bluuebunny/crossref_metadata_2025 huggingface dataset:
User Study of Hand Gestures for Gesture Based 3D CAD Modeling
Authors: Thakur Aditya , Rai Rahul
Published: January 2016

Gestures are an important medium of human communication and have been studied throughout the centuries from different viewpoints and in different domains ranging from arts, linguistics, philosophy and engineering. Recent developments in gestures based human-computer interaction (HCI) studies are noteworthy. However, commercial application of hand gestures in computer aided sketching and modeling is rarely found. The present study focuses on identifying various aspects of hand gestures that can be used as an input to a gesture based CAD software for sketching and 3D modeling tasks. First, we experimentally observed and studied hand gestures performed by users to convey CAD sketch and 3D modeling commands. Next, we performed literature study to compile a repository of gestures used by researchers in conveying various commands for gesture based human computer interaction. With the knowledge gleaned from these two steps a simplified yet representative taxonomy was created to classify hand gestures which can be used for drawing tasks in CAD. During the course of these studies we identified various attributes/requirements of a gesture based CAD software, consideration of which will help in enhancing the CAD designer experience.
Conformal 3D Printing of Sensors
Authors: Siwach Gaurav , Rai Rahul
Published: January 2016

A sensor is unobtrusive if it doesn’t interfere with the design, mechanical properties, and the functionality of the structure it is integrated with. This paper discusses the development of unobtrusive piezo-resistive sensors and their production using additive manufacturing. Short carbon fibers were dispersed in an acrylate resin and subsequently cured with UV DLP 3D printer to be used as a strain-sensing device. Varying the amount of carbon fiber resulted in resistivity variation of the composite. The composite was found to be piezo-resistive, and gauze factor at a concentration of 12% carbon fiber by volume was obtained through mechanical load testing.
HPC Methods for Domains of Attraction Computation
Authors: Belardinelli Pierpaolo , Lenci Stefano
Published: January 2016

The work is devoted to the development of efficient parallel algorithms for the computation of large-scale basins of attraction. Since the required computational resources increase exponentially with the dimension of a dynamical system, it is common to get into memory saturation or in a secular elaboration time.

This paper presents a code, based on a cell mapping method, that evaluates basins of attraction for high-dimensional systems by exploiting the parallel programming. The proposed approach, by using a double-step algorithm, permits, i) to fully determine the basins in all the dimensions ii) to evaluate 2D Poincaré sections of the system. The code is described in all its parts: the shell, in charge of the core management, permits to split over a multi-core environment the computing domain, it carries out an efficient use of the memory.

A preliminary analysis of the performances is undertaken also by considering different dimensional grids; the optimal balance between computing cores and memory management cores is studied.
Analysis of Hybrid Dynamical Systems With Uncertainty in Initial Conditions
Authors: He Yuhua , Mukherjee Arpan , Rai Rahul
Published: January 2016

Hybrid dynamical systems (HDS) models are backbone of modeling a myriad of systems found in systems engineering, buildings, manufacturing, auto-pilot control, and chemical processes domains among others. Uncertainty quantification (UQ) techniques to ascertain output variability in HDS with parametric uncertainty is relatively understudied topic. In this paper, we present a novel method to enable UQ of HDSs. Specifically, we outline a computational pipeline to solve different types of Stochastic Hybrid Systems (SHS) with uncertainty in initial conditions. The developed method is based on a numerical integration technique Conjugate Unscented Transform (CUT) and discrete UQ technique. The developed method has been applied to different range of problems including theoretical problems and real life mechanical systems modeled in Simulink environment. Performance of the proposed method has been compared against Monte Carlo and Unscented Transform methods. Results indicate superior performance of the proposed technique over the existing methods.
Characterization of a Microfabricated Differential Scanning Calorimeter
Authors: Wang Shuyu , Yu Shifeng , Zuo Lei
Published: January 2016

Calorimeters are critical tools for structural based drug design and drug stability assessment. Current pharmaceutical industry is seeking for high throughput calorimeters to reduce the research time and expenditure. MEMS-based calorimeter is a potential solution for it, since they are miniaturized to detect the enthalpy change during macro molecular interaction with smaller amount of samples, shorter time and could easily enable parallel measurement. Consequently, we present a Differential Scanning Calorimeter (DSC) that requires 2μL sample volume. It has high thermal insulation (1210μW/K), small time constant (6.95s) and high sensitivity (7.5V/W). The low noise equivalent temperature difference (NETD) could lead to 130nW of power resolution. These characterization results indicate the device could be potentially applied for macromolecular interaction application and increase the throughput with high performance.
Topology Optimization on the Cloud: A Confluence of Technologies
Authors: Suresh Krishnan
Published: January 2016

Topology optimization is a systematic method of generating designs to meet specific engineering requirements. It is exploited today in several industries including aircraft, automobile, and machinery, and it strongly complements the emerging field of additive manufacturing. Yet, the wide-spread use of topology optimization has been deterred due to high computational cost and significant software/hardware investment.

