Probabilistic Performance Assessment Research Articles

Time-dependent fragility analysis of a nuclear containment structure under internal pressure and chloride-induced corrosion

The prestressed concrete containment structure, serving as the ultimate barrier against nuclear fuel leakage, holds paramount importance in ensuring the uninterrupted operation of nuclear power plants. Particularly in the aftermath of the Fukushima nuclear disaster, the influence of material aging and degradation of containment structures has been emphasized. Consequently, a probabilistic performance assessment of containment structures under chloride-induced corrosion condition is of significant relevance. This study presents a method for time-dependent fragility analysis of nuclear containment structures subjected to internal pressure, considering the effect of chloride-induced corrosion of steel reinforcement. A highly efficient and accurate finite element model with multi-layered shell element is formulated for damage and failure analysis. Furthermore, a corrosion degradation model of reinforced concrete, aligned with the attributes of multi-layered shell elements, is derived to reduce the reduce parameter samples generated by Latin Hypercube sampling technique. Material uncertainties and time-dependent effects are jointly integrated into the finite element analysis process, culminating in the establishment of fragility curves for the containment structure under various service lifetimes. The results indicate that within first 40 years of service, the load-bearing capacity of the containment structure has slightly decreased, while the probabilities of functional and structural failures in the containment structure will significantly increase after 60 years of service.

SMA-braced steel frames influenced by temperature: Practical modelling strategy and probabilistic performance assessment

This study presents a practical and efficient modelling approach for shape memory alloy (SMA)-braced steel frames under various temperatures, and examines their probabilistic performance affected by temperature. A one-dimensional constitutive model is developed in OpenSees to capture the superelasticity (SE), partial SE, shape memory effect (SME), and permanent yielding behaviors of SMA elements subjected to varying temperatures. The proposed modelling approach is partly validated against an experimental study newly conducted in the present work. The material-level investigation is followed by a comprehensive probabilistic performance assessment of a typical steel frame employing SMA-based self-centering braces (SMA-SCBs), where a practical and realistic modelling strategy for the SMA-SCB is developed to capture the degradation behavior, especially at low temperatures. Seismic risk assessment is conducted to evaluate the collapse resistance and resilience performance of the considered structures, with the influence of temperature highlighted. Among other important findings, it is shown that the decrease in environment temperature significantly increases the peak inter-story drift (PID) and residual inter-story drift (RID) responses. Under the maximum considered earthquake (MCE), the probability of collapse increases from 2.7% to 19.7% when the temperature decreases from 30 °C to −15 °C. From a self-centering capability point of view, the probabilistic of exceedance of 0.5% RID threshold soars from negligible to nearly 100%, considering the same temperature variation. The study highlights the fact that temperature plays a significant role in the annual rate of exceedance of all damage states, and warns that the idealized flag-shaped modelling approach for SMA components is extremely unsafe at low temperatures.

Influence of uncertainties on the seismic performance of steel moment resisting frames

The present paper investigates the probabilistic assessment of the seismic performance of steel MRFs designed according to Eurocodes. The considered MRFs are three- and five-storey high and are analysed by the multiple stripe method of analysis by means of sets of earthquake ground motions that depend in frequency content, energy and duration on the value of the selected seismic intensity measure. Additional uncertainties are related to the mechanical properties of steel, dead and live loads and equivalent viscous damping ratio. Different criteria are defined to assess the performance at the achievement of different limit states, in terms of interstorey drifts and damage indexes. To reach a synthetic evaluation of the seismic performances, the mean annual frequency of exceedance of the assigned limit state condition is also reported. Based on a Monte Carlo simulation the paper evaluates the effects of the single uncertainties on the seismic performances and suggests proper modifications to the simplified approach included in FEMA documents to mime the results of a full probabilistic approach.

Probabilistic Models for Temperature-Dependent Compressive and Tensile Strengths of Timber

Reliable reduction factors for timber mechanical properties at elevated temperatures are needed to design timber structures for fire safety as well as to assess the safety of historic timber structures against fire hazards. In this paper, a compilation of the available data on the compressive and tensile strengths of timber at elevated temperatures is carried out. Then, a probabilistic modeling approach to predict the temperature-dependent reduction factors applicable to fire design is proposed. The collected data cover both solid and engineered timber at temperatures from 20°C to 300°C, with a variety of sample sizes, wood species, test protocols, and moisture content used in the experiments. The data revealed a large scatter in elevated temperature strengths, and a large conservativeness of the relationships of the current European standard, which is commonly used for the advanced design of timber structures under fire. To address this variability, multiple probability density functions were calibrated across the temperature range, quantifying the goodness of fit with statistical criteria. Two-parameter Weibull functions provided the best fit, and continuous temperature-dependent relationships were derived for the parameters of the distribution. The proposed probabilistic models can be implemented in a numerical code, facilitating their use in analytical and computational approaches, and can be applied to the probabilistic assessment of the structural performance and reliability of timber structures against fire.

