scholarly journals Experimental and low-dimensional numerical study on the application of conventional NOx reduction methods in pulse detonation combustion

2021 ◽  
Vol 233 ◽  
pp. 111593
Author(s):  
Niclas Garan ◽  
Neda Djordjevic
Author(s):  
Niclas Hanraths ◽  
Fabian Tolkmitt ◽  
Phillip Berndt ◽  
Neda Djordjevic

Recently, the focus has been laid on the characteristics of pollutant emissions from pulse detonation combustion. Initial studies indicate possibly high nitrogen oxides (NOx) emissions, so the assessment of potential primary reduction methods is advisable. The present work considers the following reduction methods: lean combustion, nitrogen and steam dilution as well as flue gas recirculation. Since such changes in the combustion mixture reduce its reactivity and thus detonability, they can impair a reliable operation in technical systems. In order to explore the potential and limitations of each of these reduction methods, they are compared for mixtures featuring an identical characteristic detonation cell size at given initial conditions. Furthermore, building upon the use of steam dilution, a modified method to add steam to the combustible mixture is investigated. In order to avoid the strong reduction of mixture detonability by steam addition and ensure a robust detonation formation, steam is injected into the already developed detonation front. It was found that, for sufficiently even steam distribution, NOx reduction comparable to a premixed dilution could be achieved. This approach enables the realization of NOx reduction in pulse detonation combustion also for such conditions, for which premix dilution is not feasible. Therefore, combining the premix dilution with post-shock injection offers a promising strategy to substantially reduce NOx emissions from pulse detonation combustion, while at the same time ensuring its reliable operation.


Author(s):  
Niclas Hanraths ◽  
Fabian Tolkmitt ◽  
Phillip Berndt ◽  
Neda Djordjevic

Recently, the focus has been laid on the characteristics of pollutant emissions from pulse detonation combustion (PDC). Initial studies indicate possibly high nitrogen oxides (NOx) emissions, so the assessment of potential primary reduction methods is advisable. The present work considers the following reduction methods: lean combustion, nitrogen and steam dilution, as well as flue gas recirculation. Since such changes in the combustion mixture reduce its reactivity and thus detonability, they can impair a reliable operation in technical systems. In order to explore the potential and limitations of each of these reduction methods, they are compared for mixtures featuring an identical characteristic detonation cell size at given initial conditions. Furthermore, building upon the use of steam dilution, a modified method to add steam to the combustible mixture is investigated. In order to avoid the strong reduction of mixture detonability by steam addition and ensure a robust detonation formation, steam is injected into the already developed detonation front. It was found that, for sufficiently even steam distribution, NOx reduction comparable to a premixed dilution could be achieved. This approach enables the realization of NOx reduction in PDC also for such conditions, for which premix dilution is not feasible. Therefore, combining the premix dilution with postshock injection offers a promising strategy to substantially reduce NOx emissions from PDC, while at the same time ensuring its reliable operation.


2012 ◽  
Vol 602-604 ◽  
pp. 1317-1324
Author(s):  
Yao Xun Feng ◽  
Xiao Feng Zheng ◽  
Ming Sheng Jia

In this study, a methane/oxygen-enriched air counterflow diffusion flame was analyzed numerically using detailed chemical kinetics, on the condition that the oxygen mass fraction in the oxidizer stream varied from 21% to 99%. The obtained results show that as the oxygen concentration in air increases, the maximum temperature increases; the region of combustion reaction is gradually divided into two parts, and the total NO production rate and especially the thermal NO production rate increase greatly. With consideration of the possibility of gas recirculation to minimize NOX in the industrial combustor, the usefulness of NOX reduction in combustion was analyzed numerically when the methane stream was diluted with the inert gases N2 or CO2. The obtained results show that the flame structure and dominant mechanism of NO formation change greatly with the concentration of diluents in fuel; the emission index of NO decreases gradually when the concentration of diluent CO2 increases.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Joshua T. Vogelstein ◽  
Eric W. Bridgeford ◽  
Minh Tang ◽  
Da Zheng ◽  
Christopher Douville ◽  
...  

AbstractTo solve key biomedical problems, experimentalists now routinely measure millions or billions of features (dimensions) per sample, with the hope that data science techniques will be able to build accurate data-driven inferences. Because sample sizes are typically orders of magnitude smaller than the dimensionality of these data, valid inferences require finding a low-dimensional representation that preserves the discriminating information (e.g., whether the individual suffers from a particular disease). There is a lack of interpretable supervised dimensionality reduction methods that scale to millions of dimensions with strong statistical theoretical guarantees. We introduce an approach to extending principal components analysis by incorporating class-conditional moment estimates into the low-dimensional projection. The simplest version, Linear Optimal Low-rank projection, incorporates the class-conditional means. We prove, and substantiate with both synthetic and real data benchmarks, that Linear Optimal Low-Rank Projection and its generalizations lead to improved data representations for subsequent classification, while maintaining computational efficiency and scalability. Using multiple brain imaging datasets consisting of more than 150 million features, and several genomics datasets with more than 500,000 features, Linear Optimal Low-Rank Projection outperforms other scalable linear dimensionality reduction techniques in terms of accuracy, while only requiring a few minutes on a standard desktop computer.


