bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards Computer Aided Design and Analysis of Spatial Flexure Mechanisms
Authors: Turkkan Omer Anil , Su Hai-Jun
Published: December 2016

Flexure mechanisms are the central part of numerous precision instruments and devices that are used in a wide range of science and engineering applications and currently, design of flexure mechanisms often heavily relies on designers’ previous hands-on experience. Therefore, a design tool that will speed up the design process is needed and this paper will introduce a systematic approach for building the necessary equations that are based on screw theory and linear elastic theory to analyze flexure mechanisms. A digital library of commonly used flexure elements must be available for a design tool and therefore, we first present the compliance matrices of commonly used flexure components. Motion twists and force wrenches of the screw theory can be related with these compliance matrices. Then, we introduce an algorithm that constructs the required linear system equations from individual compliance equations. This algorithm is applicable to flexure mechanisms with serial, parallel or hybrid chains. Finally, the algorithm is tested with a flexure mechanisms and it is shown that this approach can be the core of a future design tool.
Computational Modeling of 2D Thermal Barrier Coating Microstructures
Authors: Wimmer Stephanie A. , DeGiorgi Virginia G. , Gorzkowski Edward , Johnson Scooter
Published: December 2016

Thermal barrier coatings are used to reduce base metal temperature and can be found on many engine components such as turbine blades and exhausts. The presented work is part of a broader effort which is focused on maintaining mechanical properties while improving thermal properties of candidate thermal barrier coating materials. Specifically this effort is investigating new and novel processing techniques to improve thermal properties while maintaining sufficient mechanical properties so that coatings do not fail due to the loads inherent to normal operation of the component. Processing methods have been investigated that create new microstructures by the inclusion of spherical, micron size pores to reflect radiation (i.e. heat) at high temperatures providing additional thermal protection while maintaining strength. This paper computationally examines the size, distribution, and structure of pores that develop during bulk processing of a model material, yttria-stabilized zirconia (YSZ) to aid in the formulation of an optimized process. Heat transfer and stress-displacement analyses are performed to determine effective bulk material properties. Two-dimensional microstructures are the first step towards understanding the impact of pores, voids and microcracks on thermal and mechanical characteristics. In this work two-dimensional microstructures are computer generated to determine the influence on variations in pore number, size and relative percent of pores and cracks. Comparisons are made to experimental measurements when appropriate.
Need for Optimization Under Uncertainty: Designing Flow Exchanges in Eco-Industrial Parks
Authors: Afshari Hamid , Farel Romain , Peng Qingjin
Published: December 2016

Eco-Industrial Parks (EIPs) and Industrial Symbioses (IS) have provided several cost-effective and environmental friendly solutions for the economic growth of countries. The need for excessive materials, water and energy can be reduced by exchanging wastes, by-products and energy among different clusters of industries, which is the fundamental goal of establishing synergies among industries. Symbioses design looks for the best set of connections among industries to satisfy defined objectives. However, there are not enough data to support the design of a new EIP for some industries. The existing research contains multiple objective optimization methods, but lacks details in the real industrial world to consider comprehensive criteria in design of flow exchanges due to the large cost and long establishment time for those synergies. This paper presents a multi-objective model to decide the best network of industries for several exchanges among them. The model helps minimizing costs for multiple product exchanges while considering environmental impacts to be reduced. Moreover, this paper investigates uncertainties affecting synergies within EIPs by incorporating in a modeling process. The presented models are validated through optimizing symbioses in an EIP. The efficiency of single and multiple objective models is analyzed for effects of the selected uncertainties. Future research directions are also discussed.
A Closed-Form Model for the Support Stiffness of Spatial Flexure Strips With Limited Twist
Authors: Nijenhuis Marijn , Brouwer Dannis M.
Published: December 2016

The stiffness characteristics of flexure strips in the constrained directions are an important attribute of their behavior when serving as a constituent of flexure mechanisms. The decrease in support stiffness that accompanies movement in the intended degrees of freedom limits the performance of mechanisms comprised of such strips. This paper presents a closed-form nonlinear model that describes the support stiffness in 3-D under arbitrary end-load for the elementary flexure strip. The formulation takes into account geometrical nonlinearities by means of finite strain relations and deformed-configuration equilibrium equations. By distinguishing the low-stiffness large-deflection motion (the degrees of freedom) from the high-stiffness small-deflection motion (the constrained motion) with the appropriate simplification of limited twist, a closed-form stiffness model is obtained for dimension and load ranges of practical interest.
Reliability Estimation of Stretchable Electronics Using a Dimension Reduction Framework
Authors: Hwang Sungkun , Gorguluarslan Recep M. , Choi Seung-Kyum , Min Junki , Moon Jack
Published: December 2016

