• Steel and Composite Structures
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• v.51 no.1
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• pp.25-41
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• 2024

The measurement of pile bearing capacity is crucial for the design of pile foundations, where in-situ tests could be costly and time needed. The primary objective of this research was to investigate the potential use of fuzzy-based techniques to anticipate the maximum weight that concrete driven piles might bear. Despite the existence of several suggested designs, there is a scarcity of specialized studies on the exploration of adaptive neuro-fuzzy inference systems (ANFIS) for the estimation of pile bearing capacity. This paper presents the introduction and validation of a novel technique that integrates the fire hawk optimizer (FHO) and equilibrium optimizer (EO) with the ANFIS, referred to as ANFIS_FHO and ANFIS_EO, respectively. A comprehensive compilation of 472 static load test results for driven piles was located within the database. The recommended framework was built, validated, and tested using the training set (70%), validation set (15%), and testing set (15%) of the dataset, accordingly. Moreover, the sensitivity analysis is performed in order to determine the impact of each input on the output. The results show that ANFIS_FHO and ANFIS_EO both have amazing potential for precisely calculating pile bearing capacity. The R² values obtained for ANFIS_FHO were 0.9817, 0.9753, and 0.9823 for the training, validating, and testing phases. The findings of the examination of uncertainty showed that the ANFIS_FHO system had less uncertainty than the ANFIS_EO model. The research found that the ANFIS_FHO model provides a more satisfactory estimation of the bearing capacity of concrete driven piles when considering various performance evaluations and comparing it with existing literature.

• Journal of the Korean earth science society
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• v.36 no.6
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• pp.567-579
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• 2015

The accurate simulation of micro-scale weather phenomena such as fog using the mesoscale meteorological models is a very complex task. Especially, the uncertainty arisen from initial input data of the numerical models has a decisive effect on the accuracy of numerical models. The data assimilation is required to reduce the uncertainty of initial input data. In this study, the limitation of the mesoscale meteorological model was verified by WRF (Weather Research and Forecasting) model for a summer fog event around the Nakdong river in Korea. The sensitivity analyses of simulation accuracy from the numerical model were conducted using two different initial and boundary conditions: KLAPS (Korea Local Analysis and Prediction System) and LDAPS (Local Data Assimilation and Prediction System) data. In addition, the improvement of numerical model performance by FDDA (Four-Dimensional Data Assimilation) using the observational data from AWS (Automatic Weather System) was investigated. The result of sensitivity analysis showed that the accuracy of simulated air temperature, dew point temperature, and relative humidity with LDAPS data was higher than those of KLAPS, but the accuracy of the wind speed of LDAPS was lower than that of KLAPS. Significant difference was found in case of relative humidity where RMSE (Root Mean Square Error) for LDAPS and KLAPS was 15.7 and 35.6%, respectively. The RMSE for air temperature, wind speed, and relative humidity was improved by approximately $0.3^{\circ}C$, $0.2m\;s^{-1}$, and 2.2%, respectively after incorporating the FDDA.

• Fire Science and Engineering
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• v.31 no.2
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• pp.52-60
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• 2017

Numerical simulations were performed to evaluate the habitability of an operator for a cabinet fire in the main control room of a nuclear power plant presented in NUREG-1934. To this end, a Fire Dynamics Simulator (FDS), as a representative fire model, was used. As the criteria for determining the habitability of operator, toxic products, such as CO, were also considered, as well as radiative heat flux, upper layer temperature, smoke layer height, and optical density of smoke. As a result, the probabilities of exceeding the criteria for habitability were evaluated through the sensitivity analysis of the major input parameters and the uncertainty analysis of fire model for various fire scenarios, based on V&V (Verification and Validation). Sensitivity analyses of the maximum heat release rate, CO and soot yields, showed that the habitable time and the limit criterion, which determined the habitability, could be changed. The present methodology will be a realistic alternative to enhancing the reliability for a habitability evaluation in the main control room using uncertain information of cabinet fires.

