bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Graph Algorithm for the Design of Functionally Graded Alloy Components
Authors: Allen Marshall D. , Arróyave Raymundo , Malak Richard 
Published: November 2024

Abstract
One of the promising capabilities of metal additive manufacturing (AM) is the potential to manufacture metal parts with spatially varying alloy compositions. It is hypothesized that these compositionally graded alloy (CGA) parts can satisfy competing cost and performance requirements that cannot be met with a monolithic alloy. However, there are significant challenges in their design and manufacture, such as the formation of deleterious material phases and solidification cracking during AM. Prior work addresses the materials design of CGAs between two alloy targets in trivial geometries. However, there are no formal approaches to designing complex CGA parts, limiting the application of these promising materials for further research and implementation. In current practice, most manufactured CGAs are unidirectional, with composition changing in planar, cylindrical, or spherical layers. In this paper, we introduce a novel graph-based algorithm for designing manufacturable general CGA components. Given a component geometry with two or more alloy composition targets at select locations, the algorithm uses a labeled property graph representation of material compatibilities and properties to generate a valid alloy gradient throughout the entire part. We show that the algorithm will always find an alloy gradient solution if one exists, demonstrate it on subsea valve body design problem using the Fe-Ni-Cr ternary system, and study the algorithm’s scalability concerning several key problem discretization parameters.
Dynamics, Analysis and Experiments of Obstacle Negotiation for Wheeled Mobile Robots
Authors: Kfouri Mathew J. , Kövecses József 
Published: November 2024

Abstract
Hybrid wheel-leg robots combine the high efficiency of wheeled locomotion with the obstacle negotiation abilities of articulated suspension. Effective performance indicators are needed as optimization goals for both mechanism design and trajectory planning to take full advantage of the abilities of these robots. This work investigates the concept of admissible kinetic energy and related performance indicators to develop a framework for obstacle negotiation analysis, design, and control. A four wheeled-legged robot was used as a test platform to analyze the suite of performance indicators based on velocity and joint position, and predict which wheels are in contact at the moment of impact. A physical test platform including current sensors, encoders and an accelerometer was designed and constructed to validate the simulation results. A dynamic model of the test platform constructed for impact analysis is validated through a combination of high-speed camera measurements, force measurements and current sensing. Selected performance indicators based on admissible kinetic energy are shown to influence the abilities of these robots to negotiate an obstacle, with and without accounting for the configuration dependent effect of traction.
Reverse Engineering and Prototyping of a Nasal Cavity Model for Odorant Detection Experiments
Authors: Bertolini Michele , Rossoni Marco , Carulli Marina , Dubreuil Romain , Colombo Giorgio , Bordegoni Monica 
Published: November 2024

Abstract
Reverse engineering (RE) is an evolving discipline in information science that offers computer-based reproductions of components, products, or even anatomical structures. Focusing on the human nose, various approaches, including basic 3D scanning, silicone rubber impressions, or medical imaging techniques, have been used for acquisition. Among these, just imaging techniques such as CT and MRI allow us to completely visualize the internal anatomy of the nose, also enabling three-dimensional reconstructions.
Based on these considerations, this work aims to create an accurate 3D reconstruction of the nose, with a special focus on the nasal cavity, starting from a preoperative CT scan dataset. A thresholding-based segmentation approach was chosen to derive the inner volume occupied by the air. From this, a constant-thickness wall was generated with a hollowing operation. After further design modifications and improvements, the assembly was 3D printed with a stereolithography machine.
The obtained model was then integrated into an experimental setup, including an odor sensor and a vacuum pump to generate airflow. Preliminary tests were run to evaluate the effectiveness of the proposed solution in guaranteeing signal detection.
As a preliminary output, this study showed the feasibility of an experimental workbench to replicate human sniff. This was successfully tested with odorant molecules and an odor sensor. Now, more extensive tests will have to be conducted, even comparing results with those from numerical simulation.
Enhancing Isogeometric Analysis With NURBS-Based Synthesis
Authors: Yang Shaoliang , Wang Kang , Wang Jun 
Published: November 2024

