Robust Control of Propane Pre-Cooled Mixed Refrigerant Process for Natural Gas Liquefaction

Mohd Shariq Khan,Mun Kyu Yoon,Yuli Amalia Husnil,Moonyong Lee 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10

Natural Gas are often found at remote locations to bring it to the world market liquefaction is required [1]. In liquefaction natural gas is cooled to around -160℃, hence required considerable amount of energy. To maximize the profit from the existing design it is necessary that the process should operate efficiently, reliably and safely. Hence a good and Robust control is required. Due to tight control strategy the stability is an issue in the main cryogenic heat exchanger(MCHE) and in the Refrigerant flash drum. In this study the C3MR process was considered and the dynamic model was made in Hysys simulator and used to implement the proposed control algorithm. By judiciously choosing control variables we have proposed more robust control strategy and its performance was observed under simulation environment which provide satisfactory robustness for stability and performance.

Surrogate-assisted modeling and optimization of a natural-gas liquefaction plant

Ali, Wahid,Khan, Mohd Shariq,Qyyum, Muhammad Abdul,Lee, Moonyong Elsevier 2018 Computers & chemical engineering Vol.118 No.-

<P><B>Abstract</B></P> <P>In this study, surrogate-assisted modeling and optimization of the single mixed refrigerant process of natural-gas liquefaction is presented. The mixed refrigerant liquefaction process is highly nonlinear owing to the involved thermodynamics that increase the computational burden of any optimization algorithm. To address the computational-burden issue and obtain the results in a reasonable time for the complex single mixed refrigerant process, an approximate surrogate model was developed using a radial basis function combined with a thin-plate spline approach. Even with the reduced model, all the results obtained were comparable with those by rigorous first-principle models. This confirms that all the important characteristics of the model are correctly captured, and the surrogate models of the liquefaction plant are acceptable replacements of first-principle models, especially in computationally demanding situations.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Hysys and Matlab model were linked by HDSS code. </LI> <LI> Surrogate model using RBF approach with thin plate spline kernel function was employed. </LI> <LI> Adaptation of feasible region and model identification was made. </LI> <LI> PSO and GA optimization algorithm were applied to both Hysys and surrogate model. </LI> <LI> Results obtained were found to be promising with less computational efforts. </LI> </UL> </P> <P><B>Graphical Abstract</B></P> <P>[DISPLAY OMISSION]</P>

Simulation Study of a Reactive Batch Distillation Column

Wahid Ali,Mohd. Shariq Khan,Yus Donald Chaniago,Reizqa Andika,Le Cao Nhien,Bong Gu Choi,Moonyong Lee 제어로봇시스템학회 2014 제어로봇시스템학회 국내학술대회 논문집 Vol.2014 No.5

Optimization of modified single mixed refrigerant process of natural gas liquefaction using multivariate Coggin’s algorithm combined with process knowledge

Pham, Tram Ngoc,Khan, Mohd Shariq,Minh, Le Quang,Husmil, Yuli Amalia,Bahadori, Alireza,Lee, Sanggyu,Lee, Moonyong Elsevier 2016 Journal of natural gas science and engineering Vol.33 No.-

<P><B>Abstract</B></P> <P>The optimization of a mixed refrigerant liquefaction process is a challenge because of its non-linear characteristics with stringent multiple process constraints. This study proposes a novel hybrid approach for the optimization of a newly developed, modified single mixed refrigerant process of natural gas liquefaction targeted for offshore applications. This contribution focuses on interpreting the geometric pattern of a plot of the temperature difference between the hot and cold composite curves in a cryogenic heat exchanger to understand the profound effects of the flow rates of the individual refrigerant components and the operating pressure on the liquefaction efficiency. From this, an effective method to generate a proper initial approach temperature profile was developed to ensure robust convergence of the main optimization step. An enhanced coordinate descent methodology was implemented in the main optimization procedure to accelerate the optimization of the modified single mixed refrigerant liquefaction process. The proposed knowledge-inspired hybrid optimization approach showed a robust convergence on determining the optimal design condition. The total energy requirement for natural gas liquefaction cycle was reduced by 21.9% compared to the base case. The proposed methodology can be extended directly to solve optimization problems for other mixed refrigerant based natural gas liquefaction processes.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Analysis of the TDCC plot of the MSMR process. </LI> <LI> Effects of decision variables on the performance of NG liquefaction. </LI> <LI> An enhanced coordinate descent methodology to accelerate the optimization. </LI> <LI> A good initial point and search sequence to ensure robust convergence. </LI> <LI> The compression energy for NG liquefaction was reduced significantly. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Knowledge-inspired operational reliability for optimal LNG production at the offshore site

Ali, Wahid,Qyyum, Muhammad Abdul,Khan, Mohd Shariq,Duong, Pham Luu Trung,Lee, Moonyong Elsevier 2019 Applied Thermal Engineering Vol.150 No.-

