bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Effects of Obstacles on Two-Wheeled Inverted-Pendulum Transporters
Authors: Harber John , Adams Christopher , Castro Arnoldo , Singhose William
Published: January 2016

Two-wheeled inverted pendulums can be used as personal transporters. Their maneuverability and small footprint give them some desirable properties for this application. However, given the unstable mechanical design and the complicated control system that is required, inverted pendulums make complex and unexpected motions in response to both movements of the rider and disturbances from the operating environment. These complex motions lead to dynamic hazards that may cause the rider to fall off or the device to fall over. To better understand some of the complex motions, the response of a two-wheeled inverted-pendulum transporter traveling over bumps of various sizes is studied. Three effects of riding over bumps are demonstrated through an experimental investigation. When striking a bump, the transporter may bounce in the vertical direction, depending on the approach speed and size of the bump. Bumps also cause the transporter to pitch forward. When striking a bump with one wheel, the transporter turns towards the bump. All three effects can act to destabilize the machine and rider.
Optimization of Renewable Energy Power Systems for Remote Communities
Authors: Freire-Gormaly M. , Bilton A. M.
Published: January 2016

Many remote communities rely on diesel generators as their primary power source, which is expensive and harmful to the environment. Renewable energy systems, based on photovoltaics and wind turbines, present a more sustainable and potentially cost-effective option for remote communities with abundant sun and wind. Designing and implementing community-owned and operated renewable power generation alternatives for critical infrastructure such as hospitals, water sanitation, and schools is one approach towards community autonomy and resiliency. However, configuring a cost-effective and reliable renewable power system is challenging due to the many design choices to be made, the large variations in the renewable power sources, and the location specific renewable power source availability. This paper presents an optimization-based approach to aid the configuration of a solar photovoltaic (PV), wind turbine generator and lead-acid battery storage hybrid power system. The approach, implemented in MATLAB, uses a detailed time-series system model to analyze system Loss of Load Probability (LOLP) and a lifetime system cost model to analyze system cost. These models are coupled to a genetic algorithm to perform a multi-objective optimization of system reliability and cost.

The method was applied to two case studies to demonstrate the approach: a windy location (Gibraltar, UK), and a predominantly sunny location (Riyadh, Saudi Arabia). Hourly solar and wind resource data was extracted for these locations from the National Oceanic and Atmospheric Administration for five-year data sets. The village load requirements were statistically generated from a mean daily load for the community estimated based on the population and basic electricity needs. The case studies demonstrate that the mix and size of technologies is dependent on local climatic conditions. In addition, the results show the tradeoff between system reliability and cost, allowing designers to make important decisions for the remote communities.
On Design of Mechanical Metamaterials Using Level-Set Based Topology Optimization
Authors: Wang Xiao , Chen Shikui , Zuo Lei
Published: January 2016

Recently, engineered metamaterials have aroused considerable interests in many fields, due to their distinctive characteristics different from conventional materials. This paper proposes a level-set based topological optimization method for design of the mechanical metamaterials with negative Poisson’s ratio. The strain energy method is employed to predict the effective properties of the periodic microstructure. The adjoint variable method is applied to calculate the shape sensitivity, which is further used to construct the design velocity field. Finally, the level set method is applied to achieve shape evolution and topological changes of the microstructure until the desired materials properties like negative Poisson’s ratios are achieved.
Visual Performance Maps for Human Choice in Hybrid Electric Vehicle’s In-Wheel Motors: Part I — Purchase Criteria
Authors: Lee Hoon , Ashok Pradeepkumar , Tesar Delbert
Published: January 2016

Satisfying human needs means to respond directly to human choice / human commands at the time of purchase, in real time operation, for maintenance / tech mods over the life history of the vehicle, and for refreshment in the future hybrid electric vehicles (HEV) equipped with four-independent in-wheel motors (IWM). This leads to maximizing human choice. To meet human choice means not only to keep the human fully informed on a series of choices, but also to maximize their self-awareness.

Meeting human choice requires visual performance maps. Based on the future HEV with an open (modular) architecture, visual performance maps help customers make right choices what they want, so that a vehicle can be tailored to a particular customer priority such as cost and drivability for an aggressive driver. This paper demonstrates how different types of an IWM are matched to different types of customers. The decision framework developed in this paper is based on detailed human needs structured by performance maps to visually guide the customer in terms of purchase / operation / maintenance / refreshment decisions. Part I is focused on purchase criteria, while Part II discusses operation / maintenance / refreshment criteria.
Effect of Sitting Occupancy on Lateral Dynamics and Trajectory of a Passenger Car
Authors: Joshi Divyanshu , Deb Anindya
Published: January 2016

