Mechanical Engineering Publications

Permanent URI for this collection

https://hdl.handle.net/1911/64878

Browse

Now showing 1 - 20 of 185

Teflon AF–Coated Nanotextured Aluminum Surfaces for Jumping Droplet Thermal Rectification
(Wiley, 2024) Shimokusu, Trevor J.; Nathani, Alia; Liu, Zhen; Yap, Te Faye; Preston, Daniel J.; Wehmeyer, Geoff
Jumping droplet thermal diodes (JDTDs) are promising candidates to achieve thermal rectification for next-generation thermal control. However, most prior demonstrations of JDTDs have relied on monolayer-coated copper-based superhydrophobic (SHPB) surfaces, while lower-cost aluminum JDTDs with more durable thin polymeric coatings have not been explored. In this work, a JDTD is constructed that employs SHPB aluminum surfaces coated with protective thin films of Teflon AF (amorphous fluoropolymer) 1601. Measurements for different heating orientations, gap heights (H), and fill ratios (ϕ) show that a maximum thermal rectification ratio of 7 can be achieved for H = 2.4 mm and ϕ = 10%. A thermal circuit is demonstrated that uses the JDTD to rectify time-periodic temperature profiles, achieving thermal circuit effectiveness values up to 30% of the ideal-diode limit. Coupon-level durability tests and device-level cycling show that dip coated Teflon AF enables stable operation of Al JDTDs over >20 cycles, improving on the performance of a monolayer-coated surface that fails after 5 cycles. The findings of this work signify that Teflon AF coated Al SHPB surfaces can be used for thermal rectification and motivate future research into Al JDTDs for advanced thermal management applications.
Thermally accelerated curing of platinum-catalyzed elastomers
(Elsevier, 2024) Yap, Te Faye; Rajappan, Anoop; Bell, Marquise D.; Rasheed, Rawand M.; Decker, Colter J.; Preston, Daniel J.
Silicone elastomers exhibit extraordinary compliance, positioning them as a material of choice for soft robots and devices. To accelerate curing times of platinum-catalyzed silicone elastomers, researchers have employed elevated temperatures; however, knowledge of the requisite duration for curing at a given temperature has remained limited to specific elastomers and has relied primarily on empirical trends. This work presents an analytical model based on an Arrhenius framework coupled with data from thermo-rheological experiments to provide guidelines for suitable curing conditions for commercially available addition-cured platinum-catalyzed silicone elastomers. The curing reaction exhibits self-similarity upon normalizing to a dimensionless reaction coordinate, allowing quantification of the extent of curing under arbitrary time-varying thermal conditions. Mechanical testing revealed no significant changes in properties or performance as a result of thermally accelerated curing. With this framework, higher throughput of elastomeric components can be achieved, and the design space for elastomer-based manufacturing can be developed beyond conventional casting.
Evaluation of finite element modeling methods for predicting compression screw failure in a custom pelvic implant
(Frontiers Media S.A., 2024) Zhu, Yuhui; Babazadeh-Naseri, Ata; Brake, Matthew R. W.; Akin, John E.; Li, Geng; Lewis, Valerae O.; Fregly, Benjamin J.
Introduction: Three-dimensional (3D)-printed custom pelvic implants have become a clinically viable option for patients undergoing pelvic cancer surgery with resection of the hip joint. However, increased clinical utilization has also necessitated improved implant durability, especially with regard to the compression screws used to secure the implant to remaining pelvic bone. This study evaluated six different finite element (FE) screw modeling methods for predicting compression screw pullout and fatigue failure in a custom pelvic implant secured to bone using nine compression screws. Methods: Three modeling methods (tied constraints (TIE), bolt load with constant force (BL-CF), and bolt load with constant length (BL-CL)) generated screw axial forces using functionality built into Abaqus FE software; while the remaining three modeling methods (isotropic pseudo-thermal field (ISO), orthotropic pseudo-thermal field (ORT), and equal-and-opposite force field (FOR)) generated screw axial forces using iterative physics-based relationships that can be implemented in any FE software. The ability of all six modeling methods to match specified screw pretension forces and predict screw pullout and fatigue failure was evaluated using an FE model of a custom pelvic implant with total hip replacement. The applied hip contact forces in the FE model were estimated at two locations in a gait cycle. For each of the nine screws in the custom implant FE model, likelihood of screw pullout failure was predicted using maximum screw axial force, while likelihood of screw fatigue failure was predicted using maximum von Mises stress. Results: The three iterative physics-based modeling methods and the non-iterative Abaqus BL-CL method produced nearly identical predictions for likelihood of screw pullout and fatigue failure, while the other two built-in Abaqus modeling methods yielded vastly different predictions. However, the Abaqus BL-CL method required the least computation time, largely because an iterative process was not needed to induce specified screw pretension forces. Of the three iterative methods, FOR required the fewest iterations and thus the least computation time. Discussion: These findings suggest that the BL-CL screw modeling method is the best option when Abaqus is used for predicting screw pullout and fatigue failure in custom pelvis prostheses, while the iterative physics-based FOR method is the best option if FE software other than Abaqus is used.
