Kinematic Behavior Research Articles

Modeling of spindle speed and feed rate considering the kinematic behavior of CNC lathe in face turning

Modeling of spindle speed and feed rate considering the kinematic behavior of CNC lathe in face turning

Influence of the neck length of urease-powered flask-like colloidal motors on their kinematic behavior.

Enzyme-powered synthetic colloidal motors hold promising potential for in vivo medical applications because of their unique features such as self-propulsion, sub-micrometer size, fuel bioavailability, and structural and functional versatility. However, the key parameters influencing the propulsion efficiency of enzyme-powered colloidal motors still remain unclear. Here, we report the effect of the neck length of urease-powered pentosan flask-like colloidal motors on their kinematic behavior resembling the role of bacterial flagella. The sub-micrometer-sized and streamlined pentosan flask-like colloidal motors with variable neck lengths are synthesized through a facile interfacial dynamic assembly and polymerization strategy. The urease molecules are loaded through vacuum infusion technology and thus the urease-triggered catalytic reaction can propel the pentosan flask-like colloidal motors to move autonomously in the urea solution. The self-propelled speed of these pentosan flask-like colloidal motors significantly increases with the elongating neck lengths. The mechanism of the relationship between the neck length and self-propelled motion is that a longer neck can provide a larger self-propelled force due to the larger force area and stabilize the rotation because of the increased rotational friction. This research can provide guidance for the design of biomedical colloidal motors.

Design and Development of a Four-Wheeled Mobile Robot (WMR) for Any Terrain

This paper presents the design, development, and analysis of an all-terrain Wheeled Mobile Robot (WMR). A Wheeled Mobile Robot (WMR) is an autonomous robot that uses wheels for locomotion, allowing it to move efficiently on flat surfaces. These robots are commonly used in various applications, from industrial automation to service robots and research platforms. The robot aims to achieve high mobility on diverse terrains, remote teleoperation, and an effective payload handling capability. The research includes the design and implementation of the mechanical structure, electronic components, control systems, and robot performance analysis. Special focus is given to the kinematic behavior, vibration analysis, and simulation of various components. The robot can carry loads up to 5 kg and navigate complex terrains, including stair climbing. The methodology followed includes structure design, integration of electronic components, assembly, and subsequent trials and simulations. The results demonstrate the robot's potential for practical applications in diverse fields such as exploration, rescue operations, and industrial automation. In summary, wheeled mobile robots are versatile, efficient, and widely used in various industries. Their design carefully balances mechanical, electronic, and software components to achieve reliable and autonomous operation. As technology advances, WMRs become more capable and adaptable, expanding their range of applications.

Real-time monitoring of asphalt pavement structure fatigue response based on tri-axis accelerometer

ABSTRACT Fatigue damage is a notable distress of asphalt pavements. However, monitoring the development process of such distresses in real-time remained challenges for researchers. In this paper, the self-developed sensing facility has been utilized to obtain aggregate kinematic response of semi-circular specimen during the fatigue loading process in the upper-middle (H/2), lower-middle (L/2) and lower-right (L/3) positions of the specimen. Angle and acceleration variation in the X, Y, and Z directions were analysed independently at three positions. The correlation between the kinematic characteristic of the aggregate and the vertical deformation of the asphalt mixture specimen is established. The results illustrated that the asphalt mixture viscoelasticity attenuation during fatigue test caused the angle accumulation and acceleration response change of the specimen. The angle accumulation in the X-axis direction and acceleration variation in Y-axis direction of the aggregate at the H/2 position exhibited a significant three-stage change. Angle-Accumulation Rate (AAR) of change is suggested as a long-term monitoring index for the fatigue development of the asphalt mixture. The proposal of AAR index creatively combines the long-term kinematic behaviour and mechanical behaviour of asphalt mixture, making long-term and real-time monitoring of the asphalt pavement health from the perspective of kinematics become possible.