In the current work, the effects of sitting locations and combinations of occupants on handling performance of a four-wheeled passenger car have been investigated. A new multi-occupant nonlinear lumped parameter model (LPM) is developed by coupling 1-DOF longitudinal vehicle model, 2-DOF lateral vehicle model, 13-DOF nonlinear vehicle ride model including seats, 6-DOF nonlinear human occupant model, and 1-DOF tire model. The combined model with a maximum of 50 degrees-of-freedom (in case of all five seats occupied) is simulated in MATLAB/SIMULINK environment. Model subsystems i.e. occupant and vehicle models including tires are validated independently by comparing biodynamic responses of seated occupants, vehicle vertical response and handling behavior with published results. The coupled model can facilitate the study of vehicle dynamics considering the combined effects of road inputs, vehicle maneuvering and seat occupancy while taking into account the nonlinear behavior of vehicle suspension. Further the yaw rate and vehicle trajectories are compared and studied for various cases of sitting occupancies at a given vehicle velocity with a road input representing harsh and abrupt scenario. The current study shows that appreciable changes in yaw rate and vehicle trajectory can be caused due to varying sitting occupancies and vehicle velocities.
Optimization of Cutting Conditions in Vibration Assisted Drilling of Composites via a Multi-Objective EGO Implementation
Authors: Sadek Ahmed , Aly Mohamed , Hamza Karim , Meshreki Mouhab , Nassef Ashraf O. , Attia Helmi
Published: January 2016

A recent and promising technique to overcome the challenges of conventional drilling is vibration-assisted drilling (VAD) whereby a controlled harmonic motion is superimposed over the principal drilling feed motion in order to create an intermittent cutting state. Two additional variables other than the feed and the speed are introduced, namely the frequency and the amplitude of the imposed vibrations. Optimum selection of cutting conditions in VAD operations of composite materials is a challenging task due to several reasons; such as the increase in the number of controllable variables, the need for costly experimentation, and the limitation on the number of experiments that can be performed before tool degradation becomes an issue in the reliability of measurements. Additionally, there are often several objectives to consider, some of which may be conflicting, while others may be somewhat correlated. Pareto-optimality analysis is needed for conflicting objectives; however the existence of several objectives (high-dimension Pareto space) makes the generation and interpretation of Pareto solutions difficult. An attractive approach to the optimization task is thus to employ Kriging meta-models in a multi-objective efficient global optimization (m-EGO) framework for incremental experimentation of optimal setting of the cutting parameters. Additional challenge posed by constraints on machine capabilities is accounted for through domain transformation of the design variables prior to the construction of the Kriging models. Study results using a baseline exhaustive experimental data shows opportunity for employing m-EGO for the generation of well distributed Pareto-frontiers with fewer experiments.
Constrained Multi-Objective Wind Farm Layout Optimization: Introducing a Novel Constraint Handling Approach Based on Constraint Programming
Authors: Sorkhabi Sami Yamani Douzi , Romero David A. , Beck J. Christopher , Amon Cristina H.
Published: January 2016

Recently, land has been exploited extensively for onshore wind farms and turbines are frequently located in proximity to human dwellings, natural habitats, and infrastructure. This proximity has made land use constraints and noise generation and propagation matters of increasing concern for all stakeholders. Hence, wind farm layout optimization approaches should be able to consider and address these concerns. In this study, we perform a constrained multi-objective wind farm layout optimization considering energy and noise as objective functions, and considering land use constraints arising from landowner participation, environmental setbacks and proximity to existing infrastructure. The optimization problem is solved with the NSGA-II algorithm, a multi-objective, continuous variable Genetic Algorithm. A novel hybrid constraint handling tool that uses penalty functions together with Constraint Programming algorithms is introduced. This constraint handling tool performs a combination of local and global searches to find feasible solutions. After verifying the performance of the proposed constraint handling approach with a suite of test functions, it is used together with NSGA-II to optimize a set of wind farm layout optimization test cases with different number of turbines and under different levels of land availability (constraint severity). The optimization results illustrate the potential of the new constraint handling approach to outperform existing constraint handling approaches, leading to better solutions with fewer evaluations of the objective functions and constraints.
Creating a Digital Homework Set for a Kinematics and Dynamics of Machinery Course
Authors: Canfield Stephen L. , Hill Scott , Hill Tristan , Zuccaro Stephen
Published: January 2016

Dynamics of Machinery is a traditional engineering course; in fact kinematics was one of the earliest fields of study in engineering. The course relies on a strong combination of learning new theory and acquiring the skills to apply this theory through regular and repeated practice. This practice is commonly incorporated through homework sets, provided through a combination of book or instructor-given assignments. This homework includes testing conceptual understanding of key concepts, creating kinematic schematics, vector model construction, constructing equations, and performing mathematical analyses. The use of online, electronic tools for automating homework has been widely incorporated in K-12 education and in some college-level curriculum, but not, to the authors’ knowledge, significantly in a kinematics and dynamics of machinery class. This paper will present a framework for creating these problems, provide an overview of an entire set of problems associated with the common kinematics curriculum, and present an evaluation of this digitized coursework throughout four semesters of implementation.
Analytical Methods for Solution Sets of Interval Wrench
Authors: Notash Leila
Published: January 2016

