Rigid Body Model Research Articles

Data-Driven Modeling and Regulation of Aircraft Brakes Degradation via Antiskid Controllers

In ground vehicles, braking actuator degradation and tire consumption do not represent a significant maintenance cost as the lifespan of both components, at least in common situations, is rather long. In the aeronautical context, and for aircraft in particular, instead, braking actuator degradation and tire consumption significantly contribute to an aircraft maintenance cost due to the frequency of their replacement. This is mainly due to the fact that aircraft braking maneuvers last significantly longer than those in the automotive context. So that the antilock braking system is always active during the braking maneuver, making its impact on the consumption of the two components significant. This work proposes an innovative data-driven model of brake and tire degradation, showing how they are related to the antiskid controller parameters. The analysis is carried out in a MATLAB/Simulink environment on a single wheel rigid body model, validated experimentally, which includes all the nonlinear effects peculiar of the aeronautic context. The results show that by using an appropriate antiskid control approach, it is possible to directly regulate the consumption of these components while at the same time guaranteeing the required braking performance.

Calibration of Holzapfel-Gasser-Ogden collateral ligament properties in a hybrid post-arthroplasty knee joint model for laxity testing

Knee collateral ligaments play a vital role in providing frontal-plane stability in post-total knee arthroplasty (TKA) knees. Finite element models can utilize computationally efficient one-dimensional springs or more physiologically accurate three-dimensional continuum elements like the Holzapfel-Gasser-Ogden (HGO) formulation. However, there is limited literature defining subject-specific mechanical properties, particularly for the HGO model. In this study, we propose a co-simulation framework to obtain subject-specific material parameters for an HGO-based finite element ligament model integrated into a rigid-body model of the post-TKA knee. Our approach achieves comparable accuracy to spring formulations while significantly reducing coefficient calibration time and demonstrating improved correlation with reference knee kinematics and ligament strains throughout the tested loading range.

Identification of Aeroelastic Quasi-Steady Effects Through Flex Factor

Rigid body modeling for estimation of aerodynamic derivatives from the flight responses of a flexible aircraft does not yield the true stability and control parameters of the aircraft, as the estimated derivatives absorb the aeroelastic effects present in the data. The analytical expressions for computing the rigid body derivatives from the flight-estimated values require knowledge of aircraft modal mass and generalized elastic deflections which is not always available. This paper considers a simplified approach based on quasi-steady representation of aeroelastic effects to identify the rigid body parameters from the flexible aircraft responses. Results show that, by combining data at several flight conditions, system identification method can be applied to separate the rigid body derivatives and the dynamic pressure dependent quasi-steady effects caused by structural deformation.

An integrated path-tracking and control allocation method for autonomous racing electric vehicles

In recent years, path-tracking controllers for autonomous passenger vehicles and Control Allocation (CA) methods for handling and stability control have both received extensive discussion in the literature. However, the integration of the path-tracking control with CA methods for autonomous racing vehicles has not attracted much attention. In this study, we design an integrated path-tracking and CA method for a prototype autonomous racing electric vehicle with a particular focus on the maximising the turning speed in tight cornering. The proposed control strategy has a hierarchical structure to improve the computational efficiency: the high-level path-tracking Model Predictive Control (MPC) based on a rigid body model is designed to determine the virtual control forces according to the desired path and desired maximum velocity profile, while the low-level CA method uses a Quadratically Constrained Quadratic Programming (QCQP) formulation to distribute the individual control actuator according to the desired virtual control values. The proposed controller is validated in a high-fidelity simulation vehicle model with the computational time of the optimisation controller presented to demonstrate the real-time control performance.

