Multi-body Dynamics Simulation Research Articles

Research on intelligent formation operation performance of straddle-type rapid transit vehicles in heterogeneous operating environment

This paper presents an intelligent formation operation mode (IFOM) based on straddle-type rapid transit vehicles. Taking the straddle-type rapid transit vehicles operating in IFOM as the object, the operation mode of the vehicle is defined in the control system architecture of the straddle-type rapid transit system. In addition, considering the heterogeneous operating environ-ment of formation vehicles, an evaluation index system for formation vehicles is proposed. Then, according to the vehicle longitudinal dynamics model and the artificial potential field formation algorithm, we build the formation vehicle operation controller. After that, referring to the vehicle dynamics model, a multi rigid body dynamics simulation model of formation vehicles in a heterogeneous operating environment is established. Finally, the operating performance of formation vehicles in heterogeneous operating environment is analyzed. The analysis results show that the operation performance of the formation vehicle meets the requirements of the evaluation index system, which proves the feasibility of the formation operation of straddle-type rapid transit vehicles operating in IFOM.

Nonlinear Torsional Stiffness Analysis of Harmonic Drives Using Flexible Multibody Dynamics Simulation

Predicting the nonlinear torsional stiffness of harmonic drives is important not only for system control but also for the further development of the drive. However, it is difficult to predict the torsional stiffness because of the elastic deformation of the flexspline and the many contacts involved. Furthermore, nonlinear dynamic contact simulations between the elastic components of the harmonic drive are disadvantaged by high computational burden and convergence problems. To address these challenges, we establish a flexible multibody modeling process using augmented formulations of a floating reference frame to simulate the operation of the harmonic drive. The elastic deformation of the flexspline and the dynamic contacts between the main components are considered in the reproduction of the contact mechanism of the drive. Coordinate reduction techniques are used to properly replicate an elastic shaft, enabling the effective simulation of flexible multibody dynamics, including nonlinear elastic tooth contact analysis. The performance of the proposed modeling process is evaluated using catalog and experimental data on two types of standard harmonic drives (SHG-25-100-UH and SHG-40-100-UH). The hysteresis curve is predicted through flexible multibody dynamics simulation and the accuracy of parameters of torsional stiffness is approximately 91.7% on average. The proposed modeling method can be improved to predict other measures of performance and it remains a potential research topic.

Multi-body dynamics analysis for the wear of front-rod bearing during the switching operation of railroad switches (Effect of adjustment condition)

Since the wear of front-rod bearings of railroad switches induce the switch failure, wear evaluation is indispensable. On the other hand, the various parts of railroad switches are adjusted so as to avoid derailment. For example, the attachment position of the adjustment nut of switch adjuster rod could enlarge the contact force between tongue rail and stock rail. The extension of front rod is also used to eliminate the gap between the toe of tongue rail and stock rail. In this paper, the bearing wear during the switching operation is estimated by multi-body dynamics simulation. The effects of the attachment position of adjustment nut and the extension of front rod are also evaluated. When the switch moves rightward, the driving force of electric point machine is transmitted to switch rod through switch adjuster rod. Then, the force is transmitted to right tongue rail through right switch rod bracket which connects switch rod and right tongue rail. Although the attachment position of adjustment nut controls the contact force between tongue rail and stock rail, that does not change the path of force transmission and the force acting on the bearing. Therefore, the attachment position does not affect the bearing wear. On the other hand, the extension of front rod changes the path of force transmission. The most of driving force of electric point machine is transmitted to the left switch rod bracket, front rod and right tongue rail in order. Therefore, the increase in the force acting on the bearing increases its wear. In the case of 6 mm extension of front rod, the estimated amount of wear is 3.44 μm, which is 3 times larger than the case of no extension.