The proposed study develops a framework that accurately captures and models input and output variables for multidisciplinary systems in order to mitigate the computational cost when uncertainties are involved. Under this framework, the dimension of the random input variables is reduced depending on the degree of correlation calculated by an entropy based correlation coefficient (e). According to the obtained value of e, the dimension is truncated by two different methods. First feature extraction methods, namely Principal Component Analysis and the Auto-Encoder algorithm, are utilized when the input variables are highly correlated. In contrast, the Independent Features Test is implemented as the feature selection method if the correlation is too low to select a critical subset of model features. An Artificial Neural Network, including a Probabilistic Neural Network, is integrated into the framework to correctly capture the complex response behavior of the multidisciplinary system with low computational cost. The efficacy of the proposed method is demonstrated with electro-mechanical engineering examples, including a solder joint and a stretchable patch antenna.
A Semi-Autonomous Control Method to Improve Performance of Small Unmanned Ground Vehicles With Communication Latency
Authors: Storms Justin , Chen Kevin , Tilbury Dawn
Published: December 2016

Teleoperated unmanned ground vehicles are very useful in environments that are hazardous for humans. When controlled manually, speed of operation can be very slow due to degraded and delayed feedback of information to/from the vehicle’s environment. Adding autonomy to the vehicle can make control for the human teleoperator easier and improve performance. This paper presents a semi-autonomous control method for avoiding collisions while driving a vehicle. The method is well suited for small unmanned ground vehicles in unstructured environments (i.e. environments without predefined roads/paths to follow). The semi-autonomous control method and the effect of communication latency are evaluated with a human subject study (N = 20) involving teleoperation of a simulated robot search task. Results show that while semi-autonomy does improve performance at low communication latency, the improvement is much larger at higher latencies.
Enhanced Rotating Nonlinear Energy Sink
Authors: Al-Shudeifat Mohammad A. , Saeed Adnan S.
Published: December 2016

An enhanced rotating nonlinear energy sink (NES) is numerically investigated in this study. The rotating NES in the literature is coupled with the associated linear structure by its nonlinear inertial coupling through a rigid arm that couples the rotating NES mass with the structure. Here, the coupling arm is assumed to be elastic. Consequently, the NES mass rotates about a fixed vertical axis and allowed to oscillate along the coupling arm in a radial direction. According to this modification, the rotating NES dissipates the transferred energy from the associated structure through its angular and radial viscous damping. Therefore, the modified rotating NES by elastic arm is found to absorb and dissipate more energy than the old one for a wide range of initial input energies induced into the associated linear structure. The arm length and the angular damping coefficient of the old rotating NES are optimized first by assuming a rigid coupling arm and later the stiffness and the damping coefficients in the radial direction are optimized accordingly. The obtained numerical results have shown a significant improvement in the rotating NES performance when the NES is allowed to oscillate through the coupling arm by a linear coupling restoring spring rather than locking the NES to a rigid arm.
Forecasting Technological Impacts on Customers’ Co-Consideration Behaviors: A Data-Driven Network Analysis Approach
Authors: Wang Mingxian , Sha Zhenghui , Huang Yun , Contractor Noshir , Fu Yan , Chen Wei
Published: December 2016

Forecasting customers’ responses and market competitions is essential before launching major technological changes in product design. In this research, we present a data-driven network analysis approach to understand the interactions among technologies, products, and customers. Such an approach provides a quantitative assessment of the impact of technological changes on customers’ co-consideration behaviors. The multiple regression quadratic assignment procedure (MRQAP) is employed to quantitatively predict product co-consideration relations as a function of various effect networks created by associations of product attributes and customer demographics. The uniqueness of the proposed approach is its capability of predicting complex relationships of product co-consideration as a network. Using vehicles as a case study, we forecast the impacts of two technological changes — adopting the fuel economy-boosting technology and the turbo engine technology by individual auto companies. The case study provides vehicle designers with insights into the change of market competitions brought by new technological developments. Our proposed approach links the market complexity to technology features and subsequently product design attributes to guide engineering design decisions in the complex customer-product systems.
Estimation and Simulation of Shape Deviation for Additive Manufacturing Prototypes
Authors: Taufik Mohammad , Jain Prashant K.
Published: December 2016

