• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1163-1170
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• 2009

Reliability analysis is of great importance in the advanced product design, which is to evaluate reliability due to the associated uncertainties. There are three types of uncertainties: the first is the aleatory uncertainty which is related with inherent physical randomness that is completely described by a suitable probability model. The second is the epistemic uncertainty, which results from the lack of knowledge due to the insufficient data. These two uncertainties are encountered in the input variables such as dimensional tolerances, material properties and loading conditions. The third is the metamodel uncertainty which arises from the approximation of the response function. In this study, an integrated method for the reliability analysis is proposed that can address all these uncertainties in a single Bayesian framework. Markov Chain Monte Carlo (MCMC) method is employed to facilitate the simulation of the posterior distribution. Mathematical and engineering examples are used to demonstrate the proposed method.

• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.311-330
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• 2007

Model-based predictions of structural behavior are negatively affected by uncertainties of various type and in various stages of the structural analysis. The present paper focusses on dynamic analysis and addresses the effects of uncertainties concerning material and geometric parameters, mainly in the context of modal analysis of large-scale structures. Given the large number of uncertain parameters arising in this case, highly scalable simulation-based methods are adopted, which can deal with possibly thousands of uncertain parameters. In order to solve the reliability problem, i.e., the estimation of very small exceedance probabilities, an advanced simulation method called Line Sampling is used. In combination with an efficient algorithm for the estimation of the most important uncertain parameters, the method provides good estimates of the failure probability and enables one to quantify the error in the estimate. Another aspect here considered is the uncertainty quantification for closely-spaced eigenfrequencies. The solution here adopted represents each eigenfrequency as a weighted superposition of the full set of eigenfrequencies. In a case study performed with the FE model of a satellite it is shown that the effects of uncertain parameters can be very different in magnitude, depending on the considered response quantity. In particular, the uncertainty in the quantities of interest (eigenfrequencies) turns out to be mainly caused by very few of the uncertain parameters, which results in sharp estimates of the failure probabilities at low computational cost.

• Smart Structures and Systems
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• v.22 no.4
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• pp.441-457
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• 2018

Characteristic parameter values of seismic isolators deviate from their nominal design values due to uncertainties and/or errors in their material properties and element dimensions, etc. Deviations may increase over service life due to environmental effects and service conditions. For accurate evaluation of the seismic safety level, all such effects, which would result in deviations in the structural response, need to be taken into account. In this study, the sensitivity of the probability of failure of the structures equipped with nonlinear base isolation systems to the uncertainties in various isolation system characteristic parameters is investigated in terms of various isolation system and superstructure response parameters in the context of a realistic three-dimensional base-isolated building model via Monte Carlo Simulations. The inherent record-to-record variability nature of the earthquake ground motions is also taken into account by carrying out analyses for a large number of ground motion records which are classified as those with and without forward-directivity effects. Two levels of nominal isolation periods each with three different levels of uncertainty are considered. Comparative plots of cumulative distribution functions and related statistical evaluation presented here portray the potential extent of the deviation of the structural response parameters resulting from the uncertainties and the uncertainty levels considered, which is expected to be useful for practicing engineers in evaluating isolator test results for their projects.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.57-65
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• 2024

In a fire-resistant structure, uncertainties arise in factors such as ventilation, material elasticity modulus, yield strength, coefficient of thermal expansion, external forces, and fire location. The ventilation uncertainty affects thefactor contributes to uncertainties in fire temperature, subsequently impacting the structural temperature. These temperatures, combined with material properties, give rise to uncertain structural responses. Given the nonlinear behavior of structures under fire conditions, calculating fire fragility traditionally involves time-consuming Monte Carlo simulations. To address this, recent studies have explored leveraging machine learning algorithms to predict fire fragility, aiming to enhance efficiency while maintaining accuracy. This study focuses on predicting the fire fragility of a steel moment frame building, accounting for uncertainties in fire size, location, and structural material properties. The fragility curve, derived from nonlinear structural behavior under fire, follows a log-normal distribution. The results demonstrate that the proposed method accurately and efficiently predicts fire fragility, showcasing its effectiveness in streamlining the analysis process.

