Roll Angle Research Articles

Experimental investigation and intelligent control of the magnus anti-rolling device for ship stability at zero speed

Under zero-speed conditions, ships are particularly susceptible to the effects of waves, which directly impact the safety of the vessel. A ship anti-rolling device based on the Magnus effect is designed to mitigate rolling motions across a full range of speeds, thereby enhancing the vessel's stability. This study presents an experimental investigation and intelligent control of Magnus anti-rolling devices aimed at enhancing ship stability at zero speed. The test setup, intelligent control algorithm, and experimental procedures specifically tailored for evaluating the Magnus anti-rolling device were designed. Following this, a comprehensive analysis was conducted to assess the effects of different cylinder geometries, swinging speeds, initial roll angles, and control methods on the anti-rolling characteristics of the device. Results demonstrate that the intelligent control method achieves an average anti-rolling efficiency of 89%. Additionally, the optimised geometric model of the Magnus anti-rolling device exhibits improved anti-rolling efficiency relative to the original model. The study confirms the stability and robustness of the intelligent Magnus anti-rolling device and suggests future research directions for practical applications aboard full-scale vessels in complex marine environments.

Superior droplet bouncing, anti-icing/anti-frosting and self-cleaning performance of an outstanding superhydrophobic PTFE coating

The prevention of ice/frosting formation is crucial in cold region for various applications. Superhydrophobic coatings are known for their excellent anti-icing/anti-frosting properties. In this study, a durable superhydrophobic PTFE coating on a stainless steel surface was fabricated with a high water contact angle of 171.4° and a low rolling angle of 1.1°. The freezing of water droplets on the coating exhibits a significantly prolonged duration of 809 s at −10 °C, representing a 25-fold increase compared to the uncoated stainless steel surface. The ice adhesion strength is reduced by 83.7%, making ice easier to remove. Anti-frosting tests show that a thinner and lower-density layer of frost formed on the PTFE coating due to its micro-nano hierarchical structure. Furthermore, the superhydrophobic PTFE coating demonstrates excellent mechanical stability, droplet bouncing dynamics and self-cleaning properties. It is anticipated that this durable superhydrophobic PTFE coating will be a candidate for anti-icing/anti-frosting and self-cleaning applications

Highly thermally conductive multifunctional graphene-based composite membrane for remarkable passive heat dissipation and robust superhydrophobicity

Graphene membrane is considered the preferred item of thermal conductivity material for wearable devices due to its unique flexibility and high thermal conductivity. However, water condensation beads are easily generated on the surface of graphene membranes under high heat and humidity operating conditions. Water condensation beads not only reduce the thermal conductivity of the membrane but may also cause damage to electronic components. To address this issue, an anti-liquid film condensation function can be obtained by spraying an alumina/multi-walled carbon nanotubes/thermoplastic elastomer composite powder (Al2O3/MWCNTs/SEBS) modified by 1H, 1H, 2H, 2H-perfluorooctyltriethoxysilane (POTS) on graphene membranes. In addition, the obtained composite films have high thermal conductivity (up to 483.1 W/m·K), good superhydrophobicity and antifouling properties, and stable physicochemical properties. The hydrophobicity angle could reach 166 ± 3.3° and the rolling angle 7 ± 2.4°. Under 300 times of bending, it can still maintain its superhydrophobic performance. Therefore, the development of graphene-based composite membrane with high thermal conductivity, hydrophobicity and an excellent water-resistant condensation bead effect is expected to provide a new thermally conductive material solution for heat dissipation in electronic components.

Proposal of a New Control System Making Use of AI Tools to Predict a Ship’s Behaviour When Approaching the Synchronism Phenomenon

In spite of the IMO’s efforts to improve the safety of intact stability on ships, synchronous rolling still causes large rolling angles, resulting in a very dangerous situation on board. The implementation of automatic tools to predict this undesirable situation has not been widely implemented. Furthermore, the safety of ship stability is not the only responsibility of people involved in the design process, so ship operators must have enough knowledge to predict and avoid these dangerous situations well in advance. Therefore, from a theoretical point of view, in the first part, this paper aims to present a valuable guiding tool for ship operators in order to predict synchronous rolling and avoid undesirable situations on board by making use of only empirical observations of the wave profile and moments. With this purpose, mathematical models are first proposed, with the ship sailing in the worst condition, i.e., with and without considering the damping factor, at zero speed and considering the influence of any pure beam and trochoidal waves. Relevant results shown provide the exact time and wave profile at which the maximum rolling angles are reached. In the second part of the paper, a new control system making use of AI tools is proposed in order to be used by ship operators on board, avoiding dangerous situations. Finally, the results are validated using a set of ship rolling simulations for the most common and representative ship loading conditions and wave periods.

