bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effects of Locus of Control and Big Five Personality Traits on Collaborative Engineering Design Tasks With Negotiation
Authors: Avşar Alkım Z. , Valencia-Romero Ambrosio , Grogan Paul T.
Published: November 2019

Collaborative systems design is a human-centered activity dependent on individual decision-making processes. Personality traits have been found to influence individual behaviors and tendencies to compete or cooperate. This paper investigates the effects of Big Five and Locus of Control personality traits on negotiated outcomes of a simplified collaborative engineering design task. Secondary data includes results from short-form personality inventories and outcomes of pair design tasks. The data includes ten sessions of four participants each, where each participant completes a sequence of 12 pair tasks involving design space exploration and negotiation. Regression analysis shows a statistically-significant relationship between Big Five and Locus of Control and total individual value accumulated across the 12 design tasks. Results show the Big Five, aggregating extraversion, agreeableness, conscientiousness, neuroticism, and intellect/imagination to a single factor, negatively affects individual value and internal Locus of Control positively affects individual value. Future work should consider a dedicated experiment to refine understanding of how personality traits influence collaborative systems design and propose interventions to improve collaborative design processes.
Laboratory Experiment of Slide Drilling Tool-Face Control Based on Model Similarity Theory
Authors: Zhong Xiaoyu , Chen Kaidong , Cheng Zaibin , Lu Yingjie , Lu Qiuhai
Published: November 2019

Slide drilling is widely used in directional drilling because of its lower cost, but the tool-face adjustment during the drilling process is almost completed by the driller, and the automatic control has not yet been realized. The main difficulty is that the drill string system has a large amount of contact and friction with the wellbore. Moreover, it is also affected by the viscous force of the mud fluid, which brings more difficulty to achieve accurate dynamic model. Considering that the actual drilling is too costly, it is necessary to establish an indoor experimental system to simulate the response of the slide drilling tool-face, thus providing an experimental platform for the research of the control method. In this paper, the dynamic equation of the torsion process of the drill pipe is established. According to the model similarity theory, the similarity condition of parameters and scale correspondence between the experimental model and the drilling prototype are obtained, which provides the basis for selection of simulated drill pipe and mud. Then the expert PID method is used to realize the automatic tool-face control based on the laboratory experimental system. The experimental results show that the expert PID method can obtain better control effect rather than the traditional PID method, and it could be used in the actual slide drilling because of the dynamic similarity.
Regular 2D and 3D Linkage-Based Origami Tessellations
Authors: Yellowhorse Alden D. , Howell Larry L.
Published: November 2019

Linkage origami is one effective approach for addressing stiffness and accommodating panels of finite size in origami models and tessellations. However, successfully implementing linkage origami in tessellations can be challenging. In this work, multiple theorems are presented that provide criteria for designing origami units or cells that can be assembled into arbitrarily large tessellations. The application of these theorems is demonstrated through examples of tessellations in two and three dimensions.
Complexity Reduction in Mass Customization to Facilitate Better Decision Support
Authors: Banerjee Jai Nath , Mundale Madhura , Sachche Adnan , McComb Christopher
Published: November 2019

Mass customization provides a way to satisfy an increasing number of customers by tailoring product details to their preferences. Moreover, there is a considerable amount of pressure on industries that embrace mass customization in their product portfolios to consistently produce innovative and market defining technology. To ease this pressure, this study offers organizations a perspective on what combination of attributes is most influential on choice when approaching decision support for the purchase of a Configure-to-Order product. Laptops are used here as a case study, but the approach is generalizable to any family of products. This approach first uses metrics gained from a modified conjoint analysis applied to data gathered from a student consumer base. Customer satisfaction is measured as a function of how many product offerings are provided, identifying and quantifying a trade-off between customizability and consumer satisfaction. This aims to cater to the requirements of the consumer base and key business advantages allowing for greater usability and maximum profits.
On the End-Point Deflection of Static Balanced Manipulators With Various Spring Configurations
Authors: Jhuang Chi-Shiun , Chen Dar-Zen
Published: November 2019

This paper presented the accumulation deflection of manipulator with different spring configuration. Spring configurations achieve perfect static balance but they are different in deflection. Assuming the axial deflection is enough smaller than bending deflection and negligible; deflection is small and the link is rigid. Based on gravitational and elastic matrix, for most effective balancing, attachment angles of a spring are determined as four types (90, 0), (270, 90), (0,0) and (180,180). Attachment lengths of a spring are determined by magnitude of gravitational energy. Then, spring force, reaction force and deflection are determined. For illustrated examples, a given manipulator with configuration 4-1 S23 (180,180), S23 (0,0) and 4-2 S34 (180,180), S34 (0,0), the accumulation deflection in global workspace and maximum, minimum and RMS accumulation deflection are presented. In conclusion, the spring configuration 4-1 with S23 (180,180) is the best choice for designers.
On the Deployment of Multistable Kresling Origami-Inspired Structures
Authors: Kidambi Narayanan , Wang K. W.
Published: November 2019

