bluuebunny/crossref_metadata_2025 huggingface dataset:
A Mean Value Reliability Method for Bimodal Distributions
Authors: Hu Zhangli , Du Xiaoping
Published: November 2017

In traditional reliability problems, the distribution of a basic random variable is usually unimodal; in other words, the probability density of the basic random variable has only one peak. In real applications, some basic random variables may follow bimodal distributions with two peaks in their probability density. For example, the random load of a bridge may have two peaks, with a distribution consisting of a weighted sum of two normal distributions, suggested by traffic load data. When binomial variables are involved, traditional reliability methods, such as the First Order Second Moment (FOSM) method and the First Order Reliability Method (FORM), will not be accurate. This study investigates the accuracy of using the saddlepoint approximation for bimodal variables and then employs a mean value reliability method to accurately predict the reliability. A limit-state function is at first approximated with the first order Taylor expansion so that it becomes a linear combination of the basic random variables, some of which are bimodally distributed. The saddlepoint approximation is then applied to estimate the reliability. Examples show that the new method is more accurate than FOSM and FORM.
Lattice Structure Design Advisor for Additive Manufacturing Using Gaussian Process
Authors: Tang Tsz Ling Elaine , Liu Yan , Lu Da , Arisoy Erhan Batuhan , Musuvathy Suraj
Published: November 2017

Additive manufacturing (AM) exemplifies the potential of lattice structures to revolutionize structural design. It enables light weight lattice structures to be produced while maintaining the desirable structural performance. Lattice design can vary in different shapes and dimensions. Obtaining the structural performance of a particular lattice structure design is not a straight-forward process. Significant effort is required to perform mechanical testing experiments or to perform finite element analysis (FEA) to characterize the lattice design. In view of that, a guidance system to determine lattice design parameters based on desired functional performance for a specific lattice type is developed, which can be used in interactive design processes and workflows. Homogenization using FEA experiments is applied to characterize the macroscopic lattice structural properties. Mechanical properties of orthotropic cubic lattice f2ccz are estimated. It follows with a design of experiment study to characterize the effective structural properties of 39 lattices with respect to lattice design parameters (unit cell length and strut diameter). A Gaussian process is applied to develop models relating the lattice design parameter to macroscopic structural properties (forward model), and vice versa (inverse model). Both the forward and inverse models are examined and shown to be capable of modeling the FEA experimental dataset of 39 lattices. To illustrate the potential application of the lattice design advisor framework, a structural design use case including lattice part is presented. In the use case, the lattice structure design advisor is proven to be able to estimate an accurate homogenized material property of arbitrary lattice design parameter. This lattice structure design advisor can simplify and streamline the design, modeling and simulation process of lattice-filled structural designs.
Disturbance Rejection FOPID Control of Rotor by Multi-Objective BB-BC Optimization Algorithm
Authors: Ates Abdullah , Alagoz Baris Baykant , Yeroglu Celaleddin , Yuan Jie , Chen YangQuan
Published: November 2017

This paper presents a FOPID tuning method for disturbance reject control by using multi-objective BB-BC optimization algorithm. Proposed method allows multi-objective optimization of set-point performance and disturbance rejection performances of FOPID control system. The objective function to be minimized is composed of the weighted sum of MSE for set-point performance and RDR for disturbance rejection improvement. The proposed optimization performs maximization of RDR and minimization of MSE and it can deal with the tradeoff between RDR performance and step-point performance. Application of the method is shown for auto-tuning of FOPID controller that is employed for control of TRMS model. We observed that low-frequency RDR indices can be used to improve disturbance rejection performance in multi-objective controller tuning problems. Particularly, for flight control application, disturbance reject control is very substantial to robust performance of propulsion systems.
Folding Star-Shaped Acoustic Transducers for Real-Time Guidance of Radiated Acoustic Waves
Authors: Zou Chengzhe , Harne Ryan L.
Published: November 2017

Directed acoustic energy is used throughout medical practices, scientific research, and engineering applications. Conventionally, arrays of transducer constituents are assembled and driven with inputs that are determined by digital signal processing methods, which guides the acoustic waves for signal transmission and reception purposes. Beamforming is the term for this approach, although inherent limitations of stability and computational efficiency hinder the outcomes. Recent efforts have revealed the broad merits of folding origami-inspired acoustic array architectures so that the transducer constituent and array shapes change, giving rise to direct control of acoustic energy radiation characteristics. Because the design of the origami tessellation used to create the array is pivotal to the adaptive acoustic energy steering, a new star-shaped foldable transducer is studied in this work for its unique inward and outward shape change characteristics. In order to facilitate this investigation, an analytical framework is developed to identify the connections between the folding-induced topology and radiated sound field. The high-fidelity boundary element method verifies the analytical model while experimental efforts validate the theoretical predictions. The adaptation of radiated sound pressure from the star-shaped transducer is shown to be several orders of magnitude, which illustrates its great potential in acoustic energy guidance and prospective applications.
Innovation of Matching Structures Through Clustering and Reconstructing Basic Operation Actions in the Form Layer
Authors: Yu-Tong Li , Yuxin Wang
Published: November 2017

