bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linear Stability Analysis of a Waveboard Multibody Model With a Minimal Set of Equations
Authors: Agúndez A. G. , García-Vallejo D. , Freire E. , Mikkola A. M. 
Published: November 2021

Abstract
In this paper, the stability of a waveboard, the skateboard consisting in two articulated platforms, coupled by a torsion bar and supported of two caster wheels, is analysed. The waveboard presents an interesting propelling mechanism, since the rider can achieve a forward motion by means of an oscillatory lateral motion of the platforms. The system is described using a multibody model with holonomic and nonholonomic constraints. To perform the stability analysis, the nonlinear equations of motion are linearized with respect to the forward upright motion with constant speed. The linearization is carried out resorting to a novel numerical linearization procedure, recently validated with a well-acknowledged bicycle benchmark, which allows the maximum possible reduction of the linearized equations of motion of multibody systems with holonomic and nonholonomic constraints. The approach allows the expression of the Jacobian matrix in terms of the main design parameters of the multibody system under study. This paper illustrates the use of this linearization approach with a complex multibody system as the waveboard. Furthermore, a sensitivity analysis of the eigenvalues considering different scenarios is performed, and the influence of the forward speed, the casters’ inclination angle and the tori aspect ratios of the toroidal wheels on the stability of the system is analysed.
Tristable Properties in Electrostatically Actuated Initially Curved Coupled Micro Beams
Authors: Medina Lior , Seshia Ashwin A. 
Published: November 2021

Abstract
A limit point behaviour analysis of a metastructure, composed of two double clamped, initially curved beams, coupled via a rigid truss at their respective centres, is carried out when subjected to a distributed electrostatic load. The analysis is based on a reduced order (RO) model resulting from Galerkin’s decomposition, with symmetric buckling modes taken as the base functions, for either beam. All solutions employed the implicit arc-length “Riks” method to accommodate for winding equilibrium paths, while validation of the said results were carried out against finite differences (FD) direct solutions. In addition, local stability analysis via the energy method, conducted on the primary beam was instrumental in clarifying the role of the various extremum points by characterising which branches are stable, and which are not. The combined analysis has shown that the driving beam, which directly encounters the load, is able to possess bistable as well as tristable properties, provided that the metastructure meets certain geometrical parameters. Several variations of tristability are disclosed in the study. The analysis indicates that a model with at least three degrees of freedom (DOF) is needed to predict such configurations, as well as the various critical thresholds, with reasonable errors of around one percent when compared against FD. In so doing, the model can be used to provide static characterisation of the structure.
Design of a New Piezoelectrically Actuated Compliant Microgripper With High Area Usage Efficiency
Authors: Lyu Zekui , Xu Qingsong 
Published: November 2021

Abstract
Microgripper acts as an end-effector in the microassembly system, which completes pick-transport-release actions during the assembly process. Usually, the working space of the microassembly robot is small, and the operating environment is complicated. In addition, the assembled micro-objects are light, thin, brittle, and prone to damage. Thus, the microgripper should be able to provide a compact construction, a suitable clamping range, and safe clamping force for microassembly use. This paper presents the design, modeling, optimization, and simulation of a new piezoelectrically actuated compliant microgripper for microassembly application. The designed clamp has the advantages of large motion displacement and high area usage efficiency. A three-stage amplification mechanism based on bridge-type mechanism and leverage mechanism arranged in series is introduced to achieve a large jaw displacement. The optimization based on response surface analysis has been applied to determine the structural parameters of the amplification mechanism. The displacement amplification ratio of the microgripper is analyzed via the pseudo-rigid-body model approach. Finite element analysis is conducted to evaluate and validate the performance of the gripper. The simulation results indicate that the gripper can achieve a maximum gripping displacement of 545.12 μm with an area usage efficiency of 370.32 nm/mm2, which is better than available designs in the literature.
An Analytic Condition for the Finite Degree-of-Freedom of Linkages and Its Computational Evaluation
Authors: Müller Andreas 
Published: November 2021

Abstract
The finite degree of freedom (DOF) of a mechanism is determined by the number of independent loop constraints. In this paper a method is introduced to determine the maximal number of loop closure constraints (which is independent of a specific configuration) of multi-loop linkages and is applied to calculate the finite DOF. It rests on an algebraic condition on the joint screws and the corresponding computational algorithm to determine the maximal rank of the constraint Jacobian in an arbitrary (possibly singular) reference configuration, making use of the analytic condition that minors of certain rank and their higher derivatives vanish. Unlike the Lie group methods for estimation the DOF of so-called exceptional linkages, this method does not rely on partitioning kinematic loops into partial kinematic chains, and it is applicable to multi-loop linkages. The DOF computed with this method is at least as accurate as the DOF computed with the Lie group methods. It gives the correct DOF for any (possibly overconstrained) linkage where the constraint Jacobian has maximal rank in regular configurations. The so determined maximal rank has further significance for classifying linkages as being exceptional or paradoxical, but also for detecting singularities and shaky linkages.
Enhanced Multiple Surface Properties of Biometallic Materials by Laser Microprocessing
Authors: Wang Bing , Zhang Jiaru , Guan Yingchun 
Published: November 2021

