bluuebunny/crossref_metadata_2025 huggingface dataset:
Topology Optimization in Consideration of Overhang Constraint for Additive Manufacturing Based on Coupled Fictitious Physical Model in Thermal Design Problem
Authors: Tajima Mikihiro , Yamada Takayuki
Published: November 2023

Additive manufacturing can be used to create complex optimal structures through topology optimization. However, the overhang constraint, which requires costly support materials, is a problem when part of the structure is unsupported. Previously, the fictitious physical model was proposed to consider geometric manufacturing requirements, e.g., the overhang constraint. However, converging to a single optimal structure is challenging in the fictitious physical model because the model acts noninteractively as the mechanical model describing physical phenomena. To solve the convergence problem, we propose a coupled fictitious physical model, where two models interact by changing the material constants of the mechanical model in regions where geometric constraints defined in the fictitious physical model are violated such that the objective function worsens. In this paper, the proposed model is formulated based on the steady-state heat conduction problem with overhang constraint. Then, the optimization problem and sensitivity analysis are discussed. Finally, the proposed model is verified using an example two-dimensional heat conduction problem.
Mechanical Logic Gates and Processors Using Hinge-Connected Pinned-Pinned Arches
Authors: Maharana Priyabrata , Shekhar Sudhanshu , Ananthasuresh G. K.
Published: November 2023

Physical limitations such as extreme temperature and intense radiation restrict the use of electronic circuits in military, space, and geothermal applications. Hence, there is a need for alternative ways to process information for specific applications using mechanical devices that provide functions similar to that of electronic systems. Furthermore, mechanical devices are preferred over others as they consume less energy and dissipate less. In this paper, we present compact mechanical logic gates using connected pinned-pinned bistable arches that are stress-free in their as-fabricated state. The connected arches possess multiple stable states for different inputs and do not require external axial compression as a preload. Our mechanical logic gates consist of three pinned-pinned arches, which makes them compact compared to other designs. The three serially connected arches have alternate signs of curvatures, and they can flip and switch to their second stable state when input is given to their neighbors. We present criteria for flipping and switching as design charts using non-dimensional geometric parameters. As a first step, with the appropriate selection of geometric parameters of input and output arches, we designed, prototyped, and validated AND, NAND, OR, and NOR gates. Next, we used the mechanical gates to design logic processors. The cases of encoder and de-multiplexer are used as demonstrative examples with experimental validation.
Bayesian Mesh Optimization for Graph Neural Networks to Enhance Engineering Performance Prediction
Authors: Park Jangseop , Kang Namwoo
Published: November 2023

In the field of engineering design, surrogate models for 3D computer-aided design (CAD) have been widely used to replace computationally expensive simulations. However, the conventional surrogate modeling process, which relies on the geometric parameters (or design variables) of CAD, has limitations when dealing with complex structural shapes commonly found in industry datasets. These limitations include information loss in low dimensions and difficulty in parametrization. This study proposes a Bayesian graph neural network (GNN) framework for a 3D deep-learning-based surrogate model that predicts engineering performance by directly learning the geometric features of CAD with mesh representation. Our proposed framework derives the optimal size of the mesh elements, creating a high-accuracy surrogate model with Bayesian optimization. It also solves the heterogeneity problem of 3D CAD data in that 2D images have regular pixel structures, whereas 3D CADs have irregular structures. From the experimental results, the mesh quality is highly correlated with the prediction accuracy of the surrogate model, and there exists an optimal mesh size that satisfies the high-performance requirements of the surrogate model. We expect that our proposed framework has the potential to be applied to mesh-based simulations in various engineering fields, reflecting the physics-based information widely used in computer-aided engineering.
Feasibility of Small-Scale, Off-Grid Desalination in Navajo Nation
Authors: Brei Melissa
Published: November 2023

Water scarcity is affecting billions of people around the world and the utilization of brackish water, defined as having total dissolved salt content between 500–10,000 mg/L, could provide a potential solution. This paper focuses on the Navajo Nation in the southwest of the United States, an extremely water stressed region, due to many homes lacking piped water and electricity. Previous work points to membrane desalination being a suitable off-grid technology for providing potable water. By analyzing overlaps of various maps, feasible regions for desalination were identified due to high potential for positive impact and opportunity for desalination to succeed. This geographic analysis revealed the southern region as the focal point for this study, which was corroborated by various partners. Water haulers and stakeholders in diverse organizations affiliated with water management were interviewed to elucidate design requirements for a highly-adoptable desalination system. Engaging with stakeholders at the beginning of the design process validated the proposal of desalination as a technical solution. Additionally, the interviews revealed sensitive design requirements and unique challenges that will aid the designers in the following stages of the design process. Future work will include a robust evaluation of membrane desalination technologies to select the best suited for this application.
Reducing Data Requirements for Wiener Series Identification With Gaussian Process Priors
Authors: Massingham Joseph , Nielsen Ole , Butlin Tore
Published: November 2023

