Search

This paper proposes a novel framework for missile launch dynamics modeling and simulation, with a focus on ground-based missile launching vehicles. Our model treats the launching vehicle as a hybrid rigid-flexible multibody system, capturing spatial vibrations with the launch canister modeled as a flexible beam and other as rigid bodies, applying the linear multibody system transfer matrix method. The equations of motion of the rigid missile, with respect to the launch canister, are derived through the Newton-Euler method. The missile is equipped with sliders that interact with the guide inside the launch canister, ensuring stability and adherence to a predefined trajectory during launch. Crucially, our framework also accounts for the clearance between the slider and guide, a factor often overlooked in existing models. When the slider contacts the guide, an impact occurs, and its dynamic response is modeled by the contact impact force, which is considered an external force on the system. Acknowledging the bending characteristics of the launch canister, we propose a mathematical model for detecting contact between the slider and guide and calculating their relative position and velocity. Subsequently, we formulate coupled equations of motion for the launching vehicle and missile. Validation of our framework was conducted using experiments with simplified launch vehicle models and commercial software simulations, confirming its applicability. The simulation parameters for the comprehensive launching vehicle model are ascertained through modal testing and parameter identification. Our analysis reveals that slider-guide clearance and the introduction of an additional slider pair significantly influence missile stability and angular variation during launch dynamics. [ABSTRACT FROM AUTHOR]

Due to the intermittent contact with the wellbore, determining torque and drag for deviated wells is difficult. Most models have ignored drill string stiffness and assumed continual contact to simplify derivation. However, the accuracy of these 'soft-string' models is restricted, especially at high dogleg severities. On the other hand, most 'stiff-string' models rely on computationally intensive approaches or continuous contact assumptions. To mitigate these issues, a computationally efficient penalty-based wellbore contact algorithm has been developed based on vector calculation, which at most requires two dot products and three arithmetic operations to determine contact locations. This algorithm is incorporated into a 3D multibody dynamics (MBD) model, which utilizes rigid drill-string segments based on the Newton-Euler formulation, connected via axial, shear, torsional, and bending springs to capture drill string flexibility. This model performs simulations faster than real-time and has been validated using surface measurements from a completed well. [ABSTRACT FROM AUTHOR]

Considering the contact between robot feet and the ground is unpredictable in unstructured terrains, robots require fast and accurate contact detection capability. This paper presents a contact detection method through estimating external force that benefits from compensating friction torque and driving torque effectively. For estimating external force, a new estimation method for joint angular velocity/acceleration is proposed. Furthermore, filter parameters are selected theoretically based on the leg control model, which achieves the optimal solution of the parameters. A control compensation strategy of the low-velocity zone of the motor is also implemented for optimizing the estimation of contact force. In contrast to the classic generalized momentum method, the proposed method allows high bandwidth estimation. The proposed contact detection method and the angular velocity/acceleration estimation method using only discrete position feedback information are verified on the developed quadruped robot platform SCIT Dog. [ABSTRACT FROM AUTHOR]

Ship detection, a crucial task, relies on the traditional CFAR (Constant False Alarm Rate) algorithm. However, this algorithm is not without its limitations. Noise and clutter in radar images introduce significant variability, hampering the detection of objects on the sea surface. The algorithm's theoretically Constant False Alarm Rates are not upheld in practice, particularly when conditions change abruptly, such as with Beaufort wind strength. Moreover, the high computational cost of signal processing adversely affects the detection process's efficiency. In previous work, a four-stage methodology was designed: The first preprocessing stage consisted of image enhancement by applying convolutions. Labeling and training were performed in the second stage using the Faster R-CNN architecture. In the third stage, model tuning was accomplished by adjusting the weight initialization and optimizer hyperparameters. Finally, object filtering was performed to retrieve only persistent objects. This work focuses on designing a specific methodology for ship detection in the Peruvian coast using commercial radar images. We introduce two key improvements: automatic cropping and a labeling interface. Using artificial intelligence techniques in automatic cropping leads to more precise edge extraction, improving the accuracy of object cropping. On the other hand, the developed labeling interface facilitates a comparative analysis of persistence in three consecutive rounds, significantly reducing the labeling times. These enhancements increase the labeling efficiency and enhance the learning of the detection model. A dataset consisting of 60 radar images is used for the experiments. Two classes of objects are considered, and cross-validation is applied in the training and validation models. The results yield a value of 0.0372 for the cost function, a recovery rate of 94.5%, and an accuracy rate of 95.1%, respectively. This work demonstrates that the proposed methodology can generate a high-performance model for contact detection in commercial radar images. [ABSTRACT FROM AUTHOR]

