Mohd Shariq Khan

Studying the effect of feed composition variation on typical natural gas liquid (NGL) recovery processes

In this work, the different process schemes used for known NGL recovery methods have been studied with various feed compositions. The original turbo-expander process scheme (ISS) was considered as a base case. The GSP, CRR, RSV and RSVE process schemes are those which focus on improvement at the top of the demethanizer column, while the IPSI-1 and IPSI-2 at the bottom of the demethanizer column. All the process schemes have initially built using ASPEN HYSYS with a common set of operating criteria. Numerous simulation runs have been made later by taking various typical feed compositions classified as lean and rich. Regardless of the common operating conditions set to each process schemes, there exist different performance results obtained from the simulation. Accordingly, the reboiler duty requirement is high for the GSP, CRR, RSV and RSVE due to the need for external refrigeration. However, the IPSI-1 and IPSI-2 simulation result show relatively lower reboiler duty requirement for the self-refrigeration system applied to the systems.

Modeling and simulation of multi-stream heat exchanger using artificial neural network

Abstract A multi-stream heat exchanger (MSHE) is the heart of LNG plant where 40% of the entire energy is consumed in this section. Moreover, the plant operation is subject to number of variations from the plant inlet such as ambient temperature, pressure, feed flow or composition. In industrial application, the mitigating of these variations is usually performed using trial and error approaches. Thus developing a competent and accurate model to predict the performance of the MSHE is an inevitable step to overcome those variations. In this study, a model for the MSHE operation is developed using artificial neural network. The modeling is made in such a way that the information about the internals of heat exchanger could allow the MSHEs from any variation that arises from the process itself or upstream conditions. A number of simulation runs have been made by taking a case study for the MSHE operation. The developed model can predict and provide prior information for the MSHE in order to take action during the plant performance.

Dynamic modelling and optimization of an LNG storage tank in a regasification terminal with semi-analytical solutions for N-2-free LNG

Abstract A comprehensive dynamic model for an LNG storage tank in a typical regasification terminal, operating in holding mode, is presented. The model incorporates LNG recirculation for cooling the transfer lines for loading/unloading. It assumes a hypothetical thin vapour interface in equilibrium with the liquid to compute LNG evaporation, which allows the boil-off gas to be hotter than the tank LNG, as observed in practice. A numerical procedure based on the secant method is implemented in MATLAB for solving the governing ordinary differential equations. For the special case of N 2 -free LNG, a semi-analytical solution is proposed to solve the dynamic model for this relatively complex system and compute the amount of boil-off gas (BOG). The semi-analytical solution is subsequently used to optimize the LNG storage tank and recirculation loop designs.

Robust control of Propane Pre-cooled mixed refrigerant process for natural gas liquefaction

Natural Gas are often found at remote locations to bring it to the world market liquefaction is required. In liquefaction natural gas is cooled to around -160°C, 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.

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

Abstract The practical quantification of a models 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.

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

Abstract 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.

Process and Heat Integrated Design of a Novel NGL Recovery Scheme

Abstract This study addresses the development of a novel intensified NGL (natural gas liquids) recovery scheme aimed at high efficiency and product recovery with lower operating and capital expenditure. The article unfolds the design and characteristics of the new NGL recovery scheme and put forward a comparison study of the proposed design performance with four commercial NGL recovery schemes using capital/operating cost, propane recovery, and required heat exchanger area as indices. Owing to the excellent heat integration the propose design gives superior performance over all comparison indices.