bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Application of Machine Learning to Predict Stiffness Discrimination Thresholds Using Haptics
Authors: Karadoğan Ernur 
Published: November 2021

Abstract
The effectiveness of our interaction with the computer-generated environments is subject to our physical limitations in real life such as our ability of discriminating differences in stiffness or roughness. This ability, represented by Weber fractions, is usually quantified by means of psychophysical experimentation. The experimentation process is tedious and repetitive as it requires the same task to be completed by participants until the mastery at a certain stimulus level can be ensured before moving onto the next level. Moreover, these thresholds are dependent on the tested standard stimulus level and, therefore, need to be identified by separate experiments for every possible standard stimulus level. The purpose of the current study is to reduce the amount of experimentation and predict the thresholds for stiffness discrimination of individuals after being tested at a single stimulus level. The prediction models tested provide a moderate level of prediction power, but more features, potentially physical and demographical in nature, are needed to increase their effectiveness. The procedure described herein can be extended to any modality other than stiffness and, therefore, has the potential to predict overall palpation effectiveness of an individual after a feasible amount of data is obtained through experimentation.
Comparing Change Management Processes for Requirements and Manufacturing: An Interview Based Study
Authors: Sutton Meredith , Summers Joshua D. 
Published: November 2021

Abstract
The study presented in this paper compares requirement and manufacturing change management processes to determine if similar processes can be used for both types of changes. A literature review is used to identify prescribed process stages. Ten stages are identified for both requirements and manufacturing change management. A series of interviews are then conducted with three different population groups to determine the process stages actually used in the field. The resulting process models are compared with the process models from the literature. Further, a thematic analysis is performed on the interview findings. Ultimately, differences are found between the prescribed and practiced change management models for both types of changes. Formal documentation stages are more prevalent for the manufacturing domain, though documentation in practice is less than what is prescribed. This includes the issuance of change requests and change orders in manufacturing change management that are not present in requirement change management processes. Significant differences were also found between the two change types; namely, requirement changes deal with more abstract concepts and as such can afford more informal documentation, whereas manufacturing changes deal with existing artifacts and require solid documentation. Additional research thrusts are identified to help reconcile change management processes across the life cycle.
A Family of Novel Compliant Linear-Motion Mechanisms Based on Compliant Rolling-Contact Element Pivot
Authors: Huo Tonglong , Yu Jingjun , Zhao Hongzhe , Wei Xian 
Published: November 2021

Abstract
Compliant linear-motion mechanisms are of great use in precision machines, due to their excellent performances such as infinite resolution and low cost. The accuracy of the mechanisms is an important consideration for mechanical design in applications, especially in the case of large working load. Considering Compliant Rolling-contact Element (CORE) pivot is characterized with high bearing capacity, the paper adopts it as a building block to design a family of compliant linear-motion mechanisms for heavy load applications. These mechanisms are achieved by replacing four rigid pivots in parallel four-bar mechanism with CORE pivots, and the motion accuracy is improved by means of contacting surfaces design of four CORE pivots. Firstly, the CORE pivot is introduced and five extended arrangements for bearing heavy load are given. Meanwhile, configuration of the compliant linear-motion mechanisms constructed by CORE pivots is obtained. In addition, kinematics of the mechanisms is analyzed and parametric design condition for achieving rectilinear motion is modeled. Based on the condition, detailed topological structures of the mechanisms are designed. Finally, motion simulations are implemented to verify accuracy of the proposed mechanisms. The results demonstrate that the mechanisms proposed in this paper are capable of offering a high-precision linear motion and providing a promising application prospect in precision machines.
Understanding the Energy Behavior of Building Occupants Through the Chronology of Their Energy Interactions
Authors: Preziuso Danielle , Kaminski Gregory , Odonkor Philip 
Published: November 2021

Abstract
The energy consumption of buildings has traditionally been driven by the consumption habits of building occupants. However, with the proliferation of smart building technologies and appliances, automated machine decisions are beginning to impart their influence on building energy behavior as well. This is giving rise to a disconnect between occupant energy behavior and the overall energy consumption of buildings. Consequently, researchers can no longer leverage building energy consumption as a proxy for understanding human energy behavior. This paper addresses this problem by exploiting the habitual and sequential nature of human energy consumption. By studying the chronology of human energy actions, the results of this work present a promising new approach for non-intrusively learning about human energy behavior directly from building energy demand data.
Analysis and Synthesis of Conical Coil Springs
Authors: Patel Harshkumar , Zhou Hong 
Published: November 2021

