bluuebunny/crossref_metadata_2025 huggingface dataset:
Separation and Identification of Diesel Engine Noise Sources Based on Adaptive Variational Mode Extraction
Authors: Zhang Junhong , Lin Gengyi , Li Xiaozhen , Zhou Qidi , Lin Jiewei
Published: November 2022

An accurate and efficient method of identifying noise sources can provide guidance for acoustic improvement and troubleshooting of diesel engines. Due to the complexity and impact of diesel engine acoustic and vibration signal, the current signal decomposition methods are not adaptive enough in dealing with diesel engine acoustic signal, and it is difficult to identify non-order noise sources. In order to solve the above problems, an adaptive variational mode extraction method (AVME) was proposed by constructing the mutual correlation coefficient between decomposition signals and source signals as a judgment index. The accuracy and robustness of AVME algorithm were verified by constructing analog signals. The noise signal from the top of diesel engine was decomposed by AVME, and the time-frequency characteristics of the intrinsic mode function (IMF) components were extracted and decomposed. The acoustic-vibration coherence analysis and acoustic array technique were combined to identify the diesel engine noise source. The results show that the algorithm can successfully identify the oil pan noise, combustion noise, piston knock noise and air compressor noise of diesel engine.
Systematic Review and Classification of the Engineering for Global Development Literature Based on Design Tools and Methods for Social Impact Consideration
Authors: Armstrong Andrew G. , Suk Hailie , Mabey Christopher S. , Mattson Christopher A. , Hall John , Salmon John L.
Published: November 2022

While many tools and methodologies for assessing social impact exist and are used in the social science and development fields, there is a lack of standard methods for considering the broader social impact of products in the engineering community. Some reasons these methods are not as widely used in the engineering community include designers not being aware of the methods, or methods not being widely applicable. The purpose of this research is to help designers and researchers find relevant design tools and methods for implementing social impact considerations. This is done through the classification of 374 papers in the Engineering for Global Development (EGD) literature along several dimensions including method purpose, industry sector, social impacts considered, sustainable development goals, paper setting, and data inputs required. This paper describes how designers and researchers can use this classified paper set to locate relevant design tools and methods to improve social impact considerations in their work.
Capturing Designers’ Experiential Knowledge in Scalable Representation Systems: A Case Study of Knowledge Graphs for Product Teardowns
Authors: Goridkov Nicole , Rao Vivek , Cui Dixun , Grandi Daniele , Wang Ye , Goucher-Lambert Kosa
Published: November 2022

Knowledge collection, extraction, and organization are critical activities in all aspects of the engineering design process. However, it remains challenging to surface and organize design knowledge in a scalable and accessible manner given it often contains implicit or tacit dimensions that are difficult to capture. Knowledge graphs have been explored to address this issue but have been primarily semantic in nature in engineering design contexts, typically focusing on sharing explicit knowledge. In this work, we explore how knowledge graphs could offer a mechanism to organize experiential design knowledge and afford its use in complex queries. We develop a searchable knowledge graph based on data from a previous virtual product teardown activity with 23 professional designers. Examples of the underlying data within this corpus include descriptions of product components and their purpose as well as participant-determined relationships between these components. To structure the knowledge graph, we develop a schema that uses its constituent nodes and edges to represent design knowledge, relational information, and properties such as the node author’s discipline and the node’s function-behavior-structure classification. We propose and demonstrate two user-driven graph search types — intentional and exploratory — and four data-driven graph search methods, and illustrate through two extended examples their potential to reveal insights and patterns from teardown knowledge. These findings suggest that knowledge graphs can be a valuable approach to organizing and availing experiential design knowledge emerging from complex design activities.
Exploring How the Heterogeneity of Building Types in Community Microgrids Impact Their Value Proposition
Authors: Odonkor Philip
Published: November 2022

Community microgrids present a compelling new approach for designing and operating the next generation of power grids. The extent to which their benefits can be realized depends on their constituent buildings, energy infrastructure, and the control algorithms that maintain grid balance. Conventional practice has been to treat the former as inflexible, meaning micro-grids are often designed for a preset group to buildings. However, as microgrids evolve to consider multiple stakeholder needs (such as consumers, prosumers and utilities), the ability for them to maximize stakeholder value — in terms of demand flexibility and energy resiliency — relies on an optimal building composition. This work advances the hypothesis that heterogeneous microgrid compositions exhibit distinguishable value propositions for different stakeholders which, if identified and understood, can provide decision support for microgrid design and adoption at scale. By leveraging the US Department of Energy’s ComStock dataset, we conduct an in-depth empirical study which uncovers trends to support the inclusion (and in some cases exclusion) of a variety of building types when composing community microgrids. The pairing of hotels with quick service restaurants, for example, was one of several key findings that illustrate how complimentary building relationships can be leveraged to advance energy self sufficiency and demand flexibility in community microgrids.
Level-Set-Based Shape & Topology Optimization of Thermal Cloaks
Authors: Xu Xiaoqiang , Chen Shikui
Published: November 2022