In many geological hazards, such as landslides, a large number of irregular blocks start moving. Their interaction on the way down renders prediction of disaster scopes difficult. To study this process and to provide a novel method for validation and calibration of numerical tools for its simulation, a cube movement test is designed. The goal of this research is to obtain patterns of movement of cubes, starting from different initial stacking arrangements. Cubes of four sizes are inserted into a hollow cylinder. Their distribution after lifting the cylinder is determined. Three categories of tests refer to three different strategies of filling the cubes into the cylinder. In order to simulate cube movement tests, a numerical tool is developed in the framework of the continuum–discontinuum element method (CDEM). The contact between the individual cubes is modeled by the contact‐pairs‐based algorithm. Both the contact state and type are detected by determining the half‐space relation between contact pairs. The final positions of the cubes are strongly related to their initial arrangement. The latter is different in every test, even if the same strategy is used to fill the cubes into the cylinder. It is found that at least 20 experiments/simulations are required to obtain statistically representative results. The new test provides valuable data for validation of numerical tools used for the simulation of mass movement processes. The proposed numerical method captures the complicated movements of blocks. [ABSTRACT FROM AUTHOR]

Compared with the single pin crawler, a double pin caterpillar platform has lower vibration and noise, which is widely used in tracked vehicles. However, its dynamical model is more complex due to its high degrees of freedom and laborious contact detection involved. It is significant to develop an accurate and efficient contact algorithm between tracks and wheels. In this paper, the profiles of the track connector and the tooth groove are discretized into several arc surfaces. The contact between them is characterized as convex and concave. Accordingly, a general mathematical description of the tooth profile is established to describe the real tooth groove geometry. Then a generalized cylindrical contact model is developed to evaluate forces. In the contact detection process, the local frames of the sprocket and tooth groove are employed, resulting in the vector quantities and coordinate transformations describing the contact arc surfaces constantly. This approach can facilitate programming and effectively improve calculation efficiency. Subsequently, a field test was performed to verify the correctness of the dynamical model. To reduce the wear of the sprocket, different cases are simulated, and a reasonable radius of the rubber ring is proposed. [ABSTRACT FROM AUTHOR]

Ship detection, a crucial task, relies on the traditional CFAR (Constant False Alarm Rate) algorithm. However, this algorithm is not without its limitations. Noise and clutter in radar images introduce significant variability, hampering the detection of objects on the sea surface. The algorithm’s theoretically Constant False Alarm Rates are not upheld in practice, particularly when conditions change abruptly, such as with Beaufort wind strength. Moreover, the high computational cost of signal processing adversely affects the detection process’s efficiency. In previous work, a four-stage methodology was designed: The first preprocessing stage consisted of image enhancement by applying convolutions. Labeling and training were performed in the second stage using the Faster R-CNN architecture. In the third stage, model tuning was accomplished by adjusting the weight initialization and optimizer hyperparameters. Finally, object filtering was performed to retrieve only persistent objects. This work focuses on designing a specific methodology for ship detection in the Peruvian coast using commercial radar images. We introduce two key improvements: automatic cropping and a labeling interface. Using artificial intelligence techniques in automatic cropping leads to more precise edge extraction, improving the accuracy of object cropping. On the other hand, the developed labeling interface facilitates a comparative analysis of persistence in three consecutive rounds, significantly reducing the labeling times. These enhancements increase the labeling efficiency and enhance the learning of the detection model. A dataset consisting of 60 radar images is used for the experiments. Two classes of objects are considered, and cross-validation is applied in the training and validation models. The results yield a value of 0.0372 for the cost function, a recovery rate of 94.5%, and an accuracy rate of 95.1%, respectively. This work demonstrates that the proposed methodology can generate a high-performance model for contact detection in commercial radar images.

Introduction: Poor patellar tracking can result in painful contact pressures, patella subluxation, or dislocation. The use of musculoskeletal models and simulations in orthopedic surgeries allows for objective predictions of post-treatment function, empowering clinicians to explore diverse treatment options for patients. Although a promising approach for managing knee surgeries, the high computational cost of the Finite Element Method hampers its clinical usability. In anticipation of minimal elastic deformations in the involved bodies, the exploration of the Multibody Dynamics approach emerged as a viable solution, providing a computationally efficient methodology to address clinical concerns related to the knee joint.Methods: This work, with a focus on high-performance computing, achieved the simulation of the patellofemoral joint through rigid-body multibody dynamics formulations. A comparison was made between two collision detection algorithms employed in the simulation of contact between the patellar and femoral implants: a generic mesh-to-mesh collision detection algorithm, which identifies potential collisions between bodies by checking for proximity or overlap between their discretized mesh surface elements, and an analytical contact algorithm, which uses a mathematical model to provide closed-form solutions for specific contact problems, but cannot handle arbitrary geometries. In addition, different digital twins (3D model geometries) of the femoral implant were compared.Results: Computational efficiency was considered, and histories of position, orientation, and contact force of the patella during the motion were compared with experimental measurements obtained from a sensorized 3D-printed test bench under pathological and treatment scenarios. The best results were achieved through a purely analytical contact detection algorithm, allowing for clinical usability and optimization of clinical outcomes.