Due to a lack of essential knowledge to support functional reasoning from the design requirements of the kinematic compound mechanisms to their constituent mechanisms, the creative conceptual design of kinematic compound mechanisms based on functional synthesis approach is still a challenging task. Through introducing the dynamic partition-matching process between the function layer and the form layer to substitute for the direct function-structure matching in the FBS model, the function-structure matching problem corresponding to deficient functional reasoning knowledge for kinematic compound mechanisms is solved by the authors. The following challenge is how to cluster the divided subset of basic operation actions generated in the form layer during the partition-matching process into a well-organized and complete kinematic behavior that can be matched by the sub-function in the function layer and implemented by a structure in the database. The adopted strategies in this paper are: through defining the correlation indexes between basic operation actions, the basic operation action and its realized function behavior, and its embodied structure, as well as its dynamic behavior characteristics, the clustering possibility for a group of basic operation actions is determined. With the aid of the compatibility conditions between basic operation actions in the form layer and the consistency of the order relations between basic operation actions in the function layer and the form layer respectively, the consistency of the order relations among basic operation actions between the sub-functions in the function layer and the sub-behaviors in the form layer are guaranteed. Then, the optimal matching structures corresponding to the sub-functions in the function layer are determined based on the maximum matching coefficients of basic operation actions. In this way, the subsets of basic operation actions in the form layer are clustered into a number of complete behaviors that can be realized by mechanisms in the structure database and matched by the sub-functions in the function layer. Since multiple functional behaviors of each constituent basic mechanism take part in matching, some novel schemes of compound mechanisms with fewer and simpler constituent mechanisms to implement the overall function may be dug out.
Probabilistic Analysis of a Metamorphic Mechanism Based on a Global Sensitivity Analysis: A Preliminary Study
Authors: Baxter Sarah C. , Voglewede Philip A.
Published: November 2017

Mathematical modeling is an important part of the engineering design cycle. Most models require application specific input parameters that are established by calculation or experiment. The accuracy of model predictions depends on underlying model assumptions as well as how uncertainty in knowledge of the parameters is transmitted through the mathematical structure of the model. Knowledge about the relative impact of individual parameters can help establish priorities in developing/choosing specific parameters and provide insight into a range of parameters that produce ‘equally good’ designs. In this work Global Sensitivity Analysis (GSA) is examined as a technique that can contribute to this insight by developing Sensitivity Indices, a measure of the relative importance, for each parameter. The approach is illustrated on a kinematic model of a metamorphic 4-bar mechanism. The model parameters are the lengths of the four links. The results of this probabilistic analysis highlight the synergy that must exist between all four link lengths to create a design that can follow the desired motion path. The impact of individual link lengths, however, rises and falls depending on where the mechanism is along its motion path.
From Mining Affective States to Mining Facial Keypoint Data: The Quest Towards Personalized Feedback
Authors: Lopez Christian E. , Tucker Conrad S.
Published: November 2017

Personalized and timely feedback has the potential to improve an individual’s performance on a wide variety of engineering tasks. The ability to capture an individual’s affective state(s) and performance on a task is a key component needed to advance personalization of feedback. While automated methods exist for quantifying task performance, the ability to quantify an individual’s affective state(s) remains an open research area. Existing methods for quantifying an individual’s affective state(s) are challenging to implement where real-time assessment is needed (e.g., engineering workshop environments). This has sparked a growing interest for automated systems capable of inferring individuals’ affective state(s), based on their projected facial or body cues. However, existing methods attempt to employ a general model to label an individual’s affective state(s) into discrete categories, such as fear, joy, surprise, etc. Nonetheless, emotional expressions are far more complex, as individual differences in facial expressions, may deteriorate the performance of these systems in providing personalized feedback. To overcome these limitations, this work proposes a machine learning method for predicting an individual’s performance on a task by utilizing his/her unique facial keypoint data, hereby bypassing the need to infer his/her discrete affective states. A case study involving 31 participants is presented. The support vector machine model employed to predict an individual’s performance yielded an accuracy of 77.15% for an individual-task specific model. In contrast, a general model yielded an accuracy of only 52.69%, hereby supporting the authors’ argument that individual-task specific models are more suitable for advancing personalized feedback.
A Novel Performance Analysis Method for a Full Vehicle Suspension Based on Quarter Car Model
Authors: Wu Long , Zuo Lei
Published: November 2017

