bluuebunny/crossref_metadata_2025_split huggingface dataset:
Belt-Drive Mechanics: Energy Losses in the Presence of Detachment Waves
Authors: Wu Yingdan , Leamy Michael J. , Varenberg Michael 
Published: November 2019

Abstract
The dissipative rolling friction moment in a simple belt-drive system is estimated both experimentally and computationally while taking into account the detachment events at the belt-pulley interface. Shear traction is estimated based on measurements of the shear strain along the contact arc. It is shown that the dissipative moment can be approximated by taking the difference between the shear traction and the load carried by the belt. A model is developed for analyzing the contributions of different components to this dissipative moment by considering both the volumetric and surface hysteresis losses. The computed rolling friction moment is found to be in good agreement with that estimated based on the experiments. It is also found that while the shear- and stretching-induced energy losses contribute the most to the dissipation in the belt drive system, the losses associated with the Schallamach waves of detachment make up a considerable portion of the dissipation in the driver case.
Design of Gradient Nanotwinned Metal Materials Using Adaptive Gaussian Process Based Surrogate Models
Authors: Zhou Haofei , Chen Xin , Li Yumeng 
Published: November 2019

Abstract
Inspired by gradient structures in the nature, Gradient Nanostructured (GNS) metals have emerged as a new class of materials with tunable microstructures. GNS metals can exhibit unique combinations of material properties in terms of ultrahigh strength, good tensile ductility and enhanced strain hardening, superior fatigue and wear resistance. However, it is still challenging to fully understand the fundamental gradient structure-property relationship, which hinders the rational design of GNS metals with optimized target properties. In this paper, we developed an adaptive design framework based on simulation-based surrogate modeling to investigate how the grain size gradient and twin thickness gradient affect the strength of GNS metals. The Gaussian Process (GP) based surrogate modeling technique with adaptive sequential sampling is employed for the development of surrogate models for the gradient structure-property relationship. The proposed adaptive design integrates physics-based simulation, surrogate modeling, uncertainty quantification and optimization, which can efficiently explore the design space and identify the optimized design of GNS metals with maximum strength using limited sampling data generated from high fidelity but computational expensive physics-based simulations.
Improving Cuckoo Search Algorithm With Mittag-Leffler Distribution
Authors: Wei Jiamin , Chen YangQuan , Yu Yongguang , Chen Yuquan 
Published: November 2019

Abstract
Cuckoo search (CS), as one of the recent nature-inspired metaheuristic algorithms, has proved to be an efficient approach due to the combination of Lévy flights, local search capabilities and guaranteed global convergence. CS uses Lévy flights in global random walk to explore the search space. The Lévy step is taken from the Lévy distribution which is a heavy-tailed probability distribution. In this case, a fraction of large steps are generated, which plays an important role in enhancing search capability of CS. Besides, although many foragers and wandering animals have been shown to follow a Lévy distribution of steps, investigation into the impact of other different heavy-tailed probability distributions on CS is still insufficient up to now. Based on the above considerations, we are motivated to apply the well-known Mittag-Leffler distribution to the standard CS algorithm, and proposed an improved cuckoo search algorithm (CSML) in this paper, where a more efficient search is supposed to take place in the search space thanks to the long jumps. In order to verify the performance of CSML, experiments are carried out on a test suite of 20 benchmark functions. In terms of the observations and results analysis, CSML can be regarded as a new potentially promising algorithm for solving optimization problems.
Interpreting Measures of Rarity and Novelty: Investigating Correlations Between Relative Infrequency and Perceived Ratings
Authors: Weaver Morgan B. , Caldwell Benjamin W. , Sheafer Vicki 
Published: November 2019

Abstract
Central to the struggle in design ideation research is the quantification of abstract and qualitative measures. Among these measures, creativity, originality, and novelty are some of the most subjective and generally disagreed upon constructs. In recent years in the design community, novelty has primarily been measured with two distinct styles of metrics: relative infrequency and perceived ratings. Relative infrequency captures how rare an idea is within an idea set for an objective representation of novelty, while ratings quantify the perceptions of appropriate judges for an intuitive understanding of novelty. This paper investigates the convergent validity between these two styles through the implementation of three previously published methods. Moderate convergent validity is shown between a measure of relative infrequency and perceived ratings leading to clear and meaningful recommendations for metrics in future research. However, the degree of disagreement warrants differentiation between the two styles regarding terminology and analysis. This study will aid in the research and interpretation of future studies of creativity in ideation.
Comparing Multifidelity Model Management Strategies for Multidisciplinary Design Optimization
Authors: Chell Brian , Hoffenson Steven , Blackburn Mark R. 
Published: November 2019

