bluuebunny/crossref_metadata_2025 huggingface dataset:
Modular Modeling Method for Energy Analysis of the Mechanical Servo Press
Authors: Tao Jing , Li Lu , Yu Suiran , Peng Qingjin
Published: January 2016

This paper aims to develop the energy flow model of mechanical servo press, which serves as the quantitative analysis tool for servo press energy efficiency optimization. A modular modeling method is used to address the variety of component configuration and complexity in electromechanical coupling mechanisms of mechanical servo press. Based on the general function principles and structure model of the servo motor drive linkage press, the consisting modules of the energy analysis model are first identified and interactions between modules are established. Then, the module of the servo motor and linkage mechanism, which are the major configurable parts are presented with more details. A case study of six-bar servo press energy analysis using the proposed model is also presented. The proposed method can strengthen product model building and enhance the convenience of energy efficiency design of mechanical servo press.
Shape Optimization of 2D Compliant Links for Design of Inherently Safe Robots
Authors: She Yu , Su Hai-Jun , Hurd Carter J.
Published: January 2016

In this paper, we represent a preliminary work towards the design of compliant mechanisms for human safe co-robots. We developed a shape optimization framework for design of planar compliant links for inherently safe robotic manipulators. It is well known intentionally introducing compliance to mechanical design can increase safety of robots. However traditional approaches such as elastic joints or uniform compliant links, were either at the cost of significantly reduced performance or with increased extra complexity and cost. Here, we propose a novel method to design compliant robotic links with a safety constraint which is quantified by Head Injury Criterion (HIC). The robotic links are modeled as a 2D beam with a variable width. Given a safety threshold i.e. HIC constraint, the width of the beam is optimized to give a uniform distribution of HIC along the longitudinal direction of the link. Links with a uniform HIC distribution have a better control performance. Finally, this solution is validated by an huamn-robot impact simulation program built in Matlab.
Flexible Design of Systems Considering Time-Dependent Reliability
Authors: Pandey Vijitashwa , Mourelatos Zissimos P. , Skowronska Annette
Published: January 2016

Many repairable systems degrade with time and are subjected to time-varying loads. Their characteristics may change over time considerably, making the assessment of their performance and hence their design difficult. To address this issue, we introduce in this paper the concept of flexible design of repairable systems under time-dependent reliability considerations. In flexible design, the system can be modified in the future to accommodate uncertain events. As a result, regardless of how uncertainty resolves itself, a modification is available that will keep the system close to optimal provided failure events have been properly characterized. We discuss how flexible design of repairable systems requires a fundamentally new approach and demonstrate its advantages using the design of a hydrokinetic turbine. Our results show that long-term metrics are improved when time-dependent characteristics and flexibility are considered together.
Stiffness Design, Analysis and Validation of a Parallel-Mechanism Equivalent Suspension System
Authors: Qiu Chen , Zhang Ketao , Zhao Jing Shan , Dai Jian S.
Published: January 2016

This paper provides a systematic approach to design a vehicle’s independent suspension system. In this approach, multi-link type suspension is selected. By treating it as a parallel mechanism, both the kinematic design and force analysis are conducted in the same framework of screw theory. Regarding the kinematic design, constraint-based approach is used to find suitable layouts of constraint limbs in accordance with desired degree of freedom. In the force analysis, stiffness matrix of the suspension mechanism is developed, leading to the deformation and stress analysis under various critical loads. The developed formulae are further utilized to design suitable suspension mechanism, followed by finite-element-simulation validation as well as optimization design to reduce the resulted maximum stresses.
A Computational Model of Human Perception With Prior Expectation: Bayesian Integration and Efficient Coding
Authors: Yanagisawa Hideyoshi
Published: January 2016

Human perception of sensory stimuli is affected by prior prediction of the sensory experience. For example, perception of weight of an object changes depending on weight predicted with size of the object appearance. We call such psychological phenomena expectation effect. The expectation effect is a key factor to explain a gap between physical variables and their perceptions. In this paper, we propose a novel computational model of human perception involving the expectation effect. We hypothesized that perceived physical variable was estimated using a Bayesian integration of prior prediction and sensory likelihood of a physical variable. We applied efficient coding hypothesis to form a shape of sensory likelihood. We formalized the expectation effect as a function of three factors: expectation error (difference between predicted and actual physical variables), prediction uncertainty (variance of prior distributions), and external noise (variance of noise distributions convolved with likelihood). Using the model, we conducted computer simulations to analyze the behavior of two opposite patterns of expectation effect, that is, assimilation and contrast. The results of the simulation revealed that 1) the pattern of expectation effect shifted from assimilation to contrast as the prediction error increased, 2) uncertainty decreased the extent of the expectation effect, 3) and external noise increased the assimilation.
Designing Variable-Geometry Extrusion Dies That Utilize Planar Shape-Changing Rigid-Body Mechanisms
Authors: Li Bingjue , Murray Andrew P. , Myszka David H.
Published: January 2016

