Range Of Variation Research Articles

First evidence of ichnopathologies in Rhinoceripeda tasnadyi tracks from the Miocene of Hungary

Despite a vast record, ichnological evidence of malformed or injured animals is extremely rare. During the re-examination of slabs collected from the Ipolytarnóc tracksite (Early Miocene, North Hungary) and housed at the Supervisory Authority for Regulatory Affairs, three “atypical” tracks were detected along the same trackway. They belong to the ichnotaxon Rhinoceripeda tasnadyi, attributed to a medium- to large-sized “hornless” Miocene rhinocerotids. The hoof of the left digitIII appears to be split, rather than oval, at approximatively half of its width, giving an almost tetradactyl appearance to the footprints. The deformation due to overprinting is excluded because of the number of tracks showing the same variation. This injury/malformation could be identified as the atypical tracks belong to a trackway where the opposite impression is preserved and due to the large number of accessible R. tasnadyi footprints. These account for a wide range of the standard variability of the morphology at Ipolytarnóc. If the track record was limited, or when the abnormal tracks do not belong to a trackway, it would not be possible to recognise those differences as ichnopathologies and, as a result, a different trackmaker would have been assessed, or a wrong ichnotaxonomical diagnosis would have been attributed.

A quick parameter configuration tool for SCHISM’s ocean transport simulation of radioactive materials

Abstract A quick tool capable of processing output files generated by the SCHISM particle tracking module has been developed to handle complex data processing procedures and conduct parameter sensitivity testing. This tool performs calculations, considering the influence of half-lives and partition coefficients, for the conversion of activity concentrations, plots particle diffusion trajectories, conducts statistical analyses of regional particle amounts, and presents activity concentration within the defined area. Using the IAEA MODARIA program as an example, this study investigates the transport of radioactive 137Cs in the ocean following the Fukushima accident on March 11, 2011. A three-year diffusion simulation was conducted by incorporating data such as ocean currents, wind fields, and tides. The calculated results demonstrate a high level of consistency with measurements, and the calculated results in the low activity concentration fall within the variability range reported in the literature.

Stability Conditions and Stiffness Variability of General Tensegrity Systems with Kinematic Joints

Abstract Tensegrity systems represent promising candidate mechanisms with in-situ stiffness variability through changing the cables' prestress levels. However, prestress-based stiffness behaviors of tensegrity systems with arbitrary kinematic joints have not been analyzed systematically. This paper adopts the natural absolute coordinates for static modeling of tensegrity systems consisting of rigid members and tension elements. Then, a generic stiffness analysis method is developed to formulate the reduced-basis tangent stiffness matrix, which is found to include three parts: positive semi-definite material and geometric stiffness matrices, and an indefinite constraint stiffness matrix. Based on these findings, a systematic stability-checking procedure is derived to determine prestress and super stability, which are qualitative indicators of the softening and stiffening effects in different tensegrity systems. Then, we proceed to quantify the range of prestress-based stiffness variability by formulating semidefinite programming problems that numerically pinpoint the maximum and zero stiffness points. Furthermore, this paper reveals the composable nature of multiple self-stress states, enabling the composability of stiffness properties in mechanism designs. Several numerical examples verify the efficacy and versatility of the proposed method and demonstrate interesting stiffness behaviors of tensegrity systems with kinematic joints.

Flow dependence of forecast uncertainty in a large convection‐permitting ensemble

AbstractThe flow dependence of forecast distributions is studied using a 120‐member ICON‐D2 ensemble for two representative case studies of weak and strong synoptic forcing of convection. The bootstrapping technique is used to investigate the convergence of sampling error for a range of surface and midtroposphere variables. Convergence is generally observed for the mean and the standard deviation, but not for the 95th percentile, especially in strong forcing. Additionally, maps of uncertainty are introduced, which allow for a more detailed analysis of the spatial pattern of uncertainty and facilitate the interpretation of the sources and evolution of forecast uncertainty in different synoptic forcing conditions. It is found that convection significantly increases uncertainty in model variables and shapes the spatial uncertainty pattern, with weak forcing leading to patchy uncertainty and strong forcing resulting in a more coherent pattern due to large convective systems. Overall, the main result of this work is the strong connection between uncertainty of forecast variables and convection, with synoptic forcing being crucial in determining the spatial distribution and uncertainty evolution within 24 h.

