bluuebunny/crossref_metadata_2025 huggingface dataset:
LDV Measurement of Turbulent Pipe Flow With Traveling Wavy Elastic Wall for Drag Reduction
Authors: Nakazawa Seiya , Shimura Takaaki , Mitsuishi Akihiko , Iwamoto Kaoru , Murata Akira
Published: November 2019

Drag reduction effect by traveling wavy wall deformation control in turbulent pipe flow was experimentally investigated. From the visualization, we confirmed the downstream traveling wave although it was not uniform in the circumferential direction. When the frequency is 110 Hz, the wall deformation amplitude and the wavelength indicated that the effective values for drag reduction. The wavespeed is approximately effective values for drag reduction. As a result, the maximum drag reduction rate of 6.8 % is obtained. The result of a LDV measurement shows that the mean streamwise velocity gradient decreased near the wall by the control, which leads to drag reduction.
A Hierarchical Bayesian Method for Time Domain Structure Damage Detection
Authors: Feng Wei , Li Qiaofeng , Lu Qiuhai
Published: November 2019

A time domain structural damage detection method based on hierarchical Bayesian framework is proposed. Due to local stiffness reductions, the responses of damaged structures vary from those in undamaged status under the same external excitation. In this paper, the responses of damaged structures are assumed as the result of a summation of known external forces and unknown virtual forces exerted on corresponding undamaged structures. The damages can thus be detected, located, and quantified by the identification of associated virtual forces. A hierarchical Bayesian formulation considering all undetermined damage-related variables is adopted for the identification of virtual forces. The reasonable values of the variables and their uncertainties are depicted by their posterior distributions, sampled by Markov chain Monte Carlo method. Compared with traditional Bayesian formulations, manual choice of prior parameters is avoided and less prior information is required. The proposed virtual force indicator provides a more intuitive perspective for damage detection tasks and is potentially more operable in engineering practice. These advantages are illustrated by simulation of a cantilever beam under various damage conditions.
Cross-Well Dynamics of Bistable Cross-Ply Laminates
Authors: Emam Samir A. , Inman Daniel J.
Published: November 2019

This paper presents an experimental analysis of the dynamic response of bistable composite laminates that are harmonically excited. Bistable composite laminates are unsymmetric thin laminates that possess two self-equilibrated positions at room temperature. The resonant frequencies of bending under small harmonic excitations have been identified to serve as natural frequencies of the underlying linear system. Amplitude sweep and frequency sweep have been performed and the plate’s dynamics has been identified and analyzed. Four-ply and eight-ply laminates have been tested and showed similar behavior. The main conclusion is that when the cross-ply bistable laminates are harmonically excited and either the excitation amplitude or resonant frequency is varied, the single-well dynamic response experiences a period-doubling bifurcation and a cross-well harmonic response is obtained. Chaotic cross-well response was also identified.
Energy Dissipation of Damper Rings for Thin-Walled Gears
Authors: Li Zichao , Wang Yanrong , Jiang Xianghua , Ye Hang , Yang Weichao
Published: November 2019

When the gear generates a nodal mode shape vibration, there are two directions of possible relative displacement between the corresponding points on the contact surface of the damper ring and the damper groove, which are circumferential direction and axial direction respectively. In this paper, the relative displacement of the damper ring and the damper groove are considered in two directions, and the calculation method of energy dissipation is proposed. When the nodal vibration occurs in the gear, due to the existence of the strain difference between the damper ring and the damper groove on the contact surface, circumferential slip of partial area would occur. The energy dissipation in one vibration cycle is accurately determined by analytical solution. Since the aviation gears are mostly thin-walled structures, the axial displacement is large when resonance occurs. Based on the discrete damper ring model which considers interaction between every segment of the ring, the first-order harmonic balance method is used to calculate the axial displacement of the damper ring under the given gear rim amplitude. And then the hysteresis curve area of each discrete segment on the contact surface is summed to obtain energy dissipation in one vibration cycle. In this paper, based on the energy method, the damping effect of the damper ring is predicted. The damping ratio curve obtained by energy dissipation in two directions is compared and analyzed. The occurrence conditions of the two directions of possible relative displacement and the influence of the damper ring parameters on both situations are summarized.
Topology Design and Analysis of a Novel 3-Translational Parallel Mechanism With Analytical Direct Position Solutions and Partial Motion Decoupling
Authors: Shen Huiping , Chablat Damien , Zeng Boxiong , Yang Ting-li
Published: November 2019

