Structural performance of FRP composite bars reinforced rubberized concrete compressive members: Tests and numerical modeling.

Waste tyre rubber has become an environmental and health concern that needs to be sustainably managed to avoid fire hazards and save natural resources. This research work aims to study the structural behavior of glass fiber reinforced polymer (glass-FRP) reinforced rubberized concrete (GRC) compressive elements under monotonic axial compression loads. Nine GRC circular compressive elements with different axial and crosswise reinforcement ratios were fabricated. All the elements were 300 mm in diameter and 1200 mm in height. A 3D nonlinear finite element equation (FEM) was suggested for the GRC compressive elements using a commercial package ABAQUS. A parametric study has been done to examine the effect of various parameters of GRC elements. The test outcomes revealed that the ductility of GRC elements ameliorated with the lessening in the spaces of glass-FRP ties. The addition of rubberized concrete improved the ductility of GRC elements. The damage to GRC elements occurred due to the vertical cracking along the height of the elements. The estimates of FEM were in close agreement with the test outcomes. The suggested empirical equation depending on the 600 test elements, which considered the lateral confinement effect of FRP ties, presented higher accuracy than previous equations.

Effect of banana tree leaves ash as cementitious material on the durability of concrete against sulphate and acid attacks.

The construction industry's rapid growth poses challenges tied to raw material depletion and increased greenhouse gas emissions. To address this, alternative materials like agricultural residues are gaining prominence due to their potential to reduce carbon emissions and waste generation. In this context this research optimizes the use of banana leaves ash as a partial cement substitution, focusing on durability, and identifying the ideal cement-to-ash ratio for sustainable concrete. For this purpose, concrete mixes were prepared with BLA replacing cement partially in different proportions i.e. (0 %, 5 %, 10 %, 15 %, & 20 %) and were analyzed for their physical, mechanical and Durability (Acid and Sulphate resistance) properties. Compressive strength, acid resistance and sulphate resistance testing continued for 90 days with the intervals of 7, 28 and 90 days. The results revealed that up to 10 % incorporation of BLA improved compressive strength by 10 %, while higher BLA proportions (up to 20 %) displayed superior performance in durability tests as compared to the conventional mix. The results reveal the potentials of banana leave ash to refine the concrete matrix by formation of addition C-S-H gel which leads towards a better performance specially in terms of durability aspect. Hence, banana leaf ash (BLA) is an efficient concrete ingredient, particularly up to 10 % of the mix. Beyond this threshold, it's still suitable for applications where extreme strength isn't the primary concern, because there may be a slight reduction in compressive strength.

Evaluating the compressive strength of glass powder-based cement mortar subjected to the acidic environment using testing and modeling approaches.

This study conducted experimental and machine learning (ML) modeling approaches to investigate the impact of using recycled glass powder in cement mortar in an acidic environment. Mortar samples were prepared by partially replacing cement and sand with glass powder at various percentages (from 0% to 15%, in 2.5% increments), which were immersed in a 5% sulphuric acid solution. Compressive strength (CS) tests were conducted before and after the acid attack for each mix. To create ML-based prediction models, such as bagging regressor and random forest, for the CS prediction following the acid attack, the dataset produced through testing methods was utilized. The test results indicated that the CS loss of the cement mortar might be reduced by utilizing glass powder. For maximum resistance to acidic conditions, the optimum proportion of glass powder was noted to be 10% as cement, which restricted the CS loss to 5.54%, and 15% as a sand replacement, which restricted the CS loss to 4.48%, compared to the same mix poured in plain water. The built ML models also agreed well with the test findings and could be utilized to calculate the CS of cementitious composites incorporating glass powder after the acid attack. On the basis of the R2 value (random forest: 0.97 and bagging regressor: 0.96), the variance between tests and forecasted results, and errors assessment, it was found that the performance of both the bagging regressor and random forest models was similarly accurate.

Exploring the antecedents of AI adoption for effective HRM practices in the Indian pharmaceutical sector.

