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Article

Multi-Criteria Optimization of Energy-Efficient Cementitious Sandwich Panels Building Systems Using Genetic Algorithm

1
FirstElement Fuel Company, Irvine, CA 92617, USA
2
Civil & Environmental Engineering Department, University of California, Irvine, CA 92697, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Fernando Pacheco Torgal
Energies 2021, 14(18), 6001; https://doi.org/10.3390/en14186001
Received: 8 July 2021 / Revised: 26 August 2021 / Accepted: 10 September 2021 / Published: 21 September 2021
This paper presents results of a study that focuses on developing a genetic algorithm (GA) for multi-criteria optimization of orthotropic, energy-efficient cementitious composite sandwich panels (CSP). The current design concept of all commercially produced CSP systems is based on the assumption that such panels are treated as doubly reinforced sections without the consideration of the three-dimensional truss contribution of the orthotropic panel system. This leads to uneconomical design and underestimating both the strength and stiffness of such system. In this study, two of the most common types of commercially produced sandwich were evaluated both numerically and experimentally and results were used as basis for developing a genetic algorithm optimization process using numerical modeling simulations. In order to develop a sandwich panel with high structural performance, design optimization techniques are needed to achieve higher composite action, while maintaining the favorable features of such panels such as lightweight and high thermal insulation. The study involves both linear and nonlinear finite element analyses and parametric optimization. The verification and calibration of the numerical models is based on full-scale experimental results that were performed on two types of commercially produced sandwich panels under different loading scenarios. The genetic algorithm technique is used for optimization to identify an optimum design of the cementitious composite sandwich panels. The GA technique combines Darwin’s principle of survival of fittest and a structured information exchange using randomized crossover operators to evolve an optimum design for the cementitious sandwich panel. Parameters evaluated in the study include: (i) shear connectors’ geometry, its volume fraction and distribution; (ii) exterior cementitious face sheets thickness and (iii) size and geometry steel wires reinforcements. The proposed optimization method succeeded in reducing cost of materials of CSP by about 48% using genetic algorithm methodology. In addition, an optimized design for CSP is proposed that resulted in increasing the panel’s thermal resistance by 40% as compared to existing panels, while meeting ACI Code structural design criteria. Pareto-optimal front and Pareto-optimal solutions have been identified. Correlation between the design variables is also verified and design recommendation are proposed. View Full-Text
Keywords: 3D sandwich panels; construction; multi-criteria optimization; genetic algorithm; composite action; numerical simulation; energy-efficient buildings 3D sandwich panels; construction; multi-criteria optimization; genetic algorithm; composite action; numerical simulation; energy-efficient buildings
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MDPI and ACS Style

Mirnateghi, E.; Mosallam, A.S. Multi-Criteria Optimization of Energy-Efficient Cementitious Sandwich Panels Building Systems Using Genetic Algorithm. Energies 2021, 14, 6001. https://doi.org/10.3390/en14186001

AMA Style

Mirnateghi E, Mosallam AS. Multi-Criteria Optimization of Energy-Efficient Cementitious Sandwich Panels Building Systems Using Genetic Algorithm. Energies. 2021; 14(18):6001. https://doi.org/10.3390/en14186001

Chicago/Turabian Style

Mirnateghi, Ehsan, and Ayman S. Mosallam. 2021. "Multi-Criteria Optimization of Energy-Efficient Cementitious Sandwich Panels Building Systems Using Genetic Algorithm" Energies 14, no. 18: 6001. https://doi.org/10.3390/en14186001

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