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Facility management maintains building service quality through cycles of condition assessments and rehabilitation. Building components, however, differ in their nature, service lives, deterioration patterns, and textual/visual inspection data. This complicates the condition assessment process and subsequent rehabilitation decisions. This paper proposes a smart condition assessment framework that uses different artificial intelligence (AI) techniques that suit the condition data analysis of different building components. The framework has been applied to a dataset of over 2000 maintenance requests for roof and heating, ventilation, and air conditioning (HVAC) systems across a 600-villa portfolio. To address their varying needs, convolutional neural networks were used on images of roof defects, while enhanced data mining was used on textual data of HVAC systems. Accordingly, work packages of deteriorated components were identified, and a 60-day schedule was developed to repair 203 HVAC units. This research shows how AI can assist facility management with respect to condition assessment, rehabilitation planning, and resource allocation. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents results of a research project completed to compare the ice-melting capabilities of environmentally friendly alternative deicers with average road salt. Tests were conducted in an environmental chamber where temperatures could be controlled to a certain degree to ensure that the test specimens were in the ideal condition for the most accurate results. There were 168 samples tested and their results were recorded and interpreted throughout this paper. The outcome of this research is based on the amount of brine solution produced during the melting tests, and the depth of ice penetrated for the penetration test. The data showed that all alternative deicers competed evenly or in some cases slightly outperformed rock salt. The results show that there is no clear preference that can be given to the materials; the preference could only be given based on factors not related to ice melting and penetration. [ABSTRACT FROM AUTHOR]

The global emphasis on reducing greenhouse gas emissions means that engineers and architects are increasingly required to account for embodied carbon in their designs. However, there is a lack of knowledge and tools in the structural engineering community to enable calculation of embodied carbon for reinforced concrete structures. This paper aims to address this concern by providing a review of the most up-to-date approaches for calculating embodied carbon as well as the important factors that engineers should consider during the design phase to reduce embodied carbon. Environmental product declarations for concrete in four Canadian provinces will also be compared to illustrate the variability in the embodied carbon and the factors that influence this variability. Finally, the paper will present a case-study on the design of a reinforced concrete beam to demonstrate how to calculate embodied carbon and to illustrate how changes in design can influence the total embodied carbon. [ABSTRACT FROM AUTHOR]

This paper investigates the possibilities and challenges of using mass timber as a sustainable alternative for retrofitting existing buildings in Canada. To create the knowledge foundation on which to devise a holistic framework tailored to the specific characteristics of Canada's built environment, a detailed analysis of the types, geographical distribution, structural, and energy features of the local building stock is first presented. Then, previous strategies for enhancing and upgrading existing buildings with engineered timber are reviewed, classified, and evaluated. Finally, to explore economic and environmental implications, a detailed assessment of available life-cycle cost–benefit analysis approaches is conducted alongside their adaptation to Canada's building context. The findings of this paper can inform policymakers, builders, and designers in developing more sustainable building retrofit practices, design, and regulations, in line with Canada's efforts toward net zero emissions. [ABSTRACT FROM AUTHOR]

Effective winter road maintenance relies on precise road friction estimation. Machine learning (ML) models have shown significant promise in this; however, their inherent complexity makes understanding their inner workings challenging. This paper addresses this issue by conducting a comparative analysis of road friction estimation models using four ML methods, including regression tree, random forest, eXtreme Gradient Boosting (XGBoost), and support vector regression (SVR). We then employ the SHapley Additive exPlanations (SHAP) explainable artificial intelligence (AI) to enhance model interpretability. Our analysis on an Alberta dataset reveals that the XGBoost model performs best with an accuracy of 91.39%. The SHAP analysis illustrates the logical relationships between predictor features and friction within all three tree-based models, but it also uncovers inconsistencies within the SVR model, potentially attributed to insufficient feature interactions. Thus, this paper not only showcase the role of explainable AI in improving the ML interpretability of models for road friction estimation, but also provides practical insights that could improve winter road maintenance decisions. [ABSTRACT FROM AUTHOR]

