Double-layer barrel vault roofs with double-layer vertical walls are widely used in important public buildings because of their high structural efficiency, favorable stiffness-to-weight ratio, and architectural versatility. Although incremental dynamic analysis (IDA) is a widely accepted approach for seismic assessment, it requires numerous nonlinear time-history analyses (NTHAs), resulting in high computational cost. This study presents an artificial neural network (ANN)-based surrogate modeling framework to accurately predict the seismic response of these structural systems, reducing the need for repeated NTHAs, enabling rapid estimation of structural dynamic responses, and facilitating direct development of seismic fragility curves. The proposed framework substantially decreases computational effort while maintaining an effective balance between accuracy and efficiency. A comprehensive seismic damage database is first generated using finite element (FE) models developed in OpenSees. Fragility curves are then obtained using both the conventional IDA procedure and the proposed ANN-based surrogate approach. Results show that the ANN surrogate accurately predicts the responses of structures subjected to scaled ground motions and effectively captures their nonlinear seismic behavior. Furthermore, the resulting fragility curves closely match those from the conventional IDA method, demonstrating the accuracy, reliability, and efficiency of the proposed framework for rapid seismic assessment of double-layer barrel vault structures with double-layer walls.
Automated pavement distress detection is essential for transportation infrastructure maintenance and road asset management. In practice, however, such detectors often need to run on embedded devices mounted on inspection vehicles, and two challenges hinder real-world deployment: (1) cracks and potholes possess markedly different geometric priors—thin, elongated topology versus blob-like shapes—so a generic backbone tends to under-represent at least one class, and (2) accuracy-oriented detectors are typically too heavy for the embedded GPUs commonly mounted on inspection platforms. To address these issues, this paper proposes a lightweight real-time pavement distress detection network. First, a multi-scale coordinate attention (MSCA) module is embedded in the neck so that long-range row/column-wise dependencies are encoded together with multi-scale local context, which is helpful for slender cracks while remaining computationally efficient. Second, a slender-aware detection head (SADH) couples a 1 × k/k × 1 asymmetric branch with the standard square branch, giving the head an explicit inductive bias for elongated objects. Third, a multi-granularity knowledge distillation (MGKD) scheme is designed, which transfers teacher knowledge from a heavier teacher to the proposed student at three complementary granularities—pixel-level attention-masked features, instance-pair relations, and decoupled class-prior logits—thereby covering the three distinct levels of information that a multi-class dense detector relies on. The network is trained and evaluated on the public RDD2022 benchmark together with a supplementary in-house set of asphalt potholes. Under the fixed-seed, single-run evaluation used in this study, the proposed method achieves an mAP@0.5 of 71.65% on the author-defined test split, which is not directly comparable with evaluations on the official RDD2022 test set, with the comparison restricted to seven representative baselines evaluated under the same protocol, and runs at 72.5 FPS on an NVIDIA Jetson Orin Nano. Although its latency is modestly higher than that of YOLOv8s, it retains real-time inference capability for on-vehicle pavement inspection.
Fully enclosed noise barriers (FENBs) are widely used in high-speed railway systems to mitigate environmental noise; however, the transient aerodynamic loads generated by train passage can induce complex structural responses. The relationship between the spatial–temporal evolution of these aerodynamic loads and the dynamic response of the complete FENB structural system remains insufficiently understood. To address this issue, this study develops a sequential computational fluid dynamics–finite element analysis (CFD–FEA) framework that directly relates the transient pressure evolution during the complete train-passage process to the deformation and stress responses of the principal FENB components. The unsteady aerodynamic field generated by high-speed train passage is simulated using a moving-mesh CFD model, and the resulting time-dependent pressure loads are subsequently applied to a finite-element structural model. Train speeds ranging from 250 to 330 km/h are considered. The results reveal strongly transient and spatially non-uniform pressure distributions inside the FENB, characterized by nose-induced compression, a middle negative-pressure region, and wake-induced pressure fluctuations. Both structural deformation and equivalent stress increase with train speed, and the exit stage produces the most pronounced structural response because of the strong negative-pressure effect. Different structural components exhibit distinct response characteristics, with localized stress concentrations occurring in the glass panels and H-section steel columns. By establishing the correspondence between transient aerodynamic pressure evolution, train-passage stages, and component-level structural responses, this study provides a more comprehensive understanding of the aerodynamic load–structural response mechanism of FENBs and provides a basis for structural design and engineering assessment under increasing train speeds.
