bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Slack Tolerant, Sliding Pulley Differential Mechanism for Adaptive Grasping
Authors: Khatik Vitthal , Saxena Anupam
Published: November 2023

Use of differential mechanisms in adaptive grasping is a prominent way to reduce the number of actuators, weight, and control complexity of the system without compromising on functionality. Towards this, we present a novel sliding pulley differential mechanism (SPDM) designed systematically for hand prosthetic or exoskeleton devices to enhance their portability and performance. The toroidal arch in the SPDM’s pulleys helps address and eliminate string derailment encountered in conventional rotating pulley-based differentials under string slackness. Sliding and rotation degrees of freedom for pulleys aid SPDM against changes in string orientation within and out of their sliding plane. An analytical model is developed to compute the actuator force, which closely matches with the experimental results.
Pareto Optimization of Tissue and Blood Vessel Growth in 3D Printed Bone Scaffolds
Authors: Arefin Amit M. E. , Egan Paul F.
Published: November 2023

Computational design is necessary for advancing biomedical technologies, particularly complex systems with numerous complicated trade-offs. For instance, 3D printed tissue scaffolds constructed as lattices necessitate consideration of tissue and vasculature growth trade-offs in relation to complex geometries. In this paper, curvature-based tissue growth models and agent-based vascularization simulations are used to predict growth. NSGA-II (non-dominated sorting genetic algorithm) is used for Pareto optimization of growth for heterogeneous unit cell scaffolds. Cube and BC-Cube (Body Centered-Cube) unit cells are considered with beam diameters from 64 to 313 μm that are arranged in lattices with No Voids or Channel Voids configurations. The Channel Voids configuration has channels consisting of no unit cells that promote unobstructed vascularization. Seeding the algorithm with high-performing scaffolds with homogenous unit cells improved search efficiency and quality, since unit cells can be configured either for high tissue growth or high vasculature growth. The Pareto front of solutions demonstrates that scaffolds with large porous areas for the Channel Voids improve vasculature growth while lattices with no larger void areas result in higher tissue growth. Results demonstrate the advantages in using NSGA-II for dual-objective search in complex biomedical systems, which provides a foundation for future multi-objective optimization for advanced tissue engineering systems.
The Objective Way to Detect the Path to Purchase by Clustering Shoppers’ Trajectories
Authors: Paolanti Marina , Pierdicca Roberto , Placidi Valerio , Mancini Adriano , Zingaretti Primo , Frontoni Emanuele
Published: November 2023

The trajectories of shopping carts and baskets in a supermarket are an information-rich feature that can help in understanding the retail environment, gives idea about the interactions between objects and the ongoing events. This paper is interested in understanding, improving and personalising shopping experience by clustering the trajectories acquired by shopping carts and baskets in a real retail environment (a real supermarket during the business hours). In order to reach this, sCREEN (Consumer REtail ExperieNce) dataset has been previously built and the tracking system is built around Ultra-WideBand (UWB) technology. The approach proposed in this paper enables retailers to analyse the impact of different store layouts (maps) and shelf layouts (planograms) on issues such as ease of selection, affairs and the overall shopping experience. The first assumption is that some common sub-trajectories can be missed when seeing clustering trajectories as a whole. After the trajectory partitions into a set of line segments, similar line segments are grouped together to finally form a cluster. Then, a novel macro-clustering is developed, able to improve the robustness of the method and take into account the fact that trajectories are ordered collections of points. Finally, the performance of the proposed method is tested on a real-world dataset.
Dynamic Modeling and Robust Torque Control of a Discrete Variable Stiffness Actuator
Authors: Yu Ziqing , Fu Jiaming , Yao Bin , Chiu George , Voyles Richard , Gan Dongming
Published: November 2023

Collaborative robots, or cobots, have been developed as a solution to the growing need for robots that can work alongside humans safely and effectively. One emerging technology in robotics is the use of Discrete Variable Stiffness Actuators (DVSAs), which enable robots to adjust their stiffness in a fast-discrete manner. This enables cobots to work in both low and high stiffness modes, allowing for safe collaboration with human workers or operation behind safety barriers. However, achieving good performance with different stiffness modes of DVSAs is a challenging problem. This paper proposes a method to provide force control of a DVSA by exploiting the dynamic model and the discrete stiffness levels. The two-mass dynamic model, a widely accepted model of flexible systems, is used to model and analyze the DVSA. The proposed method involves using Gain-scheduling and Deterministic Robust Control (DRC) controllers as modelbased control algorithms for the DVSA to achieve high-precision force control. We also conducted a comparison with the commonly used proportional integral derivative (PID) control algorithms. The paper presents a detailed analysis of the dynamic behavior of the DVSA and demonstrates the effectiveness of the proposed control algorithms through simulation with different scenario comparisons, even in the presence of external disturbances.
Magnetization, Geometry, and Segmentation Analysis of Nested Halbach Cylinders for Optimizing the Interactive Torque
Authors: Biggs Elijah , Kuo Chin-Hsing , Ren Ting
Published: November 2023

