Rolling Resistance Research Articles

Comparison of Radial Ply and Cross Ply Tire in Terms of Achieved Rolling Resistance and Soil Compaction in a Soil Test Channel

Many literature sources state that radial ply tires achieve lower rolling resistance values than cross ply tires. From a certain point of view, radial ply tires are gentler on the ground than cross ply tires. The effort was therefore to experimentally verify this statement for two radial ply and cross ply tires similar in shape and size. The work deals with the diagnostics of rolling resistance levels achieved by radial ply and cross ply tires on selected forest soil under the laboratory conditions of a soil test channel. BKT 210/95 R16 Agrimax RT 855 and Özka 7.50-16 8PR KNK 50 were chosen as radial ply and cross ply tires, respectively, and had approximately the same dimensions. The soil in the soil test channel can be characterized as a loamy sand with an average moisture content of 30% and an initial bulk density of 1445.07 kg·m−3. Another monitored parameter was the diagnostics of changes in soil density caused by tire movement in order to assess the degree of soil compaction. From the results of the work, it follows that there is no statistically significant difference between radial ply and cross ply tires in terms of the achieved levels of rolling resistance on the soil. The observed tires also caused intense compaction of the soil in the soil test channel, especially at higher tire pressures and higher vertical loads. The analysis of the results also shows that changes in tire pressure in both tires cause more energy loss and soil compaction than changes in the vertical load.

Solid-state friction rolling repair technology for various forms of defects through multi-layer multi-pass deposition

The current Friction Stir Welding (FSW) based solid-state defect repairing method is an ideal repair technology for high-strength aluminum alloy. However, due to the limitation of pin length and the existence of shoulder, the stirring pin cannot penetrate deep into the root of defects and is difficult to extend in the width direction, which poses great challenges for components with large defects, such as one-dimensional, two-dimensional and volume defects. To overcome these limitations, this study successfully achieved effective repair of various forms of defects using the solid-state Friction Rolling Repair (FRR) technology through multi-layer multi-bead deposition. The microstructure and mechanical properties of the repaired ZL114A cast aluminum alloy joints were investigated. The results demonstrate well-bonded repaired boundaries, significant grain refinement at the junction between the repaired area and boundary, and ultimate tensile strength exceeding 80 % of base material strength. The average grain size of the repaired area can reach a minimum of 2.82 μm. The grain refinement degree of the side joint of the surface defect repair sample is higher than that of the bottom joint, and the corner joint of the bottom surface shows the highest proportion of recrystallized grains. Fracture locations were consistently within the interior of the repair zone in tensile specimens, indicating superior properties at side joints compared to those within the interior. The research proves that FRR has the ability to repair a variety of typical defects, including one-dimensional, two-dimensional and volume defects, in the process of processing and service, which lays a foundation for the industrial application of FRR.

Predicting glass transition temperature of polymers by combining molecular dynamics simulations and machine learning techniques

Polymeric materials, valued for their cost-effectiveness and ease of processing, play a pivotal role in diverse applications. Among them, solution polymerized styrene butadiene rubber (SSBR) stands out with low rolling and wet skid resistance, ideal for eco-friendly tire. The glass transition temperature (Tg) is an important parameter in determining the performance of SSBR, which is time-consuming to test with conventional experiments. In recent years, machine learning (ML) has emerged as a useful tool in materials science. In this study, all-atom molecular dynamics (AAMD) simulation provided the foundational training data. Subsequently, ML techniques are utilized to efficiently predict SSBR’s Tg based on its content of four key structural components. To address the challenge of limited sample sizes, the innovative integration of Ordinary Kriging (OK) from geostatistics and Nearest Neighbor Interpolation (NNI) was employed to compute label values for interpolation points, which surpasses previous studies relying solely on NNI. Comparative analysis of four ML models (XGBoost, Ridge, LASSO, and SVR) reveals XGBoost’s superior performance in handling this nonlinear problem, with consistently high R2 and low RMSE scores. Through 900 repeated experiments, the model demonstrates robustness, maintaining an average R2 of approximately 0.9703. Ultimately, the novel integrated ML approach (NNI-OK-XGBoost) was proposed. Furthermore, four new combinations of structural unit content were evaluated using both ML predictions and AAMD simulations. The validation confirms the efficiency and accuracy of this method in predicting SSBR’s Tg across varying composition ratios within a specified composition space. This work presents a viable solution for accurately and rapidly predicting the Tg of polymeric materials, particularly in scenarios with limited sample sizes.

