bluuebunny/crossref_metadata_2025 huggingface dataset:
A Bi-Level Optimization Approach for Energy Allocation Problems
Authors: Biswas Arpan , Chen Yong , Hoyle Christopher
Published: November 2018

In our previous paper,[1] we have integrated the Robust Optimization framework with the Real Options model to evaluate flexibility, introducing the Flexible-Robust Objective. Flexibility is defined as the energy left to allocate after meeting daily demands. This integration proved more efficient in risk evaluation in energy allocation problems. However, the integration has some limitations in applying operational and physical constraints of the reservoirs. In this paper, an in-depth analysis of all the limitations is discussed. To overcome those limitations and ensure a conceptually correct approach, a bilevel programming approach has been introduced in the second stage of the model to solve the energy allocation problem. We define the proposed model in this paper as Two-Stage, Bi-Level Flexible-Robust Optimization. Stage 1 provides the maximum total flexibility that can be allocated throughout the optimization period. Stage 2 uses bi-level optimization. The Stage 2 upper level sets the target allocation of flexibility in each iteration and maximizes net revenue along with the evaluation of allocated flexibility by the real options model. The Stage 2 lower level minimizes the deviation between the level 1 target and the achievable solution, ensuring no violation in physical and operational constraints of the reservoirs. Some compatibility issues have been identified in integrating the two levels, which have been discussed and solved successfully; the model provides an optimal achievable allocation of flexibility by maximizing net revenue and minimizing violation of constraints. Uncertainty in the objective function and constraints has been handled by converting into a robust objective and probabilistic constraints, respectively. Both classical methods (SQP) and evolutionary methods (GA) with continuous decision variables have been applied to solving the optimization problem, and the results are compared. Also, the result has been compared with the simplified version in previous paper, which was limited to randomly generate discrete decision variables. The new results provided an 8% improvement over the previous simplified model.
On-Field Measurements of the Dissipated Vibrational Power of an SUV Car Traditional Viscous Shock Absorber
Authors: Abdelkareem Mohamed A. A. , Xu Lin , Ali Mohamed Kamal Ahmed , Hassan Mohamed A. , Elagouz Ahmed , Zou Junyi
Published: November 2018

The current paper provides some on-field measurements regarding the quantification of the dissipated power during the damping process of a traditional viscous shock absorber. In this regard, the HAVAL H8 SUV was driven for several trips on the Nanhu campus arena considering a velocity range of 20–50 km/h. Furthermore, two species of campus road sections were selected during the fabricated tests; straight road section with and without a speed bump. The acceleration signals of the rear-right suspension system (body and wheel) were acquired as the average power dissipation trend could be calculated from the relative suspension velocity. The findings of this investigation indicate that the average dissipated power of a traditional shock absorber can be in a range of 10–90 W for a speed range of 20–50 km/h driving on a campus road section free of speed bumps. Whilst, for another road segment with one speed bump, the shock absorber dissipated a kinetic energy between 40–140 W for a velocity range of 20–50 km/h. Suggesting that an average overall dissipated power of 160–560 W is available by means of the traditional shock absorbers. The results are of strategic interest for the researchers and vehicle manufacturers for further considerations in terms of regenerative suspension systems where a part of this energy could be harvested instead of being wholly dissipated.
Sub g Threshold Acceleration Sensor Incorporating Latched Bistable Beam
Authors: Medina Lior , Gilat Rivka , Krylov Slava
Published: November 2018

We present a concept and a theoretical feasibility study of a sub g threshold inertial micro sensor, which incorporates a curved bistable beam as a suspension element. For certain range of geometric parameters such a beam can exhibit lathing, namely remain in its switched configuration at zero actuating force. Since the device can be released from its latched state by an external acceleration force, it can therefore serve as a threshold inertial switch. While the snap-through force, associated with the switching from the initial to the buckled state, cannot be reduced without decreasing the frequency of the device, the release value of the acceleration can be tailored to be arbitrarily low. This allows design of a devices with sufficiently high stiffness in the initial and latched configurations, but with a very low release threshold. Our model show that for appropriately chosen parameters, it is possible to design a sub g threshold acceleration micro switch of realistic dimensions.
Observer-Based Power Management for Multi-Source Electric Vehicles Using Optimized Splitting Ratios
Authors: Ali Ahmed M. , Söffker Dirk
Published: November 2018

