Applied Sciences

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33 pages, 10795 KiB

Open AccessArticle

Prediction of Compressive Strength of Fly-Ash-Based Concrete Using Ensemble and Non-Ensemble Supervised Machine-Learning Approaches

by Yang Song, Jun Zhao, Krzysztof Adam Ostrowski, Muhammad Faisal Javed, Ayaz Ahmad, Muhammad Ijaz Khan, Fahid Aslam and Roman Kinasz

Appl. Sci. 2022, 12(1), 361; https://doi.org/10.3390/app12010361 - 30 Dec 2021

Cited by 35 | Viewed by 3649

Abstract

The utilization of waste material, such as fly ash, in the concrete industry will provide a valuable alternative solution for creating an eco-friendly environment. However, experimental work is time-consuming; employing soft machine learning techniques can accelerate the process of forecasting the strength properties [...] Read more.

The utilization of waste material, such as fly ash, in the concrete industry will provide a valuable alternative solution for creating an eco-friendly environment. However, experimental work is time-consuming; employing soft machine learning techniques can accelerate the process of forecasting the strength properties of concrete. Ensemble machine learning modeling using Python Jupyter Notebook was employed in the forecasting of compressive strength (CS) of high-performance concrete. Multilayer perceptron neuron network (MLPNN) and decision tree (DT) were used as individual learning which then ensembled with bagging and boosting to provide strong correlations. Random forest (RF) and gradient boosting regression (GBR) were also used for prediction. A total of 471 data points with input parameters (e.g., cement, fine aggregate, coarse aggregate, superplasticizer, water, days, and fly ash), and an output parameter of compressive strength (CS), were retrieved to train and test the individual learners. Cross-validation with K-fold and statistical error (i.e., MAE, MSE, RMSE, and RMSLE) analysis was applied to check the accuracy of all models. All models showed the best correlation with an ensemble model rather than an individual one. DT with AdaBoost and random forest gave a strong correlation of R² = 0.89 with fewer errors. Cross-validation results revealed a good response with an error of less than 10 MPa. Thus, ensemble modeling not only trains the data by employing several weak learners but also produces a robust correlation that can then be used to model and predict the mechanical performance of concrete. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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16 pages, 2199 KiB

Open AccessFeature PaperArticle

Sustainability Evaluation Using a Life Cycle and Circular Economy Approach in Precast Concrete with Waste Incorporation

by Fábio Simões, Francisco-Javier Rios-Davila, Helena Paiva, Hamid Maljaee, Miguel Morais and Victor M. Ferreira

Appl. Sci. 2021, 11(24), 11617; https://doi.org/10.3390/app112411617 - 7 Dec 2021

Cited by 7 | Viewed by 2927

Abstract

Waste valorisation as secondary or alternative raw materials in several sectors products and processes has been an important way to implement a more sustainable and circular way to manage the efficient use of natural resources. This action contributes not only to save natural [...] Read more.

Waste valorisation as secondary or alternative raw materials in several sectors products and processes has been an important way to implement a more sustainable and circular way to manage the efficient use of natural resources. This action contributes not only to save natural resources but also to prevent sending large amounts of wastes, some of them dangerous, to landfill disposal, creating a major environmental, economic and social impact. To promote circular economy, this work attempts to demonstrate the environmental gains in a competitive way, by bringing together in an industrial symbiosis action, two large producing sectors (the pulp and paper industry and concrete construction sector), which are also able to consume significant amounts of resources and to generate large amounts of wastes. A sustainability evaluation based on a life cycle and circular approach is presented and discussed using a simple case study performed at real industrial scale. The lime ash waste from the pulp and paper industry is used to replace 100% of the natural filler used in precast concrete production and the impacts and benefits from the technical, environmental, economic and social level were assessed. It was demonstrated that this simple action causes positive impacts in the evaluated dimensions of sustainability without causing any changes in production time and causes no degradation on relevant concrete properties. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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12 pages, 2664 KiB

Open AccessArticle

Reactive Powder Concrete: Durability and Applications

by Miguel Ángel Sanjuán and Carmen Andrade

Appl. Sci. 2021, 11(12), 5629; https://doi.org/10.3390/app11125629 - 18 Jun 2021

Cited by 27 | Viewed by 6707

Abstract

Reactive powder concrete (RPC) is an ultra-high-performance concrete (UHPC) developed years ago by Bouygues, with the aim to build strong, durable, and sustainable structures. Some differences can be underlined between the RPC and high-performance concrete (HPC); that is to say, RPC exhibits higher [...] Read more.

