bluuebunny/crossref_metadata_2025 huggingface dataset:
Generation and Mapping of Minimally-Restrictive Manufacturability Constraints for Mechanical Design Problems
Authors: Patterson Albert E. , Allison James T.
Published: November 2019

Traditional design-for-manufacturing (DFM) strategies focus on efficiency and design simplification and tend to be too restrictive for optimization-based design methods; recent advances in manufacturing technologies have opened up many new and exciting design options, but it is necessary to have a wide design space in order to take advantage of these benefits. What is needed is a simple but effective approach for restricting the design space to designs which are guaranteed to be manufacturable, but which leave intact as much of the design space as possible. Work has been done in this area for some specific domains, but a general method for accomplishing this has not yet been refined. This article presents an exploration of this problem and developed a framework for mapping practical manufacturing knowledge into mathematical manufacturability constraints in mechanical design problem formulations. The steps for completing this mapping and the enforcing the constraints are discussed and demonstrated. Three case studies (a milled heat exchanger fin, a 3-D printed topologically-optimized beam, and a pulley requiring a hybrid additive-subtractive process for production) were completed to demonstrate the concepts; these concepts include problem formulation, the generation and enforcement of the manufacturability constraints, and fabrication of the resulting designs with and without constraints.
A Goal-Oriented, Inverse Decision-Based Method for an American Football Helmet
Authors: Fonville Tate R. , Nellippallil Anand Balu , Horstemeyer M. F. , Allen Janet K. , Mistree Farrokh
Published: November 2019

We design two components of an American football helmet (composite shell and foam liner) to illustrate the efficacy of a goal-oriented, inverse decision-based design method for multi-component product design. The method is goal-oriented because we first identify the end performance system level goals for the helmet, namely, dissipate impact energy, minimize impulse, and minimize helmet weight. We arrange the components in the order that they receive impact energy and then find satisficing solutions for the foam liner to achieve the system-level goals as close as possible, and then we adjust the targets for the composite shell to reduce the helmet weight without a substantial loss in performance. We use the Concept Exploration Framework to systematically gather information about each component, and the compromise Decision Support Problem to generate satisficing solutions under uncertainty. Finally, we verify our design decisions with Finite Element Analysis. Although the results are interesting, our focus is to establish the efficacy of the inverse method for the design of an American football helmet.
Kinematic Analysis of the Exechon Robot Accounting Offsets in the Joint Axes
Authors: López-Custodio P. C. , Dai J. S. , Fu R. , Jin Y.
Published: November 2019

An Exechon robot with offsets between the axes of the joints that connect the legs to the fixed platform is analyzed for the first time. Ideally these axes intersect constituting two universal and one spherical joint. The insertion of imperfections in these universal and spherical joints leads to more complex forward and inverse kinematics which are solved in this paper. It is proved that the equations used for the kinematics of the ideal Exechon robot are no longer applicable when these offsets are added. The constraint system is also obtained and it is found to be different to the one of the ideal case. Finally, the combination of offsets that lead to the largest deviation in the position of the parallel platform is determined.
Study of a Biomimetic Energy-Efficient Thruster for Underwater Vehicles
Authors: Palmieri Giacomo , Callegari Massimo , Costa Daniele , Palpacelli Matteo-Claudio , Scaradozzi David
Published: November 2019

The paper presents the dynamic optimization of a biomimetic thruster for autonomuos underwater vehicles with the goal of increasing the energy efficiency of the vehicle. The main design drivers of the project are: to design a propulsion system consisting in an oscillating caudal fin; to generate the motion of the fin by means of a mechanical transmission system; to replicate the effect of elastic internal structures on the propulsion of biological systems. The propulsion mechanism is optimized by means of analytic kinematic and hydrodynamic models, whose accuracy is verified by means of CFD simulation tools. Finally, in order to demonstrate the feasibility of the project, the mechanical design of the propulsion system is illustrated.
Identification of Variable Amplitude Fatigue Loading Based on Bivariate Probability Mass Functions
Authors: Li Hewenxuan , Chelidze David
Published: November 2019

Fatigue life estimation under variable amplitude (VA) loading remains one of the major unresolved engineering problems. When engineering structures experience VA loading, the corresponding load at the crack front will be highly non-stationary. Under such conditions, the load interaction effects greatly affect fatigue crack propagation rate and can cause significant variation in the corresponding fatigue life. Existing characterization methods focus on single overload effect and their extensions to sequence of overloads which does not reflect the irregularity of the realistic loading. In this paper, numerical simulations were used to compare the fatigue life under various synthetic load time histories. The resulting time to failure estimation, concerning statistically and spectrally identical deterministic loads and their stochastic surrogates, exhibits drastic difference which reflects the corresponding differences in the temporal structure of the loads, which are not differentiated by their linear characteristics. This indicates that the temporal dynamics of the load time histories have considerable influence on fatigue crack propagation and fracture. In order to differentiate temporal dynamics of the synthetic loading, new bivariate probability mass functions (BPMFs) are proposed. They can capture and preserve the underlying temporal dynamics of locally non-stationary variable amplitude load-time histories with identical linear statistics. And qualitative explanations of the potential of this proposed method for fatigue life estimation under VA loading are discussed.
Numeric Approach on Optimal Control for the Path Following System in Autonomous Vehicle
Authors: Wu Huyao , Ran Bin
Published: November 2019