In qualifications-based selection (QBS), consultants are selected according to their competencies rather than price. However, clients are often apprehensive about the subjectivity associated with implementing QBS because non-price criteria are hard to measure. In addition, there is no complete set of all relevant consultant evaluation criteria established. There is also a lack of an automated decision support system for objectively assisting owners in selecting qualified consultants with improved consistency and transparency. In this paper, a comprehensive set of consultant evaluation criteria is identified. Evaluation rules are also established for measuring qualitative criteria, where those rules determine the linguistic performance ratings for the fuzzy TOPSIS model instead of decision-makers, which minimizes subjectivity and increases transparency. The decision support system presented in this paper is flexible, allowing the decision-maker to adjust criteria weights based on the project characteristics and to exclude any non-applicable evaluation rules that may not fit in some projects. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Moisture-induced damage has been known as a major premature distresses in asphalt pavement. Numerous review papers have been made to provide the progression in study on moisture damage of asphalt pavement. However, mechanical properties of asphalt mixtures used as a parameter for moisture susceptibility evaluation were not reviewed in detail. To make the review of moisture-induced damage in asphalt pavement more comprehensive, this paper reviews research studies on moisture damage of asphalt pavement in view of mechanical properties as a parameter during the past 50 years. These parameters include tensile strength ratio (TSR), cohesion ratio (CR), dynamic modulus ratio (DMR), resilient modulus ratio (RMR), and shear strength ratio (SSR). TSR and CR are only relevant at bottom of asphalt concrete (AC), while SSR can be used to describe moisture damage at different AC depths. DMR and RMR are concentrated on the impact of moisture damage via performance characteristics of asphalt mixtures. [ABSTRACT FROM AUTHOR]

The road agencies collect and submit weigh-in-motion (WIM) data to the Federal Highway Administration as part of their traffic monitoring program. Therefore, the WIM data should be precise and accurate. One way to evaluate WIM measurement errors is by using the test truck data collected immediately before and after equipment calibration. The limitation of this approach is that the data represent a snapshot in time and may not represent a long-term WIM site performance. This paper presents an approach for estimating WIM system accuracy based on axle load spectra attributes (normalized axle load spectra (NALS) shape factors). This alternative approach allows for characterizing temporal changes in WIM data consistency. The WIM error data collected before and after calibration were related to Class 9 NALS shape factors in the proposed methodology. This paper aims to determine WIM system errors based on axle loading without physically performing WIM equipment performance validation using test trucks. The presented methodology can be used to estimate systematic errors (drift) in the WIM system at any point in time after the equipment calibration. This approach can help highway agencies select optimum timings for routine maintenance and calibration of WIM equipment without compromising its accuracy. The results show that the WIM accuracy for the single axle (SA) and tandem axle (TA) can be estimated with SA and TA NALS shape factors with an acceptable degree of error for bending plate to quartz piezo sensors. Examples are included to demonstrate the application and significance of the developed models. [ABSTRACT FROM AUTHOR]

Bridge infrastructure assets should be planned, designed, constructed, and operated to account for the physical processes that may occur over their service lives. In ice-affected rivers, this includes the interaction of bridge infrastructure with river ice. Advancements in river-ice science and modelling of ice processes in ice-covered rivers have enhanced the abilities of civil/hydrotechnical engineers to plan, design, and construct bridges in and along rivers with seasonal ice covers. In this paper, an overview is presented of ice-related considerations with respect to bridges. The bottom-chord elevation of the bridge superstructure with respect to water and ice levels, pier design to withstand ice forces, the waterway opening for ice passage, ice-induced scour, and research needs are discussed. However, as outlined in the paper, research on ice loads and passage at bridge sites and on hydroclimatic and ice conditions that led to bridge damage and failure remains needed. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The application of deep learning in construction has attracted increasing attention among researchers in recent years. In this review article, comprehensive scientometric analysis and critical review were performed to analyze the state-of-the-art literature on the application of deep learning in construction. This research used the science mapping method to quantitatively and systematically analyze 423 related bibliographic records retrieved from the Scopus database, and further, a critical review was performed on the collected themes of all the related publications. The results of the critical review indicate that deep convolution neural networks, you only look once, single-shot detectors, recurrent neural networks, residual neural networks, and fast region-based convolution neural networks have been the most widely used deep-learning methods in the construction industry. The most commonly addressed problems in the construction industry using deep-learning methods include classification of construction equipment, worker's safety helmet detection, ergonomics analysis, image enhancement, and feature extraction. This paper provides an in-depth understanding and big-picture overview of the existing literature along with the challenges and future direction of research on deep learning in construction. [ABSTRACT FROM AUTHOR]