Shape deviation is one of the major issues in fabricating a part using Additive Manufacturing (AM) technology. During the prototype fabrication process, slicing induced conditions play a significant role in varying shape deviations. This paper provides a novel technique for the estimation and simulation of shape deviation and provides a foundation to estimate the combined effect of oversize and undersize fabrication conditions on the same layer. The research described is the initial efforts to develop a shape deviation model regarding oversize, undersize, equal size and mixed size situations. To estimate and simulate the shape deviation, an algorithm is developed and examined with seven example tessellated prototypes. The advanced program will help the user to determine the different shape deviation information during slicing stage with different preprocessing parameters. The results show that the developed methodology is robust and work as an efficient alternative to shape deviation studies.
Direct Kinematics of the Exechon Tripod
Authors: Trinh Cuong , Zlatanov Dimiter , Zoppi Matteo
Published: December 2016

This paper presents a solution to the forward kinematics problem of the Exechon parallel mechanism, a three-legged three-degree-of-freedom spatial mechanism with a complex motion pattern of the platform. In series with a universal or a spherical wrist, it has been used in a number of PKM (parallel kinematic machine) designs, and more recently as a mobile robotic fixture. The inverse kinematics solution has been known for a number of years. However, past publications on the Exechon tripod have not presented a method successfully solving the direct kinematics problem. To achieve this here, we first reduce the forward problem to a system of four non-linear equations and then use a standard numerical solver to obtain all sets of possible real roots. This solution allows the calculation of all joint displacements and from there the transformation matrix describing the pose of the end-effector. The obtained solutions divide into two groups, each for a different assembly mode of the mechanism. The method is easy to implement and can potentially be applied to other types of parallel manipulators with revolute joints at the mobile platform.
The Design and Fabrication of a Deformable Origami Wheel
Authors: Rhoads Benjamin P. , Su Hai-Jun
Published: December 2016

This paper presents manufacturing methods for origami laminates that have better fatigue and load bearing capacity than cardstock paper and polyester, two common origami prototyping materials. Three methods were developed and tested: variations of Shape Deposition Manufacturing (SDM), “desktop” Smart Composite Microstructure Fabrication (SCM), and a novel 3D printing process. The SDM based approach produced precise patterns but was limited to a work area of 60 mm by 60 mm. The 3D printed method created laminates with approximately 6.5 times the load bearing capacity of cardstock with an estimated fatigue life of 106 cycles. The variation of the SCM process carried approximately 8 times more load than card-stock. A small prototype robot was built to demonstrate the robustness of the manufacturing methods using a novel deformable origami wheel inspired by the para-cylinder fold pattern. Four deformable wheels on the chassis were able to function as the transmission, steering mechanism, and suspension of the robot.
Adaptability Tradeoffs in the Design of Self-Organizing Systems
Authors: Humann James , Khani Newsha , Jin Yan
Published: December 2016

Self-organizing systems have great potential for adaptability, but as complex systems, they can also be prone to unpredictable behavior, cascading failures, and sensitivity to perturbations. Also, designing systems for adaptability may introduce overhead that reduces their performance. This paper investigates the design tradeoffs between adaptability and performance in the context of a box-pushing task. Using a genetic algorithm to optimize a parametric behavioral model, we are able to test systems optimized under different conditions for performance and reliability. It was found that a system optimized in the face of random initial conditions and internal perturbations was more robust than a system optimized without these perturbations, showing a higher overall fitness over diverse trials, but it could not take advantage of particular initial conditions that would have allowed it to achieve a one-off high fitness in a repeatable environment. A system optimized with predesigned initial conditions was found to achieve a very high fitness, but when it was retested with random initial conditions, its performance plummeted, indicating that it was fit to the ideal initial conditions but not robust.
Makerspaces in Engineering Education: A Case Study
Authors: Skovgaard Jensen Lasse , Özkil Ali Gürcan , Mougaard Krestine
Published: December 2016

The recent years have witnessed a new generation of Makers working with new ways of knowledge generation for creation and sharing of digital and physical products. While this development has started within collaborative and grass roots organised networks; educational institutions have also embraced it by opening makerspaces and adopting elements of the Maker Movement in their offerings. This paper investigates how university driven makerspaces can affect engineering design and product development education trough a case study. We provide our findings based on interviews and data collected from educators, students the administrative and workshop staff of the makerspace. The findings are used to outline the challenges in incorporating the offerings of makerspaces. By discussing these challenges we identify opportunities for turning university makerspaces into innovation hubs and platforms that can support engineering design education.
Model Uncertainty Approximation Using a Copula-Based Approach for Reliability Based Design Optimization
Authors: Pan Hao , Xi Zhimin , Yang Ren-Jye
Published: December 2016