Co-simulation of multibody dynamics and discrete element method for hydraulic excavators

Multibody dynamics (MBD) simulation is a useful tool to analyse the kinematic function of multibody systems, while discrete element method (DEM) is widely used to simulate particle flows in various types of equipment at the individual particle scale and as an overall process. A combination of MBD and DEM methods, such as functional mock-up interface (FMI) based co-simulation, could capture both updated material behaviour and equipment behaviour and predict the equipment performance. In this work, MBD and FMI co-simulations are based on the commercial software Dymola. MBD models have been developed for hydraulic excavator system. GPU-based DEM models have also been developed for excavator digging cycles. Finally, MBD-DEM FMI co-simulation results show that solid materials can significantly affect the movement of excavators. • MBD model for a simplified excavator is developed based on Dymola. • MBD dig cycles can be flexibly adjusted. • GPU-based DEM model is developed with dynamic computational domain. • MBD-DEM FMI co-simulation models have been developed. • Co-simulation results show the mutual effect of solid materials and excavator.

A Machine-Learning-based Surrogate Modeling Methodology for Submodel Integration in the Holistic Railway Digital Twin Platform

A holistic railway infrastructure digital twin (DT) platform is sophisticated and consists of a series of submodels (e.g., turnouts, tracks, vehicles, etc.) that are built through various methodologies and software. However, integrating these submodels into the DT platform is tremendously challenging due to considerable computational complexity, software and interface restrictions. To this end, we designed a machine learning (ML) based surrogate modeling methodology for the submodel integration in the holistic railway infrastructure DT platform and illustrated the methodology through a case study. In this case study, an ML-based surrogate model for multibody simulation of railway vehicle-track dynamics is created, which can replace the railway vehicle-track simulation executed with the Multibody Dynamics (MBD) Simulation commercial software SimPACK. The well-built ML model can accurately and quickly predict the vehicle-track system's dynamic responses to different track irregularities. Besides, the integration process of the ML-based surrogate model into the DT platform through a standardized open-source Functional Mock-up Interface (FMI) is also proposed. The developed surrogate modeling methodology shows great promise owing to its high fidelity, which is verified by the measurement data collected from the Austrian national railway track system. The main contribution of our work lies in the well-built ML-based surrogate modeling methodology for reducing the computation complexity and time of different submodels, which facilitates the unification and integration of different submodels. Furthermore, this approach can also be applied to other submodels and help to build the holistic railway DT platform collaboratively.

A Railgun Secondary Propulsion System for High-Speed Hyperloop Transportation

Secondary propulsion methods for high-speed hyperloop transportation are sparsely researched. Secondary propulsion methods are essential to quickly, efficiently, and safely get a hyperloop pod up to its target speed from a stationary state. In this article, we propose and analyze the feasibility of a form of electromagnetic (EM) secondary hyperloop propulsion, called a railgun, commonly used in modern-day artillery technology for high-speed ammunition launching. We assess the feasibility of two different materials and three different geometries for a railgun armature to propel a hyperloop pod. Inverse design of multiphysics simulation of multibody dynamics, magnetic fields, and electric currents is used for material selection of the armature that minimizes rail current energy requirements and the armature geometry that maximizes structural integrity.

A unified framework for corotational flexible multibody system dynamics formulations.

Corotational formulations play an important role for flexible multibody dynamics systems, because they reflect the nature of many technical systems undergoing arbitrarily large rigid body motions but small deformations within each body. This paper defines flexible multibody dynamics and corotational formulations in this context. Furthermore, the «ingredients» and workflow of a flexible multibody dynamics simulation are briefly addressed for the reader less familiar with the topic. This part also points to major review papers and textbooks in the field, and embeds the unified formulations in the literature. The paper's main part presents state-of-the-art corotational flexible multibody dynamics formulations in a systematic and unified way. In this formulation part, the standard integral-based floating frame of reference formulation with modal reduction and with the conventionally employed lumped mass approximation is presented, and its drawbacks highlighted. Then, the so-called nodal-based, i.e., space-wise discretized, equations of motion are presented for several up-to-date nodal-displacement-based formulations within a unified framework. This approach clearly shows the equivalence of the presented formulations, and highlights the fact that the formulations differ only in the choice of degrees of freedom. Moreover, this contribution also intends to reduce the information and complexity within the scientific literature, since this unified framework allows the derivation of these formulations with significantly less effort..