• Journal of Radiation Industry
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• v.17 no.4
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• pp.471-479
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• 2023

In In-situ radioactivity measurement techniques, efficiency calibration models use predefined models to simulate a sample's geometry and radioactivity distribution. However, simplified efficiency calibration models lead to uncertainties in the efficiency curves, which in turn affect the radioactivity concentration results. This study aims to develop an efficiency calibration optimization methodology to improve the accuracy of in-situ gamma radiation measurements for byproducts from industrial facilities. To accomplish the objective, a drive mechanism for rotational measurement of an byproduct simulator and a sample was constructed. Using ISOCS, an efficiency calibration model of the designed object was generated. Then, the sensitivity analysis of the efficiency calibration model was performed, and the efficiency curve of the efficiency calibration model was optimized using the sensitivity analysis results. Finally, the radiation concentration of the simulated subject was estimated, compared, and evaluated with the designed certification value. For the sensitivity assessment of the influencing factors of the efficiency calibration model, the ISOCS Uncertainty Estimator was used for the horizontal and vertical size and density of the measured object. The standard deviation of the measurement efficiency as a function of the longitudinal size and density of the efficiency calibration model decreased with increasing energy region. When using the optimized efficiency calibration model, the measurement efficiency using IUE was improved compared to the measurement efficiency using ISOCS at the energy of ²²⁸Ac (911 keV) for the nuclide under analysis. Using the ISOCS efficiency calibration method, the difference between the measured radiation concentration and the design value for each simulated subject measurement direction was 4.1% (1% to 10%) on average. The difference between the estimated radioactivity concentration and the design value was 3.6% (1~8%) on average when using the ISOCS IUE efficiency calibration method, which was closer to the design value than the efficiency calibration method using ISOCS. In other words, the estimated radioactivity concentration using the optimized efficiency curve was similar to the designed radioactivity concentration. The results of this study can be utilized as the main basis for the development of regulatory technologies for the treatment and disposal of waste generated during the operation, maintenance, and facility replacement of domestic byproduct generation facilities.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.5
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• pp.3-13
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• 2005

The present study examined the 3 dimensional space distribution characteristics of sea water intrusion using data available from previous observations. For this study, we used 3D FEMWATER, which is a 3 dimensional finite element model. The target area was around Daechang-ri, Gimje-si, Jeollabuk-do. The area is relatively easy to formulate a conceptual model and has observation wells in operation for surveying sea water intrusion. Considering the uncertainty of numerical simulation, we analyzed sensitivity to hydraulic conductivity, which has a relatively higher effect. According to the result of the analysis, the variation of TDS concentration had an error range of $-1,336{\~}+107 mg/{\iota}$. Taking note that the survey data from observation wells were collected when the boundary between fresh water and sea water in the aquifer was in equilibrium, we set the range of time for numerical simulation and estimated the spatial distribution of TDS concentration as the range of sea water intrusion. According to the result of estimation, the spatial distribution of TDS concentration calculated when 1,440 days were simulated was taken as the range of sea water intrusion. Using the result of calculation, we can draw not only vertical views for a certain section but also horizontal views of different depth. These views will be greatly helpful in understanding the spatial distribution of the range of sea water intrusion. In addition, the result of this study can be used rationally in proposing an optimal quantity of water pumping through investigating the moving route of sea water intrusion over time in order to prevent excessive water pumping and to maintain an optimal number of water pumping wells per interval.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.529-538
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• 2010

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

• Journal of the Korean Geotechnical Society
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• v.18 no.4
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• pp.119-126
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• 2002

A reliability analysis is performed to investigate the influence of the uncertainty from few in-situ samples and inherent heterogeneity of the ground on the probability of failure for a rock cut slope. The results are compared with those of deterministic slope stability analysis. The random variables used are unit weight of the rock, the angle of potential slope of failure, and cohesion and internal friction angle of joints. It was found that the rock slope in which the factor of safety satisfied the minimum safety factor in the deterministic analysis has high probability of failure in the reliability analysis when the weak geological strata are involved in the cut slope. The probability of failure of rock slope is most sensitive to the mean and standard deviation of cohesion in rock joint among the random soil parameters included in the reliability analysis. Sensitivities of the mean values are larger than those of standard deviations, which means that accurate estimation of the mean for the in-situ geotechnical properties is important.