In vehicle dynamics researchers traditionally investigate the suspension performance based on a quarter car model and then reestablish a comprehensive model for the full car by considering additional degrees of freedom (DOF). Based on the derivation of the coupling ratios between the sprung mass of a full car and four sprung masses of quarter cars, the analysis of a full vehicle dynamics with fourteen DOFs in vertical and lateral directions is possible. The full car model can be expressed by four independent quarter car models. An analysis method will be investigated in order to provide a novel performance estimation for a full vehicle suspension. The case study shows that the vibrations of a full vehicle can be quantitatively obtained based on the test results of quarter suspensions.
Biped 4-UPU Parallel Mechanism
Authors: Miao Zhihuai , Yao Yan’an , Kong Xianwen , Li Bing
Published: November 2017

A novel biped robot based on a 4-UPU (universal-prismatic-universal) parallel mechanism with actuation redundancy is presented. The biped robot consists of two platforms and four UPU serial chains as limbs. The actuation method of the mechanism is determined based on the mobility and singularity analysis. The singular positions of the mechanism are identified and then eliminated using a redundant actuator. To meet different requirements, the multiple motion modes of the robot are discussed and simulated in the gait analysis. Moreover, the robot has special gaits for reset and self-rescue if overturned. Kinematic analysis of the mechanism and walking stability analysis are carried out in detail. Physical prototype experiments indicate that the proposed biped robot is feasible. Through properly planning the motion modes, the biped robot can quickly pass through rugged terrain containing slopes and obstacles.
Design and Application of Fractional Order PIλDµ Controller in Grid-Connected Inverter System
Authors: Pan Zhifeng , Wang Xiaohong , Hoang Thi Thu Giang , Luo Ying , Chen Yangquan , Tian Lianfang
Published: November 2017

In comparison with the traditional controller PID, the fractional order controller PIλDμ is added with two parameters (μ and λ), that increases the flexibility of the controller. The larger adjustable space makes it more favorable to the control of the nonlinear system like the three-phase grid-connected inverter. However, since the fractional calculus operator is an irrational function on the complex plane, it can’t be implemented directly in simulation or in practical applications. In this paper, the advantages of the fractional order controller PIλDμ will be analyzed, then the fractional calculus operator is fitted by the frequency domain analysis method. Based on the vector method, the fractional order controller PIλDμ of the grid-connected inverter is designed. Simultaneously, the optimal controller parameters are searched with the ITAE and IAE as the performance index. And finally, the results are compared with those of the traditional controller PID. In consideration of the defects of fractional algorithm and single discretization method, a hybrid discretization method is proposed in order to ensure that the discretized controller can keep the same time-domain response and frequency characteristics as the designed controller. The experimental results show that the proposed method has the dynamic and static characteristics better than the traditional controller PID, which proves that the application of fractional order controller in three-phase grid-connected inverter is effective and feasible.
Report of Robotic Machining Measurements Using a Stäubli TX200 Robot: Application to Milling
Authors: Huynh Hoai Nam , Rivière-Lorphèvre Edouard , Verlinden Olivier
Published: November 2017

One of the most promising manufacturing technologies nowadays is certainly the material removal using an industrial robot. Robotic machining is a fast growing technology as the number of robots used in industry is increasing continuously. Robots are indeed flexible which allows them to deal with large workpieces. On the other hand, their low stiffness restricts their use to machining operations accommodating a low accuracy or involving limited cutting forces as milling instabilities are more likely to occur. Since the impact of the machining process on the robot structure is not fully understood at this time, this paper aims to provide an in-depth analysis of experimental data obtained while machining an aluminium plate with a Stäubli robot arm. After describing the experimental set-up, three different analyses (metrological, vibration, cutting forces) were carried out on the basis of the machined workpiece and the measured signals. An identification of the cutting coefficients was eventually performed in order to fit a cutting force model to the measurements. Simulation results showed a good correlation with the experimental measurements.
Computational Modal Analysis of a Twin-Engine Rear Fuselage Mounted Aircraft Support Frame
Authors: Warwick Braden T. , Mechefske Chris K. , Kim Il Yong
Published: November 2017

The focus of this investigation was to computationally determine the vibrational characteristics of a rear fuselage mounted aircraft engine support frame. A pseudo-orthogonality check was performed to compare the computational results with experimental data. This produced a matrix with 8 modes with diagonal terms >0.9. Structural modifications were made to the computational model of the frame in order to decrease the modal density near the blade pass frequency of the engine at cruise conditions. Two independent modifications to the frame decreased the modal density within 1% of the critical engine frequency from seven to five and four respectively. It was shown that the modifications produced non-intuitive results, as each modification had a different significance in terms of how it affected each mode of the system. It is recommended that computational analysis be performed on similar structures before such modifications are put in place, as there is low predictability of how different modifications will affect the modal properties of the system.
Simulation and Design Optimization of a Tall-Form Spray Dryer
Authors: Masilungan-Manuel Joanna Tess , Soriano Allan N. , Manuel Mark Christian E. , Lin Po Ting
Published: November 2017

