| 1. |
- Sathvik, S., et al.
(författare)
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Evaluation of asphalt binder and mixture properties utilizing fish scale powder as a biomodifier
- 2024
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095 .- 2214-0697. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Fish represents an abundant and underutilized waste product from the fishing industry. This study investigated the effects of incorporating fish scale powder (FSP) at various dosages (3%, 6%, 9%, and 12%) on the properties of asphalt binder and mixtures. Conventional tests, viscosity, storage stability, Fourier transform infrared spectroscopy, and multiple stress creep recovery tests were conducted on the binder. Mix design, wheel tracking, indirect tensile strength, fatigue, and ultrasonic pulse velocity tests were evaluated for the asphalt mixtures. The results showed that FSP increased the binder’s stiffness and reduced the temperature susceptibility but compromised the low-temperature performance and workability regardless of the dosages. The storage stability test results demonstrated the improved high-temperature storage stability. In the mixtures, the permanent deformation resistance enhanced with increasing the FSP content, decreasing the rut depth from 4.3 mm for the control sample to 2.9 mm at 12% FSP. The moisture damage resistance, indicated by the tensile strength ratio, increased from 90% for the control sample to 94.1% at 12% FSP. However, the fatigue life decreased from 14010 cycles for the control sample to 11190 cycles at 12% FSP. The dynamic and elastic modulus values before conditioning increased with higher FSP dosages, and this increasing trend was also observed after conditioning, signifying greater stiffness retention and moisture resistance of the asphalt mixtures containing higher amounts of FSP. Numerically, the 6–9% FSP range offered the optimum balance, improving the rutting resistance by 18% and the moisture resistance by 3.2% compared to those of the control sample, while limiting the fatigue life to 12% and maintaining the workability. Overall, FSP has potential for use as an asphalt biomodifier by transforming an environmental liability into a value-added sustainable paving material.
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| 2. |
- Abdeldjouad, Lokmane, et al.
(författare)
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Thermal curing effects on alkali-activated treated soils with palm oil fuel ash
- 2023
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Regarding the significance of binder quantity, alkali activator molarities, and thermal curing, this work was utilized to geopolymerize with a potassium-based alkaline activator to strengthen soils. Five different molarities of palm oil fuel ash (POFA) in four different amounts were utilized to activate the clayey soil. POFA admixtures have been used to test soils. The results showed that for mixtures with 10 and 12.5 molarities, the unconfined compressive strength (UCS) with 15 % and 20 % of POFA was stronger. Comparing the strengths of the blends with various POFA amounts and concentration molarities allowed for this determination. To increase the strength, it is crucial to consider how the geopolymerization method's temperature and curing time affect the UCS of the soil-POFA mixture with and without fibers. The UCS of the treated soil mixtures was changed by heating at 30, 50, 70, and 90 degrees C. The outcomes demonstrate that increasing the curing temperature will hasten the alkaline activation process. After seven days of heating, the treated soil specimens with and without fibers exhibit the best mechanical properties at a healing temperature of about 70 degrees C, with compressive strengths of 16.7 and 11.4 MPa. The interaction between the geo-polymeric matrix and the fiber surface, the molarities of the alkaline solution, and the heating temperature were the most important aspects, according to an investigation of the microstructures, in improving the behavior of the reinforced mixes. By offering an efficient approach for increasing the qualities of soil treated by the alkali activation of POFA through the inclusion of glass fibers with adequate molarities of reagent and cure heating temperature, the current work offers new insights into soil stabilization operations. This has advantages over conventional calcium-based binders due to their emission of carbon dioxide during manufacture, which is one of the major causes of global warming.
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| 3. |
- Abdulhameed, Ali A., et al.
(författare)
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Experimental and environmental investigations of the impacts of wood sawdust on the performance of reinforced concrete composite beams
- 2023
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Ingår i: Case Studies in Construction Materials. - : Elsevier Ltd. - 2214-5095. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- It has been established that using recycled materials to replace some of the fine aggregates is a viable solution. Most researchers focused on the durability aspect of wood sawdust concrete, while less information is available on its structural performance. Therefore, this article aimed to investigate the performance of reinforced concrete beams fabricated from concrete with a partially replaced fine aggregate (FA) by wood sawdust (WS) in the range of 5–45 % (by weight). Six beams underwent 4-point bending tests till collapse. The beams' slump, density, compressive strength, cracking and failure mode, energy absorption, and economic and environmental aspects were studied. The findings showed that the failure region of sawdust concrete was more significant than the reference samples. Despite the compressive strength of the concrete containing different ratios of sawdust being reduced by about 7–30 %, the target compressive strength still has a limit of low to normal concrete grade. The results show that the increase in sawdust percentages decreased the acquired absorbed energy of the subjected load to reach failure. A cost reduction of 9 % and a cost index of 61 % is achieved using wooden sawdust-based concrete. By substituting sawdust for fine aggregate, the sustainability of sawdust concrete in terms of cost and environmental advantages may be improved. In addition, it is well-known that harnessing the transformative potential of industrial waste in concrete production not only minimizes landfill usage, but also promotes resource efficiency, reduces carbon emissions, and advances the circular economy, propelling designers, engineering and builders towards a greener and more sustainable future in the construction industry. According to the test findings, wood sawdust may be utilized to produce normal and low-strength structural concrete.