Kinematic behaviors of piggy-backed vertically loaded anchors in clay

Kinematic behaviors of piggy-backed vertically loaded anchors in clay

Comparison of 1g and centrifuge modelling of drag anchors with subsurface wireless tracking

The kinematic behaviour of drag embedment anchors has become a recent research focus due to the increase in offshore renewable energy devices. This is due to their potential use as an anchoring system for future floating wind applications, in addition to the need to understand their penetration behaviour as a part of the Cable Burial Risk Assessment. Studies on the behaviour of anchors typically consist of field scale or model centrifuge tests, where such facilities are not readily available to all and can result in significant cost. In addition to this, measuring the load–penetration behaviour of an anchor has proven to be a significant challenge, as any contact-based methods are likely to influence the penetration behaviour of the anchor. In this paper, a novel wireless method of recording the inclination of the anchor and calculating the penetration depth is presented. A comparison of the penetration behaviour of a Class F (AC-14) anchor has been made in sand using centrifuge and 1g model scale testing. The results indicate that the 1g testing can match the behaviour of the anchor testing in the centrifuge in terms of both the position of the anchor and its orientation during the dragging event.

Spine Kinematics Behavior During the Handstand Posture: A Biplanar Radiographic Analysis.

Background/Objectives: The handstand is an exercise performed in many sports, either for its own sake or as part of physical training. Unlike the upright bipedal standing posture, little is known about the sagittal alignment and balance of the spine during a handstand, which may hinder coaching and reduce the benefits of this exercise if not performed correctly. The purpose of this study was to quantify the sagittal alignment and balance of the spine during a handstand using radiographic images to characterize the strategies employed by the spino-pelvic complex during this posture. Methods: Nineteen national-level artistic gymnasts participated in this study and underwent a low-dose biplanar (frontal and lateral) radiograph in both upright bipedal standing posture and during a handstand. Then, 3D reconstruction of the spine, based on biplanar radiographic images, enabled the determination of key pelvic (pelvic incidence, sacral slope, pelvic tilt) and spinal (lumbar lordosis, thoracic kyphosis, T9 sagittal offset) parameters in both postures. Results: The results showed that most gymnasts performed pelvic retroversion during the handstand, which was accompanied by an average decrease in lumbar lordosis, thoracic kyphosis, and T9 sagittal offset. Additionally, lumbar curvature was found to depend on pelvic orientation in upright bipedal standing posture, whereas it was associated with the thoracic spine during the handstand. Conclusions: This study provides new insights into how the spine kinematically adapts to an inverted body load. The results may help coaches and physiotherapists in teaching the handstand or using it to rehabilitate and strengthen the spine through the handstand posture.

Application of Nonlinear Optimization in Flight Path Reconstruction of a Sub-scale Aircraft

One key challenge in working with free-flight test data is ensuring its compatibility with the dynamic systems of sub-scale unmanned aircraft. This is crucial to avoid errors in measurements, bias, or scaling issues that could compromise the integrity of the estimated results. We refer to this initial processing step as data compatibility checking, a rigorous process that forms the foundation of our research.Typically, this verification process involves flight path data reconstruction (FPR) predicated on estimating the aircraft’s flight kinematics. The predominant methodologies encompass the stochastic approach, the Extended Kalman Filter (EKF), and the deterministic approach, employing the Output Error Method (OEM). In this research, we propose to approach the problem from the perspective of a nonlinear optimizer to estimate the reconstruction of data derived from free-flight tests of a sub-scale aircraft.The nonlinear optimizer we employ in this research was designed to verify the authenticity of the data representing the aircraft's actual flight. It does this by comparing the measurements of attitude angles, accelerations, and velocities with the expected kinematic behavior of the aircraft. This rigorous evaluation process ensures that the reconstructed data is as close to the actual flight as possible, enhancing the reliability of our results.The sub-scale model deployed in these tests was engineered to emulate the dynamic characteristics of a full-scale aircraft, utilizing the Froude number criterion for appropriate scaling. The chosen aircraft for this project was a Cessna 177B, and the sub-scale aircraft was developed by the Aeronautical Systems Laboratory (LSA) at the Aeronautics Institute of Technology (ITA).This study will delineate the outcomes achieved through FPA employing OEM techniques and compare these results with the studies derived from the proposed nonlinear estimation method.

Understanding the Effect of Water Absorption on the Microstructure, Molecular Kinematics, and Relaxation Behavior of Polyvinyl Butyral Films

Understanding the Effect of Water Absorption on the Microstructure, Molecular Kinematics, and Relaxation Behavior of Polyvinyl Butyral Films

Kinematic Analysis of Plasticization and Transportation System of Tri-Screw Dynamic Extruder.

