Fly ash was used as a fractional substitute to cement. The fly ash was a class F type and has an SG and surface area of 2.54 and 363 m 2 /kg, respectively. The properties of the fly ash are also presented in Table I. Graphene nanoplatelets (GNPs) were used as an additive to concrete.
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Fly ash (FA) is the most commonly used supplementary cementitious material in the world. However, the reactivity of FA varies substantially. In this study, new machine learning (ML) model has been developed to efficiently predict the amorphous content in FA type F. Compared to the existing ML model using types F and C of FA …
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The prediction of compressive strength in concrete plays a crucial role in the construction industry, as it helps ensure the structural integrity of buildings and infrastructure. This study examines the utilization of fly ash and admixture combinations as input factors for predicting compressive strength using four machine learning …
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Jaxion-Harm, J., S. T. Szedlmayer, and P. A. Mudrak. 2018. "A comparison of fish assemblages according to artificial reef attributes and seasons in the Northern …
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In this paper, 871 data were collected from literature and trained by the 4 representative machine learning methods, in order to build a robust compressive strength predictive model for slag and fly ash based alkali activated concretes. The optimum models of each machine learning method were verified by 4 validation metrics and further …
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This paper investigates the mechanical properties of concrete containing recycled aggregates and fly ash as a sustainable and eco-friendly solution for construction, which can reduce the demand for natural aggregates and cement, conserves natural resources, and curtails greenhouse gas emissions.Machine learning methodology can …
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Keywords: self-compacting concrete; Class F fly ash; compressive strength; machine learning; artificial neural networks; regression trees; Gaussian process regression 1. Introduction The significant production of Portland cement results in the emission of large amounts of carbon dioxide, and the replacement of cement with fly …
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This study used three artificial intelligence-based algorithms – adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANNs), and gene expression programming (GEP) – to develop empirical models for predicting the compressive strength (CS) and slump values of fly ash-based geopolymer concrete.
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Although the machine-made sand was widely used for concrete in recent years in China, it was short of studies on the relations among the basic mechanical properties of fly-ash concrete with machine-made sand (MSFAC).
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DOI: 10.1016/j.cemconcomp.2021.104265 Corpus ID: 240533836; Predicting shrinkage of alkali-activated blast furnace-fly ash mortars using artificial neural network (ANN) @article{Adea2021PredictingSO, title={Predicting shrinkage of alkali-activated blast furnace-fly ash mortars using artificial neural network (ANN)}, author={Elijah Adea …
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In the current study, an effort is made to stabilize intermediate plastic clay using various dosages of cement and fly ash, and to develop an SVM-based machine learning model to predict the unconfined compressive strength of the stabilized soil. The materials used in the study were subjected to basic engineering tests such as …
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The compressive strength of alkali-activated slag-fly ash concrete can be well predicted based on machine learning. ... Evaluating the mechanical strength …
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Compressive strength analysis of fly ash-based geopolymer concrete using machine learning approaches ... the machine learning approach was used to predict the C–S of FA-GPC through artificial ...
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Kazemi, R. & Gholampour, A. Evaluating the rapid chloride permeability of self-compacting concrete containing fly ash and silica fume exposed to different …
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This study employed soft computing models to predict the compressive strength of fly ash-modified concrete produced with recycled aggregate concrete (RCA) …
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The mixing was done in a centrifugal mixer machine wherein the fly ash was mixed with the alkaline solution for 10 minutes to produce a dry mix having workability of 24–30 s as per Vee-Bee Consistometer test. After the mixing, the dry mix was transferred % sand . aggregate Fine Aggregate …
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The potential of industrial wastes to be utilized as raw materials for producing artificial aggregates include coal fly ash, palm oil fly ash, and bottom ash . In addition, for producing artificial aggregates with enhanced properties that are comparable to those of natural aggregates, the processing and producing methods should be …
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1. Introduction. During the past decades, promoting the utilization of blast furnace slag and fly ash based alkali activated concretes (BFS/FA-AACs) has gained increasing attention because it can alleviate carbon dioxide footprint and reduce waste disposal [1], [2], [3].Nowadays, BFS/FA-AACs using sodium hydroxide and sodium …
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This study concludes that the use of an artificial neural network (ANN) approach for numerical investigations on the parameters affecting the carbonation depth in fly-ash concrete is successful and provides scientific guidance for durability design. Concrete carbonation is one of the main causes of corrosion of the reinforcement and …
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Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms. ... (GEP), Artificial neural network (ANN), and Decision tree (DT) algorithms were ...
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Artificial neural network has strong potential as a feasible tool for predicting accurately the properties of SCC containing fly ash and a comparison of the ANN-based prediction model with other researcher's experimental results was carried out, and a good agreement was found. This paper investigates the feasibility of using artificial neural …
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The data used in the artificial neural networks and fuzzy logic models are arranged in a format of nine input parameters that cover the day, Portland cement, water, sand, crushed stone I (4–8 mm), crushed stone II (8–16 mm), high range water reducing agent replacement ratio, fly ash replacement ratio and CaO, and an output parameter …
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Using artificial intelligence (AI) and machine learning (ML) techniques, NETL researchers are exploring a way to treat water that seeps through coal combustion waste using a sorbent synthesized from fly ash, itself a coal combustion waste ─ a development with implications for improving the costs of managing future waste sites.
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Recycled aggregates (RA) can provide a sustainable solution for replacing natural aggregates (NA) in the concrete mix. However, the stakeholders and inspection professionals lack confidence in predicting their compressive strength (CS) due to limited databases. Most of them solely focus on the concrete mix with natural aggregates only. …
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Introducing the All Model Of Fly ash Brick Making Machine, the latest addition to HP Bricks Machinery Company's line of fly ash brick making machines. As a trusted manufacturer of all types of fly ash brick …
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This paper describes the progress of studies of the treatment of coal ash mixed with organic by-products by a compost process as a means of converting ash to a desirable commercial product. Mixtures of fly and bottom ash, broiler chicken litter manure, sawdust and...
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2. Methods. Machine learning (ML) is a branch of artificial intelligence and includes methods of training algorithms such that they can learn from data and make decisions and predictions, which can be applied in the modeling of the behavior of structures and materials (Table 1).The strength of ML methods lies in the fact that these methods can represent a …
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