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 …
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 …
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 …
Automated synthesis of safe digital controllers for sampled-data stochastic nonlinear systems
We present a new method for the automated synthesis of digital controllers with formal safety
guarantees for systems with nonlinear dynamics, noisy output measurements, and …
guarantees for systems with nonlinear dynamics, noisy output measurements, and …
Uncertainty quantification and global sensitivity analysis of complex chemical processes with a large number of input parameters using compressive polynomial chaos
Uncertainties are ubiquitous and unavoidable in process design and modeling while they
can significantly affect safety, reliability, and economic decisions. The large number of …
can significantly affect safety, reliability, and economic decisions. The large number of …
SMT-based synthesis of safe and robust PID controllers for stochastic hybrid systems
We present a new method for the automated synthesis of safe and robust Proportional-
Integral-Derivative (PID) controllers for stochastic hybrid systems. Despite their widespread …
Integral-Derivative (PID) controllers for stochastic hybrid systems. Despite their widespread …
Open and closed-loop stochastic dynamics of a class of nonlinear chemical processes with multiplicative noise
The open and closed-loop global state probability density function behavior of a class of
single-state nonlinear chemical processes subjected to additive and multiplicative white …
single-state nonlinear chemical processes subjected to additive and multiplicative white …
Sparse Bayesian learning for data driven polynomial chaos expansion with application to chemical processes
Uncertainties are ubiquitous in process system engineering. Hence, to develop a safe and
profitable process, uncertainty quantification (UQ) is necessary in a reliability, availability …
profitable process, uncertainty quantification (UQ) is necessary in a reliability, availability …
Robust PID design by chance-constrained optimization
A method for synthesizing proportional–integral–derivative (PID) controllers for process
models with probabilistic parametric uncertainty is presented. The proposed method …
models with probabilistic parametric uncertainty is presented. The proposed method …
A two-stage approach of multiplicative dimensional reduction and polynomial chaos for global sensitivity analysis and uncertainty quantification with a large number of …
PLT Duong, J Goncalves, E Kwok, M Lee - Journal of the Taiwan Institute …, 2017 - Elsevier
Uncertainties associated with estimates of model parameters are inevitable when simulating
and modeling chemical processes and significantly affect safety, consistency, and decision …
and modeling chemical processes and significantly affect safety, consistency, and decision …