Bearings are mechanical components designed to restrict the relative rotary motion between moving parts and transmit loads with low friction. Their performance directly impacts the durability, efficiency and reliability of various machinery. Therefore, bearing failures can lead to economic costs, repair/stoppage times, accidents and regulatory compliance issues. In the context of Industry 4.0, the development of detailed and reliable computational models for simulating bearings' dynamics plays a crucial role in establishing digital twins and implementing advanced predictive maintenance strategies. This work focuses on modelling radial-loaded deep groove ball bearings under the multibody systems dynamics framework and the components of the bearing (inner and outer rings, rolling elements, and cage) are treated as separate bodies. A smooth contact approach is utilised to characterise the contact/impact phenomena, providing flexibility and efficiency in monitoring the whole contact event. In this sense, suitable normal and friction contact force models are used to describe those interactions between the contacting bodies. The main contribution of this work relies on the modelling strategies to represent the cage/rolling element interaction. Having that in mind, several multibody models of radial-loaded deep groove ball bearings are developed considering different modelling assumptions, resulting in dynamic analyses with various levels of complexity. The underlying simplifications are described, and their main advantages and shortcomings are discussed. The simulation results demonstrated the significant impact of accurately selecting the modelling parameters. The promising results of this study pave the way for future investigations, extending to other geometries of rolling contact bearings and working conditions. [ABSTRACT FROM AUTHOR]

Several methods exist to detect and distinguish collisions of robotic systems with their environment, since this information is a critical dependency of many tasks. These methods are prevalently based on thresholds in combination with filters, models, or offline trained machine learning models. To improve the adaptation and thereby enable a more autonomous operation of robots in new environments, this work evaluates the applicability of an incremental learning approach. The method addresses online learning and recognition of motion and contact episodes of robotic systems from proprioceptive sensor data using machine learning. The objective is to learn new category templates representing previously encountered situations of the actuators and improve them based on newly gathered similar data. This is achieved using an artificial neural network based on adaptive resonance theory (ART). The input samples from the robot's actuator measurements are preprocessed into frequency spectra. This enables the ART neural network to learn incrementally recurring episodic patterns from these preprocessed data. An evaluation based on preliminary experimental data from a grasping motion of a humanoid robot's arm encountering contacts is presented and suggests that this is a promising approach. [ABSTRACT FROM AUTHOR]

Concrete can be regarded as a composite material comprising aggregates, cement mortar, and an interfacial transition zone (ITZ) at the mesoscale. The mechanical properties and durability of concrete are influenced by the properties of these three phases. The establishment of a mesoscale model of concrete and the execution of numerical simulations constitute an efficacious research method. It is an efficacious method to research concrete by establishing the mesoscale model of concrete and executing numerical simulations. By this method, the influence of an aggregate shape on concrete performance can be studied. This paper presents a systematic review of mesoscale modeling methods for concrete, with a focus on three aspects: the aggregate modeling method, the collision detection algorithm, and the particle-packing algorithm. The principal processes, advantages, and disadvantages of various methods are discussed for each aspect. The paper concludes by highlighting current challenges in the mesoscale modeling of concrete. [ABSTRACT FROM AUTHOR]

Reliable foot-to-ground contact state detection is crucial for the locomotion control of quadruped robots in unstructured environments. To improve the reliability and accuracy of contact detection for quadruped robots, a detection approach based on the probabilistic contact model with multi-information fusion is presented to detect the actual contact states of robotic feet with the ground. Moreover, a relevant control strategy to address unexpected early and delayed contacts is planned. The approach combines the internal state information of the robot with the measurements from external sensors mounted on the legs and feet of the prototype. The overall contact states are obtained by the classification of the model-based predicted probabilities. The control strategy for unexpected foot-to-ground contacts can correct the control actions of each leg of the robot to traverse cluttered environments by changing the contact state. The probabilistic model parameters are determined by testing on the single-leg experimental platform. The experiments are conducted on the experimental prototype, and results validate the contact detection and control strategy for unexpected contacts in unstructured terrains during walking and trotting. Compared with the body orientation under the time-based control method regardless of terrain, the root mean square errors of roll, pitch, and yaw respectively decreased by 60.07%, 54.73%, and 64.50% during walking and 73.40%, 61.49%, and 61.48% during trotting. [ABSTRACT FROM AUTHOR]

This review paper provides a literature survey of collaborative robots, or cobots, and their use in various industries. Cobots have gained popularity due to their ability to work with humans in a safe manner. The paper covers different aspects of cobots, including their design, control strategies, safety features, and human–robot interaction. The paper starts with a brief history and evolution of cobots, followed by a review of different control strategies and Safety features such as collision detection and avoidance, and safety-rated sensors are also examined. Further to this, a systematic review of Ergonomics is also taken into account. Additionally, the paper explores the challenges and opportunities presented by cobot's technology, including the need for standards and regulations, the impact on employment, and the potential benefits to industry. The latest research in human–robot interaction is also discussed. Finally, the paper highlights current limitations of cobot's technology and the need for further research to address technical and ethical challenges. This synthesis document is an invaluable resource for both academics and professionals interested while developing and application of cobot's technology. [ABSTRACT FROM AUTHOR]