Reliability-based design optimization (RBDO) has been widely used to design engineering products with minimum cost function while meeting defined reliability constraints. Although uncertainties, such as aleatory uncertainty and epistemic uncertainty, have been well considered in RBDO, they are mainly considered for model input parameters. Model uncertainty, i.e., the uncertainty of model bias which indicates the inherent model inadequacy for representing the real physical system, is typically overlooked in RBDO. This paper addresses model uncertainty characterization in a defined product design space and further integrates the model uncertainty into RBDO. In particular, a copula-based bias correction approach is proposed and results are demonstrated by two vehicle design case studies.
Identifying Freehand Sectional View Technical Drawing Activities in Engineering Design Graphics Course to Enhance Spatial Skills of Engineering Students
Authors: Srinivasan Anirudh , Smith Jeremy D. , Bairaktarova Diana
Published: December 2016

Spatial thinking is paramount in engineering education, however there is a lack of reliable data on instructional strategies for developing and improving these skills. In this pilot study, we investigate the feasibility of using students’ freehand sectional view drawings to measure their initial and developing spatial skills in a semester-long engineering design graphics course. Participants included 121 junior-level students (M = 98, F = 23). Preliminary results show moderate-to-strong positive correlations between drawing accuracy and performance on two spatial thinking tests: the Purdue Spatial Visualization Test (PSVT:R), and Santa Barbara Solids Test (SBST).
Tensegrity Heat Shield for Atmospheric Entry Through Celestial Bodies
Authors: Chopra Shaurya Deep , Teodorescu Mircea , Lessard Steven , Agogino Adrian , SunSpiral Vytas
Published: December 2016

Heat shields play a vital role in protecting space vehicles during the atmosphere reentry. Therefore, they are essential for space vehicles, and better designed heat shields will vastly improve the ability both of robots and humans to explore extraterrestrial destinations. The main goal of the current paper is to investigate the feasibility of designing, building and deploying a tensegrity-based heat shield, which would withstand the atmospheric reentry of a low gravity and dense atmosphere celestial body (such as Titan), where the reentry accelerations and therefore, drag forces, will be lower than in the case of a high gravity planet (e.g., Earth or Mars). The paper is a preliminary study, which investigates the parameters that would be helpful in designing tensegrity-based heat shields. We explore the dynamics of entry and how the atmospheric forces interact with the heat shield. Tensegrity structures consist of tension elements used in conjunction with rigid rods which are actuated by changing the lengths of the tension elements. The advantage of the proposed approach versus the traditional one (rigid heat shields) is that tensegrity structures are flexible structures able to adapt the shape to obtain an optimal reentry configuration. The proposed heat shield will be able to fold in a small space during transport (e.g., to the target celestial body), unfold when the target is reached and provide additional mobility for an optimal reentry pattern. However, to achieve a deployable configuration, the tensegrity structure must withstand significant dynamics and thermal loads. We will use NASA Tensegrity Robotics Toolkit (NTRT) to simulate the structural designs of the heat shield as well as for designing the controllers.
Value Proposition Design for Systems and Services by Adapting Affordance-Based Design
Authors: Ben Hamida Sonia , Jankovic Marija , Curatella Franco , Sasse Simone , Baltay Suzanne , Callot Martine , Huet Alain , Bocquet Jean-Claude
Published: December 2016

In early design stages, firms need to generate and assess their value propositions. Although both business developers and systems engineers capture customers’ needs to design the value proposition, they suffer from inefficient business and engineering processes interactions. Moreover, they lack methods to elicit the needs in a structured way and to explore the best value propositions.

We propose to extend the affordance-based design for systems and services in order support the elicitation and capture of stakeholders’values; and to identify boundaries of the system design problem to explore the best value propositions. Hence, affordances — which describe what system provides to other systems and stakeholders — help to frame the context. Today, affordance-based design is mainly used for artifact design. We propose to extend this approach to systems and services and complement it with a focus on stakeholders’ activities and external systems’ stages. With regard to the different system design perimeters defined by affordances, value propositions are designed. The proposed method is illustrated on an AIRBUS Defence & Space innovative project.
Estimating and Exploring the Product Form Design Space Using Deep Generative Models
Authors: Burnap Alexander , Liu Ye , Pan Yanxin , Lee Honglak , Gonzalez Richard , Papalambros Panos Y.
Published: December 2016

Product forms in quantitative design methods are typically expressed with a mathematical representation such as vectors, trees, graphs, and grammars. Such formal representations are restrictive in terms of realism or flexibility, and this limits their utility for human designers who typically create product forms in a design space that is restricted by the medium (e.g., free-hand sketching) and by their cognitive skills (e.g., creativity and experience). To increase the value of formal representations to human designers, this paper proposes to represent the design space as designs sampled from a statistical distribution of form and estimate a generative model of this distribution using a large set of images and design attributes of previous designs. This statistical representation approach is both flexible and realistic, and is estimated using a deep (multi-layer) generative model. The value of the representation is demonstrated in a study of two-dimensional automobile body forms. Using 180,000 form data of automobile designs over the past decade, we can morph a vehicle form into different body types and brands, thus offering human designers potential insights on realistic new design possibilities.
Modeling and Simulation of Vehicle Behavior for Design and Tuning of Electronic Differential for Formula Student Vehicle
Authors: Patel Maithili , Mahajan Manthan
Published: December 2016

A racing vehicle requires to be designed for optimum performance, stability and maneuverability considering all situations like straight line acceleration and high speed cornering. The car is driven close to its tractive limits and a control system becomes inevitable to manifest utmost performance of the car.

