Machine Learning and Sustainable Geopolymer Materials: A Systematic Review

Materials Today Sustainability, Journal Year: 2025, Volume and Issue: 30, P. 101095 - 101095

Published: March 6, 2025

Language: Английский

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Structure formation, rheology and properties of sulfur concrete mixtures and sulfur concrete modified with bitumen and stone flour

Case Studies in Construction Materials, Journal Year: 2024, Volume and Issue: 20, P. e02917 - e02917

Published: Jan. 26, 2024

The development and improvement of cementless concrete, including by use various types refuse, is especially important due to their economic environmental efficiency. Sulfur as a refuse the oil gas industry can act production binder new environmentally friendly building material - sulfur concrete (SC). purpose study was improve effective designs SC containing from stone processing industries, analyze rheological physical mechanical appearances. Methods laboratory testing samples, well microscopic analysis its structure, were applied. with best values compressive strength (CS) water occlusion has following formula according content main components: 20% mass; flour 10% crushed 40% sand 30% bitumen modifying additive 6% weight sulfur. mobility these combinations enhanced up 2.2 times adding addition formulations. Compared control design, optimal design modified presented an enhancement in CS 105% reduction 70%. structure samples does not have shrinkage cavities pronounced phase boundaries, contrast design.

Language: Английский

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Analysis of vehicle pedestrian crash severity using advanced machine learning techniques

Archives of Transport, Journal Year: 2023, Volume and Issue: 68(4), P. 91 - 116

Published: Nov. 24, 2023

In 2015, over 17% of pedestrians were killed during vehicle crashes in Hong Kong while it raised to 18% from 2017 2019 and expected be 25% the upcoming decade. Kong, buses metro are used for 89% trips, walking has traditionally been primary way use public transportation. This susceptibility road conflicts with sustainable transportation objectives. Most studies on crash severity ignored correlations between pedestrian-vehicle units engaged same impacts. The estimates factor effects will skewed models that do not consider these within-crash correlations. Pedestrians made up 20,381 traffic fatalities which 66% highways pedestrians. motivation this study is examine elements pedestrian injuries build safety endangered users. A traditional statistical model's ability handle misfits, missing or noisy data, strict presumptions questioned. reasons typically explained using models. To overcome constraints, a sophisticated machine learning technique called Bayesian neural network (BNN), combines benefits networks theory. best construction model out several constructed was finally selected. It discovered BNN outperformed other techniques like K-Nearest Neighbors, conventional (NN), random forest (RF) terms performance predictions. also time circumstances accident meteorological features critical significantly enhanced when incorporated as input. minimize number due accidents, research anticipates employing (ML) techniques. Besides, sets framework applying reduce brought by auto accidents.

Language: Английский

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Prediction of Ultra-High-Performance Concrete (UHPC) Properties Using Gene Expression Programming (GEP)

Buildings, Journal Year: 2024, Volume and Issue: 14(9), P. 2675 - 2675

Published: Aug. 28, 2024

In today’s digital age, innovative artificial intelligence (AI) methodologies, notably machine learning (ML) approaches, are increasingly favored for their superior accuracy in anticipating the characteristics of cementitious composites compared to typical regression models. The main focus current research work is improve knowledge regarding application one new ML techniques, i.e., gene expression programming (GEP), anticipate ultra-high-performance concrete (UHPC) properties, such as flowability, flexural strength (FS), compressive (CS), and porosity. addition, process training a model that predicts intended outcome values when associated inputs provided generates graphical user interface (GUI). Moreover, reported models have been created aforementioned UHPC simple limited input parameters. Therefore, purpose this study predict while taking into account wide range factors (i.e., 21) use GUI assess how these parameters affect properties. This includes diameter steel polystyrene fibers (µm mm), length (mm), maximum size aggregate particles type cement, its class, (MPa) type, contents (%), amount water (kg/m3). it fly ash, silica fume, slag, nano-silica, quartz powder, limestone sand, coarse aggregates, super-plasticizers, with all measurements kg/m3. outcomes reveal GEP technique successful accurately predicting characteristics. obtained R2, determination coefficients, from 0.94, 0.95, 0.93, 0.94 CS, FS, porosity, respectively. Thus, utilizes forecast comprehend influence factors, simplifying procedure offering valuable instruments practical model’s capabilities within domain civil engineering.