According to the topological design theory and method of parallel mechanism (PM) based on position and orientation characteristic (POC) equations, this paper design a novel 3-translation (3T) PM that has three advantages, i.e., (1) it consists on three actuated prismatic joints, (2) the PM has analytical direct position solutions, and (3) the PM is of partial motion decoupling property. Firstly, the main topological characteristics such as the POC, degree of freedom and coupling degree are calculated for kinematics modelling. Due to the special constraint feature of the 3-translation, the analytical direct position solutions of the PM can be directly obtained without needing to use one-dimensional search method. Further, the conditions of the singular configuration of the PM, as well as the singularity location inside the workspace are analyzed according to the inverse kinematics.
Coupled Origami Tubes for Stiff Deployable Cantilevers
Authors: Filipov Evgueni T. , Tachi Tomohiro , Paulino Glaucio H.
Published: November 2019

Thin sheets folded into three dimensional origami structures can be useful in various engineering applications. This work explores the stiffness of deployable origami tubes used as cantilevers. A unique “zipper” configuration is used to couple the tubes, which makes the systems easy to deploy, yet stiff for other deformation modes. The self-restricting geometry of the coupled tubes limits local deformations and makes the systems stiff for out-of-plane loading. The global deployment characteristics are explored using eigenvalue band-gaps, and indicate that tubes with lower sector angles are easy to deploy yet also stiffer for unintended motions. Cantilever analyses show that the geometry of the coupled tubes can significantly affect the stiffness, with some tube combinations having a high orthogonal stiffness throughout deployment, while others only having a high stiffness when fully deployed. Parametric studies are used to show optimal geometries for the coupled tubes that maximize the eigenvalue band-gaps and the stiffness throughout the deployment. The coupled tubes could serve applications such as adjustable robotic arms, and deployable space booms with a reliable extension sequence.
Optimization of Machine Tool Settings on Hypoid Gear Dynamics
Authors: Lin Chia-Ching , Wang Yawen , Lim Teik C. , Zhang Weiqing
Published: November 2019

Hypoid gears are widely used to transmit torque on cross axis shafts in a vehicle rear axle system. The dynamic responses of these hypoid geared rotor system have a significant effect on the performance of noise, vibration, and harshness (NVH) for the vehicle design. From past studies, the main source of excitation for this vibration energy comes from hypoid gear transmission error (TE). Thus, the design of hypoid gear pair with minimization of TE is one way to control the dynamic behavior of the vehicle axle system. In this paper, an approach to obtain minimum TE and improved dynamic response with optimal machine tool setting parameters for manufacturing hypoid gears is discussed. A neural network, named Feed-Forward Back Propagation (FFBP), with Particle Swarm Optimization (PSO) and Gradient Descent (GD) training algorithms are used to predict the TE. With the optimal machine tool setting parameters, a 14 degrees of freedom geared rotor system analysis is performed to verify the improvement on dynamic response aiming at minimizing the TE. A case study of a hypoid gear pair with specified design parameters and working condition is presented to validate the proposed method. The results conclude that minimization of TE, the main excitation of vehicle axle gear whine noise and vibration, with optimal machine tool setting parameters can improve the overall dynamic response. The proposed approach provides a better understanding of an optimal design hypoid gear set to minimize TE and effect on vehicle axle system dynamics.
Study on Path Planning of Involute Tooth Surface Milling With General Cutting Tool
Authors: Shi Zhaoyao , Feng Zhipeng , Wang Peng
Published: November 2019

