• Title/Summary/Keyword: Monte-Carlo(MC)

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Correlation between chloride-induced corrosion initiation and time to cover cracking in RC Structures

  • Hosseini, Seyed Abbas;Shabakhty, Naser;Mahini, Seyed Saeed
    • Structural Engineering and Mechanics
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    • v.56 no.2
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    • pp.257-273
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    • 2015
  • Numerical value of correlation between effective parameters in the strength of a structure is as important as its stochastic properties in determining the safety of the structure. In this article investigation is made about the variation of coefficient of correlation between effective parameters in corrosion initiation time of reinforcement and the time of concrete cover cracking in reinforced concrete (RC) structures. Presence of many parameters and also error in measurement of these parameters results in uncertainty in determination of corrosion initiation and the time to crack initiation. In this paper, assuming diffusion process as chloride ingress mechanism in RC structures and considering random properties of effective parameters in this model, correlation between input parameters and predicted time to corrosion is calculated using the Monte Carlo (MC) random sampling. Results show the linear correlation between corrosion initiation time and effective input parameters increases with increasing uncertainty in the input parameters. Diffusion coefficient, concrete cover, surface chloride concentration and threshold chloride concentration have the highest correlation coefficient respectively. Also the uncertainty in the concrete cover has the greatest impact on the coefficient of correlation of corrosion initiation time and the time of crack initiation due to the corrosion phenomenon.

Improvement and verification of the DeCART code for HTGR core physics analysis

  • Cho, Jin Young;Han, Tae Young;Park, Ho Jin;Hong, Ser Gi;Lee, Hyun Chul
    • Nuclear Engineering and Technology
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    • v.51 no.1
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    • pp.13-30
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    • 2019
  • This paper presents the recent improvements in the DeCART code for HTGR analysis. A new 190-group DeCART cross-section library based on ENDF/B-VII.0 was generated using the KAERI library processing system for HTGR. Two methods for the eigen-mode adjoint flux calculation were implemented. An azimuthal angle discretization method based on the Gaussian quadrature was implemented to reduce the error from the azimuthal angle discretization. A two-level parallelization using MPI and OpenMP was adopted for massive parallel computations. A quadratic depletion solver was implemented to reduce the error involved in the Gd depletion. A module to generate equivalent group constants was implemented for the nodal codes. The capabilities of the DeCART code were improved for geometry handling including an approximate treatment of a cylindrical outer boundary, an explicit border model, the R-G-B checker-board model, and a super-cell model for a hexagonal geometry. The newly improved and implemented functionalities were verified against various numerical benchmarks such as OECD/MHTGR-350 benchmark phase III problems, two-dimensional high temperature gas cooled reactor benchmark problems derived from the MHTGR-350 reference design, and numerical benchmark problems based on the compact nuclear power source experiment by comparing the DeCART solutions with the Monte-Carlo reference solutions obtained using the McCARD code.

Sensitivity analysis of flexural strength of RC beams influenced by reinforcement corrosion

  • Hosseini, Seyed A.;Shabakhty, Naser;Khankahdani, Fardin Azhdary
    • Structural Engineering and Mechanics
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    • v.72 no.4
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    • pp.479-489
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    • 2019
  • The corrosion of reinforcement leads to a gradual decay of structural strength and durability. Several models for crack occurrence prediction and crack width propagation are investigated in this paper. Analytical and experimental models were used to predict the bond strength in the period of corrosion propagation. The manner of flexural strength loss is calculated by application of these models for different scenarios. As a new approach, the variation of the concrete beam neutral axis height has been evaluated, which shows a reduction in the neutral axis height for the scenarios without loss of bond. Alternatively, an increase of the neutral axis height was observed for the scenarios including bond and concrete section loss. The statistical properties of the parameters influencing the strength have been deliberated associated with obtaining the time-dependent bending strength during corrosion propagation, using Monte Carlo (MC) random sampling method. Results showed that the ultimate strain in concrete decreases significantly as a consequence of the bond strength reduction during the corrosion process, when the section reaches to its final limit. Therefore, such sections are likely to show brittle behavior.

