bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designing Optimal Arbitrage Policies for Distributed Energy Systems in Building Clusters Using Reinforcement Learning
Authors: Odonkor Philip , Lewis Kemper 
Published: November 2019

Abstract
In the wake of increasing proliferation of renewable energy and distributed energy resources (DERs), grid designers and operators alike are faced with several emerging challenges in curbing allocative grid inefficiencies and maintaining operational stability. One such challenge relates to the increased price volatility within real-time electricity markets, a result of the inherent intermittency of renewable energy. With this challenge, however, comes heightened economic interest in exploiting the arbitrage potential of price volatility towards demand-side energy cost savings. To this end, this paper aims to maximize the arbitrage value of electricity through the optimal design of control strategies for DERs. Formulated as an arbitrage maximization problem using design optimization, and solved using reinforcement learning, the proposed approach is applied towards shared DERs within multi-building residential clusters. We demonstrate its feasibility across three unique building cluster demand profiles, observing notable energy cost reductions over baseline values. This highlights a capability for generalized learning across multiple building clusters and the ability to design efficient arbitrage policies towards energy cost minimization. Finally, the approach is shown to be computationally tractable, designing efficient strategies in approximately 5 hours of training over a simulation time horizon of 1 month.
Second-Order Reliability Method Based on Edgeworth Expansion With Application to Reliability-Based Design Optimization
Authors: Mansour Rami , Olsson Mårten 
Published: November 2019

Abstract
In the Second-Order Reliability Method, the limit-state function is approximated by a hyper-parabola in standard normal and uncorrelated space. However, there is no exact closed form expression for the probability of failure based on a hyper-parabolic limit-state function and the existing approximate formulas in the literature have been shown to have major drawbacks. Furthermore, in applications such as Reliability-based Design Optimization, analytical expressions, not only for the probability of failure but also for probabilistic sensitivities, are highly desirable for efficiency reasons. In this paper, a novel Second-Order Reliability Method is presented. The proposed expression is a function of three statistical measures: the Cornell Reliability Index, the skewness and the Kurtosis of the hyper-parabola. These statistical measures are functions of the First-Order Reliability Index and the curvatures at the Most Probable Point. Furthermore, analytical sensitivities with respect to mean values of random variables and deterministic variables are presented. The sensitivities can be seen as the product of the sensitivities computed using the First-Order Reliability Method and a correction factor. The proposed expressions are studied and their applicability to Reliability-based Design Optimization is demonstrated.
Experimental Study of Cochlear Dynamics With an Intracochlear Acoustic Micro-Actuator
Authors: Taylakov Sergiy , Shen I. Y. 
Published: November 2019

Abstract
An intracochlear lead-zirconate-titanate (PZT) micro-actuator can complement a cochlear implant electrode array to rehabilitate hearing loss patients with enhanced speech recognition. The presence of the intracochlear micro-actuator has significantly altered the cochlear dynamics, because the actuation now results from the micro-actuator instead of the stapes. To understand sound induction mechanisms by the micro-actuator, we design a test rig that mimics the box model of a human cochlea. The test rig consists of two connected fluid canals, one aluminum membrane sandwiched between the canals, and a PZT thin-film micro-actuator. Frequency response functions of the micro-actuator and the aluminum membrane are measured using a laser Doppler vibrometer and a spectrum analyzer. Measurements are taken when the micro-actuator is in air, in a petri dish surrounded by oil, and in the fluid canals inside the test rig. When the micro-actuator is moved from the petri dish (i.e., an open environment) to the inside of the fluid canals (i.e., a closed environment), the natural frequency and static gain of the micro-actuator both drop significantly indicating substantial increase in stiffness and inertia. A possible reason for the change, which remains to be confirmed, is the squeeze film effect from the fluid between the micro-actuator and the aluminum membrane.
Transient Vibrations of Two-Dimensional Beam Frames at Mid- and High-Frequencies
Authors: Zhang Yichi , Yang Bingen 
Published: November 2019

