bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Team Size on Problem-Solving and Solution Quality: An Empirical Study
Authors: Jacobs Seth , Pfarr Matthew , Fazelpour Mohammad , Koroma Abdul , Mesfin Tseday
Published: November 2019

The size of a team can affect how they tackle a design problem and solution quality. This paper presents a protocol study of the impact of team size on problem-solving and design solution quality. The protocols are coded with micro-strategies, and macro-strategies, and final solutions are scored using a rubric of meeting constraints, manufacturability, feasibility, and cost. The results show that the larger design team sizes analyze design solutions more frequently and propose solutions less than the smaller design teams. Among the three team sizes of 1, 3, and 5, the teams of three designers scored the best on final designs. These teams used a fair amount of both proposing solutions and analyzing solutions of micro-strategies. The teams of 5 designers use backtracking macro-strategies more frequent than teams of 3 and one because as the team size increases, more time is spent among team members to discuss previous ideas.
A Proposed Hybrid Laser Quenching Process, and Investigation of its Three-Dimensional Forming Error
Authors: Nishida Hiromichi , Manabe Yuki , Hirogaki Toshiki , Aoyama Eiichi
Published: November 2019

In this research, we focus on heat treatment, specifically during the downsizing of production systems. We devise a method designed to remedy the problem of quenching for thin plates, by using a small semiconductor laser. In this report, we investigated a method to reduce the influence, deformation amount, and three–dimensional (3D) distortion error of residual stress that occurred when a laser test was performed on a metal test piece. Regarding the residual stress, the specimen was burned out by continuous scanning. Its residual stress showed a tendency to fade as the specimen was scanned at lower speeds. We found it was possible to reduce deformation by restraining the specimen with the jig, but that 3D strain error under this constrained state remained of the same order as it was in the unconstrained state. In addition, by restraining the test piece with a jig, it was possible to prevent reverse deformation (Buckling Mechanism).
Exhaustive Synthesis and Analysis of Automotive 2-Stage Planetary Transmission Designs
Authors: Karhula Henri , Nicolai Mike , Desmet Wim
Published: November 2019

Most modern automatic automotive transmissions are complex mechanical systems composed of multiple planetary gearsets that are connected by shafts, clutches and brakes. Creating a design that supports the desired transmission ratios while requiring a minimal amount of components is a challenging task that is commonly tackled by an engineer with experience and intuition.

This paper introduces an approach for the exhaustive synthesis of automotive transmissions composed of two planetary gearsets, two clutches and two brakes that can be deployed in automotive drivetrains. By modeling the components of an automotive transmission based on their possible mechanical connections and additional user-defined specifications a constraint satisfaction problem is derived. An iterative solving process exhaustively generates all possible transmission design with the specified set of components. Further the generated designs are filtered and analyzed such that the designer is served only with unique, valid and useful transmission designs. Finally a set of generated, novel 4-speed transmission designs is presented.
A Shape Memory Alloy Driven Crawling Robot Utilizing a Bistable Mechanism
Authors: Meng Lingda , Kang Rongjie , Gan Dongming , Chen Guimin , Dai Jian S.
Published: November 2019

Shape memory alloys (SMA) can generate displacement and force via phase change and have been widely used as actuators in robotics due to their light weight and ease of control. This paper proposes a SMA-driven crawling robot which activates antagonistic SMA springs alternately through a mechanical on-off logic switching system. By introducing a cam based bistable mechanism, elastic energy is stored and released to regulate the reciprocating motion of a slider in the robot. Meanwhile, the robot feet with anisotropic friction surface are employed to convert the reciprocating motion of the slider to unidirectional locomotion of the robot. The static model of the SMA and control logic of the robot are analyzed and validated through experiments.
Effect of Rider Posture on Bicycle Comfort
Authors: Polanco Alejandra , Marconi Edoardo , Muñoz Luis , Suárez Daniel , Doria Alberto
Published: November 2019

Cyclists are exposed to vibration due to road roughness. The levels of vibration that the cyclists experience have a major effect on comfort and depend on the bicycle, rider and road characteristics. It is known that the posture of the cyclist has a relevant effect on the bicycle-cyclist system vibration response. Nevertheless, this effect has been scarcely quantified. This study focuses on the measurement of the effect of body posture on comfort while riding a bicycle.

A laboratory methodology based on the measurement of the impulsive response of sensitive points of the bicycle was implemented to predict the comfort of cyclists on the road. The posture on the sagittal plane was verified during the tests. The methodology was implemented to predict the comfort of two cyclists riding a city bicycle in two postures: upright and bent forward.

