bluuebunny/crossref_metadata_2025 huggingface dataset:
Measuring the U. S. Biomanufacturing Economy
Authors: Thomas Douglas
Published: November 2024

This paper estimates biomanufacturing (manufactured products made of biomaterials) and advanced biomanufacturing (products manufactured using activities that grow biological molecules and materials along with activities that alter biological material using non-mechanical means) value added in ways that make it consistent with estimates of U.S. GDP. Direct advanced biomanufacturing is estimated as being $94.6 billion annually while total direct biomanufacturing is $438.8 billion annually. When including supply chain and other indirect value added, the total biomanufacturing industry is $1,363.8 billion and advanced biomanufacturing is $259.9 billion. These estimates include biomanufacturing products that are excluded from estimates of the bioeconomy made by other organizations and/or individuals. For instance, a report by the National Academy of Sciences defines the bioeconomy as that being “driven by research and innovation in the life sciences and biotechnology,” which tends to exclude production of many food items that are included in this paper’s estimates. Other U.S. estimates differ from estimates of GDP and value added. This paper uses the EPA TRACI measures to evaluate the environmental impact associated with the production of products in the bioeconomy. As calculated using NIST’s Manufacturing Cost Guide, the production of biomanufacturing goods accounts for 43 % of the total environmental impact resulting from economic activity in all U.S. industries while the production of advanced biomanufacturing goods is 6.4 %. This paper also examines the assets and material flow time.
Social Network Influence on Residential Solar Photovoltaic Adoption in an Agent-Based Electricity System Model
Authors: Dello Russo Gina , Wu Lei , Lytle Ashley , Odonkor Philip
Published: November 2024

As the United States phases out traditional fossil fuels in favor of renewable energy sources, it is important to capitalize on all available avenues to increase renewable penetration. In the last decade, the costs associated with residential solar photovoltaic (PV) installations have decreased significantly, providing more homeowners with the opportunity to generate their own clean electricity. Research has found that the decision to invest in a residential solar PV system is guided by economic, social, and personal factors. Accounting for such complexities, the joint power of agent-based modeling and social network analysis is leveraged in this study to evaluate the effect of social influence on solar PV adoption. Featuring residential consumer agents with data-driven attributes, a logistic regression function to predict solar adoption, and random and small-world social network implementations, this work simulates residential solar PV adoption in New Jersey. Results indicate that including social influence in an agent-based electricity system model leads to increased installed residential solar capacity, but not necessarily higher adoption rates. These findings suggest that, with an understanding of the intricacies of consumer social networks, there are potential opportunities to bolster residential solar installations through low-cost social campaigns that motivate individuals to adopt home solar through their social ties.
Application of Munich Agile Concept for MBSE for a Holistic Approach To Collect Vehicle Data Based on Board Diagnostic System
Authors: Salehi Vahid
Published: November 2024

This paper is based on four different steps. In the first step, a literature review is provided on the topic of the application of on-board diagnostic systems and their connection to digital twins in a virtual environment. In the second step, some important research questions are addressed, which are dealt with in the following sections. Based on the research questions, this paper applies a systematic method to use generated data such as GPS position, gasoline engine parameters such as speed/revs, and the vehicle’s gasoline battery to enrich a digital data environment for virtualization and simulation. This technical paper explores the use of On-Board Diagnostic II (OBD-II) interfaces to collect data from gasoline vehicles and the subsequent analysis of this data using systems engineering methods. The paper will present the results of gasoline vehicle testing based on OBD-II data and Model Based Systems Engineering (MBSE) using the Munich Agile Concept for Systems Engineering (MAGIC) to design a system-of-systems approach based on Digital Twin Data. This paper and the corresponding research project will develop a consistent, traceable, holistic system-of-systems engineering approach for digital twins. MBSE is based on three important core pillars: 1) Methods/Processes, 2) Language and 3) Systems. The purpose of the newly developed Munich Agile Concept Approach is to manage complexity throughout the data collection, data processing and data virtualization process from a real environment to a virtual Digital Twin environment. The Munich Agile Concept contains six different levels: System Requirement, System Function, System Architecture, System Validation, System Test and System Usage Level. A graphical language called System Modeling Language (SysML) was used to define the first three levels. In the final step, this paper will report on the experiences made and the results of the applied MAGIC approach in Model Based Systems Engineering.
Development of an Optimal Variable-Pitch Controller for Floating Axial-Flow Marine Hydrokinetic Turbines
Authors: Sundarrajan Athul Krishna , Tran Thanh Toan , Wiley Will , Ross Hannah , Zalkind Daniel , Herber Daniel R.
Published: November 2024