Methodologies for calculating the solution set of actuator inputs, in the presence of uncertainty/error in parameters/data, are investigated. The enclosure for the vector of actuator torques is formulated utilizing the interval forms of the Jacobian matrix and external wrench. Two analytical methods are utilized to identify the solution set; one method generates the rays that bound the solution set in each orthant, and the other one is based on parameterizing the interval entries of the Jacobian matrix and wrench. For the parametric method, the existence of dominant parameter groups to produce the whole solution set (or a subset of solution set) is examined. Implementation of these methods on example parallel manipulators are presented to identify the solution set for the actuator torques, and the results are verified with the discrete method.
Design of Propeller-Assisted Flapping Wing Air Vehicles for Enhanced Aerodynamic Performance
Authors: Holness Alex E. , Bruck Hugh , Gupta S. K.
Published: January 2016

Flapping flight is impressive because aerodynamic performance increases whereas fixed wing aircraft performance declines in low Reynolds regimes. In order to achieve biologically-inspired flapping, motion in multiple degrees of freedom is required and power density requirements must be satisfied. Given the mass of high output actuators, weight is a key limitation as it must be offset for flight. In light of this, only recently, with developments in motor technology, has independent wing control been achieved with consumer available components. Due to power demands, motor bandwidth is used largely to sustain flight, limiting the effect of wing independence. An interesting paradigm is one where the aerodynamic flight advantages of propeller-driven flight are utilized in addition to those of flapping wings to allow hybrid vehicles that can occupy unique operational bandwidth. In this work, a propeller-assisted version of Robo Raven, a miniature independent wing flapping air vehicle developed at the University of Maryland College Park, is presented. Having successfully flown with propeller assistance and having demonstrated improved force generation for aerodynamic performance over flapping alone, this modified Robo Raven will constitute the next major iteration of the vehicle as Robo Raven V.
Robotic Assistive Device for Phlebotomy
Authors: Carvalho Paulo , Kesari Anurag , Weaver Sean , Flaherty Patrick , Fischer Gregory S.
Published: January 2016

Phlebotomy is a routine task, performed over a billion times annually in the United States alone, that is essential for proper diagnosis and treatment. We designed and constructed Phlebot, a robotic assistive device that uses a novel combination of near-infrared (NIR) monocular imaging and force-feedback to guide a needle into a forearm vein for blood sample collection or intravenous catheterization. Through initial validation on phantoms, we show that our approach offers a feasible and reliable method to automate phlebotomy. We envision the device to be a first major step towards more affordable point-of-care testing and diagnostic healthcare systems. In the long term, we expect that Phlebot will expedite healthcare delivery and drastically reduce needle stick injuries, instances of hemolysis, and infections caused by blood-borne pathogens.
Advancing Student Learning of Design for Additive Manufacturing Principles Through an Extracurricular Vehicle Design Competition
Authors: Williams Christopher B. , Sturm Logan , Wicks Alfred E.
Published: January 2016

A lack of knowledge of how to design products specifically for Additive Manufacturing (AM, also referred to as “3D Printing”) is often viewed as a barrier to industrial adoption of the technology. To advance the AM workforce, the author hosted a 10-week university-wide extracurricular competition that challenged students to design, build, and operate remotely piloted ground and air vehicles made entirely via AM and a standardized electronics kit. The context of the competition was guided by the Department of Defense’s shared vision for forward deployment of AM systems to provide agile on-site part production and reduction of supply chain complexity. The competition vehicles were designed to allow future deployed military or civilian engineers to fabricate remotely-piloted vehicles while in battlefield or austere environmental conditions, such as the site of a natural disaster to search for survivors or to carry out reconnaissance missions. The competition served as unique informal learning environment that engaged over 200 students in the emerging principles of “design for Additive Manufacturing” (DfAM). In this paper, the author presents an overview of the competition structure, and the results of preliminary assessment of the students’ gains in design learning.
Designing a Self-Replicating Robotic Manufacturing Factory
Authors: Manion Charlie , Soria Nicolás F. , Tumer Kagan , Hoyle Chris , Tumer Irem Y.
Published: January 2016

This paper presents a Multiagent Systems based design approach for designing a self-replicating robotic manufacturing factory in space. Self-replicating systems are complex and require the coordination of many tasks which are difficult to control. This paper presents an innovative concept using Multiagent Systems to design a robotic factory for space exploration. Specifically presented is an approach for coordinating a conceptual model of a self-replicating system. The arrival of a set of agents on an unknown planet is simulated, whereby these simple agents will expand into a self-replicating factory using the regolith gathered from the surface of the planet. NASA is currently investing in space exploration missions that consider using the resources on the surface of other planets, asteroids or satellites. The challenge of the project is in the implementation of a learning algorithm that allows a large number of different agents to complete simultaneous tasks in order to maximize productivity. The simulation in this work is able to present the coordination of the agents during the construction of the factory as the parameters of the learning algorithm are changed. System performance is measured with a pre-programmed method, using local and difference rewards. The results show the advantage of using a learning algorithm to better build the robotic factory.
In Vivo Testing of Noninvasive ICP Monitoring Methodology in a Porcine Model
Authors: Hawks Jeff A. , Pfeifer Chase , Twedt Max , Bashford Greg , Thorell William , Gigantelli James
Published: January 2016

