bluuebunny/crossref_metadata_2025_split huggingface dataset:
Backward Mechanical-Electric Coupling Effect of a Frequency-Up-Conversion Piezoelectric Energy Harvester
Authors: Wang Fengxia , Onsorynezhad Saeed 
Published: November 2019

Abstract
This paper developed an analytical model for a frequency-up-conversion piezoelectric energy harvester (PEH) composed of a piezoelectric bimorph and a stopper as shown in Fig.1. The whole system was subjected to a harmonic excitation. A bimodal approach was adopted to animate the beam stopper reaction. When the tip of the bimorph vibrates in free space or impacts with the stopper, a cantilever beam function was adopted. On the other hand, if the tip of the bimorph sticks with the stopper, a clamped-pinned beam function was applied to model the piezoelectric bimorph. To exam the effect of backward mechanical-electric coupling on power output, the dynamics and output energies are compared for two cases: 1) neglecting the backward mechanical-electric coupling effect in the model; 2) including the backward mechanical-electric coupling effect in the model. To obtain maximum output energy, the steady-state analytical solutions were studied to obtain the optimum gap between the piezoelectric beam and the stopper. From the results, we found that if the beam impacts and/or sticks with the stopper, the PEH model without the backward mechanical-electric coupling will exaggerate the output energy.
Proposing a Design for Tangibility Framework: A Digital Payments Case Study
Authors: Li Yanling , Baxter Weston L. 
Published: November 2019

Abstract
This research proposes a framework for designing tangibility into abstract interactions such as managing financial resources, health concerns and environmental impacts. A case study of the tangibility within cashless payments is presented, which adopted this framework to design, fabricate and test a tangible interaction in digital transactions. Digital transactions can significantly influence a consumer’s spending habits and decisions, commonly leading to increased expenditure compared to cash transactions. Several psychological mechanisms which influence conscientious spending due to differing payment methods were analyzed and employed to design a prototype incorporating a tangible interaction that is relevant to the consumer’s spending process. It is proposed that re-introducing tangibility into the payment process can increase one’s psychological ownership over their financial resources and purchased item, as well as the aversion towards paying. Results from the experiments show that the interaction enhances psychological ownership over digital currency but remain inconclusive on behavior change. The broader implications of enhancing tangibility for intangible objects is discussed.
Decentralized Informative Path Planning With Balanced Exploration-Exploitation for Swarm Robotic Search
Authors: Ghassemi Payam , Chowdhury Souma 
Published: November 2019

Abstract
Swarm robotic search is concerned with searching targets in unknown environments (e.g., for search and rescue or hazard localization), using a large number of collaborating simple mobile robots. In such applications, decentralized swarm systems are touted for their task/coverage scalability, time efficiency, and fault tolerance. To guide the behavior of such swarm systems, two broad classes of approaches are available, namely nature-inspired swarm heuristics and multi-robotic search methods. However, simultaneously offering computationally-efficient scalability and fundamental insights into the exhibited behavior (instead of a black-box behavior model), remains challenging under either of these two class of approaches. In this paper, we develop an important extension of the batch Bayesian search method for application to embodied swarm systems, searching in a physical 2D space. Key contributions lie in: 1) designing an acquisition function that not only balances exploration and exploitation across the swarm, but also allows modeling knowledge extraction over trajectories; and 2) developing its distributed implementation to allow asynchronous task inference and path planning by the swarm robots. The resulting collective informative path planning approach is tested on target search case studies of varying complexity, where the target produces a spatially varying (measurable) signal. Significantly superior performance, in terms of mission completion efficiency, is observed compared to exhaustive search and random walk baselines, along with favorable performance scalability with increasing swarm size.
A New Approach for Medical Assessment of Patient’s Injured Shoulder
Authors: Vitali Andrea , Regazzoni Daniele , Rizzi Caterina , Maffioletti Federico 
Published: November 2019

Abstract
Low cost marker-less motion capture (Mocap) systems can be considered an interesting technology for the objective assessment of rehabilitation processes. In particular, this paper presents a feasibility study to introduce a Mocap system as a tool to assess shoulder rehabilitation. The movements of a shoulder are complex and challenging to be captured with a marker-less system because the skeleton avatar usually oversimplifies shoulder articulation with a single virtual joint. The designed solution integrates a low-cost Mocap system with image processing techniques and convolutional neural networks to automatically detect and measure potential compensatory movements executed during an abduction, which is one of the first post-surgery exercises for shoulder rehabilitation.
First, we introduce the main steps of a reference roadmap that guided the development of the Mocap solution for rehab assessment of injured shoulder. Then, the acquisition of medical knowledge is presented as well as the new Mocap solution based on the integration of convolutional neural networks and 2D motion tracking techniques. Finally, the application which automatically evaluates abductions and makes available the measurements of the scapular elevations is described. Preliminary study and future works are also presented and discussed.
Multimaterial Topology Optimization of Thermoelectric Generators
Authors: Xu Xiaoqiang , Wu Yongjia , Zuo Lei , Chen Shikui 
Published: November 2019