This paper presents a kinematic synthesis methodology for planar shape-changing rigid-body mechanisms that addresses constraints arising in the design of variable-geometry polymer extrusion dies. Such a die is capable of morphing its orifice in order to create extrusions of non-constant cross section. A variable-geometry shape-changing die problem is defined by a set of design profiles of different shapes and arc lengths, which approximate various cross sections of the extrusion. The primary advantage of the presented methodology is addressing the need for bodies in the mechanism formed by fusing links in the shape-changing portion of the chain. Previous methodologies included such fused links, but only at the end of the synthesis process where revolute joints were seen to be underutilized. A new method is needed to control, or even eliminate the use of revolute joints in the shape-changing chain of rigid links. The result of this new work is an iterative method which generates an optimized morphing chain to best match the design profiles while minimizing the number of prismatic and revolute joints needed to do so. The additional variable-geometry design constraints also require a generalization to the definition of fixed-end profiles previously proposed, also allowing chain ends to be defined by prismatic joints on a fixed line of slide. A virtual-chain method is also proposed to solve closure problems caused by the reduction in the number of revolute joints.
Sensitivity and Correlation Analysis and Implications in Scalable Product Family Design for Plug-In Hybrid Electric Vehicles
Authors: Pirmoradi Zhila , Wang G. Gary
Published: January 2016

Plug-in Hybrid Electric Vehicles (PHEVs) bear great promises for increasing fuel economy and decreasing greenhouse gas emissions by the use of advanced battery technologies and green energy resources. The design of a PHEV highly depends on several factors such as the selected powertrain configuration, control strategy, sizes of drivetrain components, expected range for propulsion purely by electric energy, known as AER, and the assumed driving conditions. Accordingly, design of PHEV powertrains for diverse customer segments requires thorough consideration of the market needs and the specific performance expectations of each segment. From the manufacturing perspective, these parameters provide the opportunity of mass customization because of the high degree of freedom, especially when the component sizes and control parameters are simultaneously assessed. Based on a nonconventional sensitivity and correlation analysis performed on a simulation model for power-split PHEVs in this study, the product family design (PFD) concept and its implications will be investigated, and limitations of PFD for such a complex product along with directions for efficient family design of PHEVs will be discussed.
Fundamentals of a Mereo-Operandi Theory to Support Transdisciplinary Modeling and Co-Design of Cyber-Physical Systems
Authors: Horváth Imre , Pourtalebi Shahab
Published: January 2016

The main statement of this paper is that synergetic modeling and co-design of the hardware, software and cyberware parts of complex cyber-physical systems (CPSs) are yet not solved, even from the perspective of an underpinning transdisciplinary theory. CPSs contain functionally tightly connected analog and digital hardware, control, and application software, and knowledge, data, and media contents as cyberware. The lack of a unified theoretical framework and an all-inclusive system conceptualization methodology can be traced back to professional, methodological and cultural differences between the abovementioned domains of development. The objective of our research is to make a step towards a theoretical framework that can support transdisciplinary modeling of CPSs. Architectural and operational modeling have been identified as two principal and interrelated dimensions of system modeling, and a mereo-operandi theory (MOT) has been identified as target. Mereotopology has been considered as the basis of architectural modeling. Operational modeling has been based on parameterized representation of the underlying physical principles, the morphological characteristics, the operation elements, and the overall operation flows. A demonstrative case study is presented to evidence the practical feasibility and utility of the proposed MOT. Our follow up research will focus on using this as a conceptual framework and computational basis for specification of system manifestation features and on a computational implementation to support embedded customization.
Evaluating Industrial Products in an Innovative Visual-Olfactory Environment
Authors: Carulli Marina , Bordegoni Monica , Cugini Umberto
Published: January 2016

The sense of smell has a great importance in our daily life. In recent years, smells have been used for marketing purposes with the aim of improving the person’s mood and of communicating information about products as household cleaners and food. However, the scent design discipline can be also applied to any kind of products to communicate their features to customers. In the area of Virtual Reality several researches have focused on integrating smells in virtual environments. The research questions addressed in this work concern whether Virtual Prototypes, including the sense of smell, can be used for evaluating products as effectively as studies performed in real environments, and also whether smells can contribute to increase the users’ sense of presence in the virtual environment. For this purpose, a Virtual Reality experimental framework including a prototype of a wearable olfactory display has been set up, and experimental tests have been performed.
Membrane Shape and Transverse Load Reconstruction Using Inverse FEM
Authors: Alioli Mattia , Masarati Pierangelo , Morandini Marco , Carpenter Trenton , Osterberg N. Brent , Albertani Roberto
Published: January 2016