Purpose: The aim of this research is to investigate the factors that facilitate the adoption of artificial intelligence (AI) in order to establish effective human resource management (HRM) practices within the Indian pharmaceutical sector. Design/methodology/approach: A model explaining the antecedents of AI adoption for building effective HRM practices in the Indian pharmaceutical sector is proposed in this study. The proposed model is based on task-technology fit theory. To test the model, a two-step procedure, known as partial least squares structural equational modeling (PLS-SEM), was used. To collect data, 160 HRM employees from pharmacy firms from pan India were approached. Only senior and specialized HRM positions were sought. Findings: An examination of the relevant literature reveals factors such as how prepared an organization is, how people perceive the benefits, and how technological readiness influences AI adoption. As a result, HR systems may become more efficient. The PLS-SEM data support all the mediation hypothesized by proving both full and partial mediation, demonstrating the accuracy of the proposed model. Originality: There has been little prior research on the topic; this study adds a great deal to our understanding of what motivates human resource departments to adopt AI in the pharmaceutical companies of India. Furthermore, AI-related recommendations are made available to HRM based on the results of a statistical analysis.

Basalt Fiber Reinforced Concrete: A Compressive Review on Durability Aspects.

The creation of sustainable composites reinforced with natural fibers has recently drawn the interest of both industrial and academics. Basalt fiber (BF) stands out as the most intriguing among the natural fibers that may be utilized as reinforcement due to their characteristics. Numerous academics have conducted many tests on the strength, durability, temperature, and microstructure characteristics of concrete reinforced with BF and have found promising results. However, because the information is dispersed, readers find it problematic to assess the advantages of BF reinforced concrete, which limits its applications. Therefore, a condensed study that provides the reader with an easy route and summarizes all pertinent information is needed. The purpose of this paper (Part II) is to undertake a compressive assessment of basalt fiber reinforced concrete's durability features. The results show that adding BF significantly increased concrete durability. The review also identifies a research deficiency that must be addressed before BF is used in practice.

Evaluation of small hydropower turbines installed downstream of Nile River branches (Egypt).

The current study proposes a new strategy for using small hydroelectric turbines in downstream river branches with the least amount of construction and the lowest cost by comparing two different methods of installing the turbines, the first by installing the turbines at the river's bottom and the second by installing the turbines on floating boats. The methodology of this article is based on predicting the distribution of velocities through the watercourse using experimental data collected at various points in the river's depth, and then predicting the resulting electrical power for different sizes of turbines, as well as estimating the number of turbines for each row and the number of rows along the river. Therefore, Investigate the proposed systems. The proposed small hydropower system's economic viability and environmental impact are investigated in this article. According to the nature of the waterway, the best diameter of a turbine that can be used is 1.5 m based on water velocities and river depths. The proposed power plant generated 25.8 kW per single turbine row, with an estimated cost of produced power (0.035 USD/kWh) of approximately 20 turbines installed per row. Compared to other renewable energy sources, the proposed hydropower system is cost-effective and environmentally friendly, as generating electricity with the proposed small hydropower plant could reduce annual carbon dioxide emissions by 368 tones of CO2 per single turbine row.

A hybrid Cycle GAN-based lightweight road perception pipeline for road dataset generation for Urban mobility.

One of the major problems that cause continual trouble in deep learning networks is that training a large network requires massive labelled datasets. The preparation of a massive labelled dataset is a cumbersome task and requires lot of human interventions. This paper proposes a novel generator network 'Sim2Real' transfer is a recent and fast-developing field in machine learning used to bridge the gap between simulated and real data. Training with simulated datasets often converges due to its size but fails to generalize real-world applications. Simulated datasets can be used to train and test deep learning models, enables the development and evaluation of new algorithms and architectures. By simulating road dataset, researchers can generate large amounts of realistic road-traffic dataset that can be used to study and understand several problems such as vehicular object tracking and classification, traffic situation analysis etc. The main advantage of such a transfer algorithm is to use the abundance of a simulated dataset to generate huge realistic-looking datasets to solve data-intense tasks. This work presents a novel, robust sim2real algorithm that converts the labels of a semantic segmentation map to a realistic-looking street view using the Cityscapes dataset and aims to achieve robust urban mobility for smart cities. Further, the generalizability of the Cycle Generative Adversarial Network (CycleGAN) architecture was tested by using an origami robot dataset for sim2real transfer. We show that the results were found to be qualitatively satisfactory for different traffic analysis applications. In addition, road perception was done using a lightweight SVM pipeline and evaluated on the KITTI dataset. We have incorporated Cycle Consistency Loss and Identity Loss as the metrics to evaluate the performance of the proposed Cycle GAN model. We inferred that the proposed Cycle GAN model provides an Identity loss of less than 0.2 in both the Cityscapes dataset and KITTI datasets. Also, we understand that the super-pixel resolution has a good impact on the quantitative results of the proposed Cycle GAN models.

