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This article presents the validation of a non-linear FE numerical model of a multi-span stone arch railway bridge based on experimental tests and under in-service freight trains. Static loading tests allow evaluating the bridge response in terms of vertical displacements in the arches, opening/closure deformations on specific block joints of the arches, and vertical compressive stress variations in the piers. The bridge FE model is developed by combining the potentialities of a global continuous homogeneous model, based on FEM and Drucker-Prager model, and a local modelling approach based on a dedicated non-linear contact model. The freight vehicle modelling is based on a flexible FE approach, and the validation of the dynamic behaviour of the train-bridge system involved the comparison between numerical and experimental responses. All the numerical responses are in very good agreement with the experimental responses. Finally, a simulation of the dynamic behaviour of the train-bridge system is performed for realistic scenarios of freight traffic considering speeds between 40 and 140 km/h.

The COVID-19 pandemic has changed the way how the people live, work and move, and naturally the transport sector became one of the most affected by this global crisis. Beyond the sudden fall of mobility at the beginning of the pandemic, it is important to understand how people are regaining trust in travelling, even if it is still unpredictable if and when the transport sector will recover to the pre-pandemic levels. This study focuses on the analysis of commuting trips and the changes of travel mode preferences over the first eight months of the pandemic in Germany. A survey with an orthogonal design based on sets of cards containing different transport mode alternatives and attributes was conducted in three waves (April, June, and October 2020). The individual characteristics and the preferences of around 4800 commuters were collected through the survey and modelled using a conditional logit approach. The results show that commuters have regained some trust on public transport since the April-May 2020 lockdown, but this has occurred at a slow pace. The reduction of public transport ticket fares can be the most effective strategy to recover some of the users lost to other modes.

This study explores attitudes towards urban air mobility (UAM) for e-commerce deliveries. UAM, which utilizes drones, has the potential to revolutionize transport services and logistics, leading to economic benefits and reductions in congestion and pollution. However, public acceptance is crucial for a successful implementation; thus, understanding the people’s perspective is key. Descriptive statistics were employed to evaluate survey results from three different European regions, followed by a cluster analysis to define potential user profiles. This study revealed slightly different perceptions towards UAM between the analyzed regions, but also a generally positive attitude. The most important expected identified benefits from UAM were a decrease in congestion and pollution in city centers. High-acceptance segments are gender-balanced and correspond mostly to active population and frequent online shoppers that perceive value in drone deliveries, especially related to an increased convenience and speed. They support public investment in UAM and are willing to pay more for these services and to have their home flown over. Opposite attitudes were expressed by low-acceptance segments, which are female-dominated and include mostly non-frequent online shoppers. The identified user profiles in this study can support the development of public policy and marketing strategies to increase acceptance and adoption.

The simulation of the dynamic behavior of the train-track system is strongly dependent on the accuracy of the numerical models of the train and track subsystems. The use of calibrated numerical models of the railway vehicles, based on experimental data, enhances their ability to correctly reproduce the dynamic responses of the train under operational conditions. In this scope, studies involving the experimental calibration of freight wagon models are still scarce. This article aims to fill this gap by presenting an efficient methodology for the calibration of a numerical model of a freight railway wagon based on experimental modal parameters. A dynamic test was performed during the unloading operation of the train, adopting a dedicated approach which does not interfere with its tight operational schedule. From data collected during the dynamic test, five natural frequencies and mode shapes associated with rigid-body and flexural movements of the wagon platform were identified through the Enhanced Frequency-Domain Decomposition (EFDD) method. A detailed 3D finite-element (FE) model of the loaded freight wagon was developed, requiring precise knowledge of the vehicle design details which, in most situations, are difficult to obtain due to confidentiality reasons of the manufacturers. The model calibration was performed through an iterative method based on a genetic algorithm and allowed to obtain optimal values for seven numerical parameters related to the suspension’s stiffnesses and mass distribution. The stability of the parameters considering different initial populations demonstrated the robustness of the optimization algorithm. The average error of the natural frequencies decreased from 8.5% before calibration to 3.2% after calibration, and the average MAC values improved from 0.911 to 0.950, revealing a significant improvement of the initial numerical model., The authors would like to acknowledge the support of the Base Funding UIDB/04708/2020 and Programmatic Funding UIDP/04708/2020 of the CONSTRUCT (Instituto de I&D em Estruturas e Construções) funded by national funds through the FCT/MCTES (PIDDAC). The authors also express their gratitude to Dr. Nuno Pinto and Mr. Valdemar Luís, both technicians of LESE laboratory, for their indispensable assistance during the preparation and execution of the experimental test