Milling involute tooth surface with universal cutting tool overcomes the difficult problem of customizing tool for nonstandard gear machining. It is difficult for gear manufacturers to gain an advantage in market competition because of the long cycle of customized cutting tools. In this paper, the milling path of involute tooth surface by a general cutting tool is studied, and how to obtain the uniform surface roughness of involute tooth surface and the cutting path scheme of cutting tool is discussed. The key point of this paper is to put forward the scheme of tool path in the milling process. The end profile of involute gear is modeled by an analytic method, and the equidistant contour of the profile of involute gear is established by using the principle of normal deviation, which provides an accurate position point for the cutting tool.
Sustainable Design of Residential Net-Zero Energy Buildings: A Multi-Phase and Multi-Objective Optimization Approach
Authors: Lan Lan , Wood Kristin L. , Yuen Chau
Published: November 2019

Zero energy building (ZEB) is an important concept for sustainable building design. This paper introduces a holistic design approach for residential net-zero energy buildings (NZEB) by adopting the Triple Bottom Line (TBL) principles: social, environmental, and financial. The proposed approach optimizes social need by maximizing thermal comfort time of natural cooling, and visual comfort time of daylighting. The environmental need is addressed by optimizing energy efficiency, and the financial need is addressed by optimizing life cycle cost (LCC). Multi-objective optimizations are conducted in two phases: the first phase optimizes the utilization rate of natural cooling and daylighting, and the second phase optimizes energy efficiency and LCC. Sensitivity analysis is conducted to identify the most influential variables in the optimization process. The approach is applied to the design of a landed house in a tropical country, Singapore. The results provide a framework and modeled cases for parametric design and trade-off analysis toward sustainable and livable built environment.
Bio-Oil Upgrading via Micro-Emulsification and Ultrasound Treatment: Examples for Analysis and Discussion
Authors: Hansen Samuel , Mirkouei Amin
Published: November 2019

Blended fuels allow biofuels (e.g., bio-oil, ethanol, and biodiesel) to be commercialized by mixing them with petroleum-based fuels and address their deficiencies, such as compatibility with existing engine systems. Traditional blends (e.g., B20, E15, and E85) rely on mechanical mixing and use of surfactants (stabilizing chemicals) to prevent mixture separation, however, in many cases bio-blends suffer from reduced performance. Bio-oil, a low-grade liquid biofuel, has high potential in blended fuels production and addresses its deficiencies, such as high upgrading cost due to high oxygen-carbon ratio and H2O content. Emulsion technology is a relatively immature process, which relies on microscopic H2O blended with fuel for increased performance and stability. This study explores how residual H2O in bio-oil may increase performance and compensate for its deficiencies by using bio-oil in diesel emulsion. Our research shows that (a) H2O emulsion fuel has received little attention yet, which can offer many benefits to reduce fuel consumption and emissions, (b) H2O content in bio-oil may be significant enough to impact performance in a diesel engine if stability concerns are addressed, and (c) the stability of bio-oil derived diesel emulsions may be increased over conventional practice, using ultrasonic cavitation. It is concluded that emulsified bio-oil in diesel is able to address common upgrading challenges by skipping H2O removing operation and using H2O in bio-oil to enhance blended fuel performance. Ultimately, bio-oil can be used to supplement diesel fuel and develop a commercial market similar to the strategy’s used earlier with ethanol production from corn.
Using Complex Orthogonal Decomposition to Extract Dispersion Relationships for Mass Chain
Authors: Valente N. A. , Caldwell R. A.
Published: November 2019

Complex orthogonal decomposition (COD) was used to determine the extracted dispersion relationship of a traveling wave in a mass chain. When COD extracts a wavenumber it will produce M values for each wavenumber, γi, and N values for each frequency, ωi; where M is the number of masses and N is the number of time samples. In this work, least squares and a simple mean of the M-γi’s and N-ωi’s extracted values were used to determine each γi and ωi, respectively. An analytical dispersion relationship for the mass chain is derived in addition to an approximate dispersion relationship. The approximate derivation was found using Lindstedt-Poincaré’s perturbation method. Lastly, the effects of the sampling rate on parameter extraction was studied. COD could accurately extract the wavenumber and frequency of a traveling wave in the mass chain. Using a simple mean provided marginally better results than that of least squares. Sampling at the Nyquist criterion gave accurate results which improved both marginally and asymptotically as the sampling rate increased.
Designing Optimal Arbitrage Policies for Distributed Energy Systems in Building Clusters Using Reinforcement Learning
Authors: Odonkor Philip , Lewis Kemper
Published: November 2019