System identification of nonlinear dynamical systems aims to predict the output of a system for a given input. In many engineering applications, the underlying physics are not fully understood and so there is no analytical solution. The Wiener series is a classical data-driven technique that decomposes the system response into a set of orthogonal functionals of increasing order. Unlike standard black-box algorithms, such as neural networks, the series is highly interpretable and can offer insight into the nonlinearities present. To date, in order to calculate higher order terms in the Wiener series, vast quantities of data are needed. In this paper, a novel formulation of the Wiener series is developed in the frequency domain which applies to general stochastic inputs with an arbitrary spectrum. It is enhanced by placing Gaussian process priors over the Wiener kernels to enforce prior knowledge of their structure. This significantly reduces the quantity of data required for inference and has the benefit of enabling the calculation of the third order kernel for systems with long memory. The benefits were demonstrated in initial investigations using an idealised nonlinear oscillatory system. Decomposition of the system response into Wiener functionals also sheds light on the learnability of nonlinear dynamical systems, which could be used to assess the value of collecting additional data.
The Impact of Facilitation During Idea Generation in Engineering Design
Authors: Murphy Alexander R. , Moseley Emily , Weaver Morgan , Linsey Julie S.
Published: November 2023

During the engineering design process, group idea generation is often used to search the solution space before committing resources to the development of new products and services. The study presented investigates how trained facilitation using a brainstorming approach impacts the idea generation process. Three conditions are presented: a facilitated condition, unfacilitated condition, and nominal condition. Participants in these experimental conditions were tasked with generating ideas to a design problem leveraging a morphological matrix to record and organize their ideas. Specifically, the quantity of generated ideas, perceived task load, and psychological safety are measured when a trained facilitator is present or not present during the idea generation process. Results suggest that a trained facilitator has a positive impact on the quantity of generated ideas in an engineering context but is not as effective as nominal groups (individuals working independently), which is consistent with prior literature. However, results suggest that trained facilitation may have other benefits during idea generation such as reduced perceived task load and increased psychological safety of group members. This study shows the significant impact of trained facilitation on idea generation during engineering design and provides a foundation for future work that expands these results into how facilitation may impact other stages of the engineering design process.
Feeling the Distance: Exploring Novice Designers’ Perceptions of the Psychological Distance Towards and Empathy Induced by Problem Variations
Authors: Herzog Jenna , Fodale Rebekah , Alsager Alzayed Mohammad , Starkey Elizabeth M. , Prabhu Rohan
Published: November 2023

The accelerating depletion of natural resources has necessitated the design of environmentally sustainable engineering solutions. To meet this need for sustainable solutions, designers must actively incorporate considerations of environmental impact in their design decisions. Prior research suggests that the effects of climate change are often perceived to be psychologically distant, and this distance could inhibit individuals from actively engaging in environmentally sustainable behavior. Little research has investigated the impact of problem framing based on designers’ psychological distance on design performance. Furthermore, research suggests that empathy development could be an effective mechanism for bridging psychological distance. However, little research has assessed the utility of empathy-invoking problem framing in sustainable engineering design practice and education. Our aim in this study is to explore this research gap by comparing student designers’ perceptions of different problem formulations. Specifically, we tested the effects of variations in (1) the socio-spatial context and (2) the empathy focus of a similar design problem. The effects of these variations on the perceived psychological distance and empathy-invoking nature were tested through a 2 × 2 between-subjects experiment. From the results, we see that the variations in the problem formulation did not relate to either the perceived psychological distance or the perceived empathy-invoking nature. These findings suggest that issues related to environmental sustainability tend to be perceived similarly, despite differences in their socio-spatial context and empathy-invoking nature.
System Level Techno-Economic and Environmental Design Optimization for Ocean Wave Energy
Authors: McCabe Rebecca , Dietrich Madison , Liu Alan , Haji Maha
Published: November 2023

