Determination Of Material Properties Research Articles

Optimization of Sensor Placement for a Measurement System for the Determination of Local Magnetic Material Properties

The aim of this work is to optimize the sensor positions of a sensor–actuator measurement system for identifying local variations in the magnetic permeability of cut steel sheets. Before solving the actual identification problem, i.e., finding the material distribution, the sensor placement of the measurement setup should be improved in order to reduce the uncertainty of the identification of the material distribution. The Fisher information matrix (FIM), which allows one to quantify the amount of information that the measurements carry about the unknown parameters, is used as the main metric for the objective function of this design optimization. The forward problem is solved by the finite element method. The results show that the proposed method is able to find optimal sensor positions as well as the minimum number of sensors to achieve a desired maximum parameter uncertainty.

Determination of delamination-related material properties and sensitivities in a ply drop composite using a semi-numerical approach

The aims of this paper are to investigate damage initiation and propagation in the vicinity of a ply drop focusing on delamination, to extract delamination-related material properties without conducting classical single and mixed mode fracture tests, and to analyze the sensitivities of delamination evolution with respect to these material properties. Quasi-static tensile tests were conducted on the coupon level for a UD composite with a ply drop. A combined numerical/experimental approach was followed to identify the material properties associated with delamination evolution. For that purpose, a finite element model was created using the cohesive zone model. The delamination-related properties were characterized by fitting the numerical model to the experiments by calibrating the cohesive zone parameters such that the global coupon response and the delamination extent for different load levels were in good agreement. Based on the identified parameter set, a sensitivity analysis was carried out to raise awareness of the influence of material properties on damage evolution. Damage around the ply drop was governed by mode II delamination. Several sensitivities were found to be non-linear with respect to a variation of input parameters. The methodology can be used in future work focusing on different ply drop configurations, and the results so far can serve as a database for benchmark simulations of delamination evolution in the vicinity of ply drops.

Comparison of a quasi Newton method using Broyden’s update formula and an adjoint method for determining local magnetic material properties of electrical steel sheets

PurposePerforming accurate numerical simulations of electrical drives, the precise knowledge of the local magnetic material properties is of utmost importance. Due to the various manufacturing steps, e.g. heat treatment or cutting techniques, the magnetic material properties can strongly vary locally, and the assumption of homogenized global material parameters is no longer feasible. This paper aims to present the general methodology and two different solution strategies for determining the local magnetic material properties using reference and simulation data.Design/methodology/approachThe general methodology combines methods based on measurement, numerical simulation and solving an inverse problem. Therefore, a sensor-actuator system is used to characterize electrical steel sheets locally. Based on the measurement data and results from the finite element simulation, the inverse problem is solved with two different solution strategies. The first one is a quasi Newton method (QNM) using Broyden's update formula to approximate the Jacobian and the second is an adjoint method. For comparison of both methods regarding convergence and efficiency, an artificial example with a linear material model is considered.FindingsThe QNM and the adjoint method show similar convergence behavior for two different cutting-edge effects. Furthermore, considering a priori information improved the convergence rate. However, no impact on the stability and the remaining error is observed.Originality/valueThe presented methodology enables a fast and simple determination of the local magnetic material properties of electrical steel sheets without the need for a large number of samples or special preparation procedures.

PERIODIC CONTROL OF CONCRETE PROPERTIES IN THE SYSTEM OF TECHNICAL CONDITION ASSESSMENT FOR HIGH-STORY BUILDING

The assessment of the structures’ technical condition is conducted in accordance with current regulations. During such assessment, various methods are used to determine the physical and mechanical characteristics of the structure’s material. Usually, a single measurement is performed, but in some cases, it is necessary to establish observations to determine the behaviour of the observed defects. Particular attention should be paid to buildings that have not been in use for some time and no measures have been taken to preserve the structures. Since the conditions of concrete formation and hardening in the samples during the establishment of taring dependencies and in the structure in operation are different, the existing non-destructive testing methods do not adequately reflect the properties of the structure’s concrete. Experience in the use of ultrasonic devices and our own research to improve the ultrasonic method allowed us to recommend limiting the scope of this method to periodic inspection, since it is quite easy and accurate to track relative changes in the material of the structure. The purpose of this work – verification of the effectiveness of the improved method of conducting periodic control of concrete properties in the conditions of a real object. Results. The technical condition of the structures of the multi-story building was assessed. Within the scope of the survey, the capabilities of the modernized method of periodic control of the concrete structures’ properties during their operation were checked. Ultrasonic devices are involved in the work, provided that the measurement sites are specially prepared. An increase in the accuracy of determining material properties has been demonstrated. Conclusion. The developed method of periodic control of the concrete structures’ properties demonstrates the low complexity of the work and the sufficient reliability of the obtained results, which allows us to propose it for use in determining the technical condition of the structures in operation.

