protein flour. Only upon such an assumption can the expenditure on fertilisers and fungicides be significantly reduced.

Metaball-Imaging discrete element lattice Boltzmann method for fluid–particle system of complex morphologies with case studies

Fluid–particle systems are highly sensitive to particle morphologies. While many attempts have been made on shape descriptors and coupling schemes, how to simulate particle–particle and particle–fluid interactions with a balance between accuracy and efficiency is still a challenge, especially when complex-shaped particles are considered. This study presents a Metaball-Imaging (MI) based Discrete Element Lattice Boltzmann Method (DELBM) for fluid simulations with irregular shaped particles. The major innovation is the MI algorithm to capture the real grain shape for DELBM simulations, where the Metaball function is utilized as the mathematical representation due to its versatile and efficient expressiveness of complex shapes. The contact detection is tackled robustly by gradient calculation of the closest point with a Newton–Raphson based scheme. The coupling with LBM is accomplished by a classic sharp-interface scheme. As for refiling, a local refiling algorithm based on the bounce back rule is implemented. Validations on the Jeffery orbit of ellipsoidal particles and three settling experiments of irregular-shaped natural cobblestones indicate the proposed model to be effective and powerful in probing micromechanics of irregular-shaped granular media immersed in fluid systems. The potential of this model on studies of shape-induced physical processes is further investigated with numerical examples that consider the drag and lift forces experienced by realistic particles, as well as the “drafting, kissing and tumbling” process of pairs of non-spherical particles.

Granular Gas of Inelastic and Rough Maxwell Particles

The most widely used model for granular gases is perhaps the inelastic hard-sphere model (IHSM), where the grains are assumed to be perfectly smooth spheres colliding with a constant coefficient of normal restitution. A much more tractable model is the inelastic Maxwell model (IMM), in which the velocity-dependent collision rate is replaced by an effective mean-field constant. This simplification has been taken advantage of by many researchers to find a number of exact results within the IMM. On the other hand, both the IHSM and IMM neglect the impact of roughness—generally present in real grains—on the dynamic properties of a granular gas. This is remedied by the inelastic rough hard-sphere model (IRHSM), where, apart from the coefficient of normal restitution, a constant coefficient of tangential restitution is introduced. In parallel to the simplification carried out when going from the IHSM to the IMM, we propose in this paper an inelastic rough Maxwell model (IRMM) as a simplification of the IRHSM. The tractability of the proposed model is illustrated by the exact evaluation of the collisional moments of first and second degree, and the most relevant ones of third and fourth degree. The results are applied to the evaluation of the rotational-to-translational temperature ratio and the velocity cumulants in the homogeneous cooling state.

Separation and enrichment of trace aflatoxin B1 in grains by magnetic nanomaterials based on SiO2@Fe3O4

将SiO2包覆的Fe3O4磁性纳米材料(SiO2@Fe3O4)表面偶联识别黄曲霉毒素B1(AFB1)的抗体(Ab),用于特异性分离富集谷物中的AFB1,进而与高效液相色谱-串联质谱法(HPLC-MS/MS)结合,用于大米、玉米和小麦中AFB1的高效准确检测。采用微波辅助水热合成法制备得到Fe3O4磁性纳米颗粒,并用100 μL正硅酸乙酯(TEOS)对其进行SiO2的包覆,得到SiO2@Fe3O4磁性纳米材料,随后进行抗体的偶联得到Ab-SiO2@Fe3O4;以pH=7.4的磷酸盐缓冲液(PBS)作为富集缓冲液,加入8 mg Ab-SiO2@Fe3O4,在37 ℃下反应10 min进行AFB1的分离富集,随后采用甘氨酸-盐酸(Gly-HCl)缓冲液对Ab-SiO2@Fe3O4分离富集的AFB1进行洗涤,将洗涤液氮吹后复溶,采用高效液相色谱-串联质谱法检测。在最佳条件下,方法检测AFB1的线性范围为2~50 μg/L,相关系数(R2)>0.99,检出限为0.04 μg/kg,定量限为0.13 μg/kg。在4个不同加标水平下,AFB1在3种谷物基质中的加标回收率为76.21%~92.85%, RSD≤5.29%。大米、玉米和小麦等实际谷物样品中AFB1的测定结果显示,在1个小麦样品和2个玉米样品中检出AFB1,其含量分别为0.38、0.13和0.47 μg/kg,其他样品中并未发现AFB1。方法将磁性纳米材料与HPLC-MS/MS相结合,实现了AFB1的高效分离富集,富集材料成本低廉,储存性能好,在30 min内即可完成前处理过程,可在较短的时间内实现大批量样品的实际分析,在谷物中真菌毒素的检测方面具有良好的应用前景。

