bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Fabrication of a Containerized Micro-Grid for Disaster Relief and Off-Grid Applications
Authors: Janko Samantha , Atkinson Shaun , Johnson Nathan
Published: December 2016

Rapid solutions are needed throughout the world to meet electrical demands for disaster relief, stabilizing development, industrial or research centers, exploratory drilling and mining, military stationing, and other off-grid or weak-grid applications. This need for on-demand power requires a mobile, modular, and self-sufficient power system designed for rapid deployment and seamless integration. This paper describes a mobile power solution specifically designed for disaster response situations like the Haiti earthquake in 2010, the primary motivating case for this work. A public-private partnership between Arizona State University and NRG Energy was formed to complete the use-inspired design. The mobile system was scoped to meet electricity requirements for a command center, clinic, cellular communications, kitchen, short-term lodging and public lighting, and other critical loads needed to stabilize development in the wake of natural or anthropogenic disaster that destroys the local electrical infrastructure. Deploying modular and self-contained micro-grids has the potential to reduce human harm following disaster by providing a decentralized network of electrical generation assets designed to meet critical loads for human survival and well being. In addition, since no two emergency situations are alike, the proposed solution provides flexibility and scalability to meet constraints for local renewable resources, fuel availability, and physical deployment space. The final system includes a 20 kW solar photovoltaic (PV) array, 10 kWh of lithium-ion battery storage, a 10 kW inverter system, a control computer, and a 20 kW diesel generator for supplemental power. The solar array is packed within a 20’ steel shipping container for ease and safe transport, thereby making the solution “containerized.” Components must be firmly mounted or secured to the walls and floors of the container for transport via a cargo freighter or helicopter. A second room was created inside the container to separate the generator from the batteries for safety purposes. The prototype can be fully deployed and functional in less than one hour’s time, and was tested against a load bank during various times of the day to illustrate how the power system controls shift operation between batteries, solar PV, and the generator. Sustainability, ethics, health, and safety features were considered in relation to the design specifications, manufacturability, and design scalability. These considerations included the lifecycle of the container, maintenance, modularity, intuitive operation, accessibility, and component temperature regulation, among others. Integration of other technologies such as wind power generation and water purification have the potential to bring further benefit through the plug-and-play containerized micro-grid solution.
Kinematic Analysis of a Skid-Steer Mobile Robot Operating on Non-Planar Surfaces
Authors: Qualls Joshua , Canfield Stephen , Shibakov Alexander , Hill Tristan
Published: December 2016

Mobile robotic systems are advancing manufacturing operations in fields that generally exhibit less automation such as shipbuilding, pipe inspection, and construction applications on non-planar surfaces. Mobile robots operating in such environments are typically required to assume climbing configurations to complete desired tasks. These tasks are usually considered planar in nature, however, in practice are generally non-planar. A common task seen on non-planar surfaces is the welding of ship hulls. This process consists of welding segments together and is normally completed by a skilled laborer due to the complexity of the surface. Through the advancement of kinematic modeling of mobile robots there exists the ability to develop future platforms with the potential to perform efficient operations on non-planar surfaces. While the majority of kinematic models presented for mobile robots assume operations on planar surfaces, a number of studies consider kinematic behavior on non-planar surfaces. These past works generally take one of two approaches: developing assumed modifications to the existing kinematic constraints as algebraic equations, or making use of a set of differential equations describing the instantaneous motion of the contact point between non-planar surfaces. The second approach is more general and shown to be applicable for both general and specific terrains. However, the previous works main focus is on differential-steer platforms with a passive castor. Conversely, Skid-Steer mobile robots, (SSMR), provide simple, robust platforms that have several features making them well suited to manufacturing tasks. This paper will present a kinematic model for an SSMR operating on a non-planar, nominally spherical surface with a method readily generalized to other surface geometries.
Additive Manufacturing of Functionally Graded Objects: A Review
Authors: Zhang Binbin , Jaiswal Prakhar , Rai Rahul , Nelaturi Saigopal
Published: December 2016

Functionally graded materials (FGM) have recently attracted a lot of research attention in the wake of the recent prominence of additive manufacturing (AM) technology. The continuously varying spatial composition profile of two or more materials affords FGM object to simultaneously possess ideal properties of multiple different materials. Additionally, emerging technologies in AM domain enables one to make complex shapes with customized multifunctional material properties in an additive fashion, where laying down successive layers of material creates an object. In this paper, we focus on providing an overview of research at the intersection of AM techniques and FGM objects. We specifically discuss the FGM modeling representation schemes and outline a classification system to classify existing FGM representation methods. We also highlight the key aspects such as the part orientation, slicing, and path planning processes that are essential for fabricating a quality FGM object through the use of multi-material AM techniques.
Performance of a Bi-Stable Resonator With Random Input Vibrations
Authors: Yang Wei , Towfighian Shahrzad
Published: December 2016

