bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigating the Challenges of Crowdsourcing for Engineering Design: An Interview Study With Organizations of Different Sizes
Authors: Forbes Hannah , Shaefer Dirk , Shergadwala Murtuza N. , Panchal Jitesh H. 
Published: November 2020

Abstract
Crowdsourcing has been identified as a valuable paradigm in the open design movement. In engineering design, it offers various benefits, such as the generation of diverse ideas and the involvement of consumers. Despite the potential benefits, there are many ways in which crowdsourcing initiatives may fail. An example of such a failure is when a previously successful initiative for a large organization fails to attract a suitable number of participants with diverse expertise for a start-up. Consequently, the start-up does not receive good sets of ideas, both in quantity and variety. Such failures of crowdsourcing initiatives are common due to the lack of appropriate design of crowdsourcing initiatives based on the organizational characteristics such as its size. While frameworks and guidelines exist for the design of crowdsourcing initiatives, whether these are useful for all sizes of organizations, is yet to be determined. Large organizations such as Procter & Gamble and NASA, now conduct crowdsourcing initiatives regularly. Furthermore, start-ups are emerging that leverage crowdsourcing as an integral part of their business model. On the contrary, small and medium enterprises (SMEs) have fallen behind in the adoption of crowdsourcing processes. In this paper, we aim to identify the challenges associated with crowdsourcing and how and whether these differ according to organizational size. We present the results of an interview study with industry professionals from five organizations of varying sizes, and yield key challenges associated with the application of crowdsourcing. This paper discusses suggested support mechanisms for crowdsourcing in SMEs and directions for further research for crowdsourcing in engineering design.
Dynamic Morphing of Elastic Plates via Principal Parametric Resonance
Authors: Arena Andrea , Lacarbonara Walter 
Published: November 2020

Abstract
Principal parametric resonances of elastic plates actuated by periodic in-plane stresses effected by embedded piezoelectric wires are investigated to describe the morphing scenarios of flexible, ultra-lightweight panels. A mechanical model of elastic plate including geometric nonlinearities and the parametric actuation provided by the piezoelectric wires, is adopted to formulate the nonlinear equation of motion. A bifurcation analysis is carried out by means of an asymptotic approach based on the method of multiple scales leading to a comprehensive parametric study on the effect of the wires width on the morphing regions (i.e., parametric instability regions) associated with the principal parametric resonances. The threshold voltages triggering the onset of the principal parametric resonances of the lowest three symmetric modes are also calculated as a function of the wires size so as to determine the voltage requirements for the morphing activation.
Design and Analysis of a Wire-Driven Multifunctional Robot for Single Incision Laparoscopic Surgery
Authors: Chowdhury A. M. Masum Bulbul , Cheng Jinsai , Cullado Michael J. , Shen Tao 
Published: November 2020

Abstract
Single Incision Laparoscopic Surgery (SILS) is a fast-growing method in the field of MIS (Minimally Invasive Surgery) that has the potential to represent the future of laparoscopic surgeries. The major benefits of SILS results from a single incision which makes surgeries essentially scar-less, and it can reduce wound infection substantially as well as recuperation time. Many new researches are now focusing on developing cutting edge technologies to support SILS; however, the practical applications of SILS are constrained by a number of intricacies such as space limitation, absence of dexterous multitasking tools, lack of sufficient actuation force and poor visualization. Deployment and retraction of surgical tools or robots are done manually in the absence of a multitasking tool manipulator which increases the surgery time, risk of injury and surgeon’s fatigue. Our research focuses on designing a novel operative hardware (multitasking manipulator) to facilitate the SILS technique with automatic tool changing capability. A wire driven mechanism has been implemented in the design to minimize the damage to the electronic hardware during sterilization since the electronic actuation and sensing components are located remotely from the end-effector which requires heat or chemical sterilization before surgery. And a wire-driven articulated robotic arm has also been designed to support the manipulator. The details of the robotic design and analysis are conducted in the paper. The feasibility of this robotic method has been demonstrated by experiments.
Exploration of the Timing of Introduction of Design Heuristic Cards to Early Design Brainstorming Sessions by Interdisciplinary Student Teams
Authors: Mercado Rivera Abimelec , Lugo José E. 
Published: November 2020