Research on a Variable Universe Control Method and the Performance of Large Sprayer Active Suspension Based on an Artificial Fish Swarm Algorithm–Back Propagation Fuzzy Neural Network

In view of the typical requirements of large high-clearance sprayers, such as those operating in poor road conditions for farmland plant protection and at high operation speeds, reducing the vibration of sprayer suspension systems has become a research hotspot. In this study, the hydro-pneumatic suspension (HPS) of large high-clearance sprayers was taken as the object, and a variable universe T-S fuzzy controller with real vehicle vibration data as input was proposed to control suspension motion in real time. Different from traditional semi-active suspension, based on the characteristics of variable universe extension factors, a training method combining the artificial fish swarm algorithm and the back propagation algorithm was used to establish a fuzzy neural network controller with precise input to optimize the variable universe. Then, the time-domain and frequency-domain response characteristics of HPS were analyzed by simulating the special road conditions typical of farmland. Finally, the field performance of the sprayer equipped with the new controller was tested. The results show that the error rate of the AFSA-BP algorithm in training the FNN could be reduced to 3.9%, and compared with a passive suspension system, the T-S fuzzy controller improved the effects of spring mass acceleration, pitch angle acceleration, and roll angle acceleration by 18.3%, 23.3%, and 27.7%, respectively, verifying the effectiveness and engineering practicality of the active controller in this study.

Anti‐/Deicing Membranes with Damage Detection and Fast Healing

AbstractFlexible membrane with good anti‐wettability under giant deformation and fast healing will largely extend its adaptability and life span in anti‐/deicing application. A flexible membrane with significant dynamic water repellency and photo‐/electro‐responsive healing capability is reported, fabricated by combining the covalent grafting of fluorosilane to carbon black (F‐CB) with the optimized ablation difference between thermoplastic polyurethane (TPU) matrix and F‐CB. A rolling angle of below 5° is remained after either being stretching to 1000% strain or 2000 cycles of tensile tests at 400% strain. More importantly, multi‐scale cracks on the membrane can be diagnosed and repaired in real‐time; the healing efficiency reaches above 99% within 90 s even if completely fractured under the effect of both solar irradiation of 0.1 W cm−2 and applied voltage of 20 V; and all‐weather anti‐/deicing has the performance of an icing delay time of 323 s and an ice adhesion strength of <40 kPa, a sharp contrast to the 18 s and 1090 kPa, respectively, for bare metal surface. This work endows anti‐icing membrane with the ability of damage detection and cyclic healing, highly demanded in outdoor anti‐/deicing application that involve inevitable mechanical damages.

Stealth Aircraft Penetration Trajectory Planning in 3D Complex Dynamic Based on Radar Valley Radius and Turning Maneuver

Based on the quasi-six-degree-of-freedom flight dynamic equations, considering the changes in the elevation angle caused by an increase in the rolling angle during maneuvering turns, which leads to a rise in the radar cross-section. A computational model for the radar detection probability of aircraft in complex environments was constructed. By comprehensively considering flight parameters such as turning angle, rolling angle, Mach number, and radar power factor, this study quantitatively analyzed the influence of these factors on the radar detection probability. It revealed the variation patterns of radar detection probability under different flight conditions. The results provide theoretical support for the Radar Valley Radius and Turning Maneuver Method (RVR-TM) based on decision trees, and lay the foundation for the development of subsequent intelligent decision-making models. To further optimize the trajectory selection of aircraft in complex environments, this study combines theoretical analysis with reinforcement learning algorithms to establish an intelligent decision-making model. This model is trained using the Proximal Policy Optimization (PPO) algorithm, and through precisely defining the state space and reward functions, it accomplishes intelligent trajectory planning for stealth aircraft under radar threat scenarios.