Abstract
Over 50% of the energy from power plants, vehicles, oil refining, and steel or glass making process is released to the atmosphere as waste heat. As an attempt to deal with the growing energy crisis, the solid-state thermoelectric generator (TEG), which converts the waste heat into electricity using Seebeck phenomenon, has gained increasing popularity. Since the figures of merit of the thermoelectric materials are temperature dependent, it is not feasible to achieve high efficiency of the thermoelectric conversion using only one single thermoelectric material in a wide temperature range. To address this challenge, this paper proposes a method based on topology optimization to optimize the layouts of functional graded TEGs consisting of multiple materials. The objective of the optimization problem is to maximize the output power and conversion efficiency as well. The proposed method is implemented using the Solid Isotropic Material with Penalization (SIMP) method. The proposed method can make the most of the potential of different thermoelectric materials by distributing each material into its optimal working temperature interval. Instead of dummy materials, both the P and N-type electric conductors are optimally distributed with two different practical thermoelectric materials, namely Bi2Te3 & PbTe for P-type, and Bi2Te3 & CoSb3 for N-type respectively, with the yielding conversion efficiency around 12.5% in the temperature range Tc = 25°C and Th = 400°C. In the 2.5D computational simulation, however, the conversion efficiency shows a significant drop. This could be attributed to the mismatch of the external load and internal TEG resistance as well as the grey region from the topology optimization results as discussed in this paper.
A Robotic Tool for Magnetic Micromanipulation of Cells in the Presence of an Ambient Fluid Flow
Authors: Agarwal Dharmveer , Thakur Ajay D. , Thakur Atul 
Published: November 2019

Abstract
This paper reports an automated image-guided microrobotic tool to perform nonprehensile magnetic manipulation of large (of the order of few hundreds of microns) microscopic biological objects in the presence of an ambient fluid flow. The developed tool comprises of ferromagnetic microrobots actuated by electromagnetic coils arranged in a quadrupole configuration, a DC power source, and a pulse width modulation (PWM) based controller to vary the coil currents. In order to accomplish the stated objective of automated micromanipulation task, a two-tier approach is adopted, namely, (1) generation of a feedback planning algorithm that invokes one of the two motion maneuvers, namely, ‘arrest’ and ‘move’ and (2) development of a proportional controller that determines the currents to be passed through the coils based on the maneuver invoked so that the resultant magnetic field actuates the ferromagnetic microrobot in the desired direction. A physical experiment was conducted and reported to authenticate the validity of the developed approach. We believe that the developed tool can be used to perform automated feedback controlled micromanipulation of large biological cells and cell aggregates in the presence of an ambient fluid flow especially in in-vivo environments. The inherent biocompatibility of the microbot material provides a possibility to functionalize it with living cells and/or appropriate chemicals rendering it feasible to implement drug delivery and also perform on-chip biological experiments.
Model Bias Characterization for Effective States Estimation of Lithium-Ion Batteries
Authors: Dahmardeh Modjtaba , Xi Zhimin 
Published: November 2019

Abstract
State of charge (SOC) estimation of lithium-ion batteries has been extensively studied and the estimation accuracy was mainly investigated through the development of various battery models and dynamic estimation algorithms. All battery models, however, contain inherent model bias due to the simplifications and assumptions, which cannot be effectively addressed through the development of various algorithms such as Kalman filtering (KF) or particle filtering (PF). Consequently, as observed in our study, battery SOC estimation using a typical extended KF in fact is not very accurate where the error could range from 5% to 10% or even more depending on the battery characteristics. This paper proposes bias characterization of the battery model so that accuracy of the baseline model could be significantly improved and eventually SOC estimation could be much more accurate than the one only using the baseline model. This paper reports great potential for improving battery SOC estimation with the bias characterization and proposes two methods for actual bias modeling. In particular, the polynomial regression model and the Gaussian process (GP) regression model are proposed to examine the effects of the two methods on bias modeling and SOC estimation using a typical battery circuit model. Results are demonstrated in lab testing using three battery charging/discharging profiles with the cross-validation technique.
Energetically-Optimal Discrete and Continuous Stabilization of the Rimless Wheel With Torso
Authors: Sirichotiyakul Wankun , Satici Aykut C. , Sanchez Eric S. , Bhounsule Pranav A. 
Published: November 2019