Occupational safety hazards and risk management in construction industries are major worldwide concerns due to the unique dynamic nature of their working environment. Safety-related documentations such as injury reports, physical demand analyses (PDAs), and standard operating procedures (SOPs) contain valuable information to support the risk prevention algorithms. This paper presents a blended study on occupational risk assessment, in perspective with both attribute-based and data mining approaches. The study explored a strategy of attribute-based identification and degree of risk classification by applying distinctive quantitative analysis on the level of injuries. Data mining analysis further exposed the causality links of potentially hazardous activities and injuries. A conceptual digital transformation framework is proposed to assess digital mapping and future predictive measurements for up-to-date risk factor evaluation. The blended analysis is expected to help the construction industry identify relationships on causes of safety hazards, key safety attributes, as well as their corresponding risk controls. [ABSTRACT FROM AUTHOR]

The majority of civil infrastructure projects involve activities that are repeated across a number of linear units (e.g., highway sections) or scattered units (e.g., multi-bridge rehabilitations). For these projects, Critical Path Method (CPM)/line-of-balance (LOB) repetitive scheduling combines the benefits of CPM and LOB analyses to maintain work continuity across units, yet assumes simple sequential unit order and results in schedule delays for practical projects with non-identical units, constrained resources, and (or) strict deadlines. To improve CPM/LOB scheduling, this paper introduces powerful and easy-to-use enhancements, including (1) designed interruptions to reduce time gaps; (2) efficient resource-constrained first-come first-serve crew assignment; (3) crew adjustment loop to meet deadlines; and (4) representation of flexible unit sequence. These simplified enhancements computationally produce schedules that respect deadlines, individual resource limits, and desired sequence among units. Example projects are then presented to prove that the proposed enhancements offer flexible scheduling features that can meet the strict constraints of infrastructure projects. [ABSTRACT FROM AUTHOR]

Two optimization methods are proposed to improve faster region-based convolutional neural network (Faster R-CNN), which are (1) restructuring Faster R-CNN's backbone network and the classification and regression (C&R) network using residual networks and (2) designing the feature ensemble structure for Faster R-CNN to combine the shallow with deep feature maps of the backbone. In addition, this paper proposed a method to evaluate the model's performance, which is pixel mean value (Pmean) distribution of different channel feature maps, and quantitatively evaluate the feature representation capability of the model. Experimental results show that mean average precision (mAP) of the model optimized by the first method can reach 86.5%, which is 1.9% higher than that of baseline. However, mAP of the model optimized by the second method reaches 87.5%, which is 2.9% higher than the baseline model. The Pmean statistics of each channel feature map extracted by different backbones show that the model accuracy is higher when the Pmean of its channel feature maps is bigger, which can effectively improve the interpretability of the model accuracy. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach for measuring the cost requirements and related values for building information modeling (BIM) adoption using the adaptive analytic hierarchy process approach. The proposed approach considers the importance of each BIM use item in relation to its cost, allowing for prioritization of BIM uses based on their relative value while considering prerequisite relationships and budgetary constraints. The effectiveness of the approach was demonstrated through empirical validation involving a survey of 50 construction industry professionals, and two BIM use prioritization methods (project objective-oriented and value-oriented) were recommended for decision-making under budget constraints. The lessons learned from the empirical case study include the importance of Government's role and the industrial standards in evaluating cost-benefit and promoting for BIM adoption, the different contributions of BIM uses across project phases, and the diverse perceptions of BIM cost requirements among different participants. These lessons are invaluable for countries planning BIM implementation. This paper also demonstrates the development and empirical validation of a novel approach for BIM use adoption under limited budgets, which can assist decision-makers in selecting appropriate BIM use items and estimating their associated costs. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To improve the traffic efficiency of bus at a group of intersections and reduce their delay, this paper develops a speed guidance strategy for buses under travel time control at intersection groups. The approach considers the influence of bus departure time, bus station arrival rate, and bus station dwell time. Simulation experiments are carried out on three consecutive intersections along Jinshan Avenue in Fuzhou, China. Results show that the average travel time of buses, the average delay of buses, and the average delay per capita in the priority direction are reduced by 5.5%, 9.9%, and 9.4%, respectively. The optimal rate of the average number of bus stops reached 15.2%. The indicators of the non-priority direction of social vehicles are not significantly affected. It shows that the efficiency of buses has improved after implementing the speed guidance strategy at the intersection groups without affecting the social vehicles as far as possible. [ABSTRACT FROM AUTHOR]