In this paper, the focus is on design of an electronic differential for a rear wheel driven Formula Student Electric vehicle, with each rear wheel driven by separate motors. The electronic differential (e-diff) is aimed at both straights and corners, which is fulfilled by considering objective parameters, which assist in cornering by improving yaw rate and straights by improving traction. However, in this paper we shall focus on cornering only. The paper looks at various possible control strategies for obtaining desired values of certain parameters and describes in detail implementation of a yaw rate controlled system.

A vehicle model is created on MATLAB/Simulink platform to look at changes in vehicle behavior in response to various control strategies. The model consists of vehicle dynamics and driver models developed by the authors. The coupled model simulates the vehicle performance on any given track and provides the variation of required parameters. Iterations are done and the results are used to tune the controller parameters to optimize performance on tight turns and overall lap times at the endurance event at the Formula Student competition.
Model Bias Characterization Considering Discrete and Continuous Design Variables
Authors: Zhao Xiangxue , Xi Zhimin , Xu Hongyi , Yang Ren-Jye
Published: December 2016

Model bias can be normally modeled as a regression model to predict potential model errors in the design space with sufficient training data sets. Typically, only continuous design variables are considered since the regression model is mainly designed for response approximation in a continuous space. In reality, many engineering problems have discrete design variables mixed with continuous design variables. Although the regression model of the model bias can still approximate the model errors in various design/operation conditions, accuracy of the bias model degrades quickly with the increase of the discrete design variables. This paper proposes an effective model bias modeling strategy to better approximate the potential model errors in the design/operation space. The essential idea is to firstly determine an optimal base model from all combination models derived from discrete design variables, then allocate majority of the bias training samples to this base model, and build relationships between the base model and other combination models. Two engineering examples are used to demonstrate that the proposed approach possesses better bias modeling accuracy compared to the traditional regression modeling approach. Furthermore, it is shown that bias modeling combined with the baseline simulation model can possess higher model accuracy compared to the direct meta-modeling approach using the same amount of training data sets.
How Designs Differ: Non-Linear Embeddings Illuminate Intrinsic Design Complexity
Authors: Chen Wei , Chazan Jonah , Fuge Mark
Published: December 2016

This paper shows how to measure the complexity and reduce the dimensionality of a geometric design space. It assumes that high-dimensional design parameters actually lie in a much lower-dimensional space that represents semantic attributes. Past work has shown how to embed designs using techniques like autoencoders; in contrast, this paper quantifies when and how various embeddings are better than others. It captures the intrinsic dimensionality of a design space, the performance of recreating new designs for an embedding, and the preservation of topology of the original design space. We demonstrate this with both synthetic superformula shapes of varying non-linearity and real glassware designs. We evaluate multiple embeddings by measuring shape reconstruction error, topology preservation, and required semantic space dimensionality. Our work generates fundamental knowledge about the inherent complexity of a design space and how designs differ from one another. This deepens our understanding of design complexity in general.
Experimental and Theoretical Studies of Nonlinear Resonances in a Si Microcantilever Constrained by a Polymer Attachment
Authors: Asadi Keivan , Peshin Snehan , Yeom Junghoon , Cho Hanna
Published: December 2016

In micro/nanometer scale mechanical resonators, constructive utilization of intentional nonlinearity has suggested ways to leverage beneficial nonlinear characteristics in their design for various applications. Previous studies have also shown that the geometric nonlinearity is effectively implemented and tailored through integration of nonlinear couplings to an otherwise linear microcantilever. Here, we demonstrate experimentally a nonlinear micromechanical resonator consisting of a silicon microcantilever axially constrained by a polymer attachment exhibiting a strong nonlinear hardening behavior not only in its first flexural mode but also in higher modes. A theoretical model representing the system with geometrically nonlinear stiffness and damping is analyzed by the method of multiple scales, which is favorably validated by good agreement with experimentally obtained nonlinear responses.
Behavior of Congruent Tessellation Stacks Under Torsional Loading
Authors: Klett Yves , Muhs Fabian , Middendorf Peter
Published: December 2016