The contact method based on flexible actuator is safe and efficient for the detumbling task of space nutation targets. In this paper, a detumbling system with a rotatable flexible rod as the end effector is proposed to reduce the rotational angular velocity of the target by contacting the solar sail panel of the target with the flexible rod, and the selection of the initial relative position and attitude is discussed. First, the contact dynamics model of a rotatable flexible rod considering the nonlinear coupling term is derived using the floating frame of reference formulation and validated for comparison. Next, in order to ensure the accuracy of contact detection in the contact model, it is proposed to transform the contact detection of flexible bodies into a nonlinear programming problem and solve it using the quantum particle swarm optimization. Finally, the simulation results show that the detumbling system can effectively reduce the triaxial angular velocity of the nutation target. At the same time, in order to improve the detumbling effect, the contact point should not choose the midpoint of the sail edge in the conventional way, and the relative position and attitude of the end effector before contact must be reasonably set. [ABSTRACT FROM AUTHOR]

When studying hand kinematics, it is key to differentiate between free motion and manipulation. This differentiation can be achieved using pressure sensors or through visual analysis in the absence of sensors. Certain data gloves, such as the CyberGlove II, allow recording hand kinematics with good accuracy when properly calibrated. Other gloves, such as the Virtual Motion Glove 30 (VMG30), are also equipped with pressure sensors to detect object contact. The aim of this study is to perform a technical validation to evaluate the feasibility of using virtual reality gloves with pressure sensors such as the VMG30 for hand kinematics characterization during product manipulation, testing its accuracy for motion recording when compared with CyberGlove as well as its ability to differentiate between free motion and manipulation using its pressure sensors in comparison to visual analysis. Firstly, both data gloves were calibrated using a specific protocol developed by the research group. Then, the active ranges of motion of 16 hand joints angles were recorded in three participants using both gloves and compared using repeated measures ANOVAs. The detection capability of pressure sensors was compared to visual analysis in two participants while performing six tasks involving product manipulation. The results revealed that kinematic data recordings from the VMG30 were less accurate than those from the CyberGlove. Furthermore, the pressure sensors did not provide additional precision with respect to the visual analysis technique. In fact, several pressure sensors were rarely activated, and the distribution of pressure sensors within the glove was questioned. Current available gloves such as the VMG30 would require design improvements to fit the requirements for kinematics characterization during product manipulation. The pressure sensors should have higher sensitivity, the pressure sensor's location should comprise the palm, glove fit should be improved, and its overall stiffness should be reduced. [ABSTRACT FROM AUTHOR]

Research on the interaction between users and their environment has been conducted in various fields, including human activity recognition (HAR), human-scene interaction (HSI), computer graphics (CG), and virtual reality (VR). Typically, the interaction process commences with a human body part’s movement and involves contact with a target object or the environment. The choice of the body part to make contact depends on the interaction’s purpose and affordance, making contact a fundamental aspect of interaction. However, detecting the specific body parts in contact, especially in the context of 3D motion and complex environments, poses computational challenges. To address this challenge, this study proposes a method for contact detection using motion data. The motion data utilized in this study are limited to actions feasible in an office environment. Since contact states of different body parts are independent, the proposed method comprises two distinct models: a feature model generating common features for each body part and a part model recognizing the contact state of each body part. The feature model employs a bidirectional long-short term memory(Bi-LSTM) structure to capture the sequential nature of motion data, ensuring the incorporation of continuous data characteristics. In contrast, the part model employs separate weights optimized for each body part within the deep neural network. Experimental results demonstrate the proposed method’s high accuracy, recall, and precision, with values of 0.99, 0.97, and 0.95, respectively.

This paper presents a new method for detecting contact between polygonal particles in the beam‐particle model. The main objective is to propose a robust and efficient algorithm capable of efficiently detecting contact between particles and increasing accuracy when complex particle shapes are used. This newly developed algorithm is based on a multi‐circle approach, where a set of circles is used to describe the shape of each particle. To validate and verify the algorithm, the developed approach is compared to the polygonal approach and to analytical results. For this purpose, several examples dealing with contact problems were performed. The obtained results show that the proposed contact detection procedure has the potential to efficiently detect the contact between two‐dimensional particles of complex shapes and provides a faster way to detect contact compared to the polygonal approach. [ABSTRACT FROM AUTHOR]

