Roll Dynamics Research Articles

Moving mesh strategy for simulating sliding and rolling dynamics of droplets on inclined surfaces with finite element method

Finite element method (FEM) moving mesh strategy for simulating dynamics of droplets on inclined surfaces is designed within arbitrary Lagrangian Eulerian (ALE) framework. Depending on the physical and chemical properties of the fluid and the supporting surface, resulting droplet dynamics can exhibit sliding and/or rolling regimes. Exploiting the full potential of the ALE framework, moving mesh strategy designed in this work is capable of tracking the droplet evolution regardless of the flow regime and without the need for frequent mesh adaptation. Additional attention is invested into the discrete energy balance: possible sources of spurious energy due to the mesh motion are identified and investigated. The overall strategy exhibits a good tradeoff between the stability and efficiency, and demonstrates the ability to perform long-time simulations.The capabilities of the proposed strategy are demonstrated on a couple of fairly complex (3D) scenarios motivated by the industrial applications. In particular, droplet dynamics is simulated for the case of inclined and heterogeneous supporting surfaces, which are designed with the aim to manipulate the droplet motion. Complex dynamics, including sliding, rolling and change in movement direction and wetting area, is successfully captured by the numerical simulation.

Rock-and-Walk Manipulation: Object Locomotion by Passive Rolling Dynamics and Periodic Active Control

This study presents the method of robotic <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rock-and-walk</i> manipulation for dynamic, nonprehensile object locomotion. The object, which is in contact with an environmental surface, is basically manipulated to rock from side to side about the contact point periodically by the robot system. In the meantime, the passive dynamics due to gravity enables the object to roll along a zigzag path that leads to a forward walk. Rock-and-walk is a special-purpose method that enables the transport of a certain class of objects, which are too large, heavy to apply other primary methods such as grasping- or pushing-based operations. Our work is motivated by an interesting question in archaeology, how the giant statues of Easter Island (known as “moai”) were transported several hundred years ago, and a recent demonstration performed by archaeologists that it is possible to walk the statue by periodic rocking. We present a detailed study of the dynamics, kinematics, and mechanics of the object-robot-environment system, and devise a feedback control strategy for rock-and-walk gaiting through the effective regulation of the object’s energy and posture. An extensive set of experiments demonstrate the viability and practicality of our approach in diverse settings: Caging-based single-robot manipulation and cable-driven dual-robot manipulation using manipulator arms and aerial robots.

Two-stage control for transfer synchronisation and regularity of subsequent bus line service

Transfer synchronisation aims at reducing the waiting time of transferring passengers to achieve a seamless transfer. Taking control at the operation level is widely regarded as an effective method to make real-time response to transfer synchronisation. However, the irregularity of bus line service after transfer may be caused due to the real-time control before the transfer behaviour. In this paper, we propose a two-stage speed control strategy to improve the transfer efficiency and the regularity of bus service after transfer simultaneously. The influence of speed control is estimated by constructing dynamic rolling horizon. Considering the service performances of both the transfer node and the next stop, we develop a multi-objective optimisation model. Experimental results show that compared with the one-stage control, the two-stage control can significantly reduce the deviation of headway after transfer while reducing the transfer time.

Dynamic roll instability of liquid natural gas carrier during offloading operations and prediction of downtime cost in Malaysian waters

The loss of revenue or global loss in term of cost due to downtime conditions is always a concern for field operators. Prevailing wave conditions may suddenly appear during offloading operations, which will influence the overall process and may lead to downtime of operations. Severe weather can significantly impact downtime costs of offloading operations and cause a huge loss of revenue. This research work integrates the dynamic stability with downtime cost for LNG carrier in different location of Malaysian waters using real time metocean data. This study on downtime cost utilizes the real time and location-specific wave scatters, as well as limiting criteria of offloading in Malaysian waters. The dynamic roll stability of LNG carrier was investigated for ABS criteria in two depths of water at three real-time locations. Susceptible wave conditions had been identified along with downtime cost analysis. This domain of downtime cost study was further rendered into mathematical package in the form of graphical interfaces for field operators. This mathematical based graphical interface facilitates in predicting location-specific downtime cost charts and allows operator companies to determine the fiscal losses for different range of downtime days and various capacities of LNG carrier. Overall, this research contributes by linking dynamic stability with operating costs through real time metocean data in Malaysian waters.

