bluuebunny/crossref_metadata_2025 huggingface dataset:
Adaptive Optimization of Subjective Design Attributes: Characterizing Individual and Aggregate Perceptions
Authors: Nandy Ananya , Goucher-Lambert Kosa
Published: November 2023

Subjective attributes play a significant part in the assessment of user-facing products. Unlike performance requirements, these quantities are best evaluated through human feedback. While people share commonalities in their evaluations, allowing personalization when quantifying these subjective attributes may improve the alignment between computational and human representations of design information. We investigate this topic through a study in which participants (N = 56) make a series of pairwise decisions between parameterized mugs, and indicate their perceptions of how comfortable each is to hold. Interactive Bayesian optimization is used to adaptively arrive at a design that optimizes this subjective quantity. Participants guide the model through only their own decisions or make decisions using a model that has already been trained with simulated data (N = 25) or data from the real decisions of other participants (N = 31). The resulting designs are evaluated across the different cases, showing the impact of capturing individual and aggregate perceptions of subjective quantities. The findings imply that balancing aggregate and individual-level decisions within models simultaneously results in the best alignment with human perceptions of subjective attributes. Further implications for design include the potential for personalized control over subjective attributes for designers, users, or users-as-designers.
Subject-Specific Musculoskeletal Modeling of Adolescent Scoliosis Patients: a Pilot Study
Authors: Baus Juan , Cheng Zhiqing , Yang James
Published: November 2023

This paper presents developing and validating an algorithm-based protocol to build subject-specific musculoskeletal models using X-ray images and motion capture data. The MATLAB algorithm used bilateral X-ray images to determine the deviation angle of each vertebra in the frontal and sagittal planes and motion capture data to define the rest of the bone structure in a static posture. Previously validated musculoskeletal models were used as templates to avoid the necessity of scaling to each subject. Inverse kinematics and static optimization tools in OpenSim were used to define the joint angles and muscle activation for a scoliosis-specific exercise. Validation was done for the algorithm by comparing the vertebrae rotation angles with those obtained from a public database of scoliotic spine patients. The results showed that the Cobb angle deviation from the algorithm is smaller than the reported standard deviation for experimental measurements. Despite the successful simulation of muscle activation around the convex and concave sides of the scoliotic spine, future research could improve the protocol by including axial rotation of vertebrae and muscle scaling factors to enhance the individualization of each model. Nevertheless, the present protocol can create an individualized musculoskeletal model for a scoliosis patient.
Multi-Material and Multi-Joint Topology Optimization Considering Multiple Design Spaces
Authors: Kim Il Yong , Huang Yuhao , Crispo Luke
Published: November 2023

Today, automakers are focusing on cost reduction and lightweighting, by utilizing a combination of different materials in the vehicle design. Topology optimization is a numerical tool that provides more design freedom than other methods, such as size optimization and shape optimization. Multi-material topology optimization can optimize both material layout and material distribution to improve structural performance. However, these methods assume that dissimilar materials are perfectly bonded, which limits the manufacturability of the design. This work presents a multi-material and multi-joint topology optimization methodology that considers additional design variables for joints in the material interface region. The mechanical properties of joints are included in the analysis, which affects the overall structural behavior and the optimized result. This paper firstly introduces topology optimization methods and material interpolation functions for multiple design spaces. Then, the material interface region detection method is explained. After that, sensitivity analysis for different responses is conducted. Lastly, the results of some example models demonstrate this methodology can be used to control mass and joining cost in multiple design spaces within a structure.
Analytical Modeling and Validation of New Prismatic Compliant Joints Based on Zero Poisson’s Ratio Lattice Structures
Authors: Arredondo-Soto Mauricio , Cuan-Urquizo Enrique , Gómez-Espinosa Alfonso
Published: November 2023