Abstract
Transient vibrations of flexible structures at mid- and high-frequencies have important applications in aerospace, civil, auto and ship engineering. In this paper, a new method is developed for the determination of the transient vibration solutions of two-dimensional beam frames in mid- and high-frequency regions. In the development, the governing equations of a beam frame structure are formulated by an augmented Distributed Transfer Function Method (DTFM), without the need for discretization and approximation. The augmented DTFM differs from the traditional DTFM in that it does not contain the singularities of subsystem transfer functions, which is crucially important in a mid- or high-frequency analysis. The proposed method delivers exact eigensolutions of a beam structure from low- to high-frequencies without numerical instability. With the platform provided by the augmented DTFM, the transient response of a beam structure can be conveniently estimated by either modal expansion or the residue formula for inverse Laplace transform. A highlight of the augmented DTFM lies in that detailed information at mid- and high-frequencies, such as local displacement, slope, bending moment and shear force at any point, can be obtained, which otherwise may be difficult with conventional methods for mid- and high-frequency analysis. The proposed method is illustrated on several examples and is computationally efficient and stable from low- to high-frequency regions. In the numerical simulation, the augmented DTFM is shown to produce more accurate results than traditional finite element analysis (FEA). The proposed method is extensible to three-dimensional beam structures.
Research Based and Design Based Education: Experiences in India, UK, and USA
Authors: Naidu Jyoti Prakash , Govindasamy Siddhartan , Srinivasan Mandayam A. 
Published: November 2019

Abstract
The paper presents the recent trends and experiments being attempted in India, United Kingdom and the United States aimed at enhancing values from the approaches of Research based teaching-learning as well as Design based teaching-learning methodologies. Based on the authors’ preliminary first hand experiences and investigations on the approaches reported by peers, the paper brings out the constraints, difficulties and challenges in implementation of relatively well established steps followed in the western system of higher education, in the eastern societies. The paper further deliberates upon possible hybridization by blending of approaches followed earlier with the intended changes in pedagogy.
A Collaborative Visual Localization Scheme for a Low-Cost Heterogeneous Robotic Team With Non-Overlapping Perspectives
Authors: Abruzzo Benjamin , Cappelleri David , Mordohai Philippos 
Published: November 2019

Abstract
This paper presents and evaluates a relative localization scheme for a heterogeneous team of low-cost mobile robots. An error-state, complementary Kalman Filter was developed to fuse analytically-derived uncertainty of stereoscopic pose measurements of an aerial robot, made by a ground robot, with the inertial/visual proprioceptive measurements of both robots. Results show that the sources of error, image quantization, asynchronous sensors, and a non-stationary bias, were sufficiently modeled to estimate the pose of the aerial robot. In both simulation and experiments, we demonstrate the proposed methodology with a heterogeneous robot team, consisting of a UAV and a UGV tasked with collaboratively localizing themselves while avoiding obstacles in an unknown environment. The team is able to identify a goal location and obstacles in the environment and plan a path for the UGV to the goal location. The results demonstrate localization accuracies of 2cm to 4cm, on average, while the robots operate at a distance from each-other between 1m and 4m.
Overview of the Development and Enforcement of Process-Driven Manufacturability Constraints in Product Design
Authors: Patterson Albert E. , Lee Yong Hoon , Allison James T. 
Published: November 2019

