bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modal Analysis to Interpret Localization Phenomena of Harmonic Oscillations in Nonlinear Oscillator Arrays
Authors: Harata Yuji , Ikeda Takashi 
Published: November 2019

Abstract
This paper investigates localization phenomena in a nonlinear array with N Duffing oscillators connected by weak, linear springs when the array is subjected to harmonic excitation. In the theoretical analysis, the equations of motion are derived for: (1) the physical coordinate system, and (2) modal coordinate system. The modal equations of motion form an autoparametric system, i.e., the excitation acts directly on the first mode of vibration, and the other modes are indirectly excited because they are nonlinearly coupled with the first mode. Van der Pol’s method is employed to obtain the solutions of the harmonic oscillations, and then the expressions of the frequency response curves are given. In the numerical calculations, the frequency response curves of the amplitudes and phase angles in the cases of N = 2 and 3 are presented. The frequency response curves, obtained in the modal coordinate system, demonstrate that localization phenomena occur in the physical coordinate system when multiple vibrational modes simultaneously appear. When imperfections exist in the N Duffing oscillators, the modal equations of motion do not form an autoparametric system because the external excitation directly acts on all modes. Instead, internal resonances may occur in such systems.
Assessment of Shoulder and Chest Protection of Wearable Motorcycle Airbags
Authors: Girardi Davide , Marconi Edoardo , Massaro Matteo 
Published: November 2019

Abstract
The application of numerical simulation to wearable airbags for motorcyclists is relatively recent and only few works about this topic can be found in the literature. This research uses multi-physics simulation to analyse a new wearable airbag geometry, primarily designed to protect the shoulders of motorcycle riders, with the aim of assessing the effect of inflation pressure on the protection performance. The finite element model of the airbag employs a simple linear-isotropic material model, calibrated though the comparison between experimental and numerical outcomes of a drop test, together with the analysis of the airbag inflated geometry. The finite element model of the wearable device is then fitted to a dummy model and a human body model, in order to be used in a parametric analysis. Two set-ups are considered. The first is a thorax impact test, used to assess the effect of inflation pressure on chest protection. A modification to the bag geometry is also proposed and tested on this configuration. The second set-up is a shoulder impact test, used to assess the effect of inflation pressure on shoulder protection. In both tests an optimal inflation pressure can be found, but the maximization of shoulder protection proved more critical and should therefore drive the choice of this parameter.
Hypocycloid Gear Mechanism Versus Slider-Crank Mechanism in Engines
Authors: ElBahloul Mostafa A. , Aziz ELsayed S. , Chassapis Constantin 
Published: November 2019

Abstract
This effort investigates the feasibility of using the Hypocycloid Gear Mechanism (HGM) as an alternative to the conventional slider-crank mechanism for Internal Combustion Engine (ICE) applications. Engines incorporating the conventional slider-crank mechanism are subjected to high frictional power losses mainly due to the piston-rod assembly and the associated complex motion of the connecting rod. The unique HGM engine provides the means for the piston-rod assembly to reciprocate in a straight-line motion along the cylinder axis, thus eliminating the piston side-thrusting into the cylinder wall. To analyze the performance advantages of the HGM engine, a Matlab/Simulink model is developed for the simulation of a single-cylinder HGM engine from the throttle to the crankshaft output. The model integrates several sub-models for combustion, gas flow, heat transfer, and friction power loss of the internal gear train meshes, rolling bearings, and sliding bearings. The design of the planetary crank gearing system to satisfy the design specifications of ICE, has been derived using standard design procedures provided by AGMA. Calculated efficiency and power diagrams are plotted and compared with the performance of conventional engines in the literature. The results show that the HGM can satisfy modern ICE design requirements, achieve better engine performance characteristics, and minimize the frictional power losses. The HGM engine achieved lower frictional power losses by an average 33% of the conventional engine losses while its mechanical efficiency is enhanced by up to +24% with respect to the conventional engine.
Level Set Topology Optimization for Design Dependent Hydrostatic Loading Using the Reproducing Kernel Particle Method
Authors: Neofytou Andreas , Picelli Renato , Chen Jiun-Shyan , Kim Hyunsun Alicia 
Published: November 2019

