bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pareto Front Exploration for Hypoid Gear Multi-Objective Optimization Model
Authors: Wei Xinqi , Wang Yawen , Zhang Weiqing , Lim Teik C. 
Published: November 2024

Abstract
Optimizing hypoid gear is crucial in modern gear design to meet the increasing demand for high durability, high efficiency, and low noise. The Pareto front is used to illustrate the trade-off between the conflicting objectives in multi-objective optimization models. However, exploring the Pareto front optimization space for hypoid gear is challenging due to its non-convex nature and non-linearity, primarily caused by the complex contact behavior. These complexities often result in larger computational costs and can lead to the convergence of optimization into a local solution rather than a global one. In this study, a multi-objective optimization model is established to optimize hypoid gear contact performance such as the peak-to-peak value of loaded transmission error and maximum contact pressure. The Pareto fronts of optimization objectives are obtained based on the Pattern Search method. To explore the optimizable space of the Pareto front, the various initial values and optimization objectives range are specified. Several Pareto front and corresponding solution distributions are obtained and analyzed. Also, the best trade-off optimization solutions are reported to demonstrate the effectiveness and correctness of optimization. The results show that the optimization space of the local Pareto front has been explored effectively and gives insight for gear designers to decision-making.
Development of a Rapid Response Online Product Marketplace
Authors: Elhabashy Ahmed E. , Günay Elif Elçin , Sim Jaemun , Clements Mark W. , Benaggoun Hamza , Kabiri Mahdi , Haapala Karl R. , Okudan Kremer Gül E. , Kim Kyoung-Yun 
Published: November 2024

Abstract
The coronavirus pandemic has exposed deficiencies of global supply chains in rapidly responding to urgent medical needs and demonstrated the challenge of promptly acquiring medical supplies during emergencies. Even under policy tools and using existing online alternatives, being able to promptly acquire medical supplies, including personal protective equipment and medical devices, is still a concern for future emergency situations. Hence, the details for an open, extensible, service-oriented cloud platform that enables the rapid matchmaking between consumers and manufacturers in emergency situations is presented in this work. More specifically, the system architecture deployed for the platform, along with the details of its main components are discussed. In addition, the results of implementing a simplified prototype of the platform, where a healthcare worker is using the online product marketplace to make an order for a replacement part of a respirator mask, are also briefly demonstrated. By using this online product marketplace, manufacturers will benefit from improved accessibility to their products, services, and manufacturing resources (even under normal operations), while consumers will gain unprecedented access to existing products and manufacturing resources. The platform also has the potential to improve the nation’s ability to prevent, prepare for, and respond to future pandemics or other emergency events.
Analyzing Bifurcations of a Three-Degree-of-Freedom Gear Transmission Considering Multi-Piecewise Linear Functions
Authors: Liao Fulin , Huang Jianliang , Zhu Weidong 
Published: November 2024

Abstract
Bifurcations of a gear transmission system subjected to forced excitations considering multi-piecewise linear functions are investigated in this work by using the incremental harmonic balance (IHB) method. The nonlinear motion ordinary differential equations of the gear transmission system are formulated by employing the Newton’s second law. Analytical results reveal abundant bifurcation phenomena, including period-doubling bifurcations, saddle-node bifurcations, and Hopf bifurcations, which have not been exhibited in existing investigations on nonlinear behaviors of the gear transmission system. The bifurcation types are determined with the ways leaving the unit circle of Floquet multipliers.
Multi-Lattice Topology Optimization With Lattice Representation Learned by Generative Models
Authors: Chen Jiangce , Baldwin Martha , Narra Sneha , McComb Christopher 
Published: November 2024

