A generalised component-based model for semi-rigid beam-to-column connections including axial force versus bending moment interaction is presented. The detailed formulation of the proposed analytical model is fully described in this paper, as well as all the analytical expressions used to evaluate the model properties. Detailed examples demonstrate how to use this model to predict moment–rotation curves for any axial force level. Numerical results, validated against experimental data, form the basis of a tri-linear approach to characterise the force–displacement relationship of the joint components. The relationship of the present development to key prior studies of this topic is also explained.

Compared with other industries, construction has maintained one of the lowest growth rates in productivity and innovation over the last decades. Moreover, low compliance with schedule targets has remained a common issue throughout projects. Therefore, although methodologies developed have benefited productivity in design, construction and operation, meeting client and project objectives becomes challenging without properly integrating organization, information, systems and processes. This perspective introduces the Virtual Design and Construction (VDC) framework. First, this paper studies and reviews VDC since its creation at the Center for Integrated Facility Engineering (CIFE) of Stanford University in 2001. After that, a comprehensive bibliographical review of the VDC framework is presented and updated with examples of its application in construction projects, delving into its elements: Client Objectives, Project Objectives, Production Objectives, Controllable Factors, Integrated Concurrent Engineering (ICE), Building Information Modeling (BIM) and Project Production Management (PPM). Finally, the main benefits and project outcomes when applying the VDC framework are presented and discussed, followed by the conclusions and recommendations for future research.

Compressive strength and elasticity modulus are the main mechanical properties of concrete. The non-destructive ultrasound pulse test can be used to determine these properties without compromising the structure’s integrity. This study seeks to assess whether a correlation exists (1) between the Reinforcement Index (RI) and the mechanical properties, (2) between the RI and the dynamic properties, and (3) among the dynamic properties of polypropylene fiber-reinforced concrete. The RI was modified through fiber volume fraction (0, 0.4, 0.8 and 1.2%) and fiber length (40, 50 and 60 mm). The dynamic properties were assessed through dynamic elasticity modulus and ultrasonic pulse velocity (UPV), which were determined by direct, semi-direct, and indirect prospect methods. Finally, compressive strength, static elasticity modulus, and Poisson’s ratio were assessed through destructive tests. Their relationship with UPV and the dynamic elasticity modulus is also subsequently studied. The results reveal a correlation between RI and compressive strength and UPV; however, the static elasticity modulus only exhibits a correlation with UPV in one of its measurement methods. Finally, empirical models were developed for predicting compressive strength, elasticity modulus as a function of ultrasonic pulse velocity and RI, and dynamic elasticity modulus as a function of compressive strength and RI.

Dropout has always been a concerning issue within higher education. This research explores the relationship between mental health-related problems and undergraduate students’ dropout rates amid the COVID-19 pandemic and within a civil engineering program. The study is quantitative descriptive, with a non-experimental and longitudinal design. Results show that the dropout rates of civil engineering students from a private university have increased, comparing before and after the COVID-19 pandemic, primarily due to mental health-related problems. Three strong tendencies within these rates have been detected, directly related to the COVID-19 pandemic. It was concluded that undergraduate students’ mental health had been undermined due to the pandemics, which has had an immediate impact on the increase of dropout rates.

The use of UAV (unmanned aerial vehicle) platforms and photogrammetry in bathymetric surveys has been established as a technological advancement that allows these activities to be conducted safely, more affordably, and at higher accuracy levels. This study evaluates the error levels obtained in photogrammetric UAV flights, with measurements obtained in surveys carried out in a controlled water body (pool) at different depths. We assessed the relationship between turbidity and luminosity factors and how this might affect the calculation of bathymetric survey errors using photogrammetry at different shallow-water depths. The results revealed that the highest luminosity generated the lowest error up to a depth of 0.97 m. Furthermore, after assessing the variations in turbidity, the following two situations were observed: (1) at shallower depths (not exceeding 0.49 m), increased turbidity levels positively contributed error reduction; and (2) at greater depths (exceeding 0.49 m), increased turbidity resulted in increased errors. In conclusion, UAV-based photogrammetry can be applied, within a known margin of error, in bathymetric surveys on underwater surfaces in shallow waters not exceeding a depth of 1 m.

The construction industry requires concrete with adequate post-cracking behavior for applications such as tunnels, bridges, and pavements. For this reason, polypropylene macrofibers are used, which are synthetic fibers that fulfill the function of providing residual strength to concrete. In this study, an experimental plan is carried out to evaluate the bending behavior of concrete reinforced with polypropylene fibers using the four-point bending test according to ASTM C1609. Three fiber dosages (3.6, 7.2 and 10.8 kg/m³) and three fiber lengths (40, 50, and 60 mm) were used. The use of macro polypropylene fibers increased the post-cracking behavior of concrete. In addition, based on the experimentally obtained results and available literature data, a multivariable equation was developed to predict the concrete toughness as a function of the volume, slenderness, and modulus of elasticity of the fibers. A Pearson’s correlation coefficient, r of 0.90, showed a strong correlation between the developed equation and the experimental data. From this equation, it was possible to determine the participation of the following parameters in calculating toughness. The participation or weight of the fiber’s modulus of elasticity on the concrete’s tenacity is 26%, the volume of the fiber is 39%, the slenderness is 19%, and the reinforcement index is 16%.