Model-optimization-guided neural network (MOGNN) applied to chemical processes

In this work, a Model-Optimization-guided Neural Network (MOGNN) is proposed to optimize chemical processes. The model is trained with pre-selected process data, resulting from optimization of engineering models described by systems of algebraic equations. MOGNN aims to predict the optimal operating points for a range of input variables. The models were simulated in the Unisim-Design® process simulator for training data generation and optimized in Python using the Particle Swarm Optimization algorithm. The resulting models were applied to optimize two chemical engineering cases. The results showed that the computational cost of optimization corresponded to 0.83 % and 2.12 %, respectively, about the simulation cost for a given input dataset. Also, both processes revealed good alignment between the predicted profiles and the simulator data, while their respective objective function profiles yielded an average improvement of 9.61 % and 18.83 % for the two examples.

Selection Process Based on Advancing the Development of a Science and Technology Law System with Chinese Features

The significance of advancing socialist S&T legal system building with Chinese features is examined in this paper, along with the extensive effects it has on S&T innovation and economic growth. Against the backdrop of an increasingly competitive global scientific and technology landscape, China’s ability to innovate and achieve sustainable growth hinges on the establishment of an ideal science and technology legislative framework. This essay first examines the primary obstacles to China’s development of a science, technology, and innovation (S&T) legal system, including inadequate protection for intellectual property rights, a flawed process for transforming scientific and technological advancements, and an insufficient system for encouraging enterprise innovation. Then, this research presents a quantitative analysis model to optimize the path of science and technology legal building by applying the improved particle swarm optimization method (PSO). The model takes into account a wide range of variables, including the degree of intellectual property protection, the strength of legal backing, the pace at which scientific and technological advancements are transformed, etc. Through the analysis of simulation data, the model also confirms the promotion effect of the legal system construction on the quantity of patent applications, the success rate of innovation projects, the enterprise R&D expenditure, and the expansion of the local economy. The study’s findings demonstrate that bolstering the science and technology legal system can effectively encourage businesses to boost R&D investment and foster regional economic development in addition to greatly raising the quantity of patent applications and the success rate of innovation projects. The rigorous intellectual property protection laws and ideal legal framework for the conversion of accomplishments greatly boost the regional innovation vitality and economic efficiency, particularly in the case study of Zhongguancun in Beijing and East China. Moreover, adaptive weighting is used to enhance the PSO algorithm and optimize the development of science and technology legal system’s comprehensive performance index, thereby confirming the model’s viability and efficacy. The study’s findings offer theoretical justification and helpful advice for China’s development of a science and technology legal framework, which is crucial for fostering innovation in these fields and boosting the country’s competitiveness.

Variation in the Quanta-to-Energy Ratio of Photosynthetically Active Radiation under the Cloudless Atmosphere

The quanta-to-energy ratio plays a crucial role in converting energy units to quantum units in the context of photosynthetically active radiation (PAR). Despite its widespread use, the effects of atmospheric particles and solar zenith angle (SZA) on the quanta-to-energy ratio remain unclear. In this study, both simulation and observation data revealed that the principal wavelength, which can be transformed into the quanta-to-energy ratio using a constant, exhibits a slow initial growth, followed by a rapid increase beyond 60° solar zenith angles and a subsequent dramatic decrease after reaching its maximum value. The measured quanta-to-energy ratio demonstrates a variable range of less than 3% for SZA under 70° in a cloudless atmosphere, with significant changes only occurring at zenith angles above 80°. Simulation data indicate that ozone, wind speed, surface-level pressure, surface air temperature, and relative humidity have negligible effects on the quanta-to-energy ratio. The Ångstrom exponent exerts a minor influence on the quanta-to-energy ratio by affecting diffuse radiation. Visibility, however, is found to have a substantial impact on the quanta-to-energy ratio. As a result, two relationships are established, linking the principal wavelength to visibility and the diffuse fraction of PAR. The principal wavelength serves as an effective measure of solar spectrum variability, remaining unaffected by radiation energy. This implies that atmospheric parameters which do not alter the solar spectrum will not influence the principal wavelength. The strong correlations between the principal wavelength, visibility, and the diffuse fraction of PAR suggest a broader range of applications for the principal wavelength in various research domains, opening up new avenues for exploration and potential contributions to numerous fields.