• Structural Engineering and Mechanics
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• v.46 no.1
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• pp.53-73
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• 2013

Prediction of prestressed concrete girder integral abutment bridge (IAB) load effect requires understanding of the inherent uncertainties as it relates to thermal loading, time-dependent effects, bridge material properties and soil properties. In addition, complex inelastic and hysteretic behavior must be considered over an extended, 75-year bridge life. The present study establishes IAB displacement and internal force statistics based on available material property and soil property statistical models and Monte Carlo simulations. Numerical models within the simulation were developed to evaluate the 75-year bridge displacements and internal forces based on 2D numerical models that were calibrated against four field monitored IABs. The considered input uncertainties include both resistance and load variables. Material variables are: (1) concrete elastic modulus; (2) backfill stiffness; and (3) lateral pile soil stiffness. Thermal, time dependent, and soil loading variables are: (1) superstructure temperature fluctuation; (2) superstructure concrete thermal expansion coefficient; (3) superstructure temperature gradient; (4) concrete creep and shrinkage; (5) bridge construction timeline; and (6) backfill pressure on backwall and abutment. IAB displacement and internal force statistics were established for: (1) bridge axial force; (2) bridge bending moment; (3) pile lateral force; (4) pile moment; (5) pile head/abutment displacement; (6) compressive stress at the top fiber at the mid-span of the exterior span; and (7) tensile stress at the bottom fiber at the mid-span of the exterior span. These established IAB displacement and internal force statistics provide a basis for future reliability-based design criteria development.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3493-3505
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• 2023

Reactor containment buildings serve as the last barrier to prevent radioactive leakage due to accidents and their safety is crucial in overpressurization conditions. Thus, the Regulatory Guide (RG) 1.216 has mentioned the global strain as one of failure criteria in the free-field for cylindrical prestressed concrete containment vessels (PCCV) subject to internal pressure. However, there is a limit that RG 1.216 shows the free-field without the specific locations of failure criteria and also the global strain corresponding to only azimuth 135° has been mentioned in NUREG/CR-6685, regardless of the elevations of the structure. Therefore, in order to reevaluate the failure criteria of the 1:4 scaled PCCV, the high fidelity simulation model based on the experimental test was significantly validated in this study, and it was interesting to find that the experimental and numerical result was very close to each other. In addition, for the consideration of the material uncertainties, the Latin hypercube method was used as a statistical approach. Consequently, it was revealed that the radial displacements of various azimuth area such as 120°, 135°, 150°, 180° and 210° at elevations 4680 mm and 6,200 mm can represent as the global deformation at the free-field, obtained from the statistical approach.

• Coupled systems mechanics
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• v.12 no.5
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• pp.429-444
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• 2023

The comprehension and structural modeling of masonry constructions is fundamental to safeguard the integrity of built cultural assets and intervene through adequate actions, especially in earthquake-prone regions. Despite the availability of several modeling strategies and modern computing power, modeling masonry remains a great challenge because of still demanding computational efforts, constraints in performing destructive or semi-destructive in-situ tests, and material uncertainties. This paper investigates the shear behavior of masonry walls by applying a plane-stress FE continuum model with the Modified Masonry-like Material (MMLM). Epistemic uncertainty affecting input parameters of the MMLM is considered in a probabilistic framework. After appointing a suitable probability density function to input quantities according to prior engineering knowledge, uncertainties are propagated to outputs relying on gPCE-based surrogate models to considerably speed up the forward problem-solving. The sensitivity of the response to input parameters is evaluated through the computation of Sobol' indices pointing out the parameters more worthy to be further investigated, when dealing with the seismic assessment of masonry buildings. Finally, masonry mechanical properties are calibrated in a probabilistic setting with the Bayesian approach to the inverse problem based on the available measurements obtained from the experimental load-displacement curves provided by shear compression in-situ tests.

