Prefabricated schools are educational structures of great significance and utility, especially given our country's current challenges. They expedite construction, reduce environmental impacts, and enhance educational activities with strong structural integrity and comfortable, flexible, and healthy design. A compelling comparison can be made with traditional concrete schools. With advancements in technology and information in engineering and the construction industry, Building Information Modeling (BIM) technology has emerged, playing a vital role in prefabricated concrete engineering through 3D modeling simulations.Numerous challenges are encountered, such as meeting client requirements, project delays, cost overruns, quality issues, stakeholder conflicts, labor shortages, safety concerns, increased change orders, material wastage, and project complexity. Developed countries utilize BIM to mitigate these challenges and profoundly improve the AEC industry's performance. BIM tools provide a comprehensive building visualization, empowering stakeholders to make informed decisions that ensure efficiency, sustainability, and cost savings. These features motivate engineers and contractors to rely on them as essential engineering applications.This research involves modeling a school building in the Revit program, studying work flow between Revit and ETABS program, and conducting a dynamic analysis of the model from Revit. It also emphasizes the benefits of prefabricated construction and BIM technology, facilitated by Revit. The study emphasizes how important it is to visualize the building's actual form before beginning the design and decision-making processes.in summery, this study provides the possibility of growth and application in the industrialization of the construction industry and raise the project's overall quality. The development of tools and plugins programmed to reduce interoperability problems between various software packages allows for integrating all design activities.
Due to the expansion of industrial operations globally in recent years, waste output has risen. So these wastes must be reduced by recycling and reusing to achieve environmentally friendly buildings and find various alternative materials in critical cases. The statistical indicators are used as practical study including Multiple linear regression (MLR) and artificial neural network (ANN) models. The study's goals were to assess the effectiveness of granite waste (GW) as a replacement for cement, sand, plastic, and binder in specific building applications and the relationships between MLR and ANN approaches. Results show the efficiency of adding granite waste to some construction stages and replacing it with cement in the mixture and examining its strength, it gave excellent results in addition to good results for its use as a binder in cement mortar, while the results were weak when used as a substitute for sand and plastic in insulator because it's classified as fine sand, Therefore, it cannot be used as a substitute for sand in the construction. The statistical models give an effective indicator to use GW as an alternative material ( binder and cement) based on the coefficient of correlation (R2) for the two models MLR and ANN equal to 83.4 % and 80 % respectively.