Abstract
Isogeometric analysis (IGA) is a computational technique that integrates computer-aided design (CAD) with finite element analysis (FEA) by employing the same basis functions for both geometry representation and solution approximation. While IGA offers numerous advantages, such as improved accuracy and efficiency, it also presents several challenges related to geometric modeling. Some of these challenges include accurately representing complex geometries with NURBS (Non-Uniform Rational B-Splines) or other basis functions used in IGA and generating high-quality meshes that conform to the complex geometry represented by NURBS curves/surfaces. This paper introduces an analytical framework to provide a more efficient and theoretically grounded method for generating curvilinear configurations and its analytical solution in IGA, bridging the gap between generated data and its physical representations. This innovative approach is distinguished by integrating the NURBS parameterization in curve generation and providing a corresponding framework to achieve a broader and more accurate explanation of meshes and properties, especially constructing new coordinates and calculating the physical displacements under these conditions. Our model enables the analytical understanding of complex curves from the UIUC airfoil and superformula datasets, demonstrating a deeper dive into simulations. This study signifies a pivotal juncture wherein machine-learning-based complex geometrical formulations are synergistically combined with actual isogeometric analysis.
Functional Analysis of Cyber-Physical Systems for Confidentiality Quantum Resilience
Authors: Van Bossuyt Douglas L. , Hale Britta 
Published: November 2024

Abstract
The pending development of a cryptographically relevant quantum computer (CRQC) puts cryptographic security relying on public key cryptography at risk. Such cryptography can be found throughout systems today, including cyber-physical systems, which raises a question on when to transition security to quantum resistant alternatives, i.e., post-quantum cryptography. Criticality of transition timeline and planning can be non-trivial for system managers and the cybersecurity risk of transition delay is often opaque. This paper investigates functional system modeling techniques for planning and risk mitigation against quantum threats to confidentiality in cyber-physical systems. The research in this paper applies systems engineering and design engineering tools such as Functional Modeling in the form of Functional Failure Identification and Propagation (FFIP) and Flow State Logic (FSL) to analyze flow paths and provide quantum vulnerability metrics for cyber-physical systems. Using this insight, this work further provides guidance on how such metrics can be used to plan system transition for quantum resistance. Timeline upgrade prioritization of functions and their component solutions to prepare for the threat of a CRQC is possible with the method proposed in this paper. A simplified case study of a polar research facility is presented to demonstrate the method. This paper introduces the concept of Quantum Vulnerability Information Timeline (QVIT) in the context of system modeling and demonstrates within the case study how QVIT values can be calculated for various system components to estimate preparation timelines against quantum threats.
Spiral Development Approach for Design and Validation of Large-Scale Extrusion-Based Autonomous Construction Systems
Authors: Patterson Albert E. , Norris William R. , Soylemezoglu Ahmet , Nottage Dustin 
Published: November 2024

Abstract
Autonomous construction systems (ACSs) have become a very important area of research in several domains, particularly in expeditionary site preparation, extraterrestrial exploration and base construction, and disaster response. While these systems range from single vehicles to large systems with swarms of autonomous construction equipment, the major need for development is in the extrusion-based autonomous construction systems (EBACSs). These systems use large 3-D printers and supporting equipment to construct buildings and infrastructure in place. This article reviews a major previous study which developed a quasi-general system architecture for EBACSs and uses this as the starting place for further development in system realizability (manufacturing, assembly, and integration) and verification and validation efforts using the spiral development approach. Originally developed for software development projects, the spiral method has become more and more widely used in recent years for all kinds of risky and complex systems engineering work. Most importantly, decisions are made based on risk and the development/design process ends once the stakeholders decide the magnitude of system improvements in each cycle is too small to justify further cumulative cost. This work clearly shows the need and value of a general system architecture for EBACS and a path forward for their continued development and refinement. The conclusions and recommendations generated are relevant for the design and realization of a variety of different EBACSs configurations (gantry systems, robotic arms, delta robots, ground robot teams, and others) and will aid in the more effective realizability and fielding of these systems throughout their life cycle.
A Smooth Planning Method for Multi-Robot Transportation System With Decoupled Path and Orientation Planning
Authors: Lee Kuan-Hsien , Chan Kuei-Yuan 
Published: November 2024

Abstract
Multi-Robot Systems (MRS) are gaining popularity in various fields due to their adaptability and scalability, particularly in transporting large items. Integrating motion constraints presents a challenge for these systems, as these constraints affect the robots’ dynamics, complicating planning and control. Traditional methods that use general motion modes and constraints simplify planning but can limit maneuverability. Moreover, conventional collision detection often simplifies interactions too much, hindering the system’s ability to adjust its orientation to navigate around obstacles, a significant issue with slender objects. This paper introduces a novel planning methodology that strategically decouples path planning from orientation planning. This decoupled approach facilitates the generation of smooth trajectories that inherently accommodate static obstacle avoidance, ensuring seamless navigation throughout the transportation task. Theoretical analysis confirms the method’s efficacy in achieving smooth motion, while empirical evidence demonstrates its superiority in reducing overall travel distances when compared to existing algorithms. This dual-phase planning strategy not only enhances the operational efficiency of MRS in complex environments but also extends the potential applications of robotic transportation systems by mitigating the limitations imposed by traditional planning constraints.
A Hybrid Simulation-Gaussian Process Regression Approach for Performance Prediction and Reconfiguration of Production Layout
Authors: Lee Jongsuk , Moon Seung Ki 
Published: November 2024