Experimental investigation of dynamic failure in fabric curved composite laminates under pure shear loading
(Elsevier, 2024) Çevik, Ahmet; Yavaş, Denizhan; Çöker, Demirkan
In this paper, an experimental investigation of the failure mechanism in fabric curved composite laminates having a stacking sequence of [(45/0)7/45/45/0/45] is presented. The curved beam specimens are manufactured from AS4/8552 5 Harness Satin Fabric prepregs. The experiments were carried out with a novel test fixture designed to apply pure shear loading to one arm of the curved specimen while the other arm is fixed. The high-speed camera (HSC) is utilized to observe the mechanism of the failure occurring on the curved beam. Afterward, the crack-tip speeds are calculated using the HSC images obtained with 420,000 frame per second. Fractography was conducted with post-mortem specimens using a digital microscope to assess the type and propagation of cracks in the curved region. All curved fabric specimens exhibited failure through one major crack located in the region of high radial stresses, leading to a loss of their load-carrying capacity. HSC observations show that the crack tips reach intersonic speed, exceeding the shear wave speed, indicating that the failure event occurring on the curved region of the beam is highly dynamic. Fluctuations occurring in the crack tip speed history are also observed. The micrographs show multiple crack initiations across different plies. It is observed that the crack propagation is influenced by the weave style of the fabric specimen, which may lead to the observed fluctuations in the crack tip speed history.
Microneedle-based sampling of dermal interstitial fluid using a vacuum-assisted skin patch
(Elsevier, 2024) Jiang, Xue; Wilkirson, Elizabeth C.; Bailey, Aaron O.; Russell, William K.; Lillehoj, Peter B.
Interstitial fluid (ISF) contains a wealth of biomolecules, yet it is underutilized for diagnostic testing due to a lack of rapid and simple techniques for collecting abundant amounts of fluid. Here, we report a simple and minimally invasive technique for rapidly sampling larger quantities of ISF from human skin. A microneedle array is used to generate micropores in skin from which ISF is extracted using a vacuum-assisted skin patch. Using this technique, an average of 20.8 μL of dermal ISF is collected in 25 min, which is an ∼6-fold improvement over existing sampling methods. Proteomic analysis of collected ISF reveals that it has nearly identical protein composition as blood, and >600 medically relevant biomarkers are identified. Toward this end, we demonstrate the detection of SARS-CoV-2 neutralizing antibodies in ISF collected from COVID-19 vaccinees using two commercial immunoassays, showcasing the utility of this technique for diagnostic testing.
Interpretable Structural Model Error Discovery From Sparse Assimilation Increments Using Spectral Bias-Reduced Neural Networks: A Quasi-Geostrophic Turbulence Test Case
(Wiley, 2024) Mojgani, Rambod; Chattopadhyay, Ashesh; Hassanzadeh, Pedram
Earth system models suffer from various structural and parametric errors in their representation of nonlinear, multi-scale processes, leading to uncertainties in their long-term projections. The effects of many of these errors (particularly those due to fast physics) can be quantified in short-term simulations, for example, as differences between the predicted and observed states (analysis increments). With the increase in the availability of high-quality observations and simulations, learning nudging from these increments to correct model errors has become an active research area. However, most studies focus on using neural networks, which while powerful, are hard to interpret, are data-hungry, and poorly generalize out-of-distribution. Here, we show the capabilities of Model Error Discovery with Interpretability and Data Assimilation (MEDIDA), a general, data-efficient framework that uses sparsity-promoting equation-discovery techniques to learn model errors from analysis increments. Using two-layer quasi-geostrophic turbulence as the test case, MEDIDA is shown to successfully discover various linear and nonlinear structural/parametric errors when full observations are available. Discovery from spatially sparse observations is found to require highly accurate interpolation schemes. While NNs have shown success as interpolators in recent studies, here, they are found inadequate due to their inability to accurately represent small scales, a phenomenon known as spectral bias. We show that a general remedy, adding a random Fourier feature layer to the NN, resolves this issue enabling MEDIDA to successfully discover model errors from sparse observations. These promising results suggest that with further development, MEDIDA could be scaled up to models of the Earth system and real observations.