In this paper, we propose a cloud based topology optimization (CTO) framework to overcome these challenges, thereby promoting the wider use of topology optimization. CTO requires a confluence of several methods and technologies, each of which is discussed in this paper.

First and foremost, CTO requires a fast 3D topology optimization method that can respond rapidly to multiple clients. Here, PareTO, a topological sensitivity based method is used as the backbone of the framework. PareTO relies on limited-memory finite element analysis with a deflated linear solver that is designed to exploit multi-core and many-core architectures. At the client-end, the framework relies on JavaScript based WebGL and ThreeJS technologies to display 3D geometry and formulate structural problems within a browser. Finally, Ajax, php and HTML5 technologies are exploited to achieve asynchronous and robust user experience. An implementation of this framework is available at www.cloudtopopt.com; to use this free service, JavaScript must be enabled within the browser.
Development of an Energy-Efficient Cutting Edge Geometry for Solid End Mills: A Design of Experiments-Based Approach
Authors: Westermann Hans-Henrik , Kruse Andreas , Eisinger Eva , Steinhilper Rolf
Published: January 2016

Milling operations are commonly characterized by high energy consumptions and should be in focus for optimizations aiming sustainable manufacturing processes. Research results show that within milling operations, especially in small and medium enterprises (SME), up to 80% of the applied milling cutters are solid end mills. The paper presents a design of experiments (DOE)-based optimization of the cutting edge geometry, to improve the energy efficiency and technical capability of solid end mills. Thereby the paper describes the fractional factorial design for the first-degree polynomial model as well as the subsequent set up of a central composite design (CCD) with its second-degree polynomial model for the optimization of relevant target parameter like cutting performance, tool wear and surface quality. Based on the results of more than one hundred machining tests this comprehensive approach shall contribute to the development of new cutting edge geometries of solid end mills and thereby lead to more energy-efficient machining operations in milling applications.
A System of Multi-Sensor Fusion for Activity Monitoring of Industrial Trucks in Logistics Warehouses
Authors: Alias Cyril , Özgür Çağdaş , Yang Qingjin , Noche Bernd
Published: January 2016

Industrial trucks, such as forklifts, are key enablers of logistics performance in warehouses. Being critical resources of warehousing processes, their optimal utilization and the prevention of waste in relation to the use of forklifts are of ever increasing importance. Hence, real-time data about the activities of the trucks are required for both immediate reactions on an operational level and retrospective analyses for tactical adjustments.

In the ongoing research initiative, a technical solution concept has been developed and implemented which aims at collecting activity data of an industrial truck used in an indoor warehousing environment. For this reason, different sensors are used for monitoring individual functions of an industrial truck. The truck activities monitored by means of the sensors are its acceleration behavior, i.e. speed and vibration, as well as surrounding temperatures. In addition, the occupation status and the movement of the fork have been monitored and recorded. Thereby, logistics managers and analysts are facilitated to gain insight into the activity profile of the individual truck and the entire fleet, respectively, and to derive adequate measures of adjustment or even correction.

The paper illustrates details of the technical solution concept and presents a first set of experimentation results.
Development of Engineering Uncertainty Repository
Authors: Du Xiaoping
Published: January 2016

Uncertainty is ubiquitous in engineering, but it is not taught in most of engineering courses. One of the major problems is the lack of proper teaching materials. The objective of this project is to create an Engineering Repository with teaching and learning materials so that they can be adopted in various engineering courses. We at first discuss the basics of uncertainty and the need of uncertainty education. We then report the current status of the development of the Engineering Repository and its use in classes of Dynamics and Probabilistic Engineering Design. Several examples of the Engineering Repository are also presented.
Stochastic Optimization of Hybrid Renewable Energy Systems
Authors: Sharafi Masoud , ElMekkawy Tarek Y.
Published: January 2016

The stochastic nature of energy demand and renewable energy (RE) resources make the design of hybrid renewable energy systems as a complex problem. In this paper, an innovative stochastic optimization approach is proposed for optimal sizing of hybrid renewable energy systems (HRES) incorporating existing uncertainties in RE resources and energy load. The design problem is formulated based on multiobjective optimization framework with three objective functions including minimize total net present cost (NPC), maximize renewable energy ratio (RER), and minimize fuel emission. The reliability index named loss of load probability (LLP) is considered as a constraint with a desirable level. The Pareto front (PF) of developed multi-objective optimization problem is approximated with the help of the integration of dynamic multi-objective particle swarm optimization (DMOPSO) algorithm, simulation module, and sampling average method. Synthetic data generation approaches are applied to tackle the randomness in wind speed, solar irradiation, ambient temperature, and energy load. A building located in Canada is used as the case study to assess the performance of the developed model. Finally, the obtained PF by the stochastic optimization approach is examined against the deterministic PF using the most famous performance metrics.
A Prediction Modeling Framework: Toward Integration of Noisy Manufacturing Data and Product Design
Authors: Park Junheung , Kim Kyoung-Yun , Sohmshetty Raj
Published: January 2016

