This study aims to propose a simplified equation for estimating the bond strength of corroded reinforcing bars. To this end, extensive parametric analyses were performed using the detailed analysis method presented in the authors’ previous study, where a wide range of critical variables were considered, such as compressive strength of concrete, net cover thickness, and reinforcing bar diameter. The sensitivity in bond strength of the corroded reinforcing bar according to each variable was evaluated. On this basis, a simplified formula for the bond strength of the corroded reinforcing bar was derived through regression analysis. The proposed equation was rigorously tested and verified using the bond test results of corroded reinforcing bars collected from the literature. The results confirmed that the proposed equation could estimate the bond strengths of specimens with better accuracy than the existing models, providing a reliable tool for engineers and researchers. In addition, the proposed equation was used to analyze the development length required for corroded tensile reinforcement to exert its yield strength, and it showed that the cover thickness of concrete must be at least four times the diameter of the reinforcing bar to achieve the yielding strength of reinforcing bar even at a corrosion degree of more than 5.0%.

PURPOSES : To enhance the accuracy of predicting the compressive strength of practical concrete mixtures, this study aimed to develop a machine learning model by utilizing the most commonly employed curing age, specifically, the 28-day curing period. The training dataset consisted of concrete mixture sample data at this curing age, along with samples subjected to a total load not exceeding 2,350 kg. The objective was to train a machine learning model to create a more practical predictive model suitable for real-world applications. METHODS : Three machine learning models—random forest, gradient boosting, and AdaBoost—were selected. Subsequently, the prepared dataset was used to train the selected models. Model 1 was trained using concrete sample data from the 28th curing day, followed by a comprehensive analysis of the results. For Model 2, training was conducted using data from the 28th day of curing, focusing specifically on instances where the total load was 2,350 kg or less. The results were systematically analyzed to determine the most suitable machine learning model for predicting the compressive strength of concrete. RESULTS : The machine learning model trained on concrete sample data from the 28th day of curing with a total weight of 2,350 kg or less exhibited higher accuracy than the model trained on weight-unrestricted data from the 28th day of curing. The models were evaluated in terms of accuracy, with the gradient boosting, AdaBoost, and random forest models demonstrating high accuracy, in that order. CONCLUSIONS : Machine learning models trained using concrete mix data based on practical and real-world scenarios demonstrated a higher accuracy than models trained on impractical concrete mix data. This case illustrates the significance of not only the quantity but also the quality of the data during the machine learning training process. Excluding outliers from the data appears to result in better accuracy for machine learning models. This underscores the importance of using high-quality and practical mixed concrete data for reliable and accurate model training.

The aerospace and power generation industries have an increasing demand for high-temperature, highstrength materials. However, conventional materials typically lack sufficient fracture toughness and oxidation resistance at high temperatures. This study aims to enhance the high-temperature properties of Nb-Si-Ti alloys through ball milling. To analyze the effects of milling time, the progression of alloying is evaluated on the basis of XRD patterns and the microstructure of alloy powders. Spark plasma sintering (SPS) is employed to produce compacts, with thermodynamic modeling assisting in predicting phase fractions and sintering temperature ranges. The changes in the microstructure and variation in the mechanical properties due to the adjustment of the sintering temperature provide insights into the influence of Nb solid solution, Nb5Si3, and crystallite size within the compacts. By investigating the changes in the mechanical properties through strengthening mechanisms, such as precipitation strengthening, solid solution strengthening, and crystallite refinement, this study aims to verify the applicability of Nb-Si-Ti alloys in advanced material systems.

In order to respond to environmental pollution, developed countries, including Korea, have begun to conduct research to utilize hydrogen energy. For mass transfer of hydrogen energy, storage as liquid hydrogen is advantageous, and in this case, the volume can be reduced to 1/800. As such, the transportation technology of liquefied hydrogen for ships is expected to be needed in the near future, but there is no commercialized method yet. This study is a study on the technology to test the performance of the components constituting the membrane type storage container in a cryogenic environment as a preparation for the above. It is a study to find a way to respond by analyzing in advance the problems that may occur during the shear test of adhesives. Through this study, the limitations of ISO4587 were analyzed, and in order to cope with this, the specimen was supplemented so that fracture occurred in the adhesive, not the adhesive gripper, by using stainless steel, a low-temperature steel, to reinforce the thickness. Based on this, shear evaluation was performed under conditions lowered to minus 243℃, and it was confirmed that the breaking strength was higher at cryogenic temperatures.