Trajectory Planning of Autonomous Trucks for Collision Avoidance With Rollover Prevention

Autonomous trucks are considered as one of the most promising developments for future commercial vehicles. However, the impact of roll dynamics, which is well known as a crucial safety factor for conventional human-driven trucks, is not well studied for the trajectory planning of autonomous trucks. In this study, a trajectory planning strategy of autonomous trucks is proposed for collision avoidance scenarios with rollover prevention. The proposed three-step planning strategy can ensure both vehicle lateral and roll stability and safety, and simultaneously preserve the optimality of the planning solutions in terms of the total traveling time and distance for the whole maneuver. Specifically, the impact of vehicle roll dynamics on the trajectory planning of autonomous trucks is studied. The effectiveness and feasibility of the proposed trajectory planning strategy are evaluated via co-simulation between Matlab/Simulink and TruckSim.

Online Kinematic Calibration for Legged Robots

This paper describes an online method to calibrate certain kinematic parameters of legged robots, including leg lengths, that can be difficult to measure offline due to dynamic deformation effects and rolling contacts. A kinematic model of the robot’s legs that depends on these parameters is used, along with measurements from joint encoders, foot contact sensors, and aninertial measurement unit (IMU) to predict the robot’s body velocity. This predicted velocity is then compared to another velocity measurement from, for example, a camera or motion capture system, and the difference between them is used to compute anupdate on the kinematic parameters. The method can be incorporated into both Kalman filter or sliding-window optimization-based state estimator. We provide a theoretical observability analysis of our method, as well as validation both in simulation and on hardware. Hardware experiments demonstrate that online kinematic calibration can significantly reduce position drift when relying on odometry.

COVID-19 hospitalizations forecasts using internet search data

As the COVID-19 spread over the globe and new variants of COVID-19 keep occurring, reliable real-time forecasts of COVID-19 hospitalizations are critical for public health decisions on medical resources allocations. This paper aims to forecast future 2 weeks national and state-level COVID-19 new hospital admissions in the United States. Our method is inspired by the strong association between public search behavior and hospitalization admissions and is extended from a previously-proposed influenza tracking model, AutoRegression with GOogle search data (ARGO). Our LASSO-penalized linear regression method efficiently combines Google search information and COVID-19 related time series information with dynamic training and rolling window prediction. Compared to other publicly available models collected from COVID-19 forecast hub, our method achieves substantial error reduction in a retrospective out-of-sample evaluation from Jan 4, 2021, to Dec 27, 2021. Overall, we showed that our method is flexible, self-correcting, robust, accurate, and interpretable, making it a potentially powerful tool to assist healthcare officials and decision making for the current and future infectious disease outbreaks.

Dynamic 3D DNA Rolling Walkers via Directional Movement on a Lipid Bilayer Supported by Au@Fe3O4 Nanoparticles for Sensitive Detection of MiRNA-16.

Currently reported polyfluorene-based fluorescence detection usually shows high background signal and low detection sensitivity. This work developed a novel three-dimensional (3D) DNA rolling walker via directional movement on a lipid bilayer (LB) supported by Au@Fe3O4 nanoparticles (NPs) in a polyfluorene-based fluorescence system so that it could achieve significantly improved detection sensitivity and almost zero-background signal detection for miRNA-16. First, the carboxyl-functionalized poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-(1,4-benzo-{2,1',3}-thiadazole)] polymer nanoparticles (c-PFBT PNPs) covalently bonded with amino-labeled single-strand CP and further hybridized with single-strand AP to prepare AP-CP-coupled c-PFBT PNP probes. Meanwhile, Au@Fe3O4 NPs were developed as efficient fluorescence quenchers and served as the matrix for assembling the LB. The resulting Au@Fe3O4@LB assembled cholesterol-labeled orbital DNA L1 and L2 and further assembled hairpins H1 and AP-CP-coupled c-PFBT PNP probes to construct DNA nanomachines. Then, the target miRNA-16 was introduced to initiate the rolling circle amplification (RCA) reaction and form dynamic DNA rolling walkers, thus releasing single-strand CP-coupled c-PFBT PNP probes. The magnetic separation effect of Au@Fe3O4 NPs made it possible to detect the fluorescence signal from the released probes, thus achieving almost zero-background signal detection for miRNA-16 with a low detection limit of 95 aM. The flexible interfaces provided by the LB endowed the DNA rolling walkers with high binding efficiency and low derailment probability, thus achieving significantly improved detection sensitivity. The developed strategy provided an attractive polyfluorene-based fluorescence platform with high-sensitivity and low-background signals.

