bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vibration Characteristics of 3D Printed Viscoelastic Graded Polymeric Plates
Authors: Carter Justin , Singh Kumar Vikram , Khan Fazeel 
Published: November 2021

Abstract
The exploration of structures made of multiple materials is a growing area of research as additive manufacturing processing technologies such as fused deposition modeling (FDM) 3D printing allows for their fabrication. Such a technology allows for rapid prototyping of structural components with complex geometries or spatially distributed materials with different properties and functionalities. By selecting suitable spatial distribution of materials, the performance of structural components can be manipulated and enhanced as per different engineering application needs. For a low-cost design of structural prototypes using 3D printing processes, viscoelastic polymeric materials are often used, having inherent damping properties. In this research, vibration characteristics of thin plates which are axially graded with multiple polymeric materials are investigated. The goal is to understand the influence of material grading on the frequency and damping characteristics of graded plates. Although in literature, material grading along the thickness in designing composite laminates and their vibration characteristics are available, the performance of plates having axially graded viscoelastic polymers have not been investigated yet. Through systematic modeling and experimental plans, vibration characteristics of axially graded viscoelastic plates are presented here. In particular, the damping performance for different grading schemes is evaluated. It is anticipated that such analysis will allow accurate modeling and testing of design prototypes of structural components for future research, such as design and testing of graded panels for enhanced flutter characteristics.
Design, Modeling, and Optimization of a Novel Asymmetrical Piezoelectrically Actuated Microgripper
Authors: Lyu Zekui , Xu Qingsong 
Published: November 2021

Abstract
Microgripper, as the end-effector of a micromanipulation robot, has been widely used in semiconductors, biomedicine, optical engineering, etc. The stack piezoelectric ceramic actuated microgripper has the advantages of fast response speed, high motion resolution, and good control performance. Traditional symmetrical microgripper has defects such as lack of positioning reference and dense modal of resonance. Therefore, it is necessary to develop an asymmetrical clamp with a large clamping stroke and good dynamic characteristics. This paper introduces the design, modeling, optimization, and simulation of a new asymmetric microgripper. The designed asymmetric gripper has the advantages of large-displacement magnification and high natural frequency. The gripper’s movable side is comprised of three-level compliant amplification mechanisms including bridge mechanism, Scott-Russell mechanism, and parallelogram mechanism. The linear relationship between the input displacement and the output displacement is obtained through motion modeling. The multi-objective genetic algorithm optimizes the major parameters of the structure which affect the clamping stroke. Finite element analysis is conducted to verify the clamping stroke, clamping force, and resonance frequency of the gripper. The simulation results show that the proposed microgripper has good working performance with a clamping stroke of 156.75 μm and a natural frequency of 952.91 Hz, which is promising for practical application.
A Taxonomy for Model-Based Systems Engineering
Authors: Monteiro João P. , Gil Paulo J. S. , Rocha Rui M. 
Published: November 2021

Abstract
In this paper, we define Model Based Systems Engineering (MBSE) as a set of different approaches which vary in scope and in purpose, as opposed to defining it as a monolithic concept. To do so, we inductively extract common themes from papers proposing new MBSE methods based on the type of Systems Engineering (SE) artifacts produced and the expected benefits of MBSE implementation. These themes are then validated against the experiences depicted in a second set of papers evaluating the deployment of MBSE methods in practice. We propose a taxonomy for MBSE which identifies three main categories: system specification repositories, system execution models, and design automation models. The proposed categories map well onto common discussions of the nature of the SE activity, in that the first is employed in the management of system development processes and the second in the understanding of system performance and emergent properties. The third category is almost exclusively discussed in an academic context and is therefore more difficult to relate to SE practice, but its features are clearly distinct from the other two. The proposed taxonomy clarifies what MBSE is and what it can be, therefore helping focus research on the issues that still prevent MBSE practice from living up to expectations.
Myoelectric Control of Robotic Leg Prostheses and Exoskeletons: A Review
Authors: Nasr Ali , Laschowski Brokoslaw , McPhee John 
Published: November 2021

Abstract
Myoelectric signals from the human motor control system can improve the real-time control and neural-machine interface of robotic leg prostheses and exoskeletons for different locomotor activities (e.g., walking, sitting down, stair ascent, and non-rhythmic movements). Here we review the latest advances in myoelectric control designs and propose future directions for research and innovation. We review the different wearable sensor technologies, actuators, signal processing, and pattern recognition algorithms used for myoelectric locomotor control and intent recognition, with an emphasis on the hierarchical architectures of volitional control systems. Common mechanisms within the control architecture include 1) open-loop proportional control with fixed gains, 2) active-reactive control, 3) joint mechanical impedance control, 4) manual-tuning torque control, 5) adaptive control with varying gains, and 6) closed-loop servo actuator control. Based on our review, we recommend that future research consider using musculoskeletal modeling and machine learning algorithms to map myoelectric signals from surface electromyography (EMG) to actuator joint torques, thereby improving the automation and efficiency of next-generation EMG controllers and neural interfaces for robotic leg prostheses and exoskeletons. We also propose an example model-based adaptive impedance EMG controller including muscle and multibody system dynamics. Ongoing advances in the engineering design of myoelectric control systems have implications for both locomotor assistance and rehabilitation.
A Flexure-Based Displacement Reducer Capable of Achieving Very Large Reduction Ratio
Authors: Wu Houqi , Chen Guimin 
Published: November 2021

