bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mirroring Neurostimulation Outcomes Through Behavioral Interventions to Improve Creative Performance
Authors: Sahar A. , Farb N. A. S. , Shu L. H. 
Published: November 2020

Abstract
Creativity, a key component of engineering design, is not a static trait, but a skill that can be strategically enhanced. Neurostimulation methods, e.g., using electrical current to stimulate brain areas, have been reliably shown to improve creative performance. However, safety and ethical concerns present obstacles to the direct implementation of such methods in the engineering-design process. Thus, the current work explores whether creative performance can be enhanced using behavioral tasks that recruit the same brain regions targeted in neurostimulation studies.
Study participants were 30 undergraduate students enrolled in an introductory psychology course. Two intervention tasks, a Stroop task and a finger-tapping pattern-matching task, each with easy and hard versions, were used in a 2 (task type) x 3 (task difficulty) within-subjects design. Relative to the pretest period, difficulty was manipulated by using versions of tasks with 1) predictable responses (easy) and 2) unpredictable responses (hard). Creativity in each experimental condition was assessed via the well-validated Alternative Uses Test (AUT).
A multilevel analysis revealed a significant increase in fluency (number of alternative uses) as task difficulty increased regardless of task type. Flexibility (number of alternative-uses categories) also increased with task difficulty, but the effect was stronger for the Stroop task. These results suggest that high-difficulty versions of the selected tasks may be more effective in increasing AUT performance. Between the two tasks studied, the Stroop task has greater potential as a candidate to adapt as a behavioral intervention to improve creativity. Beyond the Stroop task, other behaviors, which activate brain regions that respond favorably to neurostimulation, may also be explored as the bases of interventions to improve creative performance in engineering design.
Experimental Study of Mullins Effect in Natural Rubber for Different Stretch Conditions
Authors: Gkouti Elli , Yenigun Burak , Jankowski Krystof , Czekanski Aleksander 
Published: November 2020

Abstract
We subjected rubber coupons to cyclical uniaxial tension to investigate the softening effect, where the primary loading at its initial position was followed by additional unloading and reloading. Less stress was required upon reloading than that required in the previous loading for the same degree of stretch, reached on the first loading. This stress softening is significant when reloading follows virgin loading. The magnitude of stress softening is related to the maximum stretch elastomers can achieve in each cycle. To investigate this phenomenon, rubber coupons were subjected to four cycles of simple tension until the desired stretch was reached. We expected that several tests under the same conditions would provide almost identical results. However, we observed different stress requirements for different degrees of stretch when multiple cycles of the same stretch were performed. For three different experimental tests of the same amount of stretch, we saw huge differences in each cycle of loading-relaxation-reloading, a phenomenon that was more obvious during stress relaxation.
Data Driven Model Identification for a Chaotic Pendulum With Variable Interaction Potential
Authors: Yesilli Melih C. , Khasawneh Firas A. 
Published: November 2020

Abstract
Data driven model identification methods have grown increasingly popular due to enhancements in measuring devices and data mining. They provide a useful approach for comparing the performance of a device to the simplified model that was used in the design phase. One of the modern, popular methods for model identification is Sparse Identification of Nonlinear Dynamics (SINDy). Although this approach has been widely investigated in the literature using mostly numerical models, its applicability and performance with physical systems is still a topic of current research. In this paper we extend SINDy to identify the mathematical model of a complicated physical experiment of a chaotic pendulum with a varying potential interaction. We also test the approach using a simulated model of a nonlinear, simple pendulum. The input to the approach is a time series, and estimates of its derivatives. While the standard approach in SINDy is to use the Total Variation Regularization (TVR) for derivative estimates, we show some caveats for using this route, and we benchmark the performance of TVR against other methods for derivative estimation. Our results show that the estimated model coefficients and their resulting fit are sensitive to the selection of the TVR parameters, and that most of the available derivative estimation methods are easier to tune than TVR. We also highlight other guidelines for utilizing SINDy to avoid overfitting, and we point out that the fitted model may not yield accurate results over long time scales. We test the performance of each method for noisy data sets and provide both experimental and simulation results. We also post the files needed to build and reproduce our experiment in a public repository.
Automated Layout Generation Methods for 2D Spatial Packing
Authors: Peddada Satya R. T. , Rodriguez Samanta B. , James Kai A. , Allison James T. 
Published: November 2020

