Infrastructures, Volume 7, Issue 4 (April 2022) – 15 articles

Higher train speeds and heavier axle loads trigger elevated stresses and vibrations in the track, potentially increasing track deterioration rates and maintenance costs. Alternative track forms made of combinations of reinforced concrete and asphalt layers have been developed. A thorough understanding of the slab and asphalt tracks is needed to investigate track performance. Thus, analytical and numerical models have been developed and validated by many researchers. This paper reviews numerical models developed to investigate railway track performance. The synthesis of major finite element models is described in detail, highlighting the main components and their outputs. For slab track models, the use of a structural asphalt layer within the railway track remains an active research topic and firm conclusions on its efficacy are not yet available. It can be expected that slab track structures will also be affected by train-induced ground vibrations. There is thus a gap in the literature regarding the measurement of dynamic effects on high-speed railway lines, and further research is needed to investigate the dynamic behaviour of slab–asphalt track systems. In this review, novel solutions for mitigating the vibrations in high-speed rail are discussed and compared. The use of asphalt material in railways appears to have beneficial effects, such as increasing the bearing capacity and stiffness of the structure and improving its dynamic performance and responses, particularly under high-speed train loads. Full article

Steel plate shear walls (SPSW) structures have been widely employed in multistory residential buildings. The traditional welding process may lead to serious welding deformation due to the thinness of the plate. In this study, a new welding process is proposed to ensure that the stiffeners and SPSWs bend as a whole, and the number of welds is reduced from 3 to 2. This process has better integrity than the traditional process owing to less welding residual stress and deformation. On the basis of low-cycle reciprocating load tests on four full-scale specimens, the shear failure pattern, hysteresis characteristics, and load-carrying capacity of SPSWs affected by the new process are studied, and the new welding process used in the vertical stiffener can meet the requirements of shear capacity. The influences of various parameters on the shear resistance of the SPSWs made by the new welding process are compared and analyzed. The results indicate that the lateral stiffness of the frame and the width–height ratios of the wall significantly influence the load-carrying capacity of the SPSWs. The SPSWs adopting the new manufacturing process are numerically simulated using ANSYS software. The same conclusions can be obtained by comparing the numerical results with the experimental results. Full article

In order to achieve a comprehensive study regarding evacuation efficiency in underground space, globally accepted regulations and standards include, among other parameters, the maximum unimpeded travel speed of occupants in case of emergency evacuation. Researchers attempt to investigate the variation of travel speed using different approaches. The aim of this paper is to study occupants’ travel speed during evacuation procedures in an underground space. Underground spaces have special requirements as they differentiate from a typical building regarding the absence of physical lighting, the fact that exit route paths are always ascending and the limited orientation awareness of their users. A total of 40 volunteers participated in a large-scale experiment that involved the evacuation of the underground space in real time. Two distinct evacuation drills took place, the first one in a smoke-free environment and the second simulated fire conditions via the presence of dense artificial smoke. During each trial, the required evacuation time as well as the walking speed of each occupant were monitored, with the aid of digital cameras positioned in appropriate spots inside the underground space. The evacuation speed resulted from the experiments is compared to those of international regulations (e.g., NFPA 130) regarding horizontal travelling, as well as travelling on an upward staircase. The effect of the presence of smoke on evacuation speed is discussed. The importance of direct and constant guidance to the occupants of an underground space is highlighted during evacuation in a smoked environment and its contribution to safety improvement. Finally, the effect of the egress route type of an underground space on occupants’ speed is discussed and how this may affect the decision making during the design of an underground infrastructure, in order to achieve a safe environment. Full article

The harmonious development of urban rail transit, underground space engineering, and social economy is the key to regional sustainable development. Based on synergetic theory, this paper constructs the coupling coordination evaluation system of “rail transport-social economy” composite system at the scale of a city cluster. With this system, the coupling and coordinated development pattern and characteristics of “rail transit-social economy” in the Yangtze River Delta city cluster from 2002 to 2020 were analyzed. The paper makes a horizontal comparison with the Beijing-Tianjin-Hebei city cluster and the Pearl River Delta city cluster, as well as analyzes the differences in development and existing problems, and puts forward policy suggestions for rail and urban underground space development. The results show that: (1) The rail transit of 11 cities in the Yangtze River Delta shows a “step by step” development pattern. That is “national central city, provincial city, second-tier city, third-tier city, etc.”, accompanied by periodic changes of coupling and coordination degree. In addition, there is also the phenomenon of unbalanced development within the region; (2) From 2002 to 2020, the development of rail transit in the three city clusters shows a situation of “the overall supply is lacking and lags behind the social economy for a long time”. Among them, the Pearl River Delta city cluster has the most serious lags. Multi-channel financing, speeding up the construction of the rail transit scale according to local conditions, and improving operating efficiency are considered to be the keys to solve this problem; (3) In general, the coupling between rail transit and the social economy in the Yangtze River Delta city cluster is better than that in the Beijing-Tianjin-Hebei city cluster and the Pearl River Delta city cluster, but the coordination is at a slight disadvantage. Full article