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Design and Simulation of a Novel High-Speed Omnidirectional Fully-Actuated Underwater Propulsion Mechanism
Authors: Njaka Taylor , Brizzolara Stefano , Ben-Tzvi Pinhas
Published: November 2019

This paper details the design and simulation of a novel position control mechanism for marine operations or inspection in extreme, hostile, or high-speed turbulent environments where unprecedented speed and agility are necessary. The omnidirectional mechanism consists of a set of counter-rotating blades operating at frequencies high enough to dampen vibrational effects on onboard sensors. Each rotor is individually powered to allow for roll control via relative motor effort and attached to a servo-swashplate mechanism, enabling quick and powerful manipulation of fluid flow direction in a hull’s coordinate frame without the need to track rotor position. The mechanism inherently severs blade loads from servo torques, putting all load on the main motors and minimizing servo response time, while exploiting consistent blade momentum to minimize the corresponding force response time. The mechanical design and kinematic analysis of each subsystem is presented, followed by kinematic and hydrodynamic analysis of the hull and surrounding fluid forces during various blade maneuvers. Special maneuvers are verified using Computational Fluid Dynamic (CFD) software. Finally, a controller is constructed with decoupled parameters for each degree of freedom.
Robotics Simulator for Development and Verification of Swarm Behaviors
Authors: Hart Shae T. , Metzger Nathan J. , Reese Maximilian E. , McDonald Robert T. , Neumann Michael A. , Kitts Christopher A.
Published: November 2019

Swarm control strategies allow for decentralized control of many simple robots to perform collective behaviors based on local interactions. We have created a new platform for developing and exploring swarm behaviors, supporting both simulation and experimental verification. The platform, designed entirely in Simulink, provides a simple implementation with satisfactory dynamics to replicate experimental trials on Santa Clara University’s Robotic Systems Laboratory’s Low-Cost Indoor Testbed. The platform allows for seamless transitions from simulation to experimentation on the testbed. The platform is currently equipped with attract, disperse, obstacle avoidance, and go-to behaviors which have been verified both in simulation and on the experimental testbed. Additionally, a composite behavior, flocking, composed of attract and go-to behaviors is presented to demonstrate the flexibility of the simulator. Future work will expand the available behaviors to include swarm adaptive navigation behavior primitives like minima and maxima finding as well as contour and ridge following.
A Deep Learning Based Approach to Predict Sequential Design Decisions
Authors: Rahman Molla Hafizur , Xie Charles , Sha Zhenghui
Published: November 2019

During a design process, designers iteratively go back and forth between different design stages to explore the design space and search for the best design solution that satisfies all design constraints. For complex design problems, human has shown surprising capability in effectively reducing the dimensionality of design space and quickly converging it to a reasonable range for algorithms to step in and continue the search process. Therefore, modeling how human designers make decisions in such a sequential design process can help discover beneficial design patterns, strategies, and heuristics, which are important to the development of new algorithms embedded with human intelligence to augment computational design. In this paper, we develop a deep learning based approach to model and predict designers’ sequential decisions in a system design context. The core of this approach is an integration of the function-behavior-structure model for design process characterization and the long short term memory unit model for deep leaning. This approach is demonstrated in a solar energy system design case study, and its prediction accuracy is evaluated benchmarked on several commonly used models for sequential design decisions, such as Markov Chain model, Hidden Markov Chain model, and random sequence generation model. The results indicate that the proposed approach outperforms the other traditional models. This implies that during a system design task, designers are very likely to reply on both short-term and long-term memory of past design decisions in guiding their decision making in future design process. Our approach is general to be applied in many other design contexts as long as the sequential design action data is available.
Optimization of Parts Consolidation for Minimum Production Costs and Time Using Additive Manufacturing
Authors: Nie Zhenguo , Jung Sangjin , Kara Levent Burak , Whitefoot Kate S.
Published: November 2019

