bluuebunny/crossref_metadata_2025 huggingface dataset:
Trust Based Cyber-Physical Systems Network Design
Authors: Wang Yan
Published: November 2018

Cyber-physical systems (CPS) extensively share information with each other, work collaboratively over Internet of Things, and seamlessly integrated with human society. Designing CPS requires the new consideration of design for connectivity where security, privacy, and trust are of the main concerns. Particularly trust can affect system behavior in a networked environment. In this paper, trustworthiness is quantitatively measured by the perceptions of ability, benevolence, and integrity. Ability indicates the capabilities of sensing, reasoning, and influence in a society. Benevolence measures the genuineness of intention and reciprocity in information exchange. Integrity captures the system predictability and dependability. With these criteria, trust-based CPS network design and optimization are demonstrated.
Liquid State Machine to Generate the Movement Profiles for the Gait Cycle of a 6 DOF Bipedal Robot in a Sagittal Plane
Authors: Franco-Robles Jesús , De Lucio-Rangel Alejandro , Camarillo-Gómez Karla A. , Pérez-Soto Gerardo I. , Rivera-Guillén Jesús
Published: November 2018

In this paper, a neuronal system with the ability to generate motion profiles and profiles of the ZMP in a 6DoF bipedal robot in the sagittal plane, is presented. The input time series for LSM training are movement profiles of the oscillating foot trajectory obtained by forward kinematics performed by a previously trained ANN multilayer perceptron. The profiles of objective movement for training are acquired from the analysis of the human walk. Based on a previous simulation of the bipedal robot, a profile of the objective ZMP will be generated for the y–axis and another for the z–axis to know its behavior during the training walk. As an experimental result, the LSM generates new motion profiles and ZMP, given a different trajectory with which it was trained. With the LSM it will be possible to propose new trajectories of the oscillating foot, where it will be known if this trajectory will be stable, by the ZMP, and what movement profile for each articulation will be required to reach this trajectory.
Investigating User Emotional Responses to Eco-Feedback Designs
Authors: Bao Qifang , Hughes Ann M. , Burnell Edward , Yang Maria C.
Published: November 2018

Emotional responses to a product can be critical to influencing how the product will be used. This study explores the emotions that arise from users’ interaction with eco-feedback products, and investigates links between emotions and users’ resource conservation behaviors. In-lab experiments were conducted with 30 participants of varying backgrounds. Each participant was shown sketches of four conceptual designs of eco-feedback products and reported how they would feel and behave in different scenarios using the products. Results showed that taking immediate resource conservation actions such as turning off lights was correlated with negative emotions such as guilt and embarrassment. Users’ evaluations of product aesthetics, usefulness and overall quality, however, were highly correlated with positive emotions, described as satisfied, hopeful, interested and/or excited. Two styles of eco-feedback design, quantitative and figurative, were compared. Figurative designs were observed to evoke much stronger emotions among younger participants than older ones. Ultimately, we hope our findings are useful to the designers of eco-feedback products.
Identification of Non-Linear Vibration Parameters of a Nuclear Fuel Rod
Authors: Amabili Marco , Balasubramanian Prabakaran , Ferrari Giovanni , Le Guisquet Stanislas , Karazis Kostas , Painter Brian , Piccagli Lorenzo
Published: November 2018

In Pressurized Water Reactors (PWR), fuel assemblies are composed of fuel rods, long slender tubes filled with uranium pellets, bundled together using spacer grids. These structures are subjected to fluid-structure interactions, due to the flowing coolant surrounding the fuel assemblies inside the core, coupled with large-amplitude vibrations in case of external seismic excitation. Therefore, understanding the non-linear response of the structure and, particularly, its dissipation, is of paramount importance for the choice of safety margins. To model the nonlinear dynamic response of fuel rods, the identification of nonlinear stiffness and damping parameters is required. The case of a single fuel rod with clamped-clamped boundary conditions was investigated by applying harmonic excitation at various force levels. Different configurations were implemented testing the fuel rod in air and in still water; the effect of metal pellets simulating nuclear fuel pellets inside the rods was also recorded. Non-linear parameters were extracted from some of the experimental response curves by means of a numerical tool based on the harmonic balance method. The axisymmetric geometry of fuel rods resulted in the presence of a one-to-one internal resonance phenomenon, which has to be taken into account modifying accordingly the numerical identification tool. The internal motion of fuel pellets is a cause of friction and impacts, complicating further the linear and non-linear dynamic behavior of the system. An increase of the equivalent viscous-based modal damping with excitation amplitude is often shown during geometrically non-linear vibrations, thus confirming previous experimental findings in the literature.
Detection of Pathogens and Formation of Biofilms Using a Three-Dimensional Biomimetic Biosensing Platform
Authors: Mazrouei Roya , Sumita Minako , Shavezipur Mohammad
Published: November 2018