Probabilistic performance assessment of eccentric braced frames using artificial neural networks combined with correlation latin hypercube sampling

Hysteretic behavior of shear links has a vital role in seismic responses of Eccentric Braced Frames (EBFs). So, their behavioral parameters have been suggested recently in order to predict their hysteresis behavior. For shear links, modeling variables have been defined through seven implicit parameters all of which having specific Coefficient of Variation (COV), and variation in these parameters may affect the structural responses. However, the effect of uncertainties in these parameters on the structural responses has not been yet addressed. In this paper, variations of seismic structural responses due to the variations in the behavioral parameters of shear links have been investigated while trying to maintain a balance between the accuracy of predicted responses and the required computational effort. For this purpose, a 4-story EBF system has been modeled and studied. Incremental Dynamic Analysis (IDA) has been employed in order to attain the seismic responses while the spectral acceleration corresponding to different performance levels (Sa(T1,5%)) is used as the Intensity Measure (IM). A sensitivity analysis is carried out to rank the modeling parameters by their effect on seismic responses of the system in two performance levels. Then, Correlation Latin Hypercube Sampling (CLHS) method has been used to propagate the uncertainties of important modeling parameters into the structural responses of the frame. In the next step, Function Approximation (FA) with Artificial Neural Networks (ANNs) is used as a practical method to approximate the structural responses with lower computational effort. Screening design has been employed to consider the most optimum input data to train the network. ANNs in conjunction with CLHS provides a very efficient tool to address the effect of uncertainties in structural responses requiring lower computational effort. It has been found that web thickness and yielding strength of shear link play a key role in variation of seismic structural responses for the model studied. Moreover, incorporating modeling uncertainties may shift the median value of the probability distribution for structural responses.

Assessing the contribution of dynamical downscaling to austral autumn Northeast Brazil seasonal precipitation prediction performance

This study aims to assess the contribution to prediction performance of dynamically downscaling seasonal precipitation for the Brazilian Northeast region (NEB) produced in February with a global climate model for the austral autumn (March-April-May). This season includes the peak precipitation period of a large portion of this region. To achieve this aim, 32 years of hindcasts for the period 1979–2010 were produced with a regional model known as the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) run at 30 km spatial resolution, which was unidirectional nested to a global model run at approximately 200 km spatial resolution. The used global model was the Atmospheric General Circulation Models of the Brazilian Center for Weather Forecast and Climate Studies (CPTEC/AGCM), which provided initial and lateral boundary conditions for BRAMS. Hindcast ensembles of 10 members were produced with both the global and the regional models, simulating an operational prediction environment using persisted sea surface temperature (SST) anomalies observed in the previous January of each of the 32 hindcast years as oceanic boundary conditions. A comparative deterministic and probabilistic performance assessment of the two models was conducted. The deterministic assessment included the investigation of the mean error (bias) of the produced seasonal precipitation hindcasts, the degree of linear association between the observed and predicted precipitation anomalies measuring phase error through the correlation of the ensemble means with the corresponding observations, and amplitude error investigated through the ratio between the hindcast ensemble mean and observed variances. The probabilistic assessment was performed investigation the reliability, resolution, and discrimination characteristics of tercile probability predictions for the above normal and below normal categories, and also for probabilistic predictions for the occurrence of the symmetric event positive (or negative) precipitation anomaly. The two investigated modeling approaches showed similar performance, with an indication for dynamically downscaled predictions to have reduced amplitude error and slightly improved reliability and resolution compared to the predictions produced with the global model.