Origami designs have attracted significant attention from researchers seeking to develop new types of deployable structures due to their ability to undergo large and complex yet predictable shape changes. The Kresling pattern, which is based on a natural accumulation of folds and creases during the twist-buckling of a thin-walled cylinder, offers a great example for the design of deployable systems that expand uniaxially into tubes or booms. However, much remains to be understood regarding the characteristics of Kresling-based deployable systems, and their dynamics during the deployment process remain largely unexplored. Hence this research investigates the deployment of Kresling origami-inspired structures, employing a full six-degree-of-freedom truss-based model to study their dynamics under different conditions. Results show that tuning the initial rotation angle of a structure gives rise to several qualitatively distinct mechanical properties and stability characteristics, each of which has different implications for the design of the deployable systems. Dynamic analyses reveal the robustness of Kresling structures to out-of-axis perturbations while remaining compliant in the axial direction. These findings suggest that Kresling-based designs can form the basis for the development of new types of deployable structures and systems with tunable performance.
A New Look to the Three Axes Theorem
Authors: Valderrama-Rodríguez Juan Ignacio , Rico José M. , Cervantes-Sánchez J. Jesús , Pérez-Zamudio Fernando Tomás
Published: November 2019

This paper analyzes the well known three axes theorem under the light of the Lie algebra se(3) of the Euclidean group, SE(3) and the symmetric bilinear forms that can be defined in this algebra. After a brief historical review of the Aronhold-Kennedy theorem and its spatial generalization, the main hypothesis is that the general version of the Aronhold-Kennedy theorem is basically the application of the Killing and Klein forms to the equation that relates the velocity states of three bodies regardless if they are free to move in the space, independent of each other, or they form part of a kinematic chain. Two representative examples are employed to illustrate the hypothesis, one where the rigid bodies are free to move in the space without any connections among them and other concerning a RCCC spatial mechanism.
Loaded Tooth Contact Pattern Analysis for Strain Wave Gear With Non-Elliptical Wave Generator
Authors: Yu Zhiyuan
Published: November 2019

This paper presents a new non-elliptical wave generator for strain wave gear to improve its contact pattern quality. The new wave generator has a polynomial profile at one cross section, then crowned along the lead direction. The lead crowning uses a parabolic function with crowning amount controlled by parabolic coefficient. Loaded tooth contact pattern analysis based on finite element method is used to evaluate the new design. The result shows that the new design will avoid the edge contact between wave generator and flexspline, which reduces contact pressure and improve the wearing life of the gear. It also improves the contact pattern quality of the tooth surface. Comparing with elliptical wave generator, the new wave generator with polynomial profile and lead parabolic crowned surface offers more design freedom to improve strain wave gear’s performance. The parametric equation of the new wave generator is defined intuitively, and it can be easily adapted for any type of strain wave gear. Furthermore, the finite element model for the strain wave gear is a new development and application for Loaded Tooth Contact Analysis (LTCA).
Estimation of Uncertainty Change of Reliability in Adaptive Sampling Under Prediction Uncertainty of Gaussian Process
Authors: Bae Sangjune , Kim Nam H.
Published: November 2019

A novel approach is introduced to estimate the change in the variance of the probability of failure by adding a sample to the Gaussian process (GP) in a conservative manner. Uncertainty in probability stems from prediction uncertainty and GP is used to represent the uncertainty. In the estimation of variance, a single-loop Monte Carlo Simulation (MCS) alleviates the computational burden. The result shows that the proposed methodology well predicts the change by a sample, maintaining the conservativeness by ignoring correlation in GP, yet the computational cost is at the same level as single-loop MCS.
Making Trimmed B-Spline B-Reps Watertight With a Hybrid Representation
Authors: Song Yang , Cohen Elaine
Published: November 2019

Watertightness is an important property for CAD models, yet it is not generally available in commercial systems. This paper introduces watertight hybrid B-spline based B-reps that maintain the original parameterization and representation except in narrow regions around trimming curves, where Bézier triangle type regions seal the model. The new representation matches the model space trimming curve exactly. It can be discretized for analysis and fabrication in a straightforward manner without requiring any post modeling repair operations. We apply this representation to mechanical models and more sculptured models to demonstrate small parametric distortion and arbitrarily small geometric error.
Powered Ankle-Foot Prostheses: A Survey on Sensing Systems and Control Strategies
Authors: Chumacero-Polanco Erik , Yang James
Published: November 2019