Internalization of pathogens inside pores and channels of fresh produce and formation of polymeric biofilm around their colonies are important phenomena in food safety due to complications they create for removal and inactivation of pathogens. The practical challenges does not allow for monitoring the pathogen-produce interaction in real time and under different ambient conditions. The present work introduces a biomimetic biosensing platform that simulates the actual produce and can detect the presence, growth and internalization of microorganisms and also potential formation of biofilm. The system consists of layers of capacitive electrodes made of polycrystalline silicon which are designed based on a standard foundry process (PolyMUMPs). The electrodes form multiple impedance-based biosensors and can simulate porous medium of the produce surface. As the cells reside on the surface of the top layer or penetrate inside the system, the capacitance value of each electrode pair changes. Monitoring the capacitance change of each biosensor allows us to determine where the microorganisms are and also whether their population is increasing. To demonstrate the applicability of our proposed biosensing system, a comprehensive FEM simulation is performed using ANSYS® APDL. The simulation results show that each pair of electrodes displays a specific pattern of capacitance change when cells reside on the system’s surface, move inside, grow or produce polymeric biofilm, because the electrostatic properties of cells and biofilm polymers are different from those of the solution. Analyzing the capacitance patterns allows us to determine that cells are at which stage of growth or internalization, and how far they have moved inside the system.
Modeling Spatiotemporal Heterogeneity of Customer Preferences in Engineering Design
Authors: Bi Youyi , Xie Jian , Sha Zhenghui , Wang Mingxian , Fu Yan , Chen Wei
Published: November 2018

Customer preferences are found to evolve over time and correlate with geographical locations. Studying spatiotemporal heterogeneity of customer preferences is crucial to engineering design as it provides a dynamic perspective for a thorough understanding of preference trend. However, existing analytical models for demand modeling do not take the spatiotemporal heterogeneity of customer preferences into consideration. To fill this research gap, a spatial panel modeling approach is developed in this study to investigate the spatiotemporal heterogeneity of customer preferences by introducing engineering attributes explicitly as model inputs in support of demand forecasting in engineering design. In addition, a step-by-step procedure is proposed to aid the implementation of the approach. To demonstrate this approach, a case study is conducted on small SUV in China’s automotive market. Our results show that small SUVs with lower prices, higher power, and lower fuel consumption tend to have a positive impact on their sales in each region. In understanding the spatial patterns of China’s small SUV market, we found that each province has a unique spatial specific effect influencing the small SUV demand, which suggests that even if changing the design attributes of a product to the same extent, the resulting effects on product demand might be different across different regions. In understanding the underlying social-economic factors that drive the regional differences, it is found that Gross Domestic Product (GDP) per capita, length of paved roads per capita and household consumption expenditure have significantly positive influence on small SUV sales. These results demonstrate the potential capability of our approach in handling spatial variations of customers for product design and marketing strategy development. The main contribution of this research is the development of an analytical approach integrating spatiotemporal heterogeneity into demand modeling to support engineering design.
A Load-Adjustable Constant-Force Mechanism
Authors: Hasara Steven , Lusk Craig
Published: November 2018

This paper outlines the design of a compliant crank slider with adjustable constant-force output. Constant-force mechanisms (CFM) are used to maintain a constant output reaction force throughout a large range of compressive motion. This novel design improves on existing CFM by introducing a second degree of freedom that adjusts the mechanism’s output without changing its kinematic structure. This second degree of freedom is the rotation of a compliant beam about its longitudinal axis as it is constrained to the initial plane of bending. The resulting change in the beam’s stiffness allows for adjustment to a specifiable range of constant-force outputs.
Analysis of Parasitic Motion in Compliant Mechanisms Using Eigenwrenches and Eigentwists
Authors: van de Sande Werner W. P. J. , Herder Just L.
Published: November 2018

Parasitic motion is undesired in precision mechanisms, it causes unwanted kinematics. These erroneous motions are especially apparent in compliant mechanisms. Usually an analysis of parasitic motion is only valid for one type of mechanism. Kinematic information is imbedded in the compliance matrix of any mechanism; an eigenscrew decomposition expresses this kinematic information as screws. It uses screw theory to identify the lines along which a force yields a parallel translation and a rotation yields a parallel moment. These lines are called eigenwrenches and eigentwists. Any other load on the compliant mechanism will lead to parasitic motion. This article introduces two parasitic motion metrics using eigenscrew decomposition: the parasitic resultant from an applied screw and the deviation of an actual degree of freedom from a desired degree of freedom. These metrics are applicable to all compliant mechanism and allow comparison between two compliant mechanisms. These metrics are applied to some common compliant mechanisms as an example.
Projection-Based Overhang Constraints: Implementing an Efficient Adjoint Formulation for Sensitivity Analysis
Authors: Behrou Reza , Guest James K. , Gaynor Andrew T.
Published: November 2018