Abstract
Metallic materials have been widely used owing to their good mechanical property and high flexibility. However, there are certain limitations for practical applications such as low anti-bacterial, cell adhesion, surface wettability and corrosion resistance property. In this paper, laser microprocessing of titanium (Ti) alloy and magnesium (Mg) alloy has been conducted, respectively. The cell adhesion of Ti6Al4V alloy and Mg-Gd-Ca alloy after laser microprocessing has been investigated. The results show that MC3T3-E1 cells have been successfully adhered to the treated surface and optical density are significantly increased due to hybrid micro/nano structure. Anti-bacterial test shows that the anti-bacterial rates against E. coli of laser-treated surface was up to 72%. Meanwhile, water contact angle has been increased from 57.4° to 135.3° indicating the changing of surface wettability from hydrophilic to hydrophobic. Moreover, corrosion test of Mg-Gd-Ca alloy has been conducted, which has been significantly improved after laser microprocessing. The present work showed that laser surface microprocessing could be a promising technique for fabricating different biomedical property surfaces.
Design of a Triple Crossed Flexure Pivot With Minimized Parasitic Shift
Authors: Thalmann E. , Henein S. 
Published: November 2021

Abstract
Thanks to their absence of play, absence of contact friction and possible monolithic fabrication, flexure pivots offer advantages over traditional bearings in small-scale, high accuracy applications and environments where lubrication and wear debris are proscribed. However, they typically present a so-called parasitic center shift that deteriorates their rotational guidance accuracy. Existing solutions addressing this issue have the drawbacks of reducing angular stroke, prohibiting planar design, or introducing overconstraints or underconstraints. This article introduces a new triple crossed flexure pivot called TRIVOT that has a reduced parasitic shift without overconstraints nor internal mobility while allowing either optimal stress distribution in the flexures or a planar design. The new architecture also makes it possible to place the center of rotation outside of the physical structure, which is not the case with traditional bearings. Based on finite element simulations, we show that the parasitic shift is reduced by one order of magnitude in comparison to the widely used crossed flexure pivot. We also derive and validate formulas for the rotational stiffness and angular stroke limit of the TRIVOT for given dimensions and material, which are valuable for its dimensioning towards practical applications. We expect this new pivot to become a competitive alternative to the crossed flexure pivot for applications where high accuracy and compactness are required.
Reliability-Informed Economic and Energy Evaluation for Design for Remanufacturing: A Case Study on a Hydraulic Manifold
Authors: Nemani Venkat P. , Liu Jinqiang , Ahmed Navaid , Cartwright Adam , Kremer Gül E. , Hu Chao 
Published: November 2021

Abstract
Design for Remanufacturing (DfRem) is an attractive approach for sustainable product development. Evaluation of DfRem strategies, from both economic and environmental perspectives, at an early design stage can allow the designers to make informed decisions when choosing the best design option. Studying the long-term implications of a particular design scenario requires quantifying the benefits of remanufacturing for multiple life cycles while considering the reliability of the product. In addition to comparing designs on a one-to-one basis, we find that including reliability provides a different insight into comparing design strategies. We present a reliability-informed cost and energy analysis framework that accounts for product reliability for multiple remanufacturing cycles within a certain warranty policy. The variation of reuse rate over successive remanufacturing cycles is formulated using a branched power-law model which provides probabilistic scenarios of reusing or replacing with new units. To demonstrate the utility of this framework, we use the case study of a hydraulic manifold, which is a component of a transmission used in some agricultural equipment, and use real-world field reliability data to quantify the transmission’s reliability. Three design improvement changes are proposed for the manifold and we quantify the costs and energy consumption associated with each of the design changes for multiple remanufacturing cycles.
Predicting the Material Removal Rate in Chemical Mechanical Planarization Process: A Hypergraph Neural Network-Based Approach
Authors: Xia Liqiao , Zheng Pai , Liu Chao 
Published: November 2021

