Articles de revista
http://hdl.handle.net/2117/3142
2024-03-19T04:25:42ZInformation retrieval from scientific abstract and citation databases: A query-by-documents approach based on Monte-Carlo sampling
http://hdl.handle.net/2117/370214
Information retrieval from scientific abstract and citation databases: A query-by-documents approach based on Monte-Carlo sampling
Lechtenberg, Fabian; Farreres de la Morena, Xavier; Galvan Cara, Aldwin Lois; Somoza Tornos, Ana; Espuña Camarasa, Antonio; Graells Sobré, Moisès
The rapidly increasing amount of information and entries in abstract and citation databases steadily complicates the information retrieval task. In this study, a novel query-by-document approach using Monte-Carlo sampling of relevant keywords is presented. From a set of input documents (seed) keywords are extracted using TF-IDF and subsequently sampled to repeatedly construct queries to the database. The occurrence of returned documents is counted and serves as a proxy relevance metric. Two case studies based on the Scopus® database are used to demonstrate the method and its key advantages. No expert knowledge and human intervention is needed to construct the final search strings which reduces the human bias. The methods practicality is supported by the high re-retrieval of seed documents of 7/8 and 26/31 in high ranks in the two presented case studies.
2022-07-14T13:13:08ZLechtenberg, FabianFarreres de la Morena, XavierGalvan Cara, Aldwin LoisSomoza Tornos, AnaEspuña Camarasa, AntonioGraells Sobré, MoisèsThe rapidly increasing amount of information and entries in abstract and citation databases steadily complicates the information retrieval task. In this study, a novel query-by-document approach using Monte-Carlo sampling of relevant keywords is presented. From a set of input documents (seed) keywords are extracted using TF-IDF and subsequently sampled to repeatedly construct queries to the database. The occurrence of returned documents is counted and serves as a proxy relevance metric. Two case studies based on the Scopus® database are used to demonstrate the method and its key advantages. No expert knowledge and human intervention is needed to construct the final search strings which reduces the human bias. The methods practicality is supported by the high re-retrieval of seed documents of 7/8 and 26/31 in high ranks in the two presented case studies.Towards an efficient generalization of the online dosage of hydrogen peroxide in photo-fenton process to treat industrial wastewater
http://hdl.handle.net/2117/363371
Towards an efficient generalization of the online dosage of hydrogen peroxide in photo-fenton process to treat industrial wastewater
Yu, Xiangwei; Cabrera Reina, Alejandro; Graells Sobré, Moisès; Miralles Cuevas, Sara; Pérez Moya, Montserrat
This work addresses the dosage of H2O2 in photo-Fenton processes and the monitoring of Dissolved oxygen (DO) that can be used to drive the dosage of H2O2. The objective of this work is to show that a smarter monitoring of a process variable such as DO (for which on-line measurement can be inexpensively obtained) enables the proposal and implementation of efficient dosage strategies. The work explores the application of a recent proposed strategy consisting of: (i) initial H2O2 addition, (ii) continuous H2O2 addition until a DO set up is reached, and (iii) automatic H2O2 addition by an on-off control system based on DO slope monitoring, and applies it to the treatment of different individual contaminants and their mixtures (paracetamol and sulfamethazine). The assays performed following this dosage strategy showed improved values of TOC removed per H2O2 consumed. For the case of sulfamethazine, this improvement increased up to 25–35% with respect to the efficiency obtained without dosage. Furthermore, a deeper analysis of the results allowed detecting and assessing the opportunity to redesign the dosage scheme and reduce its complexity and the number of control parameters. The promising results obtained are discussed in regard of future research into further increasing the simplicity and robustness of this generalized control strategy that improves the applicability of the photo-Fenton process by reducing its operating costs and increasing automation
2022-03-03T11:52:08ZYu, XiangweiCabrera Reina, AlejandroGraells Sobré, MoisèsMiralles Cuevas, SaraPérez Moya, MontserratThis work addresses the dosage of H2O2 in photo-Fenton processes and the monitoring of Dissolved oxygen (DO) that can be used to drive the dosage of H2O2. The objective of this work is to show that a smarter monitoring of a process variable such as DO (for which on-line measurement can be inexpensively obtained) enables the proposal and implementation of efficient dosage strategies. The work explores the application of a recent proposed strategy consisting of: (i) initial H2O2 addition, (ii) continuous H2O2 addition until a DO set up is reached, and (iii) automatic H2O2 addition by an on-off control system based on DO slope monitoring, and applies it to the treatment of different individual contaminants and their mixtures (paracetamol and sulfamethazine). The assays performed following this dosage strategy showed improved values of TOC removed per H2O2 consumed. For the case of sulfamethazine, this improvement increased up to 25–35% with respect to the efficiency obtained without dosage. Furthermore, a deeper analysis of the results allowed detecting and assessing the opportunity to redesign the dosage scheme and reduce its complexity and the number of control parameters. The promising results obtained are discussed in regard of future research into further increasing the simplicity and robustness of this generalized control strategy that improves the applicability of the photo-Fenton process by reducing its operating costs and increasing automationA machine learning-based methodology for multi-parametric solution of chemical processes operation optimization under uncertainty
