bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simultaneous Stiffness and Trajectory Optimization for Energy Minimization of Pick-and-Place Tasks of Sea-Actuated Parallel Robots
Authors: Kordik Thomas , Gattringer Hubert , Müller Andreas 
Published: November 2024

Abstract
A major field of industrial robot applications deals with repetitive tasks that alternate between operating points. For these so-called pick-and-place operations, parallel kinematic manipulators (PKM) are frequently employed. These tasks tend to automatically run for a long period of time and therefore minimizing energy consumption is always of interest. The latest developments addressing this issue deal with the use of elastic elements and actuators, where research on series elastic actuators (SEA) appears underrepresented. Motivated by a simplified introductory thought experiment, this paper explores the possibilities of minimizing energy consumption of PKM actuated by SEA during pick-and-place tasks. The idea is to excite eigenmotions that result from the actuator springs and exploit their oscillating characteristics. To this end, a typical cyclic pick-and-place operation is analyzed and a dynamic model of SEA driven PKM is derived. Subsequently, an energy minimizing optimal control problem is formulated where operating trajectories as well as SEA stiffnesses are optimized simultaneously. Here, optimizing the actuator stiffness does not account for variable stiffness actuators. It serves as a tool for the design and sizing process. The hypothesis on energy reduction is tested on two (parallel) robot applications where redundant actuation is also addressed. Lastly, results are shown and the validity of this approach is discussed.
Engineering Design Education: Assessing Student Learning in Cornerstone Through Capstone Programs
Authors: Fazelpour Mohammad , Joshi Shraddha , Mocko Gregory , Murphy Alexander R. , Ramnath Satchit , Renu Rahul S. , Righter James A. , Sen Chiradeep , Summers Joshua D. , Patel Apurva 
Published: November 2024

Abstract
This paper presents a “call to arms” for reconsidering how students’ engineering design learning and skill development are assessed, shifting from a traditional summative assessment to structured, repetitive formative assessment. Students are expected to have developed 21st Century Skills, engineering skills, and design skills by the time that they matriculate through the undergraduate program. These skills are often overlapping and are recognized by faculty as critical and central to student development. However, many of these skills are not directly evaluated and the formative feedback that students need to develop these skills is often lacking. This paper presents an elaboration on these skills, various means of assessment that are common through engineering design curricula, and then a review of different design education approaches used in several mechanical and general engineering programs. The three general phases of an undergraduate students career are detailed with respect to how design is integrated into the first year programs, mid-program, and capstone programs. Finally, a set of recommendations are provided to start the conversation at different institutions. These recommendations are not intended to be the final solution, but can be considered early prototypes that can be refined and edited for the unique needs of each different program. Ultimately, it is recommended that students be provided multiple engineering design project experiences where they are provided feedback and then can use the lessons learned in executing subsequent projects. It is critical that engineering design educators continue to reflect on their current practices, learning from others, and identifying opportunities for improvement, even if it might cause discomfort in a currently well run operation. The student learning should always be at the forefront of all decisions made in engineering design education.
Probability-Based Bounding Box With Confident Object Localization for Autonomous Navigation
Authors: Bae Jinwoo , Xi Zhimin 
Published: November 2024

Abstract
The Object detection, especially for autonomous navigation, requires high accuracy of the localization accuracy on the objects detected. The bounding box is devised to provide the localization of the object detection. However, the confidence score of the bounding boxes does not provide the localization reliability although the bounding boxes are selected by the confidence score through a non-maximum suppression (NMS) task. In this paper, we propose a novel bounding box regression framework to build a probability-based bounding box. The proposed bounding box leverages the spatial and confidence information of the candidate boxes removed by the NMS task. The information enables to capture the object entirely through expanding the localization extent of the tradition bounding boxes reliably, where the extent is asymmetrically expansion on each side to avoids unnecessary localization. In addition, the regression task using the information of the candidate boxes allow us to the extent of the bounding box for desire confidence level. The proposed method is evaluated on sample images from Berkery DeepDrive (BDD) dataset, where the samples include objects only partially detected by the traditional bounding box. Our experiment presents that the probability-based bounding box would provide more reliable localization compared to the tradition bounding box.
Generalized Anisotropic Multiobjective Topology Optimization for Naval Additive Manufacturing
Authors: Steuben John , Iliopoulos Athanasios , Birnbaum Andrew , Graber Benjamin , Michopoulos John 
Published: November 2024

