bluuebunny/crossref_metadata_2025_split huggingface dataset:
Light Weighting Solutions for Additively Manufactured Aviation Components
Authors: Medikonda Sandeep , Sridharan Sriraghav , Acharya Sunil , Doyle John 
Published: January 2020

Abstract
Recently, additive manufacturing methods have gained popularity for their ability to produce complex mechanical parts where conventional manufacturing methods are not suitable. Such methods not only offer a great sense of freedom to engineers but when combined with topology optimization tools can be used to simulate structures with complex shapes which satisfy the real-world loading constraints while requiring as little material as possible. Hence, combining topology optimization and additive production procedures offers a promising approach for obtaining optimized mechanical parts. This article presents a complete workflow for studying complex topology optimized parts that can be printed using additive manufacturing.
We focus on topologically optimized design approach for additive manufacturing with case studies on lightweight design of aviation safety-critical parts. The complete workflow of such a setup is discussed. The Topology Optimization of these parts has been carried out using the Solid Isotropic Material with Penalization (SIMP) algorithm [1], where a discrete optimization problem is converted to a continuous problem. The primary objective of the optimization studies is to maximize the stiffness of the chosen parts while minimizing their mass at the same time. We also investigate the effect of design constraints to account for feasible manufacturing of the part while maintaining the structural response to performance loads.
These optimized parts are then analyzed using a lumped layer approach to simulate powder bed fusion (PBF) [2] as a coupled thermal-structural analysis within ANSYS®, where the areas of maximum deformation and stress resulting from additive printing are predicted. The influence that the orientation of a part’s build direction has on the end results is investigated using a parametric study. Effect of a cartesian mesh vs a tetrahedron mesh on the results have been analyzed and best practices while working with coupled topology optimization and additive simulations have also been discussed.
Influence Study of Gas Pressure on the Volume Measurement of Engine Combustion Chamber by Using Helmholtz Resonance
Authors: Chen Kun , Jin Sun , Liu Shun , Tian Ang , Mo Wei 
Published: January 2020

Abstract
The combustion chamber of automobile engine is a place where gasoline is burned to provide power for automobile driving and its size has a great influence on engine performance. However, because of the irregularity of the combustion chamber, it is difficult to measure it accurately and efficiently. The principle of Helmholtz resonance reveals the functional relationship between the volume and the resonant frequency of the closed cavity. Having used the Helmholtz resonance principle, the equipment for measuring the combustion chamber of automobile engine accurately and efficiently has been built. The conditions under which the cavity is stimulated to produce resonance are explored, the relationship between volume and the pressure is deduced. Experiments are designed to verify the correctness and accuracy of the measurement. The measuring instrument is improved and the accuracy of the volume measurement is increased. The application of the high precision and high efficiency of non-contact acoustic principle in cavity volume dynamic measurement has been realized.
A Challenge to Adaptability: Learning From the Octopus
Authors: Fukuda Shuichi 
Published: January 2020

Abstract
Our World is expanding very rapidly, and unpredictable changes occur frequently and extensively. Yesterday, our world was small and closed with boundaries. So, we could use past experience as knowledge and solve the problems. But today, our world is an open world without boundaries. And the environment and situations change in an unpredictable manner. So, knowledge does not work anymore. The octopus does not transfer knowledge from generation to generation. They live on their own instinct alone. But they are known to adapt to the unpredictable environments and situations very well. They demonstrate the importance of direct interaction with the outside world. Movement is taken up, because movement is essential for machines and humans. Machines only move as instructed, but in the case of humans, they need to coordinate and balance many body parts to move as they wish. So, they have to proceed by trial and error. This is indeed what the octopus is doing.In this paper, a new performance indicator is proposed. It combines Mahanalobis Distance with movement patterns. This approach provides us with a movement performance measure in a unitless and quantitative manner in a very simple way. Thus, we can understand if we are doing better or worse so we can adapt to the changing situations more reasonably and in shorter time.
Dynamic Impact Properties of a Novel Auxetic Metamaterial
Authors: Chen Zeyao , Wang Zhe , Wu Xian , Shao Jianwang , Zhou Shiwei 
Published: January 2020