Abstract
Springs are mechanical devices that are employed to resist forces, store energy, absorb shocks, mitigate vibrations, or maintain parts contacting each other. Spring wires are commonly coiled in the forms of helixes for either extension or compression. Helical springs usually have cylindrical shapes that have constant coil diameter, constant pitch and constant spring rate. Unlike conventional cylindrical coil springs, the coil diameter of conically coiled springs is variable. They have conical or tapered shapes that have a large coil diameter at the base and a small coil diameter at the top. The variable coil diameter enables conical coil springs generate desired load deflection relationships, have high lateral stability and low buckling liability. In addition, conical compression springs can have significantly larger compression or shorter compressed height than conventional helical compression springs. The compressed height of a conical compression spring can reach its limit that is the diameter of the spring wire if it is properly synthesized. The height of an undeformed conical coil spring can have its height of its spring wire if the spring pitch is chosen to be zero. The variable coil diameter of conical coil springs provides them with unique feature, but also raises their synthesis difficulties. Synthesizing conical coil springs that require large spring compression or small deformed spring height or constant spring rate is challenging. This research is motivated by surmounting the current challenges facing conical coil springs. In this research, independent parameters are introduced to control the diameter and pitch of a conical coil spring. Different conical coil springs are modeled. Their performances are simulated using the created models. The deflection-force relationships of conical coil springs are analyzed. The results from this research provide useful guidelines for developing conical coil springs.
Event-Triggered Boundary Control Strategy for a Time Fractional Wave Equation Subject to Boundary Disturbance
Authors: Yuan Zhan-Mei , Zhou Hua-Cheng 
Published: November 2021

Abstract
In this paper, we investigate the event-triggered boundary feedback control problem for an unstable time fractional wave equation with unknown perturbation at the boundary. To cope with the instability of system when there is no disturbance, the backstepping method is adopted to convert the original unstable system into a stable system. An UDE-based estimator based on low-pass filter is proposed to estimate unknown time-varying input disturbance. With the estimation of disturbance, the event-triggered boundary feedback controller is proposed. It is shown that the event-triggered strategy could asymptotically stabilize system and a positive lower bounded of minimum inter-event time is ensured to exclude the Zeno phenomenon.
Evaluating Heuristics in Engineering Design: A Reinforcement Learning Approach
Authors: ElSayed Karim A. , Bilionis Ilias , Panchal Jitesh H. 
Published: November 2021

Abstract
Heuristics are essential for addressing the complexities of engineering design processes. The goodness of heuristics is context-dependent. Appropriately tailored heuristics can enable designers to find good solutions efficiently, and inappropriate heuristics can result in cognitive biases and inferior design outcomes. While there have been several efforts at understanding which heuristics are used by designers, there is a lack of normative understanding about when different heuristics are suitable. Towards addressing this gap, this paper presents a reinforcement learning-based approach to evaluate the goodness of heuristics for three sub-problems commonly faced by designers: (1) learning the map between the design space and the performance space, (2) acquiring sequential information, and (3) stopping the information acquisition process. Using a multi-armed bandit formulation and simulation studies, we learn the suitable heuristics for these individual sub-problems under different resource constraints and problem complexities. Additionally, we learn the optimal heuristics for the combined problem (i.e., the one composing all three sub-problems), and we compare them to ones learned at the sub-problem level. The results of our simulation study indicate that the proposed reinforcement learning-based approach can be effective for determining the quality of heuristics for different problems, and how the effectiveness of the heuristics changes as a function of the designer’s preference (e.g., performance versus cost), the complexity of the problem, and the resources available.
Addressing Challenges to Problem Complexity: Effectiveness of AI Assistance During the Design Process
Authors: Song Binyang , Soria Zurita Nicolás F. , Nolte Hannah , Singh Harshika , Cagan Jonathan , McComb Christopher 
Published: November 2021

Abstract
As Artificial Intelligence (AI) assistance tools become more ubiquitous in engineering design, it becomes increasingly necessary to understand the influence of AI assistance on the design process and design effectiveness. Previous work has shown the advantages of incorporating AI design agents to assist human designers. However, the influence of AI assistance on the behavior of designers during the design process is still unknown. This study examines the differences in participants’ design process and effectiveness with and without AI assistance during a complex drone design task using the HyForm design research platform. Data collected from this study is analyzed to assess the design process and effectiveness using quantitative methods, such as Hidden Markov Models and network analysis. The results indicate that AI assistance is most beneficial when addressing moderately complex objectives but exhibits a reduced advantage in addressing highly complex objectives. During the design process, the individual designers working with AI assistance employ a relatively explorative search strategy, while the individual designers working without AI assistance devote more effort to parameter design.
The Bus Factor in Conceptual System Design: Protecting a Design Process Against Major Regional and World Events
Authors: Van Bossuyt Douglas L. , Arlitt Ryan M. 
Published: November 2021

