• Nuclear Engineering and Technology
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• v.56 no.5
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• pp.1887-1894
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• 2024

Fatigue strength of the structural materials of lead-cooled fast reactors (LFRs) and accelerator-driven systems (ADS) may be degraded in liquid metal (Lead or lead-bismuth eutectic (LBE)) environments. The fatigue crack growth (FCG) data of structural materials in liquid LBE are necessary for damage tolerance design, safety assessment and life management of key equipment. A novel monitoring system for fatigue crack length was designed on the compliance method and the monitor technology of crack opening displacement (COD) of CT specimens by the linear variable differential transformers (LVDT) system. It can be used to predict the crack length by monitoring the COD of CT specimens in harsh high-temperature liquid LBE using a LVDT system. The prediction accuracy of this system was verified by FCG experiments in room temperature air and liquid LBE at 150, 250 and 350 ℃. The first results obtained in the FCG test for T91 steel in liquid LBE at 350 ℃ are presented.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.1035-1040
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• 2024

The main objective of inspecting structures is to ensure the safety of all entities that utilize these structures as cracks in structures if not attended to could lead to serious calamities. With that objective in mind, artificial intelligence (AI) based technologies to assist human inspectors are needed especially for retaining walls in structures. In this paper, we predict the crack displacement of retaining walls using an Polynomial Regressive (PR) analysis model, as well as Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) deep learning models, and compare their performance. For the performance comparison, we apply multi-variable feature inputs, by utilizing temperature and rainfall data that may affect the crack displacement of the retaining wall. The training and inference data were collected through measuring sensors such as inclinometers, thermometers, and rain gauges. The results show that the multi-variable feature model had a MAE of 0.00186, 0.00450 and 0.00842, which outperformed the single variable feature model at 0.00393, 0.00556 and 0.00929 for the polynomial regression model, LSTM model and the GRU model respectively from the evaluation performed.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.532-535
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• 2004

This paper presents a nonlinear finite element analysis procedure for the prediction of shear strength of reinforced concrete deep beams. A computer program, named RCAHESTC(Reinforced Concrete Analysis in Higher Evaluation System Technology), for the analysis of reinforced concrete structures was used. Material nonlinearity is taken into account by comprising tensile. compressive and shear models of cracked concrete and a model of reinforcing steel. The smeared crack approach is incorporated. The proposed numerical method for the prediction of shear strength of reinforced concrete deep beams is verified by comparison with the reliable experimental results.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.6
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• pp.804-811
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• 2010

The fatigue crack propagation is stochastic in nature, because the variables affecting the fatigue behavior are random and have uncertainty. Therefore, the fatigue life prediction is critical for the design and the maintenance of many structural components. In this study, fatigue experiments are conducted on the specimens of magnesium alloy AZ31 under various conditions such as thickness of specimen, the load ratio and the loading condition. The probability distribution fit to the fatigue failure life are investigated through a probability plot paper by these conditions. The probabilities of failure at various conditions are also estimated. The fatigue design life is predicted by using the Weibull distribution.

• Journal of Auto-vehicle Safety Association
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• v.6 no.2
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• pp.36-42
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• 2014

In order to prevent the sharp edge during the side impact, a cause analysis and CAE based risk prediction were carried out in this study. It was found that sharp edge occurs mainly because of stiffness difference between the major parts and structural stress concentration. It could be improved by directly reinforcing the crack initiation region or by weakening the joints connecting the parts. The fracture criterion based on major in-plain strain was suggested and the risk prediction process for sharp edge prevention was established.

• Smart Structures and Systems
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• v.29 no.6
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• pp.799-805
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• 2022

Permanent magnet synchronous motors (PMSMs) are widely used in systems requiring high control precision, efficiency, and reliability. Predicting the remaining useful life (RUL) with health monitoring of PMSMs prevents catastrophic failure and ensures reliable operation of system. In this study, a model-based method for predicting the RUL of PMSMs using phase current and vibration signals is proposed. The proposed method includes feature selection and RUL prediction based on a particle filter with a degradation model. The Paris-Erdogan model describing micro fatigue crack propagation is used as the degradation model. An experimental set-up to conduct accelerated life test, capable of monitoring various signals was designed in this study. Phase current and vibration data obtained from an accelerated life test of the PMSMs were used to verify the proposed approach. Features extracted from the data were clustered based on monotonicity and correlation clustering, respectively. The results identify the effectiveness of using the current data in predicting the RUL of PMSMs.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.1
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• pp.35-42
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• 2008

