Neural network mapping in the simplified design of mix proportions using coal bottom ash waste in concrete hollow blocks

• Main Authors: Gallardo, Ronaldo S., Ongpeng, Jason Maximino C., Otsuki, Nobuaki
• Format: text
• Published: Animo Repository 2008
• Subjects: Waste products as building materials; Coal ash; Hollow bricks; Civil Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/8873
• Institution: De La Salle University

In the operation of coal-fired power plants in the Philippines, the pulverized coal which is used as a source of energy and depending on its coal burning furnace, tends to produce approximately 80% of Coal Fly Ash and 20% of Coal Bottom Ash. Researches and studies have shown that Coal Bottom Ash can be used as a road base subbase aggregate, structural fill material (ASTM E1861-97), and as fine aggregates in asphalt paving and flowable fill. From recent studies done by Gallardo et. al. in De La Salle University-Manila, Coal Bottom Ash was used as partial substitute to sand for building materials like Concrete Hollow Blocks complying to the Philippine National Standards. The casting and testing of 429 specimens of four-inch-thick hollow blocks and variable mix proportions were considered in the research. However, with the data produced, design of simplified mix proportions was not yet done and still to be modeled. Using neural network self-organizing map to classify organized data sets, a simplified approach to mix proportions was made to meet the mechanical properties needed to comply with the Philippine National Standards in Concrete Hollow Blocks.