Anomaly Detection Method in Railway Using Signal Processing and Deep Learning

In this paper, anomaly detection of wheel flats based on signal processing and deep learning techniques is analyzed. Wheel flats mostly affect running stability and ride comfort. Currently, domestic railway companies visually inspect wheel flats one by one with their eyes after railway vehicles enter the railway depots for maintenance. Therefore, CBM (Condition-Based Maintenance) is required for wheel flats resolution. Anomaly detection for wheel flat signals of railway vehicles using Order analysis and STFT (Short Time Fourier Transform) is studied in this paper. In the case of railway vehicles, it is not easy to obtain actual failure data through running vehicles in a university laboratory due to safety and cost issues. Therefore, vibration-induced acceleration was obtained using a multibody dynamics simulation software, SIMPACK. This method is also proved in the other paper by rig tests. In addition, since the noise signal was not included in the simulated vibration, the noise signal obtained from the Seoul Metro Subway Line 7 vehicle was overlapped with the simulated one. Finally, to improve the performance of both detection rate and real-time of characteristics based on existing LeNet-5 architectures, spectrogram images transformed from time domain data were proceeded with the LeNet deep learning model modified with the pooling method and activation function. As a result, it is validated that the method using the spectrogram with a deep learning approach yields higher accuracy than the time domain data.

FPGA acceleration of planar multibody dynamics simulations in the Hamiltonian–based divide–and–conquer framework

Multibody system simulations are increasingly complex for various reasons, including structural complexity, the number of bodies and joints, and many phenomena modeled using specialized formulations. In this paper, an effort is pursued toward efficiently implementing the Hamiltonian-based divide-and-conquer algorithm (HDCA), a highly-parallel algorithm for multi-rigid-body dynamics simulations modeled in terms of canonical coordinates. The algorithm is implemented and executed on a system–on–chip platform which integrates a general-purpose CPU and FPGA. The details of the LDUP factorization, which is used in the HDCA approach and accounts for significant computational load, are presented. Simple planar multibody systems with open- and closed-loop topologies are analyzed to show the correctness of the implementation. Hardware implementation details are provided, especially in the context of inherent parallelism in the HDCA algorithm and linear algebra procedures employed for calculations. The computational performance of the implementation is investigated. The final results show that the FPGA–based multibody system simulations may be executed significantly faster than the analogous calculations performed on a general–purpose CPU. This conclusion is a good premise for various model-based applications, including real-time multibody simulation and control.

A comparison of main bearings load of two-cylinder “V” and boxer motorcycle engines

The paper deals with determining the load of the crankshaft main bearings in two-cylinder motorcycle engines. Two cylinder arrangements, used in two-cylinder motorcycle engines, are considered - the boxer-engine and V-engine. The aim of the research is to determine the influence of cylinder arrangement on the magnitude and circumferential distribution of the bearing load of the engines considered. For this purpose, models of a two-cylinder boxer engine and a corresponding V-engine crankshaft drives were developed using multibody dynamics simulation software. Previously, by using a one-dimensional gas analysis software the engine cycles were simulated in order to determine the cylinder pressure required to simulate piston dynamics. As a result of the dynamics simulations, bearing load diagrams of the boxer- and V-engine were obtained, which were then compared and analyzed.

Prediction of rail-wheel contact parameters for a metro coach using machine learning

Dynamics of metro coach is complex with frequent acceleration, braking, sharp turns and gradients. Due to sharp turns and twists in track, metro coaches are more prone to the derailment, frictional energy loss and wear. Since contact parameters are difficult to obtain experimentally and are time consuming to determine even computationally through multibody dynamics simulations, in this work, artificial neural network (ANN) and recurrent neural network (RNN) models are used to predict rail-wheel contact parameters. The determined parameters include contact forces, derailment ratio, frictional power, contact location and contact area. These models can be used for reducing derailment tendency, wheel wear and energy consumption. To tackle local extreme values, four meta-heuristic techniques namely Improved Real-coded Genetic Algorithm (IRGA), Success History based Adaptive Differential Evolution (SHADE), Bonobo Optimizer (BO) and Grey Wolf Optimizer (GWO) algorithms are used to optimize the ANN and RNN models. During training, inputs and outputs to the machine learning techniques are generated from a multibody dynamics model built in commercial software Simpack. The multibody dynamics model used is validated using instrumented field trials. Mean absolute percentage error (MAPE) is used for evaluating the performance of the machine learning techniques. Results demonstrate that SHADE is the best optimizer among the four meta-heuristic techniques considered. MAPE in tests, for SHADE-ANN and SHADE-RNN are found to be less than 7%. The developed machine learning models, particularly SHADE-RNN, can be used for onboard monitoring and can help the pilots in running the trains safely and efficiently.