Airflow stability plays a vital role in optimizing the spray dryer operation; wherein the airflow patterns present inside the drying chamber are considered as the primary factors that influences the histories of the product particle. In this paper, the optimum drying parameters that would produce a higher yield of powdered egg while retaining its quality parameter such as moisture content and water activity were determined by means of Euler-Lagrange Discrete Phase Modeling (DPM) numerical method present in the ANSYS-Fluent ver. 14.5 CFD solver. During the computational simulation, the flow pattern of the air was first identified using the Eulerian method then the results were coupled using the Lagrangian-Discrete Phase Modeling to track the particle histories of the disperse phase inside the tall-form spray drying chamber. Results showed that the optimum inlet air velocity and temperature are 8.87 m/s and 444 K respectively. At these conditions, the particle trajectories simulated exhibited that the calculated final moisture content and water activity for the dried egg powder are 1.09 % and 0.012, respectively.
Design of Miura-Ori Patterns With Acoustic Bandgaps
Authors: Pratapa Phanisri P. , Suryanarayana Phanish , Paulino Glaucio H.
Published: November 2017

We study the wave propagation behavior in Miura-ori patterns by using the Bloch-wave analysis framework. Our investigation focuses on acoustic bandgaps that act as stopping bands for wave propagation at certain frequencies in periodic solids or structures. We show that bandgaps can be created in two-dimensional periodic Miura-ori patterns by introducing material inhomogeneity. First, we perform Bloch-wave analysis of homogeneous Miura-ori patterns with finite panel rigidity and find that no bandgaps are present. We then introduce bandgaps by making the pattern non-uniform — by changing the mass and axial rigidity of origami panels of alternating unit cells. We discuss the dependence of the magnitude of the bandgap on the contrast between material properties. We find that higher magnitudes of bandgaps are possible by using higher contrast ratios (mass and stiffness). These observations indicate the potential of origami-based patterns to be useful as acoustic metamaterials for vibration control.
Experimental Modal Analysis of a Half-Scale Model Twin-Engine Aircraft Rear Fuselage Engine Mount Support Frame
Authors: Chamberlain Diego A. , Mechefske Chris K.
Published: November 2017

Experimental modal testing using an impact hammer is a commonly used method for obtaining the modal parameters of any structure for which the vibrational behavior is of interest. Natural frequencies and associated mode shapes of the structure can be extracted directly from measured FRFs (Frequency Response Functions) through various curve fitting procedures. This paper provides an overview of the modal testing conducted on an aerospace component. Testing set-up, experimental equipment and the methodology employed are all described in detail. Further validation of the testing procedure was done by ensuring that the experimental results satisfy the requirements of repeatability, reciprocity and linearity. The relevant ISO standard has been referenced and important concepts to modal analysis are expanded upon. Recorded natural frequencies, coherence and a description of the observed mode shapes are presented along with notable trends.
A 6R Single-Loop Overconstrained Spatial Mechanism That Has Two Pairs of Revolute Joints With Intersecting Axes and One Pair of Revolute Joints With Parallel Axes
Authors: Kong Xianwen , He Xiuyun , Li Duanling
Published: November 2017

This paper deals with a 6R single-loop overconstrained spatial mechanism that has two pairs of revolute joints with intersecting axes and one pair of revolute joints with parallel axes. The 6R mechanism is first constructed from an isosceles triangle and a pair of identical circles. The kinematic analysis of the 6R mechanism is then dealt with using a dual quaternion approach. The analysis shows that the 6R mechanism usually has two solutions to the kinematic analysis for a given input and may have two circuits (closure modes or branches) with one or two pairs of full-turn revolute joints. In two configurations in each circuit of the 6R mechanism, the axes of four revolute joints are coplanar, and the axes of the other two revolute joints are perpendicular to the plane defined by the above four revolute joints. Considering that from one configuration of the 6R mechanism, one can obtain another configuration of the mechanism by simply renumbering the joints, the concept of two-faced mechanism is introduced.
Proportional-Integral-Observer With Adaptive High-Gain Design Using Funnel Adjustment Concept
Authors: Bakhshande Fateme , Söffker Dirk
Published: November 2017