Cylindrical permanent magnets with a Halbach magnetization are used for a variety of applications. Nesting two such cylinders concentrically and rotating one with respect to the other generates a passive torque, which could be harnessed to counterbalance a payload attached to the rotating magnet. In this paper, we analyze the effects of critical magnetic and geometrical parameters of the nested Halbach cylinders on the generated interactive torques by using electromechanical simulation software. Specifically, the effects of the dipolar and multipolar Halbach magnetization patterns, cylinder geometric parameters, and cylinder segmentation are of major interest in this study. The results show that the optimal Halbach magnetization pattern is one where the exterior cylinder has an internal magnetic field while the interior cylinder has an external magnetic field. The simulation observes changes in the magnitude of the interactive torque for modifications in the radial width ratio, thickness-to-width ratio, and thickness ratio of the cylinders. To maximize the torque, the airgap between the cylinders should be as minimal as possible. Outer cylinders that are segmented into eight or more discrete arc shapes could reliably approximate the torque produced by the ideal continuous magnetization. Moreover, the study shows that the interactive torque of a segmented outer cylinder could approach the ideal maximum torque produced by a continuous magnetic cylinder. It is anticipated that the outcome of this study is beneficial for the optimal design of nested Halbach cylinders for gravity compensation.
Kinetostatic Modeling and Cable Tension Optimization of Cable-Driven Parallel Robots on Cylindrical Surfaces
Authors: Jin Lei , Zhang Boxiang , Alqaydi Maitha , Wang Xiaoming , Taha Tarek , Gan Dongming
Published: November 2023

This paper presents a kineto-static model for cable-driven parallel robots (CDPRs) that addresses the challenges of designing and optimizing CDPRs for cleaning and manufacturing tasks on curved surfaces. CDPRs are known for their lightweight design and scalable workspace, making them a promising solution for large part cleaning and manufacturing. However, the curvature of the cables introduces complexities in the moving platform configuration that must be addressed. The proposed model provides a solution for finding the moving platform position with a given set of cable lengths, as well as determining the cable tension force direction and magnitude for a 2-anchor-point cylindrical CDPR. Furthermore, an optimization method for multiple anchor cylindrical CDPRs is formulated using planar force balance equations and linear programming. The method defines corresponding anchor points that counter gravity, allowing for non-ordinary-anchor-location-based reconfiguration that changes the maximum cable tension requirements and surface coverage. The proposed model is demonstrated through simulations and calculations, which highlight its potential in addressing the challenges of designing and optimizing CDPRs for cleaning and manufacturing on curved surfaces. The research provides valuable insights into the potential of CDPRs in these applications and presents a tool for optimizing the design of CDPRs with multiple anchor points.
A Physics-Informed Action Selection Framework for Robotic Heating
Authors: Dhanaraj Neel , Manyar Omey M. , Krishnan Vihan , Gupta Satyandra K.
Published: November 2023

Robots are being considered for performing external heating of components in manufacturing applications. This paper presents a physics-aware action selection policy that employs forward simulation with a branch and bound search to efficiently determine the best action sequence to position the heating tool. We take inspiration from physics-informed machine learning and present a parameter learning graph-based modeling framework that enables the robot to predict the temperature evolution of the surface of interest with respect to time. We also present a state transition model to describe how the thermal characteristics of the system change based on the heating tool’s position. We demonstrate our proposed robotic heating action selection approach for the composite layup process on an industrial tool. This work demonstrates the usefulness of physics-inspired machine learning in a real-world application.
Roundabout Traffic: Simulation With Automated Vehicles, AI, 5G, Edge Computing and Human in the Loop
Authors: Previati Giorgio , Mastinu Gianpiero , Campi Elena , Gobbi Massimiliano , Uccello Lorenzo , Varela Daniel Álvaro , Albanese Antonino , Roccasalva Alessandro , Santin Gabriele , Luca Massimiliano , Lepri Bruno , Ferrarotti Laura , di Pietro Nicola
Published: November 2023

The aim of the paper is to assess how the traffic of roundabouts could be organized in the future. A mixed traffic is supposed to occur, featuring both fully automated vehicle and vehicles driven by humans. The case study is a part of a comprehensive research funded by European Commission, focusing on how improving the 5G network by Artificial Intelligence (AI) and edge computing.

The traffic flow into a reference roundabout is simulated by SUMO, a Reinforcement Learning (RL) algorithm is derived and drives the automated vehicles into the roundabout. By means of a dynamic driving simulator, a real human drives into the simulated traffic of the roundabout. The human-in-the-loop is needed to check whether the driver feels comfortable and safe while driving in presence of automated cars.