Abstract
In this work, we discuss the modeling, control, and implementation of a rimless wheel with torso. We derive and compare two control methodologies: a discrete-time controller (DT) that updates the controls once-per-step and a continuous-time controller (CT) that updates gains continuously. For the discrete controller, we use least-squares estimation method to approximate the Poincaré map on a certain section and use discrete-linear-quadratic-regulator (DQLR) to stabilize a (closed-form) linearization of this map. For the continuous controller, we introduce moving Poincaré sections and stabilize the transverse dynamics along these moving sections. For both controllers, we estimate the region of attraction of the closed-loop system using sum-of-squares methods. Analysis of the impact map yields a refinement of the controller that stabilizes a steady-state walking gait with minimal energy loss. We present both simulation and experimental results that support the validity of the proposed approaches. We find that the CT controller has a larger region of attraction and smoother stabilization as compared with the DT controller.
Computer Vision-Based Object Recognition and Automatic Pneumatic Soft Gripping
Authors: Shahabi Ebrahim , Lu Wei-Hao , Lin Po Ting , Kuo Chin-Hsing 
Published: November 2019

Abstract
During recent years, soft robotic is a new sub-class of the robots. Soft robotic has several engaging features, such as lightweight, low cost, simple fabrication, easy control, etc. Commercial products such as soft grippers are now available to apply in various fields and applications, for example, agriculture, medicine, machinery, etc. This paper proposes a novel method of grasping in soft robotic fields using computer vision to find the shape, size, and angle of the object to define the best type of grasping mode. Random Sample Consensus (RANSAC) was used to iteratively select randomly sampled 3D points to determine the working plane and identify the randomly placed object. Furthermore, we designed and fabricated a 3D-printed pneumatic soft actuator. The ratio of payload over weight is around 16. Experiments showed the proposed computer vision techniques and pneumatic soft gripper are capable of automatically recognize the object shape and perform soft gripping.
Checking the Automated Construction of Finite Element Simulations From Dirichlet Boundary Conditions
Authors: Chiu Kevin N. , Fuge Mark D. 
Published: November 2019

Abstract
From engineering analysis and topology optimization to generative design and machine learning, many modern computational design approaches require either large amounts of data or a method to generate that data. This paper addresses key issues with automatically generating such data through automating the construction of Finite Element Method (FEM) simulations from Dirichlet boundary conditions. Most past work on automating FEM assumes prior knowledge of the physics to be run or is limited to a small number of governing equations.
In contrast, we propose three improvements to current methods of automating the FEM: (1) completeness labels that guarantee viability of a simulation under specific conditions, (2) type-based labels for solution fields that robustly generate and identify solution fields, and (3) type-based labels for variational forms of governing equations that map the three components of a simulation set — specifically, boundary conditions, solution fields, and a variational form — to each other to form a viable FEM simulation. We implement these improvements using the FEniCS library as an example case. We show that our improvements increase the percent of viable simulations that are run automatically from a given list of boundary conditions. This paper’s procedures ultimately allow for the automatic — i.e., fully computer-controlled — construction of FEM multi-physics simulations and data collection required to run data-driven models of physics phenomena or automate the exploration of topology optimization under many physics.
A Computational Investigation Into the Impact of Sensor Location on the Acoustics-Based Damage Detection From an Airfoil Structure
Authors: Traylor Caleb , Inalpolat Murat 
Published: November 2019

Abstract
As the use of wind power continues to increase globally, the need for improved structural health monitoring systems for wind turbine blades increases as well. Acoustics-based methods are deemed promising in this endeavor, as they are non-contact, nondestructive and enabling distributed sensing. To systematically design an acoustics-based blade health monitoring system, a representative computational study using a NACA 0012 airfoil was conducted to examine the impact of damage location, damage size, acoustic source location, and microphone placement on the detection rate. Structural-acoustic coupled simulations were performed using a commercially available finite element based tool. Results indicated that sound pressure levels (SPL) did not increase significantly when the damage was not near the source location, indicating that using a change in SPL to identify damage may not be the best method. However, spatial variability of the change in SPL in the blade’s internal cavity was found to be a strong indicator of damage, resulting in a detection rate of 81–92% depending on the damage size. Based on the computationally obtained results, the recommendation is for further investigation into the spatial variation of sound inside the blade cavity using 2–3 microphones per cavity to identify damage, when feasible, in addition to testing the effectiveness of a one microphone per cavity design with different blade geometries. The optimal positions of these microphones and the reliability of this method will continue to be investigated in future work.
Integrating Quality of Life in Sociotechnical Design: A Review of Microgrid Design Tools and Social Indicators
Authors: Suk Hailie , Hall John 
Published: November 2019

