bluuebunny/crossref_metadata_2025_split huggingface dataset:
Does It Translate? A Case Study of Conceptual Design Outcomes With U.S. and Moroccan Students
Authors: Peng Aoran , Menold Jessica , Miller Scarlett R. 
Published: November 2020

Abstract
High globalization in the world today results in the involvement of multi-discipline, multi-cultural teams, as well as the entrance of more economic powers in the market. Effective innovation strategies are critical if emerging markets plan to become economic players in this increasingly connected global market. The current work compares the design processes of designers from emerging and established markets to understand how design methods are applied across culture. Specifically, the design decisions of designers from Morocco, one of the four leading economic power in Africa, and the U.S. are investigated. Concept generation and selection are the focus of the current study as they are critical steps in the design process that can determine project outcomes. Previous studies have identified three factors, ownership bias, gender, and idea goodness as influential during concept selection. The effect of these three factors on designers in the United States is well established. The current study expands upon previous findings to examine the influence of these factors across two cultures — U.S. and Morocco. The results of this study, although preliminary, found that U.S. students had a higher idea fluency than Morocco students. It also found a significant difference in idea fluency between genders in the U.S. but not in Morocco. In addition, it was found that overall, participants exhibited ownership bias toward ideas with high goodness.
Scalable Thermal Simulation of Powder Bed Fusion
Authors: Zhang Yaqi , Shapiro Vadim , Witherell Paul 
Published: November 2020

Abstract
Powder bed fusion (PBF) has become a widely used additive manufacturing (AM) technology to produce metallic parts. Since the PBF process is driven by a moving heat source, consistency in part production, particularly when varying geometries, has proven difficult. Thermal field evolution during the manufacturing process determines both geometric and mechanical properties of the fabricated components. Simulations of the thermal field evolution can provide insight into desired process parameter selection for a given material and geometry. Thermal simulation of the PBF process is computationally challenging due to the geometric complexity of the manufacturing process and the inherent computational complexity that requires a numerical solution at every time increment of the process.
We propose a new thermal simulation of the PBF process based on the laser scan path. Our approach is unique in that it does not restrict itself to simulations on the part design geometry, but instead simulates the formation of the geometry based on the process plan of a part. The implication of this distinction is that the simulations are in tune with the as-manufactured geometry, meaning that calculations are more aligned with the process than the design, and thus could be argued is a more realistic abstraction of real-world behavior. The discretization is based on the laser scan path, and the thermal model is formulated directly in terms of the manufacturing primitives. An element growth mechanism is introduced to simulate the evolution of a melt pool during the manufacturing process. A spatial data structure, called contact graph, is used to represent the discretized domain and capture all thermal interactions during the simulation. The simulation is localized through exploiting spatial and temporal locality, which is based on known empirical data. This limits the need to update to at most a constant number of elements at each time step. This implies that the proposed simulation not only scales to handle three-dimensional (3D) printed components of arbitrary complexity but also can achieve real-time performance. The simulation is fully implemented and validated against experimental data and other simulation results.
Towards Engineering Complex Socio-Technical Systems Using Network Motifs: A Case Study on Bike-Sharing Systems
Authors: Xiao Yinshuang , Sha Zhenghui 
Published: November 2020

Abstract
The socio-technical system (STS) is an important topic in Systems Engineering and Design Science. Its performance is not only affected by social aspects but also influenced by various technical factors. To understand the relationships and interactions among different components and subsystems in STS, many studies have been done either at individual agent level or at the system level, yet few studies were conducted at the local structural level in such systems. Motivated by this research gap, we developed an approach to analyzing STS based on the network motif theory. In this study, we apply this approach to three bike-sharing systems (BSS) to validate its feasibility. We focus on studying the size-3 motif, the most basic building block of complex networks, and its correlations to a BSS’s rebalancing performance in three different cities, i.e., NYC, Chicago, and Los Angeles. This paper reaches three conclusions. First, both seasonal and city effects play a significant role in affecting BSS’s network structure and its local motif characteristics. Second, the rebalancing issue, i.e., the imbalance between bike returns and rentals, happened at the local transit level can be different from that observed at the system level, and vice versa. Third, the average geographical distance of size-3 trip motifs follows strong patters correlated to the motif structures as well as the number of directed links in a motif. Compared with previous studies, these insights would be beneficial to guiding system designers in engineering STS, particularly from a bottom-up manner (e.g., using mechanisms or incentives), to achieve desired system-level performance. This study also provides an in-depth understanding of the relations between local system structures and system-level performance in an STS, therefore contributes to both the design theory of complex systems and the BSS research community from a new network motif-based perspective.
Effects of Locus of Control Personality Trait on Team Performance in Cooperative Engineering Design Tasks
Authors: Avşar Alkım Z. , Grogan Paul T. 
Published: November 2020

