Scholarly Works, Mechanical Engineering

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Research articles, presentations, and other scholarship

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Guest editorial: Special Issue on Artificial Intelligence and Emerging Computational Approaches for Tribology
Zhang, Zhinan; Pan, Shuaihang; Raeymaekers, Bart (2024-04-02)
SARI: Shared Autonomy across Repeated Interaction
Jonnavittula, Ananth; Mehta, Shaunak; Losey, Dylan (ACM, 2024)
Assistive robot arms try to help their users perform everyday tasks. One way robots can provide this assistance is shared autonomy. Within shared autonomy, both the human and robot maintain control over the robot’s motion: as the robot becomes conident it understands what the human wants, it intervenes to automate the task. But how does the robot know these tasks in the irst place? State-of-the-art approaches to shared autonomy often rely on prior knowledge. For instance, the robot may need to know the human’s potential goals beforehand. During long-term interaction these methods will inevitably break down Ð sooner or later the human will attempt to perform a task that the robot does not expect. Accordingly, in this paper we formulate an alternate approach to shared autonomy that learns assistance from scratch. Our insight is that operators repeat important tasks on a daily basis (e.g., opening the fridge, making cofee). Instead of relying on prior knowledge, we therefore take advantage of these repeated interactions to learn assistive policies. We introduce SARI, an algorithm that recognizes the human’s task, replicates similar demonstrations, and returns control when unsure. We then combine learning with control to demonstrate that the error of our approach is uniformly ultimately bounded. We perform simulations to support this error bound, compare our approach to imitation learning baselines, and explore its capacity to assist for an increasing number of tasks. Finally, we conduct three user studies with industry-standard methods and shared autonomy baselines, including a pilot test with a disabled user. Our results indicate that learning shared autonomy across repeated interactions matches existing approaches for known tasks and outperforms baselines on new tasks. See videos of our user studies here: https://youtu.be/3vE4omSvLvc
Additive Manufacturing of Poly(phenylene Sulfide) Aerogels via Simultaneous Material Extrusion and Thermally Induced Phase Separation
Godshall, Garrett F.; Rau, Daniel A.; Williams, Christopher B.; Moore, Robert B. (Wiley-VCH GmbH, 2023-11)
Additive manufacturing (AM) of aerogels increases the achievable geometric complexity, and affords fabrication of hierarchically porous structures. In this work, a custom heated material extrusion (MEX) device prints aerogels of poly(phenylene sulfide) (PPS), an engineering thermoplastic, via in situ thermally induced phase separation (TIPS). First, pre-prepared solid gel inks are dissolved at high temperatures in the heated extruder barrel to form a homogeneous polymer solution. Solutions are then extruded onto a room-temperature substrate, where printed roads maintain their bead shape and rapidly solidify via TIPS, thus enabling layer-wise MEX AM. Printed gels are converted to aerogels via postprocessing solvent exchange and freeze-drying. This work explores the effect of ink composition on printed aerogel morphology and thermomechanical properties. Scanning electron microscopy micrographs reveal complex hierarchical microstructures that are compositionally dependent. Printed aerogels demonstrate tailorable porosities (50.0–74.8%) and densities (0.345–0.684 g cm⁻³), which align well with cast aerogel analogs. Differential scanning calorimetry thermograms indicate printed aerogels are highly crystalline (≈43%), suggesting that printing does not inhibit the solidification process occurring during TIPS (polymer crystallization). Uniaxial compression testing reveals that compositionally dependent microstructure governs aerogel mechanical behavior, with compressive moduli ranging from 33.0 to 106.5 MPa.
