bluuebunny/crossref_metadata_2025_split huggingface dataset:
SEA-Leg: A Wheel-Leg Hybrid Locomotion Platform for Uncontrolled Environments Using Series Elastic Actuators
Authors: Swerczek Nick , Nelson Carl A. , Cerny John , Tannehill Amber 
Published: November 2023

Abstract
In this paper, we present the SEA-Leg robotic mobility platform: a wheel-leg hybrid locomotion system which uses a 2 degree-of-freedom linkage driven by two series-elastic actuators to create a passive suspension system featuring the reconfigurability that makes legged systems advantageous. A method for simplifying the wheel-leg’s nonlinear dynamics to a model analogous to the traditional suspension system model is presented along with methods for its validation. A mechanical design which meets constraints outlined for SEA-Leg’s intended application as a platform for off-world exploration is presented, and a prototype was constructed. Initial testing of the SEA-Leg’s performance confirms its ability to meet the constraints laid out in this paper and implies validation of the lumped-stiffness approximation model.
Design Process for Dimensioning Elastomer Bearings for Winch Based Point Absorbers
Authors: Andersson Kjell , Duraisamy Rimmie 
Published: November 2023

Abstract
Wave energy is a huge power source that can make a significant contribution to the production of renewable energy in the future. It can generate as much as 10% of the world’s present energy consumption [1].
However, Wave Energy Converters (WECs) is a relatively new field, which requires new technology development, and testing before efficient WECs can give any significant contribution to the energy production. The main difficulties lie in the harsh marine environment and the fact that wave power is delivered with high forces and low speeds. The high forces necessitates strong and durable mechanical structures and the slow speed makes efficient energy conversion challenging. Further, there is a very large variation in wave height over time, and during storms, the largest waves can be 10–25 times higher than the average wave height at the site. The maximum forces and motions can thereby be tremendous if not handled properly, and makes the development of efficient Wave Energy Converters (WEC) challenging. The dimensioning forces strongly depend on the wave power concept, the WEC implementation and the actual Power Take-Off (PTO) system. Of the many different types of WECs being researched and developed, this paper focuses on the development of a winch based point absorber wave energy converters (WBPA-WECs).
This paper presents the development of a solution for a flexible chain where an elastomeric bearing is used as a means to achieve the relative motion between the links in a chain. With this solution no sliding is present and the motion is achieved as a deformation in the elastomeric bearing.
A design process is formulated for determining a suitable configuration of layers of steel shims and elastomers. A test rig for bearing tests has been developed and results from these experimental tests in combination with material tests and FE analysis are presented in the paper. These are presented in the context of illustrating the proposed design process for designing these type of laminated elastomer bearings.
The different steps in this design process have been illustrated for the defined test bearing and we can conclude that our findings indicate that the proposed process can be an important support method for further development of this approach with elastomer bearings.
DC Motor Velocity Control With Integral Retarded Controller Under Unintentional Delay
Authors: Fan Haonan , Ramírez Adrián , Mondié Sabine , Sipahi Rifat 
Published: November 2023

Abstract
PID controllers are an industry standard. These controllers are not only effective in many applications, but also intuitive for practitioners to utilize them under a variety of conditions. However, balancing multiple control objectives is still not a trivial task, especially one has to deal with noisy measurements and a relatively high bandwidth of operation is expected from the closed-loop system. An alternative to PIDs has been recently revisited with promising, analytical tuning formula and capabilities to effectively control plants with noisy measurement even without low-pass filters. These controllers are called delay-based controllers whereby an intentional delay is introduced into the controller to improve speed of response, reduce noise, and even improve set point regulation. One such controller is the focus of this manuscript, namely, an Integral Retarded (IR) controller. This controller utilizes an intentional delay to reduce actuator chattering against noisy measurements, while its integral part achieves zero steady-state error for set-point regulation of Type-0 open loop systems. This controller can be tuned analytically to achieve, at the same time, rightmost root placement to render certain speed of response in closed loop. However, measurements can be unintentionally delayed in many applications. IR framework for such cases has not been studied in the literature. Here, we provide new tuning rules for such cases, as well as validations through simulations and a DC motor speed control hardware experiment.
A Framework Establishing the Bounds of Small Angle Assumptions in Multi-Material Additively Manufactured Compliant Mechanisms
Authors: Thomas Evelyn , Meisel Nicholas , Butler Jared 
Published: November 2023

