• Title/Summary/Keyword: probabilistic study

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Methodology of seismic-response-correlation-coefficient calculation for seismic probabilistic safety assessment of multi-unit nuclear power plants

  • Eem, Seunghyun;Choi, In-Kil;Yang, Beomjoo;Kwag, Shinyoung
    • Nuclear Engineering and Technology
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    • v.53 no.3
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    • pp.967-973
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    • 2021
  • In 2011, an earthquake and subsequent tsunami hit the Fukushima Daiichi Nuclear Power Plant, causing simultaneous accidents in several reactors. This accident shows us that if there are several reactors on site, the seismic risk to multiple units is important to consider, in addition to that to single units in isolation. When a seismic event occurs, a seismic-failure correlation exists between the nuclear power plant's structures, systems, and components (SSCs) due to their seismic-response and seismic-capacity correlations. Therefore, it is necessary to evaluate the multi-unit seismic risk by considering the SSCs' seismic-failure-correlation effect. In this study, a methodology is proposed to obtain the seismic-response-correlation coefficient between SSCs to calculate the risk to multi-unit facilities. This coefficient is calculated from a probabilistic multi-unit seismic-response analysis. The seismic-response and seismic-failure-correlation coefficients of the emergency diesel generators installed within the units are successfully derived via the proposed method. In addition, the distribution of the seismic-response-correlation coefficient was observed as a function of the distance between SSCs of various dynamic characteristics. It is demonstrated that the proposed methodology can reasonably derive the seismic-response-correlation coefficient between SSCs, which is the input data for multi-unit seismic probabilistic safety assessment.

Internal Event Level 1 Probabilistic Safety Assessment for Korea Research Reactor (국내 연구용원자로 전출력 내부사건 1단계 확률론적안전성평가)

  • Lee, Yoon-Hwan;Jang, Seung-Cheol
    • Journal of the Korean Society of Safety
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    • v.36 no.3
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    • pp.66-73
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    • 2021
  • This report documents the results of an at-power internal events Level 1 Probabilistic Safety Assessment (PSA) for a Korea research reactor (KRR). The aim of the study is to determine the accident sequences, construct an internal level 1 PSA model, and estimate the core damage frequency (CDF). The accident quantification is performed using the AIMS-PSA software version 1.2c along with a fault tree reliability evaluation expert (FTREX) quantification engine. The KRR PSA model is quantified using a cut-off value of 1.0E-15/yr to eliminate the non-effective minimal cut sets (MCSs). The final result indicates a point estimate of 4.55E-06/yr for the overall CDF attributable to internal initiating events in the core damage state for the KRR. Loss of Electric Power (LOEP) is the predominant contributor to the total CDF via a single initiating event (3.68E-6/yr), providing 80.9% of the CDF. The second largest contributor is the beam tube loss of coolant accident (LOCA), which accounts for 9.9% (4.49E-07/yr) of the CDF.

Modifications to fire resistance ratings of steel frames based on structural configuration: A probabilistic-based approach

  • Behnam, Behrouz
    • Structural Engineering and Mechanics
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    • v.77 no.5
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    • pp.661-672
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    • 2021
  • In this article, the role of spans number and length in fire-resistance ratings (FRRs) of fireproofed steel frames are investigated. First, over a span-lengthening scenario, two one- and three-bay frames under the ISO834 fire are examined. It is shown that the FRRs of the frames rely highly on the changes made on their span length. Second, a building designed for three spans number of three, four, and five under natural fire is investigated. The beams are designed for two load-capacity-ratios (LCRs) of optimum and ultimate. The fire curves are determined through a probabilistic-based approach. It is shown that the structural vulnerability vastly increases while the number of spans decreases. The results show that for an optimum LCR, while the five-span frame can meet the required FRR in 87% of the fire scenarios, the four- and three-span frames can meet the required FRR in only 56%, and 50% of the fire scenarios, respectively. For an ultimate LCR, the five-, four- and three-span frames can meet the required FRR in 81%, 50%, and 37.5% of the fire scenarios, respectively. Functional solutions are then proposed to resolve the insufficiencies in the results and to rectify the application of the standard-based FRRs in the cases studied. The study here highlights how employing current standard-based FRRs can endanger structural safety if they are not connected to structural characteristics; a crucial hint specifically for the structural engineering community who may be not well familiar with the fundamentals of performance-based approaches.