A generalized 3DLS-DEM scheme for grain breakage

We introduce a new generalized 3DLS-DEM (3D Level Set Discrete Element Method) scheme that incorporates grain breakage, taking an important step towards realistic modeling at the micro-scale with DEM. For the first time, simulating thousands of real 3D grains that are able to break, which was possible due to the algorithm used for grain breakage. The presented scheme is not only capable of efficiently simulating grains with real shapes but also preserving mass and grains morphology with high fidelity when breakage occurs. Hence, with this approach, further works within the original 3DLS-DEM scheme could take into account other physical phenomena at the grain-scale such as electrostatic induced cohesion, heat transfer, or the presence of a fluid, etc. On the other hand, the breakage process modified grain size and roundness distributions, which, in turn, might change the strength and critical state of the sample. Withal, the overall process seems to suggest that grain breakage may be a sufficient condition to exacerbate the prevalence of shear banding within the sample. Finally, our model is able to perform breakage on several real 3D grains of a sample consisting of thousands of grains in a generalized 3DLS-DEM scheme.

Simulation of the Loading Density for Gun Propellants with Arbitrary Shapes Using a Discrete Element Method

AbstractThe determination of the loading density that can be achieved for a certain propellant geometry is a key factor that determines the energy content and hence the performance of propellants in a gun system. Additive manufacturing on the other hand gives charge designers a new freedom in choosing propellant geometries. Therefore, it is important to have a method that can determine the loading density achievable for a given grain geometry without actually manufacturing each possible solution in sufficient quantities for an experimental determination. For this reason, a discrete element method was adapted, and a simulation was setup with the open source 3D computer graphic software Blender and its bullet physics engine, that enables the charge designer to simulate a propellant bed for arbitrary grain and shell geometries. The method is validated by simulating the loading density of real JA2 double base propellant grains (7 perforated cylinder) and comparing it with experimental measurements. It is shown that a good agreement between the simulated and experimental loading densities can be achieved by our method. Afterwards the dependence of the loading density on the length to diameter ratio for cylindrical gun propellants was investigated with the method. It is shown how the loading density decreases with increasing L/D ratio.

Kinetic study on the effect of iron on the grain growth of rutile-type TiO2 under in situ conditions

There have been many studies on the growth kinetics of titanium dioxide and doped titanium dioxide. However, most calculated the grain size after isothermal treatment and cooling to room temperature; thus, the real grain size of titanium dioxide at the real-time temperature during heat treatment could not be obtained. This study thus aimed to obtain accurate grain information during the heat treatment process. In this study, titanium oxysulfate (TiOSO4) and ferric chloride (FeCl3·6H2O) were used to hydrolyze and precipitate TiO2 precursors containing impurity iron. Then, the sample was subjected to high-temperature in situ x-ray diffraction. Using the Williamson–Hall mapping method to process the x-ray diffraction information, the grain size could be used to characterize changes in the grain size, and the change law of TiO2 during the heat treatment process was studied. Furthermore, the effect of Fe doping on the growth of TiO2 crystals was examined through the crystal growth kinetics. The results revealed that when the Fe doping amount reached a certain level, it affected the growth mechanism of the rutile type titanium dioxide grains, thereby causing a change in the growth order. Specifically, an increase in the Fe doping amount increased the growth activation energy; that is, it inhibited the growth of rutile-type titanium dioxide grains.

