Search Results (512)

Surface faulting poses an earthquake-related hazard with direct consequences for infrastructure and high-risk facilities. Probabilistic Fault Displacement Hazard Analysis (PFDHA) is widely used to estimate the annual frequency of exceedance (AFOE) of specific displacement values at sites on or near active faults. This approach requires numerous input parameters related to fault characterization and coseismic displacement distribution, yet few studies have examined how these parameter choices affect hazard results. Thus, we conduct an analysis following a One-At-a-Time (OAT) strategy, in which a single parameter is varied with respect to three kinematic-specific baselines. We explored the PFDHA outputs obtained allied to the broadly adopted regression models and scaling laws available in the literature up to 2023. We compared the hazard curves obtained for principal faulting from each calculation to a baseline parametrization, and we computed the percentage difference in AFOE, given a displacement amount, with respect to such a baseline. We obtained values in the interval −100% to +200%, computed within the displacement interval adopted for the hazard calculation, attesting that empirical regressions contribute significantly to hazard curve variations. Our sensitivity study could inform operative choices by practitioners and provides insights for optimizing data acquisition efforts in fault displacement hazard assessments. Full article

Accurately capturing muscle behavior remains a challenging task in computational biomechanics, primarily due to the nonlinear response, anisotropy, and time-dependent characteristics of muscle tissue. In this context, finite element methods have proven to be a suitable framework for representing such complex mechanical behavior. Among the available constitutive approaches, Hill’s three-element model continues to be widely adopted, largely because it offers a reasonable balance between physiological interpretability and computational efficiency. In this work, a parametric and sensitivity-oriented analysis of the Hill three-element muscle model is performed within a finite element formulation originally proposed by Kojić, Mijailović, and Zdravković (1998) and implemented in the PAK software environment. The analysis considers five key parameters, which are varied independently: the stiffness parameter of the series elastic element (α), the corresponding stress scaling parameter (β), the modulus of the parallel elastic element (E), the activation level (a), and the length ratio constant (k). To enable comparison between parameters of different physical nature, normalized sensitivity indices are used. The results show that the activation parameter a has the strongest influence on active force generation, with an increase of 36.4% at the highest considered activation level. In contrast, parameters α and β primarily affect the behavior of the series elastic component, with variations on the order of ±15–18%. It can also be observed that the influence of individual parameters depends on the deformation regime. At lower deformation levels, the response is mainly governed by the parameter E, while α and β become more relevant in the intermediate nonlinear range. At higher deformation levels, the activation parameter a becomes dominant. From a modeling perspective, these findings suggest a structured approach to parameter calibration in Hill-type finite element models. In addition, they provide further insight into the sensitivity characteristics of such formulations within computational biomechanics. Full article

Landslides are a recurrent geohazard in Andean urban environments, where weak soils, intense seasonal rainfall, and unplanned urban expansion combine to increase slope vulnerability. In such settings, sustainable hillside management requires stabilization strategies that are both technically effective and environmentally compatible. This study evaluates the effect of root reinforcement by vetiver grass (Chrysopogon zizanioides) on slope stability in two representative soils from Loja, Ecuador: sandy silt (SM) and sandy clay (SC). A reduced-scale physical model with 30 days of root development was established, and consolidated–drained direct shear tests (ASTM D3080/D3080M-23) were performed to determine the shear strength parameters under bare and vetiver-reinforced conditions. These parameters were then incorporated into numerical slope stability analyses using Slide and PLAXIS 2D, considering three slope angles (30°, 45°, and 50°), six root-positioning configurations, and hydraulic conditions with and without a water table. Vetiver increased effective cohesion by 22.7% in sandy silt and 19.0% in sandy clay, while the internal friction angle increased by 21.8% and 12.2%, respectively. Across all modeled scenarios, vetiver produced a consistent improvement in the factor of safety. The most critical case, corresponding to sandy silt at 45° with a water table, increased from FS = 0.841 in the control condition to FS = 1.309 under the full-coverage configuration. Parametric sensitivity analysis yielded coefficients of variation between 4.97% and 7.03%, indicating a stable model response under controlled parameter perturbations. These findings support vetiver as an experimentally grounded and environmentally sustainable Nature-based Solution for slope stabilization and provide relevant evidence for sustainable management of hazard-prone urban hillsides in vulnerable Andean settings. Full article