Neural Partial Differentiation for Parameter Estimation of Flexible Aircraft Dynamics

Although the parameter estimation methodologies had been successfully applied for the rigid aircraft dynamics, the aircraft with high degree of flexibility poses challenges to determine the appropriate aeroelastic models for inclusion in the parameter estimation algorithms. Application of the neural networks for the aerodynamic modeling and parameter estimation of an aeroelastic aircraft (or flexible aircraft) is addressed in this paper. A neural network with the scaled conjugate gradient learning algorithm is used for modeling lift and pitching moment coefficients. The partial differentiation of the neural network output is carried out for the estimation of equivalent parameters of an aeroelastic aircraft. It is demonstrated that a reasonable model and estimates of the equivalent parameters for the aeroelastic aircraft are possible with the neural partial differential method by using the measured motion and control variables, without any need for postulating the coupled equations of motion or initialization of the parameters to be estimated. The proposed approach reduces the large number of parameters for aeroelastic aircraft dynamics into fewer equivalent parameters, and this methodology does not require the measurements of the elastic deflections or their derivatives. The neural partial differential method is applied to the simulated flight data of an aeroelastic aircraft for the longitudinal dynamics. The performance of the neural partial differential approach is compared with the estimates obtained from the other methods like classical estimation methods, analytical computation, and values given in the literature for rigid body modeling. The performance is also validated by comparing the measured lift force and pitching moment coefficients with the neural predicted and neural reconstructed coefficients using the estimates obtained through the neural partial differential approach.

Molecular Dynamics Simulations of Deformable Viral Capsomers.

Most coarse-grained models of individual capsomers associated with viruses employ rigid building blocks that do not exhibit shape adaptation during self-assembly. We develop a coarse-grained general model of viral capsomers that incorporates their stretching and bending energies while retaining many features of the rigid-body models, including an overall trapezoidal shape with attractive interaction sites embedded in the lateral walls to favor icosahedral capsid assembly. Molecular dynamics simulations of deformable capsomers reproduce the rich self-assembly behavior associated with a general T=1 icosahedral virus system in the absence of a genome. Transitions from non-assembled configurations to icosahedral capsids to kinetically-trapped malformed structures are observed as the steric attraction between capsomers is increased. An assembly diagram in the space of capsomer-capsomer steric attraction and capsomer deformability reveals that assembling capsomers of higher deformability into capsids requires increasingly large steric attraction between capsomers. Increasing capsomer deformability can reverse incorrect capsomer-capsomer binding, facilitating transitions from malformed structures to symmetric capsids; however, making capsomers too soft inhibits assembly and yields fluid-like structures.

Computational prediction of muscle synergy using a finite element framework for a musculoskeletal model on lower limb.

Previous studies have demonstrated that the central nervous system activates muscles in module patterns to reduce the complexity needed to control each muscle while producing a movement, which is referred to as muscle synergy. In previous musculoskeletal modeling-based muscle synergy analysis studies, as a result of simplification of the joints, a conventional rigid-body link musculoskeletal model failed to represent the physiological interactions of muscle activation and joint kinematics. However, the interaction between the muscle level and joint level that exists in vivo is an important relationship that influences the biomechanics and neurophysiology of the musculoskeletal system. In the present, a lower limb musculoskeletal model coupling a detailed representation of a joint including complex contact behavior and material representations was used for muscle synergy analysis using a decomposition method of non-negative matrix factorization (NMF). The complexity of the representation of a joint in a musculoskeletal system allows for the investigation of the physiological interactions in vivo on the musculoskeletal system, thereby facilitating the decomposition of the muscle synergy. Results indicated that, the activities of the 20 muscles on the lower limb during the stance phase of gait could be controlled by three muscle synergies, and total variance accounted for by synergies was 86.42%. The characterization of muscle synergy and musculoskeletal biomechanics is consistent with the results, thus explaining the formational mechanism of lower limb motions during gait through the reduction of the dimensions of control issues by muscle synergy and the central nervous system.

Designing guiding device of suspension made of aluminum alloys for multi-purpose driverless vehicle using topological optimization method