With the growing demand for high-performance polymer composites, conventional single- and twin-screw extruders often fall short of meeting industrial requirements for effective mixing and compounding. This research investigates the kinematic behavior of the plasticization and transport mechanisms in tri-screw extruders when subjected to a vibrational force field. The study specifically examines how applying vibrational force technology can improve the efficiency of polymer mixing. Vibration force field means that in a three-screw mechanism, an axial vibration is applied to the middle screw to produce a vibration force field. Through the development of mathematical and physical models, this study analyzed the motion dynamics of the screw and the influence of a vibrational force field on polymer transport and mixing efficiency. The findings indicate that, in comparison to traditional twin-screw extruders, tri-screw systems can achieve higher shear and elongational rates, leading to enhanced polymer mixing uniformity. Furthermore, applying an axial vibrational force field significantly influenced the shear and elongational strain rates of the material, thereby optimizing its rheological behavior and processing quality. This research not only establishes a theoretical foundation for the design and optimization of tri-screw extruders but also opens new pathways for the efficient processing of high-viscosity composite materials.

Design, analysis, and demonstration of the COAST guidewire robot with middle tube rotation for endovascular interventions

Minimally invasive procedures for endovascular interventions involve manual navigation of a guidewire. Endovascular interventions encompassing highly tortuous vessels would benefit from guidewires which exhibit higher dexterity. This paper introduces a version of the COAST (COaxially Aligned STeerable) guidewire system capable of exhibiting higher dexterity. The system presented in this paper consists of three coaxially aligned tubes with a tendon to actuate the middle tube. Furthermore, it is possible to independently rotate the middle tube with respect to the outer tube. This variation enables the guidewire to achieve curvature in different planes while avoiding rotation of the entire structure. We also present the simulated stability of the guidewire with different outer tube geometries and experimentally validate the model. Experimental analysis and modeling of the kinematic behavior of the system is presented. A model to calculate the curvature vs. tendon stroke relationship for the optimal notch geometry is presented with an average RMSE of 0.16 mm. A control strategy addressing the snapping instabilities to ensure reliable operation is discussed. A custom phantom vessel and an aortic arch phantom model were used to demonstrate the ability of the system to safely navigate through tortuous pathways without exhibiting these elastic instabilities.

Deciphering the Milky Way disc formation time encrypted in the bar chrono-kinematics

Abstract We present a novel method to constrain the formation time of the Milky Way disc using the chrono-kinematic signatures of the inner Galaxy. We construct an O-rich Mira variable sample from the Gaia Long-period Variable catalogue to study the kinematic behaviour of stars with different ages in the inner Galaxy. From the Auriga suite of cosmological zoom-in simulations, we find that the age of the oldest stellar population with imprints of the bar in density and kinematics matches the disc spin-up epoch. This is because stars born before the spin-up show insufficient rotation and are not kinematically cold enough to be efficiently trapped by the bar. We find that the bar kinematic signature disappears for Mira variables with a period shorter than 190 days. Using the period-age relation of Mira variables, we constrain the spin-up epoch of the Milky Way to be younger than ∼11 − 12 Gyr (redshift ∼3). We also discuss and compare our method and result to other evidence of the Milky Way spin-up epoch under the context of a realistic age uncertainty. Age uncertainty leads to an overestimation of the disc formation time when performing backward modelling. Our constrain of the spin-up epoch is independent from previous studies because it relies on the kinematics of the inner Galaxy instead of the solar vicinity.

Removing atmospheric noise from InSAR interferograms in mountainous regions with a convolutional neural network