Probabilistic Seismic Assessment of CoSPSW Structures Using Fragility Functions

The corrugated steel plate shear wall (CoSPSW) is a new type of steel plate shear wall, in which corrugated wall plates instead of flat wall plates are adopted. The lateral stiffness and shear buckling capacity of the shear wall system could be significantly enhanced, and then, wall plate buckling under gravity loads would be mitigated. This paper presents a study on the probabilistic assessment of the seismic performance and vulnerability of CoSPSWs using fragility functions. The damage states and corresponding repair states of CoSPSWs were first established from experimental data. Then, incremental dynamic analyses were conducted on the CoSPSW structures. The structural and nonstructural fragility functions were developed, based on which the seismic performance and vulnerability of the CoSPSWs were obtained and compared with the conventional steel plate shear walls (SPSWs). It was shown that for various repair states, the 25th percentile PGA of the CoSPSW was always higher than the SPSWs with the same wall thickness and boundary frame, which indicated that the CoSPSW has a lower damage potential and better seismic performance than the SPSW.

Probabilistic performance assessment of seismically excited buildings with semi-active fluid viscous damper

Probabilistic performance assessment of seismically excited buildings with semi-active fluid viscous damper

Multi-objective optimization for probabilistic performance-based design of buildings using FEMA P-58 methodology

This research presents an automated performance-based optimal design process by integrating a multi-objective optimization algorithm and a comprehensive probabilistic performance assessment method. This process is used to provide a set of design options that comply with the minimum code requirements and are optimal in terms of both initial cost and mean annual repair cost. The FEMA P-58 methodology is utilized as a modern performance-based methodology to determine the various performance measures such as repair costs, repair time, casualty rates, environmental impacts, and unsafe placarding for the design alternatives. To account for uncertainties in the magnitude and intensity of future earthquakes, the time-based assessment, and to account for inherent uncertainties affecting seismic performance, the Monte Carlo procedure is performed in accordance with FEMA P-58 guideline. The optimization process is carried out using a well-known multi-objective optimization algorithm called NSGA-II for three example office buildings with 3-, 6- and 9-story steel moment frame structures. For each building, a detailed performance model including a set of fragility functions for the structural and non-structural components as well as contents typically present in the building is considered. Three optimal design options are selected from the Pareto front set obtained for each building based on different optimization objectives. They are compared with each other and with the other design alternatives in terms of various performance metrics under different ground motion intensities. The contribution of structural components as well as drift-, acceleration- and velocity-sensitive non-structural components to the repair costs of these optimal designs is investigated. It is shown that drift-sensitive nonstructural components have the largest contribution to the repair costs of optimal structures. The contribution of these components in earthquake events with a 29% probability of exceedance in 50 years (29%/50 yrs) is on average about 71%, which decreases to 55% with increasing seismic intensity to 3%/50 yrs.

Seismic performance assessment of reinforced concrete hilly buildings with open story

This study focuses on investigating the effect of one or more open stories in reinforced concrete hilly buildings. Two building configurations, i.e., (i) stepback and (ii) split-foundation, with three different story ratios, are considered. Open stories are provided at different levels in a building according to the prospective location of the approach road level. These buildings are subjected to bi-directional earthquake excitation, and non-linear dynamic analyses are performed under a suite of 22 ground motion records. Dynamic characteristics and seismic responses such as peak inter-story drift ratio, peak floor acceleration, peak roof displacement, and maximum story shear of the buildings are investigated. A probabilistic performance assessment of these buildings with different probable locations of the open story is presented. In general, the probabilistic assessment reveals that the presence of the open story significantly reduces the seismic performance of these buildings. Moreover, the buildings with the open story at the uppermost foundation level are found to be the most vulnerable under earthquake excitation.

Plutonium Disposition: Using and Explaining Complex Risk-Related Methods.

Applying risk assessment and management tools to plutonium disposition is a long-standing challenge for the U.S. government. The science is complicated, which has helped push risk assessment and management tools in new creative directions. Yet, communicating effectively about increasingly complicated risk-science issues like plutonium disposition requires careful planning and speakers who can address why specific tools are selected, the past record of applying these tools, why assumptions sometimes are applied instead of reliable data, and how uncertainty is characterized. Speakers addressing risk issues must also overcome obstacles in communication arising from expert-audience differences in knowledge and legal restrictions on disclosing information. This perspective seeks to highlight and illustrate five key risk questions, about probabilistic risk assessment (PRA) and performance assessment (PA) in the context of managing plutonium defense nuclear waste: objectives, experience, gaps, transparency, and difficulty of applying and communicating using each tool. While the general public needs to be involved, some issues require a level of expertise that is typically beyond local communities and therefore an expert panel should support community access.

