bluuebunny/crossref_metadata_2025 huggingface dataset:
Parametric Structural Shape and Topology Optimization With a Variational Distance-Regularized Level Set Method
Authors: Jiang Long , Chen Shikui
Published: December 2016

In conventional level set methods, the slope of the level set function needs to be well controlled to maintain the numerical stability during the topology optimization process. One common solution is to regularize the level set function to be a signed distance function, which is usually achieved by periodically implementing the so called re-initialization scheme to force the level set function to gain the desired signed distance property. However, the re-initialization scheme will bring some unwanted drawbacks to the optimization process, such as zero level set drifting, time consuming etc. In addition, re-initialization is usually implemented outside the optimization loop, which will cause convergence issues. In this paper, a distance regularization functional is introduced to the structural topology optimization objective functional to ensure the signed distance property of the level set function near the structure boundaries. This functional can also keep the level set function to be constant-value at positions far away from the structural boundaries. The radial basis function (RBF) based parameterization technique together with the mathematical programming are utilized to improve the potential capability of handling multiple constraints for the topology optimization. The combination of these two techniques makes the level set based topology optimization be capable of handling complicated multi-constrained problems with higher numerical efficiency, leaving no compromise to multiple drawbacks. To demonstrate the validity of the proposed scheme, benchmark examples on minimum compliance structural optimization are employed. This type of problem is computed by the conventional level set method with the introduced distance regularization functional, the RBF based parametric level set and at last, the distance regularized RBF based parametric level set separately to demonstrate their differences.
Topology Optimization of 3D Auxetic Metamaterials Using Reconciled Level-Set Method
Authors: Vogiatzis Panagiotis , Chen Shikui
Published: December 2016

Metamaterials with extraordinary material properties, not easily found in nature, are of great interest. In this paper, the authors employ topology optimization with a reconciled level-set method in order to design 3D negative Poisson’s ratio designs. The strain energy method has been used to predict the effective properties of the periodically assembled metamaterial, which is based on the resulted unit cell. The sensitivity analysis is derived utilizing the adjoint variable method with the general linear elastic equation combined with a weak imposition of the Dirichlet boundary condition. 3D single-material and multi-material designs have been generated showing the effectiveness of the proposed method. The advantage of the method can be located on the fact that the design can be manufactured by 3D printing, without any post-processing work on the result of the topology optimization, due to the clear boundaries between the different materials.
Meta-Modeling for Enhancing Design Optimization of Electric Motors
Authors: Ji Wei , Feng Xiaolong , Larsson Jonas , Stening Alexander , Gyllensten Freddy , Yang Hongliang
Published: December 2016

In this work, meta-models for use in design optimization of low voltage motors are investigated. The idea is to develop an automated and efficient methodology for design optimization of a family of electric motors. A few widely adopted meta-modeling algorithms are examined with concerns of their accuracy and applicability for design optimization of the motors. Meta-model based optimization is conducted for a case of single motor with two objectives, and another case of a group of motors with shared design variables of cross-section dimensions and with an overall objective of total material cost. Meta-model based optimal designs are verified with that from real solver based optimization.

Computational expense for optimization simulations can be greatly reduced by using meta-models, especially for the family design case. Neural network models give the most satisfactory optimization result among all tested meta-models, in terms of accuracy and variety of the outcome designs in the objective space.

This work demonstrates great potential as well as challenge of meta-modeling technique for use in design optimization of industrial products and processes, where requirement on accuracy and reliability of the surrogate models being high.
A Comparative Study on the Pick-and-Place Trajectories for a Delta Robot
Authors: Xie Zexiao , Wu Peixin , Ren Ping
Published: December 2016

A comparative study on the pick-and-place trajectories for high-speed Delta robots is presented in this paper. The Adept Cycle has been widely accepted as a standardized pick-and-place trajectory for industrial robots. The blending curves and optimization methods to smooth this trajectory are briefly surveyed. Three major types of trajectories: Lamé curves, clothoids and piecewise polynomials, are selected as candidates to be compared. The processes to generate these trajectories are briefly reviewed. The trajectories are firstly compared in term of their computation time. Then, based on a dynamic model and an experimental prototype of the Delta robot, different combinations of the geometric paths and motion profiles are compared in terms of power consumption, terminal state accuracy and residual vibration. The effects of trajectory configurations and parameters on the robot’s dynamic performances are investigated. Through a comprehensive analysis on both simulation and experimental results, a near-optimal pick-and-place trajectory for the Delta robot is identified and validated.
Eco-Feedback Designs: A Balance Between the Quantitative and the Emotional
Authors: Bao Qifang , Shaukat Mian Mobeen , Elantary Asmaa , Yang Maria C.
Published: December 2016