Abstract
Design-for-manufacturing (DFM) concepts have traditionally focused on design simplification; this is highly effective for relatively simple, mass-produced products, but tends to be too restrictive for more complex designs. Effort in recent decades has focused on creating methods for generating and imposing specific, process-derived technical manufacturability constraints for some common problems. This paper presents an overview of the problem and its design implications, a discussion of the nature of the manufacturability constraints, and a survey of the existing approaches and methods for generating/enforcing the minimally restrictive manufacturability constraints within several design domains. Four major design perspectives were included in the study, including the system design (top-down), the product design (bottom-up), the manufacturing process-dominant approach (specific process required), and the part-redesign approach. Manufacturability constraints within four design levels were explored as well, ranging from macro-scale to sub-micro-scale design. Very little previous work was found in many areas but it is clear from the existing literature that the problem and a general solution to it are very important to explore further in future DFM and design automation work.
Domain Randomization for Detection and Position Estimation of Multiples of a Single Object With Applications to Localizing Bolts on Structures
Authors: Ameperosa Ezra , Bhounsule Pranav A. 
Published: November 2019

Abstract
Periodic replacement of fasteners such as bolts are an integral part of many structures (e.g., airplanes, cars, ships) and require periodic maintenance that may involve either their tightening or replacement. Current manual practices are time consuming and costly especially due to the large number of bolts. Thus, an automated method that is able to visually detect and localize bolt positions would be highly beneficial. In this paper, we demonstrate the use of deep neural network using domain randomization for detecting and localizing multiple bolts on a workpiece. In contrast to previous deep learning approaches that require training on real images, the use of domain randomization allows for all training to be done in simulation. The key idea here is to create a wide variety of computer generated synthetic images by varying the texture, color, camera position and orientation, distractor objects, and noise, and train the neural network on these images such that the neural network is robust to scene variability and hence provides accurate results when deployed on real images. Using domain randomization, we train two neural networks, a faster regional convolutional neural network for detecting the bolt and predicting a bounding box, and a regression convolutional neural network for estimating the x- and y-position of the bolt relative to the coordinates fixed to the workpiece. Our results indicate that in the best case we are able to detect bolts with 85% accuracy and are able to predict the position of 75% of bolts within 1.27 cm. The novelty of this work is in the use of domain randomization to detect and localize: (1) multiples of a single object, and (2) small sized objects (0.6 cm × 2.5 cm).
Using Virtual Reality to Test Human-Robot Interaction During a Collaborative Task
Authors: Etzi Roberta , Huang Siyuan , Scurati Giulia Wally , Lyu Shilei , Ferrise Francesco , Gallace Alberto , Gaggioli Andrea , Chirico Alice , Carulli Marina , Bordegoni Monica 
Published: November 2019

Abstract
The use of collaborative robots in the manufacturing industry has widely spread in the last decade. In order to be efficient, the human-robot collaboration needs to be properly designed by also taking into account the operator’s psychophysiological reactions. Virtual Reality can be used as a tool to simulate human-robot collaboration in a safe and cheap way. Here, we present a virtual collaborative platform in which the human operator and a simulated robot coordinate their actions to accomplish a simple assembly task. In this study, the robot moved slowly or more quickly in order to assess the effect of its velocity on the human’s responses. Ten participants tested this application by using an Oculus Rift head-mounted display; ARTracking cameras and a Kinect system were used to track the operator’s right arm movements and hand gestures respectively. Performance, user experience, and physiological responses were recorded. The results showed that while humans’ performances and evaluations varied as a function of the robot’s velocity, no differences were found in the physiological responses. Taken together, these data highlight the relevance of the kinematic aspects of robot’s motion within a human-robot collaboration and provide valuable insights to further develop our virtual human-machine interactive platform.
Exploiting the Asymmetric Energy Barrier in Multi-Stable Origami to Enable Mechanical Diode Behavior in Compression
Authors: Baharisangari Nasim , Li Suyi 
Published: November 2019

