Diagnostic load testing refers to the use of the measured historical responses of the structure in the field data to better understand its dynamic and static structural behaviours. It is important and necessary to predict the health state, load capacity, and aging of the structure by updating the finite element (FE) model, which can give useful information to aid the design of retrofits and the maintenance of the existing bridge in the future. The paper presents an update of the full-scale FE model for the reinforced concrete (RC) bridge structure over the seawater river based on the experimental strains under the static load testing in which the representative FE model of the actual structure is determined from the optimisation procedures. The optimisation variables are applied, including the cross-sectional properties and concrete material calibrated through the genetic algorithm (GA) optimisation in the MATLAB software, which interfaces with the FE modelling in the scripting of the SOFISTIK TEDDY software automatically. The bending moments at the mid-span of the RC girders are determined in the FE modelling to compute stresses, which are compared with the measured stresses through optimisation scenarios with a percentage error of the objective function less than 10%. The measured data of concrete strains are recorded from reusable strain transducers installed on the mid-span girders for every bridge span, which are used to calibrate the bridge model in static load testing. The novelty of the solution is to implement innovative techniques using field data as an improved approach for calibrating automatically the analytical FE model parameters of all RC spans of the bridge until its static behaviours are very similar to those of the actual bridge. The final updated FE modelling is used to apply truck load configurations according to bridge design standards such as the AASHTO specifications, which can predict the load limits of the existing bridge structure more accurately and reliably. These proposed approaches can be applied to large bridges as well as complex structures with supporting FE analysis software and data processing software.

This article presents the research on the mechanical characteristics of concrete in the construction of three concrete bridges. A system of recording the internal temperature of concrete and automatic control of laboratory ovens was used for specimen curing. This allowed the specimens to be cured under conditions similar to those occurring in the structure. Before the construction, reference blocks were used to define similar curing conditions. Maximum setting temperatures ranged from 47.6 °C to 62.0 °C and had a favorable effect on the properties of the concrete at an early age. For concretes with the use of CEM I cement, after 3 days of curing, the strength obtained was up to 8.2 MPa (23%) higher than that for specimens cured under standard conditions. The modulus of elasticity was higher up to 4.9 GPa (21%). For concrete with the use of CEM III cement, these differences were 26.9 MPa (174%) and 10.3 GPa (64%), respectively. After 7 days of curing, the results were close to each other and after 14, 28, and 56 days, higher values were obtained for specimens cured under standard conditions. The value of the modulus of elasticity of concrete was determined using the direct method according to Eurocode and the standard A method. A test load of the bridge was carried out to verify the modulus values obtained from laboratory tests. The highest consistency (99%) between the theoretical deflections and those measured in the test load was achieved when using the stabilized modulus values obtained on specimens cured under structure conditions in the FEM model. The research confirms the necessity of determining the mechanical characteristics of concrete with taking into account the curing conditions of concrete in the structure. A procedure for determining the mechanical properties of concrete for the correct construction of a bridge is proposed. These results can also be used in the development of a digital twin for bridge management.

As Building Information Modeling (BIM) models are getting bigger, with more information linked to geometrical 3D models, a dedicated BIM search engine is important. A BIM search engine was developed to examine the value of exploiting a 3D object’s topological relationships to other 3D objects when assessing that object’s relevance to a query. The impacts of two information standards, the Industry Foundation Classes (IFC) and Uniclass-2015, on information retrieval (IR) performance were also measured. The 3DIR Autodesk Revit toolset was used on a structural model of a 16-story building from an industry partner. The retrieval performance measures of Precision and Recall did not clearly highlight the benefit, although the increased relevance values of those objects deemed by experts to be relevant demonstrates the promise of such contextual measures. The effect of shifting from the native Revit file format to various standards was tested: IR performance was poor with the Uniclass-2015 dataset and was comparable to the Revit native model with the IFC model. Although not shown conclusively to improve retrieval performance, the contextual relevance measures presented in this paper are promising and constitute a significant original contribution. Future research is needed to fine-tune these measures and fully realize their potential.

Over the past few years there has been a significant change in fire safety design and management. As the possibility of safe escape is the most crucial aspect of a building’s fire safety features, the understanding of human behaviour under fire conditions is important for a successful evacuation. Previous research studies have developed models, prototypes, and serious games that help engineers/architects to design or firefighters to improve design so that the building facilitates a smooth evacuation process. Although these studies have looked into human behaviour, perceptions of important stakeholders (such as occupants, structural engineers, fire engineers, facility managers) are still not understood. These perceptions are important for the appropriate application of technology for evacuation. The broader research effort, of which this paper is part, stems from the premise that bespoke evacuation instructions can be sent directly to evacuees’ smartphones. Information from a BIM model with the aid of sensors can be used to customise these evacuation instructions. The prospect of information being delivered to occupants during a fire emergency is still at its premature phase and more research is needed. Twenty-three interviews were conducted with occupants who currently live in high-rise residential buildings in Egypt and the United Kingdom to understand their views of using smartphones to assist during fire evacuations. The sampling strategy targeted occupants who currently live in high-rise residential buildings but have not necessarily experienced a fire evacuation. The research clearly shows the importance of smartphones during evacuation and the role they can play in assisting occupants to find the fastest and safest egress route. The interview findings will assist in future research to develop an evacuation framework system that could be implemented for high-rise residential buildings.

Over the past decade, there has been a growing recognition of the importance of indoor environmental quality (IEQ) in influencing occupant productivity. Researchers have studied various buildings, including offices, schools, hospitals, and residential settings, to understand the relationship between IEQ and productivity outcomes. Studies have taken a multifactorial approach, considering multiple aspects of IEQ. Evidence from the literature review suggests that the quality of the indoor environment is an essential factor that affects the productivity of building occupants, and it is one of the fundamental issues in the development of societies. This area of research requires the responsible participation of researchers at all levels, as there is significant scope to contribute to knowledge. Therefore, this study aims to conduct a bibliometric analysis of the published literature on indoor environmental quality and its impact on building occupant productivity through the scientific literature available from one of the largest and most famous academic databases, Scopus; the study was determined in 2011 to 2023. The search used differential thresholds for IEQ keywords affecting building occupant productivity. Three discrete queries were performed, resulting in approximately 3861 publications. These were filtered by reducing false positives and excluding publications irrelevant to the research topic. The final results were 72 publications. This study also used Excel and VOS viewer to analyse and create graphs and network visualisation maps to show the growth of publications and their types, active countries and institutions for recovered publications, international collaboration, author keywords, active journals, and citation analysis. This study can significantly advance our understanding of building occupant productivity and enhance quality of life and work. Evaluating the research outputs is essential for highlighting contributions to knowledge and global collaboration in this research area. The potential impact of this study is not just theoretical. It can shape the future of our built environments and the lives of those occupying them.