bluuebunny/crossref_metadata_2025_split huggingface dataset:
Topological Properties and Localized Vibration Modes in Quasiperiodic Metamaterials With Electromechanical Local Resonators
Authors: LeGrande Joshua , Bukhari Mohammad , Barry Oumar 
Published: November 2022

Abstract
Simultaneous energy harvesting and vibration attenuation has been a topic of great interest in many recent investigations in mechanical metamaterials. These studies have shown the ability to harvest electrical power using weak electromechanical coupling in periodic metamaterials with no effect on the material’s bandgap boundaries. However, the effect of the electromechanical resonator on the topological properties (i.e. the bandgap topology) and localized mode shapes of a quasiperiodic metamaterial has not yet been determined. In this paper, we study a quasiperiodic metamaterial coupled to electromechanical resonators to observe its bandgaps and localized vibration modes. We show here the analytical dispersion surfaces of an infinite quasiperiodic metamaterial with electromechanical local resonators. The natural frequencies of a semi-infinite system are also simulated numerically to validate the analytical results and show the band structure for different quasiperiodic patterns, load resistors, and electromechanical coupling coefficients. Furthermore, the mode shapes are presented here for a semi-infinite structure showing localized vibration within the bandgaps. The results demonstrate that quasiperiodic metamaterials with electromechanical local resonators can be used to harvest energy without changing the topology of the bandgaps for the case of weak electromechanical coupling. The observations given here can be used to guide designers in choosing electromechanical resonator parameters and quasiperiodic pattern parameters for an effective energy harvesting metamaterial.
Am I Right? Investigating the Influence of Trait Empathy and Attitudes Towards Sustainability on the Accuracy of Concept Evaluations in Sustainable Design
Authors: Alzayed Mohammad Alsager , Starkey Elizabeth M. , Ritter Sarah C. , Prabhu Rohan 
Published: November 2022

Abstract
Concept selection is an integral stage in the design process, in which designers evaluate and compare solutions to select a smaller subset of solutions for further development. In this stage, designers often rely on their self-evaluations of solutions — either independently or using design tools — to make design decisions. However, the reliance on self-evaluations among novice designers could lead to faulty decision-making, given the presence of numerous cognitive biases. Consequently, we aim to investigate the accuracy of novice designers’ self-evaluations of the sustainability of their solutions and the moderating role of (1) trait empathy and (2) their beliefs, attitudes, and intentions towards sustainability on this accuracy. Towards this aim, we conducted an experiment with first-year engineering students comprising a sustainable design lecture and a design activity. At the end of the design activity, participants were asked to evaluate the sustainability of their own solutions and these self-evaluations were compared against expert evaluations. From the results, we see that participants demonstrate some degree of accuracy in their self-evaluations, but only with the sustainable design heuristics of longevity, sharing for maximal use, and active repair of misuse. Second, we see that trait empathy moderated the accuracy of self-evaluations, with participants reporting lower levels of fantasy and empathic concern demonstrating more accurate self-evaluations. Finally, we see that beliefs, attitudes, and intentions towards sustainability also moderated the accuracy of their self-evaluations, and participants with lower levels demonstrated greater accuracy of self-evaluations. Taken together, these findings suggest that designers’ individual differences such as trait empathy could moderate the accuracy of the evaluation of their solutions, especially in the context of sustainability.
A Preliminary Approach to Select an Origami Source Pattern for Deployable Space Arrays
Authors: Bolanos Diana , Ynchausti Collin , Magleby Spencer P. 
Published: November 2022

Abstract
This paper presents a systematic approach for selecting an origami source pattern for deployable space array applications, followed by two case studies used to demonstrate the selection process. Applying origami principles to form engineering solutions can be a difficult task. Competing requirements may create confusion around which pattern is most favorable for the space array application. As a result, this paper aims to provide clarity on the process needed to effectively design an origami space array. The focus of this paper is to provide aerospace engineers and designers with a framework for identifying optimal origami source patterns for space array applications.
Now Is the Time! Exploring the Effects of Variations in the Timing of a Sustainable Design Educational Intervention
Authors: Alzayed Mohammad Alsager , Starkey Elizabeth , Prabhu Rohan 
Published: November 2022