Optimal power management in real-time is a core technology of hybrid electric vehicles (HEVs). The online application of optimized power split ratios based on driver demand is a promising approach allowing near optimal power handling decisions in real-time. However, the fulfillment of exact power delivery (driveability) is an open challenge of this approach due to interpolation of driver’s demand to the optimized discrete solutions. Finding balanced power management that handles unscheduled loads and sustains required power conversion efficiency may significantly improve the experimental application of this approach. This work proposes an observer-based control method integrated to the power management system that ensures better driveability with minimal effect on power handling optimality. Modeling of traction system for observer design is based on a simplified brushless DC motor model. Identification of system parameters is achieved by a newly introduced error minimization algorithm using NSGA-II to obtain the same dynamic response as the original system. Results analysis shows 7% reduction of power consumption and 98% improvement of driveability at minimal mitigation of power conversion efficiency.
A Pareto Trade-Off Analysis of Cost Versus Greenhouse Gas Emissions for a Model of a Mid-Sized Vehicle With Various Powertrains
Authors: Hamza Karim , Laberteaux Kenneth P. , Willard John , Chu Kang-Ching
Published: November 2018

This paper presents a simulation-based analysis of a model of a mid-sized vehicle while exploring powertrains of interest. In addition to a baseline conventional vehicle (CV), the explored powertrain architectures include: hybrid electric vehicle (HEV), plugin hybrid electric vehicle (PHEV) and batterW2Wy-only electric vehicle (BEV). The modeling also considers several different all electric driving range (AER) of the PHEVs and BEVs. Fuel economy/energy-efficiency assessment is conducted by with open source software (FASTSim), and by analyzing a large set of real-world driving trips from California Household Travel Survey (CHTS-2013), which contains a record of more than 65 thousand trips with one second interval recording of the vehicle seed. Gas and/or electric energy usage from the analyzed trips are then used to generate greenhouse gas (GHG) statistical distributions (in units of gm-CO2/mile) for a modelled vehicle powertrain. Gas and/or electric energy usage are also utilized in the calculation of the running cost, and ultimately the net average cost (in units of $/mile) for the modelled powertrains. Pareto trade-off analysis (Cost vs GHG) is then conducted for four sub-population segments of CHTS vehicle samples in a baseline scenario as well as four future-looking scenarios where carbon intensity in electric power generation gets lower, gas gets more expensive and batteries get less expensive. While noting limitations of the conducted analysis, key findings suggest that: i) mix of PHEVs and BEVs with various AER that is properly matched to driver needs would be better than one single powertrain design for all drivers, and ii) electrified powertrains do not become cost-competitive in their own right (without incentives or subsidies) until some of the future battery technology goals are attained.
Force Analysis and Mechanical Design of a Novel 3-DOF Parallel Mechanism
Authors: Zhang Dongsheng , Xu Yundou , Yao Jiantao , Zhou Yulin , Zhao Yongsheng
Published: November 2018

Parallel mechanisms (PMs) with two rotational degrees-of-freedom (DOF) and one translational DOF (2R1T) have gained much attention in recent years. In this paper, different from type synthesis method, inner properties of PMs (motion characteristics, type of joints and arrangement way of joints) are used to deduce PMs; and two novel 3-DOF PMs are presented using this method. Aiming at 2UPU/SP PM, the constraint force/torque generated on the moving platform (MP) are analysed; here, P, U and S denote prismatic, universal and spherical joints, respectively. The driving force and the constraint force/torque are drawn, which show good distribution of the constraint wrench. After that, a novel 5-DOF hybrid manipulator is constructed on the basis of the 2UPU/SP PM; according to different demands, two alternative designs of the 5-DOF hybrid manipulator are presented. The study in this paper will enhance the research applications of the 2UPU/SP PM.
Analysis of Assistive Strategies for Electric Bikes That Include Rider’s Physiological Characteristics
Authors: Zignoli Andrea , Beatrici Lorenzo , Biral Francesco
Published: November 2018

Control strategies of electric-bikes (e-bikes) do not take the physiological characteristics (e.g. aerobic fitness status) of the rider into account. By means of mathematical modelling, our aim was to analyse different assistive strategies that include these characteristics.

Particularly, we applied an Optimal Control (OC) algorithm to test whether an attentive control strategy could guarantee a sustainable effort for the rider throughout an entire climbing course with varying slope. We found that the contribution of the electric motor was pivotal during accelerations, so the effort for the kinetic energy conversion was shared between the electric motor and the cyclist.

OC seems to fit very well in a scenario where e-bikes are adopted on a daily basis for commuting or to increase the level of physical activity in a sedentary population. We suggest that intelligent control algorithms, like OC, could be embedded in the electric motors to improve e-bike experience, especially in sedentary adults.
An Identification Procedure for Evaluating the Dynamic Parameters of the Upper Limbs During Handcycling
Authors: Legnani Giovanni , Incerti Giovanni , Lancini Matteo , Azizpour Ghazaleh
Published: November 2018

The aim of this study is to develop a biomechanical model and a method to analyze the kinematic and kinetic features of the handcycling activity. By applying this model, the contribution of important factors, like muscles, inertia and weight, on the biomechanics of the handbike is investigated. In order to validate the proposed model, the kinematics and kinetics of the arm have been collected during a handcycling activity in different configurations performed by several subjects. The force applied on the handle has been measured and compared with the one assessed by the model; in addition, the arm muscles activity has been noticed. Moreover, some new indices are defined to describe the performance of handbike athletes in a more precise way to improve their benefits.
Control Solution for a Cable-Driven Parallel Robot With Highly Variable Payload
Authors: Picard Etienne , Caro Stéphane , Plestan Franck , Claveau Fabien
Published: November 2018