Experimental results showed that in the bent forward posture the acceleration levels had a significant increment for the handlebar stem and a non-significant increment for the seatpost.
Stochastic Simulation of Turbine Engine Component Under Aleatory and Epistemic Uncertainty
Authors: McKeand Austin M. , Gorguluarslan Recep M. , Choi Seung-Kyum
Published: November 2019

Quantifying the uncertainty associated with material properties in engineering analysis has become more important in the design of many components in the aerospace field. In this study, a new method is proposed to account for the uncertainty associated with the elastic modulus of materials used in aerospace components. A computerized tomography (CT) scanner is used to capture the porosity of the material and the corresponding uncertainty is represented with epistemic uncertainty. A stochastic upscaling method is used to find a homogenized modulus that correctly reflects the effect of defects inside of the material. This homogenized elastic modulus is then applied to a constructed finite-element model of an aerospace component so that the stochastic behavior can be correctly quantified. Simulations of the selected example, i.e., turbine blade, include both aleatory and epistemic uncertainty; thus, a P-Box is introduced to represent the response of the simulations. The stochastic upscaling method is applied again to match the P-Box response of the coarse scale model to that of the fine scale model. The obtained results show that the proposed framework not only significantly reduces complexity of the given engineering problem, but also produces accurate results which include both aleatory and epistemic uncertainty.
Computational Design of a Personalized Artificial Spinal Disc With a Data-Driven Design Variable Linking Heuristic
Authors: Yu Zhiyang , Shea Kristina , Stanković Tino
Published: November 2019

A personalized, 3D printed, multi-material artificial spinal disc is expected to not only achieve personalized anatomical fit, but also to restore the natural mechanics of the implanted spinal segment. However, the necessary structure for disc design is not explored and optimizing the design is challenging due to the high-dimensional search space provided by the material distribution precision of multi-material 3D printing as well as necessary nonlinear finite element simulation. Therefore, this study explores the feasibility of two multi-material spinal disc designs and a clustering-based design variable linking method to achieve efficient and effective optimization. The optimization goal is to enable the implant to have natural stiffnesses for five loading cases. The results show that a biomimetic fiber network is necessary for the disc design. Moreover, the optimization performance of the heuristic derived from a clustering-based method is shown to be a good trade-off between the objective function value and the computational time.
Design of a Triad-Pod Kinematic Flexure Mount for a Primary Mirror in Space Telescope at Cryogenic Temperature
Authors: Huo Tonglong , Yu Jingjun , Zhao Hongzhe
Published: November 2019

The paper mainly proposed a novel kinematic triad-pod flexure mount for supporting a primary mirror in space. This kind of mount is constructed by three identical pods, each of them is consisted of four rotation flexures with virtual rotation center. The mount can realize great releasement of thermal stress effect on primary mirror caused by CTE (Coefficient of Thermal Expansion) mismatch between baseplate and mirror at cryogenic temperature. Based on principles of kinematic design, the paper firstly proposes a mount configuration with three pods arranged with inclined angle. Then, the structure of pod is designed in detail, and compliance model is established. A study case is employed to illustrate how to design a triad-pod mount with higher supporting stiffness and large radialcompensate compliance. Finally, simulations by FEM are implemented to verify and analyze the performances of the proposed mount. The results demonstrate that the mount can further reduce the thermal stress in primary mirror while maintaining nearly indistinctive supporting stiffness than traditional three-bipod mount. Hence, the proposed mount can provide foundation to achieve a mount with greater performances for supporting a large-aperture mirror at a wider range of temperature.
A Novel Hierarchical Framework for Uncertainty Analysis of Multiscale Systems Combined Vine Copula With Sparse PCE
Authors: Xu Can , Liu Zhao , Tao Wei , Zhu Ping
Published: November 2019

Uncertainty analysis is an effective methodology to acquire the variability of composite material properties. However, it is hard to apply hierarchical multiscale uncertainty analysis to the complex composite materials due to both quantification and propagation difficulties. In this paper, a novel hierarchical framework combined R-vine copula with sparse polynomial chaos expansions is proposed to handle multiscale uncertainty analysis problems. According to the strength of correlations, two different strategies are proposed to complete the uncertainty quantification and propagation. If the variables are weakly correlated or mutually independent, Rosenblatt transformation is used directly to transform non-normal distributions into the standard normal distributions. If the variables are strongly correlated, multidimensional joint distribution is obtained by constructing R-vine copula, and Rosenblatt transformation is adopted to generalize independent standard variables. Then the sparse polynomial chaos expansion is used to acquire the uncertainties of outputs with relatively few samples. The statistical moments of those variables that act as the inputs of next upscaling model, can be gained analytically and easily by the polynomials. The analysis process of the proposed hierarchical framework is verified by the application of a 3D woven composite material system. Results show that the multidimensional correlations are modelled accurately by the R-vine copula functions, and thus uncertainty propagations with the transformed variables can be done to obtain the computational results with consideration of uncertainties accurately and efficiently.
Design and Analysis of Synchronous Joint for SAR Antenna Deployable Mechanism
Authors: Li Duanling , Dong Kaijie , Wang Xingze , Li Biao , Su Zhou
Published: November 2019

Synchronous joints are an important part of the SAR antenna deployment mechanism. They are the key to the synchronized deployment of antenna. By means of mechanism combination and deformation, a new type of synchronous joint with a precise cable drive system is designed in order to meet the requirements of SAR antenna deployment mechanism. This study mainly focuses on the design of the synchronous joint, including the system design and the precise cable drive system design. By applying a preload to the drive cable, the transmission gap is reduced, and the accuracy and efficiency of transmission are improved.