The combination of several layers of rigidly foldable tessellations into can produce cellular material stacks with interesting properties, especially if the resulting stack preserves the mobility of its constituting layers. To achieve this, the construction of functional joining and hinging concepts need to be developed. This paper presents a simple solution to effectively joining different 1-DOF (degree of freedom) tessellation layers. The mechanical properties of the resulting structures under torsional loads are evaluated using finite element analysis, and their potential use as structural mechanisms is discussed.
An Observational Study on Functional Behavior in Team Design
Authors: Born Werner , Schmidt Linda
Published: December 2016

Successful group work is a critical facet of engineering design. In addition to simply increasing the manpower available to solve a particular problem, team settings also leverage the variety of thinking offered by each individual. There are any number of functional behaviors that one might offer a team. This paper explores the idea that design journal records can provide key insight into the functional activities taken on by team members. The main questions asked by this study include (1) Can design journals provide consistent information about an individual’s functional behavior? (2) Are individuals likely to shift behaviors over the course of the project’s timeline? (3) Do individuals adapt to compensate for design behavior changes in other team members?

The data in this study was collected from five volunteer teams of five to six undergraduate students each (total N = 29). At the time of their participation in the study, the volunteers were enrolled in the University of Maryland’s mechanical engineering capstone design course, Integrated Product and Process Development. Four of the teams participated in fall 2015 and one team participated in spring 2014. Participants maintained individual journals throughout their semester-long design projects, after receiving a set of guidelines to steer but not restrict journal usage. After the projects were completed, journals were coded using a previously validated coding scheme which associates each journal entry with a design behavior class and activity.

Findings for this pilot study were very encouraging. Design journals proved to be a viable source of information about the functional behaviors of individuals. The majority of the undergraduate participants in this study were found to regularly shift their focuses to different behaviors as their projects progressed. When these shifts occurred, other team members regularly shifted to accommodate the change and maintain overall similar levels of activity in each area of functional behavior for the team as a whole throughout the project’s timeline.
Towards Adjoint-Based Inversion of the Lamé Parameter Field for Slender Structures With Cantilever Loading
Authors: Fatehiboroujeni Soheil , Petra Noemi , Goyal Sachin
Published: December 2016

Continuum models of slender structures are effective in simulating the mechanics of nano-scale filaments. However, the accuracy of these simulations strictly depends on the knowledge of the constitutive laws that may in general be non-homogeneous. It necessitates an inverse problem framework that can leverage the data provided by physical experiments and molecular dynamics simulations to estimate the unknown parameters in the constitutive law. In this paper, we formulate a simple but representative inverse problem as a nonlinear least-squares optimization problem whose cost functional is the misfit between synthetic observations of a cantilever displacement field and model predictions. A Tikhonov regularization term is added to the cost functional to render the problem well-posed and account for observational error. We solve this optimization problem with an adjoint-based inexact Newton-conjugate gradient method. We show that the reconstruction of the Lamé parameter field converges to the exact coefficient as the observation error decreases.
Dynamics of Axial Rods With Frictional Joints
Authors: Mathis Allen , Quinn D. Dane
Published: December 2016

Almost every modern engineering structure incorporates some form of mechanical interface, a connection between two otherwise separate mechanical structures. Complex machines and structures such as automobiles, bridges, aircraft, rockets, etc. rely heavily on these interfaces; however, high-fidelity numerical analysis of such connected structures is currently extremely difficult and computationally expensive due to the disparate length and time scales of the interface as compared to those characterizing the overall structure. This paper utilizes recent work in modal analysis of joints using reduced-order models to study the nonlinear effects of these systems while remaining computationally tractable.
An Extended Pattern Search Method for Offshore Floating Wind Layout and Turbine Geometry Optimization
Authors: Forinash Caitlin , DuPont Bryony
Published: December 2016

An Extended Pattern Search (EPS) method is developed to optimize the layout and turbine geometry for offshore floating wind power systems. The EPS combines a deterministic pattern search with stochastic extensions. Three advanced models are incorporated: (1) a cost model considering investment and lifetime costs of a floating offshore wind farm comprised of WindFloat platforms; (2) a wake propagation and interaction model able to determine the reduced wind speeds downstream of rotating blades; and (3) a power model to determine power produced at each rotor, and includes a semi-continuous, discrete turbine geometry selection to optimize the rotor radius and hub height of individual turbines. The objective function maximizes profit by minimizing cost, minimizing wake interactions, and maximizing power production. A multidirectional, multiple wind speed case is modeled which is representative of real wind site conditions. Layouts are optimized within a square solution space for optimal positioning and turbine geometry for farms containing a varying number of turbines. Resulting layouts are presented; optimized layouts are biased towards dominant wind directions. Preliminary results will inform developers of best practices to include in the design and installation of offshore floating wind farms, and of the resulting cost and power production of wind farms that are computationally optimized for realistic wind conditions.
Modeling Power Requirements for Skid-Steer Mobile Robots in Manufacturing Environments
Authors: Canfield Stephen L. , Hill Tristan W. , Zuccaro Stephen G.
Published: December 2016