Reactive powder concrete (RPC) is an ultra-high-performance concrete (UHPC) developed years ago by Bouygues, with the aim to build strong, durable, and sustainable structures. Some differences can be underlined between the RPC and high-performance concrete (HPC); that is to say, RPC exhibits higher compressive and flexural strength, higher toughness, lower porosity, and lower permeability compared to HPC. Microstructural observations confirm that silica fume enhances the fiber–matrix interfacial characteristics, particularly in fiber pullout energy. This paper reviews the reported literature on RPC, and it offers a comparison between RPC and HPC. Therefore, some RPC potential applications may be inferred. For instance, some examples of footbridges and structural repair applications are given. Experimental measurements on air permeability, porosity, water absorption, carbonation rate, corrosion rate, and resistivity are evidence of the better performance of RPC over HPC. When these ultra-high-performance concretes are reinforced with discontinuous, short fibers, they exhibit better tensile strain-hardening performance. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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15 pages, 42291 KiB

Open AccessArticle

Investigating the Effect of CNTs on Early Age Hydration and Autogenous Shrinkage of Cement Composite

by Byoungsun Park and Young Cheol Choi

Appl. Sci. 2021, 11(12), 5545; https://doi.org/10.3390/app11125545 - 15 Jun 2021

Cited by 9 | Viewed by 2058

Abstract

In this study, the effect of carbon nanotubes (CNTs) on the physical properties of cement composites was investigated. The mechanism of the change of autogenous shrinkage of CNTs-reinforced cement composites was also examined. In the experiments, ordinary Portland cement (OPC) and fly ash [...] Read more.

In this study, the effect of carbon nanotubes (CNTs) on the physical properties of cement composites was investigated. The mechanism of the change of autogenous shrinkage of CNTs-reinforced cement composites was also examined. In the experiments, ordinary Portland cement (OPC) and fly ash (FA) were used as binders, and 0.0, 0.1, 0.3, and 0.5% multi-walled CNTs (MWCNTs) were added to fabricate pastes. When the hydration heat was measured through isothermal calorimetry, it was found that CNTs accelerated the early age hydration of the pastes and that the hydration rate increased as the CNT content increased. The compressive strength was the highest when the CNT content was 0.1%. As the CNT content increased, the internal relative humidity (IRH) decreased and autogenous shrinkage showed a decreasing tendency. Through the analysis of the correlation between autogenous shrinkage and IRH, it was confirmed that the reduction in autogenous shrinkage due to the addition of CNTs resulted from the decrease in bulk strain. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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12 pages, 5362 KiB

Open AccessArticle

Study on Influence of Range of Data in Concrete Compressive Strength with Respect to the Accuracy of Machine Learning with Linear Regression

by Jun-Ryeol Park, Hye-Jin Lee, Keun-Hyeok Yang, Jung-Keun Kook and Sanghee Kim

Appl. Sci. 2021, 11(9), 3866; https://doi.org/10.3390/app11093866 - 24 Apr 2021

Cited by 4 | Viewed by 2424

Abstract

This study aims to predict the compressive strength of concrete using a machine-learning algorithm with linear regression analysis and to evaluate its accuracy. The open-source software library TensorFlow was used to develop the machine-learning algorithm. In the machine-earning algorithm, a total of seven [...] Read more.

