bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lifetime Prediction Considering Nonlinearity in Degradation Progression
Authors: Jihin Rosmawati , Söffker Dirk 
Published: November 2019

Abstract
In this paper, the establishment of a prognostic approach based on a nonlinear degradation model for reliability assessment focusing on health state and remaining useful life estimation is considered. A model able to describe the non-linearity of degradation to predict future damage progression for real-time application has to be defined. Real-time data are generated during operation, so incomplete data about failure and usage up to the end of life are expected. For the accurate prediction of system lifetime, estimation of future degradation from the point of assessment is required. At this point, the unavailable data are numerically calculated by integrating linearized gradients adaptively by considering nonlinearity in current degradation. The coefficients used to define future degradation gradients are identified according to different states assuming future linear degradation increments. These coefficients are determined using an optimization-based algorithm simultaneously with the calculation of consumed lifetime by extending the previously established state machine lifetime model. For performance evaluation of the approach, the effectiveness of predicting remaining useful life using tribological experiments data is investigated. The results show the potential of this approach to deal with nonlinearity in the degradation progression.
Research on Instability Principle of Virtual Tracks Train When Braking on Curve
Authors: Zuo Jianyong , Gu Yihao , Lu Haiying , Yu Jie , Liu Cheng 
Published: November 2019

Abstract
Virtual tracks train is a new type of rail transit, which combines traditional rail vehicles and road vehicles. In order to study the effect of braking on the stability of virtual tracks train on curve, a four-axle model with train body model, steering model, braking model and tire model was built in Matlab/Simulink to research the change of yaw velocity, lateral acceleration and vehicle speed when it brakes on curve. Through step steering test of the vehicle, the model was verified to analyze the braking stability on steady steering condition.
Simulation result shows that when virtual tracks train brakes after 8s of turning with an individual axle locking up, different instability phenomena such as loss of guidance capacity, folding and drifting, would occur, which leads to instability of braking on curve. Using ABS can help improve the stability of it. With the instability principle put forward through the simulation, brake system and brake force distribution law could be designed to meet the need of virtual tracks train.
A Gear-Slider Gravity Compensation Mechanism: Design and Experimental Study
Authors: Vu Linh Nguyen , Kuo Chin-Hsing 
Published: November 2019

Abstract
This paper presents the design and experimental study of a geared five-bar module for the gravity compensation of a rotating mass. In this design, a compression spring is installed on the rotating link and a pair of spur gears are used to transmit the elastic force to counterbalance the gravitational force. The design problem is first formulated as an optimization model for minimizing the actuation torque and then simplified to an analytical equation for approximating the perfect compensation design. One unique feature of the study is that the friction effect of the meshing gears is considered in the design of the spring stiffness. A prototype of the proposed mechanism was built and experimentally investigated via the manual and motor-driven tests. In the manual test, the measured peak static motor torque due to gravity was reduced up to 84.3% with the spring attachment. On the other hand, in the motor-driven test, the measured peak motor torque was reduced up to 90% and 72.8% during the downward and upward motions, respectively, and the power reduction rate of the driving motor could achieve up to 86.5% within the overall range of motion.
A New Robustness Metric for Robust Design Optimization Under Time- and Space-Dependent Uncertainty Through Metamodeling
Authors: Wei Xinpeng , Du Xiaoping 
Published: November 2019

Abstract
Product performance varies with respect to time and space in many engineering applications. This work discusses how to measure and evaluate the robustness of a product or component when its quality characteristics are functions of random variables, random fields, temporal variables, and spatial variables. At first, the existing time-dependent robustness metric is extended to the present time- and space-dependent problem. The robustness metric is derived using the extreme value of the quality characteristics with respect to temporal and spatial variables for the nominal-the-better type quality characteristics. Then a metamodel-based numerical procedure is developed to evaluate the new robustness metric. The procedure employs a Gaussian Process regression method to estimate the expected quality loss that involves the extreme quality characteristics. The expected quality loss is obtained directly during the regression model building process. Three examples are used to demonstrate the robustness analysis method. The proposed method can be used for robustness assessment during robust design optimization under time- and space-dependent uncertainty.
The Impact of Industry Experience on Engineering Graduate Students’ Functional Design Modeling
Authors: Bohm Matt , Ingram Hannah , Reith Dalton , Nagel Robert , Linsey Julie 
Published: November 2019