Ocean waves have the potential to provide clean energy to large swaths of society. Despite their promise, wave energy converters (WECs) are prohibitively expensive, partly due to the lack of design convergence in the WEC industry. A system-level optimization facilitates cost reduction, systematic evaluation of various architectures, and ultimately design convergence. This paper outlines an optimization framework for wave energy at the industry level, starting with the selection of a suite of metrics that capture the value proposition of wave energy more fully than traditional metrics. This includes metrics that encompass environmental sustainability and economic value in addition to economic cost. Two processes for metric weighting are proposed: a heuristic process for emerging off-grid markets and a capacity expansion model for the grid market. As a demonstration of the weighting process, results from three existing studies are synthesized into weights for the levelized cost of energy, capacity factor, and standard deviation of capacity factor. Finally, the optimization design variables, parameters, objectives, and constraints are formulated, and methods to handle the many categorical or integer design variables and parameters are discussed. The process articulated here can also be applied to other emerging energy technologies, ultimately advancing decarbonization in the energy sector.
Gender-Based Social Revolutions and Their Effect on Technology Evolution: A Case Study of the Sewing Machine
Authors: Kang Samantha , Dong Andy
Published: November 2023

This paper applies a feminist critique of technology to develop a model for design trajectories, specifically the technology life cycle. The model aims to explain the origins of radical design changes even when scientific revolutions are absent (or distant) and radical performance improvements are inconsequential. The breast pump is introduced to illustrate how public health, social and cultural norms, federal policies, and identity influence a design trajectory. The breast pump’s delayed and limited evolution despite technology advances indicates the compounding consequences of these factors on a technology’s design trajectory. We then investigate the sewing machine (first patented in 1846) to explore this phenomenon more closely. Our research illustrates conditions under which a social norms lens might change the expected technological outcome predicted by purely economic or organizational models. By shifting the unit of analysis away from single designs to a trajectory of design cycles over time, this paper offers explanations for conditions under which designs will remain resistant to debiasing, with only minor incremental change, and the social dynamics associated with design discontinuities. Our model includes the social construct of gender norms as a socio-technological lens to examine the limitations of the traditional technology life cycle model. Finally, we discuss how our new model can update engineering design theory and pedagogy.
The Influence of Differential Pressure on Stability of Vertical Rotor-Seal System
Authors: Kimura Shogo , Inoue Tsuyoshi , Taura Hiroo , Heya Akira
Published: November 2023

The rotordynamic (RD) fluid force generated in fluid elements such as seals in turbomachinery affects the stability of turbomachinery and causes shaft vibrations. Various studies have been conducted to clarify the effects of seals on the stability of rotor systems. Many studies have been conducted on the rotor dynamics of horizontal shaft systems, considering the RD fluid force generated in the seals, and in these studies the stability of horizontal shaft systems has been assessed by eigenvalue analysis using RD coefficients. However, few studies have been conducted on vertical shaft systems. The dynamic behavior of vertical shafts differs significantly from that of horizontal shafts owing to their different structural arrangements. Vertical shaft systems are generally prone to instability because of the fluid film whirl, and the amplitude of shaft whirl tends to be large. When the amplitude is large, the RD fluid force cannot be linearized around the equilibrium point using RD coefficients. Therefore, destabilization and stabilization phenomena that appear in vertical shaft systems cannot be predicted by eigenvalue analysis. To predict such phenomena, Fluid-Structure Interaction (FSI) analysis is required, which considers the interaction between the shaft vibration and the RD fluid force generated in seals. This study used FSI analysis to investigate the effects of unbalance and differential pressure on the stability of a vertical shaft system subjected to RD fluid force generated in the seal.
High-Frequency Band Gap Design of Porous Phononic Crystals by Topology Optimization
Authors: Murai Naoki , Noguchi Yuki , Yamada Takayuki
Published: November 2023

Phononic crystals can control the propagation of elastic waves by their unique dispersion properties such as band gaps. In recent years, the application of phononic crystals for controlling high-frequency elastic waves, which is important for managing thermal conductivity in the nanoscale and for wireless communication, has been attracting attention. This research proposes a design method of phononic crystals which exhibit band gaps at high band order for the applications with high-frequency elastic waves. To consider manufacturability in nanoscale, phononic crystals made of a single material are assumed. A level set-based topology optimization is used for the design of phononic crystals. An objective function is proposed to achieve a band gap within an aimed range of frequency. As a numerical example, 2-dimensional silicon phononic crystal with hexagonal lattice is optimized. Our approach successfully generates a phononic crystal with a band gap at high band order.
Physics-Based Automated Data Preprocessing (ADP) for Machine Learning Applications
Authors: Valizadeh Sotubadi Saleh , Nguyen Vinh
Published: November 2023

