The FLITES project (Fiber-Laser Imaging of gas Turbine Exhaust Species) aims to provide a videorate imaging (100 fps) diagnostic tool for application to the exhaust plumes of the largest civil aero-jet engines. This remit, enabled by chemical species tomography (CST) currently targeting Carbon Dioxide (CO2), requires system design that facilitates expansion of multiple parameters. Scalability is needed in order to increase imaging speeds and spatial resolutions and extend the system towards other pertinent gases such as the oxides of Nitrogen and Sulphur and unburnt hydrocarbons. This paper presents a fully-scalable, non-invasive instrument for installation in a commercial engine testing facility, technical challenges having been tackled iteratively through bespoke optical and mechanical design, and it specifically presents the high-speed data acquisition system (DAQ) required. Measurement of gas species concentration is implemented by tunable diode laser absorption with wavelength modulation spectroscopy (TDLAS-WMS) using a custom, high-speed 10-40 MS/s/channel 14-bit DAQ. For CO2 tomography, the system uses 6 angular projections of 21 beams each. However, the presented DAQ has capacity for 192 fully-parallel 10-Hz to 3-MHz differential inputs, achieving a best-case SNR of 56.5 dB prior to filtering. Twelve Ethernet-connected digitization nodes based on field-programmable gate array (FPGA) technology with software control, are distributed around a 7-m diameter mounting "ring". Hence, the high data rates of 8.96-Gb/s per printed circuit board (PCB) and 107.52 Gb/s for the whole system, can be reduced using local digital lock-in amplifiers (DLIAs). We believe this DAQ system is unique in both the TDLAS and CST literature.

We consider the inverse problem of concentration imaging in optical absorption tomography with limited data sets. The measurement setup involves simultaneous acquisition of near-infrared wavelength-modulated spectroscopic measurements from a small number of pencil beams equally distributed among six projection angles surrounding the plume. We develop an approach for image reconstruction that involves constraining the value of the image to the conventional concentration bounds and a projection into low-dimensional subspaces to reduce the degrees of freedom in the inverse problem. Effectively, by reparameterizing the forward model, we impose, simultaneously, spatial smoothness and a choice among three types of inequality constraints, namely, positivity, boundedness, and logarithmic boundedness in a simple way that yields an unconstrained optimization problem in a new set of surrogate parameters. Testing this numerical scheme with simulated and experimental phantom data indicates that the combination of affine inequality constraints and subspace projection leads to images that are qualitatively and quantitatively superior to unconstrained regularized reconstructions. This improvement is more profound in targeting concentration profiles of small spatial variation. We present images and convergence graphs from solving these inverse problems using Gauss-Newton's algorithm to demonstrate the performance and convergence of our method.

A calibration-free first harmonic (1f) wavelength modulation spectroscopy (1f-WMS) technique for gas species parameter measurement is demonstrated. In this technique, the total magnitude of the 1f-WMS signal is normalized by a component of the 1f residual amplitude modulation signal. This method preserves the advantages of the traditional nf/1f-WMS (n ≥ 2) technique, such as the immunity to the non-absorbing systematic losses and the accurate recovery of gas parameters, without the requirement for non-absorbing regions for normalization at high pressure or high modulation index values (m-values). The proposed technique only requires the 1f signal, which has the largest magnitude of all the harmonics signals, and, therefore, fundamentally has a higher sensitivity to the nf/1f technique. Furthermore, since only the 1f-WMS signal is used, the technique is less complex in terms of signal processing and data acquisition. This paper also shows a comparison of the proposed technique and 2f /1f for measuring CO 2 in the exhaust of a combuster. The data highlight how nonlinearities in the optical detection system as a function of frequency have a considerable effect on the recovered 2f/1f spectra, causing variation in the recovered gas concentrations. This effect is not seen in the methodology proposed in this paper.

This paper is concerned with an investigation of the formation of soot from the combustion of some of the primary pyrolysis products formed during pine wood combustion. Comparisons are made between the combustion products of model compounds, furfural for cellulose and eugenol and anisole to represent lignin (and n-decane for comparison) with the smoke emissions from the previously studied combustion of pine wood. These compounds were burned in a diffusion flame burner, and the appearance and composition of the resulting particulate and the adsorbed polynuclear aromatic hydrocarbon (PAH) precursors were studied by transmission electron microscopy (TEM), mass spectrometry and pyrolysis gas chromatography mass spectrometry (Py-GC-MS). The reactions leading to soot formation were modeled. It was concluded that wood soot formation proceeded via pyrolytic breakdown followed by a mechanism based on HACA (H-abstraction−C 2 H 2addition) reactions with the participation of cyclopentadienyl intermediates, while eugenol soot originated predominantly through the CPDyl route. The formation of furfural soot is mainly via HACA.