Rolling angle measurement for carrots using computer vision and improved cyclic shift method

This paper proposed a method to measure the rolling angle for carrots. An imaging system was designed to capture the image of the cross-section located on the root–stem junction. The outer profile curve (OPC) of the cross-section was extracted and transformed into polar coordinates with the centroid serving as the origin. And a one-to-one correspondence between its polar angle and polar radius was established. Then an improved cyclic shift method (ICSM) was proposed. The ICSM was developed based on the consistent angular spacing between any two points on OPC throughout the rolling process. This addressed the issue of low efficiency. Furthermore, the additional requirements for calculation were pointed out. Finally, an experiment was conducted to measure the rolling angle of 60 carrot samples. The results show that the proposed method exhibits high accuracy and high efficiency. It provides an effective tool for full-surface image acquisition of carrots.

The influence of roll angles on unsteady aerodynamics in a canard‐configured missile

AbstractDuring the initial stage of vertical launch, a missile may exhibit an uncertain roll angle (φ) and a high angle of attack (α). This study focuses on examining the impact of roll angle variations on the flow field and the unsteady aerodynamics of a canard‐configured missile at α = 75°. Simulations were performed using the validated k‐ω SST turbulence model. The analysis encompasses the temporal development of vortices, the oscillatory characteristics of the lateral force, and the fluctuation of kinetic energy distribution within the framework of proper orthogonal decomposition (POD). The results indicate that the flow field surrounding the canard‐configured missile is characterized by inconsistent shedding cycles of Kármán‐like and canard‐separated vortices. A distinct transition zone is identified between these vortices, where vortex tearing and reconnection phenomena occur. With increasing roll angles from 0° to 45°, there is an observed shift in the dominant frequency of the lateral force from the higher frequency associated with Kármán‐like vortex shedding to the lower frequency of canard vortex shedding. The shedding frequency of Kármán‐like vortices corresponds to the harmonics of the canard vortex shedding frequency, indicative of a higher‐order harmonic resonance. The frequency of the lateral force is observed to decrease with an increase in roll angle, except in configurations lacking distinct canard‐separated vortices, which are characterized by a “+” shape. The POD analysis reveals that the majority of the fluctuation energy is concentrated in the oscillations and shedding of the canard‐separated vortices, leading to pressure fluctuations that are primarily observed on the canard and the downstream region of the canard.

Design and Development of an Air–Land Amphibious Inspection Drone for Fusion Reactor

This paper proposes a design method for a miniature air–land amphibious inspection drone (AAID) to be used in the latest compact fusion reactor discharge gap observation mission. Utilizing the amphibious function, the AAID realizes the function of crawling transportation in the narrow maintenance channel and flying observation inside the fusion reactor. To realize miniaturization, the mobile platform adopts the bionic cockroach wheel-legged system to improve the obstacle-crossing ability. The flight platform adopts an integrated rotor structure with frame and control to reduce the overall weight of the AAID. Based on the AAID dynamic model and the optimal control method, the control strategies under flight mode, hover mode and fly–crawl transition are designed, respectively. Finally, the prototype of the AAID is established, and the crawling, hovering, and fly–crawling transition control experiments are carried out, respectively. The test results show that the maximum crawling inclination of the AAID is more than 20°. The roll angle, pitch angle, and yaw angle deviation of the AAID during hovering are all less than 2°. The landing success rate of the AAID during the fly–crawl transition phase also exceeded 77%, proving the effectiveness of the structural design and dynamic control strategy.

Proposing a new control method for active stabilizer bars using an intelligent self-learning algorithm

This article’s main content is directed toward designing and applying a new control algorithm for automotive stabilizer bars. Previous studies often only used classical control algorithms or simple fuzzy algorithms to control hydraulic anti-roll systems on cars based on safety criteria. In this article, a self-learning algorithm (ANFIS) is established based on inheriting the advantages of previous algorithms. Additionally, this algorithm is modified and improved to increase the convergence of the results after the end of the steering process. Simulations show that when the self-learning solution is applied to active anti-roll bars, the roll angle value and the attenuation of the vertical force at wheels decrease significantly. In complex motion conditions (second case, v3), rollover occurs if the automobile does not have an anti-roll bar. However, roll stability and road holding ability are always ensured when applying the ANFIS algorithm to control active anti-roll bars. According to these findings, the minimum value of the vertical force at the rear wheel can be up to 1384.02 N even when the car is traveling in extremely harsh conditions (second case, v4). In addition, the response speed and convergence of values are always well-controlled when the intelligent self-learning algorithm is applied to the anti-roll control system.