Prismatic compliant joints have received limited attention compared to revolute compliant joints, thus limiting their implementation in compliant mechanisms. Lattice structures have been used effectively to increase flexibility and stiffness ratios in compliant joints. Considering these, new prismatic compliant joints based on zero Poisson’s ratio lattice structures (ZP-PCJ) are proposed. Lattices with three different cell arrangements are considered: single cells, 2 × 2, and 3 × 3 lattices. Additionally, unit cells with three different geometries are studied: triangular, chamfer, and cosine. The compliance matrices of the ZP-PCJs are assembled analytically using Castigliano’s second theorem and compliance series-parallel simplification. The compliance ratios along the three orthogonal axes of the ZP-PCJs are computed varying their geometric parameters. Finite Element models are constructed to validate the analytical results. Finally, experimental tests are performed on additively manufactured ZP-PCJs to corroborate the compliance coefficients. Results showed that analytical models can predict the ZP-PCJ’s elastic properties accurately, differences less than 3% and 15% were obtained when compared to computational and experiments, respectively. The ZP-PCJs have advantages such as eliminating axis drift and high flexibility in motion direction while maintaining stiffness in other directions due to their symmetric arrangements (with respect to the motion direction) and their zero Poisson’s ratio. The analytical models of ZP-PCJs derived, showed excellent agreement when compared with simulations and experimental results, making them a reliable option when aiming to estimate their performance in compliant systems.
Flank Modification Based on the Predetermined Contact Characteristics for Spiral Bevel and Hypoid Gears
Authors: Lee Yi-Hui , Chen Kuan-Hung , Fong Zhang-Hua
Published: November 2023

Spiral bevel and hypoid gears usually apply the flank modification with point contact to reduce gear running noise and avoid edge contact. This paper proposes the flank modification methodology based on the predetermined contact characteristics without the necessity of the tooth contact analysis. With the given gear member tooth surface, the conjugated pinion tooth surface can be derived by considering the mating gear as the cutter to roll with the work pinion. The center point of tooth-bearing is directly controlled, and the bias angle of the contact point path is designed based on the overlap ratio. Then, the flank modifications along the contact point path and the instantaneous contact lines are determined by the anticipated transmission errors and the elastic deformation as well as the length of the major axis of the contact ellipse. The generated tooth surface is approaching the modified flank by optimization. Additionally, the initial guesses for the optimization, such as the cutter parameters and the machine settings using the face-milling method, are calculated based on the theory of gearing and differential geometry. A numerical example of face-milled hypoid gear generated by the universal cradle-type generator is presented to demonstrate the validity of the proposed flank modification methodology.
Design of Mixed-Category Stochastic Microstructures: A Comparison of Curvature Functional-Based and Deep Generative Model-Based Methods
Authors: Xu Leidong , Naghavi Khanghah Kiarash , Xu Hongyi
Published: November 2023

Bridging the gaps among various categories of stochastic microstructures remains a challenge in the design representation of microstructural materials. Each microstructure category requires certain unique mathematical and statistical methods to define the design space (design representation). The design representation methods are usually incompatible between two different categories of stochastic microstructures. The common practice of pre-selecting the microstructure category and the associated design representation method before conducting rigorous computational design limits the design freedom and reduces the possibility of obtaining innovative microstructure designs. To overcome this issue, this paper proposes and compares two methods, the deep generative modeling-based method and the curvature functional-based method, to understand their pros and cons in designing mixed-category stochastic microstructures for desired properties. For the deep generative modeling-based method, the Variational Autoencoder is employed to generate an unstructured latent space as the design space. For the curvature functional-based method, the microstructure geometry is represented by curvature functionals, of which the functional parameters are employed as the microstructure design variables. Regressors of the microstructure design variables-property relationship are trained for microstructure design optimization. A comparative study is conducted to understand the relative merits of these two methods in terms of computational cost, continuous transition, design scalability, design diversity, dimensionality of the design space, interpretability of the statistical equivalency, and design performance.
Investigations on Ways to Improve the Scuffing and Wear Behaviour of Oil Free Water-Based Lubricants for Gear Applications
Authors: Barth Yves Johannes , Sagraloff Nadine , Egger Gregor , Tobie Thomas , Stahl Karsten
Published: November 2023