http://hdl.handle.net/2117/360198
A machine learning-based methodology for multi-parametric solution of chemical processes operation optimization under uncertainty
Shokry Abdelaleem Taha Zied, Ahmed; Medina González, Sergio; Baraldi, Piero; Zio, Enrico; Moulines, Eric François Victor; Espuña Camarasa, Antonio
Chemical process operation optimization aims at obtaining the optimal operating set-points by real-time solution of an optimization problem that embeds a steady-state model of the process. This task is challenged by unavoidable Uncertain Parameters (UPs) variations. MultiParametric Programming (MPP) is an approach for solving this challenge, where the optimal set-points must be updated online, reacting to sudden changes in the UPs. MPP provides algebraic functions describing the optimal solution as a function of the UPs, which allows alleviating large computational cost required for solving the optimization problem each time the UPs values vary. However, MPP applicability requires a well-constructed mathematical model of the process, which is not suited for process operation optimization, where complex, highly nonlinear and/or black-box models are usually used. To tackle this issue, this paper proposes a machine learning-based methodology for multiparametric solution of continuous optimization problems. The methodology relies on the offline development of data-driven models that accurately approximate the multiparametric behavior of the optimal solution over the UPs space. The models are developed using data generated by running the optimization using the original complex process model under different UPs values. The models are, then, used online to, quickly, predict the optimal solutions in response to UPs variation. The methodology is applied to benchmark examples and two case studies of process operation optimization. The results demonstrate the methodology effectiveness in terms of high prediction accuracy (less than 1% of NRMSE, in most cases), robustness to deal with problems of different natures (linear, bilinear, quadratic, nonlinear and/or black boxes) and significant reduction in the complexity of the solution procedure compared to traditional approaches (a minimum of 67% reduction in the optimization time).
2022-01-20T12:11:20ZShokry Abdelaleem Taha Zied, AhmedMedina González, SergioBaraldi, PieroZio, EnricoMoulines, Eric François VictorEspuña Camarasa, AntonioChemical process operation optimization aims at obtaining the optimal operating set-points by real-time solution of an optimization problem that embeds a steady-state model of the process. This task is challenged by unavoidable Uncertain Parameters (UPs) variations. MultiParametric Programming (MPP) is an approach for solving this challenge, where the optimal set-points must be updated online, reacting to sudden changes in the UPs. MPP provides algebraic functions describing the optimal solution as a function of the UPs, which allows alleviating large computational cost required for solving the optimization problem each time the UPs values vary. However, MPP applicability requires a well-constructed mathematical model of the process, which is not suited for process operation optimization, where complex, highly nonlinear and/or black-box models are usually used. To tackle this issue, this paper proposes a machine learning-based methodology for multiparametric solution of continuous optimization problems. The methodology relies on the offline development of data-driven models that accurately approximate the multiparametric behavior of the optimal solution over the UPs space. The models are developed using data generated by running the optimization using the original complex process model under different UPs values. The models are, then, used online to, quickly, predict the optimal solutions in response to UPs variation. The methodology is applied to benchmark examples and two case studies of process operation optimization. The results demonstrate the methodology effectiveness in terms of high prediction accuracy (less than 1% of NRMSE, in most cases), robustness to deal with problems of different natures (linear, bilinear, quadratic, nonlinear and/or black boxes) and significant reduction in the complexity of the solution procedure compared to traditional approaches (a minimum of 67% reduction in the optimization time).Targeting economic and environmental benefits associated with the integration of regeneration units in water systems