Abstract
Teams in engineering design tackle problems that exceed the abilities of individuals. Improved understanding of how personality traits influence human behaviors and interaction may help create new methods and tools to support design teams. This paper seeks to understand how the Locus of Control (LOC) personality trait influences designer behaviors and team performance. A designer experiment studies 12 participant pairs controlled for categorical LOC pairing factors (internal-internal, external-external, and internal-external). Each design team completes six simplified cooperative parameter design tasks to minimize completion time, yielding 72 total data points. Regression analysis shows LOC pairing affects team efficiency in agreement with literature outside engineering design: diverse LOC traits reduce design efficiency while similarity increases team effectiveness. Results contribute to an explanatory hypothesis that LOC pairing influences designer behaviors related to action effectiveness which, subsequently, affects team performance outcomes.
Elastic Metasurfaces for Low-Frequency Flexural Wavefront Control
Authors: Lin Zhenkun , Tol Serife 
Published: November 2020

Abstract
Controlling elastic/acoustic wave-front via compact designs has attracted increasing research interest in past decades. The emerging of metasurface concept provides an unconventional and attractive approach in this filed. A metasurface generally consists of a single array of subwavelength-scaled patterns in the host medium, introducing an abrupt phase shift in the wave propagation path. In this paper, we explored an elastic metasurface concept to control the propagation of low-frequency flexural Lamb waves. The phase modulation based on the Snell’s law was achieved by tailoring the thickness of thin beam resonators connecting two elastic host medium. Depending on the design of the phase-modulated structure (a.k.a. metasurface), elastic waves could be steered or focused which was verified through analytical and numerical models.
Mistuning Identification for Rotating Bladed Disks Using Stationary Measurements and Reduced Order Models
Authors: Kurstak Eric , Look Karsten , D’Souza Kiran 
Published: November 2020

Abstract
Although full-scale representative experiments provide critical data for final validation of designs, there is increasing emphasis on computational and reduced scale experiments to test out initial design concepts. This is true in many fields, especially in the field of turbomachinery; turbomachines are complex machines that operate at high temperatures and pressures for long durations of time and it is very expensive to build prototypes and conduct full scale testing. Stationary test rigs are cheaper to design and operate than rotating test rigs, but can lack the proper boundary conditions required to mimic actual operating conditions. A key characteristic of the design that is identified from experiments for bladed disks is mistuning. Mistuning are the sector to sector differences in bladed disks due to manufacturing tolerance, operational wear, or material deviations, and can lead to vibration localization. This work provides insight in correlating stationary mistuning measurements to the mistuning observed in a rotating bladed disk. The mistuning values from bench-top tests are shown to match the mistuning values from the rotating experiments. A parametric reduced order model (PROM) is constructed using stationary mistuning values to model the fully mistuned system, complete with rotational speed effects such as stress stiffening. The PROM enables changing the mistuning and rotational speed effects in the reduced space. The natural frequencies of the computational model are compared to the experimental blade frequencies to show that the computational model is similar to the experimental system. The final model can then be used to simulate the physical experiments using time integration methods.
Evolutionary Approach to Function Model Synthesis: Development of Parameterization and Synthesis Rules
Authors: Gill Amaninder Singh , Sen Chiradeep 
Published: November 2020

Abstract
The goal of this paper is to develop the groundwork for automated synthesis of function models. To this end, an evolutionary algorithm based framework has been developed. A parameterization method that can completely describe any given function models has been proposed. The parameterization makes the function models compatible for use within the evolutionary algorithm framework. Validation of the parameterization method is carried out by using an evolutionary algorithm to synthesize the function models for five different electromechanical products. The algorithm converged in each case, indicating that the method is satisfactory and that function models can actually be synthesized using an evolutionary framework. In addition, the adaptation of several a priori rules for use in this framework has been proposed. These rules are categorized as grammar, logical and feature based rules. An updated evolutionary framework that incorporates these rules is also presented.
Method Selection in Human-Centered Design Teams: An Examination of Decision-Making Strategies
Authors: Rao Vivek , Kim Euiyoung , Kwon Jieun , Agogino Alice , Goucher-Lambert Kosa 
Published: November 2020