The preliminary results are quite promising. Drivers seem not worried when they interact with Connected and Automated Vehicles (CAVs) into the roundabout. They seem preferring to share the roundabout with CAVs as they seem feeling the traffic to be more fluent. Such preliminary results deserve an extensive statistical investigation for a final assessment.
Preliminary Development of a Robotic Hip-Knee Exoskeleton With 3D-Printed Backdrivable Actuators
Authors: Sanchez Alyssia , Rossos Trent , Mihailidis Alex , Laschowski Brokoslaw
Published: November 2023

Robotic exoskeletons can provide powered locomotor assistance and rehabilitation to persons with mobility impairments due to aging and/or physical disabilities. Here we present the preliminary development and systems integration of T-BLUE — a modular, bilateral robotic hip-knee exoskeleton with 3D-printed backdriveable actuators. We retrofitted commercially available passive postoperative orthoses with open-source 3D-printed actuators to minimize cost and improve accessibility. The actuators are of quasi-direct drive design with high-torque density brushless DC motors and low gearing (15:1 transmission ratio) for low output impedance and high backdrivability, therein allowing for energy-efficient and dynamic human-robot physical interaction and legged locomotion. The modular design allows the exoskeleton to be customized and adapted to different users (e.g., persons with lateral vs. bilateral mobility impairments) and different hip-knee joint configurations. The goals of this preliminary study were to describe our experience with regards to the repeatability of the open-source 3D-printed actuators in engineering practice and the feasibility of integrating the actuators into wearable robotics hardware. This qualitative research serves as a first step towards using the robotic exoskeleton to support the development and testing of novel controller designs and rehabilitation protocols for different locomotor activities of daily living. We are especially interested in populations that could benefit from partial locomotor assistance such as older adults and/or persons with osteoarthritis. Future research will involve benchtop testing to quantitatively evaluate the actuator performance in terms of dynamics and energy-efficiency.
Bio-Inspired Gait Trajectory Design for Lizard-Inspired Wall Climbing Robot
Authors: A. K. Anugrah , Thakur Atul
Published: November 2023

Wall-climbing robots can have potential to be used in a range of areas like surveillance, reconnaissance, cleaning of high-rise building facade, and repairing. This paper presents a few improvements to the gait trajectory of a quadruped, lizard-inspired wall-climbing robot that employs a trot-like gait. The proposed enhancements build upon the earlier work of our research group, which involved the design and fabrication of a wall-climbing lizard-inspired robot that utilized pressure-sensitive adhesion [1]. The robot was equipped with a mechanical switching mechanism for transitioning between adhesion and peeling to effect climbing. However, the gait trajectory employed was not smooth resulting in occasional detachments while climbing. To improve the climbing performance, this paper paper proposes a segmentation of the foot’s path during each step into three separate regimes: peel, stride, and squat. By defining the foot’s path with respect to time increments, we aim to reduce the overall gait time, improve bio-mimicry, and enhance surefootedness. Additionally, we introduce a uniform acceleration and deceleration plan to time the movements of the feet, thereby smoothing the dynamics of the gait. Moreover, we introduce a real-time method to smoothly transition the steering angle of the robot. These proposed improvements are expected to broaden the operational capabilities of the lizard-inspired robot and improve climbing performance.
Targeted Sampling DWA: A Path-Aware DWA Sampling Strategy for Omni-Directional Robots
Authors: Shen Chen , Soh Gim Song
Published: November 2023

This paper describes a modified sampling strategy for the Dynamic Window Approach (DWA), a local path planner, for omni-directional robot motion planning. An efficient local path planner allows the robot to quickly respond to dynamic obstacles and ensures that the resultant velocity commands meet the dynamic constraints of the robot. While typical DWA implementations sample the velocity space evenly, we propose that a targeted sampling approach will result in a more fine-grained search of the relevant velocity space, leading to finer control and better performance in space-constrained environments. Our targeted sampling strategy (TS-DWA) is informed by the global planned path of the robot, allowing us to sample more velocities in the general path direction. We employ a polar velocity generator to selectively sample velocities and couple angular velocity samples to the path curvature. A bias for angular velocity is added for robots with a preferred heading, such as robots with forward-mounted sensors, to quickly turn towards the desired direction for better sensing. The strategy is implemented as a ROS Navigation Stack local_planner plugin and tested in simulation with Gazebo using an omni-directional robot platform. Experiments show that as the space around the simulated robot gets smaller, our proposed sampling strategy results in more successful navigation trials in space-constrained environments to the desired goal compared to other commonly-used methods like DWA and Timed-Elastic-Band, where planning fails or oscillates.
Topology Optimization of Fluidic Pressure-Driven Multi-Material Compliant Mechanisms
Authors: Kumar Prabhat , Pinskier Josh , Howard David , Langelaar Matthijs
Published: November 2023