In many design and manufacturing applications, data inconsistency or noise is common. These data can be used to create opportunities and/or support critical decisions in many applications, for example, welding quality prediction for material selection and quality monitoring applications. Typical approaches to deal with these data issues are to remove or alter them before constructing any model or conducting any analysis to draw decisions. However, these approaches are limited especially when each data carries important value to extract additional information about the nature of the given problem. In the literature, with the presence of noise in data, bootstrap aggregating has shown an improvement in the prediction accuracy. In order to achieve such an improvement, a bagging model has to be carefully constructed. The base learning algorithm, number of base learning algorithms, and parameters for the base learning algorithms are crucial design parameters in that aspect. Evolutionary algorithms such as genetic algorithm and particle swarm optimization have shown promising results in determining good parameters for different learning algorithms such as multilayer perceptron neural network and support vector regression. However, the computational cost of an evolutionary computation algorithm is usually high as they require a large number of candidate solution evaluations. This requirement even more increases when bagging is involved rather than a single learning algorithm. To reduce such high computational cost, a metamodeling approach is introduced to particle swarm optimization. The meta-modeling approach reduces the number of fitness function evaluations in the particle swarm optimization process and therefore the overall computational cost can be reduced. In this paper, we propose a prediction modeling framework whose aim is to construct a bagging model to improve the prediction accuracy on noisy data. The proposed framework is tested on an artificially generated noisy dataset. The quality of final solutions obtained by the proposed framework is reasonable compared to particle swarm optimization without meta-modeling. In addition, using the proposed framework, the largest improvement in the computational time is about 42 percent.
An Automatic System for Analyzing Phantom Images to Determine the Reliability of PET/SPECT Cameras
Authors: Weiss Cohen Miri , Kennedy John A. , Pirmisashvili Archil , Orlikov Gleb
Published: January 2016

This paper describes an automatic system for analyzing phantom images from two types of PET/CT scanners. The system was developed for the purpose of obtaining tomographic image quality parameters, which determine a number of different performance parameters, primarily scanner sensitivity, tomographic uniformity, contrast and spatial resolution. The system provides a method for generating and altering image masks used for the analysis of PET images, which are then automatically aligned with the PET data. The system automatically generates Quality Control (QC) reports and is currently being used at clinical PET/CT center.
Toward a Dedicated Failure Flow Arrestor Function Methodology
Authors: Slater Michael R. S. , Van Bossuyt Douglas L.
Published: January 2016

Risk analysis in engineering design is of paramount importance when developing complex systems or upgrading existing systems. In many complex systems, new generations of systems are expected to have decreased risk and increased reliability when compared with previous designs. For instance, within the American civilian nuclear power industry, the Nuclear Regulatory Commission (NRC) has progressively increased requirements for reliability and driven down the chance of radiological release beyond the plant site boundary. However, many ongoing complex system design efforts analyze risk after early major architecture decisions have been made. One promising method of bringing risk considerations earlier into the conceptual stages of the complex system design process is functional failure modeling. Function Failure Identification and Propagation (FFIP) and related methods began the push toward assessing risk using the functional modeling taxonomy. This paper advances the Dedicated Failure Flow Arrestor Function (DFFAF) method which incorporates dedicated Arrestor Functions (AFs) whose purpose is to stop failure flows from propagating along uncoupled failure flow pathways, as defined by Uncoupled Failure Flow State Reasoner (UFFSR). By doing this, DFFAF provides a new tool to the functional failure modeling toolbox for complex system engineers. This paper introduces DFFAF and provides an illustrative simplified civilian Pressurized Water Reactor (PWR) nuclear power plant case study.
Plane Recognition on the Basis of Cloud of Points Determined by Photogrammetry
Authors: Gessner Andrzej , Sobczak Marcin , Kowal Michal
Published: January 2016

The article presents the results of research on developing a mathematical model allowing to identify the planes in a measured object, based on a cloud of points located on its walls.

A basic mathematical description of surfaces is presented. An algorithm for determining the general equation of the plane on the basis of three points described in the Cartesian coordinate system has been developed. The algorithm has then been used to determine all possible planes in a given set of measured points, which were then subjected to the process of elimination and normalization. Filtered equations of the planes were grouped in order to finally determine the set of the sought-after equations.

