Body Dynamics Research Articles

Mechanism Analysis and Experimental Verification of Side-Filled Rice Precision Hole Direct Seed-Metering Device Based on MBD-DEM Simulations

In order to solve the problems of poor hole-filling performance and the high seed-breakage rate of conventional rice bud seed precision hole direct seed-metering devices, a side-filled rice precision hole direct seed-metering device was developed, and the mechanism and force analyses for seeding operations were carried out. The key factors affecting seeding quality were determined: rotation speed, seeding angle and seeding height. By coupling the discrete element method (DEM) and multi-rigid body dynamics (MBD), the seed breakage rate and seeding performance at different rotation speeds were analyzed. Single-factor bench testing was used to analyze the effect of a duckbill unit on seeding performance under different factor levels. The three-factor and five-level quadratic regression orthogonal rotation center combination test methods were used to obtain the optimal working parameter combination. The test results showed that when the rotation speed was 47 r/min, the seeding angle was 19°, and the seeding height was 180 mm, the qualified index of seeding was 92.03%, the hole diameter qualified index was 91.62%, and the hole distance variation index was 7.17%. This study provides a reference for the research of mechanical rice sprouting seed-metering devices.

Dynamics of infinitesimal body in the concentric restricted five-body problem

This research presents a model of a specific restricted five-body problem. In this model, there are four main bodies, referred to as primary bodies. The first two primary bodies have the same mass while the third and fourth primary bodies also share an identical mass, which is lesser than the former. These primary bodies are lined up in a straight line along a designated axis. They revolve in circular paths with different distances from a common central point that represents their shared center of mass. The first set of orbits has a shorter radius compared to the second set. Simplifying the motion equations of an infinitesimally small mass reveals a single governing parameter, λ, constrained within λ ∊ (λ0, 1), λ0 = 0.417221. Within the orbital plane of these primaries, seven equilibrium points are identified: four along the x-axis, two on the y-axis, and one at the system's origin. Notably, no equilibrium points were found outside this orbital plane. The study concludes that collinear equilibrium points are linearly unstable, while the non-collinear points maintain stability for values λc < λ < 1, λc = 0.971105.

The duality game: a quantum algorithm for body dynamics modeling

The duality game: a quantum algorithm for body dynamics modeling

Dust emission evaluation of the flexible metal wheel over lunar terrain and fender effect

The lunar rover’s wheels produce substantial dust emission during movement, presenting safety concerns for astronauts and potential equipment wear. Replicating the dust emission behavior in the low-gravity environment on Earth is challenging. This study proposes a numerical approach to analyze the dust emission distribution of an elastic wire mesh wheel over lunar terrain. The analysis considers adhesion and electrostatic forces within a Discrete Element Method (DEM) model of lunar dust. Then a Multi-Flexible Body Dynamics (MFBD) model of a flexible wire mesh wheel was developed. A virtual single-wheel soil bin experiment was conducted to examine dust emission features under various motion conditions and on rough terrain. Additionally, alternative structures of dust fender were designed to effectively suppress dust, and the effects of the structural features on dust emission were further explored. This comprehensive study provides a valuable reference for simulation and dust-control technologies related to elastic lunar wheels, offering insights that contribute to the effective management of dust emissions from lunar rover wheels.

The Inertial Disturbances of Fluid Movement in the Chamber of a Liquid Autobalancer

This article analyses the problem of automatic balancing rotors with a liquid balancer, which is a cylindrical chamber partially filled liquid of a certain density. This problem is related to the problem of the dynamics of bodies with cavities partially filled with liquid. As part of this task, we analyzed disturbances in the relative motion of the fluid in the ABD chamber caused by the Coriolis force inertia. The distortions of the free surface of the liquid were found, resonant phenomena in the flow of the working fluid were investigated, and the physical explanation of the received results given should be taken into account when designing the corresponding ones self-balancing devices. It was established that the axial component of the Coriolis inertial force causes peculiar wave phenomena in the correcting fluid movement. For the given nature of undisturbed motion, the conditions of this phenomenon’s occurrence are determined only by the geometric dimensions of the cylindrical chamber and the thickness of the liquid layer in undisturbed motion, and do not depend on the intensity of rotation of the liquid, nor on its density. It is shown that a decrease in the “ABD chamber height–radius” ratio leads to stabilization of the movement of the system. Experimental verification has been performed; theoretical results on the developed stand for work research rotor system with a vertical axis of rotation.

The spinal cord facilitates cerebellar upper limb motor learning and control; inputs from neuromusculoskeletal simulation.

