Ana Evangelista’s research while affiliated with Engineering Institute of Technology and other places

The Building Condition Index (BCI) is a widely adopted quantitative metric for assessing various aspects of a building’s condition, as it facilitates decision-making regarding maintenance, capital improvements and, most importantly, the identification of investment risk. In practice, longitudinal BCI scores are typically used to identify maintenance liabilities and trends and proactively provide indications when maintenance strategies need to be altered. This allows for a more efficient resource allocation and helps maximise the lifespan and functionality of buildings and their assets. Given the historical ambiguity concerns because of the reliance on visual inspections, this research investigates how AI and using ANN, DNN and CNN can improve the predictive accuracy of determining a recognisable Building Condition Index. It demonstrates how ANN and DNN perform over asset classes (apartment complexes, education and commercial buildings). The results suggest that DNN architecture is adept at dealing with diverse and complex datasets, thus enabling a more versatile BCI prediction model over various building categories. It is envisaged that with the expansion and maturity of ANN, DNN and CNN, the BCI calculation methodologies will become more sophisticated, automated and integrated with traditional assessment approaches.

BCA methodically assesses the state of a building’s deterioration to support Maintenance, Safety, Function, and Compliance purposes. Originally used to assist in identifying urgent repair requirements, it has evolved and become one of the most used tools for assessing a building’s outstanding maintenance liability when a building is transacted or acquired. Nevertheless, current practices involve several conflicts; for example, high costs are associated with inspections, inconsistent building component registers, and ambiguity and consistency regarding reporting parameters, all of which lead to compounding errors that reduce reliability. To address these gaps, the current research, involving one hundred and eighteen (118) active facilities managers and asset inspectors, suggests the development of an extension of the deterioration scale (0–7) and methodologies to reduce errors and ambiguity. Furthermore, it suggests using weighted indices to focus on crucial building components, thus improving condition assessment. As was found, these tools improve the accuracy of BCA, facilitate better management of the asset’s life cycle, and provide support in decision-making. This study adds consistency, limits subjectivity, and provides a framework applicable to different building types, assisting future management for sustainability. It, therefore, stands to serve the field by providing detailed and concise best practices for conducting condition audits on built assets.

This paper explores different building maintenance strategies in commercial buildings in Sydney, Australia, focusing on corrective maintenance (CM) and preventive maintenance (PM). While CM involves rectifying issues after they occur, PM aims to enhance productivity by anticipating potential issues. Although PM seems more logical, the decision to implement this type of maintenance strategy are typically made based on item reliability, failure frequency, and downtime cost, commonly found in manufacturing facilities or critical environments. However, as found in the selected/surveyed commercial real estate buildings, CM was more frequently adopted in aged facilities with older infrastructure, and PM was favoured for buildings without structural deficiencies; however, operating equipment failures were common. However, in many cases, decision makers did not consider the broader effects of downtime beyond direct financial losses, costs associated with customer satisfaction, worker efficiency, rent abatements, and reputation damage. While each building is unique and may require a bespoke maintenance schedule, this study’s insights may help managers select the most appropriate maintenance strategy. Nonetheless, further research is needed to investigate the role of innovative technologies (such as machine learning and artificial intelligence) in enhancing maintenance efficacy and explore the influences of economic shifts, corporate and financial objectives, and the availability of technical resources.