By converting ambient mechanical energy to electricity, vibration energy harvesting, enable powering of low-power remote sensors. However, realistic ambient vibrations are random and spread over a wide frequency spectrum, which means linear resonators fail to perform effectively because of their narrow frequency bandwidth. Hence, there is a need for thorough investigation of performance of nonlinear resonators with Gaussian random vibration. This article presents a simulation study on the use of magnets to improve a nonlinear oscillator for energy harvesting from broadband low frequency random excitation. The resonator response to Gaussian distribution random input is investigated using root mean square value and power spectral density of voltage. The obtained results show that in a broadband low frequency spectrum the nonlinear system performs better than linear resonance. The optimal performance is found when the distance between two magnets is near the mono-stable to bi-stable transition regime.
Isothermal Creep Behavior of 3M™ Scotch-Weld™ EC-2216 B\A in Single Lap Joints
Authors: Dabiri Arman , Madril Edgar
Published: December 2016

This paper studies the isothermal creep behavior of the 3M™ Scotch-Weld™ EC-2216 B\A Gray (EC-2216) epoxy in single lap joints subjected to a uniaxial tensile load. The time-independent mechanical properties of EC-2216 such as the Young’s modulus, shear modulus, and bulk modulus have been reported in the literature, but the results are not consistent. However, to the best knowledge of the authors its shear stress-strain constitutive equation has not been obtained yet. Thus, in this paper, we propose the shear stress-strain constitutive equation of the EC-2216 in single lap joints subjected to uniaxial tensile tests at room temperature (24±3°C). First, a viscoelastic model is estimated in short-term experiments within the viscoelastic regime. Second, the creep deformation of the EC-2216 is modeled by different conventional imperial models. Third, different conventional creep rate models are used to estimate the steady state creep rate of the third stage, which mainly indicates the longevity of the material. Moreover, the failure accumulate strain is obtained based on the maximum strain criterion, for different shear stress levels. Finally, the proposed models are compared to the current published data.
Performance Characterization of Multifunctional Wings With Integrated Flexible Batteries for Flapping Wing Unmanned Air Vehicles
Authors: Holness Alex , Steins Ella , Bruck Hugh , Peckerar Martin , Gupta S. K.
Published: December 2016

In this work, we investigate the integration of ultrathin galvanic cell batteries with high energy density and flexibility into the highly deformable wings of the flapping wing air vehicle (FWAV) known as “Robo Raven” that we previously developed for independent wing control. The goal of this research was to create a multifunctional wing structure that provides higher energy density than the existing, singular function, lithium polymer batteries currently being used to power the platform. The key areas of inquiry explored are the effect the integration of batteries has on the aerodynamic forces generated during flapping under simulated flight conditions, and whether there is an adverse effect on flight performance where the platform payload capacity is diminished for similar flight time. Upon investigation, we determine that the electrical performance of the battery is as expected after integration into the wing structure, while force generation is not significantly affected, which enhances flight time enhancement and/or payload capacity.
Physics-Based Piloted Flight Simulation of Helicopters Using Multibody Dynamics
Authors: Zanoni Andrea , Masarati Pierangelo , Quaranta Giuseppe
Published: December 2016

This paper describes a pilot-in-the-loop flight simulation system based on first-principles general-purpose multibody dynamics for the piloted simulation of the flight dynamics of rotor-craft. Focus is placed on aspects related to multibody simulation and the related inter-process communication requirements and solutions.
Modeling, Experiments, and Parameter Sensitivity Analysis of Hydraulic Electromagnetic Shock Absorber
Authors: Guo Sijing , Xu Lin , Liu Yilun , Liu Mingyi , Guo Xuexun , Zuo Lei
Published: December 2016

To improve the vehicle fuel economy and prolong the thermal fatigue life of the traditional shock absorbers, energy regenerative electromagnetic shock absorbers have attracted wide attentions. This paper discusses a hydraulic electromagnetic shock absorber (HESA), which has high reliability. A dynamic model of HESA is created in this paper, which shows that the damping force of HESA is composed of the electric damping force, friction damping force, the inerter force and the accumulator force. Influences of hydraulic motor and pipe diameter on the force are analyzed based on the modeling. The parameters of the nonlinear component accumulator are also studied experimentally. Both modeling and lab tests show that the accumulator force can counteract part of the effect of the inerter force, which is greatly beneficial for the vehicles. The damping characteristics and energy harvesting characteristics are also studied based on the lab tests. Results show that the damping coefficient of HESA ranges from 12000Ns/m to 92000Ns/m at a vibration input of 3Hz frequency and 5mm amplitude, and HESA has a unique damping characteristic which needs to be further studied for vehicle dynamics. In addition, the efficiency of HESA can achieve 30% at a vibration input of 3Hz frequency and 7mm amplitude with external resistance of 4 ohms. The average power at this excitation can reach 102 watts.
Identification of Subproblems in Complex Design Problems: A Study of Facility Design
Authors: Azhar Azrah , Gralla Erica L. , Tobias Connor , Herrmann Jeffrey W.
Published: December 2016