The designed algorithms have been implemented in a C++ computer program and their effect has been verified on a sample object with 3 methods of measurement: a contact measurement, a structured-light scanner method and with photogrammetry. The calculated equations have been compared with equations developed by a referenced commercial software. The results of the comparison have proved the correctness of the tested algorithms.

The mathematical model will be used for rapid assessment of the geometrical parameters of castings and of the size of the machining allowances, as well as in the automatic settings of the casting in the machining space.

The research was supported by the National Centre for Research and Development, Poland within the ongoing project No. LIDER / 07/76 / L-3/11 / NCBR / 2012.
A Conceptual Framework for Eco-Industrial Parks
Authors: Hein Andreas M. , Jankovic Marija , Farel Romain , Yannou Bernard
Published: January 2016

An eco-industrial park is a set of businesses that share resources in order to increase profitability and reduce environmental impact. The implementation of eco-industrial parks may significantly contribute to the creation of a sustainable economy. Despite this prospect, the actual development of eco-industrial parks is challenging, as a variety of factors must be considered. Not only technical, economic, and environmental factors are relevant but numerous stakeholder relationships as well, such as between firms, governmental bodies, and local communities. This paper presents a conceptual framework that is used to capture these diverse aspects and the relationships between them. The Unified Modeling Language (UML) is used for modeling its concepts and relationships. First, based on a literature survey, relevant concepts of eco-industrial parks are identified. One central concept is “industrial symbiosis”. A novel value-based interpretation of industrial symbiosis is presented. Second, the park’s economic, local and regional development context, as well as its internal technical components and their relationships are modeled. Finally, the framework is used for modeling a concrete eco-industrial park, in this case part of the Kalundborg eco-industrial park.
Blast Mitigation Seat Analysis: Assessment of the Effect of Personal Protective Equipment on the 5th Percentile Female Anthropomorphic Test Device Performance in Drop Tower Evaluations
Authors: Bosch Kelly , Harris Katrina , Clark David , Scherer Risa , Melotik Joseph
Published: January 2016

To address the lack of knowledge on the quantitative effects of Personal Protective Equipment (PPE) on the small occupant, 55 drop tower tests were conducted and the resulting responses were evaluated. A previous technical publication evaluated the results of drop tower testing of twelve models of blast energy-attenuating seats1. That study assessed the data recorded from three sizes of anthropomorphic test devices, or ATDs, including the Hybrid III 5th percentile female, the Hybrid III 50th percentile male, and the Hybrid III 95th percentile male. The forces, moments, and accelerations from the ATDs were compared to Injury Assessment Reference Values (IARVs) to validate the drop tower methodology and to evaluate the appropriateness of the IARVs developed for the three occupant sizes. The data review revealed that the maximum lumbar compression loads recorded by the ATDs was an effective “go/no-go” criteria for judging seat performance, and that the 5th percentile female ATD, or small occupant, was the most difficult to pass the corresponding lumbar compression IARV. Additionally, the 5th percentile female ATD exceeded its corresponding IARV for upper neck compression, leading to the motivation for this study; the data set from the previous technical publication was used in this study.

Historically, blast mitigation seats are designed to accommodate the average sized occupant, or 50th percentile male. Moving forward, there is a new emphasis on extending the protection afforded to the full military population, including the small female. The data presented in this paper seeks to determine the effect of PPE on the lumbar compression and upper neck loads for the small occupant.
Free Vibration of Micromembranes Subject to Prestress and Pressure
Authors: Arena Andrea , Lacarbonara Walter
Published: January 2016

Circular micromembranes, subject to in-plane tension and transverse pressure and actuated by a piezoelectric film, are modeled via a geometrically exact approach that accounts for finite motions. The free vibration properties (i.e., frequencies and mode shapes) about the nonlinear equilibrium due to the in-plane prestress and the pressure field are investigated in a wide range of pressures to purposefully explore the nonlinear range. Given the pronounced hardening membrane nonlinearity, there is a high sensitivity of the fundamental frequency with respect to the applied pressure. This is due to the nonlinear increase of the membrane tension caused by the pressure. Analytical laws can be obtained by curve fitting to describe the variation of the membrane lowest frequencies with the prestress tension and the applied pressure. Such laws are useful in feasibility studies on the design of micromembranes as pressure sensors.
Containerization Method for Logistic Cost Reduction Based on Closed-Loop Supply Chain Model
Authors: Ou Xinyan , Chang Qing , Xiao Guoxian , Arinez Jorge
Published: January 2016

Logistics cost is an important contributor to the overall cost in a supply chain system. By using collapsible containers, the frequency of return freight can be reduced and the return of containers can be optimized, leading to potential logistic cost savings. However, the dynamic behavior of container flows due to demand, inventory, storage, and repair requirements make it difficult to accurately analyze container system performance. An accurate estimation of this collapsible container usage impact is of great importance for decision-making.