Adhering to ASTM C109/C109M-20 standards ensures quality in cement mortar specimens. However, achieving the required sand gradation per ASTM C778-21 can be challenging. This paper presents a faster method for adjusting sand gradation without compromising ASTM quality standards. The proposed method involves analyzing six silica sand samples of different gradations, pre-screening sands, using Excel Solver for optimal mixture ratios, making automated gradation tweaks with precise calculations, and validating the gradation to ensure ASTM compliance. After making the adjustments, compressive strength tests were conducted on mortars with the modified sands, and the results were compared with those of standard-graded sand. Based on statistical analysis, the new method yielded reliable outcomes with compressive strengths similar to standard sands. This innovation offers a more efficient alternative, paving the way for streamlined practices in civil engineering. [ABSTRACT FROM AUTHOR]

In this paper, the suitability of digital image correlation (DIC) technology in evaluating the flexural behaviour of as-built and carbon-fiber-reinforced polymer (CFRP) strengthened reinforced concrete beams was verified by conducting a four-point bending test on four large-size beams. The DIC data obtained during the tests were compared to the results measured using traditional techniques such as displacement sensors and electrical strain gauges, as well as the findings derived from finite element (FE) numerical simulations. A good agreement was achieved between the local displacement and strain measurements and the data from DIC as a function of the applied load. Moreover, the crack patterns generated by the FE modelling were validated by the corresponding patterns derived from DIC. This suitability study is expected to contribute to the future field implementation of DIC technology to monitor the CFRP-strengthened members of critical structures such as bridges. [ABSTRACT FROM AUTHOR]

Timely road surface condition (RSC) monitoring and maintenance significantly influences road safety. The current RSC relies on fixed road surveillance cameras and in-vehicle cameras. However, the fixed camera demands higher precision, while the in-vehicle camera requires higher timeliness. To address these challenges, this paper introduces an adaptive machine learning framework for simultaneous road surface detection on both device types. Initially, a convolutional neural network-based differentiation module identifies image sources. Subsequently, an adaptive algorithm switching mechanism leads to the development of two algorithms improved upon the real-time object detection algorithms. At last, extensive experiments with datasets collected from Ontario, Canada and Iowa, U.S.A. validate the framework. Results show satisfactory classification accuracy, detection precision, and speed. Notably, the mean average precision, namely mean of the average precision for all categories (mAP), reaches 91.9% for fixed cameras and 90.6% for in-vehicle cameras, outperforming existing road surface snow detection models. [ABSTRACT FROM AUTHOR]

This paper evaluates the performance of a new flexible fluid–structure interaction (FSI) module in an open-source computational fluid dynamics (CFD) software—REEF3D—for use in modelling saltmarsh vegetation. Unlike previous studies, which focussed on hydrodynamic response to plants (for example, wave attenuation) to check the accuracy of their numerical modelling efforts, this work attempts to replicate the plants' drag force and motion behaviour, based on results from several physical modelling studies. The flexible FSI module was found to consistently overestimate both the drag and motion of the numerical plants when compared to their physical counterparts. It is hypothesized that this is due to the module's use of linearly elastic material theory for the flexible structures. This is arguably inadequate for the relatively flexible materials of saltmarsh vegetation. [ABSTRACT FROM AUTHOR]

This study aims to develop simple equations for assessing the damage of reinforced concrete (RC) columns subjected to seismic loading. A fiber element model in OpenSees, validated against experimental data, was used to generate a large dataset of 56 548 data values for various RC columns. The Monte Carlo Hierarchical Adaptive Random Partitioning strategy was then applied to evaluate the sufficiency of the dataset and propose reliable equations for estimating the residual displacement ratio, damage index, and residual curvature of RC columns under given displacement demands. A relationship between these parameters and the structural performance levels was also established. Residual displacement is a practical measure that can be observed in the field after an earthquake. The proposed equations facilitate the determination of the performance level of the structure after an earthquake event. The findings of this paper can also be used in designing new structures within a performance-based seismic design context. [ABSTRACT FROM AUTHOR]