Currently in the United States, there are more than 623,000 bridges of which 6.8% are in poor condition. Over 100 million trips are taken across these structurally deficient bridges every day and the bridge-related system rehabilitation need is estimated at $191 billion. In 1990’s, calibration of AASHTO LRFD Bridge Design Code involved extrapolation of distributions to evaluate the mean maximum 75-year live loads. However, this derivation was based on a survey of Ontario trucks with small sample size. In the meantime, the Weigh-in-Motion technology improved, and millions of vehicles are measured in various locations on a continuous basis. The objective of this study is to examine site-specific live load spectra based on WIM database in Alabama. Massive volume of data collected by the Department of Transportation is used to compute moments and shears for spans ranging from 30 ft (9 m) to 200 ft (60 m). Cumulative distribution functions of bias ratios (WIM Truck/HL-93 Loading) were plotted on normal probability paper and extrapolated. The findings show that AASHTO provisions for Strength I Limit State are not representative of vehicles at WIM sites located on interstate highways. The findings confirm the importance of continuous traffic data collection and use of reliability analysis procedures.
The shear behavior of corrugated steel web (CSW) composite girders near intermediate supports differs fundamentally from that of conventional beam segments due to the rigid restraint of concrete cross-beams, yet current design codes incorrectly assume the CSWs resist the entire shear force. This paper presents a refined analytical method, based on a three-beam composite model, that explicitly accounts for the cross-beam constraint effect. By assuming a quadratic parabolic distribution of the additional shear-flow intensity along the constraint zone, a closed-form expression for the effective shear force carried by the CSWs is derived. The proposed method is validated against three-dimensional finite element (FE) simulations and existing experimental data, and further corroborated by a parametric study covering varying structural configurations. The results confirm a shear redistribution mechanism characterized by “CSWs unloading and flange sharing.” At the section nearest to the cross-beam, the CSWs actually carry only 65.41% of the total shear force, while the flanges share approximately 35%. In contrast, the conventional code method, which neglects flange shear contribution, severely overestimates CSWs’ shear stress, producing an error as high as 35.29% at the section adjacent to the cross-beam. These findings demonstrate that the cross-beam constraint must be considered in shear design, especially near supports, and the proposed method offers a rational and accurate alternative to existing code provisions.
Connections between earth–rockfill and concrete dams are critical components of hybrid-dam seepage-control systems because material-stiffness contrasts and complex foundation conditions can create localized preferential seepage paths. Using HS Reservoir as a case study, this predictive design-stage assessment employed a full-domain three-dimensional model of the dam–foundation–abutment system and a local three-dimensional model of the cutoff-spur-wall connection. The seepage field, hydraulic gradients, and zonal seepage discharges were evaluated under the normal pool, design flood, and check flood levels, together with the responses of the connection interface and right-abutment grout curtain. Across the three baseline scenarios, the impervious core accounted for 82.2–83.6% of the total head difference at the maximum riverbed section, and the reported control-location gradients remained below the corresponding design values. At the check flood level, the modeled 178 and 179 m head contours passed above the local curtain crest at elevation 177.5 m, identifying an over-curtain seepage pathway. From the design flood level to the check flood level, right-abutment discharge increased from 259.86 to 544.49 m3/d (109.5%), while total discharge increased by 28.6%. Flow in the connection zone diverted around and beneath the cutoff spur wall, and the connection-surface gradients increased with reservoir level. These model predictions characterize the three-dimensional seepage response of the connection zone and right-abutment seepage-control system and can inform curtain-crest review, construction quality control, and post-impoundment monitoring.
