OH and Soot Optical Diagnostics for Combustion Applications for Combustion Applications

Optical diagnostics are remote non-intrusive sensing techniques. The thesis work concerns the use of OH and soot optical diagnostics for combustion research.Internal combustion (IC) engines are widely used for the generation of power and for transportation purposes. Soot emission, involving carbon particles that emanate from the combustion process, is one of major sources of pollutants in engine exhaust. Such particles can be inhaled into human lungs and have been found to be harmful to public health. For this reason, soot emissions from IC engines are strictly regulated. The flame lift-off length (LOL) of a diesel jet, which is the distance between the nozzle of the injector and the base of the flame, affects both diesel combustion and emission formation. The presence of OH radicals has been used commonly for determining LOL. Both the 2D imaging of OH* chemiluminescence and OH-laser-induced fluorescence (LIF) were employed here for determining the LOL of diesel spray flame. Laser extinction measurements (LEM), together with measurements of the natural luminosity (NL) of sooty flames and of laser-induced incandescence (LII) were made use of for in-cylinder soot detection in the thesis. The main goal in the use of optical diagnostics in engines was to answer various engine-related questions. The optical techniques and the data processing methods employed in the thesis work were also improved parallel to one another. The online/offline OH* chemiluminescence method that was used was able to successfully reduce part of the soot luminosity of the OH* chemiluminescence image obtained. A comparison of LOL results obtained on the basis of simultaneous OH* chemiluminescence and OH-LIF images was carried out. The OH-LIF resulted statistically in longer LOL than the OH*chemiluminescence results did. This can be partially explained by the difference between the two methods in the probing volumes and the flame asymmetry. A data correction for the LEM results was developed, one that helped to reduce the effects of the fluctuations in the probing laser intensities and the soot deposits on the optical window. Simultaneous OH-PLIF and soot-LII was performed for studying the soot oxidation process in the recirculation zone of a diesel optical engine. In addition to the optical diagnostics applied to the optical engines that were studied, simultaneous dual species PLIF techniques were developed and made use of in the thesis work. Splitting the beam from the multi-YAG laser into two, the one used to pump OPO and the other used directly for formaldehyde (CH2O) excitation, made the simultaneous probing of two species at a high repetition rate possible. Simultaneous OH and CH2O-PLIF was performed for demonstrations at a repetition rate of 50 kHz. The Frequency Recognition Algorithm for Multiple Exposure (FRAME) approach was also introduced. Through the use of structured illumination, FRAME permits several laser-induced signals to be superimposed upon a single detector

Invariant theory of ı\imathquantum groups of type AIII

We develop an invariant theory of quasi-split $\imath$quantum groups \mathbf{U}_n^\imath of type AIII on a tensor space associated to $\imath$Howe dualities. The first and second fundamental theorems for \mathbf{U}_n^\imath-invariants are derived.Comment: 15 page

Seen to Unseen: When Fuzzy Inference System Predicts IoT Device Positioning Labels That Had Not Appeared in Training Phase

Situating at the core of Artificial Intelligence (AI), Machine Learning (ML), and more specifically, Deep Learning (DL) have embraced great success in the past two decades. However, unseen class label prediction is far less explored due to missing classes being invisible in training ML or DL models. In this work, we propose a fuzzy inference system to cope with such a challenge by adopting TSK+ fuzzy inference engine in conjunction with the Curvature-based Feature Selection (CFS) method. The practical feasibility of our system has been evaluated by predicting the positioning labels of networking devices within the realm of the Internet of Things (IoT). Competitive prediction performance confirms the efficiency and efficacy of our system, especially when a large number of continuous class labels are unseen during the model training stage.Comment: Accepted by International Conference on Internet of Things, Big Data and Security (IoTBDS) 202

Grooming Detection using Fuzzy-Rough Feature Selection and Text Classification

Online child grooming detection has recently attracted intensive research interests from both the machine learning community and digital forensics community due to its great social impact. The existing data-driven approaches usually face the challenges of lack of training data and the uncertainty of classes in terms of the classification or decision boundary. This paper proposes a grooming detection approach in an effort to address such uncertainty based on a data set derived from a publicly available profiling data set. In particular, the approach firstly applies the conventional text feature extraction approach in identifying the most significant words in the data set. This is followed by the application of a fuzzy-rough feature selection approach in reducing the high dimensions of the selected words for fast processing, which at the same time addressing the uncertainty of class boundaries. The experimental results demonstrate the efficiency and efficacy

Spatio-Temporal Progression of Two-Stage Autoignition for Diesel Sprays in a Low-Reactivity Ambient: n-Heptane Pilot-Ignited Premixed Natural Gas

[EN] The spatial and temporal locations of autoignition depend on fuel chemistry and the temperature, pressure, and mixing trajectories in the fuel jets. Dual-fuel systems can provide insight into fuel-chemistry aspects through variation of the proportions of fuels with different reactivities, and engine operating condition variations can provide information on physical effects. In this context, the spatial and temporal progression of two-stage autoignition of a diesel-fuel surrogate, n-heptane, in a lean-premixed charge of synthetic natural gas (NG) and air is imaged in an optically accessible heavy-duty diesel engine. The lean-premixed charge of NG is prepared by fumigation upstream of the engine intake manifold. Optical diagnostics include: infrared (IR) imaging for quantifying both the in-cylinder NG concentration and the pilot-jet penetration rate and spreading angle, high-speed cool-flame chemiluminescence imaging as an indicator of low-temperature heat release (LTHR), and high-speed OH* chemiluminescence imaging as an indicator high-temperature heat release (HTHR). To aid interpretation of the experimental observations, zero-dimensional chemical kinetics simulations provide further understanding of the underlying interplay between the physical and chemical processes of mixing (pilot fuel-jet entrainment) and autoignition (two-stage ignition chemistry). Increasing the premixed NG concentration prolongs the ignition delay of the pilot fuel and increases the combustion duration. Due to the relatively short pilot-fuel injections utilized, the transient increase in entrainment near the end of injection (entrainment wave) plays an important role in mixing. To achieve desired combustion characteristics, i.e., ignition and combustion timing (e.g., for combustion phasing) and location (e.g., for reducing wall heat-transfer or tailoring charge stratification), injection parameters can be suitably selected to yield the necessary mixing trajectories that potentially help offset changes in fuel ignition chemistry, which could be a valuable tool for combustion design.This research was sponsored by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE). Optical engine experiments were conducted at the Combustion Research Facility of Sandia National Laboratories in Livermore, CA. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration (NNSA) under contract DE-NA0003525. We gratefully acknowledge the contributions of Keith Penney and Dave Cicone for their assistance in developing research tools and maintaining the optical engine.Rajasegar, R.; Niki, Y.; García-Oliver, JM.; Li, Z.; Musculus, M. (2021). Spatio-Temporal Progression of Two-Stage Autoignition for Diesel Sprays in a Low-Reactivity Ambient: n-Heptane Pilot-Ignited Premixed Natural Gas. SAE International. 1-16. https://doi.org/10.4271/2021-01-052511