The qualitative measurement is a common practice in infrastructure condition inspection when using Infrared Thermography (IRT), as it can effectively locate the defected area non-destructively and non-contact. However, a quantitative evaluation becomes more significant because it can help decision makers figure out specific compensation plans to deal with defects. In this work, an IRT-based novel damage index, damage density, was proposed to quantify the significance of subsurface defects. This index is extracted from IR images using our thermography analytics framework. The proposed framework includes thermal image processing, defect edge detection, and thermal gradient map calculations. A modified root mean square error (mRMSE), which is a novel modification to the existing RMSE, was compared to evaluate the performance of image processing methods. The results show that the histogram equalization performs better than the other methods in the image processing part as the mRMSE is the lowest among them. The Pearson correlation coefficient between the developed index and the volume of subsurface defects is 0.94, which indicates a positive linear relationship between them. Thus, the proposed damage index can be used to guide the engineering practices and maintenance decisions for the subsurface determination in the civil infrastructure. Full article

A huge volume of waste is generated by natural and human-made disasters and by rapid urbanization that leads to the demolition of structures reaching the end of their service life. Using recycled aggregates in concrete producing reduces environmental pollution by decreasing the disposal of this waste material in landfills and preserving unreasonable exploitation of natural resources. This manuscript presents the results of an experimental program aiming to study the effect of recycled aggregates on the physical and the mechanical properties of roller compacted concrete (RCC). A Dreux–Gorisse mix design method together with the modified proctor test were adopted to prepare a reference mixture with natural aggregates with three derived mixtures where coarse aggregates were replaced by 50%, 70%, and 100% of recycled aggregates. The physical properties of RCC were evaluated by means of water absorption and gas permeability tests while the mechanical properties were evaluated using compressive, tensile splitting and 3-point flexural tests. The results of physical tests showed that both water absorption ability and gas permeability increase proportionally with the replacement ratios. The results of the mechanical tests showed that the compressive strength class was approximately constant for all developed mixtures at the age of 28 days. For a substitution ratio of 100%, a drop in the compressive strength of only 6% was recorded. The reduction in the tensile and flexural strength was more pronounced than the compressive strength and was about 10% for the mixture of 100% recycled aggregates. It was found that the strength increases with time, and it can be estimated at any age using the analytical models adopted for conventional hydraulic concretes. Based on the obtained results, it was concluded that recycled aggregates up to 50% don’t negatively affect the physical and mechanical properties of RCC. Full article

The present study deals with the structural safety evaluation of a 50-year-old river bridge, called Baghetto Bridge, located in north Italy on the Adda River. Generally speaking, hydraulic processes are the main cause of bridge failure. Scour and hydrodynamic loads have been largely studied by the hydraulic engineering community; however, in practice, integration with structural analysis is often missing. The aim of this research is to provide a multidisciplinary procedure based on hydraulic and dynamic investigations devoted to the structural verification and monitoring of river bridges with traditional mechanical bearings. The deck–river interaction is addressed, studying the influence of debris accumulation on the bridge and performing structural verification of the bearing supports. The actions exerted on the bridge deck by the river current were estimated following the recommendations of the Italian code and making some further assumptions. In addition, dynamic investigations and FE modelling were performed. The results show (1) a relatively fast procedure that can be applied by practitioners to perform structural verification of river bridges with traditional mechanical bearings, and (2) an investigation method to evaluate temperature–frequency correlation as a reference for future inspections. Full article

Structural health monitoring and damage detection tools are extremely important topics nowadays with the civil infrastructure aging and deteriorating problems observed in urban areas. These tasks can be done by visual inspection and by using traditional in situ methods, such as leveling or using traditional mechanical and electrical sensors, but these approaches are costly, labor-intensive and cannot be performed with a high temporal frequency. In recent years, remote sensing has proved to be a very promising methodology in evaluating the health of a structure by assessing its deformation and thermal dilation. The satellite-based Synthetic Aperture Radar Tomography (TomoSAR) technique, based on the exploitation of a stack of multi-temporal SAR images, allows to remotely sense the movement and the thermal dilation of individual structures with a centimeter- to millimeter-level accuracy, thanks to new generation high-resolution satellite-borne sensors. In this paper, the effectiveness of a recently developed TomoSAR technique in assessing both possible deformations and the thermal dilation evolution of man-made structures is shown. The results obtained using X-band SAR data in two case studies, concerning two urban structures in the city of Naples (Italy), are presented. Full article