Progesterone (P4) exerts important vascular and immunomodulatory effects that influence platelet (PLT) activation and serotonin (5-HT) handling across mammalian species; nevertheless, its role in modulating PLT physiology during diestrus in mares remains poorly defined. This study hypothesized that physiological variations in luteal activity during diestrus are associated with changes in PLT activation and 5-HT-related parameters. The first objective was to determine whether changes in circulating P4 during diestrus are associated with alterations in PLT aggregation, circulating 5-HT, and PLT morphological indices in healthy mares; the second objective was to identify a diestrus day providing consistent physiological conditions for assessing PLT-related biomarkers. Twenty clinically healthy Spanish Purebred mares aged 4–9 years old were monitored. Blood samples were collected on days 5, 14, and 16 post-ovulation, with luteal status confirmed by ultrasonography. P4 concentrations were determined using a solid-phase I-125 radioimmunoassay (RIA), 5-HT concentrations were quantified using a competitive enzyme immunoassay, and PLT indices were measured using an ADVIA 2120i hematology analyzer. Data were compared using appropriate parametric or non-parametric tests after assessing distribution, and correlations were analyzed using rank-based correlation analysis, using Pearson or Spearman coefficients according to variable distribution. P4 concentrations were higher on days 14 and 16 compared with day 5 (p < 0.05), with no significant differences between days 14 and 16. Platelet aggregates (AGREG) showed the greatest variation, with significantly higher values on day 14 compared with day 5 (p < 0.05). In contrast, circulating 5-HT and all PLT morphological indices (PLT count, PCT, MPV, PLCR, PDW, PCDW, MPM, and PMDW) remained unchanged across diestrus. PLT aggregation showed a strong positive association with circulating P4 concentrations (r = 0.88, p < 0.05), whereas no meaningful correlations were observed between 5-HT and AGREG or between 5-HT and PLT morphological parameters. Internal correlations among PLT indices followed expected biological patterns, confirming the stability of structural PLT traits over short physiological intervals. These findings demonstrate that during diestrus, PLT activation—but not PLT morphology or circulating 5-HT—varies in parallel with P4 in mares. Day 14, corresponding to mid-diestrus, characterized by high luteal activity, represents an informative time point for assessing PLT activation and related biomarkers, providing a framework for standardizing sampling protocols for PLT-derived products in equine reproductive medicine. Full article

Hexapod robots are attractive for operation in cluttered and uneven environments, but their walking stability is strongly affected by the coupled effects of leg morphology and foot-end trajectory planning. In many existing designs, leg-segment proportions, reachable workspace, and swing-phase trajectory smoothness are considered separately, which makes it difficult to clarify how structural parameters and motion planning jointly influence locomotion stability. To address this issue, this study presents a spider-leg-inspired hexapod robot with a simplified three-degree-of-freedom leg configuration. Selected functional characteristics of spider legs, including segmented limb structure and compliant distal contact, were abstracted into an engineering-feasible hexapod platform rather than directly reproducing spider anatomy. A parametric workspace analysis was conducted under a fixed total leg length to compare six candidate femur-to-tibia ratios. Based on forward reach, vertical foot-lifting capability, stride potential, and structural compactness, a 4:6 femur-to-tibia ratio was selected. In addition, an eleventh-order Bézier curve was developed for swing-phase foot trajectory planning and compared with a conventional composite cycloid trajectory under identical tripod-gait conditions. Simulation and straight-line walking experiments showed that the Bézier-based trajectory reduced body-attitude fluctuation and produced smoother angular-velocity variation than the composite cycloid trajectory. The results indicate that the proposed structural design and Bézier-based trajectory can improve flat-ground walking stability of the hexapod robot. This work provides a practical reference for biomimetic structural design and gait-trajectory optimization of multi-legged robots, while further validation on more complex terrain remains necessary. Full article

The reliability of engineering structures is essential to ensure safety, durability, and sustainability. In reinforced concrete (RC), shear resistance is one of the most uncertain design aspects due to the natural variability of material properties and construction quality. Conventional design methods defined by Eurocode rely on characteristic values and partial safety factors that may not reflect the actual performance of in situ concrete. This study proposes a probabilistic framework for shear assessment that integrates material variability derived from conformity testing. Statistical parameters, including mean value and coefficients of variation (COV) of compressive strength, are incorporated into comparative reliability analysis using the First-Order Reliability Method (FORM) and Latin Hypercube Sampling (LHS). Parametric analyses are performed to quantify the influence of material variability on the reliability index β and failure probability $P_f$. The effect of varying the coefficient of variation (CoV) of the concrete compressive strength is investigated in the range from 0.01 to 0.2, both under the assumption of statistical independence and with consideration of correlation between selected variables. The sensitivity analysis is carried out to provide clear insight into the influence of uncertainty in the input parameters on the reliability of the considered limit state. The proposed framework provides a more realistic representation of structural safety and supports data-driven, performance-based management of concrete infrastructures. Full article