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| 4. |
- Abuhussain, Mohammed Awad, et al.
(författare)
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Data-driven approaches for strength prediction of alkali-activated composites
- 2024
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Alkali-activated composites (AACs) have attracted considerable interest as a promising alternative to reduce CO2 emissions from Portland cement production and advance the decarbonisation of concrete construction. This study describes the data-driven predictive modelling to anticipate the compressive strength (CS) of AACs. Four different modelling techniques have been chosen to forecast the CS of AACs using the selected data set. The decision tree (DT), multi-layer perceptron (MLP), bagging regressor (BR), and AdaBoost regressor (AR) were employed to investigate the precision level of each model. When it comes to predicting the CS of AACs, the results show that the AR model performs better than the BR model, the MLP model, and the DT model by providing a higher value for the coefficient of determination, which is equal to 0.91, and a lower MAPE value, which is equal to 13.35%. However, the accuracy level of the BR model was very near to that of the AR model, with the R2 value suggesting a value of 0.90 and the MAPE value indicating a value of 14.43%. Moreover, the graphical user interface has also been developed for the strength prediction of alkali-activated composites, making it easy to get the required output from the selected inputs.
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| 5. |
- Almusaed, Amjad, 1967-, et al.
(författare)
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Building materials in eco-energy houses from Iraq and Iran
- 2015
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 2, s. 42-54
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Tidskriftsartikel (refereegranskat)abstract
- Builders from the Western part of Asia are trained to make buildings that can fulfil certain required functions while giving full consideration to all sites and environmental conditions. The research covers the zone between Iraq and Iran. The first investigated region is the "Mesopotamian Marshes" or Iraqi-Iran Marshes, a wetland zone situated in southern Iraq and partially in southwestern Iran. The other region is a desert district, which includes a prominent part of the southern and western parts of Iraq and part of Iran. The last is the centre city of Basra. The building materials were the most important building element that affected the conformation of vernacular habitats from the western part of Asia in general and the Iraq-Iran area in particular. In this study, we needed to focus on the effects of ecological and energy-efficiency processes in creating vernacular habitats and the selection of optimal building systems and materials in this part of the world, which can be an essential point for sustainable environmental building processes in the future. Reeds, clay, straw, bricks, and wood were the most popular building materials used by builders from this region. The impact of building material on the environment embodies the essential method implicitly significant in this research to effectively determine traditional building materials in the environment, in addition to comparative analysis. This presents an essential factor of our analysis, in addition to the impact of environments on building systems. The main target of this study is to benefit designers and building engineers in their pursuit to find optimal and competent solutions suitable for specific local microclimates using traditional methods in the design process that are sustainable and ecological.
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| 6. |
- Alshaeer, Honin Ali Yahya, et al.
(författare)
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Optimisation of compressive strength of foamed concrete with a novel Aspergillus iizukae EAN605 fungus
- 2023
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- The production of concrete by incorporating a microorganism has emerged as a promising research area, offering potential benefits such as reduce carbon footprint, enhance durability and increased strength. The present study reported for the first time using a fungal strain (Aspergillus iizukae EAN605) in biocementation. The study aims to investigate the effectiveness of incorporating Aspergillus iizukae EAN 605 into foam concrete to improve its performance, particularly its strength. The study employs the response surface methodology (RSM) to explore the relationship between density, microorganism concentration and water /cement ratio (w/c) and their effects on compressive strength. Through a series of experiments,the highest recorded compressive strength was achieved with a density of 1800kg/m3, w/c ratio of 0.5, and Aspergillus iizukae EAN605 concentration of 0.5g/l, resulting in a remarkable 37.5% increase compared to foam concrete (FC). The variables of density, A. iizukae EAN 605 and their interaction density*fungi (D*F) significantly impacted compressive strength, with p-values of 0.000, 0.016, and 0.010, respectively.X-ray diffraction (XRD) analysis was employed to identify the crystalline composition of the precipitates formed on the fungal hyphae, providing insights into the mineralogical transformations occurring during the biocementation process. Additionally, scanning electron microscope (SEM) imaging was utilised to visualise the morphology and distribution of the calcite crystals, further supporting the evidence of fungal-mediated mineral precipitation in foam concrete. The findings of this study hold significant implications for the concrete industry, as the incorporation of Aspergillus iizukae EAN605 in foam concrete offers a sustainable solution to enhance compressive strength and contribute to environmental friendly construction practices. This study provides valuable insights for future research and practical applications in the field of bio-foamed concrete (B-FC).
