Highly concentrated hydrogen peroxide (H2O2) is an oxidant of growing interest for low-environmental-impact propulsion. Concentrating the dilute solutions commercially available, typically around 15 wt%, up to technical grade requires energy-intensive vacuum distillation. This work presents an atmospheric batch evaporator designed to pre-concentrate aqueous H2O2 from 15 to 70 wt% using forced airflow at 60◦C in an open-circuit configuration. The system was modeled in MATLAB through an ODE-based approach using the Manatt & Manatt (2004) Vapor–Liquid Equilibrium thermodynamics and a flat-plate laminar Sherwood correlation for gas-side mass transfer. The driving force was corrected with the NTU method to account for the progressive saturation of the gas along the headspace. A 3D CFD analysis (ANSYS Fluent, κ − ω SST) of the confined rectangular headspace was also performed to obtain a correction factor η on the mass transfer coefficient. Since the system uses ambient air, annual performance was assessed based on monthly averaged climate data from Monselice (PD). Results show batch times ranging from about 10 hours in winter to 11 hours in summer, with a cumulative H2O2 loss of approximately 17% of the initial charge and total energy consumption of approximately 6.25 kWh per batch. The system appears to be a viable and low-cost pre-concentration stage, able to significantly reduce the evaporative load on downstream vacuum distillation columns.

Highly concentrated hydrogen peroxide (H2O2) is an oxidant of growing interest for low-environmental-impact propulsion. Concentrating the dilute solutions commercially available, typically around 15 wt%, up to technical grade requires energy-intensive vacuum distillation. This work presents an atmospheric batch evaporator designed to pre-concentrate aqueous H2O2 from 15 to 70 wt% using forced airflow at 60◦C in an open-circuit configuration. The system was modeled in MATLAB through an ODE-based approach using the Manatt & Manatt (2004) Vapor–Liquid Equilibrium thermodynamics and a flat-plate laminar Sherwood correlation for gas-side mass transfer. The driving force was corrected with the NTU method to account for the progressive saturation of the gas along the headspace. A 3D CFD analysis (ANSYS Fluent, κ − ω SST) of the confined rectangular headspace was also performed to obtain a correction factor η on the mass transfer coefficient. Since the system uses ambient air, annual performance was assessed based on monthly averaged climate data from Monselice (PD). Results show batch times ranging from about 10 hours in winter to 11 hours in summer, with a cumulative H2O2 loss of approximately 17% of the initial charge and total energy consumption of approximately 6.25 kWh per batch. The system appears to be a viable and low-cost pre-concentration stage, able to significantly reduce the evaporative load on downstream vacuum distillation columns.

Design and modelling of an atmospheric batch concentration system for hydrogen peroxide solutions

BALLO, FEDERICO
2025/2026

Abstract

Highly concentrated hydrogen peroxide (H2O2) is an oxidant of growing interest for low-environmental-impact propulsion. Concentrating the dilute solutions commercially available, typically around 15 wt%, up to technical grade requires energy-intensive vacuum distillation. This work presents an atmospheric batch evaporator designed to pre-concentrate aqueous H2O2 from 15 to 70 wt% using forced airflow at 60◦C in an open-circuit configuration. The system was modeled in MATLAB through an ODE-based approach using the Manatt & Manatt (2004) Vapor–Liquid Equilibrium thermodynamics and a flat-plate laminar Sherwood correlation for gas-side mass transfer. The driving force was corrected with the NTU method to account for the progressive saturation of the gas along the headspace. A 3D CFD analysis (ANSYS Fluent, κ − ω SST) of the confined rectangular headspace was also performed to obtain a correction factor η on the mass transfer coefficient. Since the system uses ambient air, annual performance was assessed based on monthly averaged climate data from Monselice (PD). Results show batch times ranging from about 10 hours in winter to 11 hours in summer, with a cumulative H2O2 loss of approximately 17% of the initial charge and total energy consumption of approximately 6.25 kWh per batch. The system appears to be a viable and low-cost pre-concentration stage, able to significantly reduce the evaporative load on downstream vacuum distillation columns.
2025
Design and modelling of an atmospheric batch concentration system for hydrogen peroxide solutions
Highly concentrated hydrogen peroxide (H2O2) is an oxidant of growing interest for low-environmental-impact propulsion. Concentrating the dilute solutions commercially available, typically around 15 wt%, up to technical grade requires energy-intensive vacuum distillation. This work presents an atmospheric batch evaporator designed to pre-concentrate aqueous H2O2 from 15 to 70 wt% using forced airflow at 60◦C in an open-circuit configuration. The system was modeled in MATLAB through an ODE-based approach using the Manatt & Manatt (2004) Vapor–Liquid Equilibrium thermodynamics and a flat-plate laminar Sherwood correlation for gas-side mass transfer. The driving force was corrected with the NTU method to account for the progressive saturation of the gas along the headspace. A 3D CFD analysis (ANSYS Fluent, κ − ω SST) of the confined rectangular headspace was also performed to obtain a correction factor η on the mass transfer coefficient. Since the system uses ambient air, annual performance was assessed based on monthly averaged climate data from Monselice (PD). Results show batch times ranging from about 10 hours in winter to 11 hours in summer, with a cumulative H2O2 loss of approximately 17% of the initial charge and total energy consumption of approximately 6.25 kWh per batch. The system appears to be a viable and low-cost pre-concentration stage, able to significantly reduce the evaporative load on downstream vacuum distillation columns.
Hydrogen Peroxide
Process simulation
Batch systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/109458