Abstract
We introduce a method to help protect against and mitigate possible consequences of major regional and global events that can disrupt a system design and manufacturing process. The method is intended to be used during the conceptual phase of system design when functional models have been developed and component solutions are being chosen. Disruptive events such as plane crashes killing many engineers from one company traveling together, disease outbreaks killing or temporarily disabling many people associated with one industrial sector who travel to the same conference regularly, geopolitical events that impose tariffs or complete cessation of trade with a country that supplies a critical component, and many other similar physical and virtual events can significantly delay or disrupt a system design process. By comparing alternative embodiment, component, and low-level functional solutions, solutions can be identified that better pass the bus factor where no one disruptive event will cause a major delay or disruption to a system design and manufacturing process. We present a simplified case study of a renewable energy generation and storage system intended for residential use to demonstrate the method. While some challenges to immediate adoption by practitioners exist, we believe the method has the potential to significantly improve system design processes so that systems are designed, manufactured, and delivered on schedule and on budget from the perspective of significant disruptive events to design and manufacturing.
Goal-Oriented Inverse Design (GoID) of Feedstock Filament for Fused Deposition Modeling
Authors: Deka Angshuman , Nellippallil Anand Balu , Hall John 
Published: November 2021

Abstract
Additive manufacturing (AM) can produce complex geometrical shapes and multi-material parts that are not possible using typical manufacturing processes. The properties of multi-material AM parts are often unknown. For multi-material parts made using Fused Deposition Modeling (FDM), these properties are driven by the filament. Acquiring the properties of the products or the filament necessitates experiments that can be expensive and time-consuming. Thus, there is a need for simulation-based design tools that can determine the multi-material properties of the filament by exploring the complex process-structure-property (p-s-p) relationship.
In this paper, we present a Goal-Oriented Inverse Design (GoID) method to produce feedstock filament for FDM process with specific property goals. Using this method, the designers connects the structure and property in the p-s-p relationship by identifying satisficing material composition for specific property goals. The filament properties identified in the problem are percentage elongation, tensile strength, and Young’s Modulus. The problem is formulated using a generic decision-based design framework, Concept Exploration Framework. The solution space exploration for satisficing solutions is performed using the compromise Decision Support Problem (cDSP). The forward information flow is first established to generate the necessary mathematical relationships between the composition and the property goals. Next, the target property goals of the filament are set. The cDSP is used for solution space exploration to identify satisficing solutions for material composition for the target property goals. While the results are interesting, the focus of our work is to demonstrate, and refine, the goal-oriented, inverse design method for the AM domain.
Can Machine Learning Tools Support the Identification of Sustainable Design Leads From Product Reviews? Opportunities and Challenges
Authors: Saidani Michael , Kim Harrison , Yannou Bernard 
Published: November 2021

Abstract
The increasing number of product reviews posted online is a gold mine for designers to know better about the products they develop, by capturing the voice of customers, and to improve these products accordingly. In the meantime, product design and development have an essential role in creating a more sustainable future. With the recent advance of artificial intelligence techniques in the field of natural language processing, this research aims to develop an integrated machine learning solution to obtain sustainable design insights from online product reviews automatically. In this paper, the opportunities and challenges offered by existing frameworks — including Python libraries, packages, as well as state-of-the-art algorithms like BERT — are discussed, illustrated, and positioned along an ad hoc machine learning process. This contribution discusses the opportunities to reach and the challenges to address for building a machine learning pipeline, in order to get insights from product reviews to design more sustainable products, including the five following stages, from the identification of sustainability-related reviews to the interpretation of sustainable design leads: data collection, data formatting, model training, model evaluation, and model deployment. Examples of sustainable design insights that can be produced out of product review mining and processing are given. Finally, promising lines for future research in the field are provided, including case studies putting in parallel standard products with their sustainable alternatives, to compare the features valued by customers and to generate in fine relevant sustainable design leads.
Recommended Methods Supporting Adoption of the Agile Philosophy for Hardware Development
Authors: Peterson Matthew , Summers Joshua D. 
Published: November 2021