• Structural Engineering and Mechanics
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• v.74 no.6
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• pp.771-787
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• 2020

The paper provides an inside look into experimental measurements, followed by numerical simulations and their related uncertainties. The goal of the paper is to present findings related to blast loading and the handling of defects that are inherent in experiments. Very often it might seem that experiments are simplified reflections of real-life conditions. In most cases this is true, but there is a good reason for that. The more complex an experiment is, the larger the amount of uncertainties that can be expected. This especially applies when the blast loading of concrete is the subject of research. When simulations fail to reproduce the results of experimental measurements, it does not necessarily mean there is something wrong with the numerical model. The problem could be missing information. Put differently, the numerical simulation may lack information that seemed irrelevant with regard to the experiment. In the presented case, a reference simulation with a proven material model unexpectedly failed to replicate the results of an experiment where concrete slabs were exposed to blast loading. This resulted in a search for possible unknowns. When all of the uncertainties were examined, the missing information turned out to be the orientation of the charge to the concrete slab. Since the experiment was burdened with error, a sensitivity study had to take place so the influence of this factor could be better understood. The findings point to the fact that even the smallest defect during experiments must somehow be taken into account when designing numerical simulations. Otherwise, the simulations are not correlated to the experiments, but merely to some expectations.

• Journal of the Korean Society for Railway
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• v.8 no.4
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• pp.348-353
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• 2005

In designing the structures of railway rolling stocks, deterministic methods associated with the concept of a safety factor have been traditionally used. The deterministic approaches based on the mean values of applied loads and material properties have been used as safety verification for the design of rolling-stock car body structures. The uncertainties in the applied loading for the high speed train and the strength of new materials in the rolling stocks require the application of probabilistic approaches to ensure fatigue safety in the desired system. Pressure loadings acting on the car body when the train passes through tunnels show reflected pressure waves for high-speed trains and they may cause a fatigue failure in vehicle bodies. Use of new material technology as body structures also introduces uncertainties in the material strength. A probabilistic approach is more adaptable in designing reliable structures when the pressure waves from the tunnels pounds and new material technology is adopted. In this paper, it is proposed that a fatigue design and assessment method based on a reliability which deals with the loading variations on a railway vehicle due to the pressure reflected in tunnels and the strength variations of material. Equation for the fatigue reliability index has been formulated to calculate the reliability assessment of a vehicle body under fluctuating pressure loadings in a tunnel. Considered in this formulation are the pressure distribution characteristics, the fatigue strength distribution characteristics, and the concept of stress-transfer functions due to the pressure loading.

• Journal of Environmental Analysis, Health and Toxicology
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• v.21 no.4
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• pp.209-219
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• 2018

In the areas of RoHS, WEEE, ELV and REACH, reinforcement of environmental regulations against harmful substances is a global trend not only in EC but also in all over the world. In the fields of Korea's major export products such as material parts, electrical and electronic products and automobile parts, we are responding to these regulations consistently. To develop reference material for analyzing lead and cadmium in paints, the candidate materials were produced through the screening process which separated shapes and sizes. To secure the traceability of the candidate materials produced, the characteristics and uncertainties are estimated by ICP-AES analysis using the primary reference material. The short-term and long-term stabilities also are evaluated in parallel. In order to calculate the final certification value of the candidate material, the verification were carried out by the performance evaluation through the comparison among the KOLAS (Korea Laboratory Accreditation Scheme) laboratories, and the CRM was produced in accordance with ISO Guide 35. The certified values and uncertainties of Pb and Cd of the final paint standard, determined according to the joint analysis among laboratories, are Pb [($191.4{\pm}3.1$) mg/kg, ($944.1{\pm}5.6$) mg/kg] and Cd [($45.0{\pm}2.6$) mg/kg, ($225.5{\pm}3.5$) mg/kg]. These standard materials were developed to enhance the reliability of measurement analysis, including the validity and traceability of measurement results. Also it is expected that the CRM will be used as QCM (quality control material) for the product design and the process monitoring, so that regulation and management of hazardous heavy metals can be systematically implemented.