This study aims to develop an Automated Data Processing (ADP) algorithm for real-world applications of machine learning (ML). Specially, this work seeks to contribute to the state-of-the-art Automated ML domain by providing a framework by which all the processing units of any ML application could be automatically determined based on a set of prior knowledge provided to the algorithm without external assistance by an ML developer. For this purpose, the ADP algorithm was designed consisting of a Reinforcement Learning (RL) agent as the actor-critic at the top level and a classification unit at the lower level for the data processing of the given raw data. The ADP algorithm is tested on a set of raw data extracted from several lathe turning experiments for the purpose of cutting tool-wear classification. The data are collected using acceleration, acoustics, and temperature sensors mounted on a Computer Numerical Controller (CNC) lathe machine. The ADP is implemented on the collected data and the RL agent is trained for several episodes. The performance accuracy of the classification unit on the test data is the criterion to define the reward function of the RL agent upon which the agent is trained. After the training is conducted the best action policy is extracted based on higher state values and the number by which each state is chosen as the optimal action policy at the end of each learning episode. The results show that the policy chosen by the ADP algorithm exhibits better classification performance on the given data and can outperform other policies different from the optimal policy selected by the algorithm. Therefore the proposed RL framework incorporates physics-based knowledge of a turning process to systematically automate data processing for ML applications.
Identification of Singularities and Real and Complex Solution Varieties of the Loop Constraints of Linkages Using the Kinematic Tangent Cone
Authors: Müller Andreas , Li Zijia
Published: November 2023

The configuration space (c-space) of a mechanism is the real solution variety of a set of loop closure constraints. Singularities of this variety (referred to as c-space singularities) are singular configurations of the mechanism. In addition, a mechanism may exhibit other kinematic singularities that are not visible from the differential geometry of the c-space (referred to as hidden singularities). The latter is related to a drop in the rank of the constraint Jacobian while the c-space is locally a smooth manifold. Another kinematic feature that is only due to the corank of the constraint Jacobian is the shakiness of a mechanism. Such situations were analyzed by investigating the local geometry of the c-space and its corank stratification. It has been shown recently that hidden singularities and shakiness can be attributed to the fact that complex solution branches intersect with the c-space, i.e., with real solution branches. This paper employs the kinematic tangent cone to identify local solution branches. While the kinematic tangent cone is an established generally applicable concept, which gives rise to a computational (numeric and symbolic) algorithm, it has yet only been applied for analyzing the real solution set. The method is shown for several examples. Further, the algebraic aspects are briefly elaborated.
Who Is This Design For? Promoting Consideration of People During Concept Generation
Authors: Makhlouf Thanina E. , Murphy Laura R. , Daly Shanna R. , Seifert Colleen E.
Published: November 2023

The success of a design is not determined solely by its technical aspects. A design must work for the people who will be using it and in the context in which it will be used. Human-centered design approaches suggest strategies to remind engineering designers of the people impacted by their design decisions. While many of these strategies can be used within and across multiple design phases, during the act of sketching concepts during concept generation, there are few explicit strategies for centering people. We investigate possible impact from a simple intervention during a concept generation task through a between-subjects experiment. Working alone is a single design session, half of a group of mechanical engineering students were asked to explicitly “represent people” within their conceptual sketches. Afterwards, all students reviewed each of their concepts to answer, “Who is this idea for? Who do you imagine would use it?” Those who received the intervention requiring representation of people within concept sketches produced significantly longer reflections with greater depth compared to the control group. Adding drawings of people to sketches resulted in more consideration of the social and physical context of use and of the user’s personal preferences and values. Depicting people in generated concepts substantially reduced claims a design is “for everyone,” suggesting explicit representation of potential users produced more thoughtful consideration of diversity among potential users.
Predicting the Quantity of Recycled End-of-Life Products Using a Hybrid SVR-Based Model
Authors: Xia Hanbing , Han Ji , Milisavljevic-Syed Jelena
Published: November 2023

End-of-life product recycling is crucial for achieving sustainability in circular supply chains and improving resource utilization. Forecasting the quantity of recycled end-of-life products is essential for planning and managing reverse supply chain operations. Decision-makers and practitioners can benefit from this information when designing reverse logistics networks, managing tactical disposal, planning capacity, and operational production. To address the challenge of small sample data with multiple factors influencing the recycling number, and to deal with the randomness and nonlinearity of the recycling quantity, a hybrid predictive model has been developed in this research. The model is based on k-nearest neighbor mega-trend diffusion (KNNMTD), particle swarm optimization (PSO), and support vector regression (SVR) using the data from the field of end-of-life vehicles as a case study. Unlike existing literature, this research incorporates the data augmentation method to build an SVR-based model for end-of-life product recycling. The study shows that developing the predictive model using artificial virtual samples supported by the KNNMTD method is feasible, the PSO algorithm effectively brings strong approximation ability to the SVR-based model, and the KNNMTD-PSO-SVR model perform well in predicting the recycled end-of-life products quantity. These research findings could be considered a fundamental component of the smart system for circular supply chains, which will enable the smart platform to achieve supply chain sustainability through resource allocation and regional industry deployment.
A Heuristic Approach to Classify Geometrically Defective Bead Segments Based on Range of Curvature, Range of Sound Power and Maximum Height
Authors: Surovi Nowrin Akter , Soh Gim Song
Published: November 2023

