This research work aims to investigate the dynamic structural behaviour of pedestrian footbridges, when subjected to dynamic vandal loadings, based on the development of experimental tests and numerical modelling. The investigated footbridge is associated to a simply supported concrete structure with span of 24.4 m, currently used for pedestrian crossing, and located at the Faculty of Engineering (FEN) of the Rio de Janeiro State University (UERJ). Having in mind the strategic location of the footbridge, near the FEN/UERJ Director’s office, different loading scenarios were idealized to carry out experimental forced vibration tests on the structure, with the participation of up to 20 people, aiming to simulate dynamic vandal loads. Initially, an experimental modal analysis was performed on the investigated footbridge, in order to identify and assess the global dynamic behaviour of the system. In sequence, a finite element model was developed and calibrated through experimental results. After that, based on the forced vibration experimental tests the footbridge dynamic response was assessed. According to the results of this investigation, for the cases of 15 and 20 people exciting the footbridge (vandal loads), the peak accelerations are, respectively, 1.30 m/s² and 1.60 m/s², and excessive vibrations and human discomfort can occur. Finally, it must emphasised that the analysed footbridge should only be used to human walking.

Secondary systems are defined as the elements that are attached to, or installed on, the main structural system. The secondary systems do not support the main system; however, they are significant to ensure the normal operation and safety of the building. Structural vibration produced during an earthquake can be a threat to systems inside the structure, and it can damage the systems, partially or totally. To preserve systems installed in a building, semi-active variable dampers, which use a 2-step viscous damping force, are used to dissipate seismic forces and minimize vibrations of the building to reduce the risk of damaging the secondary systems. The reduction of seismic vibration in secondary systems mounted on a five-storied building with semi-active dampers is analysed in this study. The displacement and acceleration parameters are determined analytically by formulating and solving equations of motion using the state-space representation. Optimal configuration of semi-active dampers identified through numerical simulations. A comparative evaluation of the controlled seismic responses and their uncontrolled counterparts is executed to evaluate the efficiency of semi-active dampers within the structural framework. The study shows that using semi-active dampers, along with proper structural design, can greatly reduce earthquake-induced deformations in secondary systems as well as primary structures.

The Sultanate of Oman is focusing on the logistics/supply chain sector as part of its Vision 2040 initiative, which aims to make Oman a logistics hub at the regional and international levels. However, effective workforce localisation, or Omanisation, remains a challenge due to operational, skills, and sustainability gaps. This document examines the issues logistics companies in Oman encounter regarding workforce localisation and the efficiency of their operations. The author employed a qualitative multiple-case study methodology and obtained information through semi-structured interviews with participants from the logistics sector, including managers, human resources personnel, and policymakers. The author found that, despite Omanisation policies, the logistics sector continues to rely on expatriate labour. Omanisation challenges include a lack of local employees’ technical skills, insufficient vocational training, and over-reliance on expatriate labour. Additionally, the author discusses how operational inefficiencies and the reluctance to adopt digital tools hinder the localisation process. The author discusses a strategic alignment framework that integrates workforce localisation, process improvement, and digital enhancement to improve localisation outcomes. The author’s findings contribute to the body of knowledge in logistics and supply chain management by providing insight into the potential operational integration of nationalisation policies aimed at achieving sustainability in Oman.

Climate change, together with rapid and frequently unplanned urban expansion, is placing increasing pressure on stormwater drainage systems in inter-Andean cities such as Huancayo (Junín, Peru). This study uses the Storm Water Management Model (SWMM) to make a prediction about how Huancayo's stormwater network will work now and in the future based on climate models. Local hydrometeorological records and stormwater infrastructure data are combined and collected to model runoff response, peak discharge, ponded volume, and network overload. Simulations show that under normal conditions for 10 and 100-year return periods, the system has limited capacity. Peak outflows reach about 78 to 121 m³/s, ponded volumes rise to about 62,000 to 145,000 m³, and node surcharge is widespread. In a 2070 projection using RCP 8.5, peak discharge and ponded volume rise by about 21% and 37%, respectively, compared to the baseline. A hybrid green–gray adaptation package that includes detention tanks, Low-Impact Development (LID) practices, collector enlargement, and monitoring support cuts peak flows and ponded volumes by 30% to 46% in baseline conditions and by about 29% to 33% in the future scenario. The findings underscore that predictive hydraulic modeling can facilitate pragmatic adaptation planning and enhance flood resilience in elevated urban catchments subject to climatic variability.

Building structural integrity evaluation is important in the long-term safety and resilience of buildings. Visual inspection techniques that have been in place do not have the capability of detecting beneath surface cracks, or cracks that may develop at an early stage, that would compromise the structural performance. This paper introduces a smart crack sensor with a combination of Ultrasonic Guided Wave (UGW) and Acoustic Emission (AE) as a guide to the complicated Structural Health Monitoring (SHM) of building structures. The system proposed is based on the UGW-based wave propagation analysis along with the AE signal monitoring, which will detect, localize, and characterize surface and internal cracks with the highest accuracy. Algorithms of machine learning are used to comprehend complicated acoustic signals and distinguish between crack initiation, crack propagation, and the noise in the environment. It is experimentally verified on reinforced concrete specimens that the coupled UGW-AE methodology is more sensitive and accurate than the uniaxial methodologies. These are possible through the combination of real-time data acquisition, fusion of signals, and smart pattern recognition that allows early detection of damage and provides the ability to monitor the damage continuously. The study will help in the emergence of an intelligent, non-destructive, and scalable SHM system capable of improving structural dependability and maintenance effectiveness in contemporary infrastructure systems.