To explore the influence of temperature on the alignment of a high-span, high-tower special railway bridge by examining the temperature distribution of the bridge towers and the corresponding positional changes of the high and low towers. Deformation data from the Chongqing Nanjimen rail special bridge during the winter and summer of 2024 were analyzed. The results indicate that the temperature fluctuation of the low tower is significantly greater than that of the high tower, showing higher sensitivity to temperature variations. The maximum lateral temperature gradients of the two towers occurred at 15:00 at the crossbeam, reaching 17.9 degrees C and 21.9 degrees C, respectively. Under thermal effects, the deformation of the low tower was considerably larger than that of the high tower. During the cooling stage, the top deformation and maximum longitudinal deformation of the low tower reached 73.3 mm and -141.7 mm, respectively. Under extreme winter and summer conditions, the low tower exhibited larger longitudinal deformation, whereas the high tower showed more pronounced lateral and vertical deformations. Recommendations: enhance vertical/lateral stiffness and temperature control for the high tower; focus on longitudinal deformation, material selection, and monitoring for the low tower to ensure long-term stability.
The strength of all registered airport runways is managed through a system referred to as ACN-PCN. The International Civil Aviation Organisation is replacing ACN-PCN with a new system, known as ACR-PCR. The transition from runway PCN values to PCR values requires airports to consider the basis of the current runway PCN, the thickness, composition, and associated strength of their runway pavement. Many of the regional airports do not have adequate resources to transition from PCN to PCR in a robust manner. These regional airports require practical support and a theoretical method for estimating a PCR, from the current PCN. This research developed a theoretical method for estimating PCR from published PCN values, based on a correlation between aircraft ACN and ACR values, for aircraft applicable to regional Australian airports. The correlation between regional aircraft ACN values and ACR values provides a reasonable basis for the transition, without the need for expensive pavement testing. It was concluded that although a first-principles approach to the transition from ACN-PCN to ACR-PCR is preferred, the use of the developed, regional airport specific, correlation is better that not transitioning at all, and it comes at no financial burden to regional airports.
Concrete, the most widely utilised building material, possesses brittle characteristics, exhibiting much higher compressive strength than tensile strength. The conventional method to enhance concrete's tensile strength involves reinforcing it with continuous or discontinuous fibers. This study aims to contribute to sustainable development by incorporating discarded natural pineapple leaf fiber (PLF) as a reinforcing agent. The investigation explored the effects of incorporating 1%, 2%, 3%, and 4% PLF in concrete and compared them with a control concrete mix without PLF. Results indicate that the optimal performance is achieved with a 2% PLF dosage, resulting in a 54.28% increase in splitting tensile strength and a 10.29% improvement in compressive strength compared to the control mix. Moreover, the flexural strength experiences the most significant enhancement at 7.05% with 2% PLF. As the concentration of natural PLF rises, workability and density substantially decrease. PLF contributes to ductility, enabling concrete to resist impact. Scanning Electron Microscopy tests reveal that concrete with a 2% fiber content exhibits superior cement and aggregate bonding with the least amount of cracks. This study underscores the cost-effectiveness and sustainability of concrete with the optimal fiber dosage.
Self-compacting concrete (SCC) shows a promising way towards sustainable construction with the addition of industrial by-products and recycled materials. This research study focuses on the fresh behaviour of SCC using ground granulated blast-furnace slag (GGBS) as a cement replacement (15%, 30%, 45%) and recycled concrete aggregate (RCA) as a coarse aggregate replacement (20-100%). Twenty-four SCC mixes were made and tested with slump flow, T500, J-ring, L-box, U-box, and V-funnel tests. Scanning electron microscopy (SEM) and X-ray diffraction (XRD) results indicate that GGBS exhibits an amorphous and angular morphology, which enhances the volume of the paste and its reactivity. In contrast, RCA had high roughness and adherent mortar, resulting in lower flowability at higher replacement values. Results showed that GGBS up to 30% had a consistent effect on flowability, with slump flow improved by 15-21 mm, and T500 reduced by as much as 0.5 s. In contrast, an RCA above 80% had a significant detrimental effect on flow and passing ability. Optimal performance was achieved with 30% GGBS mixed with RCA in the range of 40-60%, striking a balance between sustainability and desirable SCC fresh properties.
