bluuebunny/crossref_metadata_2025_split huggingface dataset:
Teaching Technical Design Specifications in Product Redesign Processes Using the FBS Model
Authors: Montoya Ivan D. , Rendon-Velez Elizabeth , Gallego-Sanchez Juan A. 
Published: November 2019

Abstract
Establishment of technical design specifications for the re-design of technical systems, which are not derived from customers needs, relies heavily on designers intuition and experience. The very few methods proposed in the literature for the establishment of such technical design specifications hinders the learning process in conceptual design subjects. The objective of this article is to propose a structured method for identification of technical design specifications based on the function-behavior-state (FBS) model applied on redesign tasks. The method is being taught to students on the course of methodical design in order to develop their abilities on the identification of technical specifications without relying on previous knowledge on the system and relying more on detailed observation. This method is based on the observation and identification of the different states taken by the attributes of the entities conforming the system (i.e., flows-function carriers-environment). A small scale preliminary study was conducted in order to validate the initial performance of the proposed method. Eight groups made up of undergraduate mechanical engineering students with basic knowledge in conceptual design were instructed to identify technical design specifications. The redesign task was to create an automated solution for replacing the manual production process at small food manufacturing companies. Four groups of students had to establish the specifications using their experience while the other four groups had to use the proposed method. Initial results showed for the proposed method a 36% increase in the number of identified specifications.
Exploiting Nonlinear Dynamics and Energy Localization to Enhance the Performances of an Electromagnetic Vibration Energy Harvester
Authors: Aouali Kaouthar , Kacem Najib , Bouhaddi Noureddine , Mrabet Elyes , Haddar Mohamed 
Published: November 2019

Abstract
A multimodal electromagnetic vibration energy harvester based on a nonlinear quasi-periodic system is proposed. The multimodal approach and the nonlinearity are implemented in order to improve the output performances of the studied device. The present study investigates a periodic system composed of two weakly coupled magnets and mechanically guided by two elastic beams. The quasi-periodic system is obtained by varying the mass of one of the moving magnets which leads to the vibration energy localization in regions close to the imperfections introduced. This phenomenon is exploited to maximize the harvested energy. The mechanical nonlinearity is introduced by considering large displacements of the beams which is also investigated to maximize the harvested energy and to enlarge the bandwidth of the device. The quasi-periodic system is modeled by two coupled forced Duffing equations, which are solved using finite difference method combined with arc-length continuation method. The obtained results of the mass mistuning are analyzed and discussed in depth. It is shown that the introduction of the nonlinearity and the functionalization of the energy localization phenomenon lead to the enlargement of the bandwidth and the increase of the vibration amplitudes.
Multi-Pulse Chaotic Dynamics of Eccentric Rotating Composite Laminated Circular Cylindrical Shell by Using the Extended Melnikov Method
Authors: Zheng Yan , Zhang Wei , Liu Tao 
Published: November 2019

Abstract
The researches of global bifurcations and chaotic dynamics for high-dimensional nonlinear systems are extremely challenging. In this paper, we study the multi-pulse orbits and chaotic dynamics of an eccentric rotating composite laminated circular cylindrical shell. The four-dimensional averaged equations are obtained by directly using the multiple scales method under the case of the 1:2 internal resonance and principal parametric resonance-1/2 subharmonic resonance. The system is transformed to the averaged equations. From the averaged equation, the theory of normal form is used to find the explicit formulas of normal form. Based on the normal form obtained, the extended Melnikov method is utilized to analyze the multi-pulse global homoclinic bifurcations and chaotic dynamics for the eccentric rotating composite laminated circular cylindrical shell. The analysis of global dynamics indicates that there exist the multi-pulse jumping orbits in the perturbed phase space of the averaged equation. From the averaged equations obtained, the chaotic motions and the Shilnikov type multi-pulse orbits of the eccentric rotating composite laminated circular cylindrical shell are found by using numerical simulation. The results obtained above mean the existence of the chaos for the Smale horseshoe sense for the eccentric rotating composite laminated circular cylindrical shell.
Design of Composite Structures Through Decision Support Problem and Multiscale Design Approach
Authors: Pathan Rizwan Khan , Beemaraj Soban Babu , Salvi Amit , Sharma Gehendra , Allen Janet K. , Mistree Farrokh 
Published: November 2019