People who have suffered a transtibial amputation show diminished ambulation and impaired quality of life. Powered ankle foot prostheses (AFP) are used to recover some mobility of transtibial amputees (TTAs). Powered AFP is an emerging technology that has great potential to improve the quality of life of TTAs with important avenues for research and development in different fields. This paper presents a survey on sensing systems and control strategies applied to powered AFPs. Sensing kinematic and kinetic information in powered AFPs is critical for control. Ankle angle position is commonly obtained via potentiometers and encoders directly installed on the joint, velocities can be estimated using numerical differentiators, and accelerations are normally obtained via inertial measurement units (IMUs). On the other hand, kinetic information is usually obtained via strain gauges and torque sensors. On the other hand, control strategies are classified as high- and low-level control. The high-level control sets the torque or position references based on pattern generators, user’s intent of motion recognition, or finite-state machine. The low-level control usually consists of linear controllers that drive the ankle’s joint position, velocity, or torque to follow an imposed reference signal. The most widely used control strategy is the one based on finite-state machines for the high-level control combined with a proportional-derivative torque control for low-level. Most designs have been experimentally assessed with acceptable results in terms of walking speed. However, some drawbacks related to powered AFP’s weight and autonomy remain to be overcome. Future research should be focused on reducing powered AFP size and weight, increasing energy efficiency, and improving both the high- and the low-level controllers in terms of efficiency and performance.
Convolutional Neural Network-Based Intention Forecasting and Lane Change Path Predicting of the Human Driver
Authors: Yang Kaiming , Yan Zhanhong , Chen Di , Ji Xuewu , Nakano Kimihiko
Published: November 2019

The intention forecasting of the human driver plays an essential role in improving the safety and driver-machine coordination of the co-piloting vehicle, which is the decision-making foundation for driver assistance system (DAS). However, the quantitative prediction of the lane change decision, which determines the occasion and shape of the lane change path, has drawn little attention by the prior works. In this paper, a novel convolutional neural network (CNN)-based predictor that forecasts the driver’s lane change path is proposed. By including the driver’s eye-gazing and head-heading information, an earlier and more accurate prediction of driver’s time to lane change (TLC) and lane change duration (LCD), and we use the positive TLC and negative TLC to represent the classification results LC and RC, respectively. The classification and regression results validated that the inclusion of driver’s gazing information achieved an earlier and more precise detection of driver’s lane change intention. Furthermore, owning to the hierarchical structure of the CNN model and the parallel computing devices, the execution time of the proposed model is shorter and exhibits its powerful real-time computing performance. The estimated TLC and LCD are adopted to predict the driver’s target lane change trajectory with satisfactory accuracy. Therefore, the proposed model enables the DAS to generate a human-like lane change decision to minimize the driver-machine conflicts during lane change.
A Cloud-Based Healthcare Infrastructure for Neonatal Intensive-Care Units
Authors: Migliorelli Lucia , Cenci Annalisa , Bernardini Michele , Romeo Luca , Moccia Sara , Zingaretti Primo
Published: November 2019

Intensive medical attention of preterm babies is crucial to avoid short-term and long-term complications. Within neonatal intensive care units (NICUs), cribs are equipped with electronic devices aimed at: monitoring, administering drugs and supporting clinician in making diagnosis and offer treatments. To manage this huge data flux, a cloud-based healthcare infrastructure that allows data collection from different devices (i.e., patient monitors, bilirubinometers, and transcutaneous bilirubinometers), storage, processing and transferring will be presented. Communication protocols were designed to enable the communication and data transfer between the three different devices and a unique database and an easy to use graphical user interface (GUI) was implemented. The infrastructure is currently used in the “Women’s and Children’s Hospital G.Salesi” in Ancona (Italy), supporting clinicians and health opertators in their daily activities.
Semi-Autonomous Teleoperation, Guidance, and Obstacle Avoidance With Path Adherence
Authors: Budolak Daniel , Chauhan Raghuraj , Ben-Tzvi Pinhas
Published: November 2019

Decreasing user effort and automating subtasks such as obstacle avoidance and user guidance has shown to increase the effectiveness and utility of teleoperation. Extending the capabilities of teleoperation remains a critical research topic for tasks that need to leverage user knowledge, or for unstructured environments that autonomous solutions are not robust enough to handle. Previous methods have focused individually on joint space tasks, regression or training based user intention recognition and intervention, or application specific solutions. To overcome the limitations of these methods, this paper proposes the use of path planning based gross motion assistance with a projection based user intention recognition method, for improving task execution in semi-autonomous teleoperation. The proposed solution synthesizes an assistive architecture that leverages the benefit of supervisory level task identification with semi-autonomous trajectory tracking. With the proposed method, continuous and more immersive teleoperation is achieved, as control states are user selected and task execution is informed from the operator’s motion. The effectiveness of the proposed method is validated with a user study.
Human Computer Interface Using Electroencephalography for Driver Behavior Classification
Authors: Manchala Vamsi K. , Clara Alvaro V. , Subramanian Susheelkumar C. , Redkar Sangram , Sugar Thomas
Published: November 2019