In this paper, the control strategies for Path Following System (PFS) in autonomous vehicle, which lets vehicle stay in the center of its lane is discussed, we will create a plant mechanical, mathematical and error dynamics model for the study of PFS, which is stabilized by the state-feedback control law, also considers the output where the sensor is made. We apply mainly an optimal control or configure a Linear-quadratic Regulator (LQR) for state space systems and compare it to that based on the Pole Assignment (PA). Combined with a typical operating scenario of the road, we mainly consider static and dynamic errors in the moving process, and how intensely the error fluctuates and how errors are related to the next time. Figures and data show that the LQR controller successfully adjusts and gives appropriate input to let the vehicle approach to centerline, errors and the steering angle required to negotiate a curved road are presented and analyzed, finally relevant conclusions are drawn.
Assessing the Impact of Cognitive Assistants on Mental Workload in Simple Tasks
Authors: Maier Torsten , Donghia Vincent , Chen Chaoran , Menold Jessica , McComb Christopher
Published: November 2019

Cognitive assistants, such as Apple’s Siri or Amazon’s Alexa, are increasingly becoming routine elements of our daily lives, yet the effects of such devices on the humans using them has been largely unstudied. While much research has proposed new intelligent systems for specific contexts, few studies have characterized the dynamics between cognitive assistants and humans. In an effort to address this gap, this research study investigates the effect of cognitive assistants on mental workload. Participants perform the Wisconsin Card Sorting Task while working with a fake cognitive assistant (Mary) and concurrently completing a secondary speed and accuracy test. Performance with the cognitive assistant was found to be higher but with no significant difference in mental workload. Participants working with the cognitive assistant were found to be less frustrated than those completing the task without it.
Tip Position Control of Single Flexible Links via Parallel Feedforward Compensation
Authors: Noury Keyvan , Yang Bingen
Published: November 2019

Developed in this work, is a simple and innovative control method, by which a nonminimum-phase (NMP) process can be easily stabilized in a closed-loop setting. The method is named as the parallel feed-forward compensation with derivative effort (PFCD). Through use of a high order process, the control system designed by the PFCD method is shown to be less influenced by noise, disturbance, and model mismatch, compared to other methods. Moreover, the necessary data required for implementing the PFCD method are discussed. The proposed control method is illustrated on tip position control in a slewing beam as a flexible robot arm, in which the effectiveness of the PFCD method is demonstrated. In addition, the proposed control method is compared with the existing methods in terms of stability and performance. The paper is concluded with notes about the advantages.
Tooth Geometry Design and Two-Dimensional Finite Element Analysis for a Strain Wave Gear With Double-Circular-Arc Profile
Authors: Chen Yi-Cheng , Cheng Yun-Hao , Tseng Jui-Tang , Hsieh Kun-Ju
Published: November 2019

The mathematical model of a strain wave gear (SWG) composed of a flexspline (FS), an elliptical wave generator (WG), and a circular spline (CS) was developed and the performance was simulated by two-dimensional (2-D) finite element analysis. A rack cutter exhibiting a double-circular-arc normal section was utilized to generate the FS, and the conjugate CS was also developed based on the theory of gearing and enveloping equation. Computer program developed in Visual C++ was completed for the geometry and 2-D mesh generation. The performances as well as the rotational motion of the SWG with double-circular-arc profile were simulated and investigated by 2-D finite element analysis.
Technology Knowledge Graph for Design Exploration: Application to Designing the Future of Flying Cars
Authors: Sarica Serhad , Song Binyang , Luo Jianxi , Wood Kristin
Published: November 2019

To pursue innovation, design engineers need to continuously exploit the knowledge in their design domain and explore other relevant knowledge around the domain. While many methods and tools have been developed to retrieve knowledge within a given design domain, e.g., flying cars, knowledge discovery beyond the domain for innovation remains a challenge, and relevant methods are under-developed. Herein, we introduce a methodology to use a technology knowledge graph (TKG), which covers sematic-level knowledge in all technology fields defined in the international patent classification system, to retrieve the existing engineering knowledge in a domain and discover engineering concepts around the domain for future design considerations and innovation. We demonstrate the TKG-based methodology by applying it to explore the future designs of flying cars, an emerging domain with high uncertainty despite growing prospects.
Application of a Protocol to Observe Leadership Behaviors in Engineering Design Teams
Authors: Righter James , Wentzky Chase , Summers Joshua D.
Published: November 2019