This paper focuses on the theoretical calculation and analysis of the preload and system stiffness of the precise cable drive system. Based on the Euler equation of the flexible friction drive, the stiffness formula of the cable drive system is derived. In addition, the main design parameters affecting the stiffness of the cable drive system are analyzed parametrically.

The comparison between the results obtained from the system stiffness experiment and the theoretical calculation result indicates that the experimental values are slightly smaller than the theoretical values, and the trend of change is basically consistent. This experiment therefore verifies the validity of the stiffness calculation formula and theoretical analysis.
End-to-End Multi-Task Machine Learning of Vehicle Dynamics for Steering Angle Prediction for Autonomous Driving
Authors: Merrill Nicholas , Eskandarian Azim
Published: November 2019

The traditional approaches to autonomous, vision-based vehicle systems are limited by their dependency on robust algorithms, sensor fusion, detailed scene construction, and high-quality maps. End-to-end models offer a means of circumventing these limitations by directly mapping an image input to a steering angle output for lateral control. Existing end-to-end models, however, either fail to capture temporally dynamic information or rely on computationally expensive Recurrent Neural Networks (RNN), which are prone to error accumulation via feedback. This paper proposes a Multi-Task Learning (MTL) network architecture that leverages available dynamic sensor data as a target for auxiliary tasks. This method improves steering angle prediction by facilitating the extraction of temporal dependencies from sequentially stacked image inputs. Evaluations performed on the publicly available Comma.ai dataset show a 28.6% improvement in steering angle prediction over existing end-to-end methods.
Using Inertial Control to Improve Maneuverability of Propeller-Assisted Flapping Wing Aerial Vehicle
Authors: Holness Alex E. , Solheim Hannah , Bruck Hugh A. , Gupta S. K.
Published: November 2019

Biological creatures demonstrate tremendous feats of maneuverability and dexterity. Some of these feats are achieved by intelligent usage of mass and inertia. For example, lizards use their tail mass and inertia to change body pose during jumping to self-right in mid-air. In a similar fashion, having shown passive mass position effects during flight tests of both flapping only and propeller-assisted flapping platforms, usage of an actuated reaction mass is proposed as a means of improving the maneuverability of a propeller-assisted flapping wing aerial vehicle. A simplified model for equations of motion, utilized successfully for autonomous diving, is presented and adapted to describe the aerodynamic forces on the wings and other surfaces. A model to approximate the change in the center of mass to be used with the equations of motion is also described. A design using a linear actuator in concert with the platform battery as a reaction mass system was prototyped and flight tested. Using the prototype design, flight characteristics for improved maneuverability were demonstrated via both video footage and data gathered by an inertial measurement unit during the same flight.
Stress-Constrained Design of Functionally Graded Lattice Structures With Spline-Based Dimensionality Reduction
Authors: Zhang Jenmy Zimi , Sharpe Conner , Seepersad Carolyn Conner
Published: November 2019

This paper presents a computationally tractable approach for designing lattice structures for stiffness and strength. Yielding in the mesostructure is determined by a worst-case stress analysis of the homogenization simulation data. This provides a physically meaningful, generalizable, and conservative way to estimate structural failure in three-dimensional functionally graded lattice structures composed of any unit cell architectures. Computational efficiency of the design framework is ensured by developing surrogate models for the unit cell stiffness and strength as a function of density. The surrogate models are then used in the coarse-scale analysis and synthesis. The proposed methodology further uses a compact representation of the material distribution via B-splines, which reduces the size of the design parameter space while ensuring a smooth density variation that is desirable for manufacturing. The proposed method is demonstrated in compliance minimization studies using two types of unit cells with distinct mechanical properties. The effects of B-spline mesh refinement and the presence of a stress constraint on the optimization results are also investigated.
An Event Based Machine Learning Framework for Predictive Maintenance in Industry 4.0
Authors: Calabrese Matteo , Cimmino Martin , Manfrin Martina , Fiume Francesca , Kapetis Dimos , Mengoni Maura , Ceccacci Silvia , Frontoni Emanuele , Paolanti Marina , Carrotta Alberto , Toscano Giuseppe
Published: November 2019

