In recent decades, the design of complex systems like launch vehicles in the aerospace industry has presented engineers with challenges that go beyond system complexity. Issues such as time-to-market pressures and intricate industrial processes have underscored the increasing significance of agile design methodologies. Agile design is derived from the simplification of the design process and enhancing cross-domain data transmission and feedback. While methods based on model-based system engineering have improved iteration times in system architecture design, challenges persist in cross-domain data transmission. Due to the diversity of complex system models and data, a single-mode integration method is difficult to realize the data link construction of all tools used. To address this challenge, this paper proposes a dualmode data integration framework with expansibility, universality, and cost-efficiency which leverages the benefits of Remote Procedure Call and Intermediate Exchange Module, addressing the challenge of constructing cross-domain data links under single-mode integration. In this study, two critical requirements of the first- and second-stage separation systems, namely, weight and minimum separation gap, are selected for data feedback. A Modelica-based multiphysics simulation model is developed in MWorks; visualization and computation of the minimum gap are carried out in CoppeliaSim. To bridge the gap between domain-specific tools, Matlab and Functional Mock-up Unit modules are introduced as middleware, facilitating data feedback linkage. The entire simulation process is orchestrated using activity diagrams in the MagicDraw tool. The study delves into the influence of critical design parameters, such as the initial angular velocity of separation and the thrust of the retro rocket, on the minimum separation gap. It provides an analysis of minimum separation gap variations under uncertain operating conditions and examines design margins. Significantly, the paper highlights the significance of controlling the initial angular velocity during separation and the reliability of the retro rocket, providing essential decision supports and valuable insights to agile the process of system design.

In this work, our primary focus centered on exploring the adaptability of the dualrate sampling scheme proposed earlier to enhance the performance of multi-degree-of-freedom (multi-DOF) impedance-based haptic interfaces. The scheme employed independent sampling rates in a haptics controller, effectively mitigating the issue of reduced Z-width at higher sampling rates. A key aspect of our investigation was the intricate implementation of the dual-rate sampling scheme on a field programmable gate array (FPGA). This implementation on a logic hardware FPGA was challenging and led to the effective comparison of the uniform-rate and dual-rate sampling schemes of the multi-DOF haptic controller. We used an in-house developed two-DOF pantograph as the haptic interface and an FPGA for implementing the controller strategy. FPGA-based implementation presented challenges that were vital in testing controller performances at higher sampling rates. Virtual wall experiments were conducted to determine the stable and unstable interactions with the virtual wall. To complement the experimental results, we simulated the haptics force law for multi-DOF system on Simulink/MATLAB. Notably, the dual-rate sampling approach maintained the Z-width of the two-DOF haptic interface, even at higher controller sampling rates, distinguishing it from the conventional two-DOF uniform-rate control scheme. For example, employing a dual-rate sampling combination of 20–2 kHz consistently ensured the stable rendering of a maximum virtual stiffness of approximately 700 N/mm and maintained a reliable virtual damping range spanning from 0 to 5 Ns/mm. In contrast, the 20 kHz uniform-rate sampling approach failed to ensure interface stability in the presence of virtual damping, ultimately resulting in the unsuccessful implementation of any virtual stiffness at higher sampling rates. This work, therefore, establishes the potential of dual-rate sampling in the realm of haptic technology, with practical applications in multi-DOF systems.

This paper presents a novel approach called the boundary integrated neural networks (BINNs) for analyzing acoustic radiation and scattering. The method introduces fundamental solutions of the time-harmonic wave equation to encode the boundary integral equations (BIEs) within the neural networks, replacing the conventional use of the governing equation in physics-informed neural networks (PINNs). This approach offers several advantages. First, the input data for the neural networks in the BINNs only require the coordinates of “boundary” collocation points, making it highly suitable for analyzing acoustic fields in unbounded domains. Second, the loss function of the BINNs is not a composite form and has a fast convergence. Third, the BINNs achieve comparable precision to the PINNs using fewer collocation points and hidden layers/neurons. Finally, the semianalytic characteristic of the BIEs contributes to the higher precision of the BINNs. Numerical examples are presented to demonstrate the performance of the proposed method, and a MATLAB code implementation is provided as supplementary material.

The projectile engraving process directly influences the projectile motion in-bore and impacts the firing accuracy, firing safety, and barrel life of the gun. For this reason, attention has been focused on this research topic. To address the limitations of the “instantaneous engraving” hypothesis adopted in the classical interior ballistic theory, the VUAMP user subroutine, one of ABAQUS’s secondary development interfaces, is utilized in this paper to realize the modeling and numerical simulation of a coupled dynamics model of the projectile engraving process. In addition to facilitating engineering applications, a polynomial fitting formula of the engraving resistance obtained by simulation is proposed and then used as a supplement to establish a closed and solvable interior ballistic model considering the projectile engraving process. By comparing with test data, the simulation accuracy of the coupled dynamics model is verified. Simulation results reveal that the engraving process takes 3.8 ms, accounting for 26% of the whole launch process, which takes 14.6 ms, demonstrating that the process is not instantaneous. The results of this paper can serve as a reference for future studies on the coupled solution of the projectile engraving process and interior ballistics of guns or gun-like equipment.