Many design problems are too difficult to solve all at once; therefore, design teams often decompose these problems into more manageable subproblems. While there has been much interest in engineering design teams, no standard method has been developed to understand how teams solve design problems. This paper describes a method for analyzing a team’s design activities and identifying the subproblems that they considered. This method uses both qualitative and quantitative techniques; in particular, it uses association rule learning to group variables into subproblems. We used the method on data from ten teams who redesigned a manufacturing facility. This approach provides researchers with a clear structure for using observational data to identify the problem decomposition patterns of human designers.
Total Lagrangian Formulation for Large Deformation Modeling Using Uniform Background Mesh
Authors: Bhosale Nikhil , Kumar Ashok V.
Published: December 2016

Mesh generation difficulties can be avoided when a background mesh rather than a mesh that conforms to the geometry is used for the analysis. The geometry is represented by equations and is independent of the mesh and is immersed in the background mesh. The solution to boundary value problems is approximated or piece-wise interpolated using the background mesh. The main challenge is in applying the boundary conditions because the boundaries may not have any nodes on them. Implicit boundary method has been used for linear static and dynamic analysis and has shown to be an effective approach for imposing boundary conditions but has never been applied to nonlinear problems. In this paper, this approach is extended to large deformation nonlinear analysis using the Total Lagrangian formulation. The equations are solved using the widely used modified Newton-Raphson method with loads applied over many load steps. Several test examples are studied and compared with traditional finite element analysis software for verification.
Mechanical Design and Analysis of a Wheelchair Mounted Robotic Arm With Adaptable Gripper and Remote Actuation System
Authors: Ahlstedt Matthew , Duling Carter , Yihun Yimesker
Published: December 2016

Majority of wheelchair users experience upper-body muscular weakness, resulting from neuromuscular diseases, which limit their ability to perform common activities of daily living. A Wheelchair Mounted Robotic Arm (WMRA) will assist these individuals to eat, drink, and move objects as needed. This paper presents the design of a new WMRA as well as the analysis of its function. The design is side-mounted onto either a normal or power wheelchair, and incorporates a slim profile to allow ease of passage through doorways and be otherwise unobtrusive. The arm is easily removable, with assistance, for storage or travel. The mechanical design utilizes a belt and pulley system for remote actuation of each joint, driven by DC Gearmotors located in the base of the arm. This helps to shift the weight closer to the wheelchair and to maintain the required speed, torque and inertia while actively driving each joint of the robot. The end-effector is a unique design, intended to have the adaptability to securely lift a large variety of objects. Grasping simulations were performed on several standard objects which might be encountered daily. Structural, kinematic and workspace analyses are conducted, and results confirm that the designed WMRA is rated to lift a 4 kg payload, while also having a reach of 1.3 meters long radius.
Tracking and Disturbance Rejection for Uncertain Periodic Load Disturbed Power System by Adaptive Output Feedback Control
Authors: Zhou Guopeng , Zhou Fang , Zhou Naiding , Liang Feng
Published: December 2016

This paper studies energy storage based output tracking and disturbance rejection problems for a simple interconnected power system suffered from a periodic load disturbance with unknown amplitude and frequency. By constructing a new exosystem, the problem is converted into output regulation problem of a composite system. Internal model theorem is introduced for the composite system, and output regulation problem is changed into stabilization problem of a new augmented system by imposing an appropriate transformation. An adaptive dynamical energy storage based controller can solve stabilization problem of the augmented system as well as output tracking and disturbance rejection problem for the original system. Finally, simulation results show the effectiveness of the proposed controller.
Singularity Variety of a 3SPS-1S Spherical Parallel Manipulator
Authors: Li Ju , McCarthy J. Michael
Published: December 2016

In this paper, we study the manifold of configurations of a 3SPS-1S spherical parallel manipulator. This manifold is obtained as the intersection of quadrics in the hypersphere defined by quaternion coordinates and is called its constraint manifold. We then formulate Jacobian for this manipulator and consider its singular. This is a quartic algebraic manifold called the singularity variety of the parallel manipulator. A survey of the architectures that can be defined for the 3SPS-1S spherical parallel manipulators yield a number of special cases, in particular the architectures with coincident base or moving pivots yields singularity varieties that factor into two quadric surfaces.
System Engineering Method Based on Axiomatic Design and MBSE Modeling Framework
Authors: Haoqi Wang , Zhang Xu , Zhenyu Lv , Chengtong Tang
Published: December 2016