Predictive Maintenance concerns the smart monitoring of machine to avoid possible future failures, since because it is better to intervene before the damage occurs, saving time and money. In this paper, a Predictive Maintenance methodology based on Machine learning approach is presented and it is applied to a real cutting machine, a woodworking machinery in a real industrial group, producing accurate estimations. This kind of strategy is important to deal with maintenance problems given the ever increasing need to reduce downtime and associated costs. The Predictive Maintenance methodology implemented allows dynamical decision rules that have to be considered for maintenance prediction using a combined approach on Azure Machine Learning Studio. The Three models (RF, GBM and XGBM) allowed the accurately predict machine down ever gripped bearing thanks to the pre-processing phases.
Vehicle-Terrain Interaction Simulation With Parallelized Multiscale Moving Soil Patch Model
Authors: Yamashita Hiroki , Chen Guanchu , Ruan Yeefeng , Jayakumar Paramsothy , Sugiyama Hiroyuki
Published: November 2019

Although many physics-based off-road mobility simulation models are proposed and utilized for vehicle performance evaluation as well as for understanding of tire-soil interaction problems, full vehicle simulation on deformable terrain requires addressing the computational complexity associated with the large dimensional physics-based terrain dynamics models for practical use. This paper, therefore, presents a hierarchical multiscale tire-soil interaction model that is fully integrated into parallelized off-road mobility simulation framework. In particular, a co-simulation procedure is developed for full vehicle simulation with multiscale terrain dynamics models by exploiting the moving soil patch technique. To this end, a detailed off-road vehicle simulation model is divided into five subsystems: a multibody vehicle subsystem and four tire-soil subsystems composed of nonlinear FE tires and multiscale moving soil patches. The tire-soil subsystems are interfaced with the vehicle subsystem by MPI through force-displacement coupling. It is demonstrated that the proposed framework allows for alleviating computational intensity of a full vehicle simulation that involves complex hierarchical multiscale terrain dynamics models by effectively distributing computational loads with co-simulation techniques.
Computing Robust Inverse Kinematics Under Uncertainty
Authors: Sinha Anirban , Chakraborty Nilanjan
Published: November 2019

Robotic tasks, like reaching a pre-grasp configuration, are specified in the end effector space or task space, whereas, robot motion is controlled in joint space. Because of inherent actuation errors in joint space, robots cannot achieve desired configurations in task space exactly. Furthermore, different inverse kinematics (IK) solutions map joint space error set to task space differently. Thus for a given task with a prescribed error tolerance, all IK solutions will not be guaranteed to successfully execute the task. Any IK solution that is guaranteed to execute a task (possibly with high probability) irrespective of the realization of the joint space error is called a robust IK solution. In this paper we formulate and solve the robust inverse kinematics problem for redundant manipulators with actuation uncertainties (errors). We also present simulation and experimental results on a 7-DoF redundant manipulator for two applications, namely, a pre-grasp positioning and a pre-insertion positioning scenario. Our results show that the robust IK solutions result in higher success rates and also allows the robot to self-evaluate how successful it might be in any application scenario.
Towards an Information Archetypes Framework: Exploring the Types of Information Used in Open Source Design Engagements
Authors: Yi Sue , Lumbard Kevin , Damen Nicole B. , Germonprez Matt , Toh Christine A.
Published: November 2019

Across disciplines such as software engineering to architectural design, it is well acknowledged that the different types of information employed during the design process impacts the potential of the final design. However, a lack of understanding exists about how designers utilize and navigate the abundance of complex information types, making it difficult to develop design methodologies that support the development of competitive products and services. As part of an ongoing effort to develop an Information Archetypes Framework, this study focuses on identifying the emergence of information dimensions and archetypes during decision making. This was accomplished through a detailed analysis of interviews with designers who engage in open source work as part of their employment. The findings of this study provide empirical evidence of the types of information used during the design process, validates existing information archetypes, and identifies new archetypes that emerge from co-occurring information dimensions.
Improved Surgical Robot Design Using a Novel Compliant Rolling-Contact Joint
Authors: Nelson Carl A. , Dempsey Cole A. , Brush Ethan R. , Laribi M. Amine
Published: November 2019

This paper presents an improved design concept for a surgical robot that contributes to improved human-robot interaction and precise positioning of surgical tools. Based on a spherical wrist design, the robot incorporates new human-safe features limiting its ability to apply excessive force and uses a novel adaptation of the compliant rolling-element (CORE) joint suitable for conical rolling surfaces. The proposed safety features aim to provide novel functionality by mechanically disengaging the drive in overload conditions. This approach avoids the necessity of force sensing and control to detect and compensate for unintended device collisions. Further, proof of concept of a novel compliant rolling-element joint is presented as a low-backlash alternative to bevel gear pairs for heightened precision in angular positioning.
Constructing Scissor-Like Structures and Parallelogram Linkages With 4-Crease Single-Vertex Flat-Foldable Rigid Origami and Their Thick-Panel Versions
Authors: Xing David , You Zhong
Published: November 2019