Abstract
Designers’ choices of methods are well known to shape project outcomes. However, questions remain about why design teams select particular methodsand how teams’ decision-making strategies are influenced by project- and process-based factors. In this work, we analyze novice design teams’ decision-making strategies underlying 297 selections of human-centered design methods over the course of three semester-long project-based engineering design courses. We propose a framework grounded in 100+ factors sourced from new product development literature that classifies design teams’ method selection strategy as either agent-, outcome-, or process-driven, with eight further subclassifications. Coding method selections with this framework, we uncover three insights about design team method selection. First, we identify fewer outcomes-based selection strategies across all phases and innovation types. Second, we observe a shift in decision-making strategy from user-focused outcomes in earlier phases to product-based outcomes in later phases. Third, we observe that decision-making strategy produces a greater heterogeneity of method selections as compared to the class average as a whole, or project type alone. These findings provide a deeper understanding of designers’ method selection behavior and have implications for effective management of design teams, development of automated design support tools to aid design teams, and curation of design method repositories, e.g., theDesignExchange.
Nonlinear Time-Series Prediction Using a Single MEMS Reservoir
Authors: Hasan Mohammad H. , Alsaleem Fadi 
Published: November 2020

Abstract
In this work, we show the computational potential of MEMS devices by predicting the dynamics of a 10th order nonlinear auto-regressive moving average (NARMA10) dynamical system. Modeling this system is considered complex due to its high nonlinearity and dependency on its previous values. To model the NARMA10 system, we used a reservoir computing scheme by utilizing one MEMS device as a reservoir, produced by the interaction of 100 virtual nodes. The virtual nodes are attained by sampling the input of the MEMS device and modulating this input using a random modulation mask. The interaction between virtual nodes within the system was produced through delayed feedback and temporal dependence. Using this approach, the MEMS device was capable of adequately capturing the NARMA10 response with a normalized root mean square error (NRMSE) = 6.18% and 6.43% for the training and testing sets, respectively. In practice, the MEMS device would be superior to simulated reservoirs due to its ability to perform this complex computing task in real time.
Enabling Traceability in Agri-Food Supply Chains Using an Ontological Approach
Authors: Ameri Farhad , Wallace Evan , Yoder Reid 
Published: November 2020

Abstract
Traceability of food products to their sources is critical for quick responses to a food emergency. US law now requires stakeholders in the agri-food supply chain to support traceability by tracking food materials they acquire and sell. However, having complete and consistent information needed to quickly investigate sources and identify affected material has proven difficult. There are multiple reasons that makes food traceability a challenging task including diversity of stakeholders and their lexicons, standards, tools and methods; unwillingness to expose information of internal operations; lack of a common understanding of steps in a supply chain; and incompleteness of data. Ontologies can address the traceability challenge by creating a shared understanding of the traceability model across stakeholders in a food supply chain. They can also support semantic mediation, data integration, and data exploration. This paper reports an on ongoing effort aimed at developing a formal ontology for supply chain traceability using use cases and data from partners in the bulk grain domain. The developed ontology was validated in VocBench environment through creating RDF triples from real datasets and executing SPARQL queries corresponding to predefined competency questions.
A Life Cycle Analysis of Laser Cutter Embodied Impacts
Authors: Moore George , Goucher-Lambert Kosa , Agogino Alice M. 
Published: November 2020

Abstract
There are broad claims about how makerspaces, Fab Labs, and hacker spaces are going to make production trends more sustainable and facilitate equitable access to manufacturing opportunities. Absent from most of these discussions are metrics for success: how will these personal fabrication spaces assess their status as self-sufficient, self-serving, and sustainable? Laser cutters are one of the more popular tools in personal fabrication spaces; yet there are gaps in the literature regarding their environmental impacts as compared to popular tools. Research on embodied environmental impacts is lacking for laser cutters and this study aims to fill a part of that gap by examining the embodied impacts of the Universal Laser System’s (ULS) VL-300 laser cutter. Results showed that 49.58 ReCiPe Endpoint H points were required to produce and distribute the ULS VL-300 laser cutter. Specifically, embodied impacts of the electronics — the micro-controllers required to operate the laser cutter — are responsible for the bulk (74%) of the overall laser cutter embodied impacts.
Engineering for Global Development: Characterizing the Discipline Through a Systematic Literature Review
Authors: Burleson Grace , Austin-Breneman Jesse 
Published: November 2020

Abstract
Over the past 50 years, researchers have repeatedly proposed the establishment of a new interdisciplinary engineering field in Engineering for Global Development (EGD), whose analytical tools and design processes result in positive social impacts and poverty alleviation in a global development context. Within each discipline and research area, a growing body of work has sought to systematically create scientific knowledge in this area. However, a recent network analysis of Human-Centered Design plus Development research indicates that sub-communities are not collaborating at a high level and therefore the overall research agenda may lack cohesion. This paper presents a descriptive analysis of EGD research within mechanical engineering along four dimensions through a systematic literature review and secondary data analysis. Results from the review and a Latent Dirichlet Allocation model indicate EGD work in mechanical engineering draws upon research methodologies from a number of other fields and has low levels of consensus on technical terminology. These results suggest consensus in the broader interdisciplinary EGD field should be examined.
A Parametric Study on the Effects of Reynolds Number on the Topology Optimization of Navier-Stokes Flows
Authors: Najmon Joel C. , Wu Tong , Tovar Andres 
Published: November 2020