This paper extends a recently developed adjoint framework for an efficient overhang filtering to projection-based methods for overhang constraints. The developed approach offers a fast and efficient computational methodology and enables a minimum allowable self-supporting angle and a minimum allowable feature size within the formulation of the optimization problem, and designs components that can be manufactured without using support structures. The adjoint-based sensitivity formulation are derived to eliminate the computational intensities associated with the direct differentiation in the formulation of overhang constraints, which become prohibitive in large scale 2D and 3D problems. The developed formulation is tested on structural problems and numerical examples are provided to present efficiency of the proposed methodology.
Change Propagation During Protoyping: A Case Study of a Robotic Inspection System for Dry Nuclear Waste Storage Casks
Authors: Bracken Jennifer , Brennan Sean , Lissenden Clifford , Simpson Timothy W. , Van Sant Ian , Reichard Karl , Ng Matthew
Published: November 2018

In prototyping complex systems, concept iterations often reach a point where incremental modifications to one part in a complex system can produce unexpected, cascading changes in the rest of the system. This phenomenon can require time-consuming and expensive corrections, particularly when physical prototypes are involved — as was the situation in the case study presented here. A design tool, the Design Structure Matrix (DSM), is commonly used to predict change propagation in complex designs. Using several examples, this paper illustrates situations where conventional DSMs fail to predict change propagation in the prototypes created during a robotic inspection system design project, due to complex interactions and system design constraints. The case study discussed here, a robotic inspection system for a nuclear waste storage cask, included interactions not easily captured in a conventional DSM. It was these interactions that interfered with the use of this tool to predict design change propagation. The paper then presents a method that was conceived to manage such changes; a way of modifying conventional DSMs to include design constraints and components. The case study examples show that the resulting technique, called the C+C DSM method, would have better predicted mid-development change propagation in the prototyping process.
Assessment of Jerk As a Method of Physical Fatigue Detection
Authors: Zhang Lichen , Diraneyya Mohsen Mutasem , Ryu JuHyeong , Haas Carl T. , Abdel-Rahman Eihab
Published: November 2018

Workers’ fatigue is a significant problem in physically demanding occupations. Physical fatigue is known to result in the inability to maintain proper posture and working technique. Consequently, workers lose their ability to safely and effectively perform their duties. Thus, understanding the physical demands of labor-intensive work is of great importance in protecting workers’ safety, and maintaining productivity. Current fatigue assessments methods, including surveys and questionnaires, are subjective and lack reliability. Objective fatigue assessments based on physiological data are more reliable, however they are cumbersome to implement in real work conditions. There is a need for an objective fatigue assessment method that can monitor physical fatigue with minimal intrusion. The goal of this study was to investigate whether jerk, the time-derivative of acceleration, can be used to objectively detect physical fatigue. A pilot study on masons was conducted to determine if physical fatigue can be detected by changes in jerk values. Ten participants performed a bricklaying task using forty-five concrete masonry units (CMU). Seven body segments, namely the hands, forearms, upper arms, and pelvis, were selected for placement of IMU sensors to measure the segment accelerations. Jerk was calculated from the measured acceleration via numerical differentiation. Characteristic values of the jerk at the beginning and end of the bricklaying task were obtained to represent the rested and fatigued states. They were then compared for significant differences. Jerk values calculated from the IMU sensors located on the upper arms and pelvis showed significant differences between rested and fatigued states. The results of this pilot study indicate that the characteristic jerk can be used to detect physical fatigue, however caution must be taken in selecting sensor locations to reduce the influence of spurious signals.
Effects of Collage Priming on Sustainable Design Idea Creation and Assessment
Authors: Liao Ting , MacDonald Erin F.
Published: November 2018

Priming is a psychological technique that can alter designers’ mindsets prior to conceptual design exercises [1]. For example, priming the five senses enhanced designers’ abilities to communicate sustainability through the product features they designed [2,3]. Although the three pillars of sustainable design — social desirability, economic competitiveness, and environmental friendliness — are all important, they are not necessarily equally accessible or salient during the design process. This paper applies the collage priming method of [2] to (1) increase/improve ideas related to the sustainability pillars, in the eyes of users, and (2) reduce ownership bias and cause a more favorable judgment of others’ ideas, when compared to one’s own ideas. An experiment tests (1) and (2) for the collage priming method versus a reading preparation activity and no prime/activity for effectiveness in these two applications. The participants included graduate design student attendees at the 2016 IDETC conference and graduate engineering students at Stanford. For (1), collage priming is proven to be successful in helping designers to generate ideas that are more environmentally friendly but less successful in helping designers generate ideas related to social desirability and economic competitiveness, as judged by potential users; no more successful than a reading exercise. For (2), we find evidence that the collage priming reduces ownership bias in designers, as measured in their judgment of other (simulated) designers’ ideas, and in this case the reading exercise does not have the same effect.
A Time-Dependent Reliability Estimation Method Based on Gaussian Process Regression
Authors: Han Wang , Zhang Xiaoling , Huang Xiesi , Li Haiqing
Published: November 2018