One of the significant challenges concerning earthquake risk mitigation is the seismic vulnerability assessment of existing buildings that were not designed according to modern codes. Several authors recognized that the infill walls might significantly affect the seismic response of reinforced concrete structures (RC). Still, they are treated as “non-structural” elements by the national and international codes and they are not considered in the seismic assessment of existing RC buildings, and their impact on the seismic response of the structure is neglected. This manuscript aims to study the seismic response of an 8-storey RC structure simulated in the software OpenSees with and without masonry infill walls. The masonry infill walls were simulated considering their in-plane and out-of-plane (OOP) behaviour interaction. Two different studies were performed. First, the study of the impact of the infill walls in the global building seismic response and after that the study of the infill walls seismic performance. Several incremental dynamic analyses were carried out for these studies to study floor accelerations and velocities and determine peak floor acceleration and peak floor velocity. At the same time, floor response spectra were drawn for the design peak ground acceleration, according to Eurocode 8. Acceleration-Displacement Response Spectrum is also obtained and presented according to Eurocode 8. The OOP accelerations and OOP velocities of the masonry infill walls were recorded for all the input ground-motions. The maximum OOP accelerations and velocities reached by the infill panels at each floor were obtained and discussed. The respective infill acceleration and infill acceleration-displacement response spectrum and infill velocity response spectra were then derived and presented. Finally, the amplification of the infills OOP accelerations along the building height will be evaluated and compared with the Eurocode 8 demands. The results show that the infills increase the peak floor accelerations and modify the floor response spectra. The infills OOP accelerations are always 1.2–2 times higher than PFA. The infills acceleration response spectra do not change with the increase of the building height.

Road safety modeling enables the development of crash prediction models and the investigation of which factors contribute to crash occurrence. Developing multivariate response models is also valuable, but such models are currently under-exploited. Machine learning techniques, especially artificial neural networks (ANN), have been presented as possible alternatives. Furthermore, selecting a proper roadway segmentation is one of the first tasks in the standard crash modeling workflow. However, this is a challenging task, especially in terms of choosing a segment length. This article presents a study of the influence of segment length on the development of multivariate response models (i.e., three response variables: property damage only crashes, injured victims crashes, and fatal crashes). The models use ANN for a road segment of a Brazilian divided multilane highway. The highway to be modeled was divided into segments with 10 different fixed lengths. The model characterization included geometric and operational data available for the years from 2011 to 2017. The models were evaluated in terms of errors and by residual plot analysis. The 5-km segment of the northbound carriageway and the 4.5-km segment of the southbound carriageway presented the smallest errors and the highest values of R2. The residual analyses confirmed the trend to improve the model with the greater segment lengths. This was clear by the residues' distribution around zero, except for the output “Fatal crashes”. The better performance of the longer segments models was expected because these models aggregate more crashes into one segment. The reduction of no crash observations also facilitated the improvement of the models' goodness-of-fit. The use of ANNs also revealed its potential value. However, it is still important to seek strategies to deal with the excess of zeros in fatal crashes; a problem that also occurs in the traditional statistical modeling process.