Abstract
The accelerating depletion of natural resources has brought sustainability to the forefront and therefore, design educators must integrate sustainability into the engineering design curriculum. Several researchers have proposed educational interventions and design tools for sustainable design education. The timing of introducing such interventions, particularly in project-based courses, could influence the effectiveness of these interventions, and these effects remain largely unexplored. Our aim in this research is to investigate this research gap through a mixed-methods experiment conducted with first-year engineering design students. Specifically, we introduced a two-day module on sustainable design either in the first or sixth week of an 8-week long design project. The effects of this variation were compared by analyzing (1) changes in students’ trait empathy, (2) changes in their beliefs, attitudes, and intentions towards sustainability, and (3) their responses to a reflection assignment collected at the end of the semester/design project. From the results, we see that the timing of the sustainable design intervention did not influence changes in students’ trait empathy or their beliefs, attitudes, and intentions towards sustainability. However, students from both timing conditions reported significant increases in their attitudes and intentions towards sustainable action. Finally, students who received the intervention earlier more frequently mentioned the use of sustainable design heuristics in their reflection responses. Taken together, these findings suggest the need for educators to consider the timing of sustainable design interventions, especially when integrating them into longer project-based courses.
Concurrent Build Direction, Part Segmentation, and Topology Optimization for Additive Manufacturing Using Neural Networks
Authors: Chen Hongrui , Whitefoot Kate S. , Kara Levent Burak 
Published: November 2022

Abstract
We propose a neural network-based approach to topology optimization that aims to reduce the use of support structures in additive manufacturing. Our approach uses a network architecture that allows the simultaneous determination of an optimized: (1) part segmentation, (2) the topology of each part, and (3) the build direction of each part that collectively minimize the amount of support structure. Through training, the network learns a material density and segment classification in the continuous 3D space. Given a problem domain with prescribed load and displacement boundary conditions, the neural network takes as input 3D coordinates of the voxelized domain as training samples and outputs a continuous density field. Since the neural network for topology optimization learns the density distribution field, analytical solutions to the density gradient can be obtained from the input-output relationship of the neural network. We demonstrate our approach on several compliance minimization problems with volume fraction constraints, where support volume minimization is added as an additional criterion to the objective function. We show that simultaneous optimization of part segmentation along with the topology and print angle optimization further reduces the support structure, compared to a combined print angle and topology optimization without segmentation.
Multi-Mission Engineering With Zero Trust: A Modeling Methodology and Application to Contested Offshore Wind Farms
Authors: Van Bossuyt Douglas L. , Hale Britta , Arlitt Ryan M. , Papakonstantinou Nikolaos 
Published: November 2022

Abstract
With the growth of autonomy and augmentation of machine learning in system decision-making, systems-of-systems (SoS) have become increasingly complex. Security and safety, as well as national economic stability, are reliant on interconnected systems with multiple decision making components. While such inter-connectivity advances the speed at which action and mission control decision making can take place, it also increases the number of dependencies at risk in the case of an attack and the speed at which attacks become effective in their goals. Attacks on the supply chain and on system lifecycle phases other than the operation are also becoming more common. In this paper we consider from a mission engineering perspective a complex reconfigurable SoS covering management of a wind farm with autonomous uncrewed patrol systems, crewed maintenance vessels, back-end control and machine learning components. The complex SoS is situated in the exclusive economic zone of one country, but with perimetric position to regional power competitors. We investigate causal effects of adversarial capabilities in the case study, using a zero trust combined with Defense in Depth approach. Of particular interest are situations where an adversary injects an incipient fault during one mission that is only brought to fruition during a subsequent mission.
Design and Simulation of a MEMS Capacitive Pressure Sensor With Corrugated Membrane and Linear Capacitance-Pressure Response
Authors: Shavezipur Mohammad 
Published: November 2022

Abstract
This paper presents a new design for MEMS capacitive pressure sensor that helps to linearize the capacitance-pressures response of the sensor. Capacitive pressure sensors have two electrodes, one often fixed and one is deformed as the ambient pressure changes. In general, the two electrodes are made of flat thin films. The proposed sensor design is based on a corrugated membrane, where circular ridges and grooves are made in the membrane altering its deformation as the pressure is applied. The sensor design is analyzed using finite element simulations, and ANSYS coupled-field multiphysics solver is used to model and obtain the response of a conventional and corrugated pressure sensor as the ambient pressure changes. The simulation results show that, as expected, the sensor displays high sensitivity at lower pressure and as the pressure increases and the contact area between the membrane and fixed electrode expands, the sensitivity of the capacitance-pressure (C-P) response decreases for both sensors. However, the sensor with corrugated membrane displays high linearity at lower pressures. The response for proposed design at this pressure range is nearly a perfect line, while the conventional design exhibits nonlinearity that is visually noticeable. To quantitatively evaluate the level of linearity of the C-P responses, a linearity factor as the coefficient of linear correlation between the capacitance and pressure is used. The simulation results show that at low pressure of 0.2–1.0 MPa, the sensor with corrugated membrane has high linearity of 0.999 compared to 0.987 for conventional sensor, where for pressure range 0–1.0 MPa these values are 0.997 and 0.983, respectively. The quantitative comparison of the linearity factors for the two design show a notable improvement in the linearity of the C-P response providing nearly a constant sensitivity over the pressure range of 0.2 to 1.0 MPa.
An Empirical Study of the Impact of Task Expectation Framing on Design Decision Delegation
Authors: Malak Richard , Smallman Rachel , Lench Heather 
Published: November 2022