Atmospheric noise in interferometric synthetic aperture radar (InSAR)-derived estimates of surface deformation often obscures real displacement signals, especially in mountainous regions. As climate change disproportionately impacts the mountain cryosphere, a reliable technique for atmospheric correction in high-relief terrain is increasingly important. We developed and implemented a statistical machine learning atmospheric correction approach that relies on the differing spatial and topographic characteristics of slow-moving periglacial features and atmospheric noise. Our correction is applied at the native spatial and temporal resolution of the InSAR data, does not require external atmospheric reanalysis data, and can correct both stratified and turbulent atmospheric noise.Using Sentinel-1 data from 2017 to 2022, we trained a convolutional neural network (CNN) on observed atmospheric noise from 330 short-baseline interferograms and observed displacement signals from time series inversion of 1322 interferograms. We applied our trained CNN to correct 251 additional interferograms over an out-of-region application area, which were inverted to create displacement time series. We used the Rocky Mountains in New Mexico, Colorado, and Wyoming as our training, validation, testing, and application areas. When applied to our testing dataset, our correction offered performance improvements of 131%, 208%, and 68% in structural similarity index measure over corrections using atmospheric reanalysis data, phase correlation with topography, and high-pass filtering, respectively. The CNN-corrected time series reveals previously obscured kinematic behavior of rock glaciers and other features in the application dataset. Our flexible, robust approach can be used to correct arbitrary InSAR data to analyze subtle surface deformation signals for a range of science and engineering applications.

Deep Learning-Driven Analysis of a Six-Bar Mechanism for Personalized Gait Rehabilitation

Abstract Recent advances in robotics and artificial intelligence have highlighted the potential for the integration of computational intelligence in enhancing the functionality and adaptability of robotic systems, particularly in rehabilitation. Designing robotic exoskeletons for the lower limb rehabilitation of post-stroke patients requires frequent adjustments to accommodate individual differences in leg anatomy. This complex engineering challenge necessitates a deep understanding of human physiology, robotics, and optimization to develop adaptive robotic systems and also to swiftly quantify the required adjustments and implement them for each patient. The conventional approaches, which mostly rely on heuristics and manual tuning, often struggle to achieve optimal results. This paper presents a novel method that integrates a genetic algorithm with a deep learning approach to generate a gait trajectory of the ankle joint from a six-bar linkage mechanism of fixed dimensions. Later, using the same approach, the inverse kinematics solution for this mechanism is also devised whereby, the set of the link dimensions of the six-bar linkage mechanism is obtained for the given gait trajectory of an individual to achieve customization. We simulated the kinematic behavior of the six-bar linkage mechanism within defined mechanical constraints and utilized the generated data for training a feedforward neural network and long short-term memory models. The proposed model, when trained, can produce accurate lengths for the desired gait trajectories in the sagittal plane and vice versa, which further validates our proposed approach for inverse kinematics solution. Moreover, to evaluate the efficiency of deep learning models, we have conducted an extensive error-based, comparative, and sensitivity analysis using different performance indices. The results highlight the potential of the proposed deep-learning-driven approach in the design analysis of gait rehabilitation robots.

Four-parameter punching theory for reinforced concrete flat slabs without transverse reinforcement

Despite extensive scientific research, the underlying physical principles in theoretical models for understanding punching behavior remain a concern. In this paper, a four-parameter punching theory for reinforced concrete flat slabs without transverse reinforcement has been introduced and validated. The kinematic behavior of the slab was characterized by three key parameters, i.e., critical shear crack inclination, slab rotation, and slab translation. Four distinct shear transfer effects from aggregate interlocking, concrete residual tensile stress, reinforcement dowel action, and the shear-compression ring, were considered and quantified using a novel algorithm based on these three parameters, and the fourth parameter, i.e., the direction of the minimum principal stress within the shear-compression ring. The punching capacity was subsequently determined by summing the contributions from these effects. This model was evaluated through extensive comparisons with experimental data, demonstrating that it accurately captures the influence of various parameters. Across the collected 260 test data, the average ratio of experimental to predicted punching capacity was 1.01, with a coefficient of variance of 0.11 and a coefficient of determination of 0.97. The average ratio, coefficient of variation, and coefficient of determination improved by 8 %, 21 %, and 1 %, compared to the optimal results from other design and theoretical models. The developed model can also assess all shear contributions, slab deformation, and critical shear crack inclination. It is ultimately confirmed that the proposed model can elucidate the physical phenomena and underlying mechanisms involved in punching behavior. Slab deformation primarily arises from flexural deformation, whereas shear forces are predominantly transmitted through the shear-compression ring. Punching failure is attributed to the failure of the shear-compression ring under tension-compression-compression triaxial stress.

Kinematic Patterns of Different Loading Profiles Before and After Total Knee Arthroplasty: A Cadaveric Study.

