Heritage buildings are significant historical and architecture added value, which requires deep and precise preliminary brainstorming when considering upgrading or retrofitting these valuable buildings. In this study, we opted to highlight some passive design architecture interventions to improve the thermal comfort and the required cooling energy for buildings. The Murabba Palace in Riyadh was selected as a case study. DesignBuilder software was used to evaluate the energy performance of ten passive architectural design alternatives throughout different seasons in an attempt to improve the energy performance and thermal comfort of heritage buildings. The ten passive design scenarios encompassed double low-E glass, double reflected glass, double low-E glass and double wall with an air gap, double low-E glass and double wall with thermal insulation, double low-E glass and double wall with lightweight thermal insulation, double low-E glass and double wall with sprayed foam insulation, double reflected glass and double wall with an air gap, double reflected glass and double wall with thermal insulation, double reflected glass and double wall with lightweight thermal insulation, and double reflected glass and double wall with sprayed foam insulation. The results show that using double low-E glass and applying a double wall with polystyrene thermal insulation can enhance the thermal comfort inside the building and reduce the energy performance and CO₂ emissions to 17% and 9%, respectively.

This study addresses the vital issue of the variability associated with modeling decisions in dam seismic analysis. Traditionally, structural modeling and simulations employ a progressive approach, where more complex models are gradually incorporated. For example, if previous levels indicate insufficient seismic safety margins, a more advanced analysis is then undertaken. Recognizing the constraints and evaluating the influence of various methods is essential for improving the comprehension and effectiveness of dam safety assessments. To this end, an extensive parametric study is carried out to evaluate the seismic response variability of the Koyna and Pine Flat dams using various solution approaches and model complexities. Numerical simulations are conducted in a 2D framework across three software programs, encompassing different dam system configurations. Additional complexity is introduced by simulating reservoir dynamics with Westergaard-added mass or acoustic elements. Linear and nonlinear analyses are performed, incorporating pertinent material properties, employing the concrete damage plasticity model in the latter. Modal parameters and crest displacement time histories are used to highlight variability among the selected solution procedures and model complexities. Finally, recommendations are made regarding the adequacy and robustness of each method, specifying the scenarios in which they are most effectively applied.

The growing adoption of Building Information Modeling (BIM) within the architectural, engineering, and construction (AEC) sector raises questions about the quality of BIM data deliverables for project owners. Therefore, assessment and evaluation of such BIM data against relevant documents such as the BIM Execution Plan (BEP), the Level of Definition (LOD)/Level of Information (LOI) matrix, and quality control customized checklists become critical, especially in large construction projects. This study primarily aims to create an automated system for assessing the quality of 3D BIM model data, utilizing a proposed project quality control checklist. The automated system consists of four key elements: a BIM-based model, a Data Extraction and Analysis Module, a Data Storage Module, and a Data Visualization Module. The Data Extraction and Analysis Module extracts relevant information and parameters from BIM models to evaluate their quality against predefined checklists. Then, it transfers the information and stores the results in a database. The database is connected to an engineering project collaboration tool, ProjectWise, to automatically update and store the data in the cloud. The database is then connected to an interactive data visualization platform, Power BI, to enable automatic visualization of the generated quality assessment results of the BIM models’ data. This system was applied to a Canadian infrastructure construction project by its BIM department during the preliminary and detailed design phases. It demonstrated an average quality score (AQS) of 87.6% for the BIM models and significantly reduced failing items by around 30%. This study concludes that the system offers a robust, practical solution for enhancing the quality control process in BIM model data management, thereby aiding engineers in timely model adjustments to meet project requirements.

After the sustainability of heritage buildings (HBs) has been evaluated and it is determined that rehabilitation is needed, then the life-cycle cost (LCC) of energy for HBs can be analyzed. The objective of this research was to evaluate the LCC of energy for HBs and develop a comprehensive life-cycle model that will aid in expenditure planning and budget allocation. This study was validated through the weighted sums method and two case studies—Murabba Palace (MP), Saudi Arabia; and Grey Nuns Building (GN), Canada—were evaluated. For any HB, the project life cycle includes planning, manufacturing, transportation, construction, operation, and maintenance phases. Saudi Arabian and Canadian experts completed questionnaires to attribute a percentage of importance of each of the aforementioned phases with respect to energy consumption. The findings from this study will enable facility managers to make effective rehabilitation decisions. The operation phase has the highest impact on the energy consumption, gas consumption, and cost of the building in both case studies. Moreover, the findings from this study can be used to establish cost-effective intervention strategies. Their responses were employed in the development of a life-cycle model. Excel^® and Minitab^® were used to calculate Cronbach’s alpha values for data reliability, and the project LCC of energy for the two case studies was studied. The operation phase appeared to be the most energy-consuming phase in both case studies, contributing the most to the cost of the building.