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| 7. |
- Alyami, Mana, et al.
(författare)
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Estimating compressive strength of concrete containing rice husk ash using interpretable machine learning-based models
- 2024
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- The construction sector is a major contributor to global greenhouse gas emissions. Using recycled and waste materials in concrete is a practical solution to address environmental challenges. Currently, agricultural waste is widely used as a substitute for cement in the production of eco-friendly concrete. However, traditional methods for assessing the strength of such materials are both expensive and time-consuming. Therefore, this study uses machine learning techniques to develop prediction models for the compressive strength (CS) of rice husk ash (RHA) concrete. The ML techniques used in the present study include random forest (RF), light gradient boosting machine (LightGBM), ridge regression, and extreme gradient boosting (XGBoost). A total of 348 values of CS were collected from the experimental studies, and five characteristics of RHA concrete were taken as input variables. For the performance assessment of the models, multiple statistical metrics were used. During the training phase, the correlation coefficients (R) obtained for ridge regression, RF, XGBoost, and LightGBM were 0.943, 0.981, 0.985, and 0.996, respectively. In the testing set, the developed models demonstrated even higher performance, with correlation coefficients of 0.971, 0.993, 0.992, and 0.998 for ridge regression, RF, XGBoost, and LightGBM, respectively. The statistical analysis revealed that the LightGBM model outperformed other models, whereas the ridge regression model exhibited comparatively lower accuracy. SHapley Additive exPlanation (SHAP) method was employed for the interpretability of the developed model. The SHAP analysis revealed that water-to-cement is a controlling parameter in estimating the CS of RHA concrete. In conclusion, this study provides valuable guidance for builders and researchers to estimate the CS of RHA concrete. However, it is suggested that more input variables be incorporated and hybrid models utilized to further enhance the reliability and precision of the models.
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| 8. |
- Alyami, Mana, et al.
(författare)
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Predictive modeling for compressive strength of 3D printed fiber-reinforced concrete using machine learning algorithms
- 2024
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Three-dimensional (3D) printing in the construction industry is growing rapidly due to its inherent advantages, including intricate geometries, reduced waste, accelerated construction, cost-effectiveness, eco-friendliness, and improved safety. However, optimizing the mixture composition for 3D-printed concrete remains a formidable task, encompassing multiple variables and requiring a comprehensive trial-and-error experimentation process. Accordingly, this study used seven machine learning (ML) algorithms, including support vector regression (SVR), decision tree (DT), SVR-Bagging, SVR-Boosting, random forest (RF), gradient boosting (GB), and gene expression programming (GEP) for forecasting the compressive strength (CS) of 3D printed fiber-reinforced concrete (3DP-FRC). For model development, 299 data points were collected from experimental studies and split into two portions: 70% for model training and 30% for model validation. Various statistical metrics were employed to examine the accuracy and generalizability of the established models. The DT, RF, GB, and GEP models demonstrated higher accuracy in the validation set, achieving correlation (R) values of 0.987, 0.986, 0.986, and 0.98, respectively. The DT, RF, GB, and GEP models exhibited mean absolute error (MAE) scores of 4.644, 3.989, 3.90, and 5.691, respectively. Furthermore, the combination of SVR with boosting and bagging techniques slightly improved the accuracy compared to the individual SVR model. Additionally, the SHapley Additive exPlanations (SHAP) approach unveils the proportional significance of parameters in influencing the CS of 3DP-FRC. The SHAP technique revealed that water, silica fume, superplasticizer, sand content, and loading directions are the dominant parameters in estimating the CS of 3DP-FRC. The SHAP local interpretability unveils the intrinsic relationship between diverse input variables and their impacts on the strength of 3DP-FRC. The SHAP interpretability offers significant insights into the optimum mix proportion of 3DP-FRC.
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| 9. |
- Alyousef, Rayed, et al.