Abstract
The use of topology optimization algorithms for engineering design has become widespread. Motivated by the objective of producing lightweight, high-performance components, a wide variety of approaches have emerged, and many alternatives now exist for every stage of the associated computing pipeline. The present work introduces a generalized topology optimization framework for use in the area of additive manufacturing (AM), with a focus on naval applications. The development of this framework is outlined, with particular attention paid to the development of an anisotropic experimental data-driven material constitutive model. Additionally, methods for handling arbitrary numbers of objectives, design constraints imposed by additive manufacturing process physics, and boundary conditions particular to naval applications are explored. Steps for post-processing and refining the optimizer output in order to produce manufacturing-ready files are also discussed. The approach is demonstrated on a pair of test cases. The first is the design of an optimized “conformal” pressure vessel, which departs from the typical sphere / cylinder forms and allows for increased storage capacity by occupying a non-convex envelope space. The second application problem is the design of an optimized propulsor intended to be produced using large-scale AM. This propulsor is optimized for inertial and hydrodynamic loads, and a parametric study of the effect of outer shell thickness is performed.
Valuing Outliers: a Modeling Framework to Consider Non-Traditional Solutions From Non-Traditional Solvers
Authors: Dharmarajan Athul Chakkithara , Topcu Taylan G. , Panchal Jitesh H. , Szajnfarber Zoe 
Published: November 2024

Abstract
While the engineering design research community has developed numerous models for early-stage design over the years, these models explore the design space corresponding to the dominant solution in the domain. These models work well for making predictions for designs by experts within an organization, but they cannot compare solutions that use alternative principles to solve the same problem. With the increasing popularity of open innovation and crowdsourcing within engineering design organizations, it is important to value the non-traditional solutions from non-traditional solvers in the early-stage design to make informed decisions about structuring the problem-solving mechanism employed by the organization. This paper attempts to create a new modeling framework to predict the design outcome by valuing non-traditional solutions alongside the dominant solution, thereby capturing the potential performance and novelty offered by the solutions from the non-traditional solvers. The model is demonstrated using a case study of a robotic gripper design. The results indicate the model can predict the best solution for the same problem across different principles. In addition, we find that the model is more important for non-traditional solvers than traditional solvers, as a larger fraction of their solutions would have been missed by models considering only the dominant solution.
An Online Sequential Update Method for Reduced-Order-Model-Based Digital Twin
Authors: Tang Yifan , Sajadi Pouyan , Rahmani Dehaghani Mostafa , Wang G. Gary 
Published: November 2024

Abstract
Digital twin (DT) refers to any model that reflects a physical system and remains updated with the real-time data from the physical system. Recently, DT constructed with a reduced-order model (DT-ROM) has been applied to aerodynamics and structure health monitoring tasks, whose partial differential equations (PDEs) are used to design the online update formula for reduced bases and coefficients in DT-ROM. Although such online update methods improve the performance of DT-ROM, they are not applicable when the PDEs of a system are unknown. This paper focuses on the online update task where a system is modeled with a DT-ROM, but the system’s PDEs are unknown. To tackle the task, an online sequential update method is proposed. During the update process, the projection residual of online data on the reduced bases is applied to determine whether to update the reduced bases in ROM, and the prediction residual of online data obtained by the offline DT-ROM is adopted to infer whether to update the coefficient models. By checking both criteria sequentially, the online update method selects the necessary online data for the DT update. Three numerical problems and one engineering problem are designed to test the proposed online update method. Testing results demonstrate that (a) the proposed online update method reduces both the projection and prediction residuals gradually, and (b) the performance of the offline DT-ROM model on the testing data is improved gradually during the online update process. Both indicate that the proposed method could be applied to online DT update tasks where the PDEs of the system are unknown.
Human-AI Collaboration Among Engineering and Design Professionals: Three Strategies of Generative AI Use
Authors: Ma Kevin , Moore George , Shyam Vikram , Villarrubia James , Goucher-Lambert Kosa , Reynolds Brubaker Eric 
Published: November 2024

Abstract
Designers are increasingly using Generative Artificial Intelligence (GenAI) in design processes; however, knowing how designers use GenAI — especially in professional design practice — is under-explored. This paper presents an ethnographic study of an early-stage design team at NASA that explores the natural variation of GenAI use across team members during a speculative design workflow. We aimed to uncover when, how, and why GenAI tools were or were not employed using ethnographic observations to map the team’s speculative design process and follow-up interviews to provide deeper insights into team members’ interactions (or lackthereof) with GenAI. Through inductive qualitative coding, our analysis revealed three strategies of GenAI use observed among professional engineers and designers — intimate co-design with GenAI, selective delegation to GenAI, and minimal use of GenAI — as well as factors that appeared to influence their decisions whether or not to use GenAI. This study proposes new theory in human-AI collaboration that sheds light on the strategies, rationale, and circumstances under which design professionals do and do not use GenAI. These strategies and factors tied to GenAI use offer insights into when, how, and why professionals use GenAI in design and how GenAI could be built to better accommodate designers.
Design of Compliant Pivots Based on Three-Flexure Arrangement
Authors: Serafino Simone , Bruzzone Luca , Fanghella Pietro , Verotti Matteo 
Published: November 2024