Abstract
As products become more sophisticated and requirements for superior quality levels become more stringent, the complexity inherent in manufacturing systems increases significantly. In particular, the accuracy of predicting production performance and various operation costs is an increasingly important task under rapidly changing manufacturing conditions. In response, this paper proposes a framework to predict key performance indicators (KPIs) using Gaussian Process Regression (GPR), which can be applied to labor-intensive manufacturing systems in small and medium-sized enterprises with relatively flexible production layout changes. The proposed framework provides several alternatives to the production layout strategies by leveraging Discrete Event Simulation (DES) data from scenario-based Cellular Manufacturing System (CMS) models. Since GPR-based prediction model offers probabilistic results and captures the uncertainty inherent in the manufacturing systems, it can adaptively address the problems related to the impact of production system complexity on KPIs. In this research, three key dependent variables such as cycle time, total buffer capacity, and average manpower efficiency are extracted and utilized from the simulation results to develop a GPR model for production volume prediction under specific manufacturing conditions. This paper describes the creation and comparison of GPR models for three manufacturing layouts and demonstrates the usefulness of the proposed framework in adapting to different production environments.
Impact of Ring Gear Dynamics on Planet Load Sharing
Authors: Ozdemir Enes Timur , Inalpolat Murat 
Published: November 2024

Abstract
This paper presents an elastic continuum modelling approach for ring gears of planetary gearsets where the fixed ring gear spline supports and ring/planet gear contact stiffnesses are treated as lumped dynamic stiffnesses. The hybrid modeling approach used allows coupling of lumped discrete stiffnesses and a continuum model and their coupled solution. The ring gear is modelled as a thin-walled ring structure under the assumption that the normal stress in the direction of ring gear axis is negligible compared to stresses due to the in-plane flexural vibrations. Hamilton’s approach is used to obtain the continuum ring model equations. The spline supports are modelled as non-rotating discrete stiffnesses and the gear contact compliances are modelled as rotating discrete stiffnesses and displacement sources. The system is discretized using Galerkin’s method and Newmark’s time-step marching based integration method is used to determine transient response of the system. The proposed model is utilized to investigate the influence of number of planet gears, number of splines as well as ring gear design parameters on ring gear dynamics and its impact on planet load sharing. The case studies revealed that the planet and spline numbering have an influence on ring gear dynamics as much as ring gear design parameters.
Optimal Critical Design Parameters for Car’s Aesthetic Appearance Design
Authors: Li Yu-Tong , Wang Yu-Xin 
Published: November 2024

Abstract
This paper is devoted to finding the critical aesthetic feature parameters for controlling and determining a car’s aesthetic appearance. First, the car’s aesthetic features in markets were analyzed and represented with representative curves, in which the control parameters were taken as the critical aesthetic feature parameters to model and control the car’s virtual shapes. The survey data between the critical aesthetic feature parameters and the car’s aesthetic evaluation values described by five linguistic evaluation word pairs were collected through a questionnaire based on cars’ virtual models related to different values of such critical feature parameters. The aesthetic evaluation curves associated with the typical critical design parameters figured out through the curve-fitting approach demonstrate that the customers’ harmonious feeling for cars is positively correlated with the soft feature but negatively associated with the avant-garde feature. Customers often prioritize and favor cars with harmonious characteristics. The values of critical aesthetic design parameters proposed in this paper are beneficial in determining a car’s optimal aesthetic appearance.
Collaborative CAD in Support of Engineering Design Reviews
Authors: Petty Emily , Edmonds Nathan , Mocko Gregory , Patterson Eric 
Published: November 2024

Abstract
The focus of this paper is on evaluating the needs of distributed design reviews and establishing requirements on tools to support designer reviews. Specifically, this research explores the US Department of Defense acquisition process. This literature review and requirement generation explores the impact of Multi-User CAD (MUCAD) systems on collaborative design reviews and how quasi-asynchronous design reviews using MUCAD systems can enhance the understanding of product design. This paper describes synchronous and asynchronous design reviews to make a case for a combined approach that utilizes MUCAD systems. In this research, the generated requirements for a successful collaborative MUCAD system are divided into seven categories: concurrency, heterogeneity, annotations, IP protection, security, version control, and viewing. This paper serves as a guideline for future tests.
The Effect of Variation in Filling Rate on Hydraulic Retarder Control
Authors: Yong Huang , Yu Liangyao , Hu Ruibo 
Published: November 2024