A fundamental challenge for engineers when applying the MBSE (Model-based Systems Engineering) is to analyze complex design problems in an effective way and to represent a complex system with complete models. Aiming at providing an efficient design problem analyzing process and general modeling framework, this paper proposed an Axiomatic Design Theory (ADT) based System Engineering approach by mapping design domains, design axioms and a “Z” mapping process of ADT to complex system’s design processes, modeling and control processes and information loops respectively. Then a MBSE modeling framework that includes the Requirement Model, Functional Architecture and Physical Implementation Architecture was constructed. The presented method and modeling framework is able to guide system engineers to capture design problems effectively. After that, a case study was illustrated to demonstrate how the presented approach was applied. Last, the paper gave conclusions and future works that show lights on improving the MBSE modeling framework to function in a consistent way.
Feature Extraction for Bearing Diagnostics Based on the Characterization of Orbit Plots With Orthogonal Functions
Authors: Samadani M. , Haj Mohamad T. , Nataraj C.
Published: December 2016

This paper introduces a new feature extraction method based on the topology of the phase space of the dynamical systems. The method is based on transforming the phase space into the density space and approximating the density with orthogonal functions. The proposed method has been applied to vibration data of a rotating machine measured by proximity probes in order to identify and diagnose bearing defects. As will be shown, the proposed feature extraction method has outstanding capability in characterizing the system response and diagnosing the system, is robust to noise, does not depend on expert knowledge about the system, requires no feature ranking or selection and can easily be applied in an automated process.
Modeling Post-Impact Injury Propagation in Traumatic Brain Injury
Authors: Pillai Nikhil , Patra Abani , Esfahani Ehsan
Published: December 2016

In this paper, we investigate the effect of mechanical deformation during original impact on the propagation of bleeds during traumatic brain injury (TBI). For this purpose, we have developed a numerical framework that considers Magnetic Resonance Images (MRI) of a rat subjected to TBI modelled using controlled cortical impact (CCI). Using the MRI images of first day of impact a solid model of brain is developed and strains during impact are estimated using the finite element tool LSDyna. It was observed that the actual propagation of blood obtained from day 14 MRI data closely resembles the one developed by solving a time dependent advection equation with advection rates proportional to the strain estimates during impact from LSDyna. This numerical framework holds promise that with proper calibration and validation it can be used to predict the possible propagation of blood post-impact and therefore may be used to inform treatment protocols for such patients.
Machine Learning and Metamodel-Based Design Optimization of Nonlinear Multimaterial Structures
Authors: Liu Kai , Detwiler Duane , Tovar Andres
Published: December 2016

This study presents an efficient multimaterial design optimization algorithm that is suitable for nonlinear structures. The proposed algorithm consists of three steps: conceptual design generation, design characterization by machine learning, and metamodel-based multi-objective optimization. The conceptual design can be generated from extracting finite element analysis information or by using structure optimization. The conceptual design is then characterized by using machine learning techniques to dramatically reduce the dimension of the design space. Finally, metamodels are derived using Efficient Global Optimization (EGO) followed by multi-objective design optimization to find the optimal material distribution. The proposed methodology is demonstrated using examples from multiple physics and compared with traditional multimaterial topology optimization method.
Design, Fabrication, Experimental Analysis, and Test Flight of an Origami-Based Fixed-Wing Aerial Vehicle: µPlane
Authors: G. Faal Siamak , Chen Fuchen , Tao Weijia , T. Kalat Shadi , Razavi Payam , Eshaghian Vahideh , Onal Cagdas D.
Published: December 2016

This article covers details the design, fabrication, experimental analysis, and first flight tests of μPlane, an origami-inspired aerial vehicle. μPlane is a monoplane with a straight wing planform that has a wingspan of 580 millimeters and can reach a maximum linear velocity of 6.12 meters-per-second. The body of the μPlane is fabricated by folding a single, unified crease pattern which includes all the sections required to construct the wing, tail, fuselage, and connection ports for external components, such as actuators and batteries. The wing of the plane utilizes a cambered profile to generate the required lift force. An optimization problem is formulated to find a solution to the set of constraints that provides the desired camber form. To validate the proposed design, a 3D scan of the top surface of the wing is accrued using a high-resolution fringe projection system. Finally, the flight performance and stability of μPlane are tested in both indoor and outdoor environments.
Optimization of Power and Operation Characteristics of a New External Axis Wind Turbine
Authors: Ferdoues Mst Sunzida , Ebrahimi Sasan , Vijayaraghavan Krishna
Published: December 2016

A new class of wind turbine termed the external axis wind turbine (EAWT) has been recently developed. The EAWT is a new class of wind turbines that combines the low cost of vertical axis wind turbines with the high power of horizontal axis wind-turbine. This paper is a first step study that assumes a constant wind speed and a simple on-off controller. The paper optimizes the number of blades in the EAWT and the time at which the controller must be turned on to simultaneously maximize the power while minimizing the time required to reach optimal operation. The multi-objective optimization on the EAWT is performed on a response surface that is generated using Computational Fluid Dynamics (CFD) simulations. The turbulence model and mesh-sizing for the CFD simulations are validated against previously published experimental results on a buff body. To the best of authors’ knowledge, this paper is the first study to investigate changing blade count, and determining optimal operation speed to simultaneously maximize power, while minimizing the time needed to reach peak operational point in wind-turbines.
Identifying the Relations Between Product Features and Sales Rank From Online Reviews
Authors: Suryadi Dedy , Kim Harrison
Published: December 2016