Thermal metamaterials are gaining increasing popularity, especially for heat flux manipulation purposes. However, due to the high anisotropy of the structures resulting from the transformation thermotics or scattering cancellation methods, researchers are resorting to topology optimization as an alternative to find the optimal distribution of constituent bulk materials to realize a specific thermal function. This paper proposes to design a thermal cloak using the level-set-based shape and topology optimization. The thermal cloak design is considered in the context of pure heat conduction. The cloaking effect is achieved by reproducing the reference temperature field through the optimal distribution of two thermally conductive materials. The structural boundary is evolved by solving the Hamilton-Jacobi equation. The feasibility and validity of the proposed method to design thermal meta-devices with cloaking functionality are demonstrated through two numerical examples. The optimized structures have clear boundaries between constituent materials and do not exhibit thermal anisotropy, making it easier for physical realization. The first example deals with a circular cloaking region as a benchmark design. The robustness of the proposed method against various cloaking regions is illustrated by the second example concerning a human-shaped cloaking area. This work can inspire a broader exploration of the thermal meta-device in the heat flux manipulation regime.
The Effect of Leveraging Function-Sharing on System Modularity
Authors: Bhasin Devesh , McAdams Daniel A.
Published: November 2022

This work analyzes the change in the modularity of engineered systems upon leveraging function-sharing in the systems. Function-sharing refers to the simultaneous implementation of multiple functions by a single component. Leveraging function-sharing reduces the number of components constituting a system, and leads to improvements in the system’s performance characteristics. However, leveraging function-sharing in a system’s design is often presumed to decrease the system’s modularity and, consequently, inhibit the design benefits of maintaining a high system modularity. This work performs a simulation-based analysis to show that leveraging function-sharing may not necessarily decrease a system’s modularity. The change in a system’s modularity upon leveraging function-sharing is shown to be dependent upon the initial modularity of the system, the strength of inter-dependencies between the components that are combined to leverage function-sharing, and the strength of interactions between the teams designing the system modules. The analysis is performed by generating a sample set of hypothetical modular systems, and modeling them as undirected networks. Function-sharing is then simulated in the sample systems, and the change in the modularity of the systems upon implementing function-sharing is quantified using an existing modularity metric. The information presented in this work can support the design of systems that can simultaneously leverage function-sharing and exhibit a high modularity.
Agent-Based Simulation of Optimal Trust in a Decision Support System in One-on-One Collaboration
Authors: Lotfalian Saremi Mostaan , Bayrak Alparslan Emrah
Published: November 2022

Intelligent systems that can effectively collaborate with human users can potentially expand human decision-making capabilities in numerous domains. An important factor that determines the effectiveness of these intelligent systems is trust from human users. How much a user should trust an intelligent system to maximize the benefits is an open question. In this paper, we present a quantitative analysis of the impact of trust on the collaboration between a human user and an intelligent decision support system (DSS) in binary classification problems. Using an agent-based simulation model, we represent trust as a static quantity averaged over a set of Monte Carlo simulations calculated based on a user’s self-confidence, confidence in a DSS, and agents’ expertise. Our results show the optimal level of self-confidence and confidence in a DSS needed to maximize the collaboration performance under different problem scenarios. The results indicate that with such an optimal level of confidence, the collaboration performance can exceed the performance of the individual agents alone. Further, our results also show that having a concentrated expertise on particular types of problems is more beneficial than being somewhat knowledgeable in multiple problems given that the expertise of the user and the DSS complement each other.
Boone’s Buddies: Design of a Prosthetic Rear Limb Set for Dogs With Severe Amputations
Authors: Steinbrink Scott , Baumgarner Julia , Cardella Noah , Moretti Samantha , Schweitzer Emily , Piovesan Davide
Published: November 2022

This paper documents the design and implementation of a set of rear-limb prostheses for a dog, performed as a senior capstone design project by a team of students in the Biomedical and Mechanical Engineering programs at Gannon University. A particular target dog was selected to receive the design benefit. The unique features of this design arise from the severe nature of the dog’s amputations — the extent of injury requiring amputation resulted in very little residual limb, making secure attachment difficult. In addition, project goals included the ability to allow mobility on uneven surfaces, enhanced ability for the dog to raise and right himself, hygienic issues and ease of attachment/detachment. Benchmark studies found many competitor products on the market, but each fell short in meeting this particular dog’s needs in some way.
An Unified Approach for the Determination of Instantaneous Screw Axes for Linkages Associated With the Euclidean Group and Its Subgroups
Authors: Rico José M. , Valderrama Rodríguez Juan Ignacio , Cervantes-Sánchez J. Jesús , Pérez Zamudio Fernando Tomás
Published: November 2022