Research has suggested that elevated intracranial pressure (ICP) can cause damage to the optic nerve and reduce visual acuity. There is a need for noninvasive ICP monitoring devices. A simple, portable device capable of measuring relative changes in ICP using a noninvasive methodology would have a significant impact on clinical care. The methodology presented in this paper utilizes transcranial Doppler ultrasonography to monitor ophthalmic artery hemodynamics while small forces are applied to cornea. In vivo testing using a porcine model results in a correlation between pulsatility or resistivity indices and ICP levels. Specifically, the change in these indices while force is applied decreases as ICP increases. The data collection prototype used in these experiments contained an ultrasound transducer instrumented with a load cell to measure force applied to the cornea. These experiments are an initial step towards adapting the data collection prototype into a handheld noninvasive ICP monitoring device.
Quantifying Control Authority in Periodic Motions of Underactuated Mobile Robots
Authors: Post David C. , Goodwine Bill , Schmiedeler James P.
Published: January 2016

The locomotion of legged robots is inherently underactuated, which creates control challenges in terms of rejecting large disturbances. A detailed understanding of how the control authority of a robot evolves over a gait trajectory has the potential to inform the design of controllers that offer superior disturbance rejection capabilities without compromising the efficiency benefits that typically accompany underactuated legged robots. Previous work has shown how the system velocities of an underactuated mechanical system can be decomposed into directions aligned with the inputs, or controlled directions, and directions orthogonal to the inputs, or uncontrolled directions, and applied that decomposition to drive wheeled robots to rest. This decomposition fundamentally provides a measure of the instantaneous control authority of the robot. This paper examines how the same techniques can be applied to inform the control of biped robots walking with periodic gaits. This problem differs from those previously studied in that it necessarily involves ground impacts and non-zero desired velocities. A representative example of a two-link planar biped walking on flat ground shows how a simple open loop controller that implements heuristics identified through the velocity decomposition to make use of the available control authority can improve disturbance rejection when added to a hybrid zero dynamics-based controller.
A Detailed Five-Year Review of Medical Device Additive Manufacturing Research and its Potential for Translation to Clinical Practice
Authors: Stephenson Katherine
Published: January 2016

This paper provides a systematic review of over 350 publications that document specific medical device examples in which the design and manufacturing relied on additive manufacturing processes (more popularly referred to as “3d Printing”). Existing reviews on 3d printing for medical device design focus on the range of clinical applications and potential uses for this technology. However, existing work tends to omit key medical device development and regulatory requirements pertaining to the use of 3d printing for technology translation. These omissions often present a skewed view of each device’s potential for rapid translation to commercialization and common clinical practice.

To fill gaps in existing literature, this review includes medical device journal articles and identifies each article’s country of origin, the product development stage in which 3d printing was used, and the device’s specific type and classification under the U.S. Food and Drug Administration. The findings from this systematic review provide a detailed international snapshot of current additive manufacturing research and its near term potential for changing clinical practice.
Control of Multiple Magnetic Micro Robots
Authors: Wong Denise , Wang Jeremy , Steager Edward , Kumar Vijay
Published: January 2016

A magnetic micro robot is a microscopic magnet that is controlled by a system of electromagnetic coils that generate a magnetic field to manipulate the magnetic robot. A major challenge for manipulating multiple magnets at microscale is that the applied field affects the entire workspace, making it difficult to address individual magnets. In this paper, we propose a system where electromagnetic coils are close to the magnets being manipulated to exploit spatial non-uniformities in the magnetic field. Our model considers the magnetic field generated by the electromagnetic coils and the magnetic fields present from neighboring magnetic robots to generate the desired force on each magnet. This approach is demonstrated on a macroscopic, one-dimensional system with two magnets controlled by two electromagnets using visual feedback control. Additionally, simulation results for a linear system with three magnets and three electromagnets are shown. While demonstrated at the macroscale, our results suggest that our methods can be extended for microscale manipulation, where it is advantageous to control multiple identical magnets with global fields.
Function Extrapolation at One Inaccessible Point Using Converging Lines
Authors: Zhang Yiming , Kim Nam Ho , Park Chanyoung , Haftka Raphael T.
Published: January 2016