This article discusses the development of an optimal variable-pitch controller for floating, axial-flow marine turbines. Recently, OpenFAST, an open-source wind turbine modeling tool, has been extended to model marine turbines. A controller is necessary to simulate marine turbines for different load cases using OpenFAST, which greatly impacts the performance of the energy system. Previous studies have designed controllers using a linearized model of the marine turbine, which can be time-consuming and require the expertise of a control engineer. In this study, we use an automated approach that uses generic models of the marine turbine to identify the controller gains, which can expedite the process of designing a controller. Using an optimizer to identify the control system parameters can additionally improve the controller’s performance. The optimal controller tuned using such an approach results in a 20% reduction in the tower-base damage equivalent loading and better tracking of the rated generator speed and power.
Operating Behavior and Performance of Polymer Gears in Pulsator Tests
Authors: Reitschuster Stefan , Tobie Thomas , Stahl Karsten
Published: November 2024

For designing gears reliable strength values are essential. The determination of strength values for the tooth root load-carrying capacity is usually based on experimental fatigue tests in a pulsator due to various advantages compared to back-to-back tests. In contrast to steel gears, it is currently unclear how polymer gears perform in the pulsator test and whether the pulsator test is suitable for determining the tooth root load-carrying capacity of such gears. Against this background, theoretical and experimental investigations on the operating behavior and fatigue life of POM gears were conducted and evaluated. Measurements on the tooth temperature under dynamic load provide insights into the thermal behavior of polymer gears, which must be considered due to the high-temperature dependency of the mechanical properties. Based on theoretical studies on the tooth root stress in the pulsator, S-N curves are determined and evaluated for different tooth temperatures revealing comparable tendencies to results from the back-to-back test in terms of damage pattern as well as service life.
Characterizing Model Fidelity Through a Set-Based Approach
Authors: Taylor Evan , Louis Ed , Mocko Gregory , Li Gang , Hybl Evan
Published: November 2024

Simulation models are often used in design to predict system performance for several use cases including trade space exploration, decision-making, and validation and verification. Models are abstractions of reality and do not contain all the phenomena and details in the real world. This fact brings many concerns, such as “How can I trust this model?” or “How should I choose between models?”. In modeling and simulation (M&S), the concept of fidelity explains how a model differs from reality. This paper proposes a set-based definition of fidelity based on the reduction of information throughout the model development process. An example of a ground vehicle conducting a gradeability test demonstrates the reduction in information from reality, the known world, testing, modeling, and simulation. Overall, this set-based approach to fidelity bridges disparate definitions of fidelity and creates a greater understanding of how models reflect reality.
Walking Gait, Energy Efficiency, and Energy Harvesting of a Simple Biped Robot
Authors: Wang Fengxia
Published: November 2024