This article addresses the challenge of positioning accuracy in robotic manipulators applied to automated tape placement (ATL). A hybrid control strategy is proposed that integrates a Proportional-Integral-Derivative (PID) controller with a Backpropagation Neural Network (BP-NN). The proposed approach, called PID + NN, acts as a robust control scheme designed to compensate for parametric uncertainties and unmodeled perturbations arising from the integration of high-inertia tools in the end effector, dynamic mass variation due to tape consumption, and external reaction forces during the compaction process. Within this framework, the PID controller manages the nominal dynamics of the system, while the neural network operates as an adaptive compensator that adjusts the control signal in real time to minimize trajectory tracking errors. A rigorous stability analysis based on Lyapunov theory is presented, and the results are validated through numerical simulations on a six-degree-of-freedom manipulator. In addition, experimental tests are performed in a real operating environment to verify the practical performance of the strategy. The experimental results indicate that the proposed PID + NN controller significantly improves trajectory tracking accuracy, achieving a substantial reduction in tracking error and smoother control torque profiles compared to the conventional PID controller. These findings validate the effectiveness and robustness of the method for advanced manufacturing applications that demand high precision. Full article

This study evaluates the economic feasibility of retrofitting split-type air-conditioning systems in a university administrative building in a hot-humid tropical climate in Colombia, addressing the need for cost-effective energy-efficiency strategies in such contexts. A measurement-calibrated building energy model was developed using DesignBuilder and EnergyPlus, and a baseline scenario with low-efficiency fixed-speed split units was compared against three retrofit scenarios with higher-efficiency units defined by market-available COP levels. A 10-year life-cycle cost (LCC) analysis was conducted using a discounted cash flow approach, incorporating investment costs, operation and maintenance expenses, electricity tariff escalation, and equipment performance degradation, complemented by a parametric sensitivity analysis. The results show that air-conditioning systems account for the majority of total building electricity consumption, and that retrofit scenarios reduce cooling energy use by approximately 45–53% relative to the baseline. All retrofit options yield lower life-cycle costs despite higher initial investments, achieving total LCC reductions of up to 30%. Sensitivity analysis indicates that the economic ranking of alternatives remains stable under significant variations in electricity prices. Overall, the proposed framework provides a robust and transferable approach for assessing HVAC retrofit strategies, supporting informed decision-making for energy and cost optimization in buildings located in tropical climates. Full article

This study develops an efficient fatigue prediction framework for offshore wind turbine (OWT) monopile foundations under coupled wind–wave conditions using four surrogate models: XGBoost, Random Forest (RF), Support Vector Regression (SVR), and Gaussian Process Regression (GPR). A finite element model (FEM) incorporating soil–pile interaction is established to accurately capture structural responses under realistic environmental loading. Fatigue damage is evaluated through time-domain simulations based on this model. A surrogate modeling approach is employed to capture the nonlinear mapping between environmental variables and fatigue damage using 60 representative samples. Results show that the proposed framework significantly improves computational efficiency while maintaining predictive reliability. Among the models evaluated, GPR yields the highest prediction accuracy, while SVR shows comparable performance. In contrast, XGBoost and RF exhibit relatively larger deviations. Parametric analysis reveals that fatigue damage is positively correlated with wind speed and significant wave height, but inversely correlated with peak wave period. Further, wind-induced loading dominates fatigue accumulation, and conventional load superposition methods underestimate fatigue damage due to nonlinear wind–wave coupling effects. Furthermore, fatigue damage exhibits pronounced circumferential variation, with maximum values occurring in the fore-aft directions. Full article