Abstract
Recently, multi-stable origami structures and material systems have shown promising potentials to achieve multi-functionality. Especially, origami folding is fundamentally a three-dimensional mechanism, which imparts unique capabilities not seen in the more traditional multi-stable systems. This paper proposes and analytically examines a multi-stable origami cellular structure that can exhibit asymmetric energy barriers and a mechanical diode behavior in compression. Such a structure consists of many stacked Miura-ori sheets of different folding stiffness and accordion-shaped connecting sheets, and it can be divided into unit cells that features two different stable equilibria. To understand the desired diode behavior, this study focuses on two adjacent unit cells and examines how folding can create a kinematic constraint onto the deformation of these two cells. Via estimating the elastic potential energy landscape of this dual cell system. we find that the folding-induced kinematic constraint can significantly increase the potential energy barrier for compressing the dual-cell structure from a certain stable state to another, however, the same constraint would not increase the energy barrier of the opposite extension switch. As a result, one needs to apply a large force to compress the origami cellular structure but only a small force to stretch it, hence a mechanical diode behavior. Results of this study can open new possibilities for achieving structural motion rectifying, wave propagation control, and embedded mechanical computation.
Dynamic Transformation of an Origami String Using a Stacked-Miura Cell
Authors: Liu Chang , Aung Zwe Min Htet , Felton Samuel M. 
Published: November 2019

Abstract
Origami engineering is a promising approach to transforming structures and machines due to its potential for geometric, kinematic, and mechanical complexity. However, actuating this transformation can be expensive, slow, and unreliable. In this paper, we demonstrate repeatable and reversible transformation of a two-vertex origami string between different configurations using a stacked-Miura cell as an actuation system. We characterize the snap-through behavior of the cell and show how the cell can be coupled to the string to generate drive repeatable transformations between different configurations. We then show how gravity can affect this process. The results indicate that bistable origami cells are a promising method for lightweight, repeatable transformation.
The Design of Robust Phase Oscillator for Wearable Robotic Systems
Authors: Fuente Juan De La , Subramanian Susheelkumar C. , Chinimilli Prudhvi Tej , Redkar Sangram , Sugar Thomas 
Published: November 2019

Abstract
This paper presents the design of a phase-based robust oscillator for wearable robots that assists the human performing periodic or repetitive tasks. The robustness of the phase oscillator controller is evaluated by finding bounds for perturbations that guaranteed the stability of the output. Then, the Lyapunov redesign method is applied to construct a robust controller using a bounding function which can handle the uncertainties such as noise and perturbations in the overall human-robot system. The robust controller produces a bounded control signal to modify the amplitude and frequency of the resulting second-order oscillator to modulate the stiffness and damping properties. In this paper, the focus is put on the wearable robot that assists human hip joint while performing periodic activities such as walking. The proposed approach is verified through a simple pendulum experiment. The results show that a better limit cycle can be obtained with Lyapunov redesigned phase oscillator which controls the radial spread of the steady state. Finally, the potential of the proposed approach for hip assistance in a healthy subject wearing HeSa (Hip Exoskeleton for Superior Assistance) during periodic activities are discussed.
Exploring Design Trades to Extend Useful Life of Platform Terminal Transmitters on Sea Turtles
Authors: Kelly Bethany , Nguyen Kenny , Miles Zach , Mayoral Salvador , Piacenza Susan , Zhang Cheng , Piacenza Joseph 
Published: November 2019

Abstract
Satellite-linked platform terminal transmitters (PTTs) are important tools for conducting research of sea turtles in their marine habitats. Appropriate conservation actions can be identified using PTTs, mounted to the top of sea turtles’ shells, to collect information about migratory routes and habitat usage. However, there is concern that PTTs introduce hydrodynamic drag that may bias natural sea turtle behavior, making the migratory and habitat data inaccurate representations of the “untagged” population. PTTs also have limited attachment durations, hypothesized to be caused by hydrodynamic loading and shell expansion during growth. The aim of this research is to investigate the hydrodynamic drag induced by PTTs on juvenile hard-shelled sea turtles, with the broader goal of increasing deployment duration and minimizing behavioral effects. A computational fluid dynamics (CFD) model was created to simulate the hydrodynamics of juvenile sea turtles. The drag and lift coefficients for five PTTs, virtually attached to the sea turtle model, were calculated using numerical methods. A comparison table of PTT performance is presented. The results will be used to explore PTT form factor design trades-offs that reduce hydrodynamic loading, while still meeting operational requirements. This research could enable biologists to collect data that more accurately represents the untagged sea turtle population.
A Comparative Study of Virtual Reality and Computer-Aided Design to Evaluate Parts for Additive Manufacturing
Authors: Ostrander John K. , Ryan Lauren , Dhengre Snehal , McComb Christopher , Simpson Timothy W. , Meisel Nicholas A. 
Published: November 2019