Data Imbalance, Uncertainty Quantification, and Transfer Learning in Data-Driven Parameterizations: Lessons From the Emulation of Gravity Wave Momentum Transport in WACCM
(Wiley, 2024) Sun, Y. Qiang; Pahlavan, Hamid A.; Chattopadhyay, Ashesh; Hassanzadeh, Pedram; Lubis, Sandro W.; Alexander, M. Joan; Gerber, Edwin P.; Sheshadri, Aditi; Guan, Yifei
Neural networks (NNs) are increasingly used for data-driven subgrid-scale parameterizations in weather and climate models. While NNs are powerful tools for learning complex non-linear relationships from data, there are several challenges in using them for parameterizations. Three of these challenges are (a) data imbalance related to learning rare, often large-amplitude, samples; (b) uncertainty quantification (UQ) of the predictions to provide an accuracy indicator; and (c) generalization to other climates, for example, those with different radiative forcings. Here, we examine the performance of methods for addressing these challenges using NN-based emulators of the Whole Atmosphere Community Climate Model (WACCM) physics-based gravity wave (GW) parameterizations as a test case. WACCM has complex, state-of-the-art parameterizations for orography-, convection-, and front-driven GWs. Convection- and orography-driven GWs have significant data imbalance due to the absence of convection or orography in most grid points. We address data imbalance using resampling and/or weighted loss functions, enabling the successful emulation of parameterizations for all three sources. We demonstrate that three UQ methods (Bayesian NNs, variational auto-encoders, and dropouts) provide ensemble spreads that correspond to accuracy during testing, offering criteria for identifying when an NN gives inaccurate predictions. Finally, we show that the accuracy of these NNs decreases for a warmer climate (4 × CO2). However, their performance is significantly improved by applying transfer learning, for example, re-training only one layer using ∼1% new data from the warmer climate. The findings of this study offer insights for developing reliable and generalizable data-driven parameterizations for various processes, including (but not limited to) GWs.
Damping Enhancement Solution for Wind Turbines Through Amplifying Damping Transfer Systems
(World Scientific, 2024) Wang, Meng; Lu, Hai-Qiang; Wang, Pi-Guang; Nagarajaiah, Satish; Du, Xiu-Li
This paper proposed a novel amplifying damping transfer system (ADTS) as a new damping enhancement solution for high-rise structures like wind turbines. The proposed ADTS can transfer the upper rotation of turbine tower to its bottom with damping amplification mechanism. Hence, viscous damper can be installed on wind turbines in a very convenient and efficient way. The dynamic characteristics of wind turbines equipped with ADTS were parametrically investigated concerning the influence of the damping, stiffness, and position of the ADTS based on complex frequency analysis. It was found that each mode has a maximum damping ratio, which is affected by the ADTS stiffness and position. The optimal ADTS position of the first mode is about 0.7 H (turbine height), and the optimal positions of the second mode are at 0.3 H and 0.86 H. The proposed ADTS considerably attenuated both drift and acceleration responses of wind turbines caused by winds and earthquakes. For example, as compared to the optimized tuned mass damper, ADTS further decreases the displacement (acceleration) of wind turbine tower by about 22% (38%).
A general-purpose IGA mesh generation method: NURBS Surface-to-Volume Guided Mesh Generation
(Springer Nature, 2024) Kuraishi, Takashi; Takizawa, Kenji; Tezduyar, Tayfun E.
The NURBS Surface-to-Volume Guided Mesh Generation (NSVGMG) is a general-purpose mesh generation method, introduced to increase the scope of isogeometric analysis in computing complex-geometry problems. In the NSVGMG, NURBS patch surface meshes serve as guides in generating the patch volume meshes. The interior control points are determined independent of each other, with only a small subset of the surface control points playing a role in determining each interior point. In the updated version of the NSVGMG we are introducing in this article, in the process of determining the location of an interior point in a parametric direction, more weight is given to the closer guides, with the closeness measured along the guides in the other parametric directions. Tests with 2D and 3D shapes show the effectiveness of the NSVGMG in generating good quality meshes, and the robustness of the updated NSVGMG even in mesh generation for complex shapes with distorted boundaries.