To design energy efficient robots, researchers have dedicated themselves to examining the locomotion dynamics and walking pattern generation of passive bipeds. As the walking environment or system parameter changes, an energy use efficient robot may become inefficient, a possible approach to increase the energy efficiency is through the ability to harvest the energy used during the locomotion. The goal of the paper is to investigate the relations of a biped’s walking speed, locomotion energy consumption, as well as the ability to retrieve the lost energy as system parameter varying. Piezoelectric bimorphs were attached to the feet of the biped to harvest energy via exploiting the acceleration excitations induced vibrations at the instant foot lift and heel strike. As the incline angle of the ramp slope increases, the stable periodic-1 (P1) walking gait becomes faster and more energy costing. Also means more available energy to harvest, although the retrieved energy is much smaller compared to the locomotive energy. As the slope angle continues growth, the stable walking experiences sequence of period doubling (PD) bifurcations, becomes P2, P4, P8, and Chaos walking. As the walking gaits change, the walking speed, locomotion energy consumption, as well as the harvested energy grows as the slope becomes deeper.
Human Assembly Action Recognition Framework for Real-World Assembly Operation
Authors: Yang Chao-Lung , Kao Tzu-Ching , Lin Po Ting , Fu Pin-Cheng
Published: November 2024

In recent years, significant progress has been proceeded in human action recognition (HAR) technology. When applying HAR to practical scenarios, especially in the task of recognizing Standard Operating Procedures (SOP) for factory operators, some challenges such as resource requirements, differentiation of diverse movements, and difficulties in manual annotation exist. In this research, an assembly action recognition framework (AARF) was proposed to recognize the assembly operation conducted at the station level using the SlowFast video understanding model. First, the pre-trained YOLOv7 model is employed as a non-assembly action filter to detect the main operator, and then the irrelevant background is masked for a refined region of interest. Then, the preprocessed data is fed into SlowFast for action recognition through both temporal and spatial features. Finally, the confidence calibration strategy is implemented to enhance the robustness of results. A series of ablative experiments were conducted to study for optimizing the selection of model parameters, incorporating attention mechanism, non-assembly action filtering, and recognition result filter. Multiple assembly motion videos were collected from two similar product lines at a real-world production line. According to experimental results, the proposed method can improve the accuracy of human motion recognition on real factory production lines by up to 86.3%.
A Graph Algorithm for the Design of Functionally Graded Alloy Components
Authors: Allen Marshall D. , Arróyave Raymundo , Malak Richard
Published: November 2024

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Typology Development for Synthetic Chemistry Sub-Tasks: Towards Human-Robot Collaboration Task Design in the Wet Lab
Authors: Jung Diane N. , Bruns Carson J.
Published: November 2024

Chemical manufacturing is a growing field that contributes to many industries and employs tens of thousands of researchers in wet labs. Automation tools for synthetic chemistry are of interest not only for their potential impact on efficiency and productivity, but also on human resources and safety, since synthetic chemistry poses a number of occupational risks and is largely inaccessible to researchers with physical disabilities. Currently, most automation tools for synthetic chemistry are either designed to perform highly specialized tasks or they are designed as closed-loop systems with minimal interaction between human and machine during a synthesis procedure. We are pursuing an alternative, human-centered approach to robotic tools for synthetic chemistry, in which general-purpose collaborative robots (cobots) offer diverse forms of support to human researchers in the lab. In order to design frameworks for productive scientist-cobot collaborations, we need a deep understanding of the task space in synthetic chemistry labs and the impact of these various activities on the researchers. Based on observations and surveys from a group of experimental scientists, we have identified and analyzed 10 manual tasks commonly performed by researchers in the wet lab, each of which may be broken down into a sequence of sub-tasks. We conducted an in-depth analysis of the two most frequently performed sub-tasks: liquids dispensing and solids handling. Through subcoding, we identified 40 liquid dispensing typologies and 18 solid handling typologies, and evaluated the burden associated with each of these sub-tasks using the NASA TLX. These data will be of value for the design of human-centered automation tools that support, rather than displace, researchers performing manual tasks in the lab, in order to foster a safer and more accessible lab environment.
Method for Constructing a Compact Component Mode Synthesis Model for Analyzing Nonlinear Normal Modes of Structures With Localized Nonlinearities
Authors: Chen Xuan-Hong , Tien Meng-Hsuan
Published: November 2024

