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Geometrically weighted modal decomposition techniques
Classical data-driven modal decomposition methods are only applicable to problems with a fixed shape. They are not suitable for systems with fluid-structure interaction systems with shape-changing geometries. We proposed a novel method utilizing a conformal mapping technique to solve this issue. Through different examples with deforming geometry, the capability of the method to accurately capture the flow features associated with different system mechanisms is demonstrated. The proposed method is found to be suitable for a wide range of applications and a possible candidate for reduced-order flow modeling of complex shape-changing systems.
Mode competition in a plunging foil with an active flap
Flow-induced fluttering has a significant role in many applications. While being ubiquitous, controlling the flutter response has been primarily limited to simplified systems and, often, with the help of linear inviscid flow theories. In this study, we numerically investigate how the plunging response of a foil can be regulated using an active flap to improve structural safety or enhance the energy extraction efficiency of the foil with a tightly coupled fluid-structure interaction algorithm. A broad range of foil and flap settings was tested, and their flow dynamics have been investigated with a multiscale modal analysis technique suitable for FSI system to systematically isolate the active flap-induced and flow-induced modes.
Kernel mode decomposition for time-frequency localization
Identifying transient modes is an important topic in multiple disciplines, but the robustness and physical interpretation of the techniques used to achieve this goal has long been challenging issues. Kernel mode decomposition (KMD) is a newly proposed method that is capable of capturing the transition of modes in both amplitude and frequency. In this study, we expand the technique to spatial analysis. Results show that KMD can capture the temporal transition between different phases of a laminar separation bubble formation process, and can be used to extend the application of modal analysis methods to identify the spatial structures associated with each phase.
Dynamics of a separation bubble subject to compliant surface motion
This is a canonical benchmark numerical study to understand the interaction between a separation bubble and compliant surface. By adjusting the compliance of an elastic membrane within the separation region, the separation bubble dynamics are examined and the interplay between the flow-induced surface motion and the unsteady fluid pressure loads is investigated. Numerical simulations are utilized to explore the region of interest and reveal that the surface motion is affected by the tension strain, boundary conditions, and the location within the separation bubble. By gaining insight into the unsteady dynamics of separation we seek to pave a path for future controller schemes for the present case.
Flow-informed vibration-based health monitoring technique
Traditional structural health monitoring (SHM) techniques are often based on the assumption that the loading is either absent or can be treated as a stationary random variable. Many of the current SHM methods also necessitate strong actuation or an excessive number of sensors unsuitable for high-speed applications. An SHM technique that detects the type and extent of the damage in the presence of variable environmental conditions is proposed here. The model is tested with virtual simulations, and data acquired from the structural sensors are analyzed with a time-frequency realization technique to retrieve the system information and the location and extent of potential damages. It is shown that the proposed method is robust to the environmental effects and can be used for high-speed applications.
Correlate face mask leakage and facial features
with 3D morphable face models
The face mask “fit” affects the mask’s efficacy in preventing airborne transmission. To date, research on the face mask fit has been conducted mainly using experiments on limited subjects. The limited sample size in experimental studies makes it hard to reach a statistical correlation between mask fit and facial features in a population. Here, we employ a novel framework that utilizes a morphable face model and mask deployment simulation to test mask fit for many facial characteristics and mask designs. The proposed technique is an important step toward enabling personalized mask selection with maximum efficacy for society members.
Running of a hexapod robot with TDR-SLIP model
In recent decades, robots have gradually taken on more tasks that require mobility. Unlike animals, which are capable of coordinating complex sensing organs and muscles to achieve dynamic motion on all kinds of terrains, robots have difficulties traversing rough terrains at high speeds due to limitations of computational resources, actuator strength, etc. The aim of this research is to build a reduced-order model incorporating torque input and damping dissipation which can achieve dynamic running on rigid ground. Extensive experiments were conducted to examine how the rolling contact and energy-flowing characteristics of the proposed TDR-SLIP model interact with one another in the process of dynamic motion. Following this work, a position-torque hybrid control method was developed to enable the robot’s force-sensing ability. The experimental results revealed that the robot with hybrid control performs more stably. In addition, when the robot’s motion follows the stable dynamics derived from the model, the energy cost of the leg in stance can be significantly lower.