Seismic Upgrading of Existing Reinforced Concrete Buildings Using Friction Pendulum Devices: A Probabilistic Evaluation

In many countries around the world a huge number of existing reinforced concrete (RC) structures have been realized without account for seismic detailing, even if they are located in areas subjected to high seismicity. In this context, several passive seismic protection techniques have been developed and applied to retrofit these structures such as, for an example, seismic isolation. The aim of this work is to characterize in probabilistic terms the seismic performance of a framed RC building retrofitted by means of sliding friction pendulum (FPS) devices. Specifically, the response of an existing RC building located in a high seismicity area in Italy is investigated. After the description of the main available information about the structure, a non-linear numerical model has been defined by means of fiber-elements approach. Then, non-linear dynamic analyses considering multiple recorded ground motions with the three accelerometric components have been carried out to assess the seismic response of the building with and without the retrofitting intervention composed of FPS isolators. Finally, the results are processed to achieve a probabilistic assessment of the seismic performance of the retrofitting intervention.

Probabilistic assessment of hydrologic retention performance of green roof considering aleatory and epistemic uncertainties

Abstract Green roofs (GRs) are well known for source control of runoff quantity in sustainable urban stormwater management. By considering the inherent randomness of rainfall characteristics, this study derives the probability distribution of rainfall retention ratio and its statistical moments. The distribution function of can be used to establish a unique relationship between target retention ratio , achievable reliability AR, and substrate depth h for the aleatory-based probabilistic (AP) GR design. However, uncertainties of epistemic nature also exist in the AP GR model that makes AR uncertain. In the paper, the treatment of epistemic uncertainty in the AP GR model is presented and implemented for the uncertainty quantification of AR. It is shown that design without considering epistemic uncertainties by the AP GR model yields about 50% confidence of meeting . A procedure is presented to determine the design substrate depth having the stipulated confidence to satisfy and target achievable reliability .

Multiple-Surrogate Models for Probabilistic Performance Assessment of Wind-Excited Tall Buildings under Uncertainties

AbstractPerformance-based design (PBD) is becoming a benchmark approach for design and performance assessment of civil structures because it facilitates communication between stakeholders and desig...

Surrogate SDOF models for probabilistic performance assessment of multistory buildings: Methodology and application for steel special moment frames

This paper proposes a methodology for generating surrogate single-degree-of-freedom (SDOF) models that can be utilized to estimate the probability distribution of the roof drift ratio of multistory buildings at various ground motion intensity measures. The use of an SDOF model as a surrogate for multistory buildings can significantly alleviate the high computational cost for probabilistic seismic demand assessment considering both model uncertainty and record-to-record variability. The surrogate SDOF model generated herein explicitly accounts for model uncertainties and can be used as an alternative to the nonlinear dynamic analysis of detailed building structures. Applications for such surrogate models include regional risk and resilience analyses and comprehensive parametric studies. To showcase the proposed methodology, an SDOF surrogate model for steel special moment frame (SMF) buildings is developed using the suggested surrogate SDOF model generating methodology. The properties of the surrogate model representing a multi-degree-of-freedom (MDOF) structure are computed using a probabilistic function of the fundamental period of the structure developed using Bayesian linear regression. To validate the surrogate model for SMFs, the response statistics produced using detailed multistory SMF models are compared with those of the corresponding surrogate SDOF models. The results show that the proposed surrogate SDOF model captures the probability distribution of the roof drift ratio of SMFs up to collapse with acceptable accuracy while reducing the runtime by at least one order of magnitude.

Probabilistic performance assessment of inelastic wind excited structures within the setting of distributed plasticity

The increasing interest in applying performance-based design to structures subject to severe wind has created the need for tools that can be used for the identification of appropriate probabilistic performance-based criteria for wind. This paper outlines the development of a framework to this end, which is based on describing safety against collapse through the occurrence of the state of dynamic shakedown. In particular, a formulation is introduced that enables the direct estimation of the inelastic strains and deformations occurring at shakedown for structural systems discretized through fiber-based distributed plasticity models and subject to stochastic wind loads. The efficiency of the proposed approach allows stochastic simulation to be employed in estimating the probability of system-level failure defined through general local and global limit states. A case study is presented illustrating how typical wind excited structural systems have significant plastic reserves that could be used in defining performance-based criteria for wind.

High-resolution time-dependent probabilistic assessment of the hydraulic performance for historic coastal structures: application to Luarca Breakwater.

