bluuebunny/crossref_metadata_2025_split huggingface dataset:
316L Stainless Steel Sensitization in Carbon Nanotube CVD Growth for Bacterial Resistance
Authors: Voss Sterling , Mecham Bret , Bowden Lucy , Monroe Jacquelyn , Bowden Anton E. , Jensen Brian D. 
Published: November 2020

Abstract
Physically altering the micro-topography of a surface can dramatically affect its capacity to support or prevent biofilm growth. Growing carbon-infiltrated carbon nanotubes on biomedical materials is one such approach which has proven effective. Unfortunately, the high temperature and carbon-rich gas exposure required for this procedure has proven to have deleterious effects. This paper proposes a kinetic model to explain the rusting phenomenon observed on 316L stainless steel substrates which have undergone the chemical vapor deposition process to grow carbon-infiltrated carbon nanotubes. The model is derived from Fick’s Second Law, and predicts the growth of chromium carbide as a function of temperature and time. Chromium carbide formation is shown to be the mechanism of corrosion, as chromium atoms are leeched from the the matrix, preventing the formation of a passivating chromium oxide layer in place of problematic iron oxide (rust) formation. The model is validated using experimental methods, which involve immersion in bacteria culture, scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDX).
Comfort-Oriented Design of Model Predictive Control in Assisted and Autonomous Driving
Authors: Luciani Sara , Bonfitto Angelo , Amati Nicola , Tonoli Andrea 
Published: November 2020

Abstract
This paper presents a method based on a Model Predictive Control (MPC) aiming to optimize the passenger comforts in assisted and autonomous vehicles. The controller works on the lateral and longitudinal dynamics of the car, providing front wheel steering angle and acceleration/deceleration command. The comfort is evaluated through two indexes extracted from the ISO 2631: an equivalent acceleration aeq and a Motion Sickness Dose Value (MSDV) index. The MPC weighting parameters are designed according to the values assumed by these indexes. Specifically, each weighting parameter is changed until the most satisfying comfort evaluation and the maximum vehicle performances, in terms of lateral deviation, tracking velocity and relative yaw angle, are reached. The controller is tested numerically on a simulated scenario resulting from real GPS data obtained in a highway. The method is compared with an alternative control strategy based on the combination of a PID and a Stanley control for the longitudinal and lateral dynamics, respectively. The results demonstrate the effectiveness of the approach, leading to a low percentage of passengers can experience motion sickness.
A Novel Compliant Bistable Mechanism Incorporating a Fixed-Guided Flexural Member
Authors: Joo James J. , Myszka David H. 
Published: November 2020

Abstract
This paper presents the design of a novel compliant bistable mechanism. Bistable mechanisms are commonly used in switches and other devices that operate in two distinct modes. This mechanism is a single monolithic structure with simple geometry and does not require external components or post-manufacture assembly. As such, the design is ideally suited for additive manufacturing at large, or micro, scales. The design features a fixed-guided flexural member with surrounding geometry. When a load is applied to the mechanism in a stable configuration, the flexural member exhibits an inflection point that enables bifurcated behavior. As a result, the mechanism snaps between two stable positions in an on-off operation mode. This paper describes the mechanism geometry and its operation. Preliminary design modeling equations are formulated. A finite element simulation is presented that verifies the design equations. Lastly, a prototype is presented to confirm the operation and facilitate force and displacement measurements.
A Mobility Determination Method for Parallel Platforms Based on the Lie Algebra of SE(3) and its Subspaces
Authors: Sánchez-García A. J. , Rico J. M. , Cervantes-Sánchez J. J. , López-Custodio P. C. 
Published: November 2020

Abstract
This contribution presents a screw theory-based method for determining the mobility of fully parallel platforms. The method is based in the application of three stages. The first stage involves the application of the intersection of the subalgebras of Lie algebra, se(3), of the special Euclidean group, SE(3), associated with the legs of the platform. The second stage analyzes the possibility of the legs of the platform generating a sum or direct sum of two subalgebras of the Lie algebra, se(3). The last stage, if necessary, considers the possibility of the kinematic pairs of the legs satisfying certain velocity conditions; these conditions allow to reduce the platform’s mobility analysis to one that can solved using one of the two previous stages.
A Computational Framework Enabling Comparative Analysis of Progressive Damage Models for Composite Materials
Authors: Apetre N. A. , Michopoulos J. G. , Iliopoulos A. P. , Steuben J. C. , Phan N. 
Published: November 2020