Abstract
Level set topology optimization for the design of structures subjected to design dependent hydrostatic loads is considered in this paper. Problems involving design-dependent loads remain a challenge in the field of topology optimization. In this class of problems, the applied loads depend on the structure itself. The direction, location and magnitude of the loads may change as the shape of the structure changes throughout optimization. The main challenge lies in determining the surface on which the load will act.
In this work, the reproducing kernel particle method (RKPM) is used in combination with the level set method to handle the dependence of loading by moving the particles on the structural boundary throughout the optimization process. This allows for the hydrostatic pressure loads to be applied directly on the evolving boundary. One-way fluid-structure coupling is considered here. A hydrostatic pressure field governed by Laplace’s equation is employed to compute the pressure acting on linear elastic structures. The objective in this optimization problem is to minimize compliance of these structures. Numerical results show good agreement with those in the literature.
Novel State Estimation Method of Surface Chatter Pattern via Image Processing After End Milling
Authors: Ozaki Nobutoshi , Matsui Shota , Hirogaki Toshiki , Aoyama Eiichi 
Published: November 2019

Abstract
We studied a new analytical method for determining self-excited chatter vibration at an end mill processing site. When chatter vibration occurs, cutting marks with periodic features called “chatter marks” are generated on the processed surface. We focused on the relationship between the vibration generated during cutting and the roughness of the processed surface. We developed a method to analyze such vibrations, based on the roughness of the finished surface. Instead of using a roughness meter and laser-measuring instrument, which are often used for measuring the contours of a processed surface, we presumed the roughness of the processed surface from image data obtained using a digital camera. As a comparative experiment to verify the proposed method, side cutting with an end mill was performed. Chatter vibrations occurring during the cutting were measured using a displacement sensor and microphone, and compared with the vibration of the tool edge as determined from the processed surface. The chatter frequency read from the processed surface was close to that obtained from the displacement sensor and microphone. Thus, the proposed method can be used to analyze the information of chatter vibration inexpensively and easily. It can serve as a substitute for displacement and acceleration sensors.
Engineering Design Concept Generation: The Effect of Concept Combination and Classification
Authors: Deo Saurabh , Hölttä-Otto Katja , Bhalerao Yogesh , Malge Abhijeet 
Published: November 2019

Abstract
World economic forum reported that creativity is one of the most sought after skills by employers globally. Preliminary research lead to multiple initiatives on enhancing creativity and innovation. To contribute in this field, we investigated the effect of two interventions on the creativity of undergraduate engineering students, particularly on engineering design concept generation. The primary focus of this investigation was on assessing the effect of two interventions, combining and classifying concepts, on the originality and quantity of the concepts produced.
In this research, we used the Decision Tree for Originality Assessment in Design (DTOAD) as a measure of concept originality. Statistical analysis showed that both the combine and the classify interventions lead to concept generation with higher originality. We also found that students produced higher number of the radically different concept, i.e. concepts with originality score 7.5 and above, however this effect was observed in all the test groups.
These interventions made improvements and thus can be encouraged as a part of an ideation or an engineering problem solving task in the undergraduate engineering education to help the students develop creative skills.
Machine Learning-Augmented Stochastic Search for the Automated Synthesis and Optimization of Cooling Channels
Authors: Schwarz Jonas , Shea Kristina 
Published: November 2019

Abstract
Stochastic search methods are widely used when it comes to design synthesis and optimization of response-based objective functions. In engineering applications, the objective function is typically expensive to evaluate, and stochastic search methods lack efficiency, resulting in the necessity of extensive design evaluations. In order to improve stochastic search methods, we propose a Machine Learning (ML)-based augmentation, consisting of three modules: a design archiver, a data modeler, and a modification advisor. These three modules cooperatively work together to store the gathered data during the design process, build up a representative model of the observations made, and advise the search for further sequences of modifications to apply. The proposed method is benchmarked against its unaugmented parent method in placing cooling channels in a die casting mold. The results show that the efficiency of the method is significantly improved when augmented with ML, i.e. similar results are obtained with 25–50% fewer evaluations. Additionally, the robustness and reliability of the optimization process is improved with a standard deviation of the obtained results that is 60–85% smaller. It is shown that the search strategy can be significantly improved with the proposed method, resulting in shorter running times and more reliable convergence behavior.
Additive Manufacturing of a Bistable Mechanism Using Fused Deposition Modeling: Experimental and Theoretical Characterization
Authors: Ben Salem Mouna , Aiche Guillaume , Haddab Yassine , Rubbert Lennart , Renaud Pierre 
Published: November 2019

Abstract
Bistable mechanisms can be used for performing specific functions such as locking or negative stiffness generation. These compliant structures are then of interest at different scales, with different corresponding manufacturing technologies. One of them is additive manufacturing, which is interesting for the integration of such structures. Although this technology has undergone a revolution with the development of high-accuracy machines, the manufacturing of small-sized compliant structures is still quite a challenge especially for bistable mechanisms, which was not yet finely characterized. This is the focus of this paper, with presentation of an experimental and analytical confrontation in the case of Fused Deposition Modeling (FDM).
Internal Resonance of Plane Waves in Nonlinear Lattices
Authors: Fronk Matthew D. , Leamy Michael J. 
Published: November 2019

