A Constructal Law optimization of a boiler inspired by Life Cycle thinking. (June 2018)

• Record Type: Journal Article
• Authors: Gulotta, Teresa Maria; Guarino, Francesco; Cellura, Maurizio; Lorenzini, Giulio
• Is Part Of: Thermal science and engineering progress. Volume 6(2018)
• Page Start: 380
• Page End: 387
• Publication Date: 2018-06
• Subjects: Boiler -- Constructal Law -- Overall performance coefficient -- Life Cycle Assessment; Heat engineering -- Periodicals; Heat engineering; Thermodynamics; Periodicals; 621.402
• DOI: 10.1016/j.tsep.2018.01.008
• Languages: English
• ISSNs: 2451-9049

Abstract

Highlights: A Constructal Law optimization has led to alternate boiler designs. A life cycle (LC) inspired approach was used to extend the results of the optimization. An alternative formulation of the overall performance coefficient is proposed including the LC perspective. A 0.33% and 4% reduction in life cycle energy and environmental impacts respectively in the optimal design. Abstract: The aim of the paper is to explore how design optimization contributes to a technology's ecological evolution. The article develops this concept through an application of Constructal Law, used to account for the "evolution" of technologies design (configuration, shape, structure, pattern, rhythm), and Life Cycle Assessment (LCA), used for quantifying the environmental impacts of the design choices. The combination of both methods assesses how technology evolution affects the environment during its life, extending the concept of evolution of design. The study is applied to a case study of a real biomass boiler. The study analyses basic case and a series of alternative scenarios optimized with Constructal Law, guaranteeing the same thermal energy production. The results are analyzed graphically and analytically with an "Overall Performance Coefficient methodology", that investigates trade-offs to identify the best configuration. In addition, the use of LCA allows evaluating energy and environmental performances of different design alternatives, with the best option able to reduce the global energy required of 0.33% and the normalized impacts of 4%. The methodology is proposed to support decision-making during the optimization process.