P-graph and Monte Carlo simulation approach to planning carbon management networks
A P-graph and Monte Carlo simulation approach to planning carbon management networks
is proposed. These networks are generalized systems for minimizing emissions of CO 2 …
is proposed. These networks are generalized systems for minimizing emissions of CO 2 …
Dual mixed refrigerant LNG process: Uncertainty quantification and dimensional reduction sensitivity analysis
The dual mixed refrigerant (DMR) liquefaction process is complicated and sensitive
compared to the competitive propane pre-cooled mixed refrigerant liquefied natural gas …
compared to the competitive propane pre-cooled mixed refrigerant liquefied natural gas …
Data-driven robust optimization for minimum nitrogen oxide emission under process uncertainty
The explosive waste materials used in military weapon systems are disposed by incineration
through a fluidized bed reactor. In this process, pollutants such as nitrogen oxide (NOx) are …
through a fluidized bed reactor. In this process, pollutants such as nitrogen oxide (NOx) are …
Integrating uncertainty quantification in reliability, availability, and maintainability (RAM) analysis in the conceptual and preliminary stages of chemical process design
Traditional analysis of a proposed process design uses average input values in the
performance assessment model, thereby generating single-point estimates. The resulting …
performance assessment model, thereby generating single-point estimates. The resulting …
Uncertainty quantification and global sensitivity analysis of complex chemical process using a generalized polynomial chaos approach
Uncertainties are ubiquitous and unavoidable in process design and modeling. Because
they can significantly affect the safety, reliability and economic decisions, it is important to …
they can significantly affect the safety, reliability and economic decisions, it is important to …
Global sensitivity analysis and uncertainty quantification of crude distillation unit using surrogate model based on Gaussian process regression
This study presents a global sensitivity analysis to simplify a surrogate-model-based
uncertainty quantification of a crude distillation unit with a large number of uncertainties. To …
uncertainty quantification of a crude distillation unit with a large number of uncertainties. To …
Reliability of CHO symbiosis networks under source streams uncertainty
R Mukherjee, MM El-Halwagi - Smart and …, 2018 - asmedigitalcollection.asme.org
An ecoindustrial park (EIP) is a state-of-the-art concept in which a group of industries located
in proximity share their products, byproducts, and waste in a symbiotic manner to conserve …
in proximity share their products, byproducts, and waste in a symbiotic manner to conserve …
Knowledge-inspired operational reliability for optimal LNG production at the offshore site
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 …
reliability, availability, and maintainability (RAM) analysis. The uncertainties of 3% in each …
Reliability-based robust multi-objective optimization (RBRMOO) of chemical process systems: a case study of TEG dehydration plant
R Mukherjee - Frontiers in Sustainability, 2022 - frontiersin.org
Natural gas (NG) production has significantly increased in the past decade as new
unconventional oil and gas wells are being discovered. NG as obtained from the wellhead …
unconventional oil and gas wells are being discovered. NG as obtained from the wellhead …
Uncertainty and influence of input parameters and assumptions on the design and analysis of thermochemical waste conversion processes: A stochastic approach
Process design is a challenging task for researchers and engineers. Incomplete information
and variation in input data affect the outputs and reliability of key performance indicators …
and variation in input data affect the outputs and reliability of key performance indicators …