bluuebunny/crossref_metadata_2025 huggingface dataset:
Calculation of the Collision-Free Printing Workspace for Fully-Constrained Cable-Driven Parallel Robots
Authors: Fabritius Marc , Martin Christoph , Pott Andreas
Published: November 2018

Using fully-constrained cable robots as manipulators for 3D-printing, there is the risk of collisions between the cables and the printing part.

This paper presents a method to calculate the shape of the workspace volume within which a part can be printed without such collisions. The presented method is based on the fact that the printing part is produced in a sequence of horizontal layers. The areas occupied by the cables in the layers are scaled similar mappings of the cross-sections of the printing part. There is no collision if the 2D-shapes occupied by the cables in the printing layer do not overlap with the cross-sections of the printing part in the same layer. A procedure to find the largest printable 2D-shapes within the class of parallelograms for each layer is developed. The maximum printable 3D-volume is then given by stacking the 2D-shapes of each layer. Figures show the results of the method applied on the cable robot IPAnema 3. Finally, a guideline for the design of fully-constrained cable robots to maximize their printable volume is given.
Overhanging Feature Analysis for the Additive Manufacturing of Topology Optimized Structures
Authors: Bender Dylan , Barari Ahmad
Published: November 2018

This paper presents a methodology to find the optimum build orientation in the additive manufacturing of topologically optimized structural parts. The outlined methodology is based on applying a differential operator to the density distribution matrix of a topologically optimized design. The methodology is developed for 2D parts, where the profile of the geometry is constant. The 2D spatial difference operator effectively calculates the elemental density gradient vector, ultimately used to calculate the angles between i) overhanging surfaces of a topology optimized design, and ii) the build platform of a 3D printer. These angles, referred to as build angles, are used to estimate the relative amount of supporting structure required to print the design at a prescribed part orientation. This methodology can potentially be adopted to simulate the additive manufacturing surface quality of density based, structural topology optimization designs.
Design of a Directional Olfactory Display to Study the Integration of Vision and Olfaction
Authors: Micaroni Lorenzo , Carulli Marina , Ferrise Francesco , Bordegoni Monica , Gallace Alberto
Published: November 2018

This research aims to design and develop an innovative system, based on an olfactory display, to be used for investigating the directionality of the sense of olfaction. In particular, the design of an experimental setup to understand and determine to what extent the sense of olfaction is directional and whether there is prevalence of the sense of vision over the one of smell when determining the direction of an odor, is described. The experimental setup is based on low cost Virtual Reality (VR) technologies. In particular, the system is based on a custom directional olfactory display, an Oculus Rift Head Mounted Display (HMD) to deliver both visual and olfactory cues and an input device to register subjects’ answers. The VR environment is developed in Unity3D. The paper describes the design of the olfactory interface as well as its integration with the overall system. Finally the results of the initial testing are reported in the paper.
Identification of Human Errors During Early Design Stage Functional Failure Analysis
Authors: Irshad Lukman , Ahmed Salman , Demirel Onan , Tumer Irem Y.
Published: November 2018

Detection of potential failures and human error and their propagation over time at an early design stage will help prevent system failures and adverse accidents. Hence, there is a need for a failure analysis technique that will assess potential functional/component failures, human errors, and how they propagate to affect the system overall. Prior work has introduced FFIP (Functional Failure Identification and Propagation), which considers both human error and mechanical failures and their propagation at a system level at early design stages. However, it fails to consider the specific human actions (expected or unexpected) that contributed towards the human error. In this paper, we propose a method to expand FFIP to include human action/error propagation during failure analysis so a designer can address the human errors using human factors engineering principals at early design stages. To explore the capabilities of the proposed method, it is applied to a hold-up tank example and the results are coupled with Digital Human Modeling to demonstrate how designers can use these tools to make better design decisions before any design commitments are made.
Effects of Squeeze Film and Initial Deflection on the Resonance Frequencies and Modal Damping of Circular Microplates
Authors: Jallouli Aymen , Kacem Najib , Najar Fehmi , Lardies Joseph
Published: November 2018

We investigate the effects of squeeze air film and initial deflection on the resonance frequencies and modal damping of capacitive circular microplates. The equation of motion of a circular microplate, which are derived from the von kármán plate theory, coupled with the Reynolds equation are discretized using the Differential Quadrature Method (DQM). The eigenvalues and eigenvectors of the multiphysical problem are determined by perturbing the system of equations around a static solution. Therefore, the resonance frequencies, modal damping coefficients and mode shapes of the plate and the fluid can be determined. The advantage of using DQM is that the solution of the system can be obtained with only few grid points. The obtained numerical results are compared with the experimental data for the case of a capacitive circular microplates with an initial deflection. The increase of the static pressure leads to a shift in the resonance frequencies due to the increase in the stiffness of the plate. Also the initial deflection change the resonance frequencies due to the change in the effective gap distance. The developed model is an effective tool to predict the dynamic behavior of a microsystem under the effect of air film and with initial deflection.
Self-Improving Additive Manufacturing Knowledge Management
Authors: Lu Yan , Yang Zhuo , Eddy Douglas , Krishnamurty Sundar
Published: November 2018