Language: Английский

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Comparative study of eco-friendly wire mesh configurations to enhance sustainability in reinforced concrete structures

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: April 17, 2024

Abstract Recent and past studies mainly focus on reducing the dead weight of structure; therefore, they considered lightweight aggregate concrete (LWAC) which reduces but also affects strength parameters. Therefore, current study aims to use varied steel wire meshes investigate effects LWAC mechanical properties. Three types mesh are used such as hexagonal (chicken), welded square, expanded metal mesh, in various layers orientations LWAC. Numerous characteristics were examined, including energy absorption (EA), compressive (CS), flexural (FS). A total ninety prisms thirty-three cubes made. For FS test, forty-five 100 × 500 mm prism samples poured, 150 cube made, 400 300 75 EA specimens costed for fourteen days curing. The experimental findings demonstrate that was enhanced by adding additional forces spread over section. One layer chicken, welded, enhances 52.96%, 23.76%, 22.2%, respectively. In comparison remaining layers, a single-layer has maximum strength, 29.49 MPa. with single had greatest CS, measuring 36.56 When all three combined, CS does not vary this way is estimated be 29.79 combination chicken most recorded prior final failure, 1425.6 1108.7 J, whereas it found highest 752.3 J square mesh. first increased 82.81% crack 88.34% ultimate failure. Overall, determined suggested works better than meshes.

Language: Английский

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Synergistic effects of Bacillus subtilis and PET fiber additions on the mechanical properties of Alkali-Activated composite mortars

Materials Letters, Journal Year: 2024, Volume and Issue: 376, P. 137221 - 137221

Published: Aug. 22, 2024

Language: Английский

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Properties, Microstructure Development and Life Cycle Assessment of Alkali-Activated Materials Containing Steel Slag under Different Alkali Equivalents

Materials, Journal Year: 2023, Volume and Issue: 17(1), P. 48 - 48

Published: Dec. 22, 2023

To improve solid waste resource utilization and environmental sustainability, an alkali-activated material (AAM) was prepared using steel slag (SS), fly ash, blast furnace alkali activators in this work. The evolutions of SS content (10–50%) equivalent (4.0–8.0%) on workability, mechanical strength indicators the AAM were investigated. Furthermore, scanning electron microscopy, X-ray diffraction nuclear magnetic resonance techniques adopted to characterize micromorphology, reaction products pore structure, mechanism summarized. Results showed that paste fluidity setting time gradually increased with increase content. highest compressive obtained for at 8.0% due improved rate process, but it also risk cracking. However, able exert a microaggregate filling effect, where particles pores structural compactness hindered crack development. Based optimal strength, global warming, abiotic depletion, acidification eutrophication potential are reduced by 76.7%, 53.0%, 51.6%, 48.9%, respectively, compared cement. This work is beneficial further resources expand application environmentally friendly AAMs field construction engineering.

Language: Английский

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Efficacy of sustainable cementitious materials on concrete porosity for enhancing the durability of building materials

REVIEWS ON ADVANCED MATERIALS SCIENCE, Journal Year: 2024, Volume and Issue: 63(1)

Published: Jan. 1, 2024

Abstract The degradation of concrete structures is significantly influenced by water penetration since serves as the primary vehicle for movement harmful compounds. process capillary absorption widely recognized a crucial indicator durability unsaturated concrete, it allows dangerous substances to enter composite material. capacity intricately linked its pore structure, inherently porous. main goal this work create an innovative predictive tool that assesses porosity analyzing components using machine-learning (ML) framework. Seven distinct batch design variables were included in generated database: fly ash, superplasticizer, water-to-binder ratio, curing time, ground granulated blast furnace slag, binder, and coarse-to-fine aggregate ratio. Four distant ML algorithms, including AdaBoost, linear regression (LR), decision tree (DT), support vector machine (SVM), are utilized infer generalization capabilities algorithms estimate accurately. RReliefF algorithm was implemented calculate significant features influencing porosity. This study concludes comparison alternative techniques, AdaBoost method demonstrated superior performance with R 2 score 0.914, followed SVM (0.870), DT (0.838), LR (0.763). results evaluation indicated binder possesses remarkable influence on concrete.

Language: Английский

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