Operating room ventilation is a key engineering factor in maintaining clean air environments. This study presents an integrated three-part methodology combining Computational Fluid Dynamics parametric analysis, performance assessment with effect size analysis and multi-criteria decision analysis using quantitative engineering metrics, and surrogate modeling for thermal effect propagation in an orthopedic operating room. Simulations were conducted in ANSYS Fluent 2020 R₂, benchmarking an existing local operating room against an ASHRAE 170-2021 compliant model, followed by parametric evaluation of four ceiling inlet configurations. The existing system exhibited critically low velocities (0.05–0.10 m/s) with a coefficient of variation of 0.73, indicating severe flow non-uniformity. The proposed Multi-Velocity Ceiling Diffuser—featuring a high-velocity core (0.40 m/s) over the surgical area and a low-velocity peripheral frame (0.20 m/s)—achieved 85% coverage of the ASHRAE-recommended velocity range (0.20–0.30 m/s), a coefficient of variation of 0.14 (81% improvement), and 62 air changes per hour, representing an 86% reduction in supply airflow compared to a full-ceiling system. Effect size analysis confirmed that MVCD performance shows large practical differences from smaller inlet designs (Cohen’s d ≥ 0.41) and negligible difference from full-ceiling systems (Cohen’s d = 0.05). Multi-criteria decision analysis—with feasibility and cost quantified using engineering estimates (ductwork area, downtime days, standardized cost data)—ranked MVCD as optimal under the modeled assumptions (composite score = 0.84), outperforming the existing system (0.59) and full-ceiling design (0.51). To address the isothermal assumption limitation, a Random Forest surrogate model was implemented as a differentiable approximation strategy for parametric uncertainty propagation. Under non-isothermal conditions, the MVCD is predicted to maintain a spatial median velocity of 0.19 m/s (5th–95th percentile range: 0.17–0.21 m/s) and 71% ASHRAE compliance (parameter sampling range across literature-derived distributions: 63–78%). Achieving ASHRAE velocity criteria is an engineering surrogate for ventilation effectiveness; the relationship between these metrics and clinical infection outcomes depends on multiple factors beyond airflow, including surgical technique, patient factors, and antimicrobial prophylaxis. No clinical inference is permitted from the present results. Experimental measurement in a physical MVCD-equipped operating room is required to validate these predictions prior to clinical implementation. Full article

The decarbonization of existing buildings remains a major challenge, particularly in contexts characterized by high energy demand and heating systems based on fossil fuels. While electrification is widely recognized as a key pathway, its direct application is often limited by building and operating conditions. This study investigates the potential of hybrid heating systems as transitional solutions through a large-scale numerical parametric simulation analysis based on representative models of the Italian residential building stock. The analysis explores the interaction between climatic conditions, system operation, and energy performance under standardized assumptions. The results reveal that hybrid systems achieve significant reductions in non-renewable primary energy (up to 39–44%) and CO₂ emissions (approximately 50–58%), primarily through the substitution of natural gas with electricity. Conversely, total primary energy may increase (approximately 2–26%) due to the contribution of renewable energy associated with heat pump operation. Operating cost savings are observed in the 25–40% range, with slight variation depending on climatic conditions. The effectiveness is not uniform, with maximum benefits in intermediate climate zones and reduced performance under more severe conditions. Overall, hybrid systems show stable and reliable performance across heterogeneous building configurations, supporting their role as robust mid-term transition technologies toward building decarbonization. Full article

The radial heat transfer mechanism of compacted conductors in overhead insulated cables is unclear, and the insulation layer complicates the thermal boundary conditions, limiting the direct applicability of existing ampacity calculation methods. Based on the Morgan model framework, this paper proposes an ampacity calculation method that accounts for the “plastic-then-elastic” deformation characteristics of compacted conductors. Material plastic flow and elastic deformation of the substrate are incorporated to refine the formulations for interlayer thermal contact conductance and thin-layer air gap thickness, while the equivalent distance of air voids is corrected using the fill factor. An iterative convergence procedure for the insulation outer surface temperature is established to accurately evaluate conductor Joule losses. Validated by wind tunnel tests on JKLGYJ 240/30 cables, the proposed method yields a radial temperature difference of 2.41 °C, closely matching the measured 2.6 °C, with an error of 7.4% compared to 13.5% for the conventional Morgan model. Parametric analysis reveals that equivalent radial thermal conductivity is independent of external environmental factors. Conductor stress has a negligible effect on the ampacity (variation < 0.1%). Under low wind speeds (0–5 m/s), the ampacity increases substantially with wind speed. Full article