Several methodologies for assessing seismic risk extract information from the statistical relationship between the intensity of ground motions and the structural response. The first group is represented by intensity measures (IMs) whilst the latter by engineering demand parameters (EDPs). The higher the correlation between them, the lesser the uncertainty in estimating seismic damage in structures. In general, IMs are composed by either a single (scalar-based IMs) or a group of features of both the ground motion and the structure (vector-valued IMs); the latter category provides higher efficiency to explain EDPs when compared to the first one. This paper explores how to find new vector-valued IMs, which are highly correlated with EDPs, by means of multi-regression analysis. To do so, probabilistic nonlinear dynamic analyses have been performed by considering a seven-story reinforced concrete building as a testbed. At a first stage, 30 scalar-based IMs have been correlated with 4 EDPs (i.e., 120 groups of IM-EDP pairs have been studied). Afterwards, the structural responses have been classified as elastic, inelastic and a combination of both. It has been analyzed how efficiency behaves when making these classifications. Then, 435 vector-valued IMs have been created to enhance the predictability of the scalar EDPs (i.e., 1740 groups of IM-EDP pairs have been analyzed). Again, the most efficient IMs have been identified. Sufficiency, which is another statistical property desired in IMs, has also been examined. Results show that the efficiency and sufficiency to predict the structural response increase when considering vector-valued IMs. This sophistication has important consequences in terms of design or assessment of civil structures. Full article

Biodesign holds the potential for radically increasing the sustainability of the built environment and our material culture but comes with new challenges. One of these is the bridging of the vast differences of scale between microbiological processes and architecture. We propose that a transcalar design approach, which weaves together nonlinear dependencies using computational design tools and design methodologies through the biological generation of architectural components, is a way towards successful design implementations. Such design processes were explored in a laboratory-based fabrication and study of a column element. This column, named Protomycokion, serves to illustrate how design methodologies, particularly through the use of a demonstrator artefact, can serve to navigate the multiple scales, disciplines, and experiments that are necessary to engage the complexities of biodesign. Transcalar design processes embrace the adaptability, variability and interdependence of biological organisms and show possible gains with regard to material sustainability and increased performativity. Full article

Building information modelling (BIM) is evolving significantly in the architecture, engineering and construction industries. BIM involves various remote-sensing tools, procedures and standards that are useful for collating the semantic information required to produce 3D models. This is thanks to LiDAR technology, which has become one of the key elements in BIM, useful to capture a semantically rich geometric representation of 3D models in terms of 3D point clouds. This review paper explains the ‘Scan to BIM’ methodology in detail. The paper starts by summarising the 3D point clouds of LiDAR and photogrammetry. LiDAR systems based on different platforms, such as mobile, terrestrial, spaceborne and airborne, are outlined and compared. In addition, the importance of integrating multisource data is briefly discussed. Various methodologies involved in point-cloud processing such as sampling, registration and semantic segmentation are explained in detail. Furthermore, different open BIM standards are summarised and compared. Finally, current limitations and future directions are highlighted to provide useful solutions for efficient BIM models. Full article

Structural Health Monitoring allows an automated performance assessment of buildings and infrastructures, both during their service lives and after critical events, such as earthquakes or landslides. The strength of this technology is in the diffuse nature of the sensing outputs that can be achieved for a full-scale structure. Traditional sensors adopted for monitoring purposes possess peculiar drawbacks related to placement and maintenance issues. Smart construction materials, which are able to monitor their states of strain and stress, represent a possible solution to these issues, increasing the durability and reliability of the monitoring system through embedding or the bulk fabrication of smart structures. The potentialities of such novel sensors and systems are based on their reliability and flexibility. Indeed, due to their peculiar characteristics, they can combine mechanical and sensing properties. We present a study on the optimization and the characterization of construction materials doped with different types of fillers for developing a novel class of sensors able to correlate variations of external strains to variations of electrical signals. This paper presents the results of an experimental investigation of composite samples at small and medium scales, made of cementitious materials with carbon-based inclusions. Different from a previous work by the authors, different carbon-based filler composite sensors are first compared at a small cubic sample scale and then tailored for larger plate specimens. Possible applications are in the strain/stress monitoring, damage detection, and load monitoring of concrete buildings and infrastructures. Full article