This paper deals with the design of a robust control scheme for a suspended Cable-Driven Parallel Robot (CDPR), composed of eight cables and a moving platform (MP), suitable for pick-and-place operations of heterogeneous objects with different shapes, sizes and masses, up to a total load of 700 kg. Dynamometers measure the force applied by each cable onto the moving-platform and are used to assess the payload mass at any time. In the proposed control solution, each motor of the CDPR is directly driven by a PD torque controller, which takes benefit of the real-time payload estimation in a feedforward term. In order to evaluate its performance, experiments on a typical pick and place trajectory are realized for different payloads. As a result, three control schemes: (i) a Proportional-Derivative (PD) torque controller; (ii) a PD controller with compensation of the MP mass only and (iii) a PD controller with real-time mass estimation and compensation are experimentally compared with respect to their positioning accuracy. It turns out that a good estimation of the payload is obtained in real-time thanks to the dynamometers. Moreover, the higher the payload mass, the more accurate the proposed controller with respect to its two counterparts.
Experimentally-Infused Active System Optimization Framework: Theoretical Convergence Analysis and Airborne Wind Energy Case Study
Authors: Deodhar Nihar , Vermillion Christopher
Published: November 2018

This research presents a convergence analysis for an iterative framework for optimizing plant and controller parameters for active systems. The optimization strategy fuses expensive yet valuable experiments with less accurate yet cheaper simulations. The numerical model is improved at each iteration through a cumulative correction law, using an optimally designed set of experiments. The iterative framework reduces the feasible design space between iterations, ultimately yielding convergence to a small design space that contains the optimum. This paper presents the derivation of an asymptotic upper bound on the difference between the corrected numerical model and true system response. Furthermore, convergence of the numerical model to the true system response and convergence of the design space are demonstrated on an airborne wind energy (AWE) application.
The Function-Human Error Design Method (FHEDM)
Authors: Soria Zurita Nicolás F. , Stone Robert B. , Demirel Onan , Tumer Irem Y.
Published: November 2018

During the design of products and systems, engineers must quickly and accurately satisfy customer needs while adequately developing the required system functions with the minimum number of failures. Identifying potential failure modes during early design stages is essential to create reliable designs. Different engineering methodologies such as Failure Modes and Effects Analysis (FMEA), allows engineers to identify how a set of components could fail. These methods are popular and commonly used in industry. However, such methodologies fail to recognize potential failure modes caused by human-product interaction. During the design of products, there is often a lack of sufficient attention to the human-product interaction. Even though human factors are considered during the design process, most of the design approaches fail to incorporate the human interaction correctly. In this research, we explore the implementation of a novel design methodology named Function-Human Error Design Method (FHEDM), which identifies possible generic human errors while completing a functional decomposition of the product. This method will provide engineers with useful information about potential failure modes caused by human-function interaction during early conceptual design.
Part Monitoring and Quality Assessment of Conformal Additive Manufacturing Using Image Reconstruction
Authors: Kutzer Michael D. , DeVries Levi D. , Blas Cooper D.
Published: November 2018

Additive manufacturing (AM) technologies have become almost universal in concept development, prototyping, and education. Advances in materials and methods continue to extend this technology to small batch and complex part manufacturing for the public and private sectors. Despite the growing popularity of digital cameras in AM systems, use of image data for part monitoring is largely unexplored. This paper presents a new method for estimating the 3D internal structure of fused deposition modeling (FDM) processes using image data from a single digital camera. Relative transformations are established using motion capture, and the 3D model is created using knowledge of the deposition path coupled with assumptions about the deposition cross-section. Results show that part geometry can be estimated and visualized using the methods presented in this work.
Data-Driven Additive Manufacturing Constraints for Topology Optimization
Authors: Weiss Benjamin M. , Hamel Joshua M. , Ganter Mark A. , Storti Duane W.
Published: November 2018

The topology optimization (TO) of structures to be produced using additive manufacturing (AM) is explored using a data-driven constraint function that predicts the minimum producible size of small features in different shapes and orientations. This shape- and orientation-dependent manufacturing constraint, derived from experimental data, is implemented within a TO framework using a modified version of the Moving Morphable Components (MMC) approach. Because the analytic constraint function is fully differentiable, gradient-based optimization can be used. The MMC approach is extended in this work to include a “bootstrapping” step, which provides initial component layouts to the MMC algorithm based on intermediate Solid Isotropic Material with Penalization (SIMP) topology optimization results. This “bootstrapping” approach improves convergence compared to reference MMC implementations. Results from two compliance design optimization example problems demonstrate the successful integration of the manufacturability constraint in the MMC approach, and the optimal designs produced show minor changes in topology and shape compared to designs produced using fixed-radius filters in the traditional SIMP approach. The use of this data-driven manufacturability constraint makes it possible to take better advantage of the achievable complexity in additive manufacturing processes, while resulting in typical penalties to the design objective function of around only 2% when compared to the unconstrained case.
Road Adhesion Coefficient Estimation Based on the Steering Wheel Rebound After Steering
Authors: Yu Liangyao , Zheng Sheng , Liu Xiaohui , Chang Jinghu , Li Fei
Published: November 2018