Eco-feedback design is a strategy for encouraging sustainable behavior by making users aware of the resources they consume. Reminding users of their resource usage can help them understand the environmental impacts of their actions and evoke feelings such as sympathy or responsibility for the environment. This study investigated two aspects of presenting resource usage information in eco-feedback designs: the quantitative clarity of the information, and the strength of emotion evoked by the designs. This paper examines how these two aspects of eco-feedback influence users’ perception and preference for the designs. Four design prompts with different levels of quantitative clarity and emotion were used to generate 16 designs. An online survey with these designs was distributed among students at four universities in two countries. Results from 216 valid responses showed evidence that both the quantitative and emotional aspects are important to the eco-feedback designs. The survey also gathered data about respondents’ knowledge about resource consumption. Results suggested that students in technical majors were generally better at estimating resource consumption, and tended to prefer designs with more quantitative data. In contrast, students in non-technical majors generally made less accurate estimates and tended to prefer designs that evoke stronger emotions. These findings could inform designers on how to make more effective eco-feedback designs to promote sustainable behaviors.
Extraction of Impact of Wind Turbulence on RC Helicopters Using Machine Learning
Authors: Kumar Anil , Ben-Tzvi Pinhas
Published: December 2016

This paper presents a new cost effective wireless telemetry system capable of estimating ambient air turbulence using RC helicopters. The proposed telemetry system correlates the RC helicopter’s flight dynamics with ship air wake patterns generated by cruising naval vessels. The telemetry system consists of two instrumentation units each equipped with aviation grade INS/IMU sensors to measure dynamics of the helicopter with respect to the concerned naval vessel. The presented telemetry system extracts ship air wake patterns by removing the helicopter dynamic effects from actual measurements. This paper presents a comprehensive comparison between popular machine learning algorithms in eliminating effects of pilot inputs from helicopter’s dynamics measurements. The system was tested on data collected in a wide range of wind conditions generated by modified YP676 naval training vessel in the Chesapeake Bay area over a period of more than a year.
Dynamic Property Regulation of Axially Functional Graded Beams for Airfoil Structure
Authors: Xin Bo , Zhang Zhaolong , Zhang Jie , Rong Yiming
Published: December 2016

The development of additive manufacturing technology makes it possible to realize a designed distribution of material properties in complex geometry. The distribution can be made not only in layers, but also in the axial direction of a beam. Axially functional graded (AFG) beams may play an important role in light-weight design for airfoil structure in aerospace industry. In this research, the free vibration of AFG cantilever beams is studied by using Euler-Bernoulli beam theory. It is taken into consideration that material properties, including elasticity modulus and mass density vary continuously along the axial direction of AFG beam according to an elliptic load distribution based on the life curve of airfoil. The governing differential equations of motion has been analyzed and solved to calculate the natural frequency and fundamental mode shape accurately. In order to verify the accuracy of the present formulation and results, the natural frequencies and fundamental mode shape of several AFG beams are obtained, and compared with the dynamic simulation results from ABAQUS. Good agreement is observed. The results indicate that the proposed method is effective at forecasting the dynamic property of AFG cantilever beams for airfoil structure.
A Set-Based Method for Multilevel Design of Materials and Structures With Manufacturing Uncertainty
Authors: Morris Clinton , Seepersad Carolyn C. , Haberman Michael R.
Published: December 2016

Recent research has indicated that embedding small volume fractions of negative stiffness (NS) inclusions within a host material can create composites with macroscopic mechanical stiffness and loss properties that exceed conventional composites. To design these composites, a multi-level, set-based approach that employs Bayesian network classifiers was developed to identify sets of satisfactory designs at each level of the multilevel design space. In this paper, manufacturing uncertainties are incorporated to further refine the design space mappings created by the set-based approach. Manufacturing uncertainty refers to the random deviations in dimensions and other properties that often arise when fabricating a specimen. Joint probability distributions are used to model this manufacturing uncertainty. The joint probability distributions are formulated as kernel density estimates that can be based on manufacturing data. The joint probability distributions are incorporated within the set-based approach to identify sets of designs that not only yield satisfactory performance but also offer robustness to manufacturing uncertainty. The approach is demonstrated in the context of hierarchical composite materials, but it can be applied to other multi-level design problems to efficiently yield sets of robustly manufacturable, high performance designs.
Ontology-Based Representation of Design Decision Hierarchies
Authors: Ming Zhenjun , Yan Yan , Wang Guoxin , Panchal Jitesh H. , Goh Chung Hyun , Allen Janet K. , Mistree Farrokh
Published: December 2016

It is efficacious to capture and represent the knowledge for decision support in engineering design. Ontology is a promising knowledge modeling scheme in the engineering domain. In this paper, an ontology is proposed for capturing, representing and documenting the knowledge related to hierarchical decisions in the design of complex engineered systems. The ontology is developed based on the coupled Decision Support Problem (DSP) construct, taking into consideration the requirements for a computational model that represents a decision hierarchy. Key to the ontology is the concept of two classes, namely, Process which represents the basic hierarchy building blocks where the DSPs are embedded, and Interface which represents the DSP information flows that link different Processes to a hierarchy. The efficacy of the ontology is demonstrated using a portal frame design example.
Topology Optimization Under Linear Thermo-Elastic Buckling
Authors: Deng Shiguang , Suresh Krishnan
Published: December 2016

This paper focuses on topology optimization of structures subject to a compressive load in a thermal environment. Such problems are important, for example, in aerospace, where structures are prone to thermally induced buckling.