This paper focuses on a novel gain design approach of Proportional-Integral-Observer (known as PI-Observer) for unknown input estimation such as disturbances. Whereas estimation of the fast dynamical behavior requires large observer gains, the effect of measurement noise is not negligible. To adjust the PIO gain adaptively, in this contribution the idea of funnel control is taken into consideration. The advantage of the proposed approach compared to previously published PIO gain design is the self adjustment of the observer gains according to the actual estimation situation. To improve the control performance and robustness, in the present contribution the proposed approach is combined with exact feedback linearization (EFL) method. The effectiveness of the proposed approach is verified by simulation results of a MIMO mass-spring system.
Geometry Optimization of Flexure System Topologies Using the Boundary Learning Optimization Tool (BLOT)
Authors: Hatamizadeh Ali , Song Yuanping , Hopkins Jonathan B.
Published: November 2017

In this paper, we introduce a new computational tool called the Boundary Learning Optimization Tool (BLOT) that rapidly identifies the boundary of the performance capabilities achieved by a general flexure topology if its geometric parameters are allowed to vary from their smallest allowable feature sizes to the largest geometrically compatible feature sizes for a given constituent material. The boundaries generated by the BLOT fully define a flexure topology’s design space and allow designers to visually identify which geometric versions of their synthesized topology best achieve a desired combination of performance capabilities. The BLOT was created as a complementary tool to the Freedom And Constraint Topologies (FACT) synthesis approach in that the BLOT is intended to optimize the geometry of the flexure topologies synthesized using the FACT approach. The BLOT trains artificial neural networks to create sufficiently accurate models of parameterized flexure topologies using the fewest number of design instantiations and their corresponding numerically generated performance solutions. These models are then used by an efficient algorithm to plot the desired topology’s performance boundary. A FACT-synthesized flexure topology is optimized using the BLOT as a case study.
Fabrication of Complex-Shape Products From a Binder-Free Green Composite Using Bamboo Fibers and Powders Extracted With a Machining Center
Authors: Inoue Kota , Bigeard Antoine , Hirogaki Toshiki , Aoyama Eiichi , Ogawa Keiji , Nobe Hiromichi
Published: November 2017

Research is currently ongoing for composite materials using natural fiber with a small burden on the environment. We have been focusing on bamboo because of its fast growth, renewability, flexibility, low cost, and high specific strength. We previously proposed a novel hot press fabrication method for binder-free green composite products made from bamboo fibers extracted by end-milling with a machining center. We can use this method to form three-dimensionally shaped products, especially hemispherical shells, by using two kinds of dies. However, this method is complex and takes longer than one-step hot press forming. In the present report, we propose a new method that uses bamboo powder with a particle size of less than 500 μm. Our new method uses one-step hot press forming and is quicker than the previous method at making a hemispherical shell shape. The new method was successfully used to manufacture hemispherical shell-shape products.
Vibration Analysis of V-Shaped Beam Electrothermal Microactuators
Authors: Zhang Zhuo , Yu Yueqing , Zhang Xuping
Published: November 2017

This paper presents an analytical model for the vibration analysis of V-shaped beam electrothermal microactuators. With the consideration of the unique geometrical feature, i.e., the V-shaped beam with the two inclined half-spans interconnecting at the center of the beam, both lateral and longitudinal flexible deformations are included the vibration model established in this work. Furthermore, the vibrations in the lateral and longitudinal directions are coupled, therefore both the boundary and continuity conditions are defined to obtain the frequency equation. The natural frequencies can be calculated by solving the frequency equation numerically. To verify the established vibration model, the comparison is conducted between analytical results and finite-element (FE) simulation results using commercial software ANSYS. The comparison of the modal shapes and frequencies demonstrate the results based on the established analytical model well agree with FE simulation results. This work provides the first insight study on the vibration analysis of the V-shaped beam electrothermal microactuators with aims to lay the foundation of establishing thermo-mechanical model that could be used for the control of V-shaped actuators, and the improvement design in achieving optimal dynamic performance.
Amplitude Death Induced by Mechanical Coupling
Authors: Wei Y. M. , Peng Z. K. , Dong X. J. , Zhang W. M. , Meng G.
Published: November 2017

Amplitude death is a physical phenomenon that occurs in coupled systems where oscillation is dead and comes to fixed points. Based on the basic mechanical oscillators, a new kind of coupling named mechanical coupling is proposed to induce amplitude death. Both direct coupling and time delay coupling of mechanical oscillators are tested to be able to induce amplitude death. The amplitude death region is found to be influenced by the coupling strength. Numerical examples of lorenz oscillators and rossler oscillators are also simulated and found that the chaotic motion is induced to death with properly designed parameters. The significant practical applications of the new mechanism of amplitude death is discussed.
Electrothermally Actuated Microbeams With Varying Stiffness
Authors: Tella Sherif , Alcheikh Nouha , Younis Mohammad I.
Published: November 2017