This protocol study was conducted to increase understanding of the emergence and distribution of functional leadership behaviors in undergraduate engineering design teams. This study applies the protocol presented at the 2018 IDETC to observe design teams consisting of novice engineers constructing a function model during a video recorded session. The videos were then coded for leadership functions and analyzed to determine the distribution of informal leadership functions between the team members and the temporal emergence of the informal leadership structures within the teams. Leadership behaviors were observed to be predominantly transition and action functions with relational behaviors occurring less frequently. The behaviors were quantified by number of occurrences per quintile. The leaders observed to perform the most leadership behaviors early in the sessions often remained consistent. However, leadership functions were shared between team members as demonstrated by the leadership network graphs.
Design of an Electric Motor Transmission System Without Friction Synchronization
Authors: Alowayed Abdulmohsen , Fernandes Diarny , Jeunehomme Eric , Liu Siyang , Wang Zhishen , Yang Illina , Dorsch Daniel , Winter Amos
Published: November 2019

This paper investigates the design of a new transmission system without a friction synchronizer for high-performance hybrid vehicles. Manual and automated manual transmission systems traditionally use friction synchronizers to facilitate smooth transitions during a gearshift, ensuring speed matching and proper engagement of the gears. Active position sensing technology for dogteeth is being developed, along with the potential of speed matching using electric motors, eliminating the need for the friction synchronizer. However, in removing these friction synchronizer components, significant shock could be introduced to the transmission system with speed or position errors during a shift. This paper proposes a solution through a gear system that utilizes a face mesh design, torsional springs, and alternating teeth height. A prototype of this design was created and successfully tested as a proof of concept for a transmission system, which has the potential to improve hybrid, automated manual transmission design.
Stability Analysis of Periodic Solutions for Flexible Multibody Dynamics
Authors: Han Shilei , Bauchau Olivier A.
Published: November 2019

Discontinuous Galerkin formulation is developed for stability analysis of periodic solutions of flexible multibody dynamics. The proposed approach takes rigid-body motions of each structural nodes as the unknowns. The rigid-body motions are interpolated by using dual spherical linear interpolation (dual-SLERP). The analysis is composed of two steps: (1) the periodic solution is obtained by solving nonlinear equations resulting from Galerkin method; (2) a linearization about the periodic solution leads to a periodic linear system and its stability is assessed by using Floquet’s method.
Modeling and Control of New Multi-Mode Plug-in Hybrid Electric Vehicle
Authors: Raut Abhinandan , Phalke Suryaji , Peters Diane
Published: November 2019

Fuel economy and emission standards for internal combustion engine (ICE) vehicles lead to emergence of hybrid powertrain mechanisms. Hybrid powertrains can enable significant fuel economy improvements without sacrificing vehicle performance or utility. This requires optimization of engine operation, regenerative braking, and use of a wide range of possible combinations of engine and battery usage. The multi-mode hybrid powertrain in this paper combines many options to meet a complex driving requirement while maintaining the desired fuel economy. In this paper, a systematic design methodology is used to design a full-size hybrid vehicle with multiple components. This involves the modeling, simulation and development of optimal energy management strategy. This vehicle (full size car) has dual battery, dual fuel V6 engine with cylinder deactivation and bi-directional power flow in and from dual motor/generator. The design includes multiple gearboxes to connect these pieces. The vehicle model allows many degrees of freedom including various modes of operation depending upon the combination of degree of driver involvement, vehicle power requirement and optimized fuel economy resulting in automatic switching between modes. This model is tested for different Environmental Protection Agency (EPA) driving cycles. By integrating all components of this hybrid electric vehicle (HEV) and the highly coordinated energy management control system that performs optimum blending of torque, speed, and power from multiple power sources, the benefit from this hybridization is maximized.
Contactless Li-Ion Battery Voltage Detection by Using Walabot and Machine Learning
Authors: Wang Yanan , Niu Haoyu , Zhao Tiebiao , Liao Xiaozhong , Dong Lei , Chen Yangquan
Published: November 2019

This paper has proposed a contactless voltage classification method for Lithium-ion batteries (LIBs). With a three-dimensional radio-frequency based sensor called Walabot, voltage data of LIBs can be collected in a contactless way. Then three machine learning algorithm, that is, principal component analysis (PCA), linear discriminant analysis (LDA), and stochastic gradient descent (SGD) classifiers, have been employed for data processing. Experiments and comparison have been conducted to verify the proposed method. The colormaps of results and prediction accuracy show that LDA may be most suitable for LIBs voltage classification.
On Computation of Approximate Lyapunov-Perron Transformations
Authors: Sharma Ashu , Sinha Subhash C.
Published: November 2019