Focus of this paper is on the prediction accuracy of multidimensional functions at an inaccessible point. The paper explores the possibility of extrapolating a high-dimensional function using multiple one-dimensional converging lines. The main idea is to select samples along lines towards the inaccessible point. Multi-dimensional extrapolation is thus transformed into a series of one-dimensional extrapolations that provide multiple estimates at the inaccessible point. We demonstrate the performance of converging lines using Kriging to extrapolate a two-dimensional drag coefficient function. Post-processing of extrapolation results from different lines based on Bayesian theory is proposed to combine the multiple predictions. Selection of lines is also discussed. The method of converging lines proves to be more robust and reliable than two-dimensional Kriging surrogate for the example.
Sprung Mass Motion Emulation in a Braking Test Rig
Authors: Wang Chunjian , Wang Qian , Anderson Jeffery , Ayalew Beshah
Published: January 2016

This paper describes a quarter-car braking test rig that includes a hardware-in-the-loop (HIL) means for emulating broader vehicle dynamic effects. The test rig utilizes actual vehicle components such as the suspension-tire assembly and braking system to accurately represent a vehicle during a braking event and a chassis dynamometer’s drum is used to simulate the longitudinal vehicle dynamics. The key problem addressed in this paper is the emulation of sprung mass motion with a commercial electromagnetic linear actuator. By accurately representing the motion, detailed effects such as load transfer that happens in a real braking process can be studied for its effect on the braking performance. The stability of the system with sprung mass emulation under different actuator control modes is analyzed. The successful and stable control scheme found is a cascaded control with a velocity tracking strategy. The workings of the test are illustrated via representative test results that include a locked-wheel braking event and a stop with an anti-lock braking system (ABS).
A 4-DOF Robot for Positioning Ultrasound Imaging Catheters
Authors: Loschak Paul M. , Tenzer Yaroslav , Degirmenci Alperen , Howe Robert D.
Published: January 2016

In this paper we present the design, fabrication, and testing of a robot for automatically positioning ultrasound imaging catheters. Our system will point ultrasound (US) catheters to provide real-time imaging of anatomical structures and working instruments during minimally invasive surgeries. Manually navigating US catheters is difficult and requires extensive training in order to aim the US imager at desired targets. Therefore, a four DOF robotic system was developed to automatically navigate US imaging catheters for enhanced imaging. A rotational transmission enables three DOF for pitch, yaw, and roll of the imager. This transmission is translated by the fourth DOF. An accuracy analysis was conducted to calculate the maximum allowable joint motion error. Rotational joints must be accurate to within 1.5° and the translational joint must be accurate within 1.4 mm. Motion tests were then conducted to validate the accuracy of the robot. The average resulting errors in positioning of the rotational joints were measured to be 0.28°–0.38° with average measured backlash error 0.44°. Average translational positioning and backlash errors were measured to be significantly lower than the reported accuracy of the position sensor. The resulting joint motion errors were well within the required specifications for accurate robot motion. Such effective navigation of US imaging catheters will enable better visualization in various procedures ranging from cardiac arrhythmia treatment to tumor removal in urological cases.
Adaptation of Rehabilitation System Based on User’s Mental Engagement
Authors: Esfahani Ehsan T. , Pareek Shrey , Chembrammel Pramod , Ghobadi Mostafa , Kesavadas Thenkurussi
Published: January 2016

Recognition of user’s mental engagement is imperative to the success of robotic rehabilitation. The paper explores the novel paradigm in robotic rehabilitation of using Passive BCI as opposed to the conventional Active ones. We have designed experiments to determine a user’s level of mental engagement. In our experimental study, we record the brain activity of 3 healthy subjects during multiple sessions where subjects need to navigate through a maze using a haptic system with variable resistance/assistance. Using the data obtained through the experiments we highlight the drawbacks of using conventional workload metrics as indicators of human engagement, thus asserting that Motor and Cognitive Workloads be differentiated.

Additionally we propose a new set of features: differential PSD of Cz-Poz at alpha, Beta and Sigma band, (Mental engagement) and relative C3-C4 at beta (Motor Workload) to distinguish Normal Cases from those instances when haptic where applied with an accuracy of 92.93%. Mental engagement is calculated using the power spectral density of the Theta band (4–7 Hz) in the parietal-midline (Pz) with respect to the central midline (Cz). The above information can be used to adjust robotic rehabilitation parameters I accordance with the user’s needs. The adjustment may be in the force levels, difficulty level of the task or increasing the speed of the task.
Dual-Stiffness Behavior of Fatigued Tire Rubber
Authors: Liu Ruofan , Sancaktar Erol
Published: January 2016