• Computers and Concrete
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• v.15 no.2
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• pp.259-277
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• 2015

The lack of experimental studies on the mechanical behavior of reinforced concrete (RC) haunched beams leads to difficulties in statistical and reliability analyses. This study performs stochastic and reliability analyses of the ultimate shear capacity of RC haunched beams based on nonlinear finite element analysis. The main aim of this study is to investigate the influence of uncertainty in material properties and geometry parameters on the mechanical performance and shear capacity of RC haunched beams. Firstly, 65 experimentally tested RC haunched beams and prismatic beams are analyzed via deterministic nonlinear finite element method by a special program (ATENA) to verify the efficiency of utilized numerical models, the shear capacity and the crack pattern. The accuracy of nonlinear finite element analyses is verified by comparing the results of nonlinear finite element and experiments and both results are found to be in a good agreement. Afterwards, stochastic analyses are performed for each beam where the RC material properties and geometry parameters are assigned to take probabilistic values using an advanced simulating procedure. As a result of stochastic analysis, statistical parameters are determined. The statistical parameters are obtained for resistance bias factor and the coefficient of variation which were found to be equal to 1.053 and 0.137 respectively. Finally, reliability analyses are accomplished using the limit state functions of ACI-318 and ASCE-7 depending on the calculated statistical parameters. The results show that the RC haunched beams have higher sensitivity and riskiness than the RC prismatic beams.

• Korean Journal of Remote Sensing
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• v.36 no.2_1
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• pp.155-165
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• 2020

In this present study, the sensitivity of O₄ Air Mass Factor (AMF) to Aerosol Peak Height (APH) has been investigated using radiative transfer model according to various parameters(wavelength (340 nm and 477 nm), aerosol type (smoke, dust, sulfate), aerosol optical depth (AOD), surface reflectance, solar zenith angle, and viewing zenith angle). In general, it was found that O₄ AMF at 477 nm is more sensitive to APH than that at 340 nm and is stably retrieved with low spectral fitting error in Differential Optical Absorption Spectroscopy (DOAS) analysis. In high AOD condition, sensitivity of O₄ AMF on APH tends to increase. O₄ AMF at 340 nm decreased with increasing solar zenith angle. This dependency isthought to be induced by the decrease in length of the light path where O₄ absorption occurs due to the shielding effect caused by Rayleigh and Mie scattering at high solar zenith angles above 40°. At 477 nm, as the solar zenith angle increased, multiple scattering caused by Rayleigh and Mie scattering partly leads to the increase of O₄ AMF in nonlinear function. Based on synthetic radiance, APHs have been retrieved using O₄ AMF. Additionally, the effect of AOD uncertainty on APH retrieval error has been investigated. Among three aerosol types, APH retrieval for sulfate type is found to have the largest APH retrieval error due to uncertainty of AOD. In the case of dust aerosol, it was found that the influence of AOD uncertainty is negligible. It indicates that aerosol types affect APH retrieval error since absorption scattering characteristics of each aerosol type are various.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.203-214
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• 2000

Health risk assessment is applied to streamlining LCA(Life Cycle Assessment) using Monte carlo simulation for probabilistic/stochastic exposure and risk distribution analysis caused by data variability and uncertainty. A case study was carried out to find benefits of this application. BTC(Benzene, Trichloroethylene, Carbon tetrachloride mixture alias) personal exposure cases were assumed as production worker(in workplace), manager(in office) and business man(outdoor). These cases were different from occupational retention time and exposure concentration for BTC consumption pattern. The result of cancer risk in these 3 scenario cases were estimated as $1.72E-4{\pm}1.2E+0$(production worker; case A), $9.62E-5{\pm}1.44E-5$(manger; case B), $6.90E-5{\pm}1.16E+0$(business man; case C), respectively. Portions of over acceptable risk 1.00E-4(assumed standard) were 99.85%, 38.89% and 0.61%, respectively. Estimated BTC risk was log-normal pattern, but some of distributions did not have any formal patterns. Except first impact factor(BTC emission quantity), sensitivity analysis showed that main effective factor was retention time in their occupational exposure sites. This case study is a good example to cover that LCA with probabilistic risk analysis tool can supply various significant information such as statistical distribution including personal/environmental exposure level, daily time activity pattern and individual susceptibility. Further research is needed for investigating real data of these input variables and personal exposure concentration and application of this study methodology.