Abstract
Composite materials are increasingly being used in load bearing structures due to their high specific stiffness and strength. Designing composite structures involve solving multiple conflicting objectives (e.g weight and deflection) and constraints (e.g failure stress and strain), which is a challenging task. In the absence of an optimal solution, a compromise solution is desired. Concurrent (material selection plus sizing) design approach using Decision Support Problem (DSP) is used to arrive at a compromise solution. In this paper multiscale design approach is proposed, that incorporates the tailoring of material microstructures and sizing to achieve improved compromise solution. The microstructure properties are obtained by using analytical and computational models for various composite materials. These models compute structure-property relations between bulk material properties and their micro-structural constituents. The approach is demonstrated with an example of a sandwich composite cantilever beam subjected to multiple load cases. An efficiency factor (η) is defined to compare the results of concurrent design approach and multiscale design approach.
Augmented Microscopy for DNA Damage Quantification: A Machine Learning Tool for Environmental, Medical and Health Sciences
Authors: Bernardini Michele , Ferri Alessandro , Migliorelli Lucia , Moccia Sara , Romeo Luca , Silvestri Sonia , Tiano Luca , Mancini Adriano 
Published: November 2019

Abstract
The Comet Assay is a well-known procedure employed to investigate the DNA damage and can be applied to several research areas such as environmental, medical and health sciences. User dependency and computation time effort represent some of the major drawbacks of the Comet Assay. Starting from this motivation, we applied a Machine Learning (ML) tool for discriminating DNA damage using a standard hand-crafted feature set. The experimental results demonstrate how the ML tool is able to objectively replicate human experts scoring (accuracy detection up to 92%) by solving the related binary task (i.e., controls vs damaged comets).
Design for Additive Manufacturing Using a Master Model Approach
Authors: Wiberg Anton , Persson Johan , Ölvander Johan 
Published: November 2019

Abstract
The introduction of Additive Manufacturing opens up possibilities for creating lighter, better and customized products. However, to take advantage of the possibilities of Additive Manufacturing, the design engineer is challenged. In this paper, a general design process for the creation of complex products is proposed and evaluated. The proposed method aims to aid a design process in which Topology Optimization (TO) is used for concept development, and the result is then interpreted into a Master Model (MM) supporting design evaluations during detailed design. At the same time as the MM is created, information regarding manufacturing is saved in a database. This makes it possible to automatically generate and export models for manufacturing or CAE analyses. A tool that uses Knowledge-Based Engineering (KBE) to realize the presented methodology has been developed. The tool is specialized for the creation of structural components that connect to other components in an assembly. A case study, part of an aircraft door, has been used for evaluation of the tool. The study shows that the repetitive work when interpreting the topology-optimized design could be reduced. The result comes in the form of a parametric CAD model which allows fast changes and the coupled database enables the export of models for various purposes.
Checking Application Level Properties Using Assertion Synthesis
Authors: Wenzl Matthias , Roessler Peter , Puhm Andreas 
Published: November 2019

