bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Temperature Dynamic Mechanical Properties Characterization of Polymer Coatings via Nanoindentation
Authors: Matsuda Yusuke , Samadi-Dooki Aref , Cen Yinjie , Vasquez Gisela , Bu Luke
Published: November 2021

Polymer coatings are widely used in industrial applications. The mechanical properties of these polymer coatings are known to vary with temperature and deformation rate. The characterization of the dynamic mechanical properties of these coatings at high temperatures via traditional uniaxial testing is challenging often due to their brittleness and small size. In this paper, the mechanical properties of polymer coatings are reported with emphasis on their dynamic mechanical properties at temperatures up to 280 °C characterized by a dynamic nanoindentation technique with a sharp indenter tip. Nanoindentation was used to characterize the mechanical response with emphasis on dynamic mechanical properties of polymer coatings enclosed in a high-temperature stage. To verify the method, the viscoelastic properties of a reference polyethylene terephthalate polyester film were also characterized by uniaxial cyclic tensile testing which exhibited an excellent agreement with the proposed technique. The proposed nanoindentation method can be applied to other polymer coatings and thin films that are used in applications at high temperatures.
Experimental Study of the Sealing Performance of Metal on Polymer Conical Seals
Authors: Goltsberg R. , Gilad M.
Published: November 2021

This study describes an experimental investigation of the sealing performance of a metallic conical poppet and a polymeric annular seat with a round sealing edge. The experiments were carried out with nitrogen. The influence of the radius of the sealing edge and its surface roughness, on the sealing performance, is evaluated. Generally, it was found that for a given load, as the radius of the edge decreases, the maximum contact pressure increases, and the sealing performance improves. In addition, a lower surface roughness yielded better sealing for a given load. Surprisingly, a range of radii was identified where a smaller radius would have worse sealing compared to a larger radius under the same maximum contact pressure. It is suggested that this is due to a secondary effect of the sealing width on the sealing performance. It was shown that the contact width is influential only for relatively low loads, while for higher loads, the main contributors are the maximum contact pressure and surface roughness. This can imply that for a limited range of compressive loads, an optimal radius of the sealing edge exists, for best sealing performance.
Enhanced Thermal Conductivity of Composite Materials by Filling Sheet and Fiber Under Effect of Filler Contact
Authors: Wang Xiaojian , Wang Liangbi
Published: November 2021

The most common nongranular fillers are sheet and fiber. When they are distributed along the heat flux direction, the thermal conductivity of the composite increases greatly. Meanwhile, the filler contact also has a large effect on the thermal conductivity. However, the effect of filler contacts on the thermal conductivity of the composite with directional fillers has not been investigated. In this paper, combined effects of the filler contact, content, and orientation are investigated. The results show that the effect of filler orientations on the thermal conductivity is greater than filler contacts in the low filler content, and the exact opposite in the high filler content. The effect of filler contacts on fibrous and sheet fillers is far greater than cube and sphere fillers. This rule is affected by the filler contact. The filler content of 8% is the ideal percolation threshold of composites with fibrous and sheet fillers. It is lower than cube filler and previous reports. The space for the thermal conductivity growth of composites with directional fillers is still very large. The effect of the interfacial thermal resistance should be considered in predicting the thermal conductivity of the composite under high interfacial thermal resistances (>10−4).
Boosting the Model Discovery of Hybrid Dynamical Systems in an Informed Sparse Regression Approach
Authors: Novelli Nico , Lenci Stefano , Belardinelli Pierpaolo
Published: November 2021

We present an efficient data-driven sparse identification of dynamical systems. The work aims at reconstructing the different sets of governing equations and identify discontinuity surfaces in hybrid systems when the number of discontinuities is known a priori. In our approach, we first focus to identify the switches between the separate vector fields. Then, the dynamics among the manifolds are regressed by making use of the model discovery algorithm of Brunton et al. [1]. The reconstruction of the discontinuity surfaces comes as the outcome of a statistical analysis implemented via symbolic regression with small clusters (micro-clusters) and a rigid library of models. This allows to identify all the many possible switch points that are clustered to determine the actual discontinuity surfaces. The performances of the method are tested on two numerical examples, namely, a canonical spring–mass hopper and a free/impact electromagnetic energy harvester. These applications are characterized by the presence of a single and double discontinuity, respectively. The analyses demonstrate that in the supervised approach, i.e. where the number of discontinuities is preassigned, we are capable to determine accurately both discontinuities and set of governing equations. It is found a great improvement in time of computation reaching the maximum achievable reliability that outperform existing data-driven identification approaches for hybrid systems.
Generative Optimization for Automatic Creation of 3D CAD Platforms
Authors: Quintero-Restrepo William F. , Smith Brian K. , Ma Junfeng
Published: November 2021