Popular strategies for thermo-elastic topology optimization include Solid Isotropic Material with Penalization (SIMP) and Rational Approximation of Material Properties (RAMP). However, since both methods fundamentally rely on material parameterization, they are often challenged by: (1) pseudo buckling modes in low-density regions, and (2) ill-conditioned stiffness matrices.

To overcome these, we consider here an alternate level-set approach that relies discrete topological sensitivity. Buckling sensitivity analysis is carried out via direct and adjoint formulations. Augmented Lagrangian method is then used to solve a buckling constrained compliance minimization problem. Finally, 3D numerical experiments illustrate the efficiency of the proposed method.
Simulation Based Approach for the Origami-Performing Robot’s Hardware Design
Authors: Thai Phuong Thao , Savchenko Maria , Hagiwara Ichiro
Published: December 2016

Origami structures are now applied more and more in industry with the advantages of enough stiffness to support weight, but can be folded flat for shipping or storage. Not only ordinary paper with small thickness 0.1mm, but also special paper materials such as cardboard or coated paper, which thickness is bigger (1–2mm) is used for forming origami structures. Therefore, the idea of designing an origami-performing robot to exclude human from folding the target work is now developed and investigated carefully. In this paper, we propose to develop a general simulation-based methodology for the manipulation with the paper origami structures as the basis for the robot design. Firstly, the problems of how to form the crease lines on the structure and the folding sequence on the different thickness of paper sheets by a robot hand are investigated carefully. Secondly, about the configuration of origami performing robot, we consider the reachability of manipulators, kinematics of the designed robot to extent the opportunities of application of robotics to fold the real origami structures in industrial and craft areas. Finally, with the purpose of using the robot for folding wide range of paper sizes’ formats and thickness, we suppose to minimize the size of the robotic system as much as possible to make it light weight and easy to use.
Optimization of Vibration Isolation Mounts With Internal Rotation in Response to Shock Type Inputs
Authors: Smith Eric , Ferri Aldo , Schmitt Griffin
Published: December 2016

The design of isolation mounts is of critical importance in the protection of structures and sensitive equipment from damage or failure. Simultaneous protection from both shock and vibration is particularly challenging because of the broadband nature of the input signal and because of the deleterious effect of damping on high-frequency isolation. Prior work by the authors has shown that chains of translating and rotating mass/spring elements can act as a “mechanical filter” for input disturbances. If designed correctly, the isolator is able to trap some of the input energy into rotational vibration, preventing it from damaging the structure. However, in finite-length chains, wave reflections can result in secondary pulses that hit the structure and can diminish the effectiveness of the isolator. In this paper, the design of dynamic isolation mounts is improved using an optimization technique. Numerical simulations are performed using a parametric model of the new mount design. The simulated annealing optimization algorithm is used to determine the optimal system parameters for a given chain length. It is shown that the optimized system is able to achieve significant performance improvements. It is also shown that dynamic mounts that allow rotational movement of internal elements outperform optimized purely translational-motion systems.
Molecular Dynamics Simulation With Interval-Valued Interatomic Potentials
Authors: Tran Anh , Wang Yan
Published: December 2016

In molecular dynamics (MD) simulation, the two main sources of uncertainty are the interatomic potential functions and thermal fluctuation. The accuracy of the interatomic potential functions plays a vital role toward the reliability of MD simulation prediction. Reliable molecular dynamics (R-MD) is an interval-based MD simulation platform, where atomistic positions and velocities are represented as Kaucher (or generalized) intervals to capture the uncertainty associated with the inter-atomic potentials. The advantage of this uncertainty quantification (UQ) approach is that the uncertainty effect can be assessed on-the-fly with only one run of simulation, and thus the computational time for UQ is significantly reduced. In this paper, an extended interval statistical ensemble is introduced to quantify the uncertainty associated with the system control variables, such as temperature and pressure at each time-step. This method allows for quantifying and propagating the uncertainty in the system as MD simulation advances. An example of interval isothermal-isobaric (NPT) ensemble is implemented to demonstrate the feasibility of applying the intrusive UQ technique toward MD simulation.
Reliability Based Design Optimization Concerning Objective Variation Under Mixed Probabilistic and Interval Uncertainties
Authors: Zhou Jianhua , Xu Min , Li Mian
Published: December 2016