The current additive manufacturing (AM) product development environment is far from being mature. Both software applications and workflow management tools are very limited due to the lack of knowledge supporting engineering decision making. AM knowledge includes design rules, operation guidance, and predictive models, etc., which play a critical role in the development of AM products, from the selection of a process and material, lattice and support structure design, process parameter optimization to in-situ process control, part qualification and even material development. At the same time, massive AM simulation and experimental data sets are being accumulated, stored, and processed by the AM community. This paper proposes a four-tier framework for self-improving additive manufacturing knowledge management, which defines two processes: bottom-up data-driven knowledge engineering and top-down goal-oriented active data generation. The processes are running in parallel and connected by users, therefore forming a closed loop, through which AM knowledge can evolve continuously and in an automated way.
Novel Classification of Planar Four-Bar Mechanisms With Variable Topology
Authors: Slaboch Brian J. , Hobbs Bradley W.
Published: November 2018

This paper provides a classification system and naming convention for twelve novel types of 4R-RRRP mechanisms with variable topology (MVTs). A mechanism with variable topology is a mechanism that changes from one topological state to another due to a change in joint geometry. An example 4R-RRRP mechanism is provided for each novel mechanism type, along with the appropriate classification and naming convention. The new 4R-RRRP mechanism classes and naming conventions presented in this paper will aid designers in the analysis and synthesis of 4R-RRRP mechanisms. These novel MVTs have practical applications in areas such as manufacturing, space applications, and novel medical devices.
Modeling Trust in Self-Organizing Systems With Heterogeneity
Authors: Ji Hao , Jin Yan
Published: November 2018

Self-organizing systems (SOS) possess the potential of performing complex tasks in uncertain situations with adaptability. Despite the benefits of self-organizing, it is also subject to the influence of unpredictable behavior of individual agents and environment noises. In hostile situations for example, individual performance of self-organizing agents may deteriorate and this can lead to system malfunction, posing great challenge for the design of SOS. In this paper, we propose a trust based model as a design approach to SOS in consideration of the capability heterogeneity of the agents. A box-pushing task was presented and studied. Trust is measured using beta probability distribution, which takes into account both the positive and negative interactions between the agents. The simulation results have shown that our trust model ensures favorable interactions among agents and leads to increased system effectiveness and conditional system efficiency improvement in comparison to SOS without using a trust model.
Design of Transfer Reinforcement Learning Under Low Task Similarity
Authors: Liu Xiongqing , Jin Yan
Published: November 2018

In this paper, a deep reinforcement learning approach was implemented to achieve autonomous collision avoidance. A transfer reinforcement learning approach (TRL) was proposed by introducing two concepts: transfer belief — how much confidence the agent puts in the expert’s experience, and transfer period — how long the agent’s decision is influenced by the expert’s experience. Various case studies have been conducted on transfer from a simple task — single static obstacle, to a complex task — multiple dynamic obstacles. It is found that if two tasks have low similarity, it is better to decrease initial transfer belief and keep a relatively longer transfer period, in order to reduce negative transfer and boost learning. Student agent’s learning variance grows significantly if using too short transfer period.
Open Uniaxial Test Machine (OpenUTM): Part 1 — A Low-Cost Electrohydraulic Test Frame for Additive Manufacturing Part Qualification
Authors: Steuben John C. , Iliopoulos Athanasios P. , Michopoulos John G.
Published: November 2018

A wide variety of scientific and engineering activities require the use of testing machines in order to acquire data regarding the response of materials subjected to mechanical loads. This is particularly applicable to the domain of Additive Manufacturing (AM), where mechanical qualification is essential. Such machinery should be capable of applying loads at required levels and exhibit high mechanical stiffness. Accurate force, displacement, and strain measurements are also required. As a consequence, such testing machines are typically very costly. In the present paper we introduce the Open Uniaxial Test Machine (OpenUTM) project, aimed at providing a low-cost (less than $2500.00) material testing hardware/software framework. This paper will focus on the engineering design and hardware aspects of the OpenUTM project, with particular attention paid to the use of an electrohydraulic actuator (EHA) to provide test loads. A full bill of materials and drawings package is provided, in order to enable the use of the OpenUTM framework by research groups with minimal machine tooling. We introduce several case studies demonstrating the successful use of the OpenUTM frame in AM research efforts, including the testing and characterization of AM polymers and ceramics. We conclude with discussion of the software aspects of the OpenUTM framework, which will be elaborated upon in a follow-up paper (part two). We also present a series of potential avenues towards the improvement of the OpenUTM frame in future hardware iterations.
Assessing Component Machinability Using Voxelized Solid Models
Authors: Chan Rothanak , Haapala Karl R. , Campbell Matthew I.
Published: November 2018