Abstract
Additive manufacturing (AM) technologies are often capable of fabricating geometries that are more complex than traditional manufacturing methods. A notable innovation enabled by AM is the fabrication of multi-lattice structures, an advanced design concept featuring an array of heterogeneous lattices in the mesoscale that are arranged to achieve a diverse distribution of material properties at the macroscale. Compared to uniform lattice structures, multi-lattice structures permit greater design freedom and a larger design space, which makes it possible to achieve superior structure performance. However, the expanded design space introduces a substantial increase in the complexity of multi-lattice structure design. There is still lack of an optimization framework that can maximize the physical properties of the macro-structures through fully exploiting lattice diversity while ensuring lattice connectivity.
To solve these challenges, this paper introduces a multi-scale topology optimization (TO) framework for multi-lattice structures which simultaneously optimizes the structure topology at macroscale and the lattice heterogeneity at mesoscale. The distribution of the pseudo-densities and lattice parameters are represented by neural networks (NNs) whose weights and biases are the design variables. The spatial gradients of NN over the physical domain reflect the dissimilarity of adjacent lattices. So, the connection between the lattices can be implicitly constrained by restricting the spatial gradients of NNs. The diversity of the lattices is guaranteed through a generative lattice model which is trained over a large lattice dataset and is embedded into the optimization framework. The performances of various NN types are compared, and we found that Fourier Neural Operators (FNOs) have the best flexibility in balancing the lattice diversity and local connectivity. In the design problems of structural compliance minimization under complex loading conditions, our results show that the multi-lattice TO structures achieve a higher stiffness-to-weight ratio than normal TO structures.
Beyond the Paper: Exploring the Relationship Between the Participation of Women and the Social Relevance of Research Topics in Engineering Design
Authors: Running Ivyann O. , Parkinson Bethany , Magleby Spencer , Toh Christine 
Published: November 2024

Abstract
The increase in participation of women in Science, Technology, Engineering, and Mathematics (STEM) fields has not been uniform. In mechanical engineering, the proportion of women who participate in the profession at all levels is disproportionately low. One factor identified by education researchers that has the potential to draw higher numbers of women to the discipline is the presence of socially relevant and impactful applications of science concepts. To better understand this relationship, the gender distribution of researchers participating in sub-conferences within the mechanical engineering International Design Engineering Technical Conferences & Computer and Information in Engineering (IDETC-CIE) was investigated. The social relevance of publications within two sub-conferences with differing levels of women participants, the “Design Theory and Methodology” (DTM) and “Mechanisms and Robotics Conference” (MR), was compared. Our results showed that both sub-conferences had comparable numbers of socially relevant papers, but differed in terms of which categories of social relevance were emphasized and if specific populations were explicitly mentioned in the studies. These results indicate that the relationship between the participation of women in engineering research communities and the focus on socially relevant applications is complex and multifaceted, potentially affected by not just if socially relevant concepts are studied, but also how these concepts are integrated into the shared values and norms of each community.
A Framework to Support Co-Design Exploration of Manufacturing Supply Networks for Resilience
Authors: Baby Mathew , Mukundan Pooja , Nellippallil Anand Balu 
Published: November 2024

Abstract
Manufacturing Supply Networks (MSNs) involve group decisions to achieve group goals and network decisions to achieve network goals. These decisions are made across multiple levels of a decision hierarchy. Given the frequent disruptions in MSNs, ‘resilience’ — the ability to maintain satisfactory network functionality despite disruptions, is a vital network goal. When designing MSNs for resilience, the resilience and group goals often conflict, requiring simultaneous consideration of network and group decisions. Limited information in the early stages of MSN design necessitates focusing on design exploration. Hence, facilitating ‘co-design exploration’ — a simultaneous exploration of network and group solution spaces is crucial.
Current approaches for designing MSNs for resilience do not support simultaneous consideration of network and group decisions. To bridge this gap, we present the Co-Design Exploration of MSNs for Resilience (CoDE-MR) framework to facilitate co-design exploration of the network and the groups.
CoDE-MR framework allows designers to model multilevel network and group decisions and their interactions, manage disruptions, and visualize and simultaneously explore the multilevel network and group solution spaces. In the framework, we integrate a combination of Preemptive and Archimedean formulations of the coupled-compromise Decision Support Problem construct with Resilience Index metric and interpretable Self-Organizing Map (iSOM)-based visualization to facilitate co-design exploration of MSNs for resilience. The framework’s efficacy is demonstrated using a steel MSN test problem, considering network and group decisions across two levels. The use of information flow and generic constructs makes the framework generic and well-suited for co-design exploration of multilevel systems to ensure resilience.
Trajectory Following Control of a Cable Driven Parallel Robot on Planes With Various Inclined Angles
Authors: AlQaydi Maitha , Yu Ziqing , Jin Lei , AlAttar Ahmad , Taha Tarek , Gan Dongming 
Published: November 2024