The paper presents a classification methodology for determining geometrically good and defective bead segments for the Wire Arc Additive Manufacturing (WAAM) process based on optimally determined thresholds of three parameter metrics: namely, the range of curvature, range of sound power, and maximum height. We show how a heuristic search can be performed to systematically identify the suitable thresholds for the various parameter metrics to classify bead segments. The heuristic search for each parameter metric is performed by finding a threshold value that minimizes overlapping area between the Kernel Density Estimation (KDE)s formed by the distribution of the good and defective bead segments. We combine these thresholds to yield a three-dimensional threshold window for identifying geometrically defective bead segments. This approach is helpful for dataset labeling that overcomes the visual inspection labeling used in the literature. Experiments are conducted on the Inconel 718 material, with 660 bead segment data. We verify the results of our threshold selection using real bead scans and evaluate its mean squared error (MSE) with the parabolic bead model commonly used in literature to model bead profiles. We find that our proposed approach can separate the starting and ending segments of the beads well and identify geometrically defective bead segments between them. We also observe that the MSE of geometrically defective bead segments’ is much higher than the good segments, demonstrating the validity of our approach to classify geometrically defective bead segments.
Development of a Pillow Placement Process for Robotic Bed-Making
Authors: Cheung Chi-Hong , Tan Aaron Hao , Goldenberg Andrew
Published: November 2023

Bed-making is a common chore completed in various living environments to promote user comfort, hygiene, and well-being. Unfortunately, the physical and tedious nature of the act makes it challenging for segments of the elderly community to complete the chore, and thus the opportunity arises to develop robots to automate the task. However, despite the opportunity’s importance and positive impact, there is limited research on developing robotic bed-making systems. The aim of this research is to start addressing this gap by proposing methods for accomplishing pillow placement, a major part of the bed-making task. This paper introduces a pillow placement process to be used by a static 6-DOF (degree of freedom) one-armed robotic manipulator equipped with a 2-finger gripper. The process uses YOLOv4-tiny, image transformations, and principal component analysis (PCA) to infer pillow poses in a transformed RGB image, as well as a set of manipulator macro-actions to move pillows to their goal pose. We evaluated the proposed methodology in a real-world setting, where it enabled the robot to place pillows at desired poses on a miniature bed successfully in 89% of the experimental runs.
Resilience and Sustainability in Certified Green Buildings: Applying Ecosystem Concepts to Aid in More Dynamic Green Communities
Authors: Payne Emily , Wagner Hannah , Layton Astrid
Published: November 2023

Sustainable and resilient buildings ensure safety and lifespan while also benefiting the environment. Leadership in Energy and Environmental Design (LEED) is one respectable certification that many buildings can receive to ensure that they are meeting future climate and energy goals. However, LEED buildings have credits that do not necessarily agree with creating a sustainable environment. When comparing the orientation of LEED points and their relationship to the building and community to ecological structures, we found that a rearrangement of categories can provide visualization for organized recycling and higher cyclicity through ecological network applications. This relationship was applied to a new scorecard which has results indicating that if designers choose to meet criteria where one credit in each grouping is implemented in construction, then a sustainable building can still be efficient as well as recognized as a green building.
Impact of Shaft Misalignments in Planetary Gearboxes
Authors: Fuerst Marius , Otto Michael , Stahl Karsten
Published: November 2023

Planetary gear sets have a more complex structure than layshaft gearboxes which leads to challenges in design, analysis and operation. In this paper, design critical phenomena in planetary gear sets are addressed and latest test bench findings are presented. These focus on the impact of carrier shaft and planet pin misalignments on the load distribution in the gear mesh. Based on the deformation behavior of the loaded gearbox, which is determined by a coordinate measuring machine, a method is proposed to analyze the tooth alignment deviation with respect to the carrier rotational position. Finally, results from different test setups are analyzed and compared.
State-Space Characterization of Human Balance Through a Reinforcement Learning Based Muscle Controller
Authors: Akbaş Kübra , Zhou Xianlian
Published: November 2023