Experimental characterization and finite element investigation of SiO2 nanoparticles reinforced dental resin composite

In this study, a commercial dental resin was reinforced by SiO2 nanoparticles (NPs) with different concentrations to enhance its mechanical functionality. The material characterization and finite element analysis (FEA) have been performed to evaluate the mechanical properties. Wedge indentation and 3-point bending tests were conducted to assess the mechanical behavior of the prepared nanocomposites. The results revealed that the optimal content of NPs was achieved at 1% SiO2, resulting in a 35% increase in the indentation reaction force. Therefore, the sample containing 1% SiO2 NPs was considered for further tests. The morphology of selected sample was examined using field emission scanning electron microscopy (FE-SEM), revealing the homogeneous dispersion of SiO2 NPs with minimal agglomeration. X-ray diffraction (XRD) was employed to investigate the crystalline structure of the selected sample, indicating no change in the dental resin state upon adding SiO2 NPs. In the second part of the study, a novel approach called iterative FEA, supported by the experiment wedge indentation test, was used to determine the mechanical properties of the 1% SiO2-dental resin. Subsequently, the accurately determined material properties were assigned to a dental crown model to virtually investigate its behavior under oblique loading. The virtual test results demonstrated that most microcracks initiated from the top of the crown and extended through its thickness.

Deep Learning Regressors of Surface Properties from Atomic Force Microscopy Nanoindentations

Atomic force microscopy (AFM) is a powerful technique to study the nanomechanical properties of a wide range of materials at the piconewton level. AFM force–indentation curves can be fitted with appropriate contact models, enabling the determination of material properties for a given sample. However, the analysis of large datasets comprising thousands of curves using conventional methods presents a time-intensive challenge. As a result, there is an increasing interest in exploring alternative methodologies, such as integrating machine learning (ML) models to streamline and improve the efficiency of this process. In this work, two data-driven regressors were tuned to predict the Young’s modulus and adhesion energy from force–indentation curves of soft samples (Young’s modulus up to 10 kPa). Both models were trained exclusively on synthetic data derived from the contact theories developed by Hertz as well as Johnson, Kendall and Roberts (JKR). The PyTorch library was employed to build and train the models; then, the key hyperparameters were refined by implementing the optimization framework Optuna. The first model was successfully tested with synthetic and experimental curves from AFM nanoindentations, and the second presented promising results on the synthetic data. Our work suggests that experimental data may not be essential for training data-driven models to predict surface properties from AFM nanoindentations. By delivering accurate predictions in a computationally efficient way, our regressors validate the potential of a deep learning approach in exploring AFM nanoindentations and motivate further development of similar strategies to overcome current limitations in AFM postprocessing.

A Methodology for the Rapid Qualification of Additively Manufactured Materials Based on Pore Defect Structures

Additive manufacturing (AM) can create net or near-net-shaped components while simultaneously building the material microstructure, therefore closely coupling forming the material and shaping the part in contrast to traditional manufacturing with distinction between the two processes. While there are well-heralded benefits to AM, the widespread adoption of AM in fatigue-limited applications is hindered by defects such as porosity resulting from off-nominal process conditions. The vast number of AM process parameters and conditions make it challenging to capture variability in porosity that drives fatigue design allowables during qualification. Furthermore, geometric features such as overhangs and thin walls influence local heat conductivity and thereby impact local defects and microstructure. Consequently, qualifying AM material within parts in terms of material properties is not always a straightforward task. This article presents an approach for rapid qualification of AM fatigue-limited parts and includes three main aspects: (1) seeding pore defects of specific size, distribution, and morphology into AM specimens, (2) combining non-destructive and destructive techniques for material characterization and mechanical fatigue testing, and (3) conducting microstructure-based simulations of fatigue behavior resulting from specific pore defect and microstructure combinations. The proposed approach enables simulated data to be generated to validate and/or augment experimental fatigue data sets with the intent to reduce the number of tests needed and promote a more rapid route to AM material qualification. Additionally, this work suggests a closer coupling between material qualification and part certification for determining material properties at distinct regions within an AM part.