This paper presents a time-dependent reliability estimation method for engineering system based on machine learning and simulation method. Due to the stochastic nature of the environmental loads and internal incentive, the physics of failure for mechanical system is complex, and it is challenging to include uncertainties for the physical modeling of failure in the engineered system’s life cycle. In this paper, an efficient time-dependent reliability assessment framework for mechanical system is proposed using a machine learning algorithm considering stochastic dynamic loads in the mechanical system. Firstly, stochastic external loads of mechanical system are analyzed, and the finite element model is established. Secondly, the physics of failure mode of mechanical system at a time location is analyzed, and the distribution of time realization under each load condition is calculated. Then, the distribution of fatigue life can be obtained based on high-cycle fatigue theory. To reduce the calculation cost, a machine learning algorithm is utilized for physical modeling of failure by integrating uniform design and Gaussian process regression. The probabilistic fatigue life of gear transmission system under different load conditions can be calculated, and the time-varying reliability of mechanical system is further evaluated. Finally, numerical examples and the fatigue reliability estimation of gear transmission system is presented to demonstrate the effectiveness of the proposed method.
Dynamic Behavior of a Class of Casimir Actuated NEM Switches
Authors: Bognash Mohamed , Asokanthan Samuel F.
Published: November 2018

Dynamic behavior of a cantilever type nano-switch actuated by pure Casimir force is investigated. Residual surface stress, surface elasticity and intermolecular forces are included in Euler–Bernoulli beam model. Knudsen number dependent squeeze-film air damping model and an asperity-based contact model are incorporated. The proposed model is inherently nonlinear due to interactions between the different nonlinear physics. An approximate analytical approach based on Galerkin’s method has been employed for predicting transient dynamic responses, since no exact solutions are available. Predicted responses show that the beam tip hits the substrate and bounces before making a permanent contact. Actuation of the switch via pure Casimir force is demonstrated for certain length and gap combinations. Initial contact time which governs the switch performance, and the deflections under non-closure condition are also quantified. This study is envisaged to provide useful insights for the future design of Casimir actuated NEM switches.
A Validation Neural Network (VNN) Metamodel for Predicting the Performance of Deep Generative Designs
Authors: Cunningham James , Tucker Conrad S.
Published: November 2018

This work presents a deep neural network method for approximating the performance of generated design concepts. This deep learning meta-modeling approach minimizes the need for costly simulations that test for design concept feasibility by discovering the visual features of a design that correlated to good and bad performance. These form-function relationships are discovered by simply observing the pixels of images of many candidate designs and their corresponding performance in a simulation environment. As opposed to existing metamodeling techniques, this evaluation is agnostic to the simulation environment and applicable to any design space in which form and function are closely linked. A case study is presented in which 2D sketches of boats generated from a deep generative model are evaluated in a simulation environment based on their ability to travel through water without sinking as well as their speed of travel. It is shown through simulation that 57.5% of the designs, which are validated according to their form during the generation process, fail in their intended function. Additionally, the trained VNN is able to classify designs it has never seen before as successful or failing with an accuracy of 86.6% and an F1-Score of 0.806.
Improving Multi-Objective Genetic Algorithm Efficiency for Computational Expensive Problems Adopting Online Variable-Fidelity Metamodel
Authors: Shu Leshi , Jiang Ping , Zhou Qi , Meng Xiangzheng , Zhang Yahui
Published: November 2018

Multi-objective genetic algorithms (MOGAs) are effective ways for obtaining Pareto solutions of multi-objective optimization problems. However, the high computational cost of MOGAs limits their applications to practical engineering optimization problems involving computational expensive simulations. To address this issue, a variable-fidelity metamodel (VFM) assisted MOGA approach is proposed, in which VFM is embedded in the computation process of MOGA to replace expensive simulation models. The VFM is updated in the optimization process considering the cost of simulation models with different fidelity and the effects of the VFM uncertainty. A numerical example and an engineering case are used to demonstrate the applicability and efficiency of the proposed approach. The results show that the proposed approach can obtain Pareto solutions with high quality and it outperforms the other three existing approaches in terms of computational efficiency.
Design of One-DOF Triangular Resch Pattern With Thick-Panel Origami
Authors: Zhang Miao , Yang Fufu , Ma Jiayao , Chen Yan , You Zhong
Published: November 2018