Compressive Strength Evaluation of Ultra-High-Strength Concrete by Machine Learning.

In civil engineering, ultra-high-strength concrete (UHSC) is a useful and efficient building material. To save money and time in the construction sector, soft computing approaches have been used to estimate concrete properties. As a result, the current work used sophisticated soft computing techniques to estimate the compressive strength of UHSC. In this study, XGBoost, AdaBoost, and Bagging were the employed soft computing techniques. The variables taken into account included cement content, fly ash, silica fume and silicate content, sand and water content, superplasticizer content, steel fiber, steel fiber aspect ratio, and curing time. The algorithm performance was evaluated using statistical metrics, such as the mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The model's performance was then evaluated statistically. The XGBoost soft computing technique, with a higher R2 (0.90) and low errors, was more accurate than the other algorithms, which had a lower R2. The compressive strength of UHSC can be predicted using the XGBoost soft computing technique. The SHapley Additive exPlanations (SHAP) analysis showed that curing time had the highest positive influence on UHSC compressive strength. Thus, scholars will be able to quickly and effectively determine the compressive strength of UHSC using this study's findings.

Heat-Induced Spalling of Concrete: A Review of the Influencing Factors and Their Importance to the Phenomenon.

Heat-induced spalling in concrete is a problem that has been the subject of intense debate. The research community has, despite all the effort invested in this problem, few certain and definitive answers regarding the causes of and the way in which spalling happens. A major reason for this difficulty is the lack of a unified method for testing, which makes comparing data from various studies against each other a difficult task. Many studies have been performed that show the positive effects of using synthetic micro-fibres, such as polypropylene (PP). The mechanism with which PP fibres improve heat-induced spalling resistance in concrete, however, remains a subject of debate. This paper, therefore, looks at the work that has been performed in the field of spalling (particularly spalling of self-compacting concrete (SCC)). Influencing factors are identified and their links to each other (as reported) are discussed. A particular emphasis is put on discussing the role of PP fibres and how they improve the behaviour of high-performance concrete (HPC) at elevated temperatures. A brief summary of the reviewed papers are provided for each of the influencing factors to help the reader navigate with ease through the references. An introduction to heat-induced spalling and the common causes (as reported in the literature) is also included to highlight the wide range of theories trying to explain the spalling phenomenon.

Overview of Concrete Performance Made with Waste Rubber Tires: A Step toward Sustainable Concrete.

Utilizing scrap tire rubber by incorporating it into concrete is a valuable option. Many researchers are interested in using rubber tire waste in concrete. The possible uses of rubber tires in concrete, however, are dispersed and unclear. Therefore, a compressive analysis is necessary to identify the benefits and drawbacks of rubber tires for concrete performance. For examination, the important areas of concrete freshness, durability, and strength properties were considered. Additionally, several treatments and a microstructure investigation were included. Although it has much promise, there are certain obstacles that prevent it from being used as an aggregate in large numbers, such as the rubber's weak structural strength and poor binding performance with the cement matrix. Rubber, however, exhibits mechanical strength comparable to reference concrete up to 20%. The evaluation also emphasizes the need for new research to advance rubberized concrete for future generations.

Potential of Waste Marble Sludge for Repressing Alkali-Silica Reaction in Concrete with Reactive Aggregates.