Abstract
Development of a computationally-tractable design method for combined multi-physics optimization of packing and routing problems, at a relevant scale, within compact packaging volumes, will offer benefits across several engineering domains. But for performing multi-physics packing and routing optimization, the generation of spatially feasible initial layouts is essential. Three new and computationally efficient methods are demonstrated in this article to produce automatically interference-free 2D geometric layouts. First, a novel 2D force-directed layout method (FDLM) is proposed that implicitly ensures noninterference between components and/or the interconnect network by utilizing spring force theory without using explicit geometric constraints. Second, the A* algorithm, a well-established 2D shortest path algorithm (SPA), has been modified significantly to perform efficient routing of complex interconnect systems. Third, a new geometric topology (GT) enumeration algorithm is presented that produces all unique interconnect routing configurations for given multi-component system architecture. These layout generation methods are then compared with respect to average computational efficiencies and average success rates in attaining feasible layouts for a restricted class of topologies, including evaluation of how the methods scale to problems with an increased number of components. Limitations and future work items for each method are discussed. These methods are presented as an important step toward solution strategies that are compatible with the currently unmet challenges of real-world 2D and 3D combined packing and routing problems, including efficient navigation of the space of discrete options for interconnect geometric topology, as well as scaling to more complex problems.
A Narrow-Track Tilting Tricycle With Variable Stability That the Rider Can Control Manually
Authors: Pierson A. M. , Shortreed A. K. , Van Asten P. D. , Dressel A. E. 
Published: November 2020

Abstract
Many health, environmental, and quality-of-life benefits due to cycling have been identified, including exercise, zero-emissions, reduced pavement requirements compared to cars and busses, and nearly silent operation. A significant fraction of the population, however, is unable to join in this activity with traditional upright bicycles, including people with balance or joint limitations caused by injury, disease, or age.
One solution to these ergonomic difficulties is the recumbent bicycle, but many riders find them difficult to balance and steer because of several factors, including center of mass location and distribution. Another solution, the recumbent tricycle, must have a wide axle track and/or low center of mass for lateral stability when turning, which requires more pavement and creates more aerodynamic drag than the bicycle equivalent.
We present a solution that aims to combine the best attributes of these vehicles and eliminate the drawbacks: a tilting tricycle with variable stability that the rider can control manually. It balances and leans into corners like a bicycle when going fast, and it balances and stays upright like a tricycle when stopped or going slow to reduce the steering burden on the rider. Between these two extremes, the rider can finely adjust exactly how docile a bicycle it mimics.
Improving the Accuracy and Diversity of Feature Extraction From Online Reviews Using Keyword Embedding and Two Clustering Methods
Authors: Park Seyoung , Kim Harrison M. 
Published: November 2020

Abstract
In product design, it is essential to understand customers’ preferences for product features. Traditional methods including the survey and interview are time-consuming and costly. As an alternative, research on utilizing online data for user analysis has been actively conducted. Although various methods have been proposed in this domain, most of them focus on the main features or usages of the product. However, from the manufacturer’s perspective, sub-features are as crucial as main features or usages, because the preference for sub-features is necessary for component configuration in actual product development. As the first step to solve this problem, this paper proposes a methodology to extract and cluster sub-features by incorporating phrase embedding into the previous word embedding. Also, the presented methodology increases the accuracy and diversity of the clustering result by using X-means clustering as a noise filter and adopting spectral clustering.
Structural Design Synthesis Through a Sequential Decision Process
Authors: Ororbia Maximilian E. , Warn Gordon P. 
Published: November 2020

Abstract
This article illustrates that structural design synthesis can be achieved through a sequential decision process, whereby a sparsely connected seed configuration is sequentially altered through discrete actions to generate the best design solution, with respect to a specified objective and constraints. Specifically, the generative design synthesis is mathematically formulated as a finite Markov Decision Process. In this context, the states correspond to a specific structural configuration, the actions correspond to the available alterations that can be made to a given configuration, and the immediate rewards are constructed to be proportional to the improvement in the altered configuration’s performance. In the context of generative structural design synthesis, since the immediate rewards are not known at the onset of the process, reinforcement learning is employed to obtain an approximately optimal policy by which to alter the seed configuration to synthesize the best design solution. The approach is applied for the optimization of planar truss structures and its utility is investigated with three numerical examples, each with unique domains and constraints.
A Flexible Multi-Modal Multi-User Traffic Simulation for Studying Complex Road Design
Authors: Miller Jack , Kalivarapu Vijay , Holm Michael , Finseth Tor , Williams Jordan , Winer Eliot 
Published: November 2020