Accurately estimating road adhesion coefficient is very important for vehicle stability control system. In this paper, an innovation method to estimate the road adhesion coefficient is proposed. This method can be used in vehicles without additional sensors. And this method is especially suitable to be used in the intelligent vehicle equipped with steer-by-wire (SBW) system. When vehicle steers, releasing the steering wheel suddenly will result in rebound to a certain angle. When the steer wheel turns the same angle on different road whose adhesion coefficients are different, the front wheel rebound angles are different. The friction moment between the road and tire is the main factor to prevent the tire from turning back, and the coefficient of friction is equal to road adhesion coefficient when the vehicle is stationary. In this paper, the detailed dynamical models describing the whole process of the front wheel and tire rebound are established. Furthermore, the Luenberger reduced-order disturbance observer is established to estimate the friction moment, and then the adhesion coefficient is estimated. The SBW system which is usually equipped in intelligent vehicles can control the steer moment and steer angle accurately. When the steer wheel turns to certain angle, the SBW system is able to stop outputting torque quickly and timely, which is important for improving the experiment accuracy. In this paper, the SBW system is used to conduct an experiment on different roads. The experiment results demonstrate the validity of this method.
Stiffness Control of an Active Transtibial Prosthesis
Authors: Klein Joseph G. , Voglewede Philip A.
Published: November 2018

Active, transtibial prostheses typically use finite state control algorithms that struggle with cadence and gait variability of the amputee. Recent work in artificial neural networks (ANN) have shown the possibility to predict the users intent based on EMG activity and the current position of the ankle, which can be used as an input signal into an improved controller. This paper examines how to implement an ANN signal into a zero order impedance controller, i.e., a stiffness controller, on a specific active transtibial prosthesis. The prosthesis incorporates a linear spiral spring in parallel with a four-bar mechanism. In order to implement stiffness control, the spring was moved to being in series with the four-bar mechanism to establish a relationship between the torque of the spring and the position of the motor. To ensure stiffness control is feasible, a MATLAB Simulink model of the system was created to test the robustness of the controller and the effect of moving the spring from parallel to series. The robustness of the controller was verified as the ankle position and torque requirements are met in the simulation. The Simulink model accurately models the new system and can be used in the future to optimize the motor or the four-bar mechanism for this new type of control.
Designing Improved Teams for Crowdsourced Competitions
Authors: McComb Christopher , Maier Torsten
Published: November 2018

Teams are ubiquitous, woven into the fabric of engineering and design. Often, it is assumed that teams are better at solving problems than individuals working independently. Recent work in engineering, design, and psychology has indicated that teams may not be the problem-solving panacea that they were once thought to be. Crowdsourcing has seen increased interest in engineering design recently, and platforms often encourage teamwork between participants. This work undertakes an analysis of the performance of different team styles and sizes in crowdsourced competitions. This work demonstrates that groups of individuals working independently may outperform interacting teams on average, but that small interacting teams are more likely to win competitions. These results are discussed in the context of motivation for crowdsourcing participants.
An Algorithm for Generating 3D Lattice Structures Suitable for Printing on a Multi-Plane FDM Printing Platform
Authors: Ishak Ismayuzri B. , Moffett Mark B. , Larochelle Pierre
Published: November 2018

Manufacturing processes for the fabrication of complex geometries involve multi-step processes when using conventional machining techniques with material removal processes. Additive manufacturing processes give leverage for fabricating complex geometric structures compared to conventional machining. The capability to fabricate 3D lattice structures is a key additive manufacturing characteristic. Most conventional additive manufacturing processes involve layer based curing or deposition to produce a three-dimensional model. In this paper, a three-dimensional lattice structure generator for multi-plane fused deposition modeling printing was explored. A toolpath for an input geometric model with an overhang structure was able to be generated. The input geometric model was able to be printed using a six degree of freedom robot arm platform. Experimental results show the achievable capabilities of the 3D lattice structure generator for use with the multi-plane platform.
Unpacking Subjective Creativity Ratings: Using Embeddings to Explain and Measure Idea Novelty
Authors: Ahmed Faez , Fuge Mark , Hunter Sam , Miller Scarlett
Published: November 2018