A Markov-based prediction model of tunnel geology, construction time, and construction costs

  • Mahmoodzadeh, Arsalan;Mohammadi, Mokhtar;Ali, Hunar Farid Hama;Salim, Sirwan Ghafoor;Abdulhamid, Sazan Nariman;Ibrahim, Hawkar Hashim;Rashidi, Shima
    • Geomechanics and Engineering
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    • v.28 no.4
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    • pp.421-435
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    • 2022
  • The necessity of estimating the time and cost required for tunnel construction has led to extensive research in this regard. Since geological conditions are significant factors in terms of time and cost of road tunnels, considering these conditions is crucial. Uncertainties about the geological conditions of a tunnel alignment cause difficulties in planning ahead of the required construction time and costs. In this paper, the continuous-space, discrete-state Markov process has been used to predict geological conditions. The Monte-Carlo (MC) simulation (MCS) method is employed to estimate the construction time and costs of a road tunnel project using the input data obtained from six tunneling expert questionnaires. In the first case, the input data obtained from each expert are individually considered and in the second case, they are simultaneously considered. Finally, a comparison of these two modes based on the technique presented in this article suggests considering views of several experts simultaneously to reduce uncertainties and ensure the results obtained for geological conditions and the construction time and costs.

Enhancing the radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty quantification

  • Nguyen, Duc Hai;Kwon, Hyun-Han;Yoon, Seong-Sim;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.123-123
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    • 2020
  • The present study is aimed to correcting radar-based mean areal precipitation forecasts to improve urban flood predictions and uncertainty analysis of water levels contributed at each stage in the process. For this reason, a long short-term memory (LSTM) network is used to reproduce three-hour mean areal precipitation (MAP) forecasts from the quantitative precipitation forecasts (QPFs) of the McGill Algorithm for Precipitation nowcasting by Lagrangian Extrapolation (MAPLE). The Gangnam urban catchment located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 24 heavy rainfall events, 22 grid points from the MAPLE system and the observed MAP values estimated from five ground rain gauges of KMA Automatic Weather System. The corrected MAP forecasts were input into the developed coupled 1D/2D model to predict water levels and relevant inundation areas. The results indicate the viability of the proposed framework for generating three-hour MAP forecasts and urban flooding predictions. For the analysis uncertainty contributions of the source related to the process, the Bayesian Markov Chain Monte Carlo (MCMC) using delayed rejection and adaptive metropolis algorithm is applied. For this purpose, the uncertainty contributions of the stages such as QPE input, QPF MAP source LSTM-corrected source, and MAP input and the coupled model is discussed.

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Search for Dark Photon in e+e- → A'A' Using Future Collider Experiments

  • Kihong Park;Kyungho Kim;Alexei Sytov;Kihyeon Cho
    • Journal of Astronomy and Space Sciences
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    • v.40 no.4
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    • pp.259-266
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    • 2023
  • The Standard Model (SM) does not provide an information for 26% of dark matter of the universe. In the dark sector, dark matter is supposed to be linked with the hypothetical particles called dark photons that have similar role to photons in electromagnetic interaction in the SM. Besides astronomical observation, there are studies to find dark matter candidates using accelerators. In this paper, we searched for dark photons using future electron-positron colliders, including Circular Electron Positron Collider (CEPC)/CEPC, Future Circular Collider (FCC-ee)/Innovative Detector for Electron-positron Accelerator (IDEA), and International Linear Collider (ILC)/International Large Detector (ILD). Using the parameterized response of the detector simulation of Delphes, we studied the sensitivity of a double dark photon mode at each accelerator/detector. The signal mode is double dark photon decay channel, e+e- → A'A', where A' (dark photon with spin 1) decaying into a muon pair. We used MadGraph5 to generate Monte Carlo (MC) events by means of a Simplified Model. We found the dark photon mass at which the cross-sections were the highest for each accelerator to obtain the maximum number of events. In this paper we show the expected number of dark photon signal events and the detector efficiency of each accelerator. The results of this study can facilitate in the dark photon search by future electron-positron accelerators.