http://hdl.handle.net/2117/359134
Targeting economic and environmental benefits associated with the integration of regeneration units in water systems
Lechtenberg, Fabian; Somoza Tornos, Ana; Espuña Camarasa, Antonio; Graells Sobré, Moisès
Water treatment is traditionally seen as an "end-of-pipe" solution to deal with contaminated water satisfying discharge regulations at a minimum expense. However, the reuse of treated water as regenerated water is a promising strategy to counteract water scarcity. This approach to transform waste into resources is motivated by the circular economy paradigm. This study presents a mathematical programming approach to target both the environmental and economic benefits of water systems by introducing additional regeneration units to close the loop. In addition to water users and authorities, the approach also considers operators and dealers, which are revealed as key stakeholders. Hence, the feasible region of the regeneration units design specifications is determined and visualized through a multi-objective optimization approach targeting the systems operating cost and freshwater consumption. Its application is demonstrated on a benchmark case study from the literature, revealing a potential economic benefit of 37.5% and a freshwater reduction of 80.9% over the case without regeneration units. Furthermore, we show that a cooperative exchange strategy leads to higher benefits compared to the solutions presented in the literature. Finally, we demonstrate how the barrier plots introduced in this work can be used by different stakeholders in the water market to support their decision-making.
2021-12-23T12:41:34ZLechtenberg, FabianSomoza Tornos, AnaEspuña Camarasa, AntonioGraells Sobré, MoisèsWater treatment is traditionally seen as an "end-of-pipe" solution to deal with contaminated water satisfying discharge regulations at a minimum expense. However, the reuse of treated water as regenerated water is a promising strategy to counteract water scarcity. This approach to transform waste into resources is motivated by the circular economy paradigm. This study presents a mathematical programming approach to target both the environmental and economic benefits of water systems by introducing additional regeneration units to close the loop. In addition to water users and authorities, the approach also considers operators and dealers, which are revealed as key stakeholders. Hence, the feasible region of the regeneration units design specifications is determined and visualized through a multi-objective optimization approach targeting the systems operating cost and freshwater consumption. Its application is demonstrated on a benchmark case study from the literature, revealing a potential economic benefit of 37.5% and a freshwater reduction of 80.9% over the case without regeneration units. Furthermore, we show that a cooperative exchange strategy leads to higher benefits compared to the solutions presented in the literature. Finally, we demonstrate how the barrier plots introduced in this work can be used by different stakeholders in the water market to support their decision-making.Application of industrial symbiosis principles to the management of utility networks
http://hdl.handle.net/2117/356666
Application of industrial symbiosis principles to the management of utility networks
Galvan Cara, Aldwin Lois; Graells Sobré, Moisès; Espuña Camarasa, Antonio
Utility exchanges between different plants have shown to produce large energy savings, extending the potential advantages of Energy/Process Integration through Industrial Symbiosis principles. Systematic approaches to determine such exchanges in industrial networks have been already proposed, although some of them are only applicable to specific situations and some others introduce the figure of a central authority. However, assuming such a figure in non-cooperative situations may restrict the economic benefit of some companies involved, thus discouraging their participation and preventing eventual agreements. The aim of this work is to develop an optimization model that allows analyzing the different symbiosis alternatives in different conflicting situations, even without the presence of any authority. Scenarios inspired by Game Theory have been considered. The problem has been modelled using a Mixed Integer Linear Programming (MILP) formulation and its capacities are illustrated through a particular case from the literature. Results show that the method allows establishing utility exchanges between different plants, which can improve the energetic, economic and environmental efficiency of all of them, as well as the whole set. Considering cooperative scenarios may allow determining solutions producing total energy savings and cost reductions, but without taking the specific interests of individual companies into account. On the other hand, considering non-cooperative scenarios ensures desirable outcomes from the eventual agreements for each company. Furthermore, the model is able to identify the economic barriers of the companies for participating, thus, being a useful and applicable tool that may improve decision-making support for managing utility networks in such situations.
