Simulation Parameters Research Articles

Simulating Bacterial Membrane Models at the Atomistic Level: A Force Field Comparison.

Molecular dynamics (MD) simulations are currently an indispensable tool to understand both the dynamic and nanoscale organization of cell membrane models. A large number of quantitative parameters can be extracted from these simulations, but their reliability is determined by the quality of the employed force field and the simulation parameters. Much of the work on parametrizing and optimizing force fields for biomembrane modeling has been focused on homogeneous bilayers with a single phospholipid type. However, these may not perform effectively or could even be unsuitable for lipid mixtures commonly employed in membrane models. This work aims to fill this gap by comparing MD simulation results of several bacterial membrane models using different force fields and simulation parameters, namely, CHARMM36, Slipids, and GROMOS-CKP. Furthermore, the hydrogen isotope exchange (HIE) method, combined with GROMOS-CKP (GROMOS-H2Q), was also tested to check for the impact of this acceleration strategy on the performance of the force field. A common set of simulation parameters was employed for all of the force fields in addition to those corresponding to the original parametrization of each of them. Furthermore, new experimental order parameter values determined from NMR of several lipid mixtures are also reported to compare them with those determined from MD simulations. Our results reveal that most of the calculated physical properties of bacterial membrane models from MD simulations are substantially force field and lipid composition dependent. Some lipid mixtures exhibit nearly ideal behaviors, while the interaction of different lipid types in other mixtures is highly synergistic. None of the employed force fields seem to be clearly superior to the other three, each having its own strengths and weaknesses. Slipids are notably effective at replicating the order parameters for all acyl chains, including those in lipid mixtures, but they offer the least accurate results for headgroup parameters. Conversely, CHARMM provides almost perfect estimates for the order parameters of the headgroups but tends to overestimate those of the lipid tails. The GROMOS parametrizations deliver reasonable order parameters for entire lipid molecules, including multicomponent bilayers, although they do not reach the accuracy of Slipids for tails or CHARMM for headgroups. Importantly, GROMOS-H2Q stands out for its computational efficiency, being at least 3 times faster than GROMOS, which is already faster than both CHARMM and Slipids. In turn, GROMOS-H2Q yields much higher compressibilities compared to all other parametrizations.

Dynamic impact analysis of the time-delay levitation control system on maglev vehicle system after adding smith predictor

The time delay (TD) in the levitation control system significantly affects the dynamic performance of the closed-loop system in electromagnetic suspension (EMS) maglev vehicles. Excessive TD can cause levitation instability, making it essential to explore effective mitigation methods. To address this issue, a Smith Predictor (SP) is integrated into the traditional PID levitation control system. The combination of theoretical analysis and numerical simulation is employed to assess the stability of the time-delay levitation control system after the integration of the Smith Predictor. Theoretical analysis reveals that when TD exceeds a critical threshold, the levitation system becomes unstable. The addition of SP alters the root trajectory of the system characteristic equation from positive to negative, and recovers the levitation system to stable status. Assuming complete knowledge of the dynamic system, the TD compensation value in the SP becomes a key parameter that determines its performance. A minimum effective value (MEV) for TD compensation is identified, correlating with the system's stability region. Under the influence of TD, more complex systems and higher running speeds of the maglev vehicle lead to a narrower stable region and a larger MEV for TD compensation. Given the simulation parameters in this paper, with a system TD of 15 ms and a maximum vehicle speed of 160 km/h, the MEV for TD compensation in the SP should be set at 12 ms.

Assessing key parameters in simultaneous simulation of rapid kinetics of chlorophyll a fluorescence and trans-thylakoid electric potential difference.

Our study attempts to address the following questions: among numerous photosynthetic modules, which parameters notably influence the rapid chlorophyll fluorescence (ChlF) rise, the so-called O-J-I-P transient, in conjunction with the P515 signal, as these two records are easily obtained and widely used in photosynthesis research, and how are these parameters ranked in terms of their importance? These questions might be difficult to answer solely through experimental assays. Therefore, we employed an established photosynthesis model. Firstly, we utilized the model to simulate the measured rapid ChlF rise and P515 kinetics simultaneously. Secondly, we employed the sensitivity analysis (SA) tool by randomly altering model parameters to observe their effects on model output variables. Thirdly, we systematically identified significant parameters for both or one of the kinetics across various scenarios. A novel aspect of our study is the application of the Morris method, a global SA tool, to simultaneously assess the significance of model parameters in shaping both or one of the kinetics. The Morris SA technique enables the quantification of how much a specific parameter affects O-J-I-P transient during particular time intervals (e.g., J, I, and P steps). This allowed us to theoretically analyze which step is more significantly influenced by the parameter. In summary, our study contributes to the field by providing a comprehensive analysis of photosynthesis kinetics and emphasizing the importance of parameter selection in modelling this process. These findings can inform future research efforts aimed at improving photosynthesis models and advancing our understanding of photosynthetic processes.