Many dynamical systems can be modeled by a set of linear/nonlinear ordinary differential equations with quasi-periodic coefficients. Application of Lyapunov-Perron (L-P) transformations to such systems produce dynamically equivalent systems in which the linear parts are time-invariant. In this work, a technique for the computation of approximate L-P transformations is suggested. First, a quasi-periodic system is replaced by a periodic system with a ‘suitable’ large principal period to which Floquet theory can be applied. Then, the state transition matrix (STM) of the periodic system is computed in the symbolic form using shifted Chebyshev polynomials and Picard iteration method. Finally, since the STM can be expressed in terms of a periodic matrix and a time-invariant matrix (Lyapunov-Floquet theorem), this factorization is utilized to compute approximate L-P transformations. A two-frequency quasi-periodic system is investigated using the proposed method and approximate L-P transformations are generated for stable, unstable and critical cases. These transformations are also inverted by defining the adjoint system to the periodic system. Unlike perturbation and averaging, the proposed technique is not restricted by the existence of a generating solution and a small parameter. Approximate L-P transformations can be utilized to design controllers using time-invariant methods and may also serve as a powerful tool in bifurcation studies of nonlinear quasi-periodic systems.
Analysis of Constraint Forces in Multibody Systems Based on the Differential Null Space Matrix Method
Authors: Kamiya Keisuke
Published: November 2019

This paper treats a problem to determine constraint forces in rigid mutibody systems. One of the most often applied algorithms for determination of constraint forces is based on the use of recursive Newton-Euler formalism. Another algorithm often applied for determination of constraint forces is based on the use of Lagrange multipliers. This paper presents a new method to determine constraint forces in rigid multibody systems. First relative displacements which violate the constraints, called anti-constraint relative displacements, are introduced, and governing equations which involve the constraint forces explicitly are derived. In the derived equations, the constraint forces appear independently from the Lagrange multipliers. Then, a method is proposed to determine the constraint forces by eliminating the Lagrange multipliers based on the methods proposed in previous papers by the author. The method is extended to have ability to treat systems with redundant constraints. Finally, validity of the proposed method is confirmed via numerical examples.
Manufacturing Vulnerability: How Resource Scarcity Hinders Team Coordination During Manufacturing in Nigerian Factories
Authors: Kusimo Abisola C. , Sheppard Sheri
Published: November 2019

The purpose of this research is to learn how less-skilled workers (LSWs) and highly-skilled workers (HSWs) coordinate in Nigerian factories, where the formal education gap between these two groups can be quite significant. The study takes place in two factories and two universities across four Nigerian states over the summer of 2018. Drawing on methods of ethnography (i.e. a collection of qualitative methods to closely observe social interactions and practices as to interpret and build theory), it was discovered that resource scarcity hinders team coordination through the occurrence of four obstacles: (1) unclear role boundaries and work processes, (2) poor attitude towards work, (3) under- and overutilization of employees, and (4) worker demoralization and feelings of being undervalued. This paper builds upon previous work on factory coordination in cross-occupational functional groups in Silicon Valley. Theoretically, this paper reveals how the studied manufacturing firms in Nigeria currently perform team coordination and the challenges that prevent them from reaching high efficiency. Additionally, it offers premises for future field experiments to test the generalizability of the findings and interventions to enhance coordination effectiveness and the product development process in Sub-Saharan African manufacturing firms. Implications for the literature on engineering for global development is discussed. Ultimately, this research is a small step towards enabling independent African firms to have the skills, tools, and resources to design and create their own unique solutions for challenges faced in-country.
Influence of Omitted Variables in Consumer Choice Models on Engineering Design Optimization Solutions
Authors: Gowharji Waleed , Whitefoot Kate S.
Published: November 2019

This paper examines the impact of Omitted Variable Bias (OVB) within consumer choice models on engineering design optimization solutions. Engineering products often have a multitude of attributes that influence consumers’ purchasing decisions, many of which are difficult to include in revealed-preference models due to a lack of data. Correlations among these omitted variables and product attributes included in the model can bias demand parameter estimates. However, engineering design optimization studies typically do not account for this bias. We examine the influence consumer-choice OVB can have on design optimization results. We first mathematically derive how OVB propagates into biased optimal design solutions and characterize properties of optimization problems that affect the magnitude of this bias. We then demonstrate the impact of OVB on optimal designs using a more-realistic engineering optimization case study of automotive powertrain design. In the demonstration, we estimate two sets of choice models: one using only “typically observed” vehicle attributes commonly found in the literature, and one with an additional set of “typically unobserved” attributes gathered from Edmunds.com. We find that the model with omitted variables leads to, in some scenarios, substantial bias in parameter estimates (5–143%) which propagates up to 21% bias in the optimal engine size.
Discontinuous Dynamics of a Frequency Up-Conversion Piezoelectric Harvester
Authors: Onsorynezhad Saeed , Wang Fengxia
Published: November 2019

This study investigates an impact based frequency up-conversion mechanism via discontinuous dynamics analysis. The mechanism composed of a stopper and a piezoelectric bimorph. The piezoelectric beam is subjected to a sinusoidal base excitation and impacts with the stopper. In this system, complex dynamics are induced by impacts, hence to better understand the energy harvesting performance of the piezoelectric beam, we seek the steady state periodic motions of the system. As the excitation frequency varies, the output voltage and power of the piezoelectric beam with periodic motions were obtained.

