Canadian Journal of Civil Engineering

This study investigates safety performance of permeable friction courses (PFCs) in terms of hydroplaning. An analytical model was derived to calculate water depth on PFC under static rainfalls. A tire-water-pavement interaction model was used to predict hydroplaning speeds. The results show that water film depth increases from innermost to outermost traffic lanes. PFC can mitigate hydroplaning risk under 0.5cm/h rain rate. At rain rate of 1cm/h, the impact of horizontal hydraulic conductivity and PRF thickness on hydroplaning speed is less than 10%, but becomes negligible at higher rain rates. On the other hand, the flow slope of PFC significantly affects hydroplaning speed by over 50%, while this effect decreases as rain rate increases. The surface macrotexture of PFC shows less than 5% impact on hydroplaning speed at all rain rates. An analysis framework with design example is proposed to incorporate hydroplaning speed in decision-making of roadway design with PFC.

Two beam-to-rectangular hollow section (RHS) column connections were investigated to assess the CSA S16:24 design requirements for limited-ductility (Type LD) moment resisting frames (MRFs). The first connection was reinforced externally using T-stiffeners, and the second had top and bottom flange plates welded to a doubler plate reinforced RHS wall. This paper presents a comparison of the CSA S16:24 design requirements for Type LD MRF connections to the AISC 341-22 design requirements for ordinary moment frames; a rational design approach for each of the two beam-to-column connections; and the results of an experimental program comprising two quasi-static and four reverse cyclic tests on full-scale assemblies. An evaluation of the connections’ strength, stiffness, and overall behaviour is made, and both connections are shown to meet the performance requirements of CSA S16:24 Clause 27.4.4.c). Recommendations are provided to facilitate the use of RHS columns in Type LD MRFs.

Concrete brick prisms prepared with Type S masonry mortar that included sodium nitrite and/or nanocellulose as potential antifreeze admixtures were cured for 28 days at -10°C before measuring compressive and flexural bond strengths. Addition of sodium nitrite allowed masonry prisms cured at -10°C to reach 88% and 86% of the compressive and flexural bond strengths, respectively, of control specimens cured at room temperature. Nanocellulose was only effective when used in combination with sodium nitrite, improving the compressive and flexural bond strengths by an additional 3% and 27%, respectively. Results are primarily attributed to the ability of the sodium nitrite to lower the freezing point, allowing hydration to continue in subfreezing conditions, as confirmed by results of companion tests on mortar samples. Both additives also reduced the required w/c ratio and porosity. The findings offer a sustainable alternative to energy-intensive protective heating methods, potentially lengthening the construction season into colder periods.

Concrete is known to be the most prevalent human-made material globally owing to its durability, versatility and affordability which; however, contributes significantly to global CO2 emissions. Consequently, efforts have intensified to reduce concrete's embodied carbon, with emerging or conventional alternative technologies aiming to mitigate emissions and produce "sustainable" and "low carbon" concrete; a set of terms which have been used inconsistently leading to potential greenwashing and confusion in the industry. Simultaneously, there is a pressing need for tools and policies to guide the design of low-carbon concrete structures and infrastructure. This paper introduces an embodied carbon classification system as a practical solution to address industry confusion and facilitate sustainable practices in the concrete construction sector. It consists of a universally applicable tool that can be used by designers, manufacturers, asset owners and policy makers to enable a robust evaluation of the embodied carbon concrete, develop pathways to concrete decarbonisation.

The aggregate gradation of asphalt concrete for a road pavement is a critical element since it influences its strength and mechanical properties, and also has a major role on the thermal properties. An experimental study was set up to develop a multi-criteria optimization of AC12 dense-graded asphalt mixtures designed for asphalt solar collector layers according to the Bailey method (fine, middle or coarse gradation). Samples were tested in terms of thermal potential, surface properties and mechanical performance. It was found that a coarser gradation increased the heat concentration within the asphalt (more efficient mixture for asphalt solar collector), thanks to lower specific surface area, thicker asphalt films and fewer interconnected internal voids. The surface and mechanical performance of all asphalt systems matched the common technical prescription limits for surface road layers. Overall, the multi-criteria evaluation was effective in optimizing the characteristics of the solar collector asphalt concrete.