We report on duality in stiffness values for both carbon black and silica-filled SBR-based (styrene butadiene rubber) tire rubber materials after cyclic loading (and not with no-cycle, neat samples). We believe, this behavior is due to morphological changes occurring due to cycling and not necessarily due to larger scale void/crack initiation. Causes may be chain breakage, reduced crosslinking in all samples, and agglomerate break-up/particle redistribution in silica systems, which represent early damage initiation and morphological changes in these systems. Therefore, we get a dual stiffness vs. strain behavior which is essentially superposition of two separate stiffness vs. strain curves, each being similar to the stiffness-strain curves for the neat (no fatigue) samples. We believe that the second superposed portion represents the sections deteriorated/rearranged due to cyclic loading (lower crosslinking/rearranged particle distributions) coming in-line during the straining process, and when the non-deteriorated/non-rearranged sections weaken.
A Virtual Reality Application for Additive Manufacturing Process Training
Authors: Renner Alex , Holub Joseph , Sridhar Shubang , Evans Gabe , Winer Eliot
Published: January 2016

The promise of cheap and widely available 3D printers may be one of the best and worst aspects of Additive Manufacturing (AM). A non-technical consumer may pay significantly more for a 3D printer with “no assembly required”. Since it is reasonable to assume that they may not understand how the printer works and what will come out of it, they may wind up returning it because it does not meet their expectations. While consumers are starting to use 3D printers, designers in industry are utilizing Rapid Prototyping (RP) machines to manufacture final products in addition to prototypes. Designers will need to know AM principles in order to communicate design specifications to a RP lab technician so that a part passes Quality Assurance inspection. Training users on fundamental layer-based manufacturing methods can assist before and after a 3D printer purchase and reduce the strain on RP labs in industry.

This paper presents an extensible software application that simulates an AM process in a Virtual Reality (VR) environment. The application parses machine component movements and printed segment attributes from G-code files exported from the MakerBot® Computer Aided Manufacturing (CAM) software. Position, speed, and type of movement are used to simulate the physical machine movements. A print “segment” is created at the start and end positions of a print movement. Color-coding segment attributes and modifying their size and shape establishes a visual relationship between terminology for a print setting and its representation in the virtual environment. This visual relationship between printed segments and print settings makes it easier to learn the 3D printing process and associated terminology. Novice and expert users can modify print settings in the virtual environment before and after printing a prototype. Identifying and fixing a mistake in the virtual environment reduces the time and cost to print a part with the desired quality.

Training multidisciplinary users in a virtual world allows them to explore AM processes in detail from any angle or scale desired. This application has been tested in a cube shaped virtual reality CAVE system with each side measuring ten feet powered by a 96-node graphics computer cluster. Approximately 20 hours of demonstrations have been performed for public outreach programs related to STEM initiatives and visitors from industry who have had a variety of AM experience.
Using Two-Third Power Law for Segmentation of Hand Movement in Robotic Assisted Surgery
Authors: Shafiei Somayeh B. , Guru Khurshid A. , Esfahani Ehsan T.
Published: January 2016

In this study, we have developed a robust and accurate algorithm based on concept of two-third power law in human motor control to segment the hand trajectory of robotic surgeons into smaller segments. We hypothesis that tracking a longer trajectory is subjected to higher cognitive workload that may lead in to an imperfect CNS performance in programming muscle activation which will lead to more number of segment trajectories and pause points in hand movements.

To test our hypothesis, after segmenting the trajectory, we determine the correlation between affine velocity and workload extracted from Surgeon’s Electroencephalography (EEG) features. EEG features are extracted by using brain waves recorded by wireless brain computer interface (B-Alert X-10 system). In our experimental study, 2 groups of participants three “experts” and five “Competent and Proficient” performed Urethro-vesical Anastomosis on an inanimate model, using the da-Vinci Surgical System® (Sunnyvale, CA).
Pseudo Elimination of Geometry Dependence in Surrogate Models of Distributed Knee Loads From an Explicit Dynamic Finite Element Analysis
Authors: Adams Matthew J. , Silverman Anne K. , Turner Cameron J.
Published: January 2016

The premise of a total knee replacement (TKR) is to alleviate pain and increase joint mobility. The expected 20 year life span of the knee insert exceeds that of the standard patient given traditional wear and tear. With more active lifestyles, greater wear rates and shorter life spans are predicted for tibial inserts. Greater wear rates increase the probability that a patient will require additional surgery later in life. This research provides a knee loading model to estimate the pressure loading distribution through Finite Element Modeling (FEM). The publicly available patient data was used to eliminate the geometry dependence in a surrogate model of distributed knee loads from an explicit Finite Element Analysis (FEA). The developed method based upon FEM and FEA, produced two notable results. The secondary results showed the FEM accurately estimated the medial and lateral contact forces during the stance phase. However, the primary result was that the surrogate model successfully interpolated the contact surface forces using results from the FEA without requiring any knowledge of the geometry of the contact surfaces.
Optimization of Process Parameters in Laser Engineered Net Shaping (LENS) Deposition of Multi-Materials
Authors: Yan Jingyuan , Masoudi Nafiseh , Battiato Ilenia , Fadel Georges
Published: January 2016