The continuous development of the marble industry has led to an increase in the accumulation of waste marble sludge causing landfilling and health-associated issues. The intention of the current study is to explore the potential of waste marble sludge powder (MS) utilization as a means of controlling alkali-silica reaction (ASR) in concrete. Specimen (cubes, prisms, and mortar bars) were prepared to incorporate reactive aggregates and various proportions of MS ranging from 5% to 40% as a replacement for aggregates. Expansion and mechanical strength characteristics were determined to investigate the effectiveness of MS to control ASRfor up to 150 days. Results revealed that on replacing aggregates in the control specimen with 25% MS, the ASR expansion at 14 days reduced from 0.23% to 0.17%, and the expansion at 28 days reduced from 0.28% to 0.17% which is within limits as per American Standard for Testing of Materials (ASTM) C1260. Furthermore, specimens incorporating MS exhibited improved compressive and flexural strength as compared to the identical specimen without MS. Microstructural analysis using Scanning electron microscopy (SEM) revealed micro-cracks in the control specimen while the specimen incorporating MS was found intact. Thus, it can be foreseen that the use of MS as a partial replacement of aggregates can control ASR in concrete as well as reduce the dumping and harmful emissions issue.

Concrete Made with Partially Substitutions of Copper Slag (CPS): A State Art of Review.

Copper slag (CPS) is a large amount of waste material produced during the manufacture of copper. The disposal of this waste material becomes a problem for environmental concerns. Therefore, it is necessary to explore feasible alternate disposal options. They may also be utilized in concrete manufacturing to cut down on the usage of cement and natural aggregates. A lot of researchers focus on utilizing CPS in concrete, either as a cement replacement or as a filler material. This article aims to summarize the literature already carried out on CPS in conventional concrete to identify the influence of CPS on the fresh, hardened and durability performance of cement concrete. Results indicate that CPS improved the strength and durability performance of concrete but simultaneously decreased the slump value of concrete. Furthermore, an increase in the durability performance of concrete was also observed with CPS. However, the higher dose results declined in mechanical and durability aspects owing to a scarcity of flowability. Therefore, it is suggested to use the optimum dose of CPS. However, a different researcher recommends a different optimum dose ranging from 50 to 60% by weight of fine aggregate depending on the source of CPS. The review also recommends future researcher guidelines on CPS in concrete.

A Review on Strength and Durability Properties of Wooden Ash Based Concrete.

The partial replacement of cement in concrete with other building materials has come to light because of research on industrial waste and sustainable building practices. Concrete is made more affordable by using such components, and it also helps to ease disposal worries. Ash made by burning wood and other wood products is one example of such a substance. Many researchers focused on the utilization of wooden ash (WA) as a construction material. However, information is scattered, and no one can easily judge the impact of WA on concrete properties which restrict its use. Therefore, a details review is required which collect the past and current progress on WA as a construction material. relevant information. This review aims to collect all the relevant information including the general back of WA, physical and chemical aspects of WA, the impact of WA on concrete fresh properties, strength properties, and durability aspects in addition to microstructure analysis. The results indicate the WA decreased the slump and increased the setting time. Strength and durability properties improved with the substitution of WA due to pozzolanic reaction and micro-filling effects. However, the optimum dose is important. Different research recommends different optimum doses depending on source mix design etc. However, the majority of researcher suggests a 10% optimum substitution of WA. The review also concludes that, although WA has the potential to be used as a concrete ingredient but less researchers focused on WA as compared to other waste materials such as fly ash and silica fume etc.

Two-Way Shear Resistance of FRP Reinforced-Concrete Slabs: Data and a Comparative Study.

This study aims to investigate the two-way shear strength of concrete slabs with FRP reinforcements. Twenty-one strength models were briefly outlined and compared. In addition, information on a total of 248 concrete slabs with FRP reinforcements were collected from 50 different research studies. Moreover, behavior trends and correlations between their strength and various parameters were identified and discussed. Strength models were compared to each other with respect to the experimentally measured strength, which were conducted by comparing overall performance versus selected basic variables. Areas of future research were identified. Concluding remarks were outlined and discussed, which could help further the development of future design codes. The ACI is the least consistent model because it does not include the effects of size, dowel action, and depth-to-control perimeter ratio. While the EE-b is the most consistent model with respect to the size effect, concrete compressive strength, depth to control perimeter ratio, and the shear span-to-depth ratio. This is because of it using experimentally observed behavior as well as being based on mechanical bases.