Abstract
This research focuses on improving the outcome of idea generation sessions of interdisciplinary student teams working in the early design stages of a product or solution by measuring the effect of incorporating Design Heuristics Cards at different points of ideation sessions that adhere to the brainstorming guidelines. Using the design thinking methodology, an open-ended challenge was given to the participating teams for a Brainstorming exercise divided into a fifteen-minute individual segment followed by a thirty-minute team ideation segment. Three experimental treatments were designed where Design Heuristics Cards were introduced at different points of the ideation exercise: the start of the individual ideation segment, the start of the team ideation segment, or the second half of the team ideation segment. A fourth control treatment did not introduce the cards at any point but used the Brainstorming guidelines throughout. The metrics observed were Fluency, Novelty, Feasibility, and Market Fit of the ideas generated by the students. Eighty-four students participated in the experiment, with 58.3% being from majors in the College of Engineering, 28.6% from majors in the College of Business Administration, 7.1% from majors in the College of Arts and Sciences, and 6.0% from majors in the College of Agriculture. No significant difference was found among the experimental treatments; however the results are not considered final due to the explorative nature of the study. Recommendations are made on future work and possible improvements to the experiment.
Machine-Specific Energy Estimation Using the Unit Process Life Cycle Inventory (UPLCI) Model
Authors: Thoft Krogshave Johan , Boettjer Till , Ramanujan Devarajan 
Published: November 2020

Abstract
This paper discusses a method for machine-specific energy estimation in milling processes using the unit process life cycle inventory (UPLCI) model. To this end, we develop a standard methodology for constructing an adjusted UPLCI model that includes adjustment factors for uncertainties in machine tool specifications and the specific cutting energy of a workpiece material. The adjustment factors are calculated through experimental measurement of energy consumption for a standard test part on a specific machine tool. To validate the adjusted UPLCI model, we conducted a case study which experimentally measured the energy consumption for machining three parts made of Aluminum 6082 on a Chevalier QP2040-L three-axis vertical milling machine. Results show that the UPLCI model consistently overestimated the total energy consumption for machining the three parts and had significant estimation errors (314%, 499%, 286%). The largest sources of error in the UPLCI model were from overestimating the idle and basic power consumption of the machine tool. The adjusted UPLCI model significantly reduced the estimation errors for the same tests (27%, 0.3%, 36%).
Neuroadaptive Controller for Physical Interaction With an Omni-Directional Mobile Nurse Assistant Robot
Authors: Saadatzi Mohammad N. , Abubakar Shamsudeen , Das Sumit Kumar , Saadatzi M. Hossein , Popa Dan 
Published: November 2020

Abstract
Robot-assisted healthcare could help alleviate the shortage of nursing staff in hospitals and is a potential solution to assist with safe patient handling and mobility. In an attempt to off-load some of the physically-demanding tasks and automate mundane duties of overburdened nurses, we have developed the Adaptive Robotic Nursing Assistant (ARNA), which is a custom-built omnidirectional mobile platform with a 6-DoF robotic manipulator and a force sensitive walking handlebar. In this paper, we present a robot-specific neuroadaptive controller (NAC) for ARNA’s mobile base that employs online learning to estimate the robot’s unknown dynamic model and nonlinearities. This control scheme relies on an inner-loop torque controller and features convergence with Lyapunov stability guarantees. The NAC forces the robot to emulate a mechanical system with prescribed admittance characteristics during patient walking exercises and bed moving tasks. The proposed admittance controller is implemented on a model of the robot in a Gazebo-ROS simulation environment, and its effectiveness is investigated in terms of online learning of robot dynamics as well as sensitivity to payload variations.
Identifying Sustainable Solutions for Sanitation, Energy, and Water Needs in Off-Grid Indian Villages
Authors: Nair Anju Vijayan , Balu Nellippallil Anand , Das Ashok K. , Hall John , Allen Janet K. , Mistree Farrokh 
Published: November 2020

Abstract
Food, energy, and water are the significant factors necessary for the social and economic well-being and prosperity of people, particularly to accelerate rural development. In order to attain sustainable development in off-grid villages, the issues associated with the Food-Energy-Water (FEW) nexus must be addressed with respect to social, economic and environmental aspects. SunMoksha, a socio-technical enterprise, has proposed a model that includes smart technical solutions or intelligent assets, such as, Smart AQUAnet™, Smart Nanogrid™, Smart MEZ™, etc., addressing food, energy and water needs in off-grid villages. Its development model allows for multiple sustainable solutions to be introduced into the rural community, to address specific needs as the community moves up in the development process.
In this paper, a method is presented to identify such sustainable smart solutions. The method involves the use of the dilemma triangle and Go/No-Go analysis to address the needs in off-grid Indian villages. We demonstrate the efficacy of the method by first identifying the key issues in an Indian off-grid village from the perspective of the FEW nexus using the dilemma triangle construct. A Go/No-Go analysis is used to select the best feasible solution from a set of possible solutions addressing the dilemmas and issues. Additionally, the needs for sanitation in the village is also considered in the analysis, keeping in mind the health and well-beings of the communities. The method is generic and will support stakeholders/decision-makers in identifying and selecting the best suitable solution from a set of potential solutions. The method is illustrated for an off-grid village to identify an intelligent asset to simultaneously address the sanitation, energy and water needs.
Large-Scale Three-Dimensional Anisotropic Topology Optimization of Variable-Axial Composite Structures
Authors: Zhou Yuqing , Nomura Tsuyoshi , Zhao Enpei , Zhang Wei , Saitou Kazuhiro 
Published: November 2020