During the past few years, metal based additive manufacturing technologies have evolved and may enable the direct fabrication of heterogeneous objects with full spatial material variations. A heterogeneous object has potentially many advantages and in many cases can realize appearance and/or functionality that homogeneous objects cannot achieve. In this work we employ a preprocess computing combined with a multi-objective optimization algorithm based on the modeling of the LENS deposition of multiple materials to optimize the fabrication process. The optimization methodology is applied to the fabrication of cermet composite (using Inconel 718 and ceramic powders) with prescribed material feeding rates. The multi-objective optimization considers that the energy consumption and the material waste during the fabrication process should be minimized, while the probability of the melting of the powders should be maximized. The optimization software modeFRONTIER® is used to drive the computation procedure with a MATLAB code. The results show the design and objective spaces of the Pareto optimal solutions, and enable the users to select preferred setting configurations from the set of optimal solutions.
Analysis of Contact Mechanics and Smoothed Particle Hydrodynamic Simulations of Viscoelastic Polymer Sine Waves
Authors: Cramer Nick , Chao Janet , Tollefson Travis , Teodorescu M.
Published: January 2016

According the American Cancer Society’s data, in 2013, an estimated 53,640 people developed head and neck cancers [1], which accounts for about 3% to 5% of all cancers in the United States. Removing head and neck malignant neoplasms is one of the first stages towards patient recovery. However, these types of invasive procedures often lead to disfiguring scars and resections with functional and aesthetical drawbacks (see Figure 1).
Designing a Fast Adaptive Clustering Approach for Traffic Wave Simulation
Authors: Lan Lijun , Wu Xian , Liu Ying
Published: January 2016

Traffic wave, also known as stop wave or traffic shockwave, is travelling disturbance in the distribution of vehicles on the highways. In this paper, we attempt to study this problem using a simulation approach. Largely inspired by an interesting observation from ant chain movement, we explore how such a vivid pattern can be mathematically modeled and whether the similar way of behavior is helpful for dealing traffic wave issue in our highway systems. Therefore, a decentralized fast-adaptive clustering approach is proposed jointly with considerations for traffic optimization. To validate the proposed approach and to better understand its mechanism in lifting traffic flow, simulation study is carried out using real-world traffic data. Results have revealed the applicability and effectiveness of the proposed approach and have also indicated that both road configuration and traffic demand affect the effectiveness of the proposed model.
Autonomous Robotic System for Pin Pulling Operation in Rail Yard
Authors: Boddiford Andrew , Chheda Dhiral , Hammel Chris , Ashok Pradeepkumar , Tesar Delbert
Published: January 2016

The railroad industry expends significant effort to increase operational safety and efficiency by using a variety of sensors for machine health monitoring and inspection purposes. This paper proposes to advance rail technology even further to use similar sensor data for the control of a robotic system designed to automate the uncoupling of freight cars, a hazardous operation that currently requires human operators to interact with moving trains. To automate this process, an intelligent robotic system was developed to detect, track, approach, grasp, and manipulate semi-constrained objects on equipment in motion. This work presents a system prototype that utilizes machine vision, force feedback, and complex end-effector technology capable of autonomously uncoupling full-scale freight cars using visual and tactile feedback. Laboratory tests have proven that modern robotic and sensing hardware can be used to reliably separate pairs of rolling stock at 3.25 kilometers per hour. The results to date suggest that speeds of up to 7 km/h are feasible for a system deployed in a rail yard.
Sequential Cooperative Robust Optimization (SCRO) for Multi-Objective Design Under Uncertainty
Authors: Hamel J. M.
Published: January 2016

The optimal design of systems under uncertainty is a critical challenge faced by design engineers. Robust optimization is a well-studied and widely used technique for the design of engineering systems that possess uncertainty, and numerous robust optimization techniques have been presented in recent years. The majority of the robust optimization techniques presented in the literature suffer from a computational efficiency challenge, either due to the expense of obtaining objective or constraint function uncertainty information, or due to the fact that many robust optimization approaches (with a few notable exceptions) require that a potentially expensive uncertainty analysis calculation (e.g. Monte-Carlo simulation) be nested within an already potentially expensive optimization solver (e.g. a genetic algorithm). Additionally, many robust optimization approaches focus solely on design problems that possess a single design objective, and the robust techniques that do consider problems with multiple design objectives often require various simplifying assumptions or are even more computationally expensive to implement. Clearly there are opportunities for improvement in the area of robust optimization, and this paper presents a new robust design Optimization approach called Sequential Cooperative Robust Optimization (SCRO), which uses both a sequential approach and multi-objective optimization techniques in an effort to decouple the deterministic system optimization problem from the associated uncertainty analysis problem. The SCRO approach first fits surrogate models to the system objective and constraint functions, in addition to system sensitivity functions, using as few function calls as possible in order to improve computational efficiency. The approach then performs a series of sequential multi-objective optimizations using the developed surrogate models. These optimizations work to find points in the design space that are optimal with respect to deterministic performance and both objective and feasibility robustness metrics based on predicted system sensitivities. The SCRO approach has the potential to find solutions not available to other robust optimization approaches, and can be more efficient than other more traditional robust optimization techniques due to its use of surrogate approximation and a sequential framework.
A Novel Approach to the Design and Development of an Interactive Learning App for Automotive IVI Systems
Authors: Chen Yifan , Tonshal Basavaraj , Mitra Pramita , Simonds Craig , Aldighieri Paul
Published: January 2016