Abstract
Piezo actuators and giant magnetostrictive actuators are widely used in micropositioning and micromanipulating devices. Due to their limited output stroke, flexure-based displacement amplifiers are usually employed to meet the large-stroke requirements. Although amplifiers increase the stroke of the actuators, they lower the resolution of the motion, making it difficult to obtain positioning of nanometer or even sub-nanometer resolution. To achive very high resolution from these actuators, a compact flexure-based displacement reducer, which shows the capability of obtaining very large reduction ratio, is proposed in this work. The reducer contains two bridge-type flexure mechanisms connected in a way that the output of the reducer equals the difference of the outputs of the two mechanisms (thus is called the bridge-type differential displacement reducer). If the two bridge-type flexure mechanisms are identical, no matter how large the input is, the output will always be 0, indicating an infinite reduction ratio theoretically. Therefore, introducing a slight difference between the two mechanisms can yield a very large reduction ratio. A kinetostatic model for the reducer is developed, base on which a reducer exhibiting a reduction ratio of 100 is designed and prototyped. The results of the kinetostatic model, the finite element model and the experiment agree well with each other, validating the effectiveness of the proposed reducer and the correctness of kinetostatic model.
A Graph Neural Network Approach for Product Relationship Prediction
Authors: Ahmed Faez , Cui Yaxin , Fu Yan , Chen Wei 
Published: November 2021

Abstract
Graph representation learning has revolutionized many artificial intelligence and machine learning tasks in recent years, ranging from combinatorial optimization, drug discovery, recommendation systems, image classification, social network analysis to natural language understanding. This paper shows their efficacy in modeling relationships between products and making predictions for unseen product networks. By representing products as nodes and their relationships as edges of a graph, we show how an inductive graph neural network approach, named GraphSAGE, can efficiently learn continuous representations for nodes and edges. These representations also capture product feature information such as price, brand, and engineering attributes. They are combined with a classification model for predicting the existence of a relationship between any two products. Using a case study of the Chinese car market, we find that our method yields double the F-1 score compared to an Exponential Random Graph Model-based method for predicting the co-consideration relationship between cars. While a vanilla Graph-SAGE requires a partial network to make predictions, we augment it with an ‘adjacency prediction model’ to circumvent this limitation. This enables us to predict product relationships when no neighborhood information is known. Finally, we demonstrate how a permutation-based interpretability analysis can provide insights on how design attributes impact the predictions of relationships between products. Overall, this work provides a systematic method to predict the relationships between products in a complex engineering system.
Correlation of Reduced-Order Models of a Threaded Fastener in Multi-Axial Loading
Authors: Moreno Kevin , Murugesan Avaneesh , Sheng Michael , Alqawasmi Laith , Khraishi Tariq A. , Hubbard Neal B. 
Published: November 2021

Abstract
Fasteners are represented with varying degrees of fidelity in finite element models in order to meet solver constraints and accuracy requirements. Three reduced-order models are evaluated to quantify how well they perform in terms of calibration effort and accuracy. To baseline their performance, a new series of test data are developed by pulling NAS1351-3-20P screws at angles between pure tension (0°) and pure shear (90°) in 15° increments. First, a nonlinear elastic spring element joins two portions of the fastener shank. Unique load-displacement curves for tension and shear are taken directly from the test data, making it easy to calibrate yet fairly accurate. Second, the fastener is modeled with a solid cylindrical shank. The material properties are only calibrated to the tensile test results; consequently, this model is less accurate for predicting the ultimate shear load, though it comes reasonably close to the ultimate displacement in shear and combined loading. Third, a solid cylinder is divided into tensile and shear regions, and the material properties in each region are calibrated to the corresponding test data. This model deviates further from the ultimate displacement but effectively predicts the ultimate load in combined tension and shear. Each model has advantages, but the first is easiest to implement and most accurate overall.
Complexity Should Not Be in the Eye of the Beholder: How Representative Complexity Measures Respond to the Commonly-Held Beliefs of the Literature
Authors: Hennig Anthony , Topcu Taylan G. , Szajnfarber Zoe 
Published: November 2021