Abstract
Understanding the differences in functional models between traditional full-time graduate students and graduate students working in industry may allow for a deeper understanding of the impact of an engineer’s work on their ability to model a system in terms of its functions. To explore these differences, the researchers assigned two groups of students the task of creating a functional model of a can opener. One group of graduate students was traditional full-time graduate students while the other group was comprised of graduate students who are actively working in industry as engineers in the consumer appliance sector. This paper explores both the mechanics and plausibility behind the functional models created by the two groups of students and the impact of the industry standard parameter diagrams on the functional models of the graduate students’ working in industry.
After an initial analysis of the data, the researchers noticed an abnormal trend of the industry students to include more information beyond the common functional model elements which affected their models’ logical plausibility. Because this trend seemed to occur in higher quantities in the industry students’ functional models than the traditional graduate students’ models, the researchers decided to evaluate both groups’ functional models with a rubric developed for parameter diagrams — a model format common to the industry in which the industry students were employed. After re-analyzing the functional models of both groups using the parameter diagram rubric, it was observed that the industry students’ functional models did indeed include higher traces of parameter diagrams than the average graduate student. The researchers believe this may have been due to design fixation and incomplete conceptual change in practicing engineers. Implications of this finding are discussed herein.
A Conceptual Framework and a Research Roadmap Towards Enhancing Team Working in Engineering Education
Authors: Takai Shun , Esterman Marcos 
Published: November 2019

Abstract
While design processes have been studied for many years, relationships among design team characteristics, teamwork, and team performance have not yet been fully understood. As such, there is no consensus on how to form design teams or enhance teamwork. In this paper, we propose a conceptual design-team effectiveness model based on team effectiveness theory in which we divide team process into two components: team member collaboration and design process. Built on this model, we then present a six-step research roadmap towards enhancing teamwork in engineering education by 1) improving methodology to form design teams and 2) finding a team-building design exercise to promote team member collaboration. We propose to improve team formation methodology by 1) comprehensively studying associations among team factors and team performance and 2) investigating how associations among team factors and team performance change with team-building design exercises. Together, we expect both team performance and team member collaboration to improve, which should lead to a better teamwork experience in engineering education.
On Nonlinear Dynamics and Control of an Inverted Flexible Pendulum System With Chaos
Authors: Kahar Hartiny , Söffker Dirk 
Published: November 2019

Abstract
In this paper, the dynamical behavior of a nonlinear mechanical system is considered, namely an inverted flexible pendulum excited in its base by a cart driven by a motor. In this experimental procedure, the chaotic motion of the pendulum tip was identified, in combination with a specific range of parameters. Time-frequency energy analysis is performed to be used for modeling the transition between the equilibria of the chaotic systems. Controlling the chaotic behavior of the system is realized using impulsive control method, where additive impulses are injected into the system, designed with specific impulses energy content at a specific frequency band. The experimental results are presented and discussed in detail, concentrating on how the designed impulses have to be injected to affect the system, specifically the transition between states of equilibria. The results from this experimental modeling procedure show that both additive impulse design and frequency filtering of the injected additive impulses are able to stimulate the equilibrium shift and therefore to control the chaotic behavior of the system.
Actuator Rate Limit Effects on Proportional-Integral Controller for First-Order Plus Time-Delay Systems
Authors: Wu Zhenlong , Yuan Jie , Li Donghai , Xue Yali , Chen YangQuan 
Published: November 2019

Abstract
Actuator rate limit deteriorates control performance with amplitude attenuation and phase delay, and may lead to system instability in process control. In this paper, great challenges for first-order plus time delay (FOPTD) systems are concerned. Based on the preliminary knowledge of the definition of rate limiter, the concept of closed-loop onset frequency with rate limiter and classic proportional-integral (PI) tuning rules, the rate limit effects on PI controller are analyzed by simulations. The results show that the rate limiter has significant influence on the stability regions of PI parameters which can be reduced greatly. Besides, PI tuning rules with the same robustness constraint can be obviously effected where Skogestad internal model (SIMC) tuning rule is more robust to the rate limit variation than that of maximize the integral gain (Åström) and robustness constrained optimization (DRO) tuning rule. These results can offer a guideline to tune PI parameters when actuators have non-ignorable rate limit for industrial applications.
Defining the Space of Feasible Transmission Designs for Retrofitting a Rear-Wheel-Drive Automobile With a Power Split CVT
Authors: Vermillion Sean D. 
Published: November 2019