Introduction (problem statement and relevance). Currently, mobile driverless transport and technological means are widely used for automation of work processes and remote control over a vehicle, excluding immediate human attendance in dangerous areas. Generally, such vehicles feature an electric powerplant while using batteries as energy storage devices. In order to reduce the number of operations during such vehicle driving, it is convenient to use a running gear design that is symmetric relative to its longitudinal and transverse planes. Reducing energy consumption will allow increasing in energy efficiency when performing transport and other technological operations. One of the ways to improve energy efficiency is to reduce the weight of elements of such vehicles. This can be achieved by using materials with high specific strength, such as aluminum alloys, and by developing optimum loading patterns for such element structures. The object of the study is a driverless 4x4 vehicle with the fully loaded weight of 830 kg. The research subject is the methods of optimum designing of vehicle load-bearing structures and their use taking into account the operating conditions. The purpose of the study is to develop the methodology for designing suspension elements for a vehicle with a symmetric design of the running gear made of aluminum alloy taking into account the loading modes.Methodology and research methods. The paper presents a dynamic mathematical model of the wheeled vehicle for determination of loads created in a program for rigid bodies dynamics modeling, the methodology for bringing the loads to one suspension unit (front left wheel), loading patterns for suspension elements obtained with the use of topological optimization and strength calculations performed with application of the finite element method confirming the design functionality.Scientific novelty and results. The paper presents the method for bringing the loads obtained for all suspension elements to the front left point, since the driverless vehicle has a symmetrical running gear design. Taking this into account, a rigid-body dynamic model and an algorithm for processing the obtained loads for a finite element model were developed. Also, typical modes of vehicle loading were selected. The loads were distributed among the following types: operational, extreme and emergency ones. Recommendations were given for the choice of restrictions when conducting topological optimization depending on the mode type. As a result, loading patterns for suspension guiding device elements were obtained. Check calculations were carried out to confirm the design functionality.Practical significance. The obtained results can be used in development of highly loaded elements of wheeled vehicles.

Optimization of Fixture Layout and Clamping Force in a Concurrent Environment to Improve the Part Quality in Milling Operations

Fixture layout design (FLD) determines the specific position of locators and clamps to position and support the workpiece with respect to a machine tool. The FLD approaches that use Finite Element Analysis (FEA) are widely used in previous works, and it becomes computationally expensive and specific to a particular problem. Further, the FLD and clamping force optimization were often performed separately, ignoring their interdependence. In the present work, to maximize the dimensional and form quality of the part, the reaction forces of the locators are made uniformly distributed by suitably varying the fixture layout and clamping force. The parametric rigid body model is used to depict the behaviour of the workpiece-fixture system, and it is incorporated with the genetic algorithm to optimize the design variables. A prismatic workpiece with slot milling operation is considered to validate the proposed methodology. Stability criterion and tool-fixture interference are considered constraints. Subsequently, FEA is used to verify the integrity of the proposed approach. The results infer that the uniformity in distribution of maximum elastic deformation of the workpiece is achieved due to the uniform distribution of reaction forces. Further, the effects of cutting forces on fixture layout and clamping forces are studied.

Improved spatial-temporal graph convolutional networks for upper limb rehabilitation assessment based on precise posture measurement.

After regular rehabilitation training, paralysis sequelae can be significantly reduced in patients with limb movement disorders caused by stroke. Rehabilitation assessment is the basis for the formulation of rehabilitation training programs and the objective standard for evaluating the effectiveness of training. However, the quantitative rehabilitation assessment is still in the experimental stage and has not been put into clinical practice. In this work, we propose improved spatial-temporal graph convolutional networks based on precise posture measurement for upper limb rehabilitation assessment. Two Azure Kinect are used to enlarge the angle range of the visual field. The rigid body model of the upper limb with multiple degrees of freedom is established. And the inverse kinematics is optimized based on the hybrid particle swarm optimization algorithm. The self-attention mechanism map is calculated to analyze the role of each upper limb joint in rehabilitation assessment, to improve the spatial-temporal graph convolution neural network model. Long short-term memory is built to explore the sequence dependence in spatial-temporal feature vectors. An exercise protocol for detecting the distal reachable workspace and proximal self-care ability of the upper limb is designed, and a virtual environment is built. The experimental results indicate that the proposed posture measurement method can reduce position jumps caused by occlusion, improve measurement accuracy and stability, and increase Signal Noise Ratio. By comparing with other models, our rehabilitation assessment model achieved the lowest mean absolute deviation, root mean square error, and mean absolute percentage error. The proposed method can effectively quantitatively evaluate the upper limb motor function of stroke patients.

Insights from a Nine-Segment Biomechanical Model and Its Simulation for Anthropometrical Influence on Individualized Planche Learning and Training in Gymnastics.

