Search Results (2,427)

Last-mile delivery systems are under greater pressure to deliver cost-efficient, reliable, environmentally friendly, and resilient services amid operational challenges. Distance/cost is the usual optimization criterion for traditional vehicle routing methods, and factors related to disruptions, such as the delay frequency, delay severity, and delivery failure risk, are often treated separately or neglected. This study proposes a green-resilient last-mile delivery optimization framework that integrates operational costs, delivery delays, carbon emissions, and operational risk within a single multi-objective decision model. The proposed framework models the capacitated vehicle routing problem with time windows, accounting for vehicle capacity, service time commitments, fuel consumption, emission-level estimates, working hour limits, and lateness penalties and incorporating a disruption-based operational risk score. The risk score is based on the delay frequency, delay severity, and failure probability and can inform routing decisions based on efficiency and resilience. The framework is tested with a case study of urban last-mile delivery and compared with several benchmark scenarios: the current operational plan, a distance-based vehicle routing problem (VRP), a cost-based VRP, a green VRP, and a delay-aware vehicle routing problem with time windows (VRPTW). The results reveal balanced improvements in key performance indicators, in line with the proposed framework. It reduces the total distance by 35.11%, total operational cost by 34.01%, fuel consumption by 10.46%, CO₂ emissions by 9.34%, estimated late orders by 93.45%, and total delay minutes by 80.10%, and there are no working hour violations compared to the current case. Other sensitivity, weight, and ablation analyses illustrate the trade-offs among cost/service reliability/environmental goals and risk exposures. The results show that operational risk can be incorporated into the green last-mile routing problem to facilitate more comprehensive—and thus more robust and sustainable—delivery planning in the context of disruptions in urban environments. Full article

Optical ground wire (OPGW) cables are subjected to extreme electromagnetic stresses from lightning and short circuits. Existing models have three main limitations: (i) they assume uniform current distribution, (ii) they use constant material properties, and (iii) they do not couple the electromagnetic, thermal, and mechanical domains. This paper proposes a coupled multiphysics model that incorporates non-uniform current distribution with ${\mu }_r$ dependent on the magnetic field, temperature-dependent properties, and differentiated failure criteria. The model was implemented in COMSOL Multiphysics and was validated against experimental short-circuit tests (15–30 kA) conducted at the HPT-Laboratory (FEC). For the lightning scenario (10/350 μs impulse), the model predictions were compared with experimental results reported in the literature, showing good agreement in temperature rise and damage patterns. Results show that including a non-uniform current distribution modifies the predicted maximum temperature by 15.8% and shifts its location from the center to the outer aluminum layers. The model reproduces the experimental temperature with an RMSE of <7 °C and a relative error of <8%. A combined failure criterion (thermal + mechanical) predicts strand breakage with 89.2% accuracy, outperforming the purely thermal (72.5%) and mechanical (78.3%) criteria. Specific $I-t$ and $I^{2}t$ curves were generated for two commercial OPGW cable configurations (Manufacturer A and Manufacturer B), with $I^{2}t$ capacities at 500 ms of 128 kA²s and 98 kA²s, respectively. The proposed model provides a useful tool for protection selection and coordination in transmission lines with OPGW cables. Full article

Reliable data collection is essential for disaster-oriented Internet of Things (IoT) systems, where damaged terrestrial communication infrastructure often leaves sensed data buffered at disconnected end devices. In Unmanned Aerial Vehicle (UAV)-Internet of Things device (IoTD) collaborative data collection, random UAV faults and limited energy and buffer resources further complicate mission execution, making fault-tolerant scheduling crucial for robust data recovery. To address these issues, a unified framework is developed by integrating dynamic UAV reliability modeling, Maximum Distance Separable (MDS)-coded fault-tolerant backup, and collaborative scheduling optimization. Within this framework, a data fault-tolerance mechanism, termed MFTB, and a bilevel collaborative scheduling algorithm, termed LP-DCFS, are proposed. Simulation results indicate that, in the evaluated scenarios, the proposed methods achieve better overall performance than the considered baselines. In a representative high-load, high-failure scenario, MFTB reduces data loss by 4.8% and 37.5% compared with Buffer-Limited Retransmission (BLR) and Replication, respectively, while LP-DCFS increases the amount of recovered data by 33.9%, 32.3%, and 53.1% compared with ACEPSO, ADE-DMRM, and DQN, respectively. Under the modeled independent random crash and non-return faults and the evaluated simulation settings, these results suggest that coordinating failure-risk characterization, data-protection mechanisms, and task-scheduling strategies can improve the robustness and data-recovery capability of disaster-oriented UAV-assisted data collection. Full article