Thin structural components characterize a broad class of Micro-Aerial Vehicles (MAV). This work presents an original approach for the determination of transverse load distribution based on distributed strain measurements. A variational formulation is developed for the inverse problem of the reconstruction of full-field structural displacement of membrane wings subjected to static and unsteady loads. Surface strain measurements are estimated from Digital Image Correlation (DIC). Moving Least Squares are used to smooth and remap measurements as needed by the inverse solution meshing, and to map the structural and fluid interface kinematics and loads during the fluid-structure co-simulation. The inverse analysis is verified by reconstructing the deformed solution obtained with an analogous direct formulation, based on nonlinear membrane structural analysis implemented in a general-purpose multibody solver and tightly coupled in co-simulation with a CFD solver. The direct analysis is performed on a different mesh and subsequently re-sampled. Both the direct and the inverse analyses are validated by comparing the direct predictions and the reconstructed deformations with experimental data for prestressed rectangular membranes subjected to static and unsteady loads. The reconstructed load distributions are compared with the corresponding ones obtained using the direct analysis.
Analysis on Three-Mode Configurations of Power-Split Hybrid Electric Vehicle
Authors: Liu Chunwang , Hu Jibin , Peng Zengxiong , Yang Shujun
Published: January 2016

A systematic analysis methodology is proposed to design the suitable three-mode configurations based on the lever model. Based upon the torque and speed relationship among four powertrain elements, three suitable configurations are selected. In designing dual-mode powertrain, method of adding the number of PG and the DOF of configuration are applied based on the compound split mode. On the basis of dual-mode powertrain, three-mode powertrains are designed though adding input split in low speed ratio or compound split in high speed ratio. Comparing the relationship of motor’s speed and torque in dual-mode and three-mode powertrains separately, the structure which has low requirements for motors is selected.
A Set-Based Design Method for Material-Geometry Structures by Design Space Mapping
Authors: Rosen David W.
Published: January 2016

The objective of this work is a multiscale, set-based design method for mechanical components and their manufacturing processes and materials with interactive identification of feasible design regions. A unique aspect of the proposed method is the ability to adjust both material properties, through process planning, and part geometry, through exploration of various cellular structures (e.g., lattices, honeycombs), in order to achieve design goals. More specifically, the proposed design method can effectively explore the achievement of desired mechanical properties by controlling process conditions, material properties, and/or selecting appropriate feature configurations. Material process-property relationships and cellular structure structure-property relationships are modeled to create a comprehensive multiscale design space mapping database. Bayesian network classifiers enable real-time “inverse mapping” that identify feasible regions of the unit cell, feature, and process spaces, thus providing immediate feedback to the designer regarding the feasibility of the current component design. The design method is demonstrated on a class of mechanical components that are manufactured by electron-beam melting (EBM) in Ti-6Al-4V.
Casimir Effect on Simultaneous Resonances of Electrostatically Actuated MEMS Resonators
Authors: Caruntu Dumitru I. , Reyes Christian
Published: January 2016

This paper deals with the influence of Casimir effect on MEMS resonator sensors under double electrostatic actuation and simultaneous resonances. The MEMS cantilever is between two parallel plates (electrodes) under soft AC double actuation. The AC voltage with the bottom electrode is of frequency near half natural frequency of the resonator and the AC voltage with the top electrode is of frequency near natural frequency of the resonator. The method of multiple scales is used to model the behavior of the system. In the model the damping, fringing, voltage, and Casimir forces are taken into consideration and the effects of these parameters on the frequency response are reported. Designing MEMS resonators for applications in fields such as automotive and biomedical can benefit from this work.
The Kinematic Principle for Designing DNA Origami Mechanisms: Challenges and Opportunities
Authors: Su Hai-Jun , Castro Carlos E. , Marras Alexander E. , Zhou Lifeng
Published: January 2016

DNA origami nanotechnology is a recently developed self-assembly process for design and fabrication of complex 3D nanostructures using DNA as functional materials. This paper aims to review our recent progress in applying DNA origami to design of kinematic mechanisms of nanometer scale. These nanomechanisms, which we call DNA Origami Mechanisms (DOM), are made of relatively stiff bundles of double-stranded DNA (dsDNA) which function as rigid links, connected by highly compliant single-stranded DNA (ssDNA) strands which function as kinematic joints. The designs of kinematic joints such as revolute, prismatic, cylindrical, universal and spherical are presented. The steps as well as necessary software or experimental tools for designing DOM with DNA origami links and joints are detailed. To demonstrate the designs, we presented the designs of Bennett 4-bar and crank-slider linkages. At last, a list of technical challenges such as design automation, computational modeling are presented. These challenges could also be opportunities for mechanism and robotics community to apply the well developed kinematic theories and computational tools to design of nanorobots and nanomachines.
ecoRacer: Game-Based Optimal Electric Vehicle Design and Driver Control Using Human Players
Authors: Ren Yi , Bayrak Alparslan Emrah , Papalambros Panos Y.
Published: January 2016