Online product reviews have become an efficient source to gather consumer needs, instead of going through the labor-intensive surveys. The contribution of the paper is to relate the content of online reviews to a product’s sales rank, that implicitly reflects the needs and motivation behind what drives customers to purchase the product. In particular, the review content includes product features stated in the review, together with the sentiment expressed towards the feature. Part-of-speech tagging is used to extract the features and sentiment from the reviews. The extracted data from reviews and price then subsequently become independent variables in the regression model, while sales rank is the dependent variable. An experiment is run for the wearable technology products to illustrate the methodology and interpret the results. In general, the features in reviews that are related to sales rank significantly are button, calorie tracker, design, time functions, and waterproof abilities. Moreover, the products are further stratified based on price average. In the cluster of the most expensive items, the sales rank is found to be not significantly related to price.
A Dual-Frequency Approach Based on the Subspace Method for Identifying Nonlinear Vibration Structures
Authors: Zhang M. W. , Wei Y. M. , Wei S. , Peng Z. K. , Dong X. J. , Zhang W. M.
Published: December 2016

Subspace-based state space system identification method is well known for its computational efficiency and robustness. However, when directly applied to nonlinear models, intrinsic drawbacks exist and may lead to less accurate estimation. This paper explains how the error is generated when transforming continuous-time model to discrete-time one and then presents an approach to identify nonlinear systems by choosing two different sample frequencies for different parts of the discrete-time state-space model. The method allows to identify the nonlinear coefficients and the underlying linear system more robustly based on only the input and output of the structural system. Several numerical examples are given to illustrate the correctness of the analysis and the effectiveness of the method.
Using Kinect to Capture Human Motion for Mechanism Synthesis, Motion Generation and Visualization
Authors: Purwar Anurag , Desai Rumit
Published: December 2016

In this paper, we are presenting a framework for capturing human motions using Microsoft Kinect sensor for the purpose of 1) generating task positions for mechanism and robot synthesis, and 2) generation and visualization of B-spline inter-polated and approximated motion from the captured task positions. The theoretical foundation of this work lies in Kinematic Mapping, Dual and Bi-quaternions, and NURBS (Non-Uniform Rational B-spline) geometry. Lately, Kinect has opened doors for creation of natural and intuitive human-machine interactive (HMI) systems in medicine, robotic manipulation, CAD, and many other fields, where visual-sensing and -capture is a central theme. Kinect has made a huge impact in physical therapy area, achieving new benchmarks in tele-rehabilitation by improving physical exercise assessment, monitoring and supervision using the skeletal data. Moreover, Kinect’s depth sensing capability has helped in retrieving depth information required for robotic vision in grasping, object recognition which was previously done using computationally demanding computer vision algorithms. Kinect’s point cloud data with interactive gestures has proven to be useful in various CAD software for conceptual design of shapes. Mechanism synthesis is one of the areas in Kinematics, where Kinect-provided skeletal data can be leveraged to design and develop highly customized end-user collaborated mechanism solutions. We demonstrate that using Kinect, OpenGL, and Openframeworks, we can capture discrete (or, key) rigid body displacements, continuous motions, and generate and visualize rational B-spline motions from captured key positions. Capturing only a few key positions results in significant data savings and also provides a natural way to create tasks for mechanism synthesis problems. The output is a set of dual quaternions and 4 × 4 homogeneous transforms representing a task motion, which can be used as an input for mechanism synthesis applications. The tool produced also allows users to generate trajectories of various points on a moving rigid body interactively. A Kinect-based capture of such motions can help create highly-customized assistive devices for people who suffer from a range of motion-related difficulties due to old age or disabilities.
The Response Surface Single Loop Reliability-Based Design Optimization Method With Reliability Requirement on System Failure
Authors: Mansour Rami , Olsson Mårten
Published: December 2016