Purpose: Commercially available microtechnology devices containing accelerometers, gyroscopes, magnetometers, and global positioning technology have been widely used to quantify the demands of rugby union. This study investigated whether data derived from wearable microsensors can be used to develop an algorithm that automatically detects scrum events in rugby union training and match play. Methods: Data were collected from 30 elite rugby players wearing a Catapult OptimEye S5 (Catapult Sports, Melbourne, Australia) microtechnology device during a series of competitive matches (n = 46) and training sessions (n = 51). A total of 97 files were required to "train" an algorithm to automatically detect scrum events using random forest machine learning. A further 310 files from training (n = 167) and match-play (n = 143) sessions were used to validate the algorithm's performance. Results: Across all positions (front row, second row, and back row), the algorithm demonstrated good sensitivity (91%) and specificity (91%) for training and match-play events when the confidence level of the random forest was set to 50%. Generally, the algorithm had better accuracy for match-play events (93.6%) than for training events (87.6%). Conclusions: The scrum algorithm was able to accurately detect scrum events for front-row, second-row, and back-row positions. However, for optimal results, practitioners are advised to use the recommended confidence level for each position to limit false positives. Scrum algorithm detection was better with scrums involving ≥5 players and is therefore unlikely to be suitable for scrums involving 3 players (eg, rugby sevens). Additional contact- and collision-detection algorithms are required to fully quantify rugby union demands. [ABSTRACT FROM AUTHOR]

The major obstacle for the application of discontinuous deformation analysis (DDA) in engineering problems is the high computational cost and poor efficiency. In this paper, the main algorithms of disk‐based DDA are redesigned and implemented on graphics processing unit (GPU) to improve its performance. First, a contact pair‐wise scheme is proposed to assemble the stiffness matrix on GPU. Second, a buffer strategy and a GPU version of grid‐based contact detection algorithm are developed to improve the efficiency of contact detection. Third, for solving the simultaneous equations, two iterative methods are considered along with the direct solver method. The parallel performances of proposed strategies are tested and compared with the CPU counterparts. The results show that the maximum speedup ratio is 14 for the assembly of the stiffness matrix and 215 for contact detection. The speedup ratio for solving simultaneous equations depends on several factors, and the preconditioned conjugate gradients method (pcg) is suggested. Finally, the effectiveness and performance of the proposed GPU accelerated disk‐based DDA is further demonstrated by several examples, one of which consisted of over 500,000 particles. The results show that the proposed method can achieve a satisfactory speedup ratio, and is ready for large‐scale problems. [ABSTRACT FROM AUTHOR]

While numerical physical models of contact mechanics have become increasingly prevalent, the implementation of these models to efficiently resolve geometric contact with a robust contact search strategy remains lacking. Our research endeavors to address this gap by introducing a comprehensive solution with an exact geometric contact mechanics algorithm for thin shell finite elements with an explicit time scheme. The method has several key features, including precise geometrical resolution of self-contact interactions enabled by a sub-time-step marching method, adaptive data structures to minimize computational overhead, and a dedicated parallelization implementation with load-balancing capability. An efficient detection algorithm is implemented to reduce the natural polynomial time complexity of the problem by decomposing it into two phases: global and local phase contact detection. The impact equations are then applied to resolve the contact event by enforcing the conservation of kinematic energy and momentum. This contact algorithm is fully integrated with the MPI-based parallelization of the thin-shell finite element solver to ensure even load-balancing. The robustness and correctness of the algorithm is demonstrated in three numerical studies. Additionally, a strong scaling study showcases the scalability of the parallelization associated with the algorithm. • A geometric exact contact algorithm for explicit thin-shell mechanics is developed. • The parallel contact algorithm reduces search load with a two-phase detection method. • The parallel contact search uses a strong communication pattern for load balancing. [ABSTRACT FROM AUTHOR]

The linked cell method is widely used in the discrete element method (DEM) to detect contact between particles because of its high efficiency for uniform particles. However, the efficiency is reduced for polydisperse particles which are common in nature and engineering applications and have a wide size range. In this paper, a hierarchical linked cell method based on scale-proportional multi-level DEM grids is developed to improve the efficiency for polydisperse particles. The performance of the hierarchical linked cell method is verified by simulating different polydisperse particles. The results show that the hierarchical linked cell method can significantly reduce the elapsed CPU time of contact detection in all simulated cases. The scale proportion and the number of levels of the DEM grids are found to be two important parameters influencing the efficiency improvement. The elapsed CPU time decreases as the scale proportion decreases or as the number of levels increases. For a given scale proportion, the optimal number of levels to achieve maximum efficiency should satisfy two conditions: (1) the grid cell granularity is less than 10; (2) the exponential decrease of the grid cell granularity with the number of levels is broken. [Display omitted] • A hierarchical linked cell method based on scale-proportional multi-level DEM grids is developed. • Improvement in efficiency of contact detection for polydisperse particles is demonstrated. • Effects of scale proportion and number of levels on efficiency improvement are investigated. • Standards for determining optimal number of levels are provided. [ABSTRACT FROM AUTHOR]