Concrete Made with Iron Ore Tailings as a Fine Aggregate: A Step towards Sustainable Concrete.

The need for low-cost raw materials is driven by the fact that iron ore tailings, a prevalent kind of hazardous solid waste, have created major environmental issues. Although many studies have focused on using iron ore tailing (IOT) in concrete and have reported positive results, readers may find it difficult to accurately assess the behaviors of IOT in concrete due to the scattered nature of the information. Therefore, a comprehensive assessment of IOT in concrete is necessary. This paper thoroughly reviews the characteristics of concrete that contains IOT such as fresh properties, mechanical properties and durability at different age of curing. The outcome of this review indicates that by using IOT, concrete's mechanical properties and durability improved, but its flowability decreased. Compressive strength of concrete with 20% substitution of IOT is 14% more than reference concrete. Furthermore, up to 40% substitution of IOT produces concrete that has sufficient flowability and compactability. Scan electronic microscopy results indicate a weak interfacial transition zone (ITZ). The optimum IOT dosage is important since a greater dose may decrease the strength properties and durability owing to a lack of fluidity. Depending on the physical and chemical composition of IOT, the average value of optimum percentages ranges from 30 to 40%. The assessment also recommends areas of unsolved research for future investigations.

Mechanical and Durability Performance of Coconut Fiber Reinforced Concrete: A State-of-the-Art Review.

The push for sustainability in the construction sector has demanded the use of increasingly renewable resources. These natural fibers are biodegradable and non-toxic, and their mechanical capabilities are superior to those of synthetic fibers in terms of strength and durability. A lot of research recommends coconut fibers as an alternative to synthetic fibers. However, the knowledge is scattered, and no one can easily judge the suitability of coconut fibers in concrete. This paper presents a summary of research progress on coconut fiber (natural fibers) reinforced concrete. The effects of coconut fibers on the properties of concrete are reviewed. Factors affecting the fresh, hardened, and durability properties of concrete reinforced with coconut fiber are discussed. Results indicate that coconut fiber improved the mechanical performance of concrete due to crack prevention, similar to the synthetic fibers but decreased the flowability of concrete. However, coconut fibers improved flexure strength more effectively than compressive strength. Furthermore, improvement in some durability performance was also observed, but less information is available in this regard. Moreover, the optimum dose is an important parameter for high-strength concrete. The majority of researchers indicate that 3.0% coconut fiber is the optimum dose. The overall study demonstrates that coconut fibers have the creditability to be used in concrete instead of synthetic fibers.

Plastic Waste Management Strategies and Their Environmental Aspects: A Scientometric Analysis and Comprehensive Review.

Plastic consumption increases with the growing population worldwide and results in increased quantities of plastic waste. There are various plastic waste management strategies; however, the present management progress is not sustainable, and plastic waste dumping in landfills is still the most commonly employed strategy. Being nonbiodegradable, plastic waste dumping in landfills creates several environmental and human health problems. Numerous research studies have been conducted recently to determine safe and ecologically beneficial methods of plastic waste handling. This article performed a bibliographic analysis of the available literature on plastic waste management using a computational approach. The highly used keywords, most frequently cited papers and authors, actively participating countries, and sources of publications were analyzed during the bibliographic analysis. In addition, the various plastic waste management strategies and their environmental benefits have been discussed. It has been concluded that among the six plastic waste management techniques (landfills, recycling, pyrolysis, liquefaction, road construction and tar, and concrete production), road construction and tar and concrete production are the two most effective strategies. This is due to significant benefits, such as ease of localization, decreased greenhouse gas emissions, and increased durability and sustainability of manufactured materials, structures, and roadways. Conversely, using landfills is the most undesirable strategy because of the associated environmental and human health concerns. Recycling has equal benefits and drawbacks. In comparison, pyrolysis and liquefaction are favorable due to the production of char and fuel, but high energy requirements limit their benefits. Hence, the use of plastic waste for construction applications is recommended.