Resch patterns have a great potential to be utilized in many engineering applications, as they can be folded into curved profiles from planar sheets. They are rigid foldable but with a large number of degrees of freedom (DOF) when there are many units tessellating in the patterns, which constrains the applications due to the difficulty in control the motion symmetrically. In this paper, in order to achieve the single mobility for a limited number of triangular Resch pattern units, the thick-panel technique is employed at each vertex to reduce the DOF to one. Then the compatibility among all the vertices has to be satisfied by the systematical kinematic analysis on the geometric parameters of the Resch pattern and panel thickness. Eventually, two design schemes are obtained to form the one DOF origami structure with doubly-curved intermediate folding configurations, which could be further tessellated into a large pattern for various engineering applications.
Exploring the Design Space Using a Surrogate Model Approach With Digital Human Modeling Simulations
Authors: Ahmed Salman , Gawand Mihir Sunil , Irshad Lukman , Demirel H. Onan
Published: November 2018

Computational human factors tools are often not fully-integrated during the early phases of product design. Often, conventional ergonomic practices require physical prototypes and human subjects which are costly in terms of finances and time. Ergonomics evaluations executed on physical prototypes has the limitations of increasing the overall rework as more iterations are required to incorporate design changes related to human factors that are found later in the design stage, which affects the overall cost of product development. This paper proposes a design methodology based on Digital Human Modeling (DHM) approach to inform designers about the ergonomics adequacies of products during early stages of design process. This proactive ergonomics approach has the potential to allow designers to identify significant design variables that affect the human performance before full-scale prototypes are built. The design method utilizes a surrogate model that represents human product interaction. Optimizing the surrogate model provides design concepts to optimize human performance. The efficacy of the proposed design method is demonstrated by a cockpit design study.
Back to Basics: Sketching, Not CAD, Is the Key to Improving Essential Engineering Design Skills
Authors: Hilton Ethan C. , Gamble Taylor , Li Wayne , Hammond Tracy , Linsey Julie S.
Published: November 2018

The ability to visually communicate ideas and the willingness to generate free-hand sketches are critical skills for engineers. With the advent of CAD, schools no longer teach drafting, prompting a concern over the lost art of free-hand sketching. Recent empirical data from senior design indicates they do not sketch until forced to do so and this agrees with much anecdotal data. This paper describes a novel approach to teaching sketching in a freshman CAD course using an industrial design methodology during the first six weeks of the semester. As expected, sketching skills improved, but there was concern that this may be at the expense of spatial visualization skills typically taught through isometric drawing. Spatial visualization skills are critical for engineers and have been linked to success in engineering programs. The current study measured spatial visualization skills at three points during the freshman CAD course. The industrial design approach to perspective sketching led to significant improvements in spatial visualization scores that were not statistically different from the more traditional approach within engineering. Overall, it was the sketching portion, not the CAD, that significantly improved the students’ spatial visualization scores. Including free-hand sketching in engineering not only improves sketching ability, but also improves the spatial visualization skills crucial for success in engineering in a way that CAD alone does not.
Learning by Doing: A Simple Educational Method for Modelling Vehicle Suspensions
Authors: Kames Elisabeth , Thiess David , Morkos Beshoy
Published: November 2018

This paper examines the educational benefit of modeling and analyzing a quarter car suspension system to simulate the vehicle response to various road inputs. The response of the vehicle was considered both theoretically and experimentally. The primary goal of the study is to test the ability to integrate similar approaches in an educational setting to allow students to gain a “real world” perspective on their theoretical coursework. Typical engineering curriculum focuses heavily on theoretical computational models. However, some students have trouble relating this calculated data to practical occurrences. This paper outlines the challenges and considerations for implementing experimental procedures into common coursework to compare to theoretical calculated data.

For the theoretical model, the equation of motion of the dynamic response of the suspension system was obtained using Lagrange’s equation. Using a 2013 Jeep Wrangler Sport, the suspension spring constant, the tire spring constant, the tire damping coefficient, and the suspension damping coefficient were calculated or estimated experimentally (these parameters were used for both the theoretical and the experimental models). The combination of the MATLAB and Simulink files were used to produce visual representations of the response of the vehicle to road inputs.

The experimental model is obtained using a combination of MATLAB and accelerometer data. The 2013 Jeep Wrangler was exposed to three different real-world inputs: a step up, a step down, and a sinusoidal input (a speed bump). The experimental and theoretical data is compared to exhibit trends of the vehicle to these road inputs. While the models do not align numerically, the trends of the experimental and theoretical data are shown to coincide for each of the responses.