Risk factors of diphtheria outbreak in damt district of Al Dhalea Governorate, 2023 -Yemen: a case–control study

BackgroundIn Yemen, diphtheria has become an important health problem since 2017 when diphtheria re-emergence as a consequence of war and the collapse of the health system. In 2023, there has been a 57% increase in diphtheria cases compared to 2021 and 2022. Damt district of Al Dhalea Governorate had the highest reported cases for year 2023. The study aims to determine the risk factors associated with diphtheria outbreak in Damt District.MethodsA retrospective matched case–control (1:2) was used. All confirmed cases based on the WHO case definition reported from Damt district during 2023 were considered cases. Two age-matched (± 5years) neighborhood controls were recruited per case. A pretested questionnaire was used for collecting data during household interviews including demographic and household characteristics, knowledge of diphtheria, vaccination status, contact with a case of diphtheria, and travel history. Frequency and proportion for quantitative and median with interquartile range (IQR) for quantitative variables. Chi-square and Mann–Whitney tests to compare the distribution of categorical and numerical variables between cases and controls. Univariate and multivariate conditional binary logistic regression, and Adjusted Odds ratio (AOR) with a 95% confidence interval at P < 0.05 were used to identify risk factors.ResultsA total of 118 cases and 236 controls were enrolled, 56% were females (63% of cases vs. 53% of controls). The median (IQR) age was 14 (9,22) years for cases vs 12(7,23) of control, it was significantly higher for females than males in the case group: (16(10,29) Vs 10(6,18), P < 0.001) and control group: (15(8,25) vs 12(7,18), p-value = 0.022). Partial vaccination status AOR = 13.7(6.1–31.1), P-value < 0.001), contacts with a case of diphtheria AOR = 8.5(2.3–31.0), P value < 0.001) and Female gender, AOR = 3.3(CI; 1.1–9.5, P value = 0.029), were the main risk factors.ConclusionsPoor vaccination and contact with a case of diphtheria were the main contributors to diphtheria in the Damt district particularly among adult females. Increasing the vaccination coverage with a diphtheria-containing vaccine through routine immunization as well as tetanus-diphtheria vaccine for childbearing age females along with community awareness regarding protection measures during home care of diphtheria cases. Vaccination services as well as gender barriers related to Td vaccination should be investigated.

Anatomically-detailed segmented representative adult and pediatric nasal models for assessing regional drug delivery and bioequivalence with suspension nasal sprays

In vitro nasal models can potentially facilitate development and approval of nasal drug products. This study aims to evaluate the potential for using regional deposition measurements from in vitro nasal models to evaluate nasal spray performance across several products. To accomplish this, the posterior regions of six anatomically realistic nasal airway models of adult and pediatric subjects, representing Low (L), Mean (M) and High (H) posterior drug deposition (PD) for each of the two age groups, were segmented with high anatomical precision into five regions of interest. These models were previously developed with the goal of quantifying the range of intersubject variability of PD following administration of inhaled corticosteroids. The in vitro regional drug deposition values were measured for the reference listed drug (RLD) product for triamcinolone acetonide and two corresponding generic (test) nasal spray products, as well as an RLD product for fluticasone furoate nasal spray. In general, the pediatric models mostly demonstrated higher PD compared to the adult models. The majority (>85 %) of PD was confined to the front and the inferior meatus regions. Subsequent population bioequivalence (PBE) analyses of the regional nasal deposition suggested that the anatomical differences among subjects may impact the nasal spray performance across different nasal products.

Study on the Weibull distribution function-based stochastic damage evolution law for uniaxial compression in high-performance concrete with full aeolian sand

The issues of environmental degradation due to natural sand overextraction are becoming increasingly severe. In desert regions, utilizing aeolian sand as a substitute for natural sand in construction projects facilitates the resource economization and the effective management of desertification. The concrete industry is expected to significantly contribute to this objective, as high-performance concrete with full aeolian sand (FA-HPC) has demonstrated excellent mechanical properties. However, current researches have yet to establish a rational damage evolution law for uniaxial compression in FA-HPC from the perspective of damage characteristics. In this study, uniaxial compression tests were conducted on FA-HPC with different mixture proportions. Simultaneously, the stress-strain behavior was examined, and acoustic emission (AE) signals were collected and localized. Based on the Weibull distribution function-based stochastic damage evolution law for uniaxial compression, regression analyses of the stress-strain and AE cumulative ringing count for FA-HPC were performed. Damage evolution model for effective stress and damage variable were established and validated with experimental data to confirm their applicability. The scale and shape parameters of the model were predicted using the mixture proportions as independent variables. The results show that the rationality of the damage evolution law assumption was validated through AE source localization. The goodness of fit values for damage variable and effective stress equation range from 0.87 to 0.98, with the ascending segment and the vicinity of the peak point closely matching the experimental data, indicating that the Weibull distribution function-based stochastic damage model for uniaxial compression is applicable for FA-HPC. The predicted values of the damage evolution model parameters based on the mixture proportions align well with the measured values, achieving a goodness of fit of 0.99, thereby guiding the study of FA-HPC's compressive characteristics prior to the formation of primary cracks. Notably, there remains a need to propose corrective equations to enhance the correlation between regression curves and experimental data in the late failure stages of FA-HPC in future research, achieving precise predictions by considering the interactions of multiple factors.