To reuse the biomass ash effectively in the construction industry and to assist the evolution of coal-independent thermal power plants, in this research work, an attempt is initiated to develop an eco-friendly geopolymer concrete using sugarcane bagasse biomass ash. For this purpose, the sugarcane bagasse ash was treated and used for the first time as both supplementary precursor material and an alternative silicate activator. The role of sugarcane biomass ash on the precursor and activator phases of the developed geopolymer concrete was assessed in the aspects of strength, durability and microstructural characteristics. From the results, it was inferred that the use of 10% sugarcane bagasse ash in the precursor portion exhibited the maximum compressive strength of 36.8 MPa, which is almost similar to that of conventional fly ash-based geopolymer concrete. Similarly, the usage of alternate silicate activator derived from the sugarcane bagasse ash attributed to the excellent filler effect by means of reactive silica and resulted in 43% reduced water absorption, 34.85% reduced chloride ion penetration, 13.03% improved post-fire residual strength, better thermal insulation characteristics and 9.89% reduced construction cost which will pave a sustainable and economical way for the development of biomass activated geopolymer concrete.
The primary objective of this study is to develop a machine learning model capable of predicting tunnel-induced settlement resulting from excavation processes. To achieve this, a set of finite element - based datasets was generated from rigorously calibrated and validated numerical models. These datasets were then employed to construct an ensemble learning model for settlement prediction. The input variables were selected to include key geotechnical and geometric factors, specifically the surrounding soil properties and tunnel configuration parameters, which collectively govern the deformation behaviour during excavation. The selected soil parameters comprise cohesion, internal friction angle, Poisson's ratio, and the elastic modulus. The tunnel-related parameters include tunnel diameter, depth of cover, and excavation method. The maximum surface settlement above the tunnel was designated as the output variable. Two machine learning models - Gradient Boosting and XGBoost - were developed for this purpose. The advantage of employing these two algorithms lies in their complementary strengths, where their integration helps to mitigate the individual limitations of each model especially in the case of relatively small data-set. The findings confirm the effectiveness of the proposed approach in predicting excavation-induced tunnel settlement, demonstrating its practical utility for risk assessment and mitigation planning.
Timber-Cardboard Sandwich (TCS) composites have emerged as sustainable, lightweight structural systems for rapid deployment in temporary housing, particularly in post-disaster contexts. While prior studies have addressed structural configuration and assembly methods, little is known about their long-term serviceability, particularly time-dependent deformation due to creep under natural environmental exposure. This study presents the first investigation into the short- and long-term creep performance of TCS beams under uncontrolled ambient weather conditions. Twelve full-scale TCS beams incorporating either recycled or scrap cardboard cores were subjected to sustained flexural loading over periods up to 9 months. Key variables included core material type, loading duration and exposure to hygrothermal conditions. Post-creep flexural testing was conducted to evaluate residual strength, stiffness and failure modes. Results show that beams with recycled cores exhibited more stable and consistent creep performance than those with scrap cores. Both variants met acceptable deflection criteria under short-term loading, supporting their viability for service conditions. While environmental exposure significantly influenced creep deformation, post-creep bending strength and failure modes remained consistent with control specimens, indicating no substantial degradation of structural performance. The findings establish a foundational dataset for evaluating the long-term behaviour of TCS composites and provide critical insights for their application in sustainable temporary construction.
The paper presents the development of fragility curves for two types of frames considering reduced beam section (RBS) connections, based on the results obtained from extensive nonlinear time history analysis (NLTHA). Two different classes of MRF are considered with bolted and welded connections. Due to some limitations inherent in both experimental and empirical based fragility curves, analytical fragility curves are considered to be the most reliable ones for the assessment of seismic vulnerability. In the present work, first, the force-displacement behaviour of bidirectional bolted connections (ordinary and RBS) was obtained by experimental test and numerical simulation, while the force-displacement behaviour of welded connections (ordinary and RBS) was obtained by numerical simulation using finite element analysis in ABAQUS. Subsequently, moment-rotation (M-theta) curves for all the connections were extracted from the backbone curves to obtain the behaviour of the plastic hinges of each connection. These plastic hinges were then used to derive the accurate force-displacement behaviour of the medium-rise frame modelled in SAP 2000. Finally, NLTHA was performed to obtain the maximum roof drift, considered the engineering demand parameter (EDP) in this study. Finally, standard goodness-of-fit test was performed using standard statistical methods and probability distribution function was fit to maximum roof drift data. A comparison of the fragility functions for each type of frame with different RBS-column connections was carried out. The results indicate the significant low seismic vulnerability of the considered medium-rise frames with RBS for both the bolted and welded connections, in comparison to the ordinary frame.