A light-fueled self-rolling unicycle with a liquid crystal elastomer rod engine

Active materials hold substantial potential for self-sustaining motion, however, the dependency on movable light or extensive area illumination in current structures often restricts the design and practical deployment of such active machines. In this study, we report a novel zero-energy-mode, self-rolling unicycle equipped with a liquid crystal elastomer rod engine, which fueled by a fixed, small-area light source. By employing an elaborate dynamic model for liquid crystal elastomer, we derive the lateral curvature of the liquid crystal elastomer rod and the driving moment necessary for the unicycle's self-rolling. The study results demonstrate that the self-rolling of the unicycle is driven by a moment induced by the shift in the center of gravity of the curved liquid crystal elastomer rod. Our numerical simulations indicate the presence of a supercritical Hopf bifurcation point delineating the transition between the self-rolling mode and the static mode within the unicycle system. Additionally, the rolling velocity of the unicycle relies on a handful of key system parameters, notably including light intensity, light penetration depth, length of the liquid crystal elastomer rod, rolling friction coefficient, total mass of the unicycle, and wheel radius of the unicycle. The experimental validation of a self-rolling unicycle with zero-energy-mode has been conducted. The self-rolling unicycle constructed in this paper has excellent characteristics of simple structure, zero-energy-mode, horizontal constant light source, and small area light source, providing valuable insights for the utilization of photoresponsive liquid crystal elastomer rods in soft robotics, medical devices, energy harvesting systems, and actuators.

Experimental Study on the Longitudinal Motion Performance of a Spherical Robot Rolling on Sandy Terrain

To provide the necessary theoretical models of sphere–soil interaction for the structural design, motion control, and simulation of spherical robots, this paper derives analytical expressions for traction force and driving torque when spherical robots slide and sink into sandy terrain, based on terramechanics and multibody dynamics. Furthermore, orthogonal experimental analysis identifies the load, joint angular acceleration, and maximum joint angular velocity of spherical robots as influencing factors, highlighting that the load significantly affects their longitudinal motion performance. Experimental results indicate that rolling friction and additional resistance on sandy terrain cannot be ignored. The corrected theoretical model effectively replicates the temporal variation of driving torque exerted by spherical robots on sandy terrain. Numerical computations and experimental analyses demonstrate that increasing the radius of the sphere shell, the load, and the slip ratio all lead to increased traction force and driving torque. However, traction force and driving torque begin to decrease once the slip ratio reaches approximately 0.5. Therefore, in the design of spherical robot structures and control laws, appropriate parameters such as load and slip ratio should be chosen based on the established sphere–soil interaction theoretical model to achieve high-quality longitudinal motion performance on sandy terrain.

A software-agnostic benchmark for DEM simulation of cohesive and non-cohesive materials

Although DEM (Discrete Element Method) was introduced >40 years ago, there are still various challenges in applying it with a certain level of confidence. To develop a realistic material model, calibration, validation, particle shape representation and scaling are well-known challenges that have been studied by various researchers over the past two decades. In addition, once a realistic DEM material model is developed and published in line with open science principles, it is unknown to what extent the calibrated values can be used across software packages. Although a benchmark between 8 open source codes was recently published, it did not cover cohesive materials, rolling friction models, realistic calibrated material behaviour, and commercial software that is widely used in industries.The aim of this study is to investigate the portability of input parameters between different codes and to identify if software independent calibration is possible. We propose a framework to assist DEM users in industry and academia to reach a software independent DEM simulation when required.To compare the results between software packages, the framework considers the following aspects: 1) identical implementation of contact models, 2) single contact modelling, 3) bulk level simulation, and 4) identical post-processing. This framework is demonstrated for two contact models (Hertz-Mindlin and Edinburgh Elasto Plastic Adhesive) with rolling friction model and two commercial software packages (EDEM and PFC) but is applicable for any other (open-source) software. Moreover, two realistic calibrated material models are included to cover a range of material characteristics, from free-flowing incompressible materials to cohesive compressible materials. This study shows that individual particle level simulations give identical results, bulk level simulations show differences for both contact models. In general, users should use parameter values from other software packages with caution, especially where critical or sensitive applications are modelled. This paper also highlights the use of novel computation techniques, such as the GPU engine, to achieve practical computation times when modelling industrial applications.