Scissor-like structures are commonly composed of two straight rigid supports in a crisscross pattern connected by a pivot at its point of intersection [1]. Opposite angles formed by the supports are equal regardless of the structure’s folded state. Parallelogram linkages have a similar property. Rigid origami can be used to create these structures by combining two identical copies of a 4-crease single-vertex flat-foldable rigid origami, a single 4C, to form a flat-foldable composite structure, a double 4C. In this paper, we prove mathematically that regardless of the folded state of a single-4C, its even dihedral angles are equal, and odd dihedral angles are equal. As a result, the double 4C consists of 2 scissor-like structures. A past method to prove these dihedral angle equalities requires a more complex approach involving rotation matrices using Denavit and Hartenberg parameters [2,3]. This paper will provide a more intuitive method that proves the same equalities. We will also show that a similar construction of the double 4C using thick-panel versions of the single 4C satisfies the same dihedral angle equalities necessary for the formation of parallelogram linkages. The construction of the double 4C can help design self-folding mechanisms and useful metamaterials.
A Proposal for a Decision Support Framework to Solve Design Problems in the Automotive Industry
Authors: Sissoko Timothé M. , Jankovic Marija , Paredis Christiaan J. J. , Landel Eric
Published: November 2019

Decision-makers often rely on heuristics and experience to make complex decisions in the industrial context. Often, integrating implicit or expert knowledge as well as uncertainties can lead to decisions that are not necessarily the best ones. Moreover, in engineering design, the decision-making approaches focus on the product itself and do not investigate the necessary effort that is needed to gather additional data in order to devise more precise decision-making models. In our research, we propose to integrate this estimation of additional effort needed for data gathering and decision-making refinement in order to support design teams. This research has been conducted in collaboration with a major car manufacturing company, and in particular in the development process through Modeling and Simulation. The objective is to propose a decision-making model that integrates data-gathering estimation, hence integrating also the estimation of postponing one decision. A decision problem model based upon expected utility combined with the value of information theory is proposed to address this issue. The model has been developed and tested on 4 case studies. We define a decision support framework by integrating the model into a tool and by proposing roles in the decision-making process. We finally present its application on a concrete example.
Dynamic Analysis of a Rotating Planar Timoshenko Beam Using an Accurate Global Spatial Discretization Method
Authors: Fan W. , Zhu W. D. , Zhu H.
Published: November 2019

A new formulation is developed for dynamic analysis of a rotating planar Timoshenko beam. The configuration of Timoshenko beam is described using its slope angle and axial and shear strains; hence, the shear locking problem can be naturally avoided. While six boundary conditions are needed for choices of trial functions of three dependent variables, there are only four boundary conditions that can be determined and two boundary conditions are undetermined. An accurate global spatial discretization method is used, where dependent variables are divided into internal and boundary-induced terms. Internal terms only need to satisfy homogeneous boundary conditions, which can be easily chosen as trigonometric functions. Boundary-induced terms are interpolated using dependent variables at boundaries that are taken as generalized coordinates. When the hub rotates at a constant angular velocity, nonlinear governing equations can be linearized for vibration analysis. Frequency veering and mode shift phenomena occur. Nonlinear dynamic responses of the system are then calculated and compared with those from the commercial software ADAMS, and they are in good agreement. Axial and shear strains of the beam and their spatial derivatives are also calculated. Since trial functions in the assumed modes method cannot satisfy undetermined boundary conditions, inaccurate results of strains and their spatial derivatives are obtained using the assumed modes method. Hence, use of the accurate global spatial discretization method in the current formulation is essential.
A Feasibility Study on the Benefits of Feedback Aerator Control in Precision Aquaculture Applications for the Developing World
Authors: Cruz Francis Cedric , Mahmudov Kamran , Marouchos Andreas , Bilton Amy
Published: November 2019

Aquaculture is a growing source of food and income for many in the developing world. In developing countries, where more than 18 million people engage in aquaculture, yields have been low due to lacking infrastructure. Aeration has been shown to improve dissolved oxygen (DO) and increase yields, but its use has been low in many developing world environments due to high operating costs. Even when used, they are operated in an ad-hoc manner, resulting in higher than required costs. A potentially more effective implementation is the use of feedback control to maintain adequate DO and increase energy savings. To demonstrate the potential, a feasibility study was conducted comparing the energy consumption of a diffused aeration system, with and without the use of a feedback control system. The effect of the diffused aeration system was simulated for a 100 m3 pond in Bangladesh for extensive and intensive fish farming. The interaction between the aerators and the pond was simulated on ANSYS FLUENT and was used with a DO model to predict the oxygen dynamics of the pond. Results indicated that the addition of a feedback control system could result in 78.66%, and 52.48% in energy cost savings compared to continuous operation for extensive and intensive fish farming respectively. Further work in smart instrumentation has the potential to decrease the energy requirements of aeration technologies and improve production for farmers in the developing world.
Kinematic Optimization of a 2-DOF U, 2PSS Parallel Wrist Device
Authors: Bajaj Neil M. , Dollar Aaron M.
Published: November 2019