To improve the dynamic balancing accuracy of the micro-motor rotor, an unbalanced vibration feature extraction based on an all-phase fast Fourier transform (APFFT) method is proposed. The amplitude and phase of the signal are extracted by spectrum analysis after windowing the unbalanced signal. The mathematical model is derived to simulate the weak signal of rotor unbalance. The simulation results show that this method is accurate in extracting the weak signal of the rotor under different noise levels. The micro-motor rotor unbalanced test system is developed for experimental validations. The accuracy and stability of the vibration amplitude and phase extracted by the APFFT are better than the accuracy and stability from the hardware filtering method. The rotor unbalance is reduced by more than 80%. Furthermore, secondary balance of the rotor after the first balance is carried out. The proposed method can still extract the residual unbalance of the rotor. The results demonstrated that the proposed method can achieve a reduction rate of 90% and the accuracy is within 5mg, verifying the effectiveness of the proposed method for high-precision rotor dynamic balance.

A three-magnet-ring quasi-zero stiffness (QZS-TMR) isolator is designed to solve the problem of low-frequency vibration isolation in the vertical direction of precision equipment. QZS-TMR has both positive and negative stiffness structures. The positive stiffness structure consists of two mutually repelling magnetic rings and the negative stiffness structure consists of two magnetic rings nested within each other. By modulating the relative distance between positive and negative stiffness structures, the isolator can have QZS characteristics. Compared with other QZS isolators, the QZS-TMR is compact and easy to manufacture. In addition, the working load of QZS-TMR can be flexibly adjusted by varying the radial widths of the inner magnetic ring. In this paper, the static analysis of QZS-TMR is carried out to guide the design, and the low-frequency vibration isolation performance is studied. In addition, the experimental prototype of QZS-TMR is designed and manufactured. The static and vibration isolation experiments are carried out on the prototype. The results show that the initial vibration isolation frequency of the experimental prototype is about 4 Hz. The results show an excellent low-frequency vibration isolation effect, which is consistent with the theoretical research. This paper introduces a new approach to the design of the QZS isolator.

This review paper presents a comprehensive evaluation and forward-looking perspective on the underexplored topic of servicing target objects using spacecraft swarms. Such targets can be known or unknown, cooperative or uncooperative, and pose significant challenges in modern space operations due to their inherent complexity and unpredictability. Successfully servicing space objects is vital for active debris removal and broader on-orbit servicing tasks such as satellite maintenance, repair, refueling, orbital assembly, and construction. Significant effort has been invested in the literature to explore the servicing of targets using a single spacecraft. Given its advantages and benefits, this paper expands the discussion to encompass a swarm approach to the problem. This review covers various single-spacecraft approaches and presents a critical examination of the existing, although limited, body of work dedicated to servicing orbital objects using multiple spacecraft. The focus is also broadened to include some influential studies concerning the characterization, capture, and manipulation of physical objects by general multiagent systems, a subject with significant parallels to the core interest of this manuscript. Furthermore, this article also delves into the realm of simultaneous localization and mapping, highlighting its application within close-proximity operations in space, especially when dealing with unknown uncooperative targets. Special attention is paid to the benefits that this field can receive from distributed multiagent architectures. Finally, an exploration of the promising field of swarm robotics is presented, with an emphasis on its potential to revolutionize the servicing of orbital target objects. Concurrently, a survey of general research directly engaging swarms in the orbital context is conducted. This review aims to bridge the knowledge gap and stimulate further research in the underexplored domain of servicing space targets with spacecraft swarms.

Design of earth structures, such as dams, tunnels, and embankments, against the vibrational loading caused by high-speed trains, road traffic, underground explosions, and, more importantly, earthquake motion, demands solutions of the dynamic soil–structure Interaction (SSI) problem. This paper presents a velocity-based space–time finite element procedure, v-ST/finite element method (FEM), to solve dynamic SSI problems. The main goal of this study is to present the computation details of implementing viscous boundary conditions of Lysmer–Kuhlemeyer to truncate the unbounded soil domain. Furthermore, additional time-dependent boundary conditions, in terms of the free-field response, are included to facilitate energy flow from the far field to the computation domain at the vertical truncated boundaries. In the FEM, seismic input motion is applied to an effective nodal force vector, which can be obtained explicitly in the numerical simulations. Finally, the response of a concrete gravity dam resting on an elastic half-space to the horizontal component of earthquake motion is computed and successfully compared with the results of semidiscrete FEM using the Newmark-β method.