Identifying markers of health-seeking behaviour and healthcare access in UK electronic health records

ObjectiveTo assess the feasibility of identifying markers of health-seeking behaviour and healthcare access in UK electronic health records (EHR), for identifying populations at risk of poor health outcomes and adjusting...

Design optimization of inner and outer‐rotor PMSGs for X‐ROTOR wind turbines

AbstractThis article presents an analytical design approach for the inner and outer rotor Permanent Magnet Synchronous Generators (PMSGs) that are a key component of wind turbines. By developing the analytical model, sensitivity analysis has been performed to determine the effect of some important geometrical and electromagnetic parameters on the generator's output characteristics. The GA optimization algorithm was used to find optimized designs in terms of efficiency, weight, cost, and temperature rise. In order to find the global optimization solution within the allowed variable range and in accordance with the constraints, a combined objective function has also been defined. In order to validate the analytical model, ANSYS electromagnetic and thermal simulations have been used. With this approach, the designer is provided with a good understanding of the input parameters and constraints in light of the application requirements.

High-frequency study of megafaunal communities on whale bone, wood and carbonate in hypoxic Barkley Canyon

Organic-rich whale bones and wood falls occur widely in the deep sea and support diverse faunal communities, contributing to seafloor habitat diversity. Changes in community structure through succession on deep-sea bone/wood substrates are modulated by ecosystem engineers, i.e., bone-eating Osedax annelids, and wood-boring Xylophaga bivalves. Here, we use a comparative experimental approach and Ocean Networks Canada’s (ONC) cabled observatory in hypoxic Barkley Canyon to study, at high temporal resolution, colonization and succession on whale-bone, Douglas fir wood, and control carbonate rock over 8.3 mo. Experimental substrates were similar in size and mounted on PVC plates near the seafloor at 890 m depth and monitored by high-definition video camera for 5-min intervals every 6-12 h over a period of 8.3 mo. A broad range of seafloor and sea-surface environmental variables were also monitored at this site over the 8.3 mo to account for environmental variability and food input. Following loss of the high-definition camera, substrates were surveyed approximately annually with lower resolution ROV video for an additional 8.5 y. We find that megafaunal abundances, species diversity, and community structure varied substantially over 8.3 mo on each substrate, with markedly different patterns on whale bones due to the development of extensive white bacterial mats. A combination of seafloor and sea surface variables explained &amp;lt; 35% of bone/wood community variation. Bone-eating Osedax annelids failed to colonize whale bones even after 9.2 years, and boring Xylophaga bivalves colonized the wood at much lower rates than in better oxygenated deep-sea locations. Species diversity on whale-bone and wood substrates appeared to be substantially reduced due to the absence of ecosystem engineers and the low oxygen concentrations. We hypothesize that Osedax/Xylophaga colonization, bone/wood degradation, and bone/wood community development may be limited by oxygen concentrations of 0.22 - 0.33 ml.l on the NE Pacific margin, and that OMZ expansion due to climate change will reduce whale-bone and wood degradation, and the contribution of whale falls and wood falls to beta diversity, on the NE Pacific margin.

Structural, electrical, leakage current, and magnetic characteristics of double perovskite Nd2NiTiO6

AbstractThis study investigates the structural, electrical, leakage current, and magnetic characteristics of the double perovskite material Nd2NiTiO6 synthesized through the sol–gel citrate auto‐ignition method. The Rietveld refinement of the X‐ray diffraction patterns confirmed a monoclinic symmetry (space group P21/n) with an ordered arrangement of alternate NiO6 and TiO6 octahedra. Impedance spectroscopic analysis exhibited the material's non–Debye‐type relaxation mechanism and semi‐conductive nature. AC conduction analysis revealed that the conduction of charge carriers occurs via the nonoverlapping small polaron hopping mechanism, consistent with Mott's variable range hopping model. Temperature‐ and frequency‐dependent dielectric measurements were interpreted using the Maxwell–Wagner interfacial polarization model. The analysis of thermal‐ and field‐dependent leakage currents established that conduction is ohmic, which the Schottky barrier model explains. Studies on magnetization ruled out the presence of magnetic ordering connected to indirect interaction between Ni2+ ions via Ti4+ ions and the rare‐earth cation (Nd3+) moment.