We investigate the cost and benefit of crowdsourcing solutions to an NP-complete powertrain design and control problem. Specifically, we cast this optimization problem as an online competition, and received 2391 game plays by 124 anonymous players during the first week from the launch. We compare the performance of human players against that of the Efficient Global Optimization (EGO) algorithm. We show that while only a small portion of human players can outperform the algorithm in long term, players tend to formulate good heuristics early on, from where good solutions can be extracted and used to constrain the solution space. Incorporating this constraint into the search enhances the efficiency of the algorithm, even for problem settings different from the game. These findings indicate that human computation is promising in solving comprehensible and computationally hard optimal design and control problems.
Time-Dependent Reliability Analysis of Vibratory Systems With Random Parameters
Authors: Mourelatos Zissimos P. , Majcher Monica , Geroulas Vasileios
Published: January 2016

The field of random vibrations of large-scale systems with millions of degrees of freedom is of significant importance in many engineering disciplines. In this paper, we propose a method to calculate the time-dependent reliability of linear vibratory systems with random parameters excited by non-stationary Gaussian processes. The approach combines principles of random vibrations, the total probability theorem and recent advances in time-dependent reliability using an integral equation involving the up-crossing and joint up-crossing rates. A space-filling design, such as optimal symmetric Latin hypercube sampling, is first used to sample the input parameter space. For each design point, the corresponding conditional time-dependent probability of failure is calculated efficiently using random vibrations principles to obtain the statistics of the output process and an efficient numerical estimation of the up-crossing and joint up-crossing rates. A time-dependent metamodel is then created between the input parameters and the output conditional probabilities allowing us to estimate the conditional probabilities for any set of input parameters. The total probability theorem is finally applied to calculate the time-dependent probability of failure. The proposed method is demonstrated using a vibratory beam example.
Forward Kinematic Analysis of Non-Deterministic Articulated Multibody Systems With Kinematically Closed-Loops in Polynomial Chaos Expansion Scheme
Authors: Sabet Sahand , Poursina Mohammad
Published: January 2016

This paper presents the method of polynomial chaos expansion (PCE) for the forward kinematic analysis of nondeterministic multibody systems with kinematically closed-loops. The PCE provides an efficient mathematical framework to introduce uncertainty to the system. This is accomplished by compactly projecting each stochastic response output and random input onto the space of appropriate independent orthogonal polynomial base functions. This paper presents the detailed formulation of the kinematics of a constrained multibody system at the position, velocity, and acceleration levels in the PCE scheme. This analysis is performed by projecting the governing kinematic constraint equations of the system onto the space of appropriate polynomial base functions. Furthermore, forward kinematic analysis is conducted at the position, velocity, and acceleration levels for a non-deterministic four-bar mechanism with single and multiple uncertain parameters in the length of linkages of the system. Time efficiency and accuracy of the intrusive PCE approach are compared with the traditionally used Monte Carlo method. The results demonstrate the drastic increase in the computational time of Monte Carlo method when analyzing complex systems with a large number of uncertain parameters while the intrusive PCE provides better accuracy with much less computation complexity.
Solar Power Ramp Events Detection Using an Optimized Swinging Door Algorithm
Authors: Cui Mingjian , Zhang Jie , Florita Anthony , Hodge Bri-Mathias , Ke Deping , Sun Yuanzhang
Published: January 2016

Solar power ramp events (SPREs) significantly influence the integration of solar power on non-clear days and threaten the reliable and economic operation of power systems. Accurately extracting solar power ramps becomes more important with increasing levels of solar power penetrations in power systems. In this paper, we develop an optimized swinging door algorithm (OpSDA) to enhance the state of the art in SPRE detection. First, the swinging door algorithm (SDA) is utilized to segregate measured solar power generation into consecutive segments in a piecewise linear fashion. Then we use a dynamic programming approach to combine adjacent segments into significant ramps when the decision thresholds are met. In addition, the expected SPREs occurring in clear-sky solar power conditions are removed. Measured solar power data from Tucson Electric Power is used to assess the performance of the proposed methodology. OpSDA is compared to two other ramp detection methods: the SDA and the L1-Ramp Detect with Sliding Window (L1-SW) method. The statistical results show the validity and effectiveness of the proposed method. OpSDA can significantly improve the performance of the SDA, and it can perform as well as or better than L1-SW with substantially less computation time.
Decomposition-Based Design Optimization of Hybrid Electric Powertrain Architectures: Simultaneous Configuration and Sizing Design
Authors: Bayrak Alparslan Emrah , Kang Namwoo , Papalambros Panos Y.
Published: January 2016

