Gaming scenarios and virtual environments have shown beneficial results in Engineering Education. Various activities conducted in different fields demonstrate that students reveal appraisal for the integration of innovative technologies such as Virtual or Augmented Reality in the learning process. In this paper, Virtual Reality (VR) applications developed by first year students during an introductory class of the Integrated Masters in Civil Engineering are described. Additionally, two trials concerning the application of VR and Augmented Reality (AR) to Civil Engineering held at a local school (K-12 students) are also detailed. After the tests, students were surveyed and data was collected. Results and considerations are revealed in the final sections of this paper.

Salt damage can affect the service life of numerous building structures, both historical and contemporary, in a significant way. In this review, various damage mechanisms to porous building materials induced by salt action are analyzed. The importance of pretreatment investigations is discussed as well; in combination with the knowledge of salt and moisture transport mechanisms they can give useful indications regarding treatment options. The methods of salt damage treatment are assessed then, including both passive techniques based on environmental control, reduction of water transport, or conversion to less soluble salts and active procedures resulting in the removal of salts from deterioration zones. It is concluded that cellulose can still be considered as the favorite material presently used in desalination poultices but hydrophilic mineral wool can serve as its prospective alternative in future applications. Another important cause of building pathologies is the rising damp and, in this phenomenon, it is particularly severe considering the presence of salts in water. The treatment of rising damp in historic building walls is a very complex procedure and at Laboratory of Building Physics (LFC-FEUP) a wall base hygroregulated ventilation system was developed and patented.

The work presents the results of an experimental campaign carried out on concrete elements in order to investigate the potential of using artificial neural networks (ANNs) to estimate the compressive strength based on relevant parameters, such as the water–cement ratio, aggregate–cement ratio, age of testing, and percentage cement/metakaolin ratios (5% and 10%). We prepared 162 cylindrical concrete specimens with dimensions of 10 cm in diameter and 20 cm in height and 27 prismatic specimens with cross sections measuring 25 and 50 cm in length, with 9 different concrete mixture proportions. A longitudinal transducer with a frequency of 54 kHz was used to measure the ultrasonic velocities. An ANN model was developed, different ANN configurations were tested and compared to identify the best ANN model. Using this model, it was possible to assess the contribution of each input variable to the compressive strength of the tested concretes. The results indicate an excellent performance of the ANN model developed to predict compressive strength from the input parameters studied, with an average error less than 5%. Together, the water–cement ratio and the percentage of metakaolin were shown to be the most influential factors for the compressive strength value predicted by the developed ANN model.

Modular construction provides numerous benefits over traditional methods, especially when combined with digital technologies, offering a faster, safer, leaner, and more sustainable construction environment. This literature review follows the PRISMA method to assess recent advancements in digital-oriented modular construction towards a sustainable and climate-neutral built environment, identifying research trends and gaps based on three pillars: digital tools, building solutions, and environmental sustainability. This review examines the integration of digital technologies with modular construction methods, extending the analysis to circular and bioclimatic efforts, renewable energy sources, and passive building design strategies. While most articles focus on BIM uses, there is an increasing emphasis on IoT applications that leverage real-time data to achieve sustainability goals. However, no full-scale automated Digital Twin was found in this context. Additionally, Building Energy Modelling (BEM) and Life Cycle Assessment (LCA) tools are frequently discussed, reflecting the push for climate-friendly housing. Despite the interest in parametric and generative design, the integration of machine learning and artificial intelligence applications for sustainable modular construction strategies remains underexplored. Only a few papers acknowledged reaching nZEB requirements despite the great emphasis on passive building solutions and renewable energy sources that contribute to this goal. However, material circularity has yet to achieve its full potential for sustainable modular construction. Moreover, there is some interest in off-grid modular buildings, although further research should be undertaken to analyse the modular construction feasibility for sustainable off-grid communities. Furthermore, the findings highlight the potential of digitalisation in modular construction to enhance efficiency and ensure environmental sustainability within the Architecture, Engineering, and Construction (AEC) sector.