Relationship between static and dynamic balance in 4-to-5-year-old preschoolers: a cross-sectional study

BackgroundBalance is crucial for physical development in preschool children. Exploring the relationship between different types of balance can help understand early physical development in children. Currently, research is mostly focused on the relationship between different types of balance in the adult population and lacks exploration of the preschool population. The aim of this study explored the relationship between static and dynamic balance in preschool children aged 4 to 5 years.MethodsA total of 128 preschool children between the ages of 4 to 5 years were selected. The following tests were conducted as they wore inertial sensors detecting their centers of mass (COM): T1, standing with eyes open; T2, standing with eyes closed; T3, standing with eyes open on foam; T4, standing with eyes closed on foam; and T5, walking on the balance beam. Static balance was measured by the angular velocity modulus (ω−T1–ω−T4) of the shaking COM, as well as the pitch angle (θ−T1–θ−T4) and roll angle (φ−T1–φ−T4) indicators in T1–T4 testing. Dynamic balance was measured by the time (t) and angular velocity modulus (ω−T5), as well as the pitch angle (θ−T5) and roll angle (φ−T5) indicators in the T5 test. The Pearson product-moment correlation coefficient was used to test the correlation between static and dynamic balance indicators.ResultsThere is no correlation between ω−T1–ω−T4 and t (P > 0.05), while ω−T1–ω−T4 and ω−T5 (r = 0.19–0.27, P < 0.05) and ω−T1–ω−T4 and θ−T5, φ−T5 (r = 0.18–0.33, P < 0.05) were weakly correlated. There is no correlation between θ−T1–θ−T4, φ−T1–φ−T4 and t (P > 0.05), while θ−T1–θ−T4, φ−T1–φ−T4, and θ−T5, φ−T5 were weakly correlated (r = 0.01–0.28, P < 0.05).ConclusionsThe relationship between static and dynamic balance in preschool children aged 4–5 years is weak. Static and dynamic balance in children needs to be intervened separately for the development of children.

Method for measuring non-stationary motion attitude based on MEMS-IMU array data fusion and adaptive filtering

The error characteristics of a typical commercial MEMS-IMU were analyzed. Using 15 ICM-42688 sensors, a 3*5 MEMS-IMU array was designed, and a weighted data fusion method based on Allan variance for the MEMS-IMU array was proposed. This effectively reduces the random measurement errors of the MEMS-IMU, providing a data foundation for the precise measurement of motion and attitude of robots, vehicles, aircraft, and other systems under low-cost conditions. The text describes a measurement method for non-stationary motion attitudes of sports vehicles based on adaptive Kalman-Mahony. Specifically, it first uses adaptive Kalman filter on array sensor data to calculate the measurement noise in real-time and adaptively adjust the filtering gain. Then, it determines the compensation coefficient of the accelerometer to the gyroscope angular velocity based on the motion state of the vehicle, and solves the attitude through complementary filtering to obtain the motion attitude quaternion. Finally, it converts it into the roll angle, pitch angle, and yaw angle of the sports vehicle. Experimental results show that the proposed MEMS-IMU array weighted data fusion method based on Allan variance has significant advantages over traditional single MEMS-IUM methods and traditional average weighting methods in reducing sensor angle random walk and zero drift instability. The proposed adaptive Kalman-Mahony attitude measurement method also shows a significant improvement in the accuracy of non-stationary motion attitude measurement compared to traditional methods.

A transparent superhydrophobic coating on wood-based panel surfaces

ABSTRACT A transparent, environmentally friendly and durable superhydrophobic coating preparation process was developed to effectively isolate water molecules in the air, aiming to reduce the use limitations of the wood-based panel substrate and to realize its improved performance in terms of water resistance, stain resistance and durability. This study employs a coating method to apply a silica sol-modified nanocellulose (CNF) and polyvinyl alcohol (PVA) solution onto a wood-based panel substrate, creating a micro-nano rough structure. Subsequently, the vapor deposition method was employed to functionalize the silanol groups on the coating surface, resulting in the formation of fluorinated alkyl groups and achieving transparent superhydrophobic wood-based panels. The water contact angle measures 152.6°, the rolling angle was 4.5°, and the coating exhibits a light transmittance of 92%. Notably, the superhydrophobicity of the coating persists even after repeated polishing paper abrasion, demonstrating excellent anti-pollution self-cleaning properties. This study is of great significance for the long-term use of wood-based panels indoors and outdoors, as well as their application in complex and high humidity environments.

