bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluating Crowdsourced Design Concepts With Machine Learning
Authors: Camburn Bradley , He Yuejun , Raviselvam Sujithra , Luo Jianxi , Wood Kristin 
Published: November 2019

Abstract
Automation has enabled design of increasingly complex products, services, and systems. Advanced technology enables designers to automate repetitive tasks in earlier design phases, even high level conceptual ideation. One particularly repetitive task in ideation is to process the large concept sets that can be developed through crowdsourcing. This paper introduces a method for filtering, categorizing, and rating large sets of design concepts. It leverages unsupervised machine learning (ML) trained on open source databases. Input design concepts are written in natural language. The concepts are not pre-tagged, structured or processed in any way which requires human intervention. Nor does the approach require dedicated training on a sample set of designs. Concepts are assessed at the sentence level via a mixture of named entity tagging (keywords) through contextual sense recognition and topic tagging (sentence topic) through probabilistic mapping to a knowledge graph. The method also includes a filtering strategy, the introduction of two metrics, and a selection strategy for assessing design concepts. The metrics are analogous to the design creativity metrics novelty, level of detail, and a selection strategy. To test the method, four ideation cases were studied; over 4,000 concepts were generated and evaluated. Analyses include: asymptotic convergence analysis; a predictive industry case study; and a dominance test between several approaches to selection of high ranking concepts. Notably, in a series of binary comparisons between concepts that were selected from the entire set by a time limited human versus those with the highest ML metric scores, the ML selected concepts were dominant.
Automated Tradeoff Analysis of Cost Versus Machinability for Design Feedback
Authors: Grier Alan T. , Campbell Matthew I. 
Published: November 2019

Abstract
As CAD tools become more sophisticated, engineers are able to more easily create complex part geometries with minimal mass given strength and stiffness requirements. However, these complex part geometries can be difficult to subtractively manufacture, which consequently increases manufacturing cost and production time. This paper presents a method independent of CAD kernels for use early in the design process to automatically evaluate a given part’s machinability and to provide visual geometric additions that decrease manufacturing cost while maintaining the part’s strength and stiffness requirements. Using tessellated and voxelized representations of a part geometry, potential machining orientations are identified and selectively combined to form a set of candidate solutions. The resulting part geometry for each candidate is determined by intersecting the machinable geometries for each individual machine setup, and may have some amount of added volume over the as-designed part. Manufacturing costs for each candidate are estimated based on the volume to be machined and number of required machining setups. Evaluating and culling candidates based on these two objectives (added volume and cost) provides the design engineer with a set of Pareto-optimal solutions that show where material can be added to reduce manufacturing costs. The method is implemented and is tested on three example parts to demonstrate its capability and utility.
Towards Dynamic Simulation Guided Optimal Design of Tumbling Microrobots
Authors: Xie Jiayin , Bi Chenghao , Cappelleri David J. , Chakraborty Nilanjan 
Published: November 2019

Abstract
Design of robots at the small scale is a trial-and-error based process, which is costly and time-consuming. There are no good dynamic simulation tools to predict the motion or performance of a microrobot as it moves against a substrate. At smaller length scales, the influence of adhesion and friction, which scales with surface area, becomes more pronounced. Thus, rigid body dynamic simulators, which implicitly assume that contact between two bodies can be modeled as point contact are not suitable. In this paper, we present techniques for simulating the motion of microrobots where there can be intermittent and non-point contact between the robot and the substrate. We use this simulator to study the motion of microrobots of different shapes and select shapes that are most promising for performing a given task.
Study on Transfer Matrix of Single-Ended Input and Single-Ended Output Plate With Large Motion and Small Deformation
Authors: He Zihao , Rui Xiaoting , Zhang Jianshu , Zhang Lina , Hu Shaoheng 
Published: November 2019