The worldwide generation of construction and demolition waste is about 30% to 35% of the total solid waste produced annually. In addition, the extraction of minerals leaves a high-grade environmental liability with tailings, such as kaolin clay, Brazil being one of the countries with the largest deposits and production of this mineral in the world. The kaolin clay extraction serves several industries such as ceramics, crockery, and paper, among others. The objective of this work is to insert these two wastes as raw material of construction elements, specifically masonry concrete blocks, thus giving an end to the residues, demonstrating their reutilization potential. Here, blocks were manufactured with replacement of natural aggregates, stone powder, and sand, by construction and demolition waste and of kaolin clay waste. The replacement percentages were up to 34% and 16%, respectively. The blocks made with pneumatic vibration compacting procedure presented strength beyond than what is established by norm, thus giving a favorable perspective of use for these residues as building elements.

Esse trabalho tem como objetivo analisar os impactos econômicos causados à indústria da construção civil com a manifestação da pandemia da Covid-19 e as suas diversas medidas de combate e prevenção adotadas, além de evidenciar a importância de um sistema eficaz de gerenciamento. Trata-se de um estudo descritivo, do tipo revisão integrativa da literatura, com abordagem qualitativa, realizado nas bases de dados: SCIELO e Google Acadêmico. As buscas nos bancos de dados resgataram um total de 36 artigos, dos quais foram incluídos na amostra apenas 11. Os artigos utilizados evidenciaram que a indústria da construção civil se adaptou às restrições impostas em meio a pandemia e demonstrou ser um setor extremamente importante para a economia brasileira, onde mesmo durante a referida crise sanitária, auxiliou na ampla criação de empregos e obteve êxito financeiro. O tempo atual mostra-se desafiador para todos os segmentos e o pós-pandemia ainda é algo imprevisível. Contudo, é necessário que o setor da construção civil adquira formas viáveis de continuar a desenvolver-se, já que representa um dos setores mais importantes para a economia do país.

Introduction In a context of increasing automation of road transport, many researchers have been dedicated to analyse the risks and safety implications of resuming the manual control of a vehicle after a period of automated driving. This paper performs a systematic review about drivers’ performance during takeover manoeuvres in driving simulator, a tool that is widely used in the evaluation of automated systems to reproduce risky situations that would not be possible to test in real roads. Objectives The main objectives are to provide a framework for the main strategies, experimental conditions and results obtained by takeover research using driving simulation, as well as to find whether different approaches may lead to different outcomes. Methodology First, a literature search following the PRISMA statement guidelines and checklist resulted in 36 relevant papers, which were described in detail according to the type of scenarios and takeover events, drivers’ engagement in secondary tasks and the assessed takeover performance measures. Then, those papers were included in a meta-analysis combining PAM clustering and ANOVA techniques to find patterns among the experimental conditions and to determine if those patterns have influence on the observed takeover performance. Conclusions Less complex experiments without secondary task engagement and conducted in low-fidelity simulators are associated with lower takeover times and crash rates. The takeover time increases with the time budget of the first alert, which reduces the pressure for a driver’s quick intervention.

Mexico highway network has more than 14,000 bridges. Most of them are reinforced concrete (RC) structures. The bridges design process incorporates the use of an overstrength factor that is not justified and has received little attention in published works. Mexican regulations allow using an overstrength factor for buildings in the range of 2?3, to reduce the design spectra as a function of the selected seismic behavior factor. However, for bridges, a single factor of 1.5 is proposed independent of any design parameter. The bridges in Mexico are mostly simply supported structures with maximum span lengths of 50 m. A relevant and distinctive aspect of the bridges designed in Mexico is the large load amplitudes of the trucks used to define the live load and the high seismic activity in the country. This study determines overstrength factors of a family of medium-length RC bridges composed of simply supported superstructures and substructure made up of single and multi-column RC piers. Non-linear dynamic analyzes using a set of 80 accelerograms were carried out. The results show that the height of the bridges and their seismic location are relevant parameters in the overstrength of the structures. Finally, analytical expressions are proposed to assess the overstrength factors of a very common bridge typology in Mexico and the world. 6612-034D-AE05 | PEDRO DA SILVA DELGADO N/A