Intelligent prediction for digging load of hydraulic excavators based on RBF neural network

Traditional modeling methods for digging load of excavators are often computationally expensive and require prior knowledge of soil parameters, which severely limits their engineering applications. According to the digging load characteristics in typical digging tasks, this paper presents an intelligent prediction method for digging load based on radial basis function (RBF) neural networks. The recursive least-squares (RLS) algorithm is used for weights updating. Back propagation neural network (BPNN), coupled discrete element method (DEM) and multi-body dynamics (MBD) simulation, and analytical model are applied for comparative studies. The simulation results illustrate that the RBF neural network model outperforms other comparative models in terms of prediction accuracy and computational cost. The hardware-in-loop (HIL) experiments are conducted to validate the proposed approach. Experimental results demonstrate that the error in the dynamic behavior of the excavator under the predicted digging load is less than 7%. This paper lays the foundation for digging load prediction in intelligent excavators.

Car and train platoon simulations

Detailed simulations of car and train platoons are critical steps towards successful implementations of the platooning technologies. This paper developed a simulation method that can be used for both car and train platoon simulations. The method includes three main parts: (1) a scalable adaptive longitudinal space controller, (2) 2D multibody dynamics simulations that consider wheel-rail contact (Polach model), tyre-road contact (Magic Formula), suspensions and in-train forces, and (3) a scalable parallel computing method that processes the dynamics simulation of each individual vehicle (one car or one carriage) by using one independent computer core. Two case studies were conducted to simulate a 6-car platoon and a 3-train platoon on real-world road and track. The maximum space errors for the car platoon and the train platoon results were about 0.32 and 0.23 m, respectively. When the platoons were running at a steady speed, space errors were well controlled within ±0.05 m for both car and train platoons. Example dynamics results were presented including wheel-rail contact forces, tyre-road contact forces, and carbody vibrations. This information can be used to conduct a wide range of related studies such as passenger ride comfort and system damage assessments.

Research on structural parameters and kinematic properties of a drill-in granary grain condition detector

Abstract. In order to realize the real-time monitoring of the grain condition, grain condition information should be collected during storage operations. A drill-in granary grain condition detector which can drill into a grain pile in a granary is proposed. The kinematic models of four Archimedes screw mechanisms were established, and the motion characteristics of grain particles in spiral grooves were described. Several groups of single variable simulation experiments are designed to discuss the important factors affecting the motion performance of the detector. Based on a discrete element method with multi-body dynamics (DEM-MBD) simulation calculation, the force and velocity change images of grain particles were obtained to verify the feasibility of the scheme. The steering function of the detector is verified by simulation, and the relationship between the steering radius and the screw rotation speed difference is analyzed. The results show that the drill-in granary grain condition detector can move forward and turn when it is immersed in the grain pile. It has the characteristics of excellent flexibility and a high degree of freedom. It compensates for the current situation in which robots cannot go deep inside the grain pile and complete the steering.