Singularities in the rolling motion of a spherical robot

The dynamics of a spherical robot rolling on a rough support due to the movement of internal masses is studied. The possibility of paradoxical situations of two types when the equations of motion are incompatible or ambiguous is shown. The singularity of the first type is due to the unrealistic assumption of an arbitrarily large friction force during rolling. This situation does not arise in practice because the body will start sliding earlier. As for the ambiguity paradox, it has been found in numerical experiments for values of the sliding friction coefficient of the order of unity. This creates a situation of bistability when two types of movement are realistic: rolling and jumping. These general results are applied to the analysis of robot-ball dynamics with constant or variable eccentricity and moment of inertia.

Concerted Rolling and Penetration of Peptides during Membrane Binding.

Peptide binding to membranes is common and fundamental in biochemistry and biophysics and critical for applications ranging from drug delivery to the treatment of bacterial infections. However, it is largely unclear, from a theoretical point of view, what peptides of different sequences and structures share in the membrane-binding and insertion process. In this work, we analyze three prototypical membrane-binding peptides (α-helical magainin, PGLa, and β-hairpin tachyplesin) during membrane binding, using molecular details provided by Markov state modeling and microsecond-long molecular dynamics simulations. By leveraging both geometric and data-driven collective variables that capture the essential physics of the amphiphilic and cationic peptide-membrane interactions, we reveal how the slowest kinetic process of membrane binding is the dynamic rolling of the peptide from an attached to a fully bound state. These results not only add fundamental knowledge of the theory of how peptides bind to biological membranes but also open new avenues to study general peptides in more complex environments for further applications.

China’s commercial bank stock price prediction using a novel K-means-LSTM hybrid approach

China’s commercial Bank shares have become the backbone of the capital market. The prediction of a bank's stock price has been a hot topic in the investment field. However, the stock price is always unstable and non-linear, challenging the traditional statistical models. Inspired by this problem, a novel hybrid deep learning approach is proposed to improve prediction performance. By modifying the distance measurement algorithm into DTW, an improved K-means clustering algorithm is proposed to cluster out banks with similar price trends. Then those clustered stocks are used to train a long and short-term memory (LSTM) neural network model for static and dynamic stock price prediction. Besides, by transforming the output of the LSTM network into multi-step output to predict multi-time intervals at one time, the performance of the long-term forecasts is improved. Through experiments, it is found that the hybrid model performs better than the single model in generalization ability and accuracy(i.e. R-SQUARE, MAE, MSE). Moreover, the multi-step output static prediction outperforms the dynamic rolling prediction for long-term prediction. In summary, this approach can predict stock prices more accurately and help investors and companies to make more profitable decisions.

Transcriptomic analysis of OsRUS1 overexpression rice lines with rapid and dynamic leaf rolling morphology

Moderate leaf rolling helps to form the ideotype of rice. In this study, six independent OsRUS1-GFP overexpression (OsRUS1-OX) transgenic rice lines with rapid and dynamic leaf rolling phenotype in response to sunlight were constructed. However, the mechanism is unknown. Here, RNA-Seq approach was utilized to identify differentially expressed genes between flag leaves of OsRUS1-OX and wildtype under sunlight. 2920 genes were differentially expressed between OsRUS1-OX and WT, of which 1660 upregulated and 1260 downregulated. Six of the 16 genes in GO: 0009415 (response to water stimulus) were significantly upregulated in OsRUS1-OX. The differentially expressed genes between WT and OsRUS1-OX were assigned to 110 KEGG pathways. 42 of the 222 genes in KEGG pathway dosa04075 (Plant hormone signal transduction) were differentially expressed between WT and OsRUS1-OX. The identified genes in GO:0009415 and KEGG pathway dosa04075 were good candidates to explain the leaf rolling phenotype of OsRUS1-OX. The expression patterns of the 15 genes identified by RNA-Seq were verified by qRT-PCR. Based on transcriptomic and qRT-PCR analysis, a mechanism for the leaf rolling phenotype of OsRUS1-OX was proposed. The differential expression profiles between WT and OsRUS1-OX established by this study provide important insights into the molecular mechanism behind the leaf rolling phenotype of OsRUS1-OX.

Rolling, tilting and spinning spherical wheels: Analytical results using the brush theory

This paper investigates the rolling dynamics of spherical wheels using the theoretical framework provided by the brush models. The analysis is mainly conducted under the assumption of vanishing sliding inside the contact patch. Different types of kinematics are considered: simply rolling wheels, rolling and tilting, and purely spinning. For the first two cases, a complete solution is derived concerning both the steady-state and transient behaviours. Some qualitative trends for the forces and moments generated inside the contact patch are then provided when accounting for limited friction. For the case of a purely spinning spherical wheel, it is shown that steady-state conditions are never possible owing to the assumption of vanishing sliding. Moreover, it is demonstrated that the shear stresses acting inside the contact patch grow unbounded if the additional contribution relating to the deflection of the bristle is not taken into account when calculating the total sliding velocity. In this case, a stationary solution may be eventually recovered as an asymptotic distribution only by assuming limited friction inside the contact patch.