An experimental investigation of 198 hollow concrete block masonry prisms was conducted to assess the influence of web geometry on their response to either concentric loading using a test setup conforming to CSA S304 requirements or axially eccentric loading. Prisms were five courses tall and one block wide, constructed in running bond, and were either constructed using concrete masonry units with full height webs conforming to the requirements of CSA A165 or ASTM C90, or knock-out units meeting the normalized web area requirements in ASTM C90. The stress versus strain response for prisms constructed with any of the three concrete masonry unit geometries were consistent for each type of loading applied. Prisms constructed with concrete blocks with thicker webs experienced lower strain immediately prior to failure. Results also showed that web geometry influenced resistance to concentric loading but does not affect resistance to eccentric loading.

Concrete with high volumes of supplementary cementitious materials often have lower early age compressive strength and slower strength gain with time. It has been reported that the addition of graphene nanoplatelets (GNPs) enhances concrete compressive strength. However, the ability of GNPs to increase the early age concrete compressive strength has not been investigated, and there has been limited testing of structural elements of GNP-containing concrete. This study examines the mechanical properties of low cement concrete between 1- and 28-days of curing with varying GNP concentrations. Furthermore, reinforced concrete beams with GNPs were tested at 3 and 28 days to investigate their structural behaviour. The results show compressive strength increases of up to 31% at early ages for a GNP concentration of 0.15 wt% of cement, but no overall changes in the structural behaviour.

The VENoL analytical model was developed to reproduce the nonlinear viscoelastic behaviour of asphalt concrete in dynamic analysis. In this paper, it is integrated as a contact law in a 2D model using the Discrete Element Method. The asphalt concrete is modelled on a macroscopic scale. The VENoL model is applied in the numerical code without any recalibration of its analytical parameters. Particular attention is paid to modelling variations in the Poisson's ratio as a function of test conditions. This integration is checked by comparing the results of the numerical model with those extracted from the literature for complex modulus tests in direct tension-compression. Despite the use of a macroscopic scale, it appears that the model can reproduce porosity effects through the mechanisms of DEM. Using the same set of parameters, two-point bending tests are also conducted to ensure their compliance in the characterisation of bituminous mixes.

The New Zealand government has introduced cycleways on existing narrow roads, leading to disruptions and inconsistencies for both motorists and cyclists. The effect on their behaviour about positioning, however, remains uncertain. This research paper investigated lateral positioning and lateral clearance using multiple Internet of Things (IoT) prototypes to quantify the relationship between motor vehicles and cyclists. Two methods were used, (1) sensors mounted on the pavement curb to collect positioning data, and (2) sensors mounted on a cyclist to collect lateral clearance data. Results show that heavy vehicles have the highest encroachment rate. Additionally, the cycleway helps steer motorists slightly farther away from cyclists while passing. The lateral clearance between cyclists and motorists on roads with cycle lanes is higher than on roads without cycle lanes. It was found that over 90% of motor vehicles meet the 1-meter separation standard, as recommended by the NZ Cycling Safety Panel.

This study examines the safety impacts of introducing a connected cruise control-equipped vehicle with a collision warning system using a driving simulator. The collision warning system serves to alert drivers to downstream collisions. Various scenarios were designed, taking into account factors like message content, delivery method, and vehicle-to-vehicle connectivity range. To determine the effects of connected cruise control, surrogate safety indicators, such as speed and time headway variabilities, minimum time to collision, and maximum braking, were examined. Additionally, the study identified tailgaters, individuals prone to rear-end collisions, using a newly developed rear-end accident risk index. Further, the association of driver characteristics with their car-following behaviour was tested using ANOVA. The findings revealed that in the connected environment, safety metrics exhibited reduced mean values compared to the non-connected environment. The risk index effectively detected tailgating behaviour when specific thresholds were applied. Moreover, interesting findings were observed in the ANOVA analysis.