Estimating ski orientation using IMUs in alpine skiing

Ski-snow interaction is the essential component of alpine skiing. To understand how a skier manipulates his ski to turn, we need to develop methods to measure the orientation of the ski throughout a complete run. Recent studies tried to use IMUs to estimate edge angle (EA) during skiing. We introduce and validate a method on how to calibrate and employ IMUs to precisely and accurately measure roll angles (RA) as a matter of changing orientation of the ski around its longitudinal axis in 3D space during skiing. Static orientation measurements on an inclined plane perfectly correlate (r2 = 1) with 3D motion capturing: RMSE = 0.18° and 0.24° respectively. Bland Altman showed a mean bias of 0.23° (95% CI: -0.16°, 0.63°) and 0.21° (95% CI: -0.3°, 0.73°). Accuracy and drift tests against constant standardised rotational velocities showed no drift behaviour over time, but RA estimation accuracy is reduced with increasing angular velocities (SD @ ±300°/s: 0.57°, max. difference from average at ±300°/s: 2.7°). During skiing on a ski ergometer the comparison of maximum RA against Vicon showed a mean bias of 0.13° (95% CI: -0.86° to 1.1°). Even though ski ergometer skiing has a similar frequency and angular velocity profile like outdoor skiing, there are more rotational degrees of freedom in outdoor skiing. The foundation is provided in this paper. To understand how a skier manipulates the ski on snow and to understand RA and EA progression during a turn in detail, further research should validate the method in the field and additionally look into RA progression within individual turns.

A novel method for measuring roll angle

The precise measurement of the spin speed of a high-speed autonomous unmanned aerial vehicle (HSA-UAV) is a key element in mastering flight stability, and the measurement of roll angle is the key to determining the accuracy of navigation control systems. We put forward a novel method for measuring roll angle. This method starts from the time–frequency domain analysis of the output signal of the geomagnetic sensor, extracts the time–frequency ridge of the time–frequency matrix (TFM) to obtain the spin speed of the HSA-UAV, and reconstructs the output signal of the geomagnetic sensor. It can calculate the roll angle when the calibration parameters of the geomagnetic sensor are unknown and have good engineering practical value. In addition, we also propose an improved nonlinear short-time Fourier transform with high-frequency resolution and a forward penalty dynamic path ridge-extraction method with frequency jump suppression to extract instantaneous frequency in the TFM.

A novel joint depth sensor calibration method without fixture for mobile robots’ navigation

AbstractCommercial mobile robots are usually equipped with multiple depth sensors that can measure the point cloud information around the robot's environment. The installation process of these sensors contains assembly error and sensor measurement error, so it is necessary to calibrate each sensor to align the point cloud. In order to obtain the sensor calibration results of commercial robots under normal working conditions, this study proposes a fixture free multi depth sensor joint calibration method that can be deployed on low‐cost embedded computing units, which efficiently aligns the point clouds of each sensor. During the calibration process, the robot is placed in the center of three upright thin plates perpendicular to the ground. 2D LIDAR depicts high‐precision contours of the upright thin plates. In the calibration process of each depth sensor, the roll angle and pitch angle of the sensor point cloud are first calibrated to make it perpendicular to the ground, and then the yaw angle and position of the point cloud are calibrated to fit the high‐precision contour of the upright thin plate. The results show that this method can be deployed on low‐cost embedded computing units, with real‐time and accurate calibration results. The convergence of calibration results can be achieved through up to 5 iterations, and the average running time is less than 120 ms. This research achievement provides a reference for multi‐sensor calibration of commercial robots.