New automated approaches in design often generate nonmanufacturable component geometries. Improved machinability of topology optimized parts, for example, has been under exploration for over a decade with limited success. Recent work is pursuing novel design approaches enabled by developments in voxel-based representation and advanced process technologies. Research reported here suggests a featureless approach for analyzing the machinability of a given geometry using voxels. The input is a tessellated shape, which is converted into a voxel representation. The voxelized shape is then filled in the orthogonal toolpath directions defined by the minimum bounding box to approximate the reach of the cutting tool in each part orientation. The filled shapes are intersected with each other to achieve a solid representation that can be readily accessed by a cutting tool. Overlaying this solid shape against the original tessellated shape will highlight the non-machinable regions of the part when visualized. The volume of non-machinable material can be estimated and used to inform a larger search process for separating and adding part features together to improve component manufacturability.
A Spatial Parametric Model for the Nonlinear Stiffness Characteristics of Flexure Strips
Authors: Nijenhuis Marijn , Meijaard J. P. , Brouwer Dannis M.
Published: November 2018

The flexure strip is commonly used to provide support stiffness in flexure mechanisms for precision applications. While the flexure strip is often treated in a simplified form, e.g. by assuming planar deformation or linearized stiffness, the deformation in practice is spatial and sufficiently large that nonlinear effects due to the geometrical stiffness are significant.

This paper presents an understandable analytical model for the nonlinear stiffness characteristics of flexure strips that deform spatially due to a general 3-D loading condition. This model provides closed-form expressions in a mixed stiffness and compliance matrix format that is tailored to flexure mechanism analysis. The effects of bending, elongation, and torsion deformation are taken into account. The geometrically nonlinear effects of the model are verified numerically.

The approach for deriving closed-form solutions in a nonlinear context is detailed in this paper. Based on the Hellinger–Reissner variational principle, it can also be extended to the analysis of multi-flexure strip mechanisms. This is demonstrated with the case of a spatially deforming parallelogram flexure mechanism.
Evaluating the Effectiveness of Virtual Reality As an Interactive Educational Resource for Additive Manufacturing
Authors: Ostrander John K. , Tucker Conrad S. , Simpson Timothy W. , Meisel Nicholas A.
Published: November 2018

Demand for a highly skilled workforce in the field of additive manufacturing (AM) is growing but is underserved due to limited academic course offerings and high barriers for incorporating industrial AM systems into education. Virtual reality (VR) is proposed as a medium to help teach introductory concepts of AM to a broader audience in an interactive, scalable manner. Before implementing VR as a standard tool to teach the concepts of AM, we must evaluate the effectiveness of this medium for the subject. Our research aims to answer the question: can VR be used to teach introductory concepts of additive manufacturing in a way that is as effective as teaching the same concepts in a physical setting? The research looks at the learning differences between two groups: (1) students exposed to an interactive AM lesson in a traditional physical setting and (2) students exposed to the same lesson within a virtual environment. The study assesses participants’ AM knowledge through pre-/post-AM lesson evaluation. AM conceptual knowledge gained and changes in self-efficacy are evaluated to make an argument for the effectiveness of VR as an AM learning tool.
Dynamic Data-Driven Spatiotemporal System Behavior Prediction With Simulations and Sensor Measurement Data
Authors: Zhao Xiangxue , Azarm Shapour , Balachandran Balakumar
Published: November 2018

Online prediction of dynamical system behavior based on a combination of simulation data and sensor measurement data has numerous applications. Examples include predicting safe flight configurations, forecasting storms and wildfire spread, estimating railway track and pipeline health conditions. In such applications, high-fidelity simulations may be used to accurately predict a system’s dynamical behavior offline (“non-real time”). However, due to the computational expense, these simulations have limited usage for online (“real-time”) prediction of a system’s behavior. To remedy this, one possible approach is to allocate a significant portion of the computational effort to obtain data through offline simulations. The obtained offline data can then be combined with online sensor measurements for online estimation of the system’s behavior with comparable accuracy as the off-line, high-fidelity simulation. The main contribution of this paper is in the construction of a fast data-driven spatiotemporal prediction framework that can be used to estimate general parametric dynamical system behavior. This is achieved through three steps. First, high-order singular value decomposition is applied to map high-dimensional offline simulation datasets into a subspace. Second, Gaussian processes are constructed to approximate model parameters in the subspace. Finally, reduced-order particle filtering is used to assimilate sparsely located sensor data to further improve the prediction. The effectiveness of the proposed approach is demonstrated through a case study. In this case study, aeroelastic response data obtained for an aircraft through simulations is integrated with measurement data obtained from a few sparsely located sensors. Through this case study, the authors show that along with dynamic enhancement of the state estimates, one can also realize a reduction in uncertainty of the estimates.
Development and Kinematic Position Analysis of a Novel Class 2 Tensegrity Robot
Authors: Manríquez-Padilla Carlos G. , Camarillo-Gómez Karla A. , Pérez-Soto Gerardo I. , Rodríguez-Reséndiz Juvenal , Crane Carl D.
Published: November 2018