This paper will outline the quarter car model used and the mathematical model of it, the methods used to solve the model, the results obtained from the study, and the ability to integrate methods such as this into a classroom setting as a supplement.
Creep and Stress Relaxation Behavior of Homogeneous and Reinforced Compliant Mechanisms and Segments
Authors: Crews Joshua , Dharani Lokeswarappa R. , Midha Ashok
Published: November 2018

Two critical disadvantages of compliant mechanisms constructed of engineering plastics are poor creep and stress relaxation resistance. Metallic reinforcement is investigated as a method to improve the creep and stress relaxation behaviors of compliant mechanisms and compliant segments. The stress relaxation and creep behaviors of homogeneous compliant segments are compared to those of metallic reinforced compliant segments. Special specimens and fixtures were designed for conducting physical tests. Test results show that metallic reinforced compliant segments significantly outperform homogeneous compliant segments with respect to both creep and stress relaxation. This vein of research is undertaken using metallic reinforcement (inserts) toward the development of a new class of compliant mechanisms with significantly greater performance, particularly insofar as the problems of fatigue and creep are concerned.
Parameters Identification of the Path Placement Optimization Problem for a Redundant Coordinated Robotic Workcell
Authors: FarzanehKaloorazi Mohammad H. , Bonev Ilian A. , Birglen Lionel
Published: November 2018

This paper proposes a method to identify the number of independent parameters in order to optimize the placement of a given path for a coordinated redundant robotic workcell. The workcell consists of a generic 6 DoF serial manipulator and a 1 DoF redundancy provider (RP). The RP is not attached to the serial manipulator, but the workpiece is attached to the RP. Two cases of RPs are investigated, namely a rotary table and a linear guide. In general, 6 parameters are needed in order to place a path on the RP, and 6 parameters to place the RP in the workspace of the serial manipulator. However, because of the symmetricities and the degree of redundancy involved in the problem, not all 12 parameters can independently affect the placement operation. Therefore, it is important to identify the number of independent parameters in order to improve the efficiency of the placement optimization process. This paper presents an innovative method for determining the number of independent parameters for both cases under study, i.e., the rotary table and the linear guide, with and without considering each one’s joint limits. The optimization process is briefly introduced and the results of using all 12 parameters, as opposed to only the independent ones, are compared. Finally, the performance of the rotary table is compared to the linear guide, for a sample path.
Temperature Compensation in MEMS Capacitive Pressure Sensors for Harsh Environment Applications
Authors: Suthar Rahul Jitendrab , Shavezipur Mohammad
Published: November 2018

A novel design for MEMS capacitive pressure sensors is presented that can effectively eliminate the temperature drift in sensor for high temperature applications. The design uses a bilayer membrane made of a thin metal film deposited on the top of membrane to balance the deformation the membrane experiences when the ambient temperature changes. The thermal expansion mismatch of the metal layer and the membrane results in out-of-plane bending if the temperature changes. This deformation can compensate the deformation in the membrane due to the temperature change. By optimizing the dimensions of the top metal layer (shape and thickness), it is possible to minimize the change in the device capacitance due to temperature rise. A coupled-field multiphysics solver in ANSYS® APDL is used for design, simulation and optimization of the sensor’s structure and to solve the governing equations of the coupled electrostatic and structural physics. The membrane material is silicon carbide (SiC), the top metal layer is nickel (Ni) and the substrate is a single-crystal silicon wafer. The thickness and dimensions of top metal layer is optimized using FEM simulations. The results display a very stable capacitance value for a large pressure range and over a wide range of ambient temperature (0–600°C), demonstrating the proposed design can effectively eliminate the temperature effect. Different pressure values ranging from 0.0 to 20 bars have been examined in the simulations and for most of the pressure range, a highly stable capacitance value is observed with less than 0.5% error over 600 °C temperature range.
Design of a Compliant Mechanism to Generate an Arbitrary Nonlinear Force-Deflection Profile
Authors: Buschkoetter Kyle , Midha Ashok
Published: November 2018

This paper presents a compliant mechanism that can generate a wide range of force-deflection profiles. This partially compliant mechanism is comprised of a wedge cam with a compliant follower. The designer specifies the material and geometric properties of the compliant segment, as well as a desired force-deflection profile. A cam surface is then synthesized that helps generate this profile. The synthesis method is validated experimentally with the help of two case studies. Some possible areas of application include robotics, variable stiffness actuators, electrical connectors, design for automotive crashworthiness, and variable resistance exercise equipment.
Most Probable Point-Based Approximated Dimension Reduction Method in Reliability-Based Design Optimization
Authors: Jung Yongsu , Cho Hyunkyoo , Lee Ikjin
Published: November 2018