Dynamic Rolling Horizon Scheduling of Waterborne AGVs for Inter Terminal Transportation: Mathematical Modeling and Heuristic Solution

The demand for transport between terminals within port areas, known as inter terminal transportation (ITT), is increasing. This paper proposes a dynamic rolling horizon scheduling strategy for ITT using a fleet of waterborne Autonomous Guided Vessels (waterborne AGVs). The strategy is dynamic in that it can handle dynamically arriving ITT requests. Every certain period of time, transport schedules are updated according to the current vessel states, dynamic waterway transport network, and ITT requests over a future time horizon. Specifically, the dynamic scheduling problem is mathematically modeled in a rolling horizon fashion considering time windows of ITT requests, capacity limits of waterborne AGVs and load/unload service times at terminals. Considering the computational complexity for possible large scale ITT scenarios, we further propose an efficient solution approach based on improved insertion, tabu search and restart heuristics. Initial routes are first constructed by inserting new ITT requests into the previously computed routes in the rolling horizon framework. Tabu search with two types of neighborhoods are then designed to improve the initial routes. Moreover, a select-remove-insert restart procedure is activated to diversify the search space whenever necessary. A waterborne ITT network in the port of Rotterdam is considered. Comprehensive simulations based on realistic ITT dataset are run to demonstrate the effectiveness of the proposed dynamic scheduling strategy. This work could be readily used to build towards a fully autonomous waterborne ITT system. Insights that support long term strategical decisions, such as the fleet size, could also be gained from the simulations.

Sliding and Rolling Motion of a Ferro-Liquid Droplet on the Hydrophobic Surface under Magnetic Influence.

The ferro-liquid droplet manipulation on hydrophobic surfaces remains vital for various applications in biomedicine, sensors and actuators, and oil-water separation. The magnetic influence of ferro-liquid droplets on the hydrophobic surface is elucidated. The mechanisms of a newborn droplet formation under the magnetic force are explored. The sliding and rolling dynamics of the ferro-liquid droplets are assessed for the various concentrations wt % of ferro-particles. High-speed recording and a tracker program are used to evaluate the droplet sliding and translational velocities. It is demonstrated that the mode of droplet motion changes from sliding to rolling as the magnetic Bond number increases, in which case, the droplet position becomes close to the magnet surface. The translational velocity of the droplet under rolling mode increases as the ferro-particle concentration in the droplet fluid increases. A further increase of the magnetic Bond number results in the creation of a newborn droplet attached to the magnet surface.

Leaf rolling dynamics for atmospheric moisture harvesting in wheat plant as an adaptation to arid environments

Plant species surviving in the arid regions have developed novel leaf features to harvest atmospheric water. Before the collected water evaporates, it is absorbed and transported for storage within the tissues and move toward the root zone through the unique chemistry of leaf structures. Deep insights into such features reveal that similarities can be found in the wheat plant. Therefore, this study aimed to evaluate the leaf rolling dynamics among wheat genotypes and their relationships with moisture harvesting and its movement on the leaf surface. For this purpose, genotypes were characterized for leaf rolling at three distinct growth stages (tillering, booting, and spike emergence). The contact angle of leaf surface dynamics (adaxial and abaxial), water budget, and morphophysiological traits of genotypes were measured. The results indicate that leaf rolling varies from inward to twisting type among genotypes and positively affected the water use efficiency and soil moisture difference at all growth stages under normal and drought conditions. Results of wetting property (hydrophilic < 90°) of the leaf surface were positively associated with the atmospheric water collection (4–7 ml). The lower values of contact angle hysteresis (12–19°) also support this mechanism. Thus, genotypes with leaf rolling dynamics (inward rolled and twisted) and surface wettability is an efficient fog harvesting system in wheat for interception and utilization of fog water in drought-prone areas. These results can be exploited to develop self-irrigated and drought-tolerant crops.

Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground.