This paper describes the development of a mathematical model of the container dynamic flow system by using the collapsible containers. A continuous time, discrete space Markov process is used for stochastic scenario. The model determines the total cost savings, based on the collapsible rate, the number of collapsible containers, the performance of the factory and the supplier and the transportation environment. The presented mathematical formulation enables the evaluation of the system performance. A case study of collapsible container supply chain system demonstrates the advantages of this methodology. In addition, a simulation model of this stochastic system is presented to verify the mathematical model. Simulation tests are conducted to demonstrate the potential logistics cost savings in the closed-loop supply chain system.
Modeling Large Spatial Deflections of Slender Bisymmetric Beams in Compliant Mechanisms Using Chained Spatial-Beam-Constraint-Model (CSBCM)
Authors: Chen Guimin , Bai Ruiyu
Published: January 2016

Modeling large spatial deflections of flexible beams has been one of the most challenging problems in the research community of compliant mechanisms. This work presents a method called chained spatial-beam-constraint-model (CSBCM) for modeling large spatial deflections of flexible bisymmetric beams in compliant mechanisms. CSBCM is based on the spatial beam constraint model (SBCM), which was developed for the purpose of accurately predicting the nonlinear constraint characteristics of bisymmetric spatial beams in their intermediate deflection range. CSBCM deals with large spatial deflections by dividing a spatial beam into several elements, modeling each element with SBCM, and then assembling the deflected elements using the transformation defined by Tait-Bryan angles to form the whole deflection. It is demonstrated that CSBCM is capable of solving various large spatial deflection problems whether the tip loads are known or the tip deflections are known. The examples show that CSBCM can accurately predict the large spatial deflections of flexible beams, as compared to the available nonlinear FEA results obtained by ANSYS. The results also demonstrated the unique capabilities of CSBCM to solve large spatial deflection problems that are outside the range of ANSYS.
Optimization of Injection Mold Design Through Application of External Selective Induction Heating
Authors: Mrozek Krzysztof
Published: January 2016

The aim of the presented research project is to optimize the injection mold for a better quality of thin-walled moldings without significant increase in cycle time, through application of external selective induction heating. The injection process of thin-walled parts is one of the most problematic procedures in plastics processing. Most commonly occurring defects of said parts are: short shots, diesel effect, welding lines, excessive internal stresses and warping. In order to reduce the number of these deficiencies, electromagnetic induction heating in concern with water cooling has been proposed to achieve rapid temperature cycling during the injection process. High-frequency induction is one of the most efficient methods of injection mold surface heating, by virtue of electromagnetic induction effect. The present study investigates selective induction heating of the cavity surface for three different thin-walled parts. Feasibility of the localized heating method was investigated through simulation of melt flow through the heated areas. The latter were selected on the basis of defects occurrence. To evaluate the applicability and efficiency of the induction heating process (within an area of 32×20 mm), a the plate with cooling channels and a movable heated insert were constructed. During the heating process, an inductor with a concentrator and a 10 kW generator. The measurement was performed by means of the Flir T620 thermographic camera and a Pt100 temperature sensor. Preliminary results allowed continuation of the experiment. For this purpose, an injection mold, consisting of three exchangeable cavity inserts on the stamp and matrix side, was assembled. In order to evaluate the applicability of induction heating, the injection process was carried out and its results were compared to those obtained through utilization of conventional means. The investigation showed that selective heating of the cavity surface to 150 °C afforded elimination of the majority of defects.
Robust Design of Sounds in Mechanical Mechanisms
Authors: Jensen Annemette Boegedal , Munch Natasja , Howard Thomas J. , Pedersen Soeren Nygaard
Published: January 2016

Current practices for creating a desired sound by a mechanical mechanism are irrelative design-build-test processes. It seems that very little guidance is available relating design to the sound output. The focus of this study was to identify, which parameters that affect the sound output of a click mechanism consisting of a toothed rack and a click arm. First several geometries of the teeth and the click arm’s head were investigated to identify the most robust and repeatable design. It was found that a flat surface in the valleys between the teeth is very beneficial in relation to repeatability. Design of Experiments was used to identify the sensitivity of all the dimensions of the parts. Here, it was found that many dimensions have an impact on the response e.g. the arm length, the tooth height and the gap between the parts. The results provide a useful basis for a sound-design guide for click mechanisms.
Contact Pressure Sensitivity Analysis in N95 Filtering Facepiece Respirator With Strap Location, Friction, and Headform Material Property
Authors: Xu Ming , Yang James
Published: January 2016