Discrete element modeling of JLU-H lunar highland simulant

In order to accurately model the machine-lunar soil simulant interaction, this study combined physical and simulation experiments to calibrate the discrete element simulation parameters of the JLU-H lunar highland simulant. First, the intrinsic parameters and the true angle of repose of the JLU-H were determined through physical tests to provide data for subsequent simulation tests. A Plackett-Burman test was designed to identify and select the parameters that have a significant effect on the angle of repose. The range of values of the significant parameters was then optimized using the steepest climb test. The Box-Behnken test was then utilized to calibrate and obtain the optimal parameter combinations. Finally, a validation test of the angle of repose was conducted using the calibrated DEM parameters. The relative error between the simulation results and the test results was 1.54 %. Then further straight shear tests were conducted to verify the accuracy and validity of the DEM parameters. The results show that the calibrated parameters can provide a reference for the selection of discrete element simulation parameters for lunar soil simulant and the design and optimization of drilling and excavation machinery for lunar exploration.

Coronal energy release by MHD avalanches

Context. Magnetohydrodynamic (MHD) instabilities, such as the kink instability, can trigger the chaotic fragmentation of a twisted magnetic flux tube into small-scale current sheets that dissipate as aperiodic impulsive heating events. In turn, the instability could propagate as an avalanche to nearby flux tubes and lead to a nanoflare storm. Our previous work was devoted to related 3D MHD numerical modeling, which included a stratified atmosphere from the solar chromosphere to the corona, tapering magnetic field, and solar gravity for curved loops with the thermal structure modelled by plasma thermal conduction, along with optically thin radiation and anomalous resistivity for 50 Mm flux tubes. Aims. Using 3D MHD modeling, this work addresses predictions for the extreme-ultraviolet (EUV) imaging spectroscopy of such structure and evolution of a loop, with an average temperature of 2–2.5 MK in the solar corona. We set a particular focus on the forthcoming MUSE mission, as derived from the 3D MHD modeling. Methods. From the output of the numerical simulations, we synthesized the intensities, Doppler shifts, and non-thermal line broadening in 3 EUV spectral lines in the MUSE passbands: Fe IX 171 Å, Fe XV 284 Å, and Fe XIX 108 Å, emitted by ∼1 MK, ∼2 MK, and ∼10 MK plasma, respectively. These data were detectable by MUSE, according to the MUSE expected pixel size, temporal resolution, and temperature response functions. We provide maps showing different view angles (front and top) and realistic spectra. Finally, we discuss the relevant evolutionary processes from the perspective of possible observations. Reults. We find that the MUSE observations might be able to detect the fine structure determined by tube fragmentation. In particular, the Fe IX line is mostly emitted at the loop footpoints, where we might be able to track the motions that drive the magnetic stressing and detect the upward motion of evaporating plasma from the chromosphere. In Fe XV, we might see the bulk of the loop with increasing intensity, with alternating filamentary Doppler and non-thermal components in the front view, along with more defined spots in the topward view. The Fe XIX line is very faint within the chosen simulation parameters; thus, any transient brightening around the loop apex may possibly be emphasized by the folding of sheet-like structures, mainly at the boundary of unstable tubes. Conclusions. In conclusion, we show that coronal loop observations with MUSE can pinpoint some crucial features of MHD-modeled ignition processes, such as the related dynamics, helping to identify the heating processes.