Abstract
This work presents a proof-of-concept of a new approach on automatic generation of digital hardware that is able to check application-level properties of an embedded system such as a faulty system behavior at runtime. The approach makes use of assertion-based verification setups that today are very common in the area of digital hardware design with, however, the sole focus on logic simulation. Thus, a PSL-to-VHDL compiler is introduced that generates VHDL (Very High Speed Integrated Circuit Description Language) code out of PSL (Property Specification Language) assertions which can be further processed by a traditional digital logic synthesis tool. That way, runtime checker units can be automatically generated with little effort because of the already existing assertion-based test benches. Furthermore, a model railway demonstrator is presented herein as an example for a safety-critical application to prove the proposed tool flow on a use case. Implementation results based on that use case are discussed. Finally, the paper concludes with a brief outlook on related future work of the authors.
Dimensional Prediction for FDM Machines Using Artificial Neural Network and Support Vector Regression
Authors: Lyu Jiaqi , Manoochehri Souran 
Published: November 2019

Abstract
With the development of Fused Deposition Modeling (FDM) technology, the quality of fabricated parts is getting more attention. The present study highlights the predictive model for dimensional accuracy in the FDM process. Three process parameters, namely extruder temperature, layer thickness, and infill density, are considered in the model. To achieve better prediction accuracy, three models are studied, namely multivariate linear regression, Artificial Neural Network (ANN), and Support Vector Regression (SVR). The models are used to characterize the complex relationship between the input variables and dimensions of fabricated parts. Based on the experimental data set, it is found that the ANN model performs better than the multivariate linear regression and SVR models. The ANN model is able to study more quality characteristics of fabricated parts with more process parameters of FDM.
sBF-BO-2CoGP: A Sequential Bi-Fidelity Constrained Bayesian Optimization for Design Applications
Authors: Tran Anh , Wildey Tim , McCann Scott 
Published: November 2019

Abstract
Bayesian optimization is an effective surrogate-based optimization method that has been widely used for simulation-based applications. However, the traditional Bayesian optimization (BO) method is only applicable to single-fidelity applications, whereas multiple levels of fidelity exist in reality. In this work, we propose a bi-fidelity known/unknown constrained Bayesian optimization method for design applications. The proposed framework, called sBF-BO-2CoGP, is built on a two-level CoKriging method to predict the objective function. An external binary classifier, which is also another CoKriging model, is used to distinguish between feasible and infeasible regions. The sBF-BO-2CoGP method is demonstrated using a numerical example and a flip-chip application for design optimization to minimize the warpage deformation under thermal loading conditions.
Wide Range Highly Sensitive Pressure Sensor Based on Heated Micromachined Arch Beam
Authors: Alcheikh Nouha , Hajjaj Amal Z. , Younis Mohammad I. 
Published: November 2019

Abstract
Miniaturized air-pressure sensing devices has received increasing attention during the past few decades. Pressure sensors have been explored in various potential applications, such as industrial control, healthcare, medical testing, and environmental monitoring [1–2]. Different sensing mechanisms and designs have been used for the detection of air-pressure. Of particular importance are resonant pressure sensors based on tracking the change in resonance frequency of the device with pressure. To improve the pressure sensor sensitivity, various designs have been investigated including carbon nanotubes, microcantilever, and bridge resonators. In a recent study [3], we showed a resonant pressure sensor based on an electrothermally heated clamped-clamped straight beam (cooling effect). We showed that operating the resonator near the buckling point maximizes its sensitivity [3]. In this work, we will focus on the detection of air pressure using an electrothermally heated initially curved beam exhibiting veering among its first two symmetric vibration modes, which offers more continuity in frequency variations, and hence measurements compared to buckled beams. The presented approach shows significant advantages in term of sensitivity and wide pressure range.
Multibody Dynamics vs. Fluid Dynamics: Similarities and Differences
Authors: Rakhsha Milad , Kelly Conlain , Olsen Nic , Serban Radu , Negrut Dan 
Published: November 2019