Uncertainties, inevitable in nature, can be classified as probability based and interval based uncertainties, in terms of its representations. Corresponding optimization strategies have been proposed to deal with these two types of uncertainties individually. However, it is more likely that both types of uncertainty occur in one single problem and so it is trivial to treat all uncertainties the same. In this paper a novel formulation for reliability based design optimization (RBDO) under mixed probability and interval uncertainties is proposed, in which the objective variation or the objective robustness is also concerned. Furthermore, it is proposed to efficiently solve the worst case parameter resulted from the interval uncertainty by utilizing the Utopian solution presented in a single-looped robust optimization approach, in which the inner optimization problem can be solved by performing matrix operations. The remaining problem can be solved utilizing any existing RBDO method. This work applies the performance measure approach to search for the most probable failure point (MPFP) and sequential quadratic programming (SQP) to solve the entire problem. Two engineering examples are given to demonstrate the applicability of the proposed approach and to illustrate the necessity to consider the objective robustness under certain circumstances.
Novel Monitoring Method of Hypoid Gear Meshing Based on Thermal Network Model and Infrared Thermography Imagery
Authors: Suzuki Mitsuhiko , Hirogaki Toshiki , Aoyama Eiichi
Published: December 2016

Hypoid gears, used in automobile differentials, have a complex shape; thus, it is difficult to estimate tooth contact conditions. Therefore, a non-contact method of analysis is proposed for determining tooth contact conditions by using high-response thermography to analyze temperature distribution during meshing between the pinion and the gear. High-speed photography was performed using thermography and an extraction line was defined in the obtained thermal images to extract temperature data from them.

Furthermore, we constructed a novel model to predict tooth surface temperature distribution during tooth meshing based on a thermal network model that represents the thermal conductivity of an object by a simple RC circuit. In this report, by comparing the temperature changes obtained from the thermal images with the calculated results, we identify the thermal properties of a material from the thermal images, and discuss the effects of parameters such as heat capacity and thermal resistance. The comparison shows that infrared tooth surface imagery is effective in estimating hypoid gear tooth meshing. That is, by using infrared image and a thermal network model, heat conduction in a gear can be considered. It was confirmed that it is possible to predict temperature rise on tooth surfaces due to gear meshing.
Application of Digital Human Models to Physiotherapy Training
Authors: Kakizaki Takao , Urii Jiro , Endo Mitsuru
Published: December 2016

The importance of physiotherapy is becoming more significant with the increasing number of countries with aging populations. Thus, the education of physiotherapists is a crucial concern in many countries. Information and communications technologies, such as motion capture systems, have been introduced to sophisticate the training methods used in physiotherapy. However, the methods employed in most training schools for physiotherapists and occupational therapists remain dependent on more conventional materials. These materials include conventional textbooks with samples of traditional gait motion photographs and video archives of patients’ walking motion. Actual on-site clinical training is also utilized in current physiotherapy education programs. The present paper addresses an application of previously developed digital human model called kinematic digital human (KDH) to physiotherapy education with a focus on improving students’ understanding of the gait motion of disabled patients. KDH models for use in physiotherapy were constructed based on Rancho Los Amigos National Rehabilitation Center terminology, which is considered the preferred standard among clinicians. The developed KDH models were employed to allow the three-dimensional visualization of the gait motion of a hemiplegic patient.
Limit Points Behavior in Electrostatically Actuated Initially Curved Micro Plate
Authors: Medina Lior , Gilat Rivka , Krylov Slava
Published: December 2016

The axisymmetric snap-through of an initially curved circular micro plate, subjected to a transversal distributed electrostatic force is studied. The analysis is based on a reduced order (RO) model resulting from the Galerkin decomposition, with buckling modes of a flat plate used as the base functions. In order to check the validity of the RO model, the corresponding problem for a displacement-independent (“mechanical”) load is solved, and a comparison between the RO model and those obtained using finite elements (FE) analysis is carried out. It is shown, that the two are in good agreement, indicating that the RO model can be used for a plate undergoing electrostatic loading. However, the study shows that at least three degrees of freedom (DOF) are required for an accurate prediction of the equilibrium path and bistability. The coupled electromechanical analysis shows that due to the nonlinearity of the electrostatic load, the snap-through occurs at a lower displacement than in the case of the “mechanical” load. Moreover, the study concludes that actuation of plates of realistic dimensions can be achieved by reasonably low voltages.
A Decision Support Tool to Foster Sustainability in Industrial Context
Authors: Rossi Marta , Germani Michele , Marconi Marco
Published: December 2016

In the last few years, the environmental problem has become a very serious issue and the research world has answered to this growing interest with the development of a high number of ecodesign methods and tools. However their use in real contexts is still quite low, due to their complexity, time consuming and need for specific knowledge. From this reason, it comes the need for tools that support designers in the implementation of ecodesign strategies.