The contact pressure between an N95 filtering facepiece respirator (FFR) and the human face plays an important role in FFR performance. In this paper, the effects of several important factors (strap locations on headback, friction, and facial soft tissue material property) on contact pressures are studied using validated N95 FFR/headform finite element models. Sixteen different FFR/headform combinations including six FFRs and five digital headforms (small, medium, large, long/narrow, and short/wide) are studied. For each FFR/headform combination, the facial contact pressure distribution is recorded from the finite element results. The maximum contact pressures from six key areas are recorded for sensitivity study. The results show that the strap locations on the headback produce the largest effect on the maximum contact pressure values and the pressure distribution. The friction and the facial soft tissue material property have limited effects on the maximum contact pressure although they can affect the pressure distribution.
The Importance of Contextual Factors in Determining the Greenhouse Gas Emission Impacts of Solar Photovoltaic Systems
Authors: O’Rourke Julia M. , Seepersad Carolyn C.
Published: January 2016

Small-scale residential solar photovoltaic (PV) systems are becoming increasingly common. In some cases, governments or individual homeowners promote PV technology because of concerns about climate change and a desire to reduce global greenhouse gas emissions (GHGs). While solar PV directly emits no GHGs during use, the panels are associated with a significant amount of embedded GHG emissions, resulting from the manufacturing of the panels, for instance. A review of relevant literature reveals that the life cycle GHG emissions of solar PV panels are significantly influenced by contextual factors, such as the location of the panels during use. The purpose of this paper is to illustrate the many ways context could affect the GHG emissions associated with solar PV systems and to demonstrate — via calculations from a simple analytical model — the potential magnitude of the GHG emissions differences associated with using PV panels in different contexts.
Non Prismatic Air-Breathing Fuel Cells: Concept, Design and Manufacturing
Authors: Isanaka Sriram Praneeth , Liou Fuewen Frank , Newkirk Joseph W.
Published: January 2016

This paper details the research into Axis Symmetric Architecture (ASA) Proton Exchange Membrane (PEM) fuel cells, which are fuel cells that possess a non-prismatic cylindrical architecture as compared to the traditional flat plate designs. The paper elucidates the advantages on the ASA designs versus flat plate designs, including increased fuel flow characteristics, reduced sealing area, reduced weight characteristics and increased power densities (power/weight ratios). Finite element analysis will show improvements to flow characteristics on both the cathode and anode side along with a study of the flow channel cross-sections. The ASA design facilitates natural convective flow to promote improved reactant availability and the prototypes created show the ease of manufacture and assembly. ASA’s unlike traditional fuel cells do not require bulky clamping plates and extensive fastening mechanisms and hence lead to prototypes with reduced size, weight and cost.
Design, Kinematics and Prototype of a Flexible Robot Arm With Planar Springs
Authors: Qi Peng , Liu Hongbin , Seneviratne Lakmal , Althoefer Kaspar
Published: January 2016

Flexible robot arms have been developed for various medical and industrial applications because of their compliant structures enabling safe environmental interactions. This paper introduces a novel flexible robot arm comprising a number of elastically deformable planar spring elements arranged in series. The effects of flexure design variations on their layer compliance properties are investigated. Numerical studies of the different layer configurations are presented and finite Element Analysis (FEA) simulation is conducted. Based on the suspended platform’s motion of each planar spring, this paper then provides a new method for kinematic modeling of the proposed robot arm. The approach is based on the concept of simultaneous rotation and the use of Rodrigues’ rotation formula and is applicable to a wide class of continuum-style robot arms. At last, the flexible robot arms respectively integrated with two different types of compliance layers are prototyped. Preliminary test results are reported.
An Origami Parallel Structure Integrated Deployable Continuum Robot
Authors: Zhang Ketao , Qiu Chen , Dai Jian S.
Published: January 2016

This paper presents a novel design for continuum robots in light of origami inspired folding techniques. The work of the present paper starts from design of a crease pattern, which consists of two triangular bases and three waterbomb bases, and folding process for creating an origami parallel structure in 3D from the crease pattern in 2D. Mapping the origami parallel structure to an equivalent kinematic model, the motion characteristics of the origami structure are unraveled in terms of kinematic principles. The analysis reveals that mixed rotational and translational motion of the origami parallel structure enables both axial contraction and bending motion. A novel multi-section continuum robot with integrated origami parallel structures and bias elements is then proposed to imitate not only bending motion but also contraction of continuum apparatus in nature. According to kinematics of the proposed continuum robot and features of the embedded helical spring in each module, three actuation schemes and their enabled two typical working phases with a tendon driven system are presented. A prototype of the continuum robot with six modules connected in serial is produced and tested. The functionality of the proposed continuum robot by integrating the origami parallel structure as its skeleton and helical springs as the compliant backbone is validated by the preliminary experimental results.
Simulated and Experimental Verification of CMM Feature Fitting Algorithms
Authors: Mohan Prashant , Shah Jami , Davidson Joseph
Published: January 2016

