Lijun Xu

Bio: Lijun Xu is an academic researcher from Beihang University. The author has contributed to research in topics: Iterative reconstruction & Electrical capacitance tomography. The author has an hindex of 28, co-authored 316 publications receiving 2965 citations. Previous affiliations of Lijun Xu include The Royal Marsden NHS Foundation Trust & Peking University.

Laser absorption spectroscopy for combustion diagnosis in reactive flows: A review

Abstract: Laser absorption spectroscopy (LAS) has been rapidly developed and widely applied to combustion diagnosis in recent decades. As a cost-effective tool for measuring multiple combustion parameters, L...

Development of a fan-beam TDLAS-based tomographic sensor for rapid imaging of temperature and gas concentration

Abstract: This work aims to develop a fan-beam tomographic sensor using tunable diode lasers that can simultaneously image temperature and gas concentration with both high spatial and temporal resolutions. The sensor features three key advantages. First, the sensor bases on a stationary fan-beam arrangement, by which a high spatial resolution is guaranteed because the distance between two neighboring detectors in a view is approximately reduced to the size of a photodiode. Second, fan-beam illumination from five views is simultaneously generated instead of rotating either the fanned beams or the target, which significantly enhances the temporal resolution. Third, a novel set of optics with the combination of anamorphic prism pair and cylindrical lens is designed, which greatly improves the uniformity of the planar beams, and hence improves the reconstruction fidelity. This paper reports the tomographic model, optics design, numerical simulation and experimental validation of the sensor. The sensor exhibits good applicability for flame monitoring and combustion diagnosis.

MXenes: Synthesis, Optical Properties, and Applications in Ultrafast Photonics.

Abstract: Recently, 2D materials are in great demand for various applications such as optical devices, supercapacitors, sensors, and biomedicine. MXenes as a kind of novel 2D material have attracted considerable research interest due to their outstanding mechanical, thermal, electrical, and optical properties. Especially, the excellent nonlinear optical response enables them to be potential candidates for the applications in ultrafast photonics. Here, a review of MXenes synthesis, optical properties, and applications in ultrafast lasers is presented. First, aqueous acid etching and chemical vapor deposition methods for preparing MXenes are introduced, in which the storage stability and challenges of the existing synthesis techniques are also discussed. Then, the optical properties of MXenes are discussed specifically, including plasmonic properties, optical detection, photothermal effects, and ultrafast dynamics. Furthermore, the typical ultrafast pulsed lasers enabled by MXene-based saturable absorbers operated at different wavelength regions are summarized. Finally, a summary and outlook on the development of MXenes is presented in the perspectives section.

Reconstruction of Axisymmetric Temperature and Gas Concentration Distributions by Combining Fan-Beam TDLAS With Onion-Peeling Deconvolution

Abstract: Fan-beam tunable diode laser absorption spectroscopy (TDLAS) system was combined with onion-peeling deconvolution to reconstruct axisymmetric temperature and gas concentration distributions. The fan-beam TDLAS system consists of two tunable distributed feedback diode lasers at 7185.597 and 7444.36 cm -1 , a cylindrical lens and multiple photodiode detectors in a linear detector array. When a well-collimated laser beam penetrates through a cylindrical lens, a fan-beam laser was formed. Then, the fan-beam laser penetrates through the target region and is detected by the photodiode detectors in the detector array. After transforming the fan-beam geometry to equivalent parallel-beam geometry, axisymmetric temperature and gas concentration distributions can be reconstructed using the onion-peeling deconvolution. To obtain the reconstruction results with higher accuracy, a revised Tikhonov regularization method was adopted in the onion-peeling deconvolution. In this paper, numerical simulation and experimental verification were carried out to validate the feasibility of the proposed methods. The results show that the proposed methods can be used to on-line monitor the axisymmetric temperature and gas concentration distributions with higher accuracy and robustness in combustion diagnosis.

Online Cross-Sectional Monitoring of a Swirling Flame Using TDLAS Tomography

Abstract: The purpose of this paper is to monitor the dynamic cross-sectional behavior of swirling flames using the tunable diode laser absorption spectroscopy (TDLAS) tomographic system. The newly developed online and highly spatially resolved imaging system based on TDLAS tomography was employed to monitor and reveal directly the reaction process in the swirling flame by reconstructing the 2-D distributions of temperature and H2O concentration over a cross section of the flame. The system was demonstrated to be capable of capturing the temperature distribution accurately and inferring the thermal expansion over the cross section of interest in the swirling flame generated by a model swirl injector operating in partially premixed combustion mode. As the equivalence ratio was decreased, thermal oscillations extracted from the real-time 2-D reconstructions were used to infer the instability of the swirling flame. Furthermore, the developed system was applied to capture dynamically the process of blowout of the swirling flame, illustrating that the system can provide firsthand and reliable visual data to help prevent the flame from lean blowout (LBO). This paper reports the first experimental observation of the dynamic cross-sectional behavior of the swirling flame, enabled by the high spatial and temporal resolutions provided by the TDLAS tomographic imaging system. The developed system can help better understand the LBO mechanism so as to improve the performance of low-emission gas turbine combustors.

Fourier-transform method of fringe-pattern analysis for computer-based topography and interferometry

Abstract: A fast-Fourier-transform method of topography and interferometry is proposed. By computer processing of a noncontour type of fringe pattern, automatic discrimination is achieved between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour-generation techniques. The method has advantages over moire topography and conventional fringe-contour interferometry in both accuracy and sensitivity. Unlike fringe-scanning techniques, the method is easy to apply because it uses no moving components.

Artificial neural networks

Abstract: Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

A reflectance model for computer graphics

Abstract: This paper presents a new reflectance model for rendering computer synthesized images. The model accounts for the relative brightness of different materials and light sources in the same scene. It describes the directional distribution of the reflected light and a color shift that occurs as the reflectance changes with incidence angle. The paper presents a method for obtaining the spectral energy distribution of the light reflected from an object made of a specific real material and discusses a procedure for accurately reproducing the color associated with the spectral energy distribution. The model is applied to the simulation of a metal and a plastic.

Regularization Of Inverse Problems

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