bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Defect Prevention Concept Using Artificial Intelligence
Authors: Eddy Douglas , Krishnamurty Sundar , Grosse Ian , White Michael , Blanchette Damon 
Published: November 2020

Abstract
Defect prevention is particularly critical in operations such as aircraft assembly or service. Failure Modes and Effects Analysis (FMEA) procedures have been deployed manually for many years. However, the manual procedures fail to utilize capability to build intelligence into inspection processes that can facilitate elimination of human error. In this work, we introduce an artificial intelligence (AI)-based concept that can iteratively learn to assure zero defects from a given inspection process. This work introduces a schema that can serve as a knowledge management framework in a relational database for instantiation with inspection process information and data from a detection system. A companion algorithm is presented for the case of a wiring harness bracket installation in a fuselage. The schema and algorithm analyze and assess potential defects posed by Foreign Object Debris (FOD) in parallel to the assembly inspection. A closed loop of logic was introduced to enable anomaly detection by this algorithm to assure zero defects.
Design and Laboratory Validation of a Force-Amplified Piezoelectric Energy Harvesting Unit
Authors: Chen Cheng , Sharafi Amir , Flores Jason , Louie Dela Pena Ralph , Mendoza Priscilla , Ayala Helen , Ortiz-Donato Steven , Sun Jian-Qiao 
Published: November 2020

Abstract
In this paper, an innovative piezoelectric energy harvesting unit (PEHU) for the piezoelectric energy harvesting system (PEHS) from highway traffic is introduced. The proposed PEHU contains a non-linear force amplification mechanism, which substantially increases the electricity output of the PEHU in contrast to the conventional designs with direct loading to the piezoelectric stacks. Quasi-static laboratory tests have been performed to validate the design and the mathematical model. In a quasi-static load cycle of 1333N, a preloaded PEHU prototype is able to generate a voltage of 128V and a potential electric energy of 120mJ with a displacement as small as 2.54mm. The energy density that the PEHS can potentially deliver is estimated to be 8.64J/(m.pass.lane) and is the highest reported in the literature. This level of power generation suggests that the PEHU has a great potential for roadway energy harvesting.
Design a Four-Bar Linkage for Upper Limb Muscle Rehabilitation Exercise: A Simulation Study
Authors: Quarnstrom Joel , Xiang Yujiang 
Published: November 2020

Abstract
In this study, a four-bar linkage with coupler point is designed to guide the arm motion exercise for muscle strength rehabilitation. The hand grasps the coupler point during rotation. The coupler point can generate different shape of trajectories by changing the coupler point’s relative location and the linkage’s dimensions. The rotating coupler point is used to guide the user’s hand to exercise arm muscles for rehabilitation. A two-dimensional (2D) musculoskeletal arm model is used to simulate the arm motion. The inverse-dynamics-based optimization method is used for trajectory reconstruction to determine the joint torque and muscle forces. The effect of different shapes of coupler point trajectory on specific muscle force excise is investigated, such as kidney shape, heart shape, and woven shape trajectories.
Error Quantification in Dynamic Applications of Weakly Nonlinear Transducers
Authors: Cilenti Lautaro , Chijioke Akobuije , Vlajic Nicholas , Balachandran Balakumar 
Published: November 2020

Abstract
Characterization and quantification of dynamic measurements is an ongoing area of research in the metrological community, as new calibration methods are being developed to address dynamic measurement applications. In the development undertaken to date, one largely assumes that nominally linear transducers can be used with linear assumptions in deconvolution of the input from the response and in system identification. To quantify the errors that arise from these assumptions, in this article, the effects of weak nonlinearities in transducers that are assumed to behave linearly during dynamic excitations are studied. Specifically, a set of first-order and second-order systems, which can model many transducers with weak nonlinearities, are used to numerically quantify the systemic errors due to the linear assumptions underlying the deconvolution. We show through the presented results the evolution of different error metrics over a large parameter space of possible transducers. Additionally, an example of quantification of the errors due to linear assumptions in system identification is demonstrated by using a time-series sparse regression system identification strategy. It is shown that the errors generated from linear identification of a nonlinear transducer can counteract the systemic errors that arise in linear deconvolution when the linear system identification is performed in similar loading conditions. In general, the methodology and results presented here can be useful for understanding the effect of nonlinearity in single degree of freedom transient dynamics deconvolution and specifically in specifying certain metrics of errors in transducers with known weak nonlinearities.
Towards Data-Driven Modeling of Pathological Tremors
Authors: Wang Jiamin , Gupta Sunit K. , Barry Oumar 
Published: November 2020

