Dynamic modeling and simulation of a pressurized system used in flight vehicle

Sun, Bing; Xu, Qiang; Chen, Yang

doi:10.1016/j.cja.2018.03.005

Cited by 8 publications

(5 citation statements)

References 35 publications

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“…Besides 0~7 eight calculation schemes of flow coefficient [14,24], the ninth scheme can be obtained by fitting the flow-rate characteristic curve of the Vanessa 30,000 series valves provided by the manufacturer:…”

Section: Valve-spool Throttling Modelsmentioning

confidence: 99%

“…By using Fluent 15.0 to conduct steady-state computation for the triple eccentric butterfly valve, Sun et al [18] discovered that the surface roughness may result in a big difference between the flow coefficient obtained by simulation without friction and the actual flow coefficient. The second type of research [24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42] focuses on the whole system rather than the valve, and thus generally uses the traditional 0D throttling flow-rate equation instead of the momentum equation to describe the dynamic throttling effect of the valve spool. In order to accurately describe the throttling effect, this simplified modeling method must take flow-rate equation, flow coefficient calculation, and valve-spool opening and closing rule into full consideration.…”

Section: Introductionmentioning

confidence: 99%

“…Firstly, as the core of the throttling model, the valve-spool or orifice throttling flow-rate equation is a semi-theoretical and semi-empirical formula. By the form of relationship between the flow rate and the upstream and downstream pressures, it can be roughly divided into the pressure ratio-based form [15,24,25] and the pressure difference-based form [15,[27][28][29][30][31][32][33][34][35][40][41][42]. The former generally applies to the condition of gas flow medium while the latter usually applies to the condition of liquid flow medium.…”

Section: Introductionmentioning

confidence: 99%

“…The model of gas mixing apparatus is often studied on component level and uses Fick's law, and it generally does not consider wall heat transfer in the process of gas mixing [45,46]. The modularization simulation models are derived from the flow/heat transfer two-field coupling pipe-flow model subsystem [16,24] in combination with the typical component structure. The effectiveness of the model system is verified by comparing the simulation results of the whole process of the system in two operating conditions with the test results, so it can be used as a building block for a so-called digital twin.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Modeling and Full-Process Simulation of the Core Engine Test Rig Main Test System

et al. 2021

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As a virtual digital model that can reflect physical entities or systems, digital twins are revolutionizing industry. The first prerequisite for the construction of digital twins is the establishment of high-precision and complex entities or system models. A 47-components numerical system is established for the core engine test rig main test system by using the finite volume modularization modeling method. A comprehensive solution to the system-level valve-spool/orifice throttling modeling, the key issue of the fluid pipeline system modeling, is presented, and the algorithms of throttling and mixing are deepened and expanded. The full-process simulation study on two tests of normal-temperature 1400 s and low-temperature 1240 s shows that the combined regulation of five regulator valves and the change of cold source directly decide dynamic change of the system in each stage; the simulation reveals the phenomena such as the gas cylinder cooling with deflation, the air cooling when expanding from main pipeline to two branch pipelines, shunting flow by branch pipeline, and the cold and hot gases mixing; the overall variation trends of the simulation curves are consistent with those of all the experimental curves of the test rig normal-temperature/low-temperature air supply lines, exhaust bypass, and engine main line in two operating conditions, and the maximum error between simulation curves and test curves of pressure, total pressure, and total temperature is less than 12%. The numerical system can be used for the construction of virtual models of digital twins, and the modeling method provides a feasible solution to the key technology of digital twins.

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Section: Valve-spool Throttling Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic Modeling and Full-Process Simulation of the Core Engine Test Rig Main Test System

et al. 2021

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“…Pressure regulators are designed to maintain constant output pressure regardless of the variations in the upstream pressure or the downstream flow [1]. These control valves are widely applied in the fields of industries and household, such as aircraft [2], aerospace [3], vehicle [4], mining [5], etc. In cooking and heating fields [6], the compressed natural gas, regulated by a series of pressure regulators, eventually goes to household supply systems at a lower pressure.…”

Section: Introductionmentioning

confidence: 99%

Fault Diagnosis of Gas Pressure Regulators Based on CEEMDAN and Feature Clustering

et al. 2019

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Gas pressure regulators are widely applied in natural gas pipeline networks, correspondingly, establishing an efficient fault diagnosis approach of regulators plays a critical role in optimizing the safety and reliability of pipeline network systems. In our paper, considering that the outlet pressure signals of gas regulators are nonstationary and nonlinear, we propose a fault diagnosis approach combining a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and fuzzy c-means (FCM) clustering to classify three typical faults of gas regulators. First, we propose to apply the CEEMDAN approach for decomposing intrinsic mode functions (IMFs). Then feature vectors of the typical faults are established by Hilbert marginal spectrum (HMS) of IMFs. Finally, we adopt cluster centers and feature clustering algorithm to distinguish the types of faults. The experimental results indicate the high performance of the present fault diagnosis approach. The membership degrees of test samples obtained from the CEEMDAN algorithm are optimized to be within 0.9 to 1. INDEX TERMS Gas pressure regulators, fault diagnosis, CEEMDAN, feature extraction, spectral analysis, fuzzy c-means clustering.

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Modeling and simulation of xenon storage and supply system for electric propulsion system based on fundamental equation of state

Chen,

Yan,

Jia

et al. 2024

Applied Thermal Engineering

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Dynamic modeling and simulation of a pressurized system used in flight vehicle

Cited by 8 publications

References 35 publications

Dynamic Modeling and Full-Process Simulation of the Core Engine Test Rig Main Test System

Dynamic Modeling and Full-Process Simulation of the Core Engine Test Rig Main Test System

Fault Diagnosis of Gas Pressure Regulators Based on CEEMDAN and Feature Clustering

Modeling and simulation of xenon storage and supply system for electric propulsion system based on fundamental equation of state

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