bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Cross-Axis Pivots Orientation on Accuracy Performance of Compliant Mechanisms
Authors: Serafino Simone , Fanghella Pietro , Verotti Matteo 
Published: November 2023

Abstract
In the last decades, compliant mechanisms have been extensively adopted in engineering applications and many methods and approaches have been proposed for their design. Among this variety, the rigid-body replacement method has proved to be an effective tool for both the analysis and the synthesis of the compliant systems. A fundamental step of this method consists of replacing the revolute joints of the pseudo-rigid body model with flexible elements. Generally, this substitution is based on a proper positioning of the flexible element with respect to the rotation axis of the kinematic pair. In case of cross-axis flexural pivots, the intersection point of the crossing flexures usually serves as nominal center of rotation. In this paper, besides the positioning, the orientation of the flexural pivot is considered as a fundamental parameter of the design phase. A procedure is defined to determine the optimal orientation of the flexure that guarantee the prescribed rotation of the connected links. According to the proposed method, a compliant four-bar linkage is designed and numerical simulations are performed to asses its kinetostatic behavior. Numerical simulations are also carried out to compare the performance of the designed mechanism to the performance of compliant mechanisms based on non-specific orientation of their flexible elements.
A Heuristics Derivation Approach for the Digital Twin Designs
Authors: Kotecha Maulik C. , McAdams Daniel A. 
Published: November 2023

Abstract
This article illustrates an approach to developing design heuristics for digital twins (DTs). DTs are virtual replicas of physical systems or objects. Heuristics are rules of thumb used to facilitate problem-solving and decision-making. Heuristics can be used in DT design to simplify the complex design process and guide designers through creating a virtual representation of physical objects. Heuristics can help designers strike the right balance between detail and simplicity; speed and accuracy; and help identify the key parameters and variables that impact the behavior and performance of the system or product being modeled. They can also guide the selection of appropriate simulation tools, the validation of the DT against physical data, and the optimization of the virtual representation for specific performance metrics. The derivation of heuristics for DT design can help streamline the conceptualization process, reduce unnecessary design complexity, and ensure that the virtual representation accurately reflects the behavior and performance of the physical system or product. As DTs continue to grow in popularity, DT design heuristics will likely become an increasingly important tool for designers and engineers. We studied several examples of DT implementations from academia and industry and derived a set of heuristics using a systematic approach. This paper illustrated our process and outcomes via an example study. Finally, we propose a user study-based heuristics validation approach to validate the design heuristics.
Design Justice Strategies for Design Education: Evidence and Recommendations From Syllabus Analysis
Authors: Ostrowski Anastasia K. , Zhang Jennifer , Das Madhurima , Breazeal Cynthia , D’Ignazio Catherine , Verma Aditi 
Published: November 2023

Abstract
The need to embed equity, ethics, and justice considerations in design education is becoming increasingly crucial to ensure we cultivate and foster engineers who can critically engage with and design for social challenges related to inequality. Previously, our team completed a syllabi analysis of design courses at a technical institution across six different departments (both in engineering and non-engineering fields) through a systematic approach guided by a rubric informed by design justice. Design justice, as conceptualized by the design justice Network, is a framework that explores how a designed artifact distributes benefits and burdens to various groups. As part of this analysis, evaluators of the syllabi provided recommendations for how the instructors could engage with or further embed design justice considerations in the course content. This paper seeks to elucidate strategies for engaging in design justice in design education by analyzing the evaluators’ recommendations from the syllabi analysis to understand what strategies can be used to further embed design justice into design courses. We reveal design justice education strategies related to each of the six departments, finding that there was a wide range of recommendations among the departments often focused on specific technologies related to the discipline but also broad recommendations as well. We synthesize the design justice education pedagogical approaches across the departments, providing a cohesive list of nine pedagogical approaches for design instructors to consider incorporating in their courses when wanting to engage deeper with design justice.
Teaching AI to Design From Humans: a Comparison of Behavioral Cloning Architectures
Authors: Boozarjomehry Ghazal Bozorgmehry , Thekinen Joseph 
Published: November 2023

