An environmental sustainability roadmap for partially substituting agricultural waste for sand in cement blocks

Agricultural waste can be used in cement block production for a number of reasons, including its environmental, economic, and labor benefits. This study examines the mechanical, durability, and cost-effectiveness characteristics of cement blocks. A cement block made from agriculture waste promotes sustainable construction practices, since waste agriculture is often dumped in landfills and regarded as a waste material. Carbon dioxide (CO2) emissions produced by the construction sector, either from the firing of clay bricks or from the production of cement, contribute significantly to global warming. In many developing countries, air pollution from agricultural activities is primarily accounted for the emissions from agricultural machinery and openly burning agro-waste. Farming is one of the leading causes of water and soil pollution. Hence, adopting agricultural waste into cement production would significantly reduce the environmental impact of concrete structures. The goal of this research is to determine whether agricultural waste products, such as vermiculite, pistachio shells, sugarcane bagasse, and coconut husks, can be used to substitute sand in concrete blocks. The water absorption capacity of waste materials, density, flexural strength, fire resistance, and compressive strength of waste materials as admixtures in concrete were evaluated using experimental tests. In most cases, the concrete blocks made from agricultural waste were strong enough to satisfy ASTM standards. The specimens containing coconut husks and pistachio shells, among others, were found to be fairly strong and durable, even when isolating them from water

An environmental sustainability roadmap for partially substituting agricultural waste for sand in cement blocks

Agricultural waste can be used in cement block production for a number of reasons, including its environmental, economic, and labor benefits. This study examines the mechanical, durability, and cost-effectiveness characteristics of cement blocks. A cement block made from agriculture waste promotes sustainable construction practices, since waste agriculture is often dumped in landfills and regarded as a waste material. Carbon dioxide (CO2) emissions produced by the construction sector, either from the firing of clay bricks or from the production of cement, contribute significantly to global warming. In many developing countries, air pollution from agricultural activities is primarily accounted for the emissions from agricultural machinery and openly burning agro-waste. Farming is one of the leading causes of water and soil pollution. Hence, adopting agricultural waste into cement production would significantly reduce the environmental impact of concrete structures. The goal of this research is to determine whether agricultural waste products, such as vermiculite, pistachio shells, sugarcane bagasse, and coconut husks, can be used to substitute sand in concrete blocks. The water absorption capacity of waste materials, density, flexural strength, fire resistance, and compressive strength of waste materials as admixtures in concrete were evaluated using experimental tests. In most cases, the concrete blocks made from agricultural waste were strong enough to satisfy ASTM standards. The specimens containing coconut husks and pistachio shells, among others, were found to be fairly strong and durable, even when isolating them from water

Application of Artificial Neural Network (ANN) for Prediction and Optimization of Blast-Induced Impacts

Drilling and blasting remain the preferred technique used for rock mass breaking in mining and construction projects compared to other methods from an economic and productivity point of view. However, rock mass breaking utilizes only a maximum of 30% of the blast explosive energy, and around 70% is lost as waste, thus creating negative impacts on the safety and surrounding environment. Blast-induced impact prediction has become very demonstrated in recent research as a recommended solution to optimize blasting operation, increase efficiency, and mitigate safety and environmental concerns. Artificial neural networks (ANN) were recently introduced as a computing approach to design the computational model of blast-induced fragmentation and other impacts with proven superior capability. This paper highlights and discusses the research articles conducted and published in this field among the literature. The prediction models of rock fragmentation and some blast-induced effects, including flyrock, ground vibration, and back-break, were detailed investigated in this review. The literature showed that applying the artificial neural network for blast events prediction is a practical way to achieve optimized blasting operation with reduced undesirable effects. At the same time, the examined papers indicate a lack of articles focused on blast-induced fragmentation prediction using the ANN technique despite its significant importance in the overall economy of whole mining operations. As well, the investigation revealed some lack of research that predicted more than one blast-induced impact