Interactions between irregular particles and structures always exist in the natural environment and industrial production process. For the desired simulation into the dynamic behaviors of arbitrarily shaped particles in complex structures, a general polygon mesh discrete element method (DEM) is developed based on the general energy-conserving contact theory. Within this method, a complete normal contact model for a contact pair with a complex contact region is proposed when the elastic strain energy density is utilized to specify a contact energy function. Since the shape of both complex particles and structures are uniformly constructed by polygon meshes, a unified contact detection implementation performed in this method is introduced in detail. This proposed method is characterized by the universal and uniform models of shape construction, contact detection, and contact force calculation for both particle-particle contact pairs and particle-structure contact pairs. To qualitatively demonstrate the conservation and robustness of the method, a set of validations or simulations considering the differently shaped particles, such as convex particles, concave particles, and particles with surface asperities, are applied. It is concluded from these validations or simulations that the general polygon mesh DEM and the corresponding proposed models are valid tools for research into the behavior of granular materials in complex structures. [ABSTRACT FROM AUTHOR]

• A rigid multibody dynamic model of the stacked satellite system is established. • A contact detection algorithm is proposed based on convex optimization. • Three contact-free releasing approaches for the system are proposed and compared. Stacked satellites have a promising application in aerospace engineering for the merits of high launch efficiency and networking capability. As one of the key technical points, releasing tens or even hundreds of satellites from the stacked state in a simple and contact-free manner is of importance. In this paper, the contact-free release dynamics of tens of stacked satellites is studied with only the initial multiaxial rotations of the system. First of all, a rigid multibody dynamic model of the stacked satellite system is established via the natural coordinate formulation (NCF). The NCF modeling scheme is able to describe the large overall motions of the satellites without any singularity and makes it possible to simplify the varying constraints between the satellites. Then, the orbital dynamics of the stacked satellite system is derived via coordinate transformation by taking the Coriolis forces, centrifugal forces, and gravity gradient into consideration. In order to rapidly and accurately detect the possible contact between satellites, a convex optimization model for minimum distance computation is proposed by using a hyperelliptic approximation for a cubic satellite. Finally, a benchmark example is given to validate the contact detection algorithm and three release dynamic cases for the stacked satellites are presented to demonstrate the effectiveness of the contact-free releasing approach with multiaxial rotations. [ABSTRACT FROM AUTHOR]

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents a geometrical modelling principle for the modelling of yarns at the fibre level. The woven and the knitted textile structures are built of yarns, which on the other side, are fibrous assemblies. In many yarn and fabric modelling works, yarns are considered as a single line element; however, most yarns are composed of a number of staple or filament fibres. It is then very important to understand the yarn at the micro level for a better understanding, production and application of the above structures. The current paper aims to present the modelling and implementation of yarn structures at the fibre level using the algorithmic geometrical modelling principle. The research work uses basic assumptions for the building of the models and various implementation issues, connected with the proper representation of the single multi-filament yarns, plied yarns and finally the staple fibre yarns. Except for visualization, the generated yarn models are prepared as a basis for mechanical, thermal, fluid flow and other simulations of textile structures using FEM, CFD and other numerical tools. [ABSTRACT FROM AUTHOR]

Sampling asteroid soil is one of the main tasks of asteroid exploration projects. The dynamic analysis for sampling with a flexible brush is of great interest in aerospace engineering. It is a typical dynamic problem of multi-body systems, including the flexibility of structure, granular material, the contact impact among the rigid bodies, flexible bodies, and granular matters, as well as the contact detection algorithm. To solve such a problem, this paper presents a strong coupling modelling method for the rigid bodies and the large deformed beams in interaction with the granular matter to simulate the sampling process. The absolute nodal coordinate (ANCF) Euler–Bernoulli beam element is adopted to discretize the flexible beams, while the motions of the rigid bodies and the particles are described by the Cartesian coordinates. A multi-level contact detection method is proposed to improve the simulation efficiency. The nonlinear continuous impact force model and velocity-based friction model are employed to describe the normal contact force and the tangential friction force, respectively. The coupling dynamic equations are solved simultaneously to achieve high precision. The dynamic model is verified via comparison with the commercial software on a benchmark problem. Finally, the dynamic performance of the flexible brush sampling mechanism is investigated, and the effects of structural parameters on sampling results are analysed. [ABSTRACT FROM AUTHOR]

Concrete can be regarded as a composite material comprising aggregates, cement mortar, and an interfacial transition zone (ITZ) at the mesoscale. The mechanical properties and durability of concrete are influenced by the properties of these three phases. The establishment of a mesoscale model of concrete and the execution of numerical simulations constitute an efficacious research method. It is an efficacious method to research concrete by establishing the mesoscale model of concrete and executing numerical simulations. By this method, the influence of an aggregate shape on concrete performance can be studied. This paper presents a systematic review of mesoscale modeling methods for concrete, with a focus on three aspects: the aggregate modeling method, the collision detection algorithm, and the particle-packing algorithm. The principal processes, advantages, and disadvantages of various methods are discussed for each aspect. The paper concludes by highlighting current challenges in the mesoscale modeling of concrete.

