• Energy Research

Abstract The mixed fluid cascade (MFC) process is considered one of the most promising candidates for producing liquefied natural gas (LNG) at onshore sites, mainly owing to its high capacity and relatively high potential energy efficiency. The MFC process involves three refrigeration cycles for natural gas precooling, liquefaction, and subcooling, making its operation more complex and sensitive. Each refrigeration cycle consists of a different mixed refrigerant, which must be optimized to change feed and ambient conditions to operate efficiently. Any sub-optimal solution can lead to high exergy losses, ultimately reducing the process energy efficiency. Operating optimally is a challenging task, mainly owing to the non-linear interactions between the constrained decision (design) variables and complex thermodynamics involved in MFC refrigeration cycles. In this context, we employ a multivariate Coggins step-up approach to reduce the exergy losses associated with the MFC process. This study reveals that the overall exergy losses can be minimized to 35.91%; resulting in 25.4% overall energy savings compared to sub-optimal MFC processes.

Abstract The mixed fluid cascade (MFC) process is considered one of the most promising candidates for producing liquefied natural gas (LNG) at onshore sites, mainly owing to its high capacity and relatively high potential energy efficiency. The MFC process involves three refrigeration cycles for natural gas precooling, liquefaction, and subcooling, making its operation more complex and sensitive. Each refrigeration cycle consists of a different mixed refrigerant, which must be optimized to change feed and ambient conditions to operate efficiently. Any sub-optimal solution can lead to high exergy losses, ultimately reducing the process energy efficiency. Operating optimally is a challenging task, mainly owing to the non-linear interactions between the constrained decision (design) variables and complex thermodynamics involved in MFC refrigeration cycles. In this context, we employ a multivariate Coggins step-up approach to reduce the exergy losses associated with the MFC process. This study reveals that the overall exergy losses can be minimized to 35.91%; resulting in 25.4% overall energy savings compared to sub-optimal MFC processes.

Abstract 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.

Abstract 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.

The protection of the environment and pollution control are issues of paramount importance. Researchers today are engrossed in mitigating the harmful impacts of petroleum waste on the environment. Lubricating oils, which are essential for the smooth operation of engines, are often disposed of improperly after completing their life. In the experimental work presented in this paper, deteriorated engine oil was regenerated using the acid treatment method and was reused in the engine. The comparison of the properties of reused oil, the engine’s performance, and the emissions from the engine are presented. The reuse of regenerated oil, the evaluation of performance, and emissions establish the usefulness of the regeneration of waste lubricating oil. For the used oil, total acid number (TAN), specific gravity, flash point, ash content, and kinematic viscosity changed by 60.7%, 6.7%, 4.4%, 96%, and 15.5%, respectively, compared with fresh oil. The regeneration partially restored all the lost lubricating oil properties. The performance parameters, brake power (BP), brake specific fuel consumption (BSFC), and exhaust gas temperature (EGT) improved with regenerated oil in use compared with used oil. The emissions CO and NOX contents for acid-treated oil were 9.7% and 17.3% less in comparison with used oil, respectively. Thus, regenerated oil showed improved performance and oil properties along with significantly reduced emissions when employed in an SI engine.

The protection of the environment and pollution control are issues of paramount importance. Researchers today are engrossed in mitigating the harmful impacts of petroleum waste on the environment. Lubricating oils, which are essential for the smooth operation of engines, are often disposed of improperly after completing their life. In the experimental work presented in this paper, deteriorated engine oil was regenerated using the acid treatment method and was reused in the engine. The comparison of the properties of reused oil, the engine’s performance, and the emissions from the engine are presented. The reuse of regenerated oil, the evaluation of performance, and emissions establish the usefulness of the regeneration of waste lubricating oil. For the used oil, total acid number (TAN), specific gravity, flash point, ash content, and kinematic viscosity changed by 60.7%, 6.7%, 4.4%, 96%, and 15.5%, respectively, compared with fresh oil. The regeneration partially restored all the lost lubricating oil properties. The performance parameters, brake power (BP), brake specific fuel consumption (BSFC), and exhaust gas temperature (EGT) improved with regenerated oil in use compared with used oil. The emissions CO and NOX contents for acid-treated oil were 9.7% and 17.3% less in comparison with used oil, respectively. Thus, regenerated oil showed improved performance and oil properties along with significantly reduced emissions when employed in an SI engine.