(författare)
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Predicting the properties of concrete incorporating graphene nano platelets by experimental and machine learning approaches
- 2024
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Ingår i: Case Studies in Construction Materials. - : Elsevier Ltd. - 2214-5095. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Modern infrastructure requirements necessitate structural components with improved durability and strength properties. The incorporation of nanomaterials (NMs) into concrete emerges as a viable strategy to enhance both the durability and strength of the concrete. Nevertheless, the complexities inherent in these nanoscale cementitious composites are notably intricate. Traditional regression models face constraints in comprehensively capturing these intricate compositions. Thus, posing challenges in delivering precise and dependable estimations. Therefore, the current study utilized three machine learning (ML) methods, including artificial neural network (ANN), gene expression programming (GEP), and adaptive neuro-fuzzy inference system (ANFIS), in conjunction with experimental investigation to study the effect of the integration of graphene nanoplatelets (GNPs) on the electrical resistivity (ER) and compressive strength (CS) of concrete containing GNPs. Concrete containing GNPs demonstrated an improved fractional change in resistivity (FCR) and strength. The experimental measures depict that strength enhancement was notable at GNP concentrations of 0.05% and 0.1%, showcasing increases of 13.23% and 16.58%, respectively. Simultaneously, the highest observed FCR change reached −12.19% and −13%, respectively. The prediction efficacy of the three models proved to be outstanding in forecasting the characteristics of concrete containing GNPs. For CS, the GEP, ANN, and ANFIS models demonstrated impressive correlation coefficient (R) values of 0.974, 0.963, and 0.954, respectively. For electrical resistivity, the GEP, ANN, and ANFIS models exhibited high R-values of 0.999, 0.995, and 0.987, respectively. The comparative analysis of the models revealed that the GEP model delivered precise predictions for both ER and CS. The mean absolute error (MAE) of the GEP-CS model demonstrated a 14.51% reduction compared to the ANN-CS model and a substantial 48.15% improvement over the ANFIS-CS model. Similarly, the ANN-CS model displayed an MAE that was 38.14% lower compared to the ANFIS-CS model. Moreover, the MAE of the GEP-ER model demonstrated a 56.80% reduction compared to the ANN-CS model and a substantial 82.47% improvement over the ANFIS-CS model. The Shapley Additive explanation (SHAP) analysis provided that curing age exhibited the highest SHAP score. Thus, indicating its predominant contribution to CS prediction. In predicting ER, the graphene content exhibited the highest SHAP score, signifying its predominant contribution to ER estimation. This study highlights ML's accuracy in predicting the properties of concrete with graphene nanoplatelets, offering a fast and cost-effective alternative to time-consuming experiments.
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| 10. |
- Çelik, Ali İhsan, et al.
(författare)
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Mechanical performance of geopolymer concrete with micro silica fume and waste steel lathe scraps
- 2023
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Ingår i: Case Studies in Construction Materials. - : Elsevier. - 2214-5095. ; 19
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Tidskriftsartikel (refereegranskat)abstract
- Environmental studies for solutions are among the most important agendas of the scientific world. Most of the new studies are taking into account environmental effects. However, it is interesting for the scientific world to find solutions for accumulated environmental problems, to reduce harmful production, and to turn wastes that cause environmental pollution into useful products. In addition to incorporating fly ash, a recognized environmentally friendly and sustainable material, geopolymer concrete, utilizes micro silica fume (micro silica) as a binding agent. Furthermore, waste lathe scraps are introduced to enhance and safeguard the concrete’s mechanical properties. During the preparation phase, significant enhancements have been identified in the workability and setting time of concrete. A total of 16 test samples were prepared in this study. Micro silica of 0%, 5%, 10%, and 20%, and lathe scraps of 0%, 1%, 2%, and 3% were examined. Experimental findings revealed that incorporating 5% micro silica resulted in notable improvements in the compressive, flexural, and splitting tensile strengths, with the increases of 14.4%, 7.45%, and 6.18%, respectively. However, higher additions of 10% and 20% were found to decrease these strengths. In contrast, the inclusion of 1% lathe scraps led to considerable increases in the compressive, flexural, and splitting tensile strengths by 11.4%, 6.35%, and 8.23%, respectively. However, the addition of 2% and 3% lathe scraps resulted in the reduced capacity. The findings demonstrated that combining 5% micro silica with 1% lathe scraps provided the highest strength, with the improvements of 25.7%, 14.4%, and 12% in the compressive, flexural,and splitting tensile strengths, respectively. Considering the enhancements in the workability, setting time, and strengths observed in all the tests, the recommended optimal geopolymer mixture is 5% micro silica together with 1% lathe scraps.
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