Determination of Material and Fracture Properties of a Case-Hardened Planet Gear and Its Homogenisation Method to Obtain the Damage Mechanism Caused by Fragment Ingestion.

Before a new type of engine is introduced into civil aviation, it must comply with various safety regulations. These regulations include the analysis of secondary damage caused by the re-ingestion of a tooth fragment. The purpose is to prevent crack propagation through the gear rim, which would lead to catastrophic failure. In this context, identification of the initial crack location is crucial to determine the crack propagation path. Therefore, this paper presents a technique to determine and validate a constitutive material model and fracture locus for case-hardened spur gears. As the modelling of the surface-hardened layer is computationally intensive, it is necessary to homogenise the model. This paper comprehensively reviews and discusses the associated effects and errors. To determine the plastic behaviour of the case-hardened external gear (30CrNiMo8) and the nitrided internal gear (35CrAlNi7-10), the widely acknowledged Johnson-Cook material model is implemented using compression and Vickers indenter tests to define the necessary parameters. The fracture locus implementation is also based on the Johnson-Cook method and an axial shift of the fracture locus based on the hardness profile of the spur gears is determined by quasi-static pulsator tests. For validation, a project-specific gearbox test rig is used, enabling consistent ingestion of defined fragments. In addition, to check the likelihood of a tooth flank crack and to validate the results, a simplified ingestion experiment is performed.

Çimentosuz Kompozitlerde Tahribatlı ve Tahribatsız Testlerin Elektrisksel Direnç ile İlişkilendirilmesi

In the construction industry, tests such as compressive strength, density porosity, and water absorption porosity are frequently used to determine material properties. In general, experimental studies are divided into two categories: destructive and non-destructive testing methods. According to the common consensus, destructive testing methods produce more dependable results than non-destructive testing methods. However, it is not possible to reuse the samples in destructive tests, and there are difficulties in taking samples from the building whose construction process has been completed. In addition, the experimental implementation of destructive tests creates time and cost disadvantages. Within the scope of this study, destructive and non-destructive experiments have been carried out on alkali-activated concrete composites, which have attracted interest as sustainable environmentally friendly composite building materials in recent years. Compressive strength, density, porosity, water absorption, etc. traditional test methods have been associated with electrical resistance measurements. Electrical measurements have been taken with the MEGGER equipment, and resistance values have been directly correlated with the other parameters. The positive results indicate that different structures of materials used in the construction industry can be evaluated regardless of sample size or localization.

Investigation of the Motion of a Spherical Object Located at Soft Elastic and Viscoelastic Material Interface for Identification of Material Properties

Measuring the properties of soft viscoelastic materials is challenging. Here, the motion of a spherical object located at the soft elastic and viscoelastic material interface for the identification of material properties is thoroughly investigated. Formulations for different loading cases were derived. First, the theoretical models for a spherical object located at an elastic medium interface were derived, ignoring the medium viscosity. After summarizing the model for the force reducing to zero following the initial loading, we developed mathematical models for the force reducing to a lower non-zero value or increasing to a higher non-zero value, following the initial loading. Second, a similar derivation process was followed to evaluate the response of a spherical object located at a viscoelastic medium interface. Third, by performing systematic analyses, the theoretical models obtained via different approaches were compared and evaluated. Fourth, the measured and predicted responses of a spherical object located at a gelatin phantom interface were compared and the viscoelastic material properties were identified. It was seen that the frequency of oscillations of a spherical object located at the sample interface during loading was 10–15% different from that during unloading in the experimental studies here. The results showed that different loading cases have immense practical value and the formulations for different loading cases can provide an accurate determination of material properties in a multitude of biomedical and industrial applications.

On the importance of accurate elasto-plastic material properties in simulating plate osteosynthesis failure.