Abstract
In an increasingly interconnected & cyber-physical world, the ability to coherently measure and manage complexity is vital for the engineering design and systems engineering community. To this end, numerous measures have been promulgated in the literature, yet these measures differ in terms of their intellectual foundations and perspectives, with limited cross-validation among them. In this paper, we propose a framework for benchmarking the status quo of existing complexity measurement approaches in terms of their alignment with the commonly-held beliefs in the literature. We discover that the literature broadly suggests an understanding of complexity based on a system’s size, number of interconnections, and architectural structure. We adopt a design of experiments approach and synthetically create system architectures to mimic the variation across these dimensions. We then use these architectures as a shared test-bed to document the response of four complexity measures that are representative of the predominant perspectives of the literature. We do this by evaluating the change in measurement of a complexity measure as we incrementally varied the levels of one system architecture property believed to affect complexity while keeping the others constant. We find that none of the measures fully satisfy the commonly-held beliefs of the literature and provide a discussion on the underlying factors that lead to these discrepancies. We note that multiple independent discussions coexist in the literature, with little cohesion and communication across the groups, suggesting that further research is required to understand the interactions and influences among these communities. For this purpose, our rigorous, structured, and grounded in literature benchmarking approach can serve as a testbed for development and verification of future architectural assessment tools and measures.
An Approach to Design Controllers for MIMO Fractional Order System Based on RFN Method
Authors: Li Tingxue , Xue Dingyu , Cui Xinshu 
Published: November 2021

Abstract
Fractional calculus has attracted more and more attention and is applied in different fields. However the controller design techniques for fractional order systems mostly focus on single input single output (SISO) ones. This paper deals with the design of controllers for multiple inputs multiple outputs (MIMO) fractional order systems. A method to synthetize controller based on the eigenvalue function and singular value decomposition (SVD) is proposed with aid of fractional order transfer function (FOTF) MATLAB toolbox for the computation and fitting. Instead of setting specification to the controller, the method proposed aiming at achieving the target closed-loop control effect of the system as a whole. Several models evolved from fractional-order Proportional-Integral-Derivative (fPID) controller are selected to form the designed multivariable controller. The effectiveness and robustness of the proposed method are illustrated by an example via simulation.
Constant Force Compliant Mechanisms Without Preloading
Authors: Pujali Premkumar , Zhou Hong 
Published: November 2021

Abstract
A constant force compliant mechanism generates an output force that keeps invariant in a large range of input displacement. Because of the constant force feature and the merits of compliant mechanisms, they are utilized in many applications. A problem in the current constant force compliant mechanisms is their preloading range that is a certain starting range of the input displacement. In the preloading displacement, the output force of a constant force compliant mechanism does not have the desired value. It goes up from zero value. The preloading displacement often occupies one quarter or more of the entire input displacement range, which weakens the performance of constant force compliant mechanisms. The preloading issue is eradicated in this research by using prebuckled beams as components for constructing constant force compliant mechanisms. It is difficult to synthesize constant force compliant mechanisms that are composed of prebuckled beams because of the intertwined force, buckling and deflection characteristics. In this research, the undeformed beams are represented by spline curves and controlled by its interpolation points. The synthesis of constant force compliant mechanisms is systemized as optimizing the design parameters of the composed prebuckled beams. Fully compliant constant force compliant mechanisms are synthesized without preloading. The synthesis solutions are validated by experimental results.
Model Predictive Control of Fixed Wing Aircraft Using a Disturbance Observer Approach
Authors: Deshpande Vinayak , Zhang Youmin 
Published: November 2021

Abstract
This paper develops a novel cascading Proportional-Integral-Derivative (PID) with Model Predictive Control (MPC) formulation for lateral control of a fixed wing aircraft in the presence of a constant load disturbance, with the consideration of actuator constraints. A Constrained Quadratic Programming (QP) problem is used to solve this MPC problem, via the Primal-Dual procedure. Furthermore, a disturbance observer is utilized to estimate this disturbance so that the setpoint calculation can be adjusted accordingly. Numerical simulations demonstrate steady-state tracking of the aircraft’s roll angle whilst rejecting this disturbance. In addition, heading (yaw) control is implemented via the outer PID loop, and perfect tracking is achieved for this as well. Throughout the entire simulation, the aircraft’s control inputs (aileron and rudder) do not violate their position and rate constraints, thus demonstrating the successful performance of the QP algorithm.
Simulation of a Pole Saw Assisted by a Gyroscopic Effect Device
Authors: Okabe Eduardo P. , Miletto Daniel L. , Misuta Milton S. , Brittes José Luiz P. 
Published: November 2021