The effect of Silver addition and deformation parameters on mechanostructure, biodegradation, antimicrobial and mechanical properties of Zn-based biodegradable alloys.

Although low mechanical properties, Zinc (Zn) alloy systems with Copper (Cu) and Silver (Ag) as alloying elements have strong biocompatibility and biodegradability characteristics. This study examined the effects of rolling parameters and Ag alloying on the mechanical, biodegradable, and final structure of an alloy based on Zn. Comparing treated and untreated specimens, the addition of Ag led to a considerable improvement in both hardness and compressive strength. The produced alloys with varying amounts of Ag (between 1 and 4wt%) were cold rolled at 400-800r/min and friction coefficients between 0.3 and 0.5. The alloys' ultimate strength rose with an increase in rolling speed for Zn1Cu4Ag, and hardness and compressive strengths rose to 80HV and 470MPa, respectively. It was demonstrated that rolling force rose somewhat with Ag concentration but significantly increased with rolling speed and friction. E. Coli and S. aureus were used to assess the biodegradable alloys' antibacterial properties. For the Zn-1Cu-2Ag alloy, the inclusion of Ag resulted in a considerable (50%) rise in antibacterial activity that exceeded the effects seen in other alloy systems.

Optimization of Discrete Element Method Model to Obtain Stable and Reliable Numerical Results of Mechanical Response of Granular Materials

The discrete element method (DEM) is largely used to simulate the geotechnical behavior of granular materials. However, numerical modeling with this type of code is expensive and time consuming, especially when fine particles are involved. This leads researchers to make use of different approaches to shorten the time of calculation without verifying the stability and reliability of numerical results, even though a compromise between the time of calculation and accuracy is commonly claimed. The particle size distribution (PSD) curve of studied granular material is completely ignored or arbitrarily cut. It is unclear if the ensued numerical results are still representative of the studied granular materials. Additionally, one can see a large number of numerical models established on a basis of calibration by ignoring the physical meaning and even measured values of some model parameters. The representativeness and reliability of the obtained numerical results are questionable. All these partly contribute to reducing the public’s confidence in numerical modeling. In this study, a methodology is illustrated to obtain an optimal DEM model, which minimizes the time of calculation and ensures stable and reliable numerical results for the mechanical behavior of a waste rock. The results indicate that the PSD curve of the studied waste rock can indeed be cut by excluding a portion of fine particles, while the Young’s modulus of the waste rock particles can also be decreased to accelerate the numerical calculations. A physical explanation of why the time of calculation can be shortened by reducing the Young’s modulus of waste rock particles is provided for the first time. Overall, the PSD cut, reduction in Young’s modulus, and time step must be determined through sensitivity analyses to ensure stable and reliable results with the shortest time of calculation. In addition, it is important to minimize the number of model parameters determined through the process of calibration, especially for those having physical meanings. In this study, the only model parameter having a clear physical meaning but difficult to measure is the rolling resistance coefficient for repose angle tests on the studied waste rock. Its value has to be obtained through a process of calibration against some experimental results. The validity and predictability of the calibrated numerical model have been successfully verified against additional experimental results.