Coordinate Measuring Machines (CMMs) collect a sampling of points on measured features for use in dimensional metrology. Conformance to specified geometric tolerances is done by analyzing the point cloud to fit the corresponding feature to the point cloud to determine if the simulated feature lies within the specified tolerance limits. Different types of feature fitting algorithms are needed: nominal, minimal/maximal, circumscribing/inscribing, and zone. Studies have shown that the same point cloud data sent to different vendors CMM software, produces different results. It is suspected that some of these algorithms may be inconsistent with the tolerance class definitions in tolerance standards and, in some cases, with shop floor conventional practices. We have previously reported on the development of normative algorithms and a feature fitting library that could be used by all CMMs. This paper gives a summary of those algorithms and then reports on methods used for verification. Three different types of verification methods were used to validate the algorithms developed. The scope of the current work is limited to linear, planar, circular, and cylindrical features. This set of algorithms described conforms to the international Standards for GD&T. In order to reduce the number of points to be analyzed, and to identify the possible candidate points for linear, circular and planar features, 2D and 3D convex hulls are used. For minimum, maximum, and Chebyshev cylinders, geometric search algorithms are used. Algorithms are divided into three major categories: least square, unconstrained, and constrained fits. Primary datums require one sided unconstrained fits for their verification. Secondary datums require one sided constrained fits for their verification. For size and other tolerance verifications, we require both unconstrained and constrained fits. Use of three different methods has validated the robustness, efficiency and accuracy of the algorithms.
Design and Qualitative Testing of a Prosthetic Foot With Rotational Ankle and Metatarsal Joints to Mimic Physiological Roll-Over Shape
Authors: Olesnavage Kathryn M. , Winter Amos G.
Published: January 2016

This paper presents the analysis, design, and preliminary testing of a prototype prosthetic foot for use in India. A concept consisting of a rigid structure with rotational joints at the ankle and metatarsal with rotational stiffnesses provided by springs is discussed. Because literature suggests that prosthetic feet that exhibit roll-over shapes similar to that of physiological feet allow more symmetric gait, the joint stiffnesses were optimized to obtain the best fit between the roll-over shape of the prototype and of a physiological foot. Using a set of published gait data for a 56.7 kg subject, the optimal stiffness values for roll-over shape that also permit the motion required for natural gait were found to be 9.3 N·m/deg at the ankle and 2.0 N·m/deg at the metatarsal. The resulting roll-over shape has an R2 value of 0.81 when compared with the physiological roll-over shape. The prototype was built and tested in Jaipur, India. Preliminary qualitative feedback from testing was positive enough to warrant further development of this design concept.
Justification, Design, and Analysis of a Village-Scale Photovoltaic-Powered Electrodialysis Reversal System for Rural India
Authors: Wright Natasha C. , Van de Zande Georgia , Winter Amos G.
Published: January 2016

This paper presents the merits of village-scale photovoltaic (PV) powered electrodialysis reversal (EDR) systems for rural India and the design and analysis of such a system built by the authors with planned testing to be completed in March 2015 in Alamogordo, New Mexico. The requirements for the system include daily water output of 6–15 m3/day (enough potable water for the average village size of 2,000–5,000 people), removal of dissolved salts in addition to biological contaminants, photovoltaic power source, recovery ratio of greater than 85% and appropriate maintenance and service scheme. At present, most village-scale desalination systems use reverse osmosis (RO), however the managing NGOs have found the systems to be cost prohibitive in off-grid locations. EDR has the potential to be more cost effective than currently installed village-scale RO systems in off-grid locations due to the lower specific energy consumption of EDR versus RO at high recovery ratios. This leads to lower power system cost and overall capital expense.

The system developed in this study is designed to validate whether the system requirements can be met in terms of recovery ratio, product water quality, specific energy consumption, and expected capital cost. The system is designed to desalinate 3600 ppm brackish groundwater to 350 ppm at a rate of 1.6 m3/hour and a recovery of 92%. This paper reviews the scope of the market for village scale desalination, existing groundwater salinity levels, and presents the design methodology and resulting system parameters for a village-scale PV-EDR field trial.
Pseudo-Rigid-Body Models for End-Loaded Heavy Cantilever Beams
Authors: Logan Philip J. , Lusk Craig P.
Published: January 2016

The large deflection of cantilever beams has been widely studied. A number of models and mathematical techniques have been utilized in predicting the path coordinates and load-deflection relationships of such beams. The Pseudo-Rigid-Body Model (PRBM) is one such method which replaces the elastic beam with rigid links of a parameterized pivot location and torsional spring stiffness. In this paper, the PRBM method is extended to include cases of a constant distributed load combined with a parallel endpoint force. The phase space of the governing differential equations is used to store information relevant to the characterization of the PRBM parameters. Correction factors are also given to decrease the error in the load-deflection relationship and extend the angular range of the model, thereby further aiding compliant mechanism design. Our calculations suggest a simple way of representing the effective torque caused by a distributed load in a PRBM as a function of easily calculated model parameters.
Towards Nonlinear Multimaterial Topology Optimization Using Unsupervised Machine Learning and Metamodel-Based Optimization
Authors: Liu Kai , Tovar Andrés , Nutwell Emily , Detwiler Duane
Published: January 2016