Dam-break floods pose severe threats to downstream urban areas due to their sudden onset, rapid propagation, and potentially catastrophic socioeconomic consequences. This study develops a multi-indicator fuzzy comprehensive evaluation framework for urban flood risk assessment under dam-break scenarios. The framework integrates hydrodynamic simulation outputs with geographic information system-based spatial analysis to characterize spatial variations in flood risk. It incorporates flood hazard factors (inundation depth, arrival time, and inundation duration) derived from a coupled one-dimensional/two-dimensional hydrodynamic model and socioeconomic vulnerability factors (population density and road network density) derived from spatial statistics. Indicator weights were determined using a combined Analytic Hierarchy Process and entropy-weight method, and risk levels were obtained through membership-function calculation and spatial overlay analysis. The framework was applied to the Dongpu and Dafangying reservoirs in Hefei, China, under a scenario of simultaneous dam failure during a probable maximum flood. Results show that, compared with hazard-only assessment, the comprehensive evaluation substantially reduced the extent of high-risk areas and altered their spatial distribution. Very high-risk zones were concentrated along the upstream main channel, where high-velocity floodwaters coincide with dense population and economic activity. Flood arrival time and population density were identified as the most influential indicators in the proposed risk assessment framework. The proposed framework provides a more comprehensive and spatially refined tool for urban dam-break flood risk management and emergency decision-making. Full article

Drought stress is a major environmental factor limiting plant growth and distribution, with severe drought leading to plant mortality. This study investigates the physiological mechanisms underlying drought-induced mortality in one-year-old seedlings of the valuable timber tree species Phoebe bournei (Hemsl.) Yang, aiming to clarify the relative roles of hydraulic failure and carbon starvation. A 51-day controlled pot experiment was conducted to simulate progressive drought using 10 experimental groups (n = 6): a well-watered control and four drought treatment groups harvested at key physiological stages. Stage I (baseline) corresponded to a relative soil water content of approximately 89%. Stage II (photosynthetic cessation) was reached after approximately 15 days of water withholding, at a relative soil water content of approximately 60% and a predawn leaf water potential of approximately −3.4 MPa. Stage III (complete leaf wilting) was reached after approximately 36 days of water withholding. Stage IV (stem browning) occurred at a relative soil water content of approximately 18%, after approximately 45–51 days of water withholding. We systematically measured key physiological parameters, including leaf water potential, gas exchange parameters, the percentage loss of xylem conductivity in stems, and the concentrations of non-structural carbohydrates (including soluble sugars and starch) in different tissues. Results showed that stomatal conductance and net photosynthetic rate approached zero when leaf water potential fell to approximately −3.4 MPa. Stem percentage loss of xylem conductivity increased significantly with advancing drought, exceeding 75% at complete leaf wilting and reaching over 98% at stem browning, reflecting a near-complete loss of xylem hydraulic conductance. Concurrently, non-structural carbohydrate concentrations underwent transient accumulation during early drought, reflecting sink-limited carbon dynamics, followed by progressive depletion. Notably, partial non-structural carbohydrate reserves persisted even at the stem browning stage, suggesting that these reserves may have become physically inaccessible or metabolically unavailable rather than entirely exhausted. The findings point to a tightly coupled, sequential interaction between hydraulic failure and carbon starvation across the drought progression. The findings will provide a scientific basis for evaluating drought tolerance, informing adaptive management practices, and ensuring the sustainable cultivation of P. bournei under future climate scenarios. Full article