This paper demonstrates an approach for predicting and optimizing energy consumption in skid-steer mobile robots (SSMRs) conducting manufacturing tasks. This work is unique in that it considers the energy associated with real-time predictions of slipping in the SSMR and further considers a specific application in which the SSMR is operating in an inverted (climbing) configuration on metal surfaces with homogeneous properties. The approach is based on a dynamic model that provides estimates of SSMR slipping motion during simulation. The model is used to estimate the underlying components of energy and will serve as the tool for objective function evaluation. The approach will follow previous path optimization strategies, parameterizing the path to provide design parameters and using appropriate optimization tools. A method to select the desired trajectory prior to conducting a manufacturing task is demonstrated. This paper primarily focuses on a scenario in which a climbing SSMR maneuvers on a steel surface by means of magnetic-based tracks with strong adhering forces. For this case, the friction due to slipping represents the primary source of energy consumption. This implies that the path selection is the most important parameter for the optimization.
A Validation Approach for the Multiscale Modeling of Additively Manufactured Lattice Structures
Authors: Gorguluarslan Recep M. , Choi Seung-Kyum
Published: December 2016

A validation approach is proposed to ensure that the computational models corresponding to each scale level in a hierarchical multiscale modeling process can produce accurate simulations in the material characterizations at multiple levels. In the validation approach, the stochastic upscaling method is utilized for the homogenization of the geometry and material properties of material structure at each scale level of interest. The experimental data is utilized for the validation of the predictions made by the multiscale models with homogenized properties at each scale level. For the quantitative assessment of the model’s prediction accuracy, a validation metric that integrates the u-pooling method with the Kolmogorov-Smirnov test will be presented. Additively manufactured cellular structures are used as application examples to demonstrate the efficacy of the proposed multiscale validation approach. The results from the examples show that the proposed method effectively captures the predictive capability of the models with an unbiased decision criterion based on the test statistic at multiple scales.
Control Optimization and Dynamic Programming-Informed Sizing for Novel Energy-Recovering Hydraulic Actuation
Authors: Pena Oscar , Leamy Michael
Published: December 2016

This study explores optimal control and sizing of a recently introduced efficient architecture for hydraulic actuation. Previous work established a physical model of the architecture posed as a single-input single-output (SISO) system in which the ratio of two hydraulic pump/motor swash plate angles served as the control input for regulating actuation speed. The architecture was heuristically sized and controlled within the context of a hydraulic elevator. High-fidelity simulations of the system demonstrated an upwards of 75% decrease in energy consumption compared to a throttling architecture. Monte Carlo simulations are now used to achieve optimal sizing of the system. Several uniformly random points in the design space are chosen and evaluated using Dynamic Programming, which provides both a deterministic and optimal value for energy efficiency of the system. Aggregation of evaluated points reveals a region within the three-dimensional space wherein the architecture is optimally sized for efficiency. Dynamic Programming is then used to inform efficient rule-based control strategies. Control techniques learned from Dynamic Programming suggest efficient operation of the system results through the maximization of pump/motor 1 displacement and the use of the auxiliary electric motor during retraction of the hydraulic cylinder. Dynamic Programming informed system achieved a 61% level of optimality. Additionaly, it exhibited a 21% improvement over a heuristically sized and controlled version. It is anticipated that optimal control and sizing guidelines presented are applicable within the context of other hydraulic actuation technologies for which the studied architecture may be used.
A Non-Redundant Formulation for the Dynamics Simulation of Multibody Systems in Terms of Unit Dual Quaternions
Authors: Müller Andreas , Terze Zdravko , Pandza Viktor
Published: December 2016

Quaternions are favorable parameters to describe spatial rotations of rigid bodies since they give rise to simple equations governing the kinematics and attitude dynamics in terms of simple algebraic equations. Dual quaternions are the natural extension to rigid body motions. They provide a singularity-free purely algebraic parameterization of rigid body motions, and thus serve as global parameters within the so-called absolute coordinate formulation of MBS. This attractive feature is owed to the inherent redundancy of these parameters since they must satisfy two quadratic conditions (unit condition and Plcker condition). Formulating the MBS kinematics in terms of dual quaternions leads to a system of differential-algebraic equations (DAE) with index 3. This is commonly transformed to an index 1 DAE system by replacing the algebraic constraints with their time derivative. This leads to the well-known problem of constraint violation. A brute force method, enforcing the unit constraint of quaternions, is to normalize them after each integration step. Clearly this correction affects the overall solution and the dynamic consistency. Moreover, for unit dual quaternions the two conditions cannot simply be enforced in such a way. In this paper a non-redundant formulation of the motion equations in terms of dual quaternions is presented. The dual quaternion constraints are avoided by introducing a local canonical parameterization. The key to this formulation is to treat dual unit quaternions as Lie group. The formulation can be solved with any standard integration scheme. Examples are reported displaying the excellent performance of this formulation regarding the constraint satisfaction as well as the solution accuracy.
A New Spatial and Temporal Incremental Harmonic Balance Method for Obtaining Steady-State Responses of a One-Dimensional Continuous System
Authors: Wang X. F. , Zhu W. D.
Published: December 2016