The piezoelectric bimorph was modeled as an Euler-Bernoulli beam, and the linear piezoelectric constitutive equations were used to obtain the equations of the piezoelectric beam. The generated voltage and power were obtained using discontinuous dynamics analysis. In order to better analyze the energy harvesting performance of the piezoelectric energy harvester, the stable and unstable periodic motions were obtained. The bifurcation diagram of the period-1 and period-2 motions were obtained analytically as the excitation frequency varying.
Critical Stability of a Hinged Beam With Dynamic Moment: With and Without External Flow
Authors: Abdullatif Mahmoud , Mukherjee Ranjan , Hellum Aren
Published: November 2019

The stability characteristics of a hinged beam subjected to a dynamic moment is investigated. The moment is proportional to the curvature of the beam at some point along its length. The stability investigations are carried out using a Galerkin approximation, both in the presence and absence of external flow. In the absence of external flow, stability is lost through divergence and flutter depending on the location of the point of measurement of curvature and the sign of the applied moment. In the presence of external flow, additional terms are introduced in the dynamic model. This alters the mechanism of flutter, reduces the value of the parameter at the critical point, and changes the nature of oscillations from standing waves to traveling waves.
Command Shaping Control of a Vertically Rotating Flexible Beam
Authors: Alhazza Khaled A.
Published: November 2019

Vertically rotating flexible beam under the effect of gravity adds some challenges to the existing input- and command shaping techniques. Classical shapers usually have zero initial conditions while vertically rotating beam may have initial or final deflections. These conditions may introduce large residual vibrations at the end of rest-to-rest maneuvers. Furthermore, the system contains some nonlinearities that may reduce the effectiveness of classical input- and command-shapers. In this work, a waveform command shaping profile is used initially and then optimized to reduce rest-to-rest residual vibrations of a vertically rotating flexible beam. The system equation of motion is determined, discretized, and then linearized to find an initial command shaper. The parameters of the proposed command shaper is then optimized to find a better performance. Only the first mode is considered in this work since higher modes usually have negligible amplitudes. To show the importance of the proposed work, comparisons between the uncontrolled shaper, double step shaper, smooth wave form command shaping, and the optimized command shaping are performed. The proposed technique is tested numerically using two cases, with different maximum velocities, flexible beam length, and acceleration times. Results show that the effectiveness of the proposed technique in reducing residual vibrations in rest-to-rest maneuvers.
Indoor Testbed for Vector Field Multirobot Adaptive Navigation: Feasibility Study
Authors: Rajabhandharaks Danop , McDonald Robert T. , Neumann Michael A. , Kitts Christopher A.
Published: November 2019

Multirobot adaptive navigation maneuvers a multi-vehicle system based on characteristics of the environment to autonomously localize features of interest. This navigation method can be more time and energy efficient than conventional navigation methods. Most work in this area explores scalar fields, where a single characteristic value is associated with every point in the environment. This work is an initial testbed exploration of adaptive navigation for vector fields, where every point in the environment is associated with a multi-parameter value. A vector field can represent a single physical quantity such as water/air flow or multiple simultaneous and collocated scalar quantities such as temperature and gas concentration. The contribution of this work is the extension of an existing adaptive navigation testbed to support vector field representations, navigation, and further research. Vector fields are generated using a large-format printer to print 8-bit colored floor mats. Mobile robots, equipped with RGB sensors, sense the color and, through calibration, estimate the underlying vector field. This paper will walk through our process of generating vector fields and a calibration method to be used for adaptive navigation. Successful results from two adaptive navigation experiments are shown in the paper: finding a source with a single robot and using a two-robot formation to straddle a crest of high velocity flow in a vector field.
A Neuroevolution-Based Learning of Reciprocal Maneuver for Collision Avoidance in Quadcopters Under Pose Uncertainties
Authors: Behjat Amir , Gabani Krushang , Chowdhury Souma
Published: November 2019