Enhancing Autonomous Vehicle Navigation with a Clothoid-Based Lateral Controller
Shaju, Aashish; Southward, Steve; Ahmadian, Mehdi (MDPI, 2024-02-22)
This study introduces an advanced lateral control strategy for autonomous vehicles using a clothoid-based approach integrated with an adaptive lookahead mechanism. The primary focus is on enhancing lateral stability and path-tracking accuracy through the application of Euler spirals for smooth curvature transitions, thereby reducing passenger discomfort and the risk of vehicle rollover. An innovative aspect of our work is the adaptive adjustment of lookahead distance based on real-time vehicle dynamics and road geometry, which ensures optimal path following under varying conditions. A quasi-feedback control algorithm constructs optimal clothoids at each time step, generating the appropriate steering input. A lead filter compensates for the vehicle’s lateral dynamics lag, improving control responsiveness and stability. The effectiveness of the proposed controller is validated through a comprehensive co-simulation using TruckSim^® and Simulink^®, demonstrating significant improvements in lateral control performance across diverse driving scenarios. Future directions include scaling the controller for higher-speed applications and further optimization to minimize off-track errors, particularly for articulated vehicles.
Predicting Ion Sequestration in Charged Polymers with the Steepest-Entropy-Ascent Quantum Thermodynamic Framework
McDonald, Jared; von Spakovsky, Michael R.; Reynolds, William T. (MDPI, 2024-03-01)
The steepest-entropy-ascent quantum thermodynamic framework is used to investigate the effectiveness of multi-chain polyethyleneimine-methylenephosphonic acid in sequestering rare-earth ions (Eu³⁺) from aqueous solutions. The framework applies a thermodynamic equation of motion to a discrete energy eigenstructure to model the binding kinetics of europium ions to reactive sites of the polymer chains. The energy eigenstructure is generated using a non-Markovian Monte Carlo model that estimates energy level degeneracies. The equation of motion is used to determine the occupation probability of each energy level, describing the unique path through thermodynamic state space by which the polymer system sequesters rare-earth ions from solution. A second Monte Carlo simulation is conducted to relate the kinetic path in state space to physical descriptors associated with the polymer, including the radius of gyration, tortuosity, and Eu-neighbor distribution functions. These descriptors are used to visualize the evolution of the polymer during the sequestration process. The fraction of sequestered Eu³⁺ ions depends upon the total energy of the system, with lower energy resulting in greater sequestration. The kinetics of the overall sequestration are dependent on the steepest-entropy-ascent principle used by the equation of motion to generate a unique kinetic path from an initial non-equilibrium state.
Dual-Use Strain Sensors for Acoustic Emission and Quasi-Static Bending Measurements
Stiefvater, Jason; Kang, Yuhong; de Clerck, Albrey; Mao, Shuo; Jones, Noah; Deem, Josh; Wicks, Alfred; Ruan, Hang; Ng, Wing (MDPI, 2024-03-02)
In this paper, a MEMS piezoresistive ultrathin silicon membrane-based strain sensor is presented. The sensor’s ability to capture an acoustic emission signal is demonstrated using a Hsu–Nielsen source, and shows comparable frequency content to a commercial piezoceramic ultrasonic transducer. To the authors’ knowledge, this makes the developed sensor the first known piezoresistive strain sensor which is capable of recording low-energy acoustic emissions. The improvements to the nondestructive evaluation and structural health monitoring arise from the sensor’s low minimum detectable strain and wide-frequency bandwidth, which are generated from the improved fabrication process that permits crystalline semiconductor membranes and advanced polymers to be co-processed, thus enabling a dual-use application of both acoustic emission and static strain sensing. The sensor’s ability to document quasi-static bending is also demonstrated and compared with an ultrasonic transducer, which provides no significant response. This dual-use application is proposed to effectively combine the uses of both strain and ultrasonic transducer sensor types within one sensor, making it a novel and useful method for nondestructive evaluations. The potential benefits include an enhanced sensitivity, a reduced sensor size, a lower cost, and a reduced instrumentation complexity.
Molecular modeling of Poly(methyl methacrylate-block-acrylonitrile) as Precursors of Porous Carbon Fibers
Hao, Xi; Serrano, Joel; Liu, Guoliang; Cheng, Shengfeng (2023-04-22)
MEMTRACK: A Deep Learning-Based Approach to Microrobot Tracking in Dense and Low-Contrast Environments.