This study proposes a quality-aware multimodal framework for health-state assessment and remaining useful life (RUL) prediction of cold-region tunnels. The framework integrates structural-response, environmental, apparent-defect, and engineering-inspectiondata, with the apparent-defect pathway jointly encoding raw images through a convolutional neural network and structured defect variables. Five data-quality dimensions-completeness, accuracy, consistency, timeliness, and traceability are incorporated intoreliability-guided multimodal fusion. Their base weights were re-audited through two rounds of expert consultation, each comprising 323 valid questionnaires. The Cr-weighted group analytic hierarchy process yielded weights of 0.0548, 0.1326, 0.1372, 0.2279, and 0.4474, respectively, with a group consistency ratio of 0.0455; the ranking remained stable under one-at-a-time +10% perturbations. In the primary tunnel case study, the framework achieved 89.7% health-state accuracy, a 6.3% RUL mean absolute percentage error, and 84.1% accuracy under Gaussian perturbation of standardized numerical inputs at a noise scale of 0.15. To further examine the reliability contribution of data-quality information, an independent field panel comprising 600 segment-month observations from 25 segments across three operational tunnels was evaluated using target-excluded specifications, two-way fixed effects, leave-one-tunnel-out validation, multiple baseline models, and five fixed random seeds. A one-standard-deviation increase in lagged quality instability was associated with a 0.0151 increase in the subsequent state-error index (95% CI: 0.0118-0.0184; p < 0.001). In cross-tunnel random-forest tests, incorporating quality information increased mean R2 from 0.8277 to 0.8323 for state-error prediction and from 0.8517 to 0.8673 for RUL-contraction prediction, with both improvements significant in paired tests (p < 0.001). Split-conformal intervals achieved mean cross-tunnel coverage of 95.8% and 95.9%, respectively. These findings demonstrate that data-quality information provides a modest but statistically supported improvement in cross-tunnel reliability, whilethe principal contribution lies in integrating auditable data governance, reliability-aware fusion, and engineering decision support within a unified tunnel health-management framework.
The shaft resistance of cast-in-place piles in permafrost regions is commonly estimated using the initial moisture content and frozen-soil strength parameters obtained during site investigation. However, concrete hydration heat disturbs the temperature field of the surrounding frozen soil. During thawing and subsequent refreezing, this disturbance induces unfrozen-water migration and moisture redistribution. The resulting changes in the frozen pile–soil interface may cause the measured shaft resistance to deviate from the initial design estimate. In this study, laboratory direct shear tests and engineering-oriented reduced-scale pile–soil segment tests were conducted. The effects of initial moisture content and soil stratification on interface shear strength, the surrounding temperature field, and the post-test moisture distribution were investigated. Vertical pile compression tests were also performed to evaluate changes in pile shaft resistance. The main results are as follows. (1) The shear strength of the concrete–frozen-soil interface varied nonlinearly with moisture content. It increased initially and then decreased, reaching its maximum at a moisture content of 30%. (2) The temperature rise in the surrounding frozen soil was jointly controlled by soil stratification and initial moisture content. Higher moisture contents produced smaller peak temperature rises. In the near-pile region, the maximum difference in peak temperature among soil layers with different moisture contents was approximately 10.8%. (3) During thawing and refreezing, moisture migration was jointly affected by the temperature gradient and the moisture conditions of different soil layers. Unfrozen water migrated toward colder regions or lower-moisture soil layers under temperature gradients, capillary effects, and freezing suction, resulting in near-pile moisture depletion and localized moisture enrichment. For the Group A model, the initial-state estimate underestimated the measured peak shaft resistance by 12.45%. In contrast, for the layered B1 model, the initial-state estimate overestimated the measured peak shaft resistance by 20.58%. (4) A preliminary lumped equivalent coefficient, keq, was introduced to establish a relationship between moisture content and local equivalent interface resistance. After the measured post-test near-pile moisture distributions were incorporated into the calculation, the relative deviation decreased from 12.45% to 7.36% for Group A and from 20.58% to 9.66% for B1.