This work introduces a multimaterial density-based topology optimization method suitable for nonlinear structural problems. The proposed method consists of three stages: continuous density distribution, clustering, and metamodel-based optimization. The initial continuous density distribution is generated following a synthesis strategy without penalization, e.g., the hybrid cellular automaton (HCA) method. In the clustering stage, unsupervised machine learning (e.g., K-means clustering) is used to optimally classify the continuous density distribution into a finite number of clusters based on their similarity. Finally, a metamodel (e.g., Kriging interpolation) is generated and iteratively updated following a global optimization algorithm (e.g., genetic algorithms) to ultimately converge to an optimal material distribution. The proposed methodology is demonstrated with the design of multimaterial stiff (minimum compliance) structures, compliant mechanisms, and a thin-walled S-rail structure for crashworthiness.
Wave Energy Converter Array Optimization: A Review of Current Work and Preliminary Results of a Genetic Algorithm Approach Introducing Cost Factors
Authors: Sharp Chris , DuPont Bryony
Published: January 2016

Currently, ocean wave energy is a novel means of electricity generation that is projected to potentially serve as a primary energy source in coastal areas. However, for wave energy converters (WECs) to be applicable on a scale that allows for grid implementation, these devices will need to be placed in close relative proximity to each other. From what’s been learned in the wind industry of the U.S., the placement of these devices will require optimization considering both cost and power. However, current research regarding optimized WEC layouts only considers the power produced. This work explores the development of a genetic algorithm (GA) that will create optimized WEC layouts where the objective function considers both the economics involved in the array’s development as well as the power generated. The WEC optimization algorithm enables the user to either constrain the number of WECs to be included in the array, or allow the algorithm to define this number. To calculate the objective function, potential arrays are evaluated using cost information from Sandia National Labs Reference Model Project, and power development is calculated such that WEC interaction affects are considered. Results are presented for multiple test scenarios and are compared to previous literature, and the implications of a priori system optimization for offshore renewables are discussed.
Uneven Preload for Improving Motion Straightness in Closed Hydrostatic Guideways
Authors: Zha J. , Jia Q. , Cong H. D. , Chen Y. L.
Published: January 2016

Hydrostatic guideways have varied applications in precision or ultra-precision machine tools due to their high motion accuracy and low friction coefficient. Slider motion straightness is an important accuracy index for evaluating precision of hydrostatic guideways. It can be defined as the linear deviation of the slider center within the entire or any assigned stroke. This paper mainly focuses on the relationship between the keeper rail (upper guiderail) preload and slider motion straightness in the closed hydrostatic guideways, where the slider is enveloped by the guiderails. A finite element method was used to calculate keeper rail deformation under different screw preloads, slider motion straightness was measured by laser interferometer. Mapping relationship between screw preload and slider motion straightness was obtained. Experimental results shown that the end of the keeper rail had larger deformation for same preload conditions on all screws. This had an obvious effect on slider motion straightness. When oil supply pressure was 0.85 Mpa, slider motion straightness was 2.08 μm and 1.85 μm (within the entire stroke 330 mm) with torque on all screws as 15Nm and 20Nm, respectively. After uneven preload was employed, slider motion straightness was 0.87 μm and 0.84 μm for the above mentioned two cases. Accuracy increased by more than 50 percent. Screw preload approach proposed in this study can be used to guide the assembly processes of closed hydrostatic guideways with other forms for improving the motion straightness.
Automated CAD Based Trajectory for Spray Painting Robot: Variable Velocity Approach
Authors: Andulkar Mayur V. , Chiddarwar Shital S.
Published: January 2016

This paper proposes a new automated offline trajectory generation approach for free form surfaces targeted towards spray painting application. The spray gun trajectory is generated from the computer aided design (CAD) model of the surface to be painted for a structured environment. A variable velocity approach is proposed to overcome the effect of surface curvature on the desired paint thickness. The proposed approach is divided into three problems: paint pass generation, optimal gun velocity and overlap distance computation. These problems are solved independently of each other using standard optimization techniques. The paint passes consisting of points and corresponding normals are generated using a ‘section’ based approach. An optimal variable spray gun velocity depending on the surface curvature is calculated based on the paint thickness function using genetic algorithm and curve fitting technique. The overlap distance is calculated depending on paint thickness of every paint pass. The approach was implemented on test surfaces and the simulation and experimental results reveal that minimal paint thickness deviation is obtained for simple as well as highly curved surfaces.