2021-11-18T11:36:17ZGalvan Cara, Aldwin LoisGraells Sobré, MoisèsEspuña Camarasa, AntonioUtility exchanges between different plants have shown to produce large energy savings, extending the potential advantages of Energy/Process Integration through Industrial Symbiosis principles. Systematic approaches to determine such exchanges in industrial networks have been already proposed, although some of them are only applicable to specific situations and some others introduce the figure of a central authority. However, assuming such a figure in non-cooperative situations may restrict the economic benefit of some companies involved, thus discouraging their participation and preventing eventual agreements. The aim of this work is to develop an optimization model that allows analyzing the different symbiosis alternatives in different conflicting situations, even without the presence of any authority. Scenarios inspired by Game Theory have been considered. The problem has been modelled using a Mixed Integer Linear Programming (MILP) formulation and its capacities are illustrated through a particular case from the literature. Results show that the method allows establishing utility exchanges between different plants, which can improve the energetic, economic and environmental efficiency of all of them, as well as the whole set. Considering cooperative scenarios may allow determining solutions producing total energy savings and cost reductions, but without taking the specific interests of individual companies into account. On the other hand, considering non-cooperative scenarios ensures desirable outcomes from the eventual agreements for each company. Furthermore, the model is able to identify the economic barriers of the companies for participating, thus, being a useful and applicable tool that may improve decision-making support for managing utility networks in such situations.Manufacturing and application of 3D printed photo fenton reactors for wastewater treatment
http://hdl.handle.net/2117/356505
Manufacturing and application of 3D printed photo fenton reactors for wastewater treatment
Nasr Esfahani, Kourosh; Zandi, Mohammad Damous; Travieso Rodríguez, José Antonio; Graells Sobré, Moisès; Pérez Moya, Montserrat
Additive manufacturing (AM) or 3D printing offers a new paradigm for designing and developing chemical reactors, in particular, prototypes. The use of 3D printers has been increasing, their performance has been improving, and their price has been reducing. While the general trend is clear, particular applications need to be assessed for their practicality. This study develops and follows a systematic approach to the prototyping of Advanced Oxidation Processes (AOP) reactors. Specifically, this work evaluates and discusses different printable materials in terms of mechanical and chemical resistance to photo-Fenton reactants. Metallic and ceramic materials are shown to be impracticable due to their high printing cost. Polymeric and composite materials are sieved according to criteria such as biodegradability, chemical, thermal, and mechanical resistance. Finally, 3D-printed prototypes are produced and tested in terms of leakage and resistance to the photo-Fenton reacting environment. Polylactic acid (PLA) and wood–PLA composite (Timberfill®) were selected, and lab-scale raceway pond reactors (RPR) were printed accordingly. They were next exposed to H2O2/Fe(II) solutions at pH = 3 ± 0.2 and UV radiation. After 48 h reaction tests, results revealed that the Timberfill® reactor produced higher Total Organic Carbon (TOC) concentrations (9.6 mg·L-1) than that obtained for the PLA reactor (5.5 mg·L-1) and Pyrex® reactor (5.2 mg·L-1), which suggests the interference of Timberfill® with the reaction. The work also considers and discusses further chemical and mechanical criteria that also favor PLA for 3D-printing Fenton and photo-Fenton reactors. Finally, the work also provides a detailed explanation of the printing parameters used and guidelines for preparing prototypes
