The Fourth Industrial Revolution and sensor technology have led to increased utilization of sensor data. In our modern society, data complexity is rising, and the extraction of valuable information has become crucial with the rapid changes in information technology (IT). Recurrent neural networks (RNN) and long short-term memory (LSTM) models have shown remarkable performance in natural language processing (NLP) and time series prediction. Consequently, there is a strong expectation that models excelling in NLP will also excel in time series prediction. However, current research on Transformer models for time series prediction remains limited. Traditional RNN and LSTM models have demonstrated superior performance compared to Transformers in big data analysis. Nevertheless, with continuous advancements in Transformer models, such as GPT-2 (Generative Pre-trained Transformer 2) and ProphetNet, they have gained attention in the field of time series prediction. This study aims to evaluate the classification performance and interval prediction of remaining useful life (RUL) using an advanced Transformer model. The performance of each model will be utilized to establish a health index (HI) for cutting blades, enabling real-time monitoring of machine health. The results are expected to provide valuable insights for machine monitoring, evaluation, and management, confirming the effectiveness of advanced Transformer models in time series analysis when applied in industrial settings.

Bentonite is a widely used buffer material in high-level radioactive waste repositories due to its favorable properties, including its ability to swell and low permeability. Bentonite buffers play an important role in safe disposal by providing a low permeability barrier and preventing radionuclides migration into the surrounding rock. However, the long-term performance of the bentonite buffer is still an area of research, and one of the main concerns is the erosion of the buffer due to swelling and groundwater flow. Erosion of the bentonite buffer can have a significant impact on repository safety by reducing the integrity of the buffer and forming colloids that can transport radionuclides through groundwater, potentially increasing the risk of radionuclide migration. Therefore, understanding the mechanisms and factors that influence the erosion of the bentonite buffer is critical to the safety assessment of high-level radioactive waste repositories. In this study, we attempted to develop the bentonite buffer erosion model using Adaptive Processbased total system performance assessment framework for a geological disposal system (APro) proposed by the Korea Atomic Energy Research Institute (KAERI). First, the erosion phenomenon was divided into two stages: bentonite buffer penetration into rock fractures and colloid formation. As an initial step in the development of the buffer erosion model, a bentonite buffer intrusion into the fracture and consequent degradation of buffer property were considered. For this purpose, a tworegion model based on the dynamic bentonite diffusion model was adopted which is one of the methods for simulating bentonite buffer intrusion. And, it was assumed that the buffer properties, such as density, porosity and permeability, thermal conductivity, modulus of elasticity, and mechanical strength, are degraded as the buffer erodes. The bentonite buffer degradation model developed in this study will serve as a foundation for the comprehensive buffer erosion model, in conjunction with the colloidal formation model in the future.

With the recent concern regarding cellulose enhancing radionuclide mobility upon its degradation to ISA, disposal of cellulosic wastes is being held off until the disposal safety is vindicated. Thus, a rational assessment should be conducted, applying an appropriate cellulose degradation model considering the disposal environment and cellulose degradation mechanisms. In this paper cellulose degradation mechanisms and the disposal environment are studied to propose the best-suitable cellulose degradation model for the domestic 1st phase repository. For the cellulose to readily degrade, the pH should be greater than 12.5. As in the case of SKB, 1BLA is excluded from the safety assessment because the pH of 1BLA remains below 12.5. Furthermore, despite cellulose degradation occurring, it does not always produce ISA. At low Ca2+ concentration, the ISA yield rate is around 25%, but at high Ca2+ concentration, the ISA yield rate increases up to 90%. Thus, for the cellulose to be a major concern, both pH and Ca2+ concentration conditions must be satisfied. To satisfy both conditions, the cement hydration must be in 2nd phase, when the porewater pH remains around 12.5 and a significant amount of Ca2+ ion is leaching out from the cement. However, according to the safety evaluation and domestic research, 2nd phase of cement hydration for silo concrete would achieve a pH of around 12.4, dissatisfying cellulose degradation condition like in 1BLA. Thus, cellulose degradation would be unlikely to occur in the domestic 1st phase repository. To derive waste acceptance criteria, a quantitative evaluation should be conducted, conservatively assuming cellulose is degraded. To conduct a safety evaluation, an appropriate degradation model should be applied to determine the degradation rate of cellulose. According to overseas research, despite the mid-chain scission being yet to be seen in the experiments, the degradation model considering mid-chain scission is applied, resulting in an almost 100% degradation rate. The model is selected because the repositories are backfilled with cement, achieving a pH greater than 13, so extensive degradation is reasonably conservative. However, under the domestic disposal condition, where cellulose degradation is unlikely to occur, applying such model would be excessively conservative. Thus, the peeling and stopping model derived by Van Loon and Haas, which suggests 10~25% degradation rate, is reasonably conservative. Based on this model, cellulose would not be a major concern in the domestic 1st phase repository. In the future, this study could be used as fundamental data for planning waste acceptance criteria.

In this study the existing degradation model for the coated steel member is reviewed, and a new model is recalculated with the deterioration index, ‘rusting’ and ‘flaking’ only. In the case of durability evaluation with the two indexes only some considerations are suggested by the comparison of the existing and recalculated degradation model.

The correlation between the degradation scores and service life of the coating is derived by tests and inspection for the coated steel member according to each service environment of several facilities. This correlation called to as the deterioration model can be used to determine the performance grade for the durability of coated steel member of facilities under each service environment, for example, atmospheric, fluvial and marine environment.

Indices are selected for the evaluation of deterioration of coated steel, and an evaluation method is proposed for each index. The evaluation methods proposed in this study are then applied on the existing inspection data measured on site, and the correlation between the resulting evaluation scores and service life of the coating is derived statistically. This correlation called to as the deterioration model can be used to determine the performance grade for the durability of coated steel.

This study was conducted for the development of degradation model for the coated steel member in the atmospheric environment. Field inspection data was assessed against the existing evaluation factors which were proposed by the related research process. A correlation between evaluated degradation score and service life of coated steel member was plotted on the graph, and degradation of the coated steel member could be evaluated by quantitative analysis method.

Steel structure such as steel bridges are severely affected by the corrosion, and thus has to be maintained by periodic inspection and repetitive painting. In this study, existing empirical models for the degradation of coating are reviewed which is used for evaluation of corrosion, and in addition applied to definition of the state inspection criteria and condition rating by further research.

The hydrolytic kinetics of biodegradable poly(l-lactide) (PLLA) have been studied by using two model systems, solution-grown single crystal (SC) and Langmuir monolayer techniques, for elucidating the mechanism for both alkaline and enzymatic degradations. The present study investigated the parameters such as degradation medium and time. The Langmuir monolayers of PLLA showed faster rates of hydrolysis when they were exposed to a basic subphase rather than they did when exposed to neutral subphase. Both degradation mediums had moderate concentrations to show a maximized activity, depending on their sizes. An alkaline degradation of SCs of PLLA showed the decrease of molecular weight of the remained crystals due to the erosion of chain-folding surface. However, the enzymatic degradation of SCs of PLLA occurred in the crystal edges thus the molecular weight of remained crystals was not changed. This behavior might be attributed to the size of enzymes which is much larger than that of alkaline ions; that is, the enzymes need larger contact area with monolayers to be activated.