Background: Plate osteosynthesis is a widely used technique for bone fracture fixation; however, complications such as plate bending remain a significant clinical concern. A better understanding of the failure mechanisms behind plate osteosynthesis is crucial for improving treatment outcomes. This study aimed to develop finite element (FE) models to predict plate bending failure and validate these against in vitro experiments using literature-based and experimentally determined implant material properties. Methods: Plate fixations of seven cadaveric tibia shaft fractures were tested to failure in a biomechanical setup with various implant configurations. FE models of the bone-implant constructs were developed from computed tomography (CT) scans. Elasto-plastic implant material properties were assigned using either literature data or the experimentally derived data. The predictive capability of these two FE modelling approaches was assessed based on the experimental ground truth. Results: The FE simulations provided quantitatively correct prediction of the in vitro cadaveric experiments in terms of construct stiffness [concordance correlation coefficient (CCC) = 0.97, standard error of estimate (SEE) = 23.66, relative standard error (RSE) = 10.3%], yield load (CCC = 0.97, SEE = 41.21N, RSE = 7.7%), and maximum force (CCC = 0.96, SEE = 35.04, RSE = 9.3%), when including the experimentally determined material properties. Literature-based properties led to inferior accuracies for both stiffness (CCC = 0.92, SEE = 27.62, RSE = 19.6%), yield load (CCC = 0.83, SEE = 46.53N, RSE = 21.4%), and maximum force (CCC = 0.86, SEE = 57.71, RSE = 14.4%). Conclusion: The validated FE model allows for accurate prediction of plate osteosynthesis construct behaviour beyond the elastic regime but only when using experimentally determined implant material properties. Literature-based material properties led to inferior predictability. These validated models have the potential to be utilized for assessing the loads leading to plastic deformation in vivo, as well as aiding in preoperative planning and postoperative rehabilitation protocols.

Archaeometric characterization and restoration proposal for filling mortars of Oshki (Öşvank) church

In order to ensure the sustainability of cultural, historical and architectural heritage, preserving and restoring historical buildings and transferring them to future generations is one of the important issues of today. Restoration decisions regarding the repairs of historical buildings are of great importance in this context. Developing correct intervention decisions requires the thorough analysis of the structure, the determination of the structural and material properties meticulously, and the use the most appropriate materials for repairing it. However, only physical and chemical analyses are not sufficient to determine material properties of historical buildings; therefore, archaeometric analyses are needed to determine them more appropriately. In this study, it is aimed to determine the components and characteristics of the filling mortars of Oshki (Öşvank) Church, one of the most magnificent structures of the Eastern Anatolia region, in order to preserve the masonry structure and guide the restoration studies in the light of archaeometric analyses. The raw material properties of the samples taken from the filling mortars of the church were determined by the physical, chemical and petrographic analyses. As a result of the analyses, the aggregate-binding properties of Oshki Church filler mortars were determined. It was revealed that the aggregate content was determined as petrographic, lime was used as a binder and all samples contained pozzolan whereas no cement was used in any of the samples, and the samples did not contain marble rice/powder and organic additives like oil, protein etc. It has also been observed that the aggregate in the mortar content is compatible with the geological formations of near surrounding of the church. In this context, this study emphasizes the importance of archaeometric analysis in restoration of historical buildings. Moreover, differing from other studies in the literature, this study proposes mortar recipe to be used in the restoration of the church, which can pioneer to future studies in the field of architectural restoration.

Mapping local atomic structure of metallic glasses using machine learning aided 4D-STEM

Amorphous materials such as polymers, metallic and oxidic glasses consist of heterogeneous atomic/molecular packing at the nanoscale. Spatial variation of the local structure plays an important role in determining material properties. Experimentally probing the local atomic structure within the amorphous phase has been one of the main challenges for material research. Here, we present a new approach to characterize the local atomic structure and map structural variants in the amorphous phase using machine learning (ML) aided four dimensional-scanning transmission electron microscopy (4D-STEM). We utilized nonnegative matrix factorization (NMF) to identify the local structural types of metallic glasses in 4D-STEM datasets. Using Fe-based metallic glasses as a model system, we demonstrate that two basic structural types, one with a more liquid-like and another with a more solid-like structure, are distributed throughout the glass with a characteristic length scale of a few nanometers. Thermal annealing induces a change in their distribution and relative population but without the appearance of any additional phase. This provides new insights into the relaxation phenomena of metallic glasses and solid experimental evidence for the theoretical hypothesis on atomic packing in glassy structures.