A Study on the Influence of Unsteady Forces on the Roll Characteristics of a Submarine during Free Ascent from Great Depth

The maximum diving depth of modern submarines has always been increasing. Although this has been useful and in some cases necessary, it usually comes with some risks. For instance, when a submarine encounters an emergency situation that requires immediate ascent from great depths, the situation becomes more dangerous, especially due to its rolling characteristics. To investigate the effect of unsteady forces during free ascent motion of submarines at great depths on submarine rolling, in this study, the SST-DDES model combined with the overset grid technique was used for the numerical simulation of a submarine free ascent. Water tank experiments for free ascent were conducted to validate the numerical approach, which confirmed the reliability of the numerical method. Following this, the CFD method was employed to conduct an initial exploratory investigation into the free ascent motion of deep-submergence submarines. The free ascent motion of submarines at great depths under five different degrees of freedom combinations was studied. The computational results indicated that submarines are more prone to roll over during free ascent at great depths. At a depth six times the length of the submarine, the maximum roll angle underwater reaches 22.8°. In addition, unsteady rolling moments, lateral forces, and yawing moments have a significant effect on submarine rolling, intensifying the tendency to roll. Furthermore, it was observed that the vertical hydrodynamic attack angle β is related to the rolling stability of the submarine, such that a moderate decrease in β is beneficial for the rolling stability. The numerical calculation method and preliminary research findings can provide theoretical support for controlling the ascent motion of real submarines.

Hierarchical Structure with Microcrater Covered with Nanograss Enhancing Condensation and Its Antifrosting/Anti-Icing Performance Inspired by Euphorbia helioscopia L.

Over an extended period of evolution and natural selection, a multitude of species developed a diverse array of biological interface features with specific functions. These biological structures provide a rich source of inspiration for the design of bionic structures on superhydrophobic surfaces. Understanding the functional mechanism of plant leaves is of paramount importance for the advancement of new engineering materials and the further promotion of engineering applications of bionic research. The hierarchical structure of microcrater-covered nanograss (MCNG) on the surface of E. helioscopia L. leaf provided the inspiration for the bionic MCNG surface, which was successfully prepared on a copper substrate by hybrid laser micromachining technology and chemical etching. The combined action of texture structure and surface chemistry resulted in a contact angle of 169° ± 1° for MCNG surface droplets and a rolling angle of less than 1°. Notably, the condensation-induced adhesion force does not augment with the increase of the temperature difference, which facilitated the shedding of hot droplets from the surface. The microscope observation revealed a high density of condensed droplets on the MCNG surface and the tangible jumping behavior of the droplets. The fabricated MCNG also demonstrated excellent antifrost/anti-icing abilities in low-temperature and high-humidity environments. Finally, the study confirmed the exceptional mechanical durability and reusability of the MCNG surface through various tests, including scratch damage, sandpaper wear, water flow impact and flushing, and condensation-drying cycle tests. The nanograss can be effectively protected within the microcrater structure. This research presents a promising approach for preventing and/or removing unwanted droplets in numerous engineering applications.

Multivariate USV Motion Prediction Method Based on a Temporal Attention Weighted TCN-Bi-LSTM Model

Unmanned surface vehicle (USV)’s motion is represented by time-series data that exhibit highly nonlinear and non-stationary features, significantly influenced by environmental factors, such as wind speed and waves, when sailing on the sea. The accurate prediction of USV motion, particularly crucial parameters, such as the roll angle and pitch angle, is imperative for ensuring safe navigation. However, traditional and single prediction models often struggle with low accuracy and fail to capture the intricate spatial–temporal dependencies among multiple input variables. To address these limitations, this paper proposes a prediction approach integrating temporal convolutional network (TCN) and bi-directional long short-term memory network (Bi-LSTM) models, augmented with a temporal pattern attention (TPA) mechanism, termed the TCN-Bi-LSTM-TPA (TBT) USV motion predictor. This hybrid model effectively combines the strengths of TCN and Bi-LSTM architectures to extract long-term temporal features and bi-directional dependencies. The introduction of the TPA mechanism enhances the model’s capability to extract spatial information, crucial for understanding the intricate interplay of various motion data. By integrating the features extracted by TCN with the output of the attention mechanism, the model incorporates additional contextual information, thereby improving prediction accuracy. To evaluate the performance of the proposed model, we conducted experiments using real USV motion data and calculated four evaluation metrics: mean square error (MSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and R-squared (R2). The results demonstrate the superior accuracy of the TCN-Bi-LSTM-TPA hybrid model in predicting USV roll angle and pitch angle, validating its effectiveness in addressing the challenges of multivariate USV motion prediction.