Abstract
In this paper, we describe a strategy for modeling the feasible set of power-split continuously variable transmission (CVT) system designs for retrofitting rear-wheel-drive consumer automobiles. A design is considered feasible if it produces a higher fuel economy than the stock vehicle’s fuel economy rating. Towards modeling the feasible set of designs, we first model a vehicle with a power-split CVT system taking into account the system’s mass and CVT efficiency. In this model, the effective design variables are the mass of the transmission system, the CVT functional efficiency, and effective gear ratio defining the allowable power split through and around the CVT. We formulate the set of feasible design solutions utilizing a multiobjective optimization problem to define the boundaries of the maximum allowable system mass, minimum allowable efficiency, and minimum allowable effective gear ratio. We solve this multiobjective optimization problem using NSGA-II and fit a quadratic model to the NSGA-II results to define a surrogate model of the feasible design set. We show that this surrogate modeling approach is sufficient for predicting the feasibility of a candidate transmission design.
Multi-Resolution Energy Strategy for Battery Management System of Unmanned Ground Vehicles in Agriculture
Authors: Wang Yanan , Tian Junwei , Niu Haoyu , Wang Peng , Liao Xiaozhong , Chen Yangquan 
Published: November 2019

Abstract
This paper has proposed a multi-resolution energy strategy for battery management system (BMS) of unmanned ground vehicles (UGVs) in farming. On the basis of “Smart Farm” definition, battery energy consumption and management have been taken into consideration during the working process and system control. A battery energy controller has been proposed for the low-cost ($1000) UGVs designed by our lab for farming usage. Moreover, three levels of energy control loops have been developed, that is, motor control, path planning, and mission arrangement. In this way, an energy-efficient UGV can prolong its working time and also decrease the cost. The three closed-loop energy strategy of BMS provides not only separate working methods for the three levels, but also a weights way to adjust the influence of three levels on the performance of the UGV in different tasks.
On the Effect of Glassy Coatings on the Wear of a Sliding Contact via Multiphysics Modeling
Authors: Michopoulos John G. , Iliopoulos Athanasios P. , Steuben John C. , Birnbaum Andrew J. , Apetre Nicole A. 
Published: November 2019

Abstract
A recently developed multiphysics computational framework is exercised to predict the wear behavior of two deformable and heat conducting bodies under conditions of sliding contact. This framework enables the solution of a high dimensional thermo-mechanical problem simultaneously and tightly coupled with the associated wear evolution models for each of the wear pair bodies, thus enabling predictions of wear for both of them. Two distinct slider-base pairs are modeled. The first involves an aluminum alloy slider and a copper alloy base. The second is a pair identical to the first except it contains a thin strip of soda lime glass embedded in the surface of the base. The objective of this effort is to establish the effects of this glass layer on the wear of all participating bodies in comparison to the pair that does not contain this layer. The results indicate that while the glass layer has a wear mitigation effect for the stationary base it slightly increases the wear of the slider when compared with the respective bodies when the glass is not present.
Deep Reinforcement Learning for Transfer of Control Policies
Authors: Cunningham James D. , Miller Simon W. , Yukish Michael A. , Simpson Timothy W. , Tucker Conrad S. 
Published: November 2019

Abstract
We present a form-aware reinforcement learning (RL) method to extend control knowledge from one design form to another, without losing the ability to control the original design. A major challenge in developing control knowledge is the creation of generalized control policies across designs of varying form. Our presented RL policy is form-aware because in addition to receiving dynamic state information about the environment, it also receives states that encode information about the form of the design that is being controlled. In this paper, we investigate the impact of this mixed state space on transfer learning. We present a transfer learning method for extending a control policy to a different design form, while continuing to expose the agent to the original design during the training of the new design. To demonstrate this concept, we present a case study of a multi-rotor aircraft simulation, wherein the designated task is to achieve a stable hover. We show that by introducing form states, an RL agent is able to learn a control policy to achieve the hovering task with both a four rotor and three rotor design at once, whereas without the form states it can only hover with the four rotor design. We also benchmark our method against a test case that removes the transfer learning component, as well as a test case that removes the continued exposure to the original design to show the value of each of these components. We find that form states, transfer learning, and parallel learning all contribute to a more robust control policy for the new design, and that parallel learning is especially important for maintaining control knowledge of the original design.
Product Service System Design in New Situations: Prediction of Demand Surfaces From Environment
Authors: Watson Bryan C. , Telenko Cassandra 
Published: November 2019