Abstract
Recent studies have employed perturbation techniques to derive amplitude-dependent band structures in nonlinear periodic materials. The associated applications include amplitude-dependent filters, waveguides, and diodes. However, for a range of frequencies and wavenumbers, perturbation-based dispersion corrections for a single wave break-down due to internal resonance between the primary wave and its nonlinearity-induced higher-harmonics. This work presents a perturbation analysis of one-dimensional plane waves in lattices with internal resonances. The exchange of energy between propagating modes within the same branch of the lattice’s band structure is considered, and the stability of the energy exchange is assessed through a local analysis. Direct numerical integration of the lattice equations of motion validates the analytical expressions for energy exchange. These findings can be used to resolve discontinuities in band diagrams that do not account for internal resonances and may inspire new technology that enables long-range coherent signal transmission in nonlinear media.
Molding Parameters Design for Meso and Micro Components Using Polylactic Acid (PLA)
Authors: Surace Rossella , Bellantone Vincenzo , Fassi Irene 
Published: November 2019

Abstract
Currently, the increasing interest in the study of Polylactic acid (PLA) polymer has been motivated by the potential of such material for consumer and biomedical applications. PLA is a thermoplastic polymer, biodegradable, compostable and deriving from renewable natural sources as starch and sugar. Injection molding is the most widely used process for thermoplastic micro-featured parts for to its capacity to manufacture low-cost and high repeatable micro-parts. The use of PLA for injection molded micro components is still not well stabilized due to the slow crystallization kinetics, not suitable for high performance applications. In this work, preliminary experimental studies have been performed to analyze the filling ability of PLA in a meso and a micro parts using different molding conditions to evaluate process parameters influence. The experiments results are discussed in the paper and show that injection molding proved to be suitable for meso-micro PLA product manufacturing.
Analysis of a Multibody Elastodynamic Model for Closed-Loop Kinematic Mechanisms
Authors: Carbonari Luca , Brillarelli Stefano , Palpacelli Matteo-Claudio , Callegari Massimo 
Published: November 2019

Abstract
This paper is focused on the analysis of an elastodynamic model, typically referred to single-link flexible manipulators, when it is extended to multibody systems with closed-loop kinematic chains subject to vibrations, caused by the slenderness of their mechanical structure together with severe dynamic working conditions. The work is aimed at analyzing the relationship between the degree of accuracy of the proposed elastodynamic model, compared with more complete but time consuming models developed with software, and the time required for its computation, with the final aim of guiding its implementation in real-time control algorithms. Notwithstanding the study is proposed for parallel kinematic machines, the results are also valid for serial kinematic chains.
An Optimal Quantity of Scheduling Model for Mass Customization-Based Additive Manufacturing
Authors: Oh Yosep , Behdad Sara 
Published: November 2019

Abstract
The purpose of this study is to optimize production planning decisions in additive manufacturing for mass customization (AMMC) systems in which customer demands are highly variable. The main research question is to find the optimal quantity of products for scheduling, the economic scheduling quantity (ESQ). If the scheduling quantity is too large, the time to collect customer orders increases and a penalty cost occurs due to the delay in responding to consumer demands. On the other hand, if the scheduling quantity is too small, the number of parts per jobs decreases and parts are not efficiently packed within a workspace and consequently the build process cost increases. An experiment is provided for the case of stereolithography (SLA) and 2D packing to demonstrate how the build time per part increases as the scheduling quantity decreases. In addition, a mathematical framework based on ESQ is provided to evaluate the production capacity in satisfying the market demand.
Combined Lane Keeping and Longitudinal Speed Control for Autonomous Driving
Authors: Feraco Stefano , Bonfitto Angelo , Amati Nicola , Tonoli Andrea 
Published: November 2019

Abstract
This paper presents a technique for the lane keeping and the longitudinal speed control of an autonomous vehicle with the combination of an MPC and a PID control. The goal of the proposed control method is to minimize the lateral deviation and relative yaw angle with respect to the planned trajectory, while driving the vehicle at the highest acceptable longitudinal speed. The reference profile of the longitudinal speed is computed considering both the lateral and longitudinal dynamic of the vehicle. The vehicle is represented by means of a linear 3-DoF bicycle model. The control algorithm takes the road lane boundaries as the only external input. The proposed strategy is validated in simulation on three distinct driving scenarios.
Collaborating With Style: Using an Agent-Based Model to Simulate Cognitive Style Diversity in Problem Solving Teams
Authors: Lapp Samuel , Jablokow Kathryn , McComb Christopher 
Published: November 2019