This paper focuses on the idea of energy efficient cooperative collision avoidance between two quadcopters. Two strategies for reciprocal online collision-avoiding actions (i.e., coherent maneuvers without requiring any real-time consensus) are proposed. In the first strategy, UAVs change their speed, while in the second strategy they change their heading to avoid a collision. The avoidance actions are parameterized in terms of the time difference between detecting the collision and starting the maneuver and the amount of speed/heading change. These action parameters are used to generate intermediate way-points, subsequently translated into a minimum snap trajectory, to be executed by a PD controller. For realism, the relative pose of the other UAV, estimated by each UAV (at the point of detection), is considered to be uncertain — thereby presenting substantial challenges to undertaking reciprocal actions. Performing supervised learning based on optimization derived labels (as done in prior work) becomes computationally burden-some under these uncertainties. Instead, an (unsupervised) neuroevolution algorithm, called AGENT, is employed to learn a neural network (NN) model that takes the initial (uncertain) pose as state inputs and maps it to a robust optimal action. In neuroevolution, the NN topology and weights are simultaneously optimized using a special evolutionary process, where the fitness of candidate NNs are evaluated over a set of sample (in this case, various collision) scenarios. For further computational tractability, a surrogate model is used to estimate the energy consumption and a classifier is used to identify trajectories where the controller fails. The trained neural network shows encouraging performance for collision avoidance over a large variety of unseen scenarios.
Numerical Study of Superharmonic Resonances in a Mistuned Horizontal-Axis Wind-Turbine Blade-Rotor Set
Authors: Sapmaz Ayse , Acar Gizem D. , Feeny Brian F.
Published: November 2019

This paper is on a simplified model of an in-plane blade-hub dynamics of a horizontal-axis wind turbine with a mistuned blade. The model has cyclic parametric and direct excitation due to gravity and aerodynamics. This work follows up a previous perturbation study applied to the blade equations written in the rotor-angle domain and decoupled from the hub, in which superharmonic and primary resonances were analyzed. In this work, the effects of mistuning, damping, and forcing level are illustrated. The first-order perturbation solutions are verified with comparisons to numerical simulations at superharmonic resonance of order two. Additionally, the effect of rotor loading on the rotor speed and blade amplitudes is investigated for different initial conditions and mistuning cases.
Design and Kinematics of a Modular Robot for Assistive Tasks for the Disabled
Authors: Nelson Carl A. , Bruckner Mitchell A. , Chae Jay S. , Burnfield Judith M. , Buster Thad W. , Cesar Guilherme M. , Pfeifer Chase M. , Dasgupta Prithviraj
Published: November 2019

This paper presents a modular robot for adaptively providing assistance to individuals with spinal cord injury or other similar physical limitations. The design rationale is given, and details of prototyping are described. The robot’s kinematic model is elaborated, and preliminary testing and validation are presented.
Rule of Mixtures Model to Determine Elastic Modulus and Tensile Strength of 3D Printed Carbon Fiber Reinforced Nylon
Authors: Deng Kaiyue , Nejadkhaki Hamid Khakpour , Pasquali Felipe M. , Amaria Anosh P. , Armstrong Jason N. , Hall John F.
Published: November 2019

A model to compute the elastic modulus and tensile properties of 3D printed Carbon Fiber Reinforced Polymers (CFRP) is presented. The material under consideration is Carbon Fiber Reinforced Nylon (CFRN) produced in a Fused Deposition Modeling (FDM) process. A relationship between the nylon raster in each layer and the carbon fiber volume fraction was devised with the help of a scanning electron microscope (SEM). Thirteen groups with different layer configurations and carbon-fiber percentages were formulated and tested to obtain the elastic modulus and tensile strength. This study focused only on the properties along the printed fiber direction. The results from these tests were analyzed within the rule of mixtures framework. The results suggest that the rule of mixtures can be successfully applied to unidirectional CFRP fabricated using additive manufacturing.
Gaussian Process Emulation for Big Data in Data-Driven Metamaterials Design
Authors: Bostanabad Ramin , Chan Yu-Chin , Wang Liwei , Zhu Ping , Chen Wei
Published: November 2019

Our main contribution is to introduce a novel method for Gaussian process (GP) modeling of massive datasets. The key idea is to build an ensemble of independent GPs that use the same hyperparameters but distribute the entire training dataset among themselves. This is motivated by our observation that estimates of the GP hyperparameters change negligibly as the size of the training data exceeds a certain level, which can be found in a systematic way. For inference, the predictions from all GPs in the ensemble are pooled to efficiently exploit the entire training dataset for prediction. We name our modeling approach globally approximate Gaussian process (GAGP), which, unlike most largescale supervised learners such as neural networks and trees, is easy to fit and can interpret the model behavior. These features make it particularly useful in engineering design with big data. We use analytical examples to demonstrate that GAGP achieves very high predictive power that matches or exceeds that of state-of-the-art machine learning methods. We illustrate the application of GAGP in engineering design with a problem on data-driven metamaterials design where it is used to link reduced-dimension geometrical descriptors of unit cells and their properties. Searching for new unit cell designs with desired properties is then accomplished by employing GAGP in inverse optimization.
Whole-Body Balancing Criteria for Biped Robots in Sagittal Plane
Authors: Mummolo Carlotta , Peng William Z. , Kim Joo H.
Published: November 2019