Effective electrification of automotive vehicles requires designing the powertrain’s configuration along with sizing its components for a particular vehicle type. Employing planetary gear systems in hybrid electric vehicle powertrain architectures allows various architecture alternatives to be explored, including single-mode architectures that are based on a fixed configuration and multi-mode architectures that allow switching power flow configuration during vehicle operation. Previous studies have addressed the configuration and sizing problems separately. However, the two problems are coupled and must be optimized together to achieve system optimality. An all-in-one system solution approach to the combined problem is not viable due to the high complexity of the resulting optimization problem. In this paper we propose a partitioning and coordination strategy based on Analytical Target Cascading for simultaneous design of powertrain configuration and sizing for given vehicle applications. The capability of the proposed design framework is demonstrated by designing powertrains with one and two planetary gears for a mid-size passenger vehicle.
Nonlinear Harmonic Vibration Analysis of a Fully Clamped Micro-Beam
Authors: Sadri Mehran , Younesian Davood , Esmailzadeh Ebrahim
Published: January 2016

Nonlinear harmonic vibration analysis of a clamped-clamped micro-beam is studied in this paper. Nonlinear forced vibration of a special kind of micro-actuators is examined for the first time. Galerkin method is employed to derive the equation of motion of the micro-beam with two symmetric potential wells. An electric force composed of DC and AC components is applied to the structure. Multiple Scales method (MSM) is used to solve the nonlinear equation of motion. Primary and secondary resonances are taken into account and steady-state response of the microbeam is obtained. A parametric study is then carried out to investigate the effects of different parameters on the amplitude-frequency curves. Finally, phase plot and Poincare map have been taken into consideration to investigate the influence of the amplitude of the harmonic excitation on stability of the microelectromechanical system.
Modeling Consumer Decisions on Returning End-of-Use Products Considering Design Features and Consumer Interactions: An Agent Based Simulation Approach
Authors: Raihanian Mashhadi Ardeshir , Esmaeilian Behzad , Behdad Sara
Published: January 2016

As electronic waste (e-waste) becomes one of the fastest growing environmental concerns, remanufacturing is considered as a promising solution. However, the profitability of take back systems is hampered by several factors including the lack of information on the quantity and timing of to-be-returned used products to a remanufacturing facility. Product design features, consumers’ awareness of recycling opportunities, socio-demographic information, peer pressure, and the tendency of customer to keep used items in storage are among contributing factors in increasing uncertainties in the waste stream. Predicting customer choice decisions on returning back used products, including both the time in which the customer will stop using the product and the end-of-use decisions (e.g. storage, resell, through away, and return to the waste stream) could help manufacturers have a better estimation of the return trend. The objective of this paper is to develop an Agent Based Simulation (ABS) model integrated with Discrete Choice Analysis (DCA) technique to predict consumer decisions on the End-of-Use (EOU) products. The proposed simulation tool aims at investigating the impact of design features, interaction among individual consumers and socio-demographic characteristics of end users on the number of returns. A numerical example of cellphone take-back system has been provided to show the application of the model.
Predictive Modeling of Product Returns for Remanufacturing
Authors: Ma Jungmok , Kim Harrison M.
Published: January 2016

As awareness of environmental issues increases, the pressures from the public and policy makers have forced OEMs to consider remanufacturing as the key product design option. In order to make the remanufacturing operations more profitable, forecasting product returns is critical with regards to the uncertainty in quantity and timing. This paper proposes a predictive model selection algorithm to deal with the uncertainty by identifying better predictive models. Unlike other major approaches in literature (distributed lag model or DLM), the predictive model selection algorithm focuses on the predictive power over new or future returns. The proposed algorithm extends the set of candidate models that should be considered: autoregressive integrated moving average or ARIMA (previous returns for future returns), DLM (previous sales for future returns), and mixed model (both previous sales and returns for future returns). The prediction performance measure from holdout samples is used to find a better model among them. The case study of reusable bottles shows that one of the candidate models, ARIMA, can predict better than the DLM depending on the relationships between returns and sales. The univariate model is widely unexplored due to the criticism that the model cannot utilize the previous sales. Another candidate model, mixed model, can provide a chance to find a better predictive model by combining the ARIMA and DLM. The case study also shows that the DLM in the predictive model selection algorithm can provide a good predictive performance when there are relatively strong and static relationships between returns and sales.
Design as a Sequential Decision Process: A Method for Reducing Design Set Space Using Models to Bound Objectives
Authors: Miller Simon W. , Simpson Timothy W. , Yukish Michael A.
Published: January 2016