The efficient creation of 3D CAD platforms can be achieved by the optimization of their design process. The research presented in this article showcases a method for allowing such efficiency improvement. The method is based on the DMADV six sigma approach. During the Define step, the definition of the scope and design space is established. In the Measure step, the initial evaluation of the platforms to be improved is done with the help of a Metrics framework for 3D CAD platforms. The Analyze Step includes the identification and optimization of the systems’ model of the process based on the architecture and the multiple objectives required for the improvement. The optimization method used that is based on evolutionary algorithms allows for the identification of the best improvement alternatives for the next step. During Design step of the method, the improvement alternatives are planned and executed. In the final Verification step, the evaluation of the improved process is tested against the previous status with the help of the Metrics Framework for 3D CAD platforms. The method is explained with an example case of a 3D CAD platform for creating metallic boxes for electric machinery.
Fractional Order Filter Discretization With Marine Predators Algorithm
Authors: Ates Abdullah , Chen YangQuan
Published: November 2021

In this study, discrete time models of continuous time fractional order filters are obtained by using the Marine Predators Algorithm (MPA).

Marine Predators optimization algorithm is a population-based heuristic method. This method is inspired by the hunting behavior of marine predators. The algorithm works on three basic phases. These phases occur according to the difference or equality of the velocity of the prey and the predator. As it is known, uniform distribution is generally used in stochastic based optimization algorithms. However, in the MPA method, Brownian and Levy distributions are also used as well as uniform distribution.

First, continuous time frequency responses of fractional order filters are generated. Then, fourth order discrete time filters are designed that can give similar responses with generated continues time filter frequency responses. Ten parameters were optimized for the design of fourth order discrete time filters numerator and denominator. The Marine Predators method’s results are compared with the results of the Fractional order Darwinian Particle Swarm Optimization (FODPSO) algorithm, from which discrete time filters are obtained for two fractional order continuous time filter models. In this way, it has been shown comparatively that the Marine Predators Algorithm can be used in real engineering problems and can do filter discretization better.
Printability and Fidelity of Protein-Enriched 3D Printed Foods: A Case Study Using Cricket and Pea Protein Powder
Authors: Chirico Scheele Stefania , Hoque Mohammed Naimul , Christopher Gordon , Egan Paul F.
Published: November 2021

3D food printing has received high attention in personalized meal production and customized food designs in recent years due to its potential advantages over traditional food manufacturing methods. A current challenge in 3D food printing is the design of extrudable food materials that enable customized shape fabrication and retention. Additives such as starches and gums have been employed to improve food printability, however, these often detrimentally affect taste, texture, and nutrients. Our study explores the printability and shape fidelity of mashed potatoes when adding protein-rich cricket and pea protein powders. Different percentages of these additives (5%, 15%, and 30%) with varied water to protein ratios (0, 1, 2, and 3) were added to 100g of mashed potatoes. Mashed potatoes with the addition of cricket powder and pea powder provided the highest fidelity prints for water to additive ratios of 2 and 3, respectively. Rheological testing demonstrated these high-fidelity prints had complex modulus values ranging from 15Pa to 25Pa. Trade-offs were explored between print fidelity, complex modulus, and protein content for mashed potatoes with cricket protein that highlighted the relative trade-offs in 3D food printing recipes. These findings demonstrate that a design space including shape fidelity, printability, and nutritional profile provides rich trade-offs for promoting user satisfaction and health, thereby providing designers new opportunities to leverage 3D food printing to provide value for consumer needs and health.
Learning From Insects to Increase Multi-Agent System Resilience: Functional Decomposition and Transfer to Support Biologically Inspired Design
Authors: Hernandez Isabella V. , Watson Bryan C. , Weissburg Marc , Bras Bert
Published: November 2021

Resilience is an emergent property of complex systems that describes the ability to detect, respond, and recover from adversity. Much of the modern world consists of multiple, interacting, and independent agents (i.e. Multi-Agent Systems). However, the process of improving Multi-Agent System resilience is not well understood. We seek to address this gap by applying Biologically Inspired Design to increase complex system resilience. Eusocial insect colonies are an ideal case study for system resilience. Although individual insects have low computing power, the colonies collectively perform complex tasks and demonstrate resilience. Therefore, analyzing key elements of eusocial insect colonies may offer insight on how to increase Multi-Agent System resilience. Before the strategies used in eusocial insects can be adapted for Multi-Agent Systems, however, the existing research must be identified and transferred from the biological sciences to the engineering field. These transfers often hinder or limit biologically inspired design. This paper translates the biological investigation of individual insects and colony network behavior into strategies that can be tested to increase Multi-Agent System resilience. These strategies are formulated to be applied to Agent-Based Modeling. Agent-Based Modeling has been applied to many Multi-Agent Systems including epidemiology, traffic management, and marketing. This provides a key step in the design-by-analogy process: Identifying and decoding analogies from their original context. The design principles proposed in this work provide a foundation for future testing and eventual implementation into Multi-Agent Systems.
On MBS Constraints and Projections
Authors: Pfeiffer Friedrich
Published: November 2021