Compliant mechanisms actuated by pneumatic loads are receiving increasing attention due to their direct applicability as soft robots that perform tasks using their flexible bodies. Using multiple materials to build them can further improve their performance and efficiency. Due to developments in additive manufacturing, the fabrication of multi-material soft robots is becoming a real possibility. To exploit this opportunity, there is a need for a dedicated design approach. This paper offers a systematic approach to developing such mechanisms using topology optimization. The extended SIMP scheme is employed for multi-material modeling. The design-dependent nature of the pressure load is modeled using the Darcy law with a volumetric drainage term. Flow coefficient of each element is interpolated using a smoothed Heaviside function. The obtained pressure field is converted to consistent nodal loads. The adjoint-variable approach is employed to determine the sensitivities. A robust formulation is employed, wherein a min-max optimization problem is formulated using the output displacements of the eroded and blueprint designs. Volume constraints are applied to the blueprint design, whereas the strain energy constraint is formulated with respect to the eroded design. The efficacy and success of the approach are demonstrated by designing pneumatically actuated multi-material gripper and contractor mechanisms. A numerical study confirms that multiple-material mechanisms perform relatively better than their single-material counterparts.
Additive Gaussian Process Regression for Metamodeling in High-Dimensional Problems
Authors: Tran Anh , Maupin Kathryn , Mishra Ankush Kumar , Hu Zhen , Hu Chao
Published: November 2023

Gaussian process (GP) regression is an important scientific machine learning (ML) tool that naturally embeds uncertainty quantification (UQ) in a Bayesian context. Thanks to its rigorous mathematical foundation and not-so-many hyperparameters, GP has been one of the most commonly used ML tools for a wide range of engineering applications, including UQ, sensitivity analysis, and design optimization, among others. As same for many similar functional approximation methods, GP also suffers from the curse of dimensionality, where its accuracy degrades exponentially as the number of input dimensions grows given a fixed amount of training data. In this paper, we revisit a variant of GP called the additive GP, which employs high-dimensional model representation to decompose the kernel additively, and benchmark the additive GP over a range of numerical functions, dimensionalities, and the number of training data points. A drawback of the additive GP is that the computational cost is proportional to the dimensionality in constructing the co-variance, due to the number of additive terms considered. Numerical results show that for functions that can be additively decomposed to multiple lower-order functions, additive GP can approximate those functions very well, even at high dimensionality (d > 50).
Application of a Continuous Variable Density Infill: Manipulating Center of Gravity
Authors: Murphy Patrick N. , Khoda Bashir
Published: November 2023

In mechanical design mass properties, such as center of gravity and total mass, are an important consideration. As such the distribution of mass, i.e., the effective density distribution of a part, is a key consideration. When producing parts with additive manufacturing techniques like Fused Deposition Modeling, parts are typically hollowed to reduce manufacture time and replaced with a uniform infill structure. This process will affect the mass properties and provides only adjustment to the total mass. However, manipulating the center of gravity of a part can beneficial as it can change the total mass, moment of inertia, and vibration response of a part. Methods have been proposed in the past like the works of Chiu et. al., Yamanaka et. al., and Grigolato et. al. with each seeking to overcome certain limitations. In this paper, a method is proposed for the manipulation of the center of gravity of an additively manufactured part. The method first creates a density distribution with the desired mass properties then a novel process-aware continuous variable density infill algorithm is utilized to create the infill structure. With this algorithm it is ensured that a manufacturable functionally graded infill structure can be generated. The algorithm proposed for realizing this density distribution achieves this in two steps: variation of extrusion line spacing and width of the standard rectilinear infill pattern. This paper focuses on a 2D case, as implementing variation in the z axis was shown to be trivial. The methodology has been implemented within MATLAB to first generate the density distribution, then apply the continuous variable density infill generation algorithm, and finally generate the g-code. All sample prints were made with an extrusion-based, fused deposition modeling (FDM) printer. A preliminary test showed inconsistent behavior from the variable extrusion width. As such, each test case was printed with and without the variable extrusion width to further evaluate. While relatively high, the total error from input density gradient to print for the samples with only VLS showed very good consistency, both being ∼10%. This is favorable as a consistent error can be corrected for with pre/post processing. The samples with variable extrusion width did improve the results, however the degree of the improvement was not consistent, varying from ∼3% to ∼8%. This behavior was predicted as the range of extrusion width variation is rather limited at ±50%. The feasibility of the proposed method has been demonstrated and could be implemented for 3D arbitrary shapes in future work.
Multi-Degree-of-Freedom Load Distribution Modeling of Cross-Axis Gearing
Authors: Amin Nishank , Talbot David
Published: November 2023