We present axially loaded clamped-guided microbeams that can be used as resonators and actuators of variable stiffness, actuation, and anchor conditions. The applied axial load is implemented by U-shaped electrothermal actuators stacked at one of the beams edges. These can be configured and wired in various ways, which serve as mechanical stiffness elements that control the operating resonance frequency of the structures and their static displacement. The experimental results have shown considerable increase in the resonance frequency and mid-point deflection of the microbeam upon changing the end conditions of the beam. These results can be promising for applications requiring large deflection and high frequency tunability, such as filters, memory devices, and switches. The experimental results are compared to multi-physics finite-element simulations showing good agreement among them.
A Multiobjective Adaptive Surrogate Modeling-Based Optimization (MO-ASMO) Framework Using Efficient Sampling Strategies
Authors: Lee Yong Hoon , Corman R. E. , Ewoldt Randy H. , Allison James T.
Published: November 2017

A novel multiobjective adaptive surrogate modeling-based optimization (MO-ASMO) framework is proposed to utilize a minimal number of training samples efficiently for sequential model updates. All the sample points are enforced to be feasible, and to provide coverage of sparsely explored sparse design regions using a new optimization subproblem. The MO-ASMO method only evaluates high-fidelity functions at feasible sample points. During an exploitation sample phase, samples are selected to enhance solution accuracy rather than the global exploration. Sampling tasks are especially challenging for multiobjective optimization; for an n-dimensional design space, a strategy is required for generating model update sample points near an (n − 1)-dimensional hypersurface corresponding to the Pareto set in the design space. This is addressed here using a force-directed layout algorithm, adapted from graph visualization strategies, to distribute feasible sample points evenly near the estimated Pareto set. Model validation samples are chosen uniformly on the Pareto set hypersurface, and surrogate model estimates at these points are compared to high-fidelity model responses. All high-fidelity model evaluations are stored for later use to train an updated surrogate model. The MO-ASMO algorithm, along with the set of new sampling strategies, are tested using two mathematical and one realistic engineering problems. The second mathematical test problems is specifically designed to test the limits of this algorithm to cope with very narrow, non-convex feasible domains. It involves oscillatory objective functions, giving rise to a discontinuous set of Pareto-optimal solutions. Also, the third test problem demonstrates that the MO-ASMO algorithm can handle a practical engineering problem with more than 10 design variables and black-box simulations. The efficiency of the MO-ASMO algorithm is demonstrated by comparing the result of two mathematical problems to the results of the NSGA-II algorithm in terms of the number of high fidelity function evaluations, and is shown to reduce total function evaluations by several orders of magnitude when converging to the same Pareto sets.
Geometry of Modular Origami Metamaterials
Authors: Yang Yunfang , You Zhong
Published: November 2017

Modular origami is a type of origami where multiple pieces of paper are folded into modules, and these modules are then interlocked with each other forming an assembly. Some of them turn out to be capable of large scale shape transformation, making them ideal to create metamaterials with tuned mechanical properties. In this paper, we carry out a fundamental research on 2D modular origami assemblies using mathematical tiling and patterns and mechanism analysis, which leads to the development of various patterns consisting of interconnected quadrilateral modules. Due to the existence of 4R linkages within the patterns, they become transformable, and can be compactly packaged. Moreover, by the introduction of paired modules, we are able to adjust the expansion ratio of the pattern. Additionally, we also show that transformable patterns with higher mobility exist for other polygonal modules. Our findings provide more design flexibility to achieve truly programmable metamaterials.
A Concurrent Design Exploration Method for Realizing Networked Manufacturing Systems
Authors: Milisavljevic Jelena , Commuri Sesh , Allen Janet K. , Mistree Farrokh
Published: November 2017

Multistage manufacturing processes (MMPs) are networked manufacturing systems consisting of multiple operational stations that have characteristics of mechanical and control systems. Common challenges in the design of MMPs are the selection of sensors and tools as this not only affects the dimensional quality of the finished product, but also influences the computational complexity in representing and analyzing the problem. Imprecise or incomplete information results in uncertainty in the models used to represent the MMP and limit the use of traditional design approaches. In this paper, an exploration method for the concurrent design (CDEM) of MMPs under uncertainty is presented wherein the attributes of tools and sensors are treated as design variables, thereby allowing flexibility in a design process. The proposed method is illustrated using an example of automotive panel stamping process. Our focus in this paper is on the method rather than the results per se.
Folding Thick Materials Using Axially Varying Volume Trimming
Authors: Ku Jason S.
Published: November 2017

Many new and complex methods have been proposed for building folded structures from thick materials. Volume trimming was one of the first and simplest techniques for fabricating ideal hinges using thick materials, though has remained largely unmodified since it was proposed. This paper extends and customizes constant thickness volume trimming for layered fabrication processes. Previously, constant thickness volume trimming uniformly removed material local to each hinge, leaving layers near the hinge vulnerable to delamination. We provide a method to retain material on both sides of the fold line to create stronger hinges by varying the profile of removed material along the axis of the hinge, even for hinges with large fold angle.
Multistability and Bifurcation Topology in Electrostatically Coupled Nanobeams Under Parametric Resonance
Authors: Bitar Diala , Kacem Najib , Bouhaddi Noureddine
Published: November 2017