Sawhney, Medha; Karmarkar, Bhas; Leaman, Eric J.; Daw, Arka; Karpatne, Anuj; Behkam, Bahareh (2023)
Tracking microrobots is challenging, considering their minute size and high speed. As the field progresses towards developing microrobots for biomedical applications and conducting mechanistic studies in physiologically relevant media (e.g., collagen), this challenge is exacerbated by the dense surrounding environments with feature size and shape comparable to microrobots. Herein, we report Motion Enhanced Multi-level Tracker (MEMTrack), a robust pipeline for detecting and tracking microrobots using synthetic motion features, deep learning-based object detection, and a modified Simple Online and Real-time Tracking (SORT) algorithm with interpolation for tracking. Our object detection approach combines different models based on the object’s motion pattern. We trained and validated our model using bacterial micro-motors in collagen (tissue phantom) and tested it in collagen and aqueous media. We demonstrate that MEMTrack accurately tracks even the most challenging bacteria missed by skilled human annotators, achieving precision and recall of 77% and 48% in collagen and 94% and 35% in liquid media, respectively. Moreover, we show that MEMTrack can quantify average bacteria speed with no statistically significant difference from the laboriously-produced manual tracking data. MEMTrack represents a significant contribution to microrobot localization and tracking, and opens the potential for vision-based deep learning approaches to microrobot control in dense and low-contrast settings. All source code for training and testing MEMTrack and reproducing the results of the paper have been made publicly available https://github.com/sawhney-medha/MEMTrack.
Inducing stratification of colloidal mixtures with a mixed binary solvent
Liu, Binghan; Grest, Gary S.; Cheng, Shengfeng (Royal Society of Chemistry, 2023-12-06)
Molecular dynamics simulations are used to demonstrate that a binary solvent can be used to stratify colloidal mixtures when the suspension is rapidly dried. The solvent consists of two components, one more volatile than the other. When evaporated at high rates, the more volatile component becomes depleted near the evaporation front and develops a negative concentration gradient from the bulk of the mixture to the liquid-vapor interface while the less volatile solvent is enriched in the same region and exhibit a positive concentration gradient. Such gradients can be used to drive a binary mixture of colloidal particles to stratify if one is preferentially attracted to the more volatile solvent and the other to the less volatile solvent. During solvent evaporation, the fraction of colloidal particles preferentially attracted to the less volatile solvent is enhanced at the evaporation front, whereas the colloidal particles having stronger attractions with the more volatile solvent are driven away from the interfacial region. As a result, the colloidal particles show a stratified distribution after drying, even if the two colloids have the same size.
Detection of passageways in natural foliage using biomimetic sonar
Wang, Ruihao; Liu, Yimeng; Müller, Rolf (IOP, 2022-08-10)
The ability of certain bat species to navigate in dense vegetation based on trains of short biosonar echoes could provide for an alternative parsimonious approach to obtaining the sensory information that is needed to achieve autonomy in complex natural environments. Although bat biosonar has much lower data rates and spatial (angular) resolution than commonly used human-made sensing systems such as LiDAR or stereo cameras, bat species that live in dense habitats have the ability to reliably detect narrow passageways in foliage. To study the sensory information that the animals may have available to accomplish this, we have used a biomimetic sonar system that was combined with a camera to record echoes and synchronized images from 10 different field sites that featured narrow passageways in foliage. The synchronized camera and sonar data allowed us to create a large data set (130 000 samples) of labeled echoes using a teacher-student approach that used class labels derived from the images to provide training data for echo-based classifiers. The performance achieved in detecting passageways based on the field data closely matched previous results obtained for gaps in an artificial foliage setup in the laboratory. With a deep feature extraction neural network (VGG16) a foliage-versus-passageway classification accuracy of 96.64% was obtained. A transparent artificial intelligence approach (class-activation mapping) indicated that the classifier network relied heavily on the initial rising flank of the echoes. This finding could be exploited with a neuromorphic echo representation that consisted of times where the echo envelope crossed a certain amplitude threshold in a given frequency channel. Whereas a single amplitude threshold was sufficient for this in the previous laboratory study, multiple thresholds were needed to achieve an accuracy of 92.23%. These findings indicate that despite many sources of variability that shape clutter echoes from natural environments, these signals contain sufficient sensory information to enable the detection of passageways in foliage.