The load distribution model presented here is designed to be used on cross-axis gear pairs. It employs the surface of roll concept of Kolivand and Kahraman, and applies it directly to cross-axis gearing. This application uses novel interpolation techniques in order to correctly implement the approach and applies fully 3-dimensional (12 degree-of-freedom) load distribution which has yet to be attempted in a semi-analytical model. It can accommodate variations in pinion and gear apex, shaft angle and shaft offset. The uniqueness of the model lies in the fact that it is independent of the manufacturing technique. Due to the lower computational time of the model when compared to prevalent FE models, it can be used as design tool to help improve power density, strength, and noise characteristics. Example analyses are shown to demonstrate the ability of the model to accurately predict the load distribution and highlight the sensitivity of cross axis gearing to misalignments.
Introduction of Local Resonators to a Nonlinear Metamaterial With Topological Features
Authors: Malla Arun , LeGrande Joshua , Bukhari Mohammad , Barry Oumar
Published: November 2023

Metamaterials have been shown to benefit from the addition of local resonators, nonlinear elements, or topological properties, gaining features such as additional bandgaps and localized vibration modes. However, there is currently no work in the literature that examines a metamaterial system including all three elements. In this work, we model a 1-dimensional metamaterial lattice as a spring-mass chain with coupled local resonators. Quasiperiodic modulation in the nonlinear connecting springs is utilized to achieve topological features. For comparison, a similar system without local resonators is also modeled. Both analytical and numerical methods are used to study this system. The infinite chain response of the proposed system is solved through the perturbation method of multiple scales. This analytical solution is compared to the finite chain response, estimated using the method of harmonic balance and solved numerically. The resulting band structures and mode shapes are used to study the effects of quasiperiodic parameters and excitation amplitude on the system behavior both with and without the presence of local resonators. Specifically, the impact of local resonators on topological features such as edge modes is established, demonstrating the appearance of a trivial bandgap and multiple localized edge states for both main cells and local resonators.
On How a Self-Organizing System Produces Collective Behavior
Authors: Cao Jinhui , Ming Zhenjun , Allen Janet K. , Mistree Farrokh
Published: November 2023

In this paper we address the following question:

How can the designers of self-organizing systems use the relationships among relevant parameters to quantitatively characterize how a self-organizing system produces the collective behavior process, to better control and design a self-organizing system?

A self-organizing system has advantages in performing dangerous and exploratory tasks that are not suitable for humans. However, it is often difficult for designers to design self-organizing systems, because, in an environment with dynamic complexity, the process of how self-organizing systems behave collectively is unknown. To address this difficulty, we propose a method to quantitatively represent environmental complexity as well as the system behavior, and study the relationship between them so as to gain insights into how a self-organizing system produces collective behavior. In this paper, we identify four collective behavior patterns that a self-organizing system produces when the environment complexity changes, namely, initialing pattern, adjusting behavior, stabilizing pattern, and restarting pattern. We illustrate the efficacy of our method using a box-pushing problem. Our focus is on describing the method rather than the results.
Air Shield Design for Preventing Inhalation on Turbofan-Engines of Passenger-Jets
Authors: Li Yunchen , Wang Jun
Published: November 2023

Due to the recent frequent inhalation accident of turbofan engines on passenger jet planes, this paper designs a type of protection equipment that prevents it. We utilize the high-speed airflow generated by the outer duct of the high bypass ratio turbofan engine to protect the intake port of the large passenger aircraft with high-speed airflow, thereby greatly reducing the damage caused by the inhalation of the bird by the engine. In this paper, we analyze the working conditions when the equipment installs on a high bypass ratio turbofan engine, demonstrate the rationality of the system design, describe the design structure of the scheme in detail, and select the suitable gas source available for this scheme based on the structure diagram of GE-nX-1B74 turbofan engine. According to the parameters of the engine, the length of the GasTube was calculated, and the structure of the equipment was theoretically analyzed. Then, we performed a hydrodynamic analysis of the air and its jet in the pipe system. We use SolidWorks to model the GasTube, fan rotor, low-pressure compressor components, adapter, TubeFlower, high-pressure compressor, turbine block, and the simplified model of the engine nacelle and assemble them. A kinematics simulation was carried out. The 3D model is then subjected to force and airflow trajectory analysis using SolidWorks and Fluent. The 3D model is improved based on the simulation results. To more holistically evaluate the performance, we have simulated the design in the hardest work condition (i.e.. landing) of jet planes. Based on the theoretical and finite element analyses, suggestions for designing the aircraft engine protection equipment are proposed. The revised opinions are proposed and demonstrated in four aspects theoretically.
Design for Additive Manufacturing of Pneumatic Soft Robotics via a Large-Scale, High-Viscosity Vat Photopolymerization Process
Authors: Carbonell Roxana , Song Hongtao , Seepersad Carolyn , Crawford Richard
Published: November 2023