Research on nonlinear dynamics analysis is a crucial topic in mechanical and aerospace engineering. The analysis of nonlinear normal modes (NNMs) provides us with an effective mathematical tool for interpreting complex nonlinear vibration phenomena. Unlike the invariant normal modes of linear systems, NNMs often exhibit frequency-energy dependence and cannot be computed using the traditional eigen-decomposition method. Calculating NNMs relies on numerical methods that involve expensive iterative computations especially for systems of a large number of degrees of freedom. To relieve computational costs, this paper proposes a mode selection method for the component mode synthesis technique to enable compact reduced-order modeling of structures with localized nonlinearities. The reduced-order model is then combined with a numerical continuation scheme to establish a low-cost NNM analysis framework. This framework can efficiently predict the NNMs of high-dimensional finite element models. In this work, the proposed framework is demonstrated on an I-shaped cantilever beam with localized nonlinear stiffness. The results show that the proposed approach can identify the key modes in the reduced-order modeling procedure. The NNMs of the nonlinear I-shaped beam structure can then be analyzed with significant reduction in computational costs.
HairTouch: Investigating the Design Space of Hair-Based Tactile Output
Authors: Zhou Yi , Li Yan , Lu Yujia
Published: November 2024

This paper proposes a innovative notification method leverages hair-based tactile cues, HairTouch. This study explored the intensity and diversity of this tactile sense, HairTouch provided subtle and effective reminders in hands-free and eyeless interaction scenarios, comparing to vibration and electrical stimulation. The study focused on five body locations: forehead, ear contours, cheeks, side of the neck, and back of the neck. The experiments were conducted subsequently to explore the design space of HairTouch. The aim of the experiment was to determine the suitable intensity of the hair touch stimuli at these locations and to evaluate the user’s acceptance of this new method of interaction. The results of the study showed that users perceived significant differences in the intensity and locations of touch, suggesting that the touch of the hair could offer a new method of reminding of information. The study also found that the angle of hair’s swings significantly affects the user’s perception, suggesting that this parameter can be manipulated to express different information.

In summary, HairTouch showcases the potential of utilizing hair movement as a innovative and unique method of haptic interaction, offering a new dimension to interactive design. This approach can enhance the privacy of notifications and expand the types of available sensory in immersive technologies such as VR and AR. Future work will investigate the effect of hair movement speed on perception and explore more precise equipment to refine the instrument results.
Sandpiper Food Search Algorithm: A New Optimization Algorithm With Limited Knowledge
Authors: Wira Hadipoernomo Jessica Christa , Watson Bryan C.
Published: November 2024

Optimization problems in mechanical engineering play a crucial role in refining complex system designs, improving performance, and maximizing efficiency across various applications. These problems have become increasingly complex, stretching the limits of conventional methods such as convex optimization or the Newton-Raphson method. To address this challenge, numerous metaheuristic algorithms, often inspired by nature, have emerged including Particle Swarm Optimization, Genetic Algorithm, Bat Algorithm, Firefly Algorithm, and Cuckoo Search. However, most of these existing algorithms have global knowledge, which is unrealistic for some real-world complex systems such as underground mining and spacecraft trajectory. To bridge this gap, this article develops and presents a new biologically inspired optimization algorithm, the Sandpiper Food Search Algorithm. This algorithm is inspired by the food search behavior of sandpipers at the beach where each agent (sandpiper) explores the problem space to find the optimal area by exploiting the local search for candidate solutions around them. Moreover, this algorithm includes the wave action that forces these birds to shift from their current solution to increase exploration of the solution space. The performance of the algorithm is evaluated using four standard benchmark functions in comparison with the Firefly Algorithm. Firefly Algorithm was selected for comparison because it shares similar parameterization characteristics, and its use of decreasing light brightness with distance between fireflies mirrors the limitation of knowledge imposed by the visibility radius in sandpipers. This research provides a conceptual design of the new Sandpiper Food Search Algorithm and its performance when compared to Firefly Algorithm over four benchmark functions. Our work shows that the Sandpiper Food Search Algorithm outperforms the Firefly Algorithm in three of the four benchmark functions with at least 3% improvement in mean best solution and is on average 38% more reliable at finding a solution at least 95% of the optimal.
Influence of Tooth Deflections and Local Contact Deformations on the Tooth-Root Stress of Internal Spur Gears: Definition of a Load-Sharing Coefficient for the AGMA J-Factor
Authors: Pedrero José I. , Sánchez Miryam B. , Fuentes-Aznar Alfonso
Published: November 2024