Today, mineral or synthetic oils that are made out of fossil raw materials, are the most common lubricants in gear drive applications. Most of them are non-biodegradable and may pose a risk to the environment. An important step to minimize the risk and the ecological footprint is the use of biodegradable and eco-friendly lubricants. Former research shows the potential of water-based lubricants in gear applications. Therefore, an oil-free, water-based lubricant, was developed for this study. The base lubricant contains plant-based thickeners to generate an appropriate viscosity for a sufficient lubricant film thickness in the tooth contact. In experimental investigations, the sliding wear and scuffing performance has been examined under variation of the added polymers and additives. The scuffing tests A/8.3/RT are performed acc. to DIN ISO 14635-1. The wear tests procedure is based on DGMK 377-01. In both scuffing tests with the sample the failure load stage = 8 was achieved. For case-carburized gears a “medium” to “high” amount of wear can be detected. Additional tests with nitrided gears show a “low” amount of wear. This paper aims to show the great potential of water-based oils for gear lubrication and suggests operating conditions for maximum wear and scuffing carrying capacity.
Design and Justice: A Scoping Review in Engineering Design
Authors: Syal Sita M. , Kramer Julia
Published: November 2023

Our society faces complex social justice challenges, often exacerbated by existing engineered products and technologies. Engineering designers play a critical role in creating and studying products and technologies that can both aim to solve and unintentionally contribute to social injustice. There is a growing priority in the engineering design research community to incorporate justice into design work and to do so meaningfully and intentionally. Therefore, there is a need to more deeply understand how scholars have integrated concepts of justice into their design work and to bring to light areas of future research. In this paper, we conduct a scoping review of design and justice in eleven scholarly venues relevant to the engineering design community. A scoping review allowed for a broad range of topics to be covered to identify major research themes and gaps, and to explore boundaries of the nascent study of design and justice. After searching the relevant venues, we conducted a thematic analysis to capture the major themes in the dataset of papers relating to justice and design. We found that scholars connected justice to their design work in ways that can be categorized into three main areas of design: Designers, Design Outcomes, and Design Process. Our analysis highlighted areas of future research in studying justice as relevant to Designers, Outcomes, and Processes, as well as identifying an overall call to redefine design as a whole in the pursuit of justice.
Design and Optimization of a Wearable Under-Actuated Mechanism for Spinal Posture Measurement
Authors: Hsu Ming-Chang , Chen Hsuan-Yu , Yeh Ting-Jen
Published: November 2023

This paper proposes a novel wearable device that can monitor the spinal posture. The proposed device adopts an underactuated mechanism design which allows it to adapt to the multiple-degrees-of-freedom spinal posture with minimum weight and complexity. To ensure the validity of measurement and comfort of wearing, the mechanism parameters are determined by an optimization algorithm so that uniform contact forces for selected spinal postures can be achieved. Experiments demonstrate that the device can automatically maintain contact with the wearer’s back and produce real-time spinal posture data for medical diagnosis and treatment.
On-the-Fly Dual Reduction Method on Transient Fluid Topology Optimization
Authors: Wang Tianye , Qian Xiaoping
Published: November 2023

Transient topology optimization (TO) requires huge computational resources in terms of both computing time and storage. In this study, we have applied the proper orthogonal decomposition (POD) based on-the-fly dual reduction method on TO problems for time-dependent incompressible fluid channel optimization. The fluid motion was governed by time-dependent Navier-Stokes equation. Total energy dissipation over a given period was considered as the cost function, and total fluid volume was constrained during optimization process. POD based reduced order modeling (ROM) was applied to both the primal equations and the adjoint equations for reduction. We examined the reduction efficacy though examples including U-bend channel and nozzle. Tolerance and snapshot set size were studied as hyper-parameters to improve the reduction performance. The best cases can reach 99% of skip ratios, 50% reduction in computational time, and 96% saving of memory storage.
Selection of Inverse Kinematics Solution Type for Cooperative Robots and Singularity Avoidance Based on Reinforcement Learning
Authors: Kato Daiki , Maeda Naoki , Takeuchi Ayumu , Sekioka Masataka , Hirogaki Toshiki , Aoyama Eiichi
Published: November 2023