Accurate and fast contact detection between a robot manipulator and objects is crucial for safe robot–object and human–robot interactions. Traditional collision detection techniques relied on force–torque sensors and Columb friction cone estimation. However, the strain gauges used in the conventional force sensors require low-noise and high-precision electronics to deliver the signal to the final user. The Signal-to-Noise Ratio (SNR) in these devices is still an issue in light contact detection. On the other hand, the Eccentric Rotating Mass (ERM) motors are very sensitive to subtle touch as their vibrating resonant state loses immediately. The vibration, in this case, plays a core role in triggering the tactile event. This project's primary goal is to use generated and received vibrations to establish the scope of object properties that can be obtained through low-frequency generation on one end and Fourier analysis of the accelerometer data on the other end. The main idea behind the system is the phenomenon of change in vibration propagation patterns depending on the grip properties. Moreover, the project's original aim is to gather enough information on vibration feedback on objects of various properties and compare them. These data sets are further analyzed in terms of frequency and applied grip force correlations in order to prepare the ground for pattern extraction and recognition based on the physical properties of an object. [ABSTRACT FROM AUTHOR]

A fast direct search (FDS) algorithm is presented to increase the efficiency of contact detection for convex polygonal and polyhedral particles. All contact types are detected using only a small subset of these contact types: vertex-to-edge for polygons while vertex-to-face and edge-to-edge for polyhedra. First, an initial contact list is generated. Then in subsequent steps the contact list is updated by checking only local boundaries of the blocks and their separation. An exclusion algorithm is applied to avoid unnecessary examination for particles that are near but not-in-contact. The benchmark tests show that the FDS produces significant speed-up in various cases.

A fast direct search (FDS) algorithm is presented to increase the efficiency of contact detection for convex polygonal and polyhedral particles. All contact types are detected using only a small subset of these contact types: vertex-to-edge for polygons while vertex-to-face and edge-to-edge for polyhedra. First, an initial contact list is generated. Then in subsequent steps the contact list is updated by checking only local boundaries of the blocks and their separation. An exclusion algorithm is applied to avoid unnecessary examination for particles that are near but not-in-contact. The benchmark tests show that the FDS produces significant speed-up in various cases.

In this paper we introduce the surface of revolution discrete element method (SR-DEM) for simulating systems of axi-symmetric, non-spherical particles with a closed surface of revolution. Due to the cylindrical symmetry of a surface of revolution, the geometry of any cross-section about the axis of rotation remains constant. Exploiting this geometric feature, we propose a node-to-cross-section contact algorithm to efficiently detect contact between particles with a surface of revolution. Within the SR-DEM, the contact algorithm operates in a master–handler fashion: the master particle is approximated by its surface nodes, while the handler particle is represented by a signed distance field of the cross-section about the axis of rotation. This hybrid formulation in both 2D and 3D space enables efficient contact calculations with a relatively simple implementation with a low computational cost. The SR-DEM is validated with various test cases, including particle–particle collisions, particle–wall collisions, a granular packing in a cylindrical container, and the motion of tablets in a rotating drum. Finally, we propose a straightforward approach to determine the optimal surface resolution of a non-spherical particle by increasing the number of surface nodes until the bulk properties characterizing the system converge. [Display omitted] • Node-to-cross-section algorithm to handle contacts between axi-symmetric particles. • Very efficient contact detection if the cross-section of the particles consists of few curves. • The algorithm is validated with various test-cases. • A strategy is presented to find the optimal resolution of a node-based particle surface. [ABSTRACT FROM AUTHOR]

• Propose a comprehensive framework for accuracy analysis of deployable structures. • Flexibility, dimensional deviations, joint clearances, and loads are all considered. • Propose a linear-complementarity-based method to handle the joint clearance problem. • Avoid searching for pre-categorized contact configurations in the clearance problem. • The proposed method is validated by simulations and practical experiments. The surface accuracy of the deployable structure is crucial in determining the electromagnetic performance of the large satellite antenna. This paper proposes a comprehensive accuracy analysis framework for deployable structures considering clearances of spatial joints, geometric deviations, elastic deformations, external loads, and preloads, all of which can affect surface accuracy during the assembly process. Surface accuracy is calculated by combining the global equilibrium analysis of the deployable structure with the local equilibrium analysis of clearance-affected joints. First, a global elastostatic equilibrium analysis of the deployable structure is performed based on a unified mathematical formulation that describes the elasticity of beams and joints. Then, the local equilibrium analysis for the clearance-affected joints is transformed into a quadratic optimization problem through a linear-complementarity-based method. This method avoids the necessity for a combinatorial search for several traditional discontinuous contact configurations. Considering both global and local equilibrium in iterative analysis, the surface accuracy of the antenna is calculated. This integration avoids prior artificial assumptions about contact configurations of the joints. Finally, the proposed method is validated by comparing it with simulations and experimental results. [ABSTRACT FROM AUTHOR]