Failures and leakages in water distribution pipelines affect the sustainable operation of water supply systems. While water losses caused by leaks are widely recognized, their impact on soil stability and internal erosion processes remains insufficiently investigated. This study examines water flow velocity distributions in soil around leaking water pipes regarding suffosion risk. Numerical simulations were performed using the FEFLOW software for four scenarios combining two pipe diameters and two internal pressure levels. Each scenario assumed circumferential leakage with continuous water outflow into the surrounding soil. The numerical model was validated through field experiments conducted on four experimental setups. The simulation results showed that flow velocities near the pipe exceeded critical values in all scenarios, indicating a risk of suffosion. Although hydraulic pressure and leakage area significantly affected local flow velocities, their influence on the extent of the potential suffosion zone was negligible. In all cases, the zone where critical velocities were exceeded extended more than 1.5 m from the leakage location. The results highlight the importance of considering suffosion risk in the operation and risk assessment of sustainable water supply systems. They also indicate that this hazard should be taken into account during the design stage, particularly when selecting pipeline routes and assessing ground conditions. Full article

Film-mulched drip irrigation (FMDI) is used increasingly for cotton (Gossypium hirsutum L.) production in arid regions. However, salts often accumulate in the soil, eventually leading to soil salinization and crop failure when using FMDI with brackish water inappropriately. Evaluation of the leaching requirement (LR) for cotton under FMDI with brackish water that comprehensively considers cotton yield, water saving, soil conditions, and economic benefits needs to be investigated more completely. The present study compared the cotton growth for different leaching fractions (LF) under FMDI with brackish water and provides comprehensive analysis of LR for cotton and its relationships with soil conditions. A higher LF was related to a lower cotton yield when the LF was larger than 0.15. Moreover, a larger LF led to a lower ratio of reproductive growth and irrigation water productivity when the LF was larger than 0.2. A high soil water content (SWC) strip was observed in the 40–60 cm soil layers for all scenarios. Moreover, a higher SWC proportion in the deeper soil layers as for LF_0.15 or LF_0.2 may also be beneficial to cotton growth. Soil salinity decreased with decreases in irrigation water quantity when the LF was lower than 0.2, but increased when the LF was higher than 0.2. Either too much or too little irrigation water was not beneficial from an economic perspective. Our study indicated that the LR values between 0.05 and 0.15 were recommended for FMDI when the total dissolved solids for brackish water is within 1.61–3.21 g L⁻¹. Integrated strategies, including optimized irrigation-fertilizer management, groundwater depth monitoring, and halophyte intercropping, are required to sustain production while mitigating secondary salinization and groundwater pollution under FMDI with brackish water. Full article

To address ecological security challenges in karst urban agglomerations, this study proposes a green infrastructure network (GIN) optimization framework that integrates geological characteristics with complex network theory. A fracture-modified minimum cumulative resistance (FM-MCR) model, coupled with an ant colony algorithm, was developed to enhance GIN extraction accuracy. Using a cascade failure model, the structural response of the GIN under simulated attack scenarios was systematically evaluated across four edge enhancement strategies, enabling spatial layout optimization. Network clustering and node centrality assessments were further applied to identify critical corridors and strategic nodes. Results identified 108 ecological sources, with Qiannan contributing the largest area (3141.97 km², 23.96% of the total), and 162 corridors in the original GIN. Among the four edge enhancement strategies, the low-degree-first (LDF) strategy significantly improved network robustness, decreasing percolation thresholds by 20.9%, 22.98%, and 16.99% under random, degree, and betweenness attacks, respectively. Network cluster analysis further delineated 45 GIN clusters, 19 critical corridors, and 11 strategic nodes, revealing cross-scale ecological hubs linking the Wumengshan–Daloushan corridor with Guiyang’s urban green wedge. This framework, characterized by geological correction, dynamic edge enhancement, and cluster-based management, offers a scientific basis for improving GIN resilience in karst regions. Full article