This paper presents the Case Based Reasoning (CBR) methodology and tool, which represents the knowledge and the best practices for manufacturing products. It supports designers in the re-design process of products, by allowing them to gradually acquire knowledge and to solve problems in a rapid and simplified way, through the collection and sharing of ecodesign knowledge in a structured Database. The tool has been tested into two industrial companies to verify its potentialities, evaluate its usability and identify its limits.
Design and Optimization of a Flexion/Extension Mechanism for a Hand Exoskeleton System
Authors: Bianchi Matteo , Buonamici Francesco , Furferi Rocco , Vanni Niccolò
Published: December 2016

Hand impairments represent a significant category of injuries, which can be limiting and impeding in the execution of Activities of Daily Living (ADLs). As can be widely appreciated in scientific literature, a great number of solutions has been proposed in last years for rehabilitating and assisting the patient in both mechanical (e.g. object manipulation) and also social tasks (e.g. shaking hands). Among the numerous approaches, robotic Hand Exoskeleton Systems (HES) represent a vast class of solutions to the problem, as they have several advantages. Contrarily to functional electrical stimulation techniques, for example, HES devices are less invasive and entail to a lesser induced muscular fatigue.

In the present work, the authors propose the redesign of a HES robotic device developed at the University of Florence, by means of Topological Optimization (TO) techniques. Even if the existing device is already functional and tested it is still characterized by high encumbrances and masses, in disrespect to the functional requirements. The redesign process has been addressed to a future production of the final object prototype in a titanium alloy, by means of an Electron Beam Melting (EBM) 3D printing machine. The entire procedure was carried out starting from a complete kinematic and dynamic study, followed by the application of TO techniques and it was finally validated by Finite Element Method (FEM) analysis. A single-finger mechanism prototype has been fabricated through additive manufacturing (by means of PolyJet technology) to test the ergonomics and aesthetics of the device.

The problem is introduced and contextualized in the Introduction section, while the methodology is subsequently extensively explained, followed by the presentation of the results. In the Conclusion section, the discussion of the process and the result is presented, while possible improving and developments are briefly hinted at.
Design and Study for Dynamics Characteristics of Double-Layer Loop Deployable Antenna Mechanism
Authors: Guo Hongwei , Shi Chuang , Tang Yuzhen , Liu Rongqiang , Deng Zongquan
Published: December 2016

In order to design lightweight and high stiffness large-sized deployable antenna mechanism, a kind of slider crank basic deployable mechanism unit which is driven by elastic hinges and one sort of double-layer loop deployable antennas mechanism which is composed of the units are put forward. In this paper, the method of finite element dynamic models for double-layer loop deployable antenna mechanism and the control variable method are combined to conclude the interaction relationship between the fundamental frequency of double-layer loop deployable antenna with the mechanism geometric parameters of the antenna diameter, height, thickness and other geometrical parameters of the double layer loop antenna. On this basis, an empirical formula of fundamental frequency calculation of double-layer loop deployable antenna mechanism is achieved. According to the performance of the frequency of the antenna mechanism, the antenna diameter is divided into small diameter, large diameter and super large diameter three grades. The influences of the mass and the stiffness of antenna mechanism are taken into comprehensive consideration, then a comprehensive evaluation index of the single-layer and double-layer loop deployable antenna mechanism characteristics is set up to make comparative analysis of the dynamic characteristics of the unfolded single-layer and double-layer deployable antenna mechanism with different diameters. It is concluded that the applicable diameter range of the single-layer loop deployable mechanism is 1m to 20m, while the applicable diameter range of the double-layer loop is 20m to 100m.
Geometrically Graded Origami Tubes
Authors: Xie Ruikang , Hou Degao , Ma Jiayao , Chen Yan , You Zhong
Published: December 2016

Functionally graded structures existing in nature can achieve adaptive mechanical properties in response to external loadings through optimizing material distribution. In this paper, a family of origami tubes with systematically varied geometrical parameters are designed and their axial crushing behaviors are analyzed numerically to investigate the concept of inducing graded response through geometrical variation. Three rigid origami patterns are chosen to form the graded origami tubes, and three approaches are adopted to vary tube geometries, including changing the dihedral angle, changing the number of units, and the combinations of them. Numerical results indicate that compared with normal tubes with uniform geometry which have reaction forces with periodic peaks of very close magnitudes, graded origami tubes shows reaction force curves that have different peak values at different stages of deformation. As a result, the amount of axial deformation of the tubes depends on the magnitude of external forces. In the optimal case, a reaction force, the peaks of which are approximately aligned along an ascending straight line, is generated by a tube with both varied dihedral angles and number of units. This work demonstrates that systematic geometrical variation in origami tubes has great potential to trigger graded response.
Nonlinear Deformation Analysis of Superelastic Flexure Hinges
Authors: Yang Miao , Lin Junxian , Du Zhijiang , Dong Wei
Published: December 2016