This paper presents a unified approach for the determination of the instantaneous screw axes for one-DOF linkages associated with the different subgroups of the Euclidean group. The theory behind the approach is based on the most general form of the three-axes theorem and the invariant symmetric forms, Killing and Klein, defined on se(3), the Lie algebra of the Euclidean group, SE (3). Using the Killing and Klein forms on the general form of the three-axes theorem provides sufficient equations to find the instantaneous screw axes of any linkage. The contribution provides a unified approach for the determination of the instantaneous screw axis associated with the relative motion of two bodies in general spatial motion. Further, the equations can be simplified when considering the different subalgebras of the Lie algebra of the Euclidean group, in particular, the spherical and planar subalgebras. The contribution includes two subgroups (subalgebras) that have not been previously analyzed. Further, it is proven that in general both the Killing and Klein forms are required to find the instantaneous screw axes of spatial linkages. Several examples for the general spatial case, and the two subal-gebras, that have been not previously analyzed, are presented.
Investigating the Relationship Between Geometric Features and Inspectability of Additive Manufactured (AM) Parts
Authors: Roy Debrina , Srbinovich Tanner , Arguelles Andrea P. , Menold Jessica
Published: November 2022

The versatility of Additive Manufacturing (AM) has enabled engineers and designers to realize previously impossible geometries. However, the increasing geometric complexities of these components pose a significant challenge for traditional inspection methods. If a part cannot be appropriately inspected costly redesign will be required, or worse fatal flaws and imperfections may not be identified prior to part-use. Considering the constraints of inspection techniques early in the design process could help designers make better design decisions. This paper aims to identify and investigate the fundamental relationship between the geometric features, geometric complexity, and overall inspectability of AM parts. Results suggest that traditionally accepted indicators of geometric complexity, such as lattice structures, do not significantly predict part inspectability.
A Local Constraint Resolution Approach for Dynamics Modeling of Parallel Kinematic Manipulators With Single-Loop Complex Limbs
Authors: Müller Andreas
Published: November 2022

A large class of parallel kinematic manipulators (PKM) possess complex limbs, i.e. limbs that comprise kinematic loops. This paper addresses the modeling of PKM with complex limbs with a single closed loops. The best known representative is the Delta robot. A systematic approach to the kinematics and dynamics modeling has been proposed recently. The remaining open issue was the computationally efficient solution of the geometric loop constraints. This is particularly important for model-based control of PKM. Global solution of the overall system of constraints is not efficient. In this paper, a local constraint resolution is introduced. A nested iteration scheme is applied for the local constraint resolution. This implements a constraint embedding technique, as a special case of the general concept known for multibody systems. Among others, one advantage is that the method allows dealing with redundant constraints locally or may even avoid them. As an example, the method is applied to the well-known Delta robot. This PKM is modeled as a 3R[2UU] PKM, which is known to be overconstrained. It is shown that the local constraint embedding can deal with this redundancy.
Parametric Analysis of the Nonlinear Dynamics of Cracked Cantilever Beams
Authors: Hsu Chia-Ling , Tien Meng-Hsuan
Published: November 2022

Structural damage occurs in a variety of civil, mechanical, and aerospace engineering systems, and it is critical to identify the damage at its early stage to prevent from catastrophic failures. When cracks are present in a structure, the breathing phenomenon between the crack surfaces typically triggers nonlinearity in the dynamic response. In order to thoroughly understand the nonlinear effect of cracks on the structural dynamics, two modeling approaches are integrated together in this work to investigate the crack-induced nonlinear response of a cantilever beam. First, a modeling method referred to as the discrete element (DE) method is employed to construct the discrete model of the cracked beam. The model constructed using DE is able to characterize the breathing phenomenon of the crack. Next, a simulation technique referred to as the hybrid symbolic-numeric computational (HSNC) method is then used to analyze the nonlinear response of the cracked beam. The HSNC method provides an efficient way to evaluate both stationary and non-stationary dynamics of the cracked system since it combines the efficient linear techniques and optimization tool to capture the system’s response. The proposed computational platform enables efficient multi-parametric analysis of cracked structures. The effects of crack location, crack depth, and excitation frequency on the cantilever beam are parametrically investigated using the proposed method. Nonlinear features such as the sub-harmonic resonance, non-stationary motion, multi-stability, and frequency shift are discussed in this paper.
Multibody Model Simplification by Parameter Reduction
Authors: Ros Javier , Plaza Aitor , Fuentes Jose D. , Iriarte Xabier
Published: November 2022

