bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Stakeholder Agreement Metric (SAM): Quantifying Preference Agreement Between Product Stakeholders
Authors: Chou Suzanne , Arezoomand Mojtaba , Coulentianos Marianna J. , Nambunmee Kowit , Neitzel Richard , Adhvaryu Achyuta , Austin-Breneman Jesse 
Published: November 2020

Abstract
Go/no-go decisions require engineering design teams to evaluate whether a concept is worth further investment of resources. These decisions can be difficult when product success depends on multiple stakeholders in addition to the end-user. This study proposes the Stakeholder Agreement Metric (SAM) framework to estimate the level of agreement between stakeholder preferences via the distance between optimal designs calculated from a preference model derived from conjoint analysis. The framework was compared to the analytical hierarchy process (AHP) in an empirical case study describing the design and piloting of a hand tool for informal electronic waste workers in Thailand. Data from a follow-up assessment indicate the SAM estimate aligned with future metrics of stakeholder satisfaction. The study further demonstrated AHP may have practical limitations due to survey requirements. This study suggests that the SAM framework is a promising tool to further explore as a way to support designers making go/no-go decisions which involve multiple stakeholders.
Electromechanical Diode: Acoustic Non-Reciprocity in Weakly Nonlinear Metamaterial With Electromechanical Resonators
Authors: Bukhari Mohammad A. , Barry Oumar R. 
Published: November 2020

Abstract
Recent attention has been given to acoustic non-reciprocity in metamaterials with nonlinearity. However, the study of asymmetric cells has been limited to mechanical diodes only. There is no work reported on electromechanical rectifiers or diodes. This problem is investigated here by analytically and numerically studying a combination of nonlinear and linear chains coupled with electromechanical resonators. The system is simulated numerically using MATLAB built in integrator and the results are validated by results found in the literature. Numerical examples are carried out to obtain band structure, operation range of electromechanical diode, harvested power, and significant frequency shift, which is demonstrated using spectro-spatial analyses. The observed frequency shift is used to construct an electromechanical diode to guide the wave to propagate in one direction only. This only allows signal sensing for waves propagating in one direction and rejects any other signals. Furthermore, this electromechanical diode is evaluated by calculating the transmission ratio and the asymmetric ratio for a transient input signal.
Stochastic Stackelberg Games for Agent-Driven Robust Design
Authors: Rismiller Sean C. , Cagan Jonathan , McComb Christopher 
Published: November 2020

Abstract
Products must often endure unpredictable and challenging conditions while fulfilling their intended functions. Game-theoretic methods make it possible for designers to design solutions that are robust against complicated conditions, however, these methods are often specific to the problems they investigate. This work introduces the Game-Augmented Robust Simulated Annealing Teams (GARSAT) framework, a game-theoretic agent-based architecture that generates solutions robust to variation, and models problems with elementary information, making it easily extendable. The platform was used to generate designs under consideration of a multidimensional attack. Designs were produced under various adversarial settings and compared to designs generated without considering adversaries to validate the model. The process successfully created robust designs able to withstand multiple combined conditions, and the effects of the adversarial settings on the designs were explored.
An Efficient Multi-Objective Robust Optimization Method by Sequentially Searching From Nominal Pareto Solutions
Authors: Xia Tingting , Li Mian 
Published: November 2020

Abstract
Multi-objective optimization problems (MOOPs) with uncertainties are common in engineering design problems. To find the robust Pareto fronts, multi-objective robust optimization methods with inner-outer optimization structures generally have high computational complexity, which is always an important issue to address. Based on the general experience, robust Pareto solutions usually lie somewhere near the nominal Pareto points. Starting from the obtained nominal Pareto points, the search process for robust solutions could be more efficient. In this paper, we propose a method that sequentially approaching to the robust Pareto front (SARPF) from the nominal Pareto points. MOOPs are solved by the SARPF in two optimization stages. The deterministic optimization problem and the robustness metric optimization problem are solved in the first stage, and nominal Pareto solutions and the robust-most solutions can be found respectively. In the second stage, a new single-objective robust optimization problem is formulated to find the robust Pareto solutions starting from the nominal Pareto points in the region between the nominal Pareto front and the robust-most points. The proposed SARPF method can save a significant amount of computation time since the optimization process can be performed in parallel at each stage. Vertex estimation is also applied to approximate the worst-case uncertain parameter values which can save computational efforts further. The global solvers, NSGA-II for the multi-objective case and genetic algorithm (GA) for the single-objective case, are used in corresponding optimization processes. Two examples with comparison to a previous method are presented for the applicability and efficiency demonstration.
Two-Phase Thermal Metamaterial
Authors: Xu Zifu , Li Longqiu , Li Jiaxin 
Published: November 2020