Design is a sequential decision process that increases the detail of modeling and analysis while simultaneously decreasing the space of alternatives considered. In a decision theoretic framework, low-fidelity models help decision-makers identify regions of interest in the tradespace and cull others prior to constructing more computationally expensive models of higher fidelity. The method presented herein demonstrates design as a sequence of finite decision epochs through a search space defined by the extent of the set of designs under consideration, and the level of analytic fidelity subjected to each design. Previous work has shown that multi-fidelity modeling can aid in rapid optimization of the design space when high-fidelity models are coupled with low-fidelity models. This paper offers two contributions to the design community: (1) a model of design as a sequential decision process of refinement using progressively more accurate and expensive models, and (2) a connected approach for how conceptual models couple with detailed models. Formal definitions of the process are provided, and a simple one-dimensional example is presented to demonstrate the use of sequential multi-fidelity modeling in determining an optimal modeling selection policy.
An Adaptive Copula-Based Approach for Model Bias Characterization
Authors: Pan Hao , Xi Zhimin , Yang Ren-Jye
Published: January 2016

A copula-based approach for model bias characterization was previously proposed (18) aiming at improving prediction accuracy compared to other model characterization approaches such as regression and Gaussian Process. This paper proposes an adaptive copula-based approach for model bias identification to enhance the available methodology. The main idea is to use cluster analysis to pre-process data, then apply the copula-based approach using information from each cluster. The final prediction accumulates predictions obtained from each cluster. Two case studies will be used to demonstrate the superiority of the adaptive copula-based approach over its predecessor.
Online Estimation of Lithium-Ion Battery Capacity Using Sparse Bayesian Learning
Authors: Hu Chao , Jain Gaurav , Schmidt Craig , Strief Carrie , Sullivan Melani
Published: January 2016

Lithium-ion (Li-ion) rechargeable batteries are used as one of the major energy storage components for implantable medical devices. Reliability of Li-ion batteries used in these devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, patients and physicians. To ensure a Li-ion battery operates reliably, it is important to develop health monitoring techniques that accurately estimate the capacity of the battery throughout its life-time. This paper presents a sparse Bayesian learning method that utilizes the charge voltage and current measurements to estimate the capacity of a Li-ion battery used in an implantable medical device. Relevance Vector Machine (RVM) is employed as a probabilistic kernel regression method to learn the complex dependency of the battery capacity on the characteristic features that are extracted from the charge voltage and current measurements. Owing to the sparsity property of RVM, the proposed method generates a reduced-scale regression model that consumes only a small fraction of the CPU time required by a full-scale model, which makes online capacity estimation computationally efficient. 10 years’ continuous cycling data and post-explant cycling data obtained from Li-ion prismatic cells are used to verify the performance of the proposed method.
Development of Wheel Chair With Center Articulated Body and Autonomous Control System
Authors: Takita Yoshihiro , Ohkawa Shinya , Date Hisashi
Published: January 2016

Our research object is to develop a wheel chair that is able to climb up and down stairs. Conventional wheel chairs use a parallel two-wheel type mobile base that is effective for moving on even surfaces but has limited clearance, posing difficulties in climbing over obstacles. In IROS2014, authors proposed and demonstrated an Octal Wheel unit that has 8 wheels with link-mechanisms and is able to climb up and down stairs. This robot is just a prototype to show the effectiveness of the mechanism. This research has begun to develop an AR chair that is able to carry a passenger, move autonomously, and climb up and down stairs. The first step of the AR chair project is to develop and construct a wheel chair with a center articulated body. The 8-wheel mechanism is applied to the AR chair model after the construction of an autonomous system. A control system with 3D LIDAR was installed on the prototype and it autonomously moved 1.4km in the Real World Robotics Challenge (RWRC) 2014 in Tsukuba on the official pedestrian road. Experimental results demonstrate the effectiveness of this method.
Expectation Design Based on User’s Cognitive Process
Authors: Ueda Kazutaka , Nagai Ayami
Published: January 2016

In today’s market, points of contact between users and products now extend to pre-product release situations such as rollout events. In order to design an attractive product that exceeds users’ expectations, it is necessary to take into account a set of cognitive processes associated with the user experience, such as product expectations and the memories of product-related experiences that led to the formation of these expectations. This study aimed to model the situation surrounding users’ expectations and to elucidate the mechanisms regulating these expectations. To do so, situations in which expectations arise were experimentally reproduced, participants predicted their future emotions based on emotional valence and probability of occurrence, and a hypothetical model was verified. Furthermore, focusing on participants’ feelings of self-efficacy formed by past experiences and their subjective view of the probability of events occurring as regulating parameters of future emotional states, it was found that they are connected to changes in emotional valence when predicting emotions.
Development of a Conservative Model Validation Approach for Reliable Analysis
Authors: Moon Min-Yeong , Choi K. K. , Cho Hyunkyoo , Gaul Nicholas , Lamb David , Gorsich David
Published: January 2016