Abstract
The delegation of decision authority is a routine part of engineering systems design. Examples include hiring an outside subcontractor and assigning specific design tasks to a subordinate engineer. In all cases, the delegator is responsible for describing the task to the delegate in a way that clarifies expected outcomes. Ideally, the delegate executes the task in a manner consistent with the preferences of the delegator. For systems design tasks, this means the delegate specifies an artifact with engineering attributes desired by the delegator. Whether such expectations are conveyed successfully can have a major impact on the success of a project. However, despite the central nature of such communications in engineering systems design and the potential consequences miscommunication, there has been little empirical investigation of decision delegation in design. This experimental study examines how the framing of decision task expectations impact task outcomes. Subjects participate in an engineering-themed computer game in which they make design choices. Subjects are assigned to conditions randomly, with some given instructions framed as traditional design requirements and others given instructions in a value-driven design framing (e.g., to maximize a figure of merit). A total of 472 engineering students participated in the study. Results indicate that task outcome expectation framing can impact task performance, with design requirement task framings exhibiting advantages over a value-driven framing. This suggests theoretical arguments favoring value-driven framings may not capture adequately the effect of human behavior.
Multi-Fidelity Reduced-Order Models for Multiscale Damage Analyses With Automatic Calibration
Authors: Deng Shiguang , Mora Carlos , Apelian Diran , Bostanabad Ramin 
Published: November 2022

Abstract
Predicting the fracture behavior of macroscale components containing microscopic porosity relies on multiscale damage models which typically ignore the manufacturing-induced spatial variabilities in porosity. This simplification is made due to the prohibitive computational costs associated with explicitly modeling spatially varying microstructures in a macroscopic component. To address this challenge, we propose a data-driven framework that integrates a mechanistic reduced-order model (ROM) with a calibration scheme based on latent map Gaussian processes (LMGPs). Our ROM drastically accelerates direct numerical simulations (DNS) by using a stabilized damage algorithm and systematically reducing the degrees of freedom via clustering. Since clustering affects local strain fields and hence the fracture response, we construct a multi-fidelity LMGP to inversely estimate the damage parameters of an ROM as a function of microstructure and clustering level such that the ROM faithfully surrogates DNS. We demonstrate the application of our framework in predicting the damage behavior of a multiscale metallic component with spatially varying porosity.
Generative Pre-Trained Transformers for Biologically Inspired Design
Authors: Zhu Qihao , Zhang Xinyu , Luo Jianxi 
Published: November 2022

Abstract
Biological systems in nature have evolved for millions of years to adapt and survive the environment. Many features they developed can be inspirational and beneficial for solving technical problems in modern industries. This leads to a specific form of design-by-analogy called bio-inspired design (BID). Although BID as a design method has been proven beneficial, the gap between biology and engineering continuously hinders designers from effectively applying the method. Therefore, we explore the recent advance of artificial intelligence (AI) for a computational approach to bridge the gap. This paper proposes a generative design approach based on the pre-trained language model (PLM) to automatically retrieve and map biological analogy and generate BID in the form of natural language. The latest generative pre-trained transformer, namely GPT-3, is used as the base PLM. Three types of design concept generators are identified and fine-tuned from the PLM according to the looseness of the problem space representation. Machine evaluators are also fine-tuned to assess the correlation between the domains within the generated BID concepts. The approach is then tested via a case study in which the fine-tuned models are applied to generate and evaluate light-weighted flying car concepts inspired by nature. The results show our approach can generate BID concepts with good performance.
Estimating the Complete Solution Set of the Approximate Path Synthesis Problem for Four-Bar Linkages Using Random Monodromy Loops
Authors: Baskar Aravind , Hills Caroline , Plecnik Mark , Hauenstein Jonathan D. 
Published: November 2022