Constraints in multibody systems are usually treated by a Lagrange I - method resulting in equations of motion together with the constraint forces. Going from non-minimal coordinates to minimal ones opens the possibility to project the original equations directly to the minimal ones, thus eliminating the constraint forces. The necessary procedure is described, a general example of combined machine-process dynamics discussed and a specific example given. For a n-link robot tracking a path the equations of motion are projected onto this path resulting in quadratic form linear differential equations. They define the space of allowed motion, which is generated by a polygon-system.
A Novel Dual-Mass Accelerometer Exploiting Mode Localization in Electrostatically Coupled Resonators
Authors: Lyu Ming , Zhao Jian , Kacem Najib , Liu Pengbo
Published: November 2021

A novel dual-mass accelerometer is proposed while exploiting the phenomenon of mode localization in two electrostatically coupled resonators with an adjustable coupling strength. The external inertial forces are transmitted differentially to the resonators in term of axial load change through the two levering mechanisms, breaking the balanced state and resulting in a drastic change in the amplitudes of the two resonators. Based on the Euler Bernoulli theory, the governing equations of the coupled system are derived and numerically solved. The sensitivity in term of relative shift of amplitude ratio can be improved by 4 orders of magnitude compared to frequency shift. Finally, the effect of the quality factor on the sensor dynamics has also been investigated, and the results show that it only affects the vibration magnitude of the resonators while operating below the critical amplitude.
Differential Utility: Accounting for Correlation in Performance Among Design Alternatives
Authors: Jolini Sahar , Hazelrigg George A.
Published: November 2021

Recognizing expected utility as a valid design criterion, there are cases where uncertainty is such that this criterion fails to distinguish clearly between design alternatives. These cases may be characterized by broad and significantly overlapping utility probability distributions. Not uncommonly in such cases, the utility distributions of the alternatives may be highly correlated as the result of some uncertain variables being shared by the alternatives, because modeling assumptions may be the same across alternatives, or because difference information may be obtained by means of an independent source. Because expected utility is evaluated for alternatives independently, maximization of expected utility typically fails to take these correlations into account, thus failing to make use of all available design information. Correlation in expected utility across design alternatives can be taken into account only by computing the expected utility difference, namely the “differential expected utility,” between pairs of design alternatives. However, performing this calculation can present significant difficulties of which excessive computing times may be key. This paper outlines the mathematics of differential utility and presents an example case, showing how a few simplifying assumptions enabled the computations to be completed with approximately 24 hours of desktop computing time. The use of differential utility in design decision making can, in some cases, provide significant additional clarity, assuring better design choices.
Fast Cutter Location Surface Computation Using Ray Tracing Cores
Authors: Ishii Daiki , Inui Masatomo , Umezu Nobuyuki
Published: November 2021

By using the cutter location (CL) surface, fast and stable computation of the cutter path for machining complicated molds and dies can be realized. State-of-the-art graphics processing units (GPUs) are equipped with special hardware named ray tracing (RT) cores dedicated to image processing (called ray tracing) for 3D computer graphics. Using RT cores, it is possible to quickly compute the intersection points between a set of straight lines and polygons. In this paper, we propose a novel CL surface computation method using the RT core. The RT core was originally designed to accelerate 3D computer graphics processing. For the development of software using RT cores, it is necessary to use the OptiX application programming interface (API) library for computer graphics. We demonstrate how to use the OptiX API in the development of software for CL surface computations. Computational experiments were carried out, and it was confirmed that it is possible to obtain the CL surface based on a very high-resolution Z-map several times faster than the depth buffer-based method, which has been considered to be the fastest to date.
SuperMeshing: A Deep Learning Method for Boosting Mesh Density in Numerical Computation Within 2D Domain
Authors: Xu Handing , Nie Zhenguo , Xu Qingfeng , Liu Xinjun
Published: November 2021

Due to the limit of mesh density, the improvement of the spatial resolution of numerical computation always leads to a decrease in computing efficiency. Aiming at this inability of numerical computation, we propose a novel method for boosting the mesh density in finite element method (FEM) within 2D domain. Based on the von Mises stress fields of 2D plane-strain problems computed by the FEM, this method utilizes a deep neural network named SuperMeshingNet to learn a non-linear mapping from low mesh-density to high mesh-density in stress fields, and realizes the improvement of numerical computation accuracy and efficiency simultaneously. We adopt residual dense blocks into our mesh-density boost model – SuperMeshingNet to extract abundant local features and enhance the prediction capacity. The results indicate that SuperMeshingNet is able to effectively increase the spatial resolution of the von Mises stress fields under the multiple scaling factors: 2X,4X,and8X. Compared with the targets, the relative error of SuperMeshingNet is 2.44%, which shows better performance than the interpolation methods. Besides, SuperMeshingNet reveals an astonishing strength in predicting the maximum stress value. We publicly share our work with full detail of implementation at https://github.com/zhenguonie/2021_SuperMeshing_2D_Plane_Strain.
Systems Thinking Assessment: A Method Through Computer Simulation
Authors: Arnold Ross D. , Wade Jon P. , Bayrak Alparslan Emrah
Published: November 2021