Abstract
This paper explores the control mechanisms for Cable-Driven Parallel Robots (CDPRs) operating on inclined surfaces and addresses the challenges introduced by gravity. It provides a comprehensive analysis aimed at evaluating the effectiveness of various control strategies, including Proportional-Derivative (PD) controllers, gain scheduling, and Active Disturbance Rejection Control (ADRC), across different inclinations. The study explores how these approaches contribute to maintaining operational efficiency and precision in trajectory generation. The effectiveness of the proposed control model in generating trajectories is demonstrated through simulations. These simulations reveal the limitations of PD controllers, gain scheduling for CDPRs on inclined surfaces, and show ADRC as a better alternative. This research significantly improves the efficiency and accuracy of CDPRs in trajectory generation, broadening their practical applications across diverse scenarios.
Topology Optimization of Multibody Systems Undergoing Dynamic Loading Using an Equivalent Static Displacement Method
Authors: Gupta Aakash , Tovar Andres 
Published: November 2024

Abstract
Structural topology optimization for vehicle structures under static loading is a well-established practice. Unfortunately, extending these methods to components subjected to dynamic loading is challenged by the absence of sensitivity coefficients: analytical expressions are unavailable and numerical approximations are computationally impractical. To alleviate this problem, researchers have proposed methods such as hybrid cellular automata (HCA) and equivalent static load (ESL). This work introduces a new approach based on equivalent static displacement (ESD). The proposed ESD method utilizes the nodal displacement of the dynamic analysis at various simulation times to define the boundary conditions for corresponding models — one model per simulation time. A scalarized multi-objective function is defined considering all the models. A gradient-based optimizer is incorporated to find the optimal topology. Then, a new dynamic analysis is performed, the new ESD is defined for each model, and a new topology is obtained. The iterative process continues until convergence. Furthermore, this work also demonstrates the extension of the proposed ESD method in the topology optimization of multibody systems. To this end, the result shows an internal combustion engine’s iterative topology optimization of the connecting rod and piston. Additionally, results from multiple load case problems have been presented to prove the effectiveness of the ESD methodology.
Towards Physically Talented Aerial Robots With Intelligent Swarm Behavior Thereof: an Efficient Co-Design Approach
Authors: KrisshnaKumar Prajit , Paul Steve , Manjunatha Hemanth , Corra Mary , Esfahani Ehsan , Chowdhury Souma 
Published: November 2024

Abstract
The collective performance or capacity of collaborative autonomous systems such as a swarm of robots is jointly influenced by the morphology and the behavior of individual systems in that collective. In that context, this paper explores how morphology impacts the learned tactical behavior of unmanned aerial/ground robots performing reconnaissance and search & rescue. This is achieved by presenting a computationally efficient framework to solve this otherwise challenging problem of jointly optimizing the morphology and tactical behavior of swarm robots. Key novel developments to this end include the use of physical talent metrics and modification of graph reinforcement learning architectures to allow joint learning of the swarm tactical policy and the talent metrics (search speed, flight range, and cruising speed) that constrain mobility and object/victim search capabilities of the aerial robots executing these tactics. Implementation of this co-design approach is supported by advancements to an open-source Pybullet-based swarm simulator that allows the use of variable aerial asset capabilities. The results of the co-design are observed to outperform those of tactics learning with a fixed Pareto design, when compared in terms of mission performance metrics. Significant differences in morphology and learned behavior are also observed by comparing the baseline design and the co-design outcomes.
Investigating Mechanical Behavior of 3D Printed Compliant and Origami-Inspired Mechanisms
Authors: Parkinson Bethany , Martel Austin , Wing Davis , Magleby Spencer 
Published: November 2024

Abstract
The fused filament fabrication 3D printer is growing in popularity amongst designers. When manufacturing actuating mechanisms, however, it can often be difficult to use 3D printers to achieve desired behavior. Two essential areas of active mechanisms — compliant mechanisms and origami-based mechanisms — are explored in this paper.
The design of compliant mechanisms for specific applications often requires them to achieve specific kinetics, which necessitates knowledge of material and mechanical properties. When 3D printing with polymers, mechanical properties vary widely based on a variety of factors, including process parameters. Through a thorough study involving systematically changing several parameters of the slicer and performing a three-point bending test on a 3D printed specimen, mechanical properties for a variety of parameters are recorded. These tests indicate that compliant mechanisms can be 3D printed from polymers to achieve desired mechanical properties from the mechanism.
Manufacturing origami-inspired mechanisms often requires assembly, where precise alignment of panels is essential. Through changing process parameters, thickened origami flashers and patterns may be 3D printed in a single operation, thus eliminating the need for assembly. This is achieved through designing compliant living hinges into the 3D model and altering process parameters to ensure that these hinges are flexible and durable.
Through using these process parameters and test results or through applying the framework presented here with their own 3D printer or material, designers can more effectively use 3D printing to design and rapidly prototype compliant mechanisms and origami-inspired mechanisms.
ConceptVis: Generating and Exploring Design Concepts for Early-Stage Ideation Using Large Language Model
Authors: Duan Runlin , Karthik Nachiketh , Shi Jingyu , Jain Rahul , Yang Maria C. , Ramani Karthik 
Published: November 2024