This research describes the design for additive manufacturing (AM) of a pneumatic soft robotic actuator that is uniquely enabled by a novel vat photopolymerization (VPP) AM process. Specifically, the device is a PneuNet style bending mechanism that is designed specifically for a high-viscosity, large-scale VPP AM system. This novel system is capable of fabricating high performance elastomeric materials, such as polydimethylsiloxane (PDMS) loaded with fumed silica nanoparticles or other fillers that result in viscosities too high to be printed with most existing VPP processes. Herein, a tough double network PDMS (DN-PDMS) is designed for printing pneumatic actuators. The mechanical properties of the DN-PDMS, along with the geometric resolution of resulting features, are characterized through experiments, and the results are used to guide the design process of the pneumatic actuator. The results show that the broad design space accessible through the high-viscosity VPP process corresponds with the target geometry identified in this research (determined by maximum bending angle). This design would be challenging or impossible to manufacture using other means; however, this VPP process enables printing of high viscosity materials, large overhangs, internal features, and a fully enclosed hollow structure. Results show that altering the chamber shape and incorporating internal structures leads to a 29.8% improvement in bending angle when compared with the original PneuNet actuator geometry simulated with the same material and pressurization.
An Invariant Representation of Coupler Curves Using a Variational Autoencoder: Application to Path Synthesis of Four-Bar Mechanisms
Authors: Nurizada Anar , Purwar Anurag
Published: November 2023

This paper focuses on the representation and synthesis of coupler curves of planar mechanisms using a deep neural network. While the path synthesis of planar mechanisms is not a new problem, the effective representation of coupler curves in the context of neural networks has not been fully explored. This study compares four commonly used features or representations of four-bar coupler curves: Fourier descriptors, wavelets, point coordinates, and images. The results demonstrate that these diverse representations can be unified using a generative AI framework called Variational Autoencoder (VAE). This study shows that a VAE can provide a standalone representation of a coupler curve, regardless of the input representation, and that the compact latent dimensions of the VAE can be used to describe coupler curves of four-bar linkages. Additionally, a new approach that utilizes a VAE in conjunction with a fully connected neural network to generate dimensional parameters of four-bar linkage mechanisms is proposed. This research presents a novel opportunity for automated conceptual design of mechanisms for robots and machines.
Performance Investigation of Fluid-Lubricated Thrust Bearings With Varying Textured Pad Surfaces Using Computational Fluid Dynamics
Authors: Yildiz Saltuk , Untaroiu Alexandrina
Published: November 2023

It is known that surface texturing provides enhanced mechanical and thermal behavior in the application of journal/thrust bearings and seals. This work presents an examination of parallel sector-pad thrust bearings consisting of twelve pads with textured surfaces in terms of load carrying capacity, friction torque and thermal performance. In this respect, the influence of different texturing patterns on the thrust bearing performance are presented and studied through 3D computational fluid dynamics (CFD) simulations based on the governing equations of incompressible lubricant, and these simulations are conducted in ANSYS-CFX. The previous studies commonly find optimum pattern geometry by keeping each pattern geometry the same such as only square and only elliptical. Unlike existing research studies, the use of varying dimple patterns which are the combinations of commonly used dimple geometries such as circular-elliptical, circular-square, and elliptical-square is investigated to demonstrate the performance of textured pads with varying pattern geometries. The simulation results are verified through experimental data provided in the literature. The CFD simulation results of varying patterned pads are compared with existing ones that are single patterned optimal designs. This study carries out optimal selection of varying dimple patterns that provides an insight for further optimization efforts on surface textured bearing and seals.
Understanding the State of Sanitation in India Through Qualitative Methods and a Septic Tank Sensing Device
Authors: Naik Monisha , Cotera Rivera Pablo , Garad Meghraj , Patil Digvijay P. , Rao Bakul , Bilton Amy M.
Published: November 2023

Worldwide, 3.6 billion people lack access to safely managed sanitation. India bears the brunt of this statistic, with over 395 million citizens lacking access today. Currently, Phase 2 of the Clean India Mission program focuses on connecting septic tanks to treatment facilities. However, according to previous studies, households only empty their septic tanks once they become completely full. A septic tank can only function properly until it is at approximately 70% of its capacity, and it is recommended that tanks should be emptied every 3 to 5 years. The authors hypothesize that a device to detect when a septic tank should be emptied could encourage households to empty their tanks on time. To gain a better understanding of how such a device would fit into the broader sanitation chain and the requirements of this device, a field study encompassing interviews, questionnaires, and septic tank data collection was conducted in three municipalities along the Warna River in Maharashtra, India. The results of the study reveal that the proposed device should only be introduced once a municipality has access to a functional fecal sludge treatment facility. Once a treatment plant has been built, depending on the municipality, different stakeholders need to be engaged in the device’s installation. Finally, the proposed device should detect a septic tank’s hydraulic retention time rather than the number of years since it was last emptied. This device will enable the Indian government to successfully implement Phase 2 of the Clean India Mission by alerting households to empty their tanks.
Design Space Enumerations for Pneumatically Actuated Soft Continuum Manipulators
Authors: Ripperger Evan , Krishnan Girish
Published: November 2023