Mapping mechanical stress in curved epithelia of designed size and shape
Marin-Llaurado, Ariadna; Kale, Sohan; Ouzeri, Adam; Sunyer, R.; Torres-Sanchez, A.; Latorre, E.; Gomez-Gonzales, M.; Roca-Cusach, P.; Arroyo, M.; Treapat, X. (2023-07-07)
The function of organs such as lungs, kidneys and mammary glands relies on the three-dimensional geometry of their epithelium. To adopt shapes such as spheres, tubes and ellipsoids, epithelia generate mechanical stresses that are generally unknown. Here we engineer curved epithelial monolayers of controlled size and shape andmap their state of stress. We design pressurized epithelia with circular, rectangular and ellipsoidal footprints. We develop a computational method, called curved monolayer stress microscopy, to map the stress tensor in these epithelia. This method establishes a correspondence between epithelial shape and mechanical stress without assumptions of material properties. In epithelia with spherical geometry we show that stress weakly increases with areal strain in a size-independent manner. In epithelia with rectangular and ellipsoidal cross-section we find pronounced stress anisotropies that impact cell alignment. Our approach enables a systematic study of how geometry and stress influence epithelial fate and function in three dimensions.
Using covariant Lyapunov vectors to quantify high-dimensional chaos with a conservation law
Barbish, John; Paul, Mark R. (American Physical Society, 2023-11-02)
We explore the high-dimensional chaos of a one-dimensional lattice of diffusively coupled tent maps using the covariant Lyapunov vectors (CLVs). We investigate the connection between the dynamics of the maps in the physical space and the dynamics of the covariant Lyapunov vectors and covariant Lyapunov exponents that describe the direction and growth (or decay) of small perturbations in the tangent space. We explore the tangent space splitting into physical and transient modes and find that the splitting persists for all of the conditions we explore. In general, the leading CLVs are highly localized in space and the CLVs become less localized with increasing Lyapunov index. We consider the dynamics with a conservation law whose strength is controlled by a parameter that can be continuously varied. Our results indicate that a conservation law delocalizes the spatial variation of the CLVs. We find that when a conservation law is present, the leading CLVs are entangled with fewer of their neighboring CLVs than in the absence of a conservation law.
The dynamics of an externally driven nanoscale beam that is under high tension and immersed in a viscous fluid
Barbish, John; Ti, C.; Ekinci, K. L.; Paul, Mark R. (AIP Publishing, 2022-07-15)
We explore the dynamics of a nanoscale doubly clamped beam that is under high tension, immersed in a viscous fluid, and driven externally by a spatially varying drive force. We develop a theoretical description that is valid for all possible values of tension, includes the motion of the higher modes of the beam, and accounts for a harmonic force that is applied over a limited spatial region of the beam near its ends. We compare our theoretical predictions with experimental measurements for a nanoscale beam that is driven electrothermally and immersed in air and water. The theoretical predictions show good agreement with experiments, and the validity of a simplified string approximation is demonstrated.
