Building Information Modeling can help in predicting the energy efficiency in future based on dynamic patterns obtained by visualization of data. The aim of this study was to investigate the effective parameters of energy consumption using BIM technology which can evaluate the Buildings energy performance. First, three forms of general states in the Building were modeled to evaluate the proposed designs in Autodesk Revit Software. Then, the main Building form for energy Modeling and analysis was selected. Autodesk Revit 2020 software was also used to obtain the results of climate data analysis and Building energy consumption index. Finally, the most optimal mode was selected by examining different energy consumption modes. The results showed that the use of Building Information Modeling technology in adjusting the parameters affecting energy consumption can save energy cost up to 58. 23% in block D. Energy cost savings for block C and the western lobby were obtained as 51. 03% and 43. 05%, respectively. Based on energy use intensity, energy cost savings for blocks C, D, and the western lobby were estimated as 16. 67%, 16. 30%, and 11%, respectively. The results of parametric studies on alternative schemes of energy use intensity optimization showed that 16. 30% savings could be achieved by the base Building model in a 30-year time horizon. Therefore, it was concluded that optimization of energy consumption would reduce the environmental pollutants emission and contribute to preservation and sustainability of the environment.

Building envelopes and regional conditions can significantly contribute to the cost and energy performance of the Buildings. Structured methods that take into account the impacts of both the envelope materials and the regional conditions to find the most feasible envelope materials within a region, however, are still missing. This study responds to this need by proposing a novel method using the capabilities of Building Information Modeling (BIM). The proposed method is used for identifying cost- and energy-efficient Building envelope materials within a region over the life cycle. First, commonly used envelope materials in a region are identified. Then, BIM is employed for simulating the energy performance and evaluating the life cycle cost of the materials. The method was implemented in Tehran, Iran. It was successfully utilized for improving the cost and energy performance of a nine-story residential Building case. The achieved results indicated a potential energy performance enhancement of 31%, and the life cycle cost improvement of 28% by replacing conventionally used envelope materials with the available high-performance Building materials. The proposed method can benefit various stakeholders in the Building construction industry, including municipalities, owners, contractors, and consumers, by enhancing the cost and energy performance of the Buildings.

BACKGROUND AND OBJECTIVES: Decision-making in Building demolition is complex, involving structural, environmental, economic, and regulatory considerations. Traditional approaches often rely on subjective judgment and lack data-driven analysis. This study seeks to create a comprehensive decision-support framework that integrates Building Information Modeling and Bayesian Networks to optimize go or no-go decision processes. The objectives of the study were to provide a more accurate, reliable, and systematic tool that improves planning, reduces uncertainty, and promotes safety, efficiency, and sustainability in Building demolition practices.METHODS: This study integrates Building Information Modeling data with Bayesian Network probabilistic analysis to assess structural, environmental, and managerial factors influencing demolition decisions. A case study was conducted on a three-story market Building located in South Jakarta. Expert insights were utilized to create conditional probability tables, improving the model's precision and its applicability to actual demolition situations. The model was validated through simulation and sensitivity analysis, identifying key variables affecting go or no-go outcomes.FINDINGS: The integrated Building Information Modeling–Bayesian Network model effectively supports go or no-go demolition decisions by addressing uncertainty and risk factors probabilistically. According to the case study findings, there is a 55.10 percent chance of demolition, influenced by inadequate structural integrity (70 percent) and significant retrofit costs (59 percent). Mechanical demolition was preferred (56 percent) for its efficiency and lower risk. Sensitivity analysis identified structural integrity, retrofit cost, Building age, environmental impact, and permit status as key influencing variables. Validation by experts has established the model's practical importance, illustrating its potential to boost planning accuracy and encourage sustainable, data-centric decision-making in complex urban demolition endeavors.CONCLUSION: Integrating Building Information Modeling and Bayesian Network improves demolition decision-making by addressing uncertainty and supporting risk-informed analysis. The model boosts the precision of planning and aids in pinpointing significant influencing factors, like structural integrity and the costs associated with retrofitting. Furthermore, it fosters sustainable, data-driven approaches, rendering it an effective tool for complicated urban demolition initiatives.

BACKGROUND AND OBJECTIVES: The conventional disposal of demolition waste in landfills poses significant ecological harm. Integrating principles of the circular economy can help alleviate this impact by encouraging the reuse, recycling, and recovery of materials. This study presents a groundbreaking approach to demolition that aims to tackle the growing waste problem and bridge the existing regulatory loopholes. The framework leverages Building Information Modeling for Just-In-Time delivery and circular economy practices to prioritize environmentally friendly, efficient, and sustainable operations. The framework aims to transform demolition practices, reduce environmental impact, and promote sustainability within the construction sector by incorporating these principles.METHODS: The study outlines a plan for demolishing high-rise Buildings by incorporating Building Information Modeling, Just-In-Time delivery, and the circular economy in a specific case analysis. Autodesk Revit streamlines waste estimation and inventory of reusable, repairable, refurbished, and recyclable waste, thereby optimizing waste management planning with improved effectiveness and efficiency. Navisworks visualizes the demolition process in a reverse four-dimensional model. Microsoft Project ensures on-time delivery, while a Sankey diagram visually represents the concept of a circular economy.FINDINGS: Building Information Modeling, just-in-time delivery, and circular economy principles maximize demolition planning for efficiency, effectiveness, and sustainability. The green demolition framework serves as a valuable project management tool that enhances planning and resource allocation efficiency, all the while reducing environmental impact through the implementation of selective demolition and enhanced waste management practices.The process completed the demolition of a 6-story Building in 88 days, producing 160 cubic meters of reusable waste, eight cubic meters of repairable and refurbishable waste, and 3,972 cubic meters of recyclable wasteThe waste collection for the circular economy is efficiently carried out within a timeframe of 1-2 days, thanks to the implementation of the Just-In-Time delivery schedule.CONCLUSION: This study delves into advancements in waste management and strategic demolition scheduling. The government should consider the green demolition framework when refining regulations to include Information Communication Technologies and circular economy concepts. Future studies have the potential to improve the green demolition framework by prioritizing environmentally conscious strategies and ensuring effective coordination among all stakeholders involved to achieve the best possible outcomes in demolition projects.

Improving management of complex and congested facilities in hospital Buildings is a potential point for both reducing money spent and enhancing quality level of the medical services provided in public hospitals of Iran. Although Building Information Modeling (BIM) is identified as an effective tool for improving Facility Management (FM), use of advantages it offers to the FM processes of hospitals has been neglected thus far in the country. To address this issue, this research aims to investigate the BIM capabilities and the supporting organizational structure of public hospitals in Iran which can help improve their FM processes. A comprehensive literature review of applicable capabilities of BIM to the FM processes was conducted. Hierarchical FM structure of public hospitals in the country was recognized through a review of the related regulations. A public hospital case was chosen for in-depth recognition of FM process operations and validation of the proposed BIM-based improvements. It was argued that the use of BIM capabilities could substantially improve the FM processes of public hospitals. Reduced duration of FM activities, improved facility layouts, enhanced communication and coordination, facilitated training, and improved emergency management are some of the expected outcomes.