Model selection methods are used in different scientific contexts to represent a characteristic data set in terms of a reduced number of parameters. Apparently, these methods have not found their way in the multibody systems dynamics literature. Multibody models can be considered parametric models in terms of their dynamic parameters and model selection techniques can then be used to express these models in terms of a reduced number of parameters. These parameter-reduced models are expected to have a computational complexity smaller than the original one, and still preserve the desired level of accuracy. They are also known to be good candidates for parameter estimation purposes. In this work, simulations of the actual model are used to define a data set representative of the standard working conditions of the system. A parameter-reduced model is chosen and its parameter values estimated so that they minimize a prediction error on these data. To that end, model selection heuristics as well as normalized error measures are proposed. Using this methodology two multibody systems with very different characteristic mobility are analyzed. Very important reductions in the number of parameters and in the computational cost are obtained without compromising too much on the reduced model accuracy. As an aside result, a generalization of the base parameter concept to the context of parameter-reduced models is proposed.
Design of a Single-Input Morphing Compliant Mechanism With Separate Gripping and Retraction Modes
Authors: McGowan Patrick , Hao Guangbo
Published: November 2022

A key aspect of robotics and automation is continuous repetition of predefined travel and actions. One such example is a robotic gripper, gripping an object and displacing it linearly. Compliant mechanisms are designed to replicate the motion of rigid mechanisms through the use of flexible beam elements that take advantage of the elastic deformation properties of a material. Arrangements of compliant beams can be used to successfully transmit or transform purposeful motion and force. In this paper a compliant gripper is proposed that grips an object (X displacement) and retracts it linearly (Y displacement) based on a single actuation. The design is comprehensively analyzed through finite element analysis (FEA) method and is optimized using the design exploration tools. The mechanism is firstly designed by the Rigid Body Replacement method and is based on the double slider mechanism. Morphing is successfully achieved through the use of contact aided features and a pseudo spring beam to decouple the X and Y displacements. The design is refined and optimized using commercial finite element analysis software to closely match an ideal X and Y displacement path and displacement activated transition from X displacement to Y displacement whilst minimizing the input actuation force. Experimental tests are to be conducted to validate the design.
Universal Design Analysis for Improving the Usability of Fused Filament Fabrication 3D Printers
Authors: Grey Rebecca , Sinha Swapnil , de Vries Charlotte Marr
Published: November 2022

To accommodate a variety of users with the growing popularity of 3D printing technology, the concept of usability; the effectiveness of a user’s interaction with the product, must be considered. A seamless user interaction with the currently available commercial 3D printer systems assumes that the users have the required hand strength, ability to stand, and vision, which could be challenging for some learning this new technology. This research intends to utilize the principles of universal design, i.e., the idea of appealing design for all age groups or abilities towards operating the physical 3D printer in order to expand its field of use. Physical challenges of the human body as it moves to interact with desktop fused filament fabrication (FFF) 3D printers were investigated. Following that, a survey was collected, to understand the perspective of 3D printer users in terms of challenges faced while interacting with the machine and troubleshooting them. The survey indicated that users found print bed levelling the most challenging task. As a result, the redesign process for print bed leveling was initiated by the development of design specifications. This paper attempts to shed light on potential improvements that can be made in commercially available desktop systems by implementing universal design guidelines, such that the technology is accessible to a larger population. The process used in this paper is applicable for redesign of any existing product for Universal Design.
Dynamics of a Nonlinear Absorber and Hand-Held Impact Machine
Authors: Alabi Oreoluwa , Gupta Sunit Kumar , Barry Oumar
Published: November 2022

Due to the severity of vibrations transmitted to a worker’s hand through hand-help impact machines (HHIM), workers often suffer from hand-arm vibration syndrome (HAVS). Symptoms of HAVS include vibration white fingers, finger numbness, impaired tactile function, and muscle fatigue. To attenuate the level of transmitted vibrations and, hence, reduce the severity of HAVS, a method of using a nonlinear vibration absorber inerter (NVAI) has been proposed recently. It was observed that the use of NVAI can significantly reduce the transmitted vibration. However, a detailed nonlinear analysis of the HHIM with NVAI has not been performed, which can further help in the optimum design of the NVAI. This is the focus of the current work. The hand-arm system (HAS) coupled to an HHIM with an NVAI is modeled using a lumped parameter model. A detailed nonlinear analysis is performed numerically. A parametric study is performed to explore the effects of different system parameters on the system dynamic and identify key design parameters of the NVAI. We observe that the system exhibits quasi-periodic and periodic motion, which is further confirmed by Poincare maps and Phase portraits. It is further revealed that a careful selection of the absorber properties can significantly reduce harmful vibrations.
Design-Engineers’ Selection of Agency: Harm Mitigation in Ambient Intelligent Environments
Authors: Ballestas Caseysimone , Kim Euiyoung , Lanoy Jesuël , Janssens Jules
Published: November 2022