Optimization of Bucket Size of Garlic Metering Device Using Multibody Dynamics Simulation

Optimization of Bucket Size of Garlic Metering Device Using Multibody Dynamics Simulation

Assessment of contact forces and stresses, torque ripple and efficiency of a cycloidal gear drive and its involute kinematical equivalent

In this paper, we assess and compare a conventional cycloidal drive and its involute-tooth kinematical equivalent via finite element (FE) and dynamical multi-body analysis. The analysis of the stiffer conventional cycloidal configuration reveals multiple points of contacts, although some of these have little contribution to the torque transmission. Significant non-torque loads are self-induced, with contact forces constantly changing in magnitude and orientation, consistently with the contact characteristics of the cycloid. In the involute alternative, the stress concentration was more localized to two or three points of contact, according to the involute contact ratio, leading to increased stresses. The contact forces remained constant relative to the tangential direction, as per the constant involute pressure angle, contributing to desirable torque loads. The torque ripple was found to have two components, one at the tooth engagement frequency ( f z ) and one at the high-speed shaft rotation frequency ( f n ), the former being more pronounced in the conventional cycloidal case, while the latter being larger for the cycloidal drive with involute teeth. Moreover, both analytical calculations and the multi-body dynamics simulations suggest that the involute-tooth design is more efficient compared to the conventional cycloidal-tooth design.

Mass design method considering force control errors for two-redundant cable-suspended parallel robots

• Three design indexes were proposed to analyze the wrench-feasibility for cable-suspended parallel robots from a new perspective. • Comprehensive methodology is devised to design the mass (gravity) of the end-effector. • The methodology enables the selection of the force-controlled cable set from the possible combinations. For redundant cable-suspended parallel robots, gravity imposes a predictable minimum or maximum limit on the tension in all cables. The hybrid joint-space control strategy is adopted in this study. In this case, the chosen redundant cables are force-controlled, whereas the remaining ones are length-controlled in the joint space. This strategy aims at maintaining all cable tensions within the pre-defined force boundaries under the influence of force control errors. This is by designing the end-effector mass while simultaneously ensuring that the cable force control errors can be realized by the controllers in the physical world. Three design indexes are proposed for the basic mathematical framework and a comprehensive methodology is devised to design the end-effector mass (gravity) of cable-suspended parallel robots with two degrees of redundancy. A trajectory planning, based on the French CoGiRo layout, is adapted to validate the analysis and design process by using multibody dynamics simulations. Further, we found that the choice of the optimal cable combination is essential for performing force control, and control failures may occur when inappropriate combinations are selected.

Study of Wall Climbing Robot through the Simulation of Multi-Body Dynamics

Study of Wall Climbing Robot through the Simulation of Multi-Body Dynamics

Multi-body dynamics modeling and driving performance evaluation of oil recovery vehicle

In this study, the design and driving performance evaluation of a driving system for driving on deformable terrain was performed using terramechanics theory and multi-body dynamics simulation. For the design of the driving system, the mechanical interaction of track-terrain was analyzed using a Bekker-based model. Based on the analyzed results, the design of a track suitable for the deformable terrain to be driven and selection of a power source (engine, transmission, etc.) were carried out. A multi-body simulation model of the tracked vehicle reflecting the designed track and the selected power source was developed, and a ground model reflecting the mechanical property of terrain was also developed to analyze the mechanical interaction of the track-terrain through simulation. In addition, each link constituting the track was modeled as a 6 DOF spring/damper system to consider the track's tension force and load distribution under the track, and through this, different ground pressure and soil thrust were applied according to the motion state of each link. Finally, driving performance analyses were performed using the developed tracked vehicle, and as a result, it was confirmed that the driving requirements of the tracked vehicle were satisfied.

Computational study and validation of a novel passive hand tremor attenuator

Tremors are a prevalent movement disorder due to a nervous system condition that leads to involuntary muscle movements observed in patients. This paper converts the tremorous anatomical human arm model to a single degree of freedom (SDOF) forced vibration problem. The mathematical modelling with Euler–Lagrange’s equation is performed for the SDOF human arm model with two different potential vibration absorbers. A computational study is conducted on MATLAB Simulink by MathWorks Inc. (Natick, MA) to compare two absorbers, and the results are verified on the multibody dynamics simulation solution software, MSC Adams by Hexagon AB. It is concluded that the T beam-shaped vibration absorber represented a higher amplitude reduction, up to 80%, compared to the inertial mass absorber, which had an amplitude reduction of 65% over the range of frequencies. Experiments conducted with the T beam absorber prototype also support the computational findings. Future research focuses on designing an ergonomic wearable device with a proposed T-beam absorber that can passively attenuate the tremor at various frequencies.