In this study, we propose a method to avoid singularity by selecting solution types of inverse kinematics for a six-degree-of-freedom (6-DOF) manipulator based on reinforcement learning. A general 6-DOF manipulator has eight solution types of inverse kinematics for any position/posture of the end-effector. Owing to the complex structure of cooperative robots to prevent pinching during cooperative operations, inverse kinematics is often solved using numerical methods. Because the numerical solution depends on the initial values, it is difficult to select suitable solution types. According to the selection of the solution types, the robot may pass through a singularity, causing some joints to rotate rapidly. To avoid this, solution types must be selected considering the entire motion path of the robot. Therefore, we constructed Deep Q-Learning (DQN), a type of reinforcement learning, to select the solution types that minimize the angular velocity of each joint during the motion path. This was verified by a 6-DOF cooperative robot, where the robot was commanded to take a path through the singularity, and the solution types of inverse kinematics were selected by the DQN. Consequently, singularity was avoided by selecting suitable solution types, and the angular velocity was minimized.
Numerical Analysis and Wave Tank Test of a Point Absorber Wave Energy Converter Using a Tether Driven Power Take-Off System
Authors: Zhang Hu , Sun Liang , Liu Jingxuan , Mi Jia , Li Xiaofan , Xu Lin , Zuo Lei
Published: November 2023

Technologies to enhance the survivability of wave energy converters (WECs) in harsh ocean environment and reduce the difficulty and cost of deployment and operation are important. Traditional two-body point absorber with a rigid Power Take-off (PTO) may result in two essential problems on the deployment and operation. This study proposes a novel a two-body self-reactive point absorber with a flexible tether drive PTO. This flexible PTO design can avoid the request of supporting structures on the WEC to constrain the motion and harvest energy from multiple degree of freedoms (DOFs) motion without requirement of a taut mooring. System dynamics considering 4-DOF with the proposed flexible PTO system are formulated. A scaled prototype is designed, fabricated, and tested in a wave tank. Results show that the proposed flexible PTO can greatly increase the power absorption and add a reactive peak in the frequency domain. This study reveals that the proposed PTO is desirable for the two-body point absorber and thus holding the advantages of fast and easy deployment with slack mooring and good survivability under large wave conditions.
Print As a Dance Duet: Communication Strategies for Collision-Free Arm-Arm Coordination in Cooperative 3D Printing
Authors: Stone Ronnie F. P. , Zhou Wenchao , Akleman Ergun , Krishnamurthy Vinayak Raman , Sha Zhenghui
Published: November 2023

One of the major challenges in 3D printing is its lack of scalability both in size and speed, which directly impacts its economic feasibility for large-scale industrial applications. Cooperative 3D printing (C3DP) is an emerging paradigm that aims to address these issues by employing multiple mobile printers that work in parallel. However, a crucial step in enabling C3DP is the development of a collision-free communication framework between the printers during the manufacturing process. Many C3DP systems found in the literature develop solutions for collision-free printing that are specific to the setup being used, thus not allowing the solution to be transferred to other similar systems. In this paper, we formulate a general framework that generates four distinct collision-free communication strategies to enable arm-arm coordination for C3DP using robotic manipulators. We considered collisions both between the arms with themselves and between the arms and the part being printed. The strategies are general in that they are agnostic to the number of printers, their kinematics, and their spatial configurations in the manufacturing environment. We conducted a study of the four strategies using a two-printer scenario and then physically validated them with four test cases of varying geometries. The results show that the strategies successfully produce printed parts while being collision-free. The makespan reduction using our strategies when compared to a single printer varied from 20% to 42% depending on the strategy used. Finally, we discuss the limitations of the framework, as well as future research directions.
Defining and Modeling of Height-Related Geometrical Parameters for Thin Wall Structures Manufactured by Metal Additive Manufacturing
Authors: Rahmani Dehaghani Mostafa , Tang Yifan , Panicker Suraj , Wu Di , Coatanea Eric , Wang G. Gary
Published: November 2023