In reliability-based design optimization (RBDO), an optimal design which minimizes an objective function while satisfying a number of probabilistic constraints is found. As opposed to deterministic optimization, statistical uncertainties in design variables and design parameters have to be taken into account in the design process in order to achieve a reliable design. In the most widely used RBDO approaches, the First-Order Reliability Method (FORM) is used in the probability assessment. This involves locating the Most Probable Point (MPP) of failure, or the inverse MPP, either exactly or approximately. If exact methods are used, an optimization problem has to be solved, typically resulting in computationally expensive double loop or decoupled loop RBDO methods. On the other hand, locating the MPP approximately typically results in highly efficient single loop RBDO methods since the optimization problem is not necessary in the probability assessment. However, since all these methods are based on FORM, which in turn is based on a linearization of the deterministic constraints at the MPP, they may suffer inaccuracies associated with neglecting the nonlinearity of deterministic constraints. In a previous paper presented by the authors, the Response Surface Single Loop (RSSL) Reliability-based design optimization method was proposed. The RSSL-method takes into account the non-linearity of the deterministic constraints in the computation of the probability of failure and was therefore shown to have higher accuracy than existing RBDO methods. The RSSL-method was also shown to have high efficiency since it bypasses the concept of an MPP. In RSSL, the deterministic solution is first found by neglecting uncertainties in design variables and parameters. Thereafter quadratic response surface models are fitted to the deterministic constraints around the deterministic solution using a single set of design of experiments. The RBDO problem is thereafter solved in a single loop using a closed-form second order reliability method (SORM) which takes into account all elements of the Hessian of the quadratic constraints. In this paper, the RSSL method is used to solve the more challenging system RBDO problems where all constraints are replaced by one constraint on the system probability of failure. The probabilities of failure for the constraints are assumed independent of each other. In general, system reliability problems may be more challenging to solve since replacing all constraints by one constraint may strongly increase the non-linearity in the optimization problem. The extensively studied reliability-based design for vehicle crash-worthiness, where the provided deterministic constraints are general quadratic models describing the system in the whole region of interest, is used to demonstrate the capabilities of the RSSL method for problems with system reliability constraints.
Incorporating Constraints in System Modularization by Interactive Clustering of Design Structure Matrices
Authors: Sanaei Roozbeh , Otto Kevin N. , Hölttä-Otto Katja , Wood Kristin L.
Published: December 2016

Modularity is an approach to manage the design of complex systems by partitioning and assigning elements of a concept to simpler subsystems according to a planned architecture. Functional-flow heuristics suggest possible modules that have been demonstrated in past products, but using them still leaves it to the designer to choose which heuristics make sense in a certain architecture. This constitutes an opportunity for a designer to take other constraints and objectives into account. With large complex systems, the number of alternative groupings of elements into modular chunks becomes exponentially large and some form of automation would be beneficial to accomplish this task. Clustering algorithms using the design structure matrix (DSM) representation search the space of alternative relative positioning of elements and present one ideal outcome ordering which “optimizes” a modularity metric. Beyond the problems of lack of interactive exploration around the optimized result, such approaches also partition the elements in an unconstrained manner. Yet, typical complex products are subject to constraints which invalidate the unconstrained optimization. Such architectural partitioning constraints include those associated with external force fields including electric, magnetic, or pressure fields that constrain some functions to perform or not perform in different regions of the field. There are also supplier constraints where some components cannot be easily provided with others. Overall, it is difficult to simply embed all objectives of modular thinking into one metric to optimize. We develop a new type of interactive clustering algorithm approach considering multiple objectives and partitioning constraints. Partitioning options are offered to a designer interactively as a sequence of clustering choices between elements in the architecture. A designer can incorporate constraints that determine the compatibility or incompatibility of elements by choosing among alternative groupings progressively. Our aim is to combine computational capability of clustering algorithms with the flexibility of manual approaches. Through applying these algorithms to a MRI machine injector, we demonstrate the benefits of interactive cooperation between a designer and modularity algorithms, where constraints can be naturally considered.
A Dynamic Model of Electrostrictive Unimorph Actuators for Haptic Devices
Authors: Safwat Tahzib , Tosto Ryan , Grissom Michael D. , Rahn Christopher D.
Published: December 2016

Piezoelectric materials are commonly found in many devices, but their usage is limited by the low strain and high stiffness of the material. This prevents their use in “soft” applications, such as compliant actuators for haptic feedback devices and wearable technology. The actuation dynamics of a ferro-electric relaxor terpolymer, a type of soft and high strain electroactive polymer (EAP), are examined. This paper studies the unimorph actuator via a linearized time-domain model and experiments to validate the model include step response and frequency response of tip displacement.
A Method for Classifying Products Designed for the Developing World
Authors: Troxell Paden M. , Kim Charles
Published: December 2016

Researchers in the area of design for the developing world have synthesized knowledge from location-specific product case studies in the form of design guidance, which includes pitfalls, principles, and methods. Much of the design guidance relates to specific product classes and regions, while recent work is directed towards generalized principles. The aim of this paper is to fill gaps in product class-specific design guidance by creating larger groups of similar products, which share design characteristics. In this paper, we present a method for classifying products into such groups utilizing cluster analysis. We present a five-step method, which includes optional synthesis of design principles. The potential value of the method is demonstrated in a case study. The result included two distinct product groups, titled Products for Relief and Products for Development, and corresponding design principles for each group.
Extending Expected Improvement for High-Dimensional Stochastic Optimization of Expensive Black-Box Functions
Authors: Pandita Piyush , Bilionis Ilias , Panchal Jitesh
Published: December 2016