Abstract
Multifidelity optimization leverages the fast run times of low-fidelity models with the accuracy of high-fidelity models, in order to conserve computing resources while still reaching optimal solutions. This work focuses on the multidisciplinary multifidelity optimization of an unmanned aerial system model with finite element analysis and computational fluid dynamics simulations in-the-loop. A two-step process is used where the lower-fidelity models are optimized, and then the optimizer is used as a starting point for the higher-fidelity models. By starting the high-fidelity optimization routine at a nearly optimal section of the design space, the computing resources required for optimization are expected to decrease when using gradient-based algorithms. Results show that, at least in some cases, the multifidelity workflows save time over optimizing the original high fidelity model alone. However, the model management strategy did not find statistically significant differences between the differing optimization approaches when used on this test problem.
Evaluating the Potential of Design for Additive Manufacturing Heuristic Cards to Stimulate Novel Product Redesigns
Authors: Blösch-Paidosh Alexandra , Ahmed-Kristensen Saeema , Shea Kristina 
Published: November 2019

Abstract
Additive manufacturing (AM) affords those who wield it correctly the benefits of shape, material, hierarchical, and functional complexity. However, many engineers and designers lack the training and experience necessary to take full advantage of these benefits. They require training, tools, and methods to assist them in gaining the enhanced design freedom made possible by additive manufacturing. This work, which is an extension of the authors’ previous work, explores if design heuristics for AM, presented in a card-based format, are an effective mechanism for helping designers achieve the design freedoms enabled by AM. The effectiveness of these design heuristic cards is demonstrated in an experiment with 27 product design students, by showing that there is an increase in the number of unique capabilities of AM being utilized, an increase in the AM novelty, and an increase in the AM flexibility of the generated concepts, when given access to the cards. Additionally, similar to the previous work, an increase in the number of interpreted heuristics and AM modifications present in the participants’ designs when they are provided with the heuristic cards is shown. Comparisons are also made between 8-heuristic and 29-heuristic experiments, but no conclusive statements regarding these comparisons can be drawn. Further user studies are planned to confirm the efficacy of this format at enhancing the design freedoms achieved in group and team design scenarios.
Quasi-Static Curve Negotiation Analysis of Railway Vehicle Considering Nonlinear Air Suspension LV and DPV Flow Characteristics
Authors: Tanaka Takayuki , Sugiyama Hiroyuki 
Published: November 2019

Abstract
Accurate prediction of vehicle curve negotiation performance is critically important for evaluation of railway vehicle safety. Although multibody dynamics vehicle simulation has been widely utilized for the vehicle performance evaluation, nonlinearities associated with the air suspension behavior are vastly simplified and the air mass flows of the leveling valve (LV) and differential pressure valve (DPV) are neglected in many cases. It is, however, known that changes in the air spring pressure caused by the LV and DPV make a non-negligible impact on the vertical wheel load variation and the derailment safety in small radius curved tracks. Therefore, this paper presents a numerical procedure for the analysis of the coupled vehicle and air suspension system behavior, considering nonlinearities associated with LV and DPV flow characteristics. To enable quick and accurate prediction of the history-dependent LV-induced wheel load unbalance and its impact on the derailment safety, quasi-static vehicle motion solvers for the fully coupled vehicle and air spring system flow equations are developed. Several numerical examples are presented to demonstrate the simulation capabilities developed in this study and numerical results are validated against the test data.
Modeling Nonlinear Oscillators via Variable-Order Fractional Operators
Authors: Patnaik Sansit , Semperlotti Fabio 
Published: November 2019

Abstract
Fractional derivatives and integrals are intrinsically multiscale operators that can act on both space and time dependent variables. Contrarily to their integer-order counterpart, fractional operators can have either fixed or variable order (VO) where, in the latter case, the order can also be function of either independent or state variables. When using VO differential governing equations to describe the response of dynamical systems, the order can evolve as a function of the response itself therefore allowing a natural and seamless transition between largely dissimilar dynamics (e.g. linear, nonlinear, and even contact problems). Such an intriguing characteristic allows defining governing equations for dynamical systems that are evolutionary in nature. In this study, we present the possible application of VO operators to a class of nonlinear lumped parameter models that has great practical relevance in mechanics and dynamics. Specific examples include hysteresis and contact problems for discrete oscillators. Within this context, we present a methodology to define VO operators capable of capturing such complex physical phenomena. Despite using simplified lumped parameters nonlinear models to present the application of VO operators to mechanics and dynamics, we provide a more qualitative discussion of the possible applications of this mathematical tool in the broader context of continuous multiscale systems.
On-Line Programming of Robot Skills
Authors: Heikkilä Tapio , Saukkoriipi Janne , Ahola Jari M. , Seppälä Tuomas 
Published: November 2019