Abstract
Material removal rate (MRR) plays a critical role in the operation of chemical mechanical planarization (CMP) process in the semiconductor industry. To date, many physics-based and data-driven approaches have been proposed to predict the MRR. Nevertheless, most of the existing methodologies neglect the potential source of its well-organized and underlying equipment structure containing interaction mechanisms among different components. To address its limitation, this paper proposes a novel hypergraph neural network-based approach for predicting the MRR in CMP. Two main scientific contributions are presented in this work: 1) establishing a generic modeling technique to construct the complex equipment knowledge graph with a hypergraph form base on the comprehensive understanding and analysis of equipment structure and mechanism, and 2) proposing a novel prediction method by combining the Recurrent Neural Network based model and the Hypergraph Neural Network to learn the complex data correlation and high-order representation base on the Spatio-temporal equipment hypergraph. To validate the proposed approach, a case study is conducted based on an open-source dataset. The experimental results prove that the proposed model can capture the hidden data correlation effectively. It is also envisioned that the proposed approach has great potentials to be applied in other similar smart manufacturing scenarios.
A Compliant Micromechanism for Biaxially Stretching Biological Cells
Authors: Fartyal Neeraj Singh , Marwah Himanshu , Balakrishnan Sreenath 
Published: November 2021

Abstract
Biological cells are known to respond to mechanical forces. Diverse biological phenomena such as tissue development and cancer are regulated by mechanical forces acting on cells. One such mechanical loading found in various tissues such as alveoli, pericardium, blood vessels, and urinary bladder is biaxial stretching. To study the effect of such a loading pattern, it is necessary to develop mechanical tools that can apply controlled biaxial stretching on cells. Here we present the design for such a device, a compliant micromechanism for biaxially stretching single cells.
We first designed a compliant, double-input, biaxial stretching mechanism based on re-entrant structures. Various stretch ratios, defined as the ratio between deformations in orthogonal directions, could be obtained by changing the dimensions of this mechanism. Next, we derived an analytical expression relating the geometric parameters to the stretch ratio. This analytical expression was verified using finite element analysis. By numerically solving this expression, multiple designs for a desired stretch ratio were obtained. Furthermore, we converted our design into a single-input mechanism by coupling the double-input biaxial stretcher to a single-input gripper mechanism. Finally, we demonstrate the functioning of our design using a macroscale, 3D-printed version.
Data-Driven Design-by-Analogy: State of the Art
Authors: Jiang Shuo , Hu Jie , Luo Jianxi 
Published: November 2021

Abstract
Design-by-Analogy (DbA) is a design methodology that draws inspiration from a source domain to a target domain to generate new solutions to problems or designs, which can benefit designers in mitigating design fixation and improving design ideation outcomes. Recently, the increasingly available design databases and rapidly advancing data science and artificial intelligence technologies have presented new opportunities for developing data-driven methods and tools for DbA support. Herein, we survey the prior data-driven DbA studies and categorize and analyze individual study according to the data, methods and applications in four categories including analogy encoding, retrieval, mapping, and evaluation. Based on such structured literature analysis, this paper elucidates the state of the art of data-driven DbA research to date and benchmarks it with the frontier of data science and AI research to identify promising research opportunities and directions for the field.
Periodic Temperature Responses in a Thermal System Under a Periodic Heating
Authors: Yu Bo , Luo Albert C. J. 
Published: November 2021

Abstract
In this paper, the periodic temperature responses of a thermal system under a periodic heating input are studied. Using the implicit mapping method, periodic temperature responses varying with excitation frequency are predicted for different input amplitudes. The corresponding stability of the periodic responses are discussed through eigenvalue analysis. The experimental and numerical results of the periodic response are presented for comparison to the analytical results.
Segmentation of Additive Manufacturing Defects Using U-Net
Authors: Wong Vivian Wen Hui , Ferguson Max , Law Kincho H. , Lee Yung-Tsun Tina , Witherell Paul 
Published: November 2021

Abstract
Additive manufacturing (AM) provides design flexibility and allows rapid fabrications of parts with complex geometries. The presence of internal defects, however, can lead to deficit performance of the fabricated part. X-ray Computed Tomography (XCT) is a non-destructive inspection technique often used for AM parts. Although defects within AM specimens can be identified and segmented by manually thresholding the XCT images, the process can be tedious and inefficient, and the segmentation results can be ambiguous. The variation in the shapes and appearances of defects also poses difficulty in accurately segmenting defects. This paper describes an automatic defect segmentation method using U-Net based deep convolutional neural network (CNN) architectures. Several models of U-Net variants are trained and validated on an AM XCT image dataset containing pores and cracks, achieving a best mean intersection over union (IOU) value of 0.993. Performance of various U-Net models is compared and analyzed. Specific to AM porosity segmentation with XCT images, several techniques in data augmentation and model development are introduced. This work demonstrates that, using XCT images, U-Net can be effectively applied for automatic segmentation of AM porosity with high accuracy. The method can potentially help improve quality control of AM parts in an industry setting.
Global Sensitivity Analysis for Field Response Based on the Manifold of Feature Covariance Matrix
Authors: Song Zhouzhou , Liu Zhao , Xu Can , Zhu Ping 
Published: November 2021