The wrist plays the crucial role of orienting a hand or end effector without significant translational motion, a critical requirement of successful manipulation. In this paper, we present the kinematic design optimization a two degree of freedom universal, two-prismatic-spherical-spherical (U, 2-PSS) parallel wrist mechanism. By varying the geometric parameters of the mechanism, we examine configurations that maximize the Global Conditioning Index, a metric describing the quality of the motion and torque, over the desired workspace, which mimics a healthy human wrist range of motion in circumduction (flexion/extension and abduction/adduction). We further investigate the effects of sizing constraints on the resulting optimized design which satisfies the imposed sizing constraints.
Evaluation of the ISHM Method Applied for Composite Rotors
Authors: Tsuruta Karina M. , Rocha Lucas A. A. , Cavalini Aldemir Ap. , Finzi Neto Roberto M. , Steffen Valder
Published: November 2019

The use of SHM (structural health monitoring) techniques has shown promising results for fault detection in rotating machines, making possible to identify various malfunctions. SHM methods provide maintainability and safe operation for these systems. The objective of the present work is to evaluate the SHM method based on the electromechanical impedance (ISHM) to detect faults in a composite rotor shaft. Composite materials present complex damage mechanisms due to their anisotropy and heterogeneity. Moreover, the process of damage detection in these materials is more challenging than in metallic structures. The ISHM approach uses piezoelectric (PZT – Lead Zirconate Titanate) patches as sensors and actuators coupled to the monitored structure. Variations in their electrical impedance are associated with changes in the mechanical integrity of the system. The electrical impedance of the PZT sensor is directly related to the mechanical impedance of the structure, which changes according to variations in the mass, stiffness, and damping properties of the structure. Damage metrics are used to quantify variations in the electrical impedance (impedance signatures) of the PZT patches. Despite the ISHM approach be able to detect incipient faults, it presents some disadvantages. For instance, the impedance signatures are susceptible to temperature variation. In the present contribution, to detect damages in the considered composite rotor shaft, the ISHM technique was implemented based on a data normalization methodology. Thus, an optimization procedure based on hybrid optimization was used to avoid false diagnostics.
Experimental and Numerical Investigation of Residual Stress Stiffening Influence on Dynamic Response of Welded Structures
Authors: MajidiRad AmirHossein , Yihun Yimesker S.
Published: November 2019

This paper presents the study of welding residual stress-stiffening effect on the dynamic responses and vibrational parameters of welded aluminum parts through an experimental modal analysis and Center Hole Drilling (CHD) residual stress measurement methods. Having a great corrosion resistance, AA5056 was utilized in this research that has been used in aircraft and ship structures; making the welding assesment of crucial. Natural frequencies and damping factors of several specimens are compared before and after the welding along with verification of experimental modal analysis integrity using Euler-Bernoulli relations. Finite element modeling of welding, cutting and modal/stress analysis of samples are also done to compare the experimental results. The results obtained from the precise modal analysis of all samples show that welding made the structure harder leading to 2% increase in natural frequencies and changing damping factors of different mode shapes. Cutting also reduced the level of residual stresses up to 34%. A good agreement is shown between the modal analysis and the experimental results. The technique used in the experiment and finite element simulation along with modeling assumptions are beneficial to other applications where model updating is required or a prediction of residual stress stiffening influence on modal responses is important.
Approximate Force History Estimation in Multi-Point Non-Smooth Collisions
Authors: Chatterjee Abhishek , Bowling Alan , Ghaednia Hamid , Brake Matthew
Published: November 2019

Collisions between hard objects cause abrupt changes in the velocities of the system, which are characterized by very large contact forces over very small time-durations. A common approach in the analysis of such collisions is to describe the system velocities using an impulse-momentum based relationship. The time-duration of impact and the deformations at the contact points are usually assumed to be negligible in such impact models, and the system velocities are evolved in terms of the impulses on the system. This type of impact models are usually relevant for hard (rigid) impacts, where deformations at the contact points can be considered negligible. However, these models cannot determine the forces during the impact process. The main objective of this work is to reformulate the impulse-momentum based model to determine the forces during an impact event, by relaxing the rigidity assumption to allow small deformations at the contact points.
Study of Industry 4.0 and its Impact on Lean Transformation in Aerospace Manufacturing
Authors: James Sagil , Cervantes Alejandro
Published: November 2019

