CFD Simulation Investigation on the Flow Field Distribution Pattern under Different Operating Environment Pressures in a Jet Impingement-Negative Pressure Reactor

Dong, Yingying; Qiu, Facheng; Chai, Xinjie

doi:10.1021/acsomega.3c08692

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…Then, a jet impact-negative pressure reactor (JI-NPR) has been developed to obtain a good deamination effect . Due to the complex randomness and instantaneity of the impact flow behavior of porous jets under negative pressure conditions, this situation increases the difficulty of investigation of flow characteristics within the reactor. , Thus, a highly applicable flow signal feature recognition method is helpful for studying the internal flow behavior of the JI-NPR.…”

Section: Introductionmentioning

confidence: 99%

Characteristic Investigation on Fluid Signals Based on a Combination of Empirical Mode Decomposition and Hilbert Transform in a Jet Impact-Negative Pressure Deamination Reactor

Zhang,

Chai,

Qiu

et al. 2024

Ind. Eng. Chem. Res.

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The jet impact-negative pressure reactor (JI-NPR) is a novel wastewater treatment technology developed for the efficient removal of high-concentration ammonia nitrogen. However, the complex and transient nature of the flow behavior within the JI-NPR poses significant challenges for understanding the underlying fluid dynamics. In this work, a comprehensive signal-processing framework was developed to elucidate the flow characteristics inside the JI-NPR. First, a flow signal acquisition platform was established to capture the negative pressure signals during the treatment process. The empirical mode decomposition (EMD) technique was then employed to decompose the turbulent flow signals into a series of intrinsic mode functions (IMFs), representing multiscale turbulent eddy characteristics. To mitigate the effects of local noise and abrupt changes, various curve fitting methods, including cubic spline interpolation, piecewise cubic Hermite interpolating polynomial, and Makima interpolation, were utilized to smooth the IMF signals. The Hilbert transform was subsequently applied to extract the instantaneous frequency features of the smoothed IMFs, enabling more accurate quantification of the nonstationary and nonlinear flow behavior. The results revealed that the low-frequency IMFs were associated with the interactions between the wastewater jet and negative pressure, while the highfrequency IMFs reflected the internal dynamic evolution of the fluid. Furthermore, the multiple regression analysis approach was adopted to quantify the relationship between the IMF feature parameters and the critical performance metric of the denitrification efficiency. The decision tree regression model was identified as a particularly suitable technique, as it can flexibly capture both linear and nonlinear dependencies and effectively identify the most influential variables. This integrated approach of EMD, curve fitting, Hilbert transform, and regression analysis methods provides valuable insights into the quantitative impact of multiscale turbulent eddies on the overall performance of the JI-NPR system. These findings are expected to guide targeted optimization of the reactor design to enhance the denitrification efficiency, a crucial goal for the practical application of this wastewater treatment technology.

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Section: Introductionmentioning

confidence: 99%

Characteristic Investigation on Fluid Signals Based on a Combination of Empirical Mode Decomposition and Hilbert Transform in a Jet Impact-Negative Pressure Deamination Reactor

Zhang,

Chai,

Qiu

et al. 2024

Ind. Eng. Chem. Res.

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Numerical simulation of the effect of jet small orifice structure on cavitation characteristic and jet impact flow field

Yang,

Hu,

Qiu

et al. 2024

Chemical Engineering and Processing - Process Intensification

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Microscopic mechanism of nanofluids electrospray: A molecular dynamics study

Dai,

Wang,

Chen

et al. 2024

Physics of Fluids

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Cone-jet electrospray is widely used in various fields, such as electrospinning, nanostructured porous coating preparation, and inkjet printing, for which it can produce a large number of monodisperse and high charge-to-mass ratio droplets. A molecular dynamics method is employed to investigate the cone-jet electrospray emission behavior of nanofluids, where the microscopic mechanism of cone-jet electrospray including the formation of the cone, disintegration of the jet, stability of hydrogen bond, and interactions between molecules is revealed. In this paper, the influence of operating parameters and liquid physical properties were numerically conducted and extensively analyzed. The results show that the cone-jet electrospray only occurs in a certain range of applied voltage and flow rate, and the temperature and concentration of nanoparticles have a great effect on the jet length and the number of clusters produced by jet disintegration. When the electric field intensity increases, the length of the jet and the number of clusters increase. However, regardless of the electric field intensity, the maximum axial density is always located near the capillary outlet and the maximum radial density is located at the central axis of the capillary. As the temperature increases, the number of clusters increases significantly due to the synthetical effect of electric field-induced disintegration and evaporation, whereas the jet length is reduced. With an increase in concentration of nanoparticles at room temperature, the Taylor cone not only appears earlier but also has a larger angle. Meanwhile, the non-bonded interactions between ethanol molecules become stronger. This work provides microscopic mechanisms of nanofluids cone-jet electrospray and is potentially useful to optimize the design parameters of industrial applications.

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CFD Simulation Investigation on the Flow Field Distribution Pattern under Different Operating Environment Pressures in a Jet Impingement-Negative Pressure Reactor

Cited by 3 publications

References 25 publications

Characteristic Investigation on Fluid Signals Based on a Combination of Empirical Mode Decomposition and Hilbert Transform in a Jet Impact-Negative Pressure Deamination Reactor

Characteristic Investigation on Fluid Signals Based on a Combination of Empirical Mode Decomposition and Hilbert Transform in a Jet Impact-Negative Pressure Deamination Reactor

Numerical simulation of the effect of jet small orifice structure on cavitation characteristic and jet impact flow field

Microscopic mechanism of nanofluids electrospray: A molecular dynamics study

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