Cold metal transfer wire and arc additive manufacturing (CMT-WAAM) is a type of metal additive manufacturing technology that has attracted attention in recent years due to its ability to print walls with less dimensional inaccuracies than regular WAAM. To print near net shape parts by CMT-WAAM, there is a need to define a set of height-related geometrical parameters (HGPs) that can capture, quantify, and compare the quality of the height of the produced parts. In this study, a set of HGPs, namely, the average height error (AHE), maximum height variation (MHV), and average absolute slope (AAS) are defined and assessed. Fifteen single-track multi-layer walls are printed to check the effect of process parameters on the defined HGPs. It is found that the stability of the print cannot be guaranteed by checking the visual appearance of the single beads and at least five-to-ten-layer walls should be printed to check the quality and stability of the print. It is also found that the travel speed (TS) and wire feed speed (WFS) have positive monotonic relationships with AAS and MHV, respectively. Correlations between process parameters and HGPs are modeled and validation tests are performed to check the validity of the developed models. The defined three HGPs are shown to be able to quantify, capture, and compare the quality of a height of a wall and can be used for other similar applications.
Testing and Validation of a Mobile Damping Robot for Power Lines
Authors: Choi Andrew , Barry Oumar
Published: November 2023

Fixed passive vibration absorbers (FPVAs) are widely used on power lines and other continuous systems, but they are inherently limited since changes in wind conditions affect absorber performance due to changing mode shapes. A mobile damping robot (MDR) can overcome these limitations by actively transporting a passive absorber to conductor antinodes where the absorbers can most effectively remove energy from the system. While many analyses have been performed for fixed masses on power line conductors, they have not been in the context of interactions between the conductor and a mobile damping robot (MDR). There is a need to explore the potential impact of the MDR on the power line and the resulting implications for the MDR’s development as current methods of vibration control do not adequately address fatigue failure caused by wind-induced vibrations (WIV). In this paper, we define a mathematical model of the system and perform numerical analysis in MATLAB® using equations of motion obtained via Hamilton’s Principle. We investigate the adequacy of an experimental test bench for testing. Then we experimentally validate the ability of a mobile robot to transport a mass along a conductor to antinode locations. Experimental results indicate that the robot is able to navigate to the locations of highest amplitude on the cable. The insights gained from this work lay a foundation to guide future experiments that will better define the operating conditions of the MDR and lead to the creation of an appropriate control framework.
Localisation of Mobile Robots via Ultra-Wideband Systems
Authors: Neri Federico , Annoni Luca Alfredo , Palmieri Giacomo , Palpacelli Matteo-Claudio , Callegari Massimo
Published: November 2023

This paper presents an innovative solution that allows an autonomous mobile robot (AMR) to locate itself in space via UWB nodes. This reduces the possibility of error caused by the modularity of warehouses and makes it possible to send variable missions based on the data received. To this end, it was decided to use ultra-wideband (UWB) nodes, which allow to calculate the spatial coordinates of a reference tag with respect to the robot. Using this approach, material was taken from a storage facility and loaded on board using an anthropomorphic arm positioned on the mobile robot. Subsequently, other reference tags are used to locate a mobile truck equipped with a loading platform. In this way, a mission can be sent to the mobile robot to get on the truck and be transported to another work area. The article describes the advantages and difficulties of this localisation methodology and shows how tests were carried out to verify its functioning. The study is part of eMOBOTS (electric mobility robot & shuttle), a project that aims to develop mobility solutions for the smart factory developed by TEKNE srl, the Department of Industrial Engineering and Mathematical Sciences, Polytechnic University of Marche and the company Joytek.
Effect of Cross-Axis Pivots Orientation on Accuracy Performance of Compliant Mechanisms
Authors: Serafino Simone , Fanghella Pietro , Verotti Matteo
Published: November 2023

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

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

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

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

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

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

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

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

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

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

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

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

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

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.