Ground-motions site and event specificity: Insights from assessing a suite of simulated ground motions in the San Francisco Bay Area

This article presents the results of a research that is part of a larger collaborative effort between the Lawrence Berkeley National Laboratory and the Pacific Earthquake Engineering Research Center, funded by the US Department of Energy Office of Cybersecurity, Energy Security and Emergency Response. The main objective of this study is to assess a suite of near and far-field simulated ground motions obtained from 20 realizations of an M7 Hayward Fault earthquake in the San Francisco Bay Area, California USA, and inform the selection of rupture simulation parameters leading to strong motions. To this aim, comparisons are conducted with NGA-W2 and directivity ground-motion models and a selected population of records. An archetypal steel moment-resisting frame is utilized to assess infrastructure response distributions. The analyses carried out for each simulated event and subdomain with consistent properties in terms of shallow shear-wave velocity proved to be instrumental for better interpreting the differences between simulated motions and empirical models. The main reasons identified for variances between simulations and empirical relationships included (1) directivity effects fully captured by the simulations across the full breadth of rupture models; (2) site vicinity to ruptures that incorporate large-slip patches, particularly if these are in the forward-directivity direction; and (3) presence of geologic structures that can “trap” seismic waves and produce ground motions with large amplitude and long signal duration. The analyses carried out in this work provide a path for interpreting ground-motion site and event specificity obtained from a suite of physics-based simulations, differing only in the rupture model characterization, to inform the selection of simulation scenarios for site-specific engineering analyses under strong excitations. Evidence from this work points to the possibility that current hazard models may underestimate ground-motion intensities in areas where the combined effect of directivity and site conditions results in large ground-motion amplitudes.

LPCE-Based Replacement Scheme for Enhancing Caching Performance in Named Data Networking

The substantial surge in users has adversely impacted the performance of the present IP-based Internet. Named data networking (NDN) emerges as a future alternative, given its distributed content caching system, where data can be cached in multiple routers and retrieved from the closest one instead of the original producer, enhancing content availability, reducing latency, and minimizing data loss. This paper introduces the less popular content eviction (LPCE) policy, a novel cache replacement scheme designed to enhance the caching performance of the conventional LFU (least frequently used) policy in NDN routers, thereby improving overall network efficiency. The proposed method subsumes LFU and FIFO (first in first out) policies and employs an additional list controlled by the LRU (least recently used) policy. Utilizing the ccnSim simulator, we conduct a comparison of LPCE’s performance with that of the LFU technique and other competing caching techniques, considering variations in several simulation parameters. Experimental results reveal that the proposed LPCE algorithm excels over others across a majority of performance metrics, such as cache hit ratio, content delivery delay, upstream hop count, network traffic, and producers’ load. Besides, the findings indicate that LPCE outperforms LFU, with an increase in cache hit ratio ranging from 1.32% to 5.75%.

Estimation and uncertainty quantification of magma interaction times using statistical emulation

The evolution of volcanic plumbing systems, which controls the style and size of eruptions, is largely determined by processes at depths that are not observable. Scientists use numerical models to simulate these processes and compare the outputs with data on erupted products to understand the plumbing system and eruption processes. However, our ability to explore the parameter space in order to match petrological and geophysical observations is limited by the computational cost required for such simulations. As an alternative, we present a statistical emulator that can reproduce the numerical results as a function of a set of input parameters. This approach can be used to invert the observed distribution of whole rock chemistry to determine the duration of interaction between magmas preceding an eruption and identify the best matching input parameters. This method intrinsically includes error propagation, thus providing reliable confidence intervals for the relevant parameters of the numerical simulations.

A hyper-viscoelastic uniaxial characterization of collagenous embolus analogs in acute ischemic stroke

PurposeAcute ischemic stroke is a leading cause of death and morbidity worldwide. Despite advances in medical technology, nearly 30% of strokes result in incomplete vessel recanalization. Recent studies have demonstrated that clot composition correlates with success rates of mechanical thrombectomy procedures. To understand clot behavior during thrombectomy, which exerts considerable strains on thrombi, in vitro studies must characterize the rate-dependent high-strain behavior of embolus analogs (EAs) with different formation conditions, which can be used to fit models of hyper-viscoelasticity. MethodsIn this study, the effect of collagen infiltration as a carotid-induced collagen-rich thrombosis surrogate is considered as a contributor to embolus analog high-strain stiffness, when compared to 40% hematocrit EAs. ResultsEA high-strain stiffnesses, characterized on a uniaxial load frame, increase by an order of magnitude for collagenous clot analogs. Chandler loop analogs show high-strain stiffnesses and clot compositions commensurate with previous reports of stroke patient clots, and collagenous clots show significant increase in stiffness when compared to stroke patient clots. Finally, hyper-viscoelastic curve fitting demonstrates the asymmetry between tension and compression. Nonlinear, rate-dependent models that consider clot-stiffening behavior match the high strain stiffness of clots fairly well. Furthermore, we demonstrate that the stability of the elastic energy needs to be considered to obtain optimal curve fits for high-strain, rate dependent data. ConclusionThis study provides a framework for the development of dynamically formed EAs that mimic the mechanical and structural properties of in vivo clots and provides parameters for numerical simulation of clot behavior with hyper-viscoelastic models.