The motion capability of a flexure hinge made of shape memory alloy (SMA) can be greatly improved because of the material’s superelasticity. In this paper, the nonlinear deformation characteristics of a superelastic flexure hinge are analyzed. The flexure hinge is considered as a non-prismatic cantilever beam subjected to a combined load at the free end. Superelastic behavior of the SMA is represented by Auricchio’s constitutive model. Govern equations of the large deformation superelastic flexure hinge are derived by using the Bernoulli-Euler beam theory and solved numerically. Based on the static deformation model, the rotation capacity, the stiffness characteristic and the rotation error of the flexure hinge are discussed respectively. Numerical examples compared with Finite Element analysis (FEA) show the accuracy of the proposed methodology.
Analyzing the Robustness of Two-Scale Command Shaping for Reducing Powertrain Vibration During Engine Restart
Authors: Wilbanks J. Justin , Leamy Michael J.
Published: December 2016

This paper analyzes the robustness of a two-scale command shaping strategy for reducing vibrations in hybrid electric vehicle (HEV) powertrains during engine restart. Propagation of HEVs through the automobile market depends on their perceived quality and performance. In this work, a two-scale command shaping strategy addresses the drivability of the vehicle by focusing on the reduction of noise, vibration, and harshness (NVH) issues associated with restarting the internal combustion engine (ICE) during a mode transition. The strategy tailors the electric machine (EM) torque profile, which consists of a linear and time-varying component, to significantly mitigate the powertrain and chassis vibrations for a smoother ICE startup. The time-varying EM torque component is calculated by applying a perturbation technique for separating the scales of an analytical ICE model, which isolates the ICE nonlinear response. Command shaping is then applied to the linear problem governed by the remaining scale. Simulations confirm that the two-scale command shaping strategy is a straightforward technique for reducing powertrain and chassis vibrations during ICE restart. In real-time implementation, inaccuracies or variations in system parameters and initial conditions arising from the operating condition or from general wear during a vehicle’s life cycle will occur. Therefore, successful implementation of the two-scale command shaping strategy relies upon the robustness of the perturbation technique and command shaping to these variations. This paper validates the perturbation technique’s robustness to variations in the ICE parameters and initial conditions. Robust command shaping methods are also explored to decrease the impact of system parameter variations on the efficacy of command shaping. Improving the overall robustness of the two-scale command shaping strategy will increase the applicability to consumer HEVs by ensuring its performance under variations in system parameters.
A Gesture-Based Application for Aspiring Orchestra Conductors
Authors: Cavalieri Lorenzo , Mengoni Maura , Germani Michele
Published: December 2016

A product is chosen by users not only for the features it offers but also for the perceived experience of use. This statement widely recognized in literature highlight that key issues for the success of interactive products are the practical, experiential, affective, meaningful and valuable aspects of interaction.

In the last years, gesture-based interfaces have been introduced to make the experience of interaction more emotional, intuitive and natural. For this reason, the design and development of products integrated gesture-based interfaces represent a challenging issue.

In this context, a User-Centered Design (UCD) method to implement novel interaction paradigms into traditional consumer products is proposed. Its application in a real case study addresses the development and prototyping of a system exploiting gesture-based interaction to train aspiring conductors of orchestra. If a young musician wants to play a guitar, it is usually no great problem to find one, but if a musician wants to learn the ins and outs of being a conductor, the problem shifts to search for an electronic device managed by hands as used by conductors. The developed system provides three main functionalities: tempo control, velocity control and instruments activation. It represents both a use case to validate the proposed UCD method and an innovative solution in the context of aspiring conductor’s training.
Process Control Using a Novel Machine Tool Equipped With Automatic Idling Reduction System
Authors: Ota Ryo , Sato Wataru , Aoyama Eiichi , Hirogaki Toshiki
Published: December 2016

A novel concept named sustainable development has come to be considered important to prevent the intensification of climate change. Thus, there have been many reports about the environmental load of consumer goods such as home electronics, car electronics, and so on. However, there have been few reports about the environmental load of industrial goods. Specifically, there has been no report dealing with the environmental load of compact five-axis controlled machine tools and how to use linear-axes and rotational-axes in them.

