bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparative Study of Formulations and Algorithms for Reliability-Based Co-Design Problems
Authors: Cui Tonghui , Allison James T. , Wang Pingfeng 
Published: November 2019

Abstract
Co-design, or integrated physical and control system design, has been demonstrated successfully for several engineering system design optimization applications, primarily in a deterministic manner. An opportunity exists to study non-deterministic co-design strategies, including incorporation of uncertainty-induced failures, into an integrated co-design framework. Reliability-based design optimization (RBDO) is one such method that can be used to increase the likelihood of having a feasible design that satisfies all reliability constraints. While significant recent advancements have been made in co-design and RBDO separately, limited work has been done where reliability-based dynamic system design and control design optimization are considered jointly. In this paper, the co-design problem is integrated with the RBDO framework to yield a system-optimal design and the corresponding control trajectory, which satisfy all reliability constraints in the presence of parameter variations. Different problem formulations and RBDO algorithms are compared through numerical examples. The design of a horizontal-axis wind turbine (HAWT) supported by a lattice tower (with parameter uncertainties) is presented to demonstrate the applicability of the proposed method.
Computing Poincaré-Lyapunov Constants via Carleman Linearization
Authors: Hubay Csanád Árpád , Kalmár-Nagy Tamás 
Published: November 2019

Abstract
Using Carleman linearization an approximation is given for the solution of a system at Hopf bifurcation. The values of the Poincaré-Lyapunov constants (whether they are zero or not) affect the linear algebraic properties of the Carleman matrix and they appear in solvability conditions (through the Fredholm alternative). We provide a linear algebra based algorithm to compute the Poincaré-Lyapunov constants.
Estimating the Value of Excess: A Case Study of Gaming Computers, Consoles and the Video Game Industry
Authors: Yadav Darshan , Long Daniel , Morkos Beshoy , Ferguson Scott 
Published: November 2019

Abstract
A widely held belief among design practitioners is that an ideal design solution is the one that meets all the requirements while minimizing surplus cost incurred by exceeding requirements. In this research, we challenge this notion by exploring if providing design “excess”, the ability of a solution to exceed certain requirements, can increase the value of a solution to its end users. A case study is performed in the video game industry to explore if design excess is prevalent and its impact on the industry. This study is performed by examining various PC builds (budget, mid-range, and high-end dream) and gaming consoles (Microsoft Xbox and Sony PlayStation) over an 18-year period. Based on a thorough investigation of video game requirements and capacity of different hardware, we find that design excess has existed in computer hardware and is intentionally used as a design property. The results indicate that mid-range solution provide the greatest value to its customers. Further, PC excess based value is adjusted during years when consoles are released. Using measurements of excess, this study also reveals a shift in technology push versus pull that occurs during the mid-2000s and is observable through the lens of system excess.
Using Semantic Fluency Models Improves Network Reconstruction Accuracy of Tacit Engineering Knowledge
Authors: Sexton Thurston , Fuge Mark 
Published: November 2019

Abstract
Human- or expert-generated records that describe the behavior of engineered systems over a period of time can be useful for statistical learning techniques like pattern detection or output prediction. However, such data often assumes familiarity of a reader with the relationships between entities within the system — that is, knowledge of the system’s structure. This required, but unrecorded “tacit” knowledge makes it difficult to reliably learn patterns of system behavior using statistical modeling techniques on these written records. Part of this difficulty stems from a lack of good models for how engineers generate written records of a system, given their expertise, since they often create such records under time pressure using shorthand notation or internal jargon. In this paper, we model the process of maintenance work order creation as a modified semantic fluency task, to build a probabilistic generative model that can uncover underlying relationships between entities referenced within a complex system. Compared to more traditional similarity-metric-based methods for structure recovery, we directly model a possible cognitive process by which technicians may record work-orders. Mathematically, we represent this as a censored local random walk over a latent network structure representing tacit engineering knowledge. This allows us to recover implied engineering knowledge about system structure by processing written records. Additionally, we show that our model leads to improved generative capabilities for synthesizing plausible data.
Machine Learning Driven Individualized Gait Rehabilitation: Classification, Prediction, and Mechanism Design
Authors: Loya Amol , Deshpande Shrinath , Purwar Anurag 
Published: November 2019