Design optimization under uncertainty is notoriously difficult when the objective function is expensive to evaluate. State-of-the-art techniques, e.g., stochastic optimization or sampling average approximation, fail to learn exploitable patterns from collected data and, as a result, they tend to require an excessive number of objective function evaluations. There is a need for techniques that alleviate the high cost of information acquisition and select sequential simulations in an optimal way. In the field of deterministic single-objective unconstrained global optimization, the Bayesian global optimization (BGO) approach has been relatively successful in addressing the information acquisition problem. BGO builds a probabilistic surrogate of the expensive objective function and uses it to define an information acquisition function (IAF) whose role is to quantify the merit of making new objective evaluations. Specifically, BGO iterates between making the observations with the largest expected IAF and rebuilding the probabilistic surrogate, until a convergence criterion is met. In this work, we extend the expected improvement (EI) IAF to the case of design optimization under uncertainty. This involves a reformulation of the EI policy that is able to filter out parametric and measurement uncertainties. We by-pass the curse of dimensionality, since the method does not require learning the response surface as a function of the stochastic parameters. To increase the robustness of our approach in the low sample regime, we employ a fully Bayesian interpretation of Gaussian processes by constructing a particle approximation of the posterior of its hyperparameters using adaptive Markov chain Monte Carlo. An addendum of our approach is that it can quantify the epistemic uncertainty on the location of the optimum and the optimal value as induced by the limited number of objective evaluations used in obtaining it. We verify and validate our approach by solving two synthetic optimization problems under uncertainty. We demonstrate our approach by solving a challenging engineering problem: the oil-well-placement problem with uncertainties in the permeability field and the oil price time series.
Influence of Chaotic Characteristics on Ride and Comfort of the Electric Vehicle
Authors: Wu Guangqiang , Niu Zhidong
Published: December 2016

In this paper, the influence of chaotic motions on ride and comfort was studied through analyzing the vibration acceleration signal. By considering the stabilizer, the rigid-flexible coupling dynamics model of electric vehicle was built. The vertical vibration acceleration signals of the human trunk mass and head mass was acquired by the simulation. Two sets of data were selected according to the data of multiple simulations. In the first set, the vertical acceleration signals of the human trunk and head had the characteristics of chaotic motions, but in the second set, the signals did not have. The chaotic dynamic characteristics of the two sets were analyzed by numerical method. The total weighted acceleration root mean squared values of the two sets were calculated, and the value of the first set was larger than the second. The results showed that the ride and comfort of electric vehicle became worse when the system appeared chaotic motions. The vehicle test was carried out, it is found that the possibility of the existence of chaotic motions in driving an electric vehicle.
Investigating the Use of Smell in Vehicle-Driver Interaction
Authors: Bordegoni Monica , Carulli Marina , Shi Yuan
Published: December 2016

Every year approximately more than one million people die on world’s road. Human factors are the largest contributing factors to the traffic crashes and fatality, and recent researches have identified drivers’ cognitive aspect as the major cause of human errors in 80% of crash events. Thus, the development of countermeasures to manage drivers’ cognitive aspect is an important challenge to address. Driver-Assistance Systems have been developed and integrated into vehicles to acquire data about the environment and the driver, and to communicate information to the driver, usually via the senses of vision and hearing. Unfortunately, these senses are already subjected to high demands, and the visual and auditory stimuli can be underestimate or considered as annoying. However, other sensory channels could be used to elicit the drivers’ cognitive aspect. In particular, smell can impact on various aspects of humans’ psychological state, such as people’s attention level, and can induce activation states in people.

The research presented in this paper aims at investigating whether olfactory stimuli, instead of auditory ones, can be used to influence the cognitive aspect of the drivers. For this purpose, an experimental framework has been set up and experimental testing sessions have been performed. The experimental framework is a multisensory environment consisting of an active stereo-projector and a screen used for displaying a video that reproduces a very monotonous car trip, a seating-buck for simulating the car environment, a wearable Olfactory Display, in-ear earphones and the BioGraph Infiniti system for acquiring the subjects’ physiological data.

The analysis of the data collected in the testing sessions shows that, in comparison to the relaxation state, olfactory stimuli are effective in increasing subjects’ attention level more than the auditory ones.
Curved Compliant Facet Origami-Based Self-Deployable Gliding Wing Module for Jump-Gliding
Authors: Baek Sang-Min , Lee Dae-Young , Cho Kyu-Jin
Published: December 2016

In this paper, we propose a self-deployable origami structure and its application to a gliding wing module for jump-gliding. Generally, origami structures are composed of flat rigid facets. By using curved compliant facets instead of flat rigid facets, we endowed the origami structure with the ability to self-deploy and self-lock. When the origami structure is folded, the curved facets gradually flatten, and potential energy is stored on the flattened facets. By using the stored energy, the structure can rapidly deploy without an actuator. The geometry of the curved facet generates a notably high joint stiffness in the deployed state, which can be used as a self-locking mechanism.

