Gaffney, R. L. | Search NASA

NASA NTRS2012

Spatially Resolved Temperature and Water Vapor Concentration Distributions in Supersonic Combustion Facilities by TDLAT

Detailed knowledge of the internal structure of high-enthalpy flows can provide valuable insight to the performance of scramjet combustors. Tunable Diode Laser Absorption Spectroscopy (TDLAS) is often employed to measure temperature and species concentration. However, TDLAS is a path-integrated line-of-sight (LOS) measurement, and thus does not produce spatially resolved distributions. Tunable Diode Laser Absorption Tomography (TDLAT) is a non-intrusive measurement technique for determining two-dimensional spatially resolved distributions of temperature and species concentration in high enthalpy flows. TDLAT combines TDLAS with tomographic image reconstruction. More than 2500 separate line-of-sight TDLAS measurements are analyzed in order to produce highly resolved temperature and species concentration distributions. Measurements have been collected at the University of Virginia's Supersonic Combustion Facility (UVaSCF) as well as at the NASA Langley Direct-Connect Supersonic Combustion Test Facility (DCSCTF). Due to the UVaSCF s unique electrical heating and ability for vitiate addition, measurements collected at the UVaSCF are presented as a calibration of the technique. Measurements collected at the DCSCTF required significant modifications to system hardware and software designs due to its larger measurement area and shorter test duration. Tomographic temperature and water vapor concentration distributions are presented from experimentation on the UVaSCF operating at a high temperature non-reacting case for water vitiation level of 12%. Initial LOS measurements from the NASA Langley DCSCTF operating at an equivalence ratio of 0.5 are also presented. Results show the capability of TDLAT to adapt to several experimental setups and test parameters.

Busa, K. M.↗

NASA NTRS2007

The Art of Extracting One-Dimensional Flow Properties from Multi-Dimensional Data Sets

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e:g: thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

Baurle, R. A.↗