Abstract
Design of mechanisms for human-machine interaction involves numerous subjective criteria and constraints in addition to the kinematic task. This is particularly important for the rehabilitation devices, where the size, complexity, weight, cost, and ease of use are critical factors. A large majority of the approaches towards the design of such devices, which are based on limited degree-of-freedom mechanisms start with finding numerically optimal solutions to the task path followed by pruning for feasible design concepts. Given the highly nonlinear nature of the problem, this approach discards a large proportion of numerically sub-optimal solutions, which could potentially be pragmatically optimal solutions if the subject criteria were applied from the start. To overcome this limitation, in this paper, we present an end-to-end computational approach for developing a device for individualized gait rehabilitation using machine learning techniques focusing on gait classification, prediction, and specialized device design. These models generate a distribution of linkage mechanisms, which strongly correlate to the distribution of target path variations. This way of formulating the problem results in a large variety of solutions to which subjective criteria can be applied to yield practically useful design concepts that would otherwise not be possible using traditional synthesis methods.
Establishing Baseline Performance for Off-the-Shelf Nitrile Seals for the India Mark II Hand Pump System
Authors: Ottosson Hans J. , Naylor Thomas A. , Johnson Oliver K. , Mattson Christopher A. 
Published: November 2019

Abstract
Accessing clean water is a persistent, and life threatening, challenge for millions of people in the world. Mechanical hand pumps have a long history of helping people access clean ground water for drinking and daily use. Among the most ubiquitous are the India Mark II and III pump systems, for which there are more than 4,000,000 installed across the world. These are estimated to serve between 600M and 1B people. All pumps degrade in performance over time, requiring service; many do not receive it causing pumps to become dysfunctional. The purpose of this paper is to establish a baseline for nitrile seal performance of India Mark II hand pump systems. Understanding off-the-shelf performance and using it as a baseline is an important step toward understanding degradation of performance over time, which is the focus of a much larger study to understand — mechanically and socially — how hand pumps perform, degrade, and ultimately meet human needs. In this paper, 110 off-the-shelf nitrile seals that were purchased in Uganda were tested and the following was characterized: (i) geometric variation, (ii) material variation, (iii) leak performance, and (iv) correlation between these. The seal leak performance was found to be very robust to variations in geometry and material at zero cycles. This important baseline supports our future work to understand how and to what degree seals become sensitive to geometric and material degradation during use.
Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks
Authors: Nie Zhenguo , Jiang Haoliang , Kara Levent Burak 
Published: November 2019

Abstract
The demand for fast and accurate structural analysis is becoming increasingly more prevalent with the advance of generative design and topology optimization technologies. As one step toward accelerating structural analysis, this work explores a deep learning based approach for predicting the stress fields in 2D linear elastic cantilevered structures subjected to external static loads at its free end using convolutional neural networks (CNN). Two different architectures are implemented that take as input the structure geometry, external loads, and displacement boundary conditions, and output the predicted von Mises stress field. The first is a single input channel network called SCSNet as the baseline architecture, and the second is the multi-channel input network called StressNet. Accuracy analysis shows that StressNet results in significantly lower prediction errors than SCSNet on three loss functions, with a mean relative error of 2.04% for testing. These results suggest that deep learning models may offer a promising alternative to classical methods in structural design and topology optimization. Code and dataset are available at https://github.com/zhenguonie/stress_net.
Dynamic Analysis of Multiple Launch Rocket System Under the Action of Jet Flow
Authors: Li Shutian , Wang Guoping , Miao Yunfei , Rui Xiaoting 
Published: November 2019

Abstract
Jet flow is one of the important factors affecting the vibration, initial disturbance and firing dispersion of Multiple Launch Rocket System (MLRS). In this research, based on the rocket gas jet dynamics, MLRS launch dynamics theory and transfer matrix method for multibody system, a physical model of jet flow model and a MLRS launch dynamics model considering the multiple launch rocket device and the launch of rocket are built. The launching dynamic process of rocket jet flow of MLRS is numerical simulated by using the technology of overset mesh and the Computational Fluid Dynamics (CFD) methods. The nephogram of mach number and contour map of velocity are obtained. The impact effect force on the air-facing surface of rocker launcher after the rocket slides and leaves the directional barrel is acquired. Regarding the calculated data of impact force to MLRS as external force, the MLRS launch dynamics equation is solved by using the transfer matrix method for multibody system. Finally, the dynamics response of MLRS under the effect of jet flow is analyzed.
Development and Experimental Evaluation of a Quad-Tilt-Wing Flying Robot Platform
Authors: Aihaitijiang A. , Onal Cagdas D. 
Published: November 2019