It is important to know and be able to classify the drivers’ behavior as good, bad, keen or aggressive, which would aid in driver assist systems to avoid vehicle crashes. This research attempts to develop, test, and compare the performance of machine learning methods for classifying human driving behavior. It also proposes to correlate driver affective states with the driving behavior. The major contributions of this work are to classify the driver behavior using Electroencephalograph (EEG) while driving simulated vehicle and compare them with the behavior classified using vehicle parameters and affective states. The study involved both classical machine learning techniques such as k-Nearest Neighbor (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) and latest “unsupervised” Hybrid Deep Learning techniques, and compared the accuracy of classification across subjects, various driving scenarios and affective states.
Gaussian Process Based Crack Initiation Modeling for Design of Battery Anode Materials
Authors: Zheng Zhuoyuan , Xu Yanwen , Chen Bo , Wang Pingfeng
Published: November 2019

Silicon-based anode is one of the promising candidates for the next generation lithium ion batteries (LIBs) to achieve high power/energy density. However, the major drawback limiting the practical application of Si anode is that Si experiences significant volume change during its lithiation/de-lithiation cycles, which induces high stress and causes degradation and pulverization of the anode. This study focuses on the crack initiation performances of Si anode during the de-lithiation process. A multi-physics based finite element (FE) model is built to simulate the electrochemical process and crack generation during de-lithiation. On top of that, a Gaussian Processes (GP) based surrogate model is developed to assist the exploration of the crack initiation performances within the anode design space. It is found that, the thickness of the Si coating layer TSi, the yield strength σFc of Si material, the cohesive strength between Si and substrate σFs, and the curvature of the substrate ρ have large impacts on the cracking behavior of Si. This coupled FE simulation-GP surrogate model framework is also applicable to other types of LIB electrodes.
Design for Nonassembly: Current Status and Future Directions
Authors: Jung Sangjin , Laureijs Rianne E. , Combemale Christophe , Whitefoot Kate S.
Published: November 2019

In this paper, we review the literature on design for nonassembly (DFNA) and the broader literature on design for manufacturing that has design guidelines and metrics applicable to nonassembled products, including both monolithic single-part products and nonassembly mechanisms. Our review focuses on guidelines that apply across multiple manufacturing processes. We identify guidelines and metrics that seek to reduce costs as well as provide differentiated products across a product family. We find that existing DFNA guidelines fall into four main categories pertaining to: (1) geometry and size, (2) material, (3) production process, and (4) clearance and tolerances. We also identify existing product family metrics that can be modified for nonassembled products to capture some aspects of these categories. Finally, we discuss possible future research directions to more accurately characterize the relationships between design variables and manufacturing costs, including investigating factors related to the complexity of operations at particular process steps and across process steps.
Efficient Finite Element Formulation for Geometrically Exact Beams
Authors: Bauchau Olivier A. , Han Shilei
Published: November 2019

This paper proposes a new approach to the modeling of geometrically exact beams based on motion interpolation schemes. Motion interpolation schemes yield simple expressions for the sectional strains and linearized strain-motion relationships at the mesh nodes. The classical formulation of the finite element method starts from the weak form of the continuous governing equations obtained from a variational principle. Approximations, typically of a polynomial nature, are introduced to express the continuous displacement field in term of its nodal values. Introducing these approximations into the weak form of the governing equations then yields nonlinear discrete that can be solved with the help of a linearization process. In the proposed approach, the order of the first two steps of the procedure is reversed: approximations are introduced in the variational principle directly and the discrete equations of the problem then follow. This paper has shown that for geometrically exact beams, the discrete equations obtained from the two procedure differ significantly: far simpler discrete equations are obtained from the proposed approach.
Fractional-Order Extreme Learning Machine With Mittag-Leffler Distribution
Authors: Niu Haoyu , Chen Yuquan , Chen YangQuan
Published: November 2019

Extreme Learning Machine (ELM) has a powerful capability to approximate the regression and classification problems for a lot of data. ELM does not need to learn parameters in hidden neurons, which enables ELM to learn a thousand times faster than conventional popular learning algorithms. Since the parameters in the hidden layers are randomly generated, what is the optimal randomness? Lévy distribution, a heavy-tailed distribution, has been shown to be the optimal randomness in an unknown environment for finding some targets. Thus, Lévy distribution is used to generate the parameters in the hidden layers (more likely to reach the optimal parameters) and better computational results are then derived. Since Lévy distribution is a special case of Mittag-Leffler distribution, in this paper, the Mittag-Leffler distribution is used in order to get better performance. We show the procedure of generating the Mittag-Leffler distribution and then the training algorithm using Mittag-Leffler distribution is given. The experimental result shows that the Mittag-Leffler distribution performs similarly as the Lévy distribution, both can reach better performance than the conventional method. Some detailed discussions are finally presented to explain the experimental results.
Finite Element Model of Schallamach Waves in Belt-Drives
Authors: Khattab Mohammed , Wasfy Tamer
Published: November 2019