Abstract
Additively-manufactured multi-material compliant mechanisms are an emergent class of mechanisms; these mechanisms have a higher reliance on material properties to drive deflection when compared to other compliant mechanisms. As a result, material-specific properties such as Young’s modulus, strain response, and Poisson’s ratio must be analyzed to properly predict the performance of multi-material additively manufactured compliant mechanisms. This paper creates a framework for additive manufacturing users to characterize acceptable force-deflection relationship predictors using strain data associated with a generalized multi-material cantilever beam. This allows designers to have more confidence in the performance of their designs prior to production. When applied, the framework allows the user to identify the applied deflections where Hooke’s Law and small angle assumptions are, or are not, appropriate. This process will be useful for multi-material additive manufacturing processes capable of producing multi-material prints: directed energy deposition (metals) and material extrusion (thermoplastics). This process will serve as the basis for encouraging the widespread adoption of additively manufactured multi-material compliant mechanisms.
Computational Modal Analysis of Half Scale Business Jet Fuselage Tail Section
Authors: Gunawardana Rochana , Mechefske Christopher K. 
Published: November 2023

Abstract
Acoustic noise caused by structural vibrations directly affect the comfort of passengers on aircrafts throughout the duration of their flight., The dynamic characteristics of a system that dictate the behavior of such vibrations is critical to the improvement of flight conditions. Modal analysis is the practice of determining these dynamic characteristics of a structure under loading [1]. A computational modal analysis was conducted in this study with the objective of validating the previous experimental modal analysis, and providing a reliable model that can predict accurate frequency responses based on future modifications to the structure. This paper focuses on the development, validation and preliminary comparisons of the computational modal analysis. The mode shapes and natural frequencies were analyzed and validated for connectivity. The Frequency response curves for all measured points showed repeatability for the tests. Modal Assurance Criterion was measured against the data that demonstrated good similarity in mode shapes. A preliminary comparison was done between the experimental and computational data that compared differences between natural frequencies in correlated mode pairs, which were minimal. It was found that the model is underdamped in comparison to the experimental model. The next stage of this work is determined to be iteratively finding these damping values, then doing a comparison with the experimental data using a pseudo orthogonality check.
Gaussian Process Regression for Sim-to-Real Transfer of Hopping Gaits
Authors: Krause Jeremy , Alaeddini Adel , Bhounsule Pranav A. 
Published: November 2023

Abstract
Simulation-based controllers are relatively easy to build and evaluate, but rarely transfer seamlessly to hardware. This is because of the reality-gap which is the discrepancy between simulations and hardware. Narrowing the reality-gap can speed up the deployment of simulated controllers to hardware, also known as sim-to-real. This paper presents sim-to-real transfer of controllers on a single leg hopping robot, a system that cycles between under-actuation during the stance phase to no-actuation during flight phase. Using simulations, we design a controller to achieve speed and height regulation once-per-step, but the controller cannot achieve accurate control on hardware. Using data from hardware, we model the mis-match between simulation and hardware using Gaussian Process Regression (GPR), recompute the controller, and redeploy it in hardware. It takes about 4 iterations to achieve accurate tracking. The results show that when GPR is used to model the step-to-step level model inaccuracy, it can lead to high accuracy sim-to-real transfer while maintaining sample efficiency. A video is here: tiny.cc/idetc2023
AI-Accelerated Design of Evidence Synthesis for Global Development
Authors: Edwards Kristen M. , Song Binyang , Porciello Jaron , Engelbert Mark , Huang Carolyn , Ahmed Faez 
Published: November 2023

Abstract
When designing evidence-based policies and programs, decision-makers must distill key information from a vast and rapidly growing literature base. Identifying relevant literature from raw search results is time and resource intensive, and is often done by manual screening. In this study, we develop an AI agent based on a bidirectional encoder representations from transformers (BERT) model and incorporate it into a human team designing an evidence synthesis product for global development. We explore the effectiveness of the human-AI hybrid team in accelerating the evidence synthesis process. To further improve team efficiency, we enhance the human-AI hybrid team through active learning (AL). Specifically, we explore different sampling strategies, including random sampling, least confidence (LC) sampling, and highest priority (HP) sampling, to study their influence on the collaborative screening process. Results show that incorporating the BERT-based AI agent into the human team can reduce the human screening effort by 68.5% compared to the case of no AI assistance and by 16.8% compared to the industry standard of using an n-gram language model to encode texts and a support vector machine (SVM)-based classifier for identifying 80% of all relevant documents. When we apply the HP sampling strategy for AL, the human screening effort can be reduced even more to 78.3% for identifying 80% of all relevant documents compared to no AI assistance. We apply the AL-enhanced human-AI hybrid teaming workflow in the design process of three evidence gap maps (EGMs) for USAID and find it to be highly effective. These findings demonstrate how AI can accelerate the development of evidence synthesis products and promote timely evidence-based decision making in global development in a human-AI hybrid teaming context.
Physics-Informed Multi-Output Surrogate Modeling of Fusion Simulations
Authors: Maupin Kathryn A. , Tran Anh , Lewis William E. , Glinsky Michael E. 
Published: November 2023