Pipelines and Power: Psychological Distress, Political Alienation, and the Breakdown of Environmental Justice in Government Agencies’ Public Participation Processes
Bell, Shannon E.; Hughes, Michael; Tuttle, Grace; Chisholm, Russell; Gerus, Stephen; Mullins, Danielle R.; Baller, Cameron; Scarff, Kelly; Spector, Rachel; Nalamalapu, Denali (Elsevier, 2024-01-25)
Environmental health research has demonstrated that living near industrial activity is associated with increased stress, depressive symptoms, and feelings of powerlessness. Little is known, however, about the effects of new natural gas pipelines—or the institutional processes dictating their approval and construction—on the mental health of local residents. Through our analysis of a mail survey, an online survey, and a set of semi-structured interviews, we examine how engagement with public participation processes associated with new interstate natural gas pipelines affects mental health. Our results suggest that the public participation opportunities offered by regulatory agencies during the pipeline certification process are primarily performative, and we find that many of the people who have taken part in these performative public input opportunities experience psychological distress, stress-activated physical health effects, and a loss of trust in government institutions. We argue that when people engage in public participation processes that have little or no effect on agency decision-making, it not only disempowers, but can harm those individuals and erode their trust in government institutions. Furthermore, we contend that providing the public with participation opportunities that are merely performative, with little ability to influence decision-making outcomes, is a violation of both procedural and recognition justice, two of the core tenets of environmental justice.
PID-Based Longitudinal Control of Platooning Trucks
Shaju, Aashish; Southward, Steve; Ahmadian, Mehdi (MDPI, 2023-12-05)
This article focuses on the development and assessment of a PID-based computationally cost-efficient longitudinal control algorithm for platooning trucks. The study employs a linear controller with a nested architecture, wherein the inner loop regulates relative velocities while the outer loop governs inter-vehicle distances within platoon vehicles. The design of the proposed PID controller entails a comprehensive focus on system identification, particularly emphasizing actuation dynamics. The simulation framework used in this study has been established through the integration of TruckSim^® and Simulink^®, resulting in a co-simulation environment. Simulink^® serves as the platform for control action implementation, while TruckSim^® simulates the vehicle’s dynamic behavior, thereby closely replicating real world conditions. The significant effort in fine-tuning the PID controller is described in detail, including the system identification of the linearized longitudinal dynamic model of the truck. The implementation is followed by an extensive series of simulation tests, systematically evaluating the controller’s performance, stability, and robustness. The results verify the effectiveness of the proposed controller in various leading truck operational scenarios. Furthermore, the controller’s robustness to large fluctuations in road grade and payload weight, which is commonly experienced in commercial vehicles, is evaluated. The simulation results indicate the controller’s ability to compensate for changes in both road grade and payload. Additionally, an initial assessment of the controller’s efficiency is conducted by comparing the commanded control efforts (total torque on wheels) along with the total fuel consumed. This initial analysis suggests that the controller exhibits minimal aggressive tendencies.
Development of an OpenFOAM Solver for Hydroacoustic Simulations: An Application for Acoustic Fish Deterrence
George, Edwin; Palmore, John A., Jr.; Alexander, William Nathan; Politano, Marcela; Smith, David; Woodley, Christa (2023-11-20)
Construction inspection & monitoring with quadruped robots in future human-robot teaming: A preliminary study
Halder, Srijeet; Afsari, Kereshmeh; Chiou, Erin; Patrick, Rafael; Hamed, Kaveh Akbari (Elsevier, 2023-04-15)
Construction inspection and monitoring are key activities in construction projects. Automation of inspection tasks can address existing limitations and inefficiencies of the manual process to enable systematic and consistent construction inspection. However, there is a lack of an in-depth understanding of the process of construction inspection and monitoring and the tasks and sequences involved to provide the basis for task delegation in a human-technology partnership. The purpose of this research is to study the conventional process of inspection and monitoring of construction work currently implemented in construction projects and to develop an alternative process using a quadruped robot as an inspector assistant to overcome the limitations of the conventional process. This paper explores the use of quadruped robots for construction inspection and monitoring with an emphasis on a human-robot teaming approach. Technical development and testing of the robotic technology are not in the scope of this study. The results indicate how inspector assistant quadruped robots can enable a human-technology partnership in future construction inspection and monitoring tasks. The research was conducted through on-site experiments and observations of inspectors during construction inspection and monitoring followed by a semi-structured interview to develop a process map of the conventional construction inspection and monitoring process. The study also includes on-site robot training and experiments with the inspectors to develop an alternative process map to depict future construction inspection and monitoring work with the use of an inspector assistant quadruped robot. Both the conventional and alternative process maps were validated through interview surveys with industry experts against four criteria including, completeness, accuracy, generalizability, and comprehensibility. The findings suggest that the developed process maps reflect existing and future construction inspection and monitoring work.