Peatlands are relatively common in the province of Quebec (Canada) where they occupy about 12% of the surface. The hydrology of peatlands remains insufficiently documented, more specifically during the spring period where data are currently lacking in many regions, including in the Quebec boreal territory. The paucity of spring data is due to snowmelt that causes flooding in peatlands and along rivers, which makes hydrometry complicated during this period of the year. In this paper, the Peatland Hydrological Impact Model (PHIM) was coupled with a snowmelt module (CemaNeige) to simulate spring flows in an ombrotrophic peatland located in the Romaine River watershed (Quebec). Discharge data from two summer seasons (2019 and 2020) were used to calibrate the hydrological model. Despite the relatively short time series, the results show a good performance. The simulated spring flows resulting from the PHIM+CemaNeige combination are of the right order of magnitude.

Aquatic Oliogochaete worms (Lumbriculus variegatus) combined with straw led to improved geotechnical properties of fluid fine tailings (FFT) and thickened tailings (TT) in large-scale column studies. Gravity settling caused 19.9% and 20.6% consolidation of FFT and TT over 125 and 127 days, while the addition of straw and worms increased consolidation to 22.0 – 24.3% for FFT and 28.1 – 28.9% for TT. Solids content and peak undrained shear strength were up to 1.1x and 6.6x higher in straw and worm columns, with greatest improvements seen in the top tailings layers where worm tunnels were visually observed. Surviving worms were only found in one column, suggesting the worms provide benefits extending past their depth of penetration and lifespan. The addition of straw stimulated methanogenic activity, decreasing pH, increasing alkalinity, and creating strictly anaerobic conditions (-300 mV), which may have impacted the survivability of the worms but provided another bio-consolidation pathway.

Despite the potential of synthetic construction images, it remains unknown whether they can strengthen real-data volume and variety in real-world scenarios, wherein a given, real training dataset is small and biased, or large but biased. To address this, we synthetize artificial images in a computer environment to strengthen a real training dataset and test its supplementary effects in both scenarios. Specifically, we simulate a worker’s physical behaviors, capture 2D synthetic images, and annotate its bounding box using a 3D-2D projection algorithm. After combining these synthetic images with a real dataset, we train a vision-based worker detection model and evaluate its performance in each scenario. Results show that the model’s performance is improved by up to 59.1% and 12.8% in each scenario, respectively, comparing to only adopting real images. This indicates that synthetic images can enrich the restricted volume and variety of a given, real training dataset in field application scenarios.

Global research on using plastic waste in asphalt roads highlights its benefits: recycling waste, reducing greenhouse gas emissions, and providing an alternative to non-renewable asphalt binders. This study aims to bridge the gap between laboratory results and field performance of recycled plastic-modified asphalt in cold regions, promoting broader adoption. Laboratory analysis of core samples was performed as part of a quality assurance program. High-temperature rutting resistance was evaluated using the Hamburg wheel tracking test, while low-temperature cracking resistance was assessed through semi-circular bending testing. Results show that the impact of recycled plastics and fibers on rutting resistance varies with temperature, with the greatest benefit at the highest temperatures. For low-temperature cracking resistance, polyethylene terephthalate (PET) fibers outperform mixed plastics by delaying crack propagation. Low-temperature conditioning can induce thermal shrinkage in the asphalt mixture, slightly moderating the effects of recycled plastics and fibers.

Tubular joints are crucial structural components in steel tubular truss structure. Doubler or collar plate reinforcement has gained popularity in strengthening square hollow section (SHS) joints on the chord. But the existing design rules for the reinforced tubular joints require improvement. This paper reviews literature on SHS joints strengthened by doubler or collar plate. Key geometrical parameters, structural behaviour and failure modes of reinforced SHS joints reported in literature were discussed. Design methods in specifications and literature were evaluated by comparing the design values with experimental results. It was shown that the approach using linear fitting coefficients obtained by key parameters is able to provide a more accurate prediction. The SHS joint strengthening process with doubler plate or collar plate is discussed, highlighting some construction restrains. Finally, the trend and development direction of this field are proposed.