Simulation models are approximations of real-world physical systems. Therefore, simulation model validation is necessary for the simulation-based design process to provide reliable products. However, due to the cost of product testing, experimental data in the context of model validation is limited for a given design. When the experimental data is limited, a true output PDF cannot be correctly obtained. Therefore, reliable target output PDF needs to be used to update the simulation model. In this paper, a new model validation approach is proposed to obtain a conservative estimation of the target output PDF for validation of the simulation model in reliability analysis. The proposed method considers the uncertainty induced by insufficient experimental data in estimation of predicted output PDFs by using Bayesian analysis. Then, a target output PDF and a probability of failure are selected from these predicted output PDFs at a user-specified conservativeness level for validation. For validation, the calibration parameter and model bias are optimized to minimize a validation measure of the simulation output PDF and the conservative target output PDF subject to the conservative probability of failure. For the optimization, accurate sensitivity of the validation measure is obtained using the complex variable method (CVM) for sensitivity analysis. As the target output PDF satisfies the user-specified conservativeness level, the validated simulation model provides a conservative representation of the experimental data. A simply supported beam is used to carry out the convergence study and demonstrate that the proposed method establishes a conservatively reliable simulation model.
Design and Validation of a Dynamic Digital Ruler for Hands-Free Chronic Wound Assessment
Authors: Dumesnil Etienne , Konda Divya , Aldaz Gabriel , Ookhin Hnin , Pickham David , Shluzas Lauren Aquino
Published: January 2016

This paper documents the design and validation of a measurement tool for chronic wound assessment. Using the Google Glass™ head-mounted display (HMD) as a platform for research, we developed a digital ruler to dynamically capture wound dimensions in a hands-free manner. The system consists of the Glass HMD equipped with an infrared light emitting diode (IR-LED) distance sensor, lithium polymer battery, and a custom printed circuit board. Programmed using Android 4.4.2 (API 19), orthogonal rulers along the X and Y axes are superimposed on the Glass eyepiece and calibrated for measurement accuracy. To evaluate system performance, we conducted an ANOVA Gage Repeatability and Reproducibility (R&R) analysis with six wound care nurses measuring seven artificial wounds of various dimensions, two times each. Data was analyzed using Minitab statistical software. For width measurements, the results indicate that the total Gage R&R percent contribution was 10.2%, with 4.2% attributed to equipment variation (repeatability) and 6.0% to operator variation (reproducibility). Wound-to-wound variation was 89.8%. For length measurements, the total Gage R&R percent contribution was 16.7%, with 14.1% attributed to equipment variation and 2.6% to operator variation. Wound-to-wound length variation was 83.3%. The system received positive feedback from nurses as a hands-free measurement tool for sterile wound handling. Yet, further refinements are needed to improve system accuracy and depth measurement capabilities.
Analyzing Motion Properties of Proteins Affected by Localized Structures From a Robot Kinematics Perspective
Authors: Arikawa Keisuke
Published: January 2016

On the basis of robot kinematics, we have thus far developed a method for predicting the motion of proteins from their 3D structural data given in the Protein Data Bank (PDB data). In this method, proteins are modeled as serial manipulators constrained by springs and the structural compliance properties of the models are evaluated. We focus on localized instead of whole structures of proteins. Employing the same model used in our method of motion prediction, the motion properties of the localized structures and the relation between the motion properties of localized and whole structures are analyzed. First, we present a method for graphically expressing the deformation of objects with a complex shape, such as proteins, by approximating the shape as a rectangular prism with a mesh on its surface. We then formulate a method for comparing the motion properties of localized structures cleaved from the whole structure and those remaining in it by expressing the motion of the latter using the decomposed motion modes of the former according to the structural compliance. Finally, we show a method for evaluating the effect of a localized structure on the motion properties of proteins by applying forces to localized structures. In the formulations, we demonstrate applications as illustrative examples using the PDB data of a real protein.
Experimental Study of Manufacture and Mechanical Behavior of Sandwich Structure With Composite Foldcores
Authors: Jiang Kaiyu , Cai Keqian , Wang Minjie , Zhao Danyang , You Zhong
Published: January 2016

Foldcore Sandwich structures with high specific strength and specific stiffness will be the aeronautic and astronautic main load-carrying structure materials. Curing process temperature of the Carbon and Kevlar prepreg materials were determined by the best curing process extrapolation method. And then, three dimensional foldcore specimens were manufactured by hot-pressing and piecewise curing molding process. In the compression test, compression force-displacement variation laws and deformation failure modes of the foldcores with different thickness were studied by changing the thickness of core wall. Furthermore, the panel constraints on the properties of compression are studied by pasting panel on the bottom of core and both sides of the core. The researches shows: the compression strength and compression modulus was multiplied increased, and the brittle degree of core was increased with the core wall thickness increasing. The panel restriction for foldcore greatly improved the compression modulus and compression strength.
Latching Criteria in Bistable Prestressed Curved Micro Beams
Authors: Medina Lior , Gilat Rivka , Krylov Slava
Published: January 2016