Abstract
Robot skills provide a way to model and reuse sensor and robot technologies in effective ways. Skills can integrate and synchronize robot actions and sensor data in a consistent way and provide a framework for configurable robot systems, enabling quick setups of applications. Skills and skill modeling can be used not only for representing the composition of sensor based robot tasks, but also for programming on-line such tasks. In this paper we will introduce a skill based approach for representing on-line programming of skill based tasks. We will also give a practical example for modelling and implementing on-line programming of a handling skill relying on use of object localization sensors.
Collaborative Mind-Mapping: A Study of Patterns, Strategies, and Evolution of Maps Created by Peer-Pairs
Authors: Chen Ting-Ju , Mohanty Ronak R. , Hoffmann Rodriguez Miguel A. , Krishnamurthy Vinayak R. 
Published: November 2019

Abstract
We present a study on collaborative mind-mapping to understand how peers collaborate in pairs to create mind-maps, how the maps evolve over time, and how collaboration changes between the peer-pair across multiple maps. Mind-mapping is an important tool that is studied and taught in design practice and research respectively. While widely used as a brainstorming technique, the collaborative aspects of mind-mapping are little understood in comparison to other ideation methods such as concept sketching etc. In addition to presenting creativity ratings on the outcome (i.e. the mind-map), we extensively report on the patterns of collaborative exploration, strategies that emerge from the collaborators, inhibition, and the overall process of map creation. We discuss the implications of these observations on the development of computer-support for mind-mapping.
Feasibility Study of an Aerial Lifting Device Using Aerodynamic Drag for Ascent
Authors: Lin Xuan , Fernandez Gabriel , Ghassemi Sepehr , Hong Dennis W. 
Published: November 2019

Abstract
Flying typically involves thrust or buoyancy in order to climb in altitude while trying to minimize drag. These setups can result in large, energy-exhaustive mechanisms. This paper presents a novel alternative to the traditional approaches of flying by utilizing aerodynamic drag. Drag can be used as an opposing force needed to lift a load off of the ground. The concept is verified through a series of experiments in which a balloon is used to lift a parachute to a desired height, and then an actuator with a load on the ground retracts a rope connected to the parachute. Aerodynamic drag is translated into a lifting force. This cost-effective, energy efficient, and modular method can increase the mobility of robots, delivery systems etc.
A Coarea Formulation for Grid-Based Evaluation of Volume Integrals
Authors: Uchytil Christopher , Storti Duane 
Published: November 2019

Abstract
We present a new method for computing volume integrals based on data sampled on a regular cartesian grid. We treat the case where the domain is defined implicitly by a trivariate inequality f(x,y,z) &lt; 0, and the input data includes sampled values of the defining function f and the integrand. The method employs Federer’s coarea formula to convert the volume integral to an integral over level set values where the integrand is an integral over the level sets. Application of a standard quadrature method produces an approximation of the integral over the continuous range of f in the form of a sum of integrals on level sets corresponding to a discrete set of values of f. The integrals on the discrete collection of level sets are evaluated using the grid-based approach presented by Yurtoglu et al. [1].
We describe how the implementation relates to the implementation described in [1], and we present results for sample problems with known exact results to support a discussion of accuracy and convergence along with a comparison with a traditional Monte Carlo method.
Dimensions of Product Similarity in Design by Analogy: An Exploratory Study
Authors: Gill Amaninder Singh , Tsoka Arnold N. , Sen Chiradeep 
Published: November 2019

Abstract
This paper explores dimensions of similarity in analogy-based design through a user study. Analogy is used in design to help designers use knowledge that exists between and across domains in order to solve design problems at hand. The five dimensions of similarity that were explored in this paper are: function, form, energy flow, material flow, and motion. Fifty student volunteers, majoring in Mechanical Engineering, were given electro-mechanical products that are to be designed, and were asked to select, from a set of options, other products that they considered could be useful references for their task, if those options were offered by a hypothetical design-by-analogy web-service. In their response, they were also asked to identify the dimensions along which they found their preferred reference products to be similar to the design product. It was observed that participants selected products based on similarity along multiple dimensions of analogy. Function-based similarity was the most dominant trait, followed by energy, motion, material, and form. The results from this study will help to design more elaborate studies that will inform the design of computational support algorithms that will aid designers by recommending analogous solutions to help with solution search and ideation.
Multi-Scale Design of Meta-Materials With Offset Periodicity
Authors: Sadiwala Rushabh , Fadel Georges 
Published: November 2019