Abstract
A new version of the transfer matrix method for multibody system, where the translational and angular accelerations as well as the internal forces and torques are taken as new state variables, is used to study the dynamics of plate with large motion and small deformation. Modal synthesis method is used to describe the deformation of the plate. The transfer matrix of plate with large motion and small deformation is derived. A continuously accelerating rotating plate subjected to constant torque and a rigid-flexible coupling pendulum containing a plate with large motion and small deformation are studied respectively, their overall transfer equations are established. Dynamic simulation of two examples is carried out and the result is compared with other methods.
Topology Optimization of Cable-Actuated, Shape-Changing, Tensegrity Systems for Path Generation
Authors: Myszka David H. , Joo James J. , Woods Daniel C. , Murray Andrew P. 
Published: November 2019

Abstract
This paper presents a topology optimization methodology to synthesize cable-actuated, shape-changing, tensegrity systems specified through path generation requirements. Estabished tensegrity topology optimization procedures exist for static structures. For active tensegrity systems, motion characteristics are typically explored after the structural topology is determined. The work presented in this paper extends the established procedure to introduce prescribed motion into the topology optimization. A ground structure approach is used in conjunction with the design space. The topology optimization problem is formulated into a mixed integer linear programming problem. Desired motion is prescribed by identifying trace points in the design space and corresponding paths. The result of this methodology is the creation of a tensegrity system that can achieve shape-change as specified with prescribed paths.
A Computational Framework to Support Social Entrepreneurs in Creating Value for Rural Communities in India
Authors: Yadav Abhishek , Das Ashok K. , Allen Janet K. , Mistree Farrokh 
Published: November 2019

Abstract
Over 250 million people in India currently lack access to basic services needed to live a rudimentary lifestyle. Most of these people reside in rural parts of the country. Lack of employment, economic opportunities, and development in rural areas are foundational to low socio-economic levels in these communities. Added to this are environmental issues such as natural resource depletion, yearlong droughts, climate change. We hypothesize that social enterprises developed at the community level can improve the quality of life of people in rural India.
The lack of access to investment and resources to identify and develop social enterprises are major challenges for the creation of social enterprises. We hypothesize that a successful partnership between two major stakeholders, namely, social entrepreneurs and corporate social responsibility (CSR) investors is the key in developing multiple social enterprises to foster rural development. However, CSR and other investors require quantitative information along with impact evaluation of the value proposition before investing. Social entrepreneurs lack tools to develop and present value propositions for the village in a quantitative form. In this paper, we propose a computational framework to fill this gap and to facilitate dialog between CSR investors and social entrepreneurs that may result in a mutually favorable investment.
Design Optimization of a Three-Stage Planetary Gear Reducer Using Genetic Algorithm
Authors: Feng Yanbiao , Zhang Wenming , Yang Jue , Dong Zuomin 
Published: November 2019

Abstract
The multi-stage reducer, especially the planetary gear reducer, usually serves in heavy-duty machinery such as shield tunneling machine, tracked excavator, mining truck and crusher. Those application areas require great load capacity, long life, and high geometrical mechanical performance, and the high ratio so on. This paper first presents a novel architecture of three-stage reducer. To achieve those objectives collectively, this paper presents an optimization methodology based on genetic algorithm (GA). The geometrical volume is set as objective function. The gear module, teeth number, and gear face width are chosen as design variables, taking the life, geometrical spacing, efficiency and load capacity, etc. as constraints. The optimization results are satisfactory and can help designer to employ novel architecture by fulfilling requirements.
Effects of Head Supported Mass on Predicted Neck Musculoskeletal Loadings During Walking and Running
Authors: Zhou Xianlian , Chen Xinyu , Roos Paulien E. , Whitley Phillip 
Published: November 2019