The computing paradigm where sensor and actuator technology work in tandem to track and act on events in real Euclidean space, known as ambient intelligence (AmI), is likely to become increasingly common due to the rapid maturation of computing technology. Installing AmI in the built environment creates ambient intelligent environments (AmIE), which strive to make the places we inhabit (invisibly) sensitive and responsive to our presence, needs, wants, and preferences. Given that built environments and the goings-on therein are complicated in an of them selves, implementing AmI for (increasingly) complicated tasks in (increasingly) complicated scenarios, increases the difficulty of managing the outcomes in AmIEs. Our previous research indicates that industry practitioners attribute the agency of AmI artifacts as responsible for these outcomes; especially when harm perpetuation is (one of) the outcome(s), which we codified as the Agency/Intelligence Axis [1]. Due to the nascence of AmI, research on best practices for the design-engineering of AmI is still emerging. This research seeks to add to this literature by evaluating our formerly identified Agency/Intelligence Axis in the context of AmIE through a case study of VyZee, a retail company working on transitioning their retail stores to “smart” stores. Our findings highlight that while VyZee seems largely unaware of any relationship between agency and perpetuating un-anticipated/-desired outcomes, they do implement an array of levels of AmI agency in their retail stores, and their justifications for their choices are presented in the discussion. Finally, coding the data revealed more nuance then previously documented in the Agency/Intelligence Axis, and a new Ambient Intelligent Agent Model, which suggests that AmI agents have six properties, is proposed.
Latent Variable Representations for Interactive Structural Design Exploration
Authors: Valdez Sofia , Rodriguez Nicholas , Seepersad Carolyn
Published: November 2022

Additive manufacturing and topology optimization are complementary technologies that enable unprecedented levels of design freedom for realizing complex structures. This increasing design freedom is accompanied by increasing complexity, such that it can become difficult for either computational algorithms or human designers alone to search these expansive design spaces effectively. Our previous work laid the foundation for an interactive design framework that enables human designers to use their expertise and intuition to guide computational algorithms quickly towards promising solutions. The framework established a latent representation of a library of designs by combining classical topology optimization techniques with a conditional generative adversarial network (cGAN). Our goal is to expand on this framework by creating interactive functionalities that allow users to more efficiently visualize and search an expansive structural design space by manipulating its latent variable representation.
Tradespace Organizational Practices: A Case Study
Authors: Daniels Julia , Wagner John R. , Turner Cameron J. , Gorsich David , Rizzo Denise , Hartman Greg , Agusti Rachel , Skowronska Annette , Castanier Matt , Rapp Stephen H.
Published: November 2022

Tradespace analysis capabilities are critical for organizations either selecting large programmatic efforts or those engaged in providing solutions to major program opportunities. The ability of an organization to effectively use the tradespace in their decision-making process had a substantial impact upon programmatic success. Poorly bounded tradespaces may lead to prototype vehicles (or any other system to be designed) that are ultimately unacceptable due to performance, cost, or technical risk issues. Tradespaces that are over-constrained can unduly limit design options and lead to stagnant designs that are unable to incorporate technical innovations. Most organizations find that tradespace analysis presents numerous challenges, so this research aims to address the evaluation of strengths, weaknesses, and opportunities for improvement within an organization. In this study, we explain how an interview-based process was used to perform this analysis and make recommendations for opportunities for process improvement within an organization (Ground Vehicle Systems Center or GVSC). Similar approaches could be applied to other organizations to facilitate the development of an organizational self-assessment that can aid in the identification of internal strengths, weaknesses, and opportunities for improvement within organizations performing tradespace activities.
Design of a Bed Rotation Mechanism to Facilitate In-Situ Photogrammetric Reconstruction of Printed Parts
Authors: Roberts Travis A. , Karmakar Sourabh , Turner Cameron J.
Published: November 2022