Abstract
While there are many factors that affect traffic accidents, safe road design plays a key role. It is critical to understand traffic flow and driver response to various scenarios. Furthermore, with the inclusion of new traffic trends such as bicycle friendly roads and autonomous vehicles, it is ever more important to study the complex relationships between traffic entities. However, controlled experiments can be difficult to implement in the real world. Traffic simulation has been researched for decades to understand the flow of traffic in a variety of environments and how users interact within it. However, these platforms are limited in simulation and authoring capabilities, do not allow for multiple human agents, or are not accessible by roadway designers. This research explores the technical development of a multi-user multi-modal traffic simulation platform that expands on the capabilities of traditional traffic simulators. Traffic simulation of virtual cars and pedestrian agents were generated through VISSIM and networked into a simulation platform. Multiple human agents can interface with the system through a physical car and bicycle rig featuring both a virtual reality head mounted display and a multi-monitor display. Furthermore, the multi-user nature of the platform allows for a variety of complex research applications including multi-user behavior. By utilizing low-cost commodity hardware and software, the accessibility of this platform is greatly increased. A testbed environment was created to evaluate the technical limitations of the platform and assess where further work is needed. Through this evaluation, the authoring process and networking capabilities were optimized. Additionally, the core functionality of the platform, including the various simulator modes and multi-user functionality, was found to be successful. Through this research, combining commodity hardware with traffic simulation will allow a larger number of researchers to better understand traffic environments and how humans may interact within them.
Design Exploration of a Tensegrity-Based Twisting Wing
Authors: Kim Pham Nguyen , Peraza Hernandez Edwin A. 
Published: November 2020

Abstract
In the modern days of air travel, more fuel-efficient aircraft is desired to meet the demanding requirements of the long-haul market. This paper explores the feasibility of using a tensegrity column topology as the means for the internal mechanism of a twisting wing, which can be potentially applied to more fuel-efficient aircraft. This new morphing wing design removes the need for separate control surfaces such as ailerons and allow the wing to have a continuous surface which in turn will reduce aerodynamic drag and improve the overall performance. Furthermore, the tensegrity-based design can potentially reduce the weight of the wing by replacing conventional metal-based support structures with a lightweight tensegrity design. A design-of-experiments (DOE) study on the influence of the topological parameters of the torsional tensegrity mechanism on the achievable twist angle, structural mass, and the stresses in the different wing components is performed. It is found that for a wing with a span and chord length of 2 m, the maximum achievable twist angle from root to tip per unit mass, without any component exceeding their maximum allowable stress value, is 0.0659°/kg. The tensegrity column mechanism for this design consists of four torsional cells (equivalent to five ribs) and ten sets of actuating wires along the circumference of the column sections.
Global Product Design Platforming: A Comparison of Two Methods to Find Equilibrium Solutions
Authors: Case Sarah S. , Whitefoot Kate S. 
Published: November 2020

Abstract
We examine optimal-profit product design platforming problems for products sold across multiple markets. Firms have an incentive to platform to take advantage of cost reductions that are possible with increased production quantity, such as learning-by-doing. However, platforming may decrease sales compared to if the designs were customized for each market. The problem can be represented as a Nash equilibrium between multiple competing firms, each with a nonconvex mixed-integer nonlinear programing (MINLP) problem for maximizing their individual profits. We derive the Karush-Kuhn-Tucker (KKT) conditions for the problem and compare results from two algorithmic approaches: (1) an iterative MINLP approach that uses the BARON algorithm to solve each firm’s design and platforming problem and iterates until convergence to an equilibrium, and (2) an approach that solves the KKT conditions directly holding platforming decisions fixed, and compares profits for these platforming decisions to find an equilibrium. Results are presented for a case study of plug-in hybrid electric vehicles (PHEVs) where firms choose whether or not to platform the battery pack across the U.S. and China, and set the optimal battery capacity. We vary the learning rate and the difference in consumer willingness to pay for all-electric range between China and the U.S. Both algorithms agree on the same equilibrium solution in 98.4% of the cases. Results show that the optimum for each firm is to platform when learning rates are low, or the difference between optimal battery capacity in each market is relatively small.
The Determination of a Cost Optimal Design for a Multiple Stage Continuous Electrodialysis Desalination Device for Use in Domestic Point of Use Water Purification
Authors: Varner Hannah M. , Shah Sahil R. , Winter Amos G. 
Published: November 2020