Abstract
The present work is motivated by the need for an efficient and quantifiable assessment of how various strain- or stress-based composite materials failure criteria and damage evolution models that capture the load-induced material degradation, along with their intrinsic parameters, can affect our understanding of material behavior and facilitate suitability decisions of such criteria. The difficulty of performing comparative analysis among many of these criteria and models has been a significant impediment to the composite materials design and material certification communities. In response to these needs, the present work describes the development, verification and validation of such a general computational framework. This framework enables not only increasing the user’s understanding of the effect of parameters associated with models under consideration on the model predicted results but also allowing the user to address more advanced problems such as material design, optimization and potentially certification. The framework implemented into “COMSOL Multiphysics” utilizes symbolic algebra to automatically generate the required expressions to be used in the respective computational modules. Two strain-based models for two distinct specimen geometries are used to show the framework capabilities: one model is described by three damage modes and a second one is given by four damage modes. The first geometry is that of a unnotched coupon whereas the second is that of an open hole specimen in tension. The theoretical predictions are compared with the experimental ones in terms of load-strain responses. The results indicate that by proper selection of specific input parameters, these models can accurately predict the structural response of composite laminate structural systems up to failure.
A New Approach to Solution of Time-Independent One-Dimensional Schrödinger Wave Equation
Authors: Sinha Alok 
Published: November 2020

Abstract
A new approach has been developed in this paper to solve time-independent Schrödinger wave equation for any arbitrary potential and space varying mass as well. The method is based on the state transition matrix used in the analysis of linear time-varying systems, and can determine both bound states and reflection and transmission coefficients associated with scattering problems. Numerical examples for the computation of eigenvalues and eigenmodes associated with bound states are presented for quadratic potential, quartic potential, constant potential well and arbitrary potential well with both constant and space-varying or position-dependent masses. Similarly, transmission coefficients for scattering problems without any infinite potential, and time delays for scattering problems with an infinite potential are computed for arbitrary potential wells.
Measured Data Alignments for Monitoring Metal Additive Manufacturing Processes Using Laser Powder Bed Fusion Methods
Authors: Feng Shaw C. , Lu Yan , Jones Albert T. 
Published: November 2020

Abstract
The number and types of measurement devices used for monitoring and controlling Laser-Based Powder Bed Fusion of Metals (PBF-LB/M) processes and inspecting the resulting AM metal parts have increased rapidly in recent years. The variety of the data collected by such devices has increased, and the veracity of the data has decreased simultaneously. Each measurement device generates data in a unique coordinate system and in a unique data type. Data alignment, however, is required before 1) monitoring and controlling PBF-LB/M processes, 2) predicting the material properties of the final part, and 3) qualifying the resulting AM parts can be done. Aligned means all data must be transformed into a single coordinate system. In this paper, we describe a new, general data-alignment procedure and an example based on PBF-LB/M processes. The specific data objects used in this example include in-situ photogrammetry, thermography, ex-situ X-ray computed tomography (XCT), coordinate metrology, and computer-aided design (CAD) models. We propose a data-alignment procedure to align the data from melt pool images, scan paths, layer images, XCT three-dimensional (3D) model, coordinate measurements, and the 3D CAD model.
Analysis of High Fidelity Modeling of Drone Dynamics and Aerodynamics for Reduced Energy Consumption
Authors: Hoang Samantha , Marsh Laurel , Aliseda Alberto , Shen I. Y. 
Published: November 2020

Abstract
This paper studies the effect of rotor blade aerodynamics and rotor grouping on the accuracy of open-loop simulations with respect to generated trajectories and energy consumption for multi-rotor drones. To examine these effects an 18-rotor high performance drone carrying a 30 kg payload is used. The effect of the rotor blade aerodynamic model on simulation results is examined by comparing roll, pitch, yaw, and vertical motion trajectories produced when using blade element theory model with trajectories produced when using a lumped blade model. The results show a 20% difference between the maximum roll and pitch angle achieved, a 58% difference in maximum altitude achieved, and a 91% percent difference in the maximum yaw angle achieved. These results indicate that the choice of aerodynamic model for the rotor blades has a significant effect on the simulated trajectories and in the calculated energy consumption of those trajectories. The effect of rotor groupings on energy consumption is examined by comparing two different rotor groupings for the 18-rotor drone. Roll, pitch, and yaw motions are simulated for both groupings and the resulting energy calculation shows a 4–5% difference in energy with a motor efficiency curve and a 8–9% difference with a motor efficiency curve included in the power calculation. These results indicate that rotor grouping is important in over-actuated drones for reducing the overall energy consumption of the drone, and thus increase its endurance. This energy reduction may become especially important when closing the loop with a control system or in extreme flight conditions such as stall or strong gusts.
Orthogonal Distance Fields Representation for Machine-Learning Based Manufacturability Analysis
Authors: Balu Aditya , Ghadai Sambit , Sarkar Soumik , Krishnamurthy Adarsh 
Published: November 2020