Pneumatically actuated soft continuum manipulators (SCMs) are constructed by combining several extending or contracting fiber reinforced elastomeric enclosure (FREE) actuators in series, parallel and a combination thereof. While it is well known that architectures with serial combinations of FREEs yield large workspace and dexterity, they suffer from design and control complexity, increased number of valves and inertia. Recent advances in exploring the FREE design space has demonstrated using parallel combinations of dissimilar FREEs (bending and rotating) to improve workspace and dexterity. This paper presents a comprehensive investigation of SCM design architectures by enumerating possibilities of serial and parallel combinations of similar and dissimilar FREEs. A novel dexterity metric is proposed to enable objective comparison of different SCM designs based on shape similarity and end-effector tangent. Given a fixed resource of control inputs (actuator and valve inputs), the paper systematically selects the best architecture of the SCM (serial, parallel, similar or dissimilar FREE) that maximizes dexterity and workspace. It is seen that optimal designs are heavily dependent on the context of the application, which may change how these manipulators are deployed. The paper presents two practical design applications that demonstrate the usefulness of the enumeration framework. While in general, serial design combinations using symmetric bending actuators result in larger workspace and dexterity, some architectures with asymmetric combinations of FREEs may see similar levels of dexterity and workspace.
Empathic Ability Vs. User Satisfaction: Evaluating the Role of Preference Accuracy in Engineering Design
Authors: Johnson Erin , Letting Cynthia , Soria Zurita Nicolás F. , Menold Jessica
Published: November 2023

Prior work has identified the importance of empathy and the effect on design outcomes such as increased quality, originality, and usability. The measurement of empathy in the context of design, however, remains a pervasive issue. While several studies have proposed interventions, tools or methods to enhance designers’ empathy, it remains unclear how managers or designers can practically measure empathic abilities. Many of the existing methods are either incredibly time-consuming and thus not feasible in design practice or are not grounded in design work, making the translation and interpretation of instruments or surveys challenging. To address this gap, we study preference accuracy as a measure of empathic ability, and investigate its relationship with design outcomes, specifically user satisfaction. We review a case study implementing this method; fourteen participants were recruited and randomly paired with a partner. Individuals were tasked with designing a chair to meet their partner’s needs. Each participant interviewed their partner and completed two preference assessments: one detailing their own design preferences, and one detailing their perceptions of their partner’s design preferences. To calculate preference accuracy, the preference assessments for each participant were compared. Results from this study suggest preference accuracy may not be linked with user satisfaction, but may be a useful tool to differentiate empathic abilities across a population of designers.
Design Interviews Conducted by Intra- and Intercultural Teams: A Case Study on Dialysis in Zimbabwe
Authors: Grover Micki , Lauff Carlye A. , Ndhlovu Chiratidzo , Wright Natasha C.
Published: November 2023

In global development engineering, semi-structured, direct-dialogue interviews are often recommended in order to generate a deep understanding of stakeholders’ needs and to create products that meet those needs. In this study, interviews were used to explore the existing dialysis treatment program for end-stage kidney disease in Zimbabwe. This study has two aims: (i) to understand the dialysis service model and limits to its expansion, and (ii) to examine the impact of the cultural background of the interviewing team on interview outcomes.

Virtual training on exploratory interviewing was developed and administered to 12 undergraduate students living in the United States, Uganda, and Zimbabwe. Six teams, each having either an intercultural or intracultural composition conducted field interviews (n = 18) with Zimbabwean dialysis professionals to better understand the existing service model associated with hemodialysis (HD) and peritoneal dialysis (PD) treatment modalities. Interviews were coded in NVivo to develop an overall service model map including relevant people, props, and processes. Key limitations to expanding PD programs include: lack of clean water sources, no in-country dialysate production, insufficient financial resources, limited nursing staff, and difficulty in tracking medical information during home-based treatment, among others.

The service model map was additionally used to quantify the number of codes uncovered in individual interviews. Intercultural pairs produced a higher proportion of top scoring interviews than did the intracultural pairs. The small sample size, however, results in only an early indication of potentially replicable findings. The work represents a potential methodology for further research in this space.
A Customizable and Responsive Mechanism for a Chair to Assist During All Phases of Stand-To-Sit and Sit-To-Stand Maneuvers
Authors: Jhunjhunwala Sanchit , Kumar R Manoj , K. L. Chandrashekhara , Patil Sanjay , J. Kiran , Shaikh Ahmad , Ananthasuresh G. K.
Published: November 2023