Abstract
Variable-axial fiber-reinforced composites allow for local customization of fiber orientation and thicknesses. Despite their significant potential for performance improvement over the conventional multiaxial composites and metals, they pose challenges in design optimization due to the vastly increased design freedom in material orientations. This paper presents an anisotropic topology optimization (TO) method for designing large-scale, 3D variable-axial composite structures. The computational challenge for large-scale 3D TO with extremely low volume fraction is addressed by a tensor-based representation of 3D orientation that would avoid the 2π periodicity of angular representation such as Eular angles, and an adaptive meshing scheme, which, in conjunction with PDE regularization of the density variables, refines the mesh where structural members appear and coarsens where there is void. The proposed method is applied to designing a heavy-duty drone frame subject to complex multi-loading conditions. Finally, the manufacturability gaps between the optimized design and the fabrication-ready design for Tailored Fiber Placement (TFP) is discussed, which motivates future work toward fully-automated design synthesis.
Decision-Based Design Method for Computing Marginal Cost of Durability
Authors: Pasquali Felipe M. , Meza Jonatan , Hall John F. 
Published: November 2020

Abstract
Product durability impacts both the environment and the economy. Companies are changing their business models to the circular economy. In this model, the ownership of the product remains with the manufacturer. With this new paradigm, determining the life of the product becomes even more important for the success of the business model. The metric defined as the Marginal Cost of Durability (MCD) determines the cost to increase or decrease the life of the system. For a system to last longer, more materials are needed to counteract the fatigue damage. While this metric has been defined and used in studies throughout the literature, there is a need for a formal method of collecting this data. This paper presents a novel method for measuring the MCD aided by Metamodel-Based Optimization. A case study is presented to demonstrate this method when applied to a wind turbine tower. The results indicate that there is an increasing linear relationship between life and cost. A wind turbine tower designed for 80 years has 34% more mass and cost than a 20-year design.
Muscle Contracture Modeling and Optimal Control for Crouch Gait Prediction
Authors: Tomasi Matilde , Artoni Alessio 
Published: November 2020

Abstract
Prediction of human movement, and especially of pathological gait, is nowadays an important and mostly unsolved research challenge. In this work, a recently developed computational framework based on optimal control was adopted and explored to assess its potential for predicting a pathological gait pattern, in particular the crouch gait typical of subjects affected by cerebral palsy. To this end, the generic musculoskeletal model on which this optimal control framework is based was made representative of such pathological case by modeling contracture of relevant muscle groups commonly associated with crouch gait, namely knee and hip flexors. All the conducted simulations succeeded in inducing the model into a crouch gait pattern, despite their diversity in cost functions. Moreover, the obtained joint angle trajectories correlated well with the experimental ones obtained from a CP child walking in crouch. These kinematic results suggest that optimal control techniques and proper tuning of musculotendon parameters are an important pairing for predictive simulations of human walking. On the other hand, the obtained results confirm that estimation of muscle activations is strongly dependent on the selected objective function and still requires deeper investigations.
RATS: A Robotic Arm Training System Designed for Rats
Authors: Zhang Haohan , Luna Tatiana , Yang Lillian , Martin John , Agrawal Sunil 
Published: November 2020

Abstract
This paper presents a novel robotic system to characterize and retrain reaching in rats. This robot is intended to be a research platform for rehabilitation of forelimb movements in rats. In this paper, we focus on the design of this robotic system. We present the design requirements, mathematical models, and details of the physical device. A parallel mechanism with a special alignment of the component chains is used to accommodate observed reaching motions of a rat’s forelimb. Additionally, we demonstrate the use of this robot to record forelimb trajectories. Three healthy rats were used to record repeated reaching motions while the robot applied nearly zero force. We believe that this robotic system can be used in future training studies with rats who have impaired arm motions due to a neurological insult.
Design for Flexibility: A Graph Coloring Technique to Study Design Changes in the Tethered Economy World
Authors: Estrada Spenser , Green Emilyn , Jahanbekam Sogol , Behdad Sara 
Published: November 2020

