Exergy-based multi-objective optimization of the green flash ironmaking process

Ironmaking and steelmaking are major contributors to global CO2 emissions, with traditional processes heavily reliant on fossil fuels. Recognizing the urgent need for decarbonization, the hydrogen-based flash ironmaking process offers a promising alternative for sustainable iron production. However, comprehensive performance assessments of this innovative approach remain limited. To address this gap, this study presents an exergy-based multi-objective optimization of the process, integrating a robust framework that combines thermodynamic, economic, and environmental analyses. Specifically, a detailed thermodynamic process model is developed, incorporating a kinetically controlled, non-isothermal reactor model alongside economic and environmental sub-models. The resulting models are used to perform exergy, exergoeconomic, and exergoenvironmental assessments, and are optimized using a surrogate-based black-box approach that efficiently navigates the multi-dimensional design space. In the base case, the process achieves an exergetic system efficiency of approximately 55 %. Targeted thermodynamic optimization improves this efficiency to 57.3 %, while an economic optimum reduces specific production costs to 12.9 $ ct kWh−1 and environmental optimization attains a minimum environmental impact intensity of 2.63 mPt kWh−1 relative to the chemical exergy in the reduced iron. These multi-objective trade-offs are comprehensively analyzed and visualized through Pareto frontiers that clearly relate decision variables to optimization objectives. A comparative assessment with conventional hydrogen-based shaft furnace reduction underscores the economic benefits of bypassing pelletization, yielding potential cost savings of 14-47$tDRI⁻¹. In summary, this study demonstrates the potential of hydrogen-based flash ironmaking and establishes a versatile, multi-dimensional exergy-based optimization framework applicable to a wide range of energy-intensive industrial processes.