Background: Thyroid function tests are frequently requested, but manufacturer reference intervals often lack age- or sex-based stratification. This study established indirect reference intervals for thyroid stimulating hormone (TSH), free thyroxine (fT4) and free triiodothyronine (fT3) in a large adult population. We evaluated unsupervised algorithms and conventional partitioning to identify subgroups, compared multiple limit estimation methods, and assessed the diagnostic performance of the derived intervals against an independent, clinically defined external validation cohort. Methods: Data from 37,255 adults (age ≥ 18) collected between 2022 and 2024 were analyzed; a reference population of 5870 individuals was established following standardized exclusion criteria. Age-based subgroups were identified through hierarchical clustering with the Elbow method, and variable importance was assessed using Random Forest analysis. Reference intervals were calculated using non-parametric, Bhattacharya, refineR, and reflimR algorithms, applied to three population frameworks: (1) the total population without stratification, (2) subgroups derived from hierarchical clustering and (3) subgroups defined by the conventional Harris–Boyd partitioning method. Diagnostic performance was subsequently evaluated in an independent external cohort (National Health and Nutrition Examination Survey [NHANES]; N = 2297) for all estimated reference intervals. Three classification scenarios were assessed: TSH-only, fT4-only, and combined TSH + fT4, with sensitivity, specificity, Youden index, and decision curve analysis performed for each. Results: Random Forest analysis identified age as the dominant variable influencing TSH, fT4 and fT3 distributions (mean decrease in accuracy: TSH 41.62, fT4 44.18, fT3 43.7), while sex showed the lowest impact. Clustering yielded six age-based subgroups for analytes. Harris–Boyd partitioning yielded six age-based subgroups for TSH, two sex-based subgroups for fT4, and six combined age-and-sex subgroups for fT3. TSH limits were broadly concordant across all three approaches (six-subgroup partitioning: 0.36–0.68 to 4.75–5.67 mIU/L). For fT4, conventional (sex-based) and clustering (age-based) partitioning produced similar ranges (11.33–20.08 pmol/L), except reflimR’s notably lower limit (10.90 pmol/L). For fT3, conventional (age + sex) and clustering (age-only) partitioning showed comparable ranges (3.36–7.03 pmol/L), with clustering revealing a clearer age-related decline in the oldest group. Diagnostic performance varied markedly by analyte. TSH-only classification achieved positive discrimination across all 13 methods (Youden index: 0.173–0.239). In contrast, fT4-only and combined TSH + fT4 classifications performed at or below chance for most methods, with 75% of the cohort falling outside fT4 reference intervals, indicating an inter-platform harmonization issue rather than a partitioning failure. Decision curve analysis confirmed TSH-only classification’s superiority, exceeding universal testing from pt ≈ 0.20 onward across all methods. Conclusions: Age-stratified reference intervals combined with limit estimation showed potential diagnostic advantages over manufacturer and non-stratified intervals; however, an independent external validation using a clinically defined outcome indicated that this advantage was not consistently reproduced and was dependent on the clinical decision threshold considered. These results suggest that age stratification and algorithm choice merit further clinically adjudicated validation before broad clinical adoption, and that unsupervised clustering offers a practical, objective alternative to manual subgrouping for laboratories pursuing this approach. Full article

Tuned viscous mass dampers (TVMDs) are effective devices for wind-induced vibration control in supertall buildings, but their performance depends on a precise resonance condition that can be disturbed by manufacturing tolerances. This study identifies an insufficiently examined asymmetric sensitivity mechanism, termed the “dangerous diagonal effect”, in which opposite-sign errors in TVMD inertance and stiffness amplify tuning-frequency drift and create a worst-case sensitivity space that conventional symmetric uncertainty models may underestimate. To tackle this challenge without requiring prior statistical distributions unavailable at the design stage, an Info-Gap Decision Theory (IGDT) robust optimization framework tailored to TVMDs under stochastic wind excitation is developed. A Kriging-metamodel-assisted Efficient Global Optimization bi-level strategy reduces the computational burden of the nested worst-case search. Applied to a 76-story, 306 m benchmark building under a dual-criterion constraint combining the ISO 10137 comfort limit and a 30% relative degradation bound, the framework certifies comfort compliance for manufacturing errors up to 23.44% along the dangerous-diagonal direction. Under the most severe coupled degradation scenario, which integrates opposite-sign manufacturing detuning, 50-year power-law aging, and Arrhenius thermal drift, the nominal H₂-optimal design collapses to 36.7% vibration reduction efficiency while the IGDT robust design sustains 51.7%, reducing the Monte Carlo failure probability from 3.8% to 1.2% across 500 random realizations. An aeroelastic wind tunnel campaign spanning 620 detuning configurations on a 1:350 scaled model provides physical validation of IGDT design reliability for a TVMD system. The experiments corroborate the dangerous-diagonal sensitivity asymmetry, support the predicted robustness plateau under severe parameter detuning, and show that the IGDT framework maintains comfort compliance where the H₂-optimal design fails. Full article