Most of the assistive chairs do not provide support during the body-extension and stabilization phases of sit-to-stand maneuver because they only pivot about a horizontal axis. And there is limited scope for customization to individual’s needs. To address this, we present a mechanism that combines a compliant hinge mechanism with a linkage that includes a gas-spring. The compliant hinge mechanism uses open-circular cross-section shells that bend and twist to provide customized torque-angle characteristics with negative stiffness and bistability features. By adding a linkage with a gas-spring, the mechanism in this work is designed such that it provides the necessary support right from the intent to rise until the last phase of stabilizing in the standing position. Similar full support is provided for the stand-to-sit maneuver. Furthermore, the mechanism is responsive entirely by virtue of the compliant hinge mechanism and the gas-spring, and without using any sensors or external actuation. This completely mechanical device with two degrees of freedom allows the users to control the trajectory of the hip joint to their comfort and ability. Additionally, the envelope of trajectories of the seat that slides vertically and rotates about a horizontal axis can be mass-customized to ergonomic parameters of the population. We present the concept, customization features, kinetoelastic analysis, prototyping, and preliminary testing. We illustrate the efficacy of the mechanism through EMG data.
The Impact of Additive Manufacturing Constraints and Design Objectives on Structural Topology Optimization
Authors: Dangal Babin , Jung Sangjin
Published: November 2023

To analyze the impact of different objective functions and additive manufacturing (AM) constraints on structural topology optimization, it is necessary to perform an in-depth comparative study. This analysis should consider specific structural design factors, such as compliance, volume, or stress minimization, and assess their effects on the topology optimization for AM. In addition, the inclusion of AM constraints can have a significant influence on various aspects, including optimal part geometry, part volume, support structure volume, and structural performance. Thus, it is essential to examine and compare these factors to determine the optimal part design for AM. This study focuses on comparing topology optimization results obtained using compliance, stress, or multi-objective minimization, with and without AM constraints. The comparative analysis is conducted in the study, utilizing three structural design examples: cantilever beam, bridge-shaped structure, and L-shaped beam. The comparison results provide insights into the effects of build orientation, AM constraints such as overhang, and different design objectives on the structural topology optimization for AM.
Lifting Task Stability Evaluation Based on Balanced State Basins of a Humanoid Robot
Authors: Song Hyunjong , Peng William Z. , Kim Joo H.
Published: November 2023

Stability evaluation is a vital aspect of successful balance control and design for humanoid robots. While balance stability has been extensively explored for push recovery during legged locomotion tasks in response to perturbations, less effort has been devoted toward developing a similar understanding for lifting tasks. Lifting involves unique interactions between the robot and lifted object, whose mass can significantly alter the mass distribution of the loaded robot and the upper extremities, which are typically ignored in legged robot balance. In this study, the balance stability of a humanoid robot during a lifting task is evaluated with a partition-based approach in the augmented center-of-mass-state space. The balanced state boundary is computed through an optimization-based method that incorporates the loaded robot’s whole-body system properties, such as kinematic and actuation limits, with full-order nonlinear system dynamics in the sagittal plane subject to foot-ground contact interactions and lifting task requirements. The boundaries are constructed for different combinations of object masses and lifting trajectories obtained with a zero-moment point constraint-based pattern generator. Trends in the boundaries and comparisons among them are used to identify the effect of different loading conditions and task parameters on balance stability due to kinematic and actuation limits, linear and angular momenta regulation, and mass distribution.
Multiphysics-Informed Machine Learning for Battery Design and Health Monitoring
Authors: Bansal Parth , Li Yumeng
Published: November 2023

Current Lithium-ion battery (LIBs) designs are nearing the end of their performance capabilities. As the application and demand on these LIBs are growing continuously, there is also a need for continuous innovation both in the area of battery design and the area of battery state of health (SoH) monitoring. Using a silicon (Si) anode instead of a traditionally used graphite electrode allows an increase in the performance of existing LIBs. However, this increased performance comes at the cost of large stresses that develop in the anode as a result of large volumetric changes due to the unique alloying mechanism of the Lithium (Li) into the Si during the battery cycling. These volumetric stresses cause the development of cracks within the Si anode and delamination of the anode from the substrate, which leads to the capacity loss in the battery along with the growth of solid-electrolyte interface (SEI) on the exposed surfaces of the anode. In this study, we develop a physics-informed machine learning (PIML) model to monitor the SoH of the battery based on the output of these coupled failure modes of Si. 3D finite element (FE) models are built to explore how the large volumetric changes cause cracking and delamination in Si and how the SEI growth on the resultant exposed interfaces leads to the degradation of the battery. The outputs of these FE simulations will finally be used to train multiple Gaussian process regression (GPR) models, which combine together to estimate the SoH of the battery under the interactive effects of the studied failure modes. From the results of the study, it is evident that the developed PIML model which uses the output of LIB FE models, which include coupled failure modes, can be used to efficiently (using only 11.4% of charging time) estimate the SoH of the battery with reasonable accuracy (3.04% error).