A Fluid-Structure Interaction case study on a square sail in a wind tunnel

2018 ◽  
Vol 163 ◽  
pp. 136-147 ◽  
Author(s):  
Stefano Ghelardi ◽  
Andrea Freda ◽  
Cesare Mario Rizzo ◽  
Diego Villa
2013 ◽  
Author(s):  
Hannes Renzsch ◽  
Kai Graf

In this paper the results of wind tunnel tests on two different asymmetric spinnakers are presented. During these tests forces and flying shapes at different apparent wind angles and trims were recorded by 6DoF balance and photogrammetry. As these tests are intended as a validation benchmark for FSI simulations on downwind sails, the sail moulds, incident flow data as well as measured forces and flying shapes will be made publically available.


2015 ◽  
Vol 103 ◽  
pp. 10-20 ◽  
Author(s):  
Sharad Dhavalikar ◽  
Sachin Awasare ◽  
Ramkumar Joga ◽  
A.R. Kar

Aviation ◽  
2018 ◽  
Vol 22 (4) ◽  
pp. 136-142
Author(s):  
Xiaoshun Zhao ◽  
Xue Yang ◽  
Li Yu ◽  
Xin Liu ◽  
Jingjing Wang

The reefing ratio for the first stage of a parachute limits the reefing ratio for the subsequent stages, so its minimal effective value is very important. In this paper, an empirical formula is derived to calculate the minimal effective reefing ratio. The empirical parameters are obtained by the arbitrary Lagrangian–Eulerian/fluid–structure interaction (ALE/FSI) method. By using the FSI method, the typical flow and structure fields of effective and ineffective reefed parachutes are revealed. The numerical results including drag characteristics and final shape are very consistent with wind tunnel tests. The curves of the empirical parameters with reefing ratios are obtained. The minimal effective reefing ratio obtained by the empirical formula is consistent with that of the numerical results, which shows that the empirical formula has high accuracy.


Author(s):  
Thomas G. Shepard ◽  
Kyle Schneider ◽  
Sarah Baxter ◽  
William Schwartz

Abstract Validation of numerical simulations is a key step in gaining confidence in the fidelity of computational models for a given application. These simulations take on additional complexity in fluid structure interactions when the body being studied experiences flow-induced deformation. In this study, experiments are conducted on a cantilevered aluminum plate mounted in a wind tunnel. Experimentally, deflections are measured using Digital Image Correlation and axial bending strains are measured using strain gages and. These values are compared to a coupled fluid-structure interaction simulation, which co-simulated the structural (Lagrangian FEA) and fluid (Navier-Stokes CFD) computational methods. Within the simulations, FEA parameters including mesh size, mapping method, and mesh type were varied; CFD parameters that were varied include turbulence theory, mesh sizing, inflation layer, mapping method, and Courant Number. Values were varied to study their effects on the simulation solution, as well as to ensure mesh independence of the solution relative to both simulation domains. Experiments were conducted on an Aluminum (6061-T6) plate measuring 152.4 × 50.8 × 0.61 mm. The plate was positioned in the wind tunnel at two different angles relative to the oncoming flow and Reynolds numbers of 98,000–247,000 were considered. The numerical simulation demonstrates agreement with DIC displacements and good agreement with measured strains with deflections up to ∼ 11 mm. Future steps are discussed.


Author(s):  
Rajmohan Waghela ◽  
Matthew Bryant

A cyber-physical system (CPS) combines active actuation, sensing, and a control algorithm to virtually replicate a physical structure with desired inertia, stiffness, and damping properties. The interaction of a CPS with a fluid flow can be used to study complex fluid-structure interaction phenomena. This paper highlights some of the control design challenges associated with the design of CPS and elaborates on issues pertaining to performance and lag. A model for including the interaction force and a potential work-around to inertia compensation are presented. Finally, a case study compares classical PID control with H∞ based model-matching control design.


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