Probabilistic Assessment Research Articles

Hybrid-self-centring steel frames: Insights and probabilistic seismic assessment

This paper comprehensively discusses the seismic performance of steel moment-resisting frames with hybrid-self-centring connections (SMRF-HSCC) employing energy dissipation sequences by probabilistic seismic assessment. The hysteretic model of the HSCC was first developed based on experimental results, and a simplified nonlinear-spring-based model to simulate the behaviour of the connection was proposed and verified by physical test data. A series of codified prototype structures were developed, considering the fracture behaviour of post-tensioned (PT) steel strands in the connections. The seismic performance of prototype structures was assessed in terms of nonlinear static analyses and nonlinear dynamic analyses. The results indicated that the hysteretic response of SMRF-HSCC exhibited trilinear hysteretic features with the expected energy dissipation sequences. The influence of the high-mode effects on SMRF-HSCC was mitigated with the increase in energy dissipation and post-yield stiffness of the structure. Finally, the fragility analyses of the prototype structures were further performed, and the risk assessment was also made considering a 50-year service period. The collapse probability and the exceedance probability of target residual drift over a 50-year service period of SMRF with conventional self-centring connections showing flag-shaped hysteresis were higher than that of SMRF-HSCCs. The results also confirmed that the collapse probability and exceedance probability of target residual drift over a 50-year service period of SMRF-HSCC can be adjusted by reasonably modulating the arrangement of the HSCCs.

Probabilistic seismic hazard assessment framework for Uganda: a stochastic event-based modelling approach

Uganda lies between the eastern and western arms of the East African Rift System, the largest seismically active rift above sea level. With increasing population, urbanisation and rapid construction, seismic risk in the country is escalating fast and is compounded by the high vulnerability of the building stock and inadequate disaster prevention and mitigation strategies. Hence, there is an urgent need to assess Uganda’s resilience against seismic risks. This paper presents a Monte-Carlo based probabilistic seismic hazard model for Uganda, as the first step towards the development of a seismic risk and resilience assessment framework for the country. In addition to fault segment data, earthquake catalogues are compiled for the period between 1900 and 2022 to estimate recurrence parameters for source zones in the area of interest. Area source zones incorporating focal mechanisms are used to stochastically model a national hazard framework for Uganda. A logic tree approach is applied to implement four ground motion prediction equations for both stable continental and active shallow crust geologies. Mean hazard curves, uniform hazard spectra, earthquake disaggregation and spectral pseudo-accelerations for major Ugandan cities are derived in addition to hazard maps for the country. The findings are largely consistent with previous regional studies and confirm that western Uganda is exposed to the highest level of seismicity. The model presented herein can be used to kick-start the update and continuous improvement of Uganda Seismic Design Code and the National Policy for Disaster Preparedness and Management.

Earthquake forecasting model for Albania: the area source model and the smoothing model

Abstract. We proposed earthquake forecasting models for Albania, one of the most seismogenic regions in Europe, to give an overview of seismic activity by implementing area source and smoothing approaches. The earthquake catalogue was first declustered to remove foreshocks and aftershocks when they are within the derived distance windows and time windows of mainshocks. Considering catalogue completeness, the events with M≥4.1 during the period of 1960–2006 were implemented for the learning forecast model. The forecasting is implemented into an area source model that includes 20 sub-regions and a smoothing model with a cell size of 0.2∘ × 0.2∘ to forecast the seismicity in Albania. Both models show high seismic rates along the western coastline and in the southern part of the study area, consistent with previous studies that discussed seismicity in the area and currently active regions. To further validate the forecast performance of the two models, we introduced the Molchan diagram to quantify the correlation between models and observations. The Molchan diagram suggests that the models are significantly better than a random distribution, confirming their forecasting abilities. Our results provide crucial information for subsequent research on seismic activity, such as probabilistic seismic hazard assessment.