Assessing similarity between design ideas is an inherent part of many design evaluations to measure novelty. In such evaluation tasks, humans excel at making mental connections among diverse knowledge sets and scoring ideas on their uniqueness. However, their decisions on novelty are often subjective and difficult to explain. In this paper, we demonstrate a way to uncover human judgment of design idea similarity using two dimensional idea maps. We derive these maps by asking humans for simple similarity comparisons of the form “Is idea A more similar to idea B or to idea C?” We show that these maps give insight into the relationships between ideas and help understand the domain. We also propose that the novelty of ideas can be estimated by measuring how far items are on these maps. We demonstrate our methodology through the experimental evaluations on two datasets of colored polygons (known answer) and milk frothers (unknown answer) sketches. We show that these maps shed light on factors considered by raters in judging idea similarity. We also show how maps change when less data is available or false/noisy ratings are provided. This method provides a new direction of research into deriving ground truth novelty metrics by combining human judgments and computational methods.
Design Automation by Integrating Generative Adversarial Networks and Topology Optimization
Authors: Oh Sangeun , Jung Yongsu , Lee Ikjin , Kang Namwoo
Published: November 2018

Recent advances in deep learning enable machines to learn existing designs by themselves and to create new designs. Generative adversarial networks (GANs) are widely used to generate new images and data by unsupervised learning. Certain limitations exist in applying GANs directly to product designs. It requires a large amount of data, produces uneven output quality, and does not guarantee engineering performance. To solve these problems, this paper proposes a design automation process by combining GANs and topology optimization. The suggested process has been applied to the wheel design of automobiles and has shown that an aesthetically superior and technically meaningful design can be automatically generated without human interventions.
Shifting Control of Uninterrupted Multi-Speed Transmission Used in Electric Vehicle
Authors: Lu Zhenghong , Song Jian , Fang Shengnan , Li Fei , Yu Liangyao
Published: November 2018

Electric Vehicles (EVs) with single-ratio gearbox provide high levels of smoothness, but using two-speed gearbox can provide significant benefits in terms of vehicle acceleration, max speed, and energy consumption. However, a smooth and seamless shifting is hard to be achieved due to the relatively large transmission ratio gap between two gears and the high speed characteristic of drive motor (DM). The purpose of this paper is to demonstrate a new seamless shifting control algorithm using DM torque for a novel multi-speed EV powertrain. First of all, a novel two-speed uninterrupted mechanical transmission, which consists of a planetary gear, a dry clutch and a band brake, is presented and modeled. In addition to clutch and band brake shift control strategies, new DM torque integration strategies are involved based on quick torque response feature of motors. According to the proposed algorithm, DM torque compensation in torque phase during upshift and less off-going clutch disengagement with DM torque compensation in inertia phase during downshift can both contribute to the uninterrupted output. To shorten the inertia phase time, the half-engagement of oncoming brake and reverse DM torque compensation are recommended. Simulation studies are taken to determine the shift transient behavior of the clutch, band brake and DM during two typical shifting conditions, power-on (when positive DM power is transmitted through the transmission when vehicles speed up or cruise) upshift and power-on downshift, which particularly demand uninterrupted output torque. The simulation results prove that the algorithm works effectively.
A Representation of the Transfer Matrix Method for Linear Controlled Multibody Systems Using Matrix Signal Flow Graph
Authors: Zhou Qinbo , Rui Xiaoting
Published: November 2018

The obtaining of the overall transfer equation of a linear controlled multibody system is one of the key problems when the transfer matrix method for multibody systems (MSTMM) is applied to study controlled multibody dynamics. This paper applies the theory of matrix signal flow graphs (MSFG) to MSTMM. The transfer matrix signal flow graphs (TMSFG) of a mechanical element and a control subsystem can be drawn according to their transfer equations. By merging the nodes corresponding to the same state vector, the TMSFG of the entire system can be obtained. Eventually, the overall transfer equation of the linear controlled system can be systematically obtained according to the reduction rules of MSFG. An example is taken to sketch the idea and the simulation results are compared with other ordinary dynamics methods to validate the proposed method. This paper lays a foundation for automatic deduction of overall transfer equations of linear controlled multibody systems.
Representing Complex Analogues Using a Function Model to Support Conceptual Design
Authors: Siddharth L. , Chakrabarti Amaresh , Venkataraman Srinivasan
Published: November 2018

Analogical design has been a long-standing approach to solve engineering design problems. However, it is still unclear as to how analogues should be presented to engineering design in order to maximize the utility of these. The utility is minimal when analogues are complex and belong to other domain (e.g., biology). Prior work includes the use of a function model called SAPPhIRE to represent over 800 biological and engineered systems. SAPPhIRE stands for the entities: States, Actions, Parts, Phenomena, Inputs, oRgans, and Effects that together represent the functionality of a system at various levels of abstraction. In this paper, we combine instances of SAPPhIRE model for representing complex systems (also from the biological domain). We use an electric buzzer to illustrate and compare the efficacy of this model in explaining complex systems with that of a well-known model from literature. The use of multiple-instance SAPPhIRE model instances seems to provide a more comprehensive explanation of a complex system, which includes elements of description that are not present in other models, providing an indication as to which elements might have been missing from a given description. The proposed model is implemented in a web-based tool called Idea-Inspire 4.0, a brief introduction of which is also provided.
Approaches for Supporting Exploration for Analogical Inspiration With Behavior, Material and Component Based Structural Representations of Patent Databases
Authors: Song Hyeonik , Fu Katherine
Published: November 2018