This paper presents a novel class 2 tensegrity robot which has contact between its rigid elements with a universal joint. Also, an strategy to obtain the forward and inverse position kinematic analysis using the parameters Denavit–Hartenberg in the distal convention is presented, obtaining the closed–form solution for the inverse position analysis and it was validated through simulation where a point of the robot followed the desired trajectory. Finally, the results were implemented in the experimental prototype of the novel class 2 tensegrity robot.
Modeling the Selective Laser Melting of Multi-Component Thermoelectric Powders
Authors: Wu Yongjia , Zuo Lei , Sun Kan
Published: November 2018

Thermoelectrics enables thermal and electrical energy conversion or device cooling without any moving parts. It has remained a significant challenge to manufacture compact and high performance thermoelectric modules in a large volume using the conventional methods because of their drawbacks in practice, such as the long processing time and misalignment of individual thermoelectric elements. Selective laser melting (SLM) based additive manufacturing approach might offer a unique method to fabricate the low cost, reliable, highly efficient, scalable, and environmentally friendly thermoelectric modules. To understand the thermodynamic and hydrodynamic phenomenon during the SLM processing is of critical importance to ensure high quality products. In this paper, we developed a model which can be used to guide the SLM manufacturing of thermoelectric material with other nanoparticles embedded for higher thermoelectric performance. This physical model based on the continuous equations had the ability to analyze the fluid flow driven by buoyancy force and surface tension, which can be used to analyze the influence of the process parameters on the pool size, particle segregation, as well as temperature distribution within the powder bed. This information is very useful for developing robust SLM for thermoelectric device fabrication.
A Method for Evaluating Maintenance Capabilities in a Developing Community Using a Multiple DSM Framework
Authors: Nik Mutasim Ammar , Sayers Dillan , Pasquali Felipe M. , Hall John F.
Published: November 2018

Introducing new technology to an inexpert society can be challenging. Rural communities are often deprived of technology that promotes a higher standard of living. Today there are sustainable energy solutions that, if correctly implemented, could close this gap. The literature indicates that a large number of humanitarian and relief projects failed because the communities were not able to perform the equipment maintenance. This work proposes a method for identifying the capability of a region to perform the necessary maintenance of a new technology. The method works by measuring both the system requirements and region abilities and resources. The proposed technique is devised with a design structure matrix in which each subsystem maintainability is analyzed. The resulting framework generates a comparative analysis that contributes to the decision making process. A case study is performed to evaluate the model on selecting an energy solution for a given community. The results provide designers a better understanding on the dependence of each component maintainability. Furthermore, it provides insights on the effect of region abilities and resources in the maintainability of a system.
Implicit and Explicit Trust Behavior: Does Stereotype Congruence Affect User Trust in a Home Automation Device?
Authors: Damen Nicole B. , Toh Christine A.
Published: November 2018

Although trust is widely accepted as important for technology adoption and usage, it has received little attention in home automation, where users interact closely with these devices to enhance their quality of life. Research is needed to investigate how design considerations such as agent gender and automation location impact trust. This study expands on a pilot study by examining how stereotype congruence impacts implicit and explicit measures of trust in home automation devices. A smart lock simulation was utilized to examine how users interacted with systems that confirm and violate social expectations. The results show that users displayed more trusting behavior towards systems that were stereotype congruent than incongruent. That is, users extended their expectations of stereotypical social behaviors to their interaction with the home automation simulation. In addition explicit trust measures, or directly observable behaviors, differed from implicit trust measures, such as reaction time with the system. These findings provide a foundation for empirically testing and understanding the complex relationship between users and increasingly social automated devices.
Investigation of Neural-Network-Based Inverse Kinematics for a 6-DOF Serial Manipulator With Non-Spherical Wrist
Authors: Hargis Benjamin E. , Demirjian Wesley A. , Powelson Matthew W. , Canfield Stephen L.
Published: November 2018

This study proposes using an Artificial Neural Network (ANN) to train a 6-DOF serial manipulator with a non-spherical wrist to solve the inverse kinematics problem. In this approach, an ANN has been trained to determine the configuration parameters of a serial manipulator that correspond to the position and pose of its end effector. The network was modeled after the AUBO-i5 robot arm, and the experimental results have shown the ability to achieve millimeter accuracy in tool space position with significantly reduced computational time relative to an iterative kinematic solution when applied to a subset of the workspace. Furthermore, a separate investigation was conducted to quantify the relationship between training example density, training set error, and test set error. Testing indicates that, for a given network, sufficient example point density may be approximated by comparing the training set error with test set error. The neural network training was performed using the MATLAB Neural Network Toolbox.
Two-Dimensional Contact Analysis Using Trigonometric Polynomials: Some Early Verification Problems
Authors: Chauda Gaurav , Segalman Daniel J.
Published: November 2018