Author(s):  
C. Allery ◽  
S. Gue´rin ◽  
A. Hamdouni ◽  
A. Sakout

We present in this paper an experimental and numerical study about the Coanda effect which causes the sudden reattachment of a jet to an inclined plane. This phenomenon induces a large hysteresis loop, which can be used to reduce the noise produced by an airflow crossing two diaphragms in tandem inside a duct. The angle of the inclined wall with horizontal plane and the flow velocity are the two main parameters studied here. With the aim of doing optimal control, we propose to construct for this flow configuration a low-dimensional dynamical system with a basis issued from a Proper Orthogonal Decomposition.


2020 ◽  
Vol 49 (3) ◽  
pp. 421-437
Author(s):  
Genggeng Liu ◽  
Lin Xie ◽  
Chi-Hua Chen

Dimensionality reduction plays an important role in the data processing of machine learning and data mining, which makes the processing of high-dimensional data more efficient. Dimensionality reduction can extract the low-dimensional feature representation of high-dimensional data, and an effective dimensionality reduction method can not only extract most of the useful information of the original data, but also realize the function of removing useless noise. The dimensionality reduction methods can be applied to all types of data, especially image data. Although the supervised learning method has achieved good results in the application of dimensionality reduction, its performance depends on the number of labeled training samples. With the growing of information from internet, marking the data requires more resources and is more difficult. Therefore, using unsupervised learning to learn the feature of data has extremely important research value. In this paper, an unsupervised multilayered variational auto-encoder model is studied in the text data, so that the high-dimensional feature to the low-dimensional feature becomes efficient and the low-dimensional feature can retain mainly information as much as possible. Low-dimensional feature obtained by different dimensionality reduction methods are used to compare with the dimensionality reduction results of variational auto-encoder (VAE), and the method can be significantly improved over other comparison methods.


Author(s):  
Akira Imakura ◽  
Momo Matsuda ◽  
Xiucai Ye ◽  
Tetsuya Sakurai

Dimensionality reduction methods that project highdimensional data to a low-dimensional space by matrix trace optimization are widely used for clustering and classification. The matrix trace optimization problem leads to an eigenvalue problem for a low-dimensional subspace construction, preserving certain properties of the original data. However, most of the existing methods use only a few eigenvectors to construct the low-dimensional space, which may lead to a loss of useful information for achieving successful classification. Herein, to overcome the deficiency of the information loss, we propose a novel complex moment-based supervised eigenmap including multiple eigenvectors for dimensionality reduction. Furthermore, the proposed method provides a general formulation for matrix trace optimization methods to incorporate with ridge regression, which models the linear dependency between covariate variables and univariate labels. To reduce the computational complexity, we also propose an efficient and parallel implementation of the proposed method. Numerical experiments indicate that the proposed method is competitive compared with the existing dimensionality reduction methods for the recognition performance. Additionally, the proposed method exhibits high parallel efficiency.


Shock Waves ◽  
2020 ◽  
Author(s):  
S. Bengoechea ◽  
J. Reiss ◽  
M. Lemke ◽  
J. Sesterhenn

Abstract This work presents a numerical study of detonation initiation by means of a focusing shock wave. The investigated geometry is a part of a pulsed detonation combustion chamber, consisting of a circular pipe in which the flow is obstructed by a single convergent–divergent axisymmetric nozzle. This obstacle acts as a focusing device for an incoming shock wave, serving as a low-energy detonation initiator. The chamber is filled with stoichiometric premixed hydrogen-enriched air. The simulation uses a one-step chemical model with variable parameters optimized by the adjoint approach in terms of the induction time $$\tau _{\text {c}}$$ τ c . The model reproduces $$\tau _{\text {c}}$$ τ c of a complex kinetics model in the range of pressures and temperatures appearing at the focusing point. The results give a comprehensive description of the shock-induced detonation initiation, which is the mechanism for the deflagration-to-detonation transition in this type of configurations. Potential geometry design improvements for technical applications are discussed. The first attempt to parameterize the transition process is also undertaken.


1987 ◽  
Vol 25 (5) ◽  
pp. 643-648
Author(s):  
Jose L.M. Clemente

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