Infrastructures, Volume 6, Issue 10 (October 2021) – 12 articles

Underwater tunnel structures are vital in urban areas, and their use is continuously increasing. The engineering assessments for these impressive phenomena have to be performed from both geotechnical and structural engineering perspectives. The designer should take account of the requirements of the underwater structures to adequately withstand different applied loads. The underwater tunnel might be particularly vulnerable at locations where the geological conditions are uncertain. This study will cover all aspects concerning the stability of the tunnel crossing of the River Nile. The protentional exists for the tunnel failure during construction due to insufficient cover thickness and after construction due to a combination of long-term degradation and local scour. There were no imposed constraints on the alignment and the original design with a cover between the tunnel crown and the riverbed of at least one tunnel diameter. The tunnel stability was analyzed based on the most critical underwater section with a minimum cover thickness of the Greater Cairo Metro, Line 2 as the case study. Then, three-dimensional (3D) numerical analysis based on the Finite Element (F.E.) models was employed to explore soil–tunnel interactions. Comparison between numerical models’ results indicated that the safe cover thickness was equal to the tunnel diameter. The minimum cover thickness can be used to verify the required factor of safety calculated by theoretical analysis. The safety factor of the tunnel stability should not be less than 1.5 for construction and service stages and 1.3 for the exceptional case; scour accrues. Full article

This paper examines the performance of multi-binder conventional geopolymer mixes (GCMs) with relatively high early strength, achieved through curing at ambient temperature. Mixes incorporating ground granulated blast-furnace slag (GGBS), fly ash (FA) and microsilica (MS) and sodium metasilicate anhydrous, were assessed in terms of workability, mechanical properties and embodied carbon. A cement mortar was also prepared for the sake of comparison. The best performing GCM was then used as a reference for rubberised geopolymer mixes (RuGM) in which the mineral aggregates were replaced by recycled rubber particles in proportions up to 30% by volume. Experimental results were combined with embodied carbon estimations in a multi-criteria assessment to evaluate the performance of each material. A mix with a 75/25 GGBS-to-FA ratio, in which 5% MS was added, had the best performance in terms of strength, workability, water absorption and environmental impact. The compressive strength was above 50 MPa, similar to that of the cement mortar. The latter had significantly higher embodied carbon, with factors ranging between 3.48 to 4.20, compared with the CGM mixes. The presence of rubber particles reduced the mechanical properties of RuGM proportionally with the rubber amount, but had similar workability and embodied carbon to CGMs. Finally, a strength degradation model is validated against the tests from this paper and literature to estimate the compressive strength of RuGM, providing reliable predictions over a wide range of rubber contents. Full article

Unforeseen ground conditions are some of the main contributors to construction cost over-runs and late completion. Recent research trends have witnessed the scopes of building information modeling (BIM) technology being extended to subsoil and substructure constructions, or simply known as geotechnical BIM. This paper aimed to explore the procedures of developing 3D subsoil models through two case studies in Malaysia. The geotechnical BIM processes were performed by commercial software, AutoCAD Civil 3D 2017, with the extension of the Geotechnical Module. The modeling procedures can be divided into three main stages, namely data collection, data interpretation, and data visualization. The subsoil models were successfully developed at different levels of detailing to serve for different applications. The results showed that the 3D subsoil modeling required huge modeling and computational efforts, particularly when dealing with tropical residual soil profiles in Malaysia that are highly intricate. Thus, an adequate soil strata generalization was required to simplify the generated subsoil model. Data collection and management was identified as one of the main challenges of promoting geotechnical BIM in Malaysia at a macro-scale. Despite the challenges, successful implementation of the geotechnical building information in the present case studies were proved to be capable of promoting interoperability of soil data, which is an essential element in sustainable construction. Full article

For dynamic analysis in seismic design, selection of input ground motions is of huge importance. In the presented scheme, complex Continuous Wavelet Transform (CWT) is utilized to simulate stochastic ground motions from historical records of earthquakes with phase disturbance arbitrarily localized in time-frequency domain. The complex arguments of wavelet coefficients are determined as phase spectrum and an innovative formulation is constructed to improve computational efficiency of inverse wavelet transform with a pair of random complex arguments introduced and make more candidate wavelets available in the article. The proposed methodology is evaluated by numerical simulations on a two-degree-of-freedom system including spectral analysis and dynamic analysis with Shannon wavelet basis and Gabor wavelet basis. The result shows that the presented scheme enables time-frequency range of disturbance in time-frequency domain arbitrarily oriented and complex Shannon wavelet basis is verified as the optimal candidate mother wavelet for the procedure in case of frequency information maintenance with phase perturbation. Full article