Damping efficiency of the fractional Duffing system and an assessment of its solution accuracy

Dynamical systems with high damping efficiency in a wide frequency band can be useful on a small scale – for harvesting energy from ambient vibrations, and on a large scale – for damping harmful vibrations of mechanical structures. In this paper we present an assessment of the quality of solutions and damping efficiency of systems with fractional order derivatives. To simulate the fractional system the fourth-order Runge–Kutta method and Grünwald–Letnikov methods are used. We propose a coefficient for assessing the quality of solutions to fractional systems by reference to the quality of the calculated energy balance. As an exemplary system we study the Duffing model with embedded additional fractional-order derivative terms. Based on this coefficient, intervals of key numerical simulation parameters are determined to ensure the appropriate quality for the calculations of energy flows and energy balance. The determined values of these parameters are then used in tests of the damping efficiency of the studied system. Our results show that by modifying the fractional terms it is possible to configure a system that exhibits a “broadband effect”, i.e. a system that is characterized by high-amplitude vibrations and, consequently, high energy efficiency in a wide range of excitation frequencies.

A framework for measuring the quality of business process simulation models

Business Process Simulation (BPS) is an approach to analyze the performance of business processes under different scenarios. For example, BPS allows us to estimate the impact of adding one or more resources on the cycle time of a process. The starting point of BPS is a process model annotated with simulation parameters (a BPS model). BPS models may be manually designed, based on information collected from stakeholders and from empirical observations, or automatically discovered from historical execution data. Regardless of its provenance, a key question when using a BPS model is how to assess its quality. In particular, in a setting where we are able to produce multiple alternative BPS models of the same process, this question becomes: How to determine which model is better, to what extent, and in what respect? In this context, this article studies the question of how to measure the quality of a BPS model with respect to its ability to accurately replicate the observed behavior of a process. Rather than pursuing a one-size-fits-all approach, the article recognizes that a process covers multiple perspectives. Accordingly, the article outlines a framework that can be instantiated in different ways to yield quality measures that tackle different process perspectives. The article defines a number of concrete quality measures and evaluates these measures with respect to their ability to discern the impact of controlled perturbations on a BPS model, and their ability to uncover the relative strengths and weaknesses of two approaches for automated discovery of BPS models. The evaluation shows that the proposed measures not only capture how close a BPS model is to the observed behavior, but they also help us to identify the sources of discrepancies.

An automated framework for material property calibration in loudspeaker simulation model

The shift to virtual meetings, online classes, and remote work has established a new norm, leading to a surge in the use of virtual communication platforms such as Zoom and Microsoft Teams. This shift has increased the demand for high-quality headsets and speakerphones, emphasizing the need for clear, superior audio quality. The process of calibrating material properties typically relies on repetitive simulations guided by experts' intuition, presenting challenges in establishing new Finite Element Models (FEMs) of loudspeakers, as it requires the repeated identification of material property values. We present a systematic framework for calibrating the mechanical material properties of loudspeaker drivers, a crucial prerequisite for developing accurate FEMs of loudspeakers. Specifically, we propose a statistically-driven approach to replace the conventional manual calibration process, which typically relies on multiple simulations guided by expert intuition. Efficient Global Optimization (EGO) is applied to address the expensive optimization problems of loudspeaker simulation. To tackle the curse of dimensionality, the objective function is decomposed into several functions based on effective parameter groups using Global Sensitivity Analysis (GSA) results. The parameters of the FEM are then calibrated to the reference data from the Lumped Parameter Model (LPM) using the decomposed-reduced objective function, providing the calibrated parameters for the loudspeaker simulation. By implementing this novel approach, even individuals without prior knowledge or experience in loudspeaker material properties can effectively and reliably obtain the necessary data for finite element modeling.