Abstract
Computer-aided Design for Manufacturing (DFM) systems play an essential role in reducing the time taken for product development by providing manufacturability feedback to the designer before the manufacturing phase. Traditionally, DFM rules are hand-crafted and used to accelerate the engineering product design process by integrating manufacturability analysis during design. Recently, the feasibility of using a machine learning-based DFM tool in intelligently applying the DFM rules have been studied. These tools use a voxelized representation of the design and then use a 3D-Convolutional Neural Network (3D-CNN), to provide manufacturability feedback. Although these frameworks work effectively, there are some limitations to the voxelized representation of the design. In this paper, we introduce a new representation of the computer-aided design (CAD) model using orthogonal distance fields (ODF). We provide a GPU-accelerated algorithm to convert standard boundary representation (B-rep) CAD models into ODF representation. Using the ODF representation, we build a machine learning framework, similar to earlier approaches, to create a machine learning-based DFM system to provide manufacturability feedback. As proof of concept, we apply this framework to assess the manufacturability of drilled holes. The framework has an accuracy of more than 84% correctly classifying the manufacturable and non-manufacturable models using the new representation.
Improving Linearity of Circular Capacitive Pressure Sensor by Using a Dimple Mask
Authors: Bhuiyan Md Ebrahim Khalil , Shavezipur Mohammad 
Published: November 2020

Abstract
A new design concept for MEMS capacitive pressure sensors is presented that can be used to improve the linearity of the capacitance-pressure (C-T) response of the sensor. The sensor uses an extra dimple mask and etching step in the fabrication process of the device to create small bumps under the pressure sensitive and flexible membrane. Different designs, including a conventional sensor, are modeled and simulated using FEM coupled-field multiphysics solver in ANSYS®. Polycrystalline silicon is used as the structural material in the simulations. Coefficient of linear correlation between device capacitance and ambient pressure is used as the linearity factor to quantitatively compare the performance of different sensors. The finite element analysis show that the linearity factor improves from 0.938 for a conventional design to 0.973 for a design with a central bump. For a design with five bumps (one at the center of membrane and four off-center) the linearity factor increases to 0.997 for bumps of 1.5 μm thickness for wide pressure range of 0.0–4.0 MPa. The proposed design can be tailored for different applications that require certain sensor materials or different pressure ranges by using optimized sensor dimensions.
Back and Forth: Using Conversation Analysis to Explore Dialogues of Sharedness of Mental Models
Authors: Yi Sue , Damen Nicole B. , Toh Christine A. 
Published: November 2020

Abstract
Shared mental models have been shown to enhance team performance. However, research has not observed the different types of sharedness of mental models that may uniquely impact the design process. Therefore, this study examines the types of sharedness of mental models that occur in design teams using Conversation Analysis on data collected from two design teams that performed activities in the early design process in a controlled lab environment. Designers were asked to develop an agreed upon list of ranked design principles, and then generate one or two solutions using the list. These design activities allow for the examination of the varying ways that designers share knowledge, negotiate, and reach understanding. Through our analysis, we identify characteristics of conversation that designers used to build shared understanding. Our results also show how team mental models are built from patterns of conversation that are evident during open-ended and unstructured design discussions. This work sets a foundation for future research to gain a deeper understanding of how designer mental models are shared in unstructured conversations that take place during design practice.
Comparison of Parallel Elastic and Series Elastic Configurations of Vertical Hopping Spring Mass Model Controlled With Virtual Tuning of Damping
Authors: Candan Sinan Sahin , Saranli Uluc , Yazicioglu Yigit 
Published: November 2020

Abstract
Spring Loaded Inverted Pendulum (SLIP) is a simple, descriptive and accurate model to study dynamic legged locomotion. Critical design decisions to realize SLIP based legged robots with high energy efficiency and control accuracy are actuation topology and controller. Recent studies converge on series elastic actuation (SEA) and parallel elastic actuation (PEA) regarding actuation whereas, a recently introduced control method, virtual tuning of damping (VTD) have proven to be superior for SEA over other control techniques. However, actuation topology is still under discussion and it is a highly coupled problem with the control approach. In this study, vertical hoppers with PEA and SEA configurations are compared under VTD controller to determine the one results in better energy efficiency and accuracy. PEA and SEA models are extended with drive-train details to provide more realistic results. Models are simulated with various gearboxes and motors to understand their effects. Comparisons among optimum topologies showed that VTD-PEA achieves 0.02% percent apex error where VTD-SEA achieves 0.5% apex-to-apex accuracy (25 times). VTD-PEA also achieved 40% better energy efficiency and 38% higher cost of transport than VTD-SEA.
Deep Learning of (Periodic) Minimal Coordinates for Multibody Simulations
Authors: Angeli Andrea , Naets Frank , Desmet Wim 
Published: November 2020