This paper presents a novel assessment method for Systems Thinking and its supporting competencies. Systems Thinking is a key component in engineering education, providing students with the means to explore, understand, and design engineered systems both holistically and in terms of the relationships between their components, which can be both technical and non-technical. The assessment method described in this paper is implemented as a software simulation of a domain-agnostic system to support integration of Systems Thinking into engineering education. The simulation was tested with a group of beta-testers and then fully deployed online as a freely available tool for a 6-month experimental period. The pool of volunteer participants included students and mixed professionals from a diverse set of geographical, educational, and career backgrounds. Results of the assessment show success at both evaluating Systems Thinking Maturity as a whole, and at assessing complex facets of Systems Thinking that have eluded assessment in prior methods. The tool shows promise at evaluating competencies within all four Systems Thinking domains — Mindset, Content, Structure, and Behavior. These domains contain key systemic skills such as the ability to recognize interconnections and feedback loops, see non-linear causal relationships, and understand dynamic behavior. When examined holistically through multiple regression analysis, participants’ scores in the 11 assessed competencies show a moderate to high ability to predict their levels of overall Systems Thinking performance in the simulation. The results also reveal previously unknown dependencies and strengths of relationships between Systems Thinking competencies.
Vibration Analysis of Beams Using Alternative Admissible Functions With Penalties
Authors: Kateel Srividyadhare , Baddour Natalie
Published: November 2021

Assumed mode methods are often used in vibrations analysis, where the choice of assumed mode affects the stability and useability of the method. System eigenfunctions are often used for these expansions, however a change in the boundary conditions usually results in a change in eigenfunction. This paper investigates the use of Alternative Admissible Functions (AAF) with penalties for the vibration analysis of an Euler-Bernoulli beam for different boundary conditions. A key advantage of the proposed approach is that the choice of AAF does not depend on the boundary conditions since the boundary conditions are modelled via penalty functions. The mathematical formulation of the system matrices, and the effect of beam geometry changes on the computed natural frequencies and modeshapes are presented. The computed natural frequencies and mode shapes show an excellent agreement when compared with closed-form Euler-Bernoulli beam values. The study reveals that with an increase in the stiffness of the beam, the values of the penalties need to be increased. The results of this study suggest that boundary conditions, as well as beam geometrical parameters should be considered when selecting appropriate values of the penalties.
Vibration Characteristics of 3D Printed Viscoelastic Graded Polymeric Plates
Authors: Carter Justin , Singh Kumar Vikram , Khan Fazeel
Published: November 2021

The exploration of structures made of multiple materials is a growing area of research as additive manufacturing processing technologies such as fused deposition modeling (FDM) 3D printing allows for their fabrication. Such a technology allows for rapid prototyping of structural components with complex geometries or spatially distributed materials with different properties and functionalities. By selecting suitable spatial distribution of materials, the performance of structural components can be manipulated and enhanced as per different engineering application needs. For a low-cost design of structural prototypes using 3D printing processes, viscoelastic polymeric materials are often used, having inherent damping properties. In this research, vibration characteristics of thin plates which are axially graded with multiple polymeric materials are investigated. The goal is to understand the influence of material grading on the frequency and damping characteristics of graded plates. Although in literature, material grading along the thickness in designing composite laminates and their vibration characteristics are available, the performance of plates having axially graded viscoelastic polymers have not been investigated yet. Through systematic modeling and experimental plans, vibration characteristics of axially graded viscoelastic plates are presented here. In particular, the damping performance for different grading schemes is evaluated. It is anticipated that such analysis will allow accurate modeling and testing of design prototypes of structural components for future research, such as design and testing of graded panels for enhanced flutter characteristics.
Design, Modeling, and Optimization of a Novel Asymmetrical Piezoelectrically Actuated Microgripper
Authors: Lyu Zekui , Xu Qingsong
Published: November 2021