Abstract
Cross-axis pivots, thanks to their high precision and large range of motion, are widely used in mechanical systems. However, their axis drift is generally not negligible and reduces the joint accuracy, limiting the range of the possible implementations. In Literature, this issue has been addressed by following different approaches, often based on the optimization of various kinetostatic parameters or on the combination of more than two flexible elements. In this paper, a novel family of compliant joints is presented. The novel layout is based on the arrangement of three flexures. More specifically, the design of the triple-axis pivots consists of the combination of two crossed flexures with initial curvature and of an auxiliary straight beam. The design procedure includes a proper positioning of the flexures’ centroids and the definition of an equivalence criterion for the rotational stiffness. Non-linear finite element analysis simulations have been performed to evaluate the kinetostatic response of the joint. The results are collected in the form design maps representing the effects of the design parameters on accuracy and stiffness characteristics. An application of the design procedure is presented, and the performance of the defined triple-cross axis pivot are compared to the ones referring to a traditional double-axis joint.
A Design Method for a Self-Organizing Closed-Loop Control System Based on Stigmergy and Bi-Level Planning
Authors: Cao Jinhui , Ming Zhenjun , Allen Janet K. , Mistree Farrokh 
Published: November 2024

Abstract
Self-organizing systems are capable of executing tasks in complex and unknown domains that are unsuitable for humans. However, designing of self-organizing systems is challenging due to balancing global and local decision-making and in enabling the system to adaptively generate desired behaviors in different environments. To address these challenges, in this paper we propose a self-organizing system design framework based on stigmergy and bi-level planning. We use the multi-agent box-pushing problem as an example to verify the framework. Within this framework, the upper-level planning (which is used for box position prediction) and the lower-level planning (which is used for agent position allocation) are designed to connect and coordinate between the global and local decisions. The influence of states based on stigmergy creates a closed-loop control mechanism with “pheromones” as input, allowing the system to adapt to various environments. In this paper we use Webots as the simulation platform to conduct multi-agent box-pushing experiments and compare the results with an ant colony handling method, to demonstrate the effectiveness and advantage of our approach.
Towards a Multiphysics-Based Digital Twin for Predicting Aging of Multimaterial Adhesive Step Lap Joints
Authors: Michopoulos John G. , Apetre Nicole A. , Iliopoulos Athanasios P. , Steuben John C. 
Published: November 2024

Abstract
We present the initial steps towards formulating a multiphysics-based digital twin for predicting aging for multi-material adhesive step lap joints (ASLJs) that accounts for mechanical and environmental generalized loading. Initially, we provide a definition of the digital twin context and the particular digital twin architecture considered associated with the data-driven digital twin flavor. Subsequently, focus is given to establishing and exercising a theoretical and computational framework accounting for the degradation of properties for materials participating in ASLJs due to environmentally-aided damage accumulation. A thermodynamics-based theory is derived as a first step. An initial computational implementation of it is developed and applied to two models of multi-material ASLJs involving a titanium Ti-6Al-4V alloy and carbon epoxy composite adherent and an FM-300K adhesive. Several studies have been performed to identify the effect of parameters related to the choice of element order, mesh density, damage parameters and inclusion of damage models for the participating domains. Finally, the predictions obtained from the framework are compared with experimental results to establish the necessary validation for two environmental conditions of room and elevated temperatures at low ambient humidity. These results provide an initial insight into the characteristics of the aging degradation of ASLJ performance when both the adhesive and the composite material adherent are accumulating damage and contribute to aging of the respective materials.
Elicitron: A Framework for Simulating Design Requirements Elicitation Using Large Language Model Agents
Authors: Ataei Mohammadmehdi , Cheong Hyunmin , Grandi Daniele , Wang Ye , Morris Nigel , Tessier Alexander 
Published: November 2024