Abstract
Digitization, connected networks, embedded software, and smart devices have resulted in a major paradigm shift in business models. Transformative service-based business models are dominating the market, where advancement in technology has paved the way for offering not only a set of new services but also altering product functionalities and services over time. This paradigm shift calls for new design approaches. Designers should be able to design flexible products and services that can adapt to a wide range of consumer needs over time. To address the need for designing for flexibility, the objective of this study is to develop a graph coloring technique that can model changes in the functional requirements of a product and determine the minimum number of physical parts needed to meet future functionalities. This technique relies on vertex labeling by the designer and the construction of a core graph combining key elements of all desired iterations, which is then colored by label. One numerical example and one real-world example are provided to show the application of the proposed model.
Discontinuous Dynamics of a Frequency Up-Conversion Piezoelectric Harvester With an Impact Controlling Mechanism
Authors: Onsorynezhad Saeed , Wang Fengxia 
Published: November 2020

Abstract
In this study, an impact based frequency up-conversion mechanism is studied using discontinuous dynamics theory. The mechanism consists of a sinusoidal vibrating plastic beam as a driving element and a piezoelectric bimorph as a generator. In order to remove the unfavorable stick motion and enhance the performance of the energy harvester, two pairs of racks and pinion gears and a slider-crank have been added to the system, which makes us able to control the impact occurring time between the driving beam and the generator.
In this work, the Rayleigh-Ritz method was applied to obtain the distributed-parameter models of the driving beam and the piezoelectric generator. Both the forward and the backward mechanical-electrical coupling effects were considered during the modeling of the generator. The electrical and mechanical dynamic behaviors of the proposed piezoelectric energy harvester were analytically studied to better understand the effect of system parameters on the performance of piezoelectric energy harvester. Discontinuous dynamics theory was applied to obtain the generated power and voltage. The stability of the periodic solutions was obtained, and the bifurcation diagrams of displacements, impact velocities, generated power, and voltage were obtained analytically as the excitation frequency varying.
Mechanical System Modelling Using Physics-Based and Data-Based Subsystems
Authors: Arbatani Siamak , Kövecses József 
Published: November 2020

Abstract
Mechanical systems have been traditionally represented using parametric physics-based models. In this work, we introduce a novel concept, in this part of the mechanical system is represented using data-based subsystem models, and the overall mechanical system model is composed of these data-based and other, physics-based subsystems. A core element is the interfacing of the subsystems, which gives rise to interaction forces. The interfacing problem is formulated in a way that makes it possible to give a general representation to the interaction forces. We demonstrate that from the point of view of the physics-based subsystems the important element is that the data-based models can represent the interaction force systems properly. The data-based subsystems are developed using deep recurrent neural networks, and the training data is generated based on simulations using the fully parametric physics-based model of the system. Such training data could also be obtained through physical experimentation.
Simulation of Hyper-Elasticity by Shape Estimation
Authors: Matte Christopher-Denny , Kwok Tsz-Ho 
Published: November 2020

Abstract
The simulation of complex geometries and non linear deformation has been a challenge for standard simulation methods. There has traditionally been a trade off between performance and accuracy. With the popularity of additive manufacturing and the new design space it enables, the challenges are even more prevalent. Additionally multiple additive manufacturing techniques now enable the use of hyperelastic materials as raw material for fabrication, and multi-material capabilities. This allows designers more freedom, but also introduces new challenges for control and simulation of the printed parts. In this paper, a novel approach to implementing non-linear material capabilities is devised with negligible additional computational for geometry based approaches. Material curves are fitted with a polynomial expression which can determine the tangent modulus, or stiffness, of a material based on strain energy. The moduli of all elements are compared to determine relative shape factors used to establish the blended shape of an element. This process is done dynamically to update the stiffness of a material in real-time, for any number of materials, regardless of linear or non-linear material curves.
The Role of Idea Fluency and Timing on Highly Innovative Design Concepts
Authors: Mirabito Yakira , Goucher-Lambert Kosa 
Published: November 2020

Abstract
Ongoing work within the engineering design research community seeks to develop automated design methods and tools that enhance the natural capabilities of designers in developing highly innovative concepts. Central to this vision is the ability to first obtain a deep understanding of the underlying behavior and process dynamics that predict successful performance in early-stage concept generation. The objective of this research is to better understand the predictive factors that lead to improved performance during concept generation. In particular, this work focuses on the impact of idea fluency and timing of early-stage design concepts, and their effect on overall measures of ideation session success. To accomplish this, we leverage an existing large-scale dataset containing hundreds of early-stage design concepts; each concept contains detailed ratings regarding its overall feasibility, usefulness, and novelty, as well as the completion time of each idea. Surprisingly, results indicate that there is no effect of idea fluency or timing on the quality of the output when using a holistic evaluation mechanism, such as the innovation measure, instead of a single measure such as novelty. Thus, exceptional concepts can be achieved by all generator segments independent of idea fluency. Furthermore, in early-stage concept generation sessions, highest-rated concepts have an equal probability of occurring early and late in a session. Taken together, these findings can be used to improve performance in ideation by effectively determining when and which types of design interventions future design tools might suggest.