The interest in restoration and maintenance of old masonries towards their durability is nowadays combined with the concept of sustainability and the need to implement more suitable materials for building heritage interventions. This has led to the importance of having a better knowledge of air lime mortars, namely on the effect of pozzolanic additions, curing conditions and evolution at early stages. This study consisted in the characterization of mortars based on hydrated air lime and sand, with 1:2 (lime:sand) volumetric composition, with different weight percentages of substitution of lime by metakaolin (Mk): 0%, 10% and 20%. Mortar prisms were analyzed in three different curing environments: maritime (by the Atlantic Ocean), in laboratory humidity (95 ± 5% relative humidity, RH) and standard (65 ± 5% RH) conditioning. Tests were conducted to evaluate fresh and hardened properties of mortars, considering physical, chemical and mechanical performance at 28, 90 and 180 days. Results showed the viability of applying air lime-Mk mortars with curing conditions similar to the tested ones. In the standard curing, the mortar with 20% Mk revealed advantages in mechanical parameters. Concerning the behaviour towards water, improvements were shown at an early stage with the humid curing, while maritime curing benefited its behaviour for at least up to 6 months. Full article

This study presents a rigorous approach for the extraction of the modulus of soil and unbound aggregate base materials for quality management using intelligent compaction (IC) technology. The proposed approach makes use of machine-learning methods in tandem with IC technology and modulus-based spot testing as a local calibration process to estimate the mechanical properties of compacted geomaterials. A calibrated three-dimensional finite element (FE) model that simulates the proof-mapping process of compacted geomaterials was used to develop a comprehensive database of responses of a wide range of single and two-layered geosystems. The database was then used to develop different inverse solvers using artificial neural networks for the estimation of the modulus from the characteristics of the roller and information about the geomaterials. Several instrumented test sites were used for the evaluation and validation of the inverse solvers. The proposed approach was found promising for the extraction of the modulus of compacted geomaterials using IC. The accuracy of the inverse solvers is enhanced if a local calibration process is incorporated as part of a quality management program that includes the use of in situ measurements using modulus-based test devices and laboratory resilient modulus testing. Moreover, compaction uniformity plays a key role in the retrieval of the modulus of geomaterials with certainty. The proposed approach fuses artificial intelligence with mechanistic solutions to position IC as a technology that is well suited for the quality management of compacted materials. Full article

This paper presents and discusses the application of a novel energy balance scheme for assessing energy efficiency in wastewater systems. The energy balance is demonstrated with a Portuguese real-life case study, using mathematical modelling to estimate the different energy components and to compute two energy efficiency indices. The total inflow intrinsic energy can represent a significant amount (>95%) of the total energy used in systems mainly composed of gravity sewers. The total input energy is significantly (four-times) higher in the wet season than in the dry season, mostly due to undue inflows (e.g., direct rainfall and infiltration). The potential for energy recovery strongly depends on the available head and flow rate at the delivery point, being 0.01 kWh/m³ in the current case, with a project payback period of 4 years. The energy balance components and the respective energy efficiency indices strongly depend on the considered reference elevation. Thus, a unique regional reference elevation is recommended in the calculations. Full article

The extension of the current urban transportation system utilising the third dimension by air taxi (AT) operations represents a potential solution for the congestion of metropolitan areas. A major asset for AT operations is the connection to existing airports enabling the access to multiple other transportation systems. This paper develops an analytical model for AT operations and their capacity impact on airports, exemplary for Hamburg airport. The model is developed, based on the results of a fast time simulation (FTS) considering multiple aspects, such as vehicle configuration and touchdown and lift-off areas (TLOF). Collectively, three integration methods were analysed, each of them impacting the conventional air traffic differently. The results show that an integration using the runway-system is not possible with five ATs per hour. Further methods allow an integration of up to 20 air taxis per hour. Additionally, an energy consumption analysis of the ATs is conducted. Finally, proposals are given for integrating ATs at an airport and further strategies to extend the analytical model. Through this work, a model to calculate and predict an AT’s influence on the airside capacity of an airport is designed. This is an important step for the practical implementation of AT operations at airports. Full article