Abstract
Reinforcement Learning (RL) has created agents with superhuman performance in robotics and gaming. A central issue in using RL methods to automate engineering design is the inability to generalize and slow training. Even the most advanced curiosity-based RL algorithms require exploring millions of design states, which is infeasible with expensive physics models. Data from a human-subject design study shows that even novice human designers can solve design tasks in a few hundred actions. Behavioral cloning allows RL agents to imitate the policies of a human designer from their decision data. We evaluate the performance of a behavioral cloning agent trained on human design decision data collected in a controlled experiment. We compare three popular sequence learning architectures for behavioral cloning. Subsequently, we evaluate an AI design agent trained through behavioral cloning on human design decision data to automatically design an electric aircraft, starting from a baseline design. The results demonstrate that behavioral cloning effectively transfers human strategies to AI design agents with high sample efficiency.
Image Segmentation With Human-in-the-Loop in Automated De-Caking Process for Powder Bed Additive Manufacturing
Authors: Asare-Manu Vincent , Karunathilake Sachithra , Geng Zhaohui 
Published: November 2023

Abstract
Additive manufacturing (AM) becomes a critical technology that increases the speed and flexibility of production and reduces the lead time for high-mix, low-volume manufacturing. One of the major bottlenecks in further increasing its productivity lies around its post-processing procedures. This work focuses on tackling a critical and inevitable step in powder-bed additive manufacturing processes, i.e., powder cleaning or de-caking. Critical concerns can be raised with human involvement when performing this task manually. Since then, a robot-driven automatic powder cleaning system could be an alternative to reducing time consumption and increasing safety for AM operators. However, since the color and surface texture of the powder residuals and the sintered parts are similar from a computer vision perspective, it can be hard for robots to plan their cleaning path. This study proposes a machine learning framework which incorporates image segmentation and eye tracking to de-cake the parts printed by a powder bed additive manufacturing process. The proposed framework intends to partially incorporate human biological behaviors to increase the performance of an image segmentation algorithm to assist the path planning for the robot de-caking system. The proposed framework is verified and evaluated by comparing it with the state-of-the-art image segmentation algorithms.
Steps Toward Development of a Comprehensive Set-Based Design Process Model: A Case Study
Authors: Page Jonathan , Seering Warren 
Published: November 2023

Abstract
Design processes for large-scale and complex projects inevitably involve balancing competing requirements within the solution space. Set-based design has emerged as a method that enables concurrent engineering practices. However, there are few documented cases of its performance at scale. This paper presents a case study of one instance in which a U.S. Navy design team is implementing set-based methods at the system-of-systems scale for the design of an entire large ship. The researchers used participatory action research approaches to explore and document aspects of the undertaking deemed relevant to the design community and to further our understanding of set-based design. This paper describes a number of conceptual structures used to inform the set-based process and provides an overview of the ship design program’s organizational arrangements. The mechanisms by which each engineering team ruled out design options are summarized, along with the ways that teams coordinated to determine preferred system-level options. A special case of point-based design, employed within the set-based process, is shown to work as a virtual prototype for both purposes of experimentation and of communication. The challenge of reasoning and making decisions about design representations at varying abstraction levels is identified as an area of particular difficulty as design teams working in parallel look for agreement. Finally, the paper offers lessons learned and lays out opportunities for future research to inform our understanding of the set-based design process.
Designing Programmable Ferromagnetic Soft Metastructures for Minimally Invasive Endovascular Therapy
Authors: Zhuang Ran , Tian Jiawei , Tassiopoulos Apostolos , Sadasivan Chandramouli , Gu Xianfeng David , Chen Shikui 
Published: November 2023

Abstract
Minimally invasive endovascular therapy (MIET) is an innovative technique that utilizes percutaneous access and transcatheter implantation of medical devices to treat vascular diseases. However, conventional devices often face limitations such as incomplete or suboptimal treatment, leading to issues like recanalization in brain aneurysms, endoleaks in aortic aneurysms, and paravalvular leaks in cardiac valves. In this study, we introduce a new metastructure design for MIET employing re-entrant honeycomb structures with negative Poisson’s ratio (NPR), which are initially designed through topology optimization and subsequently mapped onto a cylindrical surface. Using ferromagnetic soft materials, we developed structures with adjustable mechanical properties called magnetically activated structures (MAS). These magnetically activated structures can change shape under noninvasive magnetic fields, letting them fit against blood vessel walls to fix leaks or movement issues. The soft ferromagnetic materials allow the stent design to be remotely controlled, changed, and rearranged using external magnetic fields. This offers accurate control over stent placement and positioning inside blood vessels. We performed magneto-mechanical simulations to evaluate the proposed design’s performance. Experimental tests were conducted on prototype beams to assess their bending and torsional responses to external magnetic fields. The simulation results were compared with experimental data to determine the accuracy of the magneto-mechanical simulation model for ferromagnetic soft materials. After validating the model, it was used to analyze the deformation behavior of the plane matrix and cylindrical structure designs of the Negative Poisson’s Ratio (NPR) metamaterial. The results indicate that the plane matrix NPR metamaterial design exhibits concurrent vertical and horizontal expansion when subjected to an external magnetic field. In contrast, the cylindrical structure demonstrates simultaneous axial and radial expansion under the same conditions. The preliminary findings demonstrate the considerable potential and practicality of the proposed methodology in the development of magnetically activated MIET devices, which offer biocompatibility, a diminished risk of adverse reactions, and enhanced therapeutic outcomes. Integrating ferromagnetic soft materials into mechanical metastructures unlocks promising opportunities for designing stents with adjustable mechanical properties, propelling the field towards more sophisticated minimally invasive vascular interventions.
A Digital Twin Development Framework for a Smart Saltwater Greenhouse
Authors: Cao Shiang , Chen YangQuan 
Published: November 2023