This study aims to predict the compressive strength of concrete using a machine-learning algorithm with linear regression analysis and to evaluate its accuracy. The open-source software library TensorFlow was used to develop the machine-learning algorithm. In the machine-earning algorithm, a total of seven variables were set: water, cement, fly ash, blast furnace slag, sand, coarse aggregate, and coarse aggregate size. A total of 4297 concrete mixtures with measured compressive strengths were employed to train and testing the machine-learning algorithm. Of these, 70% were used for training, and 30% were utilized for verification. For verification, the research was conducted by classifying the mixtures into three cases: the case where the machine-learning algorithm was trained using all the data (Case-1), the case where the machine-learning algorithm was trained while maintaining the same number of training dataset for each strength range (Case-2), and the case where the machine-learning algorithm was trained after making the subcase of each strength range (Case-3). The results indicated that the error percentages of Case-1 and Case-2 did not differ significantly. The error percentage of Case-3 was far smaller than those of Case-1 and Case-2. Therefore, it was concluded that the range of training dataset of the concrete compressive strength is as important as the amount of training dataset for accurately predicting the concrete compressive strength using the machine-learning algorithm. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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16 pages, 4176 KiB

Open AccessArticle

Sound-Absorbing and Thermal-Insulating Properties of Cement Composite Based on Recycled Rubber from Waste Tires

by Jakub Svoboda, Tomáš Dvorský, Vojtěch Václavík, Jakub Charvát, Kateřina Máčalová, Silvie Heviánková and Eva Janurová

Appl. Sci. 2021, 11(6), 2725; https://doi.org/10.3390/app11062725 - 18 Mar 2021

Cited by 15 | Viewed by 3451

Abstract

This article describes an experimental study aimed at investigating the potential use of recycled rubber granulate from waste tires of fractions 0/1 and 1/3 mm in cement composites as a 100% replacement for natural aggregates. The use of waste in the development and [...] Read more.

This article describes an experimental study aimed at investigating the potential use of recycled rubber granulate from waste tires of fractions 0/1 and 1/3 mm in cement composites as a 100% replacement for natural aggregates. The use of waste in the development and production of new building materials represents an important aspect for the sustainability and protection of the environment. This article is focused on the sound-absorbing and thermal-insulating properties of experimental cement composites based on recycled rubber from waste tires. The article describes the grain characteristics of recycled rubber, sound absorption capacity, thermal conductivity and strength characteristics. The results of this research show that the total replacement of natural aggregate with recycled rubber in cement composites is possible. Replacing natural aggregate with recycled rubber has significantly improved the thermal and acoustic properties of the prepared cement composites, however, at the same time; there was also the expected decrease in the strength characteristics due to the elasticity of rubber. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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11 pages, 550 KiB

Open AccessArticle

Prioritization of Factors Affecting Sustainability Property Improvement by Using Analytical Hierarchy Process and Important-Satisfaction Model: The Case of TAIPEI 101 Tower

by Tse-Hsiung Lin and Shen-Guan Shih

Appl. Sci. 2021, 11(1), 257; https://doi.org/10.3390/app11010257 - 29 Dec 2020

Cited by 4 | Viewed by 2222

Abstract

Almost without exceptions office buildings in the world investigate the approaches of optimizing the building operation and property facilities in order to maintain the best conditions of the building from the first day of opening. For sustainable buildings, how to make continuous profit [...] Read more.

Almost without exceptions office buildings in the world investigate the approaches of optimizing the building operation and property facilities in order to maintain the best conditions of the building from the first day of opening. For sustainable buildings, how to make continuous profit must rely on the maintenance and improvement of facilities to satisfy users. However, building managers often have trouble prioritizing improvement projects toward their sustainable objectives due to the large number of facilities that have different durability years and the importance and satisfaction of these facilities to users are also different. In the past, financial consideration was usually the only one that matters when improvement of facilities was brought up. Users feedback of satisfaction was not taken into consideration, resulting in huge expenditures did not bring in high user satisfaction. This research, by scientific analysis of the data from user feedback, applies the Analytic Hierarchy Process (AHP) using TAIPEI 101 Tower as a case study to explore the key factors affecting tenants’ willingness to lease office buildings by distributing questionnaires to real estate experts. By filtering out key indicators related to property facilities that users care about, this study used Importance and Satisfaction Analysis (IS Analysis) to identify items that need urgent improvement. This innovative analysis methodology can systematically and logically find out the priority of improvement projects, assisting building managers effectively invest limited resources in projects with substantial benefit, which is helpful for sustainable property management. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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15 pages, 4413 KiB