Modeling collision risk for unsafe lane-changing behavior: A lane-changing risk index approach

The lane-changing maneuvers are challenging and contributes to traffic accidents and crashes. They are complicated task that often lead to an increased risk of vehicle collisions and deteriorates traffic flow. This paper proposes a vehicle collision risk model based on vehicle lane-changing movement for autonomous vehicles using the probability threat assessment approach and the lane-changing risk index (LCRI). Given two vehicles, A and B, we first estimate the movements of vehicle B using a GPS device, which accurately identifies the vehicle while changing lanes. We then evaluate the collision risks between vehicles using the probabilistic assessment approach to determine whether a collision event occurs at a later stage. Then, we propose the LCRI, which aims to identify the risk level associated with vehicle lane-changing movement and determine the severity of the crash level. In this study, the HighD vehicle trajectory dataset is used to obtain accurate traffic information and help us investigating collision risks among vehicles. The results show that the proposed model can identify the risks of collision ahead of time. Furthermore, the random parameter ordered logit (RPOL) with heterogeneity model achieves better performance and provides a good fit model and measures for improving traffic safety.

Greenhouse Gas Emissions Performance of Electric, Hydrogen and Fossil-Fuelled Freight Trucks with Uncertainty Estimates Using a Probabilistic Life-Cycle Assessment (pLCA)

This research conducted a probabilistic life-cycle assessment (pLCA) into the greenhouse gas (GHG) emissions performance of nine combinations of truck size and powertrain technology for a recent past and a future (largely decarbonised) situation in Australia. This study finds that the relative and absolute life-cycle GHG emissions performance strongly depends on the vehicle class, powertrain and year of assessment. Life-cycle emission factor distributions vary substantially in their magnitude, range and shape. Diesel trucks had lower life-cycle GHG emissions in 2019 than electric trucks (battery, hydrogen fuel cell), mainly due to the high carbon-emission intensity of the Australian electricity grid (mainly coal) and hydrogen production (mainly through steam–methane reforming). The picture is, however, very different for a more decarbonised situation, where battery electric trucks, in particular, provide deep reductions (about 75–85%) in life-cycle GHG emissions. Fuel-cell electric (hydrogen) trucks also provide substantial reductions (about 50–70%), but not as deep as those for battery electric trucks. Moreover, hydrogen trucks exhibit the largest uncertainty in emissions performance, which reflects the uncertainty and general lack of information for this technology. They therefore carry an elevated risk of not achieving the expected emission reductions. Battery electric trucks show the smallest (absolute) uncertainty, which suggests that these trucks are expected to deliver the deepest and most robust emission reductions. Operational emissions (on-road driving and vehicle maintenance combined) dominate life-cycle emissions for all vehicle classes. Vehicle manufacturing and upstream emissions make a relatively small contribution to life-cycle emissions from diesel trucks (<5% each), but these are important aspects for electric trucks (5% to 30%).

Probabilistic and Deterministic Assessment of Seismic Soil Liquefaction Potential in The Niger Delta Region of Nigeria Using Standard Penetration Test-Based

Probabilistic and Deterministic Assessment of Seismic Soil Liquefaction Potential in The Niger Delta Region of Nigeria Using Standard Penetration Test-Based

Influence of Geomagnetic Storms on Power System Static Voltage Security

The adverse effects of geomagnetic storms on power systems have been confirmed by numerous examples and observations. However, there remains a dearth of research on the quantitative assessment of the safety risks of a system under extreme geomagnetic storm conditions. Accordingly, in this study, we developed a risk assessment model for magnetic storm disasters based on the static voltage security region theory from the global perspective of power grid security. First, we determined the boundary shape of the static security region of a system under magnetic storm conditions and analyzed its influence on the voltage stability of the system from a regional perspective. Subsequently, a static safe-distance index was proposed to characterize the influence of a magnetic storm disaster on the system voltage. Considering the uncertainty in the injected power during a magnetic storm, we calculated the static voltage instability probability of the system. Through probability index analysis, a probabilistic safety assessment of the system under magnetic storm conditions was performed, and its overall static voltage safety level was measured. Finally, a simulation analysis based on the UIUC 150 node showed the proposed method to be reasonable and effective.