Fluctuations cutoff in a 1D Hamiltonian model for DNA

Considering a one dimensional mesoscopic model for DNA, we focus on the upper bound for the base pair fluctuations, a relevant parameter in computer simulations for which contrasting estimates have been reported. Noticing that the free energy of the model can be obtained analytically in the thermodynamic limit, we derive a relation for the fluctuations upper bound in terms of temperature and elastic force constant of the stacking potential. At room temperature, the fluctuation cutoff is constrained to values ∼2 Å in fair agreement with the threshold above which hydrogen bonds break and base pairs dissociate.

Discrete Element Modelling and Simulation Parameter Calibration for the Growing Media of Seedling Nursery Blocks

Discrete Element Modelling and Simulation Parameter Calibration for the Growing Media of Seedling Nursery Blocks

Calibration and Validation of Simulation Parameters for Maize Straw Based on Discrete Element Method and Genetic Algorithm-Backpropagation.

There is a significant difference between the simulation effect and the actual effect in the design process of maize straw-breaking equipment due to the lack of accurate simulation model parameters in the breaking and processing of maize straw. This article used a combination of physical experiments, virtual simulation, and machine learning to calibrate the simulation parameters of maize straw. A bimodal-distribution discrete element model of maize straw was established based on the intrinsic and contact parameters measured via physical experiments. The significance analysis of the simulation parameters was conducted via the Plackett-Burman experiment. The Poisson ratio, shear modulus, and normal stiffness of the maize straw significantly impacted the peak compression force of the maize straw and steel plate. The steepest-climb test was carried out for the significance parameter, and the relative error between the peak compression force in the simulation test and the peak compression force in the physical test was used as the evaluation index. It was found that the optimal range intervals for the Poisson ratio, shear modulus, and normal stiffness of the maize straw were 0.32-0.36, 1.24 × 108-1.72 × 108 Pa, and 5.9 × 106-6.7 × 106 N/m3, respectively. Using the experimental data of the central composite design as the dataset, a GA-BP neural network prediction model for the peak compression force of maize straw was established, analyzed, and evaluated. The GA-BP prediction model's accuracy was verified via experiments. It was found that the ideal combination of parameters was a Poisson ratio of 0.357, a shear modulus of 1.511 × 108 Pa, and a normal stiffness of 6.285 × 106 N/m3 for the maize straw. The results provide a basis for analyzing the damage mechanism of maize straw during the grinding process.

A flexible and efficient calibration method for discrete element simulations of additive manufacturing in construction

Extrusion-based 3D concrete printing (E3DCP), as one of the most advanced Additive Manufacturing processes, is a hotspot in the construction industry. Using the Discrete Element Method (DEM), the E3DCP can be investigated with reduced prototyping- and trial costs. However, DEM parameter calibration is challenging in the accurate simulation of construction materials because they are hardly typical granular matters. In addition, the introduction of a novel extrusion-based process Near-Nozzle-Mixing calls for a more flexible, efficient, and reliable calibration procedure due to the useable wide variety of material models.In this study, DEM simulation parameters of mortar and its components (e.g. Poraver® and paste) were thoroughly calibrated based on the central composite design method. Notably, the specific shape indices of related substrates were identified in the study to achieve the precise calibration of Poraver® and paste. Moreover, the European standard-based Haegermann flow table test was applied in the calibration by quantifying mortar consistency. This work provides a holistic and efficient calibration approach for three typical and physically different construction materials, which can be universally explored in the DEM simulation of most materials in E3DCP.

Accurate Ionic Conductivity Calculations of Battery Electrolytes at High Salt Concentration Using Molecular Dynamics Simulations

The ionic conductivity of an electrolyte formulation is a crucial property influencing battery performance. The dependence of ionic conductivity on multiple parameters, such as salt and solvent type, concentration, and temperature complicates the design of next-generation electrolytes. Efficient design of superior electrolytes requires methods capable of accurately and rapidly predicting ionic conductivity. Such methods would enable high-throughput screening of electrolyte chemistries to establish structure-property relationships.The simple Nernst-Einstein approximation is widely used in the literature to estimate ionic conductivity of electrolytes using the measured self-diffusivity. However, the failure of this approximation for concentrated solutions due to stronger intermolecular interactions requires incorporating a rigorous concentrated solution theory, such as Maxwell-Stefan (MS) diffusivity. Here, we present a molecular dynamics (MD) simulation workflow for calculating the ionic conductivity of liquid electrolytes utilizing the ion-correlated MS diffusion approach. We explore the sensitivity of calculated ionic conductivity to various simulation parameters and various methods in the literature to guide a standardized simulation protocol. Through rigorous benchmarking across a diverse range of electrolyte systems, we validate the model's accuracy by directly comparing the calculated ionic conductivities against experiments and existing literature. This work is a significant step toward a more unified and comprehensive evaluation procedure for ionic conductivity, accelerating the development of advanced electrolytes for improved battery performance.