Abstract
Meta-materials are a class of artificial materials with a wide range of bulk properties that are different from the base material they are made of. The term meta-material in the context of this research refers to a continuous, heterogeneous structure with prescribed elastic properties. Such meta-materials are designed using Topology Optimization (TO). Tools like SIMP interpolation, mesh filtering and continuation methods are used to address the numerical issues with Topology Optimization.
In a previous research [1], by offsetting meta-material layers by a half-width of the Unit Cell, an auxetic honeycomb-like geometry was obtained. This was the first time such a shape was observed as the result of Topology Optimization targeting the effective shear modulus using square Unit Cells. This was obtained while designing the shear beam of a non-pneumatic wheel.
This research studies the design of meta-materials using offsets other than zero or half-widths. The same problem [1] was solved for different values of offset, and the obtained geometries and volume fractions are studied. It is concluded that it may be beneficial for designers to consider offsetting meta-material layers with offsets other than half-width, to design novel, potentially better performing structures.
The Technology/Tactics (TEC/TAC) Plot: Explicit Representation of User Actions in the Product Design Space
Authors: Stapleton Tyler , Owens Trent , Mattson Christopher , Sorensen Carl , Anderson Michael 
Published: November 2019

Abstract
The initial phases of the design process — including interactions with stakeholders, ideation of concept candidates, and the selection of the best candidates — have a large impact on the success of a project as a whole. They also tend to be the most unstructured portion of the project, and are often marginalized by teams who assume they already understand stakeholder needs and the best solution paths to pursue. Design researchers have developed methods shown to increase the creativity and divergent thinking of the design team during these initial phases of design. Nevertheless, these methods often rely on only a vague or amorphous representation of the design space (the set of all possible concepts the design team could feasibly select to meet the objective of the project). In this paper, we introduce a particular design-space structure that can help teams ideate and evaluate their ideation, thus improving the early phases of the design process. The design space presented here is a vector space with a basis of technology (the physical product people will use) and tactics (the procedure for using the product). Also presented are definitions, principles, and sub-theories that facilitate the creation and use of technology-tactics plots to represent the design space. Considering the design space in this structured way, the design team can gain valuable insights that improve the effectiveness of the initial stages of design, and may yield additional benefits to the design process as a whole, if further developed.
A Review of Machine Learning Applications in Additive Manufacturing
Authors: Razvi Sayyeda Saadia , Feng Shaw , Narayanan Anantha , Lee Yung-Tsun Tina , Witherell Paul 
Published: November 2019

Abstract
Variability in product quality continues to pose a major barrier to the widespread application of additive manufacturing (AM) processes in production environment. Towards addressing this barrier, monitoring AM processes and measuring AM materials and parts has become increasingly commonplace, and increasingly precise, making a new wave of AM-related data available. This newfound data provides a valuable resource for gaining new insight to AM processes and decision making. Machine Learning (ML) provides an avenue to gain this insight by 1) learning fundamental knowledge about AM processes and 2) identifying predictive and actionable recommendations to optimize part quality and process design. This report presents a literature review of ML applications in AM. The review identifies areas in the AM lifecycle, including design, process plan, build, post process, and test and validation, that have been researched using ML. Furthermore, this report discusses the benefits of ML for AM, as well as existing hurdles currently limiting applications.
Extending Educational Robot Sensing Capabilities Through Equipping an External Microcontroller
Authors: Qian Binsen , Cheng Harry H. 
Published: November 2019

Abstract
The popularity of the educational robot in K-12 classroom has dramatically increased in the past decades to engage students studying not only Science, Technology, Engineering and Mathematics (STEM), but also 21st-century skills. Most educational robots tend to be as simple as possible such that the lower grades can benefit from the robotics technologies safely. However, such design consideration makes most educational robots with none or minimal sensing capabilities. However, it is very important for senior students to learn more advanced robotics concepts and applications. This paper presents a concept of extending educational robots’ sensing capabilities through quipping an external microcontroller. The paper also demonstrates how the framework can be easily used in sensor-based applications through a line-following example.
Thorough Verification and Validation of CFD Prediction of FPSO Current Load for Confident Applications
Authors: Xu Wei , Huang Zhenjia (Jerry) , Kim Hyunjoe 
Published: November 2019

Abstract
In this paper, a thorough verification of FPSO current load modeling and simulation using CFD was carried out and a modeling practice developed in a joint development project [1] was adopted. The towing test data obtained with thorough quality assurance process were used as benchmark data in the verification work. To have high confidence in the CFD modeling and simulations, both steady simulations with RANS model and unsteady simulations with IDDES model were carried out. For the steady simulations, sensitivity checks were carried out for the domain size, mesh refinement, turbulence models, boundary conditions and Reynolds effect. For unsteady simulations, the wake zone mesh refinement, time step size, number of inner iterations and different RANS model for boundary layers were considered during the sensitivity verification stage. It was found in this study that the transverse load (Fy) and yaw moment (Mz) of the FPSO can be predicted fairly well using RANS model, while the DES model needs to be adopted in order to accurately predict the longitudinal forces (Fx) at certain range of current directions. The wake grid for the DES needs to be fine enough in order to capture the details of vortices and the running time trace needs to be long enough to reduce the sensitivity on the mean current forces.