One of the major goals of total knee arthroplasty (TKA) is to restore the physiological function of the knee. In order to select the appropriate TKA design for a specific patient, it would be helpful to understand whether there is an association between passive knee kinematics intraoperatively and during complex activities, such as ascending stairs. Therefore, the primary objective of this study was to compare the anterior-posterior (AP) range of motion during simulated passive flexion and stair ascent at different conditions in the same knees using a six-degrees-of-freedom joint motion simulator, and secondary, to identify whether differences between TKA designs with and without a post-cam mechanism can be detected during both activities, and if one design is superior in recreating the AP translation of the native knee. It was shown that neither TKA design was superior in restoring the mean native AP translation, but that both CR/CS and PS TKA designs may be suitable to restore the individual native kinematic pattern. Moreover, it was shown that passive and complex loading scenarios do not result in exactly the same kinematic pattern, but lead to the same choice of implant design to restore the general kinematic behavior of the native individual knee.

Real-time data sensing and digital twin model development for pavement material mixing: enhancing workability and optimisation

ABSTRACT An essential aspect of pavement construction sustainability is its low-energy consumption and emissions. The study of pavement materials workability tests holds significant importance in terms of achieving well-mixed conditions with low-energy consumption. The complex components of the material and the uncertain kinematic behaviours of aggregates during mixing make this process challenging. And, few studies of the signal response of pavement materials have been found in the field of civil engineering. For this purpose, an accurate evaluation and monitoring approach for mixing are needed. In this paper, a wireless real-time sensing method is used to monitor the dynamic behaviour of aggregates during mixing. A 3D digital twin model, combining data-sensing techniques and numerical simulation, has been proposed for rapid identification of the mixing material. This model has been validated via a data-fusion algorithm. The application of this model makes a contribution to the data-intensive analysing jobs and decision-making tasks in pavement construction engineering.

Probing barrow entropy models with future event horizon as IR cutoff

We develop formulations for barrow holographic dark energy (BHDE) in both non-interacting and interacting scenarios within a cosmological framework, applying the conventional holographic principle. Model parameter constraints are determined through the Markov Chain Monte Carlo (MCMC) method, utilizing different datasets. The investigation excavates into the models' kinematic behavior, exploring the transition from deceleration to acceleration and tracking the evolution of the equation of state parameters. Further, these models can pretend the evolution of dark energy and matter in the Universe. Additionally, a thermodynamic analysis employing future event horizons is conducted, confirming the validation of the generalized second law of thermodynamics. The resultant of the BHDE models strongly suggests that the Universe is presently experiencing an accelerated phase attributed to dark energy.

Kinematic Differences between Gradual and Impulsive Coronal Mass Ejections: The Role of Flares

Coronal Mass Ejections (CMEs) are significant solar events that involve intense explosions of magnetic fields and mass particles out from the corona. These events are known to be the main driver of space weather and other disturbances experienced by the Earth. Generally, there are two types of CMEs – gradual and impulsive, and each type has different properties which is important to be studied on as they have potential to cause breakdowns in our systems. This study is aimed to analyze and differentiate the kinematic behavior of gradual and impulsive CME with the association of weak and strong flares. Data collection is made through SOHO LASCO catalogues and STEREO database which include velocity, acceleration and angular width as well as images. At the end of this study, it can be deduced that impulsive CME (specifically associated with strong flare) is the most prominent event that has greatest angular width and average velocity. The associated flare has contributed more heat energy to speed up the magnetic energy conversion which results to high velocity of plasma discharge. Since fast CME carries huge amount of momentum during the ejection, impulsive CMEs also experience decelerations due to loss of momentum that has been transferred to background solar wind.

Low-frequency electromagnetic harvester for wind turbine vibrations

In this paper we describe and fully characterize a novel vibration harvester intended to harness energy from the vibration of a wind turbine (WT), to potentially supply power to sensing nodes oriented to structural health monitoring (SHM). The harvester is based on electromagnetic conversion (EM) and can work with vibrations of ultra-low frequencies in any direction of a plane. The harvester bases on a first prototype already disclosed by the authors, but in this paper, we develop an accurate model parameterized by a combination of physical parameters and others related to the geometry of the device. The model allows predicting not only the power generation capabilities, but also the kinematic behaviour of the harvester. Model parameters are estimated by an identification procedure and validated experimentally. Last, the harvester is tested in real conditions on a wind turbine.