Abstract
In this paper, we present the mechanical design and control system of a new indoor and outdoor Quad-Tilt-Wing flying robot. The proposed flying robot can achieve vertical takeoff, hovering, and long duration horizontal high-speed flight. All of these flight modes can be achieved by simply changing the angle of the rotors and wings by a tilt mechanism. We present the details on design and prototyping, the attitude control system, and experimental results, including wind-tunnel experiments, full flight tests, and performance tests. The experimental results show that our Quad-Tilt-Wing flying robot successfully achieves full conversion flight: vertical and rapid takeoff, high-speed cruise, and vertical landing. Performance test results show that during horizontal flight, the wings generate lift and effectively reduce energy use compared to a fixed quad rotor architecture. Consequently, the proposed platform combines unique features of multi-rotor and fixed wing systems to achieve long-duration flight with low-energy compared to a conventional multi-rotor UAV.
On Quality Factor Improvement in a NEMS Resonator With Nonlinear Damping
Authors: Ramakrishnan Subramanian , Shougat Md Raf E Ul 
Published: November 2019

Abstract
Nonlinear damping effects have been reported in experiments on nanoelectromechanical (NEMS) resonators and suggested as a pathway to improve the quality (Q) factors of the resonators. In particular, in a nonlinearly damped Duffing NEMS resonator operating in the hardening regime, it has been shown that white noise excitation can shrink the hysteresis region resulting in higher Q factors. In this paper the authors: (1) find that an analytical expression they previously derived using the method of harmonic balance for the frequency-amplitude relationship of a weakly-excited, nonlinearly damped Duffing NEMS resonator is valid for strong excitation, (2) show analytically and verify numerically that for constant values of the nonlinear damping coefficient, higher amplitude of forcing leads to increase in the resonant frequency, (3) find that white-noise induced stochastic parametric excitation can lead to enhanced Q factors and (4) show that decreasing the nonlinear damping coefficient leads to higher Q-factor. The results, in addition to being theoretically significant, are expected to be important in sensing applications using NEMS resonators.
3D Shape Synthesis for Conceptual Design and Optimization Using Variational Autoencoders
Authors: Zhang Wentai , Yang Zhangsihao , Jiang Haoliang , Nigam Suyash , Yamakawa Soji , Furuhata Tomotake , Shimada Kenji , Kara Levent Burak 
Published: November 2019

Abstract
We propose a data-driven 3D shape design method that can learn a generative model from a corpus of existing designs, and use this model to produce a wide range of new designs. The approach learns an encoding of the samples in the training corpus using an unsupervised variational autoencoder-decoder architecture, without the need for an explicit parametric representation of the original designs. To facilitate the generation of smooth final surfaces, we develop a 3D shape representation based on a distance transformation of the original 3D data, rather than using the commonly utilized binary voxel representation. Once established, the generator maps the latent space representations to the high-dimensional distance transformation fields, which are then automatically surfaced to produce 3D representations amenable to physics simulations or other objective function evaluation modules. We demonstrate our approach for the computational design of gliders that are optimized to attain prescribed performance scores. Our results show that when combined with genetic optimization, the proposed approach can generate a rich set of candidate concept designs that achieve prescribed functional goals, even when the original dataset has only a few or no solutions that achieve these goals.
Cost Effective On-Site Fault Diagnosis Home Appliance Using a Smart Phone and Support Vector Machine
Authors: Baek Ji Min , Lee Kyeong Ha , Lee Seung Ho , Koo Ja Choon 
Published: November 2019

Abstract
One of the common rotating machines of the consumer electronics might be a washing machine. The rotating machinery normally suffers mechanical failures even during daily operations that results in poor performance or shortening lifetime of the machine. Therefore, engineers have been interested in the earliest fault diagnosis of the rotating machine. Existing fault diagnosis methods for rotating machines have used fast fourier transform (FFT) method in frequency domain to detect abnormal frequency. However, it is difficult to diagnose using the FFT method if the normal frequency components of the rotating machines overlaps with the fault frequencies. In this paper, sets of acoustic signals generated by the washing machines are collected by using a smart phone in which an inexpensive microphone is equipped, and collected data are analyzed using a new algorithm, which combining the skewness, kurtosis, A-weighting filter, high-pass filter (HPF), and FFT. The analyzed data is applied to support vector machine (SVM) to determine defect existence. The proposed algorithm solves the disadvantages of the existing method and is accurate enough to discriminate the data collected by the cheap microphone of the smart phone.
Numerical and Experimental Investigation of Nanoscale Heat Transfer in the Head-Media Interface During Static Touchdown
Authors: Sakhalkar Siddhesh V. , Cheng Qilong , Ma Yuan , Ghafari Amin , Bogy David B. 
Published: November 2019