Abstract
A novel auxetic metamaterial which is organized in the lattice is presented in this paper. Dynamic uniaxial impact behavior of the auxetic lattice using experiment and finite element simulation is investigated. The corresponding results have proved that the plastic beam-based finite element model has good agreement with the experiment. To explore the rate sensitivity of the auxetic lattice metamaterial, impact simulations of auxetic metamaterials at 13.07% relative density are firstly conducted under six velocities range from 1 to 100m/s. The comparison of deformation exhibits that deformation pattern depends on impact velocities. The shock wave effect can be obviously observed in the impact procedure which results in the loss of negative Poisson’s ratio effect at high velocity. The effective impact indices including plateau stress and densification strain can be extracted from the stress-strain curves. The simplified theory model based on the rigid, perfectly-plastic, locking model is utilized to fit data from the simulation. Furthermore, the effect of relative density on impact mechanical properties is investigated. The basic theoretical model is developed by considering the relative density which accords with simulation data well in four relative densities respectively 7.35%, 13.07%, 20.42%, 29.41%. Finally, the formula of plateau stress with respect to impact velocity and relative density can be obtained. The researches herein are aiming to reveal the dynamic properties of the auxetic lattice metamaterial and provide a constitutive model for potential application.
Selective Lamb Mode Transmission Enabled by Local Resonance Based Ultrasonic Metamaterial
Authors: Tian Yiran , Shen Yanfeng 
Published: January 2020

Abstract
In this study, a kind of elastic metamaterial substructure was designed for the selective mode filtering and transmission of symmetric and antisymmetric elastic waves. It is composed of double-sided aluminum-lead composite cylinders arranged in a periodic pattern bounded on an aluminum plate. The band structure of elastic metamaterial unit cell is numerically investigated using the modal analysis of a finite element model (FEM) by treating a unit microstructural cell with the Bloch-Floquet boundary condition. Through analyzing the vibration modes of the unit cell, a complete antisymmetric wave bandgap and a complete symmetric wave bandgap can be formed in different frequency ranges. Considering the geometric complexity of the designed substructure, the dynamic effective mass density of the proposed metamaterial unit cell is calculated by considering the structure as a homogeneous medium under the sub-wavelength requirement. The negative effective mass density behavior for in-plane and out-of-plane plate modes will be presented to verify the bandgap effect of different wave modes. A FEM harmonic analysis is further conducted to obtain the spectral response of a chain model and explore the mode filtering efficiency. Finally, a coupled field transient dynamic FEM is carried out to acquire the dynamic response of the structure. The frequency-wavenumber analysis demonstrates the successful achievement of model filtering behavior. The proposed selective mode transmission control methodology possesses great potential in future SHM and NDE applications. A case study for S0 mode conversion to SH0 mode using a different metamaterial unit cell is exhibited to illustrate other wave control capabilities. The paper finishes with summary, concluding remarks, and suggestions for future work.
An Inertial / Altimetric / Infrared / Geomagnetic Integrated Navigation Method for Unmanned Aerial Vehicles
Authors: He Zilu , Bu Xiongzhu , Cao Yihan , Xu Miaomiao 
Published: January 2020

Abstract
Unmanned aerial vehicle (UAV), is an unmanned aircraft operated by radio remote control equipment and self-contained program control device. When Unmanned Aerial Vehicle is on mission, its location information needs to be acquired to navigate it. Based on the research background of Unmanned Aerial Vehicle navigation information measurement, a passive integrated navigation mode of Inertial / Altimeter / Infrared / Geomagnetism Navigation method is designed in this paper. Firstly, several methods for Unmanned Aerial Vehicle navigation, including geomagnetic navigation, infrared navigation, inertial navigation and altimeter measurement, are introduced, and the advantages and disadvantages of various navigation methods are presented. Secondly, aiming at the problem that the output of barometric altimeter is affected by temperature and pressure, a temperature and pressure compensation model of barometric altimeter is established. Then, the attitude angle, velocity and position measurement models of inertial, infrared and geomagnetic navigation are established respectively. Finally, the data information of inertial / altimeter / infrared / geomagnetism measurement model is fused by extended Kalman filter and Unscented Kalman filter, and the signals processed by the two filters are compared. The reliability of the integrated navigation method is verified by simulation. This method has remarkable effect on improving the navigation accuracy of UAV and can make UAV suitable for many applications. It is simple and effective, and has wide application prospects.
Experimental Verification of Rubber Clutch Spring Damper Torque Behavior in Time-Dependent Manner and System Optimization Using Simulated Annealing Algorithm Integrated With 1-D Modeling
Authors: Genç Mehmet Onur , Kaya Necmettin , Konakçı Süleyman 
Published: January 2020

