Experimental and Computational Analysis of the Unstable Flow Structure in a Centrifugal Compressor with a Vaneless Diffuser

Xue, Xiang; Wang, Tong

doi:10.1186/s10033-019-0379-x

Cited by 3 publications

(2 citation statements)

References 31 publications

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“…ARIMA as a time series forecasting model can be applied for nonstationary series modeling. [ 32 ] This model is easy to construct and can obtain the internal relationship of the historical data and predict future trend of a time series. The ARIMA (

p, d, q

) model combines auto regression (AR( p )), difference( d ), and moving average (MA( q )).…”

Section: Methodsmentioning

confidence: 99%

Prediction of Lithium‐Ion Battery Remaining Useful Life via Empirical Mode Decomposition‐ Autoregressive Integrated Moving Average and Regularized Particle Filter Algorithm

Cai

Zheng

et al. 2023

Energy Tech

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This article focuses on improving the prediction accuracy of lithium‐ion battery's remaining useful life (RUL) by combining empirical mode decomposition (EMD), autoregressive integrated moving average (ARIMA), and regularized particle filter (RPF). First, to obtain detailed information about the battery capacity degradation, the monitored capacity data are decoupled by EMD. Second, the long‐term predicted model is constructed by ARIMA for the decoupled components. Finally, the long‐term prediction results are utilized as the measurement equation of the RPF prediction framework. In the proposed novel hybrid framework combining EMD‐ARIMA and RPF, the capacity prediction values are corrected and updated during the iteration of the regularized particle filter. With the estimated capacity data of every cycle, it can be detected whether the batteries reach their service life threshold. To validate the performance of the aforementioned method, the comparative experiments which are based on the NASA Prognostic Center of Excellence battery data sets are performed. According to the analysis results, higher prediction accuracy has been obtained with the proposed method in the lithium‐ion battery RUL, compared with the other three methods.

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p, d, q

) model combines auto regression (AR( p )), difference( d ), and moving average (MA( q )).…”

Section: Methodsmentioning

confidence: 99%

Prediction of Lithium‐Ion Battery Remaining Useful Life via Empirical Mode Decomposition‐ Autoregressive Integrated Moving Average and Regularized Particle Filter Algorithm

Cai

Zheng

et al. 2023

Energy Tech

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show abstract

“…However, few studies have been conducted for unsteady flow analysis of centrifugal compressors based on the DMD method. 12,32 The physical interpretation and evolution procedure of the decomposed dynamic structures in compressor passages need to be further verified and investigated.…”

Section: Introductionmentioning

confidence: 99%

Dynamic mode decomposition analysis of the flow characteristics in a centrifugal compressor with vaned diffuser

Zhao

Liu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part A:

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To understand the flow dynamic characteristics of a centrifugal compressor, the dynamic mode decomposition (DMD) method is introduced to decompose the complex three-dimensional flow field. Three operating conditions, peak efficiency (OP1), peak pressure ratio (OP2), and small mass flow rate (near stall, OP3) conditions, are analyzed. First, the physical interpretations of main dynamic modes at OP1 are identified. As a result, the dynamic structures captured by DMD method are closely associated with the flow characteristics. In detail, the BPF/2BPF (blade passing frequency) corresponds to the impeller–diffuser interaction, the rotor frequency (RF) represents the tip leakage flow (TLF) from leading edge, and the 4RF is related to the interaction among the downstream TLF, the secondary flow, and the wake vortex. Then, the evolution of the dynamic structures is discussed when the compressor mass flow rate consistently declines. In the impeller, the tip leakage vortex near leading edge gradually breaks down due to the high backpressure, resulting in multi-frequency vortices. The broken vortices further propagate downstream along streamwise direction and then interact with the flow structures of 4RF. As a result, the 8RF mode can be observed in the whole impeller, this mode is transformed from upstream RF and 4RF modes, respectively. On the other hand, the broken vortices show broadband peak spectrum, which is correlated to the stall inception. Therefore, the sudden boost of energy ratio of 14RF mode could be regarded as a type of earlier signal for compressor instability. In the diffuser, the flow structures are affected by the perturbation from the impeller. However, the flow in diffuser is more stable than that in impeller at OP1–OP3, since the leading modes are stable patterns of BPF/2BPF.

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Experimental Study of Vaneless Diffuser Rotating Stall Development and Cell-Merging Phenomena

Grapow

Olasek

Liśkiewicz

et al. 2021

Journal of Turbomachinery

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This paper describes the vaneless diffuser rotating stall (VDRS) development and cell merging phenomena. A centrifugal compressor's lifespan may be limited by flow instabilities occurring in off-design operation. One such instability is the VDRS, which generates oscillating, asymmetrical flow fields in the diffuser and, thus, undesired forces acting on the rotor. Understanding and prevention of VDRS behavior is crucial for achieving safe and undisturbed compressor operation. Experimental measurements of centrifugal compressors operating under the influence of VDRS have been presented. Two different approaches were used for the identification of VDRS: pressure measurements and 2D PIV. Frequency analysis based on spectral maps and cell development processes were investigated. The presented results showed that mass flow rate has an impact on the rotating frequency of both the entire structure and single cells. Additionally, it affects radial cell size, which grows with compressor throttling and ultimately reaches the length of the diffuser. During the experiments, the cell merging phenomenon was observed which has not been widely described in the literature. The results presented in this paper allow better understanding of vaneless diffuser rotating stall behavior. The phenomenon of the change of cell size and frequency could be very important for machine fatigue. Cell merging could also have an impact on the machine's vibrations and flow stability. Since it is believed that VDRS is one of the factors inducing surge, its understanding and prevention may have positive influence on surge margins.

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Experimental and Computational Analysis of the Unstable Flow Structure in a Centrifugal Compressor with a Vaneless Diffuser

Cited by 3 publications

References 31 publications

Prediction of Lithium‐Ion Battery Remaining Useful Life via Empirical Mode Decomposition‐ Autoregressive Integrated Moving Average and Regularized Particle Filter Algorithm

Prediction of Lithium‐Ion Battery Remaining Useful Life via Empirical Mode Decomposition‐ Autoregressive Integrated Moving Average and Regularized Particle Filter Algorithm

Dynamic mode decomposition analysis of the flow characteristics in a centrifugal compressor with vaned diffuser

Experimental Study of Vaneless Diffuser Rotating Stall Development and Cell-Merging Phenomena

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