Trends in Materials Modeling and Computation for Metal Additive Manufacturing

  • Seoyeon Jeon;Hyunjoo Choi
    • Journal of Powder Materials
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    • v.31 no.3
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    • pp.213-219
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    • 2024
  • Additive Manufacturing (AM) is a process that fabricates products by manufacturing materials according to a three-dimensional model. It has recently gained attention due to its environmental advantages, including reduced energy consumption and high material utilization rates. However, controlling defects such as melting issues and residual stress, which can occur during metal additive manufacturing, poses a challenge. The trial-and-error verification of these defects is both time-consuming and costly. Consequently, efforts have been made to develop phenomenological models that understand the influence of process variables on defects, and mechanical/ electrical/thermal properties of geometrically complex products. This paper introduces modeling techniques that can simulate the powder additive manufacturing process. The focus is on representative metal additive manufacturing processes such as Powder Bed Fusion (PBF), Direct Energy Deposition (DED), and Binder Jetting (BJ) method. To calculate thermal-stress history and the resulting deformations, modeling techniques based on Finite Element Method (FEM) are generally utilized. For simulating the movements and packing behavior of powders during powder classification, modeling techniques based on Discrete Element Method (DEM) are employed. Additionally, to simulate sintering and microstructural changes, techniques such as Monte Carlo (MC), Molecular Dynamics (MD), and Phase Field Modeling (PFM) are predominantly used.

Feasibility study of spent fuel internal tomography (SFIT) for partial defect detection within PWR spent nuclear fuel

  • Hyung-Joo Choi;Hyojun Park;Bo-Wi Cheon;Hyun Joon Choi;Hakjae Lee;Yong Hyun Chung;Chul Hee Min
    • Nuclear Engineering and Technology
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    • v.56 no.6
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    • pp.2412-2420
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    • 2024
  • The International Atomic Energy Agency (IAEA) mandates safeguards to ensure non-proliferation of nuclear materials. Among inspection techniques used to detect partial defects within spent nuclear fuel (SNF), gamma emission tomography (GET) has been reported to be reliable for detection of partial defects on a pin-by-pin level. Conventional GET, however, is limited by low detection efficiency due to the high density of nuclear fuel rods and self-absorption. This paper proposes a new type of GET named Spent Fuel Internal Tomography (SFIT), which can acquire sinograms at the guide tube. The proposed device consists of the housing, shielding, C-shaped collimator, reflector, and gadolinium aluminum gallium garnet (GAGG) scintillator. For accurate attenuation correction, the source-distinguishable range of the SFIT device was determined using MC simulation to the region away from the proposed device to the second layer. For enhanced inspection accuracy, a proposed specific source-discrimination algorithm was applied. With this, the SFIT device successfully distinguished all source locations. The comparison of images of the existing and proposed inspection methods showed that the proposed method, having successfully distinguished all sources, afforded a 150 % inspection accuracy improvement.

An Application of Dirichlet Mixture Model for Failure Time Density Estimation to Components of Naval Combat System (디리슈레 혼합모형을 이용한 함정 전투체계 부품의 고장시간 분포 추정)

  • Lee, Jinwhan;Kim, Jung Hun;Jung, BongJoo;Kim, Kyeongtaek
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.42 no.4
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    • pp.194-202
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    • 2019
  • Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

Analysis of Interference Impact of UWB System on WiBro System (UWB 시스템에 의한 WiBro 시스템에서의 간섭영향에 관한 연구)

  • Yoon Young-Keun;Hong Heon-Jin;Lee Il-Kyoo;Choi Ik-Guen;Kwak Kyung-Sub
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.8A
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    • pp.814-819
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    • 2006
  • This paper presents the impacts of Ultra Wide-Band(UWB) system applied in Indoor and Handhold communications using frequency band from 3.1 GHz to 10.6 GHz on Wireless Broad-band(WiBro) system based on Orthogonal Frequency Division Multiplexing(OFDM) using frequency of 2.3 GHz. The Minimum Coupling Loss(MCL) method for the case of single interference and Monte Carlo(MC) simulation for multiple interference considering practical scenario were used to evaluate the interference effects of UWB system on WiBro system. As a result, the minimum separation distance between single interferer and the victim receiver required 34.4 m and above to guarantee the co-existence. Also, the UWB transmitting PSD of around - 81 dBm / MHz below should be required to meet the minimum throughput loss of WiBro mobile station in case of multiple UWB interference.