Complex interactions between brain regions and the spinal cord (SC) govern body motion, which is ultimately driven by muscle activation. Motor planning or learning are mainly conducted at higher brain regions, whilst the SC acts as a brain-muscle gateway and as a motor control centre providing fast reflexes and muscle activity regulation. Thus, higher brain areas need to cope with the SC as an inherent and evolutionary older part of the body dynamics. Here, we address the question of how SC dynamics affects motor learning within the cerebellum; in particular, does the SC facilitate cerebellar motor learning or constitute a biological constraint? We provide an exploratory framework by integrating biologically plausible cerebellar and SC computational models in a musculoskeletal upper limb control loop. The cerebellar model, equipped with the main form of cerebellar plasticity, provides motor adaptation; whilst the SC model implements stretch reflex and reciprocal inhibition between antagonist muscles. The resulting spino-cerebellar model is tested performing a set of upper limb motor tasks, including external perturbation studies. A cerebellar model, lacking the implemented SC model and directly controlling the simulated muscles, was also tested in the same. The performances of the spino-cerebellar and cerebellar models were then compared, thus allowing directly addressing the SC influence on cerebellar motor adaptation and learning, and on handling external motor perturbations. Performance was assessed in both joint and muscle space, and compared with kinematic and EMG recordings from healthy participants. The differences in cerebellar synaptic adaptation between both models were also studied. We conclude that the SC facilitates cerebellar motor learning; when the SC circuits are in the loop, faster convergence in motor learning is achieved with simpler cerebellar synaptic weight distributions. The SC is also found to improve robustness against external perturbations, by better reproducing and modulating muscle cocontraction patterns.

A Bio-inspired Model for Bee Simulations.

As eusocial creatures, bees display unique macro collective behavior and local body dynamics that hold potential applications in various fields, such as computer animation, robotics, and social behavior. Unlike birds and fish, bees fly in a low-aligned zigzag pattern. Additionally, bees rely on visual cues for foraging and predator avoidance, exhibiting distinctive local body oscillations, such as body lifting, thrusting, and swaying. These inherent features pose significant challenges for realistic bee simulations in practical animation applications. In this paper, we present a bio-inspired model for bee simulations capable of replicating both macro collective behavior and local body dynamics of bees. Our approach utilizes a visually-driven system to simulate a bee's local body dynamics, incorporating obstacle perception and body rolling control for effective collision avoidance. Moreover, we develop an oscillation rule that captures the dynamics of the bee's local bodies, drawing on insights from biological research. Our model extends beyond simulating individual bees' dynamics; it can also represent bee swarms by integrating a fluid-based field with the bees' innate noise and zigzag motions. To fine-tune our model, we utilize pre-collected honeybee flight data. Through extensive simulations and comparative experiments, we demonstrate that our model can efficiently generate realistic low-aligned and inherently noisy bee swarms.

Establishing the Normative Reference Values of Timed Up and Go Test among Normal Weight and Overweight Schoolage Children: A Study Protocol

Introduction: The dynamics of body posture to avoid falling are generally referred to as balance. It has been shown that child developmental skills are influenced by their body compositions. When compared to their peers who are at a healthy weight, children who are overweight or obese frequently show poorer levels of motor proficiency including balance, mobility and related features. Need of the study: The protocol will determine the typical TUG test results in children relative to their body composition, enabling clinicians to effectively screen for balance deficits in children and will enable timely interventions to prevent falls, accidents, and sports injuries in children. Aim: To find the reference values of Timed Up and Go (TUG) test in normal weight and overweight children and compare the values between them. Materials and Methods: A study protocol on school-going children aged 5 to 15 years will be recruited using convenience sampling and divided into two groups based on their Body Mass Index (BMI): normal weight and overweight. The procedure for performing TUG test will be taught to the children, and the time taken for completion will be recorded using a stopwatch. To check the normality, Kolmogorov test will be applied as sample size estimated is above 50. Parametric or non parametric tests will be used for between group analyses.