Lean manufacturing practices focus on minimizing all forms of waste from the production system. The applicability of lean manufacturing concepts and principles has often been questioned in sectors including aerospace manufacturing primarily due to their high variety - low volume environments. The key challenges include the difficulty in changing the factory layout, lack of plant-specific manufacturing strategies, lack of benchmarking between manufacturing plants and non-existence of learning through experimentation culture. Consequently, the aerospace manufacturing industries have struggled to implement lean principles over the years successfully. Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Applying the concepts of Industry 4.0 along with the conventional lean transformation technology could potentially address these challenges. The focus of this research is to study the possibilities of integrating Industry 4.0 tools with existing lean manufacturing philosophies within the aerospace manufacturing sector in order to improve various aspects of manufacturing processes in a cyber-physical environment. A case study is performed considering a quality inspection department in a typical aerospace industry. The case study is simulated using discrete event simulation tool — Arena. The study found that a hybrid approach involving the holistic merger of the lean principles along with the Industry 4.0 tools known as Lean Industry 4.0 is the best way forward for the aerospace manufacturing sector. The outcomes of this research provide an understanding of the role of industry 4.0 paradigm and their implementation in several other high-technology and high-risk manufacturing sectors including life sciences, space, and defense industries.
A Reliability Model Validation Method for Mitigating the Effects of Measurement Uncertainty
Authors: Sadoughi Mohammadkazem , Li Meng , Beck Joseph , Hu Chao
Published: November 2019

With the increasing role of numerical modeling in engineering design and development processes, improved techniques are needed for validating computational results against experimental measurements. Most existing validation methods suffer from two main limitations: (i) they are often highly sensitive to the experimental measurement uncertainty, and (ii) extending these methods for reliability model validation requires large quantities of failure data that may be very time-consuming or costly to obtain. In order to overcome the aforementioned limitations, this study proposes an indirect reliability model validation method. First, a new procedure for computing a validation metric is developed based on Richardson extrapolation (RE) to reduce the sensitivity of the metric to the experimental measurement uncertainty. Second, a new validation metric is defined based on the limit state function (LSF) approximation to extend numerical model validation to reliability model validation. The proposed method is illustrated by validating a reliability estimation model for a cantilever beam under a vertical load.
Self-Adapting Intelligent Battery Thermal Management System via Artificial Neural Network Based Model Predictive Control
Authors: Liu Yuanzhi , Zhang Jie
Published: November 2019

This paper develops a self-adaptive control strategy for a newly-proposed J-type air-based battery thermal management system (BTMS) for electric vehicles (EVs). The structure of the J-type BTMS is first optimized through surrogate-based optimization in conjunction with computational fluid dynamics (CFD) simulations, with the aim of minimizing temperature rise and maximizing temperature uniformity. Based on the optimized J-type BTMS, an artificial neural network (ANN)-based model predictive control (MPC) strategy is set up to perform real-time control of mass flow rate and BTMS mode switch among J-, Z-, and U-mode. The ANN-based MCP strategy is tested with the Urban Dynamometer Driving Schedule (UDDS) driving cycle. With a genetic algorithm optimizer, the control system is able to optimize the mass flow rate by considering several steps ahead. The results show that the ANN-based MPC strategy is able to constrain the battery temperature difference within a narrow range, and to satisfy light-duty daily operations like the UDDS driving cycle for EVs.
Data-Centric Mixed-Variable Bayesian Optimization for Materials Design
Authors: Iyer Akshay , Zhang Yichi , Prasad Aditya , Tao Siyu , Wang Yixing , Schadler Linda , Brinson L. Catherine , Chen Wei
Published: November 2019

Materials design can be cast as an optimization problem with the goal of achieving desired properties, by varying material composition, microstructure morphology, and processing conditions. Existence of both qualitative and quantitative material design variables leads to disjointed regions in property space, making the search for optimal design challenging. Limited availability of experimental data and the high cost of simulations magnify the challenge. This situation calls for design methodologies that can extract useful information from existing data and guide the search for optimal designs efficiently. To this end, we present a data-centric, mixed-variable Bayesian Optimization framework that integrates data from literature, experiments, and simulations for knowledge discovery and computational materials design. Our framework pivots around the Latent Variable Gaussian Process (LVGP), a novel Gaussian Process technique which projects qualitative variables on a continuous latent space for covariance formulation, as the surrogate model to quantify “lack of data” uncertainty. Expected improvement, an acquisition criterion that balances exploration and exploitation, helps navigate a complex, nonlinear design space to locate the optimum design. The proposed framework is tested through a case study which seeks to concurrently identify the optimal composition and morphology for insulating polymer nanocomposites. We also present an extension of mixed-variable Bayesian Optimization for multiple objectives to identify the Pareto Frontier within tens of iterations. These findings project Bayesian Optimization as a powerful tool for design of engineered material systems.
Does Visual Fixation Affect Idea Fixation?
Authors: Kwon E. , Ryan J. D. , Bazylak A. , Shu L. H.
Published: November 2019

Divergent thinking, an aspect of creativity, is often studied by measuring performance on the Alternative Uses Test (AUT). There is however a gap in creativity research concerning how visual stimuli on the AUT are most effectively perceived. Research in memory and attention have used eye-tracking studies to reveal insights into how people think and perceive visual stimuli. Thus, the current work uses eye tracking to study how eye movements are related to creativity.