Exploring intraspecific and interspecific variation of coral reef algae using a novel trait‐based framework

Abstract The development of trait‐based approaches has accelerated our understanding of how communities assemble, respond to environmental change and may best be managed in the Anthropocene. Understanding the magnitude and pattern of interspecific variability forms a critical underpinning of trait‐based approaches while exploring intraspecific variability can identify the potential of species to adapt to changing environmental drivers. Our work is motivated by the critical need for a novel conceptual framework for understanding the functional ecology of macroalgae, as the current paradigm is still mired in functional group models developed in the 1980s. Our objective was to quantify interspecific and intraspecific functional trait variability in three common and morphologically diverse species of tropical marine macroalgae by exploring traits relating to the ecological functions of resource acquisition, resistance to herbivory, and resistance to physical disturbance and the trade‐offs between them. We quantified intraspecific and interspecific variability of 11 functional traits for three common and morphologically diverse species of tropical macroalgae from five fringing reefs of Mo'orea, French Polynesia that were likely to capture a wide range of environmental variability. Differences in traits among species and sites were determined with PERMANOVA, visualised with non‐metric multidimensional scaling, and trade‐offs between pairs of traits explored with correlation. Finally, spatial patterns among select traits across all species were quantified. Species clustered together in distinctly different trait spaces driven by trade‐offs among suites of functional traits. Two of three species had considerable intraspecific variability, though this variability occurred at different scales, while one clustered tightly. Exploration of individual traits across species and sites revealed trade‐offs between two strategies for resource acquisition, growing tall and strong versus investing in large surface area. Synthesis. We captured novel patterns of interspecific and intraspecific variability for tropical marine macroalgae. We found fundamental differences in traits between species that may represent ecological strategies while considerable intraspecific variability demonstrates a wide range in abilities to respond to environmental drivers. Overall, our work provides novel insights into intra and interspecific trait variation that form an essential underpinning for using a trait‐based framework in a taxon that is increasingly dominant on tropical reefs.

Coupled Disk-star Evolution in Galactic Nuclei and the Lifetimes of QPE Sources

A modest fraction of the stars in galactic nuclei fed toward the central supermassive black hole (SMBH) approach on low-eccentricity orbits driven by gravitational-wave radiation (extreme mass ratio inspiral (EMRI)). In the likely event that a gaseous accretion disk is created in the nucleus during this slow inspiral (e.g., via an independent tidal disruption event (TDE)), star–disk collisions generate regular short-lived flares consistent with the observed quasiperiodic eruption (QPE) sources. We present a model for the coupled star-disk evolution, which self-consistently accounts for mass and thermal energy injected into the disk from stellar collisions and associated mass ablation. For weak collision/ablation heating, the disk is thermally unstable and undergoes limit-cycle oscillations, which modulate its properties and lead to accretion-powered outbursts on timescales of years to decades, with a time-averaged accretion rate ∼0.1Ṁ Edd. Stronger collision/ablation heating acts to stabilize the disk, enabling roughly steady accretion at the EMRI-stripping rate. In either case, the stellar destruction time through ablation, and hence the maximum QPE lifetime, is ∼102–103 yr, far longer than fallback accretion after a TDE. The quiescent accretion disks in QPE sources may at the present epoch be self-sustaining and fed primarily by EMRI ablation. Indeed, the observed range of secular variability broadly matches those predicted for collision-fed disks. Changes in the QPE recurrence pattern following such outbursts, similar to that observed in GSN 069, could arise from temporary misalignment between the EMRI-fed disk and the SMBH equatorial plane as the former regrows its mass after a state transition.