Asphalt bridge deck pavements are highly susceptible to rutting, shoving, and interlayer slippage under high-temperature traffic conditions, where interlayer shear stress plays a decisive role. To clarify the coupled effects of thermal gradients and moving loads, this study developed a sequential three-dimensional thermo-mechanical finite element model for a double-layer pavement in Zhongshan, China. Field-recorded air temperature, solar radiation, sunshine duration, and wind speed were used to define transient thermal boundaries. The calculated temperature field was then transferred to a fully bonded moving-load model with dual rectangular contact areas and braking-induced longitudinal traction. Axle load, roadway slope, braking coefficient, and the thicknesses of the SMA-13 and AC-20 layers were varied. The predicted temperature fluctuation attenuated and the peak time was delayed with depth. The pavement surface reached 58.95 °C at 13:00, whereas the bottom of the asphalt overlay reached 46.99 °C at 17:00. Under the adopted 14:00 near-peak summer condition, increasing axle load amplified the overall response and raised the maximum asphalt-layer shear response from 0.172 to 0.223 Mpa. Roadway slope mainly affected traffic-direction stress transfer. Increasing the braking coefficient from 0 to 0.7 increased longitudinal shear response from 57.9 to 161.2 kPa in the asphalt layers and from 56.4 to 112.6 kPa near the AC-20/concrete interface. Increasing SMA-13 thickness reduced thermal and mechanical demand in the underlying layers, whereas increasing AC-20 thickness reduced the response near the concrete deck but shifted part of the tensile and shear demand toward the upper asphalt layer.
Headed stud connectors are critical components for ensuring composite action in steel–concrete composite structures. In practical infrastructure applications, welded headed studs may be subjected not only to interface shear forces but also to additional compressive actions induced by structural restraint, self-weight, traffic effects, and other service conditions. However, the influence of axial pressure applied along the stud height direction on the post-fatigue performance of stud-connected interfaces remains insufficiently understood. This study experimentally investigates the post-fatigue shear performance of welded headed stud connections subjected to different levels of axial pressure along the stud height direction. Nine push-out specimens were divided into three groups with axial pressures of 0, 20, and 40 kN applied to each specimen. A fatigue–static loading procedure was adopted, including initial static loading, intermittent static tests after every 400,000 fatigue cycles, and final static failure tests after two million fatigue cycles under a fatigue load range of 70–130 kN. The failure mode, load–slip response, total shear-transfer capacity, shear stiffness, and slip capacity were analyzed. The results show that all specimens maintained load-carrying capacity after two million fatigue cycles under the investigated loading conditions. The final failures were mainly characterized by shear failure at the root of the welded headed studs accompanied by local concrete crushing. Axial pressure improved the total shear-transfer capacity and shear stiffness of the stud-connected interfaces, while the ultimate slip capacity remained relatively stable. The enhancement is considered to be associated with improved interface interaction and local restraint effects, although these mechanisms cannot be independently quantified using the current test setup. These findings provide experimental evidence for evaluating welded headed stud connections subjected to combined axial pressure and fatigue loading within the investigated parameter range.
To address the technical challenges of hydration retardation and low early strength of foamed concrete in low-temperature environments of cold regions, this study investigated the effects of low-temperature curing (cycling between −5 °C and 5 °C) on the mechanical properties and microstructure of foamed concrete. Single-factor experiments were conducted to explore the effects of triethanolamine (TEA), urea, and polypropylene fibers (PPF) on the mechanical performance of foamed concrete. A response surface methodology (RSM) was employed to establish regression models between the dosages of each component and the compressive strength (CS), thereby determining the optimal mix proportion under low-temperature curing. The experimental results indicate that increasing the urea dosage leads to an increase in the flowability of foamed concrete, and the effects of the three types of admixtures on the CS all exhibit a non-linear characteristic that first increases and then decreases. The significance of the three factors on the CS of the material follows the order: TEA > PPF > urea. The obtained optimal mix proportion is 0.052% TEA, 1.08% urea, and 0.194% PPF, yielding 3, 7, and 28 d CS of 1.088 MPa, 1.342 MPa, and 2.301 MPa, respectively. Microstructural analysis via SEM observations and XRD analysis suggest that the admixtures effectively compensate for the hydration retardation induced by low temperatures, promoting the abundant generation of needle-like ettringite (AFt) and C-S-H gels that interweave into a dense network, thereby achieving higher strength. This study provides a theoretical basis and technical support for the low-temperature construction of foamed concrete subgrades in cold regions.