Abstract
Computational simulation allows scientists to explore, observe, and test physical regimes thought to be unattainable. Validation and uncertainty quantification play crucial roles in extrapolating the use of physics-based models. Bayesian analysis provides a natural framework for incorporating the uncertainties that undeniably exist in computational modeling. However, the ability to perform quality Bayesian and uncertainty analyses is often limited by the computational expense of first-principles physics models. In the absence of a reliable low-fidelity physics model, phenomenological surrogate or machine learned models can be used to mitigate this expense; however, these data-driven models may not adhere to known physics or properties. Furthermore, the interactions of complex physics in high-fidelity codes lead to dependencies between quantities of interest (QoIs) that are difficult to quantify and capture when individual surrogates are used for each observable. Although this is not always problematic, predicting multiple QoIs with a single surrogate preserves valuable insights regarding the correlated behavior of the target observables and maximizes the information gained from available data. A method of constructing a Gaussian Process (GP) that emulates multiple QoIs simultaneously is presented. As an exemplar, we consider Magnetized Liner Inertial Fusion, a fusion concept that relies on the direct compression of magnetized, laser-heated fuel by a metal liner to achieve thermonuclear ignition. Magneto-hydrodynamics (MHD) codes calculate diagnostics to infer the state of the fuel during experiments, which cannot be measured directly. The calibration of these diagnostic metrics is complicated by sparse experimental data and the expense of high-fidelity neutron transport models. The development of an appropriate surrogate raises long-standing issues in modeling and simulation, including calibration, validation, and uncertainty quantification. The performance of the proposed multi-output GP surrogate model, which preserves correlations between QoIs, is compared to the standard single-output GP for a 1D realization of the MagLIF experiment.
An LSTM-Driven Simulation Approach for SOC and SOH Estimation of a Lithium-Ion Cell
Authors: Dhanagare Tejas , Singh Shikha , Pandey Vijitashwa 
Published: November 2023

Abstract
Electric vehicles are poised to replace diesel and gasoline-based vehicles all over the developed world. The benefits are many, from reducing greenhouse gas emissions to reducing overall design complexity leading to lower repair costs. One central area of investigation in this regard is battery design and efficient operation. Estimating the battery’s health is essential in successfully adapting electric vehicles. Two critical parameters of interest in the battery management system are the state of charge (SOC) and a cell’s state of health (SOH). The state of charge depicts the battery capacity percentage. It informs the end user about the remaining performance in the current cycle. The state of health suggests the battery’s remaining life before it must be replaced. In this paper, a third-order resistor-capacitor equivalent circuit model is used to model a Lithium-ion battery’s dynamic behavior. This circuit model has been shown to accurately describe the behavior of the lithium-ion battery, with high concordance between simulation results and reality. The parameters of the model are estimated using an extended Kalman filter. Subsequently, utilizing the simulation thus created, a method is introduced to perform the estimation of state of charge and state of health using a recurrent neural network model with long short-term memory architecture. The paper then presents comparison results and identifies avenues for future work.
Generative Design of Statistically Self-Similar Mechanical Structures
Authors: Hill Noah , Ebert Matthew , Maurice Mena , Krishnamurthy Vinayak 
Published: November 2023

Abstract
We present a novel methodology to generate mechanical structures based on the idea of fractal geometry as described by the chaos game. Chaos game is an iterative method that generates self-similar point-sets in the limiting case within a polygonal domain. By computing Voronoi tessellations on these point-sets, our method generates mechanical structures that adopts the self-similarity of the point-sets resulting in fractal distribution of local stiffness. The motivation behind our approach comes from the observation that a typical generative structural design workflow requires the ability to generate families of structures that possess shared behavioral (e.g. thermal, mechanical, etc.) characteristics making each structure distinct but feasible. However, the generation of the alternatives, almost always, requires solving an inverse structural problem which is both conceptually and computationally challenging. The objective of our work is to develop and investigate a forward-design methodology for generating families of structures that, while not identical, exhibit similar mechanical behavior in a statistical sense. To this end, the central hypothesis of our work is that structures generated using the chaos game can generate families of self-similar structures that, while not identical, exhibit similar mechanical behavior in a statistical sense. Furthermore, each family is uniquely identifiable from the parameters of the chaos game, namely, the polygonal domain, fractional distance, and number of samples. We present a systematic study of these self-similar structures through modal analysis and demonstrate a preliminary confirmation of our hypothesis.
The Design of a Low-Cost Voluntary Closing Finger Prosthetic for Developing Countries
Authors: Loutan Kelvin , Persad Umesh 
Published: November 2023