Flexibility justice: Exploring the relationship between electrical vehicle charging behaviors, demand flexibility and psychological factors

The adoption of electric vehicles (EVs) is transforming the landscape of energy consumption. While the technical and economic dimensions of EV adoption are increasingly well understood, the aspect of justice in demand flexibility remains underexplored. This study examines the complex relationship between flexibility in EV charging behaviors and the influence of socio-psychological and justice factors. We explore a range of demographic and social-psychological variables including charging anxiety, environmental concerns, perceived cost-saving perception, perceived privacy, and trust in utility providers. Our results reveal that these variables positively influence the changes in charging habits, including time-shifting and load-reduction. This study also uncovers disparities in charging behavior adjustments across various demographics groups. For instance, White respondents are more likely to charge their EVs during off-peak hours than their non-White counterparts and homeowners show a greater intention to reduce EV charging load during peak hours compared to renters. Additionally, high-income individuals exhibit a stronger willingness to shift charging times to off-peak, with White respondents within the high-income group being the most likely to reduce the amount of charging load during peak hours. Conversely, low-income White respondents are less inclined to make such adjustments. These disparities are likely tied to socioeconomic status, as more vulnerable groups often face greater constraints in adjusting their schedules. Therefore, it is imperative that policies prioritize flexibility justice by addressing the specific needs and behaviors of vulnerable groups, aiming to mitigate the additional burdens resulting from their limited flexibility.

The Impact of Restrictive Macroprudential Policies through Borrower-Targeted Instruments on Income Inequality: Evidence from a Bayesian Approach

This study used the panel data from 15 emerging markets to examine the impact of restrictive macroprudential policies on income inequality from 2000–2019 using Bayesian panel vector autoregression and Bayesian panel dynamics generalised method of moments models. The chosen models are suitable for addressing multiple entity dynamics, accommodating a wide range of variables, handling dense parameterisation, and optimising formativeness and heterogeneous individual-specific factors. The empirical analysis utilised various macroprudential policy proxies and income inequality measures. The results show that when the central banks tighten systems using macroprudential policy instruments to sticker debt-to-income and financial instruments for lower-income borrowers (the bottom 40% of the income distribution), they promote income inequality in these countries while reducing income inequality for high-income borrowers (the high 1 percent of the income distribution). The impact of loan-to-value ratios was found to be insignificant in these countries. Fiscal policy through government expenditure and economic development reduces income inequality, while money supply and oil-price shocks exacerbate it. The study suggests implementing a progressive debt-to-income (DTI) ratio system in emerging markets to address income inequality among lower-income borrowers. This would adjust DTI thresholds based on income brackets, allowing lenient credit access for lower-income borrowers while maintaining stricter limits for higher-income borrowers. This would improve financial stability and reduce income disparities. Additionally, targeted financial literacy programs and a petroleum-linked basic income program could be implemented to distribute oil revenue to lower-income households. A monetary supply stabilisation fund could also be established to maintain financial stability and prevent excessive inflation.

Oxygen Plasma‐Induced Modification of Structural and Electrical Properties of Pr0.5Sr0.5MnO3 Manganites

Herein, the impact of exposing the perovskite compound Pr0.5Sr0.5MnO3 to oxygen plasma is explored by comparing the structural and transport properties of the exposed samples to those of the unexposed ones. The Pr is oxidized to PrO2 in the investigated samples due to plasma exposure. The alterations in the transport properties can be linked to the changes in MnOMn bond angle and MnO bond length due to plasma exposure, as indicated by X‐ray diffraction analysis. Additionally, exposure to oxygen plasma increases the conductivity by incorporating oxygen into the exposed samples, making them oxygen‐rich. Detailed analysis of the resistivity and thermoelectric power data indicates that small polarons are responsible for conduction at high temperatures, while at low temperatures, variable range polarons take over. The negative value of the thermopower at all temperatures proclaims that the electrons behave as the dominant charge carriers.

Probabilistic Seismic Risk Assessment of Metro Tunnels in Soft Soils

Tunnels are of significant importance in the sustainable development of global urban areas, particularly in metropolitan areas. It is of the utmost importance to evaluate the seismic performance of tunnels across a wide spectrum of earthquake intensities. In order to address this, our study presents a framework for the assessment of seismic risk in tunnels. This study employs the city of Shanghai’s urban metro tunnels as case studies. The nominal values of seismic risk for the three main damage states—minor, moderate, and major—were calculated. Furthermore, the influence of utilizing disparate fragility functions on expected seismic risk assessments was investigated. In this framework, the probability density functions of the different fragility curve models are employed to treat the probability values associated with them as random variables. This approach aims to facilitate the propagation of IMV in seismic risk assessments. The results demonstrate that the Bayesian framework efficiently incorporates the full range of input model variability into risk estimation. The findings of this study offer a foundation for decision-making processes, seismic risk assessments, and the resilience management of urban infrastructure.