Pavement distresses play a pivotal role in evaluating roadway conditions and guiding maintenance strategies. In many instances, these distresses arise from construction deficiencies, substandard material quality, or inadequate maintenance practices, rather than from inherent design shortcomings. Understanding the interrelationships among different types of pavement distress is therefore essential for engineers and decision-makers seeking to enhance pavement performance and prolong service life. This study examines the statistical associations among various asphalt pavement distresses using association rule mining techniques. The dataset was collected from 18 regions in Lebanon, covering a total roadway length of 419.87 km, thereby enabling a comprehensive analysis. Ten primary categories of pavement distress were identified and analyzed using support, confidence, and Lift measures to quantify their co-occurrence patterns and dependency relationships. The results revealed strong statistical associations among most pavement distress types, with particularly strong interactions involving raveling and weathering, longitudinal cracking, alligator cracking, patching, and potholes. Raveling and weathering were the most prevalent distress factors, accounting for 20.88% of total occurrences, whereas block cracking was the least frequent, representing only 0.34%. The joint probability of raveling and weathering occurring with alligator cracking reached 37.38%, while the conditional probability of alligator cracking given the presence of raveling and weathering was 47.65%. Lift analysis further distinguished associations that were stronger than expected based on distress prevalence alone, thereby reducing the influence of frequency-driven relationships. These findings demonstrate the effectiveness of the proposed analytical framework in identifying statistically grounded pavement distress interactions and provide complementary information to support pavement management, maintenance prioritization, and resource allocation.
The post-earthquake damage state of reinforced concrete (RC) double-column piers directly affects bridge traffic capacity and emergency response efficiency. To improve the interpretability of damage assessment, this study proposes a Structural–Visual Integrated Evaluation (SVIE) framework that combines structural response analysis with image-based damage evidence. Structural responses from quasi-static tests are used to define four baseline damage states: intact-to-slight, moderate, severe, and critical damage. An improved DeepLabv3+ model is then applied to 315 global-scene images for end-to-end semantic segmentation of background, concrete spalling, and reinforcement exposure. The extracted visual evidence is used to verify its consistency with the baseline structural states. On the test set, the model effectively identified concrete spalling regions, achieving an IoU, F1-score, Precision, and Recall of 78.86%, 88.18%, 89.93%, and 86.49%, respectively. For reinforcement exposure, although IoU and Recall were relatively low because of sample scarcity and small-target characteristics, Precision reached 70.40%, indicating that detected regions can provide supplementary evidence for severe local damage. The consistency analysis showed that the morphology of visual damage was generally compatible with the progression of structural damage states. The results provide a laboratory-based proof of concept for a mechanically grounded and visually interpretable framework for rapid post-earthquake assessment of RC double-column piers.
Earthquake resilience is increasingly a problem of interactions across hazards, assets, infrastructure systems, and recovery processes [...]
To investigate the mechanical properties of coarse-grained soil in high-altitude mountainous areas, experimental research was conducted to explore the shear process, shear modulus, shear dilation, and stress axis rotation of coarse-grained soil under varying conditions. The sensitivity and mechanisms of these factors were also analyzed. The results indicate that increasing water content and fine particle content significantly diminish the strain-hardening characteristic, whereas dry density and normal stress augment this effect. Under shear stress, the samples exhibit pronounced non-uniform shear dilatancy. Elevated water content, fine particle content, and normal stress enhance shear contraction at the rear of the sample while suppressing shear dilation at the front. In contrast, dry density produces the opposite effect. The rotation of the stress axis initially follows a nonlinear growth pattern before transitioning to linear growth. The growth rate and ultimate rotation angle increase monotonically with water content, fine particle content, and normal stress but decrease with increasing dry density. Additionally, the shear modulus decreases exponentially with increasing water content and increases exponentially with dry density, fine particle content, and normal stress. Ultimately, normal stress is identified as the most sensitive factor, followed by dry density and fine particle content, with water content being the least sensitive. These findings can provide geotechnical parameters and a theoretical basis for the scientific prevention of high-altitude geological hazards. These findings can provide indoor mechanical parameters and deformation laws of coarse-grained soils for engineering.