The importance of hazard-consistency when estimating seismic residual drifts in steel moment frames

Residual drifts are routinely used to assess the post-earthquake safety of buildings. Despite their importance, studies on the probabilistic assessment of residual drifts in multi-storey buildings with Steel Moment Resisting Frames (SMRF) are far less common than those dealing with their transient peak drift counterpart. More seriously, although residual drift prediction models have been developed with a particular broad ground-motion type or soil condition in mind, all models proposed to date remain oblivious to the central issue of hazard consistency. Hence, missing the causal connection between the seismic hazard level and the ground-motion suite used and potentially compromising the meaningfulness of their results. This oversight is expected to introduce a bias in the estimation of residual drifts but its magnitude has not yet been properly evaluated. In this paper, we evaluate and quantify the significance of these effects. To this end, we use the Conditional Scenario Spectra framework, which provides a set of realistic earthquake spectra with assigned rates of occurrences based on their spectral shape and intensity, thus preserving the critical relationship of hazard consistency. Nonlinear Response History Analyses (NRHA) of 24 deteriorating SMRFs under 816 ground-motion records are performed to construct a database of residual drift demands. These NRHA results are used to examine the residual drift trends and to construct benchmark residual drift hazard curves. An extensive feature selection process employing several Machine Learning (ML) algorithms precedes the development of hybrid data-driven predictive models. Finally, we compare our hazard-consistent predictions with currently available models and quantify the massive under- and over-estimations associated with previously proposed non-hazard-consistent assumptions.

Estimation of the installation torque–capacity correlation of helical pile considering spatially variable clays

In the offshore fields, helical piles are increasingly deemed to constitute suitable tools for anchoring floating structures and wind turbines. A large number of studies have been published to explore the installation torque–capacity correlation, and most of them are conducted in a deterministic manner. However, natural soils are inherently spatially varying, and analyses taking such variation into account might be closer to the reality. To address this issue, this paper examines the installation and uplift process of helical piles considering spatially varying soils via three-dimensional large deformation random finite element analyses within a Monte Carlo framework. Computed values of the installation torques and the uplift capacities compare well with the results in existing publications, therefore verifying the applicability of the numerical model. Spatially varying soil strength is mapped through the random field, followed by Monte Carlo simulations conducted to determine the torque–capacity correlation in random soils. The results suggest that the torque–capacity correlation might be misestimated once the spatially random soil properties are overlooked. Besides, probabilistic assessments of the pile torque–capacity correlation are performed, which may be of great interest to engineering practitioners in the design method of the helical pile.

Probabilistic assessment of anchor foundation for transmission tower using multivariate adaptive regression splines

ABSTRACT This paper pertains to the reliability analysis of transmission tower foundations under variable wind loads. The reliability analysis of the anchor foundation, frequently employed for transmission towers due to their huge uplift capacity at shallow depth, is presented using a systematic probabilistic approach. The paper presents the design of an anchor foundation for a typical transmission tower based on loads obtained by applying lateral wind velocity on the tower. The Multivariate Adaptive Regression Splines (MARS) surrogate model is first developed to construct a deterministic prediction model for the anchor uplift capacity. The developed model is further used in the reliability analysis of the anchor foundation considering variabilities in the soil properties and the uplift load, and the results of the probabilistic analysis are reported in the paper. The results indicate the importance of incorporating variability in design variables for the proper safety of the structure. Soil cohesion is found to be the most sensitive parameter in the uplift capacity of the tower foundation. The comparison of the deterministic factor of safety and failure probability of the foundation brings out the importance of the reliability-based design methodology.