Generation of mesostructure for lattice discrete particle model

A preliminary study of two approaches for the internal structure generation utilized in the lattice discrete particle models (LDPM) [1] is presented. The presented methods used for particle generation and placement are meant to capture the internal structure of materials realistically. The first approach governs the positioning of the generated spherical particles by a gradient field to mimic the casting process. The second approach considers the non-spherical shape of individual particles, i.e. ellipsoidal particles. Therefore, the grain size, angularity, and flakiness can be controlled to match the real grain distribution closely.

Investigation on the Tool-Rock Interaction Using an Extended Grain-Based Model

The poor drill-ability of rock in deep hard formation leads to the problems of low rate of penetration (ROP) and high drilling cost. A detailed understanding of the rock-tool interaction is of great significance for improving the rock breaking efficiency and optimizing the cutting parameters. For this purpose, this paper establishes a numerical model of heterogeneous granite which considers the influence of mineral distribution and real grain structure. The fracture behaviors of granite under tool cutting and indentation are investigated subsequently. It is found that there are always four kinds of microcracks in granite, intragranular tensile crack, intragranular shear crack, intergranular tensile crack and intergranular shear crack, among those four crack types, the intergranular tensile crack and intragranular shear crack are dominated, almost no intergranular shear cracks occur. Lateral pressure has no great influence on the volume of cutting chips in rock cutting, but is the direct factor that affects the rock-breaking efficiency in rock indentation. The initiation and propagation of radial cracks will be obviously inhibited in large lateral pressure, and the number of radial cracks will decrease sharply, resulting in low rock-breaking efficiency. Lateral pressure seems to have little effect on the indentation force, the possible reason for this lateral pressure insensitivity is because the far-field lateral pressure has less influence on the indenter tip around field than the existence of free surface. The research results can provide the basis for improving granite rock-breaking efficiency and optimizing rock-breaking tools to a certain extent.

Contact-free wheat mildew detection with commodity wifi

Mildew is recognized as one of the most critical causes of the damages in food storage. Due to the complex operation and high cost, many advanced detection instruments cannot be widely deployed, while the detection of grain mildew are mostly carried out manually (i.e., inspection by experts) nowadays with very low efficiency. To address this problem, we present a non-destructive, non-intrusive, and low-cost mildew detection system for stored wheat implemented with off-the-shelf WiFi devices, which represents a new application of the Internet of Things (IoT) for smart agriculture. In this paper, we introduce the impact of wheat mildew in stored food, and demonstrate that it is viable to utilize WiFi Channel State Information (CSI) amplitude for detection of mildew in stored wheat. Next, we propose the MiFi system, which comprises sensing of WiFi CSI data, data preprocessing, a radial basis function (RBF) neural network-based detection model, and mildew detection. We conduct extensive experiments to validate the performance of the proposed MiFi system using real grain samples. The results show that MiFi achieves an average detection accuracy of over 90% in both line-of-sight (LOS) and non-line-of-sign (NLOS) scenarios, as well as a comparable detection performance as manual detection by an expert.

A Modeling Approach on the Correction Model of the Chromatic Aberration of Scanned Wood Grain Images

There always exists subjective and objective color differences between digital wood grain and real wood grain, making it difficult to replicate the color of natural timber. Therefore, we described a novel method of correcting the chromatic aberration of scanned wood grain to maximally restore the objective color information of the real wood grain. A point-to-point correction model of chromatic aberration between the scanned wood grain and the measured wood grain was established based on Circle 1 by adjusting the three channels (sR, sG, and sB) of the scanned images. A conversion of the color space was conducted using the mutual conversion formulas. The color change of the scanned images before and after the correction was evaluated through the L∗a∗b∗ color-mode-based ΔE∗. and the lαβ color-model-based CIQI (Color Image Quality Index) and CQE (Color Quality Enhancement). The experimental results showed that the chromatic aberration ΔE∗ between the scanned wood grain and the measured wood grain decreased and the colorfulness index CIQI of the scanned wood grain increased for most wood specimens after the correction. The values of ΔE∗ of the twenty kinds of wood specimens decreased by an average of 3.1 in Circle 1 and 2.3 in Circle 2, thus the correction model established based on Circle 1 was effective. The color of the scanned wood grain was more consistent with that of the originals after the correction, which would provide a more accurate color information for the reproductions of wood grain and had an important practical significance.