Abstract
There is a large and growing demand for point of use (POU) water desalination in emerging economies, such as India, where there is a large reliance on brackish (saline) groundwater reservoirs to meet drinking needs. In this work we propose a design for a two-stage continuous ED system that addresses the requirements of the Indian market while providing a higher water recovery than existing POU reverse osmosis products. Optimization was applied to minimize capital cost while ensuring 90% recovery of the feed, 90% salt reduction, and 15 L/hr of desalinated water production. The optimized design had a capital cost of approximately US$ 106, which is below the retail price of current RO purifiers on the market. Therefore, two-stage continuous ED shows promise for being a cost-competitive but water-efficient alternative to POU RO in India.
StressGAN: A Generative Deep Learning Model for 2D Stress Distribution Prediction
Authors: Jiang Haoliang , Nie Zhenguo , Yeo Roselyn , Farimani Amir Barati , Kara Levent Burak 
Published: November 2020

Abstract
Using deep learning to analyze mechanical stress distributions has been gaining interest with the demand for fast stress analysis methods. Deep learning approaches have achieved excellent outcomes when utilized to speed up stress computation and learn the physics without prior knowledge of underlying equations. However, most studies restrict the variation of geometry or boundary conditions, making these methods difficult to be generalized to unseen configurations. We propose a conditional generative adversarial network (cGAN) model for predicting 2D von Mises stress distributions in solid structures. The cGAN learns to generate stress distributions conditioned by geometries, load, and boundary conditions through a two-player minimax game between two neural networks with no prior knowledge. By evaluating the generative network on two stress distribution datasets under multiple metrics, we demonstrate that our model can predict more accurate high-resolution stress distributions than a baseline convolutional neural network model, given various and complex cases of geometry, load and boundary conditions.
Broadening Participation: Over Ten Years of Outreach Within the IDETC-DED Community
Authors: de Vries Charlotte , Fu Kate , Starkey Elizabeth , Toh Christine , Damen Nicole B. , Joshi Shraddha , Sylcott Brian , Jacobson Kathryn 
Published: November 2020

Abstract
A core ethos of the engineering discipline is to tackle large, complex problems of central importance to society utilizing a range of technical knowledge and skills. One major barrier to this goal is the lack of diversity in the discipline, leading to a shortage of the talent pool, reduced capacity for innovation, and it can negatively impact the educational experience of engineering students. To respond to this charge, the Broadening Participation Committee (BPart) of the American Society of Mechanical Engineering’s Design Engineering Division (ASME DED) has conducted a number of activities aimed at fostering a diverse professional community and addressing the needs of people typically under-represented within engineering. This includes professional development workshops, networking sessions, travel funds available for graduate students and postdoctoral scholars, and micro-grants available for parents with young children.
This paper discusses the activities provided by the BPart Committee since 2013, as well as the outcomes and additional initiatives that occurred as a result of the BPart Activities. Examples of such activities include seven professional development workshops, three workshop panels, and seven networking receptions. In the workshop participant feedback, we see some effect when there is a female presenter over a male presenter, but this effect appears to be limited. A discussion on future activities of BPart is presented in order to continue to grow and foster this community.
Swarms of Aquatic Unmanned Surface Vehicles (USV), a Review From Simulation to Field Implementation
Authors: Ansary Jamal , O’Donnell Jacob , Fyza Nashiyat , Trease Brian 
Published: November 2020

Abstract
Swarm robotic is a field of multi-robotics in which the robot’s behavior is inspired from nature. With rapid development in the field of the multi-robotics and the lack of efficacy in traditional centralized controls method, decentralized nature inspired swarm algorithms were introduced to control the swarm behavior. Unmanned surface vehicles (USVs) are marine crafts that they can operate autonomously. Due to their potential in operating in different areas, these vehicles have been used for variety of reason including patrolling, border protection, environmental monitoring and oil spill confrontation. This paper provides a review of the Swarm of USVs, their application, simulation environments and the algorithms that has been used in the past and current projects.
Constraint-Based Analysis of Parallel Kinematic Articulated Wrist Mechanisms
Authors: Damerla Revanth , Awtar Shorya 
Published: November 2020

Abstract
This paper presents a systematic constraint-based analysis of the motion attributes of six parallel kinematic articulated wrist mechanisms from the existing literature. These motion attributes include the number, nature (i.e. pure rotation, or translation, or a combination), and location of mechanism’s Degrees of Freedom (DoFs) in the nominal and displaced configurations, range of operation along these DoFs, load transmission capability along these DoFs, and load bearing capability along the constraint directions. This systematic analysis reveals performance tradeoffs between these motion attributes for a given mechanism, as well as design tradeoffs across these multiple mechanisms with respect to these motion attributes. This analysis should help inform the suitability of a given mechanism for specific applications.