Abstract
Understanding the dynamics of pathological tremors (e.g., Parkinson’s Disease, Essential Tremor) is crucial to developing effective treatments for these neurological disorders. This paper studies the data-driven modeling of periodic and quasiperiodic tremors. A general neuromusculoskeletal model is proposed to serve as the theoretical basis of this study. The Parkinsonian tremor data is first observed in terms of periodicity, frequency composition, and chaotic characteristics, which confirm tremor is a nonlinear dynamics problem. Two data-driven models are then proposed to predict the nonlinear dynamics of tremor: (1) a model-free approach via long short-term memory recurrent neural network, and (2) a model-based approach via extended dynamical mode decomposition. These models are compared to existing models and the results show that the proposed models outperform existing models for long term prediction of tremor.
Design of Single-DOF Immersive Upper Limb Rehabilitation System via Kinematic Mapping and Virtual Reality
Authors: Zhao Ping , Guan Haiwei , Zhang Yating , Chen Yuwen , Deng Xueting , Chen Haodong 
Published: November 2020

Abstract
Mechanical devices such as robots are widely adopted for limb rehabilitation. Due to the variety of human body parameters, the rehabilitation motion for different patients usually has its individual pattern, thus we adopt clustering-based machine learning technique to find a limited number of motion patterns for upper-limb rehabilitation, so that they could represent the large amount of those from people who have various body parameters. Using the regression motion of the clustering result as the task motion, in this paper we seek to apply kinematic-mapping-based motion synthesis framework to design a one-DOF mechanism such that it could lead the patients’ upper limb through the task motion. Also,considering rehab training generally involves a large amount of repetition in daily basis, this paper has developed an immersive rehab system with Unity3D based on Virtual Reality (VR). A patient user interface as well as an administrator user interface are presented, and a two-mode rehabilitation strategy is proposed. The construction of the integrated system and a prototype of the upper limb rehab device are also shown in the end of this paper.
Excimer Laser Treatment of Steel Fibers for Improved Adhesion to Silicone Rubber
Authors: Sancaktar Erol , Liu Xiaoxiao 
Published: November 2020

Abstract
Former investigators observed characteristic laser-induced structure on synthetic fibers and steel cord surfaces after irradiation, which is considered by us as an advantageous factor in developing bonding strength of fiber-elastomer composites. We applied various UV laser treatments on the surfaces of steel fiber in order to obtain similar topographic features. Surface modification was observed under scanning electron microscope (SEM). In consideration as factors in bonding strength, mechanical properties of the matrix elastomer (silicon rubber) had been tested in addition to its thermal properties by differential scanning calorimetry (DSC) and Carbon Black (CB) filler dispersion properties by atomic force microscopy (AFM). As the main test for adhesion strength, we performed a fiber pull-out test method developed by our research group for bonding strength of cord fibers to silicon rubber in both neat and CB filled forms for comparison purposes. Our experiment results revealed better adhesion strength when using silicone rubber matrix reinforced with CB.
Developing Training Tools for Clinicians in LICs: A Qualitative Investigation of the Patient Factors That Influence Prosthetic Prescription
Authors: Walker Michael , Saravanan Pratima , Menold Jessica 
Published: November 2020

Abstract
A prosthesis is a replacement limb that must be functionally sound, comfortably fit, durable, and aesthetically pleasing. Difficulty in prescription is further amplified by each patient’s unique needs and the variability within patient data. The clinician’ s education and prior training is critical in effectively navigating the wealth of patient specific information needed to prescribe a prosthesis and rehabilitation plan that increases the likelihood of long-term patient success. Education and training significantly vary, however, from country to country, and in Lower Income Countries (LIC) a lack of formalized prosthetic training contributes to a lower quality of life for resident amputees. Prosthetists and technicians in LICs face further challenges due to a lack of material resources and formal medical infrastructure. This study was motivated to understand the types of patient information that influence decision-making strategies during prosthetic prescription and compare strategies across expert and novice groups. The results of this study suggest that salient factors are different between each clinician group and is influenced by the complexity of the patients’ case. Activity level of the amputee influenced novices’ prescription, whereas amputee’s motivation, insurance, and health history influenced experts’ prosthetic prescription. Future work exploring the utility of complimentary or supplemental prescription tools, particularly for prosthetists in LICs, is discussed.
Predicting Average Product Lifetime Using Physics-Based Gaussian Process Method in Early Design Stage
Authors: Wei Xinpeng , Han Daoru , Du Xiaoping 
Published: November 2020