Abstract
Automobile components are subjected to high dynamic loads and vibrations under operational conditions which needs detailed system analysis for work properly. The torque generated in the engine creates oscillations, and this case occurred at different levels of frequencies. Clutch is one of the important part of automobile powertrain system with torque transmission controlling and vibration damping properties. Metallic helical springs are widely preferred within the clutch discs with their durable mechanic properties against dynamic variables on an automobile. This study develops the novel approach on the time-based investigation of rubber clutch springs, and system optimization for torsional vibration damping using the simulated annealing algorithm method. In this purpose, the torque behavior of the rubber spring instead of the helical spring was investigated by experimentally in time-dependent manner. Rubbers consist of polymer chains which are highly sensitive to dynamic variables such as operation time, frequency and thermal load. The clutch disc which includes rubber damper spring made of NBR (Nitril rubber) is experimentally tested with functional torque measurement at different compression cycle times to observe rubber damper spring viscoelastic time-based behavior. As the next step, 1-D modeling of powertrain system, including rubber clutch damper springs, were subjected to vibration optimization with simulated annealing (SA) algorithm. Thus, the simulated annealing (SA) algorithm was developed, and integrated run is provided with 1-D modeling for optimization in Python script. This methodology accelerates the powertrain system optimization using both rubber and metallic damper types with eliminating many of real vehicle testing and saving cost and time before the production phase. Also, results give an idea on the importance of 1-D simulation before design modeling of rubber clutch damper system based on time-dependent conditions.
Artificial Intelligence Based Architecture to Support Dementia Patients
Authors: Luís-Ferreira Fernando , Sarraipa João , Calado Jorge , Andrade Joana , Rodrigues Daniel , Jardim Goncalves Ricardo 
Published: January 2020

Abstract
Artificial Intelligence is driving a revolution in the most diverse domains of computational services and user interaction. Data collected in large quantities is becoming useful for feeding intelligent systems that analyse, learn and provide insights and help decision support systems. Machine learning and the usage of algorithms are of most importance to extract features, reason over collected data so it becomes useful and preventive, exposing discoveries augmenting knowledge about systems and processes. Human driven applications, as those related with physiological assessment and user experience, are possible especially in the health domain and especially in supporting patients and the community. The work hereby described refers to different aspects where the Artificial Intelligence can help citizens and wraps a series devices and services that where developed and tested for the benefit of a special kind of citizens. The target population are those under some kind of Dementia, but the proposed solutions are also applicable to other elder citizens or even children that need to be assisted and prevented from risks.
Dynamic Simulation of Planetary Gearbox With Tooth Root Crack Based on a Rigid-Flexible Coupled Model
Authors: Dai Jianchuan , Niu Hang , Hou Chenggang , Zhang Xiaodong 
Published: January 2020

Abstract
Tooth root crack is one of the most common failures in the gearbox which can lead to the failure of the whole transmission system. However, it is difficult to simulate the gear fault impact in practical work. To solve this problem and to study the relationship between tooth crack propagation and vibration features, various dynamic models have been built. However, the crack propagation path and the bearings are simplified in most of the models, which leads to obvious deviation in the dynamic response. In this paper, a rigid-flexible coupled model of a single-stage planetary gearbox in normal and fault conditions are built by ADAMS software. The crack propagation path is considered a parabolic curve and the thickness of the crack decreases along the path. As a reference, a rigid-body model has also been built to prove that the rigid-flexible coupled model can be more accurate and suitable for analyzing the response of the planetary gearbox with fault. Afterward, the effects of gear tooth root crack size on the gear dynamics are simulated and the corresponding changes in statistical indicators are investigated. By studying the torsional vibration signal of the planetary gearbox with varying severity of the damage, the fault characteristics and damage evolution mechanics can be analyzed and by comparing the fault sensitivity of these indicators, the critical and sensitive fault indicators are screened out.
Study of Two-Dimensional Flow-Boiling Morphological Characteristics in the Micro Gap With Surface Wettability on Hot Spot
Authors: Karim Anwarul , Kim Jong-Hoon 
Published: January 2020

Abstract
Thermal management is one of the most challenging problems of electronic devices today. As technology becomes increasingly miniaturized, extremely localized heat dissipation leads to the challenge of keeping devices away from overheating. Flow-boiling microchannel heat-sinks exploit the highly efficient thermal energy transport of phase change from liquid to vapor. However, the excessive consumption of liquid-phase by highly localized heat source causes the two-phase flow maldistribution, leading to greatly reduced heat transfer coefficient, high-pressure loss, and limited flow rate. In this study, we investigate two-dimensional flow-boiling morphological characteristics in a microgap with hydrophilic coating on hot-spot. The experiments are carried out on a Stainless Steel plate having a micro gap depth of 254 μm using deionized water with inlet at room temperature. A partial hydrophilic surface is created on the hot-spot (surface above the heater) which forms a wettability difference along the metal plate. A wide range of mass flux and heat flux are considered to quantify heat transfer coefficient. In addition, high-speed flow visualizations are performed to characterize the nucleation and bubble dynamics in flow boiling.
Beautiful Music in the Classroom: Marimba As a Lab Experiment for Teaching Vibration Measurement
Authors: Schaefer Mathew 
Published: January 2020