In the nuclear power plant, early detection of fatigue crack by non-destructive test (NDT) equipment due to the thermal cyclic load is very important in terms of strict safety regulation. To this end, many efforts are exerted to the fabrication of artificial cracked specimen for practicing engineers in the NDT company. The crack of this kind, however, cannot be made by conventional machining, but should be made under thermal cyclic load that is close to the in-situ condition, which takes tremendous time due to the repetition. In this study, thermal loading condition is investigated to minimize the time for fabricating the cracked specimen using simulation technique which predicts the crack initiation and propagation behavior. Simulation and experiment are conducted under an initial assumed condition for validation purpose. A number of simulations are conducted next under a variety of heating and cooling conditions, from which the best solution to achieve minimum time for crack with wanted size is found. In the simulation, general purpose software ANSYS is used for the stress analysis, MATLAB is used to compute crack initiation life, and ZENCRACK, which is special purpose software for crack growth prediction, is used to compute crack propagation life. As a result of the study, the time for the crack to reach the size of 1mm is predicted from the 418 hours at the initial condition to the 319 hours at the optimum condition, which is about 24% reduction.

• Korean Journal of Materials Research
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• v.10 no.4
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• pp.305-311
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• 2000

Applicability of crack arrest load measured from the Charpy V-notch impact test has been investigated to predict the fracture toughness of nuclear reactor pressure vessel (RPV) steels (ASME SA508 Cl.3). The temperature dependence of the crack arrest load was well described by the type of exponential function characterized by an index temperature at which the crack arrest load is 2kN. The specific index temperature, which also well correlated with $T_{NDT}\;and\;T_{41J}$ is expected to be representative index temperature characterizing the crack arrest fracture toughness of RPV steels. Also, the crack arrest load correlated well with the stable crack length measured from the fracture surface. From the measurements of the crack arrest load and the stable crack length, the lower bound fracture toughness, $K_{Ia}$ of RPV steels could be predicted with sufficient accuracy.

• Journal of the Korean Recycled Construction Resources Institute
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• v.7 no.2
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• pp.109-115
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• 2019

In case of the cracks in concrete, the penetration of deterioration ions such as chloride ions in to cracks is accelerated. According to the penetration of chloride ions, structural and durability problems to RC(Reinforced Concrete) structures are caused. In this study, the accelerated chloride diffusion coefficient which is in steady state is evaluated for 2 year aged normal and high strength FA(Fly Ash) concrete, after a range of crack depths are induced up to 1.0 mm in 56 aged day. Considering crack effect by linear regression analysis, high strength concrete has slightly less increasing ratio of diffusion coefficient by crack than normal strength concrete, and diffusion coefficient increases non-linearly as crack width is increased. Also, In two types of concrete, crack effect decrease as the curing period increase. In the case of quantifying crack and curing effect by using exponential function form, the coefficients of determination are higher than those of linear regression analysis. Under steady state, it is thought that there is not a high correlation between the crack effect and the curing effect, and considering the two independent effects, it is believed that reasonable prediction equation for diffusion of concrete with crack can be proposed.

• Corrosion Science and Technology
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• v.4 no.3
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• pp.100-107
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• 2005

Reinforcing steel bars in reinforced concrete structures are protected from corrosion by passive film on the steel surface inside concrete with high alkalinity. However, when the passive film breaks down due to chloride ion ingressed into the RC structures, a corrosion initiates at the surface of steel bars. Then, internal pressure by volume expansion of corrosion products in reinforcing bars induces cracking and spalling of cover concrete, which reduces not only durability performance but also structural performance in RC structures. In this paper, a service life prediction of RC structures is carried out by using a micro-mechanics based corrosion model. The corrosion model is composed of a chloride penetration model to evaluate the initiation of corrosion and an electric corrosion cell model and an oxygen diffusion model to evaluate the rate and the accumulated amounts of corrosion. Then, a corrosion cracking model is combined to the models to evaluate critical amount of corrosion product for initiation cracking in cover concrete. By implementing the models into a finite element analysis program, a time and space dependent corrosion analysis and a service life prediction of RC structures due to chloride attack are simulated and the results of the analysis are compared with test results. The effect of crack width on the corrosion and the service life of the RC structures are analyzed and discussed.