The valorisation of industrial by-products as supplementary cementitious materials is a promising strategy to reduce clinker consumption and improve the sustainability of cement-based materials. In this study, the influence of submerged arc welding (SAW) slag on the hydration behaviour and microstructural evolution of cement pastes was investigated. Two SAW slags from different industrial sources were incorporated as partial replacements of ordinary Portland cement at 5%, 15%, and 30% by mass. Cement pastes were prepared with water-to-binder ratios of 0.3 and 0.4 and characterised through setting time, water demand, mercury intrusion porosimetry (MIP), differential scanning calorimetry (DSC), and X-ray diffraction (XRD). The results showed that SAW slag systematically delayed both initial and final setting times, while having only a negligible effect on water demand. Under the fixed mix conditions adopted in this study, this retardation is interpreted as the combined effect of clinker dilution and modified fresh-state conditions. MIP analysis revealed higher early-age porosity in SAW-containing pastes, particularly at high replacement levels and higher water-to-binder ratios, although mixtures with up to 15% slag approached the reference pore structure at later ages. Thermal analysis indicated lower bound water and portlandite contents at early ages, mainly due to clinker dilution, while long-term hydration development remained comparable at moderate replacement levels. At higher slag contents, some mixtures showed higher calcium carbonate contents, suggesting a tendency toward increased carbonate formation under the investigated conditions. Overall, the results indicate that SAW slag primarily affected early paste behaviour and pore structure development, with clinker dilution appearing to be the main mechanism, although weak secondary physical or chemical contributions cannot be completely excluded.
Surface-breaking cracks in concrete structures can accelerate deterioration by facilitating the ingress of moisture, chlorides, and other aggressive agents. Reliable characterization of crack depth is therefore essential for structural health monitoring and maintenance of concrete infrastructure. This study presents an ultrasonic common midpoint (CMP)-based approach for crack-tip localization and crack-depth characterization in concrete. Ultrasonic measurements were acquired using a pitch-catch configuration in which the transmitter and receiver were positioned symmetrically on both sides of surface crack while maintaining a fixed midpoint. Measurements obtained at multiple transmitter–receiver separations were processed to extract the time-of-arrival (ToA) associated with crack-tip diffraction. The measured ToAs were subsequently used within a travel-time-based localization framework to generate crack-tip images and estimate crack-tip coordinates. The proposed methodology was evaluated on concrete slabs containing vertical and inclined surface-breaking cracks of varying depths. In addition, the approach was applied to a reinforced concrete beam specimen containing thin cracks caused by flexural loading. The localized crack-tip positions from ultrasonic imaging are in good agreement with the observed crack depths and geometries. The proposed method offers a non-destructive approach for crack-tip localization and crack-depth characterization in concrete and may support condition assessment of concrete infrastructure.
Graded aggregates used in high-speed railway subgrades often undergo micro breakage (i.e., corner and edge spalling) under cyclic loading, whereas the mechanism linking local particle spalling to contact-network evolution and permanent deformation remains unclear. To address the lack of a physically based micro breakage criterion and a continuous local shape-updating scheme in existing DEM approaches, this study proposes an energy-driven micro breakage method. The method uses the relationship between contact elastic energy and fracture energy for newly created free surfaces as the breakage criterion. It also employs a radial function representation to simulate local particle shape evolution. The proposed method is subsequently validated through multilevel tests and shows reasonable agreement with the experimental results for particle micro breakage and the associated mechanical responses. Furthermore, dynamic triaxial simulation results show that micro breakage exhibits a distinct cumulative characteristic and increases with loading frequency and amplitude. Meanwhile, micro breakage drives particle rearrangement and new contact formation, leading to skeleton densification and weakening of the strong force-chain network, which in turn accelerates plastic deformation accumulation. These coupled processes constitute an important mechanism governing the progressive degradation of graded aggregates under cyclic loading. This study clarifies the associated particle-scale mechanism and provides a reference for performance optimization.