To investigate the damage and failure mechanisms of external thermal insulation systems (ETIS) under horizontal seismic loads, this study conducted quasi-static tests to examine the hysteretic behaviour of ETIS on frame-structures. The research focused on analysing the influence of infill walls, insulation material types, and the bonding ratio of insulation boards on the seismic performance of ETIS on frame-structure. The experimental results demonstrated that in thin-coat ETIS, the ETIS on frame beams and columns were the first to fail under horizontal loading. Systems relying solely on adhesive bonding exhibited more severe seismic damage at lower bonding ratios. Ceramic tile claddings on these systems also detached during simulated seismic action. In contrast, at a 70% bonding ratio, delamination was confined to the corners of infill walls, while other areas remained intact. Rock wool board systems maintained complete integrity under all conditions, even with ceramic tile claddings. Furthermore, lower strength of infill wall blocks and insulation materials directly exacerbated seismic damage. For ceramic tile-clad systems, a 50% bonding ratio prevented tile detachment in phenolic/EPS-based systems, whereas rock wool systems exhibited no tile detachment regardless of bonding ratio.
This paper describes a new computational framework for characterising the effects of reclaimed asphalt pavement (RAP) parameters, sources and contents, on the structural performance of hot mix asphalt, in terms of dynamic modulus (E*), of using machine learning (ML) techniques. The ML models were developed for five RAP content percentages (0%, 10%, 20%, 30%, and 40%) for three different sources. The ML models showed promising results with Taylor diagrams and R2 values of 87% to 99% for all RAP sources and content levels. The results of pavement design using ML data showed the thicknesses of the asphalt mixture are slightly different depending on the RAP source. The same trend was found in the mixing and construction temperatures. Furthermore, analysis of sustainability showed that higher and stiffer RAP (higher E*) results in a more sustainable asphalt mixture because of lower thicknesses, and consequently lower aggregate requirements and CO2 emissions, for all ML methods and fuel types. Lastly, the incorporation of higher RAP content from any sources, the use of ML methods, and the adoption of cleaner fuel types results in massive material savings, higher energy efficiency, and improved sustainability in asphalt mix production for all RAP sources.
This study presents a mechanical model based on the component method (CM) as a reliable analytical alternative to experimental testing for assessing the strength and stiffness of boltless beam-to-column (BTC) connections in steel pallet racks (SPR). Developed within the Eurocode (EN 1993-1-8) framework, the model systematically analyses the M-theta behaviour of cold-formed steel (CFS) connections with slender geometry. By identifying critical components and using spring analogies, it quantifies the contribution of individual elements, offering insights into failure mechanisms and design optimisation. The model's predictions were validated against experimental results for a 5-tab beam-end connector (BEC). The findings highlight the influence of column profile and contact area on strength and stiffness while indicating the need for refinement to capture column stiffening effects more accurately. Although experimental methods remain indispensable for specific configurations, the CM-based model provides a cost-effective and efficient tool for the connection analysis. By reducing reliance on costly experimental testing, this model contributes to the advancement of semi-rigid BTC connection design in steel pallet racks, offering a practical and scalable solution for engineers and designers.
This study explores the combined influence of coarse steel slag (SS) and glass fibre (GF) on the durability properties of concrete. Among different SS, the current study utilises Linz-Donawitz slag (LDS) as a replacement for natural coarse aggregates (NCA) at varying percentages of 0%, 25%, 50%, 75%, and 100%. Additionally, GF is introduced in concrete mixes at concentrations of 0.15%, 0.3%, 0.45%, and 0.6%. Concrete performace was evaluated through tests on compressive strength, sulphate and acid resistance, chloride penetration, carbonation, freeze-thaw resistance, water permeability, electrical resistivity, and ultrasonic pulse velocity. The findings indicate that the integration of 50% of LDS into concrete resulted in an improvement in compressive strength, sulphate resistance, sulphuric acid resistance, hydrochloric acid resistance, chloride penetration resistance, carbonation resistance, water permeability, and ultrasonic pulse velocity by approximately 10.09%, 13.64%, 10.55%, 18.05%, 9.20%, 8.42%, 9.89%, and 4.54%, respectively. Incorporating 0.45% of GF into 50% LDS concrete further enhanced these properties by up to 27.15%, 20.45%, 19.42%, 33.25%, 14.94%, 25.05%, 25.17%, and 13.40%, respectively, owing to the combined pozzolanic and reinforcing effects of LDS and GF. The experimental findings demonstrated that the combined use of LDS with GF leads to superior performance in both strength and durability aspects.
Extreme weather events intensify landslide risks, which can significantly impact the safety and functionality of road networks. Effective risk management in this context requires identifying vulnerable areas supported by appropriate assessment methodologies. This study evaluated landslide risks on state highways using historical data and future climate projections, considering the SSP1-2.6 and SSP5-8.5 scenarios. The most recent Brazilian climate risk assessment methodology was applied, with a focus on the state of Santa Catarina in southern Brazil. The analysis combined multiple local criteria within a geoprocessing environment, resulting in maps that classify road segments into five risk levels, ranging from very low to very high. Projections indicate that, without adaptation strategies, the extent of the state road network exposed to medium and high risk could nearly double over the coming decades. Additionally, the results were compared with the original outputs of the methodology, highlighting the importance of considering regional approaches, especially in highly vulnerable areas such as Santa Catarina. This study represents one of the first applications of this methodology outside its original national context, providing insights for its replication in other regions and contributing as a decision-support tool for planning road infrastructure adaptation to climate change.