Rigid body dynamics from the Euler equations to the spacecraft attitude control in the works of scientists from Saint Petersburg State University. Part 2

This article represents the second part of a survey dedicated to the 300th anniversary of Saint Petersburg State University (SPbSU). The article is intended on analysis the scientific achievements of the Saint Petersburg School of Mathematics and Mechanics in the field of rigid body dynamics in the last 50 years. The main attention in the article is paid to theoretical research in the field of uncontrolled and controlled motions of a rigid body

Concurrent validity of embedded solutions for whole body dynamics analysis

Concurrent validity of embedded solutions for whole body dynamics analysis

Elucidation on step-out phenomenon of magnetic strain wave gear by multi flexible body dynamics and displacement measurement

Elucidation on step-out phenomenon of magnetic strain wave gear by multi flexible body dynamics and displacement measurement

Explorations of the holonomy of a rolling sphere

Consider a rigid body rolling with one point in contact with a fixed surface. Now suppose that the instantaneous point of contact traces out a closed path. As a demonstration of a phenomenon known as holonomy, the body will typically not return to its original orientation. The simplest demonstration of this phenomenon in rigid body dynamics occurs in the motion of a rolling sphere and finds application to path planning and reorientation of spherical robots. Motivated by earlier works of Bryant and Johnson, we establish expressions for the change in orientation of a rolling sphere after completing a rectangular path. We use numerical methods to show that all possible changes in orientation are possible using a single rectangular path. Based on the Euler angle parameterization of a rotation, we develop a more intuitive method to achieve a desired orientation using three rectangular paths. With regards to applications, the paths we discuss can be employed to achieve any desired reorientation of a spherical robot.

Experimental and numerical investigation on the unsteady interaction in longitudinal stage separation for parallel-staged two-body configuration

Hypersonic stage separation is a significant process, probably involving complex aerodynamic interaction, which determines the survival of two-stage-to-orbit (TSTO) vehicles. The longitudinal stage separation (LSS) scheme is proposed to improve the safety of the parallel-staged TSTO vehicle, where a small interstage gap may result in weak interference. Therefore, an experimental and numerical study of LSS for the parallel-staged TSTO vehicle at Mach 7 with different angles of attack (AoA) is carried out. The dynamic interaction, including variations in the shock structure, wall pressure distribution, and unsteady aerodynamics, is investigated by testing and numerical simulation. The LSS experiments for the TSTO vehicle were performed using a high-speed pneumatic ejection launch system in the JF-12 shock tunnel, and the method was developed using high-speed visualization and image processing techniques to capture the separating trajectory. The numerical simulations were carried out using the overset grid method and solving the Navier–Stokes equations coupled with the rigid body dynamics equations to obtain the laminar flows over the TSTO vehicle during LSS. The qualitative and quantitative comparison of the test and numerical results showed good agreement in terms of aerodynamic performance, flowfield pattern, wall pressure, and separation trajectory. They show that the small interstage gap of the LSS leads to weak type I and VI shock–shock interactions, with short-duration weak shock reflection at a higher AoA. Furthermore, no shock reflection or interstage gap is observed at lower AoA. Moreover, no stage recontact is observed, and the safety and feasibility of LSS for parallel-staged TSTO vehicles are demonstrated.

Rigid body dynamics from the Euler equations to the spacecraft attitude control in the works of scientists from Saint Petersburg State University. Part 3

This article is a continuation of the survey dedicated to the 300th anniversary of Saint Petersburg State University (SPbSU) and is an attempt to analyze the scientific achievements of the St.Petersburg School of Mechanics in the field of rigid body dynamics. This third part of the review is devoted to the 50-year period ending in 2023. It focuses on applied research carried out by scientists from St. Petersburg State University in the 1970s and devoted to the uncontrolled attitude motion of a rigid body in the gravitational and magnetic fields of the Earth. A significant place among these studies is occupied by the solution of problems related to the passive gravitational stabilization of artificial satellites using magnetic interaction to create restoring and damping torques.

Predicting base Engine Vibrations using Flexible Multi Body Dynamics Simulation

Predicting the vibratory response of a base engine is appealing as it can speed up the engine development cycle and cut down testing cost. However, there are concerns regarding predictability of base engine vibration simulation models due to various factors. This study attempts to investigate this predictability and gives more insights on what factors can affect it. In the presented work, the vibratory response of a base engine is predicted through a flexible Multi Body Dynamics simulation. Cylinder pressure excitation on the cylinder head and pistons, and reciprocating inertia excitation, are considered as inputs in this flexible Multi Body Dynamics simulation. Effects arising from overhead moving components and gear train, have been excluded from this study. The predicted vibratory response of the base engine at particular locations, is compared with the vibratory response as measured using accelerometers mounted at those locations, during testing. A reasonable level of correlation can be seen between simulation and testing. Measures that can be taken to improve this correlation are also discussed.

Artificial physics engine for real-time inverse dynamics of arm and hand movement.