Coastal and offshore steel infrastructures such as transmission towers and wind turbine towers are prone to coating degradation after long-term exposure to salt fog, high humidity, and ultraviolet radiation. The subsequent uniform corrosion significantly reduces the cross-sectional load-carrying capacity and threatens structural safety. This paper presents a numerical parametric analysis on the compression behavior of circular steel tube (CST) members subjected to uniform corrosion induced by coating failure, based on 18 accelerated corrosion tests. The effectiveness of the wall thickness reduction method for simulating uniform corrosion after coating degradation is verified, and the influence of key parameters on load-carrying capacity degradation is systematically investigated. A simplified formula for elastic local buckling of corroded CSTs is derived, and a direct strength method (DSM) calculation framework considering both global buckling and local–global interactive buckling is established. The results show that the uniform corrosion ratio is the dominant factor affecting load-carrying capacity degradation, while sectional dimension, slenderness ratio, and eccentricity have negligible influence. The proposed DSM method achieves a prediction error within 5% compared with test and numerical results. It is primarily applicable to uniformly corroded steel tubes represented by equivalent wall thickness loss, and its applicability to scenarios with localized corrosion, pitting corrosion, weld-zone corrosion, or non-uniform wall thickness reduction requires further validation. This method provides a rapid and accurate tool for residual load-carrying capacity assessment and life cycle management of coastal steel infrastructures after coating failure. Full article

The transition to a decarbonized energy infrastructure relies on repurposing existing pipelines for hydrogen–methane mixtures, which introduces significant concerns regarding hydrogen embrittlement. Accordingly, a coupled Multiphysics phase-field model was developed to predict hydrogen-assisted failure in elastic–plastic solids. This framework is numerically implemented via the finite element method to predict the structural integrity of pipeline steel strength classes representative of API 5L X65, X70, and X80 by explicitly accounting for elastoplastic deformation, hydrogen trapping effects, and stress-driven diffusion. By computing crack growth resistance curves across various scenarios, it has been demonstrated the capability of the model to capture material sensitivities by varying hydrogen–methane blend compositions, operational pressures, and the elastoplastic deformation behavior of different strength grades. The investigation revealed that methane limits surface hydrogen coverage, thereby mitigating the crack-tip decohesion mechanism. Furthermore, the model indicates that at a pressure of 7.5 MPa, a 15 vol% hydrogen–methane blend enables these materials to retain 80–90% of their fracture toughness and exhibit ductile failure. Finally, higher-strength steel classes (representative of X80) demonstrate greater susceptibility to hydrogen embrittlement under these conditions due to yield stress-amplified hydrostatic stress, whereas lower-strength steels exhibit greater defect tolerance for the hydrogen-blend transition. Full article

This study presents an empirical fleet-level assessment of 110 autonomous-range trolleybuses using anonymized records collected over 12 months. The dataset comprises 40,150 vehicle-day operating records, 40,150 energy records, 3960 pack-month SOH records, and 584 maintenance, failure, and downtime events. Outcomes are reported in absolute units: RUB/km for LCC, kg CO₂-eq/km for ELC, events per 100,000 km, and downtime hours per 10,000 km. Autonomous operation accounted for 24.5% of mileage. Average net energy consumption was 1.520 kWh/km, whereas mode-distributed gross energy was 1.521 kWh/km in contact-supply mode and 1.752 kWh/km in autonomous mode. The daily-energy model achieved a full-sample fit of R² = 0.860 and MAPE = 8.119%. Validation of vehicle-grouped data using the generated dataset showed R² = 0.842 and MAPE = 8.74%. Mean SOH decreased from 89.98% to 85.94%, accompanied by higher internal resistance. In the central 6.5-year scenario, diagnostic-gated strategy B2 reduced estimated LCC from 29.52 to 26.16 RUB/km. The event-weighted control effect by RPN decreased from 125.4 to 80.4 (35.9%). Baseline ELC decreased only from 0.6646 to 0.6594 kg CO₂-eq/km because operational electricity dominated the total. The contribution is an observation-linked framework that integrates vehicle-day operation, pack-month diagnostics, and event-level maintenance data to compare cost, emissions, and risk under explicit battery-eligibility and service-coverage constraints. The novelty is therefore the empirical, observation-level coupling and joint calibration of existing energy, battery-condition, life-cycle, and reliability methods within one auditable fleet workflow, rather than the introduction of a new standalone degradation or reliability model. Full article