Fuzzy adaptive cruise control with model predictive control responding to dynamic traffic conditions for automated driving

Traditional Adaptive Cruise Control (ACC) systems often struggle to dynamically adapt to rapidly changing traffic conditions, resulting in suboptimal performance. Additionally, with fuel consumption emerging as a critical consideration alongside safety, there is a pressing need for more advanced solutions. This paper presents a novel approach to address these challenges by integrating Fuzzy ACC with Model Predictive Control, denoted as FACMPC. This integration aims to enhance both the longitudinal safety of AVs and fuel efficiency by considering real-time traffic conditions. The FACMPC system utilizes fuzzy logic inside the MPC, adaptively generates controller's weighting factors, allowing the system to adapt instantly to varying traffic environments and driving circumstances. The findings show that this adaptation improves the balance between driving safety, efficiency, and comfort. Additionally, three interruption scenarios, Alpha, Beta and Gama, are examined. In Alpha, the study evaluates the sensitivity of the FACMPC to disturbances by applying band-limited white noise to the lead vehicle velocity. In Beta, the AV experiences a loss of the lead vehicle velocity signal for a defined period, prompting safety considerations and assumptions. The Gama scenario includes a sensitivity analysis to account for variations and uncertainties in parameters by considering a range of ±5% around the nominal values for four key parameters: road slope, wind speed, wind direction, and rolling resistance. The findings indicate that the proposed controller's mean fuel consumption is 8.110, only a 3.21% increase over the nominal, compared to a 7.03% increase for the conventional ACC, demonstrating greater robustness against uncertainties.

Schallamach waves in the rolling inception of rubber wheel

Rubber wheel exhibits complex behaviors during high-acceleration rolling, but the behind mechanism is not yet clear. Although rigorous research has been conducted on the Schallamach waves in the sliding of rubber, it is nevertheless unknown whether they exist during the rolling contact. Through micromechanical modeling and transient analysis, we found that the adhesion energy and startup acceleration jointly determine the contact behaviors in the rolling inception, with the result that Schallamach waves can emerge when rubber wheel rolls with high-acceleration and strong-adhesion. We analyzed the speed of Schallamach waves and the associated stick-slip friction, and discussed the possible drawback of surface creasing. The findings from this investigation provide new insights into the mechanisms governing the rolling friction of rubber wheels.

Simulation and verification of discrete element parameter calibration of pulverized coal particles

ABSTRACT To enhance the simulation efficiency of the EDEM discrete element numerical simulation software for coal powder mineral particles, experimental data on the rest angle of coal powder particles were collected as the response variable. Five parameters related to coal powder particles within the Hertz-Mindlin no-slip contact model were selected for investigation. Initially, the Plackett-Burman experiment identified three parameters: collision restitution coefficient, static friction coefficient, and rolling friction coefficient, significantly influencing the resting angle. Subsequently, the steepest ascent experiment determined the significant parameter ranges as follows: the collision restitution coefficient ranged from 0.20 to 0.40, the particle-particle static friction coefficient ranged from 0.30 to 0.50, and the particle-particle dynamic friction coefficient ranged from 0.06 to 0.10. Finally, the second-order regression model for the angle of repose and the saliency parameters was developed and optimized using the Box-Behnken experimental design. The following parameter combination was obtained: the collision recovery coefficient was 0.30, the particle-particle static friction coefficient was 0.49, and the particle-particle dynamic friction coefficient was 0.09. This study aimed to compare the angle of repose between the simulation experiment and the actual experiment. The relative error was only 1.02%, indicating that the simulation experiment achieved the optimal parameter combination.

How Do We Calibrate a Battery Electric Vehicle Model Based on Controller Area Network Bus Data?

Transforming an up-to-date vehicle into a measurement system is a rewarding task due to the large number of different sensors in the onboard control and diagnostic systems. These procedures are not performed by a single control unit; it is necessary to share the signal values over a communication network, to which an external device can be connected to record the real traffic. The paper aims to use these recorded data for 1 DOF longitudinal vehicle and powertrain model validation. For repeatability, three city routes are selected: plain road, smaller road grade, and higher road grade in both directions. Therefore, the drivetrain system is tested in a high load range, even with long-term recuperation. The altitude changes are recorded with a DGPS system. By the recorded measurements, the vehicle and the drivetrain model can be calibrated, such as the air drag parameters, the rolling resistances, and the efficiencies of the drivetrain. The validation criteria are defined for speed tracking, and the relative tolerance of the cumulated energy should be below 10%. At the end of the day, a developed model is ready for energetic analysis or control strategy design. The energy balance of the applied cycles is also presented to prove that.

Determination of melon seed physical parameters and calibration of discrete element simulation parameters.