Abstract
Democratization of prosthetic devices has been made possible by the availability of desktop 3D printers. Low-cost body-powered open-sourced prosthetic devices are a first choice for many patients with upper limb amputations. However, the design of these devices often stems from a ‘one shape fits all’ archetype and therefore user acceptance varies. Little or no consideration is given to kinematics, size, weight or aesthetics. Novel devices reported in the literature rely on mathematical optimization of kinematic parameters to achieve human-like finger trajectories and forces. However, these devices are not open-source and lack user testing and feedback. This paper presents the design process for a new open-source low-cost 3D printed prosthetic finger, customized for an individual amputee. Parametric optimization was used to determine key dimensional parameters for simultaneous actuation of the prosthetic medial and distal phalanges. The amputee user participated in the conceptualization and testing phases of the design process. Two design iterations are presented with user feedback on fit, comfort and functionality to validate the design. The most recent iteration included three user adjustments for fine-tuning the degree of actuation. This iteration permitted desirable actuation and grasping. Future iterations should be able to facilitate diametral changes to the user’s finger due to swelling and ageing.
A Categorical Approach to Define Makerspaces
Authors: Kumar Pavan , Summers Joshua D. 
Published: November 2023

Abstract
This paper presents an approach to identify potential categories and benchmark makerspaces based on their narrative or illustrative definitions, intent, operational aspects captured over time and their asserted impact as per existing literature. The identified categories are further mapped and classified based on an established culture-based framework. This categorization is defined at three levels. The first two levels capture and provide the macro information that is orthogonal to each other. The third level leaf node details (presented in the appendix) are codified based on a cultural framework but are excluded from the analysis presented here. However, the leaf node is an essential listing of the various terms used in the domain of makerspaces as identified in the literature and it is observed that these terms are generally used by the various stakeholders to define their makerspaces. The discussions provide context for the first two levels and its validity through the application of DSM (Design Structure Matrix) techniques to prove its orthogonality. Effective categorization of makerspaces will support the following: (1) accurate and consistent descriptions of makerspaces, (2) clear mapping and association of the values of the makerspaces to their individual characteristics, and (3) provide a framework to design makerspaces for specific uses. The literature reviewed also provides a basis for another categorization to be developed in parallel using the factors or characteristics that define the value proposition of makerspaces. Finally, this paper presents examples of using the categorization on a sample list of makerspaces based on direct observations and literature surveys. This work aims to guide efforts towards building a framework to design makerspaces.
Dealing With Loss: How Do Designers’ Resilience and Perceptions of Scarcity Affect Perceptions of Design Performance?
Authors: Sibley Grace , Letting Cynthia , Menold Jessica 
Published: November 2023

Abstract
Resources are an essential aspect of individual problem solving and their availability is critical for success. Resource scarcity is common in many industries and can affect the resources available to prototype, design creatively, and work freely. We argue that designers face scarcity and short timelines on engineering teams, and it is uncertain how these constraints may affect design outcomes and strategies. We also argue that designers must be resilient to overcome challenges faced during problem-solving. In this work, we study the interactions between resilience and perceived resource scarcity and how they affect perceptions of design performance. A controlled study was conducted to understand the linkages between resource scarcity, resilience, and scarcity mindset. We found that a perceived general scarcity of time in day-to-day life significantly predicted perceptions of design performance. Further, we found that participants with higher resilience scores were less likely to have their design idea affected by the induced resource scarcity. Our work builds foundational knowledge regarding the interactions between individual resilience, general perceptions of scarcity, and resource constraints in the context of engineering design. Further work may require more longitudinal-based studies to better understand resilience and resource scarcity over longer periods of time.
Complex Terramechanics for Mobility Assessment Part 2: Efficiency Through a Simple Terramechanics Representation
Authors: Little Joseph , Coker Chris , Thornton Ben , Pesheck Eric , Jayakumar Paramsothy 
Published: November 2023

Abstract
The trade-off between computational efficiency and accuracy of various terramechanics simulation methods is a challenge that many engineers face when conducting analysis of off-road vehicle mobility. The Discrete Element Method (DEM) can capture complex phenomena within the soil, but requires substantial time and computing resources in comparison to the lower fidelity simple terramechanics methods such as the Bekker-Wong model. In this study, we propose a novel approach that seeks to strike a balance between efficiency and fidelity in simulating tire tractive capability in soft-soils. Our approach leverages DEM to determine Bekker-Wong parameters which encapsulate the bulk response of the DEM model and can predict accurate overall tractive performance. The process involves using DEM to generate soft-soil tire performance curves and using an optimization framework to determine simple terramechanics parameters, such as Bekker-Wong parameters, that best fit the DEM response. These parameters can then be used in other simulations for quantifying vehicle performance on soft-soil without the need for cumbersome DEM simulations. The results of the study demonstrate that the approach is promising with further refinement. Future work should focus on starting with more accurate DEM soil properties and scaling the method up to the full-vehicle level. If successful this work could ultimately provide a model with good predictive capability, while still allowing fast simulation times for agile design iteration and high run-count analyses.