Abstract
Requirements elicitation, a critical yet time-consuming and challenging step in product development, often fails to capture the full spectrum of user needs. This paper introduces a novel framework that leverages Large Language Models (LLMs) to automate and enhance the requirements elicitation process. LLMs are used to generate a vast array of simulated user agents, enabling the exploration of a much broader range of user needs and unforeseen use cases. These agents then engage in product experience scenarios, based on the Action, Observation, and Challenge framework introduced in this paper, inspired by Chain-of-Thought reasoning to produce structured responses. Subsequent agent interviews uncover valuable user needs. We validate our framework with two experiments. First, we explore different methodologies for diverse agent generation, discussing their advantages and shortcomings. We measure the diversity of identified user needs and demonstrate that serial agent generation leads to greater diversity. Second, we show how our framework effectively mimics empathic lead user interviews, identifying a greater number of latent needs than conventional human interviews. Our work highlights the potential of using LLMs to accelerate early-stage product development, reduce costs, and increase innovation.
Identifying Redesign Pathways Over a Planned Number of Modifications to Support Change Management
Authors: Jacobson Lindsey , Ferguson Scott 
Published: November 2024

Abstract
Complex engineered systems evolve with the world around them as operating environments change and new demands arise. Yet, modifying these systems remains a challenge. Changes can easily propagate, making it difficult to limit the scope of system modifications. Mitigating, or preventing, change propagation enables more efficient redesign. In this paper, we develop a method for identifying feasible system configurations that are accessible within a discrete number of modifications. With this information, designers can consider modifications where change propagation is controlled. We leverage Complete Flexibility Ranges (CFRs), the extent to which a decision variable (DV) can change while maintaining system feasibility, to identify feasible changes. By modifying DVs in their CFRs, designers guarantee change will not propagate further. We also demonstrate how feasible configurations can be produced from strings of modifications, given that the final modification involves a DV changing within its CFR. The proposed method is applied to a high-powered rocket system to identify new configurations that could be created given different modification strings. The results from our study support the belief that modifying sets of DVs can be more efficient than modifying DVs independently and consecutively. We also show that making infeasible changes may enable greater exploration of the design space but may limit further change options. The proposed method could be applied in future work to 1) compare the performance of different redesign strategies, 2) explore the impact of decision selection order, and 3) develop heuristics for design for changeability. This work provides a foundation for further study on how to efficiently design and redesign changeable systems.
Modeling of a Reconfigurable Cable-Driven Parallel Robot Under Low Gravity
Authors: Ang Han Wei (Kelvin) , Nelson Carl A. 
Published: November 2024

Abstract
Cable-driven parallel robots (CDPRs) boast advantages such as large workspace and large payload to weight ratio, among others. In the context of maintenance of space structures, these properties could be beneficial. However, CDPRs have not yet been widely applied in the domain of space exploration. The goal of the work presented in this paper is to model a novel CDPR with a reconfigurable structure which can be placed to traverse large areas of space, with space structure maintenance in mind as a potential target application. Kinematics, pose feasibility, and reconfiguration strategy are discussed, and a simulation example is presented to further illustrate the concept.
A Picture or a Thousand Words: Design Description Crafting to Replicate Human Similarity Judgments in Large Language Models
Authors: Keeler Matthew , Fuge Mark , Peng Aoran , Miller Scarlett 
Published: November 2024

Abstract
Well-studied techniques that enhance diversity in early design concept generation require effective metrics for evaluating human-perceived similarity between ideas. Recent work suggests collecting triplet comparisons between designs directly from human raters and using those triplets to form an embedding where similarity is expressed as a Euclidean distance. While effective at modeling human-perceived similarity judgments, these methods are expensive and require a large number of triplets to be hand-labeled. However, what if there were a way to use AI to replicate the human similarity judgments captured in triplet embedding methods? In this paper, we explore the potential for pretrained Large Language Models (LLMs) to be used in this context.
Using a dataset of crowdsourced text descriptions written about engineering design sketches, we generate LLM embeddings and compare them to an embedding created from human-provided triplets of those same sketches. From these embeddings, we can use Euclidean distances to describe areas where human perception and LLM perception disagree regarding design similarity. We then implement this same procedure but with descriptions written from a template that attempts to isolate a particular modality of a design (i.e., functions, behaviors, structures). By comparing the templated description embeddings to both the triplet-generated and pre-template LLM embeddings, we identify ways of describing designs such that LLM and human similarity perception better agree. We use these results to better understand how humans and LLMs interpret similarity in engineering designs.
Comparison of Several Compliant Variable-Stiffness Mechanism Designs for Industrial Applications
Authors: Zwiener Benjamin L. , Nelson Carl A. 
Published: November 2024

Abstract
Integration of variable-stiffness properties into robotic actuation systems has become a topic of interest in recent decades. Potential advantages include the ability to tailor dynamic behavior of manipulators and customize their interactions with the environment. In this paper, we leverage concepts from compliant mechanisms to develop several candidate mechanisms for integrating variable-stiffness behavior into robotic end effectors, and compare and contrast their relative merits.