Curved beams subjected to transverse force may exhibit a latching phenomena, namely remain in their buckled configuration under zero force such that an opposite force is required for their release. In this study, we investigate the latching in bistable electrostatically actuated prestressed curved beams. The analysis is based on a reduced order (RO) model resulting from the Galerkin decomposition with buckling modes of a straight beam as base functions. Criteria for the existence of latching are derived in terms of the beam geometric parameters and the axial load. Two conditions are formulated: A necessary criterion establishes the appearance of latching on the symmetric response curve and a sufficient condition which assures the existence of latching in the presence of bifurcations. A comparison between the model results and those obtained by numerical analysis shows good agreement up to a certain elevation. It is noted that as the latching is not affected by the nonlinear electrostatic load, the obtained criteria stand for all types of loading.
Takagi-Sugeno Model Based Simulation Data Mining for Efficient Product Design
Authors: Li Xin , Shao Yanli , Liu Yusheng
Published: January 2016

Simulation-driven design has become the mainstream design scheme. Generally, the designer have to design from scratch and repeat the design and analysis cycle until the design satisfies its expected objectives whenever faced new design requirements as the product development is an iterative process. Therefore, it is not an easy task for the designer to efficiently reuse the huge simulation data to improve the design process since what can be reused is the knowledge rather than the simulation data themselves. In this study, Takagi-Sugeno (TS) model based simulation data mining approach is proposed to uncover the intrinsic relationship between the key design parameters and global performance parameters in order to guide the design optimization with the aim to improve product design process. Firstly, an intermediate model which supports global prediction of the simulation results is proposed and its corresponding simulation results are computed based on the mapping and interpolation algorithm. Then the TS model is trained based on the identification algorithm and is further optimized to improve the prediction accuracy. Finally, the approach of TS model based simulation data mining is applied to the actual simulation data sets to demonstrate its feasibility and effectiveness. The experimental results show that the proposed approach can achieve great prediction accuracy on the global performance evaluation as well as local performance evaluation.
An Experimental Investigation of the Dynamic Behavior of an In-Plane MEMS Shallow Arch Under Electrostatic Excitation
Authors: Ramini Abdallah , Hafiz Abdullah , Bellaredj Mohammed L. F. , Al Hennawi Qais M. , Younis Mohammad I.
Published: January 2016

We present experimental investigation of the nonlinear dynamics of a clamped-clamped in-plane MEMS shallow arch when excited by an electrostatic force. We explore the dynamic behaviors of the in-plane motion of the shallow arches via frequency sweeps in the neighborhood of the first resonance frequency. The shallow arch response is video microscopy recorded and analyzed by means of digital imaging. The experimental data show local softening behavior for small DC and AC loads. For high voltages, the experimental investigation reveals interesting dynamics, where the arch exhibits a dynamic snap-through behavior. These attractive experimental results verify the previously reported complex behavior of in-plane MEMS arches and show promising results to implement these structures for variety of sensing and actuation applications.
Automated Import of XML-Files Containing Optimized Geometric Data to 3D-CAD-Models of Non-Linear Integral Bifurcated Sheet Metal Parts
Authors: Weber Martins Thiago , Albrecht Katharina , Anderl Reiner
Published: January 2016

The Collaborative Research Centre 666 has the focus on researching fundamental new methods for the development of optimized products and production processes for integral bifurcated sheet metal parts. Technological innovations have been achieved with respect to new production processes such as linear flow splitting and linear bend splitting as well as to produce products with flexible profiles.

The use of state of art product development methodologies can be applied but these are not optimized to deal with the high complexity of the requirements and properties of integral bifurcated sheet metal products. In order to deal with that complexity a new approach of a product development methodology, the algorithm based product development process, has been established. Within the scope of the algorithm based product development methodology a topology optimization, based on mathematical algorithms using product requirements information, is already applied in the conceptual steps of product development process. By using this methodological approach an optimized concept of bifurcated sheet metal can be determined. The results are stored as optimized geometric data in XML-format files. 3D-CAD-Models are generated based on these data.

However the import of these data into 3D-CAD-Systems are not fully automated. The developed data model, from earlier works for linear flow splitting and linear bend splitting, does not take into account the variability of the profiles in the third-dimension. In addition the topology optimization does not provide production-orientated design requirements and therefore it does not take into account the production process limits (of linear flow splitting and linear bend splitting). Hence 3D-CAD-Models resulting from the optimized geometric data need to be adapted manually.

Therefore new advanced approaches in terms of virtual product development tools need to be explored. This paper describes the development of an interface within the CAD-System Siemens NX which supports the automatic import of XML-files containing the optimized geometric data of non-linear integral bifurcated sheet metal in 3D-CAD-Models. The existing data model is extended considering the requirements of the developed interface in order to represent nonlinear bifurcated profiles. An approach of the interface using the described data model and the NX Open API is introduced and explained.