Malfunctioning satellites are generally non-cooperative tumbling objects. Due to their complex tumbling motion, it is essential to stabilize the target within an acceptable rotating range in the pre-capture phase. In contrast to contactless methods, contact methods based on flexible devices are efficient and can generate sufficient operating torque through flexible contact. However, accurate dynamic analysis of the operation is challenging because of two limitations. It is difficult to obtain a high-efficiency description of the large deformation arising from the operating process. Moreover, the contact between a flexible device and a tumbling object is hard to detect efficiently. This paper proposes a method for detumbling a free-floating rotating satellite; it uses a flexible rod to contact the solar array of the target. The absolute nodal coordinate formulation is first applied to a rod-contact detumbling model in simulation to describe the large deformation of the rod precisely with a low computational burden. Next, a two-step method to detect the contact is employed to pinpoint the contact point and speed up the simulation: coarse detection in the contactless phase and fine detection in the contact phase. Finally, the feasibility of the contact detumbling method is verified. In addition, through further analysis of the contact process, some characteristics of this kind of strategy are studied for the first time. [ABSTRACT FROM AUTHOR]

X-ray computed tomography (XCT) is regularly employed in geomechanics to non-destructively measure the solid and pore fractions of soil and rock from reconstructed 3D images. With the increasing availability of high-resolution XCT imaging systems, researchers now seek to measure microfabric parameters such as the number and area of interparticle contacts, which can then be used to inform soil behaviour modelling techniques. However, recent research has evidenced that conventional image processing methods consistently overestimate the number and area of interparticle contacts, mainly due to acquisition-driven image artefacts. The present study seeks to address this issue by systematically assessing the role of XCT acquisition parameters in the accurate detection of interparticle contacts. To this end, synchrotron XCT has been applied to a hexagonal close-packed arrangement of glass pellets with and without a prescribed separation between lattice layers. Different values for the number of projections, exposure time, and rotation range have been evaluated. Conventional global grey value thresholding and novel U-Net segmentation methods have been assessed, followed by local refinements at the presumptive contacts, as per recently proposed contact detection routines. The effect of the different acquisition set-ups and segmentation techniques on contact detection performance is presented and discussed, and optimised workflows are proposed. [ABSTRACT FROM AUTHOR]

Contact detection algorithms based on a Common Plane (CP) are among the most used and investigated, despite not being the most optimal when generating a CP and thus detecting the existence of contact between particles. The generation of the CP is quite expensive in computational terms, for which some algorithms seek to check a possibility of contact between them quickly; and then verify it. For these cases, there are algorithms such as the Shortest Link Method (SLM) that efficiently generate a CP and quickly verify the existence of contact between particles. However, this algorithm has some shortcomings. The main reason for this research is to create a new algorithm based on SLM that can work without its disadvantages. [ABSTRACT FROM AUTHOR]

Space manipulator is a key mechanism for on‑orbit inspection outside capsule and assisted astronaut extravehicular activities. In order to ensure the safety and efficiency of the whole process of manipulator operation, the motion process of on‑orbit operation needs to be planned in advance on the ground to generate motion control commands, and then the motion control commands are verified by digital simulation and deduction. Because of such problems, this paper mainly designs the ground simulation verification framework from the motion space limitation, motion speed limitation and joint torque limitation, proposes a simulation verification strategy based on kinematics and dynamics modeling and analysis of the relationship between motion space and collision, and gives the calculation methods of joint motion, joint torque and contact safety distance, as well as the criteria of over limit detection and risk judgment. Finally, through joint position overrun detection, velocity overrun detection, torque overrun detection, contact detection and safety distance calculation, the control command of space manipulator is effectively verified by ground simulation experiment. [ABSTRACT FROM AUTHOR]

This work reviews the main techniques to model dynamical systems with contact-impact events. Regularized and non-smooth formulations are considered, wherein the fundamental features associated with each approach are analyzed. A brief description of contact dynamics is presented, and an overview of the state-of-the-art of the main aspects related to the contact dynamics discipline is provided. This paper ends by identifying gaps in the current techniques and prospects for future research in the field of contact mechanics in multibody dynamics. [ABSTRACT FROM AUTHOR]

Foot contact detection is critical for legged robot running control using state machine, in which the controller uses different control modules in the leg flight phase and landing phase. This paper presents an online learning framework to improve the rapidity of foot contact detection in legged robot running. In this framework, the Gaussian mixture model with three sub-components is adopted to learn the contact data vectors corresponding to running on flat ground, running upstairs, and running downstairs. An online data stream learning algorithm is used to update the model. To deal with the difficulty in obtaining contact data at landing moment online, a “trace back” module is designed to trace back the contact data in the memory stack until the data meet with the probability contact criterion. To test if the foot is in contact with the ground, a projection method is proposed. The acquiring data vector during the leg flight phase is projected onto an independent random vector space, and the contact event is triggered if all projected random variables fall within 1.5σ of the corresponding Gaussian distribution. Experiments on a legged robot show that the presented algorithm can predict the foot contact 16 ms in advance compared with the prediction using only leg force, which will ease the controller design and enhance the stability of legged robot control.