Open AccessArticle

Evaluation of Workability and Mechanical Properties of Bottom Ash Aggregate Concrete

by Yong-Hyok Kim, Hak-Young Kim, Keun-Hyeok Yang and Jung-Soo Ha

Appl. Sci. 2020, 10(22), 8016; https://doi.org/10.3390/app10228016 - 12 Nov 2020

Cited by 5 | Viewed by 2158

Abstract

The purpose of this study is to evaluate the workability and mechanical properties of concrete containing bottom ash, which is an industrial byproduct, as an aggregate. Twelve concrete mixtures, including concrete containing bottom ash aggregate (CCBA), are classified into three groups of W/C [...] Read more.

The purpose of this study is to evaluate the workability and mechanical properties of concrete containing bottom ash, which is an industrial byproduct, as an aggregate. Twelve concrete mixtures, including concrete containing bottom ash aggregate (CCBA), are classified into three groups of W/C 0.45, 0.375, and 0.3 according to the target strength. Each group includes four mixtures in which natural aggregate and bottom ash are applied as fine and coarse aggregates according to particular ratios. On the basis of the test results, a reliable model to predict the 28-day compressive strength of CCBA is proposed by applying regression analysis. The proposed model points out that when applying bottom ash as aggregate, the concrete density is lowered, and W/C should be reduced to offset the lowered compressive strength. As a result of comparing experimental values with the existing design code models, it is found that while the fib model accurately predicts compressive strength development and tensile resistance capacity in general, the ACI 318 code overestimates the elastic modulus at the oven-dried density (ρ_c) range of 1840 kg/m³ and above. Accurate prediction of the mechanical properties of CCBA requires the measurement of additional experimental data that consider W/C and ρ_c as important parameters. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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18 pages, 4453 KiB

Open AccessArticle

Compressive Strength Development of High-Volume Fly Ash Ultra-High-Performance Concrete under Heat Curing Condition with Time

by Pham Sy Dong, Nguyen Van Tuan, Le Trung Thanh, Nguyen Cong Thang, Viet Hung Cu and Ju-Hyun Mun

Appl. Sci. 2020, 10(20), 7107; https://doi.org/10.3390/app10207107 - 13 Oct 2020

Cited by 22 | Viewed by 4079

Abstract

This research investigated the effect of fly ash content on the compressive strength development of ultra-high-performance concrete (UHPC) at different curing conditions, i.e., the standard curing condition and the heat curing. A total of 20 mixtures were prepared to cast specimens to measure [...] Read more.

This research investigated the effect of fly ash content on the compressive strength development of ultra-high-performance concrete (UHPC) at different curing conditions, i.e., the standard curing condition and the heat curing. A total of 20 mixtures were prepared to cast specimens to measure the compressive strength at different ages from 3 days to 180 days. Additionally, 300 specimens were prepared to estimate the appropriate heat curing period at the early ages in terms of enhancing the 28-day compressive strength of UHPC with high content of fly ash (FA). From the regression analysis using test data, empirical equations were formulated to assess the compressive strength development of UHPC considering the FA content and maturity function. Test results revealed that the preference of the addition of FA for enhancing the compressive strength of UHPC requires the early heat curing procedure which can be recommended as at least 2 days under 90 °C. Moreover, the compressive strength of UHPC with FA under heat curing mostly reached its 28-day strength within 3 days. The proposed models based on the fib 2010 model can be a useful tool to reliably assess the compressive strength development of UHPC with high-volume fly ash (HVFA) (up to 70% fly ash content) under a heat curing condition that possesses a different performance from that of normal- and high-strength concrete. When 50% of the cement content was replaced by FA, the embodied CO₂ emission for UHPC mixture reduced up to approximately 50%, which is comparable to the CO₂ emission calculated from the conventional normal-strength concrete. Full article

(This article belongs to the Special Issue Sustainability and Performance of Advanced Construction Materials)

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