Microgripper, as the end-effector of a micromanipulation robot, has been widely used in semiconductors, biomedicine, optical engineering, etc. The stack piezoelectric ceramic actuated microgripper has the advantages of fast response speed, high motion resolution, and good control performance. Traditional symmetrical microgripper has defects such as lack of positioning reference and dense modal of resonance. Therefore, it is necessary to develop an asymmetrical clamp with a large clamping stroke and good dynamic characteristics. This paper introduces the design, modeling, optimization, and simulation of a new asymmetric microgripper. The designed asymmetric gripper has the advantages of large-displacement magnification and high natural frequency. The gripper’s movable side is comprised of three-level compliant amplification mechanisms including bridge mechanism, Scott-Russell mechanism, and parallelogram mechanism. The linear relationship between the input displacement and the output displacement is obtained through motion modeling. The multi-objective genetic algorithm optimizes the major parameters of the structure which affect the clamping stroke. Finite element analysis is conducted to verify the clamping stroke, clamping force, and resonance frequency of the gripper. The simulation results show that the proposed microgripper has good working performance with a clamping stroke of 156.75 μm and a natural frequency of 952.91 Hz, which is promising for practical application.
A Taxonomy for Model-Based Systems Engineering
Authors: Monteiro João P. , Gil Paulo J. S. , Rocha Rui M.
Published: November 2021

In this paper, we define Model Based Systems Engineering (MBSE) as a set of different approaches which vary in scope and in purpose, as opposed to defining it as a monolithic concept. To do so, we inductively extract common themes from papers proposing new MBSE methods based on the type of Systems Engineering (SE) artifacts produced and the expected benefits of MBSE implementation. These themes are then validated against the experiences depicted in a second set of papers evaluating the deployment of MBSE methods in practice. We propose a taxonomy for MBSE which identifies three main categories: system specification repositories, system execution models, and design automation models. The proposed categories map well onto common discussions of the nature of the SE activity, in that the first is employed in the management of system development processes and the second in the understanding of system performance and emergent properties. The third category is almost exclusively discussed in an academic context and is therefore more difficult to relate to SE practice, but its features are clearly distinct from the other two. The proposed taxonomy clarifies what MBSE is and what it can be, therefore helping focus research on the issues that still prevent MBSE practice from living up to expectations.
Myoelectric Control of Robotic Leg Prostheses and Exoskeletons: A Review
Authors: Nasr Ali , Laschowski Brokoslaw , McPhee John
Published: November 2021

Myoelectric signals from the human motor control system can improve the real-time control and neural-machine interface of robotic leg prostheses and exoskeletons for different locomotor activities (e.g., walking, sitting down, stair ascent, and non-rhythmic movements). Here we review the latest advances in myoelectric control designs and propose future directions for research and innovation. We review the different wearable sensor technologies, actuators, signal processing, and pattern recognition algorithms used for myoelectric locomotor control and intent recognition, with an emphasis on the hierarchical architectures of volitional control systems. Common mechanisms within the control architecture include 1) open-loop proportional control with fixed gains, 2) active-reactive control, 3) joint mechanical impedance control, 4) manual-tuning torque control, 5) adaptive control with varying gains, and 6) closed-loop servo actuator control. Based on our review, we recommend that future research consider using musculoskeletal modeling and machine learning algorithms to map myoelectric signals from surface electromyography (EMG) to actuator joint torques, thereby improving the automation and efficiency of next-generation EMG controllers and neural interfaces for robotic leg prostheses and exoskeletons. We also propose an example model-based adaptive impedance EMG controller including muscle and multibody system dynamics. Ongoing advances in the engineering design of myoelectric control systems have implications for both locomotor assistance and rehabilitation.
A Flexure-Based Displacement Reducer Capable of Achieving Very Large Reduction Ratio
Authors: Wu Houqi , Chen Guimin
Published: November 2021

Piezo actuators and giant magnetostrictive actuators are widely used in micropositioning and micromanipulating devices. Due to their limited output stroke, flexure-based displacement amplifiers are usually employed to meet the large-stroke requirements. Although amplifiers increase the stroke of the actuators, they lower the resolution of the motion, making it difficult to obtain positioning of nanometer or even sub-nanometer resolution. To achive very high resolution from these actuators, a compact flexure-based displacement reducer, which shows the capability of obtaining very large reduction ratio, is proposed in this work. The reducer contains two bridge-type flexure mechanisms connected in a way that the output of the reducer equals the difference of the outputs of the two mechanisms (thus is called the bridge-type differential displacement reducer). If the two bridge-type flexure mechanisms are identical, no matter how large the input is, the output will always be 0, indicating an infinite reduction ratio theoretically. Therefore, introducing a slight difference between the two mechanisms can yield a very large reduction ratio. A kinetostatic model for the reducer is developed, base on which a reducer exhibiting a reduction ratio of 100 is designed and prototyped. The results of the kinetostatic model, the finite element model and the experiment agree well with each other, validating the effectiveness of the proposed reducer and the correctness of kinetostatic model.
A Graph Neural Network Approach for Product Relationship Prediction
Authors: Ahmed Faez , Cui Yaxin , Fu Yan , Chen Wei
Published: November 2021