The Planche is a challenging, the most required, and a highly valued gymnastic skill. Yet, it is understudied biomechanically. This article aims to explore the anthropometric variations that could affect the quality of balancing control in the Planche and to identify the body types that have an advantage in learning and training. To achieve this goal, a 9-segment rigid-body model is designed to simulate the skill performance by using 80 different body types. The results demonstrate that body type is a critical factor in determining an individual's innate ability to perform the Planche. The innate ability is affected by body mass, height, gender, and race. The findings reveal that a personalized training plan based on an individual's body type is necessary for optimal learning and training. A one-size-fits-all approach may not be effective since each individual's body type varies. Additionally, this study emphasizes the importance of considering segmental and/or limb characteristics in designing effective training plans. This study concludes that, for a given height, individuals with relatively longer legs and a shorter trunk (the characteristics of Europeans in comparison to Asians) could be better suited to perform the Planche. This suggests that European body types are naturally more advanced than Asian body types when it comes to performing the Planche. The practical implications of the current study are that practitioners can use biomechanical modeling and simulation techniques to identify body types that are most suited for the Planche and design training programs that are tailored to individual body types for optimizing their learning and training.

UTILIZATION OF STATISTICAL ANALYSIS TO IDENTIFY INFLUENTIAL SLOPE PARAMETERS ASSOCIATED WITH ROCKFALL AT OPEN PIT MINES.

The application of statistical analysis software programs has proven useful for the investigation of rockfall runout distance along a designed slope. Rockfall modeling programs are continually being upgraded with more sophisticated analysis tools, such as the use of the rigid body versus lump mass models. Engineers at mine sites utilizing the software may have varied experience related to these models, their associated input parameters, and how to interpret the generated results. To address this concern, researchers at the Spokane Mining Research Division (SMRD) of the U.S. National Institute for Occupational Safety and Health (NIOSH) investigated the influence of slope height, slope angle, slope material, and rock size for both rigid body and lump mass models in a 2-D statistical analysis program. Based on a literature search and industry input, specific ranges common to that of an open pit mining environment were chosen for each of the input parameters to determine 90% rock runout distance as well as their sensitivity to change. Data collected from this numerical analysis and simulation will be compared to empirical rockfall data gathered through the duration of the Highwall Safety project conducted by NIOSH from 2022-2026.

Development and comparative evaluation of various fault detection algorithms for a drum brake using artificial neural networks and a physics-based model

Drum brakes are among the essential safety components in automobiles; hence, it is critical to detect any fault in the system that might hinder its performance. A fault detection framework based on artificial intelligence and a rigid-body model of a system (as a digital experiment) is proposed to detect four of the most common faults in automotive drum brakes. First, a contact mechanics-based nonlinear model of a drum brake (incorporating conformal contact between the brake shoes and the brake drum) is developed to estimate the dynamic response accurately. The predictions from this model are compared with the data available in the literature. The responses estimated from the model with a known level of faults form the input data set for various fault quantification algorithms. Sensitivity-based pruning technique in conjunction with an artificial neural network is used to select the optimal set of features for which the physical interpretations are deduced. The developed fault detection methodologies are quantitatively compared, and the most applicable among them is determined based on the detection accuracy and the computational cost. Finally, the robustness of the selected methodology is tested under the presence of white Gaussian noise in the measured signals. The proposed framework and the selected methodology will help design an accurate health monitoring tool to diagnose faults in automotive drum brakes. Though the current study focuses on drum brakes, the possible generalization of its framework to other systems is discussed.

Numerical research of high-speed oblique water-entry of projectile based on rigid body and fluid-structure interaction model

When a projectile enters the water at high speed, the projectile can suffer a huge impact of water. If a deformation occurs in the structure of the projectile during water-entry, the numerical method based on rigid body model will be limited, while the accuracy and precision of the results can be affected. The two numerical methods of the rigid body and fluid-structure interaction (FSI) model have been built to get the results of the oblique water-entry of the projectile in this paper. Moreover, the numerical results for the given projectile under the same water-entry conditions (initial angle of incidence of θ = 15°, initial angle of attack of α = 5°, initial speed of V = 200m/s ) have been contrasted. The results show that if a small deformation occurs in the body of the projectile during the water-entry, the numerical results of the FSI and the rigid body are different. Further, the small deformation within the limit of flexibility can change the motion attitude and the trajectory of projectile during the water-entry, meanwhile the change can cause the bending of the ballistic and the super-cavity. For the projectile with the structural response, the change in the distribution of the stress concentration area can affect the drag force suffered by projectile.