The conventional most probable point (MPP)-based dimension reduction method (DRM) and following researches show high accuracy in reliability analysis and thus have been successfully applied to reliability-based design optimization (RBDO). However, improvement in accuracy usually leads to reduction in efficiency. The MPP-based DRM is certainly better from the perspective of accuracy than first-order reliability methods (FORM). However, it requires additional function evaluations which could require heavy computational cost such as finite element analysis (FEA) to improve accuracy of probability of failure estimation. Therefore, in this paper, we propose MPP-based approximated DRM (ADRM) that performs one more approximation at MPP to maintain accuracy of DRM with efficiency of FORM. In the proposed method, performance functions will be approximated in original X-space with simplified bivariate DRM and linear regression using available function information such as gradients obtained during the previous MPP searches. Therefore, evaluation of quadrature points can be replaced by the proposed approximation. In this manner, we eliminate function evaluations at quadrature points for reliability analysis, so that the proposed method requires function evaluations for MPP search only, which is identical with FORM. In RBDO where sequential reliability analyses in different design points are necessary, ADRM becomes more powerful due to accumulated function information, which will lead to more accurate approximation. To further improve efficiency of the proposed method, several techniques, such as local window and adaptive initial point, are proposed as well. Numerical study verifies that the proposed method is as accurate as DRM and as efficient as FORM by utilizing available function information obtained during MPP searches.
A Buckling Flexure-Based Force-Limiting Mechanism
Authors: Slocum Jonathan T. , Kamrin Kenneth , Slocum Alexander H.
Published: November 2018

A force-limiting buckling flexure has been created which can be used in a wide array of applications where excessive force from an implement can cause harm or damage. The buckling flexure is monolithic, contains no electronics, and can be manufactured using a single shot in an injection molding machine, making it extremely cost effective. In this paper, the design of this flexure is applied to a force-limiting toothbrush as an example of how this buckling flexure may be applied in a real-world technology. An overview of the buckling flexure is presented, and a structural model is shown to predict when the flexure will elastically buckle. This model is compared to data collected from flexures fabricated with varying buckling beam thickness. The data show that the force to buckle the flexure when applied at the tip can be predicted to within 20.84%. Furthermore, a preliminary model is presented which enables design of the buckling beam’s displacement, such that the total breakaway deformation can be maximized, making sensing the sudden deformation easier. As part of the application of the buckling flexure, an ergonomic, injection moldable toothbrush was created with the flexure built into the neck of the brush. When the user applies too much force while brushing, the flexure gives way and alerts the user when they have applied too much force and when the user lets off the force, the brush snaps back to its original shape. This design methodology is generalized and can be utilized in other force limited applications where an injection moldable, pre-set force, purely mechanical breakaway device is desired.
A Large Range Spatial Linear Guide With Torsion Reinforcement Structures
Authors: Rommers J. , Naves M. , Brouwer D. M. , Herder J. L.
Published: November 2018

Flexure mechanisms are popular in the precision engineering field due to their highly repeatable behavior. However, implementations are limited to small range of motion applications. In this paper, a spatial linear guide with a range comparable to the size of its footprint is presented. The design is based on two novel ‘Triflex’ elements in which torsion reinforcement structures are used to decrease build volume and increase guiding stiffness. The mechanism is compared to a common linear guide consisting of six folded leaf springs, after optimizing both designs. The novel linear guide shows better guiding stiffness performance, while occupying a smaller and less obstructive build volume.
Prototyping Electrostatic Scanning Force Microscope
Authors: Nafissi Hamidreza , Mansour Raafat , Abdel-Rahman Eihab M.
Published: November 2018

A scanning force microscope combining commercial AFM probes, printed circuit boards, and electrostatic actuation and detection is proposed and demonstrated. The electrostatic actuator is formed by the AFM probe and a fixed trace on a PCB. It is driven by a biased harmonic voltage with a frequency close to the probe’s resonant frequency. The separation distance between the probe tip and the specimen surface is managed to perform tapping mode scanning. A lock-in amplifier measures the second harmonic of the actuator current as the sense signal in an open-loop scheme. Preliminary results produced by the current’s magnitude and phase resemble the specimen’s topography.
Development of Seated Human Model With Uncertain Parameters and Estimation of the Ride Comfort
Authors: Bae Jong-Jin , Kang Namcheol
Published: November 2018

This study deals with the biodynamic responses of the 5-degree-of-freedom mathematical human model to whole-body vibrations in a vehicle. The nonlinear equations of motion of the human model were derived, and the spring constants and damping coefficients were extracted from the experimental data in the literature using optimization process. The natural frequencies and mode shapes were also calculated using linearized human model. In order to examine the effects of the variations of the human parameters, the parametric studies with respect to the stiffness values were performed. The mode veering phenomenon was observed between fourth and fifth mode of the linearized human model. In addition, the frequency responses of the nonlinear 5-degree-of-freedom model were also obtained, and the frequency shift and jump phenomena were observed. Furthermore, the estimation of the ride comfort was performed using CarSim and Matlab/Simulink with several road profiles according to ISO classification. Besides, we also calculated the ride comfort index using BS 6841 standard. In order to calculate the statistical responses of human model, the Monte-Carlo simulation applied to the nonlinear human model having uncertain stiffness assuming Gaussian distribution. These stochastic approaches enable the proposed human model to estimate probability distributions of the ride comfort index.
The Benefits and Challenges of Kinesiology as a Pre-Allied Health Degree
Authors: Brusseau Timothy A.
Published: November 2018