Abstract
A marimba bar makes a rich and vibrant sound when played by a skilled musician. When that same marimba bar is played by the typical mechanical engineering junior, it’s a different story. Then, that same marimba key provides a complex set of vibration modes that are a useful subject for a lab experiment in their Measurements & Instrumentation course. This paper will describe development of “The Marimba Experiment”, which is part of a junior-level engineering course in measurements at Milwaukee School of Engineering. Learning outcomes for this course include “provide students with hands-on experience: using various sensors, performing data collection, and interpretation of experimental results.” In this experiment, students measure vibrations using a piezoelectric accelerometer, charge amplifier and analog-to-digital conversion. Results can be viewed in two ways. First, it may be interpreted as a general example of a vibrating structural component. It has several natural frequencies and mode shapes (transverse bending, lateral bending, torsional), which are simultaneously active. The signal represents an example of a complex periodic signal. It may be analyzed by looking at the acceleration versus time response and by examining the Fourier transform of the data, which shows results in the frequency domain. Second, results may be interpreted in musical terms. The lowest frequency is what we recognize as “the note” and the higher modes represent the higher harmonics. The distribution of frequency ratios and the relative amplitudes of the higher frequencies are what gives a musical instrument its unique character. In other words, what makes middle-C on a marimba sound different than middle-C on a clarinet or violin? A well-designed engineering experiment can give students an immediate application example. In this case, it is an example which they spontaneously want to explore because they all enjoy music and want to understand how it is created.
Predicting the Risk of Twist-Off for Rotary Shouldered Threaded Connections With a Statistical Approach
Authors: Zhang Haitao , Li Ke 
Published: January 2020

Abstract
Fatigue is one of the most frequently encountered failure modes of rotary shouldered connections (RSC) used in drill strings. Once initiated, a fatigue crack tends to grow and ultimately lead to a twist-off, which is catastrophic and often results in lengthy non-producing time and expensive fishing operations. The complexity of the fatigue mechanism, the variabilities of material properties, and the nonlinear contact interactions of the pin and the box elements of an RSC pose a substantial challenge to accurately predicting the fatigue life of the RSC. This would require considerable conservatism to be exercised to prevent a twist-off, which causes premature retirement of drilling assets. Using a statistical approach to predict the risk of twist-off (ROTO) of each RSC on the drill string could be a more economically viable solution as it would enable quantified risk assessment and scientifically calculated tradeoffs between performance, cost, and risk of failures.
In this study, a methodology for statistical prediction of the ROTO of rotary shouldered threaded connections was developed. First, static material properties, including yield strength, tensile strength, elongation, and reduction in area, were extracted from a wealth of available material certificates. Feature engineering was carried out to arrive at two independent properties, tensile strength and reduction in area. Fatigue properties were then generated with the retrieved static material data and earlier established correlations between static and fatigue properties. Afterwards, elasto-plastic finite element analyses were performed on RSCs made of the same material but with different properties to determine critical fatigue indicators, stress and strain states as respective functions of the tensile strength. Finally, Monte-Carlo simulations were conducted with respect to statistical distributions of the two independent material variables to predict the ROTO as a function of fatigue life. The predictions were found to be favorable agreement with the available full-scale fatigue test data of an API connection type.
Robust Weed Recognition Through Color Based Image Segmentation and Convolution Neural Network Based Classification
Authors: Khan M. Nazmuzzaman , Anwar Sohel 
Published: January 2020

Abstract
Current image classification techniques for weed detection (classic vision techniques and deep-neural net) provide encouraging results under controlled environment. But most of the algorithms are not robust enough for real-world application. Different lighting conditions and shadows directly impact vegetation color. Varying outdoor lighting conditions create different colors, noise levels, contrast and brightness. High component of illumination causes sensor (industrial camera) saturation. As a result, threshold-based classification algorithms usually fail. To overcome this shortfall, we used visible spectral-index based segmentation to segment the weeds from background. Mean, variance, kurtosis, and skewness are calculated for each input image and image quality (good or bad) is determined. Bad quality image is converted to good-quality image using contrast limited adaptive histogram equalization (CLAHE) before segmentation. A convolution neural network (CNN) based classifier is then trained to classify three different types of weed (Ragweed, Pigweed and Cocklebur) common in a corn field. The main objective of this work is to construct a robust classifier, capable of classifying between three weed species in the presence of occlusion, noise, illumination variation, and motion blurring. Proposed histogram statistics-based image enhancement process solved weed mis-segmentation under extreme lighting condition. CNN based classifier shows accurate, robust classification under low-to-mid level motion blurring and various levels of noise.