Maximizing Performance of Geopolymer Mortar: Optimizing Basalt and Carbon Fiber Content Composition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24210%2F24%3A00011569" target="_blank" >RIV/46747885:24210/24:00011569 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.tandfonline.com/doi/full/10.1080/15440478.2023.2293047" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/15440478.2023.2293047</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/15440478.2023.2293047" target="_blank" >10.1080/15440478.2023.2293047</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Maximizing Performance of Geopolymer Mortar: Optimizing Basalt and Carbon Fiber Content Composition

Popis výsledku v původním jazyce

This study focuses on the optimization of geopolymer composites, considering the parameters of composition and performance. The research explores the integration of algorithm-built hybrid implementations and a hybrid intelligent system to solve complex optimization problems in geopolymer composite materials. Firstly, an algorithm-built hybrid implementation is proposed, combining experimental results with various data processing methods. This approach enables the utilization of composite algorithms, offering several advantages, such as scalability and adaptability to different loads. The models developed in this study provide a flexible and extensible architecture, allowing for efficient problem-solving in optimization tasks. Secondly, a hybrid intelligent system is introduced, comprising statistical simulation models that combine different control and design problem-solving approaches. Markov chains are employed to address the quantitative aspects of loosely structured tasks and process performance evaluation. Criterion methods are utilized for quantitative conclusions, ensuring the optimal adaptation of the results from both applications. The research culminates in the identification of the optimal composition, denoted as G + FC + CFI, with specific weight content. This composition consists of cement, activator, fireclay, and carbon fiber I, with 100 g, 90 g, 100 g, and 2.5 g, respectively. The findings from this study provide valuable insights into the optimization of geopolymer composites, employing algorithm-built hybrid implementations and a hybrid intelligent system. The proposed approaches offer enhanced efficiency and accuracy in solving complex optimization problems in the field of geopolymer composite materials. The identified optimal composition demonstrates the potential for improving performance in composition and weight content.

Název v anglickém jazyce

Maximizing Performance of Geopolymer Mortar: Optimizing Basalt and Carbon Fiber Content Composition

Popis výsledku anglicky

This study focuses on the optimization of geopolymer composites, considering the parameters of composition and performance. The research explores the integration of algorithm-built hybrid implementations and a hybrid intelligent system to solve complex optimization problems in geopolymer composite materials. Firstly, an algorithm-built hybrid implementation is proposed, combining experimental results with various data processing methods. This approach enables the utilization of composite algorithms, offering several advantages, such as scalability and adaptability to different loads. The models developed in this study provide a flexible and extensible architecture, allowing for efficient problem-solving in optimization tasks. Secondly, a hybrid intelligent system is introduced, comprising statistical simulation models that combine different control and design problem-solving approaches. Markov chains are employed to address the quantitative aspects of loosely structured tasks and process performance evaluation. Criterion methods are utilized for quantitative conclusions, ensuring the optimal adaptation of the results from both applications. The research culminates in the identification of the optimal composition, denoted as G + FC + CFI, with specific weight content. This composition consists of cement, activator, fireclay, and carbon fiber I, with 100 g, 90 g, 100 g, and 2.5 g, respectively. The findings from this study provide valuable insights into the optimization of geopolymer composites, employing algorithm-built hybrid implementations and a hybrid intelligent system. The proposed approaches offer enhanced efficiency and accuracy in solving complex optimization problems in the field of geopolymer composite materials. The identified optimal composition demonstrates the potential for improving performance in composition and weight content.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20503 - Textiles; including synthetic dyes, colours, fibres (nanoscale materials to be 2.10; biomaterials to be 2.9)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Natural Fibers

ISSN

1544-0478

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

—

Kód UT WoS článku

001130052000001

EID výsledku v databázi Scopus

2-s2.0-85180370930