Abstract
Average lifetime, or mean time to failure (MTTF), of a product is an important metric to measure the product reliability. Current methods of evaluating MTTF are mainly statistics or data based. They need lifetime testing on a number of products to get the lifetime samples, which are then used to estimate MTTF. The lifetime testing, however, is expensive in terms of both time and cost. The efficiency is also low because it cannot be effectively incorporated in the early design stage where many physics-based models are available. We propose to predict MTTF in the design stage by means of physics-based models. The advantage is that the design can be continually improved by changing design variables until reliability measures, including MTTF, are satisfied. Since the physics-based models are usually computationally demanding, we face a problem with both big data (on the model input side) and small data (on the model output side). We develop an adaptive supervised training method based on Gaussian process regression, and the method can then quickly predict MTTF with minimized number of calling the physics-based models. The effectiveness of the method is demonstrated by two examples.
Investigation of the Effect of Native Oxide Layer on Performance of Interdigitated Impedance-Based Silicon Biochemical Sensors
Authors: Ebrahimpour Tolouei Nadia , Ghamari Shima , Shavezipur Mohammad 
Published: November 2020

Abstract
Chemical and biological detection using Electrochemistry Impedance Spectroscopy (EIS) highly depends on the electrical characteristics of the electrodes used in the measurement process. In this work, the effect of surface coating on behavior of interdigitated impedance-based biochemical sensors is studied. Two interdigitated sensors with the same geometry and different electrode materials are fabricated using a standard process. One electrode is made of gold and the other electrode is made of polycrystalline silicon covered with a thin layer of native silicon dioxide. Different concentrations of di(2-ethylhexyl) phthalate (DEHP) in water are used and the Nyquist responses of the two sensors exposed to these solutions are obtained. The measurement results show that at high frequency both sensors form double-layer capacitance values on their electrode surfaces, however, the silicon sensor has a much lower double-layer capacitance values, because formation of oxide layer adds to the gap between charges at the interface of the electrode and the solution. Moreover, comparing the low frequency regions of the Nyquist plots for two sensors shows that the presence of oxide layer affects the Warburg effect and the charge diffusion near the surface of the electrode, creating an extra capacitive element in series with the diffusion effect. The results of this work may be extended to other interdigitated biochemical sensors that may have other sources of contamination on their surfaces.
Resistive Force Analysis for Design of Rubber Tire Loader Buckets
Authors: Ur Rehman Atta , Awuah-Offei Kwame 
Published: November 2020

Abstract
Rubber tire loaders are key loading equipment for surface and underground mines and can load up to 35 t of material in a pass. Efficient initial penetration into the pile improves the overall efficiency of the loading operation. For efficient design for good initial penetration, we need to predict accurately the resistive forces encountered by these buckets during initial penetration. This paper examines the resistive forces on the bucket as a function of rake angle, height above the digging floor, speed, and tractive effort during initial penetration. A 1/16th scaled representative model of an 18 t (19.8 ton) capacity load haul dump is used for experimentation to understand the effects of rake angle, height above the floor, speed, and tractive effort. The results show that resistive forces are not associated with rake angle or height above the floor but significantly associated with speed, tractive effort, combined effects of speed and tractive effort, and combined effects of speed and rake angle. Future research should focus on conducting similar experiments on different materials and different buckets to better understand the ground engagement for mining and construction equipment. These insights are important to understand the full range of forces during bucket and equipment design.
Tuning Stiffness Nonlinearity: Theory and Applications
Authors: Zanaty Mohamed , Vardi Ilan , Henein Simon 
Published: November 2020

Abstract
Perfect elasticity is not achievable in real-life situation, so spring stiffness is not perfectly constant. In this paper, we study the effect of modifying non-linear stiffness terms while keeping the nominal stiffness constant. We introduce three methods to design and tune linear and nonlinear elastic behavior in the context of compliant mechanisms and we present mechanical realizations. These designs are modeled using Euler-Bernoulli beam theory. Numerical simulation and experimental measurement show a good match with the theoretical model. We then present applications of our stiffness tuning methods to mechanical meta-materials, mechanical resonators, and mechanical computation.
Multi-Fidelity Surrogate Model-Assisted Fatigue Analysis of Welded Joints
Authors: Zhang Lili , Xie Tingli , Hu Jiexiang , Jiang Ping , Koo Jasuk , Choi Seung-Kyum 
Published: November 2020

Abstract
In this study, an additive scaling function based multi-fidelity (ASF-MF) surrogate model is constructed to fast predict fatigue life as well as the stress distribution for the welded single lap joint. The influence of leg length, leg height, the width of the specimen and load in the fatigue test are taken into consideration. In the construction of the MF surrogate model, the finite element model that is calibrated with the experiment is chosen as the high-fidelity (HF) model. While the finite element model that is not calibrated with the experiment is considered as the low-fidelity (LF) model, aiming to capture the trend of the HF model. The Leave-one-out (LOO) verification method is utilized to compare the prediction performance of the ASF-MF surrogate model with that of the single-fidelity Kriging surrogate model. Results show that the ASF-MF surrogate model can better predict the fatigue life as well as the stress distribution.
A Practical Approach for Managing Uncertainty in Remanufacturing: Identifying Leverage Points Using Design Structure Matrix
Authors: Kimita Koji , Matschewsky Johannes , Sakao Tomohiko 
Published: November 2020