Then, a suitable end-milling process to reduce the power consumption with a compact five-axis controlled machine tool equipped with an automatic idling reduction servo system by using the developed formula have been discussed. As a result, the combined method of downsizing the machine tool, using suitable control axes, and equipping the machine tool with an automatic idling reduction servo system is found to be effective in reducing the power consumption in a manufacturing process.
Estimating Reliability Bounds on Industrial Plants
Authors: Hein Andreas M. , Farel Romain
Published: December 2016

Reliability analysis is particularly relevant for industrial plants where plant failures can lead to large financial losses. Existing reliability analysis approaches mostly rely on heavy-weight simulations that are computationally expensive and require extensive modeling effort. On the other hand, there is an industrial need for quickly evaluating plant reliability for developing new services and business models. In this paper, we extend and apply the reliability bound approach using linear programming to address this need. The reliability bound approach is based on a system model in the form of a graph, an event vector, and estimates for component reliabilities. Based on this model, lower and upper reliability bounds are calculated by solving a linear programming problem. The advantage of this approach is the ubiquity of solvers for linear programming. Furthermore, the approach is guaranteed to produce the narrowest bound with respect to the reliability data. We demonstrate the applicability of the approach to a subsystem of an industrial plant as a test case. Future work consists applying the method to whole plants and comparing the results with simulation-based approaches. Moreover, the approach is planned to be extended to system attributes such as buffers and multiple failure states.
Multidisciplinary Analysis and Product Family Optimization of Front-Loading Washing Machines
Authors: Jung Sangjin , Simpson Timothy W.
Published: December 2016

In the past decade, the market share of front-loading washing machines has seen explosive growth in the United States. As a result, many companies are now offering families of front-loading washing machines with a variety of features and options. Understanding the tradeoffs within these product families is challenging as existing research has focused primarily on a single disciplinary analysis (e.g., dynamic analysis, strength analysis); few models exist for cleanliness, reliability, energy efficiency, etc. In this paper, we introduce a new integrated multidisciplinary analysis using simulations, mathematical models, and response surface models based on the ratings of product attributes. In order to determine feasible design solutions for a front-loading washer family, we formulate a product family design problem using deviation functions and a product family penalty function. A multi-objective genetic algorithm is applied to solve the proposed formulation, and the results indicate that designers can successfully determine solutions for the best performance, most common, and compromise families of front-loading washers.
Design and Prototype of a Tunable Stiffness Arm for Safe Human-Robot Interaction
Authors: She Yu , Su Hai-Jun , Lai Cheng , Meng Deshan
Published: December 2016

In this paper, we present a tunable stiffness robot link for safe human-robot interaction. Stiffness of a manipulator determines the injury levels of a human from an impact between robots and operators, given a specific impact velocity. Compliance of a robot manipulator includes joint compliance and link compliance. Variable stiffness design from the viewpoint of actuators have been widely studied, while adjustable stiffness robotic link in the application of human robot interaction is rare in literatures. This paper details the design of a tunable stiffness robotic manipulator via four bar linkages which are actuated by servo motors. A 3D model of the morphing beam is constructed, and a robot which is made up of 3 morphing arms is designed. Prototypes using 3D printer are fabricated. Numerous tests have been done, and the results show that the stiffness is able to change 3.6 times given a morphing angle of π/4. Given an impact velocity of 2.2 m/s, the impact tests show that the acceleration has a 19.4% decrease comparing the curved beam and straight beam, and the head injury criteria (HIC) significantly decreases from 210.3 m5/2s−4 to 150.3 m5/2s−4, which is much safer to the operators. This paper explores the research of tunable stiffness on robotic links in the application of human robot interaction, expanding the research arena with regarding to human safe robot design.
Intelligent Genetic Algorithm Crossover Operators for Market-Driven Design
Authors: Young Kevin M. , Ferguson Scott M.
Published: December 2016

Heuristic algorithms have been adopted as a means of developing solutions for complex problems within the design community. Previous research has looked into the implications of genetic algorithm tuning when applied to solving product line optimization problems. This study investigates the effects of developing informed heuristic operators for product line optimization problems, specifically in regards to optimizing the market share of preference of an automobile product line. Informed crossover operators constitute operators that use problem-related information to inform their actions within the algorithm. For this study, a crossover operator that alters its actions based on the relative market share of preference for each product within product lines was found to be most effective. The presented results indicate a significant improvement in computational efficiency and increases in market share of preference when compared to a standard scattered crossover approach. Future work in this subject will investigate the development of additional informed selection and mutation operators, as well as problem informed schema.
Multimode Input Shaping Control of Flexible Structures Using Frequency Modulation
Authors: Masoud Ziyad N. , Alhazza Khaled A. , Nazzal Mohammad A.
Published: December 2016

