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This unit brings together physicists, mathematicians, electronic engineers, chemical engineers, and environmental science experts specializing in the design, optimization, control, and evaluation of biological and technological processes and systems. It focuses on the automation and control of complex systems in the process industry, as well as the modeling and simulation of these systems in computational environments to optimize performance, enhance operational efficiency, and promote sustainability. In the field of biological systems, the unit employs computational modeling and simulation techniques to characterize and design biological systems with innovative or enhanced metabolic capabilities, aimed at developing applications for environmental protection and industrial sustainability. Additionally, adopting a comprehensive perspective, industrial processes are assessed in terms of their techno-economic feasibility, eco-efficiency, risk management, and resilience, providing tools for informed decision-making, with a notable specialization in urban water cycle processes.
Process modeling and simulation: development of dynamic, gray box, hybrid or reduced models; simulators for personnel training; digital twins for decision support; parameter estimation; data reconciliation.
Advanced process control: control systems; model-based predictive control (MPC); Economy MPC and hybrid MPC.
Optimal process operation: real-time optimization; coordination of continuous and batch processes; scheduling; optimization with uncertainty; stochastic optimization in two stages.
Process supervision: resource use efficiency indicators (REIs/KPIs); plant-wide data reconciliation; estimation of unmeasured variables; controller supervision; fault detection and diagnosis methods.
Industrial Computing: development of control systems (DCS, MPC) and functionalities with industrial applications; OPC-based systems for communications between processes and systems; implementation of large-scale systems with real-time databases (Osisoft PI); Hardware in the Loop (HIL) systems.
Artificial neural networks
Development of sustainability indicators in the urban water cycle.
Water-energy-carbon nexus in the urban water cycle.
Analysis of economic viability including valuation of environmental externalities.
Evaluation of the technical, economic and environmental efficiency in the provision of drinking water and wastewater treatment.
Assessment of risk and resilience in the urban water cycle in the face of natural threats.
Mocholi-Arce, M., Sala-Garrido, R., Molinos-Senante, M., Maziotis, A. (2025) A comprehensive evaluation of eco-productivity of the municipal solid waste service in Chile. Frontiers of Environmental Science & Engineering. https://doi.org/10.1007/s11783-025-1931-9
Marcos-Rodrigo, E., Lebrero, R., Muñoz, R., Sousa, D.Z., Cantera, S. (2025) Syngas biological transformation into hydroxyectoine. Bioresource Technology. https://doi.org/10.1016/j.biortech.2024.131842
Herrero-Lobo, R., Torres Franco, A.F., Lebrero, R., Rodero, M.D.R., Muñoz, R. (2025) Evaluation of the influence of the gas residence time and biomass concentration on methane bioconversion to ectoines in a novel Taylor flow bioreactor. Journal of Environmental Management. https://doi.org/10.1016/j.jenvman.2024.123592
Severi, C.A., Pascual, C., Perez, V., Muñoz, R., Lebrero, R. (2025) Pilot-Scale Biogas Desulfurization through Anoxic Biofiltration. Journal of Hazardous Materials. https://doi.org/10.1016/j.jhazmat.2024.136830
de la Fuente Tagarro, C., Martín-González, D., De Lucas, A., Bordel, S., Santos-Beneit, F. (2024) Current Knowledge on CRISPR Strategies Against Antimicrobial-Resistant Bacteria. Antibiotics. https://doi.org/10.3390/antibiotics13121141