Abstract
Remanufacturing is a crucial component for our societies to move toward a circular economy. Compared to new manufacturing, the distinctive nature of remanufacturing is found to have high variability, high uncertainty and, thereby, complexity. Therefore, remanufacturers need to enhance their ability to adjust their systems flexibly. Especially, the ability to reconfigure the production planning and control is crucial for reacting to the high variability and uncertainty. However, few practical methods to do that are available so far. Therefore, to solve this problem, this paper aims to propose a method for designing processes of production planning and control in remanufacturing based on the concept of loosely coupled systems. In the proposed method, Design Structure Matrix (DSM) is applied to identify loosely coupled subsystems that enable to localize impacts of changes within themselves. These subsystems are also utilized to appropriately determine leverage points, as well as allocate human resource. Through the application to a real case of remanufacturing, the proposed method was found to be effective for reconfiguring teams and processes for production planning and control depending on given uncertainties, as well as performing production planning and control activities efficiently.
Innovative Chassis Made From EPP and CFRP of an Urban-Concept Vehicle
Authors: Stabile P. , Ballo F. , Gobbi M. , Mastinu G. 
Published: November 2020

Abstract
The paper presents a fully new chassis of a high efficiency vehicle for the Shell Eco-marathon competition. The chassis is realized by a sandwich structure with an expanded polypropylene (EPP) core and carbon fiber reinforced plastic (CFRP) external skins. The chassis is connected to the body to realize a safe and stiff structure.
Numerical analyses have been performed to assess the stiffness, safety and dynamic eigenfrequencies of the chassis. A Finite Element model of the entire chassis and body was developed. The manufacturing process of the entire chassis and body is described in the paper and some data obtained during on-track tests of the vehicle are presented.
The vehicle reached the 4th place at the 2019 edition of the Shell Eco-marathon competition, with an equivalent energy consumption of 184 km/kWh.
Creativity and Engineering Education: Assessing the Impact of a Multidisciplinary Project Course on Engineering Students’ Creativity
Authors: Deo Saurabh , Hölttä-Otto Katja , Filz Günther H. 
Published: November 2020

Abstract
Creativity is the essential driving force, and creative engineers are the drivers entrusted to propel the technology-driven industry to the pinnacle of innovations in all engineering sectors. Accordingly, creativity is being integrated into engineering education in different ways, from a single lecture to more extensive curriculum level approaches. In this paper, we measured the effect of a multidisciplinary project course, a joint effort between the School of Arts, Design and Architecture, and the School of Engineering, on students’ creativity.
In particular, we assessed the Originality, Novelty, and Quantity of solutions produced by participants in two tasks, an Alternate uses test and the ShapeStorm exercise. An alternate uses test assessed the written form of divergent thinking, and the ShapeStorm exercise assessed the visual form of divergent thinking. Statistical analysis of the data indicated that solutions for the written divergent thinking task produced by students post-course were more novel than pre-course. We did not find a statistically significant improvement in the Quantity. Similarly, for the visual divergent thinking task, we see no statistically significant increase.
Sequential Design Decision Making Under the Influence of Competition: A Protocol Analysis
Authors: Shergadwala Murtuza N. , Panchal Jitesh H. 
Published: November 2020

Abstract
In this study, we focus on crowdsourcing contests for engineering design problems where contestants search for design alternatives. Our stakeholder is a designer of such a contest who requires support to make decisions, such as whether to share opponent-specific information with the contestants. There is a significant gap in our understanding of how sharing opponent-specific information influences a contestant’s information acquisition decision such as whether to stop searching for design alternatives. Such decisions in turn affect the outcomes of a design contest. To address this gap, the objective of this study is to investigate how participants’ decision to stop searching for a design solution is influenced by the knowledge about their opponent’s past performance. The objective is achieved by conducting a protocol study where participants are interviewed at the end of a behavioral experiment. In the experiment, participants compete against opponents with strong (or poor) performance records. We find that individuals make decisions to stop acquiring information based on various thresholds such as a target design quality, the number of resources they want to spend, and the amount of design objective improvement they seek in sequential search. The threshold values for such stopping criteria are influenced by the contestant’s perception about the competitiveness of their opponent. Such insights can enable contest designers to make decisions about sharing opponent-specific information with participants, such as the resources utilized by the opponent towards purposefully improving the outcomes of an engineering design contest.