Direct comparison of two-dimensional and three-dimensional laser-induced fluorescence measurements on highly turbulent flames

Simultaneous two-plane flame front detection using PIV based on defocusing

This Letter presents a simultaneous two-plane flame front detection method. It is based on a standard single-camera single-plane particle image velocimetry (PIV) system in combination with an inexpensive and compact image splitting device. The image splitting optics places images from two depth-offset planes onto the two halves of a camera sensor. A shallow depth of field ensures only one plane is in focus on each half of the sensor. By using a high-pass filter and a novel two-step filter we have devised, the out-of-focus particle images are effectively removed, while the in-focus particle images remain, allowing the turbulent flame fronts on two planes to be detected simultaneously. Our approach could be combined with conventional polarization/wavelength discrimination methods to achieve simultaneous multi-plane flame front reconstruction with similarly high in-plane spatial resolution to single-plane measurement and is suitable for practical combustion devices with limited optical access.

The 3D Modeling System for Bioaerosol Distribution Based on Planar Laser-Induced Fluorescence

Although it is quite challenging to image and analyze the spatial distribution of bioaerosols in a confined space, a three-dimensional (3D) modeling system based on the planar laser-induced fluorescence (PLIF) technique is proposed in this paper, which is designed to analyze the temporal and spatial variations of bioaerosol particles in a confined chamber. The system employs a continuous planar laser source to excite the fluoresce, and a scientific complementary metal oxide semiconductor (sCMOS) camera to capture images of 2048 × 2048 pixels at a frame rate of 12 Hz. While a sliding platform is moving back and forth on the track, a set of images are captured at different positions for 3D reconstruction. In this system, the 3D reconstruction is limited to a maximum measurement volume of about 50 cm × 29.7 cm × 42 cm, with a spatial resolution of about 0.58 mm × 0.82 mm × 8.33 mm, and a temporal resolution of 5 s. Experiments were carried out to detect the PLIF signals from fluorescein aerosols in the chamber, and then 3D reconstruction was used to visualize and analyze the diffusion of aerosol particles. The results prove that the system can be applied to clearly reconstruct the 3D distribution and record the diffusion process of aerosol particles in a confined space.

Development and validation of a reconstruction approach for three-dimensional confined-space tomography problems

This work reports the development and validation of a new tomography approach, termed cross-interfaces computed tomography (CICT), to address confined-space tomography problems. Many practical tomography problems require imaging through optical walls, which may encounter light refractions that seriously influence the imaging process and deteriorate the three-dimensional (3D) reconstruction. Past efforts have primarily focused on developing open-space tomography algorithms, but these algorithms are not extendable to confined-space problems unless the imaging process from the 3D target and its line-of-sight two-dimensional (2D) images (defined as "projections") is properly adjusted. The CICT approach is therefore proposed in this work to establish an algorithm describing the mapping relationship between the optical signal field of the target and its projections. The CICT imaging algorithm is first validated by quantitatively comparing measured and simulated projections of a calibration plate through an optical cylinder. Then the CICT reconstruction is numerically and experimentally validated using a simulated flame phantom and a laminar cone flame, respectively. Compared to reconstructions formed by traditional open-space tomography, the CICT approach is demonstrated to be capable of resolving confined-space problems with significantly improved accuracy.

Data-driven three-dimensional super-resolution imaging of a turbulent jet flame using a generative adversarial network

Three-dimensional (3D) computed tomography (CT) is becoming a well-established tool for turbulent combustion diagnostics. However, the 3D CT technique suffers from contradictory demands of spatial resolution and domain size. This work therefore reports a data-driven 3D super-resolution approach to enhance the spatial resolution by two times along each spatial direction. The approach, named 3D super-resolution generative adversarial network (3D-SR-GAN), builds a generator and a discriminator network to learn the topographic information and infer high-resolution 3D turbulent flame structure with a given low-resolution counterpart. This work uses numerically simulated 3D turbulent jet flame structures as training data to update model parameters of the GAN network. Extensive performance evaluations are then conducted to show the superiority of the proposed 3D-SR-GAN network, compared with other direct interpolation methods. The results show that a convincing super-resolution (SR) operation with the overall error of ∼4% and the peak signal-to-noise ratio of 37 dB can be reached with an upscaling factor of 2, representing an eight times enhancement of the total voxel number. Moreover, the trained network can predict the SR structure of the jet flame with a different Reynolds number without retraining the network parameters.

Development of a modular, high-speed plenoptic-camera for 3D flow-measurement

This paper describes the development of a Modular Plenoptic Adaptor (MPA) for rapid and reversible conversion of high-speed cameras into plenoptic imaging systems, with the primary goal of enabling single-camera, time-resolved 3D flow-measurements. The MPA consists of a regular imaging lens, a microlens array, a tilt-adjustable microlens mount and an optical relay, which are collectively installed onto a high-speed camera through a standard lens mount. Each component within the system is swappable to optimize for specific imaging applications. In this study, multiple configurations of the MPA were tested and they demonstrated the ability to refocus and shift perspectives within high-speed scenes after capture. Additionally, the MPA demonstrated 3D reconstruction of captured scenes with <1% spatial error across a volume spanning approximately 50×30×50mm3. Finally, the MPA also demonstrated reconstruction of a 3D droplets-field with sufficient quality to support qualitatively accurate plenoptic particle image velocimetry (PPIV) calculations.