Piezoelectric material-based semi-active vibration control systems may effectively suppress vibration amplitude without any external power supply, or even harvest electrical energy. This bidirectional electrical energy control phenomenon is theoretically introduced and validated in this paper. A flyback transformer-based switching piezoelectric shunt circuit that can extract energy from or inject energy into piezoelectric elements is proposed. The analytical expressions of the controlled energy and the corresponding vibration attenuation are therefore derived for a classical electromechanical cantilever beam. Theoretical predictions validated by the experimental results show that the structure vibration attenuation can be tuned from −5 to −25 dB under the given electrical quality factor of the circuit and figure of merit of the electromechanical structure, and the consumed power is in the range of −13 to 25mW, which is a good theoretical basis for the development of self-sensing, self-adapting, and self-powered piezoelectric vibration control systems.

Axle-box bearings are crucial components of high-speed trains and operate in challenging conditions. As service mileage increases, these bearings are susceptible to various failures, posing a safety risk to high-speed train operations. Thus, it is crucial to examine the deployment methods of axle-box bearings. A dynamic model of axle-box bearings for high-speed trains with compound faults is constructed by setting up separate faults in two rows of double-row tapered roller bearings based on a single-fault model. The model’s high accuracy in expressing compound faults is verified through corresponding experimental results. Then, the frequency domain diagram of system vibration response under varying rotational speed conditions is obtained, and the amplitude corresponding to the single frequency is extracted and analyzed to identify the optimal rotational speed band for composite fault diagnosis. Finally, the optimal speed band is analyzed under different faults, different load sizes, and different composite fault types. It can be concluded that the determination of the optimal speed band is solely influenced by the composite fault type and is independent of the fault and load sizes. Finally, it is concluded that the energy proportion of faults in different positions changes periodically with the change in speed, and this phenomenon is not affected by the fault sizes or load magnitude.

In this paper, we study the vibrational behavior of shells in the form of truncated cones containing an ideal compressible fluid. The sloshing effect on the free surface of the fluid is neglected. The dynamic behavior of the elastic structure is investigated based on the classical shell theory, the constitutive relations of which represent a system of ordinary differential equations written for new unknowns. Small fluid vibrations are described in terms of acoustic approximation using the wave equation for hydrodynamic pressure written in spherical coordinates. Its transformation into the system of ordinary differential equations is carried out by applying the generalized differential quadrature method. The formulated boundary value problem is solved by Godunov’s orthogonal sweep method. Natural frequencies of shell vibrations are calculated using the stepwise procedure and the Muller method. The accuracy and reliability of the obtained results are estimated by making a comparison with the known numerical and analytical solutions. The dependencies of the lowest frequency on the fluid level and cone angle of shells under different combinations of boundary conditions (simply supported, rigidly clamped, and cantilevered shells) have been studied comprehensively. For conical straight and inverted shells, a numerical analysis has been performed to estimate the possibility of finding configurations at which the lowest natural frequencies exceed the corresponding values of the equivalent cylindrical shell.

During 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.

Effective fault diagnosis has a crucial impact on the safety and cost of complex manufacturing systems. However, the complex structure of the collected multisource data and scarcity of fault samples make it difficult to accurately identify multiple fault conditions. To address this challenge, this paper proposes a novel deep-learning model for multisource data augmentation and small sample fault diagnosis. The raw multisource data are first converted into two-dimensional images using the Gramian Angular Field, and a generator is built to transform random noise into images through transposed convolution operations. Then, two discriminators are constructed to evaluate the authenticity of input images and the fault diagnosis ability. The Vision Transformer network is built to diagnose faults and obtain the classification error for the discriminator. Furthermore, a global optimization strategy is designed to upgrade parameters in the model. The discriminators and generator compete with each other until Nash equilibrium is achieved. A real-world multistep forging machine is adopted to compare and validate the performance of different methods. The experimental results indicate that the proposed method has multisource data augmentation and minority sample fault diagnosis capabilities. Compared with other state-of-the-art models, the proposed approach has better fault diagnosis accuracy in various scenarios.

Compliant mechanisms with curved flexure hinges/beams have potential advantages of small spaces, low stress levels, and flexible design parameters, which have attracted considerable attention in precision engineering, metamaterials, robotics, and so forth. However, serial–parallel configurations with curved flexure hinges/beams often lead to a complicated parametric design. Here, the transfer matrix method is enabled for analysis of both the kinetostatics and dynamics of general serial–parallel compliant mechanisms without deriving laborious formulas or combining other modeling methods. Consequently, serial–parallel compliant mechanisms with curved flexure hinges/beams can be modeled in a straightforward manner based on a single transfer matrix of Timoshenko straight beams using a step-by-step procedure. Theoretical and numerical validations on two customized XY nanopositioners comprised of straight and corrugated flexure units confirm the concise modeling process and high prediction accuracy of the presented approach. In conclusion, the present study provides an enhanced transfer matrix modeling approach to streamline the kinetostatic and dynamic analyses of general serial–parallel compliant mechanisms and beam structures, including curved flexure hinges and irregular-shaped rigid bodies.