In deep-buried tunnels, the loads acting on supporting structures continuously increase due to the rheological behavior of surrounding rock, while the performance of the secondary lining gradually degrades under environmental effects. These delayed features have significant implications for tunnel safety but are rarely incorporated into the reliability evaluation of tunnels. In this study, the surrounding rock is modeled using the Burgers model, and an analytical solution is developed by incorporating the degradation and damage of the secondary lining. Parametric analysis is conducted to identify the key factors governing tunnel response. Subsequently, limit state functions are established, and a time-dependent system reliability analysis is performed. Results indicate that tunnel response and reliability are highly sensitive to rheological parameters. Among the rheological parameters, the elastic shear modulus of the Maxwell elements G_e has the most pronounced influence on deformation, whereas the elastic shear modulus of the Kelvin elements G_k governs the stress response of the secondary lining. The time-dependent failure probability increases rapidly in the early stage and gradually stabilizes thereafter. Insufficient initial support strength is identified as the dominant failure mode of system failure. Furthermore, G_e and G_k are the key parameters affecting tunnel reliability, and increasing G_k improves the reliability index by more than 1500%. Meanwhile, the variation in system reliability is mainly affected by the failure mode of insufficient initial support strength. These findings provide quantitative guidance for the design, construction, and long-term maintenance of deep-buried tunnels in rheological rock. Full article

The Earth–Air Heat Exchanger (EAHE), also referred to as an air–soil heat exchanger, represents an effective passive cooling technology that exploits the thermal inertia of the ground. This study presents a combined experimental and analytical investigation of an EAHE system installed at the Faculty of Sciences of Agadir (Morocco). A steady-state analytical model based on convective heat transfer between the airflow within a buried duct and the surrounding soil is developed to describe the axial evolution of air temperature along the exchanger. The model is formulated under a sensible heat transfer framework, where the influence of humidity is accounted for through its effect on the thermophysical properties of moist air, while latent heat transfer and condensation phenomena are neglected. An instrumented experimental setup was implemented to perform continuous measurements of air temperature and relative humidity over a seven-month monitoring period. The experimental results indicate that the outlet air temperature remains stabilized within the range of 23.5–23.8 °C, despite significant variations in ambient temperature (13–38 °C). A parametric analysis is conducted to assess the influence of duct diameter, airflow velocity, and humidity through its effect on moist air properties on the thermal performance of the system. The close agreement between experimental observations and analytical predictions demonstrates the validity and predictive capability of the proposed model. These findings highlight the potential of EAHE systems as an effective passive cooling solution for greenhouse applications in semi-arid climatic conditions. Full article

Cerebrospinal fluid (CSF) oligoclonal band (OCB) analysis remains central to the diagnostic evaluation of neuroinflammatory diseases of the central nervous system (CNS), as it reflects intrathecal immunoglobulin synthesis. However, its reliance on lumbar puncture limits its applicability for screening and repeated longitudinal assessment. Serum metabolomics offers a minimally invasive strategy to explore peripheral biochemical correlates of central immune activity. Building on previous binary OCB comparisons, the present study extends serum metabolomic analysis to encompass all five classical OCB patterns, thereby capturing a broader immunological spectrum. A total of 92 adults undergoing diagnostic evaluation for suspected CNS inflammatory disorders were retrospectively stratified according to OCB type (Types 1–5). Serum samples were analysed using targeted ¹H-NMR spectroscopy on a Bruker Avance Neo 600 MHz platform and processed using Bruker’s IVDr pipeline. Group-wise differences were assessed using non-parametric statistical testing with false discovery rate (FDR) correction, complemented by effect size estimation, exploratory multivariate analyses, and Receiver Operating Characteristic (ROC) modelling. Distributional characteristics were further examined using boxplots and violin plots. Across analytical approaches, several metabolites—most prominently leucine, 2-oxoglutaric acid, histidine, threonine, and glycerol—exhibited nominal variation and moderate effect sizes across OCB patterns. Rather than discrete metabolic separation, these metabolites demonstrated graded shifts in central tendency accompanied by substantial overlap between groups. Unsupervised principal component analysis did not reveal robust clustering, while supervised multivariate models highlighted amino acid- and tricarboxylic acid cycle-related metabolites as contributors to partial differentiation. Post hoc power analysis indicated limited sensitivity to detect small-to-moderate effects under multiple-testing correction, supporting an exploratory interpretation of the findings. Taken together, this first targeted serum ¹H-NMR metabolomic evaluation spanning all classical OCB patterns suggests that peripheral metabolic profiles may reflect graded immunometabolic variation associated with intrathecal immune activity. While not intended for diagnostic classification, these findings provide a spectrum-based framework for integrating serum metabolomics with OCB phenotyping and identify candidate metabolites for future prospectively powered and clinically characterised studies. Full article