Additive manufacturing, or 3D printing, is a complex process that creates free-form geometric objects by sequentially placing material to construct an object, usually in a layer-by-layer process. One of the most widely used methods is Fused Deposition Modeling (FDM). FDM is used in many of the consumer-grade polymer 3D printers available today. While consumer grade machines are cheap and plentiful, they lack many of the features desired in a machine used for research purposes and are often closed-source platforms. Commercial-grade models are more expensive and are also usually closed-source platforms that do not offer flexibility for modifications often needed for research. The authors designed and fabricated a machine to be used as a test bed for research in the field of polymer FDM processes. The goal was to create a platform that tightly controls and/or monitors the FDM build parameters so that experiments can be repeated with a known accuracy. The platform offers closed loop position feedback, control of the hot end and bed temperature, and monitoring of environment temperature and humidity. Additionally, the platform is equipped with cameras and a mechanism for in-situ photogrammetry, creating a geometric record of the print throughout the printing process. Through photogrammetry, backtracking and linking of process parameters to observable geometric defects can be achieved. This paper focuses on the design of a novel mechanism for spinning the heated bed to allow for photogrammetric reconstruction of the printed part using a minimal number of cameras, as implemented on this platform.
Analysis of a Nonlinear Locally Resonant Metamaterial With Resistance-Inductance Shunt
Authors: Malla Arun , Bukhari Mohammad , Barry Oumar
Published: November 2022

The study of metamaterials for simultaneous vibration control and energy harvesting is a subject with considerable recent interest. This paper investigates a weakly nonlinear meta-material with electromechanical local resonators coupled to a resistance-inductance shunt circuit, a system with no previous examination in the literature. The nonlinear band structure of the system is presented to demonstrate the effect of an inductor in the shunt circuit, including the influence on softening and hardening nonlinearity effects. The system is then excited by a transient wavepacket and simulated numerically to further explore the features of nonlinear wave propagation in the proposed structure for multiple inductance values. Particularly, the system’s voltage response is studied through spatial profiles to observe the effects of shunt inductance, nonlinearity, and any potential interaction between the two. Focus is given to the potential for vibration control and energy harvesting by this metamaterial, including comparisons to previously investigated similar systems with resistance-only shunt circuit. For certain parameters including high electromechanical coupling, the band structure of this system is shown to include three mode branches instead of the two-mode band structure observed in the absence of shunted inductor. Strong vibration attenuation is observed in the frequency range around the central mode branch. The effects of the inductor on wave propagation and harvested voltage are also shown.
X-Ray Marching for the Computational Modeling of Tomographic Systems Applied to Materials Applications
Authors: Steuben John C. , Graber Benjamin D. , Iliopoulos Athanasios P. , Michopoulos John G.
Published: November 2022

X-ray tomography (XCT) and microtomography (uCT) are powerful experimental techniques for determining the internal structure of materials and objects. However, the physics governing these systems, particularly the myriad of complex interactions between X-rays and materials, lead to the frequent generation of spurious data “artifacts.” When these techniques are used to determine the quantitatively precise dimensions and morphology of defects and other features present in the objects under study, the presence of these artifacts is highly deleterious. A computational framework for simulating and studying tomographic processes, and the physical origins of such artifacts, may increase the overall utility of these techniques. This work presents the introduction, development, and demonstration of such a framework based on a ray-marching approach. A number of physics-driven and computationally-driven considerations guiding the development of this framework are discussed. A demonstration problem taken from prior literature is examined, and it is shown that even a basic implementation of this framework offers meaningful insight which can be used to improve quantitative measurements made using XCT. We conclude with remarks regarding the usage of this technique in a broader scope, and the work required to approach such tasks.
Towards Characterizing Cognitive Style Coping Behavior in Engineering Design
Authors: Radwan Noriana , Menold Jessica , McTernan Jesse , Jablokow Kathryn , McComb Christopher
Published: November 2022

Problem solving is a crucial aspect of engineering design, and cognitive style, or preferred problem-solving style, is an important way to understand designers’ individual behavior. When there is significant misalignment between the problem frame and one’s cognitive style, it results in cognitive gaps. Large cognitive gaps may hinder effective problem solving. According to Kirton’s adaption-innovation theory, such gaps are managed through coping behavior. However, coping behavior is understudied in the literature, especially when assessing person-problem gaps. We argue that a deeper understanding of these gaps and its resulting coping strategies in problem solving can aid in facilitating effective design. Therefore, the current study was developed to understand how cognitive style and the problem frame impacts solution outcomes; and identify the design strategies and behaviors that are elicited by participants of varying cognitive styles. Through a mixed methods analysis, we found that the problem frame can impact the types of solutions that designers develop and the cognitive experience of their design — where some behaviors indicate the prevalence of coping.
A Boundary-Value Problem for Covariance Analysis of Stochastically Perturbed Limit Cycles
Authors: Ahsan Zaid , Kuehn Christian , Dankowicz Harry
Published: November 2022