2021-11-16T10:54:34ZNasr Esfahani, KouroshZandi, Mohammad DamousTravieso Rodríguez, José AntonioGraells Sobré, MoisèsPérez Moya, MontserratAdditive manufacturing (AM) or 3D printing offers a new paradigm for designing and developing chemical reactors, in particular, prototypes. The use of 3D printers has been increasing, their performance has been improving, and their price has been reducing. While the general trend is clear, particular applications need to be assessed for their practicality. This study develops and follows a systematic approach to the prototyping of Advanced Oxidation Processes (AOP) reactors. Specifically, this work evaluates and discusses different printable materials in terms of mechanical and chemical resistance to photo-Fenton reactants. Metallic and ceramic materials are shown to be impracticable due to their high printing cost. Polymeric and composite materials are sieved according to criteria such as biodegradability, chemical, thermal, and mechanical resistance. Finally, 3D-printed prototypes are produced and tested in terms of leakage and resistance to the photo-Fenton reacting environment. Polylactic acid (PLA) and wood–PLA composite (Timberfill®) were selected, and lab-scale raceway pond reactors (RPR) were printed accordingly. They were next exposed to H2O2/Fe(II) solutions at pH = 3 ± 0.2 and UV radiation. After 48 h reaction tests, results revealed that the Timberfill® reactor produced higher Total Organic Carbon (TOC) concentrations (9.6 mg·L-1) than that obtained for the PLA reactor (5.5 mg·L-1) and Pyrex® reactor (5.2 mg·L-1), which suggests the interference of Timberfill® with the reaction. The work also considers and discusses further chemical and mechanical criteria that also favor PLA for 3D-printing Fenton and photo-Fenton reactors. Finally, the work also provides a detailed explanation of the printing parameters used and guidelines for preparing prototypesSynthesis and assessment of waste-to-resource routes for circular economy
http://hdl.handle.net/2117/356132
Synthesis and assessment of waste-to-resource routes for circular economy
Pacheco López, Adrian; Somoza Tornos, Ana; Graells Sobré, Moisès; Espuña Camarasa, Antonio
The benefits of the circular economy have been proven during the past two decades, but its application poses some challenges. In particular, the increasing number of potential waste-to-resource processing alternatives obstructs the identification of the most promising ones, besides the lack of efficient knowledge management tools and standardized assessment procedures. This contribution presents a systematic way to generate and assess new processing paths including waste-to-resource technologies, based on the use of a semi-automatic ontological framework. An ontology is filled with transformation processes; then, a number of alternative paths are generated and assessed, according to a potentially available waste. The resulting list is classified according to pre-established parameters, thus presenting which are the potentially best alternatives to close the material loops and recover chemical resources. The proposed method is tested through the generation and evaluation of different routes for the treatment of plastic waste materials, with a special focus on chemical recycling.
2021-11-11T12:17:48ZPacheco López, AdrianSomoza Tornos, AnaGraells Sobré, MoisèsEspuña Camarasa, AntonioThe benefits of the circular economy have been proven during the past two decades, but its application poses some challenges. In particular, the increasing number of potential waste-to-resource processing alternatives obstructs the identification of the most promising ones, besides the lack of efficient knowledge management tools and standardized assessment procedures. This contribution presents a systematic way to generate and assess new processing paths including waste-to-resource technologies, based on the use of a semi-automatic ontological framework. An ontology is filled with transformation processes; then, a number of alternative paths are generated and assessed, according to a potentially available waste. The resulting list is classified according to pre-established parameters, thus presenting which are the potentially best alternatives to close the material loops and recover chemical resources. The proposed method is tested through the generation and evaluation of different routes for the treatment of plastic waste materials, with a special focus on chemical recycling.A CFD study of an annular pilot plant reactor for Paracetamol photo-Fenton degradation
http://hdl.handle.net/2117/353286
A CFD study of an annular pilot plant reactor for Paracetamol photo-Fenton degradation
Venier, Cesar M.; Conte, Leandro Oscar; Pérez Moya, Montserrat; Graells Sobré, Moisès; Nigro, Norberto; Alfano, Orlando M.
