Modeling and simulation of a pressure–temperature swing adsorption process for dehydration of natural gas

Aleghafouri, Abbas; Davoudi, Mehdi

doi:10.1007/s10450-017-9924-z

Cited by 30 publications

(14 citation statements)

References 20 publications

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“…Because the dew point is directly proportional to the water content, when the water content drops, so does the dew point [6]. Furthermore, as shown in (Figure 3Ac), when all process plant parameters are fixed and the mass flow rate of wet gas is increased, the tri-ethylene glycol TEG losses are reduced.…”

Section: Sensitivity Analysis Of Ngd Processmentioning

confidence: 94%

“…The number of absorption tower trays affects the TEG solvent flow rate. As a result, the absorber tower requires (6) trays to run at 0.025 m3 TEG/kg water [19], As previously stated, these values are in terms of pure TEG solvent (100 percent mass fraction). When using the ASPEN HYSYS software to investigate the influence of the TEG solvent flow rate on the water content, the findings revealed that raising the TEG solvent flow rate from 10 to 1000 kg/s increased the water content, as shown in Figure 4Ba.…”

Section: Effect Of Teg Mass Flow Ratementioning

confidence: 99%

“…As a result, the gas needs to be dried. Dehydrating natural gas can be done in a variety of ways, including: Using a solvent to absorb [4], Cooling [5], Adsorption [6], Membrane separation [7],…”

Section: Introductionmentioning

confidence: 99%

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Study The Effect of The Main Variables on The Objectives of The Natural Gas Dehydration Plant by ASPEN-HYSYS v8.8

Al-Jammali¹

2022

Journal of Petroleum Research and Studies

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In the NGD process, TEG dehydration is commonly employed to prevent corrosion and blockage of equipment, valves, and piping systems. TEG is frequently lost in the system during this procedure owing to vaporization and carryover. Therefore, it is necessary to study the affection of variables of the dehydration process the process was simulated with ASPEN-HYSYSV8.8 and the thermodynamic model was glycol-package; the process was validated by comparing the Plant results with the simulation results and demonstrating good acceptance. ASPEN-HYSYS conducted a sensitivity study to investigate the impact of variables on the main objectives. , as this study showed that not all of these variables have a strong effect, some of them have a weak effect, for example (wet gas pressure and same case of solvent pressure) and the rest of the variables have a strong effect on this process, so it must be taken into consideration by the station operators where this The changes were targeted because they are subject to change within the plant, and the highest value and the smallest value were taken according to the factory's parameters. As these variables are taken into account and the requisite improvements are made, the natural gas drying process will improve, and the dry gas requirements needed will improve, resulting in increased benefit.

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Section: Sensitivity Analysis Of Ngd Processmentioning

confidence: 94%

Section: Effect Of Teg Mass Flow Ratementioning

confidence: 99%

See 1 more Smart Citation

Study The Effect of The Main Variables on The Objectives of The Natural Gas Dehydration Plant by ASPEN-HYSYS v8.8

Al-Jammali¹

2022

Journal of Petroleum Research and Studies

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“…Terminating the adsorption and regeneration steps in a precipitated or delayed manner causes a decrease in the useful life of the fixed bed used in the TSA process; for example, in rapid cycles the TSA method is not indicated, as the maximum capacity of the adsorbent will not be used. 23,26 In the production of natural gas (NG), one of the most undesirable components in the composition of NG is water, since, besides causing corrosion, it causes the formation of hydrates that cause the clogging of the pipe. Among the methods used to remove water from NG is the adsorption dehydration with molecular sieves, due to the need to remove water at the maximum concentration of approximately 1 ppm, using the TSA or PSA method.…”

Section: Industrial and Engineering Chemistry Researchmentioning

confidence: 99%

Determination of Remaining Useful Life in Cyclic Processes

Marco

Trierweiler

Farenzena

2019

Ind. Eng. Chem. Res.

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The analysis of remaining useful life (RUL) of systems and equipment enables the prevention of failures, so that effective maintenance can be performed in time to correct failures that are close to happening. The degradation signal of a variable can be used as a basis for estimating the RUL of a given system since this signal is modeled mathematically correctly. In this paper, the RUL of cyclic processes is analyzed with the determination of the number of remaining cycles (NRC) in order to maximize production, guaranteeing operational safety. Two approaches will be considered: Bayesian methodology and time series. The Bayesian methodology is based on Bayesian inference to update the stochastic parameter, providing better representativeness in the estimation of the NRC. The deterministic parameters and the hyperparameters in the prior distribution of the stochastic parameter are estimated through the maximum likelihood estimation method, while the stochastic parameter in the degradation model of a system can be updated every time a new degradation data is obtained. On the other hand, the time series is based on training sets to be able to fit a model that is similar to the set used for validation. In the estimation of NRC, a stationary model (simple exponential smoothing), a nonstationary model (double exponential smoothing), and a model that considers the component of seasonality (triple exponential smoothing) are considered. A case study of a temperature swing adsorption unit for natural gas dehydration will be used to evaluate these two approaches in predicting NRC in cyclic processes. In this case study, we propose a novel cycle-packaging methodology that creates a new dimension, allowing the application of NRC forecasting methodologies, which is the main contribution of this article. The results suggest that the Bayesian methodology is the most indicated in the NRC estimation, while the time series are adequate to identify the cyclic pattern of the process.

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“…The results showed a decrease in dehydration efficiency by increasing water vapour concentration in the inlet gas feed. Aleghafouri and Davoudi [25] empirically conducted some experimental research and mathematical modelling of the natural gas dehydration units. They reported that the adsorption cycle time can be increased considering the weight of the loaded adsorbents.…”

Section: Introductionmentioning

confidence: 99%

Performance optimization of an industrial natural gas dehydration process to reduce energy consumption and greenhouse gases (GHGs) emission

2021

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Modeling and simulation of a pressure–temperature swing adsorption process for dehydration of natural gas

Cited by 30 publications

References 20 publications

Study The Effect of The Main Variables on The Objectives of The Natural Gas Dehydration Plant by ASPEN-HYSYS v8.8

Study The Effect of The Main Variables on The Objectives of The Natural Gas Dehydration Plant by ASPEN-HYSYS v8.8

Determination of Remaining Useful Life in Cyclic Processes

Performance optimization of an industrial natural gas dehydration process to reduce energy consumption and greenhouse gases (GHGs) emission

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