A wirelessly programmable, skin-integrated thermo-haptic stimulator system for virtual reality
(National Academy of Sciences, 2024) Kim, Jae-Hwan; Vázquez-Guardado, Abraham; Luan, Haiwen; Kim, Jin-Tae; Yang, Da Som; Zhang, Haohui; Chang, Jan-Kai; Yoo, Seonggwang; Park, Chanho; Wei, Yuanting; Christiansen, Zach; Kim, Seungyeob; Avila, Raudel; Kim, Jong Uk; Lee, Young Joong; Shin, Hee-Sup; Zhou, Mingyu; Jeon, Sung Woo; Baek, Janice Mihyun; Lee, Yujin; Kim, So Young; Lim, Jaeman; Park, Minsu; Jeong, Hyoyoung; Won, Sang Min; Chen, Renkun; Huang, Yonggang; Jung, Yei Hwan; Yoo, Jae-Young; Rogers, John A.
Sensations of heat and touch produced by receptors in the skin are of essential importance for perceptions of the physical environment, with a particularly powerful role in interpersonal interactions. Advances in technologies for replicating these sensations in a programmable manner have the potential not only to enhance virtual/augmented reality environments but they also hold promise in medical applications for individuals with amputations or impaired sensory function. Engineering challenges are in achieving interfaces with precise spatial resolution, power-efficient operation, wide dynamic range, and fast temporal responses in both thermal and in physical modulation, with forms that can extend over large regions of the body. This paper introduces a wireless, skin-compatible interface for thermo-haptic modulation designed to address some of these challenges, with the ability to deliver programmable patterns of enhanced vibrational displacement and high-speed thermal stimulation. Experimental and computational investigations quantify the thermal and mechanical efficiency of a vertically stacked design layout in the thermo-haptic stimulators that also supports real-time, closed-loop control mechanisms. The platform is effective in conveying thermal and physical information through the skin, as demonstrated in the control of robotic prosthetics and in interactions with pressure/temperature-sensitive touch displays.
Changes in walking function and neural control following pelvic cancer surgery with reconstruction
(Frontiers, 2024) Li, Geng; Ao, Di; Vega, Marleny M.; Zandiyeh, Payam; Chang, Shuo-Hsiu; Penny, Alexander N.; Lewis, Valerae O.; Fregly, Benjamin J.; Rice Computational Neuromechanics Laboratory
Introduction: Surgical planning and custom prosthesis design for pelvic cancer patients are challenging due to the unique clinical characteristics of each patient and the significant amount of pelvic bone and hip musculature often removed. Limb-sparing internal hemipelvectomy surgery with custom prosthesis reconstruction has become a viable option for this patient population. However, little is known about how post-surgery walking function and neural control change from pre-surgery conditions. Methods: This case study combined comprehensive walking data (video motion capture, ground reaction, and electromyography) with personalized neuromusculoskeletal computer models to provide a thorough assessment of pre- to post-surgery changes in walking function (ground reactions, joint motions, and joint moments) and neural control (muscle synergies) for a single pelvic sarcoma patient who received internal hemipelvectomy surgery with custom prosthesis reconstruction. Pre- and post-surgery walking function and neural control were quantified using pre- and post-surgery neuromusculoskeletal models, respectively, whose pelvic anatomy, joint functional axes, muscle-tendon properties, and muscle synergy controls were personalized using the participant’s pre-and post-surgery walking and imaging data. For the post-surgery model, virtual surgery was performed to emulate the implemented surgical decisions, including removal of hip muscles and implantation of a custom prosthesis with total hip replacement. Results: The participant’s post-surgery walking function was marked by a slower self-selected walking speed coupled with several compensatory mechanisms necessitated by lost or impaired hip muscle function, while the participant’s post-surgery neural control demonstrated a dramatic change in coordination strategy (as evidenced by modified time-invariant synergy vectors) with little change in recruitment timing (as evidenced by conserved time-varying synergy activations). Furthermore, the participant’s post-surgery muscle activations were fitted accurately using his pre-surgery synergy activations but fitted poorly using his pre-surgery synergy vectors. Discussion: These results provide valuable information about which aspects of post-surgery walking function could potentially be improved through modifications to surgical decisions, custom prosthesis design, or rehabilitation protocol, as well as how computational simulations could be formulated to predict post-surgery walking function reliably given a patient’s pre-surgery walking data and the planned surgical decisions and custom prosthesis design.