This paper discusses some of the benefits and challenges of Kinesiology as a pre-allied health degree. Specifically, it highlights the impact of large enrollment growth on resources, course offerings, student experiences, student quality, and research. It is the author’s intent that this paper will stimulate discussion among Kinesiology programs and faculty to ensure that we are staying true to the recommended Kinesiology core and preparing our students to be future physical activity leaders while also providing the flexibility for students who are interested in pursuing graduate training in an allied health field.
Development, Management, and Evaluation of Undergraduate Experiential Learning: Recommendations for Best Practices
Authors: Pangelinan Melissa , Norcross Marc , MacDonald Megan , Rudisill Mary , Wadsworth Danielle , McDonald James
Published: November 2018

Experiential learning provides undergraduate students rich opportunities to enhance their knowledge of core concepts in kinesiology. Beyond these outcomes, it enables students to gain exposure to, build empathy for, and affect the lives of individuals from diverse populations. However, the development, management, and systematic evaluation of experiential learning vary drastically across programs. Thus, the purpose of this review was to critically evaluate the experiential-learning programs at Auburn University and Oregon State University with respect to best practices outlined by the National Society for Experiential Education. The authors provide examples of lessons learned from these two programs to help others improve the implementation and impact of undergraduate experiential learning.
China fosters competition in its race to exascale computing
Authors: Normile Dennis
Published: November 2018

Three teams are developing prototypes using Chinese chips.
Restoring lost grazers could help blunt climate change
Authors: Pennisi Elizabeth
Published: November 2018

Rewilded landscapes could be cooler, less fire prone.
Molecular CT scan could speed drug discovery
Authors: Service Robert F.
Published: November 2018

Structure mapping works with vanishingly small samples in just minutes.
The political legacy of slavery
Deep Roots: How Slavery Still Shapes Southern Politics
Avidit Acharya, Matthew Blackwell, Maya Sen
Princeton University Press, 2018. 296 pp.
Authors: Spry Amber
Published: November 2018

Racial tension continues to influence political attitudes in U.S. regions that once depended on slave labor
The chromatin of cancer
Authors: Taipale Jussi
Published: November 2018

Understanding tumorigenesis and inherited risk for cancer requires a multiomic approach
Developing combination immunotherapies against cancer that make sense
Authors: Veillette André , Davidson Dominique
Published: November 2018

Mechanistic preclinical studies reveal that combination immunotherapies targeting PD-1 and GITR may demonstrate synergy in human cancer. See related Research Article by

Wang
et al
.
Lumbopelvic pain, anxiety, physical activity and mode of conception: a prospective cohort study of pregnant women
Authors: Lardon Emeline , St-Laurent Audrey , Babineau Véronique , Descarreaux Martin , Ruchat Stephanie-May
Published: November 2018

Objectives

Pregnancy-related lumbopelvic pain (LPP) is a frequent condition known to significantly affect women in their daily life. The aetiology of pregnancy-related LPP pain is still not clearly established but the mode of conception has been suggested to contribute to LPP. Anxiety related to fertility treatments may be one of the contributing factors. The primary objectives of this study were to determine the evolution of LPP prevalence and severity, and anxiety throughout pregnancy in women who conceived spontaneously (SP) or after fertility treatments (FT). A further aim was to examine the relationship between pregnancy-related LPP severity and anxiety. The secondary objective was to determine the evolution of physical activity and their correlation with the severity of pregnancy-related LPP.

Design

Prospective cohort study.

Setting

Pregnant women were recruited through physicians’ referrals, posters and newspaper advertisements in the local and surrounding communities (hospital, maternity care clinic, prenatal centres, sports centres, local university) in the city of Trois-Rivières, Canada.

Participants

59 pregnant women (33 SP and 26 FT) were assessed during the first, second and third trimester of pregnancy.

Primary and secondary outcome measures

Pregnancy-related LPP prevalence and severity (primary), trait and state anxiety, and physical activity levels (secondary).

Results

There was no relationship between the mode of conception and the outcome measures. The prevalence and severity of LPP increased over the course of pregnancy (time effect, p<0.0001) whereas trait anxiety decreased from early to mid-pregnancy (time effect, p=0.03). Activity limitations increased throughout pregnancy (time effect, p<0.0001) and physical activity levels decreased (time effect, p<0.0001). The severity of LPP was positively correlated with activity limitations (r=0.51 to 0.55) but negatively with physical activity levels (r=−0.39 to −0.41).

Conclusions

Maternal health-related factors, such as LPP, anxiety and physical activity, are not different in women who conceived spontaneously or after fertility treatments. The more LPP was severe, the more the women were physically limited and inactive.