Abstract
The capability of thermal metamaterials is required from single function to multifunction under different external heat conditions. The methods to develop thermal materials by simple structural transformations have been explored. While, the components of traditional thermal metamaterial are mainly set as solid materials, which is difficult to change the composition of materials, such as recombing and fixing the spatial position of material, because of material rigidity. Therefore, the potential of thermal materials is limited. Liquid has fluidity in spatial structure, for which the efficient combination of solid-liquid materials provides an avenue for dynamically modeling thermal field.
Herein, we propose the concept of two-phase thermal metamaterial, which is switchable by microscale elements. On one side, we develop a switchable thermal meta-unit manipulated by micro-element under the gradient field and explore the process of heat transfer by focusing on radiation and conduction under translucent media condition. Otherwise, we propose a method to achieve a non-reciprocal heat transfer system by the design of two-phase media. The propose of two-phase thermal metamaterials set a general background for a variety of applications for complex conditions.
Design of a Quadratic, Antagonistic, Cable-Driven, Variable Stiffness Actuator
Authors: Moore Ryan , Schimmels Joseph M. 
Published: November 2020

Abstract
Antagonistically actuated Variable Stiffness Actuators (VSAs) take inspiration from biological muscle structures to control both the stiffness and positioning of a joint. The design presented utilizes a cable running through a set of three pulleys, to displace a linear spring, yielding quadratic spring behavior. A quasi-static model of the mechanism is used to assess and optimize the force-displacement behavior. The mechanism prototype yielded a good match to the desired elastic behavior.
Mission Mobility Reliability Analysis of Off-Road Ground Vehicles
Authors: Liu Yixuan , Jiang Chen , Hu Zhen , Mourelatos Zissimos P. , Fu Yan , Gorsich David , Jayakumar Paramsothy , Majcher Monica 
Published: November 2020

Abstract
The NATO Reference Mobility Model (NRMM) has been developed to predict the mobility of off-road ground vehicles based on modeling and simulation (M&S). Due to various uncertainty sources in the M&S, uncertainty is inherent in the vehicle mobility. Aims to account for the uncertainty in the mobility prediction in mission planning, this paper develops a simulation-based mission mobility reliability analysis framework for off-road ground vehicles. A concept of mission mobility reliability (MMR) is first proposed to quantify the reliability of a mission path which passes through different types of soils. A single-loop Kriging surrogate modeling method is then employed to overcome the challenge in the mission mobility reliability assessment caused by the computationally expensive mobility simulation. Built upon the surrogate model-based mission mobility reliability analysis, a dynamic updating scheme is proposed to update the MMR estimation based on the on-line mobility data, during the course of a specific mission and for a particular vehicle. The online dynamic updating of MMR allows for effective and dynamic decision making during the mission phase. A case study is used to demonstrate the effectiveness of the proposed MMR analysis and updating framework.
Lineup Design Method for Intermediate Product Family by Monotonicity-Guided Optimization of Nested Mini-Max Problem
Authors: Fujita Kikuo , Ono Naoki , Mitsuhashi Yui , Nomaguchi Yutaka 
Published: November 2020

Abstract
As a product has become complicated, and its requirements have been diversified, the simultaneous and integrative design of a series of products has become so important. However, the contents of design activities have become complex across product variety and supply chain. This paper views such a situation through a chain of parts, intermediate products, and final products, and focuses on the lineup design problem of an intermediate product. The lineup design means here to secure the worst-case performance of intermediate products across a range of specifications. The problem is formulated as a mathematical problem to maximize the worst-case efficiency, i.e., the minimum efficiency of products across the range by arranging commonalization strategy, segmentation of the range, and original design variables. This paper proposes a two-phase approach, designing a framework, and optimizing contents under the framework. The latter phase is formulated as a nested mini-max optimization problem. An effective and efficient optimization scheme is configured with employing monotonicity analysis. Finally, an application to universal motors is demonstrated for ascertaining the validity and promises of the proposed design method.
Lyapunov Perron Transformation for Linear Quasi-Periodic Systems
Authors: Subramanian Susheelkumar C. , Redkar Sangram , Waswa Peter 
Published: November 2020

Abstract
It is known that a Lyapunov Perron (L-P) transformation converts a quasi-periodic system into a reduced system with a time-invariant coefficient. Though a closed form expression for L-P transformation matrix is missing in the literature, the application of combination of multiple theories would aid in such transformation. In this work, the authors have worked on extending the Floquet theory to find L-P transformation. As an example, a commutative system with linear quasi-periodic coefficients is transformed into a system with time-invariant coefficient analytically. Furthermore, for non-commutative systems, similar results are obtained in this work, with the help of an intuitive state augmentation and Normal Forms technique. The results of the reduced system are compared with the numerical integration technique for validation.
Symbolic Computation of Inverse Kinematics for General 6R Manipulators Based on Raghavan and Roth’s Solution
Authors: Arikawa Keisuke 
Published: November 2020