Abstract
Linemen performing pruning activity on vegetation entangled with overhead lines and handling a pole saw is a physically strenuous and risky job. It is a major cause of linemen musculoskeletal disorders (MSD) and others injuries, with more than one type of accumulative musculoskeletal injury like backbone, shoulder, neck and wrists. Although assisted robotic tools could reduce ergonomic issues, it also impairs the quality of work; efficiency and quality require human direct cutting due to a huge imponderability of each particular action on each particular job due different kind of vegetation and shapes. The best approach should be to aid linemen handling the pole saw during pruning. So, as a first step to develop and implement a gyroscopic platform for pruning pole saw, this paper compares and presents a simulation of a regular pole saw with a pole saw assisted by a gyroscopic device using kinematic data obtained by the motion capture system. Kinematic data obtained connects to dynamic simulation, which makes available pole saw control and kickback analysis. Simulation outcome shows that gyroscopic assistance on pole saw has great potential to mitigate harmful pruning dynamic forces for lineman, with no impact on productivity and work quality.
Model-Order-Reduction Approach for Structural Health Monitoring of Large Deployed Structures With Localized Operational Excitations
Authors: Bhouri Mohamed Aziz 
Published: November 2021

Abstract
We present a simulation-based classification approach for large deployed structures with localized operational excitations. The method extends the two-level Port-Reduced Reduced-Basis Component (PR-RBC) technique to provide faster solution estimation to the hyperbolic partial differential equation of time-domain elastodynamics with a moving load. Time-domain correlation function-based features are built in order to train classifiers such as Artificial Neural Networks and Support-Vector Machines and perform damage detection. The method is tested on a bridge-shaped structure with a moving vehicle (playing the role of a digital twin) in order to detect cracks’ existence. Such problem has 45 parameters and shows the merits of the two-level PR-RBC approach and of the correlation function-based features in the context of operational excitations, other nuisance parameters and added noise. The quality of the classification task is enhanced by the sufficiently large synthetic training dataset and the accuracy of the numerical solutions, reaching test classification errors below 0.1% for disjoint training set of size 7 × 103 and test set of size 3 × 103. Effects of the numerical solutions accuracy and of the sensors locations on the classification errors are also studied, showing the robustness of the proposed approach and the importance of constructing a rich and accurate representation of possible healthy and unhealthy states of interest.
Design of Band Gap Formation in Periodic Rotors via Optimization
Authors: Lamas Patrick B. , Nicoletti Rodrigo 
Published: November 2021

Abstract
Rotors are usually composed of rotating elements (e.g. disks, impellers, blade stages) which add mass and rotational inertia to the system. When this additional inertia of the rotating elements is evenly distributed along the rotor, inertia periodicity appears and the system presents considerably large band gaps in its frequency response, where no resonances appear. The present work shows that we can change the central frequency of these band gaps, without significantly affecting its bandwidth, by changing the distribution of the inertia along the rotor to a quasi-periodic condition. Such designing of the rotor, and consequently of the band gap, is achieved by an optimization procedure.
Subharmonic Resonance of One Fourth Order of Electrostatically Actuated MEMS Circular Plates: Amplitude-Frequency Response
Authors: Caruntu Dumitru I. , Beatriz Julio , Martinez Miguel 
Published: November 2021

Abstract
This work deals with the amplitude-frequency response subharmonic resonance of 1/4 order of electrostatically actuated circular plates. The method of multiple scales is used to model the hard excitations and to predict the response. This work predicts that the steady state solutions are zero amplitude solutions, and non-zero amplitude solutions which consist of stable and unstable branches. The effects of parameters such as voltage and damping on the response are predicted. As the voltage increases, the non-zero amplitude solutions are shifted to lower frequencies. As the damping increases, the non-zero steady-state amplitudes are shifted to higher amplitudes, so larger initial amplitudes for the MEMS plate to reach non-zero steady-state amplitudes.
A Zero-Trust Methodology for Security of Complex Systems With Machine Learning Components
Authors: Hale Britta , Van Bossuyt Douglas L. , Papakonstantinou Nikolaos , O’Halloran Bryan 
Published: November 2021

Abstract
Fuelled by recent technological advances, Machine Learning (ML) is being introduced to safety and security-critical applications like defence systems, financial systems, and autonomous machines. ML components can be used either for processing input data and/or for decision making. The response time and success rate demands are very high and this means that the deployed training algorithms often produce complex models that are not readable and verifiable by humans (like multi layer neural networks). Due to the complexity of these models, achieving complete testing coverage is in most cases not realistically possible. This raises security threats related to the ML components presenting unpredictable behavior due to malicious manipulation (backdoor attacks). This paper proposes a methodology based on established security principles like Zero-Trust and defence-in-depth to help prevent and mitigate the consequences of security threats including ones emerging from ML-based components. The methodology is demonstrated on a case study of an Unmanned Aerial Vehicle (UAV) with a sophisticated Intelligence, Surveillance, and Reconnaissance (ISR) module.