Irradiated mechanical properties predicted by a machine learning method with the Fourier-transform-based feature extension

ABSTRACT High-dimensional nonlinear relationships between the irradiated yield strength and its influencing factors, including doses, temperatures, and crystal structures, are difficult to explicitly characterize in the absence of a comprehensive database. In this study, we developed a machine learning method with the Fourier-transform-based feature extension, successfully constructing the prediction model of irradiated yield strength by a relatively small and sparse database of irradiated material properties. The analysis suggests that the proposed feature extension method improves the training performances of machine learning with small dataset. And the present model is accurate and feasible for predicting the irradiated yielding behaviors. Furthermore, we attempt the inverse machine learning model to determine material properties and irradiation conditions according to the desired yield strength. Since the parameter combinations commensurate with a fixed strength are diverse, the optimal model is helpful in reversely calculating and optimizing material performances. The data-driven machine learning method, which can detect the implicit correlations among numerous data, exhibits great prospects in investigating irradiated mechanical properties and exploring multiscale links in the nuclear material field. This work holds the promise for optimizing the design of in-pile structural components and can be further extended to other machine learning problems with the small dataset.

Coupled five-parameter dynamics of Mindlin and third-order shear deformable FG graphene-platelets reinforced viscoelastic plates with geometric and material imperfections

The present work investigates the coupled five-parameter dynamics, in particular, the coupled five-parameter structural resonance frequency, of functionally graded (FG) graphene-platelets reinforced viscoelastic plates in the presence of geometric and material (porosity) imperfections, based on the Mindlin theory and the third-order shear deformation plate theory (TSDPT). Various imperfections are often found in structures as a result of the challenges in manufacturing and operations over time. Geometric imperfection is considered in the FG reinforced plate structure by modelling an initial curvature in the out-of-plane direction. Material imperfections, in the form of closed-cell voids, are formulated as uniform and non-uniform FG porosity distributions. Uniform and thickness-wise FG gradation effects of graphene-platelets are accounted for in the determination of the effective material properties using a two-dimensional Halpin-Tsai micromechanics model, in conjunction with the rule of mixtures. Viscoelasticity of the FG imperfect plate structure is modelled by employing the Kelvin-Voigt model to consider energy dissipation. Using the Mindlin plate theory and the TSDPT, five equations of motion, which are coupled through the five parameters u, v, w, ϕ1, and ϕ2, are derived using Hamilton's variational principle. An assumed mode method is then employed to obtain the real and the imaginary components of resonance frequencies. The combined influences of the different effects on the structural resonance are examined. The results obtained offer a comprehensive understanding of how the FG graphene-platelets, FG porosity, plate thickness, geometric imperfection, and the utilisation of two different shear deformation plate theories collectively influence the coupled five-parameter dynamics of the FG graphene-platelets reinforced viscoelastic plate structure with imperfections. It was found that the difference in frequency resulted from the use of the two plate theories is most dominant with the FG GX and/or FG PX graphene-platelets reinforced porous plates, and that geometric imperfection was found to alter a graphene-platelets reinforced plate's sensitivity towards material imperfection.

Regression fitting megavoltage depth dose curves to determine material relative electron density in radiotherapy.

The relative electron density (RED) parameter is ubiquitous throughout radiotherapy for clinical dosimetry and treatment planning purposes as it provides a more accurate description of the relevant radiological properties over mass density alone. RED is in practice determined indirectly from calibrated CT Hounsfield Units (HU). While CT images provide useful 3D information, the spectral differences between CT and clinical LINAC beams may impact the validity of the CT-ED calibration, especially in the context of novel tissue-mimicking materials where deviations from biologically typical atomic number to atomic weight ratios 〈Z/A〉 occur and/or high-Z materials are present. A theoretical basis for determining material properties directly in a clinical beam spectrum via an electron-density equivalent pathlength (eEPL) method has been previously established. An experimental implementation of this approach is introduced whereby material-specific measured percentage depth dose curves (PDDs) are regressed to a PDD measured in a reference material (water), providing an inference of 〈Z/A〉, which when combined with the physical density provides a determination of RED. This method is validated over a range of tissue-mimicking materials and compared against the standard CT output, as well as compositional information obtained from the manufacturer's specifications. The measured PDD regression method shows consistent results against both manufacturer-provided and CT-derived values between 0.9 and 1.15 RED. Outside of this soft-tissue range a trend was observed whereby the 〈Z/A〉 determined becomes unrealistic indicating the method is no longer reporting RED alone and the assumptions around the eEPL model are constrained. Within the soft-tissue RED range of validity, the regression method provides a practical and robust characterisation for unknown materials in the clinical setting and may be used to improve on the CT derived RED where high Z material components are suspected.