The objective of dynamical system learning tasks is to forecast the future behavior of a system by leveraging observed data. However, such systems can sometimes exhibit rigidity due to significant variations in component parameters or the presence of slow and fast variables, leading to challenges in learning. To overcome this limitation, we propose a multiscale differential-algebraic neural network (MDANN) method that utilizes Lagrangian mechanics and incorporates multiscale information for dynamical system learning. The MDANN method consists of two main components: the Lagrangian mechanics module and the multiscale module. The Lagrangian mechanics module embeds the system in Cartesian coordinates, adopts a differential-algebraic equation format, and uses Lagrange multipliers to impose constraints explicitly, simplifying the learning problem. The multiscale module converts high-frequency components into low-frequency components using radial scaling to learn subprocesses with large differences in velocity. Experimental results demonstrate that the proposed MDANN method effectively improves the learning of dynamical systems under rigid conditions.

Reducing the effects of external disturbance on overhead crane systems is crucial, as they can impair the controller performance and cause excessive vibrations or oscillations of the payloads. One such external disturbance is the inclination of the supporting track of the crane trolley, which causes the system dynamics model to change. An open-loop control strategy is widely utilized to control the payload sway motion and generally does not require any alterations in the physical structure of a system or the installation of sensors and/or actuators. Input and command shaping are two common open-loop control techniques applied to control overhead cranes. In this paper, the effect of moving an overhead crane system along an inclined supporting track is investigated. In addition, the ability of different types of input- and command-shaping control schemes to suppress the residual vibrations due to trolley track inclination is demonstrated. Two types of input-shaping controllers, which are double-step, zero vibration, and one command waveform (WF) shaper based on a trigonometric function, are used and tested. A linear equation of motion of the overhead crane resting on an inclined surface is developed to simulate the overhead crane and payload motion. The effectiveness of the different types of open-loop controllers to suppress residual vibrations is verified by both simulation and experimental results. In addition, a newWF command shaper is proposed and designed to overcome track inclination while eliminating payload residual vibration. A comprehensive comparative analysis, both numerically and experimentally, is performed on the new proposed shaper to measure its effectiveness in handling inclination when compared to other types of open-loop controllers. The new shaper outperforms other controllers in eliminating payload residual vibration for a wider range of inclination angles.

Superior surface finish remains a fundamental criterion in precision machining operations, and tool-tip vibration is an important factor that significantly influences the quality of the machined surface. Physics-based models heavily rely on assumptions for model simplification when applied to complex high-end systems. However, these assumptions may come at the cost of compromising the model's accuracy. In contrast, data-driven techniques have emerged as an attractive alternative for tasks such as prediction and complex system analysis. To exploit the advantages of data-driven models, this study introduces a novel convolutional enhanced transformer model for tool-tip vibration prediction, referred to as CeT-TV. The effectiveness of this model is demonstrated through its successful application in ultra-precision fly-cutting (UPFC) operations. Two distinct variants of the model, namely, guided and nonguided CeT-TV, were developed and rigorously tested on a data set custom-tailored for UPFC applications. The results reveal that the guided CeT-TV model exhibits outstanding performance, characterized by the lowest mean absolute error and root mean square error values. Additionally, the model demonstrates excellent agreement between the predicted values and the actual measurements, thus underlining its efficiency and potential for predicting the tool-tip vibration in the context of UPFC.

In this paper, an asymmetric vibroacoustic system that can passively realize nonreciprocal transmission of acoustic energy is reported. This experimental system consists of a waveguide, a strongly nonlinear membrane, and three acoustic cavities with different sizes. The theoretical modeling of the system is verified by experiments, and parametric analysis is also carried out. These intensive studies reveal the nonreciprocal transmission of acoustic energy in this prototype system. Under forward excitation, internal resonance between the two nonlinear normal modes of the vibroacoustic system occurs, and acoustic energy is irreversibly transferred from the waveguide to the nonlinear membrane. However, under backward excitation, there is no internal resonance in the system. Energy spectra and wavelet analysis are used to highlight the mechanism of nonreciprocal transfer of acoustic energy. Consequently, nearly unidirectional (preferential) transmission of acoustic energy transfer is shown by this system. The nonreciprocal acoustic energy transfer method illustrated in this paper provides a new way to design the odd acoustic element.