A discretization strategy for elastic contact on a half plane has been devised to explore the significance of different friction models on joint-like interface mechanics. It is necessary to verify that discretization and accompanying contact algorithm on known solutions. An extensive comparison of numerical predictions of this model with corresponding 2-D elastic, frictional contact solutions from the literature is presented.
Categorization of Information Loss During the Dissemination of Design Ideas
Authors: Zhao Victoria , Tucker Conrad S.
Published: November 2018

Information is transferred through a process consisting of an information source, a transmitter, a channel, a receiver and its destination. Unfortunately, during different stages of the engineering design process, there is a risk of a design idea or solution being incorrectly interpreted due to the nonlinearity of engineering design. I.e., there are many ways to communicate a single design idea or solution. This paper provides a comprehensive review and categorization of the possible sources of information loss at different stages of the engineering design process. Next, the authors present an approach that seeks to minimize information loss during certain stages of the engineering design process. The paper i) explores design process and dissemination methods in engineering design; ii) reviews prior work pertaining to these stages of the engineering design process and iii) proposes an information entropy metric that designers can utilize in order to quantify information loss at different stages of the engineering design process. Knowledge gained from this work will aid designers in selecting a suitable dissemination solution needed to effectively achieve a design solution.
Computer-Aided Gear Product Realization
Authors: Yazdanshenas Alireza , Morrison Emilli , Goh Chung-Hyun , Allen Janet K. , Mistree Farrokh
Published: November 2018

To save time and resources, many are making the transition to developing their ideas virtually. Computer-aided gear production realization is becoming more and more desired in the industry. To produce gears with custom qualities, such as material, weight and shape, the trial and error approach has yielded the best results. However, trial and error is costly and time consuming. The computer-aided integrated design and manufacturing approach is intended to resolve these drawbacks. A simple one stage reduction spur gearbox is used as an example in a case study. First, the gear geometry is developed using computer aided design (CAD) modeling. Next, using MATLAB/Simulink, the gear assembly is connected virtually to other subsystems for system expectations and interaction analysis. Finally, using finite element analysis (FEA) tools such as ABAQUS, a dynamic FEA of the gear integration is completed to analyze the stress concentrations and gear tooth failures. Through this method of virtual gear design, customized dimensions and specifications of gears for satisfying system-level requirements can be developed, thereby saving time and manufacturing costs for any custom gear design request.
Using an Intelligent UAV Swarm in Natural Disaster Environments
Authors: Asbach Jamie , Chowdhury Souma , Lewis Kemper
Published: November 2018

Due to their volatile behavior, natural disasters are challenging problems as they often cannot be accurately predicted. An efficient method to gather updated information of the status of a disaster, such as the location of any trapped survivors, is extremely important to properly conduct rescue operations. To accomplish this, an algorithm is presented to control a swarm of UAVs (Unmanned Aerial Vehicles) and optimize the value of the information gathered. For this application, the UAVs are autonomously navigated with a decentralized control method. With sensor technology embedded, this swarm collects information from the environment as it operates. By using the swarm’s location history, areas of the environment that have gone the longest without exploration can be prioritized, ensuring a thorough search. Measures are also developed to prevent redundant or inefficient exploration, which would reduce the value of the gathered information. A case study of a flood scenario is examined and simulated. Through this approach, the value of the proposed swarm algorithm can be tested by tracking the number of survivors found as well as the rate at which they are discovered.
A Single Actuator Mechanism for Airfoil Shape Morphing
Authors: Ellis Andrew , Sun Cong Zhu (John) , Xi Fengfeng (Jeff) , Moosavian Amin
Published: November 2018

Presented in this paper is a single actuator mechanism for airfoil shape morphing. The said mechanism is designed as a linkage array that is driven by one actuator to provide multiple output points along the entire airfoil shape. This mechanism consists of two components, namely the shape adaptation linkage (SAL) and the connector linkage. Each connector is made up of a passive camber connector (PCC) or an active camber connector (ACC). The PCC conditions the output of an SAL while the ACC serves to create the camber morphing effect. The design method is proposed with three steps: Camber Mapping, Shape Adaptation Linkage Synthesis, and Connector Synthesis. The proposed method has been applied to design a number of NACA airfoils with camber morphing to demonstrate the effectiveness.
Optimal and Dynamically Feasible Path Planning for an Anguilliform Fish-Inspired Robot in Presence of Obstacles
Authors: Thati Santhosh Kumar , Raj Aditi , Thakur Atul
Published: November 2018