Assessing riverbank erosion is crucial for identifying hazard zones and implementing protective measures from potential disasters. Traditional in-situ measurements, though effective, are often costly and time-consuming for large-scale evaluations. This study proposes a methodology integrating machine learning (ML) applications to assess riverbank erosion across an entire area using existing submerged Jet erosion test (JET) measurements. In-situ JETs were used to measure the bank erosion rate at each site, identify influencing factors, and randomly split datasets for training and testing. Four ML techniques, random forest(RF), decision trees(DT), multiple linear regression(MLR), and gradient boosting regressor(GBR), are applied to establish the correlation between riverbank erosion and its influencing factors. The RF model demonstrated the highest accuracy (R2 = 0.94, RMSE = 3.04, and NSE = 0.93) among all algorithms, and the optimal model was applied to predict and map annual erosion rates, which were validated with additional submerged JET data. The proposed methodology can effectively model and map riverbank erosion in similar settings.

In this study, the mechanical performance of bituminous composites was predicted using an upscaling methodology that integrated both finite element analysis and analytical modeling. The FE approach was employed to incorporate intricate geometries and material characteristics. The dynamic modulus of the matrix and the elastic properties of aggregates served as inputs for the numerical models at various scales. This approach considers the distinctive attributes of the granular framework at each level. Furthermore, the investigation involved the influence of air void proportions on the composite's modulus. The numerical models encompassed the random incorporation of air voids within the matrix at varying levels. Notably, it was observed that at low frequencies air voids reduced the dynamic modulus of asphalt more than at high frequencies due to its effect on viscoelastic nature of the bituminous composite. Moreover, heightened temperatures intensified the impact of air void on the dynamic modulus of the asphalt mixture.

This paper explores the impact of projected climatic loading parameters, utilizing Environment and Climate Change Canada (ECCC) data, on flexible pavement performance and design. Despite the expectation that flexible roads should endure various structural and environmental conditions throughout their design life, premature damage often occurs within the initial three to five years of service. Therefore, understanding the impact of climate change on flexible pavements in the historical, short, intermediate, and long term becomes crucial. The Pavement Mechanistic Empirical Design (PMED) was employed to assess climatic loading effects on pavement design and performance. PMED predicted rutting performances showed sensitivity when comparing historical and projected climatic loading files up to 2093. Preliminary results based on a 25-year design life for City of Windsor revealed a 72% higher rutting impact compared to historical data, shortening the pavement's design life by 28%, 56%, and 68% for short, intermediate, and long terms, respectively.

Motorcycle food delivery riders (MFDR) face significant crash risks and some of these crashes are attributed to other vehicle drivers. This paper assesses drivers’ perceptions and observed riding behaviors of MFDRs, through a survey, and analyses driver factors that increase MFDR crash risk. Drivers indicated that MFDRs exhibited reckless riding (tailgating, filtering, and weaving), and drivers’ demographics, driving characteristics, and personality traits anger affected these observations. Personality trait anger influenced fault identified in a crash and motorcycle riding perception while driver demographics had a minor effect on the perceptions. Drivers’ motorcycle riding experience affected the understanding of MFDR behaviors and perception. Driver’s age, employment, motorcycle riding experience, violations, emotional state while driving (hurry), observed MFDR violations factor score, and motorcycle riding perception affected crash probability. The results could be used to develop strategies to promote traffic safety in mixed environments by providing motorcycle riding behavior awareness and improving driver training.

This study evaluates the safety performance of urban roundabouts in India using conflict-based Safety Performance Functions (SPFs). High-resolution aerial videos were utilized to extract vehicle trajectories, and the Surrogate Safety Assessment Model (SSAM) was employed for conflict identification. Data were collected from 27 roundabouts across various Indian cities, focusing on non-lane-based heterogeneous traffic conditions. Four SPFs were developed utilizing a Generalized Linear Model with Negative Binomial (NB) distribution and log link function for different proximity levels based on Time-to-Collision (TTC) and Post-Encroachment Time (PET) values. Key factors influencing conflict frequency included conflicting traffic volume, occupancy time, ratio of approaching and conflicting traffic volume, percentage of cars and motorcycles, inscribed circle diameter, roundabout symmetry, and number of legs. The developed conflict frequency prediction models fitted well and demonstrated robust predictive performance. This proactive framework for roundabout safety assessment can be followed to enhance road safety in developing nations.