Abstract
We discuss the symbolic computation of inverse kinematics for serial 6R manipulators with arbitrary geometries (general 6R manipulators) based on Raghavan and Roth’s solution. The elements of the matrices required in the solution were symbolically calculated. In the symbolic computation, an algorithm for simplifying polynomials upon considering the symbolic constraints (constraints of the trigonometric functions and those of the rotation matrix), a method for symbolic elimination of the joint variables, and an efficient computation of the rational polynomials are presented. The elements of the matrix whose determinant produces a 16th-order single variable polynomial (characteristic polynomial) were symbolically calculated by using structural parameters (parameters that define the geometry of the manipulator) and hand configuration parameters (parameters that define the hand configuration). The symbolic determinant of the matrix consists of huge number of terms even when each element is replaced by a single symbol. Instead of expressing the coefficients in a characteristic polynomial by structural parameters and hand configuration parameters, we substituted appropriate rational numbers that strictly satisfy the constraints of the symbols for the elements of the matrix and calculated the determinant (numerical error free calculation). By numerically calculating the real roots of the rational characteristic polynomial and the joint angles for each root, we verified the formulation for the symbolic computation.
Human Inductive Biases in Design Decision Making
Authors: Shergadwala Murtuza N. , Panchal Jitesh H. 
Published: November 2020

Abstract
Designers make information acquisition decisions, such as where to search and when to stop the search. Such decisions are typically made sequentially, such that at every search step designers gain information by learning about the design space. However, when designers begin acquiring information, their decisions are primarily based on their prior knowledge. Prior knowledge influences the initial set of assumptions that designers use to learn about the design space. These assumptions are collectively termed as inductive biases. Identifying such biases can help us better understand how designers use their prior knowledge to solve problems in the light of uncertainty. Thus, in this study, we identify inductive biases in humans in sequential information acquisition tasks. To do so, we analyze experimental data from a set of behavioral experiments conducted in the past [1–5]. All of these experiments were designed to study various factors that influence sequential information acquisition behaviors. Across these studies, we identify similar decision making behaviors in the participants in their very first decision to “choose x”. We find that their choices of “x” are not uniformly distributed in the design space. Since such experiments are abstractions of real design scenarios, it implies that further contextualization of such experiments would only increase the influence of these biases. Thus, we highlight the need to study the influence of such biases to better understand designer behaviors. We conclude that in the context of Bayesian modeling of designers’ behaviors, utilizing the identified inductive biases would enable us to better model designer’s priors for design search contexts as compared to using non-informative priors.
Experimental Forced Response Analysis of Two-Degree-of-Freedom Piecewise-Linear Systems With a Gap
Authors: Saito Akira , Umemoto Junta , Noguchi Kohei , Tien Meng-Hsuan , D’Souza Kiran 
Published: November 2020

Abstract
In this paper, an experimental forced response analysis for a two degree of freedom piecewise-linear oscillator is discussed. First, a mathematical model of the piecewise linear oscillator is presented. Second, the experimental setup developed for the forced response study is presented. The experimental setup is capable of investigating a two degree of freedom piecewise linear oscillator model. The piecewise linearity is achieved by attaching mechanical stops between two masses that move along common shafts. Forced response tests have been conducted, and the results are presented. Discussion of characteristics of the oscillators are provided based on frequency response, spectrogram, time histories, phase portraits, and Poincaré sections. Period doubling bifurcation has been observed when the excitation frequency changes from a frequency with multiple contacts between the masses to a frequency with single contact between the masses occurs.
Architecture Selection for Hybrid Electric Mobility As a Service Vehicle
Authors: Schaich Noah , Free Christian , Nekoo Nishan , Leamy Michael J. 
Published: November 2020

Abstract
This paper documents the vehicle modeling and fuel economy simulation efforts for the Georgia Tech EcoCAR Mobility Challenge team during Year 1 of the current Advanced Vehicle Technology Competition (AVTC). The goal of the first year of the competition was to propose two possible hybrid electric vehicle (HEV) architectures based on a 2019 Chevrolet Blazer platform that could be built and refined throughout Years 2–4 of the competition. A Simulink vehicle model was used to compare a variety of HEV architectures with several different combinations of engines, batteries, and electric machines. An adaptive Equivalent Consumption Minimization Strategy was used to split torque between the internal combustion engine and two electric machines so that architectures with two electric machines could be modeled. The model was validating by comparing results from simulating a conventional Chevrolet Blazer with the 2.5L naturally aspirated engine to fuel economy results obtained by the Environmental Protection Agency (EPA). In addition to developing a hybrid vehicle, the competition is focused on exploring Mobility as a Service (MaaS), which introduces some special considerations when choosing a hybrid vehicle architecture. The results of the Simulink model as well as requirements set by the MaaS market led the Georgia Tech EcoCAR team to pursue a dual electric machine P0P4 parallel through the road hybrid vehicle.
Dynamic Performance Comparison Between In-Wheel and On-Board Motor Battery Electric Vehicles
Authors: de Carvalho Pinheiro Henrique , Castro dos Santos Pedro Gabriel , Sisca Lorenzo , Scavuzzo Santo , Ferraris Alessandro , Airale Andrea Giancarlo , Carello Massimiliana 
Published: November 2020