Optimal earthquake intensity measures for probabilistic seismic demand models of ARP1400 reactor containment building

  • Nguyen, Duy-Duan;Thusa, Bidhek;Azad, Md Samdani;Tran, Viet-Linh;Lee, Tae-Hyung
    • Nuclear Engineering and Technology
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    • v.53 no.12
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    • pp.4179-4188
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    • 2021
  • This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R2), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

Probabilistic study on buildings with MTMD system in different seismic performance levels

  • Etedali, Sadegh
    • Structural Engineering and Mechanics
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    • v.81 no.4
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    • pp.429-441
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    • 2022
  • A probabilistic assessment of the seismic-excited buildings with a multiple-tuned-mass-damper (MTMD) system is carried out in the presence of uncertainties of the structural model, MTMD system, and the stochastic model of the seismic excitations. A free search optimization procedure of the individual mass, stiffness and, damping parameters of the MTMD system based on the snap-drift cuckoo search (SDCS) optimization algorithm is proposed for the optimal design of the MTMD system. Considering a 10-story structure in three cases equipped with single tuned mass damper (STMS), 5-TMD and 10-TMD, sensitivity analyses are carried out using Sobol' indices based on the Monte Carlo simulation (MCS) method. Considering different seismic performance levels, the reliability analyses are done using MCS and kriging-based MCS methods. The results show the maximum structural responses are more affected by changes in the PGA and the stiffness coefficients of the structural floors and TMDs. The results indicate the kriging-based MCS method can estimate the accurate amount of failure probability by spending less time than the MCS. The results also show the MTMD gives a significant reduction in the structural failure probability. The effect of the MTMD on the reduction of the failure probability is remarkable in the performance levels of life safety and collapse prevention. The maximum drift of floors may be reduced for the nominal structural system by increasing the TMDs, however, the complexity of the MTMD model and increasing its corresponding uncertainty sources can be caused a slight increase in the failure probability of the structure.

Blast fragility of base-isolated steel moment-resisting buildings

  • Dadkhah, Hamed;Mohebbi, Mohtasham
    • Earthquakes and Structures
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    • v.21 no.5
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    • pp.461-475
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    • 2021
  • Strategic structures are a potential target of the growing terrorist attacks, so their performance under explosion hazard has been paid attention by researchers in the last years. In this regard, the aim of this study is to evaluate the blast-resistance performance of lead-rubber bearing (LRB) base isolation system based on a probabilistic framework while uncertainties related to the charge weight and standoff distance have been taken into account. A sensitivity analysis is first performed to show the effect of explosion uncertainty on the response of base-isolated buildings. The blast fragility curve is then developed for three base-isolated steel moment-resisting buildings with different heights of 4, 8 and 12 stories. The results of sensitivity analysis show that although LRB has the capability of reducing the peak response of buildings under explosion hazard, this control system may lead to increase in the peak response of buildings under some explosion scenarios. This shows the high importance of probabilistic-based assessment of isolated structures under explosion hazard. The blast fragility analysis shows effective performance of LRB in mitigating the probability of failure of buildings. Therefore, LRB can be introduced as effective control system for the protection of buildings from explosion hazard regarding uncertainty effect.

Synthetic data generation by probabilistic PCA (주성분 분석을 활용한 재현자료 생성)

  • Min-Jeong Park
    • The Korean Journal of Applied Statistics
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    • v.36 no.4
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    • pp.279-294
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    • 2023
  • It is well known to generate synthetic data sets by the sequential regression multiple imputation (SRMI) method. The R-package synthpop are widely used for generating synthetic data by the SRMI approaches. In this paper, I suggest generating synthetic data based on the probabilistic principal component analysis (PPCA) method. Two simple data sets are used for a simulation study to compare the SRMI and PPCA approaches. Simulation results demonstrate that pairwise coefficients in synthetic data sets by PPCA can be closer to original ones than by SRMI. Furthermore, for the various data types that PPCA applications are well established, such as time series data, the PPCA approach can be extended to generate synthetic data sets.

