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Koopman Lyapunov‐based model predictive control of nonlinear chemical process systems

AIChE journal, 2019-11, Vol.65 (11), p.n/a

2019

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Operable adaptive sparse identification of systems: Application to chemical processes

AIChE journal, 2020-11, Vol.66 (11), p.n/a

2020

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Temporal clustering for order reduction of nonlinear parabolic PDE systems with time‐dependent spatial domains: Application to a hydraulic fracturing process

AIChE journal, 2017-09, Vol.63 (9), p.3818-3831

2017

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Exploring the potential of time-series transformers for process modeling and control in chemical systems: An inevitable paradigm shift?

Chemical engineering research & design, 2023-06, Vol.194, p.461-477

2023

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Multiscale modeling and multiobjective control of wood fiber morphology in batch pulp digester

AIChE journal, 2020-07, Vol.66 (7), p.n/a

2020

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Risk-based fault prediction of chemical processes using operable adaptive sparse identification of systems (OASIS)

Computers & chemical engineering, 2021-09, Vol.152, p.107378, Article 107378

2021

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Development of local dynamic mode decomposition with control: Application to model predictive control of hydraulic fracturing

Computers & chemical engineering, 2017-11, Vol.106, p.501-511

2017

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Multiscale modeling and control of Kappa number and porosity in a batch‐type pulp digester

AIChE journal, 2019-06, Vol.65 (6), p.n/a

2019

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CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers

Computers & chemical engineering, 2023-09, Vol.177, p.108339, Article 108339

2023

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Identification of cell‐to‐cell heterogeneity through systems engineering approaches

AIChE journal, 2020-05, Vol.66 (5), p.n/a

2020

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Deep hybrid model‐based predictive control with guarantees on domain of applicability

AIChE journal, 2023-05, Vol.69 (5), p.n/a

2023

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Development of a hybrid model for a partially known intracellular signaling pathway through correction term estimation and neural network modeling

PLoS computational biology, 2020-12, Vol.16 (12), p.e1008472-e1008472

2020

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Machine learning meets process control: Unveiling the potential of LSTMc

AIChE journal, 2024-07, Vol.70 (7), p.n/a

2024

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Modeling of hydraulic fracturing and designing of online pumping schedules to achieve uniform proppant concentration in conventional oil reservoirs

Computers & chemical engineering, 2018-06, Vol.114, p.306-317

2018

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Application of Koopman operator for model-based control of fracture propagation and proppant transport in hydraulic fracturing operation

Journal of process control, 2020-07, Vol.91 (C), p.25-36

2020

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Introducing Hybrid Modeling with Time-Series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization

Industrial & engineering chemistry research, 2023-12, Vol.62 (49), p.21278-21291

2023

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Deep hybrid modeling of chemical process: Application to hydraulic fracturing

Computers & chemical engineering, 2020-03, Vol.134 (C), p.106696, Article 106696

2020

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Application of offset‐free Koopman‐based model predictive control to a batch pulp digester

AIChE journal, 2021-09, Vol.67 (9), p.n/a

2021

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Feedback control of proppant bank heights during hydraulic fracturing for enhanced productivity in shale formations

AIChE journal, 2018-05, Vol.64 (5), p.1638-1650

2018

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Multiscale modeling and run-to-run control of PECVD of thin film solar cells

Renewable energy, 2017-01, Vol.100, p.129-140

2017

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A modified Bayesian network to handle cyclic loops in root cause diagnosis of process faults in the chemical process industry

Journal of process control, 2022-02, Vol.110, p.84-98

2022

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A computational approach to characterize formation of a passivation layer in lithium metal anodes

AIChE journal, 2021-01, Vol.67 (1), p.n/a

2021

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Achieving robustness in hybrid models: A physics-informed regularization approach for spatiotemporal parameter estimation in PDEs

Chemical engineering research & design, 2024-04, Vol.204, p.292-302

2024

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Experimental and thermodynamic study of aerosol explosions in a 36 L apparatus

Fuel (Guildford), 2019-06, Vol.245, p.467-477

2019

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Optimal pumping schedule design to achieve a uniform proppant concentration level in hydraulic fracturing

Computers & chemical engineering, 2017-06, Vol.101, p.138-147

2017

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Koopman Lyapunov‐based model predictive control of nonlinear chemical process systems

Operable adaptive sparse identification of systems: Application to chemical processes

Temporal clustering for order reduction of nonlinear parabolic PDE systems with time‐dependent spatial domains: Application to a hydraulic fracturing process

Exploring the potential of time-series transformers for process modeling and control in chemical systems: An inevitable paradigm shift?

Multiscale modeling and multiobjective control of wood fiber morphology in batch pulp digester

Risk-based fault prediction of chemical processes using operable adaptive sparse identification of systems (OASIS)

Development of local dynamic mode decomposition with control: Application to model predictive control of hydraulic fracturing

Multiscale modeling and control of Kappa number and porosity in a batch‐type pulp digester

CrystalGPT: Enhancing system-to-system transferability in crystallization prediction and control using time-series-transformers

Identification of cell‐to‐cell heterogeneity through systems engineering approaches

Deep hybrid model‐based predictive control with guarantees on domain of applicability

Development of a hybrid model for a partially known intracellular signaling pathway through correction term estimation and neural network modeling

Machine learning meets process control: Unveiling the potential of LSTMc

Modeling of hydraulic fracturing and designing of online pumping schedules to achieve uniform proppant concentration in conventional oil reservoirs

Application of Koopman operator for model-based control of fracture propagation and proppant transport in hydraulic fracturing operation

Introducing Hybrid Modeling with Time-Series-Transformers: A Comparative Study of Series and Parallel Approach in Batch Crystallization

Deep hybrid modeling of chemical process: Application to hydraulic fracturing

Application of offset‐free Koopman‐based model predictive control to a batch pulp digester

Feedback control of proppant bank heights during hydraulic fracturing for enhanced productivity in shale formations

Multiscale modeling and run-to-run control of PECVD of thin film solar cells

A modified Bayesian network to handle cyclic loops in root cause diagnosis of process faults in the chemical process industry

A computational approach to characterize formation of a passivation layer in lithium metal anodes

Achieving robustness in hybrid models: A physics-informed regularization approach for spatiotemporal parameter estimation in PDEs

Experimental and thermodynamic study of aerosol explosions in a 36 L apparatus

Optimal pumping schedule design to achieve a uniform proppant concentration level in hydraulic fracturing

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