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Abstract: The synthesis of heat exchanger networks (HENs) is an NP hard problem, made even more difficult by the requirement of commercial software licenses and coding ability. This paper introduces OpenHENS, a first-of-itskind open-source tool for HEN synthesis. In the literature, HEN synthesis based on mathematical programming almost exclusively relies on commercial MINLP (mixed-integer non-linear programming) solvers (e.g., BARON, Gurobi, etc.). Open source MINLP solvers, in contrast, lack the robustness, scalability and quality that are the hallmarks of commercial solvers. To overcome this challenge, OpenHENS embeds a novel three-step synthesis method that gradually increases the complexity of the model. The first two steps identify economically viable and thermodynamically feasible heat exchanger matches, removing the non-viable matches and reducing the problem size. In the third step, numerous HEN designs are obtained by evolving promising networks to obtain families of near-optimal solutions. OpenHENS was tested on thirteen benchmark problems and seven of the solutions were within 2 % of the total annualised cost (TAC) best-known solutions from literature. In eleven of the benchmark problems, OpenHENS returned more than 10 unique networks within 2 % of the best solution, enabling the engineer to select the most practical design with minimal cost difference. OpenHENS demonstrates that open-source software, when developed correctly, offers comparable performance to commercial software while promoting greater accessibility in industry.
Keywords: heat exchanger network, process integration, optimization, mathematical programming, open source, Phyton
Published in DKUM: 03.11.2025; Views: 0; Downloads: 1
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Abstract: Waste heat recovery technologies play an important role in enhancing energy efficiency and supporting sustainable energy production. This study investigates the utilization of waste heat from aluminium production through an Organic Rankine Cycle (ORC) system to generate electricity and heat simultaneously. Based on operational data from an aluminium plant, the system is firstly optimized from both the thermodynamic and economic perspectives. To maximize performance and to identify optimal configurations, a mathematical model is developed and solved using GAMS, capturing the complex interdependencies between the operational, economic and thermodynamic parameters. The environmental impact of the optimized scenarios is subsequently evaluated using a Life Cycle Assessment (LCA), considering a broad range of impact categories. The results indicate a maximum power output of 830.9 kW and a maximum net present value (NPV) of 51.71 M€, confirming the system’s technical and economic viability. The environmental assessment demonstrates the potential of ORC systems as sustainable energy solutions, with significant environmental unburdening under optimized operating conditions (up to -606.0 kg CO2 eq./h). A sensitivity analysis indicates that the greatest environmental benefits occur under the optimal thermodynamic scenario, achieved through the utilization of higher-energy flue gas streams (up to -515.0 kg CO2 eq./h), and under the optimal economic scenario by balancing the electricity and heat prices optimally for simultaneous heat and power production (up to -696.7 kg CO2 eq./h). These findings highlight the importance of the thermal input quality and availability in maximizing ORC performance. With the ability to prioritize electricity, heat, or both, the optimized ORC systems support flexible energy solutions tailored to specific applications and environmental conditions, offering a promising pathway for unburdening the environment through the efficient utilization of industrial waste heat.
Keywords: waste heat recovery, aluminium production, organic rankine cycle, environmental impact, life cycle assessment, sustainable energy solutions
Published in DKUM: 13.06.2025; Views: 0; Downloads: 19
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Abstract: This study presents an integrated design and optimization of an Organic Rankine Cycle (ORC) for the recovery of waste heat from aluminium production. Non-Linear Programming (NLP) models were developed, with the objectives of maximizing electricity production and the Net Present Value (NPV) of the system. The models account for optimizing the operating conditions and changes in thermodynamic features of the system. The developed models are applied to a case study of Slovenian aluminium company where the performance of three different working fluids (R245fa, R1234yf and R1234ze) are compared. The optimization is performed considering different temperatures and prices of produced hot water and electricity, minimum approach temperature (DTmin), concentration of CO2 in flue gas and temperature and flowrate of flue gas. Results show that the selected working fluids for the proposed waste heat-based ORC system have the potential to substitute up to about 830 kW of electricity in a sustainable and economic manner. Out of the three working fluids considered, R245fa showed up to 7.9% efficiency of the ORC cycle and was identified as the best performing working fluid considering both economic viability and the amount of electricity produced by the system, however the refrigerant inherently has higher GHG footprint.
Keywords: waste heat, waste heat utilization, aluminium industry, organic rankine cycle, power generation, optimization
Published in DKUM: 10.04.2025; Views: 0; Downloads: 7
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Abstract: The paper presents the Mixed-Integer Non-linear Programming (MINLP) approach to the synthesis of trusses. The solution of continuous/discrete non-convex and non-linear optimization problems is discussed with respect to the simultaneous topology, shape and discrete sizing optimization of trusses. A truss MINLP superstructure of different topology and design alternatives has been generated, and a special MINLP model formulation for trusses has been developed. In the optimization model, a mass objective function of the structure has been defined and subjected to design, load and dimensioning constraints. The MINLP problems are solved using the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm. Multi-level MINLP strategies are introduced to accelerate the convergence of the algorithm. The Modified Two-Phase and the Sequential Two-Phase MINLP strategies are proposed in order to solve highly combinatorial topology, shape and discrete sizing optimization problems. The importance of local buckling constraints on topology optimization is also discussed. Some simple numerical examples are shown at the end of the paper to demonstrate the suitability and efficiency of the proposed method.
Keywords: structural synthesis, topology optimization, discrete sizing optimization, mixed-integer non-linear programming, MINLP, modified OA/ER algorithm, multi-level MINLP strategies, steel structures, trusses
Published in DKUM: 11.03.2025; Views: 0; Downloads: 12
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Keywords: multiple heat sources, Organic Rankine cycle, separate and cascade designs, Steam Rankine cycle, thermodynamic optimisation
Published in DKUM: 28.02.2025; Views: 0; Downloads: 3
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