Abstract
This study aimed to investigate how muscle activation and intervertebral compressive forces during walking and running are altered with different head supported mass (HSM) types. A detailed neck musculoskeletal model was adapted and simulations were performed using existing motion data. It was found HSM wear required increased muscle activations, with the highest increase in running. Extensor activation increased particularly for the HSM with its center of mass (COM) in front of the head’s COM and flexor activation was significantly higher in running than in walking. Intervertebral compressive forces increased with HSM wear and the heaviest HSM caused the highest increase. During walking, the computed maximum compressive force at C7 was 129.7N without an HSM, and 163.6N and 208.5N with HSMs with a mass of 1.43 kg and 3.12 kg respectively. For running, it was 275.7N without an HSM, and 349.1N and 451.2N with the two HSM types. Overall muscle contributions to the compressive force varied over the gait cycle and were higher in running (26–110%) than in walking (18–58%). It was concluded that neck musculoskeletal loading increases with HSM wear, which is affected by HSM mass and mass distribution.
Learning to Design From Humans: Imitating Human Designers Through Deep Learning
Authors: Raina Ayush , McComb Christopher , Cagan Jonathan 
Published: November 2019

Abstract
Humans as designers have quite versatile problem-solving strategies. Computer agents on the other hand can access large scale computational resources to solve certain design problems. Hence, if agents can learn from human behavior, a synergetic human-agent problem solving team can be created. This paper presents an approach to extract human design strategies and implicit rules, purely from historical human data, and use that for design generation. A two-step framework that learns to imitate human design strategies from observation is proposed and implemented. This framework makes use of deep learning constructs to learn to generate designs without any explicit information about objective and performance metrics. The framework is designed to interact with the problem through a visual interface as humans did when solving the problem. It is trained to imitate a set of human designers by observing their design state sequences without inducing problem-specific modelling bias or extra information about the problem. Furthermore, an end-to-end agent is developed that uses this deep learning framework as its core in conjunction with image processing to map pixel-to-design moves as a mechanism to generate designs. Finally, the designs generated by a computational team of these agents are then compared to actual human data for teams solving a truss design problem. Results demonstrates that these agents are able to create feasible and efficient truss designs without guidance, showing that this methodology allows agents to learn effective design strategies.
Design and Analysis of an Auto-Parametrically Excited Platform for Active Vibration Control
Authors: Le Thao , Bhat Sandesh G. , Subramanian Susheelkumar C. , Waswa Peter M. B. , Redkar Sangram 
Published: November 2019

Abstract
Many researchers have proved the potential of autoparametric system in controlling stability and parametric resonance. In this paper, two different designs for auto-parametrically excited mass-spring-damper systems were studied: one system was controlled by rotational motion of the spring, and the other system was controlled by sliding motion of the spring. The theoretical models were developed to predict the behavior of the systems and also generated stability charts to analyze the systems. For each system, the numerical results from both the nonlinear equation and linearized equation were analyzed and compared. Simulation models were constructed to validate the analytical results. The error between simulation and theoretical results was within 2%. Both theoretical and simulation results displayed that the implementation of autoparametric system could help reduce the resonance by up to 33% and amplify the resonance by up to 34%.
Smart Agricultural In-Field Service Robot: From Toy to Tool
Authors: Wang Peng , Tian Junwei , Niu Haoyu , Chen YangQuan 
Published: November 2019

Abstract
A low-cost and multi-functional ground mobile robot is presented for precision agricultural application. A modified toy car is used as the hardware platform, and robotic operating system (ROS) as the software platform. By adding sensors and end effector, the robot can be controlled remotely. Our vision is to build an autonomous in-field service robot to realize some specific tasks instead of farmers.
Investigating the Impact of Component Uncertainty on Autonomous Vehicle Overtaking Maneuvers
Authors: Tsai Hsin-Ting , Chan Kuei-Yuan 
Published: November 2019