Hardness Penetration Depth Prediction in the Grind-Hardening Process through a Combined FEM model

The grind-hardening process aims to increase the surface hardness of the material through the dual action of the mechanical and thermal load. A novel approach to model the process and predict the hardness penetration depth was developed based exclusively on the prediction of austenite-martensite transformation. A combined micro and macro scale approach was implemented to forecast the temperature reached in the surface starting from the action of a single grain and using its specific cutting power to design a moving heat source representing the interaction between the grinding wheel and the material. The martensitic transformation temperature considered in this paper takes into consideration the fast heat cycle typical of this process. In order to validate the model, tangential surface grinding tests were performed on 42CrMo4 and microstructural analysis with micro-hardness measurements were performed. This research presents a first step in developing a grinding process simulation that includes multi-grain grinding, real grain geometries, binder effect, and real workpiece-grinding wheel kinematics.

Temperature Forecasting for Stored Grain: A Deep Spatiotemporal Attention Approach

The development of Internet-of-Things (IoT) technology promotes the advances of grain condition detection and analysis systems. Temperature monitoring is a main element to maintain grain quality, and effective control of grain temperature is crucial to safe storage of grain. In this article, an encoder–decoder model with attention mechanism is proposed to accurately forecast the temperature of stored grain. Considering that the points on the gradient direction of the temperature surface have a great influence on the temperature of the target point, the Sobel operator is used to extract the local characteristics of the target point. In addition, considering the correlation structure in the sensory data, the attention mechanism is used to extract the global features of the target point. The extracted spatial features are fed into long short-term memory (LSTM) networks to obtain the long-term state information of spatial factors. LSTM unit and convolutional neural network are used to encode the spatial features of the target points. Taking meteorological factors as the external input of the decoder, temporal attention mechanism and LSTM unit are used to complete the decoding process and realize the prediction of grain temperature in the future. The results with real grain storage data show that the proposed model outperforms several schemes, including Kalman-modified the least absolute shrinkage and selection operator (Kalman-modified LASSO), temporal graph convolutional network (T-GCN), LSTM, CNN-LSTM, and convolutional LSTM (Conv-LSTM), with considerable gains.

Features of structure and mechanical properties formation in shaped rolled products made of 09G2S steel in accelerated water cooling process

The article provides an analysis of methods for strengthening structural shapes in a stream of section mills, a series of active experiments was carried out, and a calculation of predictive regression equations for the dependence of mechanical properties and microstructure indicators on the geometry of profile dimensions and technological parameters of cooling. An algorithm has been developed for iterative refinement of the forecast accuracy using such equations, which provides the minimum error in determining the specified characteristics. Metal microstructure at various modes of accelerated cooling in calm water of shaped rolled in the flow of a section mill confirms the patterns of structure formation and corresponds to the theory and practice of science of metals and heat treatment of metals. The developed techno logy of accelerated water cooling provides for shaped rolling increase in strength to a class of 600 MPa and higher for a wide assortment of structural shapes and for critical purposes for pipe and ship-car building. The use of accelerated cooling in calm water of shaped rolled gives a significant economic effect (80-100 USD per 1 ton of rolled steel) instead of using microalloying steel with elements such as vanadium and niobium, which reduce the size of the austenitic and then the real grain of the metal and thereby increase the yild point and its relation to the ultimate tensile strength, providing substantial strengthening of rolled products. As a result, an efficient technology have been developed for thermal hardening of structural shapes in the flow of a section mill.