The Kashechewan First Nation (KFN) community is located on a floodplain of the north branch of the Albany River, on the west coast of James Bay. Each spring, the community faces the uncertain prospect of evacuation due to ice-jam flooding, the most severe of which occurred in 2006. A study was conducted to develop long-term options for reducing the flood risk to the community, which included dams, dykes, pier and weir type ice-control structures, and conveyance channels. This paper presents a numerical model study on the Albany River in Ontario, Canada to develop ice control as a potential means for mitigating ice-jam flooding at the KFN community using the two-dimensional ice dynamics model DynaRICE. A method was developed to simulate pier type ice-control structures within the model such that the physical channel conditions, flow conditions, and combinations of ice control could be evaluated. The model allowed detailed simulation of ice retention, resulting inundation, and the forces on the individual piers. To optimize the design of the piers, including pier spacing, height, and size, various combinations of ice, flow, and pier conditions were simulated. Numerical modeling facilitated a comparative examination of flood risk reduction to the community from the various ice control options. [ABSTRACT FROM AUTHOR]

The seismic demands of the Reinforced Concrete Shear Walls (RCSWs) system are determined based on Canada's National Building Code (NBC). NBC 2020 features the revised Canadian Seismic Hazard Model and presents the possibility of enhancing demand's accuracy by determining design spectra based on the specific average shear wave velocity, instead of specified site classes. This paper investigates the changes in design demands for RCSWs compared to the previous edition. To do so, fifty-five RCSW prototypes were modelled using distributed mass and stiffness procedure, and their dynamic response was assessed through Modal Response Spectrum Analysis at five locations across Canada. The results highlight significant changes in deformation and force demands, where the majority of cases experienced an increase in 2020 compared to 2015 when demands were determined based on specified site classes. This study also evaluates the log-log interpolation method recommended by NBC 2020 for the design spectral acceleration. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Although road surface friction is considered the most effective performance measure for maintenance operations, it is not commonly used due to the high cost of collection. As a result, most jurisdictions use subjective visual indicators that qualitatively describe the state of the road surface, even though they create measurement inconsistencies and offer less detailed maintenance tracking. For maintenance personnel to transition into using friction, the collection cost must be reduced. This paper attempts to do so by proposing a low-cost, machine learning-based method for predicting road surface friction using dash camera imagery and demonstrates its feasibility through a case study. The dataset used for this project was collected in the City of Edmonton, AB, Canada during its 2021/2022 winter season. Three models were developed using tree-based algorithms, where all three displayed high performance with an average root mean squared error of 0.0796 or 79.3% accuracy based on RMSPE. [ABSTRACT FROM AUTHOR]

Structural reliability theories are used in the calibration of load and resistance factor design (LRFD) in the Canadian Highway Bridge Design Code (CHBDC). The LRFD approach contains certain assumptions about uncertainties in the load and capacity estimation that prevent it from fully exploiting the information gathered during visual inspections. This paper presents a reliability-based framework for analyzing the visual inspection data obtained according to the Ontario structure inspection manual (OSIM). Existing deterioration models are adapted. The Bayesian interference is utilized to estimate the updated structural properties according to the prior information from the bridge maintenance and deterioration models and the new information collected from visual inspections. The criteria set by the CHBDC are used to analyze components and systems reliability. The value of the proposed framework for bridge evaluation and optimizing maintenance is demonstrated through the full implementation of a case-study bridge in the Canadian Province of NB. [ABSTRACT FROM AUTHOR]

To improve the climate resiliency of existing and new pavements, it is important to carry out pavement designs using continuous climate records at high temporal frequencies. Over the years, significant research efforts have been dedicated to obtain high-quality climatic data for pavement design including the latest adoption of the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The purpose of this study is to assess how MERRA-2 performs when compared to the Canadian Weather Energy and Engineering Datasets (CWEEDS), which provides hourly meteorological data for many parts of the country from various periods. In the first part, climate parameters at nine locations were directly compared to determine the correlation between two data sets. In the second part, long-term performances were simulated for typical flexible pavement to assess the relative impact of each climate scenario. As detailed in this paper, observed differences between MERRA-2 and CWEEDS indicate the need for further improvement of climate data quality and availability for designing resilient pavements in Canada. [ABSTRACT FROM AUTHOR]