Abstract
Mechanical systems are typically described through multi-body models with redundant coordinates, related by imposed constraints, where the dynamics is expressed with Differential Algebraic Equations. Alternatively, for rigid models, it may be preferable to employ minimal coordinates that do not require additional constraints, thus leading to Ordinary Differential Equations. However, to reduce a general multibody model to minimal coordinates and perform the simulation in the reduced space, the mapping between the minimal coordinates and the full coordinates is required. In this work, it is proposed to approximate such mapping using a neural network. In order to avoid overfitting and guarantee a continuous description of the solution manifold, the multibody dynamics information are included in the neural network training. The particular case where periodic minimal coordinates are required is treated and validated. In general, the methodology can be used when the mapping is unknown such as for spatial mechanisms with closed loops.
The Material Testing of Nanoparticle Doped 3D Printed ABS Strain Gages for Resisitance and Stiffness
Authors: Damas Sara M. , Turner Cameron J. 
Published: November 2020

Abstract
Additive manufacturing methods are becoming more prominent in the world of design and manufacturing due to their reduction of material waste versus traditional machining methods such as milling. The technology to 3D print has been around since the 1970’s. In today’s present time, we now can multi-material 3D print, however. even though we have the technology for multi-material 3D printing, standards in this field are severely lacking. Research on multi-material 3D printing and/or the combination of 3D printing filaments combined with nanoparticles is needed. One of the most common methods of 3D printing is fused deposition modeling (FDM). In this research, FDM was used to dope Acrylonitrile Butadiene Styrene (ABS), to introduce conductive properties for strain measurements.
The researchers in this paper used N-Methyl-2-Pyrrolidinone (NMP) to bind the selected nanoparticles. In the first experiment the researchers tested the conductivity of the strain gages, while in the next experiment they studied the effect the various nanoparticles had on the stiffness of the 3D printed ABS strain gages. This extensive and detailed study concluded several points. First, nickel nanoparticles consistently yields the least amount of resistance. Second, multiple binder doped nanoparticle layers yield the lowest resistance. Third, NMP, does indeed improve the performance of the nanoparticles. Finally, the research demonstrated that the various nanoparticles used, when bound increased the stiffness of the ABS strain gages.
Limits of Extramobile and Intramobile Motion of Cylindrical Developable Mechanisms
Authors: Butler Jared , Greenwood Jacob , Howell Larry L. , Magleby Spencer P. 
Published: November 2020

Abstract
Mechanisms that can both deploy and perform desired tasks offer a multifunctional advantage over traditional mechanisms. Developable mechanisms (DMs) are devices capable of conforming to a predetermined developable surface and deploying from that surface to achieve specific motions. This paper presents new terminology that defines motion of developable mechanisms while interior and exterior to a developable surface. The limits of motion are identified using defined conditions, and it is shown that the more difficult of these conditions may be treated as a non-factor during the design of cylindrical developable mechanisms given certain assumptions.
Unsupervised Method of Determining Cycle Times of Manual Assembly Processes
Authors: Renu Rahul Sharan 
Published: November 2020

Abstract
In recent years, wrist-worn devices that contain inertial measurement units have become prevalent. The data from these sensors can be used to estimate characteristics of manual processes in a manufacturing environment. The goal of this research is to determine cycle times of manually performed assembly processes using data from wrist-worn inertial sensors. Specifically, this work explores an unsupervised method of analyzing time series data to extract patterns (motifs) which represent individual cycles of an operation. From here, cycle time is computed by applying knowledge of the frequency of data collection. Testing shows that the mean cycle times obtained from stopwatch are statistically indifferent from those obtained from the proposed approach. Furthermore, results suggest that the proposed approach is insensitive to high frequency noise in the data. These encouraging results warrant further investigation and more testing.
Multi-Inputs/Outputs and Cascadable MEMS Resonator-Based Computing Devices
Authors: Tella Sherif A. , Younis Mohammad I. 
Published: November 2020

Abstract
Due to the increasing demand for smarter solutions and embedded systems, MEMS resonator-based computing devices have been under considerable attention for their simplicity and prospect of low computational power. However, most complex logic functions require multi-input/output lines that are cascadable such that the outputs of one device can be used as inputs into subsequent devices for practical applications, and this is a current limitation for MEMS logic devices. In this study, we demonstrate multi-inputs/outputs half-adder function, AND, and XOR logic gates on the basis of activating and deactivating the localization and delocalization of the multi vibrational modes of a single MEMS resonator with improved energy efficiency.