Abstract
Microgrid systems can provide distributed power to communities that lack basic access to electricity. Scalability, maintenance, and power management are prominent challenges associated with microgrid resilience. These obstacles can be limiting in the continued development of the community. As progress drives an increase in energy demand, the microgrid needs to continue to meet that demand. Designing systems with the appropriate maintenance levels is another obstacle that impacts resiliency.
There are many design tools that analyze system performance and cost. One goal of this work is to review a set of these technical models. HOMER Energy, System Advisor Model (SAM), and the Microgrid Design Toolkit (MDT) were reviewed. However, technical and economic performance is just one aspect of design. In the design procedure, social parameters also need to be considered. Few, if any, microgrid design tools consider societal dynamics. This work also aims to evaluate social indicators in the context of sustainable microgrid design. Accordingly, relationships are established between common societal indicators and the microgrid challenges of scalability, maintenance, and power management.
Fabrication and Testing of a MEMS System for Injection of DNA Into Plant Cells
Authors: Brown Taylor , Hope Sandra , Jensen Brian D. 
Published: November 2019

Abstract
This paper describes the fabrication and testing of a system to inject DNA into plant leaves. Arrays of silicon lances were made using photolithographic and STS DRIE Bosch techniques. A nanoinjector device was also made to accept the silicon lance arrays and perform nanoinjections. Nanoinjections were performed on Arabidopsis and cotton cotyledons. Changes in the force applied during a nanoinjection and varying the number of repeated nanoinjections on the same cotyledon were observed. Too much force or too many repeated injections caused physical damage to the cotyledon. An optimal force and number of repeated injections can be performed without causing physical damage to the cotyledon. Several injections using DNA were performed without successful transfection of the leaves. Possible reasons for this failure to transfect were explored.
Time Invariant Motion Controller for Physical Human Robot Interaction
Authors: Muñoz Osorio Juan D. , Castañeda Felipe , Allmendinger Felix , Zimmermann Uwe E. 
Published: November 2019

Abstract
In this paper, a new method to perform time-invariant motion is proposed. The approach uses the advantages of variable impedance control to have full interactivity with the human while tracing a desired path. The path is followed at maximum velocity while the human can disturb the robot at any instant and manipulate it far from the desired path without changing the control law. The method was proven in simulation and on a real torque-controlled serial manipulator (KUKA LWR iiwa). The chosen paths were designed to perform robotic assisted ultrasound scanning for breast cancer diagnosis. Results show that interactivity is allowed while keeping a low kinetic energy of the robot. Despite of human disturbances, the robot can keep tracing the path after the interaction is finished.
Design of a Two DOF Laminate Leg Transmission for Creating Walking Robot Platforms
Authors: Shuch Benjamin D. , Shafa Taha , Rogers Eric , Aukes Daniel M. 
Published: November 2019

Abstract
In this article we present a low-cost, two degree-of-freedom laminate robot transmission for legged locomotion applications. This transmission is specifically applied in the design of a quadrupedal robot, and has the potential to be used in other multi-legged systems. It offers a complex control space with a variety of different programmable gait trajectories, while leveraging low-cost linkages made using laminate approaches. The two-degree-of-freedom kinematics of the leg are subsequently modeled in Python, and the workspace of the robot is then experimentally verified on an initial quadrupedal design. Critical design considerations include the laminate design, the rigidity of the materials that make up the laminate, and the range of motion the device can undergo.
Using Bayesian Optimization With Knowledge Transfer for High Computational Cost Design: A Case Study in Photovoltaics
Authors: Kaya Mine , Hajimirza Shima 
Published: November 2019

Abstract
Engineering design is usually an iterative procedure where many different configurations are tested to yield a desirable end performance. When the design objective can only be measured by costly operations such as experiments or cumbersome computer simulations, a thorough design procedure can be limited. The design problem in these cases is a high cost optimization problem. Meta model-based approaches (e.g. Bayesian optimization) and transfer optimization are methods that can be used to facilitate more efficient designs. Transfer optimization is a technique that enables using previous design knowledge instead of starting from scratch in a new task. In this work, we study a transfer optimization framework based on Bayesian optimization using Gaussian Processes. The similarity among the tasks is determined via a similarity metric. The framework is applied to a particular design problem of thin film solar cells. Planar multilayer solar cells with different sets of materials are optimized to obtain the best opto-electrical efficiency. Solar cells with amorphous silicon and organic absorber layers are studied and the results are presented.
Coordinated Model Predictive Control on Multi-Lane Roads
Authors: Goulet Nathan , Ayalew Beshah 
Published: November 2019

Abstract
There are significant economic, environmental, energy, and other societal costs incurred by the road transportation sector. With the advent and penetration of connected and autonomous vehicles there are vast opportunities to optimize the control of individual vehicles for reducing energy consumption and increasing traffic flow. Model predictive control is a useful tool to achieve such goals, while accommodating ego-centric objectives typical of heterogeneous traffic and explicitly enforcing collision and other constraints. In this paper, we describe a multi-agent distributed maneuver planning and lane selection model predictive controller that includes an information sharing and coordination scheme. The energy saving potential of the proposed coordination scheme is then evaluated via large scale microscopic traffic simulations considering different penetration levels of connected and automated vehicles.