For proper balance assessment during a physical rehabilitation program, clinicians typically rely on rubric-oriented battery tests to score a patient’s physical capabilities, which can lead to subjectivity. While approaches have been taken to increase the objectivity of physical assessments and provide more detailed quantifications, many of them tend to be limited to tracking the center of pressure, which can lead to missing information that is critical to the whole-body movement. To this end, the center of mass (COM) state space presents a promising avenue for balance characterization. Previous work has shown various approaches to analyze balance in the COM state space through analytical, computational, and experimental methods. Here, we investigate balance recovery by developing a balance controller for a musculoskeletal model through reinforcement learning (RL). The RL framework is built on top of two neural networks describing the joint trajectory mimicking or targeting and the muscle activation coordinate, which in combination control the musculoskeletal model. The neural network models, i.e., the controller, are learned through the Proximal Policy Algorithm (PPO). The controller is then iteratively tested by imposing random initial states (positions and velocities) to the model and notating the trials with successful balance recovery trajectories. This allows for the construction of a balance region (BR) which describes the potential initial COM states that will yield balanced trajectories. The resulting BR was then compared to the analytical margin of stability determined through a linear inverted pendulum approach, which showed a similar trend in the successful COM states. Overall, the presented balance controller shows a promising new approach to assessing balance in bipedal systems, particularly in humans.
Designing Complex Systems for Decommissioning in a Circular Economy: A Systematic Literature Review
Authors: Dilanjaya Hewa Witharanage Shenal , Holtta-Otto Katja , Otto Kevin , Li Wen
Published: November 2023

The Circular Economy aims to replace the current linear “cradle to grave” product life cycle approach with a more circular “cradle to cradle” approach which is driven by design or “circular design”. This is done by circulating the product components back at the end of life through circular design strategies such as reuse, repurpose, remanufacturing and recycling aiming to maintain as much of their embedded value as possible. For complex systems (e.g., Aircraft), the end of life is typically the decommissioning stage during which they are withdrawn from service. In this paper, we conduct a systematic literature review to synthesize the current approaches to solve the problem of decommissioning complex systems in the context of circular economy. We identify current practices and methods can be divided into reactive approaches, barriers and enablers towards a proactive approach, and tools to support a proactive approach. In addition, the review reveals that the problem of decommissioning can be approached from two perspectives: the product and the designer. Five dimensions are identified under these two perspectives. Under the product perspective, (1) Customized designing of complex system according to the local ecosystem, (2) Designing for inter industry repurposing and (3) Designing universal components. Under the designer perspective, (4) Guidelines for selecting decommissioning options for complex systems at the design stage and (5) Evolving designer thinking towards circular design.
Distributing Design Domains for Topology Optimization in Systems Design
Authors: Endress Felix , Kipouros Timoleon , Zimmermann Markus
Published: November 2023

When objectives, constraints, boundary conditions, and loading conditions are clear, topology optimization is useful to generate the optimal shape for an individual component. However, in systems consisting of multiple components, component interfaces and their locations may have a significant influence on the component, and, thus, the global system performance. Before topology optimizations can be performed, design domains and associated loading conditions must be allocated to the individual components when designing the system. Unfortunately, to optimally define interfaces in lightweight design, the mechanical performance of each component must be known.

This paper proposes a simple and robust approach to specifying the settings for component optimization in a system context. In the first step, requirements are elicited and categorized in system- and component-level. Next, a topology optimization formulation at the component-level is derived from the requirements. Third, different interface definitions are generated, and optimal topologies are computed using sampling. This database is evaluated using a Parallel Coordinates tool, determining the optimal distribution of design domains and incorporating formal and informal constraints. Lastly, final geometries are computed using topology optimization with the setup resulting from system optimization. By informing system-level design with information from the detail design, design domains can be optimally distributed.

In a use case, the approach is applied to the control system of a glider airplane, where a common design domain is allocated to three brackets. Optimization at system- and component-levels lead to a reduction in mass by ∼11 % compared to an intuitive distribution of design domains. With the proposed approach, individual topology optimizations of single components will contribute to the global system performance in an optimal way.
Hand Assemble Action Recognition Using Spatial Temporal Graph Convolutional Network
Authors: Yang Chao-Lung , Lin Yen-Ping , Hsu Shang-Che
Published: November 2023

In the manufacturing site, more and more research works have been conducted to apply Human action recognition (HAR) to detect or recognize the human worker’s actions/motions. This research aims to develop a hand gesture recognition framework particularly in a hand assembly production site where the accuracy of human hand motion is crucial for assembly. This research investigated the number of joints that might affect the prediction accuracy of HAR models when using the same image data. In this study, the skeleton information extracted from OpenPose was used to estimate the human action of the assembly operations. The extracted skeleton was then used as the input of Spatial-Temporal Graph Convolutional Networks (ST-GCN) for action recognition. The prediction accuracy of the human action recognition model under different labels and the number of joints were analyzed. The videos collected from the real-world motherboard assembly were used to evaluate the feasibility of the proposed framework. The experiments showed that the action labeling with Right-handedness-head (26 joints) resulted in the best accuracy of the recognition model. This result also implies the skeleton information of handedness might be enough for hand assembly work when the non-handedness hand was only assigned for similar action such as fixing the components.
Inertia Parameter Identification for Closed-Loop Mechanisms: Adaptation of Linear Regression for Coordinate Partitioning
Authors: Pyrhönen Lauri , Mikkola Aki , Naets Frank
Published: November 2023

Accurate modeling and identification methods have increasing importance for design, verification, and control of multi-body systems. However, operational parameters are often unknown and inaccuracies of inertia parameters are among the main sources of uncertainty in multibody models.

