Chloride penetration into concrete is the main cause of the corrosion of steel in concrete structures exposed to chloride-rich environments. As a preventive or remedial method, surface treatments on concrete have been increasingly applied to both new and existing concrete structures to combat this problem. So far, knowledge of how a surface treatment reduces chloride diffusion is limited and the relationship between chloride diffusion resistance and surface treatment parameters, such as thickness, porosity and diffusion coefficient, has not been quantitatively identified. In this paper, chloride ion penetration modeling is performed to predict the service life of the surface treated concrete.

Chloride attack is one of the most critical deterioration due to rapid corrosion initiation and propagation which can cause structural safety problem. Extended service life through repairing is very important for determination of maintenance strategy. Conventionally adopted models for estimation of LCC (Life Cycle Cost) have shown step-shaped elevation of cost, however the extension of service life is much affected by quality of construction and repairing materials, which means engineering uncertainties in residual service life. In the paper, RC (Reinforced Concrete) column with three different mix proportions exposed to chloride attack are considered, and repairing numbers with related costs are evaluated through probabilistic technique for maintenance. When calculating repair frequency for intended service life through probabilistic model, the required repair frequency is evaluated to be 6.71 times for OPC, 4.09 times for SG30, and 2.95 times for SG 50, respectively. The probabilistic model for repairing cost is evaluated to be effective for reducing the repair frequency reasonably with changing the intended service life and design parameters.

The conventional method for estimating compressive strength of concrete has been suggested by considering only 1 to 3 influential factors. In this study, seven influential mixture factors (Water-Cement Ratio, Water, Cement, Fly ash, Blast furnace slag, Curing temperature, and humidity) of papers opened for 10 years were collected at three conferences in order to know tendency of data. The purpose of this paper is to estimate compressive strength more accurately by applying it to algorithm of the Deep learning.

본 연구는 고강도 섬유보강 시멘트 복합체(UHSCC) 접착성능을 평가하는 것이 목적이다. Direct shear test를 통해 압축전단접착강 도를 측정한 결과 NC(보통강도콘크리트)+ NC 실험체(150×150×150)에서는 모든 수준에서 유사한 압축전당접착강도를 나타내었고, 반 면 UHSCC+UHSCC에서는 지연타설 30분 후부터 0분에 비해 압축전단접착강도가 낮아지는 것을 확인할 수 있었다. 이를 통한 접착면의 파괴 모드를 분석한 결과 NC+NC 에서는 모든 수준에서 비계면 파괴를 보였고 UHSCC+UHSCC에서는 30분, 60분, 90분 시험체에서 계면파괴가 일 어났다. NC 및 UHSCC의 타설면을 XRD 시험을 통해 분석한 결과 NC 시험체에 비해 UHSCC의 시험체 에서 많은량의 SiO2의 성분이 검출되 는 것을 알 수 있었고 UHSCC에서 나타난 코팅막의 주성분의 대부분은 SiO2로 사료된다. 따라서 본 연구에서 사용된 UHSCC는 지연타설 30분 후 부터는 접착성능의 저하로 구조체로서의 사용이 어렵다고 판단된다. 금후 연구에서는 콜드조인트 발생 부위의 면처리 방법을 통한 접착성 능 향상이 필요하다고 사료된다.

Concrete with blast furnace slag (BFS) shows varied strength development properties different from normal concrete. Therefore, a precise prediction of compressive strength using a full maturity model is desired. The purpose of this study is to predict the compressive strength of concrete with BFS by calculating the apparent activation energy (Ea) and rate constant (kT) for each BFS replacement ratio. The method of Carino Model is used in this study for predicting compressive strength of concrete with BFS.

Concrete with blast furnace slag (BFS) shows varied strength development properties different from normal concrete. Therefore, a precise prediction of compressive strength using a full maturity model is desired. The purpose of this study is to predict the compressive strength of concrete with BFS by calculating the apparent activation energy (Ea) and rate constant (kT) for each BFS replacement ratio. The method of Carino Model is used in this study for predicting compressive strength of concrete with BFS.

Temperature of fresh concrete can be effectively used to predict the strength of concrete being cured and make an informed decision for stripping the molds. A hygrothermograph and thermo-couple sensors that require an extensive wiring have been applied to measure a temperature of concrete at the early stage of the curing process on site. Therefor, this study on the strength prediction using Maturity is mainly focused on, but the study on the concrete mixing blast furnace slag powder is insufficient. The purpose of this study is to investigate the relationships between compressive strength and equivalent age by Maturity function and is to compare and examine the strength prediction of concrete mixing Blast Furnace Slag Power using ACI and Logistic Curve prediction equation.