Luis Ricardez‐Sandoval
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View article: Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling Open
The optimization of expensive black-box functions is ubiquitous in science and engineering. A common solution to this problem is Bayesian optimization (BO), which is generally comprised of two components: (i) a surrogate model and (ii) an …
View article: Trends and perspectives in deterministic MINLP optimization for integrated planning, scheduling, control, and design of chemical processes
Trends and perspectives in deterministic MINLP optimization for integrated planning, scheduling, control, and design of chemical processes Open
Mixed integer nonlinear programming (MINLP) in chemical engineering originated as a tool for solving optimal process synthesis and design problems. Since then, the application of MINLP has expanded to encompass control and operational deci…
View article: A reinforcement learning approach with masked agents for chemical process flowsheet design
A reinforcement learning approach with masked agents for chemical process flowsheet design Open
This study introduces two novel Reinforcement Learning (RL) agents for the design and optimization of chemical process flowsheets (CPFs): a discrete masked Proximal Policy Optimization (mPPO) and a hybrid masked Proximal Policy Optimizatio…
View article: Insights into the role of surface oxygen vacancy in CuCeO2 catalyst for reverse water gas shift
Insights into the role of surface oxygen vacancy in CuCeO2 catalyst for reverse water gas shift Open
This study presents the synthesis, characterization, and performance evaluation of copper-doped ceria (Cu/CeO2) catalysts with varying Cu/(Cu + Ce) atomic percentages in the context of the reverse water gas shift (RWGS) reaction. Temperatu…
View article: Transition‐Metal‐Doped CeO<sub>2</sub> for the Reverse Water‐Gas Shift Reaction: An Experimental and Theoretical Study on CO<sub>2</sub> Adsorption and Surface Vacancy Effects
Transition‐Metal‐Doped CeO<sub>2</sub> for the Reverse Water‐Gas Shift Reaction: An Experimental and Theoretical Study on CO<sub>2</sub> Adsorption and Surface Vacancy Effects Open
Transition metal‐doped ceria (M−CeO 2 ) catalysts (M=Fe, Co, Ni and Cu) with multiple loadings were experimentally investigated for reverse water gas shift (RWGS) reaction. Density functional theory (DFT) calculations were performed to ben…
View article: Insights into Mechanisms of Reverse Water Gas Shift Activity Enhancement over Reverse Microemulsion‐Synthesized CuCeO<sub>2</sub>
Insights into Mechanisms of Reverse Water Gas Shift Activity Enhancement over Reverse Microemulsion‐Synthesized CuCeO<sub>2</sub> Open
Copper‐doped ceria (CuCeO 2 ) catalysts with 0–26.5 Cu/(Cu+Ce) at% were synthesized via the reverse microemulsion method. X‐ray diffraction analysis of freshly synthesized and spent (post‐reaction) catalysts showed no separate phase of cop…
View article: A recurrent reinforcement learning strategy for optimal scheduling of partially observable job-shop and flow-shop batch chemical plants under uncertainty
A recurrent reinforcement learning strategy for optimal scheduling of partially observable job-shop and flow-shop batch chemical plants under uncertainty Open
This study presents a methodology that makes use of Deep Recurrent Q-Learning to develop an agent that acts as an online scheduler for flow-shop or job-shop batch plants with zero-wait restriction under uncertainty. The environment is assu…
View article: Multicut logic‐based Benders decomposition for discrete‐time scheduling and dynamic optimization of network batch plants
Multicut logic‐based Benders decomposition for discrete‐time scheduling and dynamic optimization of network batch plants Open
This study presents the first application of a logic‐based Benders decomposition (LBBD) technique in the field of simultaneous scheduling and dynamic optimization (SSDO), applied to network batch processes with a discrete‐time scheduling f…
View article: Logic-Based Discrete-Steepest Descent: A Solution Method for Process Synthesis Generalized Disjunctive Programs
Logic-Based Discrete-Steepest Descent: A Solution Method for Process Synthesis Generalized Disjunctive Programs Open
The optimization of chemical processes is challenging due to the nonlinearities arising from process physics and discrete design decisions. In particular, optimal synthesis and design of chemical processes can be posed as a Generalized Dis…
View article: Economically optimal operation of recirculating aquaculture systems under uncertainty
Economically optimal operation of recirculating aquaculture systems under uncertainty Open
This study presents a novel economical operation scheme for recirculating aquaculture systems (RASs). The proposed approach is comprised of a moving horizon estimator and an economic model predictive controller (EMPC), which, respectively,…
View article: An optimal sustainable planning strategy for national carbon capture deployment: A review on the state of<scp>CO<sub>2</sub></scp>capture in Canada
An optimal sustainable planning strategy for national carbon capture deployment: A review on the state of<span>CO<sub>2</sub></span>capture in Canada Open
This study reviews the steps Canada is taking to address sustainable decarbonization in the context of carbon capture. This work also presents a new optimal framework for national optimal deployment in need of strategic carbon capture impl…
View article: Reactor network modelling for biomass-fueled chemical-looping gasification and combustion processes
Reactor network modelling for biomass-fueled chemical-looping gasification and combustion processes Open
A reactor network was developed to predict the performance of biomass-fueled chemical-looping gasification (CLG) and chemical-looping combustion (CLC) in packed beds. The reactor network consists of a combination of continuous stirred-tank…
View article: A multistage stochastic programming approach for short-term scheduling of batch processes under type II endogenous uncertainty
A multistage stochastic programming approach for short-term scheduling of batch processes under type II endogenous uncertainty Open
In this study, we present a novel multistage stochastic programming approach for scheduling of batch operations under type II endogenous uncertainty (where time of uncertainty realization is model dependent). The proposed multistage framew…
View article: A bibliometric study of Chitosan Applications: Insights from processes
A bibliometric study of Chitosan Applications: Insights from processes Open
Chitosan is a high-value compound in the world market and can be obtained, mostly, from crustaceans, as they are shrimps, crabs, and lobsters, but other sources are fungal cell walls and algae. In 2027, the size of the market is estimated …