Conversion of Layered WS2 Crystals into Mixed-Domain Electrochemical Catalysts by Plasma-Assisted Surface Reconstruction
(Wiley, 2024) Park, Jiheon; Cho, Iaan; Jeon, Hotae; Lee, Youjin; Zhang, Jian; Lee, Dongwook; Cho, Min Kyung; Preston, Daniel J.; Shong, Bonggeun; Kim, In Soo; Lee, Won-Kyu
Electrocatalytic water splitting is crucial to generate clean hydrogen fuel, but implementation at an industrial scale remains limited due to dependence on expensive platinum (Pt)-based electrocatalysts. Here, an all-dry process to transform electrochemically inert bulk WS2 into a multidomain electrochemical catalyst that enables scalable and cost-effective implementation of the hydrogen evolution reaction (HER) in water electrolysis is reported. Direct dry transfer of WS2 flakes to a gold thin film deposited on a silicon substrate provides a general platform to produce the working electrodes for HER with tunable charge transfer resistance. By treating the mechanically exfoliated WS2 with sequential Ar-O2 plasma, mixed domains of WS2, WO3, and tungsten oxysulfide form on the surfaces of the flakes, which gives rise to a superior HER with much greater long-term stability and steady-state activity compared to Pt. Using density functional theory, ultraefficient atomic sites formed on the constituent nanodomains are identified, and the quantification of atomic-scale reactivities and resulting HER activities fully support the experimental observations.
Generalized Damped Outrigger Systems for Suppressing Multimode Vibrations of Tall Buildings
(World Scientific, 2024) Wen, Yongkui; Chen, Lin; Nagarajaiah, Satish
Damped outrigger is a viable means for reducing dynamic responses of tall buildings. This study focuses on generalized damped outrigger (GDO) systems. A GDO is composed of a damper for energy dissipation, a negative stiffness device and an inerter for damping enhancement. The GDO system incorporates GDOs at different floors of the tall building optimized to varied structural modes. Frequency equation of a tall building simplified as a cantilever beam with multiple GDOs is first derived by complex modal analysis. A finite different model of such a system is used for verification. Parametric analyses are then performed to compare damping effects of different GDO systems. It is found that a negative stiffness damped outrigger (NSDO) or inerter damped outrigger (IDO) needs to be optimized for maximizing damping of a specific mode. GDOs, respectively, tuned to different modes can largely improve the multimode damping effects. The optimal parameters of the GDOs are slightly different from those in the case when they are installed separately. With both negative stiffness and nonzero inertance, a GDO still needs to be tuned to a specific mode because multimode damping is sensitive to the damper coefficient. The combination of an NSDO optimized to the first mode and an IDO tuned to a higher mode seems the best solution. The IDO additionally improves the first mode damping provided by the NSDO and the two-mode damping is not sensitive to the damper coefficient of the NSDO. The findings are confirmed through seismic response analyses of a tall building with different GDO systems.
Tribological Properties of h-BN, Ag and MgO Nanostructures as Lubricant Additives in Vegetable Oils
(MDPI, 2024) Granja, Victoria; Jogesh, Kollol; Taha-Tijerina, Jaime; Higgs, C. Fred; Particle Flow and Tribology Laboratory
There exists an ever-growing need for sustainable engineering solutions to improve emission control and the energy efficiency of tribosystems. This study examines the tribological properties of two environmentally friendly vegetable fluids, soybean and sunflower oil, with the addition of three non-toxic nanostructures (h-BN, silver and MgO) at different concentrations. It was found that nanostructures added to vegetable oils at specific concentrations can exhibit good friction reduction and wear preventive properties. The addition of h-BN nanosheets in sunflower oil decreased the coefficient of friction and the wear damage, as measured by the wear scar diameter. Silver and magnesium oxide nanoparticles further reduced the friction and wear, respectively. In addition to the tribological testing of the samples, investigations were performed using an optical microscope, SEM and EDX to elucidate the mechanisms that may have led to the observed friction reduction and wear-preventive properties of different nanostructure additives. The thermophysical properties of the samples were also measured. It was found that the thermal conductivity of both base oils could be enhanced by 24% when using h-BN at 0.25 wt% concentration.