Maintaining soldier musculoskeletal health using personalised digital humans, wearables and/or computer vision.

The physical demands of military service place soldiers at risk of musculoskeletal injuries and are major concerns for military capability. This paper outlines the development new training technologies to prevent and manage these injuries. Narrative review. Technologies suitable for integration into next-generation training devices were examined. We considered the capability of technologies to target tissue level mechanics, provide appropriate real-time feedback, and their useability in-the-field. Musculoskeletal tissues' health depends on their functional mechanical environment experienced in military activities, training and rehabilitation. These environments result from the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing joint tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and strain), which may be enabled by real-time biofeedback. Recent research has shown that these biofeedback technologies are possible by integrating a patient's personalised digital twin and wireless wearable devices. Personalised digital twins are personalised neuromusculoskeletal rigid body and finite element models that work in real-time by code optimisation and artificial intelligence. Model personalisation is crucial in obtaining physically and physiologically valid predictions. Recent work has shown that laboratory-quality biomechanical measurements and modelling can be performed outside the laboratory with a small number of wearable sensors or computer vision methods. The next stage is to combine these technologies into well-designed easy to use products.

Dual-Quaternion-Based Dynamics Modeling for a Rigid–Flexible Coupling Satellite

Dual quaternions can describe both three-dimensional translation and three-dimensional rotation and have the advantages of a simple form, accurate modeling, and precise physical meaning in terms of dynamic modeling. The traditional rigid-body dynamics modeling theory based on dual quaternions is only applicable to the case of modeling for the center of mass. When modeling appendages, the flexible appendages must be symmetrically configured to reduce the modeling complexity. However, in space operations, flexible appendages are usually not symmetrically installed, which significantly limits the applications of dual-quaternion theory. In this paper, we propose a new dual-quaternion derivative rule and a rigid-body dynamic modeling method suitable for any point. The theory can be applied to model flexible appendages with any configuration without changing the mathematical modeling framework. Finally, we demonstrate the integrated dynamic equation of a rigid–flexible coupling system considering the coupling of position and attitude, and we verify the correctness of the model by numerical simulation.

Experimental and Mathematical Study of Flexible–Rigid Rail Vehicle Riding Comfort and Safety

This paper analyses the dynamic behavior of a rail vehicle using experimental and simulation analysis on a multi-rigid–flex body model. The mathematical models are developed considering the car body, bogie frame, and wheel axle for rail vehicles of rigid–flexible and multi-rigid formulations, taking the car body as rigid for the rigid body analysis and the flexible car body for flex–rigid analysis. A finite element model of the car body was developed in ANSYS, and substructure and modal analyses were performed. The mathematical model is validated through an experiment conducted by the Research Design and Standards Organization. Then, the validated model is further analyzed to evaluate the running comfort, using the Sperling ride index and the running safety, by investigating the derailment coefficient and wheel load reduction rate. The impact of flexibility on the vehicle’s running stability is investigated using the rigid body dynamics model and experimental data. Compared to experimental data, the simulation results reveal that elastic vibration cannot be neglected in vehicle dynamics, since the rigid–flexible coupling model is slightly more significant than the rigid-body model for ride comfort and safety.

CALIBRATION OF HOLZAPFEL-GASSER-OGDEN COLLATERAL LIGAMENT PROPERTIES IN A HYBRID POST-ARTHROPLASTY KNEE JOINT MODEL FOR LAXITY TESTING