The collective nonlinear dynamics of electrostatically coupled nanobeams under parametric excitation is modeled and investigated, while including the main sources of nonlinearities up to the fifth order. The normalized nonlinear differential equations are solved using secular perturbation theory. Numerical simulations have been performed using the Asymptotic Numerical Method for two and three coupled nanobeams. It is shown that, the fifth order nonlinearity leads to an increase in the number of multimodal solutions and their complexity in term of bifurcation topology. This model can be exploited to design arrays of NEMS with high performances for sensing applications.
Kinematic Analysis of the Lolotte Technique in Rock Climbing
Authors: Artoni Alessio , Tomasi Matilde , Di Puccio Francesca
Published: November 2017

The lolotte or drop-knee technique is a fundamental of rock climbing that particularly involves lower limbs, and especially knee joints. To the authors’ best knowledge, no biomechanical analysis of the lolotte seems to have ever been conducted, despite its widespread use. As a first contribution to this research topic, the present work deals with an athlete-specific kinematic analysis of the lolotte aimed at quantifying the hip and knee joint angle trajectories and knee ligament strains. A marker-based motion capture system was employed to track the execution of the lolotte on a purposely designed climbing structure. The marker trajectories were then used as input for a numerical simulation in the OpenSim program, where an athlete-specific musculoskeletal model was set up to perform an inverse kinematics analysis and obtain the joint angle trajectories as well as their ranges of motion. Further processing of the model allowed to estimate the strain of the knee medial collateral ligament. Such kinematic analysis revealed characteristic hip and knee joint angle patterns and highlighted a critical phase in which the knee is considerably abducted (increased valgus). As a consequence, the medial collateral ligament is remarkably recruited, thereby substantiating the claim diffused among climbers that drop-kneeing may cause ligament injury.
Dimension Reduction and Decomposition Using Causal Graph and Qualitative Analysis for Aircraft Concept Design Optimization
Authors: Wu Di , Coatanea Eric , Wang G. Gary
Published: November 2017

With the increasing design dimensionality, it is more difficult to solve Multidisciplinary design optimization (MDO) problems. To reduce the dimensionality of MDO problems, many MDO decomposition strategies have been developed. However, those strategies consider the design problem as a black-box function. In practice, the designers usually have certain knowledge of their problem. In this paper, a method leveraging causal graph and qualitative analysis is developed to reduce the dimensionality of the MDO problem by systematically modeling and incorporating knowledge of the design problem. Causal graph is employed to show the input-output relationships between variables. Qualitative analysis using design structure matrix (DSM) is carried out to automatically find the variables that can be determined without optimization. According to the weight of variables, the MDO problem is divided into two sub-problems, the optimization problem with respect to important variables, and the one with less important variables. The novel method is performed to solve an aircraft concept design problem and the results show that the new dimension reduction and decomposition method can significantly improve optimization efficiency.
Value of Bootstrapping Staged Deployment of Infrastructure: Case Study in Space Infrastructure Deployment
Authors: Ho Koki , Chen Hao , Kim Harrison
Published: November 2017

This paper analyzes the value of staged deployment for complex infrastructure system and propose a concept of bootstrapping staged deployment. Staged deployment has been well known for its advantage of providing flexibility in an uncertain environment. In contrast, this paper demonstrates that the proposed bootstrapping staged deployment can even add values in a deterministic environment. The key idea of bootstrapping staged deployment is to have the previously deployed stages support the subsequent deployment. We develop an analytical model to demonstrate the effects of bootstrapping staged deployment with a case study in space exploration. Our analysis results show that with a well-coordinated deployment plan, staged deployment can overperform single-stage deployment even in a deterministic environment, and that there is an optimal number of stages in terms of lifecycle cost under certain conditions. Our method can find the analytical expression for the optimal number of stages and its deployment strategies. The general findings from the proposed concept and analytical method can advance our knowledge about systems staged deployment, and make operational planning of resource generation infrastructure more efficient.
Passive Prosthetic Foot Shape and Size Optimization Using Lower Leg Trajectory Error
Authors: Olesnavage Kathryn M. , Winter Amos G.
Published: November 2017

