Conventional reinforced concrete (RC) structures are commonly associated with the corrosion of steel reinforcement. The application of carbon fiber reinforced polymer (CFRP) bars as flexural reinforcement has become a new promising option. This paper presents a state-of-the art flexural strength on concrete beams reinforced with CFRP bars. Concrete compressive and CFRP bar tensile strain, reinforcement ratio, types of surface treatment on CFRP bar and concrete compressive strength were identified as aspects of behavior. Significant findings in the literature had manifested all aspects of behavior that were affecting the flexural strength, deflections and crack characteristics of CFRP RC beams. In addition, the experimental result on 98 specimens of CFRP RC beams from the literature show that ACI 440.1R-15 and CSA S806-12 standards underestimate the ultimate flexural moment capacity of CFRP RC beams. On the other hand, Kara and Ashour predictions are more accurate with the experimental values. Moreover, hotspot research topics were also highlighted for further considerations in future studies.
Silica fume (SF) is a mineral additive that is widely used in the construction industry when producing sustainable concrete. The integration of SF in concrete as a partial replacement for cement has several evident benefits, including reduced CO2 emissions, cost-effective concrete, increased durability, and mechanical qualities. As environmental issues continue to grow, the development of predictive machine learning models is critical. Thus, this study aims to create modelling tools for estimating the compressive and cracking tensile strengths of silica fume concrete. Multilayer perceptron neural networks (MLPNN), adaptive neural fuzzy detection systems (ANFIS), and genetic programming are all used (GEP). From accessible literature data, a broad and accurate database of 283 compressive strengths and 149 split tensile strengths was created. The six most significant input parameters were cement, fine aggregate, coarse aggregate, water, superplasticizer, and silica fume. Different statistical measures were used to evaluate models, including mean absolute error, root mean square error, root mean squared log error and the coefficient of determination. Both machine learning models, MLPNN and ANFIS, produced acceptable results with high prediction accuracy. Statistical analysis revealed that the ANFIS model outperformed the MLPNN model in terms of compressive and tensile strength prediction. The GEP models outperformed all other models. The predicted values for compressive strength and splitting tensile strength for GEP models were consistent with experimental values, with an R2 value of 0.97 for compressive strength and 0.93 for splitting tensile strength. Furthermore, sensitivity tests revealed that cement and water are the determining parameters in the growth of compressive strength but have the least effect on splitting tensile strength. Cross-validation was used to avoid overfitting and to confirm the output of the generalized modelling technique. GEP develops an empirical expression for each outcome to forecast future databases' features to promote the usage of green concrete.
The object of this research is concrete-filled steel tubes (CFST). The article aimed to develop a prediction Multiphysics model for the circular CFST column by using the Artificial Neural Network (ANN), the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Gene Expression Program (GEP). The database for this study contains 1667 datapoints in which 702 are short CFST columns and 965 are long CFST columns. The input parameters are the geometric dimensions of the structural elements of the column and the mechanical properties of materials. The target parameters are the bearing capacity of columns, which determines their life cycle. A Multiphysics model was developed, and various statistical checks were applied using the three artificial intelligence techniques mentioned above. Parametric and sensitivity analyses were also performed on both short and long GEP models. The overall performance of the GEP model was better than the ANN and ANFIS models, and the prediction values of the GEP model were near actual values. The PI of the predicted Nst by GEP, ANN and ANFIS for training are 0.0416, 0.1423, and 0.1016, respectively, and for Nlg these values are 0.1169, 0.2990 and 0.1542, respectively. Corresponding OF values are 0.2300, 0.1200, and 0.090 for Nst, and 0.1000, 0.2700, and 0.1500 for Nlg. The superiority of the GEP method to the other techniques can be seen from the fact that the GEP technique provides suitable connections based on practical experimental work and does not rely on prior solutions. It is concluded that the GEP model can be used to predict the bearing capacity of circular CFST columns to avoid any laborious and time-consuming experimental work. It is also recommended that further research should be performed on the data to develop a prediction equation using other techniques such as Random Forest Regression and Multi Expression Program.
Electromagnetic pollution, or electromagnetic interference (EMI), is a phenomenon that has arisen due to the fast spread of electronic gadgets. To overcome EMI problem, polymer-based composites have sparked considerable attention among researchers owing to their superior qualities. Hence, this work utilizes magnetite-modified graphene (MMG) filler with polyvinylidene fluoride (PVDF) polymer to form polymer composites in various proportions ranging from 2 to 10 wt% to study the EM properties in the X-band. It was observed that the sample composite having a MMG filler content of 10 wt% possesses a relatively higher electrical conductivity of 0.65 S/cm as compared to the other prepared composites in this research work. The same sample composite also attained a total shielding efficacy of 53.04 dB at a thickness of 3 mm. Moreover, it was observed that the filler has improved the material's thermal stability and microwave absorption capacity, making it a high-efficiency EMI shielding material appropriate for usage in the electronic and aviation industries.