Abstract
Autonomous vehicles sense the environment and act accordingly using modern electronic and mechanical components. Although these subsystems and components are delicately designed and manufactured, uncertainties in real-world vehicle operations could cause various undesirable performance deviations or even failure. In this work, we study the impact of component uncertainties on vehicle overtaking maneuver, one of the most common actions in traffic. A model is built to simulate the flow of information and the actions of each component in the control strategy of overtaking. Possible variations of major components are investigated. The impact of uncertainties on the overtaking maneuver are first analyzed. Based on the results, we see that the angle resolution of the distance-detecting device has the biggest impact while the angular velocity-detecting device has relatively small influence. While the control strategy changes, we also observe the impact swifts. Therefore, one could systematically use the existing uncertainty to see how output performance changes by using the proposed model; alternatively, one could also study the robustness of the control strategy under uncertainties.
Improvement of Thermal Performance of Pin Fin Heat Sink Using Different Types of Perforations: A Study Under Natural Convection
Authors: Kumar Aashish , Mondal Manoj Kumar 
Published: November 2019

Abstract
Improvement of thermal management can significantly enhance the coefficient of performance (COP) of the thermoelectric (TE) system which is one of the potential solutions for cooling electronic components. Since heat sinks are an integral part of all the electronic equipment, therefore, great consideration is given towards meticulous selection of heat sink for improving its reliability and performance. Various methods are being studied to improve heat transfer rates of heat sink such as microchannel, liquid cooling, nano-fluids, fin topology optimization, anodization of pins, and changing heat sink materials. Recent studies have demonstrated that perforations in pins increase the heat transfer rate of pin fin heat sink, though, the results are inadequate to infer the best geometry. Further research is hence necessary to establish the best possible combination of geometry, size, and number of perforations. The present work aims to numerically identify a heat sink configuration with maximum heat transfer rate among several configuration possibilities under laminar flow condition using ANSYS Fluent 18.2. The simulation results demonstrate that lateral perforation in fins enable higher heat transfer rate than the unmodified heat sink geometry, due to higher Nusselt number and reduced pressure drop. The parametric study also reveals that heat sink with three elliptical perforations boost heat transfer rates (about 21% higher) when compared to heat sink with solid and other perforated geometries. Furthermore, perforations reduce weight and greater effectiveness, making it more desirable for its wide-scale applications.
Muscle Force Prediction in OpenSim Using Skeleton Motion Optimization Results As Input Data
Authors: Zaman Rahid , Xiang Yujiang , Rakshit Ritwik , Yang James 
Published: November 2019

Abstract
This paper describes an integrated approach to predict human leg and spine muscle forces during lifting by integration of a predictive skeletal model with OpenSim. The two-dimensional (2D) skeletal lifting motion is first predicted by using an inverse dynamics optimization method. Then, the prediction outputs, including joint angle profiles, ground reaction forces, and center of pressure, are incorporated in OpenSim biomechanics software to analyze muscle forces for lifting. Therefore, the integrated approach has predictive capability on musculoskeletal level. By using this method, we can predict and analyze muscles forces for heavy weight lifting motion which is difficult to simulate directly using a 3D musculoskeletal model.
Image-Based Motion Analysis for Self-Reconfigurable Mobile Robot With Integrated Docking
Authors: Sohal Shubhdildeep S. , Ben-Tzvi Pinhas 
Published: November 2019

Abstract
This paper presents the design integration and experimental results of target-based autonomous locomotion of a Self-Reconfigurable Mobile Robot. Uncertainties in the sensory data can accumulate the misalignments in locomotion behavior of the robot. Such misalignments can result in a poor coupling performance resulting in the failure of the overall docked system. Therefore, it is desirable for a robot to be capable of mechanically tolerating such misalignments. As a result, a Hybrid-Wheeled mobile robot, interfaced with a 2-DOF, high misalignment tolerant coupling (GHEFT) mechanism is presented in this paper. This combined assembly is used as a source of locomotion for autonomous docking in a multi-robot assembly using Image-Based Visual Servoing (IBVS). The resulting output is then implemented in a simulated environment for the autonomous locomotion of the robot. Experimental results demonstrate the feature motion and trajectory followed under the hybrid locomotion of the robot.
Design, Analysis, and Optimization of a New Two-DOF Articulated Multi-Link Robotic Tail
Authors: Liu Yujiong , Ben-Tzvi Pinhas 
Published: November 2019