고성능 콘크리트(HPC) 압축강도는 추가적인 시멘트질 재료의 사용으로 인해 예측하기 어렵고, 개선된 예측 모델의 개발이 필수적 이다. 따라서, 본 연구의 목적은 배깅과 스태킹을 결합한 앙상블 기법을 사용하여 HPC 압축강도 예측 모델을 개발하는 것이다. 이 논 문의 핵심적 기여는 기존 앙상블 기법인 배깅과 스태킹을 통합하여 새로운 앙상블 기법을 제시하고, 단일 기계학습 모델의 문제점을 해결하여 모델 예측 성능을 높이고자 한다. 단일 기계학습법으로 비선형 회귀분석, 서포트 벡터 머신, 인공신경망, 가우시안 프로세스 회귀를 사용하고, 앙상블 기법으로 배깅, 스태킹을 이용하였다. 결과적으로 본 연구에서 제안된 모델이 단일 기계학습 모델, 배깅 및 스태킹 모델보다 높은 정확도를 보였다. 이는 대표적인 4가지 성능 지표 비교를 통해 확인하였고, 제안된 방법의 유효성을 검증하였다.

본 논문에서는 해양플랜트에 주로 사용되는 알루미늄 사다리의 독자 모델을 개발하기 위하여, 개량형 알루미늄 합금(6082-T6) 을 적용하고 국제 기준에 부합한 구조강도 설계를 하였다. 국제기준은 ISO, NORSOK, Austria Standard를 참고하였으며, 모든 조건이 만족할 수 있도록 하중 조합을 하였다. 설계된 모델은 유한요소법 [Finite elements method]을 근간으로 하는 해양플랜트 전용 해석프로그램인 SACS를 사용하여 구조 안전성을 검증하여 응력 및 처짐이 모두 허용기준 이내에 만족함을 확인하였다. 개발모델은 모든 허용기준을 만족하면서도 가볍고, 생산성이 향상되어 향후 많은 분야에서 사용이 될 것으로 기대해본다.

Cured-in-place-pipe(CIPP) is the most adopted trenchless application for sewer rehabilitation to extend the life of the existing sewer without compromising both direct construction and indirect social costs especially applied in the congested urban area. This technology is globally and domestically known to be the most suitable for partial and full deteriorated pipe structure rehabilitation in a sewer system. The typical design of CIPP requires a significant thickness of lining to support loading causing sewage flow interruption and increasing material cost. This paper presents development of a high strength glass fiber composite lining material for the CIPP application and structural test results. The test results exhibit that the new glass fiber composite lining material has 12 times of flexural strength, 6.2 times of flexural modulus, and 0.5 Creep Retention Factor. These test results can reduce lining design thickness 35% at minimum. Even though taking into consideration extra materials such as outer and inner films for actual field applications, the structural capacity of the composite material significantly increases and it reduces 20 percent or more line thickness as compared to the conventional CIPP. We expect that the newly developed CIPP lining material lowers material costs and minimizes flow capacity reduction, and fully replaceable to the conventional CIPP lining materials.

PURPOSES: The objective of this study is to evaluate the properties of high-performance concrete and compare them with the properties of ternary blended cement (OPC 60% : BFS 30% : FA 10%) as applied to all-in-one bridge decks. High-performance concrete modified with styrene-butadiene latex (SB latex) was evaluated for strength development and durability through its compressive strength and chloride ion diffusion coefficient. METHODS: The compressive strength test was conducted according to KS F 2405, and the average value of the three specimens was used as the result at each stage. The chloride ion diffusion test was performed at 28 days, 56 days, and 365 days according to NT BUILLD 492. The chloride ion penetration test was conducted according to ASTM C 1202. RESULTS: For the compressive strength of the high-performance concrete, the blast furnace slag 40% replacement (BFS40) mixture had the most similar results to those of the ternary blended cement. The BFS40 mixture exhibited a lower compressive strength at 3 days than the latex modified concrete (LMC) mixture used for the bridge deck pavement, whereas it exhibited a 3.7-9.8% higher compressive strength at 7 days. In addition, the BFS40 mixture had the lowest diffusion coefficient, which was 49.1~59.0% lower than that of the LMC mixture. Mixing with latex tended to decrease in charge passed compared to Plain which is only used ternary blended cement, and showed excellent watertighness (rated “very low”), which is lower than 1,000 coulombs in all mixtures with latex. CONCLUSIONS : The BFS40 mixture exhibited excellent compressive strength, chloride ion permeability resistance, and the lowest chloride ion diffusion coefficient although it included a small amount of latex, which makes it more expensive than the current LMC mixture. It is believed that it is possible to secure excellent economic efficiency and durability by using lesser latex than that in the LMC mixture and using a mixture of the blast furnace slag instead.

