Periodic Reporting for period 1 - R3VOLUTION (A rEVOLUTIONary approach for maximising process water REuse and REsource REcovery through a smart, circular and integrated solution)
Período documentado: 2024-01-01 hasta 2025-06-30
The R3VOLUTION project develops advanced water reuse technologies targeting minimum or zero liquid discharge in petrochemical, bio-based chemical, pulp & paper, and steel industries. It aims to achieve over 90% water reuse, >45% solute recovery, and >50% heat reuse, while eliminating hazardous substances. Innovations include biodegradable nanocellulose and ceramic membranes, enhanced through functionalization and digital tools for process optimization. With strong cross-sector transferability, R3VOLUTION promotes solution exploitation and communication for broad industry uptake. The project supports reduced water consumption, resource recovery, and EU goals on climate neutrality and circular economy.
Core technologies include high-performance filtration membranes, membrane distillation systems, machine learning-based optimization, and digital twin tools—targeting TRL 6 by the project end. A major technical focus is on designing solvent-resistant membranes and optimizing configurations for efficient water and energy reuse. Tailored membranes with adjustable flux, pore size, and strength support filtration from micro- to nanofiltration. Hydrophobic ceramic membranes in membrane distillation enable recovery of water and solutes from complex industrial effluents.
In the digital domain, the project is building digital twin models to simulate treatment processes, assess parameters, and deliver optimization insights. These include virtual sensors and computer vision tools for real-time monitoring. The system builds on and extends the existing Digital Process Assistant (DPA), improving water management across sectors.
R3VOLUTION will pilot four treatment trains in key industries and will deliver a full techno-economic and sustainability assessment to identify best practices for industrial reuse and energy recovery, aiming for widespread adoption. Project results advance the state of the art in wastewater treatment and circular resource use, supporting EU industrial water and sustainability policies. The project will provide a commercial roadmap to support long-term deployment across Europe.
Core technologies include high-performance filtration membranes, membrane distillation systems, machine learning-based optimization, and digital twin tools—targeting TRL 6 by the project end. A major technical focus is on designing solvent-resistant membranes and optimizing configurations for efficient water and energy reuse. Tailored membranes with adjustable flux, pore size, and strength support filtration from micro- to nanofiltration. Hydrophobic ceramic membranes in membrane distillation enable recovery of water and solutes from complex industrial effluents.
In the digital domain, the project is building digital twin models to simulate treatment processes, assess parameters, and deliver optimization insights. These include virtual sensors and computer vision tools for real-time monitoring. The system builds on and extends the existing Digital Process Assistant (DPA), improving water management across sectors.
R3VOLUTION will pilot four treatment trains in key industries and will deliver a full techno-economic and sustainability assessment to identify best practices for industrial reuse and energy recovery, aiming for widespread adoption. Project results advance the state of the art in wastewater treatment and circular resource use, supporting EU industrial water and sustainability policies. The project will provide a commercial roadmap to support long-term deployment across Europe.
Advanced membrane development (WP2): Nanocellulose-coated membranes were developed, characterized, and upscaled to pilot production using VTT’s roll-to-roll line. These membranes demonstrated high affinity rejection performance and are being distributed for lab-scale testing with real industrial samples. In parallel, ceramic membranes were enhanced through advanced surface functionalization techniques (FunMem and HYMEM), enabling tailored selectivity and tunable pore sizes. Lab-scale trials showed improved particle and ion rejection, validating their suitability for challenging streams. Additionally, membrane distillation using ceramic modules were tested with industrial samples, confirming great permeate quality. A semi-pilot VMD system was commissioned, supporting integration of heat recovery concepts in collaboration with SINTEF.
Process modelling, optimisation and AI tools (WP3): A robust Data Management Platform (DMP) was developed, integrating secure APIs and a PostgreSQL-based system to support seamless data exchange across use cases. Process models for membrane technologies have been calibrated for BLOOM and FELIX cases, enabling energy and mass balance estimation, and supporting WP5’s LCA and TEA. Preliminary optimisation frameworks and sensitivity analyses have been developed. In parallel, ML-based monitoring tools (including Reinforcement Learning and Virtual Sensing) were created and validated with industrial datasets. Early XAI prototypes using SHAP, LIME and PFI were applied to Celsa use case models. A Digital Twin Recommendation System powered by a RAG-enhanced LLM was deployed, with API endpoints now operational and being integrated with the user interface.