This study therefore investigates the application of a linear-regression-based identification approach for rigid multibody systems. A multibody system model, originally described with differential-algebraic equations, is transformed into a set of ordinary differential equations using coordinate partitioning. This allows the identification framework, which requires the system to be described with ordinary differential equations, to be applied for rigid multibody systems described with either relative coordinates, reference point coordinates, or natural coordinates.

The methodology is demonstrated through a numerical example of a slider-crank mechanism with a kinematic reference set for the crank arm. The measurement data for identification is produced artificially using a commercial multibody software.

The results show that the presented methodology is capable of accurately identifying the system’s inertia parameters even with a relatively short motion trajectory used for training. However, the effects of measurement noise are not covered in this study — this is because the presented model is mathematically equivalent to the models used in robotics, and the tools for measurement noise reduction for those models are already discovered in robotics literature.

The presented linear-regression-based identification approach opens new opportunities for developing more accurate multibody models. These models can be considered especially useful for state-estimation and control of multibody systems. When the static model parameters are accurately identified, different state-estimation algorithms can more effectively estimate dynamically changing uncertainties.
Effects of Recycled Permanent Magnets on Electric Machine and Hybrid Electric Vehicle Performances
Authors: Pakštys Saulius , Bonfitto Angelo , Hegde Shailesh , Ugalde Gaizka , Garramiola Fernando , Rivera Christian Alejandro
Published: November 2023

Permanent magnet price volatility is an ongoing issue that affects many industrial sectors worldwide, dictating the costs of the final product by a substantial degree. This fluctuation can be attributed to a large concentration of NdFeB magnet production and material sourcing occurring in concentrated geopolitical areas, thus motivating institutions and governments to look elsewhere for magnet material for various applications. The work presented in this paper aims to determine the viability of recycled permanent magnets in electric machines used within the automotive industry. Magnet recycling incentives are presented, along with the two main routes for magnet reprocessing. They are briefly compared to present the route selected within this study. The recycled magnets used in this study are characterised such that relevant parameters are extracted for further analyses. A P2 hybrid electric vehicle is modelled and its energy management system presented, being an Equivalent Consumption Minimisation Strategy. The performance evaluation of a baseline machine at component level is performed, with its affect on vehicle performance quantified, followed by the recycled magnet machine’s characterisation and subsequent performance evaluation at vehicle level. The recycled magnets inhibit a minor efficiency degradation at component level, leading to a performance degradation of about 0.11% at vehicle level.
Design and Optimization of a Multi-Mode Piezo-Motor Based on a Compliant Mechanism
Authors: Yao Hong , Bi Hai , Wei Junjie , Chen Fangxin
Published: November 2023

Piezo-motors are widely used in precision positioning. However, the traditional piezo-motor moves via single motion mode such as stick-slip mode, inchworm mode, and scan mode, respectively. A single motion mode cannot balance motion speed, load capacity, and resolution at the same time. Integrating multiple motion modes into a piezo-motor is a sensible approach for conflict resolution. This paper presented a multi-mode piezo-motor based on a compliant mechanism that is able to regulate the contact force to achieve different motion modes. The characteristic of the compliant mechanism is analyzed by finite element method. To improve the performance of the proposed piezo-motor, the optimization design of the compliant mechanism based on the response surface method is carried out in ANSYS Workbench. A prototype, whose structure parameters were consistent with the optimization result, was fabricated. The performances of the proposed piezo-motor were tested through a series of experiments. The results showed that the prototype possesses a stiffness of 2.861N/um, and a fundamental frequency of 1203.8Hz, which are 37.8% and 11.9% higher than the initial design, respectively.
Folding-Wall Kirigami, Design and Compressive Performance
Authors: Corrigan Tom , Srivastava Abhishek , Xie Di , Arthur Cory , Brownell Nathan
Published: November 2023