Abstract
Agriculture in arid areas is often limited by the scarcity of fresh water and increasing soil salinization problems. A saltwater greenhouse that uses salty water instead of fresh water is a promising solution for agriculture in such areas. When used in agriculture irrigation tail water processing, the salt-water greenhouse can be an effective tool for salt extraction which is an important means to mitigate the salinity accumulation problem. However, to optimize greenhouse production and energy efficiency, it is essential to incorporate smartness into the system using existing developments in AI/ML, big data, cloud/edge computing, etc. Therefore, developing a smart saltwater greenhouse leveraging these emerging, cutting edge and groundbreaking technologies becomes a center objective of today’s greenhouse development in general and saltwater greenhouse in particular. In this overview framework paper, we present a Digital Twin development framework for a smart saltwater greenhouse. First, the background of the saltwater greenhouse project is introduced together with the basic concept of smart systems and Digital Twins. The greenhouse control system is introduced with a Digital Twin in mind. We then propose the DT development framework dedicated to the saltwater greenhouse. A five-step DT development framework is reviewed and those new smartness features that could be enabled by using DT are also explained. Finally, we conclude the DT framework with some future research efforts.
Optimal Design and Process Planning for Product Adaptation With Initial Evaluation of Solutions Based on Information Entropy
Authors: Saad Mohammed , Xue Deyi 
Published: November 2023

Abstract
Adaptable products are used to satisfy different and changing customer requirements through changes of products such as reconfiguration and upgrading during their utilization stages. In this research, an optimal design and process planning approach is developed for product adaptation with initial evaluation of solutions based on information entropy. In this approach, various candidates of design configurations and operation processes for adaptation of a product are modelled by an AND-OR tree with design and process nodes. Design and process nodes are further associated with design and process parameters. Optimization to identify the adaptable product design and process is conducted at two levels: configuration/process optimization level and parameter optimization level. Information entropy is employed to evaluate the partial configuration/process candidates modelled as branches in the AND-OR tree to eliminate the branches that are unlikely to lead to the optimal solution for improvement of the optimization efficiency. Numerical example and engineering application are developed to demonstrate the effectiveness of the newly introduced approach.
Profile Synthesis of Profiled-Follower Mechanisms Using the Instant-Center Method
Authors: Shao Jing-Yi , Yang Wen-Huei , Wu Long-Iong , Hsu Kuan-Lun 
Published: November 2023

Abstract
A profiled-follower mechanism is a cam mechanism with a crank to drive a follower. The follower has an irregular profile and undergoes a translating motion or oscillating motion. In some previous literature, more complex mathematics for profiled-follower profiles were derived. This paper aims to synthesize profiled-follower profiles using the instant-center method effectively. In comparison to the past literature, those profile equations formulated in this paper have fewer unknowns and are more comprehensible. Profiled-follower profiles are constructed of contact points between the driving link and the profiled-follower. On this basis, the vector equations of contact points will be formulated first in this paper. After unknowns in the equations are solved, coordinates of contact points can be obtained. With the homogeneous coordinate transformation, various analytical profile equations of profiled-follower can be derived. In addition to those profiled-followers with a singleroller driving link and those conjugate profiled-followers with a roller driving link that have been synthesized in the previous literature, a profile of the constant-diameter profiled-follower with a roller driving link is generated in this paper which has never been mentioned before. For these contents, mathematical expressions are derived and summarized, and examples are provided to illustrate the details of the results.
An Isogeometric Approach for Reaction Diffusion Based Level Set Methods in Topology Optimization
Authors: Kumar Harsh , Rakshit Sourav 
Published: November 2023