A method is presented to optimize the shape and size of a passive prosthetic foot using the Lower Leg Trajectory Error (LLTE) as the design objective. The LLTE is defined as the root-mean-square error between the lower leg trajectory calculated for a given prosthetic foot by finding the deformed shape of the foot under typical ground reaction forces and a target physiological lower leg trajectory obtained from published gait data for able-bodied walking. In previous work, the design of simple two degree-of-freedom analytical models consisting of rigid structures, rotational joints with constant stiffness, and uniform cantilevered beams, have been optimized for LLTE. However, prototypes built to replicate these simple models were large, heavy, and overly complex. In this work, the size and shape of a single-part compliant prosthetic foot keel made out of nylon 6/6 was optimized for LLTE to produce a light weight, low cost, and easily manufacturable prosthetic foot design. The shape of the keel was parameterized as a wide Bézier curve, with constraints ensuring that only physically meaningful shapes were considered. The LLTE value for each design was evaluated using a custom MATLAB script, which ran ADINA finite element analysis software to find the deformed shape of the prosthetic keel under multiple loading scenarios. The optimization was performed by MATLAB’s built-in genetic algorithm. After the optimal design for the keel was found, a heel was added to structure, sized such that when the user’s full weight acted on the heel, the structure had a factor of safety of two. The resulting optimal design has a lower LLTE value than the two degree-of-freedom analytical models, at 0.154 compared to 0.172, 0.187, and 0.269 for the two degree-of-freedom models. At 412 g, the optimal wide curve foot is nearly half the mass of the lightest prototype built from the previous models, which was 980 g. The design found through this compliant mechanism optimization method is thus far superior to the two degree-of-freedom models previously considered.
Management of Sampling Uncertainty Using Conservative Estimate of Probability in Bayesian Network
Authors: Bae Sangjune , Kim Nam H. , Jang Seung-gyo
Published: November 2017

Since the safety of a system is often assessed by the probability of failure, it is crucial to calculate the probability accurately in order to achieve the target safety. Despite such importance, calculating the precise probability is not a trivial task due to the inherent aleatory variability and epistemic uncertainty. Therefore the safety is assessed by a conservative estimate of the probability rather than using a single value of the probability. In general, there are two ways to achieve the target probability: Shifting the probability or reducing the uncertainty. In this paper, among various sources of epistemic uncertainty, the uncertainty quantification error from sampling is considered to calculate the conservative estimate of a system probability of failure. To quantify and shape the epistemic uncertainty, Bayesian network is utilized for constituting the relationship between the system probability and component probabilities, while global sensitivity analysis is employed to connect the variance in the probabilities in system level with that in the component level. Based on this, local sensitivity of the conservative estimate with respect to a design change in a component is derived and approximated for a simple numerical calculation using Bayesian network and global sensitivity analysis. This is to show how a design can meet the probabilistic criteria considering propagated uncertainty when the design changes.
Linking Creativity Measurements to Product Market Favorability: A Data-Mining Approach
Authors: Lopez B. Christian E. , Zheng Xuan , Miller Scarlett R.
Published: November 2017

While creative ideas can lead to market success and payoff, they are also associated with high risks and uncertainties. One way to reduce these uncertainties is to provide decision makers with valuable information about the innovative potential and future success of an idea. Even though several metrics have been proposed in the literature to evaluate the creativity of early design-stage ideas, these metrics do not provide information about the future product success or market favorability of new product ideas. Hence, existing metrics fail to link the creativity of early-stage ideas to their future market favorability. In order to bridge this gap, the current work proposes a new metric to estimate early design-stage ideas’ favorability and analyzes its relationship with current creativity metrics. A data-mining driven method to assess the future favorability of new product ideas using customers’ reviews of current market products that shared similar features with the new ideas of interest is presented. The results suggest that the new product idea favorability is positively correlated with relative creativity metrics and existing product market favorability ratings. This method can be used to help designers gain a better insight into the creativity and market favorability potential of new product ideas in early design-stages via a systematic approach; hence, helping reduce the risks and uncertainties associated with early-phase ideas during the screening and selecting process.
Distributed Adaptive Fault-Tolerant Cooperative Control for Multi-UAVs Against Actuator and Sensor Faults
Authors: Yu Ziquan , Qu Yaohong , Zhang Youmin , Zhang Yintao
Published: November 2017

In this paper, a distributed adaptive fault-tolerant cooperative control (FTCC) scheme is developed for flying multiple unmanned aerial vehicles (UAVs) with consideration of actuator and sensor faults. The communication network is an undirected, fixed topology and only a subset of UAVs has access to the common reference. By using a sliding-mode observer, the common reference is estimated by each UAV. The lumped uncertainties including external disturbances, actuator and sensor faults are estimated by an adaptive mechanism. On the basis of the estimated reference and lumped uncertainties, dynamic surface control technique is utilized to eliminate the computational burden inherent in the traditional backstepping control architecture. The highlight is that external disturbances, actuator and sensor faults are considered in the distributed control scheme for multi-UAVs simultaneously. By using graph theory and Lyapunov-based method, it is proved that all signals in the closed-loop system are bounded. Furthermore, simulation results are exhibited to demonstrate the effectiveness of the proposed control scheme.