This work studies in detail the photo-Fenton degradation process of Paracetamol (PCT) on an annular pilot-plant reactor using Computational Fluid Dynamics (CFD). A cylindrical lamp emission model was originally implemented over the structure of the OpenFOAM(R) platform and a multicomponent reaction mixture model was used to compute the temporal evolution of the different species at each point of the reactor. Once the proposed model was experimentally validated, the influence of different operating conditions (i.e. different strategies for hydrogen peroxide (HO) dosage, use of low recirculation flow rates (Qr), and a completely uncovered lamp setup) was studied. The results of the analysis showed that a double addition of HO (50% before the tank and 50% before the reactor) significantly reduces the reaction times of the process. Moreover, the overall PCT degradation rate does not change when Qr is increased, thus allowing the system to be operated with a recirculation flow three times lower than that the one used in the experiments. Thereby, the developed model allows identifying the reaction conditions that maximize the overall PCT conversion, making efficient use of HO (main chemical reagent) and reducing the electrical energy consumption (recirculation flow) by operating the system under conditions present in large-scale photochemical reactors.
2021-10-07T11:50:30ZVenier, Cesar M.Conte, Leandro OscarPérez Moya, MontserratGraells Sobré, MoisèsNigro, NorbertoAlfano, Orlando M.This work studies in detail the photo-Fenton degradation process of Paracetamol (PCT) on an annular pilot-plant reactor using Computational Fluid Dynamics (CFD). A cylindrical lamp emission model was originally implemented over the structure of the OpenFOAM(R) platform and a multicomponent reaction mixture model was used to compute the temporal evolution of the different species at each point of the reactor. Once the proposed model was experimentally validated, the influence of different operating conditions (i.e. different strategies for hydrogen peroxide (HO) dosage, use of low recirculation flow rates (Qr), and a completely uncovered lamp setup) was studied. The results of the analysis showed that a double addition of HO (50% before the tank and 50% before the reactor) significantly reduces the reaction times of the process. Moreover, the overall PCT degradation rate does not change when Qr is increased, thus allowing the system to be operated with a recirculation flow three times lower than that the one used in the experiments. Thereby, the developed model allows identifying the reaction conditions that maximize the overall PCT conversion, making efficient use of HO (main chemical reagent) and reducing the electrical energy consumption (recirculation flow) by operating the system under conditions present in large-scale photochemical reactors.Economic and environmental assessment of plastic waste pyrolysis products and biofuels as substitutes for fossil-based fuels
http://hdl.handle.net/2117/351618
Economic and environmental assessment of plastic waste pyrolysis products and biofuels as substitutes for fossil-based fuels
Pacheco López, Adrian; Lechtenberg, Fabian; Somoza Tornos, Ana; Graells Sobré, Moisès; Espuña Camarasa, Antonio
The global economy is shifting toward more sustainable sources of energy. The transportation sector is a remarkable example of this fact, where biofuels have emerged as promising alternatives to traditional fossil fuels. This work presents a techno-economic and environmental assessment of existing liquid fuels in hard-to-decarbonize sectors and their emerging renewable substitutes. The comparison focuses on fossil-based, biomass-derived, and plastic waste-sourced fuel alternatives that can be used in spark-ignition (gasoline) and compression-ignition (diesel) engines. Results for diesel substitutes prove the superior performance of plastic waste pyrolysis oil in terms of production cost reduction (-25% compared to diesel) and “well-to-tank” life cycle impact reduction (-54% human health, -40% ecosystems, -98% resources). Consequently, research and development toward the conversion of plastic waste into fuels should be extended to make the technology more accessible and robust in terms of fuel quality. On the contrary, the results for gasoline alternatives are not as conclusive: bioethanol and ethanol from plastic pyrolysis have a considerably lower impact on resource scarcity than gasoline (-80% and -35% respectively) and higher on the other two life cycle endpoint categories, but they have higher production costs compared to gasoline (+57% and +130% respectively). While blends of gasoline with pyrolysis-sourced ethanol can reduce the impact on human health and ecosystems, blends with bioethanol have a lower impact on resource scarcity and increase economic profitability. This allows fuel providers to offer tradeoff solutions in the form of blends based on their priorities.