Abstract
Collaborative problem solving can be successful or counterproductive. The performance of collaborative teams depends not only on team members’ abilities, but also on their cognitive styles. Cognitive style measures differences in problem-solving behavior: how people generate solutions, manage structure, and interact. While teamwork and problem solving have been studied separately, their interactions are less understood. This paper introduces the KAI Agent-Based Organizational Optimization Model (KABOOM), the first model to simulate cognitive style in collaborative problem solving. KABOOM simulates the performance of teams of agents with heterogeneous cognitive styles on two contextualized design problems. Results demonstrate that, depending on the problem, certain cognitive styles may be more effective than others. Also, intentionally aligning agents’ cognitive styles with their roles can improve team performance. These experiments demonstrate that KABOOM is a useful tool for studying the effects of cognitive style on collaborative problem solving.
Pilot-Induced-Oscillations Issue in Driverless Car Age
Authors: Yuan Jie , Wu Zhenlong , Fei Shumin , Chen YangQuan 
Published: November 2019

Abstract
As driverless vehicles becoming more and more popular due to the development of artificial intelligence, human beings will gradually get free from the vehicle driving. However, unexpected oscillations may happen due to the unfamiliarity of the vehicle configuration when humans want to drive themselves, even the vehicle itself is stable. These driver-induced-oscillations are similar with the pilot-induced-oscillations (PIO) which is generally related with actuator rate limit in the aircraft systems. Thus, this study attempts to review the PIO issue briefly and provide a guidance to solve the potential human-in-the-loop unmanned driving challenge associated with rate limit effect.
Optimization Model for Owner-Based Microgrids Using LSTM Predicted Demand for Rural Development
Authors: Amaria Anosh P. , Nguyen Ryan , Davison Joshua A. , Chowdhury Souma , Hall John F. 
Published: November 2019

Abstract
Over the past several years, microgrids have been setup in remote villages in developing countries such as India, Kenya and China to boost the standards of living of the less privileged citizens, mostly by private companies. However, these systems succumb to increase in demand and maintenance issues over time. A method for scaling the capacity of solar powered microgrids is presented in this paper. The scaling is based on both the needs of the owner and those of the consumers. Data acquired from rural villages characterizes the electrical use with respect to time. Further, it employees a Long-Short Term Memory (LSTM) deep learning model that can help the owner predict future demand trends. This is followed by a model to determine the optimum increase in capacity required to meet the predicted demand. The model is based on empowering the owner to make informed decisions and the equity of energy distribution is the key motivation for this paper. The models are applied to a village in Eastern India to test its applicability. Acknowledging the highly varying nature of demand for electricity and its applications, we propose a rule-based adaptive power management strategy which can be tailored specifically in accordance to the preference of the communities. This will ensure a fair distribution of power for everyone using the system, thereby making it applicable anywhere in the world. We propose to incorporate social and demographic conditions of the user in the optimization to ensure that the profit of the owner does not outweigh the needs of the users.
Towards Thermal Simulation of Powder Bed Fusion on Path Level
Authors: Zhang Yaqi , Shapiro Vadim , Witherell Paul 
Published: November 2019

Abstract
Powder bed fusion (PBF) is a widely used additive manufacturing (AM) technology to produce metallic parts. Understanding the relationships between process parameter settings and the quality of finished parts remains a critical research question. Developing this understating involves an intermediate step: Process parameters, such as laser power and scan speed, influence the ongoing process characteristics, which then affect the final quality of the finished parts. Conventional approaches to addressing those challenges such as powder-based simulations (e.g., discrete element method (DEM)) and voxel-based simulations (e.g., finite element method (FEM)) can provide valuable insight into process physics. Those types of simulations, however, are not well-suited to handle realistic manufacturing plans due to their high computational complexity.
Thermal simulations of the PBF process have the potential to implement that intermediate step. Developing accurate thermal simulations, however, is difficult due to the physical and geometric complexities of the manufacturing process. We propose a new, meso-scale, thermal-simulation, which is built on the path-level interactions described by a typical process plan. Since our model is rooted in manufactured geometry, it has the ability to produce scalable, thermal simulations for evaluating realistic process plans. The proof-of-concept simulation result is validated against experimental results in the literature and experimental results from National Institute of Standards and Technology (NIST).
In our model, the laser-scan path is discretized into elements, and each element represents the newly melted material. An element-growth mechanism is introduced to simulate the evolution of the melt pool and its thermal characteristics during the manufacturing process. The proposed simulation reduces computational demands by attempting to capture the most important thermal effects developed during the manufacturing process. Those effects include laser-energy absorption, thermal interaction between adjacent elements and elements within the underneath substrate, thermal convection and radiation, and powder melting.