This paper presents an explorative-based computational methodology to aid the analogical retrieval process in design-by-analogy practice. The computational methodology, driven by Non-negative Matrix Factorization (NMF), iteratively builds a hierarchical repositories of design solutions within which clusters of design analogies can be explored by designers. In the work, the methodology has been applied on a large repository of mechanical design related patents, processed to contain only component-, behavior-, or material-based content, to demonstrate that unique and valuable attribute-based analogical inspiration can be discovered from different representations of patent data. For explorative purposes, the hierarchical repositories have been visualized with a three-dimensional hierarchical structure and two-dimensional bar graph structure, which can be used interchangeably for retrieving analogies. This paper demonstrates that the explorative-based computational methodology provides designers an enhanced control over design repositories, empowering them to retrieve analogical inspiration for design-by-analogy practice.
Product Family Redesign Using Additive Manufacturing
Authors: Jung Sangjin , Simpson Timothy W.
Published: November 2018

In this study we investigate how we can effectively redesign a product family using additive manufacturing (AM). Specifically, we propose an integrated approach to product family redesign using platform metrics for a product family that uses AM. The proposed approach can help identify what to platform and how to platform with AM. We employ a variety metric to measure the amount of redesign for each component, a commonality metric to capture different types of commonality, and Design Structure Matrix (DSM) to analyze a platform architecture. After integrating these metrics, we can optimize balancing the tradeoffs between commonality and differentiation of components. Components that offer little variety for the market can be made common and part of the platform while components that must be varied to achieve market requirements should not be platformed and may be easily customized with AM. In order to facilitate customization of AM components, we can evaluate redesign of platform interfaces to help embed flexibility and modularity into the product family. To investigate the impact of the integrated approach, we apply the proposed approach to a family of Unmanned Aerial Vehicles (UAVs) as a case study. The results show the proposed approach can be effectively employed to identify ways to redesign the UAV family to improve the balance of commonality and variety of future product offerings.
Spiral Pulley Negative Stiffness Mechanism for Morphing Aircraft Actuation
Authors: Zhang Jiaying , Shaw Alexander D. , Mohammadreza Amoozgar , Friswell Michael I. , Woods Benjamin K. S.
Published: November 2018

The energy balancing concept seeks to reduce actuation requirements for a morphing structure by strategically locating negative stiffness devices to tailor the required deployment forces and moments. One such device is the spiral pulley negative stiffness mechanism. This uses a cable connected with a pre-tension spring to covert decreasing spring force into increasing balanced torque. The kinematics of the spiral pulley are firstly developed and its geometry is then optimised by employing an energy conversion efficiency function. The performance of the optimised spiral pulley is then evaluated through the net torque, the total required energy and energy conversion efficiency. An experiment demonstrates the negative stiffness property of the mechanism and compares its characteristics with the analytical result. Exploiting the negative stiffness mechanism has a significant interest in not only the field of morphing aircraft but many other power reduction applications.an increasing output torque. The kinematics of the spiral pulley are firstly developed and its geometry is then optimised by employing an energy conversion efficiency function. The performance of the optimised spiral pulley is then evaluated through the net torque, the total required energy and energy conversion efficiency. An experiment demonstrates the negative stiffness property of the mechanism and compares its characteristics with the analytical result. Exploiting the negative stiffness mechanism has a significant interest in not only the field of morphing aircraft but also many other energy and power reduction applications.
Customization of a 3D Printed Prosthetic Finger Using Parametric Modeling
Authors: Lim Daniel , Georgiou Thomás , Bhardwaj Aashish , O’Connell Grace D. , Agogino Alice M.
Published: November 2018

Prosthetic limbs and assistive devices require customization to effectively meet the needs of users. Despite the expense and hassle involved in procuring a prosthetic, 56% of people with limb loss end up abandoning their devices [1]. Acceptance of these devices is contingent on the comfort of the user, which depends heavily on the size, weight, and overall aesthetic of the device. As seen in numerous applications, parametric modeling can be utilized to produce medical devices that are specific to the patient’s needs. However, current 3D printed upper limb prosthetics use uniform scaling to fit the prostheses to different users.