Graph representation learning has revolutionized many artificial intelligence and machine learning tasks in recent years, ranging from combinatorial optimization, drug discovery, recommendation systems, image classification, social network analysis to natural language understanding. This paper shows their efficacy in modeling relationships between products and making predictions for unseen product networks. By representing products as nodes and their relationships as edges of a graph, we show how an inductive graph neural network approach, named GraphSAGE, can efficiently learn continuous representations for nodes and edges. These representations also capture product feature information such as price, brand, and engineering attributes. They are combined with a classification model for predicting the existence of a relationship between any two products. Using a case study of the Chinese car market, we find that our method yields double the F-1 score compared to an Exponential Random Graph Model-based method for predicting the co-consideration relationship between cars. While a vanilla Graph-SAGE requires a partial network to make predictions, we augment it with an ‘adjacency prediction model’ to circumvent this limitation. This enables us to predict product relationships when no neighborhood information is known. Finally, we demonstrate how a permutation-based interpretability analysis can provide insights on how design attributes impact the predictions of relationships between products. Overall, this work provides a systematic method to predict the relationships between products in a complex engineering system.
Correlation of Reduced-Order Models of a Threaded Fastener in Multi-Axial Loading
Authors: Moreno Kevin , Murugesan Avaneesh , Sheng Michael , Alqawasmi Laith , Khraishi Tariq A. , Hubbard Neal B.
Published: November 2021

Fasteners are represented with varying degrees of fidelity in finite element models in order to meet solver constraints and accuracy requirements. Three reduced-order models are evaluated to quantify how well they perform in terms of calibration effort and accuracy. To baseline their performance, a new series of test data are developed by pulling NAS1351-3-20P screws at angles between pure tension (0°) and pure shear (90°) in 15° increments. First, a nonlinear elastic spring element joins two portions of the fastener shank. Unique load-displacement curves for tension and shear are taken directly from the test data, making it easy to calibrate yet fairly accurate. Second, the fastener is modeled with a solid cylindrical shank. The material properties are only calibrated to the tensile test results; consequently, this model is less accurate for predicting the ultimate shear load, though it comes reasonably close to the ultimate displacement in shear and combined loading. Third, a solid cylinder is divided into tensile and shear regions, and the material properties in each region are calibrated to the corresponding test data. This model deviates further from the ultimate displacement but effectively predicts the ultimate load in combined tension and shear. Each model has advantages, but the first is easiest to implement and most accurate overall.
Complexity Should Not Be in the Eye of the Beholder: How Representative Complexity Measures Respond to the Commonly-Held Beliefs of the Literature
Authors: Hennig Anthony , Topcu Taylan G. , Szajnfarber Zoe
Published: November 2021

In an increasingly interconnected & cyber-physical world, the ability to coherently measure and manage complexity is vital for the engineering design and systems engineering community. To this end, numerous measures have been promulgated in the literature, yet these measures differ in terms of their intellectual foundations and perspectives, with limited cross-validation among them. In this paper, we propose a framework for benchmarking the status quo of existing complexity measurement approaches in terms of their alignment with the commonly-held beliefs in the literature. We discover that the literature broadly suggests an understanding of complexity based on a system’s size, number of interconnections, and architectural structure. We adopt a design of experiments approach and synthetically create system architectures to mimic the variation across these dimensions. We then use these architectures as a shared test-bed to document the response of four complexity measures that are representative of the predominant perspectives of the literature. We do this by evaluating the change in measurement of a complexity measure as we incrementally varied the levels of one system architecture property believed to affect complexity while keeping the others constant. We find that none of the measures fully satisfy the commonly-held beliefs of the literature and provide a discussion on the underlying factors that lead to these discrepancies. We note that multiple independent discussions coexist in the literature, with little cohesion and communication across the groups, suggesting that further research is required to understand the interactions and influences among these communities. For this purpose, our rigorous, structured, and grounded in literature benchmarking approach can serve as a testbed for development and verification of future architectural assessment tools and measures.
An Approach to Design Controllers for MIMO Fractional Order System Based on RFN Method
Authors: Li Tingxue , Xue Dingyu , Cui Xinshu
Published: November 2021

Fractional calculus has attracted more and more attention and is applied in different fields. However the controller design techniques for fractional order systems mostly focus on single input single output (SISO) ones. This paper deals with the design of controllers for multiple inputs multiple outputs (MIMO) fractional order systems. A method to synthetize controller based on the eigenvalue function and singular value decomposition (SVD) is proposed with aid of fractional order transfer function (FOTF) MATLAB toolbox for the computation and fitting. Instead of setting specification to the controller, the method proposed aiming at achieving the target closed-loop control effect of the system as a whole. Several models evolved from fractional-order Proportional-Integral-Derivative (fPID) controller are selected to form the designed multivariable controller. The effectiveness and robustness of the proposed method are illustrated by an example via simulation.
Constant Force Compliant Mechanisms Without Preloading
Authors: Pujali Premkumar , Zhou Hong
Published: November 2021