This paper discusses a numerical model study for the simulation of flow characteristics and critical submergence for a laterally placed horizontal circular bottom intake under uniform flow. The proposed model simulates the free surface using the volume of fluid model to check the vortex formation at critical submergence. A new combined approach using phase volume fraction and swirl strength-based vortex identification mechanism is used to compute the critical submergence. The swirl strength-based vortex identification mechanism can show the vortex tube in approach flow with swirl generated at the free surface due to the axial flow withdrawal through side bottom intake at critical submergence. The computational fluid dynamics (CFD) model results were validated using experimental data, which showed a maximum error of less than ±10% in the prediction of the critical submergence. The effect of significant parameters like intake and approach flow Froude number and sill height of intake on the critical submergence is discussed. The results of this study help practitioners to adopt CFD-based numerical modelling for the design of water intakes instead of entirely relying on physical model studies, which require more finance and time. [ABSTRACT FROM AUTHOR]

Prefabricated buildings have become an effective way to sustainable development. At the same time, the process from component production to assembly also puts forward higher requirements for data between the subjects of each project. As a powerful database storage system, blockchain technology (BCT) can meet the needs of it, but the BCT has not been widely used. In addition, the Chinese government has issued a series of policy documents in recent years to promote smart digital technologies such as BCT, which have not been well implemented. Therefore, this paper analyzes the decision-making behavior mechanism of stakeholders and the factors that affect the implementation of BCT by establishing an asymmetric evolutionary game model. The model results reveal how to effectively promote the application of BCT in the supply chain of prefabricated buildings and help the government to stimulate the enthusiasm of other stakeholders to use BCT. [ABSTRACT FROM AUTHOR]

With the application of machine learning rapidly gaining popularity in computer science and other fields, neural network techniques have successfully simulated the performance of in-service pavements as they are efficient in predicting and solving nonlinear relationships and in dealing with uncertain large-area pavement problems. In this paper, we address the problem of the optimal timing of preventive maintenance of asphalt pavements to accurately predict the condition index (pavement condition index, PCI) of highway asphalt pavements and develop a highly accurate, long-period, multifactor prediction model with the suitability of preventive maintenance at its core. The prediction model is called differential evolution particle swarm optimization back propagation (DEPSO-BP) neural network, and the input dimension of the prediction model is determined by gray correlation analysis (GCA), and DEPSO is used to improve the search efficiency of BP neural network and the asphalt pavement usage performance with parameter continuity prediction model. Finally, the Qinglan Highway (G22) PCI of Gansu Province, China, is selected for example validation, and the prediction results are compared with those of the four models. The results show that the multifactor prediction model based on DEPSO-BP neural network has good generalization ability. This model is important for improving the economic efficiency of road maintenance, and can be used in the long-cycle process to provide model reference and scientific basis for the subsequent road maintenance budget application and decision-making scheme. [ABSTRACT FROM AUTHOR]

The seismic resilience of structures can be quantified through rigorous seismic assessment. Because no detailed guideline is available for nonlinear modelling parameters and the corresponding acceptance criteria for the seismic evaluation and upgrading of steel structures in Canada, the structural commentary of the National Building Code of Canada suggests using ASCE 41, which has been adopted as a standard for seismic evaluation and retrofit of buildings in the United States (U.S.). However, because the steel design standards in Canada and the U.S. are different, their applicability to steel structures in Canada needs to be investigated. To this end, this paper critically reviews the nonlinear modelling parameters and acceptance criteria, and then recommends whether these values need to be revised or are adopted as is for the seismic evaluation and upgrading of steel structures in Canada. A numerical example of a steel moment-resisting frame is presented to demonstrate the recommended parameters being used for seismic evaluation. [ABSTRACT FROM AUTHOR]

The addition of styrene butadiene styrene (SBS) to asphalt binders has led to enhanced performance in pavements across the entire range of working temperatures. SBS-modified binders have also proven to be more difficult to characterize in terms of their rheological properties. Low-temperature properties of asphalt binders are typically evaluated using the bending beam rheometer (BBR), which was developed to measure creep stiffness. Recent refinements to the BBR analysis have led to the development of ΔTc which is meant to provide more insight into the relaxation properties of the binder. The Asphalt Binder Cracking Device (ABCD) was developed to improve on this characterization by also taking into consideration the failure strength and coefficient of thermal contraction. Previous research has shown that the ABCD provides more valuable insight into the effect of SBS on the low-temperature properties of asphalt binders. This paper will evaluate the ability of these two low-temperature tests to characterize the performance of five different asphalt binders with increasing concentrations of SBS. It was found that the evaluation of the materials using ΔTc was inconsistent with binder type and generally indicated that SBS reduced cracking resistance, while the ABCD critical temperature and the proposed ΔTf parameter generally showed an improved correlation with SBS concentration. [ABSTRACT FROM AUTHOR]

