Soot volume fraction profiling of asymmetric diffusion flames through tomographic imaging

This paper presents the 3-D (three-dimensional) reconstruction of soot volume fraction of diffusion flames based on tomographic imaging and image processing techniques. Eight flexible imaging fiber bundles and two RGB (Red, Green and Blue) CCD (Charge-coupled Device) cameras are used to obtain concurrently the 2-D (two-dimensional) image projections of the flame from eight different angles of view around the burner. Algorithms which combine the tomographic and two-color pyrometric techniques are utilized to reconstruct the soot volume fraction distributions on both cross- and longitudinal-sections of the flame. A series of experiments were carried out on a gas-fired combustion rig for the determination of soot volume fraction using the algorithms proposed. Test results demonstrate the effectiveness of the developed algorithms

Two-Dimensional Tomographic Simultaneous Multi-Species Visualization—Part I: Experimental Methodology and Application to Laminar and Turbulent Flames

In recent years, the tomographic visualization of laminar and turbulent flames has received much attention due to the possibility of observing combustion processes on-line and with high temporal resolution. In most cases, either the spectrally non-resolved flame luminescence or the chemiluminescence of a single species is detected and used for the tomographic reconstruction. In this work, we present a novel 2D emission tomographic setup that allows for the simultaneous detection of multiple species (e.g., OH*, CH* and soot but not limited to these) using a single image intensified CCD camera. We demonstrate the simultaneous detection of OH* (310 nm), CH* (430 nm) and soot (750 nm) in laminar methane/air, as well as turbulent methane/air and ethylene/air diffusion flames. As expected, the reconstructed distributions of OH* and CH* in laminar and turbulent flames are highly correlated, which supports the feasibility of tomographic measurements on these kinds of flames and at timescales down to about 1 ms. In addition, the possibilities and limitations of the tomographic approach to distinguish between locally premixed, partially premixed and non-premixed conditions, based on evaluating the local intensity ratio of OH* and CH* is investigated. While the tomographic measurements allow a qualitative classification of the combustion conditions, a quantitative interpretation of instantaneous reconstructed intensities (single shot results) has a much greater uncertainty

Visualization and imaging methods for flames in microgravity

The visualization and imaging of flames has long been acknowledged as the starting point for learning about and understanding combustion phenomena. It provides an essential overall picture of the time and length scales of processes and guides the application of other diagnostics. It is perhaps even more important in microgravity combustion studies, where it is often the only non-intrusive diagnostic measurement easily implemented. Imaging also aids in the interpretation of single-point measurements, such as temperature, provided by thermocouples, and velocity, by hot-wire anemometers. This paper outlines the efforts of the Microgravity Combustion Diagnostics staff at NASA Lewis Research Center in the area of visualization and imaging of flames, concentrating on methods applicable for reduced-gravity experimentation. Several techniques are under development: intensified array camera imaging, and two-dimensional temperature and species concentrations measurements. A brief summary of results in these areas is presented and future plans mentioned

Two-dimensional tomographic simultaneous multispecies visualization—Part II: Reconstruction accuracy

Recently we demonstrated the simultaneous detection of the chemiluminescence of the radicals OH* (310 nm) and CH* (430 nm), as well as the thermal radiation of soot in laminar and turbulent methane/air diffusion flames. As expected, a strong spatial and temporal coupling of OH* and CH* in laminar and moderate turbulent flames was observed. Taking advantage of this coupling, multispecies tomography enables us to quantify the reconstruction quality completely independent of any phantom studies by simply utilizing the reconstructed distribution of both species. This is especially important in turbulent flames, where it is difficult to separate measurement noise from turbulent fluctuations. It is shown that reconstruction methods based on Tikhonov regularization should be preferred over the widely used algebraic reconstruction technique (ART) and multiplicative algebraic reconstruction techniques (MART), especially for high-speed imaging or generally in the limit of low signal-to-noise ratio

3D particle tracking velocimetry using dynamic discrete tomography

Particle tracking velocimetry in 3D is becoming an increasingly important imaging tool in the study of fluid dynamics, combustion as well as plasmas. We introduce a dynamic discrete tomography algorithm for reconstructing particle trajectories from projections. The algorithm is efficient for data from two projection directions and exact in the sense that it finds a solution consistent with the experimental data. Non-uniqueness of solutions can be detected and solutions can be tracked individually

Imaging of solid flow in a gravity flow rig using infra-red tomography

Information on flow regimes is vital in the analysis and measurement of industrial process flow. Almost all currently available method of measuring the flow of two-component mixtures in industrial pipelines endeavors to average a property of the flow over the pipe cross-section. They do not give information on the nature of the flow regime and they are unsuitable for accurate measurement where the component distribution is spatially or time varying. The overall aim of this project is to investigate the use of an optical tomography method based on infra-red sensors for real-time monitoring of solid particles conveyed by a rotary valve in a pneumatic pipeline. The infra-red tomography system can be divided into two distinct portions of hardware and software development process. The hardware development process covers the infra-red sensor selection, fixtures and signals conditioning circuits, and control circuits. The software development involves data acquisition system, sensor modeling, image algorithms, and programming for a tomographic display to provide solids flow information in pipeline such as concentration and velocity profiles. Collimating the radiated beam from a light source and passing it via a flow regime ensures that the intensity of radiation detected on the opposite side is linked to the distribution and the absorption coefficients of the different phases in the path of the beam. The information is obtained from the combination of two orthogonal and two diagonal light projection system and 30 cycles of real-time measurements. Those information on the flow captured using upstream and downstream infra-red sensors are digitized by the DAS system before it was passed into a computer for analysis such as image reconstructions and cross-correlation process that provide velocity profiles represented by 16 × 16 pixels mapped onto the pipe cross-section. This project successfully developed and tested an infra-red tomography system to display two-dimensional images of concentration and velocity

Tomographic Laser Absorption Imaging of Combustion Gases in the Mid-wave Infrared

This dissertation describes advancements in mid-infrared laser absorption tomography for spatio-temporal measurements of thermochemistry in reacting flows relevant to combustion systems. Tunable laser absorption spectroscopy is combined with tomographic reconstruction techniques to resolve small diameter ( < 1 cm) non-uniform flow fields with steep spatial gradients, leveraging emerging mid-wave infrared photonics. Multiple novel measurement methods, hardware configurations, and image processing techniques were investigated. Initially, a mid-infrared laser absorption tomography sensing method was developed for quantitative measurement of CO and CO2 concentrations and temperature distributions in turbulent premixed jet flames using a translation-stage-mounted optical system. This sensing approach was used to examine effects of varying fuel structure on carbon oxidation over a range of Reynolds number regimes. It was found that spatial and temporal resolution is limited in this method due to the finite laser beam size (~ 1 mm) and the slow mechanical translation of the optical system. To address these limitations, a novel laser absorption imaging (LAI) technique, that expands a single laser beam and replaces the detector with a high-speed infrared camera, was introduced to achieve enhanced spatial and temporal resolution for thermo-chemical imaging. As a demonstration of this new technique, distributions of combustion species were imaged in both axisymmetric and non-axisymmetric flow fields using linear tomography algorithms. For non-axisymetric flows, the limited view tomography problem often results in a blurring effect and artifacts in the reconstructed flow-field. In an effort to address these issues, state-of-the-art deep learning neural networks were developed and applied to solve the limited angle inversion. Initial results suggest that deep neural networks have potential to more accurately predict flame structures with fewer projection angles than linear tomography. This work provides a foundation for a new approach to quantitative time-resolved 3D thermo-chemical imaging in high-temperature reacting flows