Abstract
Fluid-flow topology optimization (FTO) allows the generation of innovative flow-channel layouts with minimal pressure drop (power dissipation) between inlet and outlet ports in a given design domain. FTO was first explored using Stokes flow with the material in the design domain modeled as a porous medium governed by Darcy’s law. More recently, Navier-Stokes flow has been implemented to consider higher Reynolds numbers. The objective of this work is to demonstrate the effect of the Reynolds number on the FTO results and generate a set of design rules. To this end, a density-based FTO algorithm and an in-house finite element analysis code for incompressible Navier-Stokes flow are developed. The optimization process is updated using the method of moving asymptotes so that the flow’s potential power is maximized. The nonlinear Navier-Stokes equations are solved using a trust region Newton’s method. Sensitivity analysis is carried out using the adjoint method. A parametric study of the underlying parameters of the Reynolds number in two numerical examples shows the effect of the fluid’s dynamic viscosity and velocity on the optimized flow channels. The results show that fluids with the same Reynolds number, but with different dynamic viscosity or velocity values, can generate significantly different flow channels.
Design of Passive Lower Limb Exoskeleton to Aid in Injury Mitigation and Muscular Efficiency
Authors: Tracey Dylan , Zhang Hao 
Published: November 2020

Abstract
With the duties and responsibilities of the military, they are on the cutting edge of R&D and the latest and greatest technologies. One significant problem effecting thousands of soldiers are injuries to the lower limbs, specifically the knees, as a result of high impact to the joints and muscles. Through the research of biomechanics and ergonomics during human locomotion of running, cause and effects fatigue, muscular activation during running, gait cycle force analysis, and biomimicry of kangaroos, we were able to identify lower limb exoskeletons as a viable solution to the problem. The purpose of this research was to develop a relatively inexpensive prototype of a passive lower limb exoskeleton to aid in injury mitigation and muscular efficiency for soldiers. The hypothesis was that a lower limb exoskeleton would reduce/mitigate injuries by reducing stride length and increases stride frequency to lower impact on the knees while running. The prototype was tested by one participant on a 2-mile course with two load variations tested while running. The key results were seen from the spring systems potential to increase average stride cadence/frequency by 6–14% and reduce impact on joints and muscles by increasing the number of steps and reducing high center of gravity oscillation by 13–27%. Furthermore, this study provides evidence and research that proves that a passive lower limb exoskeleton design, which increases stride frequency and reduces stride length, can mitigate injuries to the lower limbs when running with weight by reducing the impact forces on the knees and improving running economy.
A Pre-Prototyping Framework to Explore Human-Centered Prototyping Strategies During Early Design
Authors: Ahmed Salman , Demirel H. Onan 
Published: November 2020

Abstract
Current prototyping frameworks are often prompt-based and heavily rely on designers’ experience. The lack of systematic guidelines in prototyping activities causes unwanted variation in the quality of the prototype. Notably, there is limited, or no prototyping framework exists that enables human factors engineering (HFE) guidelines be part of the early product development process. In this paper, a pre-prototyping framework is proposed to render human-centered design strategies to guide designers before the hands-on prototyping activity starts. The methodology consists of extracting key factors related to prototyping and human factors engineering principles based on an extensive literature review. The key elements are then combined to form the prototyping categories, dimensions (theory), and tools (practice). The resulting prototyping framework can be used to develop prototyping strategies consist of theoretical guidelines and practical tools that are needed during the prototyping of human-centered products. The framework provides systematic guidance to designers in the early stages of the design process so that designers, in particular novices in ergonomics and human factors, can have a head start in building the prototypes in the right direction. Finally, a case study is presented to demonstrate a walk-through and efficacy of the proposed pre-prototyping framework.
Learning to Abstract and Compose Mechanical Device Function and Behavior
Authors: Wang Jun , Chiu Kevin , Fuge Mark 
Published: November 2020

Abstract
While current neural networks (NNs) are becoming good at deriving single types of abstractions for a small set of phenomena, for example, using a single NN to predict a flow velocity field, NNs are not good at composing large systems as compositions of small phenomena and reasoning about their interactions. We want to study how NNs build both the abstraction and composition of phenomena when a single NN model cannot suffice. Rather than a single NN that learns one physical or social phenomenon, we want a group of NNs that learn to abstract, compose, reason, and correct the behaviors of different parts in a system. In this paper, we investigate the joint use of Physics-Informed (Navier-Stokes equations) Deep Neural Networks (i.e., Deconvolutional Neural Networks) as well as Geometric Deep Learning (i.e., Graph Neural Networks) to learn and compose fluid component behavior. Our models successfully predict the fluid flows and their composition behaviors (i.e., velocity fields) with an accuracy of about 99%.