To improve the accuracy of the Hami melon discrete element model, the parameters of the Hami melon seed discrete element model were calibrated by combining practical experiments and simulation tests. The basic physical parameters of Hami melon seeds were obtained through physical experiments, including triaxial size, 100-grain mass, moisture content, density, Poisson's ratio, Young's modulus, shear modulus, angle of repose, suspension speed and various contact parameters. Taking the repose angle of seed simulation as an index, the parameters of each simulation model were significantly screened by the Plackett-Burman test. The results showed that the recovery coefficient, static friction coefficient and rolling friction coefficient of Hami melon seeds had significant effects on repose angle. Based on the steepest climbing test and quadratic regression orthogonal rotation combination test, it was determined that the significant order of the influence of various contact parameters on the angle of repose was static friction coefficient, collision recovery coefficient, and rolling friction coefficient. The optimal parameter combination was obtained through the mathematical regression model between the angle of repose and various contact parameters, namely, the collision recovery coefficient of Hami melon seeds was 0.518, the static friction coefficient of Hami melon seeds was 0.585 and the rolling friction coefficient of Hami melon seeds was 0.337. Under this condition, three static seed-dropping experiments and dynamic rolling accumulation experiments were carried out. The average simulated angle of repose was 31.93°, and the relative error with the actual value was only 1.71%. The average simulated rolling accumulation angle was 51.98°, and the relative error with the actual value was only 1.92%.

Аналіз впливу на прохідність автобронетанкової техніки конструктивних факторів та методика її збільшення шляхом автоматичного регулювання тиску повітря в шинах коліс

The purpose of the study is to analyze and determine the influence of various factors on the patency of armored vehicles (AMT) operated by the National Guard of Ukraine. Determination of the change in patency during the movement of AMT in different road and climatic conditions. Analysis of static and dynamic loads, which are characteristic of AMT movement over rough terrain, and their impact on the efficiency of the vehicle. The theoretical component of the study was carried out using mathematical modeling of the work process of regulating the air pressure in tires of AMT wheels, using the example of changes in the characteristics of adhesion coefficients with the supporting surface and rolling resistance depending on the change in pressure and load on the tires of the wheels when the AMT is moving off-road. As a result of mathematical modeling, the dependences of air pressure in tires of AMT wheels were obtained, depending on the coefficient of rolling resistance and the load on each of the wheels. Which, in turn, makes it possible to move to a sufficiently complete mathematical modeling of the movement of AMT on off-road, taking into account the reference cross-country ability. In the process of theoretical research, the structural parameters of the impact on the patency of AMT were analyzed quite completely, and a generalized comparative indicator of the patency parameters of vehicles was proposed. When analyzing it, it was found that the AMT tire and, specifically, the change in air pressure in it, have a significant impact on the bearing capacity. The authors propose to use the following evaluation criteria as criteria for assessing the efficiency of the passability when driving on deformable surfaces: a generalized comparative indicator of the parameters of the passability of vehicles. As a result of consideration of which, a significant influence on the patency parameters of the tires and directly the air pressure in them was established. Regulation and change of the air pressure in the tires of the wheels depending on the change in the coefficient of rolling resistance as well as the change in the load on each wheel, which are the ratio of the work that is spent on the traction force when overcoming different degrees of heaviness of the resistance of the supporting surfaces with the effect of deformation. And the load that falls on each of the AMT wheels allowed us to draw conclusions about the improvement of the regular tire pressure regulation system (RPRS) of the wheels.