Simulating human body dynamics requires detailed and accurate mathematical models. When solved inversely, these models provide a comprehensive description of force generation that considers subject morphology and can be applied to control real-time assistive technology, for example, orthosis or muscle/nerve stimulation. Yet, model complexity hinders the speed of its computations and may require approximations as a mitigation strategy. Here, we use machine learning algorithms to provide a method for accurate physics simulations and subject-specific parameterization. Several types of artificial neural networks (ANNs) with varied architecture were tasked to generate the inverse dynamic transformation of realistic arm and hand movement (23 degrees of freedom). Using a physical model, we generated representative limb movements with bell-shaped end-point velocity trajectories within the physiological workspace. This dataset was used to develop ANN transformations with low torque errors (less than 0.1 Nm). Multiple ANN implementations using kinematic sequences solved accurately and robustly the high-dimensional kinematic Jacobian and inverse dynamics of arm and hand. These results provide further support for the use of ANN architectures that use temporal trajectories of time-delayed values to make accurate predictions of limb dynamics.

A multi-stream spatio-temporal network based behavioural multiparametric pain assessment system

Existing approaches for pain assessment are mostly based on facial expressions which cannot fully describe the expressiveness of pain. Although few researchers have also implemented multimodal approaches, they have not considered body movement for pain assessment. Besides, assessing pain in an unconstrained setting is challenging due to occlusions and poor illumination. Hence, to overcome these challenges we present a multi-stream framework for behavioural multiparametric pain assessment. To detect pain from face images a domain adaptation technique with a stacked BiLSTM network is implemented for joint spatio-temporal modelling. Further, a FCN-based-BiLSTM model is implemented to learn pain-related body dynamics. To learn pain-related features from pain sound VGG-based features are extracted and then a linear model is used for pain classification. Finally, a decision-level fusion approach is implemented to learn jointly from all pain classifiers. The proposed pain assessment system has achieved 92 % of accuracy after evaluating on self-created pain dataset.

Cartesian coordinates of an intrinsically defined curve

Summarizing some old research on the dynamics of a pointall body along its own trajectory, this paper established the differential relationships between the principal curvatures of a 3D curve, that is the normal curvature and the torsional curvature, and its Cartesian coordinates. The differential system thus derived is actually a dynamical system of a representative point of the curve moving along it. This dynamic system is analyzed to see the possibilities of finding analytical solutions in finite terms, using Frobenius' integrability theorem for the general case and usual integration methods for the particular case consisting of the constant ratio between the two curvatures.

The Pragmatics, Embodiment, and Efficacy of Lived Experience Assessing the Core Tenets of Varela's Neurophenomenology

Varela's enactive approach to cognitive science has been elaborated into a theoretical framework of agency, sense-making, and sociality, while his key methodological innovation — neurophenomenology (NP) — continues to inspire empirical work. We argue that the enactive approach was originally expressed in NP as three core tenets: (1) phenomenological pragmatics, (2) embodied cognition, and (3) conscious efficacy. However, most efforts in NP have focused on applying tenet 1, while tenet 2 has received notably less attention, and there is even explicit distancing from tenet 3. By way of a critical review of four case studies, we show how NP thereby falls short of its full potential. Crucially, it needs to demonstrate that the first-person perspective matters, not only as a source of correlations with third-person data, but because lived experience, as such, makes a difference in its own right to the living body's dynamics. Given that methods for improving subjective reports have become accepted in human neuroscience (tenet 1), and given the increasing availability for recording multi-scalar organismic activity during embodied action (tenet 2), we propose it is time to integrate these research strands by using this issue of conscious efficacy as a pivot point (tenet 3). The development of genuinely experience-involving accounts of neurophysiological activity during embodied action holds promise for rebooting neurophenomenology in stronger form.

Decentralized policy learning with partial observation and mechanical constraints for multiperson modeling

Extracting the rules of real-world multi-agent behaviors is a current challenge in various scientific and engineering fields. Biological agents independently have limited observation and mechanical constraints; however, most of the conventional data-driven models ignore such assumptions, resulting in lack of biological plausibility and model interpretability for behavioral analyses. Here we propose sequential generative models with partial observation and mechanical constraints in a decentralized manner, which can model agents’ cognition and body dynamics, and predict biologically plausible behaviors. We formulate this as a decentralized multi-agent imitation-learning problem, leveraging binary partial observation and decentralized policy models based on hierarchical variational recurrent neural networks with physical and biomechanical penalties. Using real-world basketball and soccer datasets, we show the effectiveness of our method in terms of the constraint violations, long-term trajectory prediction, and partial observation. Our approach can be used as a multi-agent simulator to generate realistic trajectories using real-world data.