Space–time flow computation with boundary layer and contact representation: a 10-year history
(Springer Nature, 2024) Takizawa, Kenji; Tezduyar, Tayfun E.
In computation of flow problems with moving solid surfaces, moving-mesh methods such as the space–time (ST) variational multiscale method enable mesh-resolution control near the solid surfaces and thus high-resolution boundary-layer representation. There was, however, a perception that in computations where the solid surfaces come into contact, high-resolution boundary-layer representation and actual-contact representation without leaving a mesh protection opening between the solid surfaces were mutually exclusive objectives in a practical sense. The introduction of the ST topology change (ST-TC) method in 2013 changed the perception. The two objectives were no longer mutually exclusive. The ST-TC makes moving-mesh computation possible even without leaving a mesh protection opening. The contact is represented as an actual contact and the boundary layer is represented with high resolution. Elements collapse or are reborn as needed, and that is attainable in the ST framework while retaining the computational efficiency at a practical level. The ST-TC now has a 10-year history of achieving the two objectives that were long seen as mutually exclusive. With the ST-TC and other ST computational methods introduced before and after, it has been possible to address many of the challenges encountered in conducting flow analysis with boundary layer and contact representation, in the presence of additional intricacies such as geometric complexity, isogeometric discretization, and rotation or deformation of the solid surfaces. The flow analyses conducted with these ST methods include car and tire aerodynamics with road contact and tire deformation and ventricle-valve-aorta flow. To help widen awareness of these methods and what they can do, we provide an overview of the methods, including those formulated in the context of isogeometric analysis, and the computations performed over the 10-year history of the ST-TC.
A thermal regulator using passive all-magnetic actuation
(Elsevier, 2023) Castelli, Lorenzo; Garg, Ajay; Zhu, Qing; Sashital, Pooja; Shimokusu, Trevor J.; Wehmeyer, Geoff
Thermal regulators are two-terminal devices used for passive temperature control of electronics, batteries, or buildings. Existing thermal expansion regulators suffer from large thicknesses and substantial hysteresis. Here we report an all-magnetic thermal regulator in which the temperature of the control terminal (Tcontrol) leads to passive steady-state surface mating/demating that enables/blocks heat conduction. The mechanism relies on Tcontrol-dependent magnetic forces between gadolinium and neodymium iron boron magnets when Tcontrol is near gadolinium’s Curie temperature of 21oC. Our centimeter-scale prototype has a thermal switch ratio of 34−13+30 in vacuum and 2.1−0.2+0.2 in air, a vacuum OFF state thermal conductance of 3.5 mW/K, an average switching temperature of 20oC, a small thermal deadband of 5oC, and a relatively compact thickness <2 cm. We quantify the regulator performance over >2,000 cycles and construct the regulator using commercially available materials, showing that this thermomagnetic device can be used for effective thermal regulation near room temperature.
Hybrid method for full-field response estimation using sparse measurement data based on inverse analysis and static condensation
(Elsevier, 2022) Pal, Ashish; Meng, Wei; Nagarajaiah, Satish; Smalley-Curly Institute
In structural health monitoring, measuring the accurate and spatially dense response near critical locations of the structure can be advantageous to estimate damage to the structure. Due to several physical restrictions or limitations of the sensing method, it may not always be possible to generate reliable data at critical locations. In this study, a hybrid method is presented that makes use of the measured displacement data and finite element (FE) model of the structure to predict dense full-field response. The presented method can incorporate unknown boundary conditions and unknown body forces by applying correction/fictitious forces to match predicted and measured responses. Using static condensation followed by inverse analysis, these additional forces are found by setting up a least square problem. Due to the problem being ill-posed, L2-penalty is used to control the prediction error. Numerical simulation of a plate subjected to body force showed an accurate prediction of full-field response except for a few boundary locations. To handle this, the proposed method is used in conjunction with linear interpolation near boundary locations. The method is validated in a laboratory experiment for a plate with a notch having displacement measured using Digital Image Correlation (DIC). On comparing strains calculated using predicted displacements, FEM, and DIC, the predicted strains show better agreement with the FEM than DIC. This affirms that the proposed hybrid technique can be used at critical locations where DIC fails to provide reliable strain data.