Distracting activities while driving are common and can result in errors that threaten road users’ safety. The main objectives of this study were to investigate drivers’ perspectives of the factors contributing to distraction, determine the relative rank of types of distractions, recognize the road factors and environmental effects that make distractions more dangerous, and identify the most effective measures to reduce driver distractions. A survey was conducted to assess Jordanian drivers’ experiences with distracted driving, and what solutions they believed could be implemented to solve the problems. The study’s outcomes revealed that drivers perceive visual distractions as the most dangerous, followed by cognitive, manual, and auditory distractions, respectively. It was also found that “mobile phone texting or dialing” was ranked the top most dangerous visual and manual distracting factor. “Baby is crying or kids are fighting in the back seat” was perceived by all demographic groups as the riskiest auditory factor. Regarding cognitive distraction, four factors were perceived as the most serious, of which “Baby is crying”, “Driving while angry or sad or agitated”, “Talking on a cell phone—even a hands-free one” and “Conversing with passengers” were determined to be the top four distracting factors. The results also revealed that drivers believe that “laws and enforcement” is the most effective measure to reduce distractions while driving. Full article

Urban traffic congestion has a significant detrimental impact on the environment, public health and the economy, with at a high cost to society worldwide. Moreover, it is not possible to continually modify urban road infrastructure in order to mitigate increasing traffic demand. Therefore, it is important to develop traffic control models that can handle high-volume traffic data and synchronize traffic lights in an urban network in real time, without interfering with other initiatives. Within this context, this study proposes a model, based on deep reinforcement learning, for synchronizing the traffic signals of an urban traffic network composed of two intersections. The calibration of this model, including training of its neural network, was performed using real traffic data collected at the approach to each intersection. The results achieved through simulations were very promising, yielding significant improvements in indicators measured in relation to the pre-existing conditions in the network. The model was able to deal with a broad spectrum of traffic flows and, in peak demand periods, reduced delays and queue lengths by more than 28% and 42%, respectively. Full article

Soil-structure interaction (SSI) effects are typically neglected for relatively lightweight buildings that are less than two-three storeys high with a limited footprint area and resting on shallow foundations (i.e., not featuring a basement). However, when the above conditions are not satisfied, and in particular when large basements are present, important kinematic SSI may develop, causing the foundation-level motion to deviate from the free-field one due to embedment effects. In the literature, transfer function models that estimate the filtering effect induced by rigid massless embedded foundations are available to “transform” foundation-level recordings into free-field ones, and vice-versa. This work describes therefore a numerical study aimed at assessing potential limits of the applicability of such transfer functions through the employment of a 3D nonlinear soil-block model representing a layered soil, recently developed and validated by the authors, and featuring on top a large heavy building with basement. A number of finite element site response analyses were carried out for different seismic input signals, soil profiles and embedment depths of the building’s basement. The numerically obtained transfer functions were compared with the curves derived using two analytical models. It was observed that the latter are able to reliably predict the embedment effects in “idealised” soil/input conditions under which they have been developed. However, in real conditions, namely when a non-homogeneous profile with nonlinear behaviour under a given seismic excitation is considered, especially in presence of a basement that is more than one storey high, they may fail in capturing some features, such as the frequency-dependent amplification of the motion at the basement level of a building with respect to the free-field one. Full article

The aim of this paper is to review existing publicly available and open artificial intelligence (AI) oriented datasets in different domains and subdomains of the railway sector. The contribution of this paper is an overview of AI-oriented railway data published under Creative Commons (CC) or any other copyright type that entails public availability and freedom of use. These data are of great value for open research and publications related to the application of AI in the railway sector. This paper includes insights on the public railway data: we distinguish different subdomains, including maintenance and inspection, traffic planning and management, safety and security and type of data including numerical, string, image and other. The datasets reviewed cover the last three decades, from January 1990 to January 2021. The study revealed that the number of open datasets is very small in comparison with the available literature related to AI applications in the railway industry. Another shortcoming is the lack of documentation and metadata on public datasets, including information related to missing data, collection schemes and other limitations. This study also presents quantitative data, such as the number of available open datasets divided by railway application, type of data and year of publication. This review also reveals that there are openly available APIs—maintained by government organizations and train operating companies (TOCs)—that can be of great use for data harvesting and can facilitate the creation of large public datasets. These data are usually well-curated real-time data that can greatly contribute to the accuracy of AI models. Furthermore, we conclude that the extension of AI applications in the railway sector merits a centralized hub for publicly available datasets and open APIs. Full article