Kirigami, the cutting and folding of sheets, can create useful three-dimensional shapes from flat material. Some kirigami patterns self-deploy from their flat state when tension is applied; we call these Tension Activated Kirigami (TAK) patterns. A unique TAK pattern has been proposed that deploys under tension into connected rows of vertical, accordion-like, folded walls that visually resembles two-thirds of a full honeycomb structure. This folding-wall TAK pattern has been shown to produce a structure comparably strong to a full honeycomb structure in the same material, achieving a specific strength and specific stiffness averaging 84% and 45% respectively of a full honeycomb1. The structure is also conformable, allowing it to wrap around objects. The previous study investigated patterns with square wall sections. In this study we expand the design space of the folding-wall TAK pattern by adjusting the aspect ratio of the folded-wall. Folding-wall structures with various heights and lengths were constructed from kraft paper and compressed in a load frame. A simulation was also created to investigate the compressive performance of folding-wall kirigami structures with a larger range of heights and lengths and reinforce the experimental results. The stiffness and strength of the deployed folding-wall TAK structures are presented.
Leveraging Smart Farming Technologies for Optimal pH Adjustments With Variable Rate Lime Application
Authors: Nagchaudhuri Abhijit , Pandya Jesuraj , Nnebedum Bede , Mitra Madhumi , Nindo Caleb
Published: November 2023

Variable rate lime application involves using advanced digital and geospatial technologies to apply lime at varying rates across a field based on soil pH levels. Soil pH levels can vary significantly across a field, and applying lime uniformly may result in over-application in some areas and under-application in others. Applying lime at variable rates, based on prescription maps prepared using soil analysis data from grid sampling can improve soil pH and achieve a desired pH level. Soil pH affects nutrient availability, soil microbial activity, crop growth, and crop development and yield. The target pH level for row crops can vary depending on the crop type, soil type, and other factors. However, a good target pH range for row crops is generally between 6.0 and 7.0. In this work, the target pH level was set at 6.5 throughout the field. Soil pH levels in an agricultural field can change over time due to a variety of reasons including rainfall, topography, soil type, and fertilizer use among others. The soil pH needs to be monitored regularly and adjusted as required to maintain optimal soil conditions for crops. When the soil pH is too low or too high, it can result in nutrient deficiencies or toxicities, reduced soil microbial activity, and reduced crop yields.
A New 3-DOF 2T1R Parallel Mechanism: Topology Design and Kinematics
Authors: Huiping Shen , Du Zhongqiu , Chablat Damien , Li Ju , Wu Guanglei
Published: November 2023

This article presents a new three-degree-of-freedom (3-DOF) parallel mechanism (PM) with two translations and one rotation (2T1R), designed based on the topological design theory of the parallel mechanism using position and orientation characteristics (POC). The PM is primarily intended for use in package sorting and delivery. The mobile platform of the PM moves along a translation axis, picks up objects from a conveyor belt, and tilts them to either side of the axis. We first calculate the PM’s topological characteristics, such as the degree of freedom (DOF) and the degree of coupling, and provide its topological analytical formula to represent the topological information of the PM. Next, we solve the direct and inverse kinematic models based on the kinematic modelling principle using the topological features. The models are purely analytic and are broken down into a series of quadratic equations, making them suitable for use in an industrial robot. We also study the singular configurations to identify the serial and parallel singularities. Using the decoupling properties, we size the mechanism to address the package sorting and depositing problem using an algebraic approach. To determine the smallest segment lengths, we use a cylindrical algebraic decomposition to solve a system with inequalities.
Computational Modal Analysis of an Aircraft Hydraulic Pump Support Structure
Authors: Kersten Simon T. , Mechefske Chris K.
Published: November 2023

Computational modal analysis performed using finite element analysis is an established method for estimating the modal parameters of complex structures. This work aims to provide insight into the techniques necessary to accurately model structural components within an aircraft by performing computational modal analysis on a rear-mounted pump support structure. The results of this analysis will be used to further aid in the understanding of the vibratory transmission path from the support structure to the aircraft cabin. The frequency response functions were used to validate the finite element model via a visual and analytical comparison against experimental data. A modal frequency response analysis was used to estimate the dynamic response at a discrete set of points on the structure. A model validation study showed an excellent correlation between the experimental and computational results for frequencies between 100–2000 Hz with an average percent difference of the centre frequencies of 9.4%. The agreement between the two sets of results across the 20–4000 Hz bandwidth deteriorated slightly to 11.7 %. Modifications were made to the webbing of the pump support yoke as well as the in-board and out-board isolator plates. These tests confirmed that differences between the frequency responses of the original and modified finite element models can be justified using modal analysis theory. It was found that these particular structural design changes did not significantly influence the modal response of the structure. The methodology presented in this work provides an outline for future modelling and analysis of aircraft structural designs.