This research presents a method of evaluating and optimizing the consolidation of parts in an assembly using metal additive manufacturing (MAM). The method generates candidates for consolidation, filters them for feasibility and structural redundancy, finds the optimal build layout of the parts, and optimizes which parts to consolidate using a genetic algorithm. Optimal results are presented for both minimal production time and minimal production costs, respectively. The production time and cost model considers each step of the manufacturing process, including MAM build, post-processing steps such as support-structure removal, and assembly. It accounts for costs affected by parts consolidation, including machine costs, material, scrap, energy consumption, and labor requirements. We find that developing a closed-loop filter that excludes consolidation candidates with structural redundancy dramatically reduces the number of candidates to consider, thereby significantly reducing convergence time. Results show that, when increasing the number of parts that are consolidated, the production cost and time at first decrease due to reduced assembly steps, and then increase due to additional support structures needed to uphold the larger, consolidated parts. We present a rationale and evidence justifying that this is an inherent tradeoff of parts consolidation that generalizes to most types of assemblies. Subsystems that can be oriented with very little support structures, or have low material costs or fast deposition rates can have an optimum at full consolidation; otherwise, the optimum is likely to be less than 100%. The presented method offers a promising pathway to minimize production time and cost by consolidating parts using MAM. In our test-bed results on an aircraft fairing produced with powder-bed electron-beam melting, the solution for minimizing time is to consolidate 48 components into three discrete parts, which leads to a 33% reduction in unit production time. The solution for minimizing production costs is to consolidate the components into five discrete parts, leading to a 28% reduction in unit costs.
Experimental Investigations Into Broadband Vibration Absorption of Metastructures With Lattice Designs
Authors: Tempelman Joshua R. , Myers Audun , Yesilli Melih C. , Khasawneh Firas A.
Published: November 2019

Enhancements in manufacturing technologies, especially 3D-printing, have enabled the production of intricate micro-scale, elastic meta-structures. This study explores the broadband vibration absorption characteristics of these structures for three different geometries: simple-cubic periodic geometries as well as the more-involved diamond and octet-truss micro-lattice geometries. Broadband absorption is experimentally achieved for the basic cubic geometries with band gaps approximately 3000 Hz in width. A band gap of 3500 Hz is found in the octet-truss lattice with a 5% mass increase. The diamond lattice achieves a band gap width which doubles its cubic counterparts (6500 Hz), but only at a cost of a 4% mass increase. We compare the experimental findings to the theoretical results obtained by modeling the structure as a discrete, lumped mass system and employing modal analysis and transfer-function matrix methods. These comparisons show a mismatch between the theoretical and the experimental frequency responses. This mismatch is attributed to the inconsistencies inherent to 3D-printing processes, and to the need for more accurate modeling of the lattice structures.
Research Progress and Development Tendency of Transfer Matrix Method for Multibody Systems (Rui Method)
Authors: Rui Xiaoting , Wang Xun , Zhang Jianshu , Gu Junjie , Zhang Shujun
Published: November 2019

The transfer matrix method for multibody systems, known as the “Rui method”, is a new method for dealing with multibody system dynamics, which does not need the global dynamics equations of the system, keeps high computational speed, and is highly formalized programming. This method has been widely applied to scientific research and key engineering of many complex mechanical systems in more than 50 research fields. The following aspects regarding the transfer matrix method for multibody systems are reviewed in this paper: history, basic principles, formulas, algorithm, and applications in engineering. Some hot topics in this field are also reviewed and prospected, mainly regarding to the improvement of the computational stability and efficiency.
Periodic Motions in a Single-Degree-of-Freedom System Under Both an Aerodynamic Force and a Harmonic Excitation
Authors: Yu Bo , Luo Albert C. J.
Published: November 2019

In this paper, a semi-analytical approach was used to predict periodic motions in a single-degree-of-freedom system under both aerodynamic force and harmonic excitation. Using the implicit mappings, the predictions of period-1 motions varying with excitation frequency are obtained. Stability of the period-1 motions are discussed, and the corresponding eigenvalues of period-1 motions are presented. Finally, numerical simulations of stable period-1 motions are illustrated.