Abstract
It is natural to employ an optimization algorithm for the approximate kinematic synthesis of linkages. The hope is to find some superior points in the design space that indicate dimensions that are practically useful. One way to achieve this is to find all minima of an objective, then to filter them so the best remain. However, the prospect of finding all minima is bleak unless the optimization problem at hand is particularly small. In this work, we show how to find nearly all minima for a large optimization problem using polynomial homotopy continuation in the approximate synthesis of a four-bar path generator. The system at hand has a Bézout bound of 543,848,665 and a Schnabel estimate to the maximum number of stationary points of 6 · (303,249 ± 713), within a 95% confidence interval. At least with regards to mechanism synthesis, this work represents the largest scale deployment to date of homotopy continuation to solve an unconstrained optimization problem. The challenges of scaling and suggestions for design are given. Example usage for the design of a leg mechanism is given. On the mechanism design front, this is the first presentation of a nearly complete (within the limitations of numerical discernment) solution of the general four-bar optimal path synthesis problem.
Multi-Mode Deformation of Origami Spring: Theoretical Modeling and Experimental Verification
Authors: Zhang Zian , Liu Zuolin , Li Suyi , Fang Hongbin 
Published: November 2022

Abstract
In recent years, earthworm-like robots have been widely concerned by researchers because of their outstanding mobility in various environments. However, most of them only possess up to 2D locomotion owing to the limitation in their structures and materials. Origami springs, with extraordinary multi-mode deformation ability, have promising potential for 3D locomotion. In this study, an analytic model of the origami spring is established by introducing virtual creases to the facets. Four topologically different configurations of a single cell are therefore obtained by changing the mountain and valley assembly of the virtual creases. By iteratively stacking the cells, a rigid-folding model is derived. Besides the conventional axial stretch-twist-coupling, the proposed modeling can also describe the off-axial deformation, including the point-to-point bending, and line-to-line bending. In addition, the potential energy of the multi-mode deformations is investigated by specifying the torsional spring on the creases of the rigid-folding kinematic model. Mechanical properties, including the nonlinear restoring force under axial deformation, and the approximate linear bending moment under off-axial deformation is observed. What’s more, a mode switching phenomenon is for the first time revealed once the structure is folded to the kinematic bifurcation point, and is experimentally evaluated via PETE film-based prototypes. We believe these findings could inspire the avenue for the next generation of the earthworm-like robot with multi-modal motions.
Exploring the Integration of DSM and LCA Tools to Improve Design for Sustainability
Authors: Carter Michael , Basereh Taramsari Hossein , Hoffenson Steven 
Published: November 2022

Abstract
One of the many challenges that engineering designers face today is a deficiency in practical and value-adding design methodologies that consider sustainability. Typically, design for sustainability (DfS) principles that address environmental and social impacts are not prioritized at the same level as economic, physical, and functional needs. Additionally, many newly-introduced DfS methodologies are fragmented and underdeveloped. Furthermore, many methods are catered towards specific niche product domains or corporate workflows, making the application of these methods across a wide range of problems and products a challenge. By investigating the tools and methods available for DfS and identifying their application and limitations, this study explores the integration of design structure matrices (DSMs) and Life Cycle Assessment (LCA) tools to improve DfS. The expectation is that an integrated DSM and LCA will allow designers to explore how a single design change may propagate through to specific changes in environmental and social impacts. The initial development of a full DSM and LCA is demonstrated through two case studies of a reusable water bottle and a micro-pump, showing which components, materials, and processes have the most significant environmental impacts. The results illustrate the value in applying this approach, which may be suitable across a wide range of existing products in an effort to improve DfS.
Design and Implementation of a Power-Dense, Modular, and Compact Serpentine Articulated Tail
Authors: Pressgrove Isaac , Liu Yujiong , Ben-Tzvi Pinhas 
Published: November 2022

Abstract
Inspired by the many examples in nature, serpentine robotic tails can provide a means of expanding the feasible motion and general dexterity of mobile robots. Previous research has proven the effectiveness of robotic tails for the purpose of inertial reorientation through simulation of both simple pendulum and complex serpentine tails. There have been various experiments involving the integration of pendulum tails with a mobile base conducted to date. However, until now integration of more complex tail models has proven difficult. This paper presents an updated design of the existing Roll-Roll-Revolute Tail (R3RT) which can be readily integrated with a mobile base. The new design improves on the power density as well as form factor of the original design. Therefore, a design that is both more effective and easier to integrate with a mobile robotic base is synthesized. Kinematic and dynamic analysis are conducted to generate design targets. These targets are then met through the development of a power-dense actuator and evolution of a modular tail layout. CAD models of the new tail design integrated with the reduced complexity quadruped base are also reviewed. Finally, results of initial testing to prove the performance of the actuators are presented.