System design and demonstration (WP1): Pilot treatment trains were designed and tailored to each sector's water reuse targets and technical constraints. Key technologies across sites include UF/NF/RO combinations, MD for brine treatment, and targeted solute recovery. Procurement and construction have been initiated, with several units ready for installation. In parallel, virtual case configurations were defined for all demo sites and an additional mining case. These scenarios are aligned with the development of WP3 digital tools and will serve as a replication baseline. Early simulations and experimental data are already supporting model training and integration.
Process modelling, optimisation and AI tools (WP3): A robust Data Management Platform (DMP) was developed, integrating secure APIs and a PostgreSQL-based system to support seamless data exchange across use cases. Process models for membrane technologies have been calibrated for BLOOM and FELIX cases, enabling energy and mass balance estimation, and supporting WP5’s LCA and TEA. Preliminary optimisation frameworks and sensitivity analyses have been developed. In parallel, ML-based monitoring tools (including Reinforcement Learning and Virtual Sensing) were created and validated with industrial datasets. Early XAI prototypes using SHAP, LIME and PFI were applied to Celsa use case models. A Digital Twin Recommendation System powered by a RAG-enhanced LLM was deployed, with API endpoints now operational and being integrated with the user interface.
System design and demonstration (WP1): Pilot treatment trains were designed and tailored to each sector's water reuse targets and technical constraints. Key technologies across sites include UF/NF/RO combinations, MD for brine treatment, and targeted solute recovery. Procurement and construction have been initiated, with several units ready for installation. In parallel, virtual case configurations were defined for all demo sites and an additional mining case. These scenarios are aligned with the development of WP3 digital tools and will serve as a replication baseline. Early simulations and experimental data are already supporting model training and integration.
- Advanced membrane materials: The project is developing nanocellulose-coated and chemically functionalized ceramic membranes for enhanced selectivity, durability, and permeability. These are tailored for complex industrial effluents and tested across diverse real wastewater streams, supporting selective solute retention and reduced fouling.
- Integrated treatment systems: Pilot-scale treatment trains combine advanced filtration, membrane distillation, and electrochemical processes to recover water and key solutes. The pilots target >90% water reuse and demonstrate effective circular water management in 4 industrial sectors.
- AI-driven process optimization: A modular Digital Process Assistant is being developed that integrates machine learning, reinforcement learning, and explainable AI for predictive control and real-time fault detection. These tools outperform conventional monitoring systems and enable continuous optimization through virtual sensors and advanced data analytics.
- Energy efficiency and heat recovery: Membrane distillation units are being integrated with heat recovery concepts. Energy simulations and mass balances inform design strategies that reduce energy demand and enhance overall sustainability.
While strong technical foundations have been laid, further actions are required to ensure full impact:
- Pilot validation: Final commissioning and long-term monitoring will validate performance targets.
- Commercialisation strategy: Structured IPR protection, licensing, and business modelling are essential.
- Policy and market alignment: Broader uptake depends on clearer alignment with EU water reuse legislation, cost-performance benchmarks, and financial incentives to adopt high-efficiency treatment technologies.
- Integrated treatment systems: Pilot-scale treatment trains combine advanced filtration, membrane distillation, and electrochemical processes to recover water and key solutes. The pilots target >90% water reuse and demonstrate effective circular water management in 4 industrial sectors.
- AI-driven process optimization: A modular Digital Process Assistant is being developed that integrates machine learning, reinforcement learning, and explainable AI for predictive control and real-time fault detection. These tools outperform conventional monitoring systems and enable continuous optimization through virtual sensors and advanced data analytics.
- Energy efficiency and heat recovery: Membrane distillation units are being integrated with heat recovery concepts. Energy simulations and mass balances inform design strategies that reduce energy demand and enhance overall sustainability.
While strong technical foundations have been laid, further actions are required to ensure full impact:
- Pilot validation: Final commissioning and long-term monitoring will validate performance targets.
- Commercialisation strategy: Structured IPR protection, licensing, and business modelling are essential.
- Policy and market alignment: Broader uptake depends on clearer alignment with EU water reuse legislation, cost-performance benchmarks, and financial incentives to adopt high-efficiency treatment technologies.