In this work, the role of swing limb dynamics in the stabilization of legged systems is investigated. To quantify the contribution of arm swing during whole-body balancing, the balancing capability of a bipedal robotic platform is evaluated computationally during single and double foot contact for two configurations: arms fixed and arms free to move. The balancing capability with each arm configuration is evaluated by constructing its corresponding balance stability boundary, a threshold between balanced and falling states that includes all possible center of mass (COM) states that are balanced with respect to the specified arm and foot contact configuration. In this analysis, the bipedal robotic platform is modeled as a kinematic tree structure with floating-base dynamics in the sagittal plane. In addition to floating-base and joint-space dynamics, the complete COM-space dynamics of the system is established, including the formulation of the angular momentum (and its rate) of each rigid link, as well as a model of actuation dynamics based on motor characteristics. The comparison of the two balance stability regions yields both a quantitative measure of the enhancement in total balance capability and qualitative insights into the mechanism by which arm swing leads to enhanced capability. The role of arm swing angular momentum is also analyzed from the robot’s experimental gait trajectories as a potential means of benchmarking controller performance.
Advancing Strategies to Reduce Worker Injury Risk on Mobile Mining Equipment
Authors: Mayton Alan G. , Pollard Jonisha P. , Nasarwanji Mahiyar F. , Kim Brian Y.
Published: November 2019

Improving mine worker safety and health is a key goal for the Pittsburgh Mining Research Division of the National Institute for Occupational Safety and Health (NIOSH). Opportunities to enhance the safety and health of mobile mining equipment operators through strategies to lower the risk of musculoskeletal disorders and traumatic injuries is an important element of the overall NIOSH mining research program. This paper reviews various emerging technologies that, if fully developed and implemented, could positively impact the health and safety of mine workers who operate mobile mining equipment. Those technologies showing potential for enhancing operator safety and health in the near future are addressed herein.
Optimum Design of a New Tuned Inerter Mass Damper (TIMD) Passive Vibration Control for Stochastically Motion-Excited Structures
Authors: Tai Wei-Che
Published: November 2019

The inerter that is referred to as a two-terminal device that provides resisting forces proportional to the relative accelerations between its two terminals has been widely applied in vibration control due to its mass amplification effect. In this paper, a new inerter-based damper is proposed to take advantage of the inerter, which consists of a rack-pinion inerter in conjunction with a tuned rotational inertia damper. Unlike any other inerter-based dampers, the rotational inertia damper is connected to the pinion of the inerter via a rotational spring and damper. As a result, the weight of the damper can be significantly reduced. The proposed damper is applied to single-degree-of-freedom primary structures and a two-degree-of-freedom structure and the H2 optimization is conducted to obtain the optimum tuning ratio and damping ratio analytically. When comparing the proposed damper with its counterpart reported in the literature, the proposed damper achieves 20% to 70% improvement when their weights are identical.
Billion Degree-of-Freedom Granular Dynamics Simulation on Commodity Hardware
Authors: Kelly Conlain , Olsen Nicholas , Negrut Dan
Published: November 2019

This study describes the implementation of a granular dynamics solver designed to run on Graphics Processing Units (GPUs). The discussion concentrates on how the Discrete Element Method (DEM) has been mapped onto the GPU architecture, the software design decisions involved in the process, and the optimizations allowed by those decisions. This solver, called Chrono::Granular, has been developed as a standalone library that can interface with other dynamics engines via triangle mesh co-simulation. A scaling analysis of the code presented herein demonstrates linear scaling with problem sizes of over two billion degrees of freedom and closing in on one billion bodies. We conclude with a study of hourglass (or hopper) mass discharge rate which compares the solver to experimental results and investigates a process for determining empirical coefficients of flow rate through simulation.
Upper Limb Rehabilitation and Mobility Assistance Using Robotic Devices: A Review
Authors: MajidiRad AmirHossein , Yihun Yimesker S.
Published: November 2019

This study is aimed at reviewing the various literature on the robot-based rehabilitation and the associated technical issues, augmentation, utilization, and safeties. During recent years, Biorobotics and Collaborative Robots have played a remarkable role to provide fast, accurate and efficient therapy and assistance. Most of these robots are equipped with various types of devices to control the intensity, duration, and precision of the training while some feedback systems have also been used to monitor the efficiency of the process and help physicians and therapists to furnish a high quality treatment. Haptic devices, Electromyography (EMG)/Electroencephalography (EEG) sensors, virtual environment and other interactive approaches have been utilized to optimize the process and to investigate different mental as well as physiological aspects. This review paper provides a comprehensive background on the human robot interactions and their outcomes in medical settings and potential research areas in the domain.
Substrate Optimization for Hybrid Manufacturing
Authors: Massoni Brandon R. , Campbell Matthew I.
Published: November 2019