Concerning the environmental imbalance caused by the over-exploitation of natural aggregates and the greenhouse emission of cementitious materials in the construction industry, in this paper, abundant laterite soil and natural coconut shells were used as partial substitutes for aggregate to make the cement-less geopolymer concrete a resource-efficient product. The effect of the alternative aggregate system in the geopolymer concrete was assessed in the aspects of strength and sustainability. The inclusion of laterite soil and coconut shell in the geopolymer resulted in 1.81 times improved toughness without significant change in the compressive strength. The use of laterite soil and coconut shell aggregates maintained the thermal stability up to 600 °C and reduces the consumption of 280 kg natural sand and 390 kg coarse aggregates while casting 1 m3 concrete, which supports to promote the alternative aggregate system for the efficient production of environmental-friendly geopolymer pavers. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Canadian Journal of Civil Engineering is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Engineered wood products along with advanced processing and fabrication are pushing the limits of modern wood construction. Innovative concepts and applications facilitate the development of a new generation of structural systems. However, capacities of such systems are often governed by capabilities of the connections. This paper presents the experimental results with numerical and analytical models of angle brackets for prediction of load bearing capacity, stiffness, and ductility. Three types of metal brackets in beam-column connections have been investigated and their performance has been studied in various loading arrangements. Detailed finite-element models of each connection have been developed to gain insights into their behavior. An analytical approach is also adopted to represent the connections. Comparison with test data suggests that the models can reproduce results with good accuracy. The findings confirm feasibility of implementing ductile connections in practical mass timber structures. [ABSTRACT FROM AUTHOR]

This paper introduces a new low-damage hybrid steel–timber rocking braced frame with self-centring capability and proposes a design methodology in the framework of Canadian design standards. This system consists of a gravity load-resisting timber frame and a steel concentrically braced frame acting as the lateral load-resisting system that is connected using U-shaped steel fuses. The self-centring capability is achieved by post-tensioning strands and rocking bases within the lateral load-resisting system. The system, along with its components, is first introduced. The proposed design method and system performance objectives are then presented. The seismic performance of the system and the proposed design procedure are validated through numerical analyses considering the interaction between the lateral and gravity load-resisting systems. The results of dynamic analyses confirm the enhanced seismic performance of the proposed hybrid system with almost no residual deformations after the earthquake. Moreover, the proposed design guidelines can accurately predict the system's seismic response and demands imposed on the members. [ABSTRACT FROM AUTHOR]

Transfer between the metro (underground railway system) and buses is standard in many cities, and the simultaneous arrival of these two modes can provide passengers with a smoother transfer experience. However, previous synchronous transfer studies rarely consider different public transport modes simultaneously. This paper presents an optimization model that maximizes the number of metro and bus network synchronizations considering the connection level. An improved algorithm that combines simulated annealing (SA) and artificial bee colony (ABC) is proposed. The best nectar source position in history is combined with the SA operation. The ABC and simulated annealing and improved artificial bee colony (SA–IABC) algorithms are used to solve the model using the Nanmendou metro station and the bus stations within 1.2 km around it in Fuzhou City, China. The results show that ABC and improved SA–IABC algorithms increase the synchronization times of the metro and bus network by 17% and 24% on average, respectively, without expanding the departure frequency. [ABSTRACT FROM AUTHOR]

The recent expansion of municipality limits has resulted in an increase in the wildland–urban interface, causing fires in the wildlands to potentially encroach and enter urban centers. This paper proposes a fire-risk modeling framework within a climate resiliency context. The study uses large-scale geospatial datasets in combination with the analytical hierarchy process. Using various high-resolution-detailed datasets, an extensive list of variables was utilized to develop a novel fire-risk model. To support the goal of creating a climate-resilient urban municipality, an ecological vulnerability classification map was constructed to identify developable areas and areas under preservation. Regarding creating awareness for climate adaptation and zone, a brief discussion on the role of each stakeholder is provided. The discussion covers strategies for fire prevention and mitigation in high-risk areas/zones, as well as establishing several cornerstones for strategic planning and action to strengthen climate resilience of urban communities. [ABSTRACT FROM AUTHOR]