Abstract
Product service systems (PSS), such as DVD rental stations or the subway, face a unique problem slowing their adoption and growth: they are uniquely dependent upon timely or expensive user data for system planning, yet user datasets are only accurate for a small part of the entire PSS. Thus, methods to use the available data effectively and use data collected in one portion of a PSS for system design in another portion could transform PSS design. PSS allow customers to purchase use of a product rather than the product itself, resulting in improved environmental sustainability. The central question examined by this work is: how can designers compensate for situations where the design environment has changed and limited user data is available to inform demand estimations? Our hypothesis is that publicly available socio-demographic and environmental variables can be used to estimate the demand outside of the boundaries previously constrained by available user data. This approach was validated by applying multivariable regressions to a major Bike Share System (BSS) Expansion, outperforming the methods utilized by the BSS operators. The approach is tested in four different design scenarios. When examining all 174 stations added in 2015, our approach shows a moderate correlation with the ideal ordering (Rho = .566, Stations = 174, p &lt; .01), while the implemented operator ordering was only weakly correlated (Rho = .334, Stations = 174, p &lt; .01). This work demonstrates a partial solution to the problem of transforming available user data into demand for new situations.
Nonlinear Dynamics of Nonlinear L-Shape Piezoelectric Systems for Positive and Reverse Sweep Waveform
Authors: Yao Ming Hui 
Published: November 2019

Abstract
This paper presents a bistable inverted L-shaped piezoelectric beam power generation structure, and its dynamic behaviors and power generation performance are studied by positive and reverse sweep waveform experiments. The piezoelectric beam includes the substructure layer and the piezoelectric layer. The material of the piezoelectric layer is the piezoelectric ceramic transducer (PZT), and the material of the substructure layer is the phosphor brass. The positive and reverse sinusoidal excitation signal is selected. The snap through phenomenon and stiffness characteristic of the system are investigated by experimental results of the positive and reverse sweep waveform. The relationship between dynamic behaviors and electrical behaviors of the system is also studied. Experimental results show that the positive and reverse sweep waveform has a great influence on vibration of the nonlinear system. Due to the hard spring characteristic of the system, the large vibration amplitude is easy to appear in the positive sweep waveform. Dynamic behaviors of the piezoelectric system are related to its electrical behaviors. When dynamic behaviors bifurcate, electrical behaviors bifurcate. These results can be applied to explore the vibration characteristic and the power generation of the nonlinear piezoelectric system.
Reinforcement Learning Content Generation for Virtual Reality Applications
Authors: Lopez Christian E. , Ashour Omar , Tucker Conrad S. 
Published: November 2019

Abstract
This work presents a Procedural Content Generation (PCG) method based on a Neural Network Reinforcement Learning (RL) approach that generates new environments for Virtual Reality (VR) learning applications. The primary objective of PCG methods is to algorithmically generate new content (e.g., environments, levels) in order to improve user experience. Researchers have started exploring the integration of Machine Learning (ML) algorithms into their PCG methods. These ML approaches help explore the design space and generate new content more efficiently. The capability to provide users with new content has great potential for learning applications. However, these ML algorithms require large datasets to train their generative models. In contrast, RL based methods take advantage of simulation to train their models. Moreover, even though VR has become an emerging technology to engage users, there have been few studies that explore PCG for learning purposes and fewer in the context of VR. Considering these limitations, this work presents a method that generates new VR environments by training an RL agent using a simulation platform. This PCG method has the potential to maintain users’ engagement over time by presenting them with new environments in VR learning applications.
An Origami Crease Pattern Generating Methodology for “Origami 3D Printer”
Authors: Yang Yang , Hagiwara Ichiro , Diago Luis , Shinoda Junichi 
Published: November 2019

Abstract
The additive 3D printer (hereafter called Add-3D) creates a 3D object with materials being added together layer by layer. Before printing an object, some professional processes are indispensable, such as creating the 3D printable models by computer-aided design (CAD), or 3D scanner, and STL data modification, which are difficult for normal families. As we know, primordially, origami is the ancient art of folding a flat-piece of paper into a 3D shape, that even can be played by kids. So we aim to develop an Origami 3D printer (hereafter called Ori-3D) that can be used by ordinary families with the features of effort and no size limit of model. In Ori-3D, the object is constructed by human hands or by an Origami robot using 2D patterns generated from 3D data (obtained from photos or CAD). Ori-3D includes the following steps: 1) the surface of an object is segmented to several developable surfaces as large as possible using segmentation technique which is used in reverse engineering system. 2) Each developable surface is developed to 2D pattern with mountain & valley lines and glue parts. 3) The 2D crease pattern is optimized by a tree structure method to be easily folded by an Origami Robot. 4) With Origami robot, the object is easily constructed from the improved 2D crease pattern. This paper focuses on discuss the steps 1∼ 3: generation of the 2D crease pattern.