Вплив причіпних ланок на керованість тракторних самохідних шасі

An analysis of methods for calculating the distribution of normal reactions of the road between the axles of the tractor unit was carried out. It is shown that they are based on the misconception that traction forces and rolling resistance forces are applied in the spots of contact of the wheels with the road. The research shows that installing a towing link on a tractor self-propelled chassis through the rear suspension system at a level below the axis of the rear wheels (the diameter of which is larger in relation to the diameter of the front wheels) allows reducing the additional unloading of the front wheels. A more correct scheme of the tractor unit with the application of the traction force and the rolling resistance force on the wheel axles is calculated, which determines the increase in the total normal reaction on the front wheels of the tractor self-propelled chassis when working with the towing link. It is shown that an increase in the difference in the dynamic radii of the front and rear wheels, a decrease in the vertical coordinate of the center of mass of the tractor unit leads to an increase in the normal reaction of the road on the front wheels. Since the controllability of wheeled machines increases with the growth of the normal reaction on the front wheels, the presence of towing links with the attachment point located below the axis of the rear driving wheel increases the controllability of the tractor unit based on the self-propelled chassis. The problem of determining the total normal reaction of the road on the front wheels of a tractor self-propelled chassis with a trailing link in the case of application of the traction force and the force of movement resistance on the wheel axles has been solved. To increase the accuracy of finding the total normal reaction of the road on the front wheels of the tractor self-propelled chassis, which will allow to clarify the assessment of the controllability of the latter when moving with a towed link. Increasing the difference in the dynamic radii of the wheels and reducing the base of the tractor self-propelled chassis allows you to increase the value of the total normal reaction of the road on the wheels in relation to the horizontal reaction in the hinge of the axle of the trailer link. It was determined that the operation of the tractor self-propelled chassis with trailing links is characterized by a higher efficiency factor of its chassis compared to a universal tractor of class 0.6 and higher efforts under the condition that its front platform is loaded.

Influence of Rolling Resistance and Particle Size Distribution in the Simulation of Sand Infiltration into the Static Gravel Bed

Fine sediment infiltration and subsequent clogging in a gravel bed affect several fluvial, ecological, and biological processes, resulting in the degradation of the river ecosystem. Despite many experimental and a few numerical studies, the process is yet to be entirely understood. We employed a pure Lagrangian framework, called the Discrete Element Method (DEM), to numerically investigate the infiltration process. Special attention is given to tackling the issue of non-spherical and irregular particle shapes and particle size distributions (PSDs) in numerical simulations. Due to computational limitations, these aspects were either not considered or simplified in previous numerical studies. We implicitly included non-spherical and irregular shape effects through rolling resistance models, which do not cause excessive computational overhead. Our study shows that rolling resistance models greatly influence packing and fine sediment infiltration. However, they may also lead to unphysical particle behavior; thus, they should be carefully used in numerical simulations. Oversimplified PSDs do not mirror natural systems, and full PSDs pose computational challenges. Sufficient grain classes are needed to mimic the non-homogeneity and poly-dispersity found in natural fluvial sediments. The infiltrating characteristics of sand concerning PSD and shape effects are linked to size ratio D15,Gravel/D85,Sand, assuring physical and realistic modeling of the infiltration process.

High-resolution harvester data for estimating rolling resistance and forest trafficability

AbstractInformation on terrain conditions is a prerequisite for planning environmentally and economically sustainable forest harvesting operations that avoid negative impact on soils. Current soil data are coarse, and collecting such data with traditional methods is expensive. Forest harvesters can be harnessed to estimate the rolling resistance coefficient ($$\mu _{RR}$$ μ RR ), which is a proxy for forest trafficability. Using spatio-temporal data on engine power used, speed travelled, and machine inclination, $$\mu _{RR}$$ μ RR can be computed for harvest areas. This study describes an extensive, high-resolution data on $$\mu _{RR}$$ μ RR collected in a boreal forest landscape in Southern Finland during the non-frost period of 2021, covering roughly 50 km of harvester routes. We report improvements in removing some of the previous restrictions on calculating $$\mu _{RR}$$ μ RR on steeper slopes, enabling the calculation within a $$-10^{\circ }$$ - 10 ∘ to $$+10^{\circ }$$ + 10 ∘ slope range with a speed range of 0.6–1.2 ms$$^{-1}$$ - 1 . We characterise the variation in $$\mu _{RR}$$ μ RR both between and within 11 test sites harvested during the April-August period. The site mean $$\mu _{RR}$$ μ RR varies from $$\sim$$ ∼ 0.14 to 0.19 and shows significant differences between the sites. Using simulations of the hydrological state of the soil and open spatial data on forest and topography, we identify features that best explain the extremes of $$\mu _{RR}$$ μ RR within the sites. Several wetness-related indices, such as the depth-to-water index with varying thresholds, explain the $$\mu _{RR}$$ μ RR extremes, while biomass-related stand attributes indirectly explain these through their linkage to site and soil characteristics. Obtaining $$\mu _{RR}$$ μ RR from actual operational data extends the capabilities of large-scale harvester-based data collection and paves the way for building data-driven models for trafficability prediction.