During devastating earthquakes, soil liquefaction has disastrous outcomes on bridge foundations, as mentioned in books and published research. To avoid foundation failure when the surrounding soil is fully liquefied, a bridge’s pile foundation design could be such that the bridge pier is directly resting on the top of a large-diameter monopile instead of the traditional multiple small-diameter piles. This paper discusses the gap of insufficient studies on large-diameter monopiles to support railway bridges subjected to buckling instability and the lack of simplified tools to quickly assess structural reliability. A framework could quickly assess the structural reliability by formulating a simplified reliability analysis. This study focused on pure buckling with shear deformation and reliability assessment to calculate a monopile’s failure probability in fully liquefied soils. In reliability assessment, with the critical pile length (Lcrit) and the unsupported pile length (Luns), the limit state function g(x) = [Lcrit − Luns] thus forms the basis for assessing the safety and reliability of a structure, indicating the state of success or failure. The Lcrit formulation is accomplished with a differential equation. Here, Luns assumes various depths of liquefied soil. The reliability index’s (β) formulation is achieved through the Hasofer–Lind concept and then double-checked through a normal or Gaussian distribution. A case study was conducted using a high-speed railway bridge model from a published research to demonstrate the application of the proposed methodology. To validate the minimum pile diameter for buckling instability when a fully liquefied soil’s thickness reaches the condition that Lcrit = Luns, this study applies the published research of Bhattacharya and Tokimatsu. The validation results show good agreement for 0.85–0.90 m monopile diameters. With a monopile diameter smaller than 0.85 m, the Lcrit = Luns limit was at lesser depths, while with a monopile diameter larger than 0.90 m, the Lcrit = Luns limit was at deeper depths. A load increase notably affected the large-diameter monopiles because the Lcrit movement required a longer range. In fully liquefied soil, buckling will likely happen in piles with a diameter between 0.50 m and 1.60 m because the calculated probability of failure (Pf) value is nearly one. Conversely, buckling instability will likely not happen in monopiles with a diameter of 1.80–2.20 m because the Pf value is zero. Hence, the outcome of this case study suggests that the reliable monopile minimum diameter is 1.80 m for supporting a high-speed railway bridge. Lastly, this paper analyzed the shear deformation effect on large-diameter monopiles, the result of which was 0.30% of Lcrit. Shear deformation makes minimal contributions to large-diameter monopile buckling.

Structural design plays a very important role in reducing environmental impacts by reusing resources, recycling materials, and minimizing waste and pollution in the construction sector. Sustainable design becomes more effective than traditional solutions in achieving the transition to sustainability. The decision-making process is not simple due to the different preferences of clients, architects, and engineers. This paper aims to develop a decision framework for assessing sustainability in the early structural design stage. Multi-criteria decision-aiding (MCDA) methods have been implemented to improve the selection of regulations. A technical ranking approach, the Fuzzy Analytic Hierarchy Process (FAHP) method, has been employed to identify the optimal solution. Three alternatives including an innovative and two traditional structural systems have been selected and compared in terms of three criteria—economic, social, and environmental impacts. Nine sub-criteria for ranking the importance level of sustainable design have been determined through a literature review and professional experts. FAHP methods show that the economic impact (58%) is the most important criterion for assessing the sustainability of structural systems, followed by the environment with 31%. The social aspect contributes 11% to this method, and it is ranked as the least important criterion. This research revealed that MCDA methods can be used as a guideline for engineers to improve the selection in the process of sustainable design. The decision model proposed in this study has been verified and, therefore, can be applied for similar projects.

Introduction This study examines the complex link between regular maintenance procedures and the effectiveness of business-related assets in Australia. Commercial buildings are essential to the country’s economy, and the variables affecting their worth must be carefully analysed. Methods This study evaluates the relationship between asset value and maintenance frequency, examines how maintenance practices affect building performance, and considers industry perspectives on improperly versus correctly maintained assets. Results The study’s findings highlight the significance of renovations, along with adaptive reuse, in raising asset value; however, despite various maintenance techniques available, the Australian commercial building industry has challenges. Budgetary constraints, for instance, pose a significant hurdle, with many companies struggling to allocate sufficient funds for comprehensive maintenance plans. The findings of this research highlight the positive shift towards technology-driven maintenance procedures in business establishments in Australia. The adoption of computerised Maintenance Management Systems (CMMS) and Building Management Systems (BMS) is rising, automating repetitive tasks, improving maintenance procedures, and enabling data-driven decisions. Discussion This study thoroughly explains the complex processes influencing the value and usefulness of commercial architecture resources in the Australian setting by addressing the differing perspectives within the real estate industry. Future research on this topic should focus on recognising the psychological components of decision-making concerning maintenance practices. Investigating how psychological prejudices, perceptions of danger, and organisational culture affect the choices made by property owners, facility administration, and others can help us better understand why some maintenance methods are preferred over others.