Abstract
Based on observations from nature, tails are believed to help animals achieve highly agile motions. Traditional single-link robotic tails serve as a good simplification for both modeling and implementation purposes. However, this approach cannot explain the complicated tail behaviors exhibited in nature where multi-link structures are more commonly observed. Unlike its single-link counterpart, articulated multi-link tails essentially belong to the serial manipulator family which possesses special transmission design challenges. To address this challenge, a cable driven hyper-redundant design becomes the most used approach. Limited by cable strength and elastic components, this approach suffers from low frequency responses, inadequate generated inertial loading, and fragile hardware, which are all critical drawbacks for robotic tails design. To solve these structure related shortcomings, a multi-link robotic tail made up of rigid links is proposed in this paper. The new structure takes advantage of the traditional hybrid mechanism architecture, but utilizes rigid mechanisms to couple the motions between ith link and i + 1th link rather than using cable actuation. By doing so, the overall tail becomes a rigid mechanism which achieves quasi-uniform spatial bending for each segment and allows performing highly dynamic motions. The mechanism and detailed design for this new tail are synthesized. The kinematic model was developed and an optimization process was conducted to minimize the bending non-uniformity for the rigid tail.
Mathematical Modeling of a Two Degree of Freedom Vibration Energy Harvester for Low Speed Rotary Structure Application
Authors: Nezami Saman , Lee Soobum 
Published: November 2019

Abstract
This paper presents mathematical modeling of a two degree of freedom energy harvester which converts slow mechanical rotation into piezoelectric vibration using gravity force and magnetic repelling force, for large-scale machinery monitoring such as wind turbine blades. The harvester consists of a disk with an unbalanced mass, a piezoelectric cantilevered beam, and two magnets attached to both the beam and the disk. Three coupled equations that describe the motion of the disk, vibration of the beam, and the harvester voltage output are derived using the energy method. Then ODE45 in MATLAB software is used to solve the equations. The result shows that the energy harvester’s performance varied by blade rotational speed. At low blade speed (less than 15 rpm), the harvester generates power by regularized magnetic excitation per blade revolution. The power output of the harvester increases by increasing the blade speed. At high blade speed, however, the disk behavior and the power generation mechanism changes due to the increased centrifugal force. The results show that the model can predict the power peak as a function of blade speed, and the proposed harvester can generate a considerable amount of power for self-sustainable sensing and structural health monitoring.
Self-Starting Cogging-Torque-Assisted Motor Drive for Use in a Heavy-Duty Diesel Engine
Authors: Reinholz Devin K. , Reinholz Bradley A. , Seethaler Rudolf J. 
Published: November 2019

Abstract
This paper describes the design process and simulation results of a variable valve actuation system modeled after the cogging-torque-assisted motor drive (CTAMD) found in literature. Unlike the CTAMD, the new design is capable of handling large exhaust pressures. Furthermore, the new design incorporates damper windings to improve upon the CTAMD by enabling self-starting. The new variable valve actuator is designed for the 6-cylinder Westport 15L diesel engine. The simulated results suggest that the new variation of the CTAMD can be effectively applied to a turbocharged heavy-duty diesel engine.
Simulation results show that the designed motor is capable of self-starting, and infinitely variable lifts. The damper windings are shown to be more beneficial at enabling self-starting and infinitely variable lifts than a spring, since they do not impose additional energy requirements during a valve transition. Furthermore, the new design is also shown to be capable of actuating exhaust valves in the presence of cylinder pressures up to 16 bar with similar efficiency to that of a standard camshaft valve train.