Exploration of obstacle-ridden underwater regions for various marine applications like automated inspection, maintenance and repair of sub-sea structures and search and rescue during disaster relief is often not possible to be carried out by the human divers. Owing to their slender and hyper-redundant structure, Anguilliform-inspired robots are capable of negotiating narrow regions. However, the challenges involved in the motion planning of Anguilliform-inspired robots include the dynamic constraints imposed by the hyper-redundant joints, the interaction between fluid environment and the robot, and the presence of obstacles. This paper reports a model-predictive motion planning approach for an Anguilliform-inspired robot, wherein dynamically feasible motion primitives are generated using a dynamics simulator. The motion primitives are then used for generating a roadmap over which A* algorithm is used for searching an optimal, obstacle-free, and dynamically feasible path to the goal. Use of Euclidean heuristic in the A* based path planning for hyper-redundant underwater robots often results in the expansion of a large number of nodes and thereby slow-down the computations. Hence, we present a simulation-based admissible heuristic function that led to a speed-up of path search computation time by a factor varying from 3.1 to 5.5 over the Euclidean heuristic for our simulation-based experiments. The factor is dependent on the complexity of the scene. We also use dynamics simulation for estimating action-specific convex collision envelops for precise and efficient collision detection during the expansion of nodes in A*.
Response Characteristics of Systems With Two-Harmonic Parametric Excitation
Authors: Afzali Fatemeh , Acar Gizem D. , Feeny Brian F.
Published: November 2018

Floquet theory is combined with harmonic balance to study parametrically excited systems with two harmonics of excitation, where the second harmonic has twice the frequency of the first one. An approximated solution composed of an exponential part with unknown exponents and a periodic term consisting of a truncated Fourier series is considered. When applied to a two-harmonic Mathieu equation the analysis shows that the second harmonic alters stability characteristics, particularly in the primary and superharmonic instabilities. We also look at the initial conditions response and its frequency content. The second excitation harmonic in the system with parametric damping is seen to disrupt the coexistence phenomenon which is observed in the single-harmonic case.
Past Infrastructures and Future Machine Intelligence (MI) for Biofuel Production: A Review and MI-Based Framework
Authors: Hansen Samuel , Mirkouei Amin
Published: November 2018

Recent interest in alternative energy sources, particularly biofuels from biomass, is becoming increasingly evident due to energy security and environmental sustainability concerns, such as depletion of conventional energy reserves and carbon footprint effects, respectively. Existing fuels (e.g., biodiesel and ethanol) are neither sustainable nor cost-competitive. There is a need to integrate the recent advanced manufacturing approaches and machine intelligence (MI) techniques (e.g., machine learning and artificial intelligence), targeted on the midstream segment (i.e., pre-/post-conversion processes) of biomass-to-biofuel supply chains (B2BSC). Thus, a comparative review of the existing MI approaches developed in prior studies is performed herein. This review article, additionally, proposes an MI-based framework to enhance productivity and profitability of existing biofuel production processes through intelligent monitoring and control, optimization, and data-driven decision support tools. It is further concluded that a modernized conversion process utilizing MI techniques is essential to seamlessly capture process-level intricacies and enhance techno-economic resilience and socio-ecological integrity of B2BSC.
A Probabilistic Design Reuse Index
Authors: Vasantha Gokula , Sherlock Andrew , Corney Jonathan , Quigley John
Published: November 2018

The benefits of being able to create a number of product variations from a limited range of components, or sub-assemblies, are widely recognized. Indeed it is clear that companies who can effectively reuse elements of existing designs when creating new products will be more productive and profitable than those whose catalogues are full of parts individually tailored to specific models. Frustratingly, despite the benefits, existing approaches to quantifying the amount of design reuse within a company’s product range are laborious and often provide only aggregated reuse value that provided little explicit indication of where the highest and lowest levels of re-use occur within a product portfolio.

This paper surveys existing measures of design reuse and describes the results of applying some of them to quantify the amount of commonality in a range of flat-pack furniture. The results illustrate the differences between their definitions of design reuse. We then present a new approach to objectively quantifying levels of reuse by comparing actual probability distributions of component use with virtual ones, where every component is used with equal preference. The proposed reuse metric, named Probabilistic Design Reuse Index (PDRI), is applied to the flat-pack dataset and the results used to highlight component families with low levels of design commonality.
A Round Robin Study: Detection of Damage in a Composite Plate With a Real-Time Moving Sensor Measurement Technique
Authors: Chen Da-Ming , Xu Y. F. , Zhu W. D.
Published: November 2018

A worldwide round robin study is sponsored by the Society of Experimental Mechanics to detect damage in a composite plate with a scanning laser Doppler vibrometer (SLDV). The aim of this round robin study is to explore the potential of a SLDV for detection of damage in composite plates. In this work, a curvature-based damage detection method with use of a continuously SLDV (CSLDV) is proposed. A CSLDV can be regarded as a real-time moving sensor, since the laser spot from the CSLDV continuously moves on a structure surface and measures velocity response. An operating deflection shape (ODS) of the damaged composite plate can be obtained from velocity response by the demodulation method. The ODS of the associated undamaged composite plate is obtained by using polynomials to fit the ODS of the damaged plate. A curvature damage index (CDI) using differences between curvatures of ODSs (CODSs) associated with the ODSs from the demodulation method and the polynomial fit is proposed to detect damage. With the proposed curvature-based damage detection method, locations of two possible damage are detected in areas with consistently high CDI values at two excitation frequencies, which are in good agreement with prescribed damage locations.
Decentralized Task Allocation in Multi-Robot Systems via Bipartite Graph Matching Augmented With Fuzzy Clustering
Authors: Ghassemi Payam , Chowdhury Souma
Published: November 2018