The objective of this study is to investigate if a high-fidelity finite element model can predict the Schallamach wave phenomenon in belt-drives. To this end a computational model which closely mimics a recently developed one-pulley experimental belt-drive apparatus, was created. The dynamic response predicted by the model is compared to the experiment results in order to demonstrate that the model can be used to predict the Schallamach wave phenomenon. Furthermore, the model is used to investigate the roles of Coulomb friction coefficient, adhesion, and torque direction on stick-slip instability effects.
An Agent-Based Modeling Approach for Clean Technologies Adoption Using Theory of Planned Behavior Based Decision-Making
Authors: Pakravan Mohammad H. , MacCarty Nordica
Published: November 2019

Technology adoption in low-income regions is among the key challenges facing international development projects. Nearly 40% of the world’s population relies on open fires and rudimentary cooking devices exacerbating health outcomes, deforestation, and climatic impacts of inefficient biomass burning. Clean technology alternatives such as clean cookstoves are among the most challenging technologies to approach their target goals through sustainable adoption due to lack of systematic market-driven design for adoption. Thus, a method is needed to provide insight regarding how target customers evaluate and perceive causes for adopting a clean technology. The holistic approach of this study captures the three main aspects of technology adoption through lenses of social networks, individual and society scale beliefs, and rational decision-making behavior. Based on data collected in the Apac region in Northern Uganda, an Agent-Based Model is developed to simulate emerging adoption behavior in a community. Then, four different scenarios investigate how adoption patterns change due to potential changes in technology or intervention strategy. These scenarios include influence of stove malfunctions, price elasticity, information campaigns, and strength of social network. Results suggest that higher adoption rates are achievable if designed technologies are more durable, information campaigns provide realistic expectations for users, policy makers and education programs work toward women’s empowerment, and communal social ties are recognized for influence maximization. Application of this study provides insight for technology designers, project implementers, and policy makers to update their practices for achieving sustainable and to the scale clean technology adoption rates.
Simulation of Nucleation and Grain Growth in Selective Laser Melting of Ti-6Al-4V Alloy
Authors: Liu Dehao , Wang Yan
Published: November 2019

Selective laser melting (SLM) builds parts by selectively melting metallic powders layer by layer with a high-energy laser beam. It has a variety of applications in aerospace, medical device, and other low-volume manufacturing. Nevertheless, the lack of fundamental understanding of the process-structure-property (P-S-P) relationship for better quality control inhibits wider applications of SLM. Recently, a mesoscale simulation approach, called phase-field and thermal lattice Boltzmann method (PF-TLBM), was developed to simulate microstructure evolution of alloys in SLM melt pool with simultaneous consideration of solute transport, heat transfer, phase transition, and latent heat effect. In this paper, a nucleation model is introduced in the PF-TLBM model to simulate heterogeneous nucleation at the boundary of melt pool in SLM. A new method is also developed to estimate the thermal flux out of the SLM melt pool model given a constant cooling rate. The effects of latent heat and cooling rate on dendritic morphology and solute distribution are studied. The simulation results of Ti-6Al-4V alloy suggest that the inclusion of latent heat is necessary because it reveals the details of the formation of secondary arms, reduces overestimated microsegregation, and provides more accurate kinetics of dendritic growth.
Visualizing and Evaluating High-Dimensional Mappings of Sets of High Performance Designs
Authors: Morris Clinton B. , Haberman Michael R. , Seepersad Carolyn C.
Published: November 2019

Design space exploration can reveal the underlying structure of design problems. In a set-based approach, for example, exploration can map sets of designs or regions of the design space that meet specific performance requirements. For some problems, promising designs may cluster in multiple regions of the input design space, and the boundaries of those clusters may be irregularly shaped and difficult to predict. Visualizing the promising regions can clarify the design space structure, but design spaces are typically high-dimensional, making it difficult to visualize the space in three dimensions. To convey the structure of such high-dimensional design regions, a two-stage approach is proposed to (1) identify and (2) visualize each distinct cluster or region of interest in the input design space. This paper focuses on the visualization stage of the approach. Rather than select a singular technique to map high-dimensional design spaces to low-dimensional, visualizable spaces, a selection procedure is investigated. Metrics are available for comparing different visualizations, but the current metrics either overestimate the quality or favor selection of certain visualizations. Therefore, this work introduces and validates a more objective metric, termed preservation, to compare the quality of alternative visualization strategies. Furthermore, a new visualization technique previously unexplored in the design automation community, t-Distributed Neighbor Embedding, is introduced and compared to other visualization strategies. Finally, the new metric and visualization technique are integrated into a two-stage visualization strategy to identify and visualize clusters of high-performance designs for a high-dimensional negative stiffness metamaterials design problem.
Designing and Manufacturing a Super Excellent and Ultra-Cheap Energy Absorber by Origami Engineering
Authors: Zhao Xilu , Hagiwara Ichiro
Published: November 2019