Climate change and extreme weather events present a fundamental challenge to pavement engineering and planning practice, given that transportation infrastructure has traditionally been planned and designed using historical climate data under the implicit assumption that climate is stationary and future conditions will resemble past ones. Transportation professionals should consider future risks scenarios in road design, material selection and system operations. This will be challenging given the inherent uncertainties in any climate projections. However, changes might be needed since transportation professionals are expected to deliver cost-effective and climate-resilient transportation infrastructure. The material selection plays an important role in the durability of flexible roads; therefore, it is important to consider the whole road design life cycle in terms of climate change and extreme weather events impact on asphalt selection as well as to consider different traffic speeds. This led to the development of the NRC Climate Adaptation and Asphalt Selection Tool (CAAST).

Tyrolean and Coanda types of water intake structures are the most widely preferred bottom intake structures used to divert water from channels and river systems for various purposes, such as energy production, irrigation, and domestic use. Estimation of withdrawal water and filtered sediment amounts are important to obtain maximum efficiency from an intake structure. The purpose of this study is to numerically analyze a newly patented rotating Coanda-type intake system to achieve the highest Water Capturing Efficiency and Sediment Release Efficiency. The newly patented system (patent no: TR2021011306B) presented here incorporates Coanda screens with variable void ratios, autonomously selected based on the sediment characteristics of the inflowing water. The process of selecting and positioning the appropriate screen is fully automated, requiring no human intervention. The system rotates under motor control to place the suitable screen at the operational point based on the specific requirements of the incoming sediment-laden flow.

The reactive isocyanate-based modifier chemically reacts with asphalt components, overcoming the issues of increased viscosity and phase separation encountered with conventional modified binders. It can be used to modify binders to meet the highest performance grades currently specified by state highway agencies. This project aimed to demonstrate the constructability of an asphalt mixture modified with the reactive isocyanate-based modifier in the field and compare its performance with that of a control mixture. The project involved milling an approximately 5.0-cm (2-in) thick surface layer of two 30.5-m (100-foot) sections with similar foundation support. One section was resurfaced with a reactive isocyanate-modified mixture and the other with a conventional SBS-modified mix. The mixtures have shown no significant difference in field performance and laboratory performance test results. This study has provided insights into the field applicability of reactive isocyanate-based modifiers in asphalt mixtures, facilitating the ongoing efforts to develop durable road surfaces.

Soil and water conservation structures are vital for environmental resilience but present maintenance challenges due to their wide distribution and remote locations. To tackle these issues, a method using unmanned aerial vehicles (UAVs) combined with 360-degree photography was developed. UAVs captured images that were processed into panoramic and 3D models, enabling precise inspections of structural damage. These models were integrated into the disaster environment review and update (DER&U) rating system, enhanced by a fuzzy inference classification mechanism for improved damage estimation. Additionally, a management platform was created to boost overall efficiency and provide decision-making support for relevant authorities. The UAV-assisted inspection method demonstrated promising results, though certain limitations were also noted.

The full-depth reclamation with no stabilization (FDR-NS) is widely used as a pavement rehabilitation technique. It is important to evaluate the on-site characteristics of FDR-NS materials to avoid short-term underperformance. The need for performance-based testing could then be supported by in-situ and non-destructive testing, such as dynamic cone penetrometer (DCP). DCP allows to estimate the bearing capacity of the pavement structure and to verify its homogeneity according to the depth. The objective of this research is to evaluate the applicability of using DCP to assess the quality of FDR-NS. Overall, DCP results showed a good reliability, allows to measure the effective depth of reclamation and to observe a significant reduction (average of 75 %), in terms of DCP values, between before and after the reclamation process. Thus, the potential of using DCP for FDR-NS rehabilitation was confirmed. The results from this research provide a rational basis for establishing specifications.