A new spatial and temporal incremental harmonic balanced (STIHB) method is developed for obtaining steady-state responses of a one-dimensional continuous system. In the STIHB method, Galerkin procedure for a governing partial differential equation (PDE) in the spatial coordinate to obtain a set of ordinary differential equations (ODEs) and the harmonic balance procedure for the set of ODEs in the temporal coordinate to obtain the harmonic balanced residual are combined to be Galerkin procedures for the PDE in the spatial and temporal coordinates to simultaneously obtain the spatial and temporal harmonic balanced residual, and integrations in Galerkin procedures are replaced by the fast discrete sine transform (DST) or fast discrete cosine transform (DCT) in the spatial coordinate and the fast Fouriour transform (FFT) in the temporal coordinate, which is referred to as a DST-FFT or DCT-FFT procedure. The harmonic balanced residual for an arbitrary second-order PDE can be automatically and efficiently obtained by a computer program when the expression of the PDE is given, where numbers of basis functions in the spatial and temporal coordinates can be arbitrarily selected and no more extra derivations are needed. There are two versions of the STIHB method. In the simple version, the DST-FFT or DCT-FFT procedure to calculate the harmonic balanced residual and Broyden’s method that is a quasi-Newton method are combined to find solutions that make the residual vanish, which can be used to construct steady-state solutions of the PDE. In the complex version, the exact Jacobian matrix is derived and used in Newton-Raphson method to achieve faster convergence. While its derivation is complex, the exact Jacobian matrix for the arbitrary PDE can be automatically and efficiently obtained by following a calculation routine when the linearized expression of the PDE is given, and it can be easily implemented by a computer program. The exact Jacobian matrix can also be used to study stability of steady-state responses, where no more extra derivations are needed. The STIHB method is demonstrated by studying the transverse vibration of a string with geometric nonlinearity; its frequency-response curves with weak and strong nonlinearities and different numbers of trial functions are calculated, and stability of solutions on the curves is studied.
A Compressed Sensing Approach to Uncertainty Propagation for Approximately Additive Functions
Authors: Li Kaiyu , Allaire Douglas
Published: December 2016

Computational models for numerically simulating physical systems are increasingly being used to support decision-making processes in engineering. Processes such as design decisions, policy level analyses, and experimental design settings are often guided by information gained from computational modeling capabilities. To ensure effective application of results obtained through numerical simulation of computational models, uncertainty in model inputs must be propagated to uncertainty in model outputs. For expensive computational models, the many thousands of model evaluations required for traditional Monte Carlo based techniques for uncertainty propagation can be prohibitive. This paper presents a novel methodology for constructing surrogate representations of computational models via compressed sensing. Our approach exploits the approximate additivity inherent in many engineering computational modeling capabilities. We demonstrate our methodology on an analytical function and a cooled gas turbine blade application. The results of these applications reveal substantial computational savings over traditional Monte Carlo simulation with negligible loss of accuracy.
Multi-Objective Optimization of Complex Multibody Systems by Coupling HOTINT With MagOpt
Authors: Humer Alexander , Jungmayr Gerald , Koppelstätter Werner , Schörgenhumer Markus , Silber Siegfried , Weidenholzer Günther , Weitzhofer Simon
Published: December 2016

Multi-objective optimization of complex mechatronic systems does not only require detailed simulation models for the individual components, but often demands a multi-physics model that adequately describes their fully coupled behavior. Typically, such a multi-physics model cannot be realized within a single simulation software but rather necessitates the combination of diverse tools. The efficient handling of dependencies among several components in various physical domains within a heterogeneous simulation environment is a key challenge in the context of optimization. The present paper illustrates the multi-objective optimization of a magnetically levitated rotor combining the open-source multibody simulation software HOTINT and the optimization tool MagOpt. MagOpt uses evolutionary algorithms to determine the Pareto-optimum of the multi-physics model, which comprises the flexible multibody system, electromagnetic components and the control system.