Current vehicle energy absorbers have two defects during collision, such as only 70 % collapsed in its length and high initial peak load. It is because present energy absorbed column is the most primitive from the point of Origami structure. We developed the column so called Reversed Spiral Origami Structure; RSO which solves these 2 defects. However, for RSO, the manufacturing cost of hydroforming in the existing technology is too expensive to be applied in real vehicle structure. To address the problems, a new structure, named Reversed Torsion Origami Structure (RTO), has been developed, which can be manufactured at a low cost by using simple torsion. This structure is possible to replace conventional energy absorbers and it is expected to be widely used such as not only in automobile structures but also in building ones.
Research on Driving Style Classification for Shift Schedule of Dual Clutch Transmissions
Authors: Liu Yonggang , Wang Jiming , Zhao Pan , Sun Dongye , Yang Yang , Qin Datong
Published: November 2019

As one of the most promising vehicle automatic transmission, the dual clutch transmissions (DCT) have become a research hotspot. In order to formulate different shift schedules of DCT to meet economic and comfort requirements, it is necessary to classify and identify driving styles based on vehicle driving data. Accurate classification of driving style is a prerequisite for effective identification, and in this research, a driving style classification method is built based on feature engineering. First, a specified road test is conducted considering the influence factors, in which the driving data is collected, and the driving style is subjectively evaluated. Subsequently, the information entropy is applied to discretize the velocity and the degree of accelerator pedal degree, where 44 feature quantities are extracted to characterize the driving style. Taking into account strong correlation and redundancy between the constructed feature quantities, the principal component analysis (PCA) is employed to reduce the dimension. Finally, the fuzzy c-means (FCM) clustering algorithm is used to classify the driving style. The successful classification rate can reach 92.16% of the subjective scoring result, and is improved by 9.81% comparing with traditional feature quantities. The results show the effectiveness of the proposed driving style classification method, which lays a foundation for the adaptive control of different driving styles for the establishment of an intelligent DCT control system.
Numerical Co-Simulation of Drag Torque in the Gearbox Combined Multibody Dynamics With Moving Particle Semi-Implicit Method
Authors: Zhang Lifu , Wu Guangqiang , Ju Lijuan
Published: November 2019

In the gearbox, lubrication is an important technical measure to improve the friction state of the friction pair and ensure the smooth operation of the mechanical system, and it also plays an important role in cooling, sealing, rust prevention, shock absorption and force transmission. Common lubrication methods in automobile gearbox include dip lubrication, splash lubrication and forced lubrication, but dip and splash lubrication often result in oil churning power loss of the gearbox, and predicting this loss at design stage can help designers to modify the design and improve efficiency. In this paper, the moving particle semi-implicit method is applied to analyze the churning loss of a single helical gear in the transmission system, and the accuracy of the simulation results is verified by experimental data. This research can provide an effective new approach to study the oil churning power loss of gear in transmission.
An Augmented Reality-Based Training System for Manual Milling Operations
Authors: Chuang Tung-Jui , Yang Chih-Kai , Smith Shana
Published: November 2019

This study created an AR-based training system for manual milling machine operation. Users can operate a full-size virtual milling machine with their natural operating behavior, without additional worn or handheld devices. An Intel RealSense R200 camera was used to get the images and the depth information of the real world scenes. A Leap Motion controller was used to track user’s hand motion. Both Intel RealSense R200 and Leap Motion were mounted on an Oculus Rift head-mounted display so that users can freely walk around in the augmented environment to operate the virtual milling machine. A calibration method was developed to solve the dynamic occlusion problem in real time to increase the realism and immersiveness of the system. The system provided a safe learning-by-doing training environment, which was expected to enhance users’ learning effect and reduce accidents. User test results showed that the system was robust and helpful in improving user learning experience in manual milling machining operation.
Thick Folding Through Regionally-Sandwiched Compliant Sheets
Authors: Butler Jared , Pehrson Nathan , Magleby Spencer
Published: November 2019