In this paper, we discuss an original covariance boundary-value problem that captures the effects of white noise on the local behavior near stable periodic orbits of the corresponding deterministic dynamical systems. The methodology relies on suitably constructed adjoint variables to project the dynamics onto locally transversal hyperplanes and ensure the existence of a unique solution. For each such hyperplane, the computed co-variance matrix describes an approximately Gaussian, stationary distribution that highlights directions of particular sensitivity to noise. In contrast to previous formulations, the boundary-value problem analyzed in this paper makes predictions in the original state-space variables rather than in terms of a reduced set of local coordinates for hyperplanes perpendicular to the local vector field. The formulation is compatible with the general form of an augmented continuation problem for the software package COCO; a non-adaptive version has been implemented as a general-purpose constructor for the periodic-orbit toolbox included in the COCO release. We illustrate the efficacy of the proposed formulation and toolbox by analyzing noise-induced behavior near limit cycles in two examples of nonlinear dynamical systems with autonomous drift terms. The analysis presented in this study can be used to design safe operating regimes for systems working in stochastic environments, as well as to design optimum working conditions for systems utilizing noise, such as energy-harvesting applications.
Analytical Periodic Oscillations in a Harmonically Excited Single-Degree-of-Freedom Aerodynamical Oscillator
Authors: Yu Bo , Luo Albert C. J.
Published: November 2022

In this paper, the equation of motion of a single degree of freedom aerodynamical oscillator was presented. The critical speed for the onsite galloping was determined from linearization. Assuming small angle approximation, the nonlinear vertical aerodynamic force was expressed. Then the periodic oscillations in a harmonically excited aerodynamical model were investigated. The nonlinear aerodynamic force was approximated using a cubic polynomial for a square section. The method of generalized harmonic balance method was employed to determine the analytical solutions of periodic oscillations. The stabilities of the analytical solutions of periodic oscillations were determined through the eigenvalue analysis. Finally, the analytical and the numerical responses of periodic oscillations were illustrated. The harmonic amplitudes were presented.
A Small MEMS Neural Network to Classify Human Sitting and Standing Activities
Authors: Okour Mohammad , Megdadi Mohammad , Nikfarjam Hamed , Pourkamali Siavash , Alsaleem Fadi
Published: November 2022

The next frontier of MEMS applications is their use as computing units to harness data at the sensor level. In particular, MEMS intelligent computing unit has the unique promise of significantly increasing energy efficiency while simultaneously increasing data processing speeds and eliminating data latency in many applications such as wearable devices. Along this line, this paper presents a demonstration of the first simulated microelectromechanical (MEMS) network capable of classifying real-life experimental data based on acceleration measurement to distinguish between sitting and standing behaviors without the need for any computing or processing unit. The MEMS network is made of four MEMS; two MEMS in the input layer and two in the output layer. The first MEMS in the input layer is responsible for detecting a rising edge acceleration and allows the first MEMS in the output layer to be triggered at a following falling edge of the acceleration signal. This signature corresponds to the sitting activity. On the other hand, the second MEMS in the input layer is responsible for detecting the falling edge of the acceleration signal and allows the second output MEMS to declare a standing activity if it detects a following falling edge signal. This work demonstrates the potential of distinguishing between the sit and stand activities without any computing unit.
Designing Mindfulness Practice System Based on Biofeedback in VR Environment
Authors: Li Shuo , Zheng Hongtao , Ge Yang , Yuan Wenyu , Han Ting
Published: November 2022

Mindfulness practice has been proved to have sound intervention effects in stress relief and emotion regulation. However, traditional mindfulness therapy relies on group courses under the guidance of experts, which is limited by personnel and site resources. There has been growing interest in mindfulness practice and related interaction products without exploring the role of biofeedback mechanism in mindfulness practice. However, to translate this potential into concrete design applications, we need a qualitative understanding of how breathing feedback is embedded in game design. This article discusses the effects of different physiological feedbacks mechanism in virtual environments for mindfulness game design, exploring the impact of breathing feedback (continuous feedback) versus head orientation feedback (discontinuous feedback) on young mindfulness beginners. Using “MindJourney,” we present key insights that summarize how physiological feedback can be used in mindfulness-based games for immersive interactions, self-state perception, and motivational design experiences. The experimental results show that the MindJourney mindfulness practice system can effectively improve users’ mindfulness practice experience, promote mindfulness ability training and stress relief, and has specific theoretical significance and application value. This article shares practical experiences in the other design and exploration of mindfulness game practice in health interventions to provide youth with a healthy lifestyle.
Functional Module Identification in Product Digital Twins: A Preliminary Study
Authors: Kotecha Maulik C. , Bhasin Devesh , Staack David , McAdams Daniel A.
Published: November 2022