Estimation of uncertainty in computation of importance factors and probability of undesirable events for safety-critical multi-unit systems, based on Binary Decisions Diagrams

This paper addresses current needs of the Multi-Unit Probabilistic Safety Assessment (MUPSA) methodology, which consists of a series of eight essential steps for conducting Probabilistic Safety Assessment (PSA) in the context of a multi-unit Nuclear Power Plant (NPP), co-located on a single site. The focus of this study revolves around one of the steps of the MUPSA methodology, which includes the examination of the importance factors and uncertainty analysis. Emphasizing the role of this step within MUPSA, the paper highlights the hypothesis and estimations made, along with the determination of system importance factors and failure frequency. To illustrate the practical application of these concepts, the paper presents three illustrative examples. The first example involves a 3-terminal reliability network, while the second example features an illustrative calculation applied to a system designed for potential use in a real NPP, compared to a Monte-Carlo simulation. Moreover, the second example involves the evaluation of a medium voltage distribution system (MVDS) designed to meet the auxiliary supply requirements of a nuclear power plant. This analysis is performed using a binary decision diagram (BDD), and the results derived from the BDD evaluation are then verified with those obtained through a Monte Carlo simulation for a comprehensive comparative analysis. Finally, an uncertainty analysis is achieved using a BDD reliability model, using the results of fault trees developed by National Company SN Nuclearelectrica S.A. (SNN), Department of Nuclear Safety, in the context of the Coordinated Research Project (CRP- I31031).

Seasonal rockfall risk analysis in a touristic island: Application to the Tramuntana Range (Mallorca, Spain)

Rockfalls are an ever-present possibility in the mountainous context of the Tramuntana Region (Mallorca, Spain). Recent events have shown the high potential for direct and indirect impact on the safety of people and economic activities, lasting for weeks or even months. In the present study, we start from a probabilistic assessment of the rockfall hazard (spatial propensity and temporal recurrence), based on a detailed historical record of occurrences and rockfall modelling, which is subsequently superimposed on three exposure scenarios and on a social vulnerability assessment. Exposure considers the floating population at three seasons of the year, given the area's high tourist aptitude. Vulnerability considers on the one hand the intrinsic characteristics of individuals and, on the other, the characteristics of the surrounding territory that act to facilitate emergency operations, mitigate the immediate impact and enhance rapid recovery. Due to the characteristics of the island and the spatial distribution of tourism, the results show that the highest density of rockfall trajectories potentially affect areas of high exposure, whose access by emergency services is complex. Not being, in general, the areas of highest individual criticality, those areas have in most situations low support capability installed or nearby.The results constitute a useful tool for emergency and risk management planning in multiple sectors linked to risk governance. Despite the high geographic detail of the analysis, these studies do not replace exposure and vulnerability analysis at the building level, for which the contribution of georeferenced Census data is fundamental.

Shake table test and seismic fragility analysis of transmission tower-line system considering duration effect

Although extensive attention has been devoted to the influence of ground motion duration on the seismic performance of various structures, the integration of the duration effect into the seismic analysis of transmission tower-line systems (TTLSs) has been rarely studied, leading to a lack of understanding regarding the relationship between the ground motion duration and the seismic response of TTLSs. This paper aims to quantify the duration effect on the structural performance and seismic fragility of a TTLS through shake table tests and numerical simulations. To achieve this goal, a reduced-scale experimental model of a TTLS is carefully designed and fabricated, and a group of ground motions with contrasting durations is chosen using a spectral matching method. Subsequently, shake table tests are conducted to examine the duration effect on the seismic responses of the TTLS. The recorded data indicates that long-duration ground motions (LDGMs) significantly amplify the seismic responses and have the potential to degrade the structural performance. Furthermore, a validated finite element model of the TTLS is employed to compute its nonlinear responses from elastic behavior to complete plasticity utilizing incremental dynamic analysis. Probabilistic assessments are also conducted to investigate the seismic fragility and loss of the TTLS. The findings reveal higher damage probabilities and more severe losses caused by LDGMs, emphasizing the importance of considering the duration effect in the seismic performance assessment of TTLSs. This investigation contributes to a meaningful exploration for reliably assessing the seismic capacity of TTLSs while accounting for the duration effects.