Robotic systems, working together as a team, are becoming valuable players in different real-world applications, from disaster response to warehouse fulfillment services. Centralized solutions to coordinating multi-robot teams often suffer from poor scalability and vulnerability to communication disruptions. This paper develops a decentralized multi-agent task allocation (Dec-MATA) algorithm for multi-robot applications. The task planning problem is posed as a maximum-weighted matching of a bipartite graph, the solution of which using the blossom algorithm allows each robot to autonomously identify the optimal sequence of tasks it should undertake. The graph weights are determined based on a soft clustering process, which also plays a problem decomposition role seeking to reduce the complexity of the individual-agents’ task assignment problems. To evaluate the new Dec-MATA algorithm, a series of case studies (of varying complexity) are performed, with tasks being distributed randomly over an observable 2D environment. A centralized approach, based on a state-of-the-art MILP formulation of the multi-Traveling Salesman problem is used for comparative analysis. While getting within 7–28% of the optimal cost obtained by the centralized algorithm, the Dec-MATA algorithm is found to be 1–3 orders of magnitude faster and minimally sensitive to task-to-robot ratios unlike the centralized algorithm.
Least Bumpiness Calibration With Extrapolative Bias Correction
Authors: Park Chanyoung , Kim Nam H. , Haftka Raphael T.
Published: November 2018

Bias correction is important for model calibration to obtain unbiased calibration parameter estimates and make accurate prediction. However, calibration often relies on insufficient samples, and so bias correction often mostly depends on extrapolation. For example, bias correction with twelve samples in nine-dimensional box generated by Latin Hypercube Sampling (LHS) has less than 0.1% interpolation domain in the box. Since bias correction is coupled with calibration parameter estimation, calibration with extrapolative bias correction can lead a large error in the calibrated parameters. This paper proposes an idea of calibration with minimum bumpiness correction. The bumpiness of bias correction is a good measure of assessing the potential risk of a large error in the correction. By minimizing bumpiness, the risk of extrapolation can be reduced while the accuracy of parameter estimates can be achieved. It was found that this calibration method gave more accurate results than Bayesian calibration for an analytical example. It was also found that there are common denominators between the proposed method and the Bayesian calibration with bias correction.
Design and Modeling of a Prosthetic Venous Valve
Authors: Packer Ryan , Jensen Brian D. , Bowden Anton E.
Published: November 2018

Chronic Venous Insufficiency (CVI) is a disease of the lower limbs that affects millions of people in the United States. CVI results from incompetent venous valves. The purpose of venous valves is to prevent retrograde blood flow to the lower limbs. Valve failure can lead to edema, pain, and ulcers. One solution that has great potential is to create an implantable venous valve that could restore function of the venous system. No prosthetic venous valves are clinically used currently because of problems with biocompatiblility and thrombogenicity caused by high shear rates. This paper presents a prosthetic venous valve that could overcome these difficulties by using carbon-infiltrated carbon nanotubes (CI-CNTs). This material has been proven to be thrombo-resistant, biocompatible due to its non-reactive properties, and durable. The valve was designed to be initially open and to close with physiological pressures. Finite element modeling showed that, with a hydrostatic pressure of 20 mmHg (the minimum hydrostatic pressure in the common femoral vein), it fully closed with a maximum stress of 117 MPa, which is below the ultimate strength of CI-CNTs. A computational fluid dynamics analysis demonstrated the valve would cause a maximum shear rate of 225.1 s−1, which is less than the maximum shear rate in the body. Hence, this valve would be less likely than previous prosthetic valves to develop blood clots. Currently, this is the lowest shear rate reported for a prosthetic venous valve. These results demonstrate that a CI-CNT prosthetic venous valve has the potential to be an effective treatment for CVI.
A Framework to Support the Optimization of Modularized Oil and Gas Structures
Authors: Castorani Vincenzo , Cicconi Paolo , Germani Michele , Bondi Sergio , Marronaro Maria Grazia , Coppolaro Sonia
Published: November 2018

Modularization is a current issue in the context of plant design. A modular system aims to reduce lead time and cost in design phases. An oil & gas plant consists of many Engineered-To-Order solutions to be submitted and approved during the negotiation phase. In this context, design tools and methods are necessary to support the design life cycle from the conceptual study to the detailed project. The paper proposes an approach to optimize the design of modularized oil & gas plants with a focus on the related steel structures. A test case shows the configuration workflow applied to a modular steel structure of about 400 tons. The modularized layout has been optimized using genetic algorithms. A Knowledge Base has been described to support the configuration phase related to the conceptual design. Design rules and metrics have been formalized from the analysis of past solutions.
Reliability Analysis Using Deep Learning
Authors: Chen Chong , Liu Ying , Sun Xianfang , Wang Shixuan , Di Cairano-Gilfedder Carla , Titmus Scott , Syntetos Aris A.
Published: November 2018