Abstract
The objective of this research is to understand the historical evolution of software development, identify desirable characteristics of methods supporting agile for hardware, and recommend potential methods enabling agile development of hardware products. As technology and markets change, product development increasingly operates in a volatile, uncertain, complex, and ambiguous (VUCA) environment. While originally applied to software development, organizations are starting to see opportunity in adapting the agile philosophy for hardware development. A comparison of philosophies is made between waterfall, spiral, and agile development. The historical evolutions of software development, after agile, including Continuous Integration Continuous Deployment (CICD), Development and Operations (DevOps), and Development Security and Operations (DevSecOps) is presented. Benefits and challenges in the application of agile methods for hardware are presented. Benefits include improvements in flexibility in response to change and soft factors such as team communication, transparency and commitment. However, many challenges still remain. These are grouped into theme areas including lack of product flexibility, difficulty in separating deliverables, challenges with breaking down tasks within a sprint, changes needed in culture and mindset, difficulty scaling beyond pilot programs, team distribution, and development of an integrated approach across the product lifecycle. Potential methods to aid in the adoption of agile for hardware are discussed using the phases of the hardware development lifecycle as a framework. Recommended methods include the adaptation of Model Based Systems Engineering (MBSE) for problem definition, the use of generative methods for design, the application of Virtual Reality (VR) for prototyping, leveraging additive manufacturing for production, and favoring software defined systems to help in operations. By reducing both the duration and person-hours, these methods enable higher iteration rates for hardware products needed for an agile philosophy. The paper concludes with a discussion on future research efforts supporting the enabling agile development of hardware.
Design and Kinematic Simulation of a Novel Leg Mechanism for Multi-Legged Robots
Authors: Asci Simone , Zhang Ketao 
Published: November 2021

Abstract
Among mobile robotic research field, legged locomotion is largely applied for advanced robotic systems due to the higher degree of versatility compared to wheeled robots, which allows them to successfully move and interact in unstructured environments; nevertheless, legged robots present several designing problems and require a much more complex control system. Based on an effective robotic leg, this paper presents a novel design, which integrates a cam joint, aimed to improve the versatility performances minimizing changes in the original model and without increasing the control complexity. Furthermore, the design strategy aims to exploit the coupled action of two actuators, which are disposed in a novel configuration so to gain versatility advantage while maintaining velocity performances of legs equipped with a single actuator. The model is presented through a kinematic analysis, followed by the simulation of the leg mechanism trajectory and a comparison with the original configuration.
Methods for Shape Fitting in Morphing Compliant Mechanisms
Authors: Yellowhorse Alden , Rommers Jelle , Amoozandeh Ali , Herder Just L. 
Published: November 2021

Abstract
While compact folding is desirable for applications such as deployable mechanisms, achieving this with compliant mechanisms can be challenging. One reason for this is that the relaxed and stressed states of the mechanism are known and the loads producing the transition are unknown. The relaxed state is determined by the desired, deployed state and the stressed geometry is determined by the storage space. Approaches for solving this problem often require significant software development or cannot address problems in three dimensions. To address this problem, this work describes a method for designing 3D compliant mechanisms that can fold compactly. If the stressed and relaxed geometry are specified, an algebraic method can be used to find loads which best approximate the desired geometry. A least-squares approach is used to minimize error. A simplification of this method in two dimensions is also described. To further enhance the accuracy of the shape approximation, a method for varying the beam bending stiffness is described. For comparison, an inverse finite-element solver was implemented and paired with an optimizer and used to solve the same problem. Both methods were used to design a compliant, compactly folding beam. These results were compared with results from a commercial, finite-element software package.
Modification of Robotics Curriculum for Project-Based First Year Engineering Design Course
Authors: Nolte Hannah , Tan Xiaomei , Weaver Alexander , Starkey Elizabeth 
Published: November 2021

Abstract
Texas Instruments (TI) currently offers a comprehensive curriculum to supplement their Robotics System Learning Kit MAX (TI-RSLK MAX). While designed for all college students, TI would like to provide a modification of the curriculum specifically for first-year engineering design courses. The goal of this project was to modify the current TI-RSLX MAX curriculum, making it easier to digest for first-year engineering students and more applicable to shorter duration projects (∼8 weeks), while still being information dense. To better understand the user experience of the current TI-RSLK MAX curriculum and determine what users would want from a modified curriculum, user interviews were conducted and analyzed using inductive qualitative analysis techniques. Results showed that while the current TI robotics project has many positives, first-year students primarily struggled with the coding aspect of the project. These results directed and informed the prototype development of a modified curriculum module focused on teaching students code. Low- and medium-fidelity prototypes were developed and tested with users. Data from the usability study were analyzed using descriptive analysis techniques and results indicate that the medium-fidelity prototype helped students learn robotics coding. This research has implications for a high-fidelity modified TI-RSLX MAX curriculum and robotics education for first-year engineering design students.