Copula-Based Probabilistic Hazard Assessment Model for Debris Flow Considering the Uncertainties of Multiple Influencing Factors

This paper proposes a probabilistic hazard assessment model for debris flows considering the uncertainties of multiple influencing factors based on copula approaches. Fifty-nine rainfall-induced debris flows occurred between 2001 and 2009 in Taiwan are taken as an illustrative example to validate the proposed approaches. A copula-based probabilistic model is developed to model the joint probability distribution of debris-flow volume V and its influencing factors (e.g., rainfall intensity, RI and landslide area, AL). The developed model is then used to make probabilistic prediction of debris-flow volume for a specific hazard level, and compared with the empirical approaches. The proposed probabilistic model is also used to develop the exceedance probability charts of quantities for a specific debris-flow basin. Results show that the developed V–RI–AL probabilistic model can provide reasonable estimates of debris-flow volume in Taiwan for a specific probability level of 0.94, and show better predictive performance than the empirical relationships by using an independent debris-flow dataset in Taiwan for validation. The developed multivariate joint probabilistic model can also provide the exceedance probability of debris flows through considering the uncertainties of debris flow and its influencing factors, providing a preliminary reference for hazard assessment of the debris flows.

Probabilistic Assessment of Seismic Response of Toe-Excavated Partially Saturated Hillslopes

Probabilistic Assessment of Seismic Response of Toe-Excavated Partially Saturated Hillslopes

Probabilistic Assessment of Global Drought Recovery and Its Response to Precipitation Changes

AbstractAccurate assessment of drought recovery probability is crucial for proactive strategies in cost‐effective water resource allocation, resilient agriculture management, and sustainable energy planning. However, there has been a notable gap in assessing drought recovery from a probabilistic and multi‐variate perspective. Here, we develop a Vine Copula‐based framework to quantify global drought recovery probability and explore its elasticity to precipitation changes. Compared to the historical period (1951–1983), 51% of global land has become increasingly difficult to recover from extreme droughts over 1984–2016 within 8–14 days during growing seasons. Furthermore, the response of global drought recovery to precipitation changes depends on the background climate and varies asymmetrically between wet and dry conditions. Under an extremely wet climate, a 1% historical precipitation increase yields a mere 0.5% increase in global median drought recovery probability during June‐July‐August, but can lead to a pronounced 6.6% increase if climate gets extremely drier.

Daylight Saving Time Practice and the Rate of Adverse Cardiovascular Events in the United States: A Probabilistic Assessment in a Large Nationwide Study

We investigated the association of daylight saving time (DST) transitions with the rates of adverse cardiovascular events in a large, US-based nationwide study. The study cohort included 36,116,951 unique individuals from deidentified administrative claims data of the OptumLabs Data Warehouse. There were 74,722 total adverse cardiovascular events during DST transition and the control weeks (2 weeks before and after) in spring and autumn of 2015-2019. We used Bayesian hierarchical Poisson regression models to estimate event rate ratios representing the ratio of composite adverse cardiovascular event rates between DST transition and control weeks. There was an average increase of 3% (95% uncertainty interval, −3% to −10%) and 4% (95% uncertainty interval, −2% to −12%) in adverse cardiovascular event rates during Monday and Friday of the spring DST transition, respectively. The probability of this being associated with a moderate-to-large increase in the event rates (estimate event rate ratio, >1.10) was estimated to be less than 6% for Monday and Friday, and less than 1% for the remaining days. During autumn DST transition, the probability of any decrease in adverse cardiovascular event rates was estimated to be less than 46% and a moderate-to-large decrease in the event rates to be less than 4% across all days. Results were similar when adjusted by age. In conclusion, spring DST transition had a suggestive association with a minor increase in adverse cardiovascular event rates but with a very low estimated probability to be of clinical importance. Our findings suggest that DST transitions are unlikely to meaningfully impact the rate of cardiovascular events.

