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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: 1
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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: 3
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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: 2
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Keywords: water network, water integration, heat exchanger network, heat-integrated water network, superstructure optimisation
Published in DKUM: 14.02.2025; Views: 0; Downloads: 5
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Abstract: Excessive production, indiscriminate consumption, and improper disposal of plastics have led to plastic pollution and its hazardous environmental effects. Various approaches to tackle the challenges of reducing the plastic footprint have been developed and applied, such as the production of alternative materials (design for recycling), the production and use of biodegradable plastic and plastics from power-to-X, and the development of recycling approaches. This study proposes an optimisation strategy based on regression to evaluate and predict plastic use and end-of-life fate in the future based on historical trends. The mathematical model is formulated and correlations based on functions of time are developed and optimised by minimising the sum of squared residuals. The plastic quantities up to the year 2050 are projected based on historical trends analysis, and for improved sustainability, projections are additionally based on intervention analyses. The results show that the global use of plastics is expected to increase from 464 Mt in 2020 up to 884 Mt in 2050, with up to 4725 Mt of plastics accumulated in stock in 2050 (from the year 2000). Compared to other available forecasts, a slightly lower level of plastic use and stock are obtained. The intervention analysis estimates a range of global plastics' consumption between 594 Mt and 1018 Mt in 2050 by taking into account its different increment rates (between −1 % and 2.65 %). In the packaging sector, the implementation of reduction targets (15 % reduction in 2040 compared to 2018) could lead to a 27.3 % decrease in plastic use in 2050 as compared to 2018, while achieving recycling targets (55 % in 2030) would recycle >75 % of plastic packaging in 2050. The partial substitution of fossil-based plastics with bioplastics (polyethylene) will require significant land area, between 0.2 × 106 km2 for obtaining switchgrass and up to around 1.0 × 106 km2 for obtaining forest residue (annual yields of 58.15 t/ha and 3.5 t/ha) in 2050. The intervention analysis shows that proactive policies can mitigate sustainability challenges, however achieving broader sustainability goals also requires reduction of footprints related to energy production and virgin plastic production, the production of bio-based plastics, and the full implementation of recycling initiatives.
Keywords: plastic use, plastic waste, end-of-life fate, forecasting, hostorical trends, regression analysis, least square method, intervention analysis
Published in DKUM: 31.01.2025; Views: 0; Downloads: 2
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