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1.
Heliyon ; 10(11): e32206, 2024 Jun 15.
Artículo en Inglés | MEDLINE | ID: mdl-38933962

RESUMEN

The study assesses the mechanical efficiency, long-lasting characteristics, microstructure, and sustainability of sustainable concrete (SC) samples through several optimization methods, emphasizing the significance of the 3Rs (recycle, reuse, reduce) approach in the construction sector. The study uses advanced techniques like the Taguchi method, grey relational analysis (GRA), analysis of variance (ANOVA), and signal-noise ratio (SNR) to optimize parameters affecting the performance of SC. In this study, the properties of SC are assessed by considering various parameters. These parameters include the use of 10 %, 20 %, and 30 % of ground granulated blast furnace slag (GGBFS) as a replacement for fly ash (FA). Additionally, six different binder contents ranging from 300 kg/m3 to 600 kg/m3 are examined. The study also investigates three different molarities of sodium hydroxide (NaOH) (8 M, 12 M, and 16 M), three different ratios of alkaline activators (AA) (1.5, 2.0, and 2.5), three different AA to-binder ratios (0.30, 0.35, and 0.40), and curing temperature (CT) of 30 °C, 60 °C, and 90 °C. The study includes fresh properties such as fresh density (FD) and slump, mechanical properties such as tensile strength (TS), flexural strength (FS), modulus of elasticity (MOE), and compressive strength (CS), and durability studies such as dry density (DD), impact strength, water absorption (WA), and sorptivity. The blended proportions were obtained using the Taguchi method. The study shows that GGBFS accelerates geopolymerization in FA-based concrete, reducing setting time and early-age CS. FA is crucial for setting time, workability, and CS enhancement. GGBFS increases the densities of fresh and hardened concrete, with a highly correlated increase, allowing accurate hardened density prediction with a coefficient of 0.9057. The CS of the cube SC surpassed 40 MPa, irrespective of variables such as the AA ratio, CT, and NaOH molarity. The trail mix with a binder concentration of 600 kg/m3, 30 % GGBFS content, 12 M NaOH molarity, 1.5 AA ratio, 0.35 AA to binder ratio, and 90 °C CT exhibited the greatest strength. Mixtures containing 10 % GGBFS can attain a CS above 30 MPa after 28 days, making them suitable for structural purposes. The T18 mix exhibited a compact Calcium (alumino) silicate hydrate (C-A-S-H) and N-A-S-H gel, whereas the T3 mix displayed a varied and permeable structure. The study used GRA, ANOVA, and SNR methods to analyze properties varying by six variables, finding GGBFS content as the most influencing parameter. The study found that the SC had a lower sustainability score than the OPC mix, but had better energy efficiency.

2.
Environ Technol ; 32(7-8): 731-8, 2011.
Artículo en Inglés | MEDLINE | ID: mdl-21879548

RESUMEN

The textile hub of Coimbatore city is facing a serious water pollution problem, both for surface water and groundwater. Industrial and domestic waste is continuously discharged into surface water bodies, resulting in the degradation of groundwater quality. In order to assess the quality of groundwater, the Singanallur area was selected for the present study. The quality of groundwater is worse in this area and the physicochemical parameters exceed the permissible limits of the Indian drinking water standards. The water type of the study area was predominantly NaCl and MgCl. A statistical analysis was carried out to understand the linear relation between the best correlated parameters. The relationship for different parameters for the study area was analysed for two seasons, pre-monsoon and post-monsoon, because the water quality varies widely seasonally. The study showed that there is a good and equal correlation between total hardness and calcium, total hardness and magnesium, and calcium and magnesium in both time periods. The relationship can be utilized to determine the value of calcium and magnesium when the value of total hardness is known for the study area. Cluster analysis was performed to obtain a dendrogram for the study area, from which the source of pollution was identified for different regions.


Asunto(s)
Contaminantes Químicos del Agua/análisis , Contaminantes Químicos del Agua/química , Contaminación del Agua/análisis , Contaminación del Agua/estadística & datos numéricos , Ciudades , Simulación por Computador , India , Modelos Estadísticos , Análisis de Regresión
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