In this paper, we propose a parametric modeling method for designing prosthetic fingers. We show that a prosthetic finger designed using parametric modeling has a range of motion (ROM) (path of the finger tip) that closely aligns with the digit’s natural path. We also show that the ROM produced by a uniformly scaled prosthetic poorly matches the natural ROM of the finger. To test this, finger width and length measurements were collected from 50 adults between the ages of 18–30. It was determined that there is negligible correlation between the length and width of the index (D2) digit among the participants.

Using both the highest and the lowest length to width ratio found among the participants, a prosthetic finger was designed using a parametric model and fabricated using additive manufacturing. The mechanical design of the prosthetic finger utilized a crossed four bar linkage mechanism and its ROM was determined by Freudenstein’s equations. By simulating the different paths of the fingers, we demonstrate that parametrically modeled fingers outperform uniformly scaled fingers at matching a natural digit’s path.
Identifying Stiffness, Friction, and Kinematic Error Signature in Gear Bearing Drive Transmissions
Authors: Brassitos Elias , Jalili Nader
Published: November 2018

The Gear Bearing Drive (GBD) is a recently developed high gear-ratio transmission concept based on NASA’s high-reduction gear bearing technology and brushless outrunner motor technology. In this paper, we describe the experimental setup and characterization of the GBD transmission’s stiffness, friction, backlash, hysteresis as well as its kinematic error. Compared to conventional precision drive systems such as harmonic drives, the GBD can offer similar advantages such as high gear-ratio in a compact assembly but with the potential of better stiffness characteristics and a more predictable output speed response. The models derived in this paper were then fed into a dynamic model that can accurately simulate the velocity open-loop response of the transmission under various input current functions.
Topology Optimization of Conformal Structures Using Extended Level Set Methods and Conformal Geometry Theory
Authors: Ye Qian , Guo Yang , Chen Shikui , Gu Xianfeng David , Lei Na
Published: November 2018

In this paper, we propose a new method to approach the problem of structural shape and topology optimization on manifold (or free-form surfaces). A manifold is conformally mapped onto a 2D rectangle domain, where the level set functions are defined. With conformal mapping, the corresponding covariant derivatives on a manifold can be represented by the Euclidean differential operators multiplied by a scalar. Therefore, the topology optimization problem on a free-form surface can be formulated as a 2D problem in the Euclidean space. To evolve the boundaries on a free-form surface, we propose a modified Hamilton-Jacobi equation and solve it on a 2D plane following the conformal geometry theory. In this way, we can fully utilize the conventional level-set-based computational framework. Compared with other established approaches which need to project the Euclidean differential operators to the manifold, the computational difficulty of our method is highly reduced while all the advantages of conventional level set methods are well preserved. We hope the proposed computational framework can provide a timely solution to increasing applications involving innovative structural designs on free-form surfaces in different engineering fields.
Multi-Material Topology Optimization of Structures Infilled With Conformal Metamaterials
Authors: Vogiatzis Panagiotis , Chen Shikui , Gu Xianfeng David , Chuang Ching-Hung , Xu Hongyi , Lei Na
Published: November 2018

Topology optimization is being widely employed in designing metamaterial unit cells which can be utilized as core materials for structural components. In this paper, we carried out multi-material topology optimization using orthotropic metamaterials. After topology optimization, the microstructures of the metamaterials are mapped to the resulted irregular domains for each material phase, acting as infill. Different from the existing work, we proposed an alternative way of mapping the metamaterial microstructures to irregular domains by employing the conformal mapping theory. Conformal mapping is an angle-preserving Riemann mapping that preserves the local shape and can efficiently transform a rectangular unit cell to an irregular quadrilateral domain. Each group of metamaterials is bounded by a thin layer of material to guarantee structural connectivity between different microstructures and smooth external boundaries.
Robotic Shotcrete Thickness Estimation Using Fiducial Registration
Authors: Wrock Michael R. , Nokleby Scott B.
Published: November 2018

This paper presents the results of shotcrete thickness estimation for mining applications using a mobile robot. The method uses a fiducial marker based registration method to align initial and posterior LIDAR scans. The shotcrete thickness was calculated using point to point estimation. The registration and thickness estimation were tested in a mock mine using a LIDAR scanner on a mobile robot. It was found that the registration based thickness estimates had repeatability within a millimeter when compared to thickness estimates generated without the need for registration.
Ontology Based Behavior Verification for Complex Systems
Authors: Chen Ruirui , Liu Yusheng , Ye Xiaoping
Published: November 2018

Model Based Systems Engineering (MBSE) is a mainstream methodology for the design of complex systems. Verification is a necessary part of MBSE. Although there is significant past research on verification, some deficiencies still exist, such as behavior requirement verification in the early design stage is lacking. In this study, behavior verification at the early design stage is presented. First, a unified modeling method based on SysML is proposed and some transformation rules are defined to ensure the correctness and definiteness of the ontology generation. Second, behavior requirements are classified and formalized as rules. Finally, a hierarchical behavior verification approach based on ontology reasoning is proposed. This approach is convenient for designers to use and no additional expertise is needed. A case study is provided to demonstrate its effectiveness.
Extension of Motion/Force Transmission Index to Parallel Manipulators With Double Platforms: Case Study on the Par4 Manipulator
Authors: Meng Qizhi , Xie Fugui , Liu Xin-Jun , Takeda Yukio
Published: November 2018