Bulky rigid robotic arms require significantly large energy-consuming actuators. Lighter flexible robotic manipulators have many advantages over rigid manipulators in terms of cost, energy consumption, and speed. However, their structural flexibility compromises operation precision. This paper presents a multimode frequency-modulation input shaping control strategy for a flexible hanging beam performing rest-to-rest maneuvers. Frequency-modulation input shaping is used to produce shaped acceleration commands to the beam support. Model-based feedback is used to modulate the frequencies of the beam so that all higher mode frequencies become odd-integer multiples of the fundamental frequency of the feedback system. Single-mode input shaping techniques are implemented to eliminate vibrations in all modes of the model-based feedback system, and hence, the flexible beam. Numerical simulations are used to demonstrate the performance effectiveness of the proposed strategy.
Waveform Invariance in Nonlinear Periodic Systems Using Higher-Order Multiple Scales
Authors: Fronk Matthew , Leamy Michael J.
Published: December 2016

This paper carries-out a higher-order, multiple scales perturbation analysis on nonlinear monoatomic and diatomic chains with the intent of predicting invariant waveforms. The chains incorporate linear, quadratic, and cubic force-displacement relationships, and linear dampers. Multi-harmonic results for 1st and 2nd order expansions are reported in closed form, while results for the 3rd order are computed numerically on a case-by-case basis, thus avoiding difficulties associated with large symbolic expressions. Dimensionless parameters are introduced which characterize the amplitude-dependent nonlinear nature of a given chain. Interpretation of the perturbation solutions suggests that the nonlinear chains support certain waveforms which propagate invariantly; i.e., the spectral content does not change significantly over time and space. Numerical simulations confirm this finding using initial conditions corresponding to a specific order of the perturbation solution, and subsequent FFT’s of the response track the growth (or decay) of spatial harmonic content. A variance parameter computes mean fluctuation of the harmonics about their initial values. For a variety of parameter sets, the numerical studies confirm that spectral variance reduces when waves receive 2nd order initial conditions as compared to 1st order ones. Furthermore, chains given 3rd order initial conditions exhibit smaller variance when compared to those given 1st and 2nd order ones. The studies’ results suggest that introducing higher-order multiple scales perturbation analysis captures long-term, non-localized invariant waves (or cnoidal waves), which have the potential for propagating coherent information over long distances.
Automated Extraction of System Structure Knowledge From Text
Authors: Cheong Hyunmin , Li Wei , Iorio Francesco
Published: December 2016

This paper presents a method to automatically extract structure knowledge of mechanical systems from natural language text. The current work extends our prior work on extracting function knowledge from text, which was presented at last year’s conference. The method uses rules based on a combination of syntactic, lexical, and redundancy information to identify structure knowledge from parsed text. Three case studies were conducted to evaluate the method. The case studies involved extracting physical connections among a known set of components of a bicycle frame, an internal combustion engine, and a drum brake from Wikipedia. The current work makes progress toward addressing the challenge of knowledge acquisition for knowledge-based CAD systems.
Strain Energy Trapping due to Energetic Asymmetry in Modular Structures Inspired by Muscle Cross-Bridges
Authors: Kidambi Narayanan , Harne R. L. , Wang K. W.
Published: December 2016

The remarkable energetic versatility and adaptability of skeletal muscle provides great inspiration to develop advanced adaptive structures and materials. These notable properties may arise from the assembly of skeletal muscle’s nanoscale cross-bridges into microscale structures known as sarcomeres. Essential understanding of muscle energetics has been developed from models of the micro/nanoscale constituents which incorporate an intriguing, asymmetric, bistable potential energy landscape to capture trends in the experimental data on cross-bridge power stroke motions. Inspired by the capability of cross-bridges to strategically absorb and store elastic energy for achieving high energetic efficiency of sudden motions, this research studies the assembly of modular mechanical structures from asymmetrically bistable constituents to absorb and trap energy in higher-energy stable configurations. Specifically, energy features of a module with an asymmetrically bistable element are first studied; these modules are then assembled in series and parallel to generate structures with multiple stable configurations having different quantities of stored energy. Dynamic analyses are performed to illustrate the ability of these structures to trap a portion of the kinetic energy due to an impulsive excitation as recoverable and reusable strain energy, and insight is gained into how asymmetries and damping influence the energy trapping performance.
A Taylor Expansion Approach for Computing Structural Performance Variation Over a Shape Population
Authors: Wang Xilu , Qian Xiaoping
Published: December 2016

In this paper, we present a formal and efficient method for computing structural performance variation over its shape population. Each shape in the population is represented as discrete points. These shapes are then aligned together and principal component analysis is conducted to obtain the shape variation, which is represented as a sum of variations in multiple principal modes. Finite element analysis is conducted on the mean shape. For each shape specified by the shape parameters, we then invoke a thin-plate deformation based scheme to automatically deform the mesh nodes. The performance of the shapes is approximated via Taylor series expansion of the FE solution of the mean shape. Numerical study illustrates the accuracy and efficiency of this method.