A new method for safety assessment of complex avionic systems

In this article, we propose a new approach for safety assessment of safety-critical systems. This approach, so-called Synthesis, is dedicated to the Preliminary System Safety Assessment included within the process of Safety Certification of avionic systems. The central idea consists in decomposing the assessment into two parts aiming at studying respectively the functional and the physical characteristics of the system under study. The whole approach is supported by a fully operational tool chain, dedicated to probabilistic safety assessment, which includes the AltaRica 3.0 integrated modeling environment, and a tool dedicated to the synthesis of functional minimal cutsets into physical minimal cutsets, making possible their quantitative assessment. We illustrate the benefits of the approach by means of a concrete avionic case study.

Compilation of a Comprehensive Earthquake Catalog and Relocations in the Caucasus Region

Abstract Instrumental seismic monitoring has a long history in the Caucasus and started in 1899 when the first seismograph was installed in Tbilisi, Georgia. Much of the analog paper records from this time period are preserved in the Tbilisi archives because Georgia served as the regional data center. In the 1990s, due to the collapse of the Soviet Union and the political turmoil in the region, the analog networks and the communication between the newly formed national networks deteriorated. In Georgia, for the next 13 yr, the seismic network coverage was poor until the 2002 Tbilisi earthquake. Following this earthquake, the first permanent digital seismic station in Georgia was established in Tbilisi in 2003. The digital era progressively improved the ability to collect and archive data and today more than a hundred broadband seismic stations (including temporary arrays) are operating in the southern Caucasus. Until recently, the region lacked a coordinated effort to catalog all analog and digital era data collected by different countries into a single repository. As a result of collaboration between Lawrence Livermore National Laboratory, the Ilia State University, and the Republican Seismic Survey Center of Azerbaijan, a comprehensive earthquake catalog was compiled for the Caucasus and neighboring areas as part of a broader probabilistic seismic hazard assessment project. This project digitized Soviet-era paper bulletins, compiled a unified earthquake catalog from regional bulletins, developed 1D reference velocity model, and used it to relocate the events. The final catalog contains 16,963 events with magnitudes 3.7 and above, bringing together all the available data sets in the Caucasus region from 1900 to 2015, significantly improving locations, and generating the most complete earthquake catalog in the region, temporally and geographically.

Probabilistic Seismic Performance Assessment of Tall RC Special Moment-resisting Frame Buildings Equipped with Buckling-restrained Braces under Near-field Excitations

Many tall buildings have already been constructed near faults throughout the world, several of which have sustained casualties and economic losses during strong ground motions. This study investigates the effect of near-fault excitations on the vulnerability of tall, reinforced concrete (RC) special moment-resisting frame (SMRF) buildings equipped with buckling-restrained braces (BRBs) using seismic fragility curves. After attaining the structure’s response modification factor (R), three-dimensional (3D) models of 15-, 25- and 35-story frames were developed by the OpenSees software according to the Iranian code provisions. Thus, the seismic response of the elements was obtained. Subsequently, incremental dynamic analysis (IDA) was conducted by selecting a suitable number of compatible accelerograms in two near-field and far-field groups. Considering the maximum story drift as the demand parameter and selecting the interstory drift ratios (IDR) for the slight, moderate, extensive, and complete collapse seismic performance levels proposed by Hazus, IDA curves were plotted. Then, the seismic fragility curves were produced using the structural reliability relations. The median fragility at complete collapse damage level reduced from 0.73g, 0.62g, and 0.61g to 0.68g, 0.59, and 0.57g for the 15-, 25, and 35-story near-field and far-field earthquake models, respectively. This was attributed to increasing vulnerability and seismic fragility of the structures as a result of both height increase and distance reduction from fault. Based on the results, the most vulnerable structure, i.e., the 35-story near-fault model, experienced a 40, 17, 18, and 6% increase in median fragility at slight, moderate, extensive, and complete collapse damage levels, respectively.