The regional-sandwiching of compliant sheets (ReCS) technique presented in this work creates flat-foldable, rigid-foldable, and self-deploying thick origami-based mechanisms. Regional-sandwiching of the compliant sheet is used to create mountain/valley assignments for each fold about a vertex, constraining motion to a single branch of folding. Strain energy in deflected flexible members is used to enable self-deployment. This work presents the methods to design origami-based mechanisms using the ReCS technique, including volume trimming at the vertex of the compliant sheet and of the panels used in the sandwich. Physical models of a simple single fold mechanism and a degree-four vertex mechanism are presented to demonstrate the ReCS technique using acrylic panels and spring steel. Consideration is given to the risk of yielding of the compliant sheet due to parasitic motion with possible mitigation of yielding by decreasing the thickness of the sheet.
Compactly Folding Rigid Panels With Uniform Thickness Through Origami and Kirigami
Authors: Yang Jingyi , You Zhong
Published: November 2019

In this paper, we investigate and evaluate origami and kirigami patterns that enable folding arrays made from flat rigid panels with uniform thickness into compact stacks. In deployed state, all panels form a completely flat plane; while in folded state, no voids exist within the stack. Two approaches are proposed. The first approach folds an array of identical rectangular panels into compact stacks. By drawing a Hamiltonian circuit over the array, a method of placing revolute joints is presented. By selecting a symmetric Hamiltonian circuit, we show that the array can be folded into two stacks. The second approach is case specific, which folds arrays consisting of square and half square triangular panels into stacks. Three basic units as well as their combinations are proposed, all of which lead to compact folding. Our designs can be applied to package solar panels for aerospace applications.
Stability Analysis of High-Performance Drones With Suspended Payloads
Authors: Hoang Samantha , Liu Yifeng , Aliseda Alberto , Shen I. Y.
Published: November 2019

This paper studies the stability of a system consisting of a drone with a heavy payload through both linear stability analysis and nonlinear simulations. The stability is studied with respect to two payload parameters: the length of the arm the payload is suspended from and the mass of the payload. Linearizing the drone-payload system around vertical flight results in a linearized system that is marginally stable with five negative, real eigenvalues and seven zero-eigenvalues. The presence of seven zero-eigenvalues makes it difficult to predict the stability of the nonlinear system so nonlinear simulations are completed to understand how the drone-payload system reacts to external disturbances. To directly study the severity of the nonlinear system’s instability, the system is subjected to an initial, one-second wind disturbance that induces different initial conditions on the system. The results of the nonlinear simulations indicate that the presence of a suspended payload will always cause the drone-payload system to be unstable. Both an increase in the length of the payload arm and the payload mass will individually increase the deviation of the system from the expected path.
Periodic Control in a Stick Balancing Problem
Authors: Bencsik Laszlo , Insperger Tamas
Published: November 2019

Understanding the human balancing is a fundamental question. Investigation of simple tasks can help in this challenging problem. In order to describe the nature of the underlying control mechanism, first of all, the balancing force has to be determined. As a second step one can identify the behaviour of the controller. There are two main problems in the model of the whole control process of balancing, time-delay is unknown and the exact mathematical definition of the control goal is also not known. The explanation for this latter issue the classical inverted pendulum model has 2DoF but only one control forces exists, thus it can be handled as a typical underactuated mechanical system. In under-actuated systems the task of inverse dynamics is not well defined. Some degrees-of-freedom cannot directly be controlled, and the corresponding generalized coordinates depend on the system dynamics only. In this study we model the control mechanism as a time periodically (i.e. clock-driven) switched controller. We investigate the stability properties of the closed-loop system. We show a periodically switched controlled which can be a possible model of human balancing.
Closed Form Calculation of Lead Flank Modification Proposal for Spur and Helical Gear Stages
Authors: Weinberger Uwe , Otto Michael K. , Stahl Karsten
Published: November 2019

Due to the growing need for gearboxes to be as lightweight and efficient as possible, it is most important that the gear mesh’s potential is utilized as well as possible. One way of doing that is to define a flank modification that optimally distributes the load over the flank. Best practice for defining a flank modification is to manually check out the load distribution and to define a value of the flank modification. In general, this is an iterative method to get an optimally distributed load. This method can also be automated. To do this, the deformations of the gearbox (shafts, bearings, gear mesh) are calculated. With those results a modification proposal is calculated and applied to the calculation model. As soon as the values for the next additional modification proposal drop under a certain limit, the iteration is finished. This method consumes time and computing power. Additionally, since it is an iteration, does not always converge. A new method for calculating the lead flank modification for all gear stages in the gearbox to be calculated is presented in this paper. The method shown in this paper uses additional degrees of freedom and equations, which are integrated into the linear equation system of the gearbox model. Those degrees of freedom and the equations apply the boundary condition to the model of a constant load distribution. By introducing additional factors in the equations, it is possible to calculate a lead flank modification for an arbitrary load distribution. By integrating these additional degrees of freedom and the equations, only one additional calculation is needed to get a modification proposal. Examples throughout this paper show the results of this method.
A Capacitive MEMS Pressure Sensor With Wavy Membrane and Linear Capacitance-Pressure Response
Authors: Oke Stephen , Shavezipur Mohammad
Published: November 2019