Abstract
We present a NURBS based isogeometric analysis (IGA) solution approach to solve reaction-diffusion equation (RDE) based level set topology optimization problems. NURBS based IGA has several advantages like smooth modelling of surfaces, local support, high accuracy and low computational cost. On the other hand, the RDE-based level set method does not require re-initialization of the level set function, which is one of the drawbacks of the level set method. Our method combines the advantages of IGA with the hole-generation and stabilization capabilities of the RDE-based level set method, which has not been shown before. The same NURBS basis function is used for approximating state variables, geometry modelling and level set function. Here, the design variable is defined on the control points of the NURBS geometries and the level set RDE is formulated using the IGA approach. In order to demonstrate the efficacy of our method, we have solved two benchmark topology optimization problems, including compliance minimization and compliant mechanism design problems subjected to volume constraints. The computation cost is calculated for the numerical examples, and it is shown that the IGA approach is more efficient than finite elements for bi-quadratic basis functions. The proposed method is prospective for developing a combined topology and shape optimization approach using IGA.
Wrench Capability Analysis of a Planar Dual-Platform Cable-Driven Parallel Robot
Authors: Rasheed Tahir , Long Philip , Padir Taskin , Caro Stéphane 
Published: November 2023

Abstract
Cable-Driven Parallel Robots have several advantages over both conventional serial and parallel robots, notably in terms of scalable workspace. These robots could provide an alternative to mobile and gantry crane systems, increasing payload stability, allowing higher accelerations and reducing cost. However, in order to provide such capabilities, the base attachment points must be located outside the workspace boundaries, meaning that the cables form straight lines running through the workspace to the mobile platform. Consequently, such systems can only feasibly operate in unencumbered locations, or alternatively, be configured with a specific task in mind thus severely limiting their functionality. One potential solution to this problem is a composite mechanism that docks then deploy a sub-mechanism. In this paper, a methodology is proposed to obtain the Wrench-Feasible-Workspace of a composite Cable-Driven Parallel Robot by determining its Available Wrench Set. We define three operation modes of such system and show that the Available Wrench Set in each operation mode depends on the static equilibrium of the dual-platform and contact conditions. The Available Wrench Set is constructed by the Hyperplane Shifting Method and is validated in simulation.
Achieving High Performance and Low Cost: Development of a High-Performing Passive Prosthetic Knee for Emerging Markets
Authors: Reddie Madison , Bedi Saloni , Vaidya Manasi , Griffin Amari , Petelina Nina T. , Winter Amos G. 
Published: November 2023

Abstract
There is significant need for low-cost, high-performance prosthetic knees in low- and middle-income countries (LMICs) due to a large number of amputees and particularly challenging socioeconomic and environmental conditions. Prostheses are important for maintaining one’s participation in society, culture, and the economy, but many are either prohibitively expensive or do not provide near-able-bodied kinematics. Poor performing prosthetic knees cause discomfort and draw unwanted attention to transfemoral amputees. In this study, we refine the design of a high-performing, single-axis, passive prosthetic knee developed with a focus on the Indian market in order to reduce cost, weight, and part count; enhance manufacturability; and improve aesthetics. The load paths and functional componentry were critically analyzed to identify opportunities to streamline the design while maintaining strength and the near-able-bodied kinematics offered by the original design. The part count was reduced almost four-fold, and the mass of the prosthesis was reduced three-fold. An enclosure was also designed to encase the functional componentry in an aesthetically acceptable package. The changes made to the design are believed to significantly advance the usability and commercial viability of the prosthetic knee. This study may serve as an example of how products developed for emerging markets may achieve affordability without sacrificing performance.
From Obstacles to Opportunities: How Perceptions of Psychological Safety Affect Founders’ Abilities to Identify Resources
Authors: Letting Cynthia , Calpin Nicole , Soria Zurita Nicolás F. , Menold Jessica 
Published: November 2023

Abstract
Resources are a dynamic aspect of team problem solving and the ability to properly manage them is a critical factor for success. Engineering design teams often face challenging resource deficits, and effective resource management is paramount in resource constrained environments. While prior work has linked effective resource management at the firm level with the climate of the firm, little work has explored these linkages at the team level. Here, we study the interactions between team climate and the ability to identify meaningful resources that mitigate current obstacles. We quantify team climate as individual perceptions of psychological safety, or one’s perception of the team’s willingness to engage in interpersonal risk taking. In this work, we leveraged data from thirty-two startup company founders, a population of authentic problem solvers that often operate in resource constrained environments, to study this relationship. The results from our mixed-methods study indicate that individual perceptions of psychological safety predict founders’ ability to identify meaningful resources to mitigate obstacles they are currently facing. Thus, problem solvers that perceive their team climate to be more positive, or more psychologically safe, exhibit a greater ability to identify meaningful resources.