At present, the research of motion/force characteristics is concentrated on the single-platform parallel mechanisms (PMs). On the contrary, relatively little attention has been paid to the double-platform PMs, and there is also no unified index. What actually causes this? One of the reasons is that the complex and inaccessible wrench system of this manipulator with the double platforms. Especially the transmission wrench screws (TWSs) are no longer like its traditional concept, i.e., linear forces along the symmetric axis of the passive arms. Essentially, the TWSs in the double-platform PMs should be applied to the end effector but not to the sub-platforms from active arms. With this new idea, the concept equivalent transmission wrench screw (ETWS) of PMs with double platforms is firstly proposed and its identification process is also provided. Then, the motion/force transmission index which considers the input transmission index (ITI) and output transmission index (OTI) is extended to the area of kinematic performance evaluation of the double-platform PMs. Finally, the validity of the proposed extension is verified by the transmission index (TI) based on the concept of pressure angle. In this paper, the typical Par4 mechanism is investigated as an example. This extended approach with a new definition of the ETWS which covers the concept of the TWS in traditional mechanism actually provides a uniform kinematic performance index of both single- and double-platforms PMs.
Evaluating a Virtual Wind Power Park in a Churchyard: A Perception Study With Portable VR Devices
Authors: Ellman Asko , Tiainen Tarja , Tossavainen Aleksi
Published: November 2018

Portable VR technology enables perception studies to be put into practice in the field. This is a notable advance for several reasons: First, VR studies can be performed in natural environments, second, it is easier to reach relevant informants, and third, informants are more focused on the test. In this study, we focus on the pre-design phase of a wind power park. It is an appropriate target for perception study because it is rather new technology, many people are affected by it and there is a lot of prejudice against it. Due to this, social resistance has become the most remarkable issue for building new wind power in countryside.

The research question of this paper is if the use of Virtual prototypes can influence inhabitant’s attitudes in the pre-design phase of a Wind Power Park. We present a perception study that is performed in a village next to which a wind power park is planned. This study was performed with portable VR technology in a churchyard of the village where they could experience the virtual landscape and soundscape caused by a future wind power park. Informant group consisted of 18 people from the village.

In this study, we found out that people with strong preconception did not change their opinions. However, people with mild preconception may change their opinion. Actually, 37 % of the informants changed their opinion on wind power after the virtual inspection. It is noteworthy that the change can take place in both directions. Furthermore, portable VR technology consisting of an Oculus Rift and a Laptop computer proved to be feasible in the field study.
Design Signatures: Mapping Design Innovation Processes
Authors: Seow Olivia , Tiong Edward , Teo Kenneth , Silva Arlindo , Wood Kristin L. , Jensen Daniel D. , Yang Maria C.
Published: November 2018

Despite variances in contexts and styles of design activity, recurrent patterns emerge in design innovation approaches and processes which lend themselves to analysis and discussion. Using a Design Innovation framework [1] that is built, in part, on the UK Council’s ‘4D’ (Discover, Define, Develop, Deliver) model of design [2], we develop design signatures, graphical maps of design innovation processes. Design signature analyses of four multi-disciplinary industrial case studies illustrate the value of design signatures as useful design activity plots that can be used to plan and manage innovation teams and activities, and to identify critical features for reflection, for clarification, and for further analysis. This work is of interest to design practitioners, managers, researchers, and educators with various motivations, such as to seek a tool to convey and analyze design innovation activity.
An Automatic Interaction Method Using Part Recognition Based on Deep Network for Augmented Reality Assembly Guidance
Authors: Yin Xuyue , Fan Xiumin , Wang Jiajie , Liu Rui , Wang Qiang
Published: November 2018

Assembly process of complex electromechanical products can be quite complicated and time consuming because of high quality demands. Aiming at improving the efficiency of the manual assembly process, this paper proposes an automatic interaction method using part recognition for augmented reality (AR) assembly guidance, which improves both the accuracy of part picking and the interaction efficiency of AR guidance system. Taking sample images of similar parts as input and part types as output, a deep neural network model Part R-CNN for part recognition is build based on Faster R-CNN and is further fine-tuned by back propagation. By recognizing the assembly part, the augmented assembly guidance information of the corresponding parts assembly process is triggered in real-time without direct user interaction. Experimental results show that the deep neural network based part recognition method reaches 94% on mean average precision and the average recognition speed is 200ms per image frame. The average speed of AR guidance content triggering is about 20fps. All system performance satisfies the accuracy and real-time requirements of the AR-aided assembly system.