Getting maternal milk through nursing is vital for all newborn mammals. Despite its importance, nursing has been poorly documented in humpback whales (Megaptera novaeangliae). Nursing is difficult to observe underwater without disturbing the whales and is usually impossible to observe from a ship. We attempted to observe nursing from the calf’s perspective by placing CATS cam tags on three humpback whale calves in the Sainte Marie channel, Madagascar, Indian Ocean, during the breeding seasons. CATS cam tags are animal-borne multi-sensor tags equipped with a video camera, a hydrophone, and several auxiliary sensors (including a 3-axis accelerometer, a 3-axis magnetometer, and a depth sensor). The use of multi-sensor tags minimized potential disturbance from human presence. A total of 10.52 h of video recordings were collected with the corresponding auxiliary data. Video recordings were manually analyzed and correlated with the auxiliary data, allowing us to extract different kinematic features including the depth rate, speed, Fluke Stroke Rate (FSR), Overall Body Dynamic Acceleration (ODBA), pitch, roll, and roll rate. We found that suckling events lasted 18.8 ± 8.8 s on average (N = 34) and were performed mostly during dives. Suckling events represented 1.7% of the total observation time. During suckling, the calves were visually estimated to be at a 30–45° pitch angle relative to the midline of their mother’s body and were always observed rolling either to the right or to the left. In our auxiliary dataset, we confirmed that suckling behavior was primarily characterized by a high average absolute roll and additionally we also found that it was likely characterized by a high average FSR and a low average speed. Kinematic features were used for supervised machine learning in order to subsequently detect suckling behavior automatically. Our study is a proof of method on which future investigations can build upon. It opens new opportunities for further investigation of suckling behavior in humpback whales and the baleen whale species.

Kinematic Loggers-Development of Rugged Sensors and Recovery Systems for Field Measurements of Stone Rolling Dynamics and Impact Accelerations during Floods.

Discrete particle dynamics is one of the least understood aspects of river bedload transport, but in situ measurement of stone movement during floods poses a significant technical challenge. A promising approach to address this knowledge gap is to use sensors embedded within stones. Sensors must be waterproof and recoverable after being transported downstream and potentially buried by other sediment. To address this challenge rugged sensors (Kinematic Loggers) were developed for deployment inside stones (ranging in size from cobbles to boulders) during floods. The sensors feature a 9-axis inertial measurement unit, 3-axis high-g accelerometer, 128 MB flash memory, and a 433 MHz LoRa radio transmission module for sensor recovery. The sensors are enclosed in rugged waterproof housings for deployment in extreme conditions (i.e., bedload transport during floods). Novel relay units and drone-based recovery systems were also developed for finding the sensors after field deployments. Firmware to control the sensors and relay units was developed, as well as software for configuring the sensors and an android application for communicating with the sensors via the LoRa radio transmission module. This paper covers the technical development of the sensors, mounting them inside stones, and field recovery tests. Although designed for measurement of coarse bedload transport and particle dynamics during floods, the sensors are equally applicable for deployment in other harsh environments, such as to study landslide and rockfall dynamics.

Hydraulic control valve integrated novel semi active roll resistant interconnected suspension with vertical and roll coordinated control scheme

Though the interconnected active suspension enhances the performances of roll dynamics along with the primary functions of passive suspension, it requires an external pressurized fluid supply. Also, higher energy is required to attain the variable damping force in an active interconnected system. Therefore, this research attempts to control the vehicle roll without an external fluid supply by novel semi-active based roll-resistant interconnected suspension system (SARR-HIS). The variable damping is achieved by utilizing the pressure developed in the chambers and hydraulic control valve (HCV), while the suspension compresses. The amount of the flow passes through the HCV is controlled by a model predictive controller. In addition, GA based optimization were performed to identify the optimal passive roll-resistant hydraulic interconnected suspension (PRR-HIS) parameters. For the controller design, vehicle plant model is estimated by the simple identification method in Matlab environment. On the AMESim platform, vehicle with SARR-HIS system integrated model was built and controlled in a co-simulation environment. To assess the effectiveness of the proposed suspension and its control strategy, the anti-roll bar (ARB) integrated passive standalone suspension, optimized PRR-HIS, and proposed SARR-HIS systems are tested under C class road roughness without steer and double lane change maneuver.

Stabilization of an Inverted Pendulum on a Nonholonomic System

In this paper we investigate the problem of stabilizing the roll dynamics of a nonholonomic system that is inspired by a Chaplygin sleigh whose center of mass is at some height above the ground. The sole actuation for the extruded Chaplygin sleigh, is via the motion of an internal reaction wheel which applies a torque in the yaw direction. This torque is used to propel the Chaplygin sleigh as well as stabilize its roll. This system is motivated by the problem of the stabilization of the roll of a fish-like underwater swimmer. The dynamics of a fish-like swimmer have been shown to be similar to that of a Chaplygin sleigh. We propose a feedback control, by considering the associated linear representation due to the action of a Koopman operator on the observables. Using the Koopman operator, a constrained optimal control problem is formulated in the lifted space which we solve using model predictive control. The approach has the advantage of being systematically generalized for increased model complexity for nonholonomic systems and actuator saturation.