Distributed Planning of Collaborative Locomotion: A Physics-Based and Data-Driven Approach
Fawcett, Randall T.; Ames, Aaron D.; Hamed, Kaveh Akbari (IEEE, 2023-11-14)
This work aims to provide a computationally effective and distributed trajectory planner at the intersection of physics-based and data-driven techniques for the collaborative locomotion of holonomically constrained quadrupedal robots that can account for and attenuate interaction forces between subsystems. More specifically, this work lays the foundation for using an interconnected single rigid body model in a predictive control framework such that interaction forces can be utilized at the planning layer, wherein these forces are parameterized via a behavioral systems approach. Furthermore, the proposed trajectory planner is distributed such that each agent can locally plan for its own trajectory subject to coupling dynamics, resulting in a much more computationally efficient method for real-time planning. The optimal trajectory obtained by the planner is then provided to a full-order nonlinear whole-body controller for tracking at the low level. The efficacy and robustness of the proposed approach are verified both in simulation and on hardware subject to various disturbances, payloads, and uneven terrains.
The study of droplet internal circulation and its interaction with droplet deformation
Lin, Yushu; Palmore, John A., Jr. (2023-11-19)
The study of liquid droplet is important for applications like spray-painting, fire suppression, and spray combustion. Droplet morphology has a great impact in these applications, for example, in spray conditions, droplets of various sizes are generated from jet atomization, and the large droplets have strong deformation. The highly deformed droplets have very different characteristics compared to spherical droplets, but many studies on droplet dynamics are based on the spherical droplet assumption. To develop a more accurate modeling of liquid droplet in jet simulations, we use numerical approaches to investigate the mechanism of droplet deformation. Weber number, which measures the balance of surface tension and inertia, is a key non-dimensional group that quantifies droplet deformation. However, droplets with same Weber number do not always have an identical shape. For example, our previous work[Lin and Palmore, 2022] demonstrated that internal circulation also influences droplet shape. Therefore, a deeper understanding in droplet internal circulation is needed. In this work, we will explore a wider range of droplet parameters relevant to a wide array of applications for droplets to study the interaction between droplet internal circulation and deformation.
Computation of Direct Sensitivities of Spatial Multibody Systems with Joint Friction
Verulkar, Adwait; Sandu, Corina; Dopico, Daniel; Sandu, Adrian (ASME, 2022-07)
Friction exists in most mechanical systems and may have a major influence on the dynamic performance of the system. The incorporation of friction in dynamic systems has been a subject of active research for several years owing to its high nonlinearity and its dependence on several parameters. Consequently, optimization of dynamic systems with friction becomes a challenging task. Gradient-based optimization of dynamical systems is a prominent technique for optimal design and requires the computation of model sensitivities with respect to the design parameters. The novel contribution of this paper is the derivation of the analytical methodology for the computation of direct sensitivities for smooth multibody systems with joint friction using the Lagrangian index-1 formulation. System dynamics have been computed using two different friction models; the Brown and McPhee, and the Gonthier et al. model. The methodology proposed to obtain model sensitivities has also been validated using the complex finite difference method. A case study has been conducted on a spatial multibody system to observe the effect of friction on the dynamics and model sensitivities, compare sensitivities with respect to different parameters and demonstrate the numerical and validation aspects. Since design parameters can have very different magnitudes and units, the sensitivities have been scaled with the parameters for comparison. Finally, a discussion has been presented on the interpretation of the case study results. Due to the incorporation of joint friction, ‘jumps’ or discontinuities are observed in the model sensitivities akin to those observed for hybrid dynamical systems.

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