This review provides an intensive overview of flame retardant coating systems. The occurrence of flame due to thermal degradation of the polymer substrate as a result of overheating is one of the major concerns. Hence, coating is the best solution to this problem as it prevents the substrate from igniting the flame. In this review, the descriptions of several classifications of coating and their relation to thermal degradation and flammability were discussed. The details of flame retardants and flame retardant coatings in terms of principles, types, mechanisms, and properties were explained as well. This overview imparted the importance of intumescent flame retardant coatings in preventing the spread of flame via the formation of a multicellular charred layer. Thus, the intended intumescence can reduce the risk of flame from inherently flammable materials used to maintain a high standard of living.

The potassium (K) and sodium (Na) elements in banana are needed for hydration reaction that can enhance the strength properties of concrete. This research aims (a) to determine the material engineering properties of banana skin ash (BSA) and concrete containing BSA, (b) to measure the strength enhancement of concrete due to BSA, and (c) to identify optimal application of BSA as supplementary cement materials (SCM) in concrete. The BSA characterization were assessed through X-ray fluorescence (XRF) and Blaine’s air permeability. The workability, compressive strength, and microstructures of concrete containing BSA were analysed using slump test, universal testing machine (UTM) and scanning electron microscope (SEM). A total of 15 oxides and 19 non-oxides elements were identified in BSA with K (43.1%) the highest and Na was not detected. At 20 g of mass, the BSA had a higher bulk density (198.43 ± 0.00 cm³) than ordinary Portland cement (OPC) (36.32 ± 0.00 cm³) indicating availability of large surface area for water absorption. The concrete workability was reduced with the presence of BSA (0% BSA: > 100 mm, 1% BSA: 19 ± 1.0 mm, 2%: 15 ± 0.0 mm, 3% BSA: 10 ± 0.0 mm). The compressive strength increased with the number of curing days. The concrete microstructures were improved; interfacial transition zones (ITZ) decreased with an increase of BSA. The optimal percentage of BSA obtained was at 1.25%. The established model showed significant model terms (Sum of Squares = 260.60, F value = 69.84) with probability of 0.01% for the F-value to occur due to noise. The established model is useful for application in construction industries.

This study present of fly ash generation at generated one the power plant in Malaysia. The main purpose of this research to predict the generation of fly ash in future years by a method. This prediction is important so that fly ash generated could be used in a beneficial way. Prediction of fly ash was done by using two types of software which are Neural Network Toolbox, MATLAB and IBM SPSS Statistics 23, Linear Regression. Among these two methods, IBM SPSS Statistics 23, Linear Regression is found to be the most effective way to predict the generation of fly ash in the future by using five year’s best fit linear regression equation compared to Neural Network Toolbox, MATLAB.

Fly ash is a by-product of coal combustion. Coal ash is a waste that produces a large amount of fly ash generated at the Coal Fired Power Plant throughout the year. Continuous ash production consequents in expansion of ash dumps. Coal ash also poses significant health threats. Cenosphere is one of the value-added materials that is found in coal fly ash. This study is to determine the characteristic of cenosphere in terms of chemical composition, particle size distribution, amorphousness, and surface morphology. In order to extract the cenosphere from the fly ash sample, the separation method used is the Wet Separator method (Floatation/Float and Sink Method). Cenospheres have good potential as sustainable material due it’s the unique properties, where it can be used as an alternative material in many industrial applications. A better understanding of the cenosphere characteristic will have important implication for coal waste application and it will improve the development of sustainable materials application in industry.

The interest in the use of mathematical models for the simulation of hydrological processes has largely increased especially in the prediction of runoff. It is the subject of extreme research among engineers and hydrologists. This study attempts to develop a simple conceptual model that reflects the features of the arid environment where the availability of hydrological data is scarce. The model simulates an hourly streamflow hydrograph and the peak flow rate for any given storm. Hourly rainfall, potential evapotranspiration, and streamflow record are the significant input prerequisites for this model. The proposed model applied two (2) different hydrologic routing techniques: the time area curve method (wetted area of the catchment) and the Muskingum method (catchment main channel). The model was calibrated and analyzed based on the data collected from arid catchment in the center of Jordan. The model performance was evaluated via goodness of fit. The simulation of the proposed model fits both (a) observed and simulated streamflow and (b) observed and simulated peak flow rate. The model has the potential to be used for peak discharges’ prediction during a storm period. The modeling approach described in this study has to be tested in additional catchments with appropriate data length in order to attain reliable model parameters.