A constant force compliant mechanism generates an output force that keeps invariant in a large range of input displacement. Because of the constant force feature and the merits of compliant mechanisms, they are utilized in many applications. A problem in the current constant force compliant mechanisms is their preloading range that is a certain starting range of the input displacement. In the preloading displacement, the output force of a constant force compliant mechanism does not have the desired value. It goes up from zero value. The preloading displacement often occupies one quarter or more of the entire input displacement range, which weakens the performance of constant force compliant mechanisms. The preloading issue is eradicated in this research by using prebuckled beams as components for constructing constant force compliant mechanisms. It is difficult to synthesize constant force compliant mechanisms that are composed of prebuckled beams because of the intertwined force, buckling and deflection characteristics. In this research, the undeformed beams are represented by spline curves and controlled by its interpolation points. The synthesis of constant force compliant mechanisms is systemized as optimizing the design parameters of the composed prebuckled beams. Fully compliant constant force compliant mechanisms are synthesized without preloading. The synthesis solutions are validated by experimental results.
Model Predictive Control of Fixed Wing Aircraft Using a Disturbance Observer Approach
Authors: Deshpande Vinayak , Zhang Youmin
Published: November 2021

This paper develops a novel cascading Proportional-Integral-Derivative (PID) with Model Predictive Control (MPC) formulation for lateral control of a fixed wing aircraft in the presence of a constant load disturbance, with the consideration of actuator constraints. A Constrained Quadratic Programming (QP) problem is used to solve this MPC problem, via the Primal-Dual procedure. Furthermore, a disturbance observer is utilized to estimate this disturbance so that the setpoint calculation can be adjusted accordingly. Numerical simulations demonstrate steady-state tracking of the aircraft’s roll angle whilst rejecting this disturbance. In addition, heading (yaw) control is implemented via the outer PID loop, and perfect tracking is achieved for this as well. Throughout the entire simulation, the aircraft’s control inputs (aileron and rudder) do not violate their position and rate constraints, thus demonstrating the successful performance of the QP algorithm.
Simulation of a Pole Saw Assisted by a Gyroscopic Effect Device
Authors: Okabe Eduardo P. , Miletto Daniel L. , Misuta Milton S. , Brittes José Luiz P.
Published: November 2021

Linemen performing pruning activity on vegetation entangled with overhead lines and handling a pole saw is a physically strenuous and risky job. It is a major cause of linemen musculoskeletal disorders (MSD) and others injuries, with more than one type of accumulative musculoskeletal injury like backbone, shoulder, neck and wrists. Although assisted robotic tools could reduce ergonomic issues, it also impairs the quality of work; efficiency and quality require human direct cutting due to a huge imponderability of each particular action on each particular job due different kind of vegetation and shapes. The best approach should be to aid linemen handling the pole saw during pruning. So, as a first step to develop and implement a gyroscopic platform for pruning pole saw, this paper compares and presents a simulation of a regular pole saw with a pole saw assisted by a gyroscopic device using kinematic data obtained by the motion capture system. Kinematic data obtained connects to dynamic simulation, which makes available pole saw control and kickback analysis. Simulation outcome shows that gyroscopic assistance on pole saw has great potential to mitigate harmful pruning dynamic forces for lineman, with no impact on productivity and work quality.
Model-Order-Reduction Approach for Structural Health Monitoring of Large Deployed Structures With Localized Operational Excitations
Authors: Bhouri Mohamed Aziz
Published: November 2021

We present a simulation-based classification approach for large deployed structures with localized operational excitations. The method extends the two-level Port-Reduced Reduced-Basis Component (PR-RBC) technique to provide faster solution estimation to the hyperbolic partial differential equation of time-domain elastodynamics with a moving load. Time-domain correlation function-based features are built in order to train classifiers such as Artificial Neural Networks and Support-Vector Machines and perform damage detection. The method is tested on a bridge-shaped structure with a moving vehicle (playing the role of a digital twin) in order to detect cracks’ existence. Such problem has 45 parameters and shows the merits of the two-level PR-RBC approach and of the correlation function-based features in the context of operational excitations, other nuisance parameters and added noise. The quality of the classification task is enhanced by the sufficiently large synthetic training dataset and the accuracy of the numerical solutions, reaching test classification errors below 0.1% for disjoint training set of size 7 × 103 and test set of size 3 × 103. Effects of the numerical solutions accuracy and of the sensors locations on the classification errors are also studied, showing the robustness of the proposed approach and the importance of constructing a rich and accurate representation of possible healthy and unhealthy states of interest.
Design of Band Gap Formation in Periodic Rotors via Optimization
Authors: Lamas Patrick B. , Nicoletti Rodrigo
Published: November 2021