Abstract
Large language models (LLMs) are capable of generating cross-domain design knowledge, opening up new possibilities for creating a myriad of design concepts for early-stage design ideation. The current interfaces and interaction capabilities of LLMs, however, pose challenges in controlling the ideation process in terms of its diversity and quality. To enhance human guidance over the LLM-driven ideation process, we have developed ConceptVis, a system that organizes and symbiotically coordinates the LLM-generated design space through an interactive knowledge graph. In ConceptVis, designers can easily control the breadth and depth of the design space by intuitively prompting the LLM from the graph nodes. Natural Language Processing (NLP) algorithms extract concept keywords and related design knowledge from LLM responses, which are then added to the knowledge graph for visualization. We conducted a user study with 24 novice designers and compared the performance of ConceptVis with that of a chat-based LLM interface for concept generation. With ConceptVis, designers can explore the design space with a balance of breadth and depth. This approach prevents them from merely prompting the LLM to generate random concepts, struggling to keep track of what has been generated in long linear lists, or fixating on early ideas. Supporting users to interact with LLMs through an interactive visual interface significantly improves both the efficiency and quality of concept generation. This result highlights the importance of developing user-centered design systems to facilitate human-LLM collaboration during the early stages of design.
Transitioning Towards Circular Consumer Electronics Products
Authors: Ko Junwon , Guedes Gisele Bortolaz , Badurdeen Fazleena , Jawahir I. S. , Morris K. C. , Ferrero Vincenzo 
Published: November 2024

Abstract
In the present digital era, consumer electronics have become ubiquitous, providing numerous conveniences in various aspects of daily life. However, the significant increase in the production and use of consumer electronics products coupled with the unplanned end-of-life management leads to the depletion of rare earth materials, increasing carbon emissions, and growing electronic waste, thus presenting unique sustainability challenges. Numerous studies have emphasized the development of circular electronic products that align with Circular Economy principles to address these issues. Consumer electronics industry-led initiatives, such as the Circular Electronics Partnership (CEP), have also made a concerted effort to establish key requirements to ensure the circular flow of consumer electronics. However, the broadness of these requirements poses challenges in operationalizing them to facilitate more effective decision-making during product design. This paper addresses this gap by proposing more specific and actionable circular product attributes identified and compiled from extant literature. The relevancy of these attributes was verified in consultation with industry practitioners. These attributes were then mapped to the broad, generic requirements proposed by the CEP. By doing so, this research contributes to translating the CEP-proposed requirements into more specific and actionable attributes to facilitate the design and manufacturing of circular products in the consumer electronics industry.
Review of Commercial One-Dimensional Thermo-Fluid Solvers for Liquid Cooled Server System
Authors: Ravi Bharath Ram , Yu Jiwon , Keefe Stephen , Chu Herman , Wealther Chase 
Published: November 2024

Abstract
Recent advancements in Artificial Intelligence (AI), blockchain, the Internet of Things (IoT), and other technologies have driven the development of high-performance server systems. This progress has resulted in a significant increase in heat dissipation of servers, limiting the use of traditional air-cooling methods. Many high-performance server systems currently available in the market require liquid cooling due to their high power and power densities. Liquid cooling technologies provide a more efficient means of dissipating heat from high-power density chips and, in certain cases, can lead to reduced operating costs and carbon footprint for data centers. This study focuses on evaluating two commercially available one-dimensional thermo-fluid analysis tools by comparing their results with experimental data. The liquid cooling system under examination consists of a single coolant loop branching into two sections. Each section contains a cold plate designed for a CPU chip and ten cold plates dedicated to cooling DIMM modules. Both one-dimensional solver tools demonstrated good correlation with the experimental results. The study also discusses the limitations of the options available in these tools for modelling flow and heat transfer components.