2021-09-17T11:07:33ZPacheco López, AdrianLechtenberg, FabianSomoza Tornos, AnaGraells Sobré, MoisèsEspuña Camarasa, AntonioThe global economy is shifting toward more sustainable sources of energy. The transportation sector is a remarkable example of this fact, where biofuels have emerged as promising alternatives to traditional fossil fuels. This work presents a techno-economic and environmental assessment of existing liquid fuels in hard-to-decarbonize sectors and their emerging renewable substitutes. The comparison focuses on fossil-based, biomass-derived, and plastic waste-sourced fuel alternatives that can be used in spark-ignition (gasoline) and compression-ignition (diesel) engines. Results for diesel substitutes prove the superior performance of plastic waste pyrolysis oil in terms of production cost reduction (-25% compared to diesel) and “well-to-tank” life cycle impact reduction (-54% human health, -40% ecosystems, -98% resources). Consequently, research and development toward the conversion of plastic waste into fuels should be extended to make the technology more accessible and robust in terms of fuel quality. On the contrary, the results for gasoline alternatives are not as conclusive: bioethanol and ethanol from plastic pyrolysis have a considerably lower impact on resource scarcity than gasoline (-80% and -35% respectively) and higher on the other two life cycle endpoint categories, but they have higher production costs compared to gasoline (+57% and +130% respectively). While blends of gasoline with pyrolysis-sourced ethanol can reduce the impact on human health and ecosystems, blends with bioethanol have a lower impact on resource scarcity and increase economic profitability. This allows fuel providers to offer tradeoff solutions in the form of blends based on their priorities.An improved hybrid strategy for online dosage of hydrogen peroxide in photo-Fenton processes
http://hdl.handle.net/2117/346971
An improved hybrid strategy for online dosage of hydrogen peroxide in photo-Fenton processes
Yu, Xiangwei; Graells Sobré, Moisès; Miralles Cuevas, Sara; Cabrera Reina, Alejandro; Pérez Moya, Montserrat
This work addresses the challenge of designing H2O2 dosage strategies for improving photo-Fenton applications, as well as for further understanding the effect of the dosage. The developed strategy focuses on the limitations of the current solution schemes by adopting a hybrid methodology between open and closed loop approaches and it is based on three different stages: (i) one-shot initial H2O2 addition (ii) continuous H2O2 dosage until reaching a specific dissolved oxygen (DO) level and (iii) on-off control of H2O2 dosage using DO slope as control variable. The proposed strategy is validated in the remediation of a Paracetamol solution (100 mg L-1) and the results are assessed using H2O2 consumption and mineralization rate and level as performance criteria. The final tuning of the proposed strategy consists of: (i) only 40% of the stoichiometric H2O2 concentration, (ii) continuous feeding of H2O2 until a 4 mg L-1 DO concentration is attained, and (iii) on-off control dosage selecting DO slope set-points in 0.1 and 0.2 mg L-1 min-1. These scheme and settings show an improvement of the process performance by ~ 15% with respect to the same H2O2 amount in a single-addition. This work contributes to improving photo-Fenton operations and designing more efficient processes.
2021-06-09T13:09:26ZYu, XiangweiGraells Sobré, MoisèsMiralles Cuevas, SaraCabrera Reina, AlejandroPérez Moya, MontserratThis work addresses the challenge of designing H2O2 dosage strategies for improving photo-Fenton applications, as well as for further understanding the effect of the dosage. The developed strategy focuses on the limitations of the current solution schemes by adopting a hybrid methodology between open and closed loop approaches and it is based on three different stages: (i) one-shot initial H2O2 addition (ii) continuous H2O2 dosage until reaching a specific dissolved oxygen (DO) level and (iii) on-off control of H2O2 dosage using DO slope as control variable. The proposed strategy is validated in the remediation of a Paracetamol solution (100 mg L-1) and the results are assessed using H2O2 consumption and mineralization rate and level as performance criteria. The final tuning of the proposed strategy consists of: (i) only 40% of the stoichiometric H2O2 concentration, (ii) continuous feeding of H2O2 until a 4 mg L-1 DO concentration is attained, and (iii) on-off control dosage selecting DO slope set-points in 0.1 and 0.2 mg L-1 min-1. These scheme and settings show an improvement of the process performance by ~ 15% with respect to the same H2O2 amount in a single-addition. This work contributes to improving photo-Fenton operations and designing more efficient processes.