In jump-gliding, the gliding wing should be foldable and lightweight for efficient jumping and capable of rapid deployment for efficient gliding. By applying the suggested origami structure as a basic frame, the deployable gliding wing module can satisfy these requirements. The wing span of the module is 44.7 cm, and it weighs 20.3 g including a battery and a servo motor. The module can be folded in 1/8.1 of the deployed area, and it deploys within 350 ms when it needs to glide.
RRT-HX: RRT With Heuristic Extend Operations for Motion Planning in Robotic Systems
Authors: Pareekutty Nahas , James Francis , Ravindran Balaraman , Shah Suril V.
Published: December 2016

This paper presents a sampling-based method for path planning in robotic systems without known cost-to-go information. It uses trajectories generated from random search to heuristically learn the cost-to-go of regions within the configuration space. Gradually, the search is increasingly directed towards lower cost regions of the configuration space, thereby producing paths that converge towards the optimal path. The proposed framework builds on Rapidly-exploring Random Trees for random sampling-based search and Reinforcement Learning is used as the learning method. A series of experiments were performed to evaluate and demonstrate the performance of the proposed method.
Numerical Simulation and Structural Improvement for the Crashworthiness Capacity of M1 Type Commercial Vehicle
Authors: Wang Tao , Wang Liangmo
Published: December 2016

To investigate the crashworthiness capacity of a M1 type commercial vehicle, the full-scale finite element (FE) model of the vehicle has been established. On the basis of the FE model, the impact simulation subject to the 100% frontal impact has been carried out, and the results have been verified with the physical impact test. The analysis of the deformation path and the energy absorption indicates that the M1 vehicle lacks sufficient frontal deformation area and its peak crash acceleration (PCA) is too high, which raises a huge challenge for the sequent development of a safety restraint system. To enhance the crashworthiness of the M1 vehicle, some structural improvements have been implemented, with adding the energy absorbing box, improving the frontal frame parts and enhancing the front door. The frontal collapsing area has been investigated in order to figure out the layout position of the energy absorbing box. The design of the aluminum foam reinforced energy absorbing box has been made by using the surrogate modeling technique. The impact simulation results of the improved M1 vehicle show a significant decrease of the PCA and a more homogeneous energy absorbing status, which verifies the validity of the proposed structures for crashworthiness improvement.
On Vibration Suppression and Energy Dissipation Using Tuned Mass Particle Damper
Authors: Li Shilong , Tang J.
Published: December 2016

Particle damping has the promising potential for attenuating the unwanted vibrations in harsh environment. However, the damping performance of the conventional particle damper (PD) may be ineffective, especially when the acceleration of the particle damper is less than gravitational acceleration (1g). In order to improve the damping performance of the traditional PD, the tuned mass particle damper (TMPD) which utilizes the advantages of both the tuned mass damper and particle damper is investigated in this paper. The TMPD can act as the tuned mass damper to not only absorb the vibration of the primary structure but also amplify the motions of the particles in the enclosure, which will significantly enhance the particle damping effect. To analyze the damping effect of the TMPD, a new coupling method to integrate the TMPD into the continuous host structure is first developed. The 3D discrete element method is then adopted to accurately describe and analyze the motion of particles in the enclosure. Furthermore, the analysis is validated by correlating the numerical and experimental results. With the new method as basis, detailed numerical studies are further carried out to verify the damping effectiveness of the TMPD compared with conventional PD under various excitation levels. The results demonstrate that the TMPD can significantly improve the damping effect of the conventional PD on suppressing the vibration of the primary structure under both the low and high excitation levels.
Automated Non-Prehensile Magnetic Micromanipulation in Presence of Spatially Varying Flow Field
Authors: Kulkarni Pranav , Kumar Aditya , Thakur Ajay D. , Thakur Atul
Published: December 2016

Precise control of micro-level objects for cell sorting, cell manipulation, targeted drug delivery etc., still remains a great challenge in the field of bio-medical engineering. Even though magnetic actuation has emerged as a harmless, high actuation speed, low cost alternative for micromanipulation of cells, the throughput of the system is still low because of the undesirable effects of flow fields and sensing noise. This paper reports a parametrized feedback policy to perform non-prehensile magnetic micromanipulation [9] to push the target cell to specified goal location under the influence of flow field, sensing noise, drag and magnetic forces. We report an optimization based parameter tuning approach to reduce the transport time using developed feedback policy. Flow field and image processing noise present in the system was experimentally measured and incorporated into the developed models and simulations. We have tuned the feedback policy parameter to reduce the travel time via simulation experiments.