Abstract
In real-world applications, it is commonplace that the computational models have field responses, i.e., the temporal or spatial fields. It has become a critical task to develop global sensitivity analysis (GSA) methods to measure the effect of each input variable on the full-field. In this paper, a new sensitivity analysis method based on the manifold of feature covariance matrix (FCM) is developed for quantifying the impact of input variables on the field response. The method firstly performs feature extraction on the field response to obtain a low-dimensional FCM. An adaptive feature selection method is proposed to avoid the FCM from singularity. Thereby, the field response is represented by a FCM, which lies on a symmetric positive-definite matrix manifold. Then, the GSA technique based on the Cramér-von Mises distance for output valued on the Riemannian manifold is introduced for estimating the sensitivity indices for field response. An example of a temporal field and an example of a 2-D displacement field are introduced to demonstrate the applicability of the proposed method in estimating global sensitivity indices for field solution. Results show that the proposed method can distinguish the important input variables correctly and can yield robust index values. Besides, the proposed method can be implemented for GSA for field responses of different dimensionalities.
Evaluation of Inertial Measurement Units for Short Time Motion Tracking
Authors: Neurauter Rene , Hergel Peter , Gerstmayr Johannes 
Published: November 2021

Abstract
The goal of the present paper is to investigate inertial measurement systems for the ability to reconstruct the short time rigid body motion of objects, e.g. clumps in snow avalanches. While strapdown inertial navigation is well established, special algorithms are needed for the accurate motion reconstruction for short time motion with partially known boundary conditions. Furthermore, low cost inertial sensors are available with the ability to log translational accelerations and angular velocities as well as magnetic flux densities, which need to be extended with respect to GPS, time synchronization, and power management functionalities. In this paper, a newly developed system to measure the motion inside snow avalanches with redundant sensors, which have significantly higher measurement ranges than systems published in the past, is presented. In addition, an algorithm for motion reconstruction from measured translational accelerations, angular velocities and magnetic flux densities is derived. Furthermore, an optimization by eliminating terminal translational velocities is presented. The developed system is tested and its function is confirmed by reproducible measurement data from two experiments on skis, whereas these experiments differ in the magnitude of rotations. The presented motion reconstruction algorithm was used to evaluate the measurement data and thus the newly developed measurement system.
POD-Based Model Order Reduction for Tire-Soil Interaction Simulations
Authors: Sullivan Christopher C. , Yamashita Hiroki , Sugiyama Hiroyuki 
Published: November 2021

Abstract
The objective of this study is to develop model order reduction capabilities for high-fidelity off-road mobility simulations. The model reduction technique using the proper orthogonal decomposition (POD) is implemented at the level of the numerical solver in order to decrease the number of equations that need to be solved at each iteration of the solution procedure. The POD is, however, limited in that the modes are dependent on snapshot data collected during the running of a full order model (FOM), limiting the modes to being accurate only for the specific scenario from which they were collected. Due to this limitation, a method of mode adaptation through interpolation on a tangent space of the Grassmann manifold is investigated to allow modes to be predicted for cases in which a full order model has not been run. Modes produced for known values of a simulation parameter are used to predict the modes for a value of the simulation parameter for which POD modes have not been directly produced. For a single tire soil bin mobility model, the POD modes are found to be effective at retaining accuracy with minimal errors while also reducing computational time.
Design and Path Planning of Autonomous Solar Lawn Mower
Authors: Hazem Souhail , Mostafa Mohamed , Mohamed Ehab , Hesham Mohamed , Mohamed Abdelrahman , Lotfy Eyad , Mahmoud Ayman , Yacoub Mostafa 
Published: November 2021

Abstract
Current conventional lawn mowers have the following drawbacks; high initial costs, increasing engine noise levels, high operating costs due to high fuel consumption rates, the need to implement perimeter wires across the desired lawn mowing field, and high exhaustion of the operator in the long operating time. Hence, the need for a system that can achieve the same cutting effect of the existing lawn mowers with little or no operator’s fatigue, minimized noise pollution and running cost has risen. In present work, design of an autonomous solar lawn mower, a robotic vehicle that cut grass automatically with little human intervention, is discussed. The robotic vehicle is powered by Lithium-Ion batteries and depend on solar power delivered from a solar base station for charging the batteries. The mechanical design of the vehicle is flexible with the ability to control the height of the vehicle during grass mowing. Differential steering, with the implementation of multiple sensors is presented for obstacle avoidance. Also, a Raspberry Pi microcontroller for the image processing application through a camera is used for path planning. Furthermore, a solar based station structure is designed for charging the robotic vehicle batteries with minimized running cost, utilization of renewable energy source, no health hazards, not having any effect on the environment, and human’s effort and time are saved.