Establishment of a novel DNNSS-MOVES prediction model for carbon emissions of trucks driving on dirt roads

This study proposes a novel prediction model to accurately quantify the carbon emissions of the trucks driving on dirt roads based on the deep learning neural network for small sample (DNNSS) and the motor vehicle emission simulator (MOVES). The application range of the MOVES model was extended to the transportation of asphalt mixtures on the temporary road. The model correction method was also established based on the rolling resistance coefficient (CR) and the correction coefficient (μ). By comparing the measured fuel consumption of the truck with the carbon emissions calculated by the MOVES model, the values of CR × μ can be back-calculated. DNNSS was constructed for estimating the CR × μ. The Adaptive Moment Estimation (Adam) algorithm was used to dynamically adjust the learning rate and accelerate the convergence of the network; the Dropout function was used to alleviate overfitting; and the Rectified Linear Unit (ReLU) function was used as the activation function to solve the gradient vanishing problem. The test results showed that the vehicle speed and load greatly influence the CR × μ. The DNNSS algorithm was better at predicting the CR × μ. The proposed DNNSS-MOVES model was more accurate than the conventional methods.

Laser Ablating Biomimetic Periodic Array Fish Scale Surface for Drag Reduction.

Reducing resistance to surface friction is challenging in the field of engineering. Natural biological systems have evolved unique functional surfaces or special physiological functions to adapt to their complex environments over centuries. Among these biological wonders, fish, one of the oldest in the vertebrate group, have garnered attention due to their exceptional fluid dynamics capabilities. Fish skin has inspired innovation in reducing surface friction due to its unique structures and material properties. Herein, drawing inspiration from the unique properties of fish scales, a periodic array of fish scales was fabricated by laser ablation on a polished aluminum template. The morphology of the biomimetic fish scale surface was characterized using scanning electron microscopy and a white-light interfering profilometer. Drag reduction performance was measured in a closed circulating water tunnel. The maximum drag reduction was 10.26% at a Reynolds number of 39,532, and the drag reduction performance gradually decreased with an increase in the distance between fish scales. The mechanism of the biomimetic drag reduction surface was analyzed using computational fluid dynamics. Streamwise vortices were generated at the valley of the biomimetic fish scale, replacing sliding friction with rolling friction. These results are expected to provide a foundation for in-depth analysis of the hydrodynamic performance of fish and serve as new inspiration for drag reduction and antifouling.

Discrete Element Model of Oil Peony Seeds and the Calibration of Its Parameters

Oil peony is an important oil crop that is primarily sown by using artificial methods at present. Its seeder encounters the problems of low efficiency of seeding that significantly limits the highly efficient mechanized production of high-quality peony oil. In this study, Fengdan white oil peony seeds were used as the research object and repose angle as the response value to establish a discrete element model (DEM) and parameter calibration. The range of parameters of oil peony seeds was first obtained through an experiment, and their repose angle was obtained by an inclinometer. A three-dimensional DEM of oil peony seeds was then established. The Plackett–Burman (PB) test was utilized to screen the parameters that had a significant influence on the repose angle, and the steepest ascent (SA) test was applied to determine their optimum range of testing. Following this, based on Box–Behnken (BBD) test results, a second-order regression model between the important parameters and the repose angle was constructed. Finally, the absolute minimum difference between simulated and measured repose angles was utilized as the objective of optimization to obtain the following optimum combination of parameters: The values of the seed–steel collision recovery coefficient (CRC), seed–seed static friction coefficient (SFC), seed–steel SFC, and seed–seed rolling friction coefficient (RFC) were 0.704, 0.324, 0.335, and 0.045, respectively. This optimal combination of parameters was confirmed through simulations, and the error between simulated and measured repose angles was only 0.67%, indicating that the calibrated DEM of oil peony seeds was reliable.