Participants orally listed alternative uses for twelve objects, each visually represented for two minutes in four different views. Using eye tracking, we specifically explored where and for how long people fixate their eyes at objects during the AUT. Eye movements before and while naming alternative uses are studied.

Results revealed that naming new instances and categories of alternative uses correlates more strongly with visual fixation towards multiple views than towards a single view of the object. Alternative uses in new, previously unnamed categories are also more likely named following increased visual fixation towards blank space. These and other findings reveal the cognitive-thinking styles and eye-movement behaviors associated with finding new ideas. Such findings may be applied to reduce fixation to existing ideas during design.
The Study of Magnetorheological Elastomer Based on Natural Rubber (NR)/Polybutadiene Rubber (BR) Hybrid Matrix: Experimental and Numerical Simulation
Authors: Song Xincheng , Wang Wenju , Yang Fufeng , Wang Guoping , Rui Xiaoting
Published: November 2019

Magnetorheological elastomer (MRE) is a new kind of smart materials whose mechanical properties can be controlled under external magnetic field and it is mainly consist of matrix materials and magnetic particles. In this work, the natural rubber (NR)/polybutadiene rubber (BR) hybrid matrix based MRE were prepared and the compatibility of NR and BR were studied. The hybrid matrix was prepared by physical mixing method. The characterization results showed that the BR had excellent compatibility with NR. The measurement result using rheological showed that the MR effect can be increased to 44.19% by adding of BR. The dynamic thermomechanical analysis showed that the hybrid matrix formed a homogeneous system when the ratio of BR and NR is 1/9 and 3/7. The particles was mixed with matrix using physical technology. The process of mixing was analyzed by numerical simulation. The simulation result showed that the increase of diameter of particles would increase the temperature and velocity of matrix in mixing. The particles was distributed evenly at enough mixing time and the mixing time was decreased with the diameter of particles.
Surrogate Models for the Efficient Estimation of Residual Fields Associated With Additively Manufactured Parts
Authors: Iliopoulos Athanasios P. , Steuben John C. , Apetre Nicole A. , Michopoulos John G.
Published: November 2019

Computing residual field distributions resulting from the thermomechanical history and interactions experienced by materials build by additive manufacturing (AM) methods, can be a very inefficient and computationally expensive process. To address this issue, the present work proposes and demonstrates a data-driven surrogate modeling approach that does not require solving the thermal-structural simulation of the AM process explicitly. Instead, it introduces the employment of various types of physics-agnostic surrogate models that are trained to data produced by full order physics-informed models. This enables to efficiently predict the resulting residual fields (e.g. distortions and residual stress) throughout the entire component. More specifically, two types of surrogate models for two different requirements scenarios are selected for the proposed work: Non-Uniform Rational B-Splines (NURBs) for a regularly sampled parametric space and k-simplex interpolants approach based on a two-step 3 + 1 dimensional interpolation that can operate on irregularly sampled spaces and grids. It is demonstrated that both methodologies can operate with low error and high performance (solution can be obtained within a few seconds on a desktop computer) on additively manufactured components of complex geometries.
Dynamic Modelling of a Planar Parallel Robot Manipulator Using the Discrete Time Transfer Matrix Method
Authors: Chu Mengqiu , Si Guoning , Zhang Xuping , Li Haijie
Published: November 2019

This paper aims to develop a new computationally efficient method for the dynamic modelling of a Planar Parallel Manipulator (PPM) based on the Discrete Time Transfer Matrix Method (DT-TMM). In this preliminary work, we use a 3-PRR PPM as a study case to demonstrate the major procedures and principles of employing the DT-TMM for the dynamic modelling of a PPM. The major focus of this work is to present the basic principles of the DT-TMM for the dynamic modelling of a PPM: decomposing the whole parallel manipulator to the individual components, establishing the dynamics of each component/link, linearizing the component/element dynamics to obtain the transfer matrix of each component/link, and assembling the component dynamics into the system dynamics of the PPM using the transfer matrices of all components/elements. To make the work more readable, the brief introduction of the inverse kinematics and the inverse dynamics is also included. The numerical simulations are conducted based on the 3-PRR PPM with rigid links in this preliminary research effort. The simulation results are compared with those from the model using the principle virtual work method and ADAMS software. The numerical simulation results and comparison demonstrate the effectiveness of the dynamic modelling method using DT-TMM for the PPM.