Hybrid FES-exoskeleton control: Using MPC to distribute actuation for elbow and wrist movements
(Frontiers Media S.A., 2023) Dunkelberger, Nathan; Berning, Jeffrey; Schearer, Eric M.; O'Malley, Marcia K.; Mechatronics and Haptics Interfaces Laboratory
IntroductionIndividuals who have suffered a cervical spinal cord injury prioritize the recovery of upper limb function for completing activities of daily living. Hybrid FES-exoskeleton systems have the potential to assist this population by providing a portable, powered, and wearable device; however, realization of this combination of technologies has been challenging. In particular, it has been difficult to show generalizability across motions, and to define optimal distribution of actuation, given the complex nature of the combined dynamic system.MethodsIn this paper, we present a hybrid controller using a model predictive control (MPC) formulation that combines the actuation of both an exoskeleton and an FES system. The MPC cost function is designed to distribute actuation on a single degree of freedom to favor FES control effort, reducing exoskeleton power consumption, while ensuring smooth movements along different trajectories. Our controller was tested with nine able-bodied participants using FES surface stimulation paired with an upper limb powered exoskeleton. The hybrid controller was compared to an exoskeleton alone controller, and we measured trajectory error and torque while moving the participant through two elbow flexion/extension trajectories, and separately through two wrist flexion/extension trajectories.ResultsThe MPC-based hybrid controller showed a reduction in sum of squared torques by an average of 48.7 and 57.9% on the elbow flexion/extension and wrist flexion/extension joints respectively, with only small differences in tracking accuracy compared to the exoskeleton alone.DiscussionTo realize practical implementation of hybrid FES-exoskeleton systems, the control strategy requires translation to multi-DOF movements, achieving more consistent improvement across participants, and balancing control to more fully leverage the muscles' capabilities.
Frequency independent damped outrigger systems for multi-mode seismic control of super tall buildings with frequency independent negative stiffness enhancement
(Wiley, 2023) Wang, Meng; Sun, Fei-Fei; Koetaka, Yuji; Chen, Lin; Nagarajaiah, Satish; Du, Xiu-Li
Damped outrigger system is effective for improving energy dissipation for tall buildings. However, conventional damped outrigger (CDO) system with viscous damping has two limitations: (i) its maximum damping ratio cannot be improved when outrigger/column stiffness is inadequate; (ii) different modes achieve their maximum damping ratios at different outrigger damping values, and thus the dampers cannot be optimized to simultaneously reduce vibrations of multiple modes of concern to their minimum. In this paper, a purely frequency-independent negative stiffness damped outrigger (FI-NSDO) system is proposed by combining frequency-independent damper (FID) and negative stiffness device (NSD). The damped outrigger with FID can achieve the maximum damping ratio for all modes as compared to frequency-dependent damper like viscous damper. As the NSD has the features of assisting and enhancing motion and frequency-independence, the utilization of NSD will considerably improve the maximum damping ratios when outrigger/column stiffness is inadequate and maintain the frequency-independent feature of the whole system. Therefore, the FI-NSDO has the capability of simultaneously increasing the damping ratios of all target modes to their maximum values. Analysis in frequency domain and time domain, demonstrate that the proposed FI-NSDO performs better in controlling the multi-mode vibration of seismic responses.
Practical negative stiffness device with viscoelastic damper in parallel or series configuration for cable damping improvement
(Elsevier, 2023) Chen, Lin; Liu, Zhanhang; Zou, Yiqing; Wang, Meng; Nagarajaiah, Satish; Sun, Feifei; Sun, Limin
Negative stiffness mechanism has been found able to improve damping performance of dampers on a stay cable which otherwise is limited by the damper installation distance from a cable end. This study provides a practical negative stiffness device (NSD) with adjustable negative stiffness and experiments are performed to validate the negative stiffness effect. The NSD is then combined with a viscoelastic damper in parallel or series for cable damping improvement. Explicit design formulas are derived for optimal design with a target enhancement effect in damping considering the damper described respectively using the Kelvin model and the linear hysteretic damping model. The formulas are verified by analytical and numerical solutions. Parametric analyses show damping enhancement effects of the NSD and it is found more efficient when combined with a damper in series because both deformation amplitudes of the damper and the NSD are further increased in this configuration. Subsequently, case studies are carried out based on two cables of the Sutong Bridge respectively with a shear-type viscous damper and a high damping rubber damper. The results show that the designed NSD can fulfill practical requirements. Particularly, a 100% increase in damping can be achieved by the presented NSD when combined with the damper installed on a cable of 546.9 m long.

Browse

Recent Submissions