Molecular Dynamics Study of Adhesion-Related Structural Properties for PVDF-HFP Polymer Binders

The current lithium-ion battery (LIB) market is expanding rapidly. Binders are essential to maintaining the high capacity and longevity of batteries. These binders can be classified into organic binders used for cathodes and aqueous binders used for anodes. Among them, Poly(vinylidene fluoride) (PVDF) binder is a representative organic binder that offers excellent electrochemical stability. To solve low adhesive force and weak mechanical strength of conventional PVDF binders, hexafluoropropylene (HFP) is added to improve these properties. However, the present poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP) binders still show lower adhesive force than other polymeric binders, and therefore further research works are necessary.In this study, we employ classical molecular dynamics (MD) simulations to investigate the structural properties of the PVDF-HFP copolymers. To create realistic disordered PVDF-HFP polymers, we develop a computational scheme that can randomly arrange the angles and sequences of the constituent polymer chains. By varying the ratio of randomly arranged PVDF-HFP copolymers to 0/100, 5/95, 10/90, 15/85, and 20/80, we build a solution model that mimics the HFP concentration of PVDF-HFP (0–20%, Sigma Aldrich) used in the actual experiments. N-methyl-2-pyrrolidone (NMP) used as solvents. To create a large-scale model, we utilize the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and set parameters by using OPLS force field. This allows us to build a simulation model containing approximately 40,000 atoms consisting of 10 PVDF-HFP polymers and 1500 NMP monomers.After creating the simulation model, approximately eight steps of molecular dynamics simulation are performed by referring to the process of making the actual polymer film. In this process, NMP molecules are evaporated to produce a polymer film consisting only of PVDF-HFP polymers. Then we perform the adhesion analysis by applying forces to five polymer film models with different composition ratios in various conditions. Throughout these processes, we find the characteristic changes depending on the composition ratio. Finally, we will present the possible routes that can lead to the enhanced adhesive properties of PVDF-HFP, which is a key requirement to the development of high performance binders.

A comprehensive isogeometric analysis of frictional Hertz contact problem

The development of computational methods has advanced the solving of complex contact problems. Despite this, reproducing the analytical solution of a classical Hertz contact problem using computational methods remains challenging. Finite element method (FEM) has gained popularity, with many studies solving frictionless Hertz contact problems. However, the more general Hertz contact problem with finite friction lacks an analytical solution and is more complex. FEM was first used for this in the 1970s. Recently, isogeometric analysis (IGA) has shown enhanced efficiency than FEM. However, comprehensive studies on the frictional Hertz contact problem using IGA are lacking. The present study aims to fill this gap by examining a benchmark example and exploring contact simulation parameters using the developed in-house MATLAB® code.

DEM parameters of slope cultivated purple soil in Southwest China and interaction mechanism between very narrow tine

The establishment of discrete element method (DEM) model for simulating the behavior of viscous soil can significantly contribute to the development of agricultural machinery, particularly in hilly areas worldwide. There is limited research on the parameter calibration of the DEM for purple soil in the Southwest China and its interaction mechanism between very narrow tine. Piling up test, rotating drum test and design-expert 12.0 software were used to design Plackett–Burman test, steepest climb test and Box–Behnken test successively. Combined with soil intrinsic parameter measurement test, soil simulation parameter calibration and optimization were completed. Based on the optimized DEM simulation parameters, the average relative errors of static repose angle and dynamic repose angle were 1.934 and 2.289%, respectively. The accuracy of parameter calibration results of DEM simulation was proved. Three kinds of very narrow tines were designed and processed. The interaction model and mechanism between soil-touch parts and soil was established. The average relative errors between the DEM simulation results of the forward resistance and disturbance area of the three soil-touch parts and the soil bin test results were 7.22% and 11.24%, respectively, which further proved that the calibration results of DEM parameters of purple soil and the interaction model with the soil-touch parts in this study were reliable. The physical and interaction parameters of slope cultivated purple soil in Southwest China were determined based on static-dynamic repose angle, providing more accurate parameters for study of soil-touch parts.