Improving the reliability of NiTi endodontic files using eddy currents, thermography and fatigue tests: A multimethod approach

Non-Destructive Testing (NDT) by Eddy Currents (EC) allows for determining material properties and detecting surface and subsurface defects that can harm structural integrity of electrically conductive components. However, despite being a standard technique and with many years of accumulated experience, there are some conditions where difficulties persist, such as detecting small defects in complex components with small dimensions and conicity (e.g. endodontic files used in a clinical environment).This work aimed to design, numerically simulate, produce, and experimentally validate different configurations of EC probes for defect detection in endodontic files. For the application of NDTs, an artificial defect was introduced in the apical region of a commercial endodontic file with 4% taper and a tip’s diameter equal to 0.20 mm. The experimental results showed that most of the methodologies developed for the inspection of files through NDTs proved unable to detect the defective region, primarily due to its taper and the special Pauli paramagnetic properties of the NiTi alloy. Nevertheless, the customized EC toroidal probe operating in differential bridge mode could detect the artificial defect in the endodontic file. In parallel, a thermographic inspection of the defective instrument was made. As a result, it was possible to detect the defect by thermography, although with low Signal-to-Noise Ratio (SNR) due to its small dimensions.Finally, commercial endodontic files manufactured by Electrical Discharge Machining (EDM) were tested and compared with the results obtained for conventional manufactured endodontic files. The endodontic instruments were placed in rotation in an experimental setup designed to simulate a root canal with a radius of curvature equal to 5 mm applied along a 45° angle. The experimental results showed that the latest generation of endodontic files, manufactured using EDM process, are significantly more resistant to fatigue fracture when compared to the Controlled Memory (CM) machined files.

Characterization of Polymeric Composites for Hydrogen Tank.

Carbon neutrality has led to a surge in the popularity of hydrogen tanks in recent years. However, designing high-performance tanks necessitates the precise determination of input material properties. Unfortunately, conventional characterization methods often underestimate these material properties. To address this limitation, the current research introduces alternative designs of ring tensile specimens, which enable accurate and reliable characterization of filament-wound structures. The advantages and disadvantages of these alternative designs are thoroughly discussed, considering both numerical simulations and experimental investigations. Moreover, the proposed ring tensile methods are applied to characterize thermoplastic composites for hydrogen storage tanks. The results indicate that the mechanical strengths and stiffness of carbon fiber-reinforced thermoplastic Elium® 591 composites closely match those of epoxy-based composites. This newfound accuracy in measurement is expected to contribute significantly to the development of recyclable hydrogen tanks.

Determination of material properties from tissue samples of low strength and size

Abstract Uniaxial tensile tests are the most common method for investigating the mechanical properties of materials. However, due to the small strength and size of certain materials, larger conventional universal testing machines are sometimes not suitable for performing elongation testing, so dedicated test setups are required. Therefore, the authors developed a testing device to measure the mechanical properties of small, flexible materials, e.g. fragile specimens of the capsular bag of the eye. Also different variants for specimen holders were designed and tested. Initial tests using eggshell membranes as a model material demonstrated the functionality of the test setup at different strain rates.

Determination of Material and Interaction Properties of Granular Fertilizer Particles Using DEM Simulation and Bench Testing

The discrete element method (DEM) is an effective tool for obtaining qualitative and quantitative information on particle motion, which aids in the design and optimization of agricultural equipment structures. The accuracy of the DEM simulation parameters significantly impacts the simulation results. This study employed a combination of high-speed camera measurement, DEM simulation, and validation tests to determine the material and interaction property parameters for fertilizer particles. The basic parameters (triaxial size, bulk density, density, and coefficient of static friction) and coefficients of restitution between fertilizer and material were measured for three fertilizer varieties. There was a significant difference in the angle of repose between various material plates and fertilizer particles. The calibration values of coefficients of restitution and coefficients of rolling friction between fertilizer particles were optimized using the Box–Behnken method. The angle of repose was significantly affected by the coefficient of static friction and the coefficient of rolling friction between the fertilizer particles. The determined values for the coefficient of restitution, coefficient of static friction, and coefficient of rolling friction between the fertilizer particles were 0.323, 0.381, and 0.173, respectively. The error in the angle of the repose test was less than 3.0%, and the variation coefficient for each row consistency was less than 1.68 percentage points under the optimal simulation parameters. DEM simulations of the angle of repose and each row consistency variation coefficient test using the measured parameters can accurately predict the experimental results. The findings of this paper provide a theoretical basis for the DEM study of fertilizer particles.