Concrete technology is adopted worldwide in construction due to its effectiveness, performance, and price benefits. Subsequently, it needs to be an eco-friendly, sustainable, and energy-efficient material. This is achieved by replacing or adding energy-efficient concrete materials from industries, such as ground granulated blast furnace slag, steel slag, fly ash, bottom ash, rice husk ash, etc. Likewise, copper slag is a waste material produced as molten slag from the copper industry, which can be used in concrete production. Copper slag can perform roles similar to pozzolans in the hydration process. This paper extends the comparative study of copper slag concrete with polypropylene fiber (PPF) subjected to destructive and non-destructive testing. Under destructive testing, compressive strength of concrete cubes, compressive strength of mortar cubes, splitting tensile tests on cylindrical specimens, and flexural tests on plain cement concrete were conducted and analysed. Ultrasonic pulse velocity and rebound hammer tests were performed on the samples as per IS13311-Part 1-1992 for non-destructive testing. The 100% replacement of copper slag exhibited a very high workability of 105 mm, while the addition of 0.8% PPF decreased the flowability of the concrete. Hence, the workability of concrete decreases as the fiber content increases. The density of the concrete was found to be increased in the range of 5% to 10%. Furthermore, it was found that, for all volume fractions of fiber, there was no reduction in compressive strength of up to 80% of copper slag concrete compared to control concrete. The 40% copper slag concrete was the best mix proportion for increasing compressive strength. However, for cement mortar applications, 80% copper slag is recommended. The findings of non-destructive testing show that, except for 100% copper slag, all mixes were of good quality compared to other mixes. Linear relationships were developed to predict compressive strength from UPV and rebound hammer test values. This relationship shows better prediction among dependent and independent values. It is concluded that copper slag has a pozzolanic composition, and is compatible with PPF, resulting in good mechanical characteristics.
The construction industry relies heavily on concrete as a building material. The coarse aggregate makes up a substantial portion of the volume of concrete. However, the continued exploitation of granite rock for coarse aggregate results in an increase in the future generations' demand for natural resources. In this investigation, coconut shell was used in the place of conventional aggregate to produce coconut shell lightweight concrete. Class F fly ash was used as a partial substitute for cement to reduce the high cement content of lightweight concrete. The impact of steel fiber addition on the compressive strength and flexural features of sustainable concrete was investigated. A 10% weight replacement of class F fly ash was used in the place of cement. Steel fiber was added at 0.25, 0.5, 0.75, and 1.0% of the concrete volume. The results revealed that the addition of steel fibers enhanced the compressive strength by up to 39%. The addition of steel fiber to reinforced coconut shell concrete beams increased the ultimate moment capacity by 5-14%. Flexural toughness was increased by up to 45%. The span/deflection ratio of all fiber-reinforced coconut shell concrete beams met the IS456 and BS 8110 requirements. Branson's and the finite element models developed in this study agreed well with the experimental results. As a result, coconut shell concrete with steel fiber could be considered as a viable and environmentally-friendly construction material.
Nuclear energy offers a wide range of applications, which include power generation, X-ray imaging, and non-destructive tests, in many economic sectors. However, such applications come with the risk of harmful radiation, thereby requiring shielding to prevent harmful effects on the surrounding environment and users. Concrete has long been used as part of structures in nuclear power plants, X-ray imaging rooms, and radioactive storage. The direction of recent research is headed toward concrete's ability in attenuating harmful energy radiated from nuclear sources through various alterations to its composition. Radiation shielding concrete (RSC) is a composite-based concrete that was developed in the last few years with heavy natural aggregates such as magnetite or barites. RSC is deemed a superior alternative to many types of traditional normal concrete in terms of shielding against the harmful radiation, and being economical and moldable. Given the merits of RSCs, this article presents a comprehensive review on the subject, considering the classifications, alternative materials, design additives, and type of heavy aggregates used. This literature review also provides critical reviews on RSC performance in terms of radiation shielding characteristics, mechanical strength, and durability. In addition, this work extensively reviews the trends of development research toward a broad understanding of the application possibilities of RSC as an advanced concrete product for producing a robust and green concrete composite for the construction of radiation shielding facilities as a better solution for protection from sources of radiation. Furthermore, this critical review provides a view of the progress made on RSCs and proposes avenues for future research on this hotspot research topic.