Compressive Strength of Steel Fiber-Reinforced Concrete Employing Supervised Machine Learning Techniques.

Recently, research has centered on developing new approaches, such as supervised machine learning techniques, that can compute the mechanical characteristics of materials without investing much effort, time, or money in experimentation. To predict the 28-day compressive strength of steel fiber-reinforced concrete (SFRC), machine learning techniques, i.e., individual and ensemble models, were considered. For this study, two ensemble approaches (SVR AdaBoost and SVR bagging) and one individual technique (support vector regression (SVR)) were used. Coefficient of determination (R2), statistical assessment, and k-fold cross validation were carried out to scrutinize the efficiency of each approach used. In addition, a sensitivity technique was used to assess the influence of parameters on the prediction results. It was discovered that all of the approaches used performed better in terms of forecasting the outcomes. The SVR AdaBoost method was the most precise, with R2 = 0.96, as opposed to SVR bagging and support vector regression, which had R2 values of 0.87 and 0.81, respectively. Furthermore, based on the lowered error values (MAE = 4.4 MPa, RMSE = 8 MPa), statistical and k-fold cross validation tests verified the optimum performance of SVR AdaBoost. The forecast performance of the SVR bagging models, on the other hand, was equally satisfactory. In order to predict the mechanical characteristics of other construction materials, these ensemble machine learning approaches can be applied.

Optimization-Based Economical Flexural Design of Singly Reinforced Concrete Beams: A Parametric Study.

In the past, many studies have been conducted on the optimization of reinforced concrete (RC) structures. These studies have demonstrated the effectiveness of different optimization techniques to obtain an economical design. However, the use of optimization techniques to an obtain economical design is not so practical due to the difficulty in applying most of the optimization techniques to achieve an optimal solution. The RC beam is one of the most common structural elements encountered by a practising design engineer. The current study is designed to highlight the potential of the Solver tool in MS Excel as an easy-to-use option for optimizing the design of simply supported RC beams. A user-friendly interface was developed in a spreadsheet in which beam design parameters from a typical design can be entered and an economical design can be obtained using the Evolutionary Algorithm available in the MS Excel Solver tool. To demonstrate the effectiveness of the developed optimization tool, three examples obtained from the literature have been optimized. The results showed that up to 24% economical solution can be obtained by keeping the same material strengths that were assumed in the original design. However, if material strength is also considered as a variable, up to 44% of the economical solution can be obtained. A parametric study was also conducted to investigate the effect of different design variables on the economical design of simply supported RC beams and to derive useful rules of thumb for their design and proportioning, with the objective of cost minimization. The results of the parametric study suggest that the grade of the reinforcing steel is one of the most influential factors that affect the cost of simply supported RC beams. Practicing engineers can use the trends derived from this research to further refine their optimal designs.

A Scientometric Review on Mapping Research Knowledge for 3D Printing Concrete.

The scientometric analysis is statistical scrutiny of books, papers, and other publications to assess the "output" of individuals/research teams, organizations, and nations, to identify national and worldwide networks, and to map the creation of new (multi-disciplinary) scientific and technological fields that would be beneficial for the new researchers in the particular field. A scientometric review of 3D printing concrete is carried out in this study to explore the different literature aspects. There are limitations in conventional and typical review studies regarding the capacity of such studies to link various elements of the literature accurately and comprehensively. Some major problematic phases in advanced level research are: co-occurrence, science mapping, and co-citation. The sources with maximum articles, the highly creative researchers/authors known for citations and publications, keywords co-occurrences, and actively involved domains in 3D printing concrete research are explored during the analysis. VOS viewer application analyses bibliometric datasets with 953 research publications were extracted from the Scopus database. The current study would benefit academics for joint venture development and sharing new strategies and ideas due to the graphical and statistical depiction of contributing regions/countries and researchers.