This study addresses maritime traffic risks in the Labuan Bajo–Komodo marine tourism corridor, a spatially constrained archipelagic environment characterized by mixed vessel traffic, intensive tourism activity, and high ecological sensitivity. An integrated decision-support framework was developed by combining the Analytic Network Process (ANP) with stakeholder-supported grid-based spatial risk analysis. Expert pairwise comparisons from eight respondents were used to evaluate eight interdependent criteria: Natural Conditions, Navigational Channel, Vessel Factors, Maritime Traffic Conditions, Port Control, Authority/Stakeholders, Tourism, and Environmental Impact. The ANP calculation was conducted using geometric mean group aggregation, consistency ratio assessment, and targeted follow-up clarification for matrices requiring refinement. The final ANP results show that Port Control received the highest priority weight (0.172), followed by Natural Conditions (0.148), Maritime Traffic Conditions (0.144), Environmental Impact (0.135), Vessel Factors (0.121), Navigational Channel (0.120), Authority/Stakeholders (0.104), and Tourism (0.0566). At the global subcriteria level, communication effectiveness, channel complexity, environmental compliance, local traffic density, and seasonal traffic variation emerged as the dominant contributors to risk. A stakeholder-supported partial spatial risk index (SRI) was then calculated for 21 grid cells using spatially mappable ANP criteria. The highest-risk cells were grids 3, 5, 6, 8, 9, 10, and 14, while sensitivity analysis confirmed that grids 3, 5, 6, 9, 10, and 14 remained high risk across all tested spatial-weight scenarios. The findings indicate that maritime traffic risk in Komodo National Park is not driven by environmental exposure alone, but by the interaction of traffic control capacity, natural hazards, traffic concentration, environmental sensitivity, and institutional coordination. The proposed framework supports spatially informed traffic management, environmental compliance, and emergency preparedness planning in marine protected tourism corridors.
Road infrastructure accounts for a substantial and systematically under-reported fraction of construction-related embodied carbon globally. Despite rapid network expansion across sub-Saharan Africa, no peer-reviewed study identified in the databases searched has established a quantified embodied-carbon baseline for Ghanaian road construction, creating a notable gap in national carbon accounting and low-carbon procurement policy. This study addresses that gap through two integrated components: a PRISMA 2020-guided systematic review of road-LCA and embodied-carbon literature, and a first-pass scenario model for Ghanaian low-volume paved roads (LVRs) bounded at A1–A3 (cradle-to-gate). Database searches of Scopus and Web of Science (14 March 2026) returned 3193 records; following deduplication and two-stage screening, 574 studies were included in the review. A staged harmonisation procedure converted 211 benchmark-shortlisted studies to comparable units, yielding a harmonisation subset of 29 studies and a final benchmark pool of 10 studies expressed as kgCO2e per lane-kilometre (3.5 m lane width). The scenario model applies emission factors from the ICE Database (Educational V4.1, 2025) to three pavement configurations drawn from the Ghana Manual for Low Volume Roads (Parts B and D), all surfaced with double bituminous surface treatment (DBST); Otta seal is evaluated as a sensitivity case. Results show A1–A3 embodied carbon of 14,165 kgCO2e/lane-km for Scenarios S1 and S3 (SC2/TLC 0.01 and SC4/TLC 1.0, respectively) and 12,564 kgCO2e/lane-km for Scenario S2 (SC3/TLC 0.3). Bituminous binder accounts for 30–34% of A1–A3 emissions despite representing less than 1% of pavement mass, identifying binder supply as the primary carbon lever. The two most structurally comparable benchmark studies, chip-seal treatments in the USA, bracket the Ghana values at 12,687–16,400 kgCO2e/lane-km, providing external plausibility validation. To the best of our knowledge, this study delivers a peer-reviewed, reproducible A1–A3 (cradle-to-gate) carbon baseline for Ghanaian LVR construction, a PRISMA-compliant synthesis of road embodied-carbon evidence, and a documented framework for early-stage carbon benchmarking in West African road infrastructure planning.