PURPOSES: The object of this study is to select appropriate inorganic materials, and find the best mixing formula to secure fast curing time and enough initial strength, and then to evaluate the durability of the asphalt mixtures according to the degree of addition of the compound manufactured by the determined blending ratio. METHODS : The breaking time and reactivity between seven kinds of inorganic minerals, and the selected recycled aggregate and emulsified asphalt were compared to determine the best initial curing strength for the mixtures. Then, three inorganic materials were chosen as the materials that provide good breaking time and reactivity, and the best mixing formula for the three materials was determined. The chemical composition of the compound manufactured using the mixing formula was analyzed by energy dispersive x-ray system method. Finally, indirect tensile strength (ITS) test was performed (for two days) at room temperature to determine the proper amount of additives that will provide the best initial strength. RESULTS: From the results of the reactivity test, the best mixing formula (A:C:G = 60:30:10) for the three selected inorganic materials with short braking time and high reactivity was determined. The four types of cold reclaimed asphalt mixtures for ITS testing were manufactured by adding the inorganic material compounds at 0%, 3%, 5%, and 7%, and the ITS values were measured after two curing days. The ITS values at 5% and 7% were 0.308 MPa and 0.415 MPa, respectively. The results of quality control tests (Marshall stability, porosity, flow value, etc.) at 5% and 7% satisfied the specification criterion for the cold recycled asphalt mixtures. CONCLUSIONS : The selected inorganic materials (A, C, and G) and the best mixing formula (A:C:G = 60:30:10) accelerated the reaction with emulsified asphalt and shortened the curing time. Depending on the inorganic material used, the breaking time and reactivity can be directly related or unrelated. This is because of the chemical compositions of recycled aggregates, infiltrated foreign matter, and chemical reactions between the inorganic materials and other materials. Therefore, it is important to select the proper materials and the best mixing formula when evaluating the characteristics of the practically used materials such as recycled aggregates, inorganic materials, and emulsified asphalt.

The bond property is mightily important in asphalt construction site as overlay, post-cutting overlay and new establishment of asphalt pavement. If the bonding between the lower and upper pavements isn't approriately applied, the slipping phenomenon can happen due to the tensile stress and shear stress. It can resultantly take the forms of the rutting, failure and other damages. Moreover, the greater damage phenomenon from the intense reflection cracking can be generated when the appropriate methods regarding the cracks or failures on the lower pavement aren't conducted and the bonding with its pavements isn't properly applied. In this regard, the researched content on the existing research is shown below. The types of asphalt emulsion applied to the pavement construction site are classified as Tack-Coat and Prime-Coat in South Korea. The application purpose of Tack-Coat is to bond the pavements comprised of the rigid material. And the application objective of Prime-Coat is to attach the layers consisting the disturbed materials. The best performance related to the optimum application rates depends on the type or property of the emulsified asphalt materials. To solve these phenomenons, the various researches have been globally done. The test methods to obtain the optimum application rates of the asphalt emulsion vary in different organizations or countries. The objective of this research is to develop the tester for Tack-Coat bonding property in accordance with the standards and circumstances of the pavement construction in South Korea. In the nation, the application rate of Tack-Coat is presented as 0.3 l/m2 ~ 0.6 l/m2 in the construction specification and pavement design guideline published in the Ministry of Land, Infrastructure and Transport (MOLIT), but there aren't the specific suggestions. And, it depends on the superintendents or the ordering bodies in the construction sites. In that regard, the objectives of this paper are listed below. First, Suggestion of the test methods regarding the Interlayer Shear Strength in accordance with the domestic construction conditions and standards. Second, Development of the tester for conducting various tests using a tester. Last, Development of the predictive model for the optimum application rates of the emulsified asphalt.

The contemporary high-tech structures have become enlarged and their functions more diversified. Steel concrete structure and composite material structures are not exceptions. Therefore, there have been on-going studies on fiber reinforcement materials to improve the characteristics of brittleness, bending and tension stress and others, the short-comings of existing concrete. In this study, the purpose is to develop the estimated model with dynamic characteristics following the steel fiber mixture rate and formation ration by using the nerve network in mixed steel fiber reinforced concrete (SFRC). This study took a look at the tendency of studies by collecting and analyzing the data of the advanced studies on SFRC, and facilitated it on the learning data required in the model development. In addition, by applying the diverse nerve network model and various algorithms to develop the optimal nerve network model appropriate to the dynamic characteristics. The accuracy of the developed nerve network model was compared with the experiment data value of other researchers not utilized as the learning data, the experiment data value undertaken in this study, and comparison made with the formulas proposed by the researchers. And, by analyzing the influence of learning data of nerve network model on the estimation result, the sensitivity of the forecasting system on the learning data of the nerve network is analyzed.

As buildings are becoming larger, demand for mega-sized composite columns (over 1-meter diameter) is increased. We have developed and commercialized welded built-up CFT column (ACT Column I) since 2005 which are structurally stable and economical using cold-formed steel with rib. However, there has a limit in size of cross section (618˟618mm) by a fabrication facilities. And due to characteristics of closed cross section, there has a limit to construction of connection of moment frame. Composite mega column (ACT Column II) has same concept of forming closed cross section. But in order to enlarge cross sectional size, thick plate is inserted between cold-formed steels. Since composite mega column can control thickness and width of thick plate, steel or composite beams can be directly attached to the connection. In this study, we propose strength formula of composite mega column to beam connections with T-shaped stiffener as internal diaphragm and verified through finite element analysis and simple tensile experiment.