<P><B>Abstract</B></P> <P>To develop a safe and profitable process, uncertainty quantification is necessary for a reliability, availability, and maintainability (RAM) analysis. The uncertainties of 3% in each key decision variables are propagated which could bring the system into an unreliable/risk region. Hence, in this study, uncertainty quantification (UQ) with simultaneous determination of sensitivity indices (SI) is proposed using generalized polynomial chaos (gPC) modeling approach. This approach reduces about 90% of the total computational time when compared with the conventional simulation approaches required for a complex first principle based model. Subsequently, a knowledge inspired reliability analysis is carried out using the uncertainty analysis (UA). By using the statistical properties of the process, for example, mean/optimal value at 50% failure give the bound between [0.7174, 0.9496] for LNG product stream. Further, it was found that LNG with 10% end flash gas (or 90% liquefaction rate) can be obtained with a failure probability of 14.43%. This value of reliability is promising for a given specified deviation; hence, the process could be assumed to be near to its reliable optimal operational region.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Reliability of the SMR liquefaction process is effectively measured. </LI> <LI> A gPC based surrogate modeling approach is applied for uncertainty quantification. </LI> <LI> Sobol sensitivity indices are obtained directly from the surrogate model. </LI> <LI> Computational time is significantly reduced compared to MC/qMC approaches. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Measuring the reliability of a natural gas refrigeration plant: Uncertainty propagation and quantification with polynomial chaos expansion based sensitivity analysis

Ali, Wahid,Duong, Pham Luu Trung,Khan, Mohd Shariq,Getu, Mesfin,Lee, Moonyong Elsevier 2018 Reliability engineering & system safety Vol.172 No.-

<P><B>Abstract</B></P> <P>The practical quantification of a model's ability to describe information is extremely important for the practical estimation of model parameters. Hence, in this study, a complex sweet natural gas refrigeration chemical process was selected for uncertainty quantification (UQ) and sensitivity analysis (SA). A computer code was generated to create a hybrid digital simulation system (HDSS) to connect two commercially important software programs, namely Matlab and Aspen Hysys. Monte Carlo (MC) and Halton based quasi-MC (QMC) methods were used for uncertainty propagation (UP) and uncertainty quantification (UQ). A surrogate model based on the polynomial chaos expansions (PCE) approach was applied for SA. Sobol′ sensitivity indices were evaluated to identify influential input parameters. The proposed PCE methodology was compared with a traditional MC based approach to illustrate its advantages in terms of computational efficiency and acceptable accuracy. The results indicated that UQ and SA help in an in-depth understanding of the chemical process determining the feasibility and improving the operation based on reliability and consumer demands. This study used in the robust design by evaluating the bounds and reliability based on confidence levels and thereby increasing the reliance of the process at hand.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Uncertainty quantification was performed to measure the reliability of natural gas liquefaction process. </LI> <LI> Surrogate model using polynomial chaos expansion approach was used for sensitivity analysis. </LI> <LI> Sobol′ sensitivity indices can be obtained directly from the surrogated gPC model. </LI> <LI> Study helps the robust design by evaluating the bounds and reliability based on confidence levels. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Energy efficiency enhancement of a single mixed refrigerant LNG process using a novel hydraulic turbine

Qyyum, Muhammad Abdul,Ali, Wahid,Long, Nguyen Van Duc,Khan, Mohd Shariq,Lee, Moonyong Elsevier 2018 ENERGY Vol.144 No.-

<P><B>Abstract</B></P> <P>The advancement in hydraulic turbine (HT) technology was exploited for energy and cost benefits in natural gas liquefaction. Replacing the conventional Joule–Thompson (JT) valve with HT has the potential to recover the work input. This research investigated the effect of replacing the JT valve with HT in the energy efficiency enhancement of a single mixed refrigerant (SMR) process. To fully take the potential benefit of the HT, the proposed SMR schemes were optimized by using a modified coordinate descent optimization method, which was implemented in Microsoft Visual Studio environment and linked to the rigorous HYSYS<SUP>®</SUP> model. The results showed that the required energy of the proposed HT based SMR process could be saved up to 16.5% in comparison with the conventional SMR process using the JT valves. Utilization of the recovered energy into boosting the natural gas feed pressure could further reduce the energy requirement up to 25.7%. Exergy efficiency analysis also showed that whole exergy efficiency of the enhanced SMR process can be increased by about 11% as compared to the base case. The proposed HT based liquefaction technology can be extended to other natural gas liquefaction processes as an attractive option for enhancing the energy efficiency.</P> <P><B>Highlights</B></P> <P> <UL> <LI> An enhanced SMR process using hydraulic turbines was proposed for improving energy efficiency. </LI> <LI> Synergistic effects by hydraulic turbines with optimization were investigated. </LI> <LI> The proposed SMR process reduces energy requirement up to 16.5%. </LI> <LI> Efficient utilization of recovered energy further reduces energy requirement up to 25.7%. </LI> <LI> The proposed hydraulic turbine based liquefaction can be extended to other natural gas liquefaction processes. </LI> </UL> </P>

Synthesis, MR Relaxivities, and In Vitro Cytotoxicity of 3,5-Diiodo-L-tyrosine-Coated Gd2O3 Nanoparticles

Ahmad, Md Wasi,Ahmad, Mohammad Yaseen,Ul-Islam, Mazhar,Xu, Wenlong,Tegafaw, Tirusew,Wazwaz, Aref A.,Ibrehem, Ahmmed S.,Khan, Mohd Shariq,Oh, In-Taek,Chae, Kwon Seok,Cha, Hyunsil,Chang, Yongmin,Lee, Ga Springer-Verlag 2019 BioNanoScience Vol.9 No.1