Rotors are usually composed of rotating elements (e.g. disks, impellers, blade stages) which add mass and rotational inertia to the system. When this additional inertia of the rotating elements is evenly distributed along the rotor, inertia periodicity appears and the system presents considerably large band gaps in its frequency response, where no resonances appear. The present work shows that we can change the central frequency of these band gaps, without significantly affecting its bandwidth, by changing the distribution of the inertia along the rotor to a quasi-periodic condition. Such designing of the rotor, and consequently of the band gap, is achieved by an optimization procedure.
Subharmonic Resonance of One Fourth Order of Electrostatically Actuated MEMS Circular Plates: Amplitude-Frequency Response
Authors: Caruntu Dumitru I. , Beatriz Julio , Martinez Miguel
Published: November 2021

This work deals with the amplitude-frequency response subharmonic resonance of 1/4 order of electrostatically actuated circular plates. The method of multiple scales is used to model the hard excitations and to predict the response. This work predicts that the steady state solutions are zero amplitude solutions, and non-zero amplitude solutions which consist of stable and unstable branches. The effects of parameters such as voltage and damping on the response are predicted. As the voltage increases, the non-zero amplitude solutions are shifted to lower frequencies. As the damping increases, the non-zero steady-state amplitudes are shifted to higher amplitudes, so larger initial amplitudes for the MEMS plate to reach non-zero steady-state amplitudes.
A Zero-Trust Methodology for Security of Complex Systems With Machine Learning Components
Authors: Hale Britta , Van Bossuyt Douglas L. , Papakonstantinou Nikolaos , O’Halloran Bryan
Published: November 2021

Fuelled by recent technological advances, Machine Learning (ML) is being introduced to safety and security-critical applications like defence systems, financial systems, and autonomous machines. ML components can be used either for processing input data and/or for decision making. The response time and success rate demands are very high and this means that the deployed training algorithms often produce complex models that are not readable and verifiable by humans (like multi layer neural networks). Due to the complexity of these models, achieving complete testing coverage is in most cases not realistically possible. This raises security threats related to the ML components presenting unpredictable behavior due to malicious manipulation (backdoor attacks). This paper proposes a methodology based on established security principles like Zero-Trust and defence-in-depth to help prevent and mitigate the consequences of security threats including ones emerging from ML-based components. The methodology is demonstrated on a case study of an Unmanned Aerial Vehicle (UAV) with a sophisticated Intelligence, Surveillance, and Reconnaissance (ISR) module.
Insect Wing Buckling Influences Stress and Stability During Collisions
Authors: Jankauski Mark , Schwab Ryan , Casey Cailin , Mountcastle Andrew
Published: November 2021

Flapping insect wings frequently collide with vegetation and other obstacles during flight. Repeated collisions may irreversibly damage the insect wing, thereby compromising the insect’s ability to fly. Further, reaction torques caused by the collision may destabilize the insect and hinder its ability to maneuver. To mitigate the adverse effects of impact, some insect wings are equipped with a flexible joint called a “costal break.” The costal break buckles once it exceeds a critical angle, which is believed to improve flight stability and prevent irreversible wing damage. However, to our knowledge, there are no models to predict the dynamics of the costal break. Through this research, we develop a simple model of an insect wing with a costal break. The wing was modeled as two beams interconnected by a torsional spring, where the stiffness of the torsional spring instantaneously decreases once it has exceeded a critical angle. We conducted a series of static tests to approximate model parameters. Then, we used numerical simulation to estimate the peak stresses and reaction moments experienced by the wing during a collision. We found that costal break increased the wing’s natural frequency by about 50% compared to a homogeneous wing and thus reduced the stress associated with normal flapping. Buckling did not significantly affect peak stresses during collision. Joint buckling reduced the peak reaction moment by about 32%, suggesting that the costal break enhances flight stability.
Machine Learning Method for Forecasting Weather Needed For Crop Water Demand Estimations in Low-Resource Settings Using A Case Study in Morocco
Authors: Sheline Carolyn , Winter Amos
Published: November 2021

Low and middle income countries often do not have the infrastructure needed to support weather forecasting models, which are computationally expensive and often require detailed inputs from local weather stations. Local, low-cost weather prediction services are needed to enable optimal irrigation scheduling and increase crop productivity for rural farmers in low-resource settings. This work proposes a machine learning approach to predict the weather inputs needed to calculate crop water demand, namely evapotranspiration and precipitation. The focus of this work is on the accuracy with which Moroccan weather can be predicted with a vector autoregression (VAR) model compared to using typical meteorological year (TMY) weather, and how this accuracy changes as the number of weather parameters is reduced.