Practical modeling and quantification of a single-top fire events probabilistic safety assessment model

  • Dae Il Kang;Yong Hun Jung
    • Nuclear Engineering and Technology
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    • v.55 no.6
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    • pp.2263-2275
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    • 2023
  • In general, an internal fire events probabilistic safety assessment (PSA) model is quantified by modifying the pre-existing internal event PSA model. Because many pieces of equipment or cables can be damaged by a fire, a single fire event can lead to multiple internal events PSA initiating events (IEs). Consequently, when the fire events PSA model is quantified, inappropriate minimal cut sets (MCSs), such as duplicate MCSs, may be generated. This paper shows that single quantification of a hypothetical single-top fire event PSA model may generate the following four types of inappropriate MCSs: duplicate MCSs, MCSs subsumed by other MCSs, nonsense MCSs, and MCSs with over-counted fire frequencies. Among the inappropriate MCSs, the nonsense MCSs should be addressed first because they can interfere with the right interpretation of the other MCSs and prevent the resolution of the issues related to the other inappropriate MCSs. In addition, we propose a resolution process for each of the issues caused by these inappropriate MCSs and suggest an overall procedure for resolving them. The results of this study will contribute to the understanding and resolution of the inappropriate MCSs that may appear in the quantification of fire events PSA models.

Machine learning-based probabilistic predictions of shear resistance of welded studs in deck slab ribs transverse to beams

  • Vitaliy V. Degtyarev;Stephen J. Hicks
    • Steel and Composite Structures
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    • v.49 no.1
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    • pp.109-123
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    • 2023
  • Headed studs welded to steel beams and embedded within the concrete of deck slabs are vital components of modern composite floor systems, where safety and economy depend on the accurate predictions of the stud shear resistance. The multitude of existing deck profiles and the complex behavior of studs in deck slab ribs makes developing accurate and reliable mechanical or empirical design models challenging. The paper addresses this issue by presenting a machine learning (ML) model developed from the natural gradient boosting (NGBoost) algorithm capable of producing probabilistic predictions and a database of 464 push-out tests, which is considerably larger than the databases used for developing existing design models. The proposed model outperforms models based on other ML algorithms and existing descriptive equations, including those in EC4 and AISC 360, while offering probabilistic predictions unavailable from other models and producing higher shear resistances for many cases. The present study also showed that the stud shear resistance is insensitive to the concrete elastic modulus, stud welding type, location of slab reinforcement, and other parameters considered important by existing models. The NGBoost model was interpreted by evaluating the feature importance and dependence determined with the SHapley Additive exPlanations (SHAP) method. The model was calibrated via reliability analyses in accordance with the Eurocodes to ensure that its predictions meet the required reliability level and facilitate its use in design. An interactive open-source web application was created and deployed to the cloud to allow for convenient and rapid stud shear resistance predictions with the developed model.

PROBABILISTIC MODEL-BASED APPROACH FOR TIME AND COST DATA : REGARDING FIELD CONDITIONS AND LABOR PRODUCTIVITY

  • ChangTaek Hyun;TaeHoon Hong;SoungMin Ji;JunHyeok Yu;SooBae An
    • International conference on construction engineering and project management
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    • 2011.02a
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    • pp.256-261
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    • 2011
  • Labor productivity is a significant factor related to control time, cost, and quality. Many researchers have developed models to define method of measuring the relationship between productivity and various constraints such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only contains the average productivity data of the construction industry, and it is difficult to predict the time and cost of any particular project; hence, there are some errors in estimating duration and cost for individual activity and project. To address these issues, this research collects data, measures productivity, and develops time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites and it is possible that the result will be used as the EVMS baseline of cost management and schedule management.

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