Over the last few decades, reliability analysis has gained more and more attention as it can be beneficial in lowering the maintenance cost. Time between failures (TBF) is an essential topic in reliability analysis. If the TBF can be accurately predicted, preventive maintenance can be scheduled in advance in order to avoid critical failures. The purpose of this paper is to research the TBF using deep learning techniques. Deep learning, as a tool capable of capturing the highly complex and nonlinearly patterns, can be a useful tool for TBF prediction. The general principle of how to design deep learning model was introduced. By using a sizeable amount of automobile TBF dataset, we conduct an experiential study on TBF prediction by deep learning and several data mining approaches. The empirical results show the merits of deep learning in performance but comes with cost of high computational load.
Dynamics of a Tubular Cantilever Simultaneously Subjected to Internal and Partially-Confined External Axial Flows
Authors: Abdelbaki Ahmed R. , Misra Arun K. , Païdoussis Michael P.
Published: November 2018

In this paper the dynamics of a tubular cantilever, simultaneously subjected to internal and external axial flows, is examined theoretically. The tube is discharging fluid downwards which then flows upwards through an annular region surrounding the tube. Thus, the internal and external flows are interdependent and in opposite directions. Also, the external flow is confined over a certain range of the cantilever length and unconfined over the rest. The Heaviside step function has been used in the literature, for such a system, to model the discontinuity in the external flow velocity occurring when the flow enters the annular region. A more accurate way to model this discontinuity is introduced in this study, in which the logistic function is used instead of the Heaviside step function. The stability of the system is investigated by analysis of the system eigenfrequencies, and the effects of varying the length of the confined region are theoretically studied. The obtained results are compared to theoretical predictions and experimental data from the literature having the same system parameters. The proposed theory captures the same dynamical behaviour as observed experimentally, and has a better estimation for the onset of instability and the frequency of oscillations compared to the theory in the literature.
Mobile Robot Regulation With Image Based Visual Servoing
Authors: Hao Tan Aaron , Al-Shanoon Abdulrahman , Lang Haoxiang , El-Gindy Moustafa
Published: November 2018

The development of image processing algorithms grew exponentially over the past few decades with improvements in vision sensors and computational power. In this paper, a visual servo controller is designed and developed using the image-based method for a differential drive robot. The objective is to reach a desired pose relative to a target object placed in the world frame with four feature points. A full system model that includes the mobile base and camera is presented along with the design of a proportional controller. The system is implemented in the Husky A200 Robot by Clearpath Robotics. MATLAB Simulation and experimental results are analyzed and discussed with conclusion and future works recommendation in the end.
Optimal Kinematic Redundancy Planning for Planar Mobile Cable-Driven Parallel Robots
Authors: Rasheed Tahir , Long Philip , Marquez-Gamez David , Caro Stéphane
Published: November 2018

Mobile Cable-Driven Parallel Robots (MCDPRs) are special type of Reconfigurable Cable Driven Parallel Robots (RCDPRs) with the ability of undergoing an autonomous change in their geometric architecture. MCDPRs consists of a classical Cable-Driven Parallel Robot (CDPR) carried by multiple Mobile Bases (MBs). Generally MCDPRs are kinematically redundant due to the additional mobilities generated by the motion of the MBs. As a consequence, this paper introduces a methodology that aims to determine the best kinematic redundancy scheme of Planar MCDPRs (PMCDPRs) with one degree of kinematic redundancy for pick-and-place operations. This paper also discusses the Static Equilibrium (SE) constraints of the PMCDPR MBs that are needed to be respected during the task. A case study of a PMCDPR with two MBs, four cables and a three degree-of-freedom (DoF) Moving Platform (MP) is considered.
Vibration Analysis of a Long Boom for a Farm Machine
Authors: Zhang Qianwei , Fotouhi Reza
Published: November 2018

Crop phenotyping is frequently used by breeders and crop scientists to monitor growth of plants and to relate them to plants genotypes. Seemingly, this contributes to better crop growth and results in higher yield. Instead of traditional crop monitoring, which is labor intensive, high-throughput phenotyping (HTP) platforms using ground-based vehicle have several advantages (in speed, efficiency, and cost) over manual methods. A wheeled mobile platform for HTP was developed, and automated data collection were performed for different traits of canola and wheat. These data were compared with manual measured data. In this paper, vibration analysis of a relatively long cantilever boom attached to a vehicle is reported. The paper investigates how different factors influence the boom attached to a regular farming machine, its vibration, and effects on phenotyping sensors attached to the boom.