A novel structure for capacitive MEMS pressure sensors is presented that can be used for a wide range of pressure sensing applications. The sensor is designed such that its characteristic capacitance-pressure (C-P) response is highly linear and could cover a wide range of working pressure. A capacitive pressure sensor includes two capacitive electrodes, one patterned on the substrate and the other one suspended creating a sealed cavity. The suspended electrode acts as the pressure sensitive membrane in the device and undergoes out-of-plane deformation when there is a change in ambient pressure, resulting in a change in the device’s capacitance. The design presented in this work uses a wavy-shape membrane with controlled deformations to provide a highly linear C-P response. The wavy shape of the membrane can be fabricated using grey-scale mask and lithography. ANSYS APDL multiphysics solver is used to model and simulate the pressure sensor and optimize its response. The material used in the design and simulations of the pressure sensor is silicon carbide making this design suitable for harsh environment applications. The simulation results show that if the size and the shape of the wave form in the membrane are optimized, highly linear C-P response can be achieved and also its working pressure range can be extended.
An Analytical Investigation of Rattle Characteristics of Powder Metal Gears
Authors: Slavkovsky Elizabeth , Inalpolat Murat , Flodin Anders
Published: November 2019

This study employs an analytical model of a gear pair with transverse-torsional dynamics that allows analysis of single-sided, double-sided, and random rattle situations to contrast rattle characteristics of isotropic PM gears with a baseline steel gearset. This model utilizes time-varying gear mesh stiffness and transmission error as the internal excitation sources and time-varying operating torque as an external excitation. The gear rattle performance of PM gears is investigated under different torque conditions and operating speeds. The system kinetic and potential energy is assessed as an evaluation tool that can indicate the severity of different rattle conditions. The dynamic response of two different versions of an existing PM gear design are compared with a baseline traditional steel gear.
Dual-Arm Manipulators Kinematic Control Under Multiple Constraints via Virtual Joints Approach
Authors: Proietti Pagnotta Daniele , Freddi Alessandro , Longhi Sauro , Monteriù Andrea
Published: November 2019

A kinematic controller for a dual-arm system able to cope with kinematic constraints is presented in this paper. The kinematic controller is designed according to the Relative Jacobian method to achieve cooperation of a couple of 7 DOF robotic arms. The kinematic redundancy obtained from cooperation is exploited to execute other subtasks along the main task. The concept of virtual joint space proposed in the General Weighted Least Norm (GWLN) method is employed in order to include the constraints in the problem. Firstly, the GWLN is reformulated for a dual-arm system, including only the joint limit avoidance subtask. Then, the obstacle avoidance subtask is also considered and a new version of the kinematic controller is derived when the number of constraints is larger than the number of joints. Simulation are performed on the model of the Baxter Robot, in the Matlab-Simulink environment.
Biosensing Mechanism Using Amplitude Voltage Response of Superharmonic Resonance of Fourth Order of Electrostatically Actuated MEMS Cantilever Resonators
Authors: Caruntu Dumitru I. , Reyes Christopher
Published: November 2019

This paper deals with the amplitude voltage response of electrostatically actuated MEMS cantilever resonators undergoing superharmonic resonance of fourth order. This can be used as sensing mechanism. The system consists of a MEMS cantilever beam held parallel to a ground plate with an applied voltage of alternating current (AC) causing the cantilever to vibrate. The driving frequency of the excitation voltage is near one eighth of the first natural frequency of the cantilever. This causes the cantilever to experience superharmonic resonance of order four. In order for this resonance to occur hard excitations are required wherein the magnitude of the excitation voltage must be large enough. This work models the electrostatic force to include fringe effect. The fringe effect is modeled using Palmer’s formula. Reduced order models (ROMs) are used in this work. The methods used to solve these models are 1) the method of multiple scales (MMS), 2) homotopy analysis method (HAM), and 3) numerical integration for ROM with 2 modes of vibration. The amplitude voltage response shows a softening. The response consists of three branches: two stable and one unstable. As the voltage is increased the system is stable until the first saddle-node bifurcation point is reached. Here the system experiences instability and it jumps to higher amplitude on the stable branch. As the voltage is swept down the system is stable until the second saddle-node bifurcation point in high amplitudes is reached and the system jumps down to lower amplitudes on the first stable branch. This is the biosensing mechanism proposed in this work. All three methods show excellent agreement with one another for detuning frequency values up to σ = −0.025. As the magnitude of the detuning frequency increases the MMS and HAM begin to disagree with the time responses obtained from the numerical integration of the ROM with 2 modes of vibration (or terms).

This demonstrates the limitations of MMS and HAM to accurately predict the behavior for hard excitations where the voltage is very high.