The effect of product architectures on the digital twin (DT) modularity is previously unexplored. The authors present a functional modeling approach to identify the modules that emerge in product DTs in this article. A preliminary study on module identification is presented. A stepwise procedure for functional modeling of the physical twin (PT) followed by module identification based on the functional interdependency with DT is presented. Six examples of product DT from literature were chosen, and functional modeling followed by module identification was carried out. Based on the interdependency of modules, two types of modules were observed — discrete modules and integrated modules. The interdependency of the modules varied depending on the twinning purposes of DTs. The DTs purposed for component health monitoring were observed to have more discrete modules than the integrated ones compared to those with remote operation as their primary twinning purpose. It is also observed that the modular product architectures in PTs may not remain modular in their DT. A few key research questions arising from this exploratory study are also discussed in this paper. The study presented here can potentially offer engineers and researchers in the engineering design community a familiar approach to study novel problems and open new directions of inquiry.
A Self-Reactive Ocean Wave Energy Converter With Winch-Based Power Take-Off: Design, Prototype, and Experimental Evaluation
Authors: Liu Mingyi , Bennett Adam , Ruan Fujun , Li Xiaofan , Lou Junhui , Mi Jia , Zuo Lei
Published: November 2022

Agriculture provides a large amount of the world’s fish supply. Remote ocean farms need electric power, but most of them are not covered by the electric power grid. Ocean wave energy has the potential to provide power and enable fully autonomous farms. However, the lack of solid mounting structure makes it very challenging to harvest ocean power efficiently; the small-scale application makes high-efficiency conversion hard to achieve. To address these issues, we proposed a self-reactive ocean wave converter (WEC) and winch-based Power Take-Off (PTO) to enable a decent capture width ratio (CWR) and high power conversion efficiency. Two flaps are installed on a fish feed buoy and can move along linear guides. Ocean wave in both heave and surge directions drive the flaps to move and hence both wave potential energy and wave kinetic energy are harvested. The motion is transmitted by a winch to rotation motion to drive an electric generator, and power is harvested. Dynamic modeling is done by considering the harvester structure, the added mass, the damping, and the excitation force from ocean wave. The proposed WEC is simulated in ANSYS AQWA with excitations from regular wave and results in a gross CWR of 13%. A 1:3.5 scaled-down PTO is designed and prototyped. Bench-top experiment with Instron is done and the results show that the mechanical efficiency can reach up to 83% and has potential for real applications.
Alpha-Photovoltaics for Milliwatt Applications
Authors: Khan Muhammad , Litz Marc , Russo Johnny , Tompkins Randy
Published: November 2022

Isotope power sources can serve applications for sensor or communication nodes that are required to last the lifetime of infrastructure because they possess at least 1000 times higher energy density, long operational lifetimes (> 10 years), and wider operational temperature range compared to chemical power sources. There are different methods of converting radiation energy into electrical energy at low power (nW – mW) levels, the most prevalent is betavoltaic devices which convert beta particles energy directly into electrical energy using a semiconductor junction. However, the current state-of-the art betavoltaics can only produce 10’s of micro-watts/cm2, and are not suitable for applications requiring mW output power. Alpha particle emitting isotopes have higher energies than beta isotopes and can be used to produce power in mW range, but require radiation tolerant ultra-wide-bandgap semiconductor junctions, which are not widely available yet. Therefore, it is necessary to look at alternate approaches to harvest energy from alpha decay using existing semiconductor technology. In this paper, we have validated one such approach to convert alpha particles energy into electrical energy by employing an intermediate phosphor layer placed between an alpha source and an InGaP PV cell. We simulated the average energy emission of Am-241 using a pelletron source accelerating He2+ ions and exposed the InGaP PV with phosphor film deposited on top while measuring the IV characteristics throughout the experiment. We measured an output power of 165 μW/cm2 at 4.5 MeV beam, representing a fluence of 3.75 × 1013 ions.
Atomic-scale observation of dynamic grain boundary structural transformation during shear-mediated migration
Authors: Fang Zhengwu , Xiao Jianwei , Tan Susheng , Deng Chuang , Wang Guofeng , Mao Scott X.
Published: November 2022

Grain boundary (GB) structural change is commonly observed during and after stress-driven GB migration in nanocrystalline materials, but its exact atomic scale transformation has not been explored experimentally. Here, using in situ high-resolution transmission electron microscopy combined with molecular dynamics simulations, we observed the dynamic GB structural transformation stemming from reversible facet transformation and GB dissociation during the shear-mediated migration of faceted GBs in gold nanocrystals. A reversible transformation was found to occur between (002)/(111) and Σ11(113) GB facets, accomplished by the coalescence and detachment of

(

1
¯

1
¯

1
)
/
(
002
)

-type GB steps or disconnections that mediated the GB migration. In comparison, the dissociation of (002)/(111) GB into Σ11(113) and Σ3(111) GBs occurred via the reaction of

(
111
)
/
(
11

1
¯

)

-type steps that involved the emission of partial dislocations. Furthermore, these transformations were loading dependent and could be accommodated by GB junctions. This work provides atomistic insights into the dynamic structural transformation during GB migration.