The extension of the contact interval resulting from loaded tooth deflections and local contact deformations increases the effective contact ratio, which can exceed the value of 2 if the theoretical contact ratio is close to 2, as frequently occurs in internal spur gears. In these cases, the load is shared by at least two pairs of teeth throughout the entire cycle of meshing of one pair of teeth, which results in lower values of the tooth-root stress. This reduction in the root stresses is not adequately considered by the Standard’s calculation methods. This paper presents a study on the influence of load sharing on the tooth-root stress of internal gears. Additionally, a new coefficient to modify the AGMA J-factor is proposed to consider the reduced tooth-root stress in calculations when the effective contact ratio exceeds the value of 2.
Concept Chaining Patterns During Ideation Using Digital Tablets
Authors: Das Madhurima , Meza Jessica , Xu Christine , Yang Maria C.
Published: November 2024

Digital tablets are becoming increasingly popular as a sketching tool, in part because they allow designers to store many sketches in one place and to easily switch between types of sketching tools. These tools include features such as smoothing lines and copy/paste that aim to improve ease and quality of sketching. The ability to copy and paste elements of drawings affords designers the possibility to quickly modify and iterate on sketches, which may in turn influence the way in which designers engage with concept generation. This potential impact of digital sketching tools on concept evolution patterns has been minimally explored in a qualitative manner but not quantitatively. We present the results of a controlled human subjects study that investigates how the use of tablets (iPads) may influence concept evolution patterns when compared to pen and paper sketching during an engineering design concept generation problem.

We explore two main research questions. First, whether or not tablet use for sketching, as opposed to paper and pen sketching, is linked with more concept chaining (sequential iteration on a concept). We hypothesize that ideation on tablets will be linked with more concept chaining due to sketching features on the tablet such as copy and paste. Second, we ask whether or not concept chaining patterns will be different for design prompts that have multiple functional requirements. Here, we hypothesize that the concept chaining patterns for the primary functional requirement of a multi-component prompt will be consistent with the patterns of concept chaining for a prompt with only one requirement, but that secondary functional requirements may not exhibit these clear chaining patterns.

We find that tablet users demonstrate more concept chaining than paper and pen users despite having a similar number of related ideas overall. We also find that concept chaining patterns do change for design prompts with higher numbers of functional requirements especially because not all ideas address all parts of the prompt, but that the primary functional requirement results exhibit the same concept chaining patterns with more chains present on tablet sketching than paper and pen sketching.
Compliant Stepped-Beam Analysis for Deployable Space Structures With Flexible Panels
Authors: Skinner Mitchel , Geyser Andrew , Sargent Brandon , Magleby Spencer , Howell Larry
Published: November 2024

Deployable space structures that incorporate thin, flexible solar cells allow for innovative designs that are capable of high stowing efficiency. The purpose of this work is to present compliant stepped-beam analysis approaches that apply to deployable space structures with flexible panels connected with thin sheets and determine their deflection as a function of their material properties, geometry, and applied moments. Related methods are described. An analytical model and finite element analysis are compared and validated with a physical model. The end angle, coordinates, and radius of curvature of each segment are calculated and the results are compared. Beam thicknesses can be adjusted to increase curvature to intended sections of the beam. The approach is then applied in the preliminary design of a z-fold used as a deployable space array. The compliant-stepped beam deflected in a z-fold pattern provides designers with a straightforward model to analyze the position and curvature of a deployable array and tailor it to meet design requirements. Percent differences of each analysis are presented and discussed. The analytical model agrees well with FEA and physical solution results. Case assumptions are described and validated. Potential for future work related to large deflections of flexible-panel deployable space structures is described.