Accurate and reliable bridge asset information is crucial for the efficient management of road networks, however the scale of road networks makes collection and maintenance of this data a significant burden. While current studies have demonstrated the feasibility of the detection of bridge assets from aerial LiDAR, this research addresses the added complexities of network-scale application of such techniques, considering variability in structure types, environments, and data quality. A two-pronged LiDAR processing method was developed, employing geometric segmentation and point LAS classification. The methods were tested on public LiDAR datasets covering 6 km2 and showed average identification accuracies of 64% and 93%, with detection efficacy strongly influenced by on and under bridge use combinations. This paper also presents the first benchmarking of bridge measurement accuracy from aerial LiDAR, with median accuracies for bridge length and width of 90% and 66% as compared to ground truth data.
Food waste and the concrete industry are responsible for 16% of global greenhouse emissions. In alignment with the Australian Government's goal to achieve net-zero emissions by 2050, it is imperative to analyse and develop sustainable solutions for the potential use of food waste like Spent Coffee Grounds (SCG) and biochar. This paper investigates and provides a lower-energy approach of using SCG and biochar derived by acid hydrolysis methods. Partial replacement of fine aggregate by 5% SCG, biochar, and 0 & 10% fly ash have been used to replace cement in the mortar samples to examine the binding properties. Six mix designs were developed, and 67 samples were cast and checked for slump and compressive strength after 7 and 28 days. The average maximum compressive strength of the control samples in early stages was higher. The low-energy acid hydrolysis approach used in this research resulted in a 50% increase in the compressive strengths of biochar, similar to the high-heating methods. This result shows that reasonable strengths can be achieved with approaches confirming lower energy emissions. Potential limitations of using SCG/biochar in construction were also observed and highlighted for practitioners' benefit.
Event Tree Analysis (ETA) and FN curves are widely used for fire risk analysis and evaluation. However, both have been criticised for their drawbacks. This study addresses these gaps by proposing a Bayesian Network (BN) risk analysis model using fire incident data in Australia, which has never been explored before. The BN model is developed using a score-based approach and validated using four indicators. The innovation of this paper is the introduction of a novel risk acceptability range as a risk evaluation method by integrating BN and Causal Network Topology Analysis (CaNeTA). CaNeTA identifies critical variables through network robustness analysis, which are then used to test sensitivity against current average performance. The results highlight the importance of a rapid and efficient response to fire incidents in road tunnels in Australia. The risk acceptability range represents the current average performance of road tunnels based on actual incidents in road tunnels in Australia. This range is an alternative risk evaluation tool in the absence of specific acceptance criteria. It provides an alternative perspective on risk acceptability in the absence of fatality data. In addition, the process of converting a BN model into CaNeTA provides valuable insights into causal network analysis.
The pile foundations in onshore structures are dominantly affected by lateral forces like wave force, mooring force and the force due to lateral soil movements. These lateral forces act as active and passive to the piles in the onshore foundations. These lateral forces influence the pile's lateral responses and reduce its lateral load-carrying capacity. The present paper discusses an experimental study on the lateral responses of a single pile under the combined action of active and passive loads in the horizontal and sloping ground. From the obtained experimental results, it is concluded that, with the combination of direct forward load with and without surcharge load due to lateral soil movement, the reduction of lateral load carrying capacity of a pile is exponential with an increasing ground slope. For a direct reverse load, the lateral soil movement due to ground slope and an applied surcharge load offer passive resistance to a pile displacement. As a result, the lateral load capacity of the pile is higher in the load combination of surcharge load with the direct reverse load than other load combinations accounted for in the study.
This study compares the physical and mechanical properties of Bagged Asphalt Mixture (BAM) with Cold Premix (CP) and Asphalt Concrete (AC) control. With growing road networks and environmental concerns, the paving industry seeks innovative solutions. BAM and CP are potential alternatives due to their ease of application and lower energy requirements. The research involved determining BAM's binder content and granulometric composition and conducting standardised mechanical tests for all three mixtures. Results revealed that BAM exhibited inferior mechanical performance compared to control mixtures, contradicting manufacturer claims. CP demonstrated greater suitability for repair services. The findings emphasise the need for standardisation and regulatory guidelines for BAM, challenging previously disseminated performance claims.