Abstract
Virtual Reality (VR) has been shown to be an effective assistive tool in the engineering design process, aiding designers in ergonomics studies, data visualization, and manufacturing simulation. Yet there is little research exploring the advantages of VR to assist in the design for the additive manufacturing (DfAM) process. VR may present advantages over traditional computer-aided design (CAD) tools, and these advantages may be more evident as designs become more complex. The following study investigates two types of environments: 1) Immersive Virtual Reality (VR) and 2) Non-Immersive Virtual Reality (CAD) and the advantages that each environment gives to designers to assess parts for additive manufacturing. The two environments are compared to assess potential differences in DfAM decision-making. Participants familiar with DfAM are tasked with evaluating five designs of varying complexity using the Design for Additive Manufacturing Worksheet. Participant scores, evaluation times, and self-reported metrics are recorded and analyzed. Our findings indicate that as part complexity increases, DfAM scores and evaluation times increasingly differ between VR and CAD groups. We found that the VR group evaluates more complex parts at a faster rate, but with a lower accuracy when compared to the CAD group. In evaluating self-reported metrics, both groups were relatively similar; however, the CAD group reported improved confidence in identifying stress concentrations in DfAM parts. Our findings in this research identify VR as a design evaluation tool that enhances evaluation speed which speaks to its efficiency and usability; however, VR in its current form may not present the resolution necessary to identify smaller details when compared to CAD, the more accurate evaluation tool.
Integrated Origami-String System
Authors: Liu Ke , Kosednar Madelyn , Tachi Tomohiro , Paulino Glaucio H. 
Published: November 2019

Abstract
Origami-inspired mechanical systems are mostly composed of two-dimensional elements, a feature inherited from paper folding. However, do we have to comply with this restriction on our design space? Would it be more approachable to achieve desired performance by integrating elements of different abstract dimensions? In this paper, we propose an integrated structural system consisting of both two-dimensional and one-dimensional elements. We attach elastic strings onto an origami design to modify its mechanical behavior and create new features. We show that, by introducing elastic strings to the recently proposed Morph pattern, we can obtain bistable units with programmable energy landscape. The behavior of this integrated origami-string system can be described by an elegant formulation, which can be used to explore its rich programmability.
A Conceptual Framework for Using Videogrammetry in Blockchain Platforms for Food Supply Chain Traceability
Authors: Gopalakrishnan Praveen Kumare , Behdad Sara 
Published: November 2019

Abstract
With the modern age of using genetically engineered products and growing concerns about food recalls and outbreaks, businesses are looking for ways to secure their brand names and assuring consumers about food safety and quality. Recently, Blockchain has been introduced as a promising approach for increasing the visibility of the supply chain and reducing the sale of contaminated and counterfeit products. Along this line, this study discusses the capabilities of Blockchain for the collection and monitoring of product lifecycle information ranging from production, wholesale, and logistics to standards, business reputation, and certification. The particular focus of the study is to discuss the use of videogrammetry as a data collection mechanism for bringing the product lifecycle data on digital Blockchain platforms and solving the “last mile” problem and data verification issue on Blockchain platforms. A conceptual example of organic meat processing is discussed to describe the proposed procedure and show how videogrammetry in combination with RFID and fingerprints can be used to solve the data verification issue on Blockchain platforms.