Assessing and Monitoring of Building Performance by Diverse Methods

Application of aluminum oxide nanoparticles in asphalt cement toward non-polluted green environment using linear regression

In order to decrease the greenhouse gas emissions generated by regular Portland cement (OPC), additional cementitious ingredients have been frequently employed, even while building road bases. OPC's susceptibility to moisture and lack of flexibility make it ineffective for stabilizing road bases. This research used alkali-activated materials (AAM) with fly ash to investigate the mechanical properties of cold asphalt binder (freeze-thaw cycles) including the compressive, flexural strength, workability and porosity of cement. Dry specimens and specimens in distilled water have both been used in the experiments to study these temperature correlations. One sample was tested at 20 °C, and the other was frozen and thawed five times at a temperature of -5 °C (cold region environment). The resulting mixtures' morphologies and microstructures were analyzed via SEM images. During the 7 to 28-day curing period, the mixture's growth ratio rose. The combination registered both the greatest and lowest robust elastic modulus. The total compressive strength of the material decreased as the water-to-cement ratio increased due to the greater amount of free water accessible with a higher cationic asphalt emulsion (CAE) content. The moderate loss of flexural strength with increasing CAE concentration after 7 and 28 days of curing was seen. There is not a major impact on flexural strength in the materials by looking at the very modest gaps in flexural strength between 7 and 28 days curing periods. Due to the particle shape and size of this precursor, FA's inclusion allowed for a lower water to binder rate while maintaining a similar level of workability. The porosity and water absorption values rose with FA substitutions. Further studies might clarify the lower flexural strength observed in this study by adding other hybrids plus fly ash such as lime or nanoparticles.

Evaluation of waste management and energy saving for sustainable green building through analytic hierarchy process and artificial neural network model

A significant portion of the solid waste filling landfills worldwide is debris from construction and demolition projects. Across the world, a significant portion of the solid waste filling landfills is made up of construction and demolition waste. Recycling construction waste may help cut down on the quantity of waste sent to landfills and the requirement for energy and other natural resources. To help with construction waste reduction, a management hierarchy that begins with rethink, reduce, redesign, refurbish, reuse, incineration, composting, recycle, and eventually disposal is likely to be effective. The objective of this research is to investigate the viability of the Analytic Hierarchy Process (AHP) as a data gathering instrument for the development of a solid waste management assessment tool, followed by an examination of an artificial neural network (ANN). Using a standardized questionnaire, all data was gathered from waste management practitioners in three industry sectors. The survey data was subsequently analyzed using ANN and later AHP. The suggested framework consisted of four components: (1) the development of different level structures for fluffy AHP, (2) the calculation of weights, (3) the collection of data, and (4) the making of decisions. An ANN feedforward with error back propagation (EBP) learning computation is coupled to identify the association between the items and the store execution. It was found that the combination of AHP and ANN has emerged as a key decision support tool for landfilling, incineration, and composting waste management strategies, taking into account the environmental profile and economic and social characteristics of each choice. Composting has the highest sustainable performance when a balanced weight distribution of criteria is assumed, especially if the environmental component is considered in comparison to the other criteria. However, if social and economic features are addressed, incineration or landfilling have more favorable characteristics, respectively.