Session T08: Experimental Techniques: Aerodynamics/Wind Tunnel (8:00am - 8:45am CST)

Characterization of a multi-fan-array wind tunnel studying insect flight behavior.

How flying insects navigate dynamic wind environments with turbulence and shear flow remains an activate area of investigation. To study their behavior in a controlled manner, we are developing a multi-fan-array wind tunnel with a 90x45x45 cm cubed working section. The fan array consists of 36 80mm fans laid out in a 6x6 grid, and each fan can be independently controlled to provide wind speeds between 0 and 50 cm/s. The fans can be operated in three different configurations designed to produce laminar, shear, and turbulent flow. To characterize the fluid flow in each of these conditions, we will use a hot wire anemometer mounted to a 2D plotter to measure with wind speed and turbulent intensity in several cross sections of the wind tunnel, for each of these three configurations. Preliminary results indicate that after the addition of a horizontal dividing plate we could measure a significant change in wind speed between the top and bottom sections of 20cm/s. After characterizing the fluid flow we will determine how each of the three conditions influences the flight behavior of fruit flies using a 3D multi-camera tracking system. Our results will lay a foundation for studying how insects behave in turbulent wind environments, with a particular future interest in how turbulence modulates their odor plume tracking behavior.   

Drift compensation in hot-wire anemometry

The drift of hot-wire (or other thermal anemometry-based) sensors continues to be a concern for those using constant temperature anemometers (CTAs). Although most previous work on this subject focused on compensating for changes in fluid temperature, the current work, based on that of Hewes et al. (Meas. Sci. Tech. 2020), focuses on compensating for changes in the wire's cold resistance, which may occur as a hot-wire ages, for example. We first show that this drift may be significant, especially for certain combinations of hot-wire sensors and CTAs. We then demonstrate that this drift can be compensated, using a modified form of the relationship between the output voltage of the CTA and the fluid velocity, which takes into account the sensor resistance and other resistances involved in the Wheatstone bridge (top resistance, operating resistance, cable and probe resistances). Moreover, we show that this method can compensate for drift caused by small changes in fluid temperature, even when the temperature is not known, which is of notable practicality. Application of this method is expected to reduce the frequency of calibrations needed to maintain satisfactory degrees of accuracy and repeatability in experimental measurements of fluid flows made using CTAs.   

Abstract Withdrawn

Wind tunnel testing continues to be a cornerstone in the development of new aircraft, since experimentation in a controlled environment allows for precise measurement of actuating pressures, forces, moments and flow patterns. Despite the evolution of Computational Fluid Dynamics (CFD) over the last decades, well-planned and well-executed wind tunnel testing continues to be the highest fidelity method of representing the flow around a body. However, wind tunnel testing is a time-consuming and expensive activity. In order to reduce time and resources demanded by wind tunnel testing, in 1997 NASA Langley Research Center started developing a new wind tunnel testing process based on Modern Design of Experiments (MDOE). While the conventional methodology, also known as One Factor At a Time (OFAT), focused on high-volume data collection, MDOE focuses on the generation of adequate prediction models. The methodology developed by NASA has potential to improve wind tunnel testing efficiency, by reducing the need of data volume and, consequently, reducing the time and resources spent on the experiment. This work aims to assess this potential through the replication of the MDOE techniques developed by NASA, identify its deficiencies and propose improvements.   

Delay in transition in a plane channel flow using a wind tunnel with large contraction

Measurements were conducted for various friction Reynolds numbers (Re$_{\mathrm{\tau }})$ ranging from laminar through transition to turbulence in a phane channel. The flow was established using a wind tunnel of dimensions much larger than that of the channel, and using two nozzles with contraction ratios of 8.3 and 13 respectively, separated by a settling chamber. Skin friction was determined using friction velocity obtained from wall pressure measurements using a micromanometer and mean velocity from Pitot measurement of the velocity profile. The flow was found to be laminar till Re$_{\mathrm{\tau }}=$ 70, much higher than the usual value of 45, which is observed to the start of transition from various other experiments and direct numerical simulation (DNS). Also, the flow attained the state of fully developed turbulence at Re$_{\mathrm{\tau }}=$ 175, again much higher than the usual value of 70 observed by others. This delay in transition and turbulence is attributed to having a large effective contraction of around 108, that is expected to have largely reduced the non-uniformities in the flow, hence reducing the stress and skin friction.   

Abstract Withdrawn

The use of drones in professional applications is limited by the lack of precise regulatory framework mostly because testing and validation protocols do not exist yet. In an effort to demonstrate the feasibility of achieving performance and safety assessment of a drone as a system in controllable and repeatable wind and weather conditions, the authors have tested a typical quadcopter drone in an indoor controlled flight environment featuring a windshaper – a fan array wind facility capable of generating uniform flows, gust and time variable flows as well as shear flows with arbitrary parameters – and a motion tracking camera system. For all free-flight tests conducted, the drone was controlled in position through a traditional remote-control link using Mavlink. A GPS signal was fabricated based on the wind speed and drone position obtained with the tracking cameras and was sent to the drone control system. This setup made it possible to recreate a variety of scenarios, ranging from (1) drone flying steadily in wind, to (2) dynamically flying drone in still air. The drone response to different wind situations and perturbations is measured. A statistical analysis of the result is presented and serves as ground for discussions around indoor performance validation of drones.   

Shock Train Analysis of Varying Deck Plate Configurations for a Multi Stream Rectangular Nozzle

The interactions in a supersonic flow involve a level of complexity that oftentimes does not match natural intuition that is built concerning the usual incompressible flows. Thus, experimentation is key to making improvements in aircraft design. Concerning supersonic aircrafts, one may analyze specifically the jet outlet and the compressible interaction of the flow which is emanated. By employing a supersonic jet with a single expansion ramp nozzle, this flow can be simulated. Then, by utilizing Particle Image Velocimetry (PIV), interactions can be further identified and characterized. From these PIV images, we can observe shockwaves that form from the jet outlet which continue downstream after reflections off shear layers. These shear layers develop as the result of mixing between the supersonic flow and the ambient surroundings. By adjusting the shape of a deck plate which is positioned at the exit of the jet, the profile of the resulting shock train can be altered to achieve advantages in acoustics. This study compares the shock trains which emanate from varying deck plate configurations to a nominal case. The deck plates of interest are; a twice nominal deck plate, an infinite in span deck plate, and a triangular trailing edge deck plate.   

Dispersed Pressure Sensing for Flow Field Estimation

Fan array wind tunnels offer an ideal test environment for small unmanned aerial vehicles (UAV) due to their high configurability and ability to simulate a multitude of different flows. However, flows currently must be manually measured and adjusted to achieve desired conditions. Measurements have to be taken by sweeping across which can be inaccurate and does not provide a temporally synchronized reading of the entire field. The development of an array of pitot-static tubes can provide accurate pressure and velocity data across an entire flow field at a single instance, giving a better picture of the entire field. This measurement technique has significant potential for machine learning applications on fan arrays, particularly as a feedback system to generate and maintain desired flows. This pitot-static tube array was implemented on a small fan array in Caltech's Center for Autonomous Systems and Technology (CAST) with the primary design conditions of minimizing interference with the flow produced by maintaining a small profile and structural integrity and stability.