Abstract
The foundation for developing autonomous driving is the precise regulation of the actuator through the control system. In heavy commercial or agricultural vehicles, hydraulic retarders are a common auxiliary braking system that can prevent catastrophic accidents caused by thermal failure of the main brake system. A working chamber and a control system that work together make up the hydraulic retarder. However, most research on the hydraulic retarder’s control system is focused on the control valve’s performance characteristics. In contrast, the effects of changes in the hydraulic retarder’s working chamber during braking on the control system are neglected. This study employs a mathematical model of a hydraulic retarder based on Rankine-vertex dynamics to investigate the effects of variations in the filling rate of the working chamber on the control system, and validates these findings through bench experiments. The study can provide valuable guidance and references for refining hydraulic retarder control systems’ design and control strategies.
Numerical Estimation of Bidirectional Plant-Control Design Coupling in Control Co-Design
Authors: Fernández Bravo Elena , Ornik Melkior , Allison James T. 
Published: November 2024

Abstract
Control co-design has been shown to be an effective tool for optimizing engineering systems. One characteristic feature of these problems is the presence of design coupling between the plant and controller, and this coupling is one of the key deciding factors when selecting a solution strategy for the design optimization problem. In this paper, we provide a method to numerically estimate design coupling strength, accounting for bidirectional coupling (plant and control mutually affect each other), and for estimating design coupling when the control design variables are time-varying trajectories. Design coupling strength is one of several factors that can affect what design optimization problem formulation decisions will best meet the needs of the broader engineering design effort. Some guidelines are provided here for how to use design coupling information to help support problem formulation decisions, including identifying the most impactful design variables and design variable relationships. The coupling strength estimation and its use for problem formulation is illustrated with a spacecraft control co-design (CCD) example. In the example, the plant (physical system) and attitude control design of a satellite are optimized, and design coupling strength information is used to identify the most appropriate plant design variable choice out of a small pool of candidates.
Stochastic Response Modification: Utilizing Noise and Nonlinearities for Vibration Damping
Authors: Breunung Thomas , Balachandran Balakumar 
Published: November 2024

Abstract
In many engineering applications, vibrations cause wear, discomfort, or increase energy consumption. Hence, these vibrations are undesirable, which in turn has motivated research into vibration attenuation and various damping strategies have been proposed. Most of the proposed approaches are designed for linear vibratory systems and become inefficient in the presence of nonlinearities. While only a few damping concepts account for nonlinearities, those often do not leverage the nonlinearities present. Here, the authors present a damping strategy that exploits the interplay between nonlinearities and noise to reduce vibration amplitudes. More specifically, multi-stability, a feature characteristic of nonlinear systems is leveraged. Within the multi-stability region multiple steady state responses simultaneously exist and the addition of noise can induce jumps between these coexisting steady state responses. For the investigated mechanical systems, the added noise quickly drives the systems’ response towards a vibration pattern with a low amplitude. Especially high amplitude vibrations close to resonance are efficiently suppressed, and hence, response maxima close to resonance are significantly reduced. Through experimental and numerical investigations, it is shown that the addition of noise helps reduce the maximal response amplitude by 50% compared to the response maxima without added noise and the response maxima of the linear system.
A General Framework for Supporting Economic Feasibility of Generator and Storage Energy Systems Through Capacity and Dispatch Optimization
Authors: Azad Saeed , Gulumjanli Ziraddin , Herber Daniel R. 
Published: November 2024

Abstract
Integration of various electricity-generating technologies (such as natural gas, wind, nuclear, etc.) with storage systems (such as thermal, battery electric, hydrogen, etc.) has the potential to improve the economic competitiveness of modern energy systems. Driven by the need to efficiently assess the economic feasibility of various energy system configurations in early system concept development, this work outlines a versatile computational framework for assessing the net present value of various integrated storage technologies. The subsystems’ fundamental dynamics are defined, with a particular emphasis on balancing critical physical and economic domains to enable optimal decision-making in the context of capacity and dispatch optimization. In its presented form, the framework formulates a linear, convex optimization problem that can be efficiently solved using a direct transcription approach in the open-source software DTQP. Three case studies demonstrate and validate the framework’s capabilities, highlighting its value and computational efficiency in facilitating the economic assessment of various energy system configurations. In particular, natural gas with thermal storage and carbon capture, wind energy with battery storage, and nuclear with hydrogen are demonstrated.