Press-pack insulated-gate bipolar transistor (IGBT) devices are key components of modular multilevel converter (MMC)-based HVDC systems, yet the parallel connection of tens of chips inside one sealed housing makes their internal aging difficult to monitor—existing methods cannot determine which chip or thermal interface has degraded without invasive sensing. This paper proposes a two-layer aging condition monitoring framework based solely on non-invasive external case temperature measurements, comprising an online detection layer and a detection layer. For the diagnosis layer, a coupled thermal network state-space model of the press-pack module is established; its observability matrix is shown to be of full rank, proving that aging at any internal location is detectable from external case temperatures, and a steady-state sensitivity analysis reduces the required measurement to the module-center case-temperature pair and yields a failure-signature rule that discriminates five aging modes. A 3D electrothermal finite-element model, validated against fiber Bragg grating (FBG) measurements on an MMC sub-module with deviations below 1.2 °C at all load levels, is then used to build an aging fingerprint database of 270 scenarios that maps a measured case-temperature distribution to the aging location, the affected component, and the severity of any cooling-system degradation. For the detection layer, a deep neural network (DNN) trained only on healthy-state data provides online early warnings through its prediction residual. Experiments on a 2.2 kV/2100 A MMC sub-module platform and a solid-state DC–DC transformer platform confirm that cooling-system degradation is reliably detected and that the detection layer transfers across converter types. Even in the least sensitive aging case, the predicted case-temperature signature (0.036 °C) exceeds the 0.01 °C resolution of standard thermocouple instrumentation, which indicates that genuine device aging would be resolvable as well. The framework provides a non-invasive online health-monitoring solution that can also locate the degraded element in high-power press-pack devices. Full article

Motorcyclists are among the most vulnerable road users at roundabouts, particularly in mixed-traffic environments where rider behaviour may be influenced by geometric design. This study investigates the association between roundabout geometry and risky motorcyclist behaviour using the Chi-squared Automatic Interaction Detection (CHAID) method. Video-based observations were conducted at four selected roundabouts in Kuching, Sarawak, Malaysia, generating 15,937 risky-behaviour events from 5400 observed motorcyclists. Six risky-behaviour categories were analysed, covering entry, circulation, and exit manoeuvres. The CHAID results showed that entry radius was the primary geometric factor associated with risky motorcyclist behaviour, while exit radius and exit width acted as secondary variables under specific entry-radius conditions. Four behavioural scenarios were identified. Entry radii of 15–32 m were associated with mixed risky-behaviour patterns, with lane splitting during circulation being the most frequent behaviour. Entry radii of 37–40 m combined with exit radii ≤ 12.43 m were associated with failure to signal before exiting. Entry radii of 43–49 m combined with exit radii ≤ 25.3 m were associated with improper lane positioning when exiting. Larger entry radii of 49–64 m combined with exit widths of 7.38–9.06 m were associated with close stopping or potential blind-zone positioning. The model validation results indicated moderate internal classification performance, supporting the use of CHAID as an interpretable threshold-identification tool rather than a high-precision predictive model. The findings demonstrate that risky motorcyclist behaviour at roundabouts is shaped by non-linear interactions between entry and exit geometric elements. From a sustainability perspective, these results provide preliminary evidence for behaviour-sensitive roundabout design, safety assessment, and policy-oriented geometric improvements that support safer and more inclusive urban transport systems in motorcycle-dominant mixed-traffic contexts. Full article