While advances in metals additive manufacturing continue to make additive a viable option in more scenarios, these processes are generally slower and more expensive than subtractive methods, like machining. The combination of both additive and subtractive, often called hybrid manufacturing, can be used to get the benefits of both processes, while reducing cost. However, dividing a part into the most cost effective additive and subtractive features is often time-consuming and non-intuitive. In this paper, we present a new approach that optimizes the type, size, and position of a substrate within a part. The resulting hybrid manufacturing configuration enables engineers to reach the most cost-effective compromise between additive and machining. A fully implemented method has been developed and tested on several realistic engineering parts. The results are intuitively useful and push the state-of-the-art forward in generating hybrid manufacturing process plans.
Design, Modeling, and Optimization of a Hopping Robot Platform
Authors: Knaup Jacob W. , Aukes Daniel M.
Published: November 2019

Laminate devices have the potential to lower the cost and complexity of robots. Taking advantage of laminate materials’ flexibility, a high-performance jumping platform has been developed with the goal of optimizing jump ground clearance. Four simulations are compared in order to understand which dynamic model elements (leg flexibility, motor dynamics, contact, joint damping, etc.) must be included to accurately model jumping performance. The resulting simulations have been validated with experimental data gathered from a small set of physical leg prototypes spanning design considerations such as gear ratio and leg length, and one in particular was selected for the fidelity of performance trends against experimental results. This simulation has subsequently been used to predict the performance of new leg designs outside the initial design set. The design predicted to achieve the highest jump ground clearance was then built and tested as a demonstration of the usefulness of this simulation.
Multibody Simulation of an Electric Go-Kart: Influence of Power-Train’s Weight Distribution on Dynamic Performance
Authors: Anaya Jonathan Mikler , Calderon Santiago Camacho , Bradley Andrew , Gonzalez-Mancera Andres
Published: November 2019

A multibody model of an electric go-kart was developed in Msc-Adams Car software to simulate the vehicle’s dynamic performance. In contrast to an ICE kart, its electric counterpart bares an extra weight load accounted for the batteries and other powertrain components. The model is inspired on a prototype vehicle developed at Universidad de los Andes. The prototype was built on top of an ICE frame where a PMAC motor, controller, battery pack and the subsequent powertrain components were installed. A petrol-based Go-kart weight distribution was defined as baseline and several variants of the electric adaptation with different weight distributions were constructed. The main objective of the model is to evaluate different configurations and identify the ones that can give performance advantages. Step steer simulations ran at 40 km/h (64 mph) were analyzed to assess the dynamic performance of the vehicle for different configuration of the battery bank placement.

For most iterations of powertrain location, considerable differences in dynamic response were obtained and the handling balance was identified as Understeer contrary to a priori thoughs. Understeer gradient, weight distribution for both axles, trajectory among other results of interest were observed in the simulations. The model allowed to showcase the effect of redistribution of weight on the dynamic behavior in this specific application. Among the main consequences lies the fact that battery distribution can affect the lifting of the internal rear tire and the detriment in turning effectiveness.
An Archimedean Screw Based Energy Harvester for Oil Extraction, Water Injection, and Related Activities
Authors: Lin Rui , Jiang Boxi , Zuo Lei
Published: November 2019

This paper presents an Archimedean Screw Turbine (AST) based energy harvester designed to power wireless sensor system inside oil extraction or water injection wells. Numerical study has been carried out using CFD analysis to evaluate the performance of the harvester. Characteristics of the AST, including turbine length, blade pitch, and rotational speed were studied to determine the optimal geometry and operating conditions of the system. An AST prototype with a length of 85 mm and an outer diameter of 50 mm was fabricated through 3D printing and in-lab tests were conducted to validate the performance of the designed harvester. A maximum power output of 0.21 W was achieved under a constant pipe flow rate of 0.95 liter per second when an external resistive load of 10 Ω was connected to the harvester. Lastly, the experimental results were analyzed and compared to the CFD analysis.
Synthesis of Stephenson III Timed Curve Generators Using a Probabilistic Continuation Method
Authors: Baskar Aravind , Plecnik Mark
Published: November 2019

The kinematic synthesis equations of fairly simple planar linkage topologies are vastly nonlinear. This indicates that a large number of solutions exist, and hence a large number of design candidates might be present. Recent algorithms based in polynomial homotopy continuation have enabled the computation of entire solution sets that were previously not possible. These algorithms are based on a technique that stochastically accumulates finite roots and guarantees the exclusion of infinite roots. Here we apply the Cyclic Coefficient Parameter Continuation (CCPC) method to obtain for the first time the complete solution of a Stephenson III six-bar that traces a path and coordinates the angle of its input link along that path. Linkages of this type, called timed curve generators, are particularly useful for controlling the motion of an end effector point and influencing its transmission properties from a rotary input. For a numerically general version of the synthesis equations, we computed an approximately complete set of 1,017,708 solutions that divides into subsets of four according to the Stephenson III cognate structure. This numerically generic solution set essentially represents a design tool. It can be used in conjunction with a parameter homotopy to efficiently obtain all isolated roots of other systems of this same structure that correspond to a specific synthesis task. This is demonstrated with two example synthesis tasks.