Integrating machine learning and mathematical programming for efficient optimization of operating conditions in organic Rankine cycle (ORC) based combined …

J Zhou, YT Chu, J Ren, W Shen, C He - Energy, 2023 - Elsevier
Operations optimization in an organic Rankine cycle (ORC) based combined system is
important while computationally difficult by using mechanistic models due to complex …

A high-accuracy online transient simulation framework of natural gas pipeline network by integrating physics-based and data-driven methods

X Yin, K Wen, W Huang, Y Luo, Y Ding, J Gong, J Gao… - Applied Energy, 2023 - Elsevier
The natural gas pipeline network is an important part of the integrated energy system. The
optimal control of the integrated energy system requires accurate transient online simulation …

Accelerating operation optimization of complex chemical processes: A novel framework integrating artificial neural network and mixed-integer linear programming

J Zhou, T Shi, J Ren, C He - Chemical Engineering Journal, 2024 - Elsevier
We present an automated framework that integrates rectified linear unit activated artificial
neural network (ReLU-ANN) and mixed-integer linear programming (MILP) to enable …

[HTML][HTML] Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design

LF Santos, CBB Costa, JA Caballero… - Energy, 2023 - Elsevier
A surrogate-based multi-objective optimization framework is employed in the design of
natural gas liquefaction processes using reliable, black-box process simulation. The …

Bayesian Symbolic Learning to Build Analytical Correlations from Rigorous Process Simulations: Application to CO2 Capture Technologies

V Negri, D Vázquez, M Sales-Pardo, R Guimerà… - ACS …, 2022 - ACS Publications
Process modeling has become a fundamental tool to guide experimental work.
Unfortunately, process models based on first principles can be expensive to develop and …

Energy and economic comparison of five mixed-refrigerant natural gas liquefaction processes

MAM Pereira, LF Santos, JA Caballero… - Energy Conversion and …, 2022 - Elsevier
The demand for liquified natural gas grows as it is an energy resource that has more flexible
means of transport than non-liquefied natural gas, and is more eco-friendly than other fossil …

[HTML][HTML] Hybrid analytical surrogate-based process optimization via Bayesian symbolic regression

S Jog, D Vázquez, LF Santos, JA Caballero… - Computers & Chemical …, 2024 - Elsevier
Modular chemical process simulators are widespread in chemical industries to design and
optimize production processes with sufficient accuracy. However, convergence issues and …

[HTML][HTML] Comparison of mixed refrigerant cycles for natural gas liquefaction: From single mixed refrigerant to mixed fluid cascade processes

K Tak, J Park, I Moon, U Lee - Energy, 2023 - Elsevier
Natural gas liquefaction plants have adopted mixed refrigerant (MR) cascade configurations
to improve energy efficiency and process irreversibility. The MR cascade processes consist …

Mimo coded generalized reduced dimension fourier algorithm for 3-d microwave imaging

AM Molaei, S Hu, R Kumar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this article, to accelerate data acquisition and image reconstruction procedures in a
multistatic short-range microwave imaging scenario, an orthogonal coding approach with …

Artificial intelligence-based surrogate modeling for computational cost-effective optimization of hydrogen liquefaction process

A Rehman, B Zhang, A Riaz, K Qadeer, S Min… - International Journal of …, 2024 - Elsevier
The chemical processes are inherently complex, and obtaining desired product quality and
high energy efficiency by optimizing the design variables is challenging. The progress in …