Since its launch Ford SYNC™ with MyFord Touch™ in-vehicle infotainment (IVI) system has migrated to many vehicle programs and had multiple software updates, which presented Ford dealers with the ever-increasing challenge of training new owners effectively and efficiently. This paper presents the design, architecture and implementation of “MyFord Touch Guide”, a novel, cross-platform mobile app that delivers a unique MyFord Touch learning and familiarization experience for dealers and consumers alike. This app incorporates the production MyFord Touch graphical user interface for an interactive learning experience. Additionally, it integrates a host of video tutorials featuring a computer-animated character, which offers an insightful, personalized and self-guided tour experience of the essential features and functions of the system. MyFord Touch Guide is a cross-platform app and based on a “hybrid” app architecture that uses both native mobile and web technologies. Feedback gathered from multiple nation-wide surveys indicates that the proposed approach provides a highly effective and scalable solution towards developing a diverse range of cross-platform, interactive, mobile learning apps.
Solution to Three-Dimensional Indeterminate Contact and Impact With Friction Using Rigid Body Constraints
Authors: Rodriguez Adrian , Chatterjee Abhishek , Bowling Alan
Published: January 2016

This work analyzes three-dimensional multibody systems undergoing indeterminate contact and impact in the presence of Coulomb friction. A discrete approach is used to analyze the impact behavior upon detection of the impact events during simulation. During an impact event, the velocities of the impact points describe the systems state and can be studied to characterize the nature of impact and determine the post-impact behavior of the system. The velocities of the impact points during an impact event can be described in terms of the impulses at those points. This work uses Amontons-Coulombs law of friction and rigid body constraints to develop a technique for reducing the number of impulses required to compute the velocities of the impact point during the impact event. Indeterminacies associated with slip direction arise, when Coulombs friction is considered. Therefore, a numerical approach is used to evolve the slip direction along with the slip velocity, with respect to a normal impulse. The work-energy theorem is used to detect the end of the impact event, and determine the post-impact velocities of the system. Examples of a three-dimensional rocking block and a sphere impacting a corner are analyzed to demonstrate the proposed methodology.
Haptic Assembly Using Skeletal Densities and Fourier Transforms
Authors: Behandish Morad , Ilieş Horea T.
Published: January 2016

Haptic-assisted virtual assembly and prototyping has seen significant attention over the past two decades. However, in spite of the appealing prospects, its adoption has been slower than expected. We identify the main roadblocks as the inherent geometric complexities faced when assembling objects of arbitrary shape, and the computation time limitation imposed by the notorious 1 kHz haptic refresh rate. We solved the first problem in a recent work by introducing a generic energy model for geometric guidance and constraints between features of arbitrary shape. In the present work, we address the second challenge by leveraging Fourier transforms to compute the constraint forces and torques. Our new concept of ‘geometric energy’ field is computed automatically from a cross-correlation of ‘skeletal densities’ in the frequency domain, and serves as a generalization of the manually specified virtual fixtures or heuristically identified mating constraints proposed in the literature. The formulation of the energy field as a convolution enables efficient computation using GPU-accelerated Fast Fourier Transforms (FFT). We show that our method is effective for low-clearance assembly of objects of arbitrary geometric and syntactic complexity.
Ensemble Neural Network Model for Predicting the Energy Consumption of a Milling Machine
Authors: Ak Ronay , Helu Moneer M. , Rachuri Sudarsan
Published: January 2016

Accurate prediction of the energy consumption is critical for energy-efficient production systems. However, the majority of existing prediction models aim at providing only point predictions and can be affected by uncertainties in the model parameters and input data. In this paper, a prediction model that generates prediction intervals (PIs) for estimating energy consumption of a milling machine is proposed. PIs are used to provide information on the confidence in the prediction by accounting for the uncertainty in both the model parameters and the noise in the input variables. An ensemble model of neural networks (NNs) is used to estimate PIs. A k-nearest-neighbors (k-nn) approach is applied to identify similar patterns between training and testing sets to increase the accuracy of the results by using local information from the closest patterns of the training sets. Finally, a case study that uses a dataset obtained by machining 18 parts through face-milling, contouring, slotting and pocketing, spiraling, and drilling operations is presented. Of these six operations, the case study focuses on face milling to demonstrate the effectiveness of the proposed energy prediction model.