Separating household waste into categories such as organic and recyclable is a critical part of waste management systems to make sure that valuable materials are recycled and utilised. This is beneficial to human health and the environment because less risky treatments are used at landfill and/or incineration, ultimately leading to improved circular economy. Conventional waste separation relies heavily on manual separation of objects by humans, which is inefficient, expensive, time consuming, and prone to subjective errors caused by limited knowledge of waste classification. However, advances in artificial intelligence research has led to the adoption of machine learning algorithms to improve the $accuracy$ of waste classification from images. In this paper, we used a waste classification dataset to evaluate the performance of a bespoke five-layer convolutional neural network when trained with two different image resolutions. The dataset is publicly available and contains 25,077 images categorised into 13,966 organic and 11,111 recyclable waste. Many researchers have used the same dataset to evaluate their proposed methods with varying $accuracy$ results. However, these results are not directly comparable to our approach due to fundamental issues observed in their method and validation approach, including the lack of transparency in the experimental setup, which makes it impossible to replicate results. Another common issue associated with image classification is high computational cost which often results to high development time and prediction model size. Therefore, a lightweight model with high $accuracy$ and a high level of methodology transparency is of particular importance in this domain. To investigate the computational cost issue, we used two image resolution sizes (i.e., $225\times 264$ and $80\times 45$) to explore the performance of our bespoke five-layer convolutional neural network in terms of development time, model size, predictive $accuracy$, and cross-entropy $loss$. Our intuition is that smaller image resolution will lead to a lightweight model with relatively high and/or comparable $accuracy$ than the model trained with higher image resolution. In the absence of reliable baseline studies to compare our bespoke convolutional network in terms of $accuracy$ and $loss$, we trained a random guess classifier to compare our results. The results show that small image resolution leads to a lighter model with less training time and the $accuracy$ produced (80.88%) is better than the 76.19% yielded by the larger model. Both the small and large models performed better than the baseline which produced 50.05% $accuracy$. To encourage reproducibility of our results, all the experimental artifacts including preprocessed dataset and source code used in our experiments are made available in a public repository. Full article

A universal infrastructural issue is wetting of surfaces; millions of dollars are invested annually for rehabilitation and maintenance of infrastructures including roadways and buildings to fix the damages caused by moisture and frost. The biomimicry of the lotus leaf can provide superhydrophobic surfaces that can repel water droplets, thus reducing the penetration of moisture, which is linked with many deterioration mechanisms in infrastructures, such as steel corrosion, sulfate attack, alkali-aggregate reactions, and freezing and thawing. In cold-region countries, the extent of frost damage due to freezing of moisture in many components of infrastructures will be decreased significantly if water penetration can be minimized. Consequently, it will greatly reduce the maintenance and rehabilitation costs of infrastructures. The present study was conducted to explore any attempted biomimicry of the lotus leaf to produce biomimetic coatings. It focuses on anti-wetting characteristics (e.g., superhydrophobicity, sliding angle, contact angle), self-cleaning capability, durability, and some special properties (e.g., light absorbance and transmission, anti-icing capacity, anti-fouling ability) of lotus-leaf-inspired biomimetic coatings. This study also highlights the potential applications of such coatings, particularly in infrastructures. The most abundant research across coating materials showed superhydrophobicity as being well-tested while self-cleaning capacity and durability remain among the properties that require further research with existing promise. In addition, the special properties of many coating materials should be validated before practical applications. Full article

From the perspective of sustainability and environmental concerns, the use of cold-mix asphalt (CMA) and recycled asphalt pavement (RAP) is more advantageous than the use of hot mix asphalt (HMA) and warm mix asphalt (WMA). Some researchers used a mixture of CMA and RAP to improve the mechanical properties of pavement and made it more economical. However, only a few studies have focused on using a high content of RAP—particularly 100% RAP—as the virgin aggregate. Therefore, this study aims to analyse cold-mix asphalt (CMA) using 100% recycled asphalt pavement (RAP) instead of virgin aggregate raw materials and to determine the best mixture for the production of environmentally friendly asphalt. It is necessary to investigate the performance of CMA mixed with RAP in terms of the resilient modulus, indirect tensile strength, fatigue and rutting resistance. In this study, the percentage of bitumen emulsions added is 2%, 2.5%, 3%, 3.5%, and 4%, along with 100% RAP material. The results indicate that the fatigue life of the RAP mixture increased by 49.34% with the addition of bitumen emulsion (BE) from 2% to 4%, while the wheel tracking test experienced a decrease in rutting depth along with an increase in BE dose of 4%, which was 9 mm. The mixture containing 4% asphalt emulsion has the best performance. The results suggested that increasing the BE dosage increases the resistance against rutting and fatigue. Full article