This study aims to create a novel computational workflow for frontal plane laxity evaluation which combines a rigid body knee joint model with a non-linear implicit finite-element model wherein collateral ligaments are anisotropically modelled using subject-specific, experimentally calibrated Holzpfel-Gasser-Ogden (HGO) models.The framework was developed based on CT and MRI data of three cadaveric post-TKA knees. Bones were segmented from CT-scans and modelled as rigid bodies in a multibody dynamics simulation software (MSC Adams/view, MSC Software, USA). Medial collateral and lateral collateral ligaments were segmented based on MRI-scans and are modelled as finite elements using the HGO model in Abaqus (Simulia, USA). All specimens were submitted varus/valgus loading (0-10Nm) while being rigidly fixed on a testing bench to prevent knee flexion. In subsequent computer simulations of the experimental testing, rigid bodies kinematics and the associated soft-tissue force response were computed at each time step. Ligament properties were optimised using a gradient descent approach by minimising the error between the experimental and simulation-based kinematic response to the applied varus/valgus loads. For comparison, a second model was defined wherein collateral ligaments were modelled as nonlinear no-compression spring elements using the Blankevoort formulation.Models with subject-specific, experimentally calibrated HGO representations of the collateral ligaments demonstrated smaller root mean square errors in terms of kinematics (0.7900° +/− 0.4081°) than models integrating a Blankevoort representation (1.4704° +/− 0.8007°).A novel computational workflow integrating subject-specific, experimentally calibrated HGO predicted post-TKA frontal-plane knee joint laxity with clinically applicable accuracy. Generally, errors in terms of tibial rotation were higher and might be further reduced by increasing the interaction nodes between the rigid body model and the finite element software. Future work should investigate the accuracy of resulting models for simulating unseen activities of daily living.

THE CONTRIBUTION OF THE MASTICATORY MUSCLES TO PRODUCTION OF 3D OCCLUSAL LOADS ACROSS THE DENTAL ARCH

Occlusal loading and muscle forces during mastication aids in assessment of dental restorations and implants and jaw implant design; however, three-dimensional bite forces cannot be measured with conventional transducers, which obstruct the native occlusion. The aim of this study was to combine accurate jaw kinematics measurements, together with subject-specific computational modelling, to estimate subject-specific occlusal loading and muscle forces during mastication.Motion experiments were performed on one male participant (age: 39yrs, weight: 82kg) with healthy dentition. Two low-profile magnetic sensors were fixed to the participant's teeth and the two dental arches digitised using an intra-oral scanner. The participant performed ten continuous of chewing on a polyurethane rubber sample of known material properties, followed by maximal compression (clenching). This was repeated at the molars, premolars of both the left and right sides, and central incisors. Jaw motion was simultaneously recorded from the sensors, and finite element modelling used to estimate bite force. Specifically, simulations of chewing and biting were performed by driving the model using the measured kinematics, and bite force magnitude and direction quantified. Muscle forces were then evaluated using a rigid-body musculoskeletal model of the patient's jaw.The first molars generated the largest bite forces during chewing (left: 309 N, right: 311 N) and maximum-force biting (left: 496 N, right: 495 N). The incisors generated the smallest bite forces during chewing (75 N) and maximum-force biting (114 N). The anterior temporalis and superficial masseter muscles had the largest contribution to maximum bite force, followed by the posterior temporalis and medial pterygoid muscles.This study presents a new method for estimating dynamic occlusal loading and muscle forces during mastication. These techniques provide new knowledge of jaw biomechanics, including muscle and occlusal loading, which will be useful in surgical planning and jaw implant design.

End Motion Path Analysis of Notched Variable Cross-section Flexible Manipulator Based on 3R Pseudo-Rigid Body Model

A wire-driven planar curved notched flexible manipulator with variable cross-section is designed. Based on the Bernoulli Euler beam equation, the end track and rotation angle of the notched flexible manipulator with variable cross-section after applying force is deduced theoretically. In addition, the 3R pseudo rigid body model is used to calculate the end track and rotation angle, and ABAQUS finite element analysis software is used for motion simulation. Then, MATLAB is used for post-processing to obtain the end track of the flexible manipulator. By comparing the track of the 3R pseudo rigid body model with the ABAQUS simulation track, the relative error is obtained. The conclusion proves that the 3R pseudo rigid body model can effectively simulate the end track of a notched flexible manipulator with variable cross-section after bending, which expands a new method for solving the complex end motion problem of a flexible manipulator with variable cross-section, and also broadens the applicable structure of the 3R pseudo rigid body model.