Historic coastal structures have played a key role in small- to medium-size ports, being the driving force for the local development of coastal communities. Because coastal managers require reliable risk-based analysis of the whole life cycle of these coastal structures, previous lifetimes should be studied. This is a differentiating factor with respect to the newly built breakwaters. For this reason, in this work, a methodology for assessing how the hydraulic performance of an expired lifetime has evolved over the years is presented. It is performed following a probabilistic approach due to the uncertainty related to both the involved variables (wave climate, geometrical and structural breakwater variables) and the hydraulic response of the structure. The first ones are characterized by reliable probability distribution functions. The second ones are characterized by reliable formulae for the analysis of the hydraulic response. However, their non-conventional designs located in shallow-water locations require site-dependent formulae. To overcome this problem, a novel methodology to apply CFD numerical models is presented. Finally, it is integrated in a high-resolution time-dependent probabilistic methodology which takes into account the stochastic behaviour of all the involved variables, coastal and structural processes with a good uncertainty level. This article is part of the theme issue 'Environmental loading of heritage structures'.

Probabilistic performance assessment of power distribution infrastructure under wind events

The electric power delivery infrastructure directly contributes to essential societal functions, the economy, and the general quality of life. Recent extreme wind events, such as Hurricanes Irma and Maria, and more recently Hurricane Michael resulted in power outages that affected millions of customers and led to major social and economic disruptions throughout communities. The longer the outage duration, the greater the incurred losses. Power distribution systems have proven to be highly vulnerable to such events and responsible for 90% of the outages. Distribution structures are built according to safety standards to ensure the safety of assets in operational and extreme conditions, but the dynamic nature of the wind loading is often overlooked or only considered empirically. Therefore, in this paper, such effects are included in a comprehensive risk-informed framework to assess the performance of electric power distribution components. This methodology explicitly accounts for the inevitable uncertainty in predictions of the component response. The focus is on characterizing wind events and the component-level risk analysis of physical components of the electric power system. For this purpose, a power pole–conductor system is modeled in which wind events are simulated as one-dimensional multivariable stochastic processes along the height of the poles and the conductors. Three-second peak gust wind speeds are used as a modeling reference. A probabilistic framework is developed to estimate the capacity of the distribution poles under different aging mechanisms. The response of the power distribution poles due to the simulated wind speeds is then computed using a finite element analysis. Fragility functions are generated to estimate the probability of exceedance for different damage states. A set of hazard mitigation strategies, the associated costs, and estimated benefits are implemented, and the improved fragility functions for elements are generated. A probabilistic life-cycle cost analysis is used to assess the long-term benefits of investing in different components of the power distribution system.

Probabilistic performance assessment of shield tunnels subjected to accidental surcharges

Accidental surcharges caused by unauthorized damped waste are the most serious hazard threatening the serviceability and structural safety of shield tunnels in Shanghai, China. It is highly desirable to assess the effect of such accidental surcharges on the performance of shield tunnels. Nevertheless, the occurrence and magnitude of the accidental surcharges are both highly uncertain. In this paper, a probabilistic method is suggested to evaluate the performance of shield tunnels subjected to accidental surcharges, which can systematically consider the uncertainty in the soil properties, the uncertainty in the magnitude of the accidental surcharges, and the uncertainty of the occurrence of the accidental surcharges. The suggested method is used to analyse the potential effect of accidental surcharges on the safety of tunnels in Shanghai. It is found that the maximum height of the surcharges and the mean rate of the surcharges can significantly affect the performance of shield tunnels. Considering the past performance of shield tunnels can increase our confidence in the future performance of the tunnels. The suggested method provides a practical means to quantify the risk posed by the accidental surcharges to the performance of the shield tunnels.

Human–Robot Collaborative Site Inspection Under Resource Constraints

This paper is on human-robot collaborative site inspection and target classification. We consider the realistic case that human visual performance is imperfect (depending on the sensory input quality), and that the robot has constraints in communication with human (e.g., limited chances for query, poor channel quality). The robot has limited onboard motion and communication energy and operates in realistic channel environments experiencing path loss, shadowing, and multipath. We then show how to co-optimize motion, sensing, and human queries. Given a probabilistic assessment of human visual performance and a probabilistic channel prediction, we pose the co-optimization as multiple-choice multidimensional knapsack problems. We then propose a linear program-based efficient near-optimal solution, mathematically characterize the optimality gap, showing it to be very small, and mathematically characterize properties of the optimum solution. We then comprehensively validated the proposed approach with extensive real human data (from Amazon MTurk) and real channel data (from downtown San Francisco), confirming that the proposed approach significantly outperforms benchmark methodologies.