Abstract
With minimum fly height of less than 10 nm in contemporary hard-disk drives, understanding nanoscale heat transfer at the head-media interface is crucial for developing reliable head and media designs. Particularly, with the emergence of Heat-Assisted Magnetic Recording (HAMR) and Microwave-Assisted Magnetic Recording (MAMR), head failure due to overheating has become an increasing concern. There is a need to develop a methodology to use theoretical curves for spacing-dependent nanoscale heat transfer coefficient to predict head and media temperatures in actual hard disk drives. In this study, we present a numerical model to simulate the head and media temperature profiles during static touchdown and compare our results with experiments performed with a magnetic head on a silicon wafer. As the head approaches touchdown with increasing TFC power, the phonon conduction heat transfer coefficient between the head and the substrate increases exponentially, causing a drop in the head temperature vs TFC power curve. Our model shows that the introduction of van der Waals forces between the head and the substrate causes a steeper drop in the head temperature curve and ensures a good quantitative match with experimental results.
Optimizing Production Facilities Using a Transient Multiphase Flow Simulator
Authors: Al-Qasim Abdulaziz S. , Almudairis Fahad , Bin Omar Abdulrahman , Omair Abdullatif 
Published: November 2019

Abstract
This paper discusses a method for optimizing production facilities design for onshore/offshore wells during new field development. Optimizing the development of new oil and gas fields necessitates the use of accurate predication techniques to minimize uncertainties associated with day-to-day operational challenges related to wells, pipelines and surface facilities. It involves the use of a transient multiphase flow simulator (TMFS) for designing new oil and gas production systems to determine the feasibility of its economic development.
A synthetic offshore oil field that covers a wide range of subsurface and surface facility data is considered in this paper. 32 wells and two reservoirs are considered to evaluate the effect of varying sizes of tubing, wellhead choke, flowline, riser, and transport line. A detailed investigation of the scenario of emergency shutdowns to study its effect on the system is performed using TMFS. Other scenarios are also evaluated such as startup, depressurization, pigging, wax deposition, and hydrate formation.
This paper provides a method to minimize the cost by selecting the optimum pipelines sizes and diameters, and investigating the requirements of insulation, risk of pipeline corrosions and other related flow assurance parameters. Different facility design scenarios are considered using TMFS tool to achieve operational flexibility and eliminate associated risks. Pressure and temperature conditions are evaluated under several parametric scenarios to determine the best dimensions of the production system. This paper will also provide insight into factors affecting the flow assurance of oil and gas reservoirs.
Flow-Induced Vibration Analysis of a Water Injection System at Elevated Flow Rates of an FPSO
Authors: González Díez Néstor , Pontaza Juan P. , Awe Oluwaseun M. , van Beek Pieter , Tümer Can 
Published: November 2019

Abstract
The water injection system of an FPSO active in the Gulf of Guinea is to increase injection capacity to levels that are threatening from a flow-induced vibration perspective, such that hydrocarbon recovery can be accelerated. A three-tier method based on the internal guidelines of the system operator has been employed to assess the level of FIV threat expected from the increase in flow rate. A high-level screening analysis is followed by a more detailed approach, modified in this case by introducing knowledge obtained from field data gathered during a comprehensive measurement campaign aboard the FPSO. In particular, the data has been used to calibrate the finite element model of the mechanical layout of the pipework and associated supporting by making use of an optimization technique. The PSD of the flow excitation has been calibrated to match the measured response of the system, with descriptions of the turbulent excitation introduced in elbows by means of PSD functions available in the open literature. The PSDs, once calibrated, are further scaled to the future flow-rates so that they can be used as input to the mechanical response analysis. Though the high-level screening analysis delivers the conclusion that flow rates should be limited, the detailed analysis proves that the expected vibrations will be acceptable.
Thorough Verification and Validation of CFD Simulation for FPSO Roll Damping
Authors: Lee Donghwan , Huang Zhenjia (Jerry) 
Published: November 2019

Abstract
For floating production platform such as FPSO and FLNG, it is important to use confidently estimated roll damping coefficients in the prediction of its motions in waves since in many cases the roll response is mainly contributed from resonance. Traditionally roll damping prediction was made through model tests or empirical formulas. As computing power and numerical modeling techniques have been improved during last a few decades, offshore industry starts to consider CFD as an alternative engineering and design tool complementary and/or supplementary to physical model tests. This paper presents our verification and validation work of modeling practices with commercially available CFD software for engineering applications for FPSO roll decay damping in calm water. The numerical modeling followed a recommended modeling practice developed by a Joint Development Project – TESK JDP [1].