Engineering topics

Ngo, Christina L.

Publications and source records attributed to Ngo, Christina L..

3 records

NASA NTRS2020

Development of Unsteady Pressure-Sensitive Paint Application on NASA Space Launch System

The key measurement to acquire for understanding unsteady flow is surface pressure. Unsteady Pressure-Sensitive Paint (uPSP) is an emerging optical technique used in wind tunnel testing to measure fluctuating surface pressures. Recently, tests were conducted on NASA’s Space Launch System in NASA Ames Research Center’s Unitary Plan Wind Tunnel to determine the aeroacoustics environment and assist in developing the buffet forcing functions. Unsteady PSP data was collected during this test campaign. Steady state PSP data, infrared thermography, shadowgraph, accelerometer data, and dynamic pressure transducer data were also collected. In all 50 TB of data were collected during the three days of testing. During these three days of testing, a repeating transonic and supersonic alpha sweep condition was acquired. This paper presents these two wind tunnel conditions and examines how the temperature influences the PSP data. In the first large demonstration of uPSP in 2015 on an NESC-, AETC-sponsored wind tunnel test, lifetime PSP results highlighted the influence the model temperature had on the PSP data. A best practice of heat soaking the model before acquiring calibration images was followed during the test campaign presented in this paper. An infrared thermography camera and thermocouples were installed in the model to collect more details of the model surface temperature. Data processing schemes for uPSP are still in development but will be briefly presented here as well.

Roozeboom, Nettie H.↗

NASA NTRS2017

Inverse Force Determination on a Small Scale Launch Vehicle Model Using a Dynamic Balance

A launch vehicle can experience large unsteady aerodynamic forces in the transonic regime that, while usually only lasting for tens of seconds during launch, could be devastating if structural components and electronic hardware are not designed to account for them. These aerodynamic loads are difficult to experimentally measure and even harder to computationally estimate. The current method for estimating buffet loads is through the use of a few hundred unsteady pressure transducers and wind tunnel test. Even with a large number of point measurements, the computed integrated load is not an accurate enough representation of the total load caused by buffeting. This paper discusses an attempt at using a dynamic balance to experimentally determine buffet loads on a generic scale hammer head launch vehicle model tested at NASA Ames Research Center's 11' x 11' transonic wind tunnel. To use a dynamic balance, the structural characteristics of the model needed to be identified so that the natural modal response could be and removed from the aerodynamic forces. A finite element model was created on a simplified version of the model to evaluate the natural modes of the balance flexures, assist in model design, and to compare to experimental data. Several modal tests were conducted on the model in two different configurations to check for non-linearity, and to estimate the dynamic characteristics of the model. The experimental results were used in an inverse force determination technique with a psuedo inverse frequency response function. Due to the non linearity, the model not being axisymmetric, and inconsistent data between the two shake tests from different mounting configuration, it was difficult to create a frequency response matrix that satisfied all input and output conditions for wind tunnel configuration to accurately predict unsteady aerodynamic loads.

testing↗

NASA NTRS2016

Investigation of Unsteady Pressure-Sensitive Paint (uPSP) and a Dynamic Loads Balance to Predict Launch Vehicle Buffet Environments

This NESC assessment examined the accuracy of estimating buffet loads on in-line launch vehicles without booster attachments using sparse unsteady pressure measurements. The buffet loads computed using sparse sensor data were compared with estimates derived using measurements with much higher spatial resolution. The current method for estimating launch vehicle buffet loads is through wind tunnel testing of models with approximately 400 unsteady pressure transducers. Even with this relatively large number of sensors, the coverage can be insufficient to provide reliable integrated unsteady loads on vehicles. In general, sparse sensor spacing requires the use of coherence-length-based corrections in the azimuthal and axial directions to integrate the unsteady pressures and obtain reasonable estimates of the buffet loads. Coherence corrections have been used to estimate buffet loads for a variety of launch vehicles with the assumption methodology results in reasonably conservative loads. For the Space Launch System (SLS), the first estimates of buffet loads exceeded the limits of the vehicle structure, so additional tests with higher sensor density were conducted to better define the buffet loads and possibly avoid expensive modifications to the vehicle design. Without the additional tests and improvements to the coherence-length analysis methods, there would have been significant impacts to the vehicle weight, cost, and schedule. If the load estimates turn out to be too low, there is significant risk of structural failure of the vehicle. This assessment used a combination of unsteady pressure-sensitive paint (uPSP), unsteady pressure transducers, and a dynamic force and moment balance to investigate the integration schemes used with limited unsteady pressure data by comparing them with direct integration of extremely dense fluctuating pressure measurements. An outfall of the assessment was to evaluate the potential of using the emerging uPSP technique in a production test environment for future launch vehicles. The results show that modifications to the current technique can improve the accuracy of buffet estimates. More importantly, the uPSP worked remarkably well and, with improvements to the frequency response, sensitivity, and productivity, will provide an enhanced method for measuring wind tunnel buffet forcing functions (BFFs).

Schuster, David M.↗