Abstract
This paper intends to present a novel full-vehicle numerical approach for in-wheel and on-board motor Battery Electric Vehicle (BEV) powertrain architectures, which overcomes the electrical and mechanical deficits widely present in the current literature. Namely, neglecting of the interaction between mechanical and electrical phenomena and its impact on the vehicle dynamic performance.
A co-simulation approach is employed: whereas the mechanical systems and their interactions are simulated with Adams Car, the electrical phenomena are solved by MATLAB/Simulink. The investigation is conducted over a full throttle maneuver by monitoring a set of performance indicators.
Design and Development of a Constant Force Non-Linear Spring (CF-NLS) for Energy Storage
Authors: Qaiser Zeeshan , Kang Liping , Johnson Shane 
Published: November 2020

Abstract
Development of constant force non-linear softening (CF-NLS) springs has recently gained attention in the literature due to their energy storage potential in many applications including robotics, biomechanics, machining, etc. These springs are typically designed by using computationally exhaustive topology optimization techniques which have shown to produce stress concentrations significantly reducing the operational life of the spring. Furthermore, current design methodologies including spline based optimizations are not exploiting the design space efficiently. There is a need of a computationally efficient design methodology capable of producing mechanisms without stress concentrations while more fully exploiting the design space. A new graph based design methodology is proposed by using a modified-depth first search (M-DFS) algorithm with 2D finite element analysis. A detailed parametric study is also conducted to design a mechanism by maximizing of the stored strain energy on a general stiffest-softening behavior. The proposed CF-NLS is validated experimentally and compared with mechanisms in the literature. It is observed that the proposed CF-NLS is providing more displacement capacity without stress concentrations and with less expensive materials due to improved exploitation of the design space. This proposed CF-NLS is beneficial for dynamic activities like walking, running and jumping robots or biomechanics where high energy storage capacity is required.
Geometrico-Static Analysis of a New Collaborative Parallel Robot for Safe Physical Interaction
Authors: Jeanneau Guillaume , Bégoc Vincent , Briot Sébastien 
Published: November 2020

Abstract
This paper introduces a geometrico-static analysis of an intrinsically safe parallel manipulator called R-Min. This robot was designed to reduce the risk of injury during a collision with a human operator, thanks to an underactuated architecture which enables large internal displacements in case of a collision. Indeed, the R-Min architecture is based on a modification of the well-known planar five-bar mechanism, where additional passive joints are introduced on the distal links in order to create a planar seven-bar mechanism with two degrees of underactuation. These two additional degrees of freedom are passively driven through the use of a supplementary passive leg, in which a tension spring is mounted between the base and the end-effector.
In this paper, the conditions satisfying the equilibrium and the stability of the mechanism are introduced, based on a geometrico-static analysis. The direct and inverse problems are then solved using a numerical approach. Solutions to both problems are presented and classified. One subset of solutions to the inverse problem is isolated and projected in the Cartesian space in order to obtain the payload-invariant workspace of the R-Min robot.
A Power Analysis to Determine Appropriate Sample Size for the Study of Student Design-Team Effectiveness
Authors: Takai Shun , Smith Thomas J. , Esterman Marcos 
Published: November 2020

Abstract
Forming collaborative teams is a critical first step in team-project-based design courses as team composition directly affects not only teamwork processes and outcomes but also teamwork skills and experience. While various approaches have been used to form teams, the best methodology has not been found due to a lack of understanding of how team compositions impact team performance and teamwork learning. We need to establish a team effectiveness model for student design teams that describes relationships between team characteristics and team performance or teamwork learning. One of many challenges in such an effort is to estimate an appropriate sample size to achieve statistically significant results before starting data collection. In this paper, we demonstrate a power analysis for determining an appropriate sample size, i.e., the number of student teams, before we study the effectiveness of student design-teams. We first present a hypothesized team effectiveness model for student design teams that shows possible relationships among team factors. We then illustrate a statistical analysis procedure for studying the team effectiveness model using structural equation modeling (SEM) or path analysis. We finally demonstrate a power analysis of SEM for determining the appropriate sample size for studying the team effectiveness model.