3D tomography reconstruction improved by integrating view registration

Tomographic measurements involve two steps: view registration (VR) to determine the orientation of the projections and the subsequent tomography reconstruction. Therefore, the practical error in both steps impacts the overall accuracy of the final tomographic measurements. Past work treated these two steps separately. This work shows that the overall tomography accuracy can be enhanced substantially if these two steps are considered holistically because there is an opportunity for each step to leverage the information in the other step to improve the overall accuracy if they are considered holistically. Based on this recognition, this work has developed a new method called the reconstruction integration view registration (RIVR) method to implement such a holistic scheme. The key of this implementation involved the use of the Metropolis criterion to adjust the initial orientation provided by the traditional VR process dynamically. Both controlled experiments and accompanying numerical analyses were conducted to validate the RIVR method. Two sets of controlled experiments were conducted and analyzed, including a static uniform dye solution and turbulent flows, where the RIVR technique was demonstrated to significantly reduce the overall reconstruction error (by ∼37% and ∼35%, respectively) compared to past methods that treated VR and tomography separately.

Hybrid diagnostic for optimizing domain size and resolution of 3D measurements

This Letter reports a hybrid three-dimensional (3D) visualization approach for turbulent flows at the kilohertz range. The approach, named scanning volumetric laser induced fluorescence (SVLIF), combines 3D tomography with scanning to significantly enhance spatial resolution of 3D measurements in a given domain (or equivalently, to enlarge the domain size under a given resolution) compared to past tomographic approaches. The SVLIF technique (1) divides a large measurement domain into smaller sub-domains, (2) performs 3D tomographic measurement in each sub-domain by scanning the excitation laser pulses across them consecutively, and (3) combines the measurements in all sub-domains to form a final measurement. This hybrid approach enables the conversion of temporal resolution into spatial resolution or domain size to optimize 3D measurements in a wider design space. In this work, the SVLIF was demonstrated and validated at a scanning rate of 1.86 kHz in a volume of 38.4  mm×26.5  mm×25.2  mm with 7.1 million voxels, representing a ∼5 times enhancement in the number of voxels or the domain size compared to past tomographic techniques.

Two-color volumetric laser-induced fluorescence for 3D OH and temperature fields in turbulent reacting flows

Single-shot, two-color, volumetric laser-induced fluorescence was demonstrated for three-dimensional (3D), tomographic imaging of the structural properties of the OH radical and temperature field in a turbulent hydrogen-air flame. Two narrowband laser sources were tuned to the Q₁(5) and Q₁(14) transitions of the (1,0) band in the A²Σ←X²Π system and illuminated a volumetric region of the flame. Images from eight unique perspectives collected simultaneously from each of the two transitions were used to reconstruct overlapping OH fields with different Boltzmann fractions and map the 3D temperature distribution with nanosecond precision. Key strategies for minimizing sources of error, such as detector sensitivity and spatial overlap of the two fields, are discussed.

Rapid tomographic reconstruction based on machine learning for time-resolved combustion diagnostics

Optical tomography has attracted surged research efforts recently due to the progress in both the imaging concepts and the sensor and laser technologies. The high spatial and temporal resolutions achievable by these methods provide unprecedented opportunity for diagnosis of complicated turbulent combustion. However, due to the high data throughput and the inefficiency of the prevailing iterative methods, the tomographic reconstructions which are typically conducted off-line are computationally formidable. In this work, we propose an efficient inversion method based on a machine learning algorithm, which can extract useful information from the previous reconstructions and build efficient neural networks to serve as a surrogate model to rapidly predict the reconstructions. Extreme learning machine is cited here as an example for demonstrative purpose simply due to its ease of implementation, fast learning speed, and good generalization performance. Extensive numerical studies were performed, and the results show that the new method can dramatically reduce the computational time compared with the classical iterative methods. This technique is expected to be an alternative to existing methods when sufficient training data are available. Although this work is discussed under the context of tomographic absorption spectroscopy, we expect it to be useful also to other high speed tomographic modalities such as volumetric laser-induced fluorescence and tomographic laser-induced incandescence which have been demonstrated for combustion diagnostics.

On the quantification of spatial resolution for three-dimensional computed tomography of chemiluminescence

Three-dimensional computed tomography of chemiluminescence (CTC) for combustion diagnostics is attracting a surged research interest due to recent progress in sensor technologies and reduced costs of high-speed cameras. For example, it has been applied to recover the 3D distributions of intermediate chemical species such as CH* and OH*, heat release rate, and flame topology. Although these applications were demonstrated to be successful, there are still a few drawbacks of this technique that have not be cured. For example, to the best of the authors' knowledge, all the imaging models that have been developed so far ignore the imperfections of cameras such as lens distortion and skewness. However, this will unavoidably introduce errors into the weight matrix. In addition, spatial resolution of a CTC system is a critical performance parameter. However, it has only been studied qualitatively and no quantitative quantification method is reported so far. This work aims to solve these problems by improving the imaging model and developing a method based on edge spread function for the quantification of spatial resolution. Although this work is conducted under the context of CTC for combustion diagnostics, it also provides useful insights for other tomographic modalities such as volumetric laser-induced fluorescence and tomographic laser-induced incandescence.

4D spatiotemporal evolution of combustion intermediates in turbulent flames using burst-mode volumetric laser-induced fluorescence

High-speed (20 kHz rate), volumetric laser-induced-fluorescence imaging of combustion intermediates such as a formaldehyde (CH₂O) and polycyclic aromatic hydrocarbon (PAH) species is demonstrated for tracking the four-dimensional (4D) evolution of turbulent flames. The third-harmonic, 355 nm output of a burst-mode Nd:YAG laser with a 130 mJ/pulse is expanded to 30 mm diameter for volume illumination of the base region of a methane-hydrogen jet diffusion flame. Eight simultaneous images from different viewing angles are used to collect the resulting fluorescence signal for reconstruction of 200 time-sequential three-dimensional volumes over 10 ms duration. The signal-to-noise ratio (SNR) of 300:1 is achieved after reconstruction with a temporal resolution of 100 ns and spatial resolution of 0.85-1.5 mm.