Abstract
In large, rigid multibody dynamics problems with friction and contact, encountered for instance in granular flows, one can witness distinctly different system-level dynamics. This contribution concentrates on the case of fluid-like behavior of large multibody dynamics systems such as granular materials, when the system experiences large strains. The results reported herein draw on computer simulation; on the one hand, we solve the Newton-Euler equations of motion, which govern the evolution of multibody dynamics system featuring frictional contact. On the other hand, we solve the Navier-Stokes equations which describe the time evolution of fluids. To demonstrate the similarities and differences between the multibody and fluid dynamics we consider three problems modeled and solved using different methods; (i) a compressibility test; (ii) the classical dam break problem, and (iii) the dam break simulation with an obstacle. These experiments provide insights into conditions under which on can expect similar characteristics from multibody and fluid dynamics systems governed by manifestly different equations of motion and solved by vastly different numerical solution methods. The models and simulation platform used are publicly available and part of an open source code called Chrono. Both the multibody and fluid dynamics simulations are carried out using GPU computing.
Data Association and Fusion Framework for Decentralized Multi-Vehicle Cooperative Perception
Authors: Yoon DoHyun Daniel , Ali G. G. Md. Nawaz , Ayalew Beshah 
Published: November 2019

Abstract
Vehicular communication technology (V2V, V2I, V2X, etc.) allows participating vehicles to actively exchange information about their surrounding traffic. By sharing the local field of view (FoV) perception along with their own instantaneous states, communicating vehicles can cooperatively broaden and improve their perceptions of the overall traffic which allows more effective maneuver planning and vehicle energy management. This paper outlines a framework for decentralized multi-vehicle cooperative perception where each vehicle broadcasts its perception information and also acts as an individual fusing node for the received data. The Bhattacharyya distance filter (BDF) is applied for the data association process, identifying and grouping a set of estimates potentially representing the same vehicle. The associated estimates are then passed down to a covariance intersection-based fusion scheme that yields a single fused state estimate and covariance matrix for each vehicle. A metric is adopted to assess the performance of the cooperative perception scheme. The workings of the proposed framework and its potential advantages over other solutions is illustrated via simulations of connected vehicles in highway traffic scenarios with different vehicle densities.
Investigating the Nonlinear Dynamics of Human Balance Using Topological Data Analysis
Authors: Siegrist Kyle W. , Chagdes James R. , Kramer Ryan M. 
Published: November 2019

Abstract
Understanding the mechanisms behind human balance has been a subject of interest as various postural instabilities have been linked to neuromuscular diseases (Parkinson’s, multiple sclerosis, and concussion). This paper presents a classification method for an individual’s postural stability and estimation of their neuromuscular feedback control parameters. The method uses a generated topological mapping between a subjects experimental data and a data set consisting of time series realizations generated using an inverted pendulum mathematical model of upright balance. The performance of the method is quantified using a time series realizations with known stability and neuromuscular control parameters. The method was found to have an overall sensitivity of 85.1% and a specificity of 91.9%. Furthermore, the method was most accurate when identifying limit cycle oscillations with a sensitivity of 91.1% and a specificity of 97.6%. Such a method has the capability of classifying an individual’s stability and revealing possible neuromuscular impairment related to balance control, ultimately providing useful information to clinicians for diagnostic and rehabilitation purposes.
Design and Testing of a Solar-Powered Bicycle in Nairobi, Kenya
Authors: Maranga Ignatius , Burleson Grace , Christen Roger , Da Silva Izael 
Published: November 2019

Abstract
Globally, access to reliable and clean transportation vehicles is a growing concern. Using off-the-shelf components, researchers in Kenya have developed a solar-powered bicycle called the “Solar-E-Bike.” The bike has the potential to support the demand for mobility and electric power of the growing African population. A fully solar powered vehicle/generator for commuting and light cargo transportation as a source of electricity in the home is technically feasible and would respond to real user needs, impact the lives of many of people living in off-grid communities in Africa. Incorporating renewably-powered transportation methods could be a significant contribution to avoiding CO2 emissions in the future. The prototypes for this product have proven that a solar vehicle could easily be a practical transportation device with a daily range of 50 km per day. However, a test drive across 500 km showcased valuable design changes, such as improved component selection and durable frame design, that are needed for this product to be usable on a commercialized scale. Vehicles such as the one discussed in this paper could provide additional benefits such as power generation and provide infrastructure support for health, education, water and communications.
Online Trajectory Optimization for Legged Robotics Incorporating Vision for Dynamically Efficient and Safe Footstep Locations
Authors: Hooks Joshua R. , Ahn Min Sung , Hong Dennis 
Published: November 2019

Abstract
This paper presents a trajectory optimization algorithm for legged robotics that uses a novel cost function incorporating point cloud data to simultaneously optimize for footstep locations and center of mass trajectories. This novel formulation transforms the inherently discrete problem of selecting footstep locations into a continuous cost. The algorithm seamlessly balances the desire to choose footstep locations that enhance the dynamic performance of the robot while still choosing locations that are viable and safe. We demonstrate the success of this algorithm by navigating the ALPHRED V2 robotic system over unknown terrain in a simulation environment.
Design and Dynamics of Hybrid Wave and Current Energy Converter
Authors: Chen Shuo , Jiang Boxi , Li Xiaofan , Xiong Qiuchi , Huang Jianuo , Zuo Lei 
Published: November 2019

Abstract
The ocean has been identified as one of the most promising energy sources and it can be comprehended as the “unlimited” energy source as well. Therefore, a reasonable exploitation and development on ocean energy recovery are applicable in this energy shortage era. This paper investigates the design and dynamic analysis of the Hybrid Wave and Current Energy Converter (HWCEC), which uses current and wave to recover energy from the ocean. In general, the HWCEC system contains the oscillating buoy and rotating turbine, while the ocean wave and current pass through the system. The energy harvested from the ocean flows through the Mechanical Motion Rectifier (MMR) gearbox [1], and the oscillating motion is converted to a unidirectional rotational motion, which will drive the generator and produce electricity. The dynamic of the HWCEC is developed by combing the dynamics of a heaving buoy, a horizontal axis hydro-turbine and the working status of an MMR-based Power Take-off system (PTO). A 1:10 scaled down prototype has been manufactured and assembled. Further tests will be conducted in the cooperating facilities. Simulation is conducted based on hydrodynamic coefficients obtained from WAMIT and the blade element momentum theory for the scaled-down prototype. Considering a regular wave with 0.08 meters of wave height with 1 second of wave period together with 0.3m/s constant current velocity, Results show that the HWCEC has an improvement in the energy extraction ratio compared to a traditional Wave Energy Converter (WEC) by 53%. The simulation indicates the fact that harvesting energy from both wave and current is simply more efficient than the traditional types of ocean energy harvester, which consists of only harvesting energy from a single source.
A Customer-to-Manufacturer Design Model for Custom Compression Casts
Authors: Zhang Yunbo , Kwok Tsz-Ho 
Published: November 2019

Abstract
This paper presents a computational framework for designing and optimizing custom compression casts/braces. Different from the conventional cast/brace design, our framework generates custom casts/braces with fitness, lightweight, and good ventilation. The computational pipeline is an end-to-end solution, directly from customer to the manufacturer, which starts from a 3D scanned human model represented by mesh and ends with the 3D printed cast/brace. Our interactive tools allows users to define and edit the 3D curves on the mesh surface, and trim the mesh surface to form the cast/brace shape using the curves. These tools are efficient and simple to use, and also they enable designing the custom casts/braces fitting to the given human body. In order to reduce the weight and improve the ventilation, we adopt the topology optimization (TO) method to optimize the cast/brace design. We extend the existing three-dimensional (3D) TO method to the mesh surface by simplifying the optimization problem to a 2D problem. Therefore